semantic oriented ontology cohesion metrics for ontology-based systems

Ontologies play a core role to provide shared knowledge models to semantic-driven applications targeted by Semantic Web. Ontology metrics become an important area because they can help ontology engineers to assess ontology and better control project management and development of ontology based systems, and therefore reduce the risk of project failures. In this paper, we propose a set of ontology cohesion metrics which focuses on measuring (possibly inconsistent) ontologies in the context of dynamic and changing Web. They are: Number of Ontology Partitions (NOP), Number of Minimally Inconsistent Subsets (NMIS) and Average Value of Axiom Inconsistencies (AVAI). These ontology metrics are used to measure ontological semantics rather than ontological structure. They are theoretically validated for ensuring their theoretical soundness, and further empirically validated by a standard test set of debugging ontologies. The related algorithms to compute these ontology metrics also are discussed. These metrics proposed in this paper can be used as a very useful complementarity of existing ontology cohesion metrics.

A new frequency offset estimation for OFDM-based systems

A new carrier frequency offset estimation scheme in orthogonal frequency division multiplexing (OFDM) is proposed. The scheme includes coarse frequency offset estimation and fine frequency offset estimation. The coarse frequency offset estimation method we present is a improvement of Zhang's method. The estimation range of the new method is as large as the overall signal-band width. A new fine frequency offset estimation algorithm is also discussed in this paper. The new algorithm has a better performance than the Schmidl's algorithm. The system we use to calculate and simulate is based on the high rate WLAN standard adopted by the IEEE 802.11 stanidardization group. Numerical results are presented to demonstrate the performance of the proposed algorithm.

A new frequency offset estimation for OFDM-Based systems

A-new-carrier-frequency offset estimation scheme in orthogonal frequency division multiplexing (OFDM) is proposed. The scheme includes coarse frequency offset estimation and fine frequency offset estimation. The coarse frequency offset estimation method we present is a improvement of Zhang's method. The estimation range of the new method is as large as the overall signal-band width. A new fine frequency offset estimation algorithm is also discussed in this paper. The new algorithm has a better performance than the Schmidt's algorithm. The system we use to calculate and simulate is based on the high rate WLAN standard adopted by the IEEE 802.11 standardization group. Numerical results are presented to demonstrate the performance of the proposed algorithm.

dynamic evolutions based on ontologies

With the continuous changes in application requirements of the enterprises, Web resources must be updated, so do the underlying ontologies that are associated with the Web resources. In the situation, it is very challenging for ontological engineers to specify the changes of ontologies, keep their consistencies and achieve semantic query of Web resources based on the evolving ontologies. We propose a construct called Prioritized Knowledge Base (PKB) based on SHOQ(D) description logic, and discuss some properties of PKB.PKB can be used for describing the evolutions and updates of ontologies with conflicting information. Furthermore, we develop some algorithms for checking conflict rules and performing semantic query based on PKB.

facilitating formal specification acquisition by using recursive functions on context-free languages

Although formal specification techniques are very useful in software development, the acquisition of formal specifications is a difficult task. This paper presents the formal specification language LFC, which is designed to facilitate the acquisition and validation of formal specifications. LFC uses context-free languages for syntactic aspect and relies on a new kind of recursive functions, i.e. recursive functions on context-free languages, for semantic aspect of specifications. Construction and validation of LFC specifications are machine-aided. The basic ideas behind LFC, the main aspects of LFC, and the use of LFC and illustrative examples are described.

Evaluation of a combined wavelet and a combined principal component analysis classification system for BCG diagnostic problem

Heart disease is one of the main factor causing death in the developed countries. Over several decades, variety of electronic and computer technology have been developed to assist clinical practices for cardiac performance monitoring and heart disease diagnosis. Among these methods, Ballistocardiography (BCG) has an interesting feature that no electrodes are needed to be attached to the body during the measurement. Thus, it is provides a potential application to asses the patients heart condition in the home. In this paper, a comparison is made for two neural networks based BCG signal classification models. One system uses a principal component analysis (PCA) method, and the other a discrete wavelet transform, to reduce the input dimensionality. It is indicated that the combined wavelet transform and neural network has a more reliable performance than the combined PCA and neural network system. Moreover, the wavelet transform requires no prior knowledge of the statistical distribution of data samples and the computation complexity and training time are reduced.

research on user-centered design and recognition pen gestures

Pen-based user interface has become a hot research field in recent years. Pen gesture plays an important role in Pen-based user interfaces. But it’s difficult for UI designers to design, and for users to learn and use. In this purpose, we performed a research on user-centered design and recognition pen gestures. We performed a survey of 100 pen gestures in twelve famous pen-bases systems to find problems of pen gestures currently used. And we conducted a questionnaire to evaluate the matching degree between commands and pen gestures to discover the characteristics that a good pen gestures should have. Then cognition theories were applied to analyze the advantages of those characteristics in helping improving the learnability of pen gestures. From these, we analyzed the pen gesture recognition effect and presented some improvements on features selection in recognition algorithm of pen gestures. Finally we used a couple of psychology experiments to evaluate twelve pen gestures designed based on the research. It shows those gestures is better for user to learn and use. Research results of this paper can be used for designer as a primary principle to design pen gestures in pen-based systems.

基于知识的供应链决策框架

本文提出了一种基于知识的供应链决策框架,并且从理论和实践的角度详细探讨了知识积累和知识挖掘过程,充分利用知识优势,以期通过知识与推理机制的集成和人类智慧与枯燥数据之间的无缝链接来提高供应链性能。它不仅适用于供应链整体而且也适用于供应链各侧面。它可实现独立地、自动地、实时地及时决策以缩短顾客定货周期,降低库存,提高交付准确性和资源利用水平。决策框架同样也适用于其它类似的情况。