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"Timegrid" is a set of methods and tools geared towards working with polyphonic tempo structures. Common tempo operations such as linear and exponential accelerandi and more uncommon ones such as arbitrarily complex functions are used, which are converted to simple time and tempo pairs. Aimed at the composer these processes produce a variety of files useful for audition, graphical scoring and direct use in algorithmic composition. The methods and tools described here can be used to solve a variety of problems. As an additional example a method for the generation of random numbers from an arbitrary distribution is shown. "Timegrid" is implemented as an external and an application in MaxMSP and made publicly available together with its source code.

['Jan C. Schacher', 'Martin Neukom']

Where's The Beat? Tools for Dynamic Tempo Calculations

EVALUATION OF A TELERADIOLOGY SYSTEM - Impact and User Satisfaction

['Carla Rocha Pereira', 'Ana Ferreira', 'Luís Antunes']

EVALUATION OF A TELERADIOLOGY SYSTEM - Impact and User Satisfaction

Abstract Bipolar switching phenomenon is found for Au/n-type CuAlOx/heavily doped p-type Si devices at temperatures above 220 K. For high or low resistive states (HRS or LRS), the electrical resistance is decreased with increasing temperature, indicating a semiconducting behavior. Carrier transport at LRS or HRS is dominated by hopping conduction. It is reasonable to conclude that the transition from HRS to LRS due to the migration of oxygen vacancies (VO) is associated with electron hopping mediated through the VO trap sites. The disappearance of the resistive switching behavior below 220 K is attributed to the immobile VO traps. The deep understanding of conduction mechanism could help to control the device performance.

['Yow-Jon Lin', 'Yu-Ju Chu']

Temperature-dependent resistive switching characteristics for Au/n-type CuAlOx/heavily doped p-type Si devices

This paper presents the architecture of a Wavelength Division Multiplexing (WDM) optical packet network, called WONDER, that was designed and prototyped in the PhotonLab at Politecnico di Torino, Italy. The design and implementation of the WONDER network aim to assess the effectiveness of optical technologies with respect to electronic ones, trying to identify an optimal mix of the two technologies. The architecture shows interesting resilience properties that enable the design of fast fault-recovery schemes. In this paper, we present the physical topology and node structure of the prototype, and discuss the implementation and performance of a fault-recovery algorithm.

['Alessandro Antonino', 'Andrea Bianco', 'A. Bianciotto', 'V. De Feo', 'Jorge M. Finochietto', 'Roberto Gaudino', 'Fabio Neri']

WONDER: A resilient WDM packet network for metro applications

Networks of well-known dynamical units but unknown interaction topology arise across various fields of biology, including genetics, ecology, and neuroscience. The collective dynamics of such networks is often sensitive to the presence (or absence) of individual interactions, but there is usually no direct way to probe for their existence. Here we present an explicit method for reconstructing interaction networks of leaky integrate-and-fire neurons from the spike patterns they exhibit in response to external driving. Given the dynamical parameters are known, the approach works well for networks in simple collective states but is also applicable to networks exhibiting complex spatio-temporal spike patterns. In particular, stationarity of spiking time series is not required.

['Frank Van Bussel', 'Birgit Kriener', 'Marc Timme']

Inferring synaptic connectivity from spatio-temporal spike patterns.

Humans are confronted with an increasingly complex array of ingestion substances and dietary choices that influence health and well being. However, even with strong medical evidence that clearly links ingestion strategies and heath consequences, the general public struggles to make health-optimizing ingestion decisions. Based on our literature review, we delineate a typology of barriers to formulating health-optimizing ingestion strategies. We propose that the introduction of artificial intelligence (AI) as "decision management" (AI-DM) technology into the ingestion decision-making network would increase the likelihood of more predictable and optimized health outcomes. Also, we delineate the key informational constituencies needed to enable a comprehensive and effective AI-DM system. While no author has yet proposed AI in the particular context discussed in this paper, the theoretical and empirical literature suggests that this might be possible. We conclude by discussing areas for additional research.

['Robert Edgell', 'Roland Vogl']

A network view of human ingestion and health: instrumental artificial intelligence

Object tracking applications are gaining popularity and will soon utilize energy harvesting (EH) low-power nodes that will consume power mostly for neighbor discovery (ND) (i.e., identifying nodes within communication range). Although ND protocols were developed for sensor networks, the challenges posed by emerging EH low-power transceivers were not addressed . Therefore, we design an ND protocol tailored for the characteristics of a representative EH prototype : the TI eZ430-RF2500-SEH. We present a generalized model of ND accounting for unique prototype characteristics (i.e., energy costs for transmission/reception, and transceiver state switching times/costs). Then, we present the Power Aware ND Asynchronously (Panda) protocol, in which nodes transition between the sleep, receive, and transmit states. We analyze Panda and select its parameters to maximize the ND rate subject to a homogeneous power budget. We also present Panda-D, designed for non-homogeneous EH nodes. We perform extensive testbed evaluations using the prototypes and study various design tradeoffs. We demonstrate a small difference (less than 2%) between experimental and analytical results, thereby confirming the modeling assumptions. Moreover, we show that Panda improves the ND rate by up to $3\times $ compared with related protocols. Finally, we show that Panda-D operates well under non-homogeneous power harvesting.

['Robert Margolies', 'Guy Grebla', 'Tingjun Chen', 'Dan Rubenstein', 'Gil Zussman']

Panda: Neighbor Discovery on a Power Harvesting Budget

In this article we examine the effect of phase noise on a multi-antenna beamforming system. The effect is quantified in terms of error vector magnitude (EVM). It is shown that using independent phase noise sources improves EVM performance in the main lobe. It is further shown that when forming beams using antenna amplitude attenuation (tapering) for groups of correlated noise sources, lowest EVM is obtained when correlated noise sources are assigned to tapered amplitudes in a way which minimizes the differences between the sums of the tapering coefficients of the groups. Bounds for the variance of the phase noise in the main lobe are provided. Further a method achieving secure communication by forming a secure beam by adding uncorrelated phase noise to the antenna elements is presented.

['Thomas Höhne', 'V. Ranki']

Phase Noise in Beamforming

Modern hearing aids often contain multiple microphones to enable the use of spatial filtering techniques for signal enhancement. To steer the spatial filtering algorithm it is necessary to localize sources of interest, which can be intelligently achieved using computational auditory scene analysis (CASA). In this article, we describe a CASA system using a binaural auditory processing model that has been extended to six channels to allow reliable localization in both azimuth and elevation, thus also distinguishing between front and back. The features used to estimate the direction are one level difference and five inter-microphone time differences of arrival (TDOA). Initial experiments are presented that show the localization errors that can be expected with this set of features on a typical multichannel hearing aid in anechoic conditions with diffuse noise.

['Joachim Thiemann', 'Simon Doclo', 'Steven van de Par']

Features for speaker localization in multichannel bilateral hearing aids

Abstract Studying brain connectivity is important due to potential differences in brain circuitry between health and disease. One drawback of graph-theoretic approaches to this is that their results are dependent on the spatial scale at which brain circuitry is examined and explicitly on how vertices and edges are defined in network models. To investigate this, magnetic resonance and diffusion tensor images were acquired from 136 healthy adults, and each subject's cortex was parceled into as many as 50,000 regions. Regions were represented as nodes in a reconstructed network representation, and interregional connectivity was inferred via deterministic tractography. Network model behavior was explored as a function of nodal number and connectivity weighing. Three distinct regimes of quantitative behavior assumed by network models as a function of spatial scale are identified, and their existence may be modulated by the spatial folding scale of the cortex. The maximum number of network nodes used to model h...

['Andrei Irimia', 'Van Horn Jd']

Scale-Dependent Variability and Quantitative Regimes in Graph-Theoretic Representations of Human Cortical Networks.

This paper presents a platform developed for in production testing of modular embedded systems. These systems are flexible and low cost, with respect to production and maintenance. However, they require a complex testing process, in order to reduce the flaws in the production process and increase the rate of certified modules. For the manufacturers, modular embedded systems offer the possibility of reusing parts of a project in other projects, thus reducing the overall cost. Being reconfigurable, these systems enable the manufacturers to sell devices that fit the requirements of more users.

['Silviu Folea', 'Szilard Enyedi', 'Liviu Miclea', 'Horia Hedesiu']

Reconfigurable test platform for modular embedded systems in manufacturing processes

In the mid 1980?s Toyota came to the US and showed Detroit how to work with suppliers on a win-win basis. In just five years, Toyota was the most trusted automaker among all automotive suppliers, had the lowest procurement costs, and the highest contribution of innovation from supplier companies. What does Toyota know about working with contracts that we can learn? For starters, they know that trust lies in specific actions, not interpersonal relationships. They understand the ?game? of contracting, and know how to structure relationships so both sides are motivated to contribute to the common good. There?s much we can learn from Toyota about how to change the contracting game in software development for the benefit of both parties.

['Mary Poppendieck']

Agile Contracts

Smart Grids and Home Energy Management System (HEMS) have been propagated by energy liberalization, and there is a demand for services, which are based on analysis of energy consumption data. For instance, a recommendation on effective utilization of home appliances in order to reduce power consumption. However, it is computationally expensive to analyze data in order to provide an energy-saving handbook, which recommends low-carbon life and is written in a natural language. This kind of service is called recommendation service. Existing automated recommendation services are constrained by the range of data usage, especially when using local information, such as status of surroundings, weather, residents' behavior, etc. The proposed method of automated generation of recommendation considers this background knowledge and information by using clustering methods. The result of a questionnaire which compared a handmade recommendation with the proposed fully-automated recommendation showed that 80% of the residents selected the automated recommendation because of its appropriateness.

