Datasets:

TimSchopf

/

nlp_taxonomy_data

like 0

SCOPUS_ID:85142730373

23rd International Conference on Web Information Systems Engineering, WISE 2021

The proceedings contain 47 papers. The special focus in this conference is on Web Information Systems Engineering. The topics include: Explaining Unexpected Answers of SPARQL Queries; bitcoin Transaction Confirmation Time Prediction: A Classification View; offworker: An Offloading Framework for Parallel Web Applications; high-Performance Transaction Processing for Web Applications Using Column-Level Locking; sGrid++: Revising Simple Grid Based Density Estimator for Mining Outlying Aspect; LinGBM: A Performance Benchmark for Approaches to Build GraphQL Servers; a Service-Based Framework for Adaptive Data Curation in Data Lakehouses; retrofitting Industrial Machines with WebAssembly on the Edge; attention-Based Relation Prediction of Knowledge Graph by Incorporating Graph and Context Features; a Domain-Independent Method for Thematic Dataset Building from Social Media: The Case of Tourism on Twitter; rumor Detection in Social Network via Influence Based on Bi-directional Graph Convolutional Network; efficient Truss Computation for Large Hypergraphs; identifying Privacy Risks Raised by Utility Queries; an Empirical Assessment of Security and Privacy Risks of Web-Based Chatbots; an Information-Driven Genetic Algorithm for Privacy-Preserving Data Publishing; enhanced Topic Representation by Ambiguity Handling; enhancing Seq2seq Math Word Problem Solver with Entity Information and Math Knowledge; mitigating Multi-class Unintended Demographic Bias in Text Classification with Adversarial Learning; debias the Black-Box: A Fair Ranking Framework via Knowledge Distillation; incorporating News Summaries for Stock Predictions via Graphical Learning; domain Adversarial Training for Aspect-Based Sentiment Analysis; bootstrapping Joint Entity and Relation Extraction with Reinforcement Learning; EEML: Ensemble Embedded Meta-Learning; click is Not Equal to Purchase: Multi-task Reinforcement Learning for Multi-behavior Recommendation; multi-document Question Answering Powered by External Knowledge; a Learning-Based Approach for Multi-scenario Trajectory Similarity Search; transformer-Based Cache Replacement Policy Learning; conats: A Novel Framework for Cross-Modal Map Extraction; attentive Knowledge-Aware Path Network for Explainable Travel Mashup; extra Budget-Aware Online Task Assignment in Spatial Crowdsourcing; preface.

SCOPUS_ID:84981555662

23rd International Workshop on Logic, Language, Information, and Computation, WoLLIC 2016

The proceedings contain 26 papers. The special focus in this conference is on Logic, Language, Information, and Computation. The topics include: Compactness in infinitary godel logics; cut elimination for godel logic with an operator adding a constant; a classical propositional logic for reasoning about reversible logic circuits; the explanatory role of mathematical induction; justified belief and the topology of evidence; semantic acyclicity for conjunctive queries; expressivity of many-valued modal logics, coalgebraically; second-order false-belief tasks; how i learned to stop worrying and love two sorts; a logical approach to context-specific independence; descriptive complexity of graph spectra; causality in bounded petri nets is MSO definable; a multi-type calculus for inquisitive logic; a model-theoretic characterization of constant-depth arithmetic circuits; true concurrency of deep inference proofs; on the complexity of the equational theory of residuated boolean algebras; semantic equivalence of graph polynomials definable in second order logic; sheaves of metric structures; on the formalization of some results of context-free language theory; the semantics of corrections; characterizing relative frame definability in team semantics via the universal modality; negation and partial axiomatizations of dependence and independence logic revisited and anaphors and quantifiers.

SCOPUS_ID:85057217856

24th China Conference on Information Retrieval, CCIR 2018

The proceedings contain 22 papers. The special focus in this conference is on Information Retrieval. The topics include: Beyond pivot for extracting Chinese paraphrases; Joint attention LSTM network for aspect-level sentiment analysis; extraction new sentiment words in weibo based on relative branch entropy; two-target stance detection with target-related zone modeling; information diffusion model based on opportunity, trust and motivation; finding high-quality unstructured submissions in general crowdsourcing tasks; a hybrid neural network model with non-linear factorization machines for collaborative recommendation; identifying price sensitive customers in e-commerce platforms for recommender systems; Jointly modeling user and item reviews by CNN for multi-domain recommendation; a deep top-K relevance matching model for ad-hoc retrieval; learning target-dependent sentence representations for chinese event detection; prior knowledge integrated with self-attention for event detection; learning to start for sequence to sequence based response generation; a comparison between term-based and embedding-based methods for initial retrieval; text matching with monte carlo tree search; music mood classification based on lifelog; capsule-based bidirectional gated recurrent unit networks for question target classification; question-answering aspect classification with multi-attention representation; hierarchical answer selection framework for multi-passage machine reading comprehension; generative paragraph vector.

SCOPUS_ID:85068338217

24th International Conference on Application of Natural Language to Information Systems, NLDB 2019

The proceedings contain 37 papers. The special focus in this conference is on Application of Natural Language to Information Systems. The topics include: Gated Convolutional Neural Networks for Domain Adaptation; a Keyword Search Approach for Semantic Web Data; intent Based Association Modeling for E-commerce; from Web Crawled Text to Project Descriptions: Automatic Summarizing of Social Innovation Projects; Cross-Corpus Training with CNN to Classify Imbalanced Biomedical Relation Data; discourse-Driven Argument Mining in Scientific Abstracts; TAGS: Towards Automated Classification of Unstructured Clinical Nursing Notes; estimating the Believability of Uncertain Data Inputs in Applications for Alzheimer’s Disease Patients; deep Genetic Algorithm-Based Voice Pathology Diagnostic System; an Arabic-Multilingual Database with a Lexicographic Search Engine; model Answer Generation for Word-Type Questions in Elementary Mathematics; bug Severity Prediction Using a Hierarchical One-vs.-Remainder Approach; a Coherence Model for Sentence Ordering; unified Parallel Intent and Slot Prediction with Cross Fusion and Slot Masking; Evaluating the Accuracy and Efficiency of Sentiment Analysis Pipelines with UIMA; comparing Different Word Embeddings for Multiword Expression Identification; analysis and Prediction of Dyads in Twitter; mathematical Expression Extraction from Unstructured Plain Text; A Study on Self-attention Mechanism for AMR-to-text Generation; preMedOnto: A Computer Assisted Ontology for Precision Medicine; an Approach for Arabic Diacritization; learning Mobile App Embeddings Using Multi-task Neural Network; a Novel Approach Towards Fake News Detection: Deep Learning Augmented with Textual Entailment Features; contextualized Word Embeddings in a Neural Open Information Extraction Model; towards Recognition of Textual Entailment in the Biomedical Domain; development of a Song Lyric Corpus for the English Language.

SCOPUS_ID:85086271070

24th International Conference on Developments in Language Theory, DLT 2020

The proceedings contain 24 papers. The special focus in this conference is on Developments in Language Theory. The topics include: Operations on Permutation Automata; space Complexity of Stack Automata Models; descriptional Complexity of Semi-simple Splicing Systems; on the Degeneracy of Random Expressions Specified by Systems of Combinatorial Equations; dynamics of Cellular Automata on Beta-Shifts and Direct Topological Factorizations; avoidability of Additive Cubes over Alphabets of Four Numbers; equivalence of Linear Tree Transducers with Output in the Free Group; on the Balancedness of Tree-to-Word Transducers; on Tree Substitution Grammars; sublinear-Time Language Recognition and Decision by One-Dimensional Cellular Automata; scattered Factor-Universality of Words; complexity of Searching for 2 by 2 Submatrices in Boolean Matrices; avoiding 5/4-Powers on the Alphabet of Nonnegative Integers (Extended Abstract); transition Property for α-Power Free Languages with α ≥ 2 and k ≥ 3 Letters; Context-Freeness of Word-MIX Languages; the Characterization of Rational Numbers Belonging to a Minimal Path in the Stern-Brocot Tree According to a Second Order Balancedness; on Normalish Subgroups of the R. Thompson Groups; computing the Shortest String and the Edit-Distance for Parsing Expression Languages; an Approach to the Herzog-Schönheim Conjecture Using Automata; on the Fine Grained Complexity of Finite Automata Non-emptiness of Intersection; the State Complexity of Lexicographically Smallest Words and Computing Successors; reconstructing Words from Right-Bounded-Block Words.

SCOPUS_ID:85039788432

25 years of quality management research – outlines and trends

Purpose: The purpose of this paper is to explore and describe how research on quality management (QM) has evolved historically. The study includes the complete digital archive of three academic journals in the field of QM. Thereby, a unique depiction of how the general outlines of the field as well as trends in research topics have evolved through the years is presented. Design/methodology/approach: The study applies cluster and probabilistic topic modeling to unstructured data from The International Journal of Quality & Reliability Management, The TQM Journal and Total Quality Management & Business Excellence. In addition, trend analysis using support vector machine is performed. Findings: The study identifies six central, perpetual themes of QM research: control, costs, reliability and failure; service quality; TQM – implementation and performance; ISO – certification, standards and systems; Innovation, practices and learning and customers – research and product design. Additionally, historical surges and shifts in research focus are recognized in the study. From these trends, a decrease in interest in TQM and control of quality, costs and processes in favor of service quality, customer satisfaction, Six Sigma, Lean and innovation can be noted during the past decade. The results validate previous findings. Originality/value: Of the identified central themes, innovation, practices and learning appears not to have been documented as a fundamental part of QM research in previous studies. Thus, this theme can be regarded as a new perspective on QM research and thereby on QM.

SCOPUS_ID:85149244210

25th International Conference on Developments in Language Theory (DLT 2021): Preface

SCOPUS_ID:85113260515

25th International Conference on Developments in Language Theory, DLT 2021

The proceedings contain 30 papers. The special focus in this conference is on Developments in Language Theory. The topics include: Lyndon Words Formalized in Isabelle/HOL; the Range of State Complexities of Languages Resulting from the Cascade Product—The General Case (Extended Abstract); parsimonious Computational Completeness; second-Order Finite Automata: Expressive Power and Simple Proofs Using Automatic Structures; reversible Top-Down Syntax Analysis; symmetry Groups of Infinite Words; Bounded Languages Described by GF(2)-grammars; definability Results for Top-Down Tree Transducers; The Hardest LL(k) Language; upper Bounds on Distinct Maximal (Sub-)Repetitions in Compressed Strings; branching Frequency and Markov Entropy of Repetition-Free Languages; a Linear-Time Simulation of Deterministic d-Limited Automata; carathéodory Extensions of Subclasses of Regular Languages; pointlike Sets and Separation: A Personal Perspective; parikh Word Representable Graphs and Morphisms; a Strong Non-overlapping Dyck Code; active Learning of Sequential Transducers with Side Information About the Domain; compositions of Constant Weighted Extended Tree Transducers; Extremal Binary PFAs in a Černý Family; variations on the Post Correspondence Problem for Free Groups; reducing Local Alphabet Size in Recognizable Picture Languages; preface; morphic Sequences Versus Automatic Sequences; properties of Graphs Specified by a Regular Language; balanced-By-Construction Regular and ω -Regular Languages; weighted Prefix Normal Words: Mind the Gap; two-Way Non-uniform Finite Automata; integer Weighted Automata on Infinite Words.

SCOPUS_ID:85142752080

25th International Conference on Discovery Science, DS 2022

The proceedings contain 39 papers. The special focus in this conference is on Discovery Science. The topics include: Elastic Product Quantization for Time Series; Stress Detection from Wearable Sensor Data Using Gramian Angular Fields and CNN; multi-attribute Transformers for Sequence Prediction in Business Process Management; data-Driven Prediction of Athletes’ Performance Based on Their Social Media Presence; link Prediction with Text in Online Social Networks: The Role of Textual Content on High-Resolution Temporal Data; weakly Supervised Named Entity Recognition for Carbon Storage Using Deep Neural Networks; predicting User Dropout from Their Online Learning Behavior; efficient Multivariate Data Fusion for Misinformation Detection During High Impact Events; discovery of Differential Equations Using Probabilistic Grammars; MQ-OFL: Multi-sensitive Queue-based Online Fair Learning; multi-fairness Under Class-Imbalance; when Correlation Clustering Meets Fairness Constraints; cooperative Deep Unsupervised Anomaly Detection; on the Ranking of Variable Length Discords Through a Hybrid Outlier Detection Approach; textMatcher: Cross-Attentional Neural Network to Compare Image and Text; can Cross-Domain Term Extraction Benefit from Cross-lingual Transfer?; retrieval-Efficiency Trade-Off of Unsupervised Keyword Extraction; A Fuzzy OWL Ontologies Embedding for Complex Ontology Alignments; optimal Decoding of Hidden Markov Models with Consistency Constraints; hyperparameter Importance of Quantum Neural Networks Across Small Datasets; semi-parametric Approach to Random Forests for High-Dimensional Bayesian Optimisation; a Clustering-Inspired Quality Measure for Exceptional Preferences Mining—Design Choices and Consequences; recurrent Segmentation Meets Block Models in Temporal Networks; community Detection in Edge-Labeled Graphs; a Fast Heuristic for Computing Geodesic Closures in Large Networks; JUICE: JUstIfied Counterfactual Explanations; explaining Siamese Networks in Few-Shot Learning for Audio Data; interpretable Latent Space to Enable Counterfactual Explanations; shapley Chains: Extending Shapley Values to Classifier Chains; explaining Crash Predictions on Multivariate Time Series Data; ImitAL: Learned Active Learning Strategy on Synthetic Data; semi-supervised Change Point Detection Using Active Learning; preface.

SCOPUS_ID:85139079686

25th International Conference on Text, Speech, and Dialogue, TSD 2022

The proceedings contain 43 papers. The special focus in this conference is on Text, Speech, and Dialogue. The topics include: Linear Transformations for Cross-lingual Sentiment Analysis; TOKEN Is a MASK: Few-shot Named Entity Recognition with Pre-trained Language Models; use of Machine Learning Methods in the Assessment of Programming Assignments; ontology-Aware Biomedical Relation Extraction; balancing the Style-Content Trade-Off in Sentiment Transfer Using Polarity-Aware Denoising; a Self-Evaluating Architecture for Describing Data; a Novel Hybrid Framework to Enhance Zero-shot Classification; attention-Based Model for Accurate Stance Detection; OPTICS: Automatic MT Evaluation Based on Optimal Transport by Integration of Contextual Representations and Static Word Embeddings; DaFNeGE: Dataset of French Newsletters with Graph Representation and Embedding; exploration of Multi-corpus Learning for Hate Speech Classification in Low Resource Scenarios; on the Importance of Word Embedding in Automated Harmful Information Detection; BERT-based Classifiers for Fake News Detection on Short and Long Texts with Noisy Data: A Comparative Analysis; can a Machine Generate a Meta-Review? How Far Are We?; autoblog 2021: The Importance of Language Models for Spontaneous Lecture Speech; Transformer-Based Automatic Speech Recognition of Formal and Colloquial Czech in MALACH Project; wakeword Detection Under Distribution Shifts; end-to-End Parkinson’s Disease Detection Using a Deep Convolutional Recurrent Network; lexical Bundle Variation in Business Actors’ Public Communications; 50 Shades of Gray: Effect of the Color Scale for the Assessment of Speech Disorders; ANTILLES: An Open French Linguistically Enriched Part-of-Speech Corpus; sub 8-Bit Quantization of Streaming Keyword Spotting Models for Embedded Chipsets; detection of Prosodic Boundaries in Speech Using Wav2Vec 2.0; text-to-Text Transfer Transformer Phrasing Model Using Enriched Text Input; Lexicon-based vs. Lexicon-free ASR for Norwegian Parliament Speech Transcription; on Comparison of Phonetic Representations for Czech Neural Speech Synthesis; the Influence of Dataset Partitioning on Dysfluency Detection Systems; going Beyond the Cookie Theft Picture Test: Detecting Cognitive Impairments Using Acoustic Features.

SCOPUS_ID:85111003347

25th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2021

The proceedings contain 157 papers. The special focus in this conference is on Knowledge Discovery and Data Mining. The topics include: Self-supervised Graph Representation Learning with Variational Inference; manifold Approximation and Projection by Maximizing Graph Information; learning Attention-Based Translational Knowledge Graph Embedding via Nonlinear Dynamic Mapping; multi-Grained Dependency Graph Neural Network for Chinese Open Information Extraction; human-Understandable Decision Making for Visual Recognition; LightCAKE: A Lightweight Framework for Context-Aware Knowledge Graph Embedding; transferring Domain Knowledge with an Adviser in Continuous Tasks; inferring Hierarchical Mixture Structures: A Bayesian Nonparametric Approach; quality Control for Hierarchical Classification with Incomplete Annotations; learning Discriminative Features Using Multi-label Dual Space; universal Representation for Code; autoCluster: Meta-learning Based Ensemble Method for Automated Unsupervised Clustering; banditRank: Learning to Rank Using Contextual Bandits; a Compressed and Accelerated SegNet for Plant Leaf Disease Segmentation: A Differential Evolution Based Approach; meta-context Transformers for Domain-Specific Response Generation; a Multi-task Kernel Learning Algorithm for Survival Analysis; Meta-data Augmentation Based Search Strategy Through Generative Adversarial Network for AutoML Model Selection; tree-Capsule: Tree-Structured Capsule Network for Improving Relation Extraction; rule Injection-Based Generative Adversarial Imitation Learning for Knowledge Graph Reasoning; hierarchical Self Attention Based Autoencoder for Open-Set Human Activity Recognition; reinforced Natural Language Inference for Distantly Supervised Relation Classification; self-supervised Adaptive Aggregator Learning on Graph; SaGCN: Structure-Aware Graph Convolution Network for Document-Level Relation Extraction; addressing the Class Imbalance Problem in Medical Image Segmentation via Accelerated Tversky Loss Function; incorporating Relational Knowledge in Explainable Fake News Detection; incorporating Syntactic Information into Relation Representations for Enhanced Relation Extraction.

