游客体验真实性在三峡旅游产品商业化中的应用

旅游体验时代,游客的体验越来越备受关注,但是随着商业化的开发,旅游产品的真实性-受到了破坏,进而游客体验的真实性也受到影响,然而,游客体验的真实性与旅游产品的商业化有着密不可分的联系。本文从影响游客真实性体验的因素出发,探讨游客体验真实性对旅游产品商业化的重要作用,提高游客体验真实性并合理控制旅游产品的商业化,从而提高游客的满意度并实现三峡旅游业的可持续发展。     

高精度冷轧不锈钢管生产

介绍了用ＬＤ型冷轧管机生产高精度冷轧不锈钢管的经验和质量保证措施。     

How individual characteristics influence people's evaluation towards information technology in different contexts

Prior research on technology acceptance has primarily focused on understanding why individuals accept a particular technology, while very little is known about how individuals evaluate various types of technology, especially when they have different levels of experiences. In this research, we try to understand how individual characteristics influence their evaluation towards different types of technology. To test the research model empirically, a laboratory experiment was conducted, and the resulting data was used to test both measurement and structural models. Based on the statistic results, we found that people's need for cognition and originality cognitive style had different effects on technology evaluation in various contexts. This study sheds light on the rarely studied evaluation aspect of the technology acceptance. The main contribution of this study is that people employ different mechanisms to evaluate technology in different contexts, and individual characteristics play an important role in influencing technology evaluation.     

Eliciting positive user experiences with self-service kiosks: pursuing possibilities

Although the prominent concept of the last decade – user experience – maintains its significance in diverse disciplines, especially design, its focus has changed to eliciting positive user experiences by pursuing new possibilities for consumer products rather than by solely seeking solutions to existing problems. Designers continue to aim for rich user experiences with a variety of products, but have neglected self-service (interactive) kiosks. Hence, this paper, after giving a brief overview of the positive psychology literature, demonstrates the dimensions of positive user experiences with self-service kiosks through an empirical study conducted on coffee vending machines and automated tellers.     

Visual Assessment of Alleged Plagiarism Cases

We developed a visual analysis tool to support the verification, assessment, and presentation of alleged cases of plagiarism. The analysis of a suspicious document typically results in a compilation of categorized “finding spots”. The categorization reveals the way in which the suspicious text fragment was created from the source, e.g. by obfuscation, translation, or by shake and paste. We provide a three‐level approach for exploring the finding spots in context. The overview shows the relationship of the entire suspicious document to the set of source documents. A glyph‐based view reveals the structural and textual differences and similarities of a set of finding spots and their corresponding source text fragments. For further analysis and editing of the finding spot's assessment, the actual text fragments can be embedded side‐by‐side in the diffline view. The different views are tied together by versatile navigation and selection operations. Our expert reviewers confirm that our tool provides a significant improvement over existing static visualizations for assessing plagiarism cases.     

基于用户忠实度的应用层DDoS防御模型

针对应用层DDoS(application layer DDoS,App-DDoS)攻击,提出一种基于用户忠实度的ULDM(user loyalty defense model)防御模型,其根据用户对网站的忠实程度来区分正常用户和攻击用户。用户忠实度包含访问频率忠实度和行为忠实度,行为忠实度又包括历史行为忠实度和当前行为忠实度。从用户长期以来在请求频率和请求负载两方面的表现对用户行为进行评估,得到用户行为忠实度,根据用户长期以来对网站的访问频率得到用户访问频率忠实度;通过调度模块根据用户忠实度对请求进行调度。模拟实验验证了该模型的有效性。     

基于正交实验设计的人工蜂群算法

人工蜂群算法是近年来提出的较为新颖的全局优化算法,已成功地应用于解决不同类型的实际优化问题.然而在该算法及相关的改进算法中,侦察蜂通常采用随机初始化的方法来生成新食物源.虽然这种方法较为简单,但易造成侦察蜂搜索经验的丢失.从算法搜索过程的内在机制出发,提出采用正交实验设计的方式来生成新的食物源,使得侦察蜂能够同时保存被放弃的食物源和全局最优解在不同维度上的有益信息,提高算法的搜索效率.在16个典型的测试函数上进行了一系列实验验证,实验结果表明:1) 该方法能够在基本不增加算法运行时间的情况下,显著地提高人工蜂群算法的求解精度和收敛速度;2) 与3种典型的变异方法相比,有更好的整体性能;3) 可作为提高其他改进人工蜂群算法性能的通用框架,具备有良好的普适性.     

基于键盘行为数据的用户身份识别

用户击键行为作为一种生物特征,具有采集成本低、安全性高的特点。然而,现有的研究方法和实验环境都是基于实验室数据,并不适用于极度不平衡的真实数据。比如,在实验室数据上效果出色的分类算法在真实数据上却无法应用。针对此问题,提出了基于真实击键行为数据的用户识别算法。该方法将聚类算法和距离算法结合起来,通过比较新来的击键行为和历史击键行为相似度以实现用户识别。实验结果表明,该算法在100名用户的3015条真实击键记录组成的数据集上准确率达到88.22%,在投入实际应用后,随着样本集的增大算法的准确率还可以进一步提升。     

基于混合机制的Kerberos安全性增强方案

针对Kerberos协议的弱点和安全性问题,提出了一个基于混合加密机制的Kerberos改进方案,目的是防范口令攻击和内部攻击。给应用服务器和AS服务器分配公钥和私钥,用户与服务器之间的会话密钥由DH密钥交换生成。给出了改进后的 Kerberos 协议的六个步骤,并对安全性进行分析。分析结果表明,新方案能够增强Kerberos协议的安全性,而且比公钥加密机制高效。     

基于Hadoop的用户搜索行为分析

用户搜索网页行为的分析是目前信息搜索的研究的热点,本文针对云计算中的并行计算搜索存在的检索速度慢,效率低等缺点提出了一种基于Hadoop海量用户搜索网页行为的方法,该方法主要是在网页PageRank算法的基础上,将用户影响因子,时间向量和网页相关性因素加入到算法中,使得改进后的PageRank算法得到了提高,进一步提高用户搜索网页行为的效率,实验中通过使用优酷实验室中的查询日志分析证明了本文的算法具有良好的效果,并对云计算中的用户行为分析具有一定的指导意义.