基于本体论的电子商务知识描述语言

应用本体论对电子商务知识建模,提出电子商务知识描述的分层框架,并结合描述逻辑、框架系统设计面向电子商务的知识描述语言(KDL).介绍了KDL的语法,从一阶逻辑的角度分析KDL的语义特征,提供KDL描述到一阶逻辑表达式的映射方法.最后,通过实例证明KDL具有规范的语法、精确的语义和较强的逻辑推理能力.     

一种基于用户偏好分析的查询优化方法

该文对如何满足不同兴趣用户的查询需求进行了研究,提出了一种基于用户偏好分析的查询优化方法。该方法将用户对网页的偏好转化为对本体知识库中实例的偏好;分析本体实例之间的语义关联,发现隐含的用户偏好;综合用户偏好历史,建立用户当前状态下偏好的数学模型,以预测用户对网页的关注程度。实现了相应的原型系统,实验结果表明,相对于传统的个性化搜索技术,该文提出的方法能更有效地获取用户偏好,适应用户偏好的变化,提高搜索引擎查询的准确率。     

扩展结构包含推理算法的本体匹配

为了匹配本体时直接分析构造器和公理中所蕴含的语义信息,提出一种扩展结构包含推理算法的本体匹配方法以解决该问题。首先将本体中实体重定向为范式,使得被蕴含的语义信息明显地表示,然后比较范式之间的句法结构以推理来自不同本体的实体间的匹配。针对一组工业本体的测试结果表明该方法具有较好的性能。     

Toward agency and ontology for web-based information retrieval

This paper presents a system that selects information sources, browses websites, and monitors changes in selected websites. Its distinguishing features are 1) adopting a holistic approach for bolstering web-based information gathering using a society of agents and 2) exploiting features of ontology and lexical chain for processing user queries and filtering relevant information. By engineering web-based information gathering systems along the dimensions of agency and ontology, relations among concepts can be identified and established, and information filtering and monitoring tasks can be automated by information filtering agents (IFAs) and information monitoring agents (IMAs). IFAs and IMAs relieve users of the tasks of browsing and monitoring changes in websites and multiple web sites can be browsed and monitored in parallel by several IFAs and IMAs. By establishing ontological relations among (key)words 1) the query processing agent (QPA) selects appropriate URLs for a query and 2) IFAs search and filter information relevant to the query. Empirical results demonstrated that the QPA can find appropriate number of websites and IFAs are effective in filtering relevant information.     

生物信息学技术研究

对生物信息学的产生背景及概念进行论述,对生物信息学、计算生物学、基因组信息学等概念进行区别,重点对生物信息学的研究内容进行综述,并对研究的热点问题进行讨论,最后对发展前景提出展望.     

Ontology Management in Enterprises

In today's increasingly competitive business market, many large organisations have begun to research and develop flexible enterprises in order to be able to quickly respond to market opportunities. They are seeking ways to maximise the power of information assets stored across hundreds of their databases and application programs by bringing them into open interoperable environments. However, this effort has been seriously hindered by various kinds of heterogeneity. Each system has its own domain model for its environment and efficient task operations. However, in order for systems to communicate and co-operate effectively, a shared domain model is required. The semantics of the common, and each local, model must be captured explicitly and formally to enable meaningful information exchange.The semantics of diverse information resources are captured by ontologies — definitions of terms as used in data sources, i.e. concepts and the relationships between concepts. When defining the relationships between data sources, we rely on ontologies to make the meaning of the different vocabularies used explicit. This paper explores the role of ontologies in enterprises, and proposes a methodology for managing enterprise ontology resources and a suite of support tools.     

