基于RBAC模型实现电子政务系统业务的柔性处理

电子政务的迅速发展,加大了业务处理的复杂度,先前的系统业务处理功能虽然丰富,但随着需求的不断变更和业务处理的不断重组,使得系统的适应能力已逐渐不能满足这种变化带来的柔性需求。文中根据电子政务系统存在业务处理流程中的“固化”的现象,引进基于角色的访问控制（RBAC）模型,从顶层设计的高度,利用基于数据字典的系统实现方法,实现了系统对业务的柔性处理,增强了业务处理的灵活性,从而提高系统的适应能力,进一步使得基于电子政务的政府机构办事效率提高。     

电子政务系统中Ajax应用的模式分析

以某机关事务管理局电子政务项目为例,对电子政务项目建设过程中的基于Web富客户端技术电子政务业务实现进行阐述。进一步分析了电子政务系统客户端的需求,结合ajax的应用模式阐述客户端各功能模块的具体实现,从中对电子政务系统中富客户端的应用进行拓展和思维扩散,得出了一些常见模式的应用范围,以及总结出了在不同的应用需求下去选择最适用ajax模式的方法。     

基于工作流的服务组合在电子政务中的应用

为了解决电子政务系统建设中存在的"信息孤岛"问题,提出了一个基于工作流实现服务组合的系统框架.该框架通过流程服务中心的工作流引擎对遗留系统发布的Web服务进行组合,实现了整合遗留系统和跨部门协同办公,从而能够有效地满足业务用户的需求,以及实现对敏捷业务需求的快速响应.最后以跨部门电子政务系统验证了该框架的合理性,结果表明是可行和有效的.     

基于Android平台的现场质量数据采集系统

为了提高制造企业现场质量数据采集效率,满足移动化数据采集需求,针对目前质量数据采集方法的缺陷和不足,提出了一种基于Android平台的现场质量数据采集系统. 该系统以平板或手机作为客户端,通过WIFI或3G/4G网络与服务端通信,实现移动化数据采集;使用界面配置文件以实现用户自定义的质量数据采集界面,使得系统具有很好的柔性;使用规则配置文件来实现界面业务逻辑控制,使得客户端具有一定的智能性.     

基于语义Web服务的电子政务模型

随着政府信息化程度的不断提高,越来越多的电子政务平台提供了各类Web服务用于异构系统间的资源共享及数据交互。然而,目前通用的Web服务缺乏对语义的推理支持,使得异构的、分布式电子政务系统的管理及互操作性面临着极大的挑战。为了克服这一困难,提出了基于语义Web服务的电子政务模型,使用开放的、动态的、松耦合的、支持语义的Web服务构建了电子政务平台,以满足异构电子政务系统的资源整合及知识共享的需求。     

基于双网的会计电子政务系统的设计与实现

会计电子政务既要面对分布广的会计从业人员,又要处理大量的数据.提高办公效率是会计电子政务中一个急需解决的问题.针对会计电子政务系统的特点,基于政务网和局域网,分别采用B/S结构和C/S结构的方式,在PKI的安全平台上设计并实现了会计电子政务系统.并考虑会计电子政务系统的业务逻辑特点,确保系统的安全性、易操作性和易维护性.该系统在广东省某财政局会计科的使用中表明是可行有效的.     

工作流管理系统柔性机制

随着工作流管理系统在各个领域的应用,系统的柔性机制引起人们的极大关注。该文介绍柔性化工作流管理系统的基本概念及架构,描述从多个方面对工作流管理系统进行柔性化扩展的特点和实现机制。设计并实现一个具有更强适应能力的柔性工作流管理系统,实践证明该机制有效。该系统的实现也为异地的业务流程处理,甚至是跨平台间的业务组织和流程调用提供了良好的工作基础。     

基于Struts的用地管理信息系统

研究了基于Struts和AreIMS等技术的用地管理信息系统.系统采用了基于J2EE、Struts、AreIMS等技术的实现方案.根据以前业务系统存在的主要问题以及业务需求达到的主要目标包括业务需求目标、GIS功能目标、办公自动化目标、工作流目标、信息发布目标,系统采用了基于包括显示层.商业逻辑层和数据层的B/S三层结构设计.对具体模块的设计与实现进行了介绍.此系统方案可以作为其它基于Web的电子政务系统建设的参考.     