SCOPUS_ID:85099585993

26 years left behind: a historical and predictive analysis of electronic business research

This article reviews 26 years (1994–2020) of research on electronic business published in reputable journals of the field. The basic aim behind this study is to define the growth potential of electronic business and marketing as a theoretical field and provide insights on past, present, and future scientific production in the field. By using bibliometrics and topic modeling techniques, annual scientific production and growth, latent topic structures, and trends by years, information on total citations and networks were examined. While the authors defined the research orientations by uncovering the main topics associated with electronic business, they created an understanding of the possible future research directions of fourteen topics discovered. The results show that, while the transaction-focused publications prevailed in the early years of electronic business and marketing journals, from the mid2000s, the focus has shifted towards marketing-focused publications. Moreover, to understand the main orientations in the field, the authors conducted a citation analysis to define the most influential topics published in the journals. The article also provides information on the most influential researchers in the field.

SCOPUS_ID:85075715291

26Layer-wise de-Training and re-Training for ConvS2S machine translation

The convolutional sequence-To-sequence (ConvS2S) machine translation system is one of the typical neural machine translation (NMT) systems. Training the ConvS2S model tends to get stuck in a local optimum in our pre-studies. To overcome this inferior behavior, we propose to de-Train a trained ConvS2S model in a mild way and retrain to find a better solution globally. In particular, the trained parameters of one layer of the NMT network are abandoned by re-initialization while other layers' parameters are kept at the same time to kick off re-optimization from a new start point and safeguard the new start point not too far from the previous optimum. This procedure is executed layer by layer until all layers of the ConvS2S model are explored. Experiments show that when compared to various measures for escaping from the local optimum, including initialization with random seeds, adding perturbations to the baseline parameters, and continuing training (con-Training) with the baseline models, our method consistently improves the ConvS2S translation quality across various language pairs and achieves better performance.

SCOPUS_ID:84947721154

26th Annual European Conference on Information Retrieval, ECIR 2004

The proceedings contain 30 papers. The special focus in this conference is on User Studies and Question Answering. The topics include: From information retrieval to information interaction; traditions of representation and anti-representation in information processing; a user-centered approach to evaluating topic models; a study of user interaction with a concept-based interactive query expansion support tool; searcher’s assessments of task complexity for web searching; evaluating passage retrieval approaches for question answering; identification of relevant and novel sentences using reference corpus; answer selection in a multi-stream open domain question answering system; a bidimensional view of documents for text categorisation; query difficulty, robustness, and selective application of query expansion; combining CORI and the decision-theoretic approach for advanced resource selection; predictive top-down knowledge improves neural exploratory bottom-up clustering; contextual document clustering; complex linguistic features for text classification; eliminating high-degree biased character bigrams for dimensionality reduction in chinese text categorization; broadcast news gisting using lexical cohesion analysis; from text summarisation to style-specific summarisation for broadcast news; relevance feedback for cross language image retrieval; integrating perceptual signal features within a multi-facetted conceptual model for automatic image retrieval; improving retrieval effectiveness by reranking documents based on controlled vocabulary; a study of the assessment of relevance for the INEX’02 test collection; a simulated study of implicit feedback models; cross-language information retrieval using eurowordnet and word sense disambiguation and fault-tolerant fulltext information retrieval in digital multilingual encyclopedias with weighted pattern morphing.

SCOPUS_ID:85111418311

26th International Conference on Applications of Natural Language to Information Systems, NLDB 2021

The proceedings contain 33 papers. The special focus in this conference is on Applications of Natural Language to Information Systems. The topics include: The Importance of Character-Level Information in an Event Detection Model; sequence-Based Word Embeddings for Effective Text Classification; BERT-Capsule Model for Cyberbullying Detection in Code-Mixed Indian Languages; multiword Expression Features for Automatic Hate Speech Detection; semantic Text Segment Classification of Structured Technical Content; on the Generalization of Figurative Language Detection: The Case of Irony and Sarcasm; extracting Facts from Case Rulings Through Paragraph Segmentation of Judicial Decisions; Detection of Misinformation About COVID-19 in Brazilian Portuguese WhatsApp Messages; multi-Step Transfer Learning for Sentiment Analysis; scaling Federated Learning for Fine-Tuning of Large Language Models; improving Sentiment Classification in Low-Resource Bengali Language Utilizing Cross-Lingual Self-supervised Learning; human Language Comprehension in Aspect Phrase Extraction with Importance Weighting; exploring Summarization to Enhance Headline Stance Detection; predicting Vaccine Hesitancy and Vaccine Sentiment Using Topic Modeling and Evolutionary Optimization; sentiment Progression Based Searching and Indexing of Literary Textual Artefacts; argument Mining in Tweets: Comparing Crowd and Expert Annotations for Automated Claim and Evidence Detection; authorship Attribution Using Capsule-Based Fusion Approach; on the Explainability of Automatic Predictions of Mental Disorders from Social Media Data; using Document Embeddings for Background Linking of News Articles; let’s Summarize Scientific Documents! A Clustering-Based Approach via Citation Context; overcoming the Knowledge Bottleneck Using Lifelong Learning by Social Agents; cross-Active Connection for Image-Text Multimodal Feature Fusion; profiling Fake News Spreaders: Personality and Visual Information Matter; comparing MultiLingual and Multiple MonoLingual Models for Intent Classification and Slot Filling.

SCOPUS_ID:85130242683

26th International Conference on Developments in Language Theory, DLT 2022

The proceedings contain 25 papers. The special focus in this conference is on Developments in Language Theory. The topics include: Logarithmic Equal-Letter Runs for BWT of Purely Morphic Words; on Perfect Coverings of Two-Dimensional Grids; automata-Theoretical Regularity Characterizations for the Iterated Shuffle on Commutative Regular Languages; on the Complexity of Decision Problems for Counter Machines with Applications to Coding Theory; visit-Bounded Stack Automata; well Quasi-Orders Arising from Finite Ordered Semigroups; the Billaud Conjecture for | Σ| = 4, and Beyond; weighted Tree Automata with Constraints; performing Regular Operations with 1-Limited Automata; word Equations in the Context of String Solving; binomial Complexities and Parikh-Collinear Morphisms; rational Index of Languages with Bounded Dimension of Parse Trees; measuring Power of Locally Testable Languages; the Power Word Problem in Graph Products; on One-Counter Positive Cones of Free Groups; kolmogorov Complexity Descriptions of the Exquisite Behaviors of Advised Deterministic Pushdown Automata; a Survey on Delegated Computation; checking Regular Invariance Under Tightly-Controlled String Modifications; deciding Atomicity of Subword-Closed Languages; prefix Palindromic Length of the Sierpinski Word; preservation of Normality by Unambiguous Transducers; a Full Characterization of Bertrand Numeration Systems; on the Decidability of Infix Inclusion Problem.

SCOPUS_ID:85077525088

26th International Conference on Neural Information Processing, ICONIP 2019

The proceedings contain 111 papers. The special focus in this conference is on Neural Information Processing. The topics include: Deep learning for combo object detection; dasNet: Dynamic adaptive structure for accelerating multi-task convolutional neural network; confusion-aware convolutional neural network for image classification; feature learning and data compression of biosignals using convolutional autoencoders for sleep apnea detection; self-adaptive network pruning; text-augmented knowledge representation learning based on convolutional network; a novel online ensemble convolutional neural networks for streaming data; cross-media image-text retrieval based on two-level network; fusion convolutional attention network for opinion spam detection; adversarial learning for cross-modal retrieval with wasserstein distance; Deep CNN based system for detection and evaluation of RoIs in flooded areas; Improving deep learning by regularized scale-free MSE of representations; training behavior of deep neural network in frequency domain; on the initialization of long short-term memory networks; A multi-cascaded deep model for bilingual SMS classification; low resource named entity recognition using contextual word representation and neural cross-lingual knowledge transfer; an analysis of the interaction between transfer learning protocols in deep neural networks; representation learning for heterogeneous information networks via embedding events; unified framework for visual domain adaptation using globality-locality preserving projections; zero-shot learning for intrusion detection via attribute representation; reducing the subject variability of eeg signals with adversarial domain generalization; region selection model with saliency constraint for fine-grained recognition; siamese network based feature learning for improved intrusion detection; self-attentive pyramid network for single image de-raining; feature fusion based deep spatiotemporal model for violence detection in videos.

SCOPUS_ID:85128965239

27th International Conference on Database Systems for Advanced Applications, DASFAA 2022

The proceedings contain 52 papers. The special focus in this conference is on Database Systems for Advanced Applications. The topics include: Aligning Internal Regularity and External Influence of Multi-granularity for Temporal Knowledge Graph Embedding; AdCSE: An Adversarial Method for Contrastive Learning of Sentence Embeddings; HRG: A Hybrid Retrieval and Generation Model in Multi-turn Dialogue; FalCon: A Faithful Contrastive Framework for Response Generation in TableQA Systems; tipster: A Topic-Guided Language Model for Topic-Aware Text Segmentation; simEmotion: A Simple Knowledgeable Prompt Tuning Method for Image Emotion Classification; predicting Rumor Veracity on Social Media with Graph Structured Multi-task Learning; knowing What I Don’t Know: A Generation Assisted Rejection Framework in Knowledge Base Question Answering; medical Image Fusion Based on Pixel-Level Nonlocal Self-similarity Prior and Optimization; knowledge-Enhanced Interactive Matching Network for Multi-turn Response Selection in Medical Dialogue Systems; information Networks Based Multi-semantic Data Embedding for Entity Resolution; KAAS: A Keyword-Aware Attention Abstractive Summarization Model for Scientific Articles; e-Commerce Knowledge Extraction via Multi-modal Machine Reading Comprehension; PERM: Pre-training Question Embeddings via Relation Map for Improving Knowledge Tracing; a Three-Stage Curriculum Learning Framework with Hierarchical Label Smoothing for Fine-Grained Entity Typing; PromptMNER: Prompt-Based Entity-Related Visual Clue Extraction and Integration for Multimodal Named Entity Recognition; taskSum: Task-Driven Extractive Text Summarization for Long News Documents Based on Reinforcement Learning; concurrent Transformer for Spatial-Temporal Graph Modeling; towards Personalized Review Generation with Gated Multi-source Fusion Network; definition-Augmented Jointly Training Framework for Intention Phrase Mining; modeling Uncertainty in Neural Relation Extraction; semantic-Based Data Augmentation for Math Word Problems; query-Document Topic Mismatch Detection.

SCOPUS_ID:85097296613

27th International Conference on Neural Information Processing, ICONIP 2020

The proceedings contain 376 papers. The special focus in this conference is on Neural Information Processing. The topics include: DF-PLSTM-FCN: A Method for Unmanned Driving Based on Dual-Fusions and Parallel LSTM-FCN; learning Discrete Sentence Representations via Construction & Decomposition; sparse Hierarchical Modeling of Deep Contextual Attention for Document-Level Neural Machine Translation; improving Mongolian-Chinese Machine Translation with Automatic Post-editing; exploration on the Generation of Chinese Palindrome Poetry; error Heuristic Based Text-Only Error Correction Method for Automatic Speech Recognition; detecting Online Fake Reviews via Hierarchical Neural Networks and Multivariate Features; deep Cardiovascular Disease Prediction with Risk Factors Powered Bi-attention; a Hybrid Self-Attention Model for Pedestrians Detection; coarse-to-Fine Attention Network via Opinion Approximate Representation for Aspect-Level Sentiment Classification; CARU: A Content-Adaptive Recurrent Unit for the Transition of Hidden State in NLP; automatic Parameter Selection of Granual Self-organizing Map for Microblog Summarization; A Token-Wise CNN-Based Method for Sentence Compression; a Neural Framework for English-Hindi Cross-Lingual Natural Language Inference; WC2FEst-Net: Wavelet-Based Coarse-to-Fine Head Pose Estimation from a Single Image; unsupervised Tongue Segmentation Using Reference Labels; u-Net Neural Network Optimization Method Based on Deconvolution Algorithm; a Feature Fusion Network for Multi-modal Mesoscale Eddy Detection; triple Attention Network for Clothing Parsing; temporal Smoothing for 3D Human Pose Estimation and Localization for Occluded People; Take a NAP: Non-Autoregressive Prediction for Pedestrian Trajectories; simultaneous Inpainting and Colorization via Tensor Completion; REXUP: I REason, I EXtract, I UPdate with Structured Compositional Reasoning for Visual Question Answering; res2U-Net: Image Inpainting via Multi-scale Backbone and Channel Attention; drawing Dreams.

http://arxiv.org/abs/1704.07624v2

280 Birds with One Stone: Inducing Multilingual Taxonomies from Wikipedia using Character-level Classification

We propose a simple, yet effective, approach towards inducing multilingual taxonomies from Wikipedia. Given an English taxonomy, our approach leverages the interlanguage links of Wikipedia followed by character-level classifiers to induce high-precision, high-coverage taxonomies in other languages. Through experiments, we demonstrate that our approach significantly outperforms the state-of-the-art, heuristics-heavy approaches for six languages. As a consequence of our work, we release presumably the largest and the most accurate multilingual taxonomic resource spanning over 280 languages.

SCOPUS_ID:84970004162

29th Canadian Conference on Artificial Intelligence, Canadian AI 2016

The proceedings contain 39 papers. The special focus in this conference is on Budding Field of Computing. The topics include: Action recognition by pairwise proximity function support vector machines with dynamic time warping kernels; an agent-based architecture for sensor data collection and reasoning in smart home environments for independent living; biometric authentication by keystroke dynamics for remote evaluation with one-class classification; simulating the bubble net hunting behaviour of humpback whales; Gaussian neuron in deep belief network for sentiment prediction; grounding social interaction with affective intelligence; the mismeasure of machines; uncovering hidden sentiment in meetings; fuzzy computational model for emotions originated in workplace events; tolerance-based approach to audio signal classification; a novel dataset for real-life evaluation of facial expression recognition methodologies; visual perception similarities to improve the quality of user cold start recommendations; object-based representation for scene classification; salient object detection in noisy images; an approach to improving single sample face recognition using high confident tracking trajectories; poetry chronological classification; harnessing open information extraction for entity classification in a French corpus; a novel genetic algorithm for the word sense disambiguation problem; mining biomedical literature; word normalization using phonetic signatures; forecasting canadian elections using twitter; time-sensitive topic-based communities on twitter; on tree structures used by simple propagation; a simple method for testing independencies in Bayesian networks; flexible approximators for approximating fixpoint theory; learning statistically significant contrast sets and improving conversation engagement through data-driven agent behavior modification.

SCOPUS_ID:84865505973

2B$ - Testing past algorithms in nowadays web

In this paper we look into Who Wants to Be a Millionaire, a contest of multiple-answer questions, as an answer selection subproblem. Answer selection, in Question Answering systems, allows them to boost one or more correct candidate answers over a set of candidate answers. In this subproblem we look only to a set of four candidate answers, in which one is the correct answer. The built platform is language independent and supports other languages besides English with no effort. In this paper we compare some techniques for answer selection, employing them to both English and Portuguese in the context of Who Wants to Be a Millionaire. The results showed that the strategy may be applicable to more than a language without damaging its performance, getting accuracies around 73%. © 2012 Springer-Verlag.

SCOPUS_ID:85147094163

2D Vector Representation of Binomial Hierarchical Tree Items

Today Artificial Intelligence (AI) algorithms need to represent different kinds of input items in numeric or vector format. Some input data can easily be transformed to numeric or vector format but the structure of some special data prevents direct and easy transformation. For instance, we can represent air condition using humidity, pressure, and temperature values with a vector that has three features and we can understand the similarity of two different air measurements using cosine-similarity of two vectors. But if we are dealing with a general ontology tree, which has elements "entity"as the root element, its two children "living things"and "non-living things"as first- level elements repeatedly children of "living things"that are "Animals", "Plants"as second level elements, it is harder to represent this kind of data with numeric values. The ontology tree starts from the general items and goes to specific items. If we want to represent an element of this tree with a vector; how can it be possible? And if we want the measured similarity using some methods like cosine-similarity, which one similarity is higher, ("Animal"and "non-living thing") or ("Animal"and "Living thing")? How should we select the values of this vector for each item of the hierarchical tree? In this paper, we propose an original and basic idea to represent the hierarchical tree items with 2D vectors and in the proposed method the cosine-similarity metric works for measuring the semantic similarity of represented items at the same level as parent items. There are two important results related to our representation: (1) The "y"values of the items give the hierarchical level of the item. (2) For the same level items, the cosine similarities between the parent item and child items are higher if the child belongs to this parent compared to other childrens'. In other words, the cosine similarity between the parent item and child items is highest if the child belongs to this parent.

SCOPUS_ID:84919933302

2D and 3D video scene text classification

Text detection and recognition is a challenging problem in document analysis due to the presence of the unpredictable nature of video texts, such as the variations of orientation, font and size, illumination effects, and even different 2D/3D text shadows. In this paper, we propose a novel horizontal and vertical symmetry feature by calculating the gradient direction and the gradient magnitude of each text candidate, which results in Potential Text Candidates (PTCs) after applying the k-means clustering algorithm on the gradient image of each input frame. To verify PTCs, we explore temporal information of video by proposing an iterative process that continuously verifies the PTCs of the first frame and the successive frames, until the process meets the converging criterion. This outputs Stable Potential Text Candidates (SPTCs). For each SPTC, the method obtains text representatives with the help of the edge image of the input frame. Then for each text representative, we divide it into four quadrants and check a new Mutual Nearest Neighbor Symmetry (MNNS) based on the dominant stroke width distances of the four quadrants. A voting method is finally proposed to classify each text block as either 2D or 3D by counting the text representatives that satisfy MNNS. Experimental results on classifying 2D and 3D text images are promising, and the results are further validated by text detection and recognition before classification and after classification with the exiting methods, respectively.

SCOPUS_ID:84865290503

2D discontinuous function approximation with real-valued grammar-based classifier system

Learning classifier systems (LCSs) are rule-based, evolutionary learning systems. Recently, there is a growing interest among the researchers in exploring LCSs implemented in a real-valued environment, due to its practical applications. This paper describes the use of a real-valued Grammar-based Classifier System (rGCS) in a task of 2D function approximation. rGCS is based on Grammar-based Classifier System (GCS), which was originally used to process context free grammar sentences. In this paper, we propose an extension to rGCS, called Simple Accept Radius (SAR) mechanism, that filters invalid and unexpected input real values. Performance evaluations show that the additional Simple Accept Radius mechanism enables rGCS to accurately approximate 2D discontinuous function. Performance comparisons with another real-valued LCS show that rGCS yields competitive performance. © 2012 Springer-Verlag.

