基于矢量图形的G代码自动生成软件路径优化算法的研究

分析矢量图形的数据格式,并对矢量图形有效数据提取及G代码自动生成软件的路径优化算法进行研究。实践证明,该算法切实可行。     

双层空气板线装配要点

双层空气板线是我所早期雷达天线中的一个重要组成部分,装配质量直接影响到电测性能指标,本文通过对双层空气板线装配流程的介绍,提出装配过程中的一些要点,可作为初级操作人员装配时做出借鉴。     

浅谈广州广电运营商信息化建设规划

在信息经济时代,信息化已经对企业管理理念和经营模式产生了深远的影响,是企业实现其战略目标的重要保证.在广电逐步拥抱三网融合的今天,科学的信息化建设规划是广电实现业务转型、求变革、谋发展的重要手段之一.主要通过分析总结广州有线电视运营商的信息化建设情况,结合企业信息化建设的原则及业务发展的预测,提出了适用的应用系统信息化建设规划.     

Mathematical Model of Proton Exchange Membrane Fuel Cell with Consideration of Water Management

One‐dimensional model on the membrane electrode assembly (MEA) of proton exchange membrane fuel cell is proposed, where the membrane hydration/dehydration and the possible water flooding of the respective cathode and anode gas diffusion layers are considered. A novel approach of phase‐equilibrium approximation is proposed to trace the water front and the detailed saturation profile once water emerges in either anode or cathode gas diffusion layer. The approach is validated by a semi‐analytical method published earlier. The novel approach is applicable to the polarization regime from open circuit voltage to the limiting current density under practical operation conditions. Oxygen diffusion is limited by water accumulation in the cathode gas diffusion layer as current increases, caused by excessive water generation at the cathode catalyst layer and the electro‐osmotic drag across the membrane. The existence of liquid water in the anode gas diffusion layer is predicted at low current densities if high degrees of humidification in both anode and cathode feeds are employed. The influences of inlet relative humidity, imposed pressure drop, and cell temperature are correlated well with the cell performance. In addition, the overpotentials attributed from individual components of the MEA are delineated against the cell current densities.     

一种移动机器人的路径规划算法

本文提出一种移动机器人路径规划最短切线路径算法。依据此算法，机器人能顺利地避开障碍物到达目标位置，其原理简单，计算快捷，容易实现。仿真结果验证了它的有效性和实用性。     

Synthy: A system for end to end composition of web services

The demand for quickly delivering new applications is increasingly becoming a business imperative today. However, application development is often done in an ad hoc manner resulting in poor reuse of software assets and longer time-to-delivery. Web services have received much interest due to their potential in facilitating seamless business-to-business or enterprise application integration. A web service composition system can help automate the process, from specifying business process functionalities, to developing executable workflows that capture non-functional (e.g. Quality of Service (QoS)) requirements, to deploying them on a runtime infrastructure. Intuitively, web services can be viewed as software components and the process of web service composition similar to software synthesis. In addition, service composition needs to address the build-time and runtime issues of the integrated application, thereby making it a more challenging and practical problem than software synthesis. However, current solutions based on business web services (using WSDL, BPEL, SOAP, etc.) or semantic web services (using ontologies, goal-directed reasoning, etc.) are both piecemeal and insufficient. We formulate the web service composition problem and describe the first integrated system for composing web services end to end, i.e., from specification to deployment. The proposed solution is based on a novel two-staged composition approach that addresses the information modeling aspects of web services, provides support for contextual information while composing services, employs efficient decoupling of functional and non-functional requirements, and leads to improved scalability and failure handling. We also present Synthy, a prototype of the service composition system, and demonstrate its effectiveness with the help of an application scenario from the telecom domain.     

A knowledge intensive multi-agent framework for cooperative/collaborative design modeling and decision support of assemblies

Multi-agent modeling has emerged as a promising discipline for dealing with decision making process in distributed information system applications. One of such applications is the modeling of distributed design or manufacturing processes which can link up various designs or manufacturing processes to form a virtual consortium on a global basis. This paper proposes a novel knowledge intensive multi-agent cooperative/collaborative framework for concurrent intelligent design and assembly planning, which integrates product design, design for assembly, assembly planning, assembly system design, and assembly simulation subjected to econo-technical evaluations. An AI protocol based method is proposed to facilitate the integration of intelligent agents for assembly design, planning, evaluation and simulation process. A unified class of knowledge intensive Petri nets is defined using the O-O knowledge-based Petri net approach and used as an AI protocol for handling both the integration and the negotiation problems among multi-agents. The detailed cooperative/collaborative mechanism and algorithms are given based on the knowledge objects cooperation formalisms. As such, the assembly-oriented design system can easily be implemented under the multi-agent-based knowledge-intensive Petri net framework with concurrent integration of multiple cooperative knowledge sources and software. Thus, product design and assembly planning can be carried out simultaneously and intelligently in an entirely computer-aided concurrent design and assembly planning system.     

Learning and motivational couplings promote smarter behaviors of an animat in an unknown world

This paper reports on statistical results of an animat behavior in an unknown environment using a cognitive map. We study the coupling effect between the motivation for eating and the one for drinking. Some smart behaviors are not caused by a sophisticated “intelligent” algorithm, but only through coupling of the motivations. Adding a learning rule on the links of the cognitive map allows to reinforce particular paths, and to forget others. This also leads to reinforce the same “smart” behaviors.     

An enhanced genetic algorithm for automated assembly planning

Automated assembly planning reduces manufacturing manpower requirements and helps simplify product assembly planning, by clearly defining input data, and input data format, needed to complete an assembly plan. In addition, automation provides the computational power needed to find optimal or near-optimal assembly plans, even for complex mechanical products. As a result, modern manufacturing systems use, to an ever greater extent, automated assembly planning rather than technician-scheduled assembly planning. Thus, many current research reports describe efforts to develop more efficient automated assembly planning algorithms. Genetic algorithms show particular promise for automated assembly planning. As a result, several recent research reports present assembly planners based upon traditional genetic algorithms. Although prior genetic assembly planners find improved assembly plans with some success, they also tend to converge prematurely at local-optimal solutions. Thus, we present an assembly planner, based upon an enhanced genetic algorithm, that demonstrates improved searching characteristics over an assembly planner based upon a traditional genetic algorithm. In particular, our planner finds optimal or near-optimal solutions more reliably and more quickly than an assembly planner that uses a traditional genetic algorithm.     

Due date setting with supply constraints in systems using MRP

We propose a new model for quoting due dates in a make-to-order environment where customers request due dates. The model incorporates inventory costs, fill rate issues, and service level issues. In particular, we consider order delay costs that measure the positive difference between the due date requested by the customer and the due date committed by the supplier. The underlying two-stage production model assumes that production is constrained primarily by an uncertain procurement process, as is the case in many assembly systems. This simplification results in a news vendor-like formulation that enables us to obtain a simple approximately optimal due date setting policy that is well suited to MRP environments. The model also yields several interesting policy conclusions. For example, in environments where the importance of service level performance does not reach a certain threshold relative to the importance of order acceptance, the optimal policy is to always quote the requested due date. A special case of our formulation of the problem is to minimize lead-times. However, we show that a lead-time minimization often yields longer quoted due dates than our general formulation.