函数依赖和规范化在关系和XML间的传播

XML和关系的结合是一个重要的研究领域,讨论函数依赖和规范化在关系及XML间的传播问题.首先引入XML上函数依赖和键的定义,并进一步定义XML上的数据冗余和规范化DTD的概念.分别讨论在关系和XML相互转化的过程中,函数依赖的传播问题.针对一种一般化的关系模式DTD表示,证明原有关系中的函数依赖可以在生成的XML文档上得到表示.针对一种常见的XML关系存储方法,说明最终生成关系上的函数依赖与原有XML上函数依赖的对应关系.函数依赖传播的核心意义在于规范化的传播.证明使用上述方法时,若原有的关系是满足BCNF的,则发布得到的DTD也是规范化的;若原始的DTD是规范化的,则得到的关系存储也满足BCNF范式.     

"敏捷制造"是制造业信息化的本质要求

敏捷制造是指制造企业采用现代网络信息技术手段,通过动态地、有效地协调整合各种生产要素,快速配置各种资源(包括技术、管理和人),响应用户需求,实现制造敏捷化的一种现代制造模式.     

机械制造业CIMS网络的建立及管理

ＣＩＭＳ是指以计算机为中心的现代信息技术应用于企业管理与产品开发制造的新一代制造系统。其真谛在于以计算机来辅助制造系统的集成,即以充分的信息交流及信息共享,促进制造系统和企业组织结构的优化运行,其目的在于提高企业的竞争能力及生存能力。本文就在机械制造业建立ＣＩＭＳ网络的重要性,网络设计及管理问题进行了论述。     

考虑服务水平的产能分享平台定价策略

工业互联网和分享经济正在改变企业配置资源和产能规划的方式,制造企业之间分享空闲产能的模式逐渐显示出广阔的发展空间和经济效益.研究基于平台的产能分享情境中,利润最大化和社会福利最大化两种决策目标下,平台的最优定价策略问题.研究表明:注册费模式下的平台均衡利润大于固定交易费模式下的均衡利润,两种定价模式的平台利润与供需双方的网络外部性和服务敏感性系数均存在正相关关系,与供应方的产能定价存在负相关关系,且是平台服务水平的凹函数;两种定价模式的社会福利优劣和平台对双边用户的补贴策略均与供应方网络外部性冲销的制造成本相关.另外,存在社会福利与平台利润同时较优的情况,这也是产能分享平台良性发展的方向.     

机械制造业CIMS网络的建立及管理

ＣＩＭＳ是指以计算机为中心的现代信息技术应用于企业管理与产品开发制造的新一代制造系统。其真谛在于以计算机来辅助制造系统的集成,即以充分物信息交流及信息共享、促进制造系统和企业组织结构的优化运行,其目的在于提高企业的竞争能力及生存能力。本文就在机械制造业建立ＣＩＭＳ网络的重要性。网络设计及管理问题进行了论述。     

模糊时态数据库设计中模糊/时态向量空间特性研究

数据库设计的目标是生成一组模式,使数据存储既减少冗余,又可方便地获取信息。这是通过设计满足适当范式的模式来实现的。函数依赖FD是有效的工具。对于多粒度模糊时态数据库设计来说,模糊值和多粒度模糊时态序列的映射关系是将传统FD扩展到模糊时态函数依赖FTFD的关健,通过分析属性集的有限闭包、时态类型集的封闭集、属性集在给定时态上的依赖等概念,得到模糊/时态向量的特征描述,并对此方法的正确性进行了论证。此方法能方便地在计算机上表达模糊属性值和模糊时态序列的映射关系,为模糊时态数据库范式的判定和分解算法提供有效的手段。     

制造业信息化建设

推进制造业信息化是落实"以信息化带动工业化"战略、走新型工业化道路的重要举措。推进制造业信息化是《国家中长期科学和技术发展规划纲要》提出的重要任务;是面向国民经济建设主战场,整合科技资源、实施"以信息化带动工业化"战略、走新型工业化道路的重要举措;是推进经济结构调整和经济增长方式转变的重要手段。制造业信息化将信息技术、自动化技术、现代管理技术与制造技术结合应用,推进设计制造数字化、生产过程智能化和企业经营管理信息化。用高新技术改造和提升制造业,促进制造业研发设计、生产制造、企业管理和市场营销的变革,带动产品设计和制造模式的创新、企业管理和经营模式的创新以及企业间协作模式的创新,是新时期我国制造业适应全球竞争环境、生存和发展的必由之路,对提升我国制造业的自主创新能力和市场竞争能力具有重要意义。     

