基于学科竞赛的中医药类院校程序设计课程教学模式的探索

高素质人才培养是我国可持续发展战略、科教兴国战略以及人才强国战略等多项发展战略的一项基础性工程。本文针对中医药类院校程序设计类课程实践教学模式单一等教学实际，以“学科竞赛”为平台，“赛教结合”为理念，以《C语言程序设计》为例，从现存问题、赛教结合模式的引入、建立实施及其评价机制4个方面展开阐述，旨在提高学生学习积极性和能力。     

Exactly satisfying initial conditions neural network models for numerical treatment of first Painlevé equation

In this paper, novel computing approach using three different models of feed-forward artificial neural networks (ANNs) are presented for the solution of initial value problem (IVP) based on first Painlevé equation. These mathematical models of ANNs are developed in an unsupervised manner with capability to satisfy the initial conditions exactly using log-sigmoid, radial basis and tan-sigmoid transfer functions in hidden layers to approximate the solution of the problem. The training of design parameters in each model is performed with sequential quadratic programming technique. The accuracy, convergence and effectiveness of the proposed schemes are evaluated on the basis of the results of statistical analyses through sufficient large number of independent runs with different number of neurons in each model as well. The comparisons of these results of proposed schemes with standard numerical and analytical solutions validate the correctness of the design models.     

Weighted Superposition Attraction (WSA): A swarm intelligence algorithm for optimization problems – Part 2: Constrained optimization

This paper is the second one of the two papers entitled “Weighted Superposition Attraction (WSA) Algorithm”, which is about the performance evaluation of the WSA algorithm in solving the constrained global optimization problems. For this purpose, the well-known mechanical design optimization problems, design of a tension/compression coil spring, design of a pressure vessel, design of a welded beam and design of a speed reducer, are selected as test problems. Since all these problems were formulated as constrained global optimization problems, WSA algorithm requires a constraint handling method for tackling them. For this purpose we have selected 6 formerly developed constraint handling methods for adapting into WSA algorithm and analyze the effect of the used constraint handling method on the performance of the WSA algorithm. In other words, we have the aim of producing concluding remarks over the performance and robustness of the WSA algorithm through a set of computational study in solving the constrained global optimization problems. Computational study indicates the robustness and the effectiveness of the WSA in terms of obtained results, reached level of convergence and the capability of coping with the problems of premature convergence, trapping in a local optima and stagnation.     

Usability of a cloud-based collaborative learning framework to improve learners’ experience

Computer-Supported Collaborative Learning (CSCL) is concerned with how Information and Communication Technology (ICT) might facilitate learning in groups which can be co-located or distributed over a network of computers such as Internet. CSCL supports effective learning by means of communication of ideas and information among learners, collaborative access of essential documents, and feedback from instructors and peers on learning activities. As the cloud technologies are increasingly becoming popular and collaborative learning is evolving, new directions for development of collaborative learning tools deployed on cloud are proposed. Development of such learning tools requires access to substantial data stored in the cloud. Ensuring efficient access to such data is hindered by the high latencies of wide-area networks underlying the cloud infrastructures. To improve learners’ experience by accelerating data access, important files can be replicated so a group of learners can access data from nearby locations. Since a cloud environment is highly dynamic, resource availability, network latency, and learner requests may change. In this paper, we present the advantages of collaborative learning and focus on the importance of data replication in the design of such a dynamic cloud-based system that a collaborative learning portal uses. To this end, we introduce a highly distributed replication technique that determines optimal data locations to improve access performance by minimizing replication overhead (access and update). The problem is formulated using dynamic programming. Experimental results demonstrate the usefulness of the proposed collaborative learning system used by institutions in geographically distributed locations.     

