Towards Restructuring and Normalization of Types in Databases

The equivalence-preserving transformation and normalization of types in object-oriented databases are discussed.Specifically,A normal form of types based on set-theoretic equivalence is proposed,rewrite rules which transform types into normal forms are presented,and the uniqueness of normal form and the completeness of rewrite rules are proved.The emphasis of this work is on normal forms and corresponding rewrite rules.It provides a new formal approach for the study of restructuring of database schema and other manipulations in object-oriented databases.     

一种基于决策表的分类规则挖掘新算法

The mining of classification rules is an important field in Data Mining. Decision table of rough sets theory is an efficient tool for mining classification rules. The elementary concepts corresponding to decision table of Rough Sets Theory are introduced in this paper. A new algorithm for mining classification rules based on Decision Table is presented, along with a discernable function in reduction of attribute values, and a new principle for accuracy of rules. An example of its application to the car‘s classification problem is included, and the accuracy of rules discovered is analyzed. The potential fields for its application in data mining are also discussed.     

A Logical Design Method for Relational Databases Based on Generalization and Aggregation Semantics

In this paper,a series of esign methods for relational databases based on generalization and aggregation semantics is set up.The relationship between a class and its subclass s considered as a scheme constraint.The concept of inheritance dependencies,which describes the multiple inheritance among schemes, is presented in the paper.It is shown that the inference rules for inheritance dependencies are sound and complete.Furthermore,a series of results about the closure of inheritance dependencies and the minimal set of inheritance dependencies,which are analogues to functional dependencies,is obtained.In order to describe the aggregation semantices,the concept of aggregation dependencies is given.It is easy to implement these constraints under relational database management systems.     

A Multi-dimensional Trust-aware Cloud Service Selection Mechanism Based on Evidential Reasoning Approach

In the last few years, cloud computing as a new computing paradigm has gone through significant development, but it is also facing many problems. One of them is the cloud service selection problem. As increasingly boosting cloud services are offered through the internet and some of them may be not reliable or even malicious, how to select trustworthy cloud services for cloud users is a big challenge. In this paper, we propose a multi-dimensional trust-aware cloud service selection mechanism based on evidential reasoning(ER) approach that integrates both perception-based trust value and reputation based trust value, which are derived from direct and indirect trust evidence respectively, to identify trustworthy services. Here, multi-dimensional trust evidence, which reflects the trustworthiness of cloud services from different aspects, is elicited in the form of historical users feedback ratings. Then, the ER approach is applied to aggregate the multi-dimensional trust ratings to obtain the real-time trust value and select the most trustworthy cloud service of certain type for the active users. Finally, the fresh feedback from the active users will update the trust evidence for other service users in the future.     

Design of a fault diagnosis scheme for a class of singular nonlinear systems

A new fault detection and diagnosis approach is developed in this paper for a class of singular nonlinear systems via the use of adaptive updating rules. Both detection and diagnostic observers are established, where Lyapunov stability theory is used to obtain the required adaptive tuning rules for the estimation of the process faults. This has led to stable observation error systems for both fault detection and diagnosis. A simulated numerical example is included to demonstrate the use of the proposed approach and encouraging results have been obtained.     

A new parallel-by-cell approach to undistorted data compression based on cellular automaton and genetic algorithm

In this paper,a new parallel-by-cell approach to the undistorted data compression based on cellular automaton and genetic algorithm is presented.The local compression rules in a cellular automaton are obtained by using a gnetic evolutionary algorithm.The correctness of the hyper-parallel compression,the time complexity,and the relevant symbolic dynamic behaviour are discussed.In comparison with other traditional sequential or small-scale parallel methods for undistorted data compression,the proposed approcah shows much higher real-time performance,better suitability and feasibility for the systolic hardware implementation.     

一个软件服务协同中的信任管理框架设计

Internet-based Web application systems are gradually built as software service coordination systems. In an open, dynamic and collaborative application environment, traditional methods assumed with closeness, centralization and independence are not able to cope with these security problems efficiently. Trust management is a new method for dealing with security issues of open, distributed network application system. However, the traditional policy-based trust management systems have some shortcomings, i.e. complex in policy making, unable to deal with negative se-curity credentials, etc. So, we design a trust management framework in combination with subjective trust model for software service coordination and security decision in Internet environment. This trust management framework has characteristics of operability, reasonability, and flexibility in policy setting.     