SCOPUS_ID:84890413127

2D-to-3D conversion of pictures mixed with text and images

Even though a variety of 2D-to-3D conversion methods have been introduced and applied to commercial 3DTVs and 3D displays, the conversion of text regions has not been solved yet. Most of conversion methods generate 3D images with high quality. However, broken or unreadable texts are still visible because the conversion methods are not robust to deal with such non-natural features. Text has the property different from natural images acquired from camera sensors or generated by computer graphics. In other words, due to inherent characteristics of the texts, the best solution is not to convert into 3D, thereby displaying them in 2D. This paper presents a novel methodology of converting non-natural images mixed with texts and images into 3D. For performance evaluation, more than 8,000 images were captured from diverse webpages containing subimages and texts. As well, 3,000 natural images were tested. Experiment performed on those images demonstrates that the detection ratio of non-natural images is 97% and that of subimages reaches 98%. Furthermore, a conversion scheme suitable to non-natural images is proposed. © 2014 ISSN 1881-803X.

SCOPUS_ID:62349113827

2DVTE: A two-directional videotext extractor for rapid and elaborate design

In video indexing and summarization, videotext is the very compact and accurate information. Most videotext detection and extraction methods only deal with the static videotext on video frames. Few methods can handle motion videotext efficiently since motion videotext is hardly extracted well. In this paper, we propose a two-directional videotext extractor, called 2DVTE. It is developed as an integrated system to detect, localize and extract the scrolling videotexts. First, the detection method is carried out by edge information to classify regions into text and non-text regions. Second, referring to the localization on scrolling videotext, we propose the two-dimensional projection profile method with horizontal and vertical edge map information. Considering the characteristics of Chinese text, the vertical edge map is used to localize the possible text region and horizontal edge map is used to refine the text region. Third, the extraction method consists of dual mode adaptive thresholding and multi-seed filling algorithm. In the dual mode adaptive thresholding, it produces the non-rectangle pattern to divide the background and foreground more precisely. Referring to the multi-seed filling algorithm, it is based on the consideration of the minimum and maximum length and four directions of the stroke while the previous method only considers the minimum length and two directions of the stroke. With this multi-seed exploitation on strokes, precise seeds are obtained to produce more sophisticated videotext. Considering high throughput and the low complexity issue, we can achieve a real-time system on detecting, localizing, and extracting the scrolling videotexts with only one frame usage instead of multi-frame integration in other literatures. According to the experiment results on various video sequences, all of the horizontal and vertical scrolling videotexts can be extracted precisely. We also make comparisons with other methods. In our analysis, the performance of our algorithm is superior to other existing methods in speed and quality. © 2008 Elsevier Ltd. All rights reserved.

SCOPUS_ID:85067986361

2ED: An efficient entity extraction algorithm using two-level edit-distance

Entity extraction is fundamental to many text mining tasks such as organisation name recognition. A popular approach to entity extraction is based on string matching against a dictionary of known entities. For approximate entity extraction from free text, considering solely character-based or solely token-based similarity cannot simultaneously deal with minor name variations at token-level and typos at character-level. Moreover, the tolerance of mismatch in character-level may be different from that in token-level, and the tolerance thresholds of the two levels should be able to be customised individually. In this paper, we propose an efficient character-level and token-level edit-distance based algorithm called FuzzyED. To improve the efficiency of FuzzyED, we develop various novel techniques including (i) a spanning-based candidate sub-string producing technique, (ii) a lower bound dissimilarity to determine the boundaries of candidate sub-strings, (iii) a core token based technique that makes use of the importance of tokens to reduce the number of unpromising candidate sub-strings, and (iv) a shrinking technique to reuse computation. Empirical results on real world datasets show that FuzzyED can efficiently extract entities and produce a high F1 score in the range of [0.91, 0.97].

SCOPUS_ID:85073779311

2Gather4Health: Automatic Web Identification of Solutions in Patient Innovation

Patient Innovation is an online open platform, with a community of over 60.000 users and more than 800 innovative solutions developed by patients and informal caregivers from all over the world. These solutions and/or creators were found by manually searching the Web through a combination of appropriate keywords and using experts to curate the results. In this paper we present a dedicated web-crawler architecture that includes a text classifier able to automatically identify Patient Innovation solutions from the web. The classifier is composed by a 2-layer hybrid MNB and Fuzzy Fingerprint classifier.

SCOPUS_ID:85149518374

2Going “Rogue”: National Parks, Discourses of American Identity and Resistance on Twitter

This chapter examines three ‘alternative’ national parks Twitter accounts created in response to censorship about climate change imposed by the Trump administration in 2017. Drawing on Critical Discourse Analysis and theory by Fairclough (Language and power. Longman, London, 1989), Tracy and Robles (Everyday talk: Building and reflecting identities. The Guilford Press, New York, 2013) and Foucault (The archaeology of knowledge. Pantheon, New York, 1972), this chapter finds that the tweets call upon ideas of US national identity through the use of themes like pristine wilderness, historic legacy and wisdom by past American leaders. The authors identify Twitter as a platform that allows a space for protest and collective resistance. The tweets engendered civic participation around a perspective counter to the official line, and in doing so, foregrounded a romanticized sense of national identity.

SCOPUS_ID:85043987757

2L-APD: A two-level plagiarism detection system for Arabic documents

Measuring the amount of shared information between two documents is a key to address a number of Natural Language Processing (NLP) challenges such as Information Retrieval (IR), Semantic Textual Similarity (STS), Sentiment Analysis (SA) and Plagiarism Detection (PD). In this paper, we report a plagiarism detection system based on two layers of assessment: 1) Fingerprinting which simply compares the documents fingerprints to detect the verbatim reproduction; 2) Word embedding which uses the semantic and syntactic properties of words to detect much more complicated reproductions. Moreover, Word Alignment (WA), Inverse Document Frequency (IDF) and Part-of-Speech (POS) weighting are applied on the examined documents to support the identification of words that are most descriptive in each textual unit. In the present work, we focused on Arabic documents and we evaluated the performance of the system on a data-set of holding three types of plagiarism: 1) Simple reproduction (copy and paste); 2) Word and phrase shuffling; 3) Intelligent plagiarism including synonym substitution, diacritics insertion and paraphrasing. The results show a recall of 88% and a precision of 86%. Compared to the results obtained by the systems participating in the Arabic Plagiarism Detection Shared Task 2015, our system outperforms all of them with a plagiarism detection score (Plagdet) of 83%.

SCOPUS_ID:85112730748

2LSPE: 2D Learnable Sinusoidal Positional Encoding using Transformer for Scene Text Recognition

Positional Encoding (PE) plays a vital role in a Transformer's ability to capture the order of sequential information, allowing it to overcome the permutation equivarience property. Recent state-of-the-art Transformer-based scene text recognition methods have leveraged the advantages of the 2D form of PE with fixed sinusoidal frequencies, also known as 2SPE, to better encode the 2D spatial dependencies of characters in a scene text image. These 2SPE-based Transformer frameworks have outperformed Recurrent Neural Networks (RNNs) based methods, mostly on recognizing text of arbitrary shapes; However, they are not tailored to the type of data and classification task at hand. In this paper, we extend a recent Learnable Sinusoidal frequencies PE (LSPE) from 1D to 2D, which we hereafter refer to as 2LSPE, and study how to adaptively choose the sinusoidal frequencies from the input training data. Moreover, we show how to apply the proposed Transformer architecture for scene text recognition. We compare our method against 11 state-of-the-art methods and show that it outperforms them in over 50% of the standard tests and are no worse than the second best performer, whereas we outperform all other methods on irregular text datasets (i.e., non horizontal or vertical layouts). Experimental results demonstrate that the proposed method offers higher word recognition accuracy (WRA) than two recent Transformer-based methods, and eleven state-of-theart RNN-based techniques on four challenging irregular-text recognition datasets, all while maintaining the highest WRA values on the regular-text datasets.

SCOPUS_ID:84901494107

2nd CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2013

The proceedings contain 44 papers. The special focus in this conference is on High Language Computing and Natural Language Processing. The topics include: language model for Cyrillic Mongolian to traditional Mongolian conversion; sentence compression based on ILP decoding method; Chinese negation and speculation detection with conditional random fields; Chinese argument extraction based on trigger mapping; exploring multiple Chinese word segmentation results based on linear model; structure-based web access method for ancient Chinese characters; simulated spoken dialogue system based on IOHMM with user history; a mixed model for cross lingual opinion analysis; semi-supervised text categorization by considering sufficiency and diversity; pseudo in-domain data selection from large-scale web corpus for spoken language translation; discriminative latent variable based classifier for translation error detection; incorporating entities in news topic modeling; an efficient framework to extract parallel units from comparable data; a method to construct Chinese-Japanese named entity translation equivalents using monolingual corpora; collective corpus weighting and phrase scoring for SMT using graph-based random walk; a simple, fast strategy for weighted alignment hypergraph; research on building family networks based on bootstrapping and co reference resolution; learning sentence representation for emotion classification on microblogs; every term has sentiment: learning from emoticon evidences for Chinese micro blog sentiment analysis; active learning for cross-lingual sentiment classification; expanding user features with social relationships in social recommender systems; a hybrid approach for extending ontology from text; linking entities in short texts based on a Chinese semantic knowledge base; entity linking from micro blogs to knowledge base using listnet algorithm; automatic assessment of information disclosure quality in Chinese annual reports; a fast matching method based on semantic similarity for short texts; query generation techniques for patent prior-art search in multiple languages; improve web search diversification with intent subtopic mining; understanding temporal intent of user query based on time-based query classification; study on Tibetan word segmentation as syllable tagging; the spoken/written language classification of English sentences with bilingual information; design and implementation of news-oriented automatic summarization system based on Chinese RSS; grey relational analysis for query expansion; a comprehensive method for text summarization based on latent semantic analysis; a time-sensitive model for micro blog retrieval; feature analysis in micro blog retrieval based on learning to rank; opinion sentence extraction and sentiment analysis for Chinese micro blogs; research on the opinion mining system for massive social media data and grammatical phrase-level opinion target extraction on Chinese micro blog messages.

SCOPUS_ID:85035775879

2nd Information Retrieval Facility Conference, IRFC 2011

The proceedings contain 11 papers. The special focus in this conference is on Information Retrieval Facility. The topics include: Search result caching in peer-to-peer information retrieval networks; building queries for prior-art search; expanding queries with term and phrase translations in patent retrieval; supporting Arabic cross-lingual retrieval using contextual information; combining interaction and content for feedback-based ranking; query expansion for language modeling using sentence similarities; word clouds of multiple search results; free-text search over complex web forms; multilingual document clustering using Wikipedia as external knowledge.

SCOPUS_ID:85034980171

2nd International Colloquium on Automata, Languages and Programming, ICALP 1974

The proceedings contain 47 papers. The special focus in this conference is on Automata, Languages and Programming. The topics include: Dynamic programming schemata; semantic characterization of flow diagrams and their decomposability; On the most recent property of ALGOL-like programs; langages sans etiquettes et transformations de programmes; relations between semantics and complexity of recursive programs-; preface; the generative power of two-level grammars; on the relation between direct and continuation semantics; graph representation and computation rules for typeless recursive languages; application of Church-Rosser properties to increase the parallelism and efficiency of algorithms; combinatorial problems, combinator equations and normal forms; algorithmes d'Equivalence et de reduction a des expressions minimales dans une classe d'equations recursives simples; automatic generation of multiple exit parsing subroutines; production prefix parsing: Extended abstract; On eliminating unit productions from LR(k) parsers; deterministic techniques for efficient non-deterministic parsers; file organization, an application of graph theory; a generalisation of Parikh's theorem in formal language theory; characterizations of time-bounded computations by limited primitive recursion; on maximal merging of information in Boolean computations; on simple Goedel numberings and translations; the ‘almost all’ theory of subrecursive degrees is decidable; the computational complexity of program schemata; un resultat en theorie des groupes de permutations et son application au calcul effectif du groupe d'automorphismes d'un automate fini; sur l'Application du theoreme de suschkewitsch a l'etude des codes rationnels complets; composition of automata; context-free grammar forms; une suite decroissante de cônes rationnels; checking stacks and context-free programmed grammars accept p-complete languages; Komplexitätsmaße for Ausdrocke; Operators reducing generalized OL-systems.

SCOPUS_ID:85028693357

2nd International Colloquium on Grammatical Inference, ICGI 1994

The proceedings contain 26 papers. The special focus in this conference is on Grammatical Inference. The topics include: Learning morphology — practice makes good; a hierarchy of language families learnable by regular language learners; a characterization of even linear languages and its application to the learning problem; object-oriented inferences in a logical framework for feature grammars; automatic determination of a stochastic bi-gram class language model; the acquisition of a lexicon from paired phoneme sequences and semantic representations; inference and estimation of a long-range trigram model; application of OSTIA to machine translation tasks; inducing probabilistic grammars by Bayesian model merging; statistical estimation of stochastic context-free grammars using the inside-outside algorithm and a transformation on grammars; statistical inductive learning of regular formal languages; learning stochastic regular grammars by means of a state merging method; a comparison of syntactic and statistical techniques for off-line ocr; dynamic grammatical representations in guided propagation networks; a hybrid connectionist-symbolic approach to regular grammatical inference based on neural learning and hierarchical clustering; inference of context-free grammars by enumeration; representational issues for context free grammar induction using genetic algorithms; regular grammatical inference from positive and negative samples by genetic search; learning unification-based grammars using the spoken English corpus and stochastic optimization of a probabilistic language model.

SCOPUS_ID:84944075759

2nd International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, AH 2002

The proceedings contain 94 papers. The special focus in this conference is on Adaptive Hypermedia and Adaptive Web-Based Systems. The topics include: Adaptive linking between text and photos using common sense reasoning; resource-adaptive interfaces to hybrid navigation systems; ubiquitous user assistance in a tourist information server; automatic extraction of semantically-meaningful information from the web; towards open adaptive hypermedia; some results from the evaluation of a dynamic hypertext system; methodology for developing adaptive educational-game environments; a framework and its application to tourist services; adaptive authoring of adaptive educational hypermedia; hypermedia presentation adaptation on the semantic web; user data management and usage model acquisition in an adaptive educational collaborative environment; personalizing assessment in adaptive educational hypermedia systems; visual based content understanding towards web adaptation; knowledge modeling for open adaptive hypermedia; tracking changing user interests through prior-learning of context; prediction of navigation profiles in a distributed internet environment through learning of graph distributions; a goal-oriented search engine with commonsense; on adaptability of web sites for visually handicapped people; a framework for filtering and packaging hypermedia documents; adaptation in an evolutionary hypermedia system; evaluating the effects of open student models on learning; ephemeral and persistent personalization in adaptive information access to scholarly publications on the web; solving the navigation problemfor wireless portals; towards an adaptive web training environment based on cognitive style of learning; on evaluating adaptive systems for education and a scrutable adaptive hypertext.

SCOPUS_ID:84945175726

2nd International Conference on Advances in Speech and Language Technologies for Iberian Languages, IberSPEECH 2014

The proceedings contain 29 papers. The special focus in this conference is on Speech Production, Analysis, Coding and Synthesis. The topics include: Analysis and synthesis of emotional speech in Spanish for the chat domain; developing a basque tts for the navarro-lapurdian dialect; fine vocoder tuning for hmm-based speech synthesis; statistical text-to-speech synthesis of spanish subtitles; unsupervised accent modeling for language identification; global speaker clustering towards optimal stopping criterion in binary key speaker diarization; on the use of convolutional neural networks in pairwise language recognition; phoneme-lattice to phoneme-sequence matching algorithm based on dynamic programming; deep maxout networks applied to noise-robust speech recognition; a deep neural network approach for missing-data mask estimation on dual-microphone smartphones; language model adaptation for lecture transcription by document retrieval; articulatory feature extraction from voice and their impact on hybrid acoustic models; CVX-optimized beamforming and vector taylor series compensation with German asr employing star-shaped microphone array; flexible stand-alone keyword recognition application using dynamic time warping; confidence measures in automatic speech recognition systems for error detection in restricted domains; recognition of distant voice commands for home applications in Portuguese; assessing the applicability of surface EMG to tongue gesture detection; towards cross-lingual emotion transplantation; a preliminary study of acoustic events classification with factor analysis in meeting rooms; a spoken language database for research on moderate cognitive impairment and bootstrapping a Portuguese wordnet from galician, Spanish and English wordnets.

SCOPUS_ID:84947744813

2nd International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2001

The proceedings contain 53 papers. The special focus in this conference is on Computational Linguistic Theories and Semantics. The topics include: What is a natural language and how to describe it; a fully lexicalized grammar for french based on meaning-text theory; modeling the level of involvement of verbal arguments; magical number seven plus or minus two; spatio-temporal indexing in database semantics; russellian and strawsonian definite descriptions in situation semantics; treatment of personal pronouns based on their parameterization; modeling textual context in linguistic pattern matching; statistical methods in studying the semantics of size adjectives; numerical model of the strategy for choosing polite expressions; outstanding issues in anaphora resolution; a NLP system for spanish; belief revision on anaphora resolution; a machine-learning approach to estimating the referential properties of japanese noun phrases; lexical semantic ambiguity resolution with bigram-based decision trees; interpretation of compound nominals using wordnet; specification marks for word sense disambiguation; three mechanisms of parser driving for structure disambiguation; recent research in the field of example-based machine translation; intelligent case based machine translation system; a hierarchical phrase alignment from english and japanese bilingual text; title generation using a training corpus; a new approach in building a corpus for natural language generation systems; a study on text generation from non-verbal information on 2d charts; interactive multilingual generation; a computational feature analysis for multilingual character-to-character dialogue and experiments on extracting knowledge from a machine-readable dictionary of synonym differences.

