Snort研究及BM算法改进

Snort是一个轻型的入侵检测系统,在检测过程中,字符串匹配算法的效率决定了Snort系统的性能.分析了Snort的系统结构和工作流程,对Snort的BM字符匹配算法进行深入研究,提出了BM字符匹配算法的改进方法.实验数据表明,改进的BM字符匹配算法可提高Snort的效率.     

The design of intelligent workflow monitoring with agent technology

In recent years, workflow technology has been widely used in business process management. With the increased complexity, uncertainty and risks in business operations, workflow monitoring is gaining growing attention in business process controlling and supervision. However, monitoring functions provided in traditional workflow systems lack flexibility, and provide little support for managing complex and dynamical changes in business process. In this paper, we propose a novel workflow monitoring approach, in which various intelligent agents work together to perform flexible monitoring tasks in an autonomous and collaborative way. By using customized monitoring plan and proactive monitoring process, the workflow monitoring activities can be executed flexibly and efficiently. The application of intelligent agents for such flexible, adaptive and collaborative workflow monitoring is investigated through an intelligent monitoring system in securities trading.     

The design of a JADE-based autonomous workflow management system for collaborative SoC design

Given a fast changing electronics goods marketplace, designers of integrated circuits and components need to be more competitive, efficient, flexible, and use collaborative workflow to reduce time-to-market and a project’s life cycle. In recent years, agent-based workflow management systems (WfMS) have been widely used to monitor and control business design processes. In this paper, intelligent agents are applied to the collaborative system-on-chip (SoC) design environment. The proposed JADE-based autonomous workflow management system (JAWMS) uses a workflow coordination mechanism and an agent integration mechanism to enable the analysis, management and interaction of automated design processes. The workflow coordination mechanism uses five domain specific agents to perform the workflow enactment services and a generic agent to control the system flow logic. The system kernel of JAWMS follows the specifications of the workflow reference model provided by the workflow management coalition (WfMC). The agent integration mechanism supports an agent to interact with other JADE-based agent platforms and to coordinate and monitor workflow coordination messages. All agents are written in the Java language using the JADE platform and work together to perform flexible, adaptive and dynamic design tasks in an autonomous and collaborative way. JAWMS facilitates SoC design and team interaction in a collaborative but distributed product development environment.     

Collaborative technologies for evolving software systems

The article discusses four major collaboration theme areas: collaborative information engineering; collaborative process and workflow; collaboration support (awareness); and integration of collaborative systems. Various projects incorporating these technologies are outlined. All of the projects described are developing component technologies intended for mixing and matching with each other and with technologies under investigation by other EDCS projects not particularly concerned with collaborative work, as well as with COTS software. Only GroupSpaces intends to assemble a full-blown, directly usable software development environment framework, and that comprises components, developed under EDCS and available off-the-shelf     

面向知识应用和交互的工作流系统建模与控制

针对基于知识应用和交互的复杂工作流系统，对知识应用特性进行了分析，并构造了对应知识聚合与信息再生的过程单元。利用过程单元之间的关联分析，对面向知识应用和交互的工作流系统建模进行了深入的研究。在对一个基于知识应用的具体实例进行分析的基础上，探讨了基于知识应用和交互的工作流系统中的控制问题，提出了一种基于区域控制和交互的控制策略，并给出了控制分解所遵循的基本原则。最后，讨论了工作流技术的发展方向和热点技术。     

Automated silicon intellectual property trade using mobile agent technology

The critical success factors for enterprises operating in knowledge-based economies include the ability to effectively accumulate knowledge, the ability to utilize knowledge, and the drive to create intellectual property (IP). For the semiconductor industry, the development of system-on-a-chip (SoC) technology and silicon intellectual property (SIP) are the basis for market strategy and the formation of comparative advantage. In order to achieve quicker time-to-market integrated circuit designs, SIP trade and reuse must be considered. This research applies mobile agent technology that enables the use of SIP automatic e-trade mechanisms over the Internet. Following the principles of autonomous data sharing, asynchronous data acquisition, and parallel task processing, this research applies remote SIP information retrieval and automates the matching and trading activities. A prototype system, called the Knowledge Services and Trade Platform (KSTP), is designed and implemented with web-based interfaces. A mobile agent behavioral model is used for negotiations and knowledge acquisition. The agent-based prototype considers factors of efficiency, cost, and precision throughout the process of SIP knowledge acquisition. For trade partner matching, fuzzy set theory evaluation models are developed. The matching model efficiently and consistently suggests suitable partners for trade under different circumstances. The goal of the research is to provide an autonomous and collaborative KSTP for SIP exchanges.     