['Takahiro Hosoe', 'Tadanori Matsui', 'Hiroaki Nishi']

Automated generation method of recommendation for effective energy utilization as a HEMS service

Multiple Instance Learning (MIL) is concerned with learning from sets (bags) of feature vectors (instances), where the individual instance labels are ambiguous. In MIL it is often assumed that positive bags contain at least one instance from a so-called concept in instance space, whereas negative bags only contain negative instances. The classes in a MIL problem are therefore not treated in the same manner. One of the ways to classify bags in MIL problems is through the use of bag dissimilarity measures. In current dissimilarity approaches, such dissimilarity measures act on the bag as a whole and do not distinguish between positive and negative bags. In this paper we explore whether this is a reasonable approach and when and why a dissimilarity measure that is dependent on the bag label, might be more appropriate.

['Veronika Cheplygina', 'David M. J. Tax', 'Marco Loog']

Class-dependent dissimilarity measures for multiple instance learning

The mean-squared-error measure of quality is used as a basis for a general nearest prototype signal-classification methodology. Canonical signal features for this methodology are identified. A consistency requirement is proposed and used to develop a general approach for determining appropriate class prototypes in discriminant space. It is shown that the class indicator, which is a commonly used class prototype in pattern recognition applications, will often violate the consistency requirement. The general results are used to obtain a solution to a previously posed complexity-performance trade-off problem for matched-filter-tapped-delay-line receivers for serial signal classification in an M -ary data transmission system.

['William A. Gardner']

Design of nearest prototype signal classifiers (Corresp.)

We study the number of hidden layers required by a multilayer neural network with threshold units to compute a function f from Rd to {0, 1}. In dimension d = 2, Gibson characterized the functions computable with just one hidden layer, under the assumption that there is no "multiple intersection point" and that f is only defined on a compact set. We consider the restriction of f to the neighborhood of a multiple intersection point or of infinity, and give necessary and sufficient conditions for it to be locally computable with one hidden layer. We show that adding these conditions to Gibson's assumptions is not sufficient to ensure global computability with one hidden layer, by exhibiting a new non-local configuration, the "critical cycle", which implies that f is not computable with one hidden layer.

['Graham R. Brightwell', 'Claire Kenyon', 'Hélène Paugam-Moisy']

Multilayer Neural Networks: One or Two Hidden Layers?

Cloud storage for information sharing is likely indispensable to the future national defence library in China e.g., for searching national defence patent documents, while security risks need to be maximally avoided using data encryption. Patent keywords are the high-level summary of the patent document, and it is significant in practice to efficiently extract and search the key words in the patent documents. Due to the particularity of Chinese keywords, most existing algorithms in English language environment become ineffective in Chinese scenarios. For extracting the keywords from patent documents, the manual keyword extraction is inappropriate when the amount of files is large. An improved method based on the term frequency-inverse document frequency (TF-IDF) is proposed to auto-extract the keywords in the patent literature. The extracted keyword sets also help to accelerate the keyword search by linking finite keywords with a large amount of documents. Fuzzy keyword search is introduced to further increase the search efficiency in the cloud computing scenarios compared to exact keyword search methods. Based on the Chinese Pinyin similarity, a Pinyin-Gram-based algorithm is proposed for fuzzy search in encrypted Chinese environment, and a keyword trapdoor search index structure based on the n-ary tree is designed. Both the search efficiency and accuracy of the proposed scheme are verified through computer experiments.

['Wei Ding', 'Yongji Liu', 'Jianfeng Zhang']

Chinese-keyword fuzzy search and extraction over encrypted patent documents

Formal verification tools are often developed by experts for experts; as a result, their usability by programmers with little formal methods experience may be severely limited. In this paper, we discuss this general phenomenon with reference to AutoProof: a tool that can verify the full functional correctness of object-oriented software. In particular, we present our experiences of using AutoProof in two contrasting contexts representative of non-expert usage. First, we discuss its usability by students in a graduate course on software verification, who were tasked with verifying implementations of various sorting algorithms. Second, we evaluate its usability in verifying code developed for programming assignments of an undergraduate course. The first scenario represents usability by serious non-experts; the second represents usability on “standard code”, developed without full functional verification in mind. We report our experiences and lessons learnt, from which we derive some general suggestions for furthering the development of verification tools with respect to improving their usability.

['Carlo A. Furia', 'Christopher M. Poskitt', 'Julian Tschannen']

The AutoProof Verifier: Usability by Non-Experts and on Standard Code

A simple matrix is a (0,1)-matrix with no repeated columns. For a (0,1)-matrix $F$, we say that a (0,1)-matrix $A$ has $F$ as a Berge hypergraph if there is a submatrix $B$ of $A$ and some row and column permutation of $F$, say $G$, with $G\le B$. Letting $\|A\|$ denote the number of columns in $A$, we define the extremal function $\mathrm{Bh}(m,{ F})=\max\{\|A\|\,:\, A \hbox{ }m\hbox{-rowed simple matrix and no Berge hypergraph }F\}$. We determine the asymptotics of $\mathrm{Bh}(m,F)$ for all $3$- and $4$-rowed $F$ and most $5$-rowed $F$. For certain $F$, this becomes the problem of determining the maximum number of copies of $K_r$ in a $m$-vertex graph that has no $K_{s,t}$ subgraph, a problem studied by Alon and Shikhelman.

['Richard P. Anstee', 'Santiago Salazar']

Forbidden Berge Hypergraphs

Diff-index: Differentiated index in distributed log-structured data stores

['Wei Tan', 'Sandeep Tata', 'Yuzhe Tang', 'Liana Fong']

Diff-index: Differentiated index in distributed log-structured data stores

Search is a central component of any statistical machine translation system. We describe the search for phrase-based SMT in detail and show its importance for achieving good translation quality. We introduce an explicit distinction between reordering and lexical hypotheses and organize the pruning accordingly. We show that for the large Chinese-English NIST task already a small number of lexical alternatives is sufficient, whereas a large number of reordering hypotheses is required to achieve good translation quality. The resulting system compares favorably with the current stateof-the-art, in particular we perform a comparison with cube pruning as well as with Moses.

['Richard Zens', 'Hermann Ney']

Improvements in Dynamic Programming Beam Search for Phrase-based Statistical Machine Translation

A Combination of Knowledge and Argumentation Based System for Supporting Injection Mould Design.

['David Cabanillas', 'F. Bonada', 'Raquel Ventura', 'Francesca Toni', 'Valentinos Evripidou', 'Lucas Carstens', 'Liceth Rebolledo']

A Combination of Knowledge and Argumentation Based System for Supporting Injection Mould Design.

Monoterpenes from the essential oils of several plants have been shown to enhance the bactericidal activities of nitrofurantoin and furazolidone against the bacteria of Enterobacteriaceae family. In this study, computer-aided molecular modeling and docking techniques have been employed to simulate the theoretical mode of interaction between monoterpenes and Enterobacter cloacae nitroreductase. Enhancement of nitro drug potency in the presence of monoterpenes may be the result of modulation of nitroreductase activity. Binding nitroreductase with monoterpenes may decrease the efficient conversion of toxic reactive intermediates to final products lacking bactericidal activity.

['Sako Mirzaie', 'Fatemeh Rafii', 'Katsuaki Yasunaga', 'Kunie Yoshunaga', 'Zargham Sepehrizadeh', 'Shinji Kanno', 'Yu Tonegawa', 'Ahmad Reza Shahverdi']

Prediction of the mode of interaction between monoterpenes and the nitroreductase from Enterobacter cloacae by docking simulation

Modular exponentiation and modular multiplication are the cornerstone computations performed in public-key cryptography systems such as RSA cryptosystem. The operations are time consuming for large operands. Much research effort is directed towards an efficient hardware implementation of both operations. This paper describes the characteristics of two architectures: the first one implements modular multiplication using a systolic version of the fast Montgomery algorithm and the other to implement the parallel binary exponentiation algorithm. The latter uses two Montgomery modular multipliers. Results in terms of space and time requirements for an FPGA prototype are given.

['Nadia Nedjah', 'L. de Macedo Mourelle']

Reconfigurable hardware implementation of Montgomery modular multiplication and parallel binary exponentiation

The Forgotten Many? A Survey of Modern Web Development Practices

['Moira C. Norrie', 'Linda Di Geronimo', 'Alfonso Murolo', 'Michael Nebeling']

The Forgotten Many? A Survey of Modern Web Development Practices

Automated Analysis and Adaptation of Disaster Response Processes with Place-Related Restrictions.

['Marlen Hofmann', 'Hans Betke', 'Stefan Sackmann']

Automated Analysis and Adaptation of Disaster Response Processes with Place-Related Restrictions.

Mental simulation is proposed by cognitive psychologists as a candidate to model the human reasoning process. In this paper, we propose a methodology that models mental simulation to create realistic human behavior in simulated environments. This methodology is used to generate realistic intruder and guard behavior in physical security systems simulation. The behaviors include moving to a target while avoiding detection/capture for intruders and following and apprehending intruders for guards.

['Volkan Ustun', 'Jeffrey S. Smith']

Mental simulation for creating realistic behavior in physical security systems simulation

Web services are playing an important role in several areas. However, with the proliferation of these services, the task of searching for relevant services becomes more and more difficult. This paper presents a new framework for web service publication and discovery in a distributed architecture. The framework, based on a multi-agent system, gives services' publishing and searching another dimension. The service description includes an enriched representation, composed of contexts and quality of service (QoS) parameters, in order to make more efficient the discovery and selection stages. This representation (user/service contexts and QoS parameters) is taken into account during the discovery process. The search agent uses a new quantitative similarity measure to calculate the correspondence rate between the client and the services profiles in order to provide users with appropriate services according to their contexts and required QoS parameters.