SCOPUS_ID:84943167639

2nd International Conference on Natural Language Processing, NLP 2000

The proceedings contain 39 papers. The special focus in this conference is on Tokenization, Morphological Analysis, Lexical Knowledge Representation and Parsing. The topics include: Universal segmentation of text with the sumo formalism; functional decomposition and lazy word-parsing in modern Greek; recognition and acquisition of compound names from corpora; use of a morphosyntactic lexicon as the basis of the implementation of the Greek wordnet; some principles for implementing underspecification in NLP systems; Monte Carlo sampling for np-hard maximization problems in the framework of weighted parsing; preprocessing for unification parsing of spoken language; a semantic based approach for spontaneous spoken dialogue understanding; a practical chunker for unrestricted text; an incremental discourse parser architecture; a spatio-temporal model for the representation of situations described in narrative texts; enhancing preference-based anaphora resolution with genetic algorithms; anaphora resolution through dialogue adjacency pairs and topics; semantic knowledge-driven method to solve pronominal anaphora in Spanish texts; processing of Spanish definite descriptions with the same head; constraints, linguistic theories and natural language processing; constitution and exploitation of annotation system of electronic corpora; toward automatic generation of understandable pronouns in French language; contextual reasoning in speech-to-speech translation; improving the accuracy of speech recognition systems for professional translators; generic parsing and hybrid transfer in automatic translation; corpus-based methodology in the study and design of systems with emulated linguistic competence and dialogues for embodied agents in virtual environments.

SCOPUS_ID:84942856590

2nd Mexican International Conference on Artificial Intelligence, MICAI 2002

The proceedings contain 56 papers. The special focus in this conference is on Robotics, Computer Vision, Heuristic Search and Optimization and Speech Recognition and Natural Language. The topics include: Motion planning for car-like robots using lazy probabilistic roadmap method; a vision system for environment representation; adapting the messy genetic algorithm for path planning in redundant and non-redundant manipulators; path planning using a single-query bi-directional lazy collision checking planner; an exploration approach for indoor mobile robots reducing odometric errors; feature matching using accumulation spaces; on selecting an appropriate colour space for skin detection; a methodology for the statistical characterization of genetic algorithms; a methodology to parallelize simulated annealing and its application to the traveling salesman problem; a cultural algorithm for constrained optimization; penalty function methods for constrained optimization with genetic algorithms; automatic generation of control parameters for the threshold accepting algorithm; genetic algorithms and case-based reasoning as a discovery and learning machine in the optimization of combinational logic circuits; time-domain segmentation and labelling of speech with fuzzy-logic post-correction rules; evaluation for Spanish-english pronominal anaphora generation; out-of-vocabulary word modeling and rejection for Spanish keyword spotting systems; detecting deviations in text collections; using long queries in a passage retrieval system; a hybrid treatment of evolutionary sets; games and logics of knowledge for multi-agent systems; modelling learners of a control task with inductive logic programming; simple epistemic logic for relational database and flexible agent programming in linear logic.

http://arxiv.org/abs/2301.06790v1

2nd Swiss German Speech to Standard German Text Shared Task at SwissText 2022

We present the results and findings of the 2nd Swiss German speech to Standard German text shared task at SwissText 2022. Participants were asked to build a sentence-level Swiss German speech to Standard German text system specialized on the Grisons dialect. The objective was to maximize the BLEU score on a test set of Grisons speech. 3 teams participated, with the best-performing system achieving a BLEU score of 70.1.

https://aclanthology.org//2020.nl4xai-1.0/

2nd Workshop on Interactive Natural Language Technology for Explainable Artificial Intelligence

SCOPUS_ID:85146231277

2nd Workshop on Sentiment Analysis and Linguistic Linked Data, SALLD 2022 - held in conjunction with the International Conference on Language Resources and Evaluation, LREC 2022 - Proceedings

The proceedings contain 6 papers. The topics discussed include: from data to meaning in representation of emotions; O-Dang! the ontology of dangerous speech messages; movie rating prediction using sentiment features; evaluating a new Danish sentiment resource: the Danish sentiment lexicon, DSL; correlating facts and social media trends on environmental quantities leveraging commonsense reasoning and human sentiments; and sentiment analysis of Serbian old novels.

SCOPUS_ID:85075483985

2nd Workshop on knowledge-aware and conversational recommender systems - KaRS

Over the last years, we have been witnessing the advent of more and more precise and powerful recommendation algorithms and techniques able to effectively assess users' tastes and predict information that would probably be of interest for them. Most of these approaches rely on the collaborative paradigm (often exploiting machine learning techniques) and do not take into account the huge amount of knowledge, both structured and non-structured ones, describing the domain of interest of the recommendation engine. Although very effective in in predicting relevant items, collaborative approaches miss some very interesting features that go beyond the accuracy of results and move into the direction of providing novel and diverse results as well as generating an explanation for the recommended items or support interactive and conversational recommendation processes.

SCOPUS_ID:84940461099

3-D object retrieval using topic model

In the last few years, extensive effort has been spent to develop better performed 3-D object retrieval methods. View-based methods have attracted a significant amount of attention, not only because their state-of-art performance, but also they merely require some of a 3-D object’s 2-D view images. However, most recent approaches only deal with the images’ primordial-extracted features and ignore their hidden relationships. Considering these latent characters, a visual-topic-model 3-D object retrieval approach is introduced in this paper. In this framework, dense scale invariant feature transform(dense-SIFT) descriptors are extracted from a set of views of each 3-D object, and all the dense-SIFT descriptors are grouped into bag-of-word features using k-means clustering. Then, the topic distribution of a 3-D object is generated via latent dirichlet allocation (LDA) given its bag-of-word features. Gibbs sampling is applied in the learning and inference processing of LDA. We conduct experiments on the Princeton Shape Benchmark (PSB) and National Taiwan University 3D model database (NTU), and the experimental results demonstrate that the proposed method can achieve better retrieval effectiveness than the state-of-the-art methods under several standard evaluation measures.

SCOPUS_ID:85099330086

3-D sound image localization in reproduction of 22.2 multichannel audio based on room impulse response generation with vector composition

To simplify content creation processes and improve the realism of 22.2 multichannel system, a method to localize sound images is derived in this paper, which is an improvement of the method based on vector base amplitude panning. The sound image localization can be realized by a specific direction and distance. A sound field is simulated to make spatial impressions in 22.2 multichannel reproduction, which includes reflection and reverberation, and the simulation approach is based on room impulse response generation with vector composition. To control the sound pressure on the ears of the listener, the amplitude of the input signal is attenuated in advance by the distance of sound image. Evaluation experiments were carried out both subjectively and objectively with binaural recording. The improvement in the reproduction of sound image's distance is realized, while the direction of the sound image stays the same as the method based on vector base amplitude panning.

SCOPUS_ID:84961156299

3-step parallel corpus cleaning using monolingual crowd workers

A high-quality parallel corpus needs to be manually created to achieve good machine translation for the domains which do not have enough existing resources. Although the quality of the corpus to some extent can be improved by asking the professional translators to translate, it is impossible to completely avoid making any mistakes. In this paper, we propose a framework for cleaning the existing professionally-translated parallel corpus in a quick and cheap way. The proposed method uses a 3-step crowdsourcing procedure to efficiently detect and edit the translation flaws, and also guarantees the reliability of the edits. The experiments using the fashion-domain e-commerce-site (EC-site) parallel corpus show the effectiveness of the proposed method for the parallel corpus cleaning.

SCOPUS_ID:85067001282

30 years of contemporary hospitality management: Uncovering the bibliometrics and topical trends

Purpose: This paper aims to showcase the trends in the research topics and their contributors over a time period of 30 years in the International Journal of Contemporary Hospitality Management (IJCHM). To be specific, this paper uncovers IJCHM’s latent topics and hidden patterns in published research and highlights the differences across three decades and before and after Social Sciences Citation indexing. Design/methodology/approach: In total, 1,573 documents published over 199 issues of IJCHM were analyzed using two computational tools, i.e. metaknowledge and structural topic modeling (STM), as the basis of the mixed method. STM was used to discover the evolution of topics over time. Moreover, bibliometrics (and network analysis) were used to highlight IJCHM’s top researchers, top-cited references, the geographical networks of the researchers and differences in the collaborative networks. Findings: The number of papers published continually increased over time with changes of key researchers publishing in IJCHM. The co-authorship networks have also changed and revealed an increasing diversity of authorship and collaborations among authors in different countries. Moreover, the variety of topics and the relative weight of each topic have also changed. Research limitations/implications: Based on the findings of this study, theoretical and practical implications for hospitality and tourism researchers are provided. Originality/value: It is the first attempt to apply topic modeling to a leading academic journal in hospitality and tourism and explore the diversity in contemporary hospitality management research (topics and contributors) from 30 years of published research.

SCOPUS_ID:85130267381

30 years of hungarian cognitive psychology (1990-2020)

The review paper surveys the last 30 years of Hungarian cognitive psychology. Institutionally, support by the Soros foundation in the 90s for the university cognitive programs had as one consequence that three departments of cognition are active in Budapest today. Another aspect of insitutional development was the series of multidisciplinary conferences in Hungary (MAKOG), and Hungarian involvement in international graduate training programs in cognitive science. In its scientific substance, Hungarian cognitive research, like elsewhere in the world, moved from unanchored pure cognitive models towards neural, developmental, social, and evolutionary interpretations, partly also influenced by Hungarian traditions. Some of the most important domains of Hungarian cognitive research are perception, especially studies on the development of vision and hearing (Kovács, Winkler), neuropsychological interpretation of memory inhibition and implicit memory systems (Racsmány, Németh). In psycholinguistics, issues of Hungarian morphology and sentence processing were integrated in models of understanding (Pléh, Lukács, Gergely), alongside with a developmental and clinical characterization of Hungarian spatial language (Pléh, Lukács). Figurative language use was extensively studied in psychopathological contexts (Schnell), and a model was developed towards a neuropsychological separation of metaphoricity and frequency issues (Forgács). The most important results of developmental psycholinguistics are related to the role of ToM in early language acquisition (Kovács, Téglás, Király, Forgács). Contrastive studies also clarified that problems with language development in Williams syndrome, and the so called SLI (Lukács, Racsmány, Ladányi) are related to the modulating role of the working memory system and to general learning disturbances, with a special regard to disorders of procedural systems (Lukács, Racsmány, Ladányi). The involvement of this later system in several neurologically conditioned language disturbances was also observed (Janacsek, Németh, Lukács).

SCOPUS_ID:85046549701

3000PA-Towards a national reference corpus of German clinical language

We introduce 3000PA, a clinical document corpus composed of 3,000 EPRs from three different clinical sites, which will serve as the backbone of a national reference language resource for German clinical NLP. We outline its design principles, results from a medication annotation campaign and the evaluation of a first medication information extraction prototype using a subset of 3000PA.

SCOPUS_ID:85101222129

30th Annual European Conference on Information Retrieval, ECIR 2008

The proceedings contain 87 papers. The special focus in this conference is on Information Retrieval. The topics include: The proceedings contain 87 papers. The special focus in this conference is on Information Retrieval. The topics include: Here or there; using clicks as implicit judgments: expectations versus observations; clustering template based web documents; effective pre-retrieval query performance prediction using similarity and variability evidence; labeling categories and relationships in an evolving social network; automatic construction of an opinion-term vocabulary for ad hoc retrieval; a comparison of social bookmarking with traditional search; exploring the effects of language skills on multilingual web search; utilizing passage-based language models for document retrieval; a statistical view of binned retrieval models; video corpus annotation using active learning; automatic extraction of domain-specific stopwords from labeled documents; using a task-based approach in evaluating the usability of bobis in an e-book environment; exploiting locality of Wikipedia links in entity ranking; the importance of link evidence in Wikipedia; high quality expertise evidence for expert search; associating people and documents; modeling documents as mixtures of persons for expert finding; ranking users for intelligent message addressing; viewing term proximity from a different perspective; extending probabilistic data fusion using sliding windows; semi-supervised document classification with a mislabeling error model; improving term frequency normalization for multi-topical documents and application to language modeling approaches; probabilistic document length priors for language models; computing information retrieval performance measures efficiently in the presence of tied scores and towards characterization of actor evolution and interactions in news corpora.

SCOPUS_ID:85138685409

31st International Conference on Artificial Neural Networks, ICANN 2022

The proceedings contain 259 papers. The special focus in this conference is on Artificial Neural Networks. The topics include: From Open Set Recognition Towards Robust Multi-class Classification; gait Adaptation After Leg Amputation of Hexapod Walking Robot Without Sensory Feedback; hierarchical Dynamics in Deep Echo State Networks; jacobian Ensembles Improve Robustness Trade-Offs to Adversarial Attacks; liquid State Machine on Loihi: Memory Metric for Performance Prediction; LogBERT-BiLSTM: Detecting Malicious Web Requests; ML-FORMER: Forecasting by Neighborhood and Long-Range Dependencies; cross-Domain Learning for Reference-Based Sketch Colorization with Structural and Colorific Strategy; Real-Time Display of Spiking Neural Activity of SIMD Hardware Using an HDMI Interface; sailfish: A Fast Bayesian Change Point Detection Framework with Gaussian Process for Time Series; SAM-kNN Regressor for Online Learning in Water Distribution Networks; spatial-Temporal Semantic Generative Adversarial Networks for Flexible Multi-step Urban Flow Prediction; topic-Grained Text Representation-Based Model for Document Retrieval; training 1-Bit Networks on a Sphere: A Geometric Approach; a Neural Network Approach to Estimating Color Reflectance with Product Independent Models; linear Self-attention Approximation via Trainable Feedforward Kernel; data Augmented Dual-Attention Interactive Image Classification Network; Deep Dictionary Pair Learning for SAR Image Classification; deepfake Video Detection Exploiting Binocular Synchronization; preface; adaptive Channel Encoding Transformer for Point Cloud Analysis; dep-ViT: Uncertainty Suppression Model Based on Facial Expression Recognition in Depression Patients; ensemble of One-Class Classifiers Based on Multi-level Hidden Representations Abstracted from Convolutional Autoencoder for Anomaly Detection; Images Structure Reconstruction from fMRI by Unsupervised Learning Based on VAE; inter-subtask Consistent Representation Learning for Visual Commonsense Reasoning; invisibiliTee: Angle-Agnostic Cloaking from Person-Tracking Systems with a Tee; makeup Transfer Based on Generative Adversarial Network for Large Angle Spatial Misalignment; making Images Resilient to Adversarial Example Attacks; multi-Class Lane Semantic Segmentation of Expressway Dataset Based on Aerial View.

SCOPUS_ID:85066142191

32nd Canadian Conference on Artificial Intelligence, Canadian AI 2019

The proceedings contain 69 papers. The special focus in this conference is on Artificial Intelligence. The topics include: Automatically Learning a Human-Resource Ontology from Professional Social-Network Data; efficient Transformer-Based Sentence Encoding for Sentence Pair Modelling; instance Ranking and Numerosity Reduction Using Matrix Decomposition and Subspace Learning; hybrid Temporal Situation Calculus; 3D Depthwise Convolution: Reducing Model Parameters in 3D Vision Tasks; identifying Misaligned Spans in Parallel Corpora Using Change Point Detection; in Vino Veritas: Estimating Vineyard Grape Yield from Images Using Deep Learning; options in Multi-task Reinforcement Learning - Transfer via Reflection; the Invisible Power of Fairness. How Machine Learning Shapes Democracy; weakly Supervised, Data-Driven Acquisition of Rules for Open Information Extraction; maize Insects Classification Through Endoscopic Video Analysis; collaborative Clustering Approach Based on Dempster-Shafer Theory for Bag-of-Visual-Words Codebook Generation; memory-Efficient Backpropagation for Recurrent Neural Networks; a Behavior-Based Proactive User Authentication Model Utilizing Mobile Application Usage Patterns; sparseout: Controlling Sparsity in Deep Networks; crowd Prediction Under Uncertainty; optimized Random Walk with Restart for Recommendation Systems; inter and Intra Document Attention for Depression Risk Assessment; a Shallow Learning - Reduced Data Approach for Image Classification; multi-class Ensemble Learning of Imbalanced Bidding Fraud Data; measuring Human Emotion in Short Documents to Improve Social Robot and Agent Interactions; towards Causal Analysis of Protocol Violations; lexicographic Preference Trees with Hard Constraints; supervised Versus Unsupervised Deep Learning Based Methods for Skin Lesion Segmentation in Dermoscopy Images; lifted Temporal Maximum Expected Utility; automatic Generation of Video Game Character Images Using Augmented Structure-and-Style Networks; detecting Depression from Voice.