Knowledge integration and sharing for collaborative molding product design and process development

This study presents a systematic approach to developing a knowledge integration and sharing mechanism for collaborative molding product design and process development. The proposed approach includes the steps of (i) collaborative molding product design and process development process modeling, (ii) an ontology-based knowledge model establishment, (iii) knowledge integration and sharing system framework design, (iv) ontology-based knowledge integration and sharing methods development, and (v) ontology-based knowledge integration and sharing mechanism implementation. The mechanism can support collaborative molding product design and process development by providing functions of knowledge integration and sharing. Results of this study facilitate the knowledge integration and sharing of collaborative molding product design and process development to satisfy the product knowledge demands of participants, and thus increase molding product development capability, reduce molding product development cycle time and cost, and ultimately increase molding product marketability.     

基于知识的试油方案协同设计方法应用研究

为解决试油三项设计系统在实际应用中因认知水平、知识水平和实际需求不同导致的设计方案差异大、标准不统一的问题,如何以一种形式化、标准化的方式来表示试油方案设计领域知识,实现方案标准统一化,提高试油方案协同设计系统的智能性是面临的一个重要问题。在研究试油方案协同设计工作流的基础上引进知识的概念,将试油领域本体与试油方案协同设计的具体应用需求相结合提出了一种基于知识的试油方案协同设计方法。该方法介绍了试油领域本体构建、应用以及协同工作流构建等技术和方法,利用统一的知识表示,使知识与试油方案协同设计业务流程紧密关联,很好地解决了实际应用中方案标准统一化以及知识重用性的问题。目前系统在使用中,提高了方案设计的准确性和设计效率。     

Modeling workflow activities for collaborative process planning with product lifecycle management tools

Process planning activities are critical in manu- facturing distributed environments where different companies need to collaborate in product development. In this work, we propose a workflow model for a collaborative process planning environment in which original equipment manufacturer and suppliers companies interact with the help of Product Lifecycle Management and CAD/CAM tools. The proposed workflow model establishes the different activities, the information flows and the different stages that must be followed by all the participants. A pilot implementation has been made in order to validate the model in a realistic industrial scenario.     

基于XML和Agent联邦的工作流建模方法

介绍一种基于XML和Agent联邦的工作流建模方法，目的在于建立分布式环境下灵活的，动态的工作流管理过程。该方法将工作流管理系统组织成一个可能嵌套的Agent联邦，将工作流定义为一个由Agent联邦协同完成的活动集合。面向活动分担的联合意向是Agent进行工作流规划的依据与手段，它成功地解决了工作流过程分解的静态性与工作流过程运行的动态性之间的矛盾。文中方法采用的过程建模语言是建立在XML的基础上，与传统的过程建模语言相比，它具有更强的可操作性与可扩展性。最后介绍了工作流建模环境以及利用该环境进行工作流建模的过程与步骤。     

Extraction of user profile based on workflow and information flow

A collaborative team usually consists of team members with various domains. These members’ demands for knowledge are also different from each other. For recommending potentially useful knowledge to suitable members, their user profiles should be well managed and maintained. User profile can be input by the members, but a more intelligent way should be the automatic extraction of the user profiles. Workflow and information flow are two types of collaborative processes, which exist behind every collaborative team. This paper is mainly concerned with how to extract these team members’ user profile from the two types of contexts: workflow and information flow. This paper defines a model for the user profile. Then some methods are proposed for extracting the profile information on the basis of workflow and information flow. This study on the user profile extraction can pave the way for developing knowledge recommender systems, which can recommend proper knowledge to proper team members with a collaborative team.     

Multi-agent collaboration for B2B workflow monitoring

Business-to-business (B2B) applications environments are exceedingly dynamic and competitive. This dynamism is manifested in the form of changing process requirements and time constraints. However, current workflow management technologies have difficulties to solve the challenges problems, such as: how to deal with the dynamic nature of B2B commerce processes, how to manage the distributed knowledge and recourses, and how to reduce the transaction risk. In this paper, a collaborative multi-agent system has been proposed. Multiple intelligent agents in our system can work together not only to identify the workflow problems, but also to solve such problems, by applying business rules, such as re-organizing the procurement and the transaction processes, and making necessary workflow process changes.     

A Knowledge-based Approach to Handling Exceptions in Workflow Systems

This paper describes a novel knowledge-based approachfor helping workflow process designers andparticipants better manage the exceptions (deviationsfrom an ideal collaborative work process caused byerrors, failures, resource or requirements changesetc.) that can occur during the enactment of aworkflow. This approach is based on exploiting ageneric and reusable body of knowledge concerning whatkinds of exceptions can occur in collaborative workprocesses, and how these exceptions can handled(detected, diagnosed and resolved). This work buildsupon previous efforts from the MIT Process Handbookproject and from research on conflict management incollaborative design.     

