基于项目驱动的高职IT实训平台开发

实训平台能提升IT从业人员的工作能力和企业的管理水平,用于高职院校的人才培养使毕业生的职业能力得到有效锻炼。该文从教学实践出发,设计了计算机技术IT实训平台建设方案,为职业教育的实训平台开发提供新的思路。     

基于Web Service的远程培训系统模型设计

介绍了Web服务的体系结构和一些主要的相关协议,分析了目前流行的分布式组件技术互操作存在的问题。在分析了WebService体系结构的基础上,针对当前远程培训系统存在的一些缺陷,研究并给出了一个基于WebService的远程教学系统的模型设计方案。该模型将本体论引入到领域知识的表示中提高了教学资源的重用和共享程度;同时,充分考虑了web以及用户环境所提供的与用户相关信息在智能教学系统中重要作用。此模型具有可扩展性、跨平台的机制,能够解决典型的Web服务中的安全问题。     

高职院校《人力资源管理》计算机仿真实训发展浅析

"以能力驱动,就业为导向"的高职教育,实训是其拉近学生与岗位需求之间距离的关键环节,而计算机仿真实训则是高职实训的一个有效途径。本文就"实训的有效途径、当前计算机仿真实训现状及其发展对策"等方面,阐述了当前的计算机仿真实训还处于起步阶段,我们应结合企业用人需求,集中资源,结合先进的计算机智能技术,深耕细作,进一步改进和完善仿真系统,使高职院校的《人力资源管理》课程,理论与实践紧密结合,培养更符合社会需求。     

高职院校“订单式”人才培养模式之跨国比较

"订单式"人才培养模式,楔合了高职院校和用人企业在人才供需方面的共同利益点,是高职院校人才培养模式的未来发展方向,是解决高职学生就业的有力措施。本文通过对国内国外高职"订单式"人才培养模式比较,借鉴发达国家的成功经验,提供国内高职院校参考,以探索、创新出一条有中国特色的"订单式"人才培养模式的新路。     

计算机仿真技术在程控交换机业务训练中的应用

针对程控交换机业务训练中存在的难题,提出了利用计算机仿真技术进行程控交换机业务模拟训练的思想。并通过具体模型的设计,指出了实现的方法和途径。     

"软件蓝领"的培养与职业技术教育

本文阐述了我国软件业的人力资源现状，指出了软件蓝领的严重匮乏，说明培养软件蓝领的重要任务应落在职业技术教育这片阵地上。     

基于项目的学习在高职软件技术专业实训课程中的应用

文章阐述高职软件技术专业实训课程特点及其主体地位,详细论述基于项目的学习在高职软件技术专业实训课程教学的具体应用过程。实践表明,这一方法具有较好的教学效果。     

Coverage of a Planar Point Set With Multiple Robots Subject to Geometric Constraints

This paper focuses on the assignment of N discrete points among K geometrically constrained robots and determination of the order in which the points should be processed by the robots. This path planning problem is directly motivated by an industrial laser drilling system with two robots that are constrained to translate along a common line while satisfying collision avoidance constraints. The points lie on a planar base plate that translates normal to the axis of motion of the robots. The geometric constraints on the motions of the robots lead to constraints on points that can be processed simultaneously.We use a two step approach to solve the path planning problem: (1) Splitting Problem: Assign the points to the K robots, subject to geometric constraints, to maximize parallel processing of the points. (2) Ordering Problem: Find an order of processing the split points by formulating and solving a multidimensional Traveling Salesman Problem (TSP) in the if-tuple space with an appropriately defined metric to minimize the total travel cost. For K = 2, we solve the splitting problem optimally in O(N³) time by converting it to a maximum cardinality matching problem. Since this is too slow for large datasets, we also provide a greedy O(N log N) algorithm. We provide computational results showing that the greedy algorithm solution is very close to the optimal solution for large datasets. For the ordering problem we present local search based heuristics to improve the multidimensional TSP tour. We give computational results for the ordering problem and for the overall performance gain obtained (over a single robot system) by using our algorithm. Finally, we extend our approach to a K-robot system and give computational results for K = 4.     