SCOPUS_ID:84897638712

32nd International Convention Proceedings: Computers in Education

The proceedings contain 315 papers. The special focus in this conference is on Information and Communication Technology, Electronics and Microelectronics. The topics include: Croatian semiconductor industry cluster; rare-earth-activated nano-structures fabricated by sol-gel route; applications and recent developments in THz research; electrical activation of phosphorus by rapid thermal annealing of doped amorphous silicon films; resonant optical absorption in molecular nanofilms; Raman scattering on porous silicon; modeling of the effect of radicals on plasmas used for etching in micro-electronics; a method of slow-switching interface traps identification in silicon carbide MOS structures; strain and deformation measurement using intrinsic fiber optic low coherence interferometric sensor; modeling of gate leakage current in high-K dielectrics; compact capacitance model for drain-induced barrier-lowering of vertical SONFET; stress effect in ultra-narrow finFET structures; quantum confinement and scaling effects in ultra-thin body double-gate finFETs; optofiber-and-LED device for study of non-phototoxic photosensitizers biodistributions in bio-objects; design and characterization of soil moisture sensor using PCB technology; characterization of temperature sensor using Vt extractor device; an integrated thin film Pt/Ti heater; synthesis of DC power converters without galvanic insulation; microcontroller controlled capacitance decade box; part average analysis in multilayer ceramic manufacturing for automotive industry; improved linearity active resistors using MOS and FGMOS transistors; possibilities of current measurement in CMOS design using current mirrors and comparators; advantages and limitations of the SCW charge pump; tunable gm-C filter using FGMOS based operational transconductance amplifier; a charge-sensitive amplifier associated with APD or PMT for positron emission tomography scanners; efficient and reusable offset cancellation method implemented in CMOS design; kernighan-lin algorithm for n-way circuit partitioning; measuring and modelling of a PCB via structure; analog to digital conversion, synchronization and control and algorithm for hardware realization; AI - look over hardware design - agent with state; fault diagnosis and isolation of the marine diesel engine turbocharger system; UML modeling in design of error detection and correction circuits; the impact of multi-core processor on web server performance; the UK particle physics grid; enabling numerical modeling of mantle convection on the grid; a lightweight specialized meta-scheduler for 3D image rendering applications; the virtualization of computing cluster resources for integration in grid environment; transactional distributed memory management for cluster operating systems; a grid portal for genetic analysis of complex traits; error analysis of quasirandom walks on balls; using sobol sequence in grid environment; towards china's railway freight transportation information grid; fast system matrix generation on a GPU cluster; visualization as a sequence application for grid-based parametric studies; remote graphical visualization of interactive virtual geographical space; a data management and visualization system towards online microscopic imaging; protein data bank graphics generator on grid; real-time evaluation of L-system scene models in online multiplayer games; parallel formulation of 3D implicit function visualization; displaying large amounts of spatial data in GIS; intelligent algorithm for smoke extraction in autonomous forest fire detection; correction of digital images by arbitrary degree Bezier polynomial; wide-view visual systems for flight simulation; visualization of voltage profile and power flow in Croatian power system; network architecture evolution strategy in fixed networks; fireflies synchronization in small overlay networks; capabilities and impacts of EDGE evolution toward seamless wireless networks; adaptable architecture of provisioning system; selecting technology for interactive web application development; objective assessment of speech and audio quality; queue length influence in RED congestion avoidance algorithm; network problems frequency detection using apriori algorithm; radio over fiber technology for wireless access; reliability and scalability of DHCP access model in broadband network; success model of information system implementation; implementation of a GSM-based remotely controlled and monitored machine system; information management to reduce uncertainty in military systems; system for remote supervision and control of power electronics devices; adapting agile practices in globally distributed large scale software development; using static code analysis tools to increase source code maintainability; first time right in AXE using one track and stream line development; collecting of content enterprise knowledge by using metadata; realizacija slozenih procesa uklju_enja kroz sustave za podrsku; problems and possible solutions in offering netphone packages service; specificities of the new complex software based services implementation at mobile operators; dijagnosticiranje i rjesavanje problema u prijenosu audio signala internet protokolom; simulation of DVB-T transmission in matlab; simulators for solving traveling salesman problem variations with various graph search methods; a survey of software quality assessment; identification of persons and business subjects in text documents based on lexical analysis and scoring system; implementation of agent tehnology in web portals for data analysis and consulting; process entropy and informational macrodynamics in a ceramic tile plant; control of single-input-single-output systems with actuator saturation; design space exploration of a multi-core JPEG; 3D optoelectronic method for the steel strip flatness measurement; voltage control of a DC/DC boost converter powered by fuel cell stack; control of a standalone DC voltage source with fuel cell stack; earth fault location in medium voltage distribution networks; review of active vibration control; active control of periodic vibrations based on synchronous averaging of residual signal; energy efficient sensor based control of a greenhouse; electric power distribution protective devices allocation with genetic algorithms; upravljanje jednostavnim procesima putem GSM uredaja; upravljanje sustavom distribucije cementa; upravljanje kvalitetom vazduha u urbano - industrijskim centrima; intelligent control system, data acquisition system and data output system; tagging multimedia stimuli with ontologies; automatic generation of part-whole hierarchies for domain ontologies using web search data; a storage algorithm for a kanerva-like memory model; managing electromagnetic field pollution using genetic algorithm; evolutionary algorithm aided design of multi-switch controller; automatic diagnosis of power transformers based on dissolved gas analysis first level of diagnosis using VAC and VEV inference methods; building an expert system module for world ocean thermocline analysis; precision static and dynamic optical measurement and 3D imaging of reflective surfaces; agent based intelligent forest fire monitoring system; false alarms reduction in forest fire video monitoring system; automatic adjustment of detection parameters in forest fire video monitoring system; vehicle following control considering relative sensor information only; hidden Markov models and convolutional neural network approaches to face recognition tasks solution; digital system of textile fibers identification; exploring string and word kernels on Croatian-English parallel corpus; memetic algorithm for grammatical inference; grapheme-to-phoneme conversion for Croatian speech synthesis; uniform modified method for handwritten text reference line detection; peer assessment system for modern learning settings; semantic metadata for e-learning content; computers in education of children with intellectual and related developmental disorders; avatars and identification in online communication; research regarding introduction of electronic information at the university of jurja dobrile in pula; employment system and needs for ICT labour in the republic of Croatia; parameters estimation according to Engels law in excel; integration of business processes modelling into education; experience with the distance learning bachelor study in the field of finance, banking and investment; combining e-material and data acquisition module to support the educational process; digital repositories and possibilities of their integration into higher education; econometric analysis of the public sector economy in SPSS and excel; integrating protein visualization in the classroom with starbiochem; using web content management systems in university e-commerce courses; computer classroom management and virtualization and visualization in education; teaching, correcting and improving your language competences by means of the internet; an application of excel and VBA in comparison of lattice based option pricing models; implementation of distance learning materials; aesthetic principle in design of distance learning material; capacity testing/planning for successful implementation of LMS/CMS; using multiple-choice tests at university level courses preparation and supporting infrastructure; conceptualisation of learning context in e-learning; how digital immigrants learned to make games for digital natives; document management and exchange system - supporting education process; development of the computer aided system for controlled strikes exercises; adaption in IS integration and enterprise migration; demographic characteristics and internet access of high school teachers and their ICT competencies; advantages and disadvantages of distance learning.

SCOPUS_ID:84897617053

32nd International Convention Proceedings: Computers in Technical Systems and Intelligent Systems

The proceedings contain 315 papers. The special focus in this conference is on Information and Communication Technology, Electronics and Microelectronics. The topics include: Croatian semiconductor industry cluster; rare-earth-activated nano-structures fabricated by sol-gel route; applications and recent developments in THz research; electrical activation of phosphorus by rapid thermal annealing of doped amorphous silicon films; resonant optical absorption in molecular nanofilms; Raman scattering on porous silicon; modeling of the effect of radicals on plasmas used for etching in micro-electronics; a method of slow-switching interface traps identification in silicon carbide MOS structures; strain and deformation measurement using intrinsic fiber optic low coherence interferometric sensor; modeling of gate leakage current in high-K dielectrics; compact capacitance model for drain-induced barrier-lowering of vertical SONFET; stress effect in ultra-narrow finFET structures; quantum confinement and scaling effects in ultra-thin body double-gate finFETs; optofiber-and-LED device for study of non-phototoxic photosensitizers biodistributions in bio-objects; design and characterization of soil moisture sensor using PCB technology; characterization of temperature sensor using Vt extractor device; an integrated thin film Pt/Ti heater; synthesis of DC power converters without galvanic insulation; microcontroller controlled capacitance decade box; part average analysis in multilayer ceramic manufacturing for automotive industry; improved linearity active resistors using MOS and FGMOS transistors; possibilities of current measurement in CMOS design using current mirrors and comparators; advantages and limitations of the SCW charge pump; tunable gm-C filter using FGMOS based operational transconductance amplifier; a charge-sensitive amplifier associated with APD or PMT for positron emission tomography scanners; efficient and reusable offset cancellation method implemented in CMOS design; kernighan-lin algorithm for n-way circuit partitioning; measuring and modelling of a PCB via structure; analog to digital conversion, synchronization and control and algorithm for hardware realization; AI - look over hardware design - agent with state; fault diagnosis and isolation of the marine diesel engine turbocharger system; UML modeling in design of error detection and correction circuits; the impact of multi-core processor on web server performance; the UK particle physics grid; enabling numerical modeling of mantle convection on the grid; a lightweight specialized meta-scheduler for 3D image rendering applications; the virtualization of computing cluster resources for integration in grid environment; transactional distributed memory management for cluster operating systems; a grid portal for genetic analysis of complex traits; error analysis of quasirandom walks on balls; using sobol sequence in grid environment; towards china's railway freight transportation information grid; fast system matrix generation on a GPU cluster; visualization as a sequence application for grid-based parametric studies; remote graphical visualization of interactive virtual geographical space; a data management and visualization system towards online microscopic imaging; protein data bank graphics generator on grid; real-time evaluation of L-system scene models in online multiplayer games; parallel formulation of 3D implicit function visualization; displaying large amounts of spatial data in GIS; intelligent algorithm for smoke extraction in autonomous forest fire detection; correction of digital images by arbitrary degree Bezier polynomial; wide-view visual systems for flight simulation; visualization of voltage profile and power flow in Croatian power system; network architecture evolution strategy in fixed networks; fireflies synchronization in small overlay networks; capabilities and impacts of EDGE evolution toward seamless wireless networks; adaptable architecture of provisioning system; selecting technology for interactive web application development; objective assessment of speech and audio quality; queue length influence in RED congestion avoidance algorithm; network problems frequency detection using apriori algorithm; radio over fiber technology for wireless access; reliability and scalability of DHCP access model in broadband network; success model of information system implementation; implementation of a GSM-based remotely controlled and monitored machine system; information management to reduce uncertainty in military systems; system for remote supervision and control of power electronics devices; adapting agile practices in globally distributed large scale software development; using static code analysis tools to increase source code maintainability; first time right in AXE using one track and stream line development; collecting of content enterprise knowledge by using metadata; realizacija slozenih procesa uklju_enja kroz sustave za podrsku; problems and possible solutions in offering netphone packages service; specificities of the new complex software based services implementation at mobile operators; dijagnosticiranje i rjesavanje problema u prijenosu audio signala internet protokolom; simulation of DVB-T transmission in matlab; simulators for solving traveling salesman problem variations with various graph search methods; a survey of software quality assessment; identification of persons and business subjects in text documents based on lexical analysis and scoring system; implementation of agent tehnology in web portals for data analysis and consulting; process entropy and informational macrodynamics in a ceramic tile plant; control of single-input-single-output systems with actuator saturation; design space exploration of a multi-core JPEG; 3D optoelectronic method for the steel strip flatness measurement; voltage control of a DC/DC boost converter powered by fuel cell stack; control of a standalone DC voltage source with fuel cell stack; earth fault location in medium voltage distribution networks; review of active vibration control; active control of periodic vibrations based on synchronous averaging of residual signal; energy efficient sensor based control of a greenhouse; electric power distribution protective devices allocation with genetic algorithms; upravljanje jednostavnim procesima putem GSM uredaja; upravljanje sustavom distribucije cementa; upravljanje kvalitetom vazduha u urbano - industrijskim centrima; intelligent control system, data acquisition system and data output system; tagging multimedia stimuli with ontologies; automatic generation of part-whole hierarchies for domain ontologies using web search data; a storage algorithm for a kanerva-like memory model; managing electromagnetic field pollution using genetic algorithm; evolutionary algorithm aided design of multi-switch controller; automatic diagnosis of power transformers based on dissolved gas analysis first level of diagnosis using VAC and VEV inference methods; building an expert system module for world ocean thermocline analysis; precision static and dynamic optical measurement and 3D imaging of reflective surfaces; agent based intelligent forest fire monitoring system; false alarms reduction in forest fire video monitoring system; automatic adjustment of detection parameters in forest fire video monitoring system; vehicle following control considering relative sensor information only; hidden Markov models and convolutional neural network approaches to face recognition tasks solution; digital system of textile fibers identification; exploring string and word kernels on Croatian-English parallel corpus; memetic algorithm for grammatical inference; grapheme-to-phoneme conversion for Croatian speech synthesis; uniform modified method for handwritten text reference line detection; peer assessment system for modern learning settings; semantic metadata for e-learning content; computers in education of children with intellectual and related developmental disorders; avatars and identification in online communication; research regarding introduction of electronic information at the university of jurja dobrile in pula; employment system and needs for ICT labour in the republic of Croatia; parameters estimation according to Engels law in excel; integration of business processes modelling into education; experience with the distance learning bachelor study in the field of finance, banking and investment; combining e-material and data acquisition module to support the educational process; digital repositories and possibilities of their integration into higher education; econometric analysis of the public sector economy in SPSS and excel; integrating protein visualization in the classroom with starbiochem; using web content management systems in university e-commerce courses; computer classroom management and virtualization and visualization in education; teaching, correcting and improving your language competences by means of the internet; an application of excel and VBA in comparison of lattice based option pricing models; implementation of distance learning materials; aesthetic principle in design of distance learning material; capacity testing/planning for successful implementation of LMS/CMS; using multiple-choice tests at university level courses preparation and supporting infrastructure; conceptualisation of learning context in e-learning; how digital immigrants learned to make games for digital natives; document management and exchange system - supporting education process; development of the computer aided system for controlled strikes exercises.

SCOPUS_ID:84897632207

32nd International Convention Proceedings: Digital Economy 6th ALADIN, Information Systems Security, Business Intelligence Systems, Local Government and Student Papers

The proceedings contain 315 papers. The special focus in this conference is on Information and Communication Technology, Electronics and Microelectronics. The topics include: Croatian semiconductor industry cluster; rare-earth-activated nano-structures fabricated by sol-gel route; applications and recent developments in THz research; electrical activation of phosphorus by rapid thermal annealing of doped amorphous silicon films; resonant optical absorption in molecular nanofilms; Raman scattering on porous silicon; modeling of the effect of radicals on plasmas used for etching in micro-electronics; a method of slow-switching interface traps identification in silicon carbide MOS structures; strain and deformation measurement using intrinsic fiber optic low coherence interferometric sensor; modeling of gate leakage current in high-K dielectrics; compact capacitance model for drain-induced barrier-lowering of vertical SONFET; stress effect in ultra-narrow finFET structures; quantum confinement and scaling effects in ultra-thin body double-gate finFETs; optofiber-and-LED device for study of non-phototoxic photosensitizers biodistributions in bio-objects; design and characterization of soil moisture sensor using PCB technology; characterization of temperature sensor using Vt extractor device; an integrated thin film Pt/Ti heater; synthesis of DC power converters without galvanic insulation; microcontroller controlled capacitance decade box; part average analysis in multilayer ceramic manufacturing for automotive industry; improved linearity active resistors using MOS and FGMOS transistors; possibilities of current measurement in CMOS design using current mirrors and comparators; advantages and limitations of the SCW charge pump; tunable gm-C filter using FGMOS based operational transconductance amplifier; a charge-sensitive amplifier associated with APD or PMT for positron emission tomography scanners; efficient and reusable offset cancellation method implemented in CMOS design; kernighan-lin algorithm for n-way circuit partitioning; measuring and modelling of a PCB via structure; analog to digital conversion, synchronization and control and algorithm for hardware realization; AI - look over hardware design - agent with state; fault diagnosis and isolation of the marine diesel engine turbocharger system; UML modeling in design of error detection and correction circuits; the impact of multi-core processor on web server performance; the UK particle physics grid; enabling numerical modeling of mantle convection on the grid; a lightweight specialized meta-scheduler for 3D image rendering applications; the virtualization of computing cluster resources for integration in grid environment; transactional distributed memory management for cluster operating systems; a grid portal for genetic analysis of complex traits; error analysis of quasirandom walks on balls; using sobol sequence in grid environment; towards china's railway freight transportation information grid; fast system matrix generation on a GPU cluster; visualization as a sequence application for grid-based parametric studies; remote graphical visualization of interactive virtual geographical space; a data management and visualization system towards online microscopic imaging; protein data bank graphics generator on grid; real-time evaluation of L-system scene models in online multiplayer games; parallel formulation of 3D implicit function visualization; displaying large amounts of spatial data in GIS; intelligent algorithm for smoke extraction in autonomous forest fire detection; correction of digital images by arbitrary degree Bezier polynomial; wide-view visual systems for flight simulation; visualization of voltage profile and power flow in Croatian power system; network architecture evolution strategy in fixed networks; fireflies synchronization in small overlay networks; capabilities and impacts of EDGE evolution toward seamless wireless networks; adaptable architecture of provisioning system; selecting technology for interactive web application development; objective assessment of speech and audio quality; queue length influence in RED congestion avoidance algorithm; network problems frequency detection using apriori algorithm; radio over fiber technology for wireless access; reliability and scalability of DHCP access model in broadband network; success model of information system implementation; implementation of a GSM-based remotely controlled and monitored machine system; information management to reduce uncertainty in military systems; system for remote supervision and control of power electronics devices; adapting agile practices in globally distributed large scale software development; using static code analysis tools to increase source code maintainability; first time right in AXE using one track and stream line development; collecting of content enterprise knowledge by using metadata; realizacija slozenih procesa uklju_enja kroz sustave za podrsku; problems and possible solutions in offering netphone packages service; specificities of the new complex software based services implementation at mobile operators; dijagnosticiranje i rjesavanje problema u prijenosu audio signala internet protokolom; simulation of DVB-T transmission in matlab; simulators for solving traveling salesman problem variations with various graph search methods; a survey of software quality assessment; identification of persons and business subjects in text documents based on lexical analysis and scoring system; implementation of agent tehnology in web portals for data analysis and consulting; process entropy and informational macrodynamics in a ceramic tile plant; control of single-input-single-output systems with actuator saturation; design space exploration of a multi-core JPEG; 3D optoelectronic method for the steel strip flatness measurement; voltage control of a DC/DC boost converter powered by fuel cell stack; control of a standalone DC voltage source with fuel cell stack; earth fault location in medium voltage distribution networks; review of active vibration control; active control of periodic vibrations based on synchronous averaging of residual signal; energy efficient sensor based control of a greenhouse; electric power distribution protective devices allocation with genetic algorithms; upravljanje jednostavnim procesima putem GSM uredaja; upravljanje sustavom distribucije cementa; upravljanje kvalitetom vazduha u urbano - industrijskim centrima; intelligent control system, data acquisition system and data output system; tagging multimedia stimuli with ontologies; automatic generation of part-whole hierarchies for domain ontologies using web search data; a storage algorithm for a kanerva-like memory model; managing electromagnetic field pollution using genetic algorithm; evolutionary algorithm aided design of multi-switch controller; automatic diagnosis of power transformers based on dissolved gas analysis first level of diagnosis using VAC and VEV inference methods; building an expert system module for world ocean thermocline analysis; precision static and dynamic optical measurement and 3D imaging of reflective surfaces; agent based intelligent forest fire monitoring system; false alarms reduction in forest fire video monitoring system; automatic adjustment of detection parameters in forest fire video monitoring system; vehicle following control considering relative sensor information only; hidden Markov models and convolutional neural network approaches to face recognition tasks solution; digital system of textile fibers identification; exploring string and word kernels on Croatian-English parallel corpus; memetic algorithm for grammatical inference; grapheme-to-phoneme conversion for Croatian speech synthesis; uniform modified method for handwritten text reference line detection; peer assessment system for modern learning settings; semantic metadata for e-learning content; computers in education of children with intellectual and related developmental disorders; avatars and identification in online communication; research regarding introduction of electronic information at the university of jurja dobrile in pula; employment system and needs for ICT labour in the republic of Croatia; parameters estimation according to Engels law in excel; integration of business processes modelling into education; experience with the distance learning bachelor study in the field of finance, banking and investment; combining e-material and data acquisition module to support the educational process; digital repositories and possibilities of their integration into higher education; econometric analysis of the public sector economy in SPSS and excel; integrating protein visualization in the classroom with starbiochem; using web content management systems in university e-commerce courses; computer classroom management and virtualization and visualization in education; teaching, correcting and improving your language competences by means of the internet; an application of excel and VBA in comparison of lattice based option pricing models; implementation of distance learning materials; aesthetic principle in design of distance learning material; capacity testing/planning for successful implementation of LMS/CMS; using multiple-choice tests at university level courses preparation and supporting infrastructure; conceptualisation of learning context in e-learning; how digital immigrants learned to make games for digital natives; document management and exchange system - supporting education process; development of the computer aided system for controlled strikes exercises; adaption in IS integration and enterprise migration; demographic characteristics and internet access of high school teachers and their ICT competencies; advantages and disadvantages of distance learning.