A genetic algorithm approach for group formation in collaborative learning considering multiple student characteristics

Considering that group formation is one of the key processes in collaborative learning, the aim of this paper is to propose a method based on a genetic algorithm approach for achieving inter-homogeneous and intra-heterogeneous groups. The main feature of such a method is that it allows for the consideration of as many student characteristics as may be desired, translating the grouping problem into one of multi-objective optimization. In order to validate our approach, an experiment was designed with 135 college freshmen considering three characteristics: an estimate of student knowledge levels, an estimate of student communicative skills, and an estimate of student leadership skills. Results of such an experiment allowed for the validation, not only from the computational point of view by measuring the algorithmic performance, but also from the pedagogical point of view by measuring student outcomes, and comparing them with two traditional group formation strategies: random and self-organized.     

Markowitz-based portfolio selection with cardinality constraints using improved particle swarm optimization

This work presents particle swarm optimization (PSO), a collaborative population-based meta-heuristic algorithm for solving the Cardinality Constraints Markowitz Portfolio Optimization problem (CCMPO problem). To our knowledge, an efficient algorithmic solution for this nonlinear mixed quadratic programming problem has not been proposed until now. Using heuristic algorithms in this case is imperative. To solve the CCMPO problem, the proposed improved PSO increases exploration in the initial search steps and improves convergence speed in the final search steps. Numerical solutions are obtained for five analyses of weekly price data for the following indices for the period March, 1992 to September, 1997: Hang Seng 31 in Hong Kong, DAX 100 in Germany, FTSE 100 in UK, S&P 100 in USA and Nikkei 225 in Japan. The test results indicate that the proposed PSO is much more robust and effective than existing PSO algorithms, especially for low-risk investment portfolios. In most cases, the PSO outperformed genetic algorithm (GA), simulated annealing (SA), and tabu search (TS).     

工程图纸设计系统中的工作流授权模型研究

工程图纸设计是一个典型的工作流,它是严格的、由一系列相关设计任务组成的自动化过程.实际的工程图纸设计包含许多环节,如设计、提交、修改和审核等.不同的设计和管理人员在整个流程的不同阶段协同工作,并在每一阶段实现特定的目标.工程图纸设计工作流的这一特点使得授权成为其中的一个关键问题.针对此问题在分析经典基于角色的访问控制授权模型的基础上提出一种新的工作流授权模型SODAM.该模型引入了服务和动态授权的概念,增强了对用户权限和角色的控制,并使得授权对工作流的动态变化有了更强的适应性.最后给出了该模型在实时工程图纸设计系统中的应用.     

Augmenting Multi-Party Face-to-Face Interactions Amongst Strangers with User Generated Content

We present the results of an investigation into the role of curated representations of self, which we term Digital Selfs, in augmented multi-party face-to-face interactions. Advancements in wearable technologies (such as Head-Mounted Displays) have renewed interest in augmenting face-to-face interaction with digital content. However, existing work focuses on algorithmic matching between users, based on data-mining shared interests from individuals’ social media accounts, which can cause information that might be inappropriate or irrelevant to be disclosed to others. An alternative approach is to allow users to manually curate the digital augmentation they wish to present to others, allowing users to present those aspects of self that are most important to them and avoid undesired disclosure. Through interviews, video analysis, questionnaires and device logging, of 23 participants in 6 multi-party gatherings where individuals were allowed to freely mix, we identified how users created Digital Selfs from media largely outside existing social media accounts, and how Digital Selfs presented through HMDs were employed in multi-party interactions, playing key roles in facilitating strangers to interact with each other. We present guidance for the design of future multi-party digital augmentations in collaborative scenarios.     

Comparing the roles of representations in face-to-face and online computer supported collaborative learning

This paper reports an empirical study comparing the role of discourse and knowledge representations (graphical evidence mapping) in face-to-face versus synchronous online collaborative learning. Prior work in face-to-face collaborative learning situations has shown that the features of representational notations can influence the focus of learners' discourse and collaborative activities. Two hypotheses were considered in the present study: (1) The influence of knowledge representations in the online condition could be weaker because of the lack of shared awareness and meaning that results from working together in front of a physically shared display, and because of the greater difficulty of utilizing the representations as a resource for conversation through gestural deixis, and (2) The influence of knowledge representations in the online study could be stronger because participants must rely more on them to compensate for the absence of face-to-face modes of communication. Quantitative results largely support the second hypothesis. There was greater consideration of certain coding categories supported by the knowledge representation software. However, essay quality and other observations provide indirect support for the first hypothesis. Explanations for these results and implications for the design of online collaborative learning environments are provided.     

Efficient model sharing for scalable collaborative classification

We propose a novel collaborative approach for document classification, combining the knowledge of multiple users for improved organization of data such as individual document repositories or emails. To this end, we distribute locally built classification models in a network of participating users, and combine the shared classifiers into more powerful meta models. In order to increase the propagation efficiency, we apply a method for selecting the most discriminative model components and transmitting them to other participants. In our experiments on four large standard collections for text classification we study the resulting tradeoffs between network cost and classification accuracy. The experimental results show that the proposed model propagation has negligible communication costs and substantially outperforms current approaches with respect to efficiency and classification quality.