['Fayçal M’hamed Bouyakoub', 'Abdelkader Belkhir', 'Mohamed Amine Mellal']

A multi-agent system for web services discovery in a UDDI cloud

We analyze psychological dynamics of human-Web interaction exemplified by social tagging. Whereas previous models assumed tagging was driven by individual knowledge and social imitation, we introduce a reflective search framework that assumes user behavior (e.g., exploration and tagging of web resources) to arise from an iterative search of human memory shaped continuously by past and present learning episodes. We formalize this framework by means of a mathematical model of search of human memory which interrelates episodic and semantic memory processes. This allows us to simulate both temporal macro dynamics (stabilization of tag distribution) and underlying temporal micro dynamics (reflecting and tagging a resource). While the former are well covered by previous models, these models are not able to explain the latter. We claim that shifting away from imitation to reflective search holds great potential for understanding and designing human web interaction more generally, and to validate models of human memory in large-scale web environments.

['Paul Seitlinger', 'Tobias Ley']

Reconceptualizing imitation in social tagging: a reflective search model of human web interaction

Different from multiuser detection, synchronization in multiuser communications systems has its unique features. We revisit effective multiuser synchronizers in a systematic way and classify them into two categories: linear multiuser synchronizers and the multiuser synchronizers based on the frequency domain approach. Both categories of estimators have their special advantages according to their characteristics and are applicable to practical DS/CDMA communications systems.

['C. C. Chang', 'Kwang-Cheng Chen']

Multiuser synchronization

Commercial digital music is typically distributed in the music source market via Digital Rights Management systems (DRM). DRM systems help remotely control the music contents. The Open Mobile Alliance (OMA) DRM became the de facto standard after major market adoption because of its support for a wide variety of different business and usage models. In OMA DRM, a popular business model is a (monthly) subscription enforced by controlling the period of playback time; once the given period of time expires, the music cannot be played. In this paper, we demonstrate how to bypass the integrity checking of the rights object in the OMA DRM system through a case study of MelOn (a well-known music distribution service in South Korea) by reverse engineering its media player equipped with a DRM agent.

['Jusop Choi', 'William Aiken', 'Jungwoo Ryoo', 'Hyoungshick Kim']

Bypassing the Integrity Checking of Rights Objects in OMA DRM: a Case Study with the MelOn Music Service

Robust Scene Classification with Cross-Level LLC Coding on CNN Features

['Zequn Jie', 'Shuicheng Yan']

Robust Scene Classification with Cross-Level LLC Coding on CNN Features

Rupture of intracranial saccular aneurysms is the most common cause of spontaneous subarachnoid hemorrhage, which has significant morbidity and mortality. Although there is still controversy regarding the decision on which unruptured aneurysms should be treated, this is based primarily on their size. Nonetheless, many large lesions do not rupture whereas some small ones do. It is commonly accepted that hemodynamical factors are important to better understand the natural history of cerebral aneurysms. However, it might not always be practical to carry out a detailed computational analysis of such factors if a prompt assessment is required. Since shape is likely to be dependent on the balance between hemodynamic forces and the aneurysmal surrounding environment, an appropriate morphological 3-D characterization is likely to provide a practical surrogate to quickly evaluate the risk of rupture. In this paper, an efficient and novel methodology for 3-D shape characterization of cerebral aneurysms is described. The aneurysms are isolated by taking into account a portion of their adjacent vessels. Two methods to characterize the morphology of the aneurysms models using moment invariants have been considered: geometrical moment invariants (GMI) and Zernike moment invariants (ZMI). The results have been validated in a database containing 53 patients with a total of 31 ruptured aneurysms and 24 unruptured aneurysms. It has been found that ZMI indices are more robust than GMI, and seem to provide a reliable way to discriminate between ruptured and unruptured aneurysms. Correct rupture prediction rates of sime80% were achieved in contrast to 66% that is found when the aspect ratio index is considered.

['Raúl Millán', 'Laura Dempere-Marco', 'Jose M. Pozo', 'Juan R. Cebral', 'Alejandro F. Frangi']

Morphological Characterization of Intracranial Aneurysms Using 3-D Moment Invariants

In this paper, we consider the decentralized adaptive control design problem for uncertain mechanical systems, where uncertainty may arise due to isolated subsystem and/or interconnections among subsystems. Radial basis function neural networks are used to approximate the nonlinear functions to include both dynamic and interconnection uncertainties in each subsystem. The stability of the thus designed control system can be guaranteed by a rigid proof. Finally, a simulation example is given to illustrate the effectiveness of the proposed algorithm.

['Sunan Huang', 'Kok Kiong Tan', 'Tong Heng Lee', 'Andi Sudjana Putra']

Adaptive Control of Mechanical Systems Using Neural Networks

The increase of the technology revolution is encouraging MANET (A Mobile ad-hoc network) to be used in different sectors and for different purposes. MANET can be used in a variety of different ways such as for personal usage, meetings, and recovery and relief from disasters. The demand on this type of network raises security concerns especially in reference to its specific features such as dynamic topology and no central administration point. A MANET is not a conflict-free environment, so many attacks are aimed at it, but the focus of this study is a DoS (Denial of Service) attack. This paper presents a novel method of MrDR (Monitoring, Detection, and Rehabilitation) to detect DoS attacks and it is applied in this experiment specifically on single MANET. The MrDR method is based on a trust concept, which it is assumed is not transitive. In addition, the trust value in the proposed method is something temporal, a short-lived action, and needs to be recalculated due to the dynamic infrastructure of MANETs. The simulation results of using the MrDR method prove that the effectiveness of the use of this method can increase network performance considerably.

['Albandari Alsumayt', 'John Haggerty', 'Ahmad Lotfi']

Performance, Analysis, and Comparison of MrDR Method to Detect DoS Attacks in MANET

How Cognitively Effective is a Visual Notation? On the Inherent Difficulty of Operationalizing the Physics of Notations

['Dirk van der Linden', 'Anna Zamansky', 'Irit Hadar']

How Cognitively Effective is a Visual Notation? On the Inherent Difficulty of Operationalizing the Physics of Notations

In this article we propose a moment-based method for studying models and model selection measures. By focusing on the probabilistic space of classifiers induced by the classification algorithm rather than on that of datasets, we obtain efficient characterizations for computing the moments, which is followed by visualization of the resulting formulae that are too complicated for direct interpretation. By assuming the data to be drawn independently and identically distributed from the underlying probability distribution, and by going over the space of all possible datasets, we establish general relationships between the generalization error, hold-out-set error, cross-validation error, and leave-one-out error. We later exemplify the method and the results by studying the behavior of the errors for the naive Bayes classifier.

['Amit Dhurandhar', 'Alin Dobra']

Semi-analytical method for analyzing models and model selection measures based on moment analysis

Gaze-Based Annotations: Labels on Demand.

['Patrick Saalfeld', 'André Mewes', 'Christian Hansen', 'Bernhard Preim']

Gaze-Based Annotations: Labels on Demand.

It is well known that performance of adaptive filters is mainly a compromise among computational complexity, speed of convergence and steady-state behavior. The affine projection (AP) algorithm offers a good convergence speed that increases with the projection order N and a computational complexity that can be reduced by applying different fast strategies. However, its steady-state mean square error (MSE) worsens when N grows. This work introduces the convex combination of two AP adaptive filters in order to improve the performance capabilities of the overall filter. The purpose of the convex AP approach is to improve the convergence performance of a single AP algorithm but not at the expense of an increase of the steady-state MSE. To achieve this we combine two AP filters with different projection orders, one of high N order that performs faster than other with a lower order but with a better MSE. Moreover, the computational cost of the AP combination scheme would be similar to that of the higher order AP filter working separately. Simulation results have validated the proposed approach.

['Miguel Ferrer', 'Maria de Diego', 'Alberto Gonzalez', 'Gema Pinero']

Convex combination of affine projection algorithms

We address the 3D tracking of pose and animation of the human face in monocular image sequences using active appearance models. The classical appearance-based tracking suffers from two disadvantages: (i) the estimated out-of-plane motions are not very accurate, and (ii) the convergence of the optimization process to desired minima is not guaranteed. We aim at designing an efficient active appearance model, which is able to cope with the above disadvantages by retaining the strengths of feature-based and featureless tracking methodologies. For each frame, the adaptation is split into two consecutive stages. In the first stage, the 3D head pose is recovered using robust statistics and a measure of consistency with a statistical model of a face texture. In the second stage, the local motion associated with some facial features is recovered using the concept of the active appearance model search. Tracking experiments and method comparison demonstrate the robustness and out-performance of the developed framework.