下期主要内容

一种增加图像数据量的算法 基于C/S与B/S结合模式的企业MIS结构 通用串行总线性能特点及其应用 基于迭代函数的不规则图像快速生成算法 球面化算法的设计及其实现 VFP中倒计时器的设计 形参个数不定的函数的编制和使用 TIN的生成和存储算法 PB中下拉列表控件显示动态数据的通用函数 软件测试基本技术 MIS与EDI的关系研究 虚拟技术在证券商网络中的应用 视频检测式违章自动监测管理系统的设计 树形结构在题库系统中的应用 VC编程中的屏幕效果设计 铁路电气集中微机监测系统 避免死锁的安全算法的改进 计算机协同支持下虚拟编辑环境的研究 智能网与因特网互联的PINT业务协议研究 动画技术应Web页制作中的应用 电子商务技术的探析 基于SVM的函数模拟 基于数据仓库技术的决策支持系统 在VB中调用Windows API函数 基于小波神经网络的混沌时间序列预测 基于ATM和Internet的视频点播系统 数据库服务器与WWW之间的一种集成设计     

新型Sigma-Pi泛函网络模型

将泛函神经元结构变形，建立Sigma-Pi泛函网络模型，给出Sigma-Pi泛函网络学习算法。采用数值分析的方法，将Sigma-Pi泛函网络应用于异或问题，结果表明，该网络对于某些问题具有很强的分类能力。该方法的优点在于利用一元函数作为基函数来实现高维函数的逼近，在函数逼近技术上，有着重要的应用价值。     

多模式生成对抗网络

生成对抗网络已经成为深度学习领域最热门的研究方向之一,其最大的优势在于能够以无监督的方式来拟合一个未知的分布。目前,生成对抗网络在图像生成领域大放异彩,其能够产生一些高质量的图像,但也暴露了一些弊端。在生成图像的过程中,经常会出现模式坍塌问题,从而导致生成的样本过于单一。为了解决这个问题,对生成对抗网络的模型结构和损失函数加以改进,使判别器能够从多个角度来度量生成数据的分布和真实数据的分布之间的差异,从而改善了生成样本的多样性。通过在多个数据集上进行实验,结果显示,提出的模型在很大程度上缓解了模式坍塌问题。     

Modeling of service agents for simulation in cloud manufacturing

Cloud Manufacturing is a paradigm of intelligent manufacturing system with information opening, resource sharing, and diversified services. In order to research the issues in cloud manufacturing, such as behaviors of a service provider and service consumer, matching of service, dynamic change of resource, verification of business model, scheduling of service and evolution of service network, cloud manufacturing simulation platform is widely applied. However, the method of simulation-based on agent or rule lacks to represent the characteristics of service in cloud manufacturing. This paper presents a method of integrating the service and agent to form a service agent. The service agent integrates intelligence to the service in cloud manufacturing so that it can trade autonomously and adapt itself to the environment. A simulation case of production takt is presented in the rear of the paper. It shows that the conceptual model of the service agent and the communication architecture of the service agent can build the service agent model, which can support the cloud manufacturing simulation platform.     

Co-ordination of SME production through a co-operative network

Today, industrial production steps outside the boundaries of individual enterprises, so new management approaches are needed to be able to co-ordinate the work of the different manufacturing organizations. A new co-operative manufacturing network model is proposed for balancing the production of SMEs, based on the holonic paradigm. The model has been developed within the framework of an ESPRIT project by four countries. The paper describes the main modules of the model and briefly introduces an application under realization in Hungary, in an agricultural SME network.     

Modeling of agile intelligent manufacturing-oriented production scheduling system

Agile intelligent manufacturing is one of the new manufacturing paradigms that adapt to the fierce globalizing market competition and meet the survival needs of the enterprises, in which the management and control of the production system have surpassed the scope of individual enterprise and embodied some new features including complexity, dynamicity, distributivity, and compatibility. The agile intelligent manufacturing paradigm calls for a production scheduling system that can support the cooperation among various production sectors, the distribution of various resources to achieve rational organization, scheduling and management of production activities. This paper uses multi-agents technology to build an agile intelligent manufacturing-oriented production scheduling system. Using the hybrid modeling method, the resources and functions of production system are encapsulated, and the agent-based production system model is established. A production scheduling-oriented multi-agents architecture is constructed and a multi-agents reference model is given in this paper.     

Towards IoT-enabled dynamic service optimal selection in multiple manufacturing clouds

With the Internet of Things, it is now possible to sense the real-time status of manufacturing objects and processes. For complex Service Selection (SS) in Cloud Manufacturing, real-time information can be utilized to deal with uncertainties emerging during task execution. Moreover, in the face of diversified demands, multiple manufacturing clouds (MCs) can provide a much wider range of choices of services with their real-time status. However, most researchers have neglected the superiority of multiple MCs and failed to make a study of how to utilize the abundant and diverse resources of multiple MCs, let alone the multi-MCs service mode under dynamic environment. Therefore, we first propose a new dynamic SS paradigm that can leverage the abundant services from multiple MCs, real-time sensing ability of the Internet of Things (IoT) and big data analytics technology for knowledge and insights. In this way, providing optimal manufacturing services (with high QoS) for customers can be guaranteed under dynamic environments. In addition, considering that a relatively long time might be spent to complete a complex manufacturing task after SS, a quantified approach, based on the Analytic Hierarchy Process and big data, is proposed to evaluate whether the intended cloud manufacturing services should be reserved to make sure that eligible services are ready to use without compromising cost or time. In this paper, the problem of IoT-enabled dynamic SS across multiple MCs is formulated in detail to enable an event-driven adaptive scheduling when the model is faced with three kinds of uncertainties (of the service market, service execution and the user side respectively). Experiments with different settings are also performed, which show the advantages of our proposed paradigm and optimization model.     