SCOPUS_ID:84897654573

32nd International Convention Proceedings: Microelectronics, Electronics and Electronic Technology, MEET and Grid and Visualizations Systems, GVS

The proceedings contain 315 papers. The special focus in this conference is on Information and Communication Technology, Electronics and Microelectronics. The topics include: Croatian semiconductor industry cluster; rare-earth-activated nano-structures fabricated by sol-gel route; applications and recent developments in THz research; electrical activation of phosphorus by rapid thermal annealing of doped amorphous silicon films; resonant optical absorption in molecular nanofilms; Raman scattering on porous silicon; modeling of the effect of radicals on plasmas used for etching in micro-electronics; a method of slow-switching interface traps identification in silicon carbide MOS structures; strain and deformation measurement using intrinsic fiber optic low coherence interferometric sensor; modeling of gate leakage current in high-K dielectrics; compact capacitance model for drain-induced barrier-lowering of vertical SONFET; stress effect in ultra-narrow finFET structures; quantum confinement and scaling effects in ultra-thin body double-gate finFETs; optofiber-and-LED device for study of non-phototoxic photosensitizers biodistributions in bio-objects; design and characterization of soil moisture sensor using PCB technology; characterization of temperature sensor using Vt extractor device; an integrated thin film Pt/Ti heater; synthesis of DC power converters without galvanic insulation; microcontroller controlled capacitance decade box; part average analysis in multilayer ceramic manufacturing for automotive industry; improved linearity active resistors using MOS and FGMOS transistors; possibilities of current measurement in CMOS design using current mirrors and comparators; advantages and limitations of the SCW charge pump; tunable gm-C filter using FGMOS based operational transconductance amplifier; a charge-sensitive amplifier associated with APD or PMT for positron emission tomography scanners; efficient and reusable offset cancellation method implemented in CMOS design; kernighan-lin algorithm for n-way circuit partitioning; measuring and modelling of a PCB via structure; analog to digital conversion, synchronization and control and algorithm for hardware realization; AI - look over hardware design - agent with state; fault diagnosis and isolation of the marine diesel engine turbocharger system; UML modeling in design of error detection and correction circuits; the impact of multi-core processor on web server performance; the UK particle physics grid; enabling numerical modeling of mantle convection on the grid; a lightweight specialized meta-scheduler for 3D image rendering applications; the virtualization of computing cluster resources for integration in grid environment; transactional distributed memory management for cluster operating systems; a grid portal for genetic analysis of complex traits; error analysis of quasirandom walks on balls; using sobol sequence in grid environment; towards china's railway freight transportation information grid; fast system matrix generation on a GPU cluster; visualization as a sequence application for grid-based parametric studies; remote graphical visualization of interactive virtual geographical space; a data management and visualization system towards online microscopic imaging; protein data bank graphics generator on grid; real-time evaluation of L-system scene models in online multiplayer games; parallel formulation of 3D implicit function visualization; displaying large amounts of spatial data in GIS; intelligent algorithm for smoke extraction in autonomous forest fire detection; correction of digital images by arbitrary degree Bezier polynomial; wide-view visual systems for flight simulation; visualization of voltage profile and power flow in Croatian power system; network architecture evolution strategy in fixed networks; fireflies synchronization in small overlay networks; capabilities and impacts of EDGE evolution toward seamless wireless networks; adaptable architecture of provisioning system; selecting technology for interactive web application development; objective assessment of speech and audio quality; queue length influence in RED congestion avoidance algorithm; network problems frequency detection using apriori algorithm; radio over fiber technology for wireless access; reliability and scalability of DHCP access model in broadband network; success model of information system implementation; implementation of a GSM-based remotely controlled and monitored machine system; information management to reduce uncertainty in military systems; system for remote supervision and control of power electronics devices; adapting agile practices in globally distributed large scale software development; using static code analysis tools to increase source code maintainability; first time right in AXE using one track and stream line development; collecting of content enterprise knowledge by using metadata; realizacija slozenih procesa uklju_enja kroz sustave za podrsku; problems and possible solutions in offering netphone packages service; specificities of the new complex software based services implementation at mobile operators; dijagnosticiranje i rjesavanje problema u prijenosu audio signala internet protokolom; simulation of DVB-T transmission in matlab; simulators for solving traveling salesman problem variations with various graph search methods; a survey of software quality assessment; identification of persons and business subjects in text documents based on lexical analysis and scoring system; implementation of agent tehnology in web portals for data analysis and consulting; process entropy and informational macrodynamics in a ceramic tile plant; control of single-input-single-output systems with actuator saturation; design space exploration of a multi-core JPEG; 3D optoelectronic method for the steel strip flatness measurement; voltage control of a DC/DC boost converter powered by fuel cell stack; control of a standalone DC voltage source with fuel cell stack; earth fault location in medium voltage distribution networks; review of active vibration control; active control of periodic vibrations based on synchronous averaging of residual signal; energy efficient sensor based control of a greenhouse; electric power distribution protective devices allocation with genetic algorithms; upravljanje jednostavnim procesima putem GSM uredaja; upravljanje sustavom distribucije cementa; upravljanje kvalitetom vazduha u urbano - industrijskim centrima; intelligent control system, data acquisition system and data output system; tagging multimedia stimuli with ontologies; automatic generation of part-whole hierarchies for domain ontologies using web search data; a storage algorithm for a kanerva-like memory model; managing electromagnetic field pollution using genetic algorithm; evolutionary algorithm aided design of multi-switch controller; automatic diagnosis of power transformers based on dissolved gas analysis first level of diagnosis using VAC and VEV inference methods; building an expert system module for world ocean thermocline analysis; precision static and dynamic optical measurement and 3D imaging of reflective surfaces; agent based intelligent forest fire monitoring system; false alarms reduction in forest fire video monitoring system; automatic adjustment of detection parameters in forest fire video monitoring system; vehicle following control considering relative sensor information only; hidden Markov models and convolutional neural network approaches to face recognition tasks solution; digital system of textile fibers identification; exploring string and word kernels on Croatian-English parallel corpus; memetic algorithm for grammatical inference; grapheme-to-phoneme conversion for Croatian speech synthesis; uniform modified method for handwritten text reference line detection; peer assessment system for modern learning settings; semantic metadata for e-learning content; computers in education of children with intellectual and related developmental disorders; avatars and identification in online communication; research regarding introduction of electronic information at the university of jurja dobrile in pula; employment system and needs for ICT labour in the republic of Croatia; parameters estimation according to Engels law in excel; integration of business processes modelling into education; experience with the distance learning bachelor study in the field of finance, banking and investment; combining e-material and data acquisition module to support the educational process; digital repositories and possibilities of their integration into higher education; econometric analysis of the public sector economy in SPSS and excel; integrating protein visualization in the classroom with starbiochem; using web content management systems in university e-commerce courses; computer classroom management and virtualization and visualization in education; teaching, correcting and improving your language competences by means of the internet; an application of excel and VBA in comparison of lattice based option pricing models; implementation of distance learning materials; aesthetic principle in design of distance learning material; capacity testing/planning for successful implementation of LMS/CMS; using multiple-choice tests at university level courses preparation and supporting infrastructure; conceptualisation of learning context in e-learning.

SCOPUS_ID:84897597921

32nd International Convention Proceedings: Telecommunications and Information

The proceedings contain 315 papers. The special focus in this conference is on Information and Communication Technology, Electronics and Microelectronics. The topics include: Croatian semiconductor industry cluster; rare-earth-activated nano-structures fabricated by sol-gel route; applications and recent developments in THz research; electrical activation of phosphorus by rapid thermal annealing of doped amorphous silicon films; resonant optical absorption in molecular nanofilms; Raman scattering on porous silicon; modeling of the effect of radicals on plasmas used for etching in micro-electronics; a method of slow-switching interface traps identification in silicon carbide MOS structures; strain and deformation measurement using intrinsic fiber optic low coherence interferometric sensor; modeling of gate leakage current in high-K dielectrics; compact capacitance model for drain-induced barrier-lowering of vertical SONFET; stress effect in ultra-narrow finFET structures; quantum confinement and scaling effects in ultra-thin body double-gate finFETs; optofiber-and-LED device for study of non-phototoxic photosensitizers biodistributions in bio-objects; design and characterization of soil moisture sensor using PCB technology; characterization of temperature sensor using Vt extractor device; an integrated thin film Pt/Ti heater; synthesis of DC power converters without galvanic insulation; microcontroller controlled capacitance decade box; part average analysis in multilayer ceramic manufacturing for automotive industry; improved linearity active resistors using MOS and FGMOS transistors; possibilities of current measurement in CMOS design using current mirrors and comparators; advantages and limitations of the SCW charge pump; tunable gm-C filter using FGMOS based operational transconductance amplifier; a charge-sensitive amplifier associated with APD or PMT for positron emission tomography scanners; efficient and reusable offset cancellation method implemented in CMOS design; kernighan-lin algorithm for n-way circuit partitioning; measuring and modelling of a PCB via structure; analog to digital conversion, synchronization and control and algorithm for hardware realization; AI - look over hardware design - agent with state; fault diagnosis and isolation of the marine diesel engine turbocharger system; UML modeling in design of error detection and correction circuits; the impact of multi-core processor on web server performance; the UK particle physics grid; enabling numerical modeling of mantle convection on the grid; a lightweight specialized meta-scheduler for 3D image rendering applications; the virtualization of computing cluster resources for integration in grid environment; transactional distributed memory management for cluster operating systems; a grid portal for genetic analysis of complex traits; error analysis of quasirandom walks on balls; using sobol sequence in grid environment; towards china's railway freight transportation information grid; fast system matrix generation on a GPU cluster; visualization as a sequence application for grid-based parametric studies; remote graphical visualization of interactive virtual geographical space; a data management and visualization system towards online microscopic imaging; protein data bank graphics generator on grid; real-time evaluation of L-system scene models in online multiplayer games; parallel formulation of 3D implicit function visualization; displaying large amounts of spatial data in GIS; intelligent algorithm for smoke extraction in autonomous forest fire detection; correction of digital images by arbitrary degree Bezier polynomial; wide-view visual systems for flight simulation; visualization of voltage profile and power flow in Croatian power system; network architecture evolution strategy in fixed networks; fireflies synchronization in small overlay networks; capabilities and impacts of EDGE evolution toward seamless wireless networks; adaptable architecture of provisioning system; selecting technology for interactive web application development; objective assessment of speech and audio quality; queue length influence in RED congestion avoidance algorithm; network problems frequency detection using apriori algorithm; radio over fiber technology for wireless access; reliability and scalability of DHCP access model in broadband network; success model of information system implementation; implementation of a GSM-based remotely controlled and monitored machine system; information management to reduce uncertainty in military systems; system for remote supervision and control of power electronics devices; adapting agile practices in globally distributed large scale software development; using static code analysis tools to increase source code maintainability; first time right in AXE using one track and stream line development; collecting of content enterprise knowledge by using metadata; realizacija slozenih procesa uklju_enja kroz sustave za podrsku; problems and possible solutions in offering netphone packages service; specificities of the new complex software based services implementation at mobile operators; dijagnosticiranje i rjesavanje problema u prijenosu audio signala internet protokolom; simulation of DVB-T transmission in matlab; simulators for solving traveling salesman problem variations with various graph search methods; a survey of software quality assessment; identification of persons and business subjects in text documents based on lexical analysis and scoring system; implementation of agent tehnology in web portals for data analysis and consulting; process entropy and informational macrodynamics in a ceramic tile plant; control of single-input-single-output systems with actuator saturation; design space exploration of a multi-core JPEG; 3D optoelectronic method for the steel strip flatness measurement; voltage control of a DC/DC boost converter powered by fuel cell stack; control of a standalone DC voltage source with fuel cell stack; earth fault location in medium voltage distribution networks; review of active vibration control; active control of periodic vibrations based on synchronous averaging of residual signal; energy efficient sensor based control of a greenhouse; electric power distribution protective devices allocation with genetic algorithms; upravljanje jednostavnim procesima putem GSM uredaja; upravljanje sustavom distribucije cementa; upravljanje kvalitetom vazduha u urbano - industrijskim centrima; intelligent control system, data acquisition system and data output system; tagging multimedia stimuli with ontologies; automatic generation of part-whole hierarchies for domain ontologies using web search data; a storage algorithm for a kanerva-like memory model; managing electromagnetic field pollution using genetic algorithm; evolutionary algorithm aided design of multi-switch controller; automatic diagnosis of power transformers based on dissolved gas analysis first level of diagnosis using VAC and VEV inference methods; building an expert system module for world ocean thermocline analysis; precision static and dynamic optical measurement and 3D imaging of reflective surfaces; agent based intelligent forest fire monitoring system; false alarms reduction in forest fire video monitoring system; automatic adjustment of detection parameters in forest fire video monitoring system; vehicle following control considering relative sensor information only; hidden Markov models and convolutional neural network approaches to face recognition tasks solution; digital system of textile fibers identification; exploring string and word kernels on Croatian-English parallel corpus; memetic algorithm for grammatical inference; grapheme-to-phoneme conversion for Croatian speech synthesis; uniform modified method for handwritten text reference line detection; peer assessment system for modern learning settings; semantic metadata for e-learning content; computers in education of children with intellectual and related developmental disorders; avatars and identification in online communication; research regarding introduction of electronic information at the university of jurja dobrile in pula; employment system and needs for ICT labour in the republic of Croatia; parameters estimation according to Engels law in excel; integration of business processes modelling into education; experience with the distance learning bachelor study in the field of finance, banking and investment; combining e-material and data acquisition module to support the educational process; digital repositories and possibilities of their integration into higher education; econometric analysis of the public sector economy in SPSS and excel; integrating protein visualization in the classroom with starbiochem; using web content management systems in university e-commerce courses; computer classroom management and virtualization and visualization in education; teaching, correcting and improving your language competences by means of the internet; an application of excel and VBA in comparison of lattice based option pricing models; implementation of distance learning materials; aesthetic principle in design of distance learning material; capacity testing/planning for successful implementation of LMS/CMS; using multiple-choice tests at university level courses preparation and supporting infrastructure; conceptualisation of learning context in e-learning; how digital immigrants learned to make games for digital natives; document management and exchange system - supporting education process; development of the computer aided system for controlled strikes exercises.

SCOPUS_ID:85025156006

33rd European Conference on Information Retrieval, ECIR 2011

The proceedings contain 95 papers. The special focus in this conference is on Information Retrieval. The topics include: Knowledge-based approaches to computational advertising; the value of user feedback; text classification for a large-scale taxonomy using dynamically mixed local and global models for a node; user-related tag expansion for web document clustering; a comparative experimental assessment of a threshold selection algorithm in hierarchical text categorization; improving tag-based recommendation by topic diversification; a joint model of feature mining and sentiment analysis for product review rating; modeling answerer behavior in collaborative question answering systems; caching for realtime search; enhancing deniability against query-logs; on the contributions of topics to system evaluation; a methodology for evaluating aggregated search results; design and implementation of relevance assessments using crowdsourcing; in search of quality in crowdsourcing for search engine evaluation; summarizing a document stream; a link prediction approach to recommendations in large-scale user-generated content systems; topic classification in social media using metadata from hyperlinked objects; latent sentiment model for weakly-supervised cross-lingual sentiment classification; cross-lingual feature selection for search; balancing exploration and exploitation in learning to rank online; effective relevance feedback for entity ranking; the limits of retrieval effectiveness; learning conditional random fields from unaligned data for natural language understanding and subspace tracking for latent semantic analysis.

