云会计环境下AIS可信需求演化影响研究

在动态多变的云会计环境下,多种因素的综合作用将使AIS可信需求不断发生演化。文章建立了一个云会计环境下的AIS可信需求演化影响框架,并从云会计供应商、企业用户及第三方机构三个方面深入分析AIS可信需求演化的影响,以部分可信属性及用户需求为例进行阐述,为进一步研究提供参考。     

NET框架实现基于XML的串行化

目前越来越多的设备开始支持XML,这使得WEB开发商可以XML来建立丰富的多层WEB应用。微软已经意识到串行化数据的重要性,因此在.NET框架中包含了命名空间System.Runtime.Serialization和System.Xml.Serialization以提供串行化功能,为用户自己编写串行化方法提供了一个框架。本文主要分析在.NET环境下实现将一个类对象串行化并能自定义串行化后的格式的常规方法及相关知识点。     

数字图书馆中自适应个性化服务研究

个性化服务是数字图书馆中最重要的功能之一,数字图书馆中的自适应个性化服务很好地解决了日益严重的"信息过载"问题,本文首先针对数字图书馆中用户的特性,分析了数字图书馆中自适应个性化服务需求,其次,设计了基于情景感知的自适应个性化服务框架,可以根据用户所处的情境,快速准确地为用户推送所需要的资源,最后,讨论了自适应个性化服务实现过程中应该解决的几个关键问题。     

一种高可用、自容错及自恢复Web Service集成软件调用技术

Web Service作为SOA架构中常见的服务实现方式,通常在服务提供方实现高可用、性能管理以及容错性,成本高且实施难度大,文章提出了一种在消费方用软件实现Web Service负载管理和流量控制的调用框架,解决了不同规模的应用系统集成时造成的系统冲击问题,并实现了Web Service调用的自容错和自恢复,具有低成本和实施简单的特点,具有较高的实用价值。     

基于REST网上订餐系统的设计

随着网络技术的发展,网上订餐是继网络购物之后的另一个新兴业。网上订餐一方面以其优越的便捷性迅速打开了中国餐饮业的市场,另一方面降低了餐厅经营者的硬性条件。以REST为软件架构,Python为编程语言,根据用户的需求分析,设计可以实现网上订餐功能。     

以《网络课程设计与实践》为例的自适应学习系统用户模型研究

自适应学习系统本质上是一种个性化的学习支持系统,随着网络教育的发展,要真正实现以学习者为主体的远程教育,势必要有一个能为用户提供个性化学习服务的网络学习平台。本文以《网络课程设计与实践》这门课为例,从用户的学习风格、认知水平和兴趣偏好几方面研究自适应学习系统的用户模型。为自适应学习系统的设计提供理论基础。     

基于QoS优化的面向服务流程分解方法

面向服务的业务流程分解是构建面向服务系统的前提。文章分析了复杂业务过程的QoS因素及其计算,提出一种基于QoS的服务流程分解方法。该方法首先应用OWL-S(Ontology Web Language for Services)进行流程建模,再对OWL-S模块进行归并、组合,将复杂业务流程转化成由几种典型结构构成的服务组合形式,通过服务组合和流程QoS约束的计算,实现流程分解的优化。最后通过一个汽车贷款审批的实例验证了分解方法的有效性。     

关于动态竞争环境下企业战略能力的研究

当今世界,企业所面临的生存环境越来越复杂多变,企业如何在动态的竞争环境中做的比其他企业更出色,已成为企业经营成败的关键,而对企业战略能力的研究为我们提供了一个新的视角。我们在分析企业战略能力内涵基础上,提出研究企业战略能力的基本框架,并对研究过程中的关键环节做了必要的分析,为企业在动态环境中获取持续的竞争优势提供了借鉴和帮助。     

