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。     

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。     

MooseFS热备元数据节点设计与实现

针对MooseFS元数据节点的单点故障问题，对MooseFS源码进行改造，为其增加一个热备的备元数据节点，并通过主备之间同步元数据，备节点回放操作日志等技术使得备元数据节点内存中的元数据时刻跟主元数据节点保持一致。当主元数据节点发生故障切换到备元数据节点后，备元数据节点无需从本地加载元数据即可快速接替主元数据节点对外提供服务。测试结果表明，备元数据节点本地和内存中的元数据均与主元数据节点保持一致，且故障恢复时间小于1 s。     

An E-Business Event Stream Mechanism for Improving User Tracing Processes

With the rapid development in business transactions, especially in recent years, it has become necessary to develop different mechanisms to trace business user records in web server log in an efficient way. Online business transactions have increased, especially when the user or customer cannot obtain the required service. For example, with the spread of the epidemic Coronavirus (COVID-19) throughout the world, there is a dire need to rely more on online business processes. In order to improve the efficiency and performance of E-business structure, a web server log must be well utilized to have the ability to trace and record infinite user transactions. This paper proposes an event stream mechanism based on formula patterns to enhance business processes and record all user activities in a structured log file. Each user activity is recorded with a set of tracing parameters that can predict the behavior of the user in business operations. The experimental results are conducted by applying clustering-based classification algorithms on two different datasets; namely, Online Shoppers Purchasing Intention and Instacart Market Basket Analysis. The clustering process is used to group related objects into the same cluster, then the classification process measures the predicted classes of clustered objects. The experimental results record provable accuracy in predicting user preferences on both datasets.     

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。     

Modelling multiphasic starch digestograms: an objective procedure for slope discontinuities†

Digestograms of 101 published in vitro starch digestion were used to investigate slope discontinuities. Polynomial equations (1 to 3 orders) adequately described the first derivative of the digestograms. The derivative(s) of the equations revealed critical point(s). The third-order equation described (P ≤ 0.05) 17% of the digestograms as triphasic, the second- and third-order equations identified (P ≤ 0.05) 32% as biphasic, while 51% exhibited (P ≤ 0.05) monophasic digestograms. Using nonlinear regression with practical constraints, a modified first-order kinetic model (D_t = D₀ + D_∞−0 {1 − exp [−K t]}) described (r² > 0.56, P ≤ 0.05) segments 1–3 of the digestograms. Rapid-slow and slow-rapid digestion rates were obtained, and maximum digestible starches, D_∞, ≤100g/100g (dry) starch for an in-depth understanding of starch digestion. This is the first comprehensive objective approach for slope discontinuities in starch digestograms for consistency in modelling digestograms that advances starch digestion studies.     

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.     

安全管理平台中基于云计算的日志分析系统设计

安全管理平台(SMP)是实现安全管理工作常态化运行的技术支撑平台,在实际应用中需要实时处理来自安全设备所产生的海量日志信息。为解决现有SMP中海量日志查询效率低下的问题,设计基于云计算的SMP日志存储分析系统。基于Hive的任务转化模式,利用Hadoop架构的分布式文件系统和MapReduce并行编程模型,实现海量SMP日志的有效存储与查询。实验结果表明,与基于关系数据的多表关联查询方法相比,该系统使得SMP日志的平均查询效率提高约90%,并能加快SMP集中管控的整体响应速度。     

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.