Model transformation and formal verification for Semantic Web Services composition

Web services composition is becoming more and more important in today’s service oriented business environment. We need to compose services from different providers together to fulfill the business goals that cannot be satisfied by any single service. However, different services often have semantic inconsistencies which may lead to the failure of the services composition. In order to verify the correctness of the Semantic Web Services composition, this paper proposed a composition model of Coloured Petri Nets which is transformed from OWL-S model. This model can express the logical relations among the sub-processes of the services composition explicitly, and verify the correctness of the services composition using formalized methods of Coloured Petri Nets. This paper presented the verification algorithms for the reachability, boundness and semantic consistency of composed services. Furthermore, an example of collaborating design process was given to simulate and execute the model.     

面向服务组合的用户隐私需求规约与验证方法

用户向Web服务组合提供隐私数据时,不同用户有自身的隐私信息暴露需求,服务组合应支持用户隐私需求的可满足性验证.首先提出一种面向服务组合的用户隐私需求规约方法,用户能够定义隐私数据及不同使用情境的敏感度,采用敏感度-信誉度函数明确可以使用隐私数据的成员服务,简化隐私需求的同时,提高了隐私需求的通用性.为了验证服务组合是否满足用户隐私需求,首先通过隐私数据项依赖图（privacy data item dependency graph,简称PDIDG）描述组合中隐私数据项的依赖关系,然后采用隐私开放工作流网（privacy open workflow net,简称POWFN）构建隐私敏感的服务组合模型,通过需求验证算法验证服务组合是否满足用户隐私需求,从而能够有效防止用户隐私信息的非法直接暴露和间接暴露.最后,通过实例分析说明了该方法的有效性,并对算法性能进行了实验分析.     

A kernel machine-based secure data sensing and fusion scheme in wireless sensor networks for the cyber-physical systems

Wireless sensor networks (WSNs) as one of the key technologies for delivering sensor-related data drive the progress of cyber-physical systems (CPSs) in bridging the gap between the cyber world and the physical world. It is thus desirable to explore how to utilize intelligence properly by developing the effective scheme in WSN to support data sensing and fusion of CPS. This paper intends to serve this purpose by proposing a prediction-based data sensing and fusion scheme to reduce the data transmission and maintain the required coverage level of sensors in WSN while guaranteeing the data confidentiality. The proposed scheme is called GM–KRLS, which is featured through the use of grey model (GM), kernel recursive least squares (KRLS), and Blowfish algorithm (BA). During the data sensing and fusion process, GM is responsible for initially predicting the data of next period with a small number of data items, while KRLS is used to make the initial predicted value approximate its true value with high accuracy. The KRLS as an improved kernel machine learning algorithm can adaptively adjust the coefficients with every input, while making the predicted value more close to actual value. And BA is used for data encoding and decoding during the transmission process due to its successful applications across a wide range of domains. Then, the proposed secure data sensing and fusion scheme GM–KRLS can provide high prediction accuracy, low communication, good scalability, and confidentiality. In order to verify the effectiveness and reasonableness of our proposed approach, we conduct simulations on actual data sets that are collected from sensors in the Intel Berkeley research lab. The simulation results have shown that the proposed scheme can significantly reduce redundant transmissions with high prediction accuracy.     

软件设计模式课程实验教学系统探索

设计模式是软件工程专业的重要核心课程,兼具理论性和实践性,但其高度的抽象性给学生学习带来较大困难.针对该课程及学生的认知特点,设计开发了一个基于Spring框架的设计模式实验教学系统-在线教务管理平台,该系统采用B/S架构,综合了多种常用设计模式,不仅展示了单个设计模式的特点,同时展示了这些设计模式在实际项目开发中的复合应用,有助于学生加深设计模式方法学理论精髓的理解,提高实践动手能力,从而为进一步掌握高级软件工程知识奠定基础.     

基于云模型熟悉相似度的协同过滤推荐算法

研究了一种新的协同过滤推荐方法。针对推荐算法中相似度存在的不足,提出了兼顾"形状-距离"的云模型综合相似度测算方法;考虑用户之间的兴趣匹配,提出了云模型熟悉相似度的概念;提出了基于云模型熟悉相似度的邻居用户选择方法,进而产生推荐。实验结果表明,本方法提高了推荐准确度。     

基于分布式基站池的电力光载无线系统

为加强电力接入通信网络的建设,更好地满足电力应用的需求,依托电力系统已有专用光纤和无线通信资源,并借鉴分布式基站在公网通信中的建设模式,提出基于分布式基站池的电力光载无线通信系统。将基带处理单元以池的形式进行划分管理,并以分布式的方式进行信息交互和数据处理,同时,从远端单元侧、传输通道侧及基站池侧三个方面来实现基于认知的资源优化调度使用。理论分析表明,新系统可充分利用电力专用通信资源,适应电力通信接入网网架结构。     

基于模糊综合评价的交易结算偏差电量处理方法

随着电力市场改革不断深化,市场化电力交易愈加复杂,交易结算偏差电量需要更加规范化的处置,因此,提出了一种基于模糊综合评价理论的偏差电量处理方法。该方法基于模糊综合评价方法,综合考虑每笔交易的交易类型、交易周期、交易电量和交易电价4项重要指标,依托业务人员工作经验运用层次分析法设定各项指标权重及交易类型和交易周期隶属度函数,最终确定每笔交易的综合评价得分,以得分为依据分摊偏差电量。最后通过算例分析验证了该方法的有效性和实用性。     

大电网调度稳态自适应巡航场景架构

电力调度控制中心作为电网运行控制的指挥中枢和“决策大脑”,其自动化和智能化程度亟待提升。在此背景下,文中提出新一代电网调度稳态自适应巡航场景架构,在横向上将感知、评估、决策和控制等功能环节灵活组合和智能联动,在纵向上以任务为导向实现多级调度的协同控制。在介绍新一代电网调控系统场景理念的基础上,设计了大电网调度稳态自适应巡航场景的相关功能模块。原型系统上的试运行验证了设计的合理性。     

中低压直流配电系统的分散式统一控制策略

中低压直流配电系统由中压直流母线、低压直流母线、直流变压器等组成,具有多电压等级、多直流母线、多变换器的特点,系统的运行方式与协调控制策略更加复杂。文中以中低压直流配电系统为研究对象,提出了一种基于直流母线电压信号的分散式统一控制策略。直流母线上的光伏发电单元、储能单元、燃料电池单元均采用分散式控制策略,根据直流母线电压调整各自的工作模式。直流变压器采用统一控制策略,集功率控制、中压与低压直流母线电压调节功能于一身,直流变压器根据中压与低压直流母线电压偏差的标幺值,自动调节传输功率的大小与方向,从而实现系统的全局功率均衡。最后,在MATLAB/Simulink中搭建了中低压直流配电系统的仿真模型,并对多种运行状态和场景进行了仿真分析,验证了所提控制策略的有效性。     

基于PMU的电力系统监控体系结构优化设计

文中提出了一种利用有限数量的相量测量单元(PMU)和相量数据集中器(PDC)设计最优监控结构的方法.通过在大量的设定值场景下,使电力系统可观测性曲线的期望值最大化,同时使通信基础设施成本最小化,最终确定PMU和PDC的最佳位置.提出了一种非线性动态扩展卡尔曼滤波(EFK)状态观测器.这种状态观测器可以将暂态行为转换为由...