E-recruitment and the benefits of organizational web appeal

This study examined the influences of website design on prospective job seekers. A total of 182 participants accessed and reviewed an online job ad. Afterwards, they rated: (a) the attractiveness of the ad’s formatting, (b) the usability of the website, (c) overall evaluations of the organization’s web appeal, (d) impressions of the organization, and (e) willingness to pursue employment with the hiring organization. Although both the formatting attractiveness and usability of online recruitment materials influenced participants’ inclinations to pursue jobs, formatting was more important than usability. Moreover, impressions of the employer mediated the relationship between satisfaction with the website and willingness to pursue employment with the organization. Overall, this research advances knowledge by applying signaling theory to the web-based recruitment domain and by testing a mediated relationship implied therein. In addition, this is the first study to introduce relative weights analysis to the recruitment literature.     

A collaborative filtering framework based on both local user similarity and global user similarity

Collaborative filtering as a classical method of information retrieval has been widely used in helping people to deal with information overload. In this paper, we introduce the concept of local user similarity and global user similarity, based on surprisal-based vector similarity and the application of the concept of maximin distance in graph theory. Surprisal-based vector similarity expresses the relationship between any two users based on the quantities of information (called surprisal) contained in their ratings. Global user similarity defines two users being similar if they can be connected through their locally similar neighbors. Based on both of Local User Similarity and Global User Similarity, we develop a collaborative filtering framework called LS&GS. An empirical study using the MovieLens dataset shows that our proposed framework outperforms other state-of-the-art collaborative filtering algorithms.     

Classification of Fuzzy Mathematical Morphologies Based on Concepts of Inclusion Measure and Duality

Mathematical morphology was originally conceived as a set theoretic approach for the processing of binary images. Extensions of classical binary morphology to gray-scale morphology include approaches based on fuzzy set theory. This paper discusses and compares several well-known and new approaches towards gray-scale and fuzzy mathematical morphology. We show in particular that a certain approach to fuzzy mathematical morphology ultimately depends on the choice of a fuzzy inclusion measure and on a notion of duality. This fact gives rise to a clearly defined scheme for classifying fuzzy mathematical morphologies. The umbra and the level set approach, an extension of the threshold approach to gray-scale mathematical morphology, can also be embedded in this scheme since they can be identified with certain fuzzy approaches.

Signal enhancement of surface plasmon resonance-based immunoassays for the allergen detection

A surface plasmon resonance (SPR) biosensor was used to determine the recombinant group 1 house dust mite allergen (rDer f1) in both HBS-EP buffer and fetal bovine serum (FBS). The monoclonal antibody was immobilized onto the CM5 sensor chip surface using an amine coupling method. The procedures of antibody immobilization and the subsequent primary and enhanced immunoassay were monitored in real time. The sensitivity for rDer f1 detection was remarkably improved by using intact polyclonal antibody as signal amplifying agent. Using this signal enhanced SPR immunosensor, rDer f1 in HBS-EP buffer and FBS was detected at a concentration of 15.4 and 32.1 ng/ml, respectively. The result demonstrates that SPR biosensor is a simple and reliable method for allergen detection.     

基于云理论的煤矿安全监测数据关联规则挖掘

本文主要研究如何运用关联规则来评价巷道瓦斯危险源的风险程度,作为分析煤矿事故危险源的补充.文章在云模型的基础上,针对煤矿安全监测数据的特点,提出一种基于云理论的属性空间软划分模型,然后在此基础上对Apriori算法进行了改进,提出适用于对煤矿安全监测数据进行关联规则挖掘的算法.最后通过实例测试,验证了改进算法的有效性.     

基于博弈理论的动态入侵响应

随着计算机网络的飞速发展,人们对互联网技术的依赖程度越来越高,因此确保网络系统的安全性也变得越来越重要.近年来,由于网络攻击事件的增多,入侵检测和响应技术越来越成为目前的研究热点之一.不过与其他安全技术得到广泛应用并取得良好的效果相比,入侵检测与响应的发展是滞后的.这一方面是由于入侵检测自身检测技术的限制,另一方面是由于目前的报警响应研究未能处理好系统的收益及攻击者策略变化等问题.针对上述第2个问题,提出了一种基于博弈理论的动态入侵响应DIRBGT模型.该模型一方面对攻击者和系统双方收益计算得比较全面,因此系统在报警响应后的收益得到了保证;另一方面还将攻击者可能的策略变化纳入模型当中,与单从系统一方推理最优响应的不稳定性相比,其最优解是稳定、可靠的.实验结果表明,DIRBGT模型有效提高了报警响应的准确性和效果.     

一种实时倾斜跟踪处理机设计

针对自适应光学系统中的倾斜跟踪回路,设计了以TMS320C6701数字信号处理器和XC2V1500现场可编程门阵列为核心处理器、基于PCI 总线的新型实时倾斜跟踪处理机平台。阐述了该平台的基本组成,根据点目标介绍了质心跟踪算法的软件实现。实验结果表明,该平台能满足倾斜跟踪回路的实时性要求。     

粗糙集理论和DT_SVM在Web信息过滤中的应用

针对Web信息过滤问题,提出一种将粗糙集理论和决策树SVM(DT_SVM)相结合进行数据分类、过滤的新方法。该方法运用改进的启发式相对属性约简算法消除冗余、降低样本空间维数,通过聚类和DT_SVM相结合来训练SVM,将多分类问题转化为二值分类问题,提高了训练速度及过滤精度。实验表明,该算法得到了较高的查全率、查准率,体现了将粗糙集理论与DT_SVM算法结合的优越性。     

基于DSP的计算机泄漏发射同步信息的提取

针对计算机行同步信号产生的泄露发射信息问题,提出一种提取该信息的相关检测算法,介绍利用Matlab仿真软件模拟提取行同步的策略,给出该算法在数字信号处理上的具体实现过程。在ICETEK-C6713-A EVM实验平台上进行同步信息截取实验,结果证明该方法具有较好的鲁棒性。     

基于分配器队列模糊控制的集群负载平衡

在分析和比较现有的基于分配器的服务器集群负载平衡方案的基础上,综合运用排队论知识和模糊控制理论,提出一种适合于小型Web服务器集群的模糊动态控制队列长度的负载分配器,该分配器在注重服务质量调控的同时,兼顾了集群的总体负载均衡。通过Visual C++编程构建模拟实验平台,验证了该方案的可行性。