基于人工智能的装备保障仿真训练系统

文章指出了构建基于人工智能技术的装备保障仿真训练系统的需要,阐述了基于人工智能的装备保障仿真训练系统的设计思想和系统体系结构。该系统以联邦式作战仿真为基础,采用先进的人工智能技术,将有利于提高我军装备保障仿真训练和装备保障法研究的水平,有助于提高装备保障指挥员的指挥决策能力。     

A novel training scheme for multilayered perceptrons to realize proper generalization and incremental learning

The response of a multilayered perceptron (MLP) network on points which are far away from the boundary of its training data is generally never reliable. Ideally a network should not respond to data points which lie far away from the boundary of its training data. We propose a new training scheme for MLPs as classifiers, which ensures this. Our training scheme involves training subnets for each class present in the training data. Each subnet can decide whether a data point belongs to a certain class or not. Training each subnet requires data from the class which the subnet represents along with some points outside the boundary of that class. For this purpose we propose an easy but approximate method to generate points outside the boundary of a pattern class. The trained subnets are then merged to solve the multiclass classification problem. We show through simulations that an MLP trained by our method does not respond to points which lies outside the boundary of its training sample. Also, our network can deal with overlapped classes in a better manner. In addition, this scheme enables incremental training of an MLP, i.e., the MLP can learn new knowledge without forgetting the old knowledge.     

使用BP网络改进K-means聚类效果

K-means 算法中的 k 值的确定和初始聚类中心的选择严重影响聚类效果。针对这一问题,本文提出使用 BP神经网络改进 K-means 聚类效果的方法。通过对聚类结果进行反复训练,调整聚类数,K-means 的聚类效果得到改善。采用人工数据和实际商业数据的实验证明该方法能有效地改善传统的聚类效果。     

DCS训练仿真器中控制站的OO设计与实现

本文针对传统的过程式软件设计存在的问题,根据ＤＣＳ训练仿真器的特点,结合面向对象系统设计技术,详细介绍了工业过程ＤＣＳ训练仿真器中控制站的面向对象设计与实现。     

滑动窗口数据流上多极值查询资源共享策略研究

为了提高在同一数据流上同时计算多个连续极值查询(MAX或MIN)时的处理能力,对查询间资源共享技术进行了研究.提出了一种称为"关键点集"的裁剪策略,系统仅需保存少量数据即可满足所有查询的需要.发掘多个查询间的相似性和可共享的计算存储资源,提出了一个多极值查询处理算法MCEQP.采用链表结构实现的该算法,当一个新数据到达时最多需要O(M K)时间即可更新全部K个查询的结果,其中M为关键点集包含数据的个数.MCEQP采用触发器驱动的方式,只在某些特定时刻才需要计算因数据失效引起的查询结果变化,更新K个查询结果所需时间为O(K).理论分析和实验证明,对于滑动窗口数据流上的多个极值查询,MCEQP算法在降低存储开销和提高性能方面均优于现有的通用方法.     

基于HLA的便携防空导弹集成演练系统的研究

为满足便携防空导弹模拟训练器的需求,结合正在研究的课题,设计了模拟训练系统的体系结构,描述了其功能特点.高层体系架构HLA是建模仿真领域的通用技术框架,虚拟现实技术是现代仿真技术的重要发展方向,解决了系统协同训练的问题并使模拟训练器的可视化效果大大提高.在简单介绍HLA/RTI并分析了该训练仿真系统的工作原理之上,提出了便携防空导弹集成演练系统基于HLA的技术解决方案,并初步实现了该训练仿真系统,最后对主要的联邦成员进行了说明并描述了防空训练的整个仿真过程,为相关系统的设计提供了参考.     