基于IBN的5G网络管理系统的调度算法研究

随着5G时代的到来,多种应用场景和差异化的业务需求不断涌现,对运营商网络资源和业务需求调度分配的能力提出更高的要求。通过对5G网络新特征的分析,提出一种基于意图的网络管理调度系统,结合IBN的网络架构将多种形式的业务意愿收集并翻译成所需的网络操作和配置,实现网络的快速自动部署实施。基于该系统提出了一个快速调度算法,对任务进行有效的多级调度和同级调度,仿真实验表明,基于意图网络的快速调度系统使得任务处理效率提高,任务调度处理时间减少,对于发生重大事件等通信场景的业务需求调度保障有重要意义。     

业务流程柔性配置的研究和实现

实现了一个柔性可配置轻量级工作流引擎系统。系统使用工具JaWE进行可视化建模,生成XPDL格式的流程定义文件;并设计实现了基于 Token 的引擎执行控制机制,使得引擎系统对其所在业务系统中的业务流程执行过程的控制准确而有效率。采用适当的流程定义管理策略,实现对流程运行时修改流程定义的支持;同时引擎使用基于组件配置的方式形成业务系统,使应用引擎的业务系统具有较大的柔性。该引擎已成功应用在某制药企业的项目管理平台中,取得了良好的应用效果。     

Deep-learning neural-network architectures and methods: Using component-based models in building-design energy prediction

Increasing sustainability requirements make evaluating different design options for identifying energy-efficient design ever more important. These requirements demand simulation models that are not only accurate but also fast. Machine Learning (ML) enables effective mimicry of Building Performance Simulation (BPS) while generating results much faster than BPS. Component-Based Machine Learning (CBML) enhances the capabilities of the monolithic ML model. Extending monolithic ML approach, the paper presents deep-learning architectures, component development methods and evaluates their suitability for space exploration in building design. Results indicate that deep learning increases the performance of models over simple artificial neural network models. Methods such as transfer learning and Multi-Task Learning make the component development process more efficient. Testing the deep-learning model on 201 new design cases indicates that its cooling energy prediction (R²: 0.983) is similar to BPS, while errors for heating energy predictions (R²: 0.848) are higher than BPS. Higher heating energy prediction error can be resolved by collecting heating data using better design space sampling methods that cover the heating demand distribution effectively. Given that the accuracy of the deep-learning model for heating predictions can be increased, the major advantage of deep-learning models over BPS is their high computation speed. BPS required 1145 s to simulate 201 design cases. Using the deep-learning model, similar results can be obtained in 0.9 s. High computation speed makes deep-learning models suitable for design space exploration.     

Workflow simulation for operational decision support using event graph through process mining

It is increasingly common to see computer-based simulation being used as a vehicle to model and analyze business processes in relation to process management and improvement. While there are a number of business process management (BPM) and business process simulation (BPS) methodologies, approaches and tools available, it is more desirable to have a systemic BPS approach for operational decision support, from constructing process models based on historical data to simulating processes for typical and common problems. In this paper, we have proposed a generic approach of BPS for operational decision support which includes business processes modeling and workflow simulation with the models generated. Processes are modeled with event graphs through process mining from workflow logs that have integrated comprehensive information about the control-flow, data and resource aspects of a business process. A case study of a credit card application is presented to illustrate the steps involved in constructing an event graph. The evaluation detail is also given in terms of precision, generalization and robustness. Based on the event graph model constructed, we simulate the process under different scenarios and analyze the simulation logs for three generic problems in the case study: 1) suitable resource allocation plan for different case arrival rates; 2) teamwork performance under different case arrival rates; and 3) evaluation and prediction for personal performances. Our experimental results show that the proposed approach is able to model business processes using event graphs and simulate the processes for common operational decision support which collectively play an important role in process management and improvement.     

Biomechanical evaluation of bike power saver

Bike power saver (BPS) is a new product that claims to change the angle of pedaling forces and reduce applied power dead range (Chic Sheng Industrial Co., Ltd, Taiwan, China). In order to determine its effectiveness, we quantified how BPS operates through a 3D kinematical study and electromyography (EMG) analysis of leg muscles during pedaling. Ten kinesiology students participated in this study. A 3D motion capture system consisting of nine high-speed cameras (VICON v8i, a capture rate of 120 frames/s) was used to collect the total body and pedal motion with and without BPS at statically determined low, middle and high intensity cycling levels. The short-time test (14s) was applied to all intensity levels while the long-time test (30 min) was applied only to the low wattage level. Wireless EMG was synchronized with the 3D motion capture system to monitor the right and left tibialis anterior, gastrocnemius, quadriceps and hamstring. The results revealed that BPS did not alter hip and knee movement significantly (p>0.05), but it did vary ankle movement. BPS caused a movement change in the pedals, and consequently induced instability in ankle control. The altered pedal movement led to an increase in activity level and presumably also energy expenditure for dominant muscles, resulting in a faster fatigue process. From these data, it is likely that the BPS actually requires more effort than a standard bike.     

