16895768
A Novel Stroke Extraction Model for Chinese Characters based on Steerable Filters
The technology of stroke extraction plays a key role in the off-line Chinese character recognition field. The accuracy and computing complexity of classifying depend on the output of stroke extraction. Based on the analysis of the existing methods, this paper proposed a novel stroke extraction model with steerable filters. The experiments indicate that this model can be used to extract strokes from both printed and handwritten Chinese characters. Meanwhile, it also can be applied to eliminate the redundant stroke connections impressively with considerable low computing complexity
1301888
Auction-Based Resource Reservation Game in Small World
For read-only storages and in particular for PLA applications, improved coupling elements together with an associated personalization scheme permit the storing of at least two memory (or logic) connection patterns selectable independently of each other. Quick electrical switching between at least two functional modes in the same storage array, is also provided. One device field effect transistor (FET) cells with specific gate configurations depending on the respective personalization state are used as coupling elements. For instance, in a two-fold personalization permanent storage, the coupling elements consist of FETs with two gate sections provided one beside the other. For a connection to be established in only one of the two possible functions at the respective crosspoint, one of the gate sections is connected to the control line provided for the functional selection. The remaining gate section is connected to the associated input line. A connection in the other functional mode is provided correspondingly with only the control lines being switched. If at the respective crosspoint a connection is to be effective in both functional modes, both gate sections are jointly connected to the respective input line. By using only one common peripheral circuit, PLAs with multiple personalization properties can be made in integrated technology, with the same semiconductor area requirement as PLAs personalizable into only one functional mode.
14166643
3D Model Simplification Method Based on ROI
Based on edge-collapse algorithm and ROI (region of interest), an effective 3D mesh simplification method is proposed. During the simplification procedure, this method could successfully preserve a high resolution for the 3D part that the user is interested in while the rest parts could meet the basic requirement with lower resolution. The experiments support the conclusion.
12737531
Accelerating the 2D Mallat decomposition algorithm with cyclical convolution and FNTT
This paper presents a novel approach to accelerate the 2D Mallat decomposition algorithm. In particular the proposed approach performs the 2D Mallat decomposition algorithm by way of computing the 2D cyclical convolution, and further completes the 2D cyclical convolution with the fast number theoretical transform (FNTT). Therefore, the 2D Mallat decomposition algorithm can be speeded up. The results obtained from the theoretical analysis and the experiment show that the 2D Mallat decomposition algorithm is significantly improved.
701274
Towards a Pattern-Driven Topical Ontology Modeling Methodology in Elderly Care Homes
This paper presents a pattern-driven ontology modeling methodology, which is used to create topical ontologies in the human resource management (HRM) domain. An ontology topic is used to group concepts from different contexts (or even from different domain ontologies). We use the Organization for Economic Co-operation and Development (OECD) and the National Vocational Qualification (NVQ) as the resource to create the topical ontologies in this paper. The methodology is implemented in a tool called PAD-ON suit. The paper approach is illustrated with a use case from elderly care homes in UK.
44335940
DRC-BK: Mining Classification Rules with Help of SVM
Currently, the accuracy of SVM classifier is very high, but the classification model of SVM classifier is not understandable by human experts. In this paper, we use SVM, which is applied with a Boolean kernel, to construct a hyper-plan for classification, and mine classification rules from this hyper-plane. In this way, we build DRC-BK, a decision rule classifier. Experiment results show that DRC-BK has a higher accuracy than some state-of-art decision rule (decision tree) classifiers, such as C4.5, CBA, CMAR, CAEP and so on.
17436215
Organizing Meaning Evolution Supporting Systems Using Semantic Decision Tables
DOGMA-MESS (Meaning Evolution Support System) is a system and methodology for supporting scalable, community-grounded ontology engineering. It uses a socio-technical process of meaning negotiation to tackle the scalability problems in ontology engineering. In order to improve the effectiveness of DOGMA-MESS, we adopt the idea of Semantic Decision Table (SDT). An SDT contains semantically rich decision rules that guide DOGMA-MESS micro-processes. It separates the decision rules from DOGMA-MESS. SDT with different decision rules results in different final decisions, which can be evaluated. In this paper, we illustrate how SDTs are used and apply our approach in the domain of Human Resource Management.
22140835
The Algorithm of R Peak Detection in ECG Based on Empirical Mode Decomposition
A novel automatic R peak detection algorithm that is based on EMD (empirical mode decomposition) and adaptive threshold technique is presented. The R peaks are then identified by computing the first threshold and applying a set of adaptive thresholds that are not limited to a strict range. The proposed algorithm was able to detect R peak with high sensitivity when compared to other algorithms used in Physionet ECG database. Additionally, the new algorithm can successfully detect R peak for a wide variety of ECG shapes.