['Fadi Dornaika', 'Jörgen Ahlberg']

Efficient active appearance model for real-time head and facial feature tracking

Due to a tremendous increase in internet traffic, backbone routers must have the capability to forward massive incoming packets at several gigabits per second. IP address lookup is one of the most challenging tasks for high-speed packet forwarding. Some high-end routers have been implemented with hardware parallelism using ternary content addressable memory (TCAM). However, TCAM is much more expensive in terms of circuit complexity as well as power consumption. Therefore, efficient algorithmic solutions are essentially required to be implemented using network processors as low cost solutions. Among the state-of-the-art algorithms for IP address lookup, a binary search based on a balanced tree is effective in providing a low-cost solution. In order to construct a balanced search tree, the prefixes with the nesting relationship should be converted into completely disjointed prefixes. A leaf-pushing technique is very useful to eliminate the nesting relationship among prefixes [V. Srinivasan, G. Varghese, Fast address lookups using controlled prefix expansion, ACM Transactions on Computer Systems 17 (1) (1999) 1-40]. However, it creates duplicate prefixes, thus expanding the search tree. This paper proposes an efficient IP address lookup algorithm based on a small balanced tree using entry reduction. The leaf-pushing technique is used for creating the completely disjointed entries. In the leaf-pushed prefixes, there are numerous pairs of adjacent prefixes with similarities in prefix strings and output ports. The number of entries can be significantly reduced by the use of a new entry reduction method which merges pairs with these similar prefixes. After sorting the reduced disjointed entries, a small balanced tree is constructed with a very small node size. Based on this small balanced tree, a native binary search can be effectively used in address lookup issue. In addition, we propose a new multi-way search algorithm to improve a binary search for IPv4 address lookup. As a result, the proposed algorithms offer excellent lookup performance along with reduced memory requirements. Besides, these provide good scalability for large amounts of routing data and for the address migration toward IPv6. Using both various IPv4 and IPv6 routing data, the performance evaluation results demonstrate that the proposed algorithms have better performance in terms of lookup speed, memory requirement and scalability for the growth of entries and IPv6, as compared with other algorithms based on a binary search.

['Hyuntae Park', 'Hyejeong Hong', 'Sungho Kang']

An efficient IP address lookup algorithm based on a small balanced tree using entry reduction

We propose an algorithm for the numerical solution of the Lur’e equations in the bounded real and positive real lemma for stable systems. The algorithm provides approximate solutions in low-rank factored form. We prove that the sequence of approximate solutions is monotonically increasing with respect to definiteness. If the shift parameters are chosen appropriately, the sequence is proven to be convergent to the minimal solution of the Lur’e equations. The algorithm is based on the ideas of the recently developed ADI iteration for algebraic Riccati equations (Massoudi et al., SIAM J Matrix Anal Appl, 2016). In particular, the matrices obtained in our iteration express the optimal cost in a certain projected optimal control problem.

['Arash Massoudi', 'Mark R. Opmeer', 'Timo Reis']

The ADI method for bounded real and positive real Lur'e equations

A Hybrid Approach to Grapheme-Phoneme Conversion.

['Kay-Michael Würzner', 'Bryan Jurish']

A Hybrid Approach to Grapheme-Phoneme Conversion.

Runtime Support for Human-in-the-Loop Feature Engineering System.

['Michael R. Anderson', 'Dolan Antenucci', 'Michael J. Cafarella']

Runtime Support for Human-in-the-Loop Feature Engineering System.

Review of Statistical Theory of Signal Detection, 2nd edn.(Helstrom, C. W.; 1968)

['Andrew J. Viterbi']

Review of Statistical Theory of Signal Detection, 2nd edn.(Helstrom, C. W.; 1968)

We present a novel technique for the 3D segmentation of unknown objects from cluttered dual-energy Computed Tomography (CT) data obtained in the baggage security-screening domain. Initial materials-based coarse segmentations, generated using the Dual-Energy Index (DEI), are refined by partitioning at automatically detected regions. Partitioning is guided by a novel random forest based quality metric, trained to recognise high-quality, single-object segments. A second novel segmentation quality measure is presented for quantifying the quality of full segmentations based on the random forest metric of the constituent parts and the error in the number of objects segmented. In a comparative evaluation between the proposed approach and three state-of-the-art volumetric segmentation techniques designed for single-energy CT data (two region-growing 1,2] and one graph-based 3]) our method is shown to outperform both region-growing methods in terms of segmentation quality and speed. Although the graph-based approach generates more accurate partitions, it is characterised by high processing times and is significantly outperformed by the proposed method in this regard. The observations made in this study indicate that the proposed segmentation technique is well-suited to the baggage security-screening domain, where the demand for computational efficiency is paramount to maximise throughput. HighlightsNovel dual-energy materials-based 3D segmentation technique.Two novel random forest-based segmentation quality metrics.Novel segmentation refinement procedure.Comparative evaluation using dual-energy baggage screening CT data.Demonstrate high-quality segmentations at low processing times.

['Andre Mouton', 'Toby P. Breckon']

Materials-based 3D segmentation of unknown objects from dual-energy computed tomography imagery in baggage security screening

Numerous methods have been proposed for the expression-invariant 3D face recognition, but a little attention is given to the local-based representation for the texture of the 3D images. In this paper, we propose an expression-invariant 3D face recognition approach based on the locally extracted moments of the texture when only one exemplar per person is available. We use a geodesic texture transform accompanied by Pseudo Zernike Moments to extract local feature vectors from the texture of a face. An extensive experimental investigation is conducted using publicly available BU-3DFE face databases covering face recognition under expression variations. The performance of the proposed method is compared with the performance of two benchmark approaches. The encouraging experimental results demonstrate that the proposed method can be used for 3D face recognition in single model databases.

['Farshid Hajati', 'Abolghasem A. Raie', 'Yongsheng Gao']

Expression-Invariant 3D Face Recognition Using Patched Geodesic Texture Transform

In order to provide large embedding capacity and to minimize distortion for the stego-image, a steganographic method using multi-pixel differencing is presented in this paper. It takes into consideration four pixels of a block, and the differences between the lowest gray-value pixel and its surrounding pixels are used to determine the degree of smoothness and sharpness for embedding the secret data. If the difference values are large in a block, and the block is located in the sharp area then more data can be embedded. On the other hand, if the block is located in the smooth area less data can be embedded. The multi-pixel differencing method is employed in our scheme. We also propose the pixel-value shifting method to increase the image quality. The experimental results show that our scheme has a large embedding capacity without creating a noticeable distortion.

['Cheng-Hsing Yang', 'Shiuh-Jeng Wang', 'Chi-Yao Weng']

Capacity-Raising Steganography Using Multi-Pixel Differencing and Pixel-Value Shifting Operations

This paper presents a unification procedure which eliminates the redundant copying of structures by using a lazy incremental copying approach to achieve structure sharing. Copying of structures accounts for a considerable amount of the total processing time. Several methods have been proposed to minimize the amount of necessary copying. Lazy Incremental Copying (LIC) is presented as a new solution to the copying problem. It synthesizes ideas of lazy copying with the notion of chronological dereferencing for achieving a high amount of structure sharing.

['Martin C. Emele']

UNIFICATION WITH LAZY NON-REDUNDANT COPYING

The paper presents an MPEG-7 multimedia description schemes (MDS)-based metadata and user profile model used within an enhanced DTV environment for semantic annotation and personalized access to multiple sports DTV services. It is shown that in order to enable intelligent and personalized processing, management and use of multimedia content and services, the use of application specific metadata descriptions and adequately formulated user profiles is most important. Thus, application specific semantic metadata and user profile definitions are presented in this paper. Metadata and user profile instances are generated by authoring/annotation tools or user profile registration client applications respectively. Personalized access to sports DTV services is achieved by metadata and user profile instance description matching and content filtering at either the server or the client side. At the same time, dynamic client configuration, transparent to the end-user, is accomplished by automatically processing configuration specific metadata descriptions using specially designed application modules at the client side. The main purpose is to enable personalized integrated multimedia services access in the sports domain over DTV infrastructures

['Sofia Tsekeridou']

MPEG-7 MDS-Based Application Specific Metadata Model for Personalized Multi-Service Access in a DTV Broadcast Environment

We study a novel phenomenon for coupled identical bursters: synchronized bursts where there are changes of spike synchrony within each burst. The examples we study are for normal form elliptic bursters where there is a periodic slow passage around a Bautin (codimension two degenerate Andronov-Hopf) bifurcation. This burster has a subcritical Andronov-Hopf bifurcation at the onset of repetitive spiking, while the end of burst occurs via a fold limit cycle bifurcation. We study synchronization behavior of two and three Bautin-type elliptic bursters for a linear direct coupling scheme as well as demonstrating the phenomenon in an approximation of gap-junction and synaptic coupling. Burst synchronization is known to be prevalent among such coupled bursters, while spike synchronization is more dependent on the details of the coupling. We note that higher order terms in the normal form that do not affect the behavior of a single burster can be responsible for changes in the synchrony pattern; more precisely, we find within-burst synchrony changes associated with a turning point in the spiking frequency.

['Abul Kalam al Azad', 'Peter Ashwin']

Within-Burst Synchrony Changes for Coupled Elliptic Bursters

In this paper we describe our experience with Teapot [7], a domain-specific language for writing cache coherence protocols. Cache coherence is of concern when parallel and distributed computing systems make local replicas of shared data to improve scalability and performance. In both distributed shared memory systems and distributed file systems, a coherence protocol maintains agreement among the replicated copies as the underlying data are modified by programs running on the system. Cache coherence protocols are notoriously difficult to implement, debug, and maintain. Unfortunately, protocols are not off-the-shelf items, as their details depend on the requirements of the system under consideration. This paper presents case studies detailing the successes and shortcomings of using Teapot for writing coherence protocols in two systems. The first system, loosely coherent memory (LCM) [16], implements a particular type of distributed shared memory suitable for data-parallel programming. The second system, the xFS distributed file system [9], implements a high-performance, serverless file system. Our overall experience with Teapot has been very positive. In particular, Teapot's language features resulted in considerable simplifications in the protocol source code for both systems. Furthermore, Teapot's close coupling between implementation and formal verification helped to achieve much higher confidence in our protocol implementations than previously possible and reduced the time to build the protocols. By using Teapot to solve real problems in complex systems, we also discovered several shortcomings of the Teapot design. Most noticeably, we found Teapot lacking in support for multithreaded environments, for expressing actions that transcend several cache blocks, and for handling blocking system calls. We believe that domain-specific languages are valuable tools for writing cache coherence protocols.

