Carbon dioxide—new uses for an old refrigerant

Carbon dioxide has been used as a refrigerant in vapour compression systems of many types for over 130 years, but it is only in the last decade that inventive minds and modern techniques have found new ways to exploit the uniquely beneficial properties of this remarkable substance. This paper traces the development of the old carbon dioxide systems, considers the technical, commercial and social reasons for their slow development and subsequent decline and examines the recent renaissance across a surprisingly broad range of applications, from trans-critical car air conditioners to low temperature industrial freezer plants. The paper then concentrates on industrial refrigeration systems, which were the basis of early developments in the period 1865–1885, but which have been somewhat overlooked in the current renaissance. The paper concludes with a review of possible future developments, indicating the areas of research and product development required to maximise the potential of the only non-toxic, non-flammable, non-ozone-depleting, non-global-warming refrigerant available for Rankine cycle vapour compression systems in the 21st century.     

基于商品目录的多层关联推荐算法

提出了一种多层关联推荐算法，结合商品目录，自动快速选择最佳的匹配粒度，进行基于频繁集的在线推荐。实验结果表明，算法大大提高了在线匹配的性能和质量，可成功应用到电子商务的个性化服务中。     

Android fine-grained permission control system with real-time expert recommendations

In current Android architecture design, users have to decide whether an app is safe to use or not. Expert users can make savvy decisions to prevent unnecessary privacy breach. However, inexperienced users may not be able to decide correctly. To assist inexperienced users to make a right permission granting decisions, we propose RecDroid. RecDroid is a crowdsourcing recommendation framework that facilitates a user-help-user environment regarding smartphone permission control. In this framework, the responses from expert users are aggregated and recommended to other users. We implement our prototype on Android platform and evaluated the system through simulation and real user study.     

Comprehension and acceptability of on-board traffic information: Beliefs and driving behaviour

Co-Drive on-board traffic information system is a complementary tool providing a dynamic management of transportation infrastructure and traffic as well as the diffusion of accurate real-time information about the road environment and motorists’ driving behaviour. The aim of this study was to examine drivers’ acceptability of Co-Drive by investigating the impact of traffic information provided via on-board display devices on motorists’ beliefs and behaviour.     

对市政公用工程CECS标准编制工作及若干问题的思考

该文首先诠释了CECS标准(推荐性标准)的基本内涵,结合作者的工作实际,论述了近年来市政公用工程的工作实践和主要成果,对CECS标准编制工作提出了若干思考,并指出了存在的问题和相关建议,以期推动我国工程建设标准化工作在祖国现代化建设中发挥更大的作用.     

基于热扩散影响力传播的社交网络个性化推荐算法

有针对性地为用户提供推荐,提高互联网信息利用率是个性化推荐系统的主要目标.文中基于热扩散传播概率模型,结合用户在社交网络中隐含的跟随关系,提出基于热扩散影响力传播的社交网络个性化推荐算法.首先,算法将现实生活中人与人的朋友关系转化为购物网络中用户与用户的跟随关系,构建异构信息网络图,计算用户之间的复合相似度.然后,利用基于热扩散概率模型模拟社会网络中影响力的传播过程,计算社交网络中用户的跟随概率分数并精确排序,筛选与目标用户相似的邻近用户.最后,根据目标邻近用户对各个产品的评分,将评分较高、具有潜在兴趣的产品推荐给目标用户,实现个性化的用户推荐.在公开数据集上与现有的个性化推荐算法进行对比,实验表明,文中算法具有较好的精确度和多样化的推荐效果.     

Enhancing scalability and accuracy of recommendation systems using unsupervised learning and particle swarm optimization

Recommendation system has been a rhetoric area and a topic of rigorous research owing to its application in various domains, from academics to industries through e-commerce. Recommendation system is useful in reducing information overload and improving decision making for customers in any arena. Recommending products to attract customers and meet their needs have become an important aspect in this competitive environment. Although there are many approaches to recommend items, collaborative filtering has emerged as an efficient mechanism to perform the same. Added to it there are many evolutionary methods that could be incorporated to achieve better results in terms of accuracy of prediction, handling sparsity as well as cold start problems. In this paper, we have used unsupervised learning to address the problem of scalability. The recommendation engine reduces calculation time by matching the interest profile of the user to its partitioned and even smaller training samples. Additionally, we have explored the aspect of finding global neighbours through transitive similarities and incorporating particle swarm optimization (PSO) to assign weights to various alpha estimates (including the proposed α₇) that alleviate sparsity problem. Our experimental study reveals that the particle swarm optimized alpha estimate has significantly increased the accuracy of prediction over the traditional methods of collaborative filtering and fixed alpha scheme.     

Effects of Online Comments on Smokers' Perception of Antismoking Public Service Announcements

On YouTube antismoking PSAs are widely viewed and uploaded; they also receive extensive commentary by viewers. This study examined whether such evaluative comments with or without uncivil expressions influence evaluations by subsequent viewers. Results showed PSAs with positive (i.e. antismoking) comments were perceived by smokers as more effective than PSAs with negative (prosmoking) comments. Smokers in the no‐comment condition gave the highest perceived effectiveness score to PSAs. Smokers' readiness to quit smoking moderated the effect of comments on PSA evaluation. Smokers reading negative uncivil comments reported more negative attitude toward quitting and a lower level of perceived risk of smoking than those reading negative civil comments but positive civil and positive uncivil comments did not elicit different responses.     

MuseumFinland—Finnish museums on the semantic web

This article presents the semantic portal MuseumFinland for publishing heterogeneous museum collections on the Semantic Web. It is shown how museums with their semantically rich and interrelated collection content can create a large, consolidated semantic collection portal together on the web. By sharing a set of ontologies, it is possible to make collections semantically interoperable, and provide the museum visitors with intelligent content-based search and browsing services to the global collection base. The architecture underlying MuseumFinland separates generic search and browsing services from the underlying application dependent schemas and metadata by a layer of logical rules. As a result, the portal creation framework and software developed has been applied successfully to other domains as well. MuseumFinland got the Semantic Web Challence Award (second prize) in 2004.     

基于H.323的Intranet集成服务实现的探讨

本文以在Intranet上实现提供基于H.323标准的集成服务为目标,首先介绍了集成服务的内容,随后重点讨论了如何在遵从H.323标准的前提下,利用网守的控制功能区分实时通信和存储转发的服务要求,并进行H.323终端的呼叫管理。