Reaching for the “cloud”: How SMEs can manage

Cloud computing is an emerging new computing paradigm for delivering computing services. The approach relies on a number of existing technologies e.g., the Internet, virtualization and grid computing. However, the provision of this service in a pay-as-you-go way through the popular medium of the Internet renders this computing service approach unique compared with currently available computing service modalities. This article highlights some aspects of this uniqueness and also explores some of the concerns that might be preventing some companies from adopting it. Notwithstanding these concerns, it is argued in this article that cloud computing is likely to prove commercially viable for many small and medium enterprises (SMEs) due to its flexibility and pay-as-you-go cost structure, particularly in the current climate of economic difficulties. A case study of a cloud experience by a British SME is also presented in this study in order to further highlight the perceived values of cloud computing in terms of cost and efficiency for real small enterprises.     

Making use of cloud computing for healthcare provision: Opportunities and challenges

Cloud or utility computing is an emerging new computing paradigm designed to deliver numerous computing services through networked media such as the Web. This approach offers several advantages to potential users such as “metered” use (i.e., pay-as-you-go) which offers scalability, online delivery of software and virtual hardware services (e.g., collaboration programmes, virtual servers, virtual storage devices) which would enable organizations to obviate the need to own, maintain and update their software and hardware infrastructures. The flexibility of this emerging computing service has opened many possibilities for organizations that did not exist before. Among those organizations are those engaged in healthcare provision. The aim of this article is to shed some light on this development and explore the potential (and future) of cloud computing in contributing to the advancement of healthcare provision. A small case study will also be presented and discussed.     

浅谈云计算在网络教育中的应用——以Google操作系统Chrome OS为例

网络在远程教育中的应用让任何人、在任何时间、任何地点、从任何章节开始学习任何课程,其对教育带来的变革前所未有。只是网络带来这些便利的同时,也面临着一些问题,如师生交流面临时空障碍,设备费用高,而新兴的云计算,为解决这一问题提供了机会。文章以Chrome OS为例就云计算在远程教育中的应用进行探究。     

基于Web3.0的信息资源共建共享应用研究及实现

Web3.0是Web1.0与Web2.0的继承与发展,文章首先介绍了Web3.O及其相关概念,在此基础上,分析了Web3.0中所采用的语义网的概念及其主要相关技术,并将其与现有的实例相结合,探讨了如何建立一个基于Web3.0技术的信息共享平台。     

基于知识图谱的区块链与云会计比较及融合研究

区块链与云会计都是被会计界高度关注的新会计信息技术方向,文章应用Citespace科学知识计量发现中国区块链研究从金融领域开始正在向会计领域发展,中国云会计研究持续7年并具有长期研究热度。云会计与区块链的设计理念、竞争程度、成本节约点、技术优势等存在不同,云会计特别适合中国中小公司基数大的会计主体特点。区块链与云会计的理念融合有助于提升云会计的会计数据功能、会计信息经济职能、数据安全与伦理、会计治理模式、会计监督创新等。     

考虑服务投资影响的SaaS云外包激励机制

客户企业在实施SaaS云外包时,面临因效率参数不可观测所引发的云服务提供商（Cloud Service Provider,CSP）道德风险问题。针对该问题,在考虑服务投资影响效率参数分布情况下,以客户企业期望收入最大化为目标,应用委托-代理理论设计了云外包激励机制,并对合约性质及激励效果进行了分析。研究表明,激励相容性的自我实施条件由效率参数改进的边际效用、努力的边际负效用及边际产出决定;最优努力水平是效率参数的减函数;服务投资与效率参数进一步改进的条件概率间存在一定的相关关系;最优激励机制可由固定服务报酬及收益共享构成的线性合约表示。     

云教育视域下学习范式的转型

云教育主要是指在云技术平台的开发及其在教育领域中的应用,将各种教学与学习软件推向云端,教育部门、学校、教师、学生、家长及其他教育工作者,这些不同身份的人群,只要一个登陆账号就能进入虚拟界面,可以在同一个平台上,根据权限去进行不同的工作,能享受到教学、管理、学习、娱乐、分享、互动交流等全部应用。云教育视域下需要学习哲学、学习文化、学习方式以及学习评价的转型。为此,需要形成云教育理念,进一步解决云教育和云学习的技术性问题并深入开发云教育资源。     

Application of uncertainty reasoning based on cloud model in time series prediction

Time series prediction has been successfully used in several application areas, such as meteorological forecasting, market prediction, network traffic forecasting, etc., and a number of techniques have been developed for modeling and predicting time series. In the traditional exponential smoothing method, a fixed weight is assigned to data history, and the trend changes of time series are ignored. In this paper, an uncertainty reasoning method, based on cloud model, is employed in time series prediction, which uses cloud logic controller to adjust the smoothing coefficient of the simple exponential smoothing method dynamically to fit the current trend of the time series. The validity of this solution was proved by experiments on various data sets. Project (No. 2001AA112030) supported by the National Hi-Tech Development Program (863) of China