Web service discovery utilizing logical reasoning and semantic similarity

Web service discovery facilitates the implementation of complex and reconfigurable applications in service‐oriented architecture, such as service selection, composition, and provision. This paper presents an approach for semantic and automated Web service discovery. Our approach to semantic Web service discovery consists of ontology‐based service preprocessor, reasoning‐based service filter, and parameter‐based service matcher. An important feature of this approach is that the relationship among concepts in ontology is quantified and considered as an important factor in the matching process, which results in high precision and recall. Additionally, we propose a filtering method based on logical reasoning to preprocess the large amount of Web services. Through the filtering method, Web services which are feasible in logic are selected to be matched with user requests. So there is a great improvement in the run‐time performance of service discovery approach. Experiments show that our approach is feasible and effective to discover the required Web services.     

Tech-ware: Bioinformatics and computational biology resources [Best of the Web]

In this issue, "Best of the Web" presents online resources related to bioinformatics and computational biology. According to Wikipedia, bioinformatics is the application of information technology to the field of molecular biology. It was applied in the creation and maintenance of a database to store biological information such as nucleotide and amino acid sequences. The actual process of analyzing and interpreting data is referred to as another common term, computational biology.     

An Adaptive Scenario-Based Reasoning System Across Smart Houses

The intelligent smart home provides homeowners with various services that incorporate knowledge reasoning. However, programmers must consider such constraints as scenarios in different houses, scenarios of different users, and even different resources. That is infrastructure deployment and scenario designing are time consuming. Actually, designing a home based on the behaviors of family members is more reasonable compare with having users adapt to the functionalities of a home. Therefore, developing an efficient reasoning system for smart homes has gained considerable attention. This work presents a smart home reasoning system called the adaptive scenario-based reasoning (ASBR) system. This system learns from user preferences using adaptive history scenarios and it is a convenient method for rebuilding reasoned knowledge compare with other smart homes. Ontology based contextual information is able to be extracted from a smart home and considered as a set of scenarios. Additionally, the system derives personalized habits and store in web ontology language (OWL) files. This work then presents a novel scenario reconstruction method under computational and resource restriction. Finally, an experiment is designed for a realistic smart home and some scenarios are used to discuss the results.     

基于本体的认知无线电知识表示与推理

对知识进行有效建模是认知无线电（CR）引擎设计中关键问题之一。本文提出基于本体的认知无线电知识表示模型。首先对自然语言描述的CR知识进行概念抽取和类分析,并利用网络本体语言实现CR知识本体,最后对本体进行推理。实验结果表明,该方法支持知识的共享与重用,能够对异构的无线电知识进行融合,并实现了CR对自身状态和外界环境的理解,为参数重构提供决策依据。     

混合语义约简和选择估值优化SPARQL

本文在定义SPARQL查询优化问题基础上,利用本体中概念间的语义关系提出语义约简优化方案.并通过与选择估值策略的有机结合,给出RS-Opti优化算法及其实现.测试表明:RS-Opti优于单独使用语义约简和选择估值两种优化策略;与其它查询引擎测试对比表明:该优化方案在查询的元组模式个数较多和语义较复杂时效果明显.     

Comprehensive Electromagnetic Modeling of On-Chip Switching Noise Generation and Coupling

A comprehensive modeling methodology is presented for the investigation of on-chip noise generation and coupling due to power switching. The backbone of the methodology is an electromagnetic model for the on-chip portion of the power grid. This allows for the impact of the displacement current density and, hence, electromagnetic retardation, to be taken into account in the accurate modeling of the power grid behavior at picosecond switching speeds. In this manner, and through the interfacing of this model with an electromagnetic model for the package portion of the power grid, which is described in terms of a multiport rational matrix transfer function, the impact of package-chip electrical interactions on switching noise can be modeled with electromagnetic accuracy. The electromagnetic model for the power grid is complemented by a resistance-capacitance model for the semiconductor substrate, which is capable of modeling local substrate induced noise coupling between neighboring circuits. Finally, distributed resistance, inductance, capacitance and conductance circuits for signal wires are extracted and used to provide for a transmission line-based modeling of crosstalk and power grid induced signal degradation. Transient simulations using the proposed comprehensive model are carried out using a hybrid time-domain integration scheme which combines a SPICE-like engine for the analysis of all circuit netlists and the nonlinear drivers incorporated in the model with a numerical integration algorithm suitable for the expedient update of the state variables in the discrete electromagnetic model for the power grid.      