基于Qt Test的自动化单元测试

Qt是跨平台的应用软件开发框架,Qt Test是Qt框架的单元测试库。基于Qt Test的单元测试可以进行功能和性能测试。持续集成系统可以自动化单元测试的构建、部署、运行和结果统计过程。工程实践表明:基于Qt Test的单元测试与持续集成系统的结合可以降低软件的缺陷率,优化软件架构的设计,提高软件工程的自动化。     

人工智能背景下大学日语翻译管理系统实践研究

文章提出并设计了一种在日语翻译互动教学管理平台,该平台采用ASP.NET处理逻辑功能,采用Web Service实现业务统计,以用户层、逻辑层、数据层与物理层四个结构层及运维体系和安全体系搭建整体框架,基于B/S模式实现网络拓扑结构,通过登录模块、课程管理模块和学生管理模块实现多项功能。应用测试的结果表明,该平台功能完善,在实现了师生互动式教学模式的基础上增强了高校信息化网络教学的实效性,相比其他系统具有一定的功能和性能优势。     

A service governance mechanism based on process mining for cloud-based applications

ABSTRACT

With the widely use of cloud computing in enterprise information systems, service governance becomes critical for an enterprise to adapt to a changing business environment. In order to provide a dynamic strategy for continuous service governance, in this paper a comprehensive service analysis solution is proposed to address both design time and run-time requirements for cloud applications. First, a process-centric Semantic Scene Model is composed to combines static business requirements with dynamic execution information. Then service analysis is conducted referring both to the business process mining results from event logs and the Semantic Scene Model given by business model designers. Service governance strategies are generated from the service analysis results and are performed to qualitatively classify the Quality of Service (QoS) of the services. Finally the approach is verified with a transportation logistics service application in a cloud platform. The result shows that our method can get continuous service governance through combining business processes with run-time service analysis.     

Pricing the cloud: a QoS-based auction approach

ABSTRACT

Cloud computing is an evolutionary technology that offers on-demand resources and elastic services through the Internet. Most providers adopt fixed-price mechanisms (e.g. pay-as-you-go). However, a few providers have recently employed auction-like approaches to price cloud services. Meanwhile, cloud consumers pay more attention to Quality of Service (QoS) such as availability, which measures how well a service is performed. This paper proposes a novel auction approach that can efficiently allocate resources according to customers’ QoS preferences. The QoS-based pricing can generate more revenue than a fixed-price strategy. This research lies at the intersection of cloud computing, economics, and information systems.     

QaaS (quality as a service) model for web services using big data technologies

Quality of service (QoS) determines the service usability and utility and both of which influence the service selection process. The QoS varies from one service provider to other. Each web service has its own methodology for evaluating QoS. The lack of transparent QoS evaluation model makes the service selection challenging. Moreover, most QoS evaluation processes do not consider their historical data which not only helps in getting more accurate QoS but also helps for future prediction, recommendation and knowledge discovery. QoS driven service selection demands a model where QoS can be provided as a service to end users. This paper proposes a layered QaaS (quality as a service) model in the same line as PaaS and software as a service, where users can provide QoS attributes as inputs and the model returns services satisfying the user’s QoS expectation. This paper covers all the key aspects in this context, like selection of data sources, its transformation, evaluation, classification and storage of QoS. The paper uses server log as the source for evaluating QoS values, common methodology for its evaluation and big data technologies for its transformation and analysis. This paper also establishes the fact that Spark outperforms the Pig with respect to evaluation of QoS from logs.     

Achieving runtime adaptability through automated model evolution and variant selection

Dynamically adaptive systems propose adaptation by means of variants that are specified in the system model at design time and allow for a fixed set of different runtime configurations. However, in a dynamic environment, unanticipated changes may result in the inability of the system to meet its quality requirements. To allow the system to react to these changes, this article proposes a solution for automatically evolving the system model by integrating new variants and periodically validating the existing ones based on updated quality parameters. To illustrate this approach, the article presents a BPEL-based framework using a service composition model to represent the functional requirements of the system. The framework estimates quality of service (QoS) values based on information provided by a monitoring mechanism, ensuring that changes in QoS are reflected in the system model. The article shows how the evolved model can be used at runtime to increase the system's autonomic capabilities and delivered QoS.     

