Stochastic analysis of file-swarming systems

File swarming (or file sharing) is one of the most important applications in P2P networks. In this paper, we propose a stochastic framework to analyze a file-swarming system under realistic setting: constraints in upload/download capacity, collaboration among peers and incentive for chunk exchange. We first extend the results in the coupon system [L. Massoulie, M. Vojnovic, Coupon replication systems, in: Proc. ACM SIGMETRICS, Banff, Alberta, Canada, 2005] by providing a tighter performance bound. Then we generalize the coupon system by considering peers with limited upload and download capacity. We illustrate the last-piece problem and show the effectiveness of using forward error-correction (FEC) code and/or multiple requests to improve the performance. Lastly, we propose a framework to analyze an incentive-based file-swarming system. The stochastic framework we propose can serve as a basis for other researchers to analyze and design more advanced features of file-swarming systems.     

Threshold cryptography based on Asmuth-Bloom secret sharing

In this paper, we investigate how threshold cryptography can be conducted with the Asmuth-Bloom secret sharing scheme and present three novel function sharing schemes for RSA, ElGamal and Paillier cryptosystems. To the best of our knowledge, these are the first provably secure threshold cryptosystems realized using the Asmuth-Bloom secret sharing. Proposed schemes are comparable in performance to earlier proposals in threshold cryptography.     

An exploration of expertise of knowledge workers: towards a definition of the universe of discourse for knowledge acquisition

Abstract. Knowledge systems development and use have been significantly encumbered by the difficulties of eliciting and formalizing the expertise upon which knowledge workers rely. This paper approaches the problem from an examination of the knowledge competencies of knowledge workers in order to define a universe of discourse for knowledge elicitation. It outlines two categories and several types of knowledge that could serve as the foundations for the development of a theory of expertise.     

Developing real-time knowledge-based systems with PERFECT

PERFECT (Programming EnviRonment For Expert systems Constrained in reasoning Time) is aimed at providing the necessary engineering support in real-time knowledge-based system development. PERFECT bridges the gap between the traditional analysis and design methodologies, and the implementation tools for these systems. It does so by providing the means to construct a knowledge model and to choose a suitable inference strategy. Subsequently the properties of the knowledge model and inference strategy may be analysed. For instance, it may be checked whether the knowledge model contains sufficient knowledge to diagnose a fault in an industrial process. Moreover, it may be checked whether the inference engine is able to provide an answer to a certain problem in time. If not, the analyser of PERFECT proposes an alternative structure of the knowledge model. When the constructed knowledge model and the chosen inference strategy show the required time efficiency, the compiler of PERFECT may translate them to an actual real-time knowledge based system in COGSYS. In addition, guidelines are provided with respect to the design of the human-machine interface. The resulting system is an instrument—a source of information that can be used by the human operator during problem-solving, rather than a prosthesis—a device that solves the entire problem by itself and presents the outcome to the human operator.     

计算机生成兵力中的人工智能技术

开发CGF的难点和重点在于CGF实体行为的生成,尤其是人类智能行为的实现。人类行为建模最重要的三个方面是知识获取、知识表示和决策机制,都与人工智能技术相关。该文主要介绍人类行为描述的知识表示和知识获取问题,讨论了人工智能技术在这两个方面的应用,并对将来的研究工作做了一个简单的展望。     

Automated Support for Building and Extending Expert Models

Building a knowledge-based system is like developing a scientific theory. Although a knowledge base does not constitute a theory of some natural phenomenon, it does represent a theory of how a class of professionals approaches an application task. As when scientists develop a natural theory, builders of expert systems first must formulate a model of the behavior that they wish to understand and then must corroborate and extend that model with the aid of specific examples. Thus there are two interrelated phases of knowledge-base construction: (1) model building and (2) model extension. Computer-based tools can assist developers with both phases of the knowledge-acquisition process. Workers in the area of knowledge acquisition have developed computer-based tools that emphasize either the building of new models or the extension of existing models. The PROTÉGÉ knowledge-acquisition system addresses these two activities individually and facilitates the construction of expert systems when the same general model can be applied to a variety of application tasks.     

An empirical investigation of socio-cultural factors of information sharing in China

Understanding information sharing is an important challenge to modern organizations, and is likely to be increasingly considered when IT investment decisions are made world-wide. Our research study investigated the influence of cultural factors on information sharing in China. It was postulated that social network structures such as guanxi, Confucian dynamism, and collectivism could explain the degree to which information sharing took place between people in China. It was found that guanxi, Confucian dynamism, and collectivism all had a significant influence on information sharing.     

C++程序设计教学中的技能培养

本文阐述了知识与技能的关系,以及C++程序设计教学中知识和技能的双重性要求。以选择语句为例,演示了"先知识后技能"的教学过程。实践证明,这样的教学安排行之有效。     

基于知识图谱的互补项目推荐

在缺乏用户交互互补项目方面数据的情况下,将用户对项目的偏好融合到只考虑项目关系的互补项目推荐中,提高推荐模型的性能。提出一种基于知识图谱的互补项目推荐方法,在用户历史交互项目集中推测用户交互的互补项目,基于知识图谱提取用户对互补项目的偏好,利用图像与文本学习项目之间的互补关系,最后基于神经网络实现二者的共同学习。提出的方法在Amazon数据集上与次优的基线方法相比,ACC提升了7%,precision提升了3%,这说明提出的方法性能优异。该算法共同学习用户对项目的偏好与项目之间的互补关系,提升了推荐性能。