Repairing VLSI/WSI Redundant Memories with Minimum Cost

A new approach to repair memory chips with redundancy is proposed.This approach s based on the minimization of the repair cost.Algorithms for cost driven repair are presented.The algorithms can be executed either on -line(concurrently with the testing of the memory),or off-lin(at completion of testing).Analytical expressions for the repair cost under both circumstances are given.The presented algorithms are also perfect in the sense that they can correctly diagnose a repairable/unrepairable memory and find the optimal repair-solution.     

A semantics-based approach for achieving self fault-tolerance of protocols

The cooperation of different processes may be lost by mistake when a protocol is executed.The protocol cannot be normally operated under this condition.In this paper,the self fault-tolerance of protocols is discussed,and a semanticslbased approach for achieving self fault-tolerance of protocols is presented.Some main characteristics of self fault-tolerance of protocols concerning liveness,nontermination and infinity are also presented.Meanwhile,the sufficient and necessary conditions for achieving self fault-tolerance of protocols are given.Finally,a typical protocol that does not satisfy the self fault-tolerance is investigated,and a new redesign version of this existing protocol using the proposed approach is given.     

A necessary and sufficient stabilization condition for discrete time-varying stochastic systems with multiplicative noise

This paper investigates a fundamental problem of stabilization for time-varying multiplicative noise stochastic systems. A necessary and sufficient stabilization condition is presented based on the receding horizon approach. The explicit time-varying controller is designed if the condition is satisfied. The presented results are new to the best of our knowledge.     

信任网络中的依赖关系分析与消除

针对现有的信任聚合方法普遍存在因推荐信息损耗或重复计算等导致信任度量结果与直接推荐之间偏差增大的问题,首先引入信任子图及左部与右部结点等相关概念,并证明了信任子图中依赖关系与结点入度及出度之间的关联性,在此基础上,提出了一种有效的依赖关系消除算法,最后,给出了一个数值计算实例来说明该方法的可行性和有效性。     

Jφsang主观信任模型的优化

研究了Jφsang主观信任模型。针对模型不能惩罚恶意行为的问题,提出一种证据数据预处理算法,实验结果表明该算法能使信任随负面证据的增加呈几何级数减少,可以较好地惩罚恶意行为;针对模型传递算子不能自适应系统状态变化的问题,构建了与实体主观性和系统状态有关联的乐观因子,基于该乐观因子提出新的传递算子,理论分析表明新传递算子能够自适应系统状态变化;针对模型聚合算子聚合对立观点鲁棒性差、计算精度低的问题,基于证据数据标准化提出了新的聚合算子,理论和比较分析表明,新的聚合算子能够提高模型的精度和鲁棒性,同时降低计算的复杂性。     

服务计算环境中基于模糊修正的信任度量

针对现有信任度量方法不能解决实体间评价尺度的差异性而普遍存在信任度量准确性下降的问题,提出了一种基于模糊修正的信任度量算法。通过模糊成员函数表达了信任值的语义,并详细描述了一种推荐信任值的模糊修正算法,在此基础上提出了基于相似度的推荐信任聚合机制。实验结果表明,与PageRank和TidalTrust算法相比,该算法增强了信任度量的准确性,降低了信任决策中的误判率。     

A new evidential trust model for open communities

Open communities allow anonymous members to join and leave anytime, in which interactions commonly take place between parties who have insufficient information about each other. The openness brings risk to both the service provider and consumer. Trust is an important tool in human life, as it enables people to get along with strangers. It is accepted that trust management is a potential way to solve the above problem in computational systems. A trust management mechanism can assist members in the open community to evaluate each other and decide which and whether to interact. It provides an incentive to a good behavior and gives a punishment to a malicious behavior. The representation of trust in current computational trust and reputation models can be classified into four categories. We present a new evidential trust model based on the Dezert–Smarandache theory, which has a higher expressiveness than the trust models based on the Dempster–Shafer theory of evidence. We propose a smooth and effective approach of trust acquisition. The general rule of combination of the Dezert–Smarandache theory is used for trust aggregation. We consider that trust is transitive and present a rule of trust transitivity for our model. Lastly, we evaluate our model experimentally.     