基于样条模型的联合定轨精度分析及仿真

考虑到基于双星定位系统的近地卫星联合定轨待估参数的时间相关性,提出了1种基于样条参数模型与动力学模型相互融合的联合定轨节省参数建模新方法,并基于传统联合定轨算法进行了具体的改进算法设计。理论分析和仿真计算表明,与传统联合定轨方法相比,该方法减少了待估参数个数,提高了轨道表示精度,并且使估计结构更加稳定,估计精度也得到了一定程度的提高。     

Quick energy prediction and comparison of options at the early design stage

The energy-efficient building design requires building performance simulation (BPS) to compare multiple design options for their energy performance. However, at the early stage, BPS is often ignored, due to uncertainty, lack of details, and computational time. This article studies probabilistic and deterministic approaches to treat uncertainty; detailed and simplified zoning for creating zones; and dynamic simulation and machine learning for making energy predictions. A state-of-the-art approach, such as dynamic simulation, provide a reliable estimate of energy demand, but computationally expensive. Reducing computational time requires the use of an alternative approach, such as a machine learning (ML) model. However, an alternative approach will cause a prediction gap, and its effect on comparing options needs to be investigated. A plugin for Building information modelling (BIM) modelling tool has been developed to perform BPS using various approaches. These approaches have been tested for an office building with five design options. A method using the probabilistic approach to treat uncertainty, detailed zoning to create zones, and EnergyPlus to predict energy is treated as the reference method. The deterministic or ML approach has a small prediction gap, and the comparison results are similar to the reference method. The simplified model approach has a large prediction gap and only makes only 40% comparison results are similar to the reference method. These findings are useful to develop a BIM integrated tool to compare options at the early design stage and ascertain which approach should be adopted in a time-constraint situation.     

带输入队列并行交换的负载平衡分析

并行交换是新兴的交换技术,基于该技术能够利用小型交换模块来构建大容量的交换系统,例如太比特或更高容量的交换机.把带输入队列的并行交换称为带缓存并行交换(buffered parallel switch,简称BPS),重点研究其中并行且独立工作的交换模块之间的负载平衡问题.从不同角度出发,提出两种负载平衡的定义.基于两种定义,分别分析了BPS负载平衡的条件并提出分布式调度算法族.最后,提出一种简单而有效的调度算法,该算法能在无加速比BPS中同时满足两种定义,仿真实验结果表明了该算法的有效性和良好性能.另外,就算法的工程实现进行了讨论.     

基于三层结构的流程工业现代集成制造系统

流程工业是国民经济发展的重要支柱 ,流程工业现代集成制造系统 (CIMS)是提高流程工业竞争力的重要高技术之一 ,是工业自动化领域的前沿课题。提出了适合流程企业实现扁平化管理模式的基于经营计划系统 (BPS) /制造执行系统 (MES) /过程控制系统 (PCS)三层结构的CIMS ,并分别阐述了BPS、MES、PCS的功能及关键核心技术的发展方向     

BPS工作流平台在协同办公系统中的应用

针对企业内部管理协作高效需求的日益凸显,介绍了普元工作流平台的参考模型。基于普元BPS工作流平台,构建了企业协同办公系统功能框架,并以企业核心业务发文处理流程为例,探讨了基于BPS工作流系统的流程设计过程,对构建信息共享和业务协同的高效企业具有重要意义。     

Constrained,mixed-integer and multi-objective optimisation of building designs by NSGA-II with fitness approximation

Reducing building energy demand is a crucial part of the global response to climate change, and evolutionary algorithms (EAs) coupled to building performance simulation (BPS) are an increasingly popular tool for this task. Further uptake of EAs in this industry is hindered by BPS being computationally intensive: optimisation runs taking days or longer are impractical in a time-competitive environment. Surrogate fitness models are a possible solution to this problem, but few approaches have been demonstrated for multi-objective, constrained or discrete problems, typical of the optimisation problems in building design. This paper presents a modified version of a surrogate based on radial basis function networks, combined with a deterministic scheme to deal with approximation error in the constraints by allowing some infeasible solutions in the population. Different combinations of these are integrated with Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and applied to three instances of a typical building optimisation problem. The comparisons show that the surrogate and constraint handling combined offer improved run-time and final solution quality. The paper concludes with detailed investigations of the constraint handling and fitness landscape to explain differences in performance.