['Satish Chandra', 'Michael Dahlin', 'Bradley Richards', 'Randolph Y. Wang', 'Thomas E. Anderson', 'James R. Larus']

Experience with a Language for Writing Coherence Protocols

Nonbinary ultra sparse codes, particularly regular cycle codes, are known to approach Shannon-limit performance as the Galois field $ \mathrm {GF}(q)$ order is sufficiently large. Good cycle codes can result from a class of algebraically defined graphs called cages. Meanwhile, when smaller $q$ is desirable, the cycle codes are outperformed by quasi-regular codes. In this letter, we propose a code construction method that takes a cage as a starting point and then progressively inserts a few additional edges into the graph. The edge insertion is terminated as soon as the code performance stops improving. Our simulation results show that the obtained quasi-regular codes outperform cyclic codes for fields up to GF(64) and its performance is slightly better than the quasi-regular improved-Progressive Edge Growth-based codes. The proposed algorithm preserves the block-circulant structure of the initial cage-based graph; therefore, it can be used for structured or quasi-cyclic codes design.

['W. Sułek']

Nonbinary Quasi-Regular QC-LDPC Codes Derived From Cycle Codes

We analyse and compare the classification accuracies of six different classifiers for a two-class mental task (mental arithmetic and rest) using functional near-infrared spectroscopy (fNIRS) signals. The signals of the mental arithmetic and rest tasks from the prefrontal cortex region of the brain for seven healthy subjects were acquired using a multichannel continuous-wave imaging system. After removal of the physiological noises, six features were extracted from the oxygenated hemoglobin (HbO) signals. Two- and three-dimensional combinations of those features were used for classification of mental tasks. In the classification, six different modalities, linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), -nearest neighbour (NN), the Naive Bayes approach, support vector machine (SVM), and artificial neural networks (ANN), were utilized. With these classifiers, the average classification accuracies among the seven subjects for the 2- and 3-dimensional combinations of features were 71.6, 90.0, 69.7, 89.8, 89.5, and 91.4% and 79.6, 95.2, 64.5, 94.8, 95.2, and 96.3%, respectively. ANN showed the maximum classification accuracies: 91.4 and 96.3%. In order to validate the results, a statistical significance test was performed, which confirmed that the p values were statistically significant relative to all of the other classifiers (p < 0.005) using HbO signals.

['Noman Naseer', 'Nauman Khalid Qureshi', 'Farzan Majeed Noori', 'Keum-Shik Hong']

Analysis of Different Classification Techniques for Two-Class Functional Near-Infrared Spectroscopy-Based Brain-Computer Interface

We give an effective characterization of the lexicographically least word in the orbit closure of the Rudin-Shapiro word w having a specified prefix. In particular, the lexicographically least word in the orbit closure of the Rudin-Shapiro word is 0w. This answers a question Allouche et al. (Theoretical Computer Science 2009).

['James D. Currie']

Lexicographically least words in the orbit closure of the Rudin-Shapiro word

An Axiomatic Decision Aid for Marine Equipment Selection in Ship Machinery Design and Installation Projects.

['Selcuk Cebi', 'Metin Celik', 'Cengiz Kahraman']

An Axiomatic Decision Aid for Marine Equipment Selection in Ship Machinery Design and Installation Projects.

Combining Ontologies and Neural Networks for Analyzing Historical Language Varieties. A Case Study in Middle Low German.

['Maria Sukhareva', 'Christian Chiarcos']

Combining Ontologies and Neural Networks for Analyzing Historical Language Varieties. A Case Study in Middle Low German.

Projects Characteristics Determining Suitability of Software Development Process.

['Michel dos Santos Soares', 'Joseph Barjis']

Projects Characteristics Determining Suitability of Software Development Process.

A Random-Sampling Double-Auction Mechanism

['Erel Segal-Halevi', 'Avinatan Hassidim', 'Yonatan Aumann']

A Random-Sampling Double-Auction Mechanism

Mobile devices and apps have become an essential part of our daily life activities. Multi-touch gesture interaction directly on the touch screen is one of the most common ways to interact with mobile devices. However, in special circumstances (e.g., disabilities, wet hands, wearing heavy gloves outside in cold weather, etc.) it is difficult to interact directly on the touch screen. In this work, we focus on utilizing the 3D accelerometer sensor, available in most of the current mobile devices, as a way to provide an alternative set of gestures to the standard set of multi-touch gestures. We defined these 3D accelerometer-based gestures' definitions based on a user study and built an opens-source library, called 3DA-Gest, for providing the functionality to be used by mobile application developers. Further, we built a proof of concept map-based mobile app to check the working of our library. The preliminary conducted user study shows that users prefer to use our accelerometer-based gestures in special circumstances.

['Shah Rukh Humayoun', 'Munir Ahmad', 'Achim Ebert']

3D Accelerometer-based Gestures for Interacting with Mobile Devices

The presence of unpatched, exploitable vulnerabilities in software is a prerequisite for many forms of cyberattack. Because of the almost inevitable discovery of a vulnerability and creation of an exploit for all types of software, multiple layers of security are usually used to protect vital systems from compromise. Accordingly, attackers seeking to access protected systems must circumvent all of these layers. Resource- and budget-constrained defenders must choose when to execute actions such as patching, monitoring and cleaning infected systems in order to best protect their networks. Similarly, attackers must also decide when to attempt to penetrate a system and which exploit to use when doing so. We present an approach to modelling computer networks and vulnerabilities that can be used to find the optimal allocation of time to different system defence tasks. The vulnerabilities, state of the system and actions by the attacker and defender are used to build partially observable stochastic games. These games capture the uncertainty about the current state of the system and the uncertainty about the future. The solution to these games is a policy, which indicates the optimal actions to take for a given belief about the current state of the system. We demonstrate this approach using several different network configurations and types of player. We consider a trade-off for the system administrator, where they must allocate their time to performing either security-related tasks or performing other required non-security tasks. The results presented highlight that, with the requirement for other tasks to be performed, following the optimal policy means spending time on only the most essential security-related tasks, while the majority of time is spent on non-security tasks.

['Tristan Caulfield', 'Andrew Fielder']

Optimizing time allocation for network defence

Wireless systems often need to optimize multiple conflicting objectives (low delay, high reliability, and low cost), which are difficult to fulfill simultaneously. In such cases, the wireless system exhibits multiple optimal operation points, referred to as the optimal Pareto front (OPF). However, due to the large number of parameter settings to be evaluated and the time-consuming nature of performing wireless experiments, it is typically not possible to identify the OPF by exhaustively evaluating all possible settings. Instead, for many use cases, an approximation is good enough. To this end, this paper applies a multi-objective surrogate-based optimization (MOSBO) toolbox to efficiently optimize wireless systems and approximate the OPF using a limited number of iterations. Moreover, a real Wi-Fi conferencing scenario is optimized that has two conflicting objectives (exposure and audio quality) and four configurable parameters (Tx-Power, Tx-Rate, Codec Bit-Rate, and Codec Frame-Length). The benefits of using the MOSBO approach for such a network problem is demonstrated by approximating the OPF using 94 iterations instead of requiring the exploration of 6528 different parameter combinations, while still dominating 96.58% of the complete design space.

['Michael Tetemke Mehari', 'Eli De Poorter', 'Ivo Couckuyt', 'Dirk Deschrijver', 'Günter Vermeeren', 'David Plets', 'Wout Joseph', 'Luc Martens', 'Tom Dhaene', 'Ingrid Moerman']

Efficient Identification of a Multi-Objective Pareto Front on a Wireless Experimentation Facility

In the age of ubiquitous computing increasing amounts of personal data are being logged and shared, making privacy management a challenging task that must be integrated into our daily lives. In this paper, we explore the metaphors of 'privacy itch' for warnings and 'privacy scratch' for control of privacy preferences through real time, on-body, haptic interaction technologies. To assess the utility of these concepts, we implemented a forearm wearable prototype: the Privacy Band, and conducted a small lab-based user study.

['Vikram Mehta', 'Arosha K. Bandara', 'Blaine A. Price', 'Bashar Nuseibeh']

Privacy Itch and Scratch: On Body Privacy Warnings and Controls

Unlike the time-division duplexing (TDD) systems, the downlink (DL) and uplink (UL) channels are not reciprocal anymore in the case of frequency-division duplexing (FDD). However, some long-term parameters, e.g. the time delays and angles of arrival (AoAs) of the channel paths, still enjoy reciprocity. In this paper, by efficiently exploiting the aforementioned limited reciprocity, we address the DL channel state information (CSI) feedback in a practical wideband massive multiple-input multiple-output (MIMO) system operating in the FDD mode. With orthogonal frequency-division multiplexing (OFDM) waveform and assuming frequency-selective fading channels, we propose a scalable framework for the DL pilots design, DL CSI acquisition, and the corresponding CSI feedback in the UL. In particular, the base station (BS) can transmit the FFT-based pilots with the carefully-selected phase shifts. Then the user can rely on the so-called time-domain aggregate channel (TAC) to derive the feedback of reduced imensionality according to either its own knowledge about the statistics of the DL channels or the instruction from the serving BS. We demonstrate that each user can just feed back one scalar number per DL channel path for the BS to recover the DL CSIs. Comprehensive numerical results further corroborate our designs.

