Supporting community-based learning: case study of a geographical community organization designing its website

Community computing supports human - computer interaction among neighbours in geographical or place-based community organizations. Using a case study of such an organization, we investigate the process of designing their website. Our long-term participatory design approach, integrating developmental informal learning, allowed us to understand how this community organization adopts, evaluates, and sustains website technology. Based on our case study analysis, we present three design heuristics for developing community-based technology: align and afford new possibilities for participation, dynamically manage organizational knowledge and learning, and enhance social capital within community organizations and with the broader community.     

Community OR — Five Years of Organised Activities and Beyond

What has become known as Community Operational Research has been around in the UK for many years. The election of Jonathan Rosenhead as President of the UK OR Society in 1986–87 was the catalyst for bringing together and expanding activities which had been carried out largely by individuals working in isolation on a voluntary basis. The following five years have seen the establishment of the Community OR Unit at Northern College, the Centre for Community OR at Hull University and the Community OR Network, which supports the activities of volunteer OR workers across the UK. This paper reviews the range and types of work which have been undertaken by various practitioners. An assessment of the success of community OR is made and a number of issues which have arisen are discussed. Finally, given the diverse nature of community OR, its practice and practitioners, there is some discussion about the future of the area.     

Leveraging deployment models on low-resource devices for cloud services in community networks

Community networks are crowd-sourced IP networks that evolved into regional-scale computing platforms. This has led to adapting the cloud computing model for services that can operate and use computing resources inside a community network. The network and computing infrastructure is contributed by individuals, companies, organizations and maintained by its members. Community cloud devices are often low-capacity computing devices, such as home gateways or cabinet servers, with limited capabilities. These devices are used to install and operate specific personal or community services, but can be turned into multi-purpose execution environments applying machine or operating system (container) virtualization. However that requires addressing the problems of resource sharing in low-capacity devices, related to predictable performance and isolation. Our comparative analysis with the current infrastructure in community networks gives evidence about how devices can concurrently run multiple services, the trade offs between the number and resource requirements of services and the degradation of quality that services may suffer.     

Information,Community, and Action: How Nonprofit Organizations Use Social Media*

The rapid diffusion of “microblogging” services such as Twitter is ushering in a new era of possibilities for organizations to communicate with and engage their core stakeholders and the general public. To enhance understanding of the communicative functions microblogging serves for organizations, this study examines the Twitter utilization practices of the 100 largest nonprofit organizations in the United States. The analysis reveals there are three key functions of microblogging updates—“information,”“community,” and “action.” Though the informational use of microblogging is extensive, nonprofit organizations are better at using Twitter to strategically engage their stakeholders via dialogic and community‐building practices than they have been with traditional websites. The adoption of social media appears to have engendered new paradigms of public engagement.     

Wanted: Dead OR Alive—Ways of Using Problem-structuring Methods in Community OR

Problem structuring has often been seen as providing an appropriate framework for Community OR; from our point of view the question to raise is not how to choose the best method for any particular situation, but how to act on opportunities to use different methods in practice, i.e. making the process the central focus. In this paper we examine our use of problem-structuring methods in the context provided by postmodernist poststructuralist ideas in some Community OR (COR) case studies. In particular this paper will:

• • scrutinise the notion of 'problem' and suggest that it might open a larger space for action and choice to recast this in terms of issues;

• • show the applicability of issue-structuring methods in combination with other participatory methods, e.g. rapid appraisal and action methods, especially in the context of evaluation, which most of our case studies will be concerned with;

• • illustrate the possibilities of mixing and matching different parts of different issue structuring methods in practice.

In this way we demonstrate some ways in which the practice of OR can be revitalised, in particular through a re-conceptualisation of the notion of 'praxis'.     

Community Trolling: An Active Learning Approach for Topic Based Community Detection in Big Data

Community detection plays an important role in creation and transfer of information. Active learning has been employed recently to improve the performance of community detection techniques. Active learning provides a semi-automatic approach in a selective sampling of data. Based on this, a community trolling approach for topic based community detection in big data is proposed. Community trolling selectively samples the data relevant to the current context from polluted big data using active learning. Fine-tuned data is then used to study community and its sub-communities. Community trolling as a precursor to community detection leads to a reduction of the huge unreliable dataset into a reliable dataset and results in the better prediction of community elements such as important topics and important entities. Finally, the effectiveness of approach was evaluated by implementing it on a real world Tumbler dataset. The results illustrate that community trolling provides a richer dataset resulting in more appropriate communities.     

