基于扩展染色Petri网的工作流过程模型

尽管已有广泛领域应用,但工作流系统在处理业务流程不确定的和动态的参数规格表时存在局限性。为此,本文提出基于扩展染色petri网的CPWF-net以及定义变迁行为和原子过程作为CPWF-net工作流模式结构的支持。这些工作流模式是从微观上进行处理,并可应用于动态不稳定的与时间和数据相关的环境中。本文通过CPWF-net执行程序检测工作流错误或异常执行状态,评估动态业务流程的整体执行时间,证实所提方法的有效性。     

一种面向SOA业务恢复的服务选择算法

针对SOA业务恢复的服务选择问题,本文提出了一种QoS近似全局最优的服务选择算法GALSA:首先利用GA算法将全局QoS约束分解为最优的局部QoS约束,然后利用LSA算法选取出满足局部QoS约束的最优服务。算法不仅能作用于服务重构的服务选择过程中,而且在单个服务节点失效时亦能选取出满足全局QoS约束的服务进行替换。理论分析与实验结果说明了算法的可行性和有效性。     

敏捷化AIOps框架及运维数据质量评估方法

敏捷化智能运维(AIOps)框架将模型构建提前至测试阶段,利用该阶段产生的监控数据代替线上采集的数据以训练AIOps模型,进而实现智能运维的早开发与早使用. 运维数据质量评估方法通过最大均值差异度量方式,分别在健康评估与故障诊断运维场景下对训练数据分别进行趋势性、阶段性、可检测性及可诊断性评估,以预估数据对模型的适用性. 基于华为技术有限公司提供的测试环境设置测试用例并构建实验数据集,在该数据集上的实验结果验证了敏捷化AIOps框架的可行性及数据质量评估方法的有效性.     

A blueprint for capturing grid value in a decentralized electricity sector

This study addresses the question of how the electricity grid can best be priced, in the context of disruptive technologies, increasing decentralisation of the power sector and new business models. The emergence of business models can affect the design of tariffs, but at the same time, tariff design can trigger new business models as they can nudge adoption towards certain technologies. Network tariffs have traditionally been established using a cost accounting method. Due to its cost structure, network tariffs are second best constructs, as marginal cost pricing does not lead to cost recovery. Second best solutions, in all probability, will overcompensate some inputs which in turn will be overused (the Averch-Johnson effect). New distributed energy technologies that perform better in these overcompensated inputs will therefore see a higher penetration in the market. Penetration of some technologies over others in a previously monolithic vertically integrated power sector will open up new customer needs and therefore business opportunities. Each resulting business opportunity would make use of the grid differently from which it was originally conceived, and at one extreme, they can bypass it altogether. We provide a framework of analysis that leads to the pricing of the services provided by the electricity grid for each new business opportunity.     

工作流技术在ASP公共服务平台中的应用研究*

根据项目特点,建立了适合ASP平台的基于协调理论和反馈机制的扩展活动网络模型,采用XML模式的XPDL规范实现过程定义;然后通过DOM解析XML数据文档和J2EE的技术支持实现了系统的轻量级工作流引擎.详细介绍了系统实现中解决的两个关键问题:事务型操作的处理和并发控制,并提出了基于优先级的锁绑定机制.     

我国甲烷氯化物产品成本核算规程的探讨

从核算规程修改的原理、原则及内容等方面对甲烷氯化物产品成本核算规程的修改、规范和完善情况进行了介绍。     

The clustering-based case-based reasoning for imbalanced business failure prediction: a hybrid approach through integrating unsupervised process with supervised process

Case-based reasoning (CBR) is one of the main forecasting methods in business forecasting, which performs well in prediction and holds the ability of giving explanations for the results. In business failure prediction (BFP), the number of failed enterprises is relatively small, compared with the number of non-failed ones. However, the loss is huge when an enterprise fails. Therefore, it is necessary to develop methods (trained on imbalanced samples) which forecast well for this small proportion of failed enterprises and performs accurately on total accuracy meanwhile. Commonly used methods constructed on the assumption of balanced samples do not perform well in predicting minority samples on imbalanced samples consisting of the minority/failed enterprises and the majority/non-failed ones. This article develops a new method called clustering-based CBR (CBCBR), which integrates clustering analysis, an unsupervised process, with CBR, a supervised process, to enhance the efficiency of retrieving information from both minority and majority in CBR. In CBCBR, various case classes are firstly generated through hierarchical clustering inside stored experienced cases, and class centres are calculated out by integrating cases information in the same clustered class. When predicting the label of a target case, its nearest clustered case class is firstly retrieved by ranking similarities between the target case and each clustered case class centre. Then, nearest neighbours of the target case in the determined clustered case class are retrieved. Finally, labels of the nearest experienced cases are used in prediction. In the empirical experiment with two imbalanced samples from China, the performance of CBCBR was compared with the classical CBR, a support vector machine, a logistic regression and a multi-variant discriminate analysis. The results show that compared with the other four methods, CBCBR performed significantly better in terms of sensitivity for identifying the minority samples and generated high total accuracy meanwhile. The proposed approach makes CBR useful in imbalanced forecasting.     

Distinguishing the adoption of business intelligence systems from their implementation: the role of managers’ personality profiles

For decades, the marketing guidelines of enterprise software providers have focused on those managers who are likely to be more innovative in adopting new information systems. The current study argues that this approach demands improvements for two reasons: (1) this tactic may be biased, since past studies have only examined the single trait of innovativeness and its impact on an individual adoption intention and (2) the organisational implementation intention might be more important than the individual adoption intention, but the former has been largely ignored in the existing literature. Based on the case of business intelligence (BI) systems and data from 62 senior managers, this study is a pioneer in that it empirically reveals that managers’ individual adoption intention is distinct from their organisational implementation intention. Further, while managers’ innovativeness may be a significant determinant of their individual adoption intention towards BI systems, the issue of whether managers actually implement BI systems in their organisations is dominated by their involvement characteristics. Fruitful suggestions are proposed for practitioners and scholars.     

CRUDi framework proposal: financial industry application

The alignment of information systems with the business goals of an organisation, although a topic of great importance, is not always properly valued or taken into consideration. In general, managers have different opinions to chief information officers (CIOs) in relation to IS, especially with regard to their importance and value to the business and also in terms of investment needs. Here, we discuss and study new approaches to methods and tools for assessing the relative importance of each information system to business, focusing on the financial sector including banks and insurance companies. We suggest the introduction of new key indicators for better decision support and to identify investment priorities, and present results regarding the relative importance of each process to support the business strategy. The primary goal for the inherent research project is to analyse the main problems and difficulties encountered by IS and IT managers, featuring different players and how they relate. The main contributions of this work are the CRUDi framework as a tool to improve alignment between business and IS strategies and the CRUDi survey and its results qualifying the financial sector's opinion regarding the relative importance of processes and investments.     

浅析企业管理创新

在企业中,要使每个员工都有施展和创新的机会。每个企业都要有自己的思想和具备自身特色的经营模式,要随着时间的推移不断运用新的创新理念,从而使企业在不断的变化中立于不败之地,在创新中不断发展。