SCOPUS_ID:85089139807

360 degree view of cross-domain opinion classification: a survey

In the field of natural language processing and text mining, sentiment analysis (SA) has received huge attention from various researchers’ across the globe. By the prevalence of Web 2.0, user’s became more vigilant to share, promote and express themselves along with any issues or challenges that are being encountered on daily activities through the Internet (social media, micro-blogs, e-commerce, etc.) Expression and opinion are a complex sequence of acts that convey a huge volume of data that pose a challenge for computational researchers to decode. Over the period of time, researchers from various segments of public and private sectors are involved in the exploration of SA with an aim to understand the behavioral perspective of various stakeholders in society. Though the efforts to positively construct SA are successful, challenges still prevail for efficiency. This article presents an organized survey of SA (also known as opinion mining) along with methodologies or algorithms. The survey classifies SA into categories based on levels, tasks, and sub-task along with various techniques used for performing them. The survey explicitly focuses on different directions in which the research was explored in the area of cross-domain opinion classification. The article is concluded with an objective to present an exclusive and exhaustive analysis in the area of opinion mining containing approaches, datasets, languages, and applications used. The observations made are expected to support researches to get a greater understanding on emerging trends and state-of-the-art methods to be applied for future exploration.

SCOPUS_ID:84959053104

360-MAM-Affect: Sentiment analysis with the Google prediction API and EmoSenticNet

Online recommender systems are useful for media asset management where they select the best content from a set of media assets. We have developed an architecture for 360-MAM-Select, a recommender system for educational video content. 360-MAM-Select will utilise sentiment analysis and gamification techniques for the recommendation of media assets. 360-MAM-Select will increase user participation with digital content through improved video recommendations. Here, we discuss the architecture of 360-MAM-Select and the use of the Google Prediction API and EmoSenticNet for 360-MAM-Affect, 360-MAM-Select's sentiment analysis module. Results from testing two models for sentiment analysis, SentimentClassifer (Google Prediction API) and EmoSenticNetClassifer (Google Prediction API + EmoSenticNet) are promising. Future work includes the implementation and testing of 360-MAM-Select on video data from YouTube EDU and Head Squeeze.

http://arxiv.org/abs/1804.00982v1

360° Stance Detection

The proliferation of fake news and filter bubbles makes it increasingly difficult to form an unbiased, balanced opinion towards a topic. To ameliorate this, we propose 360{\deg} Stance Detection, a tool that aggregates news with multiple perspectives on a topic. It presents them on a spectrum ranging from support to opposition, enabling the user to base their opinion on multiple pieces of diverse evidence.

SCOPUS_ID:85149114137

37th Annual Meeting of the Association for Computational Linguistics, ACL 1999 - Proceedings of the Conference

The proceedings contain 82 papers. The topics discussed include: automatic speech recognition and its application to information extraction; the lexical component of natural language processing; measures of distributional similarity; distributional similarity models: clustering vs. nearest neighbors; finding parts in very large corpora; man vs. machine: a case study in base noun phrase learning; supervised grammar induction using training data with limited constituent information; a meta-level grammar: redefining synchronous TAG for translation and paraphrase; preserving semantic dependencies in synchronous tree adjoining grammar; and corpus-based linguistic indicators for aspectual classification.

SCOPUS_ID:84928978697

37th European Conference on Information Retrieval Research, ECIR 2015

The proceedings contain 100 papers. The special focus in this conference is on Aggregated Search and Diversity, Classification, Cross-lingual and Discourse and Efficiency. The topics include: Towards query level resource weighting for diversified query expansion; exploring composite retrieval from the users’ perspective; improving aggregated search coherence; on-topic cover stories from news archives; multi-emotion detection in user-generated reviews; classification of historical notary acts with noisy labels; a flexible scene classification framework; an audio-visual approach to music genre classification through affective color features; multi-modal correlated centroid space for multi-lingual cross-modal retrieval; a discourse search engine based on rhetorical structure theory; knowledge-based representation for transductive multilingual document classification; distributional correspondence indexing for cross-language text categorization; adaptive caching of fresh web search results; approximating weighted hamming distance by probabilistic selection for multiple hash tables; graph regularised hashing and approximate nearest-neighbour search with inverted signature slice lists.

SCOPUS_ID:85017955678

39th European Conference on Information Retrieval, ECIR 2017

The proceedings contain 80 papers. The special focus in this conference is on Information Retrieval. The topics include: Entity linking to one thousand knowledge bases; using query performance predictors to reduce spoken queries; cross-lingual sentiment relation capturing for cross-lingual sentiment analysis; hierarchical re-estimation of topic models for measuring topical diversity; collective entity linking in tweets over space and time; simple personalized search based on long-term behavioral signals; inferring user interests for passive users on twitter by leveraging followee biographies; fusion of bag-of-words models for image classification in the medical domain; learning to re-rank medical images using a Bayesian network-based thesaurus; utterance retrieval based on recurrent surface text patterns; exploring time-sensitive variational Bayesian inference LDA for social media data; a task completion engine to enhance search session support for air traffic work tasks; feature-oriented analysis of user profile completion problem; human-based query difficulty prediction; a formal and empirical study of unsupervised signal combination for textual similarity tasks; exploration of a threshold for similarity based on uncertainty in word embedding; a systematic analysis of sentence update detection for temporal summarization; a multiple-instance learning approach to sentence selection for question ranking; enhancing sensitivity classification with semantic features using word embeddings; a new scheme for scoring phrases in unsupervised keyphrase extraction; dimension projection among languages based on pseudo-relevant documents for query translation and leveraging site search logs to identify missing content on enterprise webpages.

SCOPUS_ID:85137997174

3D Audio + Augmented Reality + AI Chatbots + IoT: An Immersive Conversational Cultural Guide

Typical Augmented Reality (AR) cultural heritage (CH) guides adopt a visuo-centric approach, wherein visual virtual elements are superimposed onto the physical world. Recent research has investigated the use of Audio AR to evoke multisensory immersive experiences to visitors of CH sites adopting screen-free interfaces to ensure that user attention is not distracted from the physical exhibits. A parallel trend in the audience engagement programs of cultural institutions involves the employment of AI chatbots which are engaged in dialogues with visitors to provide meaningful responses to user questions. Herein, we present Exhibot, an intelligent audio guide system aiming at enhancing the user experience of CH site visitors. Exhibot represents the first-ever approach to combine Audio AR and chatbot technologies to enable natural visitor-exhibit interaction, while also leveraging IoT devices to contextualize the delivered information. The usability and utility of Exhibot has been tested in a case study in outdoors environment with the preliminary results indicating a very positive user experience.

SCOPUS_ID:77954438810

3D CAPTCHA: A next generation of the CAPTCHA

Nowadays, the Internet is now becoming a part of our everyday lives. Many services, including Email, search engine, and web board on Internet, are provided with free of charge and unintentionally turns them into vulnerability services. Many software robots or, in short term, bots are developed with purpose to use such services illegally and automatically. Thus, web sites employ human authentication mechanism called Completely Automated Public Turing test to tell Computers and Humans Apart (CAPTCHA) to counter this attack. Unfortunately, many CAPTCHA have been already broken by bots and some CAPTCHA are difficult to read by human. In this paper, a new CAPTCHA method called 3D CAPTCHA is proposed to provide an enhanced protection from bots. This method based on assumption that human can recognize 3D character image better than Optical Character Recognition (OCR) software bots. ©2010 IEEE.

http://arxiv.org/abs/2104.11532v1

3D Convolutional Neural Networks for Ultrasound-Based Silent Speech Interfaces

Silent speech interfaces (SSI) aim to reconstruct the speech signal from a recording of the articulatory movement, such as an ultrasound video of the tongue. Currently, deep neural networks are the most successful technology for this task. The efficient solution requires methods that do not simply process single images, but are able to extract the tongue movement information from a sequence of video frames. One option for this is to apply recurrent neural structures such as the long short-term memory network (LSTM) in combination with 2D convolutional neural networks (CNNs). Here, we experiment with another approach that extends the CNN to perform 3D convolution, where the extra dimension corresponds to time. In particular, we apply the spatial and temporal convolutions in a decomposed form, which proved very successful recently in video action recognition. We find experimentally that our 3D network outperforms the CNN+LSTM model, indicating that 3D CNNs may be a feasible alternative to CNN+LSTM networks in SSI systems.

SCOPUS_ID:85069726168

3D Gesture Interface: Japan-Brazil Perceptions

Gestures are used naturally in communication, and use with modern computer systems is becoming increasingly feasible and applicable for interaction. Analyzing how gesture interfaces are perceived in different parts of the world can help in understanding possible weak and strong points, allowing for different improvements to the interfaces. This study aims to analyze how different technological familiarization levels impacts the user experience of gestural interfaces. Our work describes the findings of an experiment that was replicated in two countries: Brazil and Japan. In each experiment, 20 subjects tested two applications; one had a mouse-based interface and the other a gesture-based interface. User experience was measured using questionnaires from AttrakDiff. Subjectivity and abstract concepts largely differed, but major agreement was found regarding room for improvement of the pragmatist quality of the gestural interface in order to be embraced by the average user.

SCOPUS_ID:85146654416

3D HUMAN MOTION GENERATION FROM THE TEXT VIA GESTURE ACTION CLASSIFICATION AND THE AUTOREGRESSIVE MODEL

In this paper, a deep learning-based model for 3D human motion generation from the text is proposed via gesture action classification and an autoregressive model. The model focuses on generating special gestures that express human thinking, such as waving and nodding. To achieve the goal, the proposed method predicts expression from the sentences using a text classification model based on a pretrained language model and generates gestures using the gate recurrent unit-based autoregressive model. Especially, we proposed the loss for the embedding space for restoring raw motions and generating intermediate motions well. Moreover, the novel data augmentation method and stop token are proposed to generate variable length motions. To evaluate the text classification model and 3D human motion generation model, a gesture action classification dataset and action-based gesture dataset are collected. With several experiments, the proposed method successfully generates perceptually natural and realistic 3D human motion from the text. Moreover, we verified the effectiveness of the proposed method using a public-available action recognition dataset to evaluate cross-dataset generalization performance.

SCOPUS_ID:85135327833

3D Smartlearning Using Machine Learning Technique

One of the most significant areas of image processing and computer vision is object detection. In modern days, Humans have a tendency to grasp things fast when we teach them in a practical way. The proposed system is designed to learn the correspondence between preached words and conceptual visual attributes from a spoken image description dataset. For this purpose, vision technology and neural network algorithm are used to do image enhancement and manipulation techniques using LABVIEW platform. First, train the PC with OCR (Optical Character Recognition) technique and continue this process for 2-3 times so that it becomes accurate. Then with the help of the KNN algorithm, an input image is compared with the predefined dataset. The acquisition and processing of images are done in the graphical programming environment of LabVIEW. This gives all the benefits of this software to the application: modularity, effortless realization, desirable user interface, springiness, and the ability to develop very simple new features. The learner can use the proposed scheme to learn things in a smarter way.

SCOPUS_ID:84887848327

3D Wikipedia: Using online text to automatically label and navigate reconstructed geometry

We introduce an approach for analyzing Wikipedia and other text, together with online photos, to produce annotated 3D models of famous tourist sites. The approach is completely automated, and leverages online text and photo co-occurrences via Google Image Search. It enables a number of new interactions, which we demonstrate in a new 3D visualization tool. Text can be selected to move the camera to the corresponding objects, 3D bounding boxes provide anchors back to the text describing them, and the overall narrative of the text provides a temporal guide for automatically flying through the scene to visualize the world as you read about it. We show compelling results on several major tourist sites.

SCOPUS_ID:84881324693

3D gender recognition using cognitive modeling

We use 3D scans of human faces and cognitive modeling to estimate the 'gender strength'. The 'gender strength' is a continuous class variable of the gender, superseding the traditional binary class labeling. To visualize some of the visual trends humans use when performing gender classification, we use linear regression. In addition, we use the gender strength to construct a smaller but refined training set, by identifying and removing ill-defined training examples. We use this refined training set to improve the performance of known classification algorithms. Results are presented using a 5-fold cross-validation scheme and also reproduced using an unseen data set. © 2013 IEEE.

SCOPUS_ID:84938816256

3D object retrieval based on Spatial+LDA model

Latent Dirichlet Allocation (LDA) is one popular topic extraction method, which has been applied in many applications such as textual retrieval, user recommendation system and video cluster. In this paper, we apply LDA model for visual topics extraction and utilized the topic distribution visual feature of image to handle 3D object retrieval problem. Different from the traditional LDA model, we add the spatial information of visual feature for document generation. First, we extract SIFT features from each 2D image extracted from 3D object. Then, we structure the visual documents according to the spatial information of 3D model. Finally, LDA model is used to extract the topic model for handling the retrieval problem. We further propose a multi-topic model to improve retrieval performance. Extensive comparison experiments were on the popular ETH, NTU and MV-RED 3D model datasets. The results demonstrate the superiority of the proposed method.

SCOPUS_ID:84917694460

3D object retrieval with multitopic model combining relevance feedback and LDA model

View-based 3D model retrieval uses a set of views to represent each object. Discovering the complex relationship between multiple views remains challenging in 3D object retrieval. Recent progress in the latent Dirichlet allocation (LDA) model leads us to propose its use for 3D object retrieval. This LDA approach explores the hidden relationships between extracted primordial features of these views. Since LDA is limited to a fixed number of topics, we further propose a multitopic model to improve retrieval performance. We take advantage of a relevance feedback mechanism to balance the contributions of multiple topic models with specified numbers of topics. We demonstrate our improved retrieval performance over the state-of-the-art approaches.

SCOPUS_ID:84989208439

3D text segmentation and recognition using leap motion

In this paper, we present a method of Human-Computer-Interaction (HCI) through 3D air-writing. Our proposed method includes a natural way of interaction without pen and paper. The online texts are drawn on air by 3D gestures using fingertip within the field of view of a Leap motion sensor. The texts consist of single stroke only. Hence gaps between adjacent words are usually absent. This makes the system different as compared to the conventional 2D writing using pen and paper. We have collected a dataset that comprises with 320 Latin sentences. We have used a heuristic to segment 3D words from sentences. Subsequently, we present a methodology to segment continuous 3D strokes into lines of texts by finding large gaps between the end and start of the lines. This is followed by segmentation of the text lines into words. In the next phase, a Hidden Markov Model (HMM) based classifier is used to recognize 3D sequences of segmented words. We have used dynamic as well as simple features for classification. We have recorded an overall accuracy of 80.3 % in word segmentation. Recognition accuracies of 92.73 % and 90.24 % have been recorded when tested with dynamic and simple features, respectively. The results show that the Leap motion device can be a low-cost but useful solution for inputting text naturally as compared to conventional systems. In future, this may be extended such that the system can successfully work on cluttered gestures.

SCOPUS_ID:74049115511

3D visible speech animation driven by prosody text

This paper proposes a new approach for generating realistic three-dimensional speech animation. The basic idea is to synthesize the animated faces using prosodic information edited by user with a kind of text markup language. By capturing characteristic trajectories of utterances from video clips, our technique builds up a parametric model based on the exponential formula. Based on this formula the static viseme is extended to dynamic one. To relate the prosody text with the 3D animation, the input attribute is mapped to be the value of formula parameter. Experimental results show that the proposed technique synthesizes animation of different effects depending on the availability with the prosodic information.

SCOPUS_ID:85049513673

3D visualization of sentiment measures and sentiment classification using combined classifier for customer product reviews

The Internet has wide reachability making many users to buy the products online using e-commerce websites. Usually, users provide their opinions, comments, and reviews about the products in social media, e-commerce websites, blogs, etc. The product review comments provided by the customers have rich information about the usage of the products they bought and their sentiments towards those products. In this research, we have collected reviews from Amazon.com and performed sentiment analysis to collect sentiment information. We have proposed 3D visualizations to represent sentiment information, such as sentiment scores and statistics about words used in the reviews. The 3D visualizations are useful to represent large sentiment related information and to have an in-depth understanding of sentiments of users. We have developed a combined classifier using Logistic Regression, Decision Tree and Support Vector Machine. From the reviews, we formed N-gram features using a bag of words and performed sentiment classification using combined classifier. On 10 fold cross-validation, a maximum classification rate for combined classifier of 90.22% is obtained for sentiment classification.

SCOPUS_ID:85136143540

3D-Pruning: A Model Compression Framework for Efficient 3D Action Recognition

The existing end-to-end optimized 3D action recognition methods often suffer from high computational costs. Observing that different frames and different points in point cloud sequences often have different importance values for the 3D action recognition task, in this work, we propose a fully automatic model compression framework called 3D-Pruning (3DP) for efficient 3D action recognition. After performing model compression by using our 3DP framework, the compressed model can process different frames and different points in each frame by using different computational complexities based on their importance values, in which both the importance value and computational complexity for each frame/point can be automatically learned. Extensive experiments on five benchmark datasets demonstrate the effectiveness of our 3DP framework for model compression.

SCOPUS_ID:85064122614

3DMMS: Robust 3D Membrane Morphological Segmentation of C. elegans embryo

Background: Understanding the cellular architecture is a fundamental problem in various biological studies. C. elegans is widely used as a model organism in these studies because of its unique fate determinations. In recent years, researchers have worked extensively on C. elegans to excavate the regulations of genes and proteins on cell mobility and communication. Although various algorithms have been proposed to analyze nucleus, cell shape features are not yet well recorded. This paper proposes a method to systematically analyze three-dimensional morphological cellular features. Results: Three-dimensional Membrane Morphological Segmentation (3DMMS) makes use of several novel techniques, such as statistical intensity normalization, and region filters, to pre-process the cell images. We then segment membrane stacks based on watershed algorithms. 3DMMS achieves high robustness and precision over different time points (development stages). It is compared with two state-of-the-art algorithms, RACE and BCOMS. Quantitative analysis shows 3DMMS performs best with the average Dice ratio of 97.7% at six time points. In addition, 3DMMS also provides time series of internal and external shape features of C. elegans. Conclusion: We have developed the 3DMMS based technique for embryonic shape reconstruction at the single-cell level. With cells accurately segmented, 3DMMS makes it possible to study cellular shapes and bridge morphological features and biological expression in embryo research.

SCOPUS_ID:85115445609

3DSRASG: 3D Scene Retrieval and Augmentation Using Semantic Graphs

Computer Vision, encompassing 3D Vision and 3D scene Reconstruction, is a field of importance to real-world problems involving 3D views of scenes. The goal of the proposed system is to retrieve 3D scenes from the database, and further augment the scenes in an iterative manner based on the user’s commands to finally produce the required output 3D scenes, in the form of a suggestive interface. The process is done recursively to facilitate additions and deletions, until the desired scene is generated. In addition to synthesizing the required 3D indoor scenes from text, a speech recognition system has been integrated with the system that will enable the users to choose from either modes of input. The application includes the projection and rendering of 3D scenes which will enable a 360-∘ view of the scene. The robustness of scene generation and quick retrieval of scenes will promote the usage of this work in avenues such as story telling, interior designing, and as a helpful educational tool for autistic children.