《电工实训》教学改革探索与实践

在对部分高校《电工实训》情况进行了解后,该文提出了几点《电工实训》教学改革的方法,并简要介绍了南昌航空大学工程训练中心《电工实训》课的实践情况。     

基于MFC的雷达模拟训练系统终端关键技术研究

雷达系统的模拟训练已成为部队训练的一种有效方式;在雷达模拟训练系统开发过程中,雷达终端显示的模拟是重点之一;为实现某雷达系统终端的模拟,达到逼真的效果,基于MFC开发环境,对雷达终端模拟中的坐标映射、目标点迹形成、目标编批消批、扫描线余辉模拟、屏幕闪烁消除等关键技术进行研究,能逼真地模拟实装终端的界面元素和显示效果;已成功应用于某雷达模拟训练系统终端设计,为训练操作手提供较真实的训练环境。     

A Convergent Hybrid Decomposition Algorithm Model for SVM Training

Training of support vector machines (SVMs) requires to solve a linearly constrained convex quadratic problem. In real applications, the number of training data may be very huge and the Hessian matrix cannot be stored. In order to take into account this issue, a common strategy consists in using decomposition algorithms which at each iteration operate only on a small subset of variables, usually referred to as the working set. Training time can be significantly reduced by using a caching technique that allocates some memory space to store the columns of the Hessian matrix corresponding to the variables recently updated. The convergence properties of a decomposition method can be guaranteed by means of a suitable selection of the working set and this can limit the possibility of exploiting the information stored in the cache. We propose a general hybrid algorithm model which combines the capability of producing a globally convergent sequence of points with a flexible use of the information in the cache. As an example of a specific realization of the general hybrid model, we describe an algorithm based on a particular strategy for exploiting the information deriving from a caching technique. We report the results of computational experiments performed by simple implementations of this algorithm. The numerical results point out the potentiality of the approach.      

Approximating common fixed points of asymptotically nonexpansive maps in uniformly convex Banach spaces

We introduce three-step iterative schemes with errors for two and three nonexpansive maps and establish weak and strong convergence theorems for these schemes. Mann-type and Ishikawa-type convergence results are included in the analysis of these new iteration schemes. The results presented in this paper substantially improve and extend the results due to [S.H. Khan, H. Fukhar-ud-din, Weak and strong convergence of a scheme with errors for two nonexpansive mappings, Nonlinear Anal. 8 (2005) 1295–1301], [N. Shahzad, Approximating fixed points of non-self nonexpansive mappings in Banach spaces, Nonlinear Anal. 61 (2005) 1031–1039], [W. Takahashi, T. Tamura, Convergence theorems for a pair of nonexpansive mappings, J. Convex Anal. 5 (1995) 45–58], [K.K. Tan, H.K. Xu, Approximating fixed points of nonexpansive mappings by the Ishikawa iteration process, J. Math. Anal. Appl. 178 (1993) 301–308] and [H.F. Senter, W.G. Dotson, Approximating fixed points of nonexpansive mappings, Proc. Amer. Math. Soc. 44 (1974) 375–380].     

Affective Temperature Control in Food SMEs using Artificial Neural Network

This paper highlights modeling affective temperature control in food small and medium-sized enterprises (SMEs). Modeling defined that workstation temperature set point could be controlled based on worker heart rate and workstation environment using Artificial Neural Network (ANN). The research objectives were: 1) to propose modeling affective temperature control in food SMEs based on heart rate and workstation environment; and 2) to develop an ANN model for predicting workstation temperature set point. Training and validation data were collected from six food SMEs in Yogyakarta Special Region, Indonesia. The data of temperature set points were verified using a simulated confined room. The inputs of the ANN model were worker heart rate, workstation temperature, relative humidity distribution and light intensity. The output was temperature set point. Research results concluded satisfactory performance of ANN. The model could be used to provide environmental ergonomics in food SMEs.     

Assessment of Resource Scheduling Changes on Flight Training Effectiveness Using Discrete Event Simulation

This study presented a resource scheduling model of the Flight Training Department at Embry Riddle Aeronautical University's Daytona Beach Campus built using Discrete Event Simulation, to assess the effect of changes in the resources available to students in Flight Training Device (FTD) course modules on Flight Training effectiveness. Historical data from the Flight Training Department was used to build and validate the model. Results showed that, on average, students who had more resources available to them during FTD modules completed the training program 1 day earlier than those in the current system. As well, Cessna 172 and PA44 Aircraft average daily utilization increased whereas Cessna 172 S and PA44 FTD average daily utilization decreased. These results are discussed and conclusions are given at the end of this paper. © 2012 Wiley Periodicals, Inc.