Model-driven migration of supervisory machine control architectures

Supervisory machine control is the high-level control in advanced manufacturing machines that is responsible for the coordination of manufacturing activities. Traditionally, the design of such control systems is based on finite state machines. An alternative, more flexible approach is based on task-resource models. This paper describes an approach for the migration of supervisory machine control architectures towards this alternative approach. We propose a generic migration approach based on model transformations that includes normalisation of legacy architectures before their actual transformation. To this end, we identify a number of key concerns for supervisory machine control and a corresponding normalised design idiom. As such, our migration approach constitutes a series of model transformations, for which we define transformation rules. We illustrate the applicability of this model-driven approach by migrating (part of) the supervisory control architecture of an advanced manufacturing machine: a wafer scanner developed by ASML. This migration, towards a product-line architecture, includes a change in architectural paradigm from finite state machines to task-resource systems.     

Manufacturing plant control challenges and issues

Enterprise control system integration between business systems, manufacturing execution systems and shop-floor process-control systems remains a key issue for facilitating the deployment of plant-wide information control systems for practical e-business-to-manufacturing industry-led issues. Achievement of the integration-in-manufacturing paradigm based on centralized/distributed hardware/software automation architectures is evolving using the intelligence-in-manufacturing paradigm addressed by IMS industry-led R&D initiatives. The remaining goal is to define and experiment with the next generation of manufacturing systems, which should be able to cope with the high degree of complexity required to implement agility, flexibility and reactivity in customized manufacturing. This introductory paper summarizes some key problems, trends and accomplishments in manufacturing plant control before emphasizing for practical purposes some rationales and forecasts in deploying automation over networks, holonic manufacturing execution systems and their related agent-based technology, and applying formal methods to ensure dependable control of these manufacturing systems.     

Product architecting for personalization

Personalization is an emerging manufacturing paradigm whereby customers can tailor products to their individual needs while maintaining high production efficiency. This paradigm necessitates “personalized product architecting” for determination of customizable/personalizable product modules and cost-effective manufacturing methods. This paper presents an initial effort in developing a method for identifying appropriate product architectures and manufacturing resolutions to achieve personalization considering functional utility and manufacturing cost. Ergonomic experiments and conjoint analysis are implemented to build functions relating manufacturability, price, and utility. Using these functions, a case study based on shoe products is conducted and the common integer programming welfare problem is expanded to a mixed-integer programming optimization problem for determination of a product family incorporating both personalized and customized offerings.     

Classifying U.S. manufacturing plant locations using an artificial neural network

This paper examines the application of an artificial neural network (ANN) for classifying the contiguous states in the USA according to their manufacturing climate. The application uses a self-organizing paradigm, the ART2. The performance of the ANN was very encouraging. Its results were compared to those obtained from a scoring model that ranked the states utilizing the same criteria. Future work is intended to further improve the network's performance and develop an Artificial Neural System (ANS) that will assist decision makers in selecting the best locations for manufacturing facilities in the U.S.A. The ANS is seen as a key component of an intelligent decision support system for improving and enhancing plant location decision making.     

A two-layer social network model for manufacturing service composition based on synergy: A case study on an aircraft structural part

Cloud manufacturing is an emerging manufacturing paradigm, with the issue of service composition being one of its most significant challenges. The current researches take the view that all manufacturing services are of equal importance. However, in fact, manufacturing services that owns scarce resources are more important than ordinary one, especially in the production of complex products. Hence, it is significant to meet the requirements of manufacturing services that own scarce resources first. Meanwhile, due to the increasing complexity of products, a high degree of synergy is required in service composition. Our study explores a new framework of social relationships from the perspective of synergy. A two-layer social network model is first proposed for resource allocation that takes synergy and priority into account. The upper layer of this model is occupied by the manufacturing services with scare resources. The lower layer is occupied by ordinary manufacturing services. All services are connected by social relationships. For the master-slave characteristic of the model, the two-layer network is embedded into bi-level programming. Then, an improved genetic algorithm is designed to solve the problem. Finally, the effectiveness of the model and algorithm are verified using a structural part of the Modern Ark 60 as an example.     

Applications of agent-based systems in intelligent manufacturing: An updated review

Agent technology has been recognized as a promising paradigm for next generation manufacturing systems. Researchers have attempted to apply agent technology to manufacturing enterprise integration, enterprise collaboration (including supply chain management and virtual enterprises), manufacturing process planning and scheduling, shop floor control, and to holonic manufacturing as an implementation methodology. This paper provides an update review on the recent achievements in these areas, and discusses some key issues in implementing agent-based manufacturing systems such as agent encapsulation, agent organization, agent coordination and negotiation, system dynamics, learning, optimization, security and privacy, tools and standards.