['Xiliang Luo', 'Penghao Cai', 'Xiaoyu Zhang', 'Die Hu', 'Cong Shen']

A Scalable Framework for CSI Feedback in FDD Massive MIMO via DL Path Aligning

In cellular orthogonal frequency division multiplexing (OFDM) networks, co-channel interference (CCI) leads to severe degradation in the BER performance. To solve this problem, maximum-likelihood estimation (MLE) CCI cancellation scheme has been proposed in the literature. MLE CCI cancellation scheme generates weighted replicas of the transmitted signals and selects replica with the smallest Euclidean distance from the received signal. When the received power of the desired and interference signals are nearly the same, the BER performance is degraded. In this paper, we propose an improved MLE CCI canceler with closed-loop Power Control (PC) scheme capable of detecting and combating against the equal received power situation at the mobile station (MS) receiver by using the newly introduced parameter power ratio (PR). At cell edge where signal to interferer ratio (SIR) is considered to have average value between -5 and 10 dB, computer simulations show that the proposed closed-loop PC scheme has a gain of 7 dB at 28 km/h and about 2 dB at 120 km/h.

['Manar Mohaisen', 'KyungHi Chang']

Maximum-Likelihood Co-Channel Interference cancellation with power control for cellular OFDM networks

Atomic Stretch is a plugin for your preferred Adobe video editing tool, allowing real-time smooth and optimally bounded retargetting from and to any aspect ratio. The plugin allows preserving of high interest pixels through a protected region, attention redirection through color-modification, countering barrelling effects through vertical stretching, and tracking of targets of interest.

['Rasmus Ramsbøl Jensen', 'Jannik Boll Nielsen']

Atomic stretch: optimally bounded real-time stretching and beyond

Network Function Virtualization (NFV) is set to disrupt the current networking ecosystem by turning vertically-integrated middleboxes into software modules running on general purpose virtualized platforms. NFV will play a key role in future wireless and mobile networks where significant cost reductions can be obtained by virtualizing different layers and functions of the radio access and core network. Such goal raises several challenges in terms of both functional decomposition of the radio nodes and for the management and orchestration of the resulting network. In this work we present Scylla a high-level declarative language for programming network functions that allows programmers to implement per-flow custom packet processing. We also introduce a set of programming abstractions modeling the fundamental aspects of VNF orchestration. Finally, we present a proof-of-concept Controller and an SDK implementing the proposed abstractions.

['Roberto Riggio', 'Imen Grida Ben Yahia', 'Steven Latre', 'Tinku Rasheed']

Scylla: A language for virtual network functions orchestration in enterprise WLANs

This paper proposes a new on-chip 3.3V-to-1.8V voltage down converter, which employs a new reference voltage generator (RVG) and a PMOS pass device with forward-biased source-to-bulk circuit. By the use of the forward-biased source-to-bulk technique, the circuit achieves approximately an 18% output current improvement over its nonforward-biased state. The proposed VDC has characteristic such as output voltage (V out ) is stabilized within ±6mV over a large load current range (0-100mA) and within ±0.16% for ±10% variation of supply voltage. The temperature dependency of Vout is only 0.53mV/0 C with temperature ranging from 0 to 100 0 C.

['Qianneng Zhou', 'Fengchang Lai', 'Mingyan Yu']

On-chip 3.3V-to-1.8V voltage down converter for low-power VLSI chips

Active bearing force reduction in non-commutated linear actuators

['Florian Poltschak']

Active bearing force reduction in non-commutated linear actuators

Web applications have witnessed a significant improvement that exhibit advanced user interface behaviors and functionalities. Along with this evolution, Rich Internet Applications (RIAs) were proposed as a response to these necessities and have combined the richness and interactivity of desktop interfaces into the web distribution model. However, RIAs are complex applications and their development requires designing and implementation which are time-consuming and the available tools are specialized in manual design. In this paper, we present a new model driven approach in which we used well known Model-Driven Engineering (MDE) frameworks and technologies, such as Eclipse Modeling Framework (EMF), Graphical Modeling Framework (GMF), Query View Transformation (QVTo) and Acceleo to enable the design and the code automatic generation of the RIA. The method focus on simplifying the task for the designer and not necessary be aware of the implementation specification.

['Sarra Roubi', 'Mohammed Erramdani', 'Samir Mbarki']

A Model Driven Approach for generating Graphical User Interface for MVC Rich Internet Application

This paper presents an analysis of usability of mobile prescription reference systems in medical practice, and presents implementation of mobilePDR (Physician's Desk Reference). Various aspects of mobilePDR are discussed: main functions, information content, performance and design issues, independent evaluation with other similar tools, and lessons learned from the system development.

['Miroslav Bojovic', 'Dragan Bojic']

mobilePDR : a mobile medical information system featuring update via Internet

Young adults with severe disabilities and learning difficulties (SLD) have very limited access to appropriate learning resources. Their unique individual needs and requirements prevent them from accessing traditional methods of online learning, and resources tend not to be age appropriate. The majority of SLD learners has difficulty accessing a computer with standard peripherals such as a mouse and relies on assistive technologies (e.g. switches) to do so. Each learner tends to have specific needs that must be addressed in order to provide an accessible and adaptive platform for learning. The aim of this research project was, with the assistance and support of the learners and their tutors, to design and develop an adaptable and inclusive online learning environment specifically catering for the needs of young adults with SLD. Each stage of development was prototyped and assessed in the college environment to ensure the needs of the learners were thoroughly addressed.

['Matthew Harrison', 'Claire Stockton', 'Elaine Pearson']

Inclusive, Adaptive Design for Students with Learning Disabilities

Based on the earlier notions of linear complexity, k-error linear linear complexity, k-error linear complexity profile and minerror, the concept of m-tight error linear complexity is presented to study the linear complexity stability of sequences. The m-tight error linear complexity of sequence S is defined as a two tuple km, LCm, which is the mth jump point of the k-error linear complexity profile of sequence S. Based on the Wang-Zhang-Xiao algorithm, an efficient algorithm for computing m-tight error linear complexity of binary sequences with period pn is given, where p is a prime and 2 is a primitive root modulo p2.

['Jianqin Zhou', 'Cheng Shangguan', 'Zemao Zhao']

Computing the m-Tight Error Linear Complexity of Periodic Binary Sequences

In this paper, robust design and tuning of power system stabilizers is considered. A new approach is presented that utilizes recently developed techniques based on linear matrix inequalities (LMIs) for mixed H/sub 2//H/sub /spl infin//-design under pole region constraints. Uncertainty about plant parameters - due to variations in generation and load patterns - is expressed in the form of a linear fractional transformation, and a systematic procedure for constructing the uncertainty representation is proposed. The design is easily carried out by solving a standard LMI problem. Simulation results on a single machine infinite bus model illustrate the method, and the results are compared with a recently proposed approach to the same problem based on quantitative feedback theory (QFT).

['Herbert Werner', 'Petr Korba', 'Tai Chen Yang']

Robust tuning of power system stabilizers using LMI-techniques

This paper focuses on the near real-time implementation of end-to-end 3DTV System. It is specially designed for the generation of high-quality disparity map and depth-image-based rendering (DIBR) on the graphics processing unit (GPU) through CUDA (Compute Unified Device Architecture) API. We propose our novel methods including a kind of stereo matching with adaptive windows and an asymmetric edge adaptive filter (AEAF) for industrial application. These algorithms are structured in a way that exposes as much data parallelism as possible and the power of shared memory and data parallel programming in GPU is exploited. We evaluate our proposed methods and implementation based on the benchmark Middlebury and the experiment results show that our method is suitable for application on the trade-off among accuracy and execution speed. Running on an NVIDIA Quadro FX4800 graphics card, for each 480x375 stereo images with 60 disparity levels, the proposed system reaches about 146ms for stereo matching and reaches the speed of DIBR 5.7ms for rendering 1 view or 14ms for rendering 8 views.

['Lianghao Wang', 'Jing Zhang', 'Shao-Jun Yao', 'Dongxiao Li', 'Ming Zhang']

GPU Based Implementation of 3DTV System

Towards Data And Goal Oriented Analysis: Tool Inter-Operability And Combinatorial Comparison

['Yoshinobu Kano', 'Ngan L. T. Nguyen', 'Rune Sætre', 'Kazuhiro Yoshida', 'Keiichiro Fukamachi', 'Yusuke Miyao', 'Yoshimasa Tsuruoka', 'Sophia Ananiadou', "Jun'ichi Tsujii"]

Towards Data And Goal Oriented Analysis: Tool Inter-Operability And Combinatorial Comparison

Display Omitted We employ machine learning to improve text mining of cancer pathology reports.Machine learning can detect structure in free-text surgical pathology reports.ML algorithms can locate fragments containing cancer staging information.These algorithms are sensitive to the degree of structure in the documents. Background and aimsMachine learning techniques for the text mining of cancer-related clinical documents have not been sufficiently explored. Here some techniques are presented for the pre-processing of free-text breast cancer pathology reports, with the aim of facilitating the extraction of information relevant to cancer staging. Materials and methodsThe first technique was implemented using the freely available software RapidMiner to classify the reports according to their general layout: 'semi-structured' and 'unstructured'. The second technique was developed using the open source language engineering framework GATE and aimed at the prediction of chunks of the report text containing information pertaining to the cancer morphology, the tumour size, its hormone receptor status and the number of positive nodes. The classifiers were trained and tested respectively on sets of 635 and 163 manually classified or annotated reports, from the Northern Ireland Cancer Registry. ResultsThe best result of 99.4% accuracy - which included only one semi-structured report predicted as unstructured - was produced by the layout classifier with the k nearest algorithm, using the binary term occurrence word vector type with stopword filter and pruning. For chunk recognition, the best results were found using the PAUM algorithm with the same parameters for all cases, except for the prediction of chunks containing cancer morphology. For semi-structured reports the performance ranged from 0.97 to 0.94 and from 0.92 to 0.83 in precision and recall, while for unstructured reports performance ranged from 0.91 to 0.64 and from 0.68 to 0.41 in precision and recall. Poor results were found when the classifier was trained on semi-structured reports but tested on unstructured. ConclusionsThese results show that it is possible and beneficial to predict the layout of reports and that the accuracy of prediction of which segments of a report may contain certain information is sensitive to the report layout and the type of information sought.

