Service Science

This paper is a first exploration of the relationship between service science and Grid computing. Service science is the study of value co-creation interactions among entities, known as service systems. Within the emerging service science community, service is often defined as the application of competences (resources) for the benefit of another. Grid computing is the study of resource sharing among entities, known as virtual organizations, which solve complex business, societal, scientific, and engineering problems. Within the Grid computing community, service is sometimes defined as protocols plus behavior. Both Grid computing and service science are connecting academic, industry, government, and volunteer sector collaborators on a range of projects including eScience, healthcare, environmental sustainability, and more. This paper compares and contrasts the notions of resource, entity, service, interaction, and success criteria for the two areas of study. In conclusion, new areas for collaborative inquiry are proposed.     

关于加强和改进基层党委中心组学习的几点思考

党委中心组学习是本级党委组织本级领导班子成员开展以党的理论和路线方针政策为主要内容的有目的、有意识、有创新的学习活动。对新时期、新形势下的基层党委中心组学习的内涵、地位、作用和基本经验做了分析和思考,并对如何改进当前基层党委中心组学习取得实效提出看法和建议。     

浅析受贿罪讯问中的逻辑错误

犯罪嫌疑人的供述是认定受贿罪的“证据之王”,而讯问中逻辑错误的常见、多发,却严重削弱了其证明力,给反贪工作造成不必要的损失。为此,侦查人员在讯问中必须杜绝预期理由、混淆论题、不正当的复杂问语、推不出、论题含混等逻辑错误。     

蕴涵式命题真值规定的现实意义

本文通过对蕴涵式命题真值规定的解读，建立了真值的大小变化与具体事件往好或往坏变化的联系，论述了蕴涵式命题定义中的真值规定完全适用于现实生活中对自然语言命题的真假判断，从发展的角度举例论述了蕴涵式真值规定的合理性和有效性，这对人们如何更好地用命题逻辑的方法判断自然语言命题是否合乎逻辑意义重大。     

经典逻辑中的不确定性及其支持度

分析了经典逻辑中命题不确定性的存在性,提出了通过推理对命题不确定性的测度方法;详细描述了如何对原逻辑系统的扩展以建立具有不确定推理能力的新的逻辑系统URS;給出了URS的语法及语义,证明了URS的合理性与完全性定理,并与其它不确定推理方法作了比较.     

双枝模糊逻辑(II)

在双枝模糊集基础上,通过对单枝模糊逻辑的合理扩展,建立了双枝模糊逻辑的框架。从双枝模糊命题入手,给出双枝模糊逻辑的性质和双枝模糊逻辑公式,以及双枝模糊逻辑的析取范式与合取范式。这些结果为研究双枝模糊推理和双枝模糊控制奠定了基础。     

基于有补T-范的F-命题演算和一类F-控制模型

本文利用有补T-范建立了一类Fuzzy命题演算系统,给出了假言推理规则,推广了二值逻辑中命题演算的主要结果,且演算简单方便。作为它的应用,文末还给出了Fuzzy控制中的一个近似推理模型。     

The Objective Conception of Context and Its Logic

In this paper, an objective conception of contexts based loosely upon situation theory is developed and formalized. Unlike subjective conceptions, which take contexts to be something like sets of beliefs, contexts on the objective conception are taken to be complex, structured pieces of the world that (in general) contain individuals, other contexts, and propositions about them. An extended first-order language for this account is developed. The language contains complex terms for propositions, and the standard predicate ist that expresses the relation that holds between a context and a proposition just in case the latter is true in the former. The logic for the objective conception features a global classical predicate calculus, a local logic for reasoning within contexts, and axioms for propositions. The specter of paradox is banished from the logic by allowing ist to be nonbivalent in problematic cases: it is not in general the case, for any context c and proposition p, that either ist(c,p) or ist(c, ¬ p). An important representational capability of the logic is illustrated by proving an appropriately modified version of an illustrative theorem from McCarthy's classic Blocks World example.     

Fuzzy Conditional Probability Relations and their Applications in Fuzzy Information Systems

In our real-world applications, data may be imprecise in which levels or degrees of preciseness of data are intuitively different. In this case, fuzzy set expressions are considered as an alternative to represent the imprecise data. In general, the degree of similarity relationship between two fuzzy (imprecise) data in real-world applications may not necessarily be symmetric or transitive. In order to provide such a degree of similarity between two fuzzy data, we introduced the fuzzy conditional probability relation. The concept of a fuzzy conditional probability relation may be considered as a concrete example of weak similarity relation which in turn is a special type of fuzzy binary relation generalizing similarity relation. Two important applications concerning the application of Knowledge Discovery and Data Mining (KDD) in the presence of a fuzzy data table (usually called fuzzy information system), namely removing redundant objects and recognizing partial or total dependency of (domain) attributes, are considered induced by the fuzzy conditional probability relation. Here, the fuzzy information system contains precise as well as imprecise data (fuzzy values) about objects of interest characterized by some attributes. Related to the dependency of attributes, we introduce the fuzzy functional dependency that satisfies Armstrongs Axioms. In addition, we also discuss some interesting applications such as approximate data reduction and projection, approximate data querying and approximate joining in order to extend the query system.     

一些命题逻辑的Groebner基算法

介绍了一种得到命题结论的新方法，即通过把逻辑命题的项转化成相应的多项式，然后计算Groebner基,从而得到命题的结论．