Do different reputation systems provide consistent signals of seller quality: a canonical correlation investigation of Chinese C2C marketplaces

In recent years, consumer-to-consumer (C2C) marketplaces such as eBay and Taobao have adopted a component rating system, and run it simultaneously with but independent of a binary rating system. This paper investigates the extent to which binary rating and component rating systems are able to provide consistent signals of sellers?? quality, focusing on the reputation system design under the Chinese context. Using field data from Taobao, we performed canonical correlation analyses and found that the reputation signals of the two systems are generally correlated. As expected, negative and neutral ratings accurately reveal buyer dissatisfaction. Our results, however, show that positive ratings exhibit negative correlations with the three component ratings (i.e., item-as-described, customer service, and on-time delivery), suggesting that large numbers of positive ratings on Taobao may encourage trust in the platform but do not help to choose credible sellers. Our results elucidate the role of cultural difference in explaining the negative relationship in China and provide important implications for the design of reputation systems.     

Enhancing collaborative filtering by user interest expansion via personalized ranking

Recommender systems suggest a few items from many possible choices to the users by understanding their past behaviors. In these systems, the user behaviors are influenced by the hidden interests of the users. Learning to leverage the information about user interests is often critical for making better recommendations. However, existing collaborative-filtering-based recommender systems are usually focused on exploiting the information about the user's interaction with the systems; the information about latent user interests is largely underexplored. To that end, inspired by the topic models, in this paper, we propose a novel collaborative-filtering-based recommender system by user interest expansion via personalized ranking, named iExpand. The goal is to build an item-oriented model-based collaborative-filtering framework. The iExpand method introduces a three-layer, user-interests-item, representation scheme, which leads to more accurate ranking recommendation results with less computation cost and helps the understanding of the interactions among users, items, and user interests. Moreover, iExpand strategically deals with many issues that exist in traditional collaborative-filtering approaches, such as the overspecialization problem and the cold-start problem. Finally, we evaluate iExpand on three benchmark data sets, and experimental results show that iExpand can lead to better ranking performance than state-of-the-art methods with a significant margin.     

Analysis and control of general logical networks – An algebraic approach

Since Boolean network is a powerful tool in describing the genetic regulatory networks, accompanying the development of systems biology, the analysis and control of Boolean networks have attracted much attention from biologists, physicists, and systems scientists. From mathematical point of view, the dynamics of a Boolean (control) network is a discrete-time logical dynamic process. This paper surveys a recently developed technique, called the algebraic approach, based on semi-tensor product. The new technique can deal with not only Boolean networks, which allow each node to take two values, but also k-valued networks, which allow each node to take k different values, and mix-valued networks, which allow nodes to take different numbers of values.The paper provides a comprehensive introduction to the new technique, including (1) mathematical background of this new technique – semi-tensor product of matrices and the matrix expression of logic; (2) dynamic models of Boolean networks, and general (multi- or mix-valued) logical networks; (3) the topological structure of Boolean networks and general networks; (4) the basic control problems of Boolean/general control networks, which include the controllability, observability, realization, stability and stabilization, disturbance decoupling, identification and optimization, etc.; (5) some other related applications.     

Network traffic classification via HMM under the guidance of syntactic structure

Network traffic classification is the basis of many network technologies including intrusion detection, traffic scheduling, and quality of service. Given the limitations of existing classification approaches based on the port number, the packet-payload and statistical characteristics of network traffic, in this paper we propose a novel classification method via a hidden Markov model. With the analysis about the time series characteristics and statistical properties of network traffic, we use a hidden Markov model to model for a type of traffic under the guidance of syntactic structure of it. And then a classification approach is presented based on the model. Experiment results on several typical network applications indicate that the combination of time series characteristics and the statistical properties not only make the established model more precise, but also improve the accuracy of network traffic classification.     

封闭循环TEA CO2激光器用催化剂的实验研究

在不同的催化剂和不同温度的条件下,用磁氧分析仪监测了封离型TEA C0₂激光器中O₂含量随时间或脉冲次数的变化。对实验现象进行了分析。对几种催化剂的特性给出了详细的比较。     

基于ADSP-BF561的视频图像采集系统设计

校本文基于ADI公司BF561的嵌入式处理器,以OV7660 CMOS图像传感器为视频图像输入源,以uClinux为操作系统,采用先进的JPEG2000图像压缩算法,设计了一种视频图像采集系统的实现方案,实现了视频图像的采集,处理及传输。测试结果表明,在上位机端可以看到比较清晰的图像。     

基于运动信息自适应的快速运动估计算法

UMHexagonS是H.264视频编码标准中所采用的快速整像素运动估计算法,但在许多实时场景的应用中,该算法还明显存在搜索点数过多、搜索速度较慢的缺憾,急需进一步的改进和优化。在UMHexagonS算法的基础上,提出一种基于运动信息自适应的快速运动估计算法。使用动态搜索窗为不同尺寸的块自适应地分配预测搜索窗;根据当前块的运动剧烈程度选择运动类型自适应的搜索方案;通过分析实际运动序列水平、垂直方向的偏向特性依次采用带方向的十字型搜索和自适应的矩形—菱形搜索;利用预测运动矢量的方向信息采用自适应的多层次八边形区域搜索;并依据块的尺寸大小采用自适应的六边形搜索。实验结果表明,本文算法相比于UMHexagonS算法而言,图像的峰值信噪比(PSNR)平均提高了0.0125 dB,同时运动估计时间减少了13%32%,其场景自适应能力和实时性能都得到了很大的增强。     

一种基于EPID的安全OA系统

文章对OA系统中存在的安全问题进行了讨论,引人了一种新的基于远程匿名身份认证EPID模式,它能通过保存设备拥有者私密信息的硬件设施进行身份鉴定。一个嵌入EPID私密的硬件设备可以向远程机构证实它的有效性,而不必暴露自己的身份和其他私密信息。可以撤消一个签名的EPID私钥,即使不知道密钥的身份。同时,把EPID和其它的一些方法进行了对比。     

浅谈中等职业学校计算机基础教学

当今社会对中职学校毕业生的计算机应用能力要求越来越高,计算机技术水平的高低以及计算机应用能力的强弱,已经成为今天衡量中职学校毕业生质量和水平的重要尺度之一。而目前计算机基础教学存在教学内容过分单一、教学手段落后等弊端,为了解决这些问题,汲取多年计算机基础教学的实践经验,针对新形式下计算机基础课程的课程体系、教学内容和教学方法的改革进行了探讨。     

温度对Ni—P化学镀层结合力影响的研究

用弯曲法、划痕法研究了镀后加热温度对Ni-P化学镀层结合力的影响,结果表明:镀后退火温度越高,镀层结合力越好,但温度过高时,镀层硬度将下降。用金相观察及电子探针分析,探讨了镀后退火温度影响结合力的机理。结果指出:退火时将在镀层和基体界面上发生Ni与Fe的互扩散,形成Ni-Fe合金扩散层,从而提高了结合力。为了能在保证镀层硬度的前提下提高结合力,本文提出了二次镀覆的设想,获得较好试验结果。