['Giulio Napolitano', 'Adele Marshall', 'Peter Hamilton', 'Anna Gavin']

Machine learning classification of surgical pathology reports and chunk recognition for information extraction noise reduction

The basic process of Hierarchical Agglomerative (HAG) clustering is described as a merging of clusters based on their proximity. The importance of the selected cluster distance measure in the determination of resulting clusters is pointed out. We note a fundamental distinction between the nearest neighbor cluster distance measure, Min, and the furthest neighbor measure, Max. The first favors the merging of large clusters while the later favors the merging of smaller clusters. We introduce a number of families of intercluster distance measures each of which can be parameterized along a scale characterizing their preference for merging larger or smaller clusters. We then consider the use of this distinction between distance measures as a way of controlling the hierarchical clustering process. Combining this with the ability of fuzzy systems modeling to formalize linguistic specifications, we see the emergence of a tool to add human like intelligence to the clustering process.

['Ronald R. Yager']

Intelligent control of the hierarchical agglomerative clustering process

We prove that any optimal tree resolution proof of PHP/sub n//sup m/ is of size 2/sup /spl theta/(n log n)/, independently from m, even if it is infinity. So far, only a 2/sup /spl Omega/(n)/ lower bound has been known in the general case. We also show that any, not necessarily optimal, regular tree resolution proof PHP/sub n//sup m/ is bounded by 2/sup O(n log m)/. To the best of our knowledge, this is the first time the worst case proof complexity has been considered. Finally, we discuss possible connections of our result to Riis' (1999) complexity gap theorem for tree resolution.

['Stefan S. Dantchev', 'Søren Riis']

Tree resolution proofs of the weak pigeon-hole principle

This paper presents a new fault injection approach, which is based on a co-operation between a simulator and an emulator. This hybrid approach utilizes the advantages of both simulation-based fault injection as well as physical fault injection to provide a good controllability, observability and also a high speed in the fault injection experiments. To do this, parts of a circuit are simulated while the rest parts of the circuit are emulated. A fault injection tool called FITSEC (Fault Injection Tool based on Simulation and Emulation Cooperation) is developed, which supports the entire process of a system design. This is based on both Verilog and VHDL languages and can be used to inject faults at different levels of abstraction. The experimental results show that this approach can significantly reduce the time needed for executing fault injection campaigns.

['Alireza Ejlali', 'Seyed Ghassem Miremadi', 'Hamid-Reza Zarandi', 'Ghazanfar Asadi', 'Siavash Bayat Sarmadi']

A hybrid fault injection approach based on simulation and emulation co-operation

Empirical search is a strategy used during the installation of library generators such as ATLAS, FFTW, and SPIRAL to identify the algorithm or the version of an algorithm that delivers the best performance. In the past, empirical search has been applied almost exclusively to scientific problems. In this paper, we discuss the application of empirical search to sorting, which is one of the best understood symbolic computing problems. When contrasted with the dense numerical computations of ATLAS, FFTW, and SPIRAL, sorting presents a new challenge, namely that the relative performance of the algorithms depend not only on the characteristics of the target machine and the size of the input data but also on the distribution of values in the input data set. Empirical search is applied in the study reported here as part of a sorting library generator. The resulting routines dynamically adapt to the characteristics of the input data by selecting the best sorting algorithm from a small set of alternatives. To generate the run time selection mechanism our generator makes use of machine learning to predict the best algorithm as a function of the characteristics of the input data set and the performance of the different algorithms on the target machine. This prediction is based on the data obtained through empirical search at installation time. Our results show that our approach is quite effective. When sorting data inputs of 12M keys with various standard deviations, our adaptive approach selected the best algorithm for all the input data sets and all platforms that we tried in our experiments. The wrong decision could have introduced a performance degradation of up to 133%, with an average value of 44%.

['Xiaoming Li', 'María Jesús Garzarán', 'David A. Padua']

A dynamically tuned sorting library

Since subtitling television content is a costly process, there are large potential advantages to automating it, using automatic speech recognition (ASR). However, training the necessary acoustic models can be a challenge, since the available training data usually lacks verbatim orthographic transcriptions. If there are approximate transcriptions, this problem can be overcome using light supervision methods. In this paper, we perform speech recognition on broadcasts of Weatherview, BBC's daily weather report, as a first step towards automatic subtitling. For training, we use a large set of past broadcasts, using their manually created subtitles as approximate transcriptions. We discuss and and compare two different light supervision methods, applying them to this data. The best training set finally obtained with these methods is used to create a hybrid deep neural network-based recognition system, which yields high recognition accuracies on three separate Weatherview evaluation sets.

['Joris Driesen', 'Steve Renals']

Lightly supervised automatic subtitling of weather forecasts

This paper investigates the problem of adaptive neural tracking control via output-feedback for a class of switched uncertain nonlinear systems without the measurements of the system states. The unknown control signals are approximated directly by neural networks. A novel adaptive neural control technique for the problem studied is set up by exploiting the average dwell time method and backstepping. A switched filter and different update laws are designed to reduce the conservativeness caused by adoption of a common observer and a common update law for all subsystems. The proposed controllers of subsystems guarantee that all closed-loop signals remain bounded under a class of switching signals with average dwell time, while the output tracking error converges to a small neighborhood of the origin. As an application of the proposed design method, adaptive output feedback neural tracking controllers for a mass-spring-damper system are constructed.

['Lijun Long', 'Jun Zhao']

Adaptive Output-Feedback Neural Control of Switched Uncertain Nonlinear Systems With Average Dwell Time

To facilitate computational study of proteins in the AlkB family and related -ketoglutarate/Fe(II)-dependent dioxygenases, we have tested a simple modeling strategy for the non-heme Fe(II) site in which the iron is represented by a simple +2 point charge with Lennard-Jones parameters. Calculations for an AlkB active site model in the gas phase and approximate to 150 ns molecular dynamics (MD) simulations for two enzyme-dsDNA complexes (E. coli AlkB-dsDNA and ABH2-dsDNA) suggest that this simple modeling strategy provides a satisfactory description of structural properties of the Fe(II) site in AlkB enzymes, provided that care is exercised to control the binding mode of carboxylate (Asp) to the iron. MD simulations using the model for AlkB-dsDNA and ABH2-dsDNA systems find that although the structural features for the latter are overall in good agreement with the crystal structure, the dsDNA, and AlkB-dsDNA interface undergo substantial changes during the MD simulations from the crystal structure. Even for ABH2, new interactions form between a long loop region and dsDNA upon structural relaxation of the loop, supporting the role of this loop in DNA binding despite the lack of interactions between them in the crystal structure. Analysis of DNA backbone torsional distributions helps identify regions that adopt strained conformations. Collectively, the results highlight that crystal packing may have a significant impact on the structure of protein-DNA complexes; the simulations also provide additional insights regarding why AlkB and ABH2 prefer single-strand and double-strand DNA, respectively, as substrate. (c) 2013 Wiley Periodicals, Inc.

['Xueqin Pang', 'Ke-Li Han', 'Qiang Cui']

A simple but effective modeling strategy for structural properties of non-heme Fe(II) sites in proteins: Test of force field models and application to proteins in the AlkB family

The Hidden Web is the vast repository of informational databases available only through search form interfaces, accessible by therein typing a set of keywords in the search forms. Typically, a Hidden Web crawler is employed to autonomously discover and download pages from the Hidden Web. Traditional hidden web crawlers do not provide the search engines with an optimal search experience because of the excessive number of search requests posed through the form interface so as to exhaustively crawl and retrieve the contents of the target hidden web database. Here in our work, we provide a framework to investigate the problem of optimal search and curtail it by proposing an effective query term selection approach based on the frequency & distribution of terms in the document database. The paper focuses on developing a term-weighing scheme called VarDF (acronym for variable document frequency) that can ease the identification of optimal terms to be used as queries on the interface for maximizing the achieved coverage of the crawler which in turn will facilitate the search engine to have a diversified and expanded index. We experimentally evaluate the effectiveness of our approach on a manually created database of documents in the area of Information Retrieval.

['Sonali Gupta', 'Komal Kumar Bhatia']

A NOVEL TERM WEIGHING SCHEME TOWARDS EFFICIENT CRAWL OF TEXTUAL DATABASES

Daniel D. Hutto and Erik Myin: Radicalizing Enactivism: Basic Minds without Content: MIT Press

['Paulo De Jesus']

Daniel D. Hutto and Erik Myin: Radicalizing Enactivism: Basic Minds without Content: MIT Press

Abstract#R##N##R##N#The nature of the tetrahedral H42+ stationary point (minimum or triply degenerate saddle) depends remarkably upon the theoretical level employed. Harmonic vibrational analyses with, e.g., the 6-31G** (and 6-31 + +G**) and Dunning's [4s2p1d;2s1p] [D95(d,p)] basis sets using the standard p exponent suggest (erroneously) that the Td geometry is a minimum at both the HF and MP2 levels. This is not the case at definitive higher levels. The C3H42+ structure with an apical H is another example of the failure of the calculations with the 6-31G**, 6-311G**, and D95(d,p) basis sets. Even at MP2/6-31G** and MP2/ cc-pVDZ levels, the C3v structure has no negative eigenvalues of the Hessian. Actually, this form is a second-order saddle point as shown by the MP2/6-31G** calculation with the optimized exponent. The D4h methane dication structure is also an example of the misleading performance of the 6-31G** basis set. In all these cases, energy-optimized hydrogen p exponents give the correct results, i.e., those found with more extended treatments. Optimized values of the hydrogen polarization function exponents eliminate these defects in 6-31G** calculations. Species with higher coordinate hydrogens may also be calculated reliably by using more than one set of p functions on hydrogen [e.g., the 6-31G(d,2p) basis set]. Not all cases are critical. A survey of examples, also including some boron compounds, provides calibration. © 1993 John Wiley & Sons, Inc.

