基于MVC的校园闲置物品置换系统设计

随着经济水平的提高、移动支付的出现,国内大学快递行业飞速发展,学生网购量日益增多,二手闲置物品也在增加。目前咸鱼市场有较多不稳定因素,存在众多欺诈行为,校园内跳蚤市场缺乏有效管理。因此,笔者构建了校园闲置物品置换系统,其能够在校园范围内实现校园闲置物品的重新利用,发挥闲置物品的价值。     

粮仓环境监测系统设计

随着科学技术的发展,粮食行业信息化发展得到了强有力的科技支撑。为满足粮库整体信息化建设的要求,打破"信息孤岛"现状,实现资源整合、数据共享,为大数据分析和数据应用提供数据基础,设计一款能够实时采集粮仓内温湿度、氧气、二氧化碳气体浓度、粮堆高度的数据集成系统。系统采用分层分布式结构,由数据集中器和多种传感器模块组成,数据集中器与各传感器模块间通过RS485总线进行数据通讯,并由数据集中器通过网络专线传输汇总的环境监测数据,通过专用软件进行数据处理和挖掘,从而实现粮仓环境监测和预警等功能。     

物联网环境下基于情境的语义Web服务选择

当前Web服务海量增加，物联网应用技术快速发展、不断普及，而现有的Web服务选择算法低效、用户匹配度低。针对该问题提出一种物联网环境下基于情境的语义Web服务选择方法。该方法应用QoS参数的无量纲化与语义Web服务动态选择方式，将物联网环境下服务与语义Web服务相结合，并根据用户需求针对QoS选择最优的服务集。实验表明，该方法能有效地提高用户服务动态选择的成功率。     

基于NB分类器重访概率预测的Web缓存替换策略

Web缓存是用来解决网络访问延迟和网络拥塞问题，缓存替换策略直接影响缓存的命中率。为此，提出一种朴素贝叶斯（NB）分类器重访概率预测的Web缓存替换策略；根据用户之前访问日志，通过分区操作提取多项特征来表示每次访问的对象，并构建特征数据集；训练NB分类器，用来确定缓存中对象被再次访问的概率，为对象分配权重；结合LRU策略来合理删除一些对象。仿真结果表明，提出的策略在保证较高命中率的同时有效降低了执行时间。     

A time-aware searchable encryption scheme for EHRs

Despite the benefits of EHRs (Electronic Health Records), there is a growing concern over the risks of privacy exposure associated with the technologies of EHR storing and transmission. To deal with this problem, a time-aware searchable encryption with designated server is proposed in this paper. It is based on Boneh's public key encryption with keyword search and Rivest's timed-release cryptology. Our construction has three features: the user cannot issue a keyword search query successfully unless the search falls into the specific time range; only the authorized user can generate a valid trapdoor; only the designated server can execute the search. Applying our scheme in a multi-user environment, the number of the keyword ciphertexts would not increase linearly with the number of the authorized users. The security and performance analysis shows that our proposed scheme is securer and more efficient than the existing similar schemes.     

数据中心内服务器能耗数据采集及特征分析

数据中心的高能耗低能效问题正受到广泛关注与研究，但目前没有公开的数据中心内服务器能耗数据集供研究人员使用，且现有过滤式特征选择并不能满足运维人员的需求。为此，提出了一套模拟数据中心内服务器运行状态的仿真环境架构，基于该架构采集了服务器运行各类任务时的多项性能指标和能耗数据。然后将基于因果关系的特征选择应用于能耗数据集的特征分析中，构建出可解释的特征子集和能耗预测结果。实验结果表明，因果特征子集大小约为过滤式特征子集大小的1/3到1/6，并且使用因果特征子集训练的模型在75%的情况下都取得了最优预测精度。     

互联网Web前端应用中的问题分析

随着Web的发展,在该领域存在的问题也逐渐显露出现,为了从根本上解决Web前端应用过程中存在的问题,需要对Web前端设计进行系统化分析。近年来,Web前端在实际应用过程中因结构设计不完善出现了很多问题,严重影响Web工作的正常运转,针对Web前端问题而提出的研究与防范措施迫在眉睫。目前,基于Web前端结构设计工作的特殊性,可以看出Web前端设计项目至关重要。文章主要介绍了Web前端的具体结构设计以及Web前端在实际应用过程中存在的问题,并提出了相应的解决对策。     

Modeling Smart Grid neighborhoods with the ENERsip ontology

The electricity consumption in the buildings sector has been steadily increasing during the last decade, up to the point that energy efficiency in this sector has become a major problem for governments, utilities, customers, and the environment. The foreseen high penetration of distributed micro-generation facilities based on renewables can help to reduce the environmental footprint of buildings and households, although the complexity of managing effectively the electric grid increases dramatically under these conditions. The IEEE 2030 standard for interoperability in the Smart Grid remarks upon the importance of well-defined data models in such complex scenarios and puts emphasis on the benefits of ontologies and OWL (Web Ontology Language) for this purpose. This paper presents an OWL-based ontology that formally defines the vocabulary and taxonomy and captures the engineering and business semantics of this domain of knowledge (i.e., energy efficiency in the so-called nZEN – nearly Zero-Energy Neighborhoods). This ontology has been defined under the scope of the EU (European Union) research project ENERsip. The paper also highlights the main benefits the ontology brought to all the phases of the project life cycle, as well as how future work can make the most out of it.     

基于Qt的一个服务器多个客户端的TCP通信

作为跨平台应用程序和UI开发框架,Qt被越来越多地用于应用程序的开发上。而网络程序又是软件开发的主要内容之一,文中对如何利用Qt开发TCP网络程序进行了研究。通过新建TCPServer类和TCPSocket类,分别继承自Qt里封装好的QTCPServer类和QTCPSocket类,完成服务器和套接字的建立与连接,从而实现了搭建针对多客户端的服务器。     

Data collection mode effect on feeling thermometer questions: A comparison of face-to-face and Web surveys

Feeling thermometer questions are widely used in political science research to estimate people’s attitudes and feelings toward a political object, like a political figure or an organization. Given the popularity of the feeling thermometer question in population surveys, more work is needed to explore the measurement of this question type. This study examines the data collection mode effect on feeling thermometers. Using the 2012 American National Election Studies, we find that the measurement of feeling thermometers is not exactly comparable between face-to-face and Web surveys. Face-to-face respondents tend to provide warmer feelings, while Web respondents give relatively more reliable responses in comparison. In both survey modes, respondents are most likely to select the response options that are verbally labeled although the effect is more striking in face-to-face than Web survey. The item nonresponse between these two modes does not differ in a meaningful way. This study ends by discussing future research directions on feeling thermometer questions.