Integrating Fuzzy C-Means and TOPSIS for performance evaluation: An application and comparative analysis

In this paper we introduce a multi-method multiple criteria approach for evaluating the performance of organizations. Performance analysis may include both strategic and operational performance, as well as financial and other less tangible factors. This paper introduces the use of Fuzzy C-Means and TOPSIS for organizational performance evaluation purposes. Using real company data and balanced scorecard accounting and performance dimensions the methodology is applied and evaluated. The predictive abilities of the technique from an organizational performance evaluation approach are evaluated using this data. One of the results from the illustrative application is that economic performance evaluation is not the best predictor of overall viability of some organizations, especially e-commerce based organizations.     

Enterprise security pattern: A model-driven architecture instance

To secure their information assets, organizations should seek support from enterprise security architectures. Security patterns are a good way to build and test new security mechanisms, but they have some limitations related to their usability. In previous work, we defined a new type of security pattern called Enterprise Security Pattern. The main objective of these patterns is to provide an instance of model-driven architecture, which offers a solution to recurring problems that have to do with information systems security. In recent years, the hiring of Software as a Service (SaaS) from cloud providers has become very popular. There seem to be many advantages of using these services, but organizations need to be aware of a variety of threats, as well as being prepared to handle them. In another work undertaken previously, we defined an enterprise security pattern called Secure Software as a Service (Secure SaaS), which the organizations could apply to protect their information assets when using SaaS. In this paper, we present different instances of the solution models of the enterprise security pattern Secure SaaS, aiming to verify the risks that an organization would assume if each of the instances were deployed. With this approach, we intend to show how the design decisions adopted when performing the transformations between the solution models can have a direct impact on the security provided by the pattern.     

A song of ice and vessels: Seasonal trends in the soundscape of the western arm of Lake Superior

The soundscapes of marine systems have been studied for decades to determine spatial and temporal patterns of biological, geological, and anthropogenic activity. However, comparatively little is known about freshwater soundscapes. Lake Superior is the world’s largest freshwater lake by surface area and home to a variety of aquatic animals. The Twin Ports of Duluth and Superior, located in the western arm of Lake Superior, are annually closed because of ice cover, providing a unique opportunity to explore sound levels in the absence of vessel traffic. Passive acoustic monitoring was conducted over 15 months between November 2018 and March 2020 to investigate seasonal patterns. Sound pressure levels were significantly lower (8 dB) at low frequencies (<100 Hz) during the winter and spring months (when ice cover increased). Quieter ambient sound pressure levels may provide an acoustic refuge to soniferous animals, especially those that vocalise during winter spawning. During the ice-free months, commercial shipping introduces a near continuous source of sound, increasing sound levels by up to 25 dB (at frequencies < 1,000 Hz). Climate change is expected to further reduce ice cover and thickness allowing the shipping season into the Twin Ports to be extended, thus warranting concern about the effect of noise from vessel activity on aquatic life. This study provides a baseline of the soundscape in the western arm of Lake Superior, against which scientists and environmental managers can assess future changes to this important habitat.     

碰撞检测技术研究综述

碰撞检测在图形学、仿真、动画和虚拟现实等技术中得到广泛的研究,这些研究具有十分重要的意义。文章对二维空间中多边形等面模型间相交,以及三维空间中多面体等体模型间干涉的角度对碰撞检测技术的研究和发展作了较为全面的论述,并对几种常用的碰撞检测算法进行了分析和比较,最后对碰撞检测算法的发展方向提出了几点建议。     

Predicting the influence of users’ posted information for eWOM advertising in social networks

Many social network websites have been aggressively exploring innovative electronic word-of-mouth (eWOM) advertising strategies using information shared by users, such as posts and product reviews. For example, Facebook offers a service allowing marketers to utilize users’ posts to automatically generate advertisements. The effectiveness of this practice depends on the ability to accurately predict a post’s influence on its readers. For an advertising strategy of this nature, the influence of a post is determined jointly by the features of the post, such as contents and time of creation, and the features of the author of the post. We propose two models for predicting the influence of a post using both sources of influence, post- and author-related features, as predictors. An empirical evaluation shows that the proposed predictive features improve prediction accuracy, and the models are effective in predicting the influence score.     

Reputation mechanism for e-commerce in virtual reality environments

The interest in 3D technology and virtual reality (VR) is growing both from academia and industry, promoting the quick development of virtual marketplaces (VMs) (i.e. e-commerce systems in VR environments). VMs have inherited trust problems, e.g. sellers may advertise a perfect deal but doesn’t deliver the promised service or product at the end. In view of this, we propose a five-sense feedback oriented reputation mechanism (supported by 3D technology and VR) particularly for VMs. The user study confirms that users prefer VMs with our reputation mechanism over those with traditional ones. In our reputation mechanism, five-sense feedback is objective and buyers can use it directly in their reputation evaluation of target sellers. However, for the scenarios where buyers only provide subjective ratings, we apply the approach of subjectivity alignment for reputation computation (SARC), where ratings provided by one buyer can then be aligned (converted) for another buyer according to the two buyers’ subjectivity. Evaluation results indicate that SARC can more accurately model sellers’ reputation than the state-of-the-art approaches.     

一种基于对等网络的云资源定位算法

提出用分布式哈希表(DHT)为每台云服务器产生一个唯一的节点编号,该编号作为网络拓扑结构、检索信息存储和信息查询共同的标志符,从而形成一个适合分布式计算的结构化P2P覆盖网.设计了新的拓扑和路由协议来解决云资源的常数跳定位问题.仿真实验表明,经典的P2P算法平均查找跳数与网络规模成正相关,无法依据云计算的实际需要人为地控制查找跳数;该算法的平均查找跳数与网络规模无关,随着网络规模的增大而趋向于设定值,可以解决云资源的常数跳定位问题.     

基于蚁群算法的遥感图像聚类方法

聚类分析是遥感图像非监督分类的有效方法,蚁群算法具有离散性和并行性的特点,蚂蚁觅食行为、蚂蚁堆积尸体行为和基于蚂蚁自我聚集行为的聚类算法是目前研究较为广泛的3种基于蚂蚁的仿生聚类算法.为验证上述3种算法的有效性,在对这3种聚类算法进行研究的基础上,针对遥感图像进行了聚类实验.实验结果表明,基于蚂蚁的聚类方法对图像的聚类分析是有效的,较传统的k均值和模糊C均值算法有一定优越性.     

CSCW环境下协同设计并发控制算法的研究

并发控制是CSCW环境下协同设计中复杂而又关键的问题之一,分析几何信息模型对象特征之间的联系,建立特征之间的相交和约束关系。运用模糊数学分析方法,提出一种优先权限分配算法,给出版本管理的解决方案。设计和实现针对共享对象协同操作的一致性维护和并发控制算法,并通过实例验证算法有效性。     

Full-scaled deep metric learning for pedestrian re-identification

Multimedia Tools and Applications - The pedestrian re-identification problem (i.e., re-id) is essential and pre-requisite in multi-camera video surveillance studies, provided the fact that...