The Limits to Safety? Culture,Politics, Learning and Man–Made Disasters

Three interrelated questions are posed. First, what is the significance of culture for theories of institutional resilience and vulnerability? Second, what are the cultural possibilities for organizational safety and learning? Third, can a theory of institutional vulnerability to disaster and crisis be translated into one of practical resilience? The paper explores these issues with reference to Barry Turner’s seminal Man-Made Disasters model of system vulnerability together with more recent extensions and critiques. Attempts to move from this framework to a theoretical characterization of the ‘safe’ organization are outlined, as is parallel research on high reliability organizations. Critique of this work in the debate over the limits to safety in complex organizations has focused in particular upon the political processes which corrupt possibilities for organizational learning. It is argued that such political problems, and in particular that of blame in organizations, ultimately require political solutions. Examples are given of solutions in aviation monitoring systems.     

Community Detection Using Jaacard Similarity with SIM-Edge Detection Techniques

The structure and dynamic nature of real-world networks can be revealed by communities that help in promotion of recommendation systems. Social Media platforms were initially developed for effective communication, but now it is being used widely for extending and to obtain profit among business community. The numerous data generated through these platforms are utilized by many companies that make a huge profit out of it. A giant network of people in social media is grouped together based on their similar properties to form a community. Community detection is recent topic among the research community due to the increase usage of online social network. Community is one of a significant property of a network that may have many communities which have similarity among them. Community detection technique play a vital role to discover similarities among the nodes and keep them strongly connected. Similar nodes in a network are grouped together in a single community. Communities can be merged together to avoid lot of groups if there exist more edges between them. Machine Learning algorithms use community detection to identify groups with common properties and thus for recommendation systems, health care assistance systems and many more. Considering the above, this paper presents alternative method SimEdge-CD (Similarity and Edge between's based Community Detection) for community detection. The two stages of SimEdge-CD initially find the similarity among nodes and group them into one community. During the second stage, it identifies the exact affiliations of boundary nodes using edge betweenness to create well defined communities. Evaluation of proposed method on synthetic and real datasets proved to achieve a better accuracy-efficiency trade-of compared to other existing methods. Our proposed SimEdge-CD achieves ideal value of 1 which is higher than existing sim closure like LPA, Attractor, Leiden and walktrap techniques.     

Integrating hierarchical balanced scorecard with fuzzy linguistic for evaluating operating room performance in hospitals

Health care organizations are operating in a complex environment. The competitive and dynamic health care sector has spurred hospitals into delivering greater flexibility and quality of services. An efficient performance evaluation system is essential for controlling, monitoring and improving service quality in health care organizations. The performance evaluation of operating room (OR) is a useful work for managers to control the operational process of OR team so as to promote the performance. This paper explores the use of a management tool: balanced scorecard (BSC), which facilitates managers to meet multiple strategic goals, and fuzzy linguistic method for evaluating OR performance. BSC is a strategic planning and management system that is used extensively in business and industry, government and nonprofit organizations. First, a model is developed for measuring the acceptable performance of OR based on the interaction financial, customers, internal business process and learning and growth perspective. After that, BSC structure integrated with fuzzy linguistic is proposed for measuring and improving the service. The aim of this study was to build a performance evaluation system for OR and use a fuzzy linguistic to convert the subjective cognition of managers into an information entity and confirmation of improvement. This research results are able to help the organisation to evaluate and revise its strategy and generally to adopt modern management approaches in every day practise.     

基于博弈论的物联网语义社区演化模型

针对物联网环境下的语义社区演化问题,提出了一种基于博弈论的语义社区动态演化模型。首先给出物联网语义社区(Internet of Things Semantic Community,ITSC)的定义和特征;然后提出了一种基于动态博弈论的物联网语义社区演化模型,给出了物联网语义社区预处理算法(SCPA)、博弈节点选择算法(GNSA)、基于博弈的语义社区演化算法(GTEA)及算法的性能分析。通过实际网络社区数据的仿真实验表明,演化模型能够真实地反映物联网语义社区的演化规律。     

基于复杂网络社区结构的论坛热点主题发现

社区结构是复杂网络的重要特征之一,该文通过构造基于兴趣的论坛用户网络,成功地将社区结构发现的理论与方法应用于论坛热点主题的自动发现,提出了极大社区的概念和反复挖掘极大社区的方法,发现网络结构和论坛主题在反复挖掘过程中均几乎保持不变。仿真结果表明,提取效果令人满意。     

基于微粒群算法的组织评估优化方法及实例

社区结构是复杂网络的重要特征之一,该文通过构造基于兴趣的论坛用户网络,成功地将社区结构发现的理论与方法应用于论坛热点主题的自动发现,提出了极大社区的概念和反复挖掘极大社区的方法,发现网络结构和论坛主题在反复挖掘过程中均几乎保持不变.仿真结果表明,提取效果令人满意.     