社会网络环境下基于信任传递的推荐模型研究

现有基于信任的推荐算法中没有充分挖掘用户间的信任关系,且缺乏合理的信任关系传递规则,极大地影响了推荐算法的可靠性和准确性。针对上述问题,通过用户评分数据与用户的社会关系建立信任传递模型,提出一种基于信任传递的推荐算法。该算法首先利用评分数据计算信任传递模型中用户的隐式直接信任关系,其次通过求解有序加权平均算子融合多条信任传递链的间接信任关系,最后将计算出的用户信任度与相似度融合为综合相似度进行预测推荐。实验结果证实了所提算法可有效提升系统的推荐质量。     

基于证据理论的云计算信任模型研究

信任模型是研究云计算中信任机制的重要问题,其研究结果可应用于云计算数据安全、服务安全,平台安全等研究.为了解决信任的量化和不确定问题,利用证据理论对信任及信任行为进行建模,并认为信任由直接的服务行为结果和间接的第三方推荐组成.提出信任的传递和聚合方式,并将建立的信任模型通过传递方式和聚合方式进行实验;结果显示该信任模型在聚合和信任行为结果纪录情况下,有利于抑制信任的不确定.     

一种带有信任度的基于角色的信任管理模型

在RT（一族基于角色的信任管理语言）的基本部分RT0的基础上提出了新的带有信任度的基于角色的信任管理模型（RTDOT）,将信任度结合到信任管理中,并给出了模糊集合的语义。新模型体现了信任的主观性和模糊性,并可对委托深度进行控制,与模糊理论的结合为信任管理提供了一个新方向。     

一种基于图论方法的开放计算系统证据信任模型

基于图论方法提出了一种新的证据信任模型(graph theory based evidential trust model, GTETM),解决了现有证据信任模型中普遍存在的在信任聚合过程中缺少对信任链之间依赖关系的有效处理等引起的模型性能下降问题.同时,GTETM在建模实体的信任度时区分实体的服务信任度与反馈信任度,并在证据理论框架下提出两种不同的信任传递方法,增强了模型抵抗恶意推荐攻击的能力.仿真实验表明,与已有信任度量模型相比,GTETM具有更强的抑制策略欺骗及共谋行为的能力,在信任度量准确性方面也有较大提高.     

Trust based consensus model for social network in an incomplete linguistic information context

A theoretical framework to consensus building within a networked social group is put forward. This article investigates a trust based estimation and aggregation methods as part of a visual consensus model for multiple criteria group decision making with incomplete linguistic information. A novel trust propagation method is proposed to derive trust relationship from an incomplete connected trust network and the trust score induced order weighted averaging operator is presented to aggregate the orthopairs of trust/distrust values obtained from different trust paths. Then, the concept of relative trust score is defined, whose use is twofold: (1) to estimate the unknown preference values and (2) as a reliable source to determine experts’ weights. A visual feedback process is developed to provide experts with graphical representations of their consensus status within the group as well as to identify the alternatives and preference values that should be reconsidered for changing in the subsequent consensus round. The feedback process also includes a recommendation mechanism to provide advice to those experts that are identified as contributing less to consensus on how to change their identified preference values. It is proved that the implementation of the visual feedback mechanism guarantees the convergence of the consensus reaching process.     

Ad hoc网络中鲁棒信任机制的研究

在Ad hoc网络中,报文转发依赖于各个分布节点间的协作.在分析了不同路由协议对信任模型的不同需求基础上,针对源路由协议特性,提出了鲁棒信任机制(RTM).该机制基于OTMF模型,采用了基于确认机制从非邻接节点获取直接信息的方法,以及基于贝叶斯决策的推荐信任度修正方法,有效提高了信任评价的正确率.实验结果表明,RTM能较好地抵御针对信任模型的虚假推荐攻击并具有较快信任评价收敛速度.