Restructuring bank networks after mergers and acquisitions: A capacitated delocation model for closing and resizing branches

During restructuring processes, due to mergers and acquisitions, banks frequently face the problem of having redundant branches competing in the same market. In this work, we introduce a new Capacitated Branch Restructuring Model which extends the available literature in delocation models. It considers both closing down and long term operations׳ costs, and addresses the problem of resizing open branches in order to maintain a constant service level. We consider, as well, the presence of competitors and allow for ceding market share whenever the restructuring costs are prohibitively expensive.We test our model in a real life scenario, obtaining a reduction of about 40% of the network size, and annual savings over 45% in operation costs from the second year on. We finally perform a sensitivity analysis on critical parameters. This analysis shows that the final design of the network depends on certain strategic decisions concerning the redundancy of the branches, as well as their proximity to the demand nodes and to the competitor׳s branches. At the same time, this design is quite robust to changes in the parameters associated with the adjustments on service capacity and with the market reaction.     

A high performance crashworthiness simulation system based on GPU

Crashworthiness simulation system is one of the key computer-aided engineering (CAE) tools for the automobile industry and implies two potential conflicting requirements: accuracy and efficiency. A parallel crashworthiness simulation system based on graphics processing unit (GPU) architecture and the explicit finite element (FE) method is developed in this work. Implementation details with compute unified device architecture (CUDA) are considered. The entire parallel simulation system involves a parallel hierarchy-territory contact-searching algorithm (HITA) and a parallel penalty contact force calculation algorithm. Three basic GPU-based parallel strategies are suggested to meet the natural parallelism of the explicit FE algorithm. Two free GPU-based numerical calculation libraries, cuBLAS and Thrust, are introduced to decrease the difficulty of programming. Furthermore, a mixed array and a thread map to element strategy are proposed to improve the performance of the test pairs searching. The outer loop of the nested loop through the mixed array is unrolled to realize parallel searching. An efficient storage strategy based on data sorting is presented to realize data transfer between different hierarchies with coalesced access during the contact pairs searching. A thread map to element pattern is implemented to calculate the penetrations and the penetration forces; a double float atomic operation is used to scatter contact forces. The simulation results of the three different models based on the Intel Core i7-930 and the NVIDIA GeForce GTX 580 demonstrate the precision and efficiency of this developed parallel crashworthiness simulation system.     

p-Median and p-dispersion problems: A bi-criteria analysis

Given a collection of n locations and a symmetric measure of distance (difference) between each pair of locations, we seek to identify (select) a subset of p locations so as to achieve two distinct objectives. The first objective is to use the selected locations as centers (medians) of p groups that would partition the entire collection and minimize the total distance between the locations and their respective group medians. The second objective is to maximize the minimum distance (diversity) among the selected locations themselves. We study this problem as a multi-objective optimization problem and propose an iterative algorithm to obtain its non-dominated frontier. At each iteration we construct and solve a 0–1 integer programming problem. Through a computational experiment we show that this algorithm is computationally effective for small to medium size instances of the problem. We also propose a Lagrangian heuristic algorithm for solving larger instances of this problem.     

基于承包商预期收益不变的不平衡报价模型

在招标实践中,通常采用最低价中标原则,使得投标人不得不压低其投标价格。基于承包商预期收益不变的不平衡报价模型,是在“工程量清单报价”的条件下,考虑到施工中工程量的变化及施工顺序的影响,体现了资金的时间价值,在保持承包商预期收益不变的前提下,通过调整各分项工程的单价,来降低工程报价,以增加中标机会而建立的。所建立的模型简单,易于操作,并配以具体的工程实例,通过计算机求得其最优解,可供承包商投标报价时参考。     

HART通信协议在汽油机速度测量和监控方面的应用

首先介绍了HART通信协议及他的优点，然后介绍了HART通信协议在汽油机测速方面的软件实现。该软件主要采用目前流行的VB编程语言。可设计出界面友好、功能强大的测量和监控软件。     

结构化编程实现Sniffer

随着各高校校园网络规模的不断扩大和各种应用的急剧增加,各种新的网络问题也在不断出现。Sniffer是网络管理员进行网络管理的有效工具,可以有效地对网络进行实时监控,及时发现网络中存在的各种问题。本文首先介绍了Sniffer的工作原理,其次给出了实现Sniffer功能的编程流程图,并用C语言给出了编程所需的关键代码。