['Mikhail N. Glukhovtsev', 'Paul von Ragué Schleyer', 'Nicolaas J. R. van Eikema Hommes', 'Jose Walkimar de M. Carneiro', 'Wolfram Koch']

Is tetrahedral H 4 2+ a minimum?: anomalous behavior of popular basis sets with the standard p exponents on hydrogen

We study the connectivity and capacity of finite area ad hoc wireless networks, with an increasing number of nodes (dense networks). We find that the properties of the network strongly depend on the shape of the attenuation function. For power law attenuation functions, connectivity scales, and the available rate per node is known to decrease like 1//spl radic/n. On the contrary, if the attenuation function does not have a singularity at the origin and is uniformly bounded, we obtain bounds on the percolation domain for large node densities, which show that either the network becomes disconnected, or the available rate per node decreases like 1/n.

['Olivier Dousse', 'Patrick Thiran']

Connectivity vs capacity in dense ad hoc networks

Programmers often create similar code snippets or reuse existing code snippets by copying and pasting. Code clones---syntactically and semantically similar code snippets---can cause problems during software maintenance because programmers may need to locate code clones and change them consistently. In this work, we investigate (1) how code clones evolve, (2) how many code clones impose maintenance challenges, and (3) what kind of tool or engineering process would be useful for maintaining code clones.Based on a formal definition of clone evolution, we built a clone genealogy tool that automatically extracts the history of code clones from a source code repository (CVS). Our clone genealogy tool enables several analyses that reveal evolutionary characteristics of code clones. Our initial results suggest that aggressive refactoring may not be the best solution for all code clones; thus, we propose alternative tool solutions that assist in maintaining code clones using clone genealogy information.

['Miryung Kim', 'David Notkin']

Using a clone genealogy extractor for understanding and supporting evolution of code clones

Bag of MFCC-based Words for Bird Identification.

['Julien Ricard', 'Hervé Glotin']

Bag of MFCC-based Words for Bird Identification.

In this paper, we consider a non-convex loss-minimization problem of learning Supervised PageRank models, which can account for features of nodes and edges. We propose gradient-based and random gradient-free methods to solve this problem. Our algorithms are based on the concept of an inexact oracle and unlike the state-of-the-art gradient-based method we manage to provide theoretically the convergence rate guarantees for both of them. Finally, we compare the performance of the proposed optimization methods with the state of the art applied to a ranking task.

['Lev Bogolubsky', 'Pavel Dvurechensky', 'Alexander Gasnikov', 'Gleb Gusev', 'Yurii Nesterov', 'Andrei M. Raigorodskii', 'Aleksey M. Tikhonov', "Maksim Evgen'evich Zhukovskii"]

Learning Supervised PageRank with Gradient-Based and Gradient-Free Optimization Methods

Frequency synthesizer is a key component used in electronic systems. Two important features for judging its performance are frequency granularity and frequency switching speed. In this paper, a synthesizer built on the principle of time-average-frequency (TAF) is implemented on an FPGA system. The synthesizer is constructed entirely on the FPGA's configurable elements. The granularity is measured as 2 ppb; the frequency switching speed is experimentally illustrated as two cycles. The configuration of the synthesizer can be adjusted in the field for accommodating various performance versus cost scenarios. The aim of this paper is to provide a field-programmable frequency generator as a handy tool to FPGA users, to enable user create innovations at application level. The key contributions are the 2 ppb frequency granularity and the reconfigurable implementation of the time-average-frequency direct period synthesis (TAF-DPS) synthesizer on FPGA.

['Liming Xiu', 'Pao-Lung Chen']

A Reconfigurable TAF-DPS Frequency Synthesizer on FPGA Achieving 2 ppb Frequency Granularity and Two-Cycle Switching Speed

In general, imitation is imprecisely used to address dierent levels of social learning from high level knowledge transfer to low level regeneration of motor commands. However, true imitation is based on abstraction and conceptualization. This paper presents a con- ceptual approach for imitation learning using feedback cues and interactive training to abstract spatio-temporal demonstrations based on their perceptual and functional char- acteristics. Abstraction, concept acquisition, and self-organization of proto-symbols are performed through an incremental and gradual learning algorithm. In this algorithm, Hid- den Markov Models (HMMs) are used to abstract perceptually similar demonstrations. However, abstract (relational) concepts emerge as a collection of HMMs irregularly scat- tered in the perceptual space. Performance of the proposed algorithm is evaluated in a human-robot interaction task of imitating signs produced by hand movements. Exper- imental results show eciency of our model for concept extraction, symbol emergence, motion pattern recognition, and regeneration.

['Hossein Hajimirsadeghi', 'Majid Nili Ahmadabadi', 'Mostafa Ajallooeian', 'Babak Nadjar Araabi', 'Hadi Moradi']

Conceptual Imitation Learning: An Application to Human-Robot Interaction

Synergistic developments across the video game industry pave the way for gaming anytime, anywhere.

['Michael R. Macedonia']

E3 2001: the birth of ubiquitous gaming?

The CreZOO (http://www.crezoo.org/) is the European virtual repository of Cre and other targeted conditional driver strains. These mice serve as tools for researchers to selectively ‘switch off’ gene expression in mouse models to examine gene function and disease pathology. CreZOO aims to capture and disseminate extant and new information on these Cre driver strains, such as genetic background and availability information, and details pertaining promoter, allele, inducibility and expression patterns, which are also presented. All transgenic strains carry detailed information according to MGI's official nomenclature, whereas their availability [e.g. live mice, cryopreserved embryos, sperm and embryonic stem (ES) cells] is clearly indicated with links to European and International databases and repositories (EMMA, MGI/IMSR, MMRRC, etc) and laboratories where the particular mouse strain is available together with the respective IDs. Each promoter/gene includes IDs and direct links to MGI, Entrez Gene, Ensembl, OMIM and RGD databases depending on their species origin, whereas allele information is presented with MGI IDs and active hyperlinks to redirect the user to the respective page in a new tab. The tissue/cell (special) and developmental (temporal) specificity expression patterns are clearly presented, whereas handling and genotyping details (in the form of documents or hyperlinks) together with all relevant publications are clearly presented with PMID(s) and direct PubMed links. CreZOO's design offers a user-friendly query interface and provides instant access to the list of conditional driver strains, promoters and inducibility details. Database access is free of charge and there are no registration requirements for data querying. CreZOO is being developed in the context of the CREATE consortium (http://www.creline.org/), a core of major European and international mouse database holders and research groups involved in conditional mutagenesis. #R##N##R##N#Database URL: http://www.crezoo.org/; alternative URL: http://www.e-mouse.org/

['Christina Chandras', 'Michael Zouberakis', 'Ekaterina Salimova', 'Damian Smedley', 'Nadia Rosenthal', 'Vassilis Aidinis']

CreZOO—the European virtual repository of Cre and other targeted conditional driver strains

Conceiving a Multiscale Dataspace for Data Analysis.

['Matheus Silva Mota', 'André Santanchè']

Conceiving a Multiscale Dataspace for Data Analysis.

Data mining is a technique to search potential valuable information from databases. Preventing personal data and high security data therefore pose a difficult task to IT experts. In this paper, we propose a novel anti-data mining (ADM) database security scheme, that protect against data mining. The scheme makes use of hierarchical clustering where noise is added to change the cluster structure of data. The proposed hierarchical anti-clustering (HAC) scheme modifies the cluster structure of the original data. Experimented results show that data may be protected against during the HAC key can be used reverse the cluster structure to its original. At the meantime, HAC also designs the key value to restore correctly the protected database.

['Tung-Shou Chen', 'Jeanne Chen', 'Yuan-Hung Kao', 'Tsang-Chou Hsieh']

A Novel Anti-data Mining Technique Based On Hierarchical Anti-clustering (HAC)

The formal specification of design patterns is widely recognised as being vital to their effective and correct use in software development. It can clarify the concepts underlying patterns, eliminate ambiguity and thereby lay a solid foundation for tool support. This paper further advances an approach that uses first order predicate logic to specify design patterns by capturing the dynamic behaviour represented in sequence diagrams. A case study of all 23 patterns in the Gang of Four catalogue demonstrates that it can not only capture dynamic features but also simplify the specification of structural properties.

['Ian Bayley', 'Hong Zhu']

Specifying Behavioural Features of Design Patterns in First Order Logic

Lexical Semantic Constraints on the Syntactic Realization of Semantic Role Theme

['Shiyong Kang', 'Minghai Zhou', 'Xiaorui Zhao']

Lexical Semantic Constraints on the Syntactic Realization of Semantic Role Theme

In this paper, a novel probabilistic Bayesian tracking scheme is proposed and applied to bimodal measurements consisting of tracking results from the depth sensor and audio recordings collected using binaural microphones. We use random finite sets to cope with varying number of tracking targets. A measurement-driven birth process is integrated to quickly localize any emerging person. A new bimodal fusion method that prioritizes the most confident modality is employed. The approach was tested on real room recordings and experimental results show that the proposed combination of audio and depth outperforms individual modalities, particularly when there are multiple people talking simultaneously and when occlusions are frequent.

['Qingju Liu', 'Teófilo Emídio de Campos', 'Wenwu Wang', 'Philip J. B. Jackson', 'Adrian Hilton']

Person Tracking Using Audio and Depth Cues