面向再制造的逆向物流产品回收预测研究

在对再制造逆向物流网络系统构建的基础上,对系统中存在的不确定性因素进行分析。以产品回收数量预测为研究对象,利用灰色模型建立产品回收数量预测模型,并进行实例计算。结果表明该模型计算精度高,所需数据量少,有良好的应用性。     

基于用户兴趣度的校园网带宽管理策略应用研究

针对校园网出口拥塞问题,提出一种基于行为分析的用户兴趣建模方法,通过用户参与时间来衡量并计算不同种类应用的用户访问兴趣度,在用户兴趣度的基础上结合通道管理技术进行带宽管理策略研究,实现动态带宽管理。实施结果表明,该方法能够有效地提高用户的网络满意度。     

编程思维训练通用模型研究与实现

程序设计类课程是培养学生逻辑编程能力的基本课程之一,但目前普遍反映出学生对此类课程的学习兴趣不浓,对程序设计与实现的逻辑思维混乱不清,学习效果较差。如何脱离编程语言本身,运用模拟现实生活的思维训练模型来形象地展示编程的原理与逻辑流程,以提高学生对程序设计的逻辑思维能力和学习效果是本文研究的重点。     

采集系统中存储技术的研究

随着光纤技术在嵌入式领域中的应用,通信数据量不断增加,高速采集网络上的数据并正确地存储到磁盘上已成为整个系统的瓶颈。本文从系统基本功能模块出发结合生产者/消费者(Producer-Consumer)模型,对多线程并发、直接读写扇区、异步I/O等技术在系统中的应用进行分析;对系统模型进行抽象,用数学方法对系统进行可行性分析。实验表明,数据采集系统中采用多线程多缓冲的方式在性能上有一定的提高。     

校园电子商务系统设计

针对校园电子商务的产生和发展进行了阐述,对校园电子商务的功能模块进行设计和描述,提出了校园电子商务带来的影响,并探讨了校园电子商务在信用、物流、市场规划、管理模式、安全支付等方面存在的问题。     

虚拟现实技术在反恐训练中的研究进展

介绍了虚拟现实技术的国内外研究现状,以及仿真技术与虚拟现实技术结合使用的发展趋势.为了更好地履行反恐使命,适应形势的发展,有必要提高反恐教学训练质量,创新反恐行动教学训练手段.将仿真技术和虚拟现实技术应用于路边炸弹的虚拟及仿真,能使反恐受训者不受时间、空间、经费和器材的限制,利用各种3D虚拟模型任意组装不同起爆方式下的路边炸弹,拓展其想象空间和创新思维,使之对路边炸弹的结构组成、工作原理及爆炸效应等有深刻理解.     

SaaS工作流访问控制模型设计

在SaaS中,人们正逐渐采用基于服务的业务流程来满足企业业务流程的灵活性和定制性。从实现工作流访问控制的角度,应当使工作流访问控制模型与流程模型分离,以支持在流程改变或组织机构变化时减少对彼此的影响。为此,设计和实现了一个面向服务的、支持访问控制模型和流程模型分离的SaaS工作流访问控制模型—RBSWAC(Role-based Service Workflow Accesss Control)。该模型可提高访问控制的适应性和灵活性,实现访问控制模型同流程模型的松耦合和灵活性。     

Layout Optimization for Greenhouse WSN Based on Path Loss Analysis

When wireless sensor networks (WSN) are deployed in the vegetable greenhouse with dynamic connectivity and interference environment, it is necessary to increase the node transmit power to ensure the communication quality, which leads to serious network interference. To offset the negative impact, the transmit power of other nodes must also be increased. The result is that the network becomes worse and worse, and node energy is wasted a lot. Taking into account the irregular connection range in the cucumber greenhouse WSN, we measured the transmission characteristics of wireless signals under the 2.4 Ghz operating frequency. For improving network layout in the greenhouse, a semi-empirical prediction model of signal loss is then studied based on the measured data. Compared with other models, the average relative error of this semi-empirical signal loss model is only 2.3%. Finally, by combining the improved network topology algorithm and tabu search, this paper studies a greenhouse WSN layout that can reduce path loss, save energy, and ensure communication quality. Given the limitation of node-degree constraint in traditional network layout algorithms, the improved algorithm applies the forwarding constraint to balance network energy consumption and constructs asymmetric network communication links. Experimental results show that this research can realize the energy consumption optimization of WSN layout in the greenhouse.     

Digital twin modeling method based on biomimicry for machining aerospace components

High-performance aerospace component manufacturing requires stringent in-process geometrical and performance-based quality control. Real-time observation, understanding and control of machining processes are integral to optimizing the machining strategies of aerospace component manufacturing. Digital Twin can be used to model, monitor and control the machining process by fusing multi-dimensional in-context machining process data, such as changes in geometry, material properties and machining parameters. However, there is a lack of systematic and efficient Digital Twin modeling method that can adaptively develop high-fidelity multi-scale and multi-dimensional Digital Twins of machining processes. Aiming at addressing this challenge, we proposed a Digital Twin modeling method based on biomimicry principles that can adaptively construct a multi-physics digital twin of the machining process. With this approach, we developed multiple Digital Twin sub-models, e.g., geometry model, behavior model and process model. These Digital Twin sub-models can interact with each other and compose an integrated true representation of the physical machining process. To demonstrate the effectiveness of the proposed biomimicry-based Digital Twin modeling method, we tested the method in monitoring and controlling the machining process of an air rudder.     

Mathematical model and discrete artificial Bee Colony algorithm for distributed integrated process planning and scheduling

With the development of the globalization of economy and manufacturing industry, distributed manufacturing mode has become a hot topic in current production research. In the context of distributed manufacturing, one job has different process routes in different workshops because of heterogeneous manufacturing resources and manufacturing environments in each factory. Considering the heterogeneous process planning problems and shop scheduling problems simultaneously can take advantage of the characteristics of distributed factories to finish the processing task well. Thus, a novel network-based mixed-integer linear programming (MILP) model is established for distributed integrated process planning and scheduling problem (DIPPS). The paper designs a new encoding method based on the process network and its OR-nodes, and then proposes a discrete artificial bee colony algorithm (DABC) to solve the DIPPS problem. The proposed DABC can guarantee the feasibility of individuals via specially-designed mapping and switching operations, so that the process precedence constraints contained by the network graph can be satisfied in the entire procedure of the DABC algorithm. Finally, the proposed MILP model is verified and the proposed DABC is tested through some open benchmarks. By comparing with other powerful reported algorithms and obtaining new better solutions, the experiment results prove the effectiveness of the proposed model and DABC algorithm successfully.