A method towards Web service combination for cross-organisational business process using QoS and cluster

How to quickly combine various Web services to support cross-organisational business processes is the key technical problem in service computing. Because of the changeability of QoS of Web services, the traditional methods are unadaptable to the new environments. In this paper, a new service composition method, called Improved Self-organising neural network Method for Web Service Composition, is proposed to achieve QoS-aware Web service combination, according to using the clustering technology. First, fuzzy mathematics is used to express each QoS attribute and the improved self-organising neural network is used to cluster services to reduce the number of candidate services. Secondly, all the centre of each cluster is selected and formed a composite service by using an exhaustive algorithm. Thirdly, the service cluster that is represented by the concrete services. Finally, the optimal service combination can be selected using integer programming or genetic algorithm. The experimental result shows the efficiency of Web service composition and demonstrates the applicability.     

项目教学法在《国际结算》课程教学中的运用

项目教学法是以实践为导向、教师为主导、学生为主体、通过师生共同实施项目完成教学的方法,它对实践性很强的课程的教学具有重要的意义。《国际结算》课程具有很强的操作性和实践性,因而采用项目教学法对培养学生的实际操作能力非常重要。为了保障项目教学法的实施,我们应从学生、教师、学校、社会等多个层面共同努力,以培养学生的应用能力。     

网格计算环境下企业的ASP-CRM模式研究

客户关系管理（Customer Relationship Management-CRM）已成为企业获得竞争优势的重要手段。但传统的客户关系管理系统投资大、周期长、投资风险高,企业、尤其是中小企业难以承受。应用服务供应商（ApplicationServiceProvider-ASP）模式通过建立公共的IT服务平台,以租赁的方式为用户提供软件平台的服务,能够有效免除企业的资金和技术困扰。但是AsP模式存在的不足与缺陷却制约着它的发展。网格计算技术能充分利用网络中的各种资源,实现强大的数据处理功能。在研究现有企业ASP运作模式和商业模式的基础上,给出网格计算环境下的企业ASP模式,并构建了新模式的运营模型。将cRM、ASP和网格计算结合起来,提出网格计算环境下企业AsP_cRM模式的体系结构和服务模型,并分析了该模式的特点。     

企业级应用架构研究:SOA架构融合SaaS模式

SOA是面向服务的架构,其理念指导把应用程序的不同单元以服务的形式提供支持,平台及底层实现均对用户透明,用户只需要以中立的接口和契约进行通信,获取相应的服务即可;而SaaS则是一种软件服务提供的模式,基于互联网为终端用户提供软件服务的软件应用模式;本文研究讨论二者所承担的角色,及其分别在不同层面如何发挥作用。在认清二者关系后,研究在目前市场发展趋势下如何融合衍生。     

Scheduling multimedia services in cloud computing environment

Currently, security is a critical factor for multimedia services running in the cloud computing environment. As an effective mechanism, trust can improve security level and mitigate attacks within cloud computing environments. Unfortunately, existing scheduling strategy for multimedia service in the cloud computing environment do not integrate trust mechanism when making scheduling decisions. In this paper, we propose a scheduling scheme for multimedia services in multi clouds. At first, a novel scheduling architecture is presented. Then, We build a trust model including both subjective trust and objective trust to evaluate the trust degree of multimedia service providers. By employing Bayesian theory, the subjective trust degree between multimedia service providers and users is obtained. According to the attributes of QoS, the objective trust degree of multimedia service providers is calculated. Finally, a scheduling algorithm integrating trust of entities is proposed by considering the deadline, cost and trust requirements of multimedia services. The scheduling algorithm heuristically hunts for reasonable resource allocations and satisfies the requirement of trust and meets deadlines for the multimedia services. Detailed simulated experiments demonstrate the effectiveness and feasibility of the proposed trust scheduling scheme.