Toward Better Understanding and Use of Business Intelligence in Organizations

This article provides valuable information on the chances and the possibilities of Business Intelligence applying in organizations. Three theories—the Resource-Based View, Maturity Models, and Critical Success Factors—were used to investigate Business Intelligence issues. They provided a comprehensive view on Business Intelligence. Using a semi-structured interview method, the results from 20 organizations applying Business Intelligence are presented. Finally, based on the analysis of the literature and on the qualitative surveys, conclusions for future research in Business Intelligence are provided.     

Nature and roles for community networks in the information society

This paper draws on the authors more than 10 years of involvement in the action research experience of the Milan Community Network. It discusses the roles that community networks play in the Information Society: starting from a neat characterization of “online community”, community networks are presented as ICT learning communities, as local online communities and as complementary to Digital Cities. Finally, critical insights into institutional aspects of community networks are considered from the perspective of their sustainability.     

基于ASSH框架的社区医院信息系统

医院信息化系统已成为当前医院运营必不可少的基础设施与技术支撑环境。社区医院信息化软件系统的功能完整、界面友好、操作方便的可提高社区医院的工作效率,大大促进社区医院的信息化发展。社区医院信息化管理系统,支持医院的行政管理与事务处理业务,减轻医务工作人员的劳动强度,辅助医院行政管理,提高医院的工作效率,从而使社区医院能够以较少的投入而获得更好的社会效益与经济效益。     

Standards-comparing, contrasting ISO 9001 and the SEI capabilitymaturity model

The Carnegie Mellon University Software Engineering Institutes's (SEI's) five-level framework for engineering practices in a successful software development organization and the International Organization for Standardization's ISO 9000 series of standards, which describes the key requirements for companies and organizations doing business in the European Community, are reviewed. The origins of the models are discussed, and the two models are compared and contrasted     

社区庭院中公共空间和私密空间的融合

社区不是一个单个空间的累加,而应该是一个适宜生活的场所。公共空间和私密空间是社区庭院的两个重要的因素。两者之间的关系对社区的生活有着很大的影响。社区感是对社区的认同,包括两个方面的内容,一个是归属感;一个是与社区内居民的情感。公共空间和私密空间的设计规划,会直接影响社区感的形成。     

Efficient multi-scale community search method based on spectral graph wavelet

Community search is an important problem in network analysis, which has attracted much attention in recent years. As a query-oriented variant of community detection problem, community search starts with some given nodes, pays more attention to local network structures, and gets personalized resultant communities quickly. The existing community search method typically returns a single target community containing query nodes by default. This is a strict requirement and does not allow much flexibility. In many real-world applications, however, query nodes are expected to be located in multiple communities with different semantics. To address this limitation of existing methods, an efficient spectral-based Multi-Scale Community Search method (MSCS) is proposed, which can simultaneously identify the multi-scale target local communities to which query node belong. In MSCS, each node is equipped with a graph Fourier multiplier operator. The access of the graph Fourier multiplier operator helps nodes to obtain feature representations at various community scales. In addition, an efficient algorithm is proposed for avoiding the large number of matrix operations due to spectral methods. Comprehensive experimental evaluations on a variety of real-world datasets demonstrate the effectiveness and efficiency of the proposed method.     

互联网宏观拓扑的社团发现

自然界中存在的大量复杂系统都可以通过复杂网络加以描述,社团结构是继小世界特性和无标度特性之后发现的最为重要的复杂网络特性。社团发现对理解互联网的宏观拓扑结构至关重要。针对互联网宏观拓扑的结构特性,基于边聚簇算法思想,设计了一个基于路由特征的社团发现算法,以互联网宏观拓扑中的探测边频为影响因子定义边相似性,改造边聚簇算法中的关键聚簇过程,以发现互联网宏观拓扑中的社团结构。实验结果表明,所提算法与原算法相比,具有更高的分割密度。进一步 以边介数替代探测边频,将该算法应用在其它类型网络中,同样取得了较好的效果。     

复杂网络重叠社团检测算法研究综述

社团结构是复杂网络的一项基本特性,对复杂网络中社团结构特别是重叠社团结构的检测,是复杂网络理论研究的一项重要且充满挑战的课题.对当前常用的重叠社团检测算法进行了分析和归纳,阐述每类算法特点,并介绍用于评价算法性能的一些基准图,对复杂网络重叠社团检测领域未来的研究方向提出了一些思考和建议.