一种基于语义优化非单调推理的方法

文章从一个例子出发,分析非单调推理产生不一致的原因,以及语义距离的作用。介绍了怎样在推理过程中利用语义信息的规则和方法,使用概念类的本体关系计算语义相似度的方法,并用实例加以说明。     

Characterization of slice-based H.264/AVC encoded video traffic using token buckets

An explicit slice-based mode type selection scheme for use in H.264/AVC has recently been developed, which reduces the burstiness effect of standard frame-based H.264/AVC by breaking up the Group of Picture structure. In this paper, slice-based encoded video streams are characterized using the token bucket traffic model and compared to standard frame-based encoded streams. Both lossless, loss bounded and delay bounded token bucket models are investigated and the high quantiles are found for the amount of loss. Loss above the amount given by the high quantiles will happen only with a very small probability. It is shown that the reduced burstiness for the slice-based video encoding leads to lower token bucket parameters compared to frame-based video encoding for a stream without scene changes, and a larger reduction in the token bucket parameters compared to the frame-based video encoding when a small amount of delay or loss is allowed for the stream with scene changes. Next, reshuffling of the frames of the video streams with scene changes is employed to better understand the effects of long-range dependence on the token bucket parameters. Only small effects are found from reshuffling the scenes, but reshuffling of the frames inside the scenes leads to lower token bucket parameters. Finally, an approach to estimate the parameters for the token bucket model using simple characteristics of the slice-based stream is developed.     

SRAM供电结构与SOC芯片供电网络设计优化

主要提出了一种优化SRAM供电结构的方案——裸露Metal4的SRAM供电网络。该方案可以在不增加使用绕线资源的条件下,显著地提升SRAM的供电以及整个芯片供电网络的性能。以一款数字电视解调芯片BTV2020为例,详细叙述了传统SRAM的供电结构,提出一种SRAM的供电结构及实现方法,以及对比了优化后的SRAM供电结构与传统SRAM供电结构,所构建的供电网络的最差电源电压降。最后通过流片结果证明本方案是有效可行的。     

Self-Configuration and Optimization for Cognitive Networked Devices

Connected devices are an integral part of the ubiquitous and pervasive systems. They are highly dynamic and can grow into complex networks with multiple connectivity options, application requirements and user contexts. Since manual configuration and optimization are tedious for such systems, autonomic management would be beneficial. This motivates the conceptualization of cognitive networked devices that follows a cognitive approach for management. One of the major architectural components considered here is a cognitive management entity supporting self configuration and self optimization with an end-to-end perspective. Here we explore an optimizing controller which follows a cognitive process that can run in real-time efficiently on resource constrained device platforms in the absence of a mathematically tractable model. A methodology is developed based on dependency graph as an ontology modeling relative influences between state variables. Concepts from monotonic influence graphs and signed graphs have been used to formulate an approach and algorithm for a qualitative optimization. Functionality of the approach has been demonstrated with an example.     

云推理在雷达干扰效果评估中的应用

鉴于雷达干扰效果评估在干扰资源优化分配中的重要地位,一种基于云模型定性规则推理的干扰效果评估方法被提出。首先对属性云模型进行参数设置,生成了一系列用云表示的基本概念集;然后基于云不确定性关联知识挖掘方法,构建了推理规则库,使得属性间的内在关联被突显出来;最后建立了基于云不确定性推理的干扰效果评估模型。通过实例,将云推理与模糊推理和概率推理进行比较,结果表明所建模型是合理的、可行的,该方法摆脱了以往概念层次的硬划分,实现了数据的软操作,通过定性推理过程,对数据对象进行定性概念的推理,实现了更符合人类思维活动的推理过程,具有更好的可操作性和可理解性。