SCOPUS_ID:85138461324

3DVQA: Visual Question Answering for 3D Environments

Visual Question Answering (VQA) is a widely studied problem in computer vision and natural language processing. However, current approaches to VQA have been investigated primarily in the 2D image domain. We study VQA in the 3D domain, with our input being point clouds of real-world 3D scenes, instead of 2D images. We believe that this 3D data modality provide richer spatial relation information that is of interest in the VQA task. In this paper, we introduce the 3DVQA-ScanNet dataset, the first VQA dataset in 3D, and we investigate the performance of a spectrum of baseline approaches on the 3D VQA task.

SCOPUS_ID:85056184090

3G structure for image caption generation

It is a big challenge of computer vision to make machine automatically describe the content of an image with a natural language sentence. Previous works have made great progress on this task, but they only use the global or local image feature, which may lose some important subtle or global information of an image. In this paper, we propose a model with 3-gated model which fuses the global and local image features together for the task of image caption generation. The model mainly has three gated structures. (1) Gate for the global image feature, which can adaptively decide when and how much the global image feature should be imported into the sentence generator. (2) The gated recurrent neural network (RNN) is used as the sentence generator. (3) The gated feedback method for stacking RNN is employed to increase the capability of nonlinearity fitting. More specially, the global and local image features are combined together in this paper, which makes full use of the image information. The global image feature is controlled by the first gate and the local image feature is selected by the attention mechanism. With the latter two gates, the relationship between image and text can be well explored, which improves the performance of the language part as well as the multi-modal embedding part. Experimental results show that our proposed method outperforms the state-of-the-art for image caption generation.

SCOPUS_ID:85035092969

3HAN: A Deep Neural Network for Fake News Detection

The rapid spread of fake news is a serious problem calling for AI solutions. We employ a deep learning based automated detector through a three level hierarchical attention network (3HAN) for fast, accurate detection of fake news. 3HAN has three levels, one each for words, sentences, and the headline, and constructs a news vector: an effective representation of an input news article, by processing an article in an hierarchical bottom-up manner. The headline is known to be a distinguishing feature of fake news, and furthermore, relatively few words and sentences in an article are more important than the rest. 3HAN gives a differential importance to parts of an article, on account of its three layers of attention. By experiments on a large real-world data set, we observe the effectiveness of 3HAN with an accuracy of 96.77%. Unlike some other deep learning models, 3HAN provides an understandable output through the attention weights given to different parts of an article, which can be visualized through a heatmap to enable further manual fact checking.

http://arxiv.org/abs/2204.03178v2

3M: Multi-loss, Multi-path and Multi-level Neural Networks for speech recognition

Recently, Conformer based CTC/AED model has become a mainstream architecture for ASR. In this paper, based on our prior work, we identify and integrate several approaches to achieve further improvements for ASR tasks, which we denote as multi-loss, multi-path and multi-level, summarized as "3M" model. Specifically, multi-loss refers to the joint CTC/AED loss and multi-path denotes the Mixture-of-Experts(MoE) architecture which can effectively increase the model capacity without remarkably increasing computation cost. Multi-level means that we introduce auxiliary loss at multiple level of a deep model to help training. We evaluate our proposed method on the public WenetSpeech dataset and experimental results show that the proposed method provides 12.2%-17.6% relative CER improvement over the baseline model trained by Wenet toolkit. On our large scale dataset of 150k hours corpus, the 3M model has also shown obvious superiority over the baseline Conformer model. Code is publicly available at https://github.com/tencent-ailab/3m-asr.

SCOPUS_ID:85076917398

3Q: A 3-Layer Semantic Analysis Model for Question Suite Reduction

Question generation and question answering are attracting more and more attention recently. Existing question generation systems produce questions based on the given text. However, there is still a vast gap between these generated questions and their practical usage, which acquires more modification from human beings. In order to alleviate this dilemma, we consider reducing the volume of the question set/suite and extracting a lightweight subset while conserving as many features as possible from the original set. In this paper, we first propose a three-layer semantic analysis model, which ensembles traditional language analysis tools to perform the reduction. Then, a bunch of metrics over semantic contribution is carefully designed to balance distinct features. Finally, we introduce the concept of Grade Level and Information Entropy to evaluate our model from a multi-dimensional manner. We conduct an extensive set of experiments to test our model for question suite reduction. The results demonstrate that it can retain as much diversity as possible compared to the original large set.

SCOPUS_ID:85142727045

3WS-ITSC: Three-Way Sampling on Imbalanced Text Data for Sentiment Classification

Sentiment analysis is an important research direction of natural language processing. The data imbalance is a critical issue in text sentiment classification task. That arises the problem of high misclassification cost. This paper proposes a three-way sampling sentiment classification model for imbalanced text data to reduce the misclassification cost. Specifically, the model extracts boundary points through three-way sampling and collaborates with cost-sensitive learning for action on sampled results. Firstly, in order to reduce sampling time, the text data is converted into a one-dimensional vector by bag mapping. Secondly, three-way sampling is used to obtain boundary points that can characterize the majority class. Finally, a sequential three-way sentiment classification algorithm is used to predict sentiment polarity. The experimental results show that the proposed model outperforms state-of-the-art sentiment classification methods in the scenario of extremely imbalanced test data.

SCOPUS_ID:85106900263

3d point cloud on semantic information for wheat reconstruction

Phenotypic analysis has always played an important role in breeding research. At present, wheat phenotypic analysis research mostly relies on high-precision instruments, which make the cost higher. Thanks to the development of 3D reconstruction technology, the reconstructed wheat 3D model can also be used for phenotypic analysis. In this paper, a method is proposed to reconstruct wheat 3D model based on semantic information. The method can generate the corresponding 3D point cloud model of wheat according to the semantic description. First, an object detection algorithm is used to detect the characteristics of some wheat phenotypes during the growth process. Second, the growth environment information and some phenotypic features of wheat are combined into semantic information. Third, text-to-image algorithm is used to generate the 2D image of wheat. Finally, the wheat in the 2D image is transformed into an abstract 3D point cloud and obtained a higher precision point cloud model using a deep learning algorithm. Extensive experiments indicate that the method reconstructs 3D models and has a heuristic effect on phenotypic analysis and breeding research by deep learning.

SCOPUS_ID:85095838041

3dtext: Perceiving sentence-level text on 3-d model of emotions

Emotion is a psychological process which reveals the sentiments and feelings of a human being. Relating emotions detection process with psychological theory of emotions serves as the strong foundation for the system. In this paper, a model, 3DText, is proposed foe textual emotion detection. VAD (Pleasure, Arousal, and Dominance), a 3-D theory of emotion is used to extract features (P-A-D) from text. For this purpose, the dataset ANEW and WordNet are used. The objective of this paper is to determine VAD values at the sentence level of any size using word level VAD values for domain independent text. The proposed approach is evaluated on ISEAR and EMOBANK datasets. To the best of authors’ knowledge, no such model exists till date.

SCOPUS_ID:85058569432

3rd China Conference on Knowledge Graph and Semantic Computing, CCKS 2018

The proceedings contain 12 papers. The special focus in this conference is on Knowledge Graph and Semantic Computing. The topics include: Knowledge augmented inference network for natural language inference; survey on schema induction from knowledge graphs; distant supervision for Chinese temporal tagging; convolutional neural network-based question answering over knowledge base with type constraint; MMCRD: An effective algorithm for deploying monitoring point on social network; deep learning for knowledge-driven ontology stream prediction; DSKG: A deep sequential model for knowledge graph completion; pattern learning for Chinese open information extraction; adversarial training for relation classification with attention based gate mechanism; a novel approach on entity linking for encyclopedia infoboxes.

SCOPUS_ID:84874413345

3rd IEEE International Conference on Cognitive Infocommunications, CogInfoCom 2012 - Proceedings

The proceedings contain 126 papers. The topics discussed include: on the perception of visual durational speech features: a comparison between native and nonnative speakers; stabilization and synchronization of dynamicons through coginfocom channels; laughter and topic changes: temporal distribution and information flow; characteristic and spectral features used in automatic prediction of vowel duration in spontaneous speech; acoustic, semantic and personality dimensions in the speech of traditional puppeteers; effect of therapeutic riding on center of gravity (COG) parameters of blind children; saliency map estimation by constructing graphs of possible eye- tracking paths; avoiding boredom and anxiety: a study for rehabilitation application; pattern distillation methods in grammar induction; and a multi-objective decision support system (DSS) for simulation and optimization of municipal solid waste (MSW) management system.

SCOPUS_ID:84959036414

3rd International Colloquium on Grammatical Inference: Learning Syntax from Sentences, ICGI 1996

The proceedings contain 27 papers. The special focus in this conference is on Algebraic Methods and Algorithms. The topics include: Learning grammatical structure using statistical decision-trees; inductive inference from positive data; unions of identifiable families of languages; characteristic sets for polynomial grammatical inference; query learning of subsequential transducers; fitting template grammars by incremental MDL optimization; selection criteria for word trigger pairs in language modelling; clustering of sequences using minimum grammar complexity criterion; a note on grammatical inference of slender context-free languages; learning linear grammars from structural information; learning of context-sensitive language acceptors through regular inference and constrained induction; inducing constraint grammars; introducing statistical dependencies and structural constraints in variable-length sequence models; a disagreement count scheme for inference of constrained markov networks; using knowledge to improve N-gram language modelling through the MGGI methodology; discrete sequence prediction with commented markov models; learning k-piecewise testable languages from positive data; learning code regular and code linear languages; incremental regular inference; an incremental interactive algorithm for grammar inference; inductive logic programming for discrete event systems; stochastic simple recurrent neural networks; inferring stochastic regular grammars with recurrent neural networks; maximum mutual information and conditional maximum likelihood estimation of stochastic regular syntax-directed translation schemes; grammatical inference using tabu search; using domain information during the learning of a subsequential transducer and data-dependant vs data-independant algorithms.

SCOPUS_ID:84920514334

3rd International Conference on Natural Language Processing and Chinese Computing, NLPCC 2014

The proceedings contain 43 papers. The special focus in this conference is on Fundamentals on Language Computing, Applications on Language Computing, Machine Translation and Multi-Lingual Information Access and Machine Learning for NLP. The topics include: A global generative model for Chinese semantic role labeling; event schema induction based on relational co occurrence over multiple documents; negation and speculation target identification; an adjective-based embodied knowledge net; a method of density analysis for Chinese characters; computing semantic relatedness using a word-text mutual guidance model; short text feature enrichment using link analysis on topic-keyword graph; detection of loan words in Uyghur texts; a novel rule refinement method for SMT through simulated post-editing; case frame constraints for hierarchical phrase-based translation; learning distributed semantics for cross-lingual sentiment classification; a short texts matching method using shallow features and deep features; a feature extraction method based on word embedding for word similarity computing; word vector modeling for sentiment analysis of product reviews; aspect-object alignment using integer linear programming; sentiment classification of Chinese contrast sentences; social media as sensor in real world; a novel calibrated label ranking based method for multiple emotions detection in Chinese microblogs; enhance social context understanding with semantic chunks; estimating credibility of user clicks with mouse movement and eye-tracking information; a unified microblog user similarity model for online friend recommendation and normalization of Chinese informal medical terms based on multi-field indexing.

SCOPUS_ID:84947605975

3rd International Workshop on Text, Speech and Dialogue, TSD 2000

The proceedings contain 75 papers. The special focus in this conference is on Text, Speech and Dialogue. The topics include: The linguistic basis of a rule-based tagger of czech; harnessing the lexicographer in the quest for accurate word sense disambiguation; an integrated statistical model for tagging and chunking unrestricted text; extending bidirectional chart parsing with an stochastic model; ensemble of classifiers for noise detection in PoS tagged corpora; towards a dynamic syntax for language modelling; a word analysis system for german hyphenation, full text search, and spell checking, with regard to the latest reform of german orthography; automatic functor assignment in the prague dependency treebank; categories, constructions, and dependency relations; local grammars and parsing coordination of nouns in serbo-croatian; realization of syntactic parser for inflectional language using XML and regular expressions; a rigoristic and automated analysis of texts applied to a scientific abstract by mark sergot and others; evaluation of tectogrammatical annotation of PDT; probabilistic head-driven chart parsing of czech sentences; aggregation and contextual reference in automatically generated instructions; information retrieval by means of word sense disambiguation; statistical parameterisation of text corpora; an efficient algorithmfor japanese sentence compaction based on phrase importance and inter-phrase dependency; word senses and semantic representations; automatic tagging of compound verb groups in czech corpora; sensitive words and their application to chinese processing; testing a word analysis systemfor reliable and sense-conveying hyphenation and other applications and the challenge of parallel text processing.

SCOPUS_ID:84928926237

3rd Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2009

The proceedings contain 17 papers. The special focus in this conference is on Natural Language Processing. The topics include: Morphology-aware spell-checking dictionary for Esperanto; yet another formalism for morphological paradigm; fast morphological analysis of Czech; domain collocation identification; deductive reasoning using TIL; temporal aspects of knowledge and information; the saara framework; verb valency frames in Czech legal texts; semantic network integrity maintenance via heuristic semi-automatic tests; exploring and extending Czech wordnet and verbalex; measuring coverage of a valency lexicon using full syntactic analysis; discovering grammatical relations in Czech sentences; applying word sketches to Russian; Prague dependency Treebank annotation errors; classification of errors in text; problems of machine translation evaluation and languages of mathematics.

http://arxiv.org/abs/1906.01675v2

4-D Scene Alignment in Surveillance Video

Designing robust activity detectors for fixed camera surveillance video requires knowledge of the 3-D scene. This paper presents an automatic camera calibration process that provides a mechanism to reason about the spatial proximity between objects at different times. It combines a CNN-based camera pose estimator with a vertical scale provided by pedestrian observations to establish the 4-D scene geometry. Unlike some previous methods, the people do not need to be tracked nor do the head and feet need to be explicitly detected. It is robust to individual height variations and camera parameter estimation errors.

SCOPUS_ID:85058194184

4-Fluoramphetamine in the Netherlands: Text-mining and sentiment analysis of internet forums

Background: Users of new psychoactive substances including 4-fluoroamphetamine (4-FA/4-FMP) frequently share their experiences or opinions in online drug forums. We have tested the potential of computerised analysis of drug users’ forum posts for monitoring and early detection of trends. Specifically, we tested whether changes in the volume of 4-FA related posts and sentiments expressed in those posts can be observed around the time 4-FA was increasingly reported by Dutch drug monitoring sources (2012–2017). Methods: Opening posts from two popular Dutch internet-based drug discussion forums, written between January 1 st, 2012 and January 1 st, 2018 were scraped: Portions of the forum posts about 4-FA were collected. To contrast 4-FA findings against other categories of forum posts, we also collected posts on two other substances (ecstasy and cocaine) and posts not related to a specific substance. Sentiments expressed in these posts were inferred using text recognition software, and analysed for trends using linear mixed modelling. Results: The number of 4-FA posts increased between 2012 and 2015: 76 posts in 2012, 138 in 2013, 322 in 2014, 323 in 2015, and decreased thereafter: 264 in 2016 and 135 in 2017; X 2 (5) = 271.8, p <.001. Over time, a decrease in positive sentiment towards 4-FA can be observed starting in 2015, compared to the period before 2015, coinciding with more news searches and reports on adverse events related to 4-FA use. Linear mixed modelling analysis confirmed a significantly higher sentiment score in 2015 compared to 2017 for 4-FA, B = 0.062; SE = 0.023; t(1252) = 2.70; p = 0.007, but not for posts on other substances. Conclusion: Changes in the volume and sentiments of forum posts coincided with news media exposure related to 4-FA and with trends observed by established drug monitoring sources. Hence, internet forum monitoring facilitates early discovery of trends in the popularity, prevalence and adverse events related to new psychoactive substances.

http://arxiv.org/abs/2108.12074v1

4-bit Quantization of LSTM-based Speech Recognition Models

We investigate the impact of aggressive low-precision representations of weights and activations in two families of large LSTM-based architectures for Automatic Speech Recognition (ASR): hybrid Deep Bidirectional LSTM - Hidden Markov Models (DBLSTM-HMMs) and Recurrent Neural Network - Transducers (RNN-Ts). Using a 4-bit integer representation, a na\"ive quantization approach applied to the LSTM portion of these models results in significant Word Error Rate (WER) degradation. On the other hand, we show that minimal accuracy loss is achievable with an appropriate choice of quantizers and initializations. In particular, we customize quantization schemes depending on the local properties of the network, improving recognition performance while limiting computational time. We demonstrate our solution on the Switchboard (SWB) and CallHome (CH) test sets of the NIST Hub5-2000 evaluation. DBLSTM-HMMs trained with 300 or 2000 hours of SWB data achieves $<$0.5% and $<$1% average WER degradation, respectively. On the more challenging RNN-T models, our quantization strategy limits degradation in 4-bit inference to 1.3%.

SCOPUS_ID:85032434949

40 Years of Applied Linguistics: Investigating Content Areas, Research Methods, and Statistical Techniques

This review study was designed to map out the research trends through an intensive text analysis of 1,366 research articles (RAs) of applied linguistics during the past 40 years (from 1976 to 2015). RAs were coded and analyzed by four analysts to identify their content of research, research methods, and statistical procedures. It was found that there has been an increase in the number and the average length of articles. The average length has been on the rise from 8.09 pages in 1976-1985 to 14.38 during 2006-2015. The extensive review of the RAs also revealed a broad range of themes that belonged to 34 research domains. SLA, Technology & Language Learning, Language Teaching Methodology, Language Testing, and Psycholinguistics were the most widely researched areas. The qualitative method with 33.97% was the dominant research method in the journals. Regarding the statistical techniques, it was illustrated that descriptive statistics, Pearson correlation, ANOVA, and t-test were the most commonly used procedures in the applied linguistic RAs.