高职计算机专业学生评价体系的探索

在德国职业教育的影响下,高职计算机专业教育开始推行任务驱动,工作过程导向的教育模式,但是其教育评价体系还没有与教学模式相统一,实现与对应就业岗位需求的完美结合。高职计算机专业教育评价体系包含了很多方面,本文主要从学生学习效果的评价体系进行探索。     

PSO和K均值混合分类算法在远程教学系统中的应用

现行的多数网络教学系统在学生按需学习和＂因材施教＂上存在局限性,本文用PSO和K均值的混合分类算法对传统的网络教学系统进行改进,根据获取的用户基本信息和兴趣特征进行聚类,充分体现＂以学习者为中心＂个性化教学模式。实验结果表明,该算法具有较好的全局收敛性,寻优能力明显提升。     

Test frame updating in CPM testing of Prolog programs

Category Partition Method (CPM) is a general approach to specification-based program testing, where test frame reduction and refinement are two important issues. Test frame reduction is necessary since too many test frames may be produced, and test frame refinement is important since during CPM testing new information about test frame generation may be achieved and considered incrementally. Besides the information provided by testers or users, implementation related knowledge offers alternative information for reducing and refining CPM test frames. This paper explores the idea by proposing a call patterns semantics based test frame updating method for Prolog programs, in which a call patterns analysis is used to collect information about the way in which procedures are used in a program. The updated test frames will be represented as constraints. The effect of our test frame updating is two-fold. On one hand, it removes “uncared” data from the original set of test frames; on the other hand, it refines the test frames to which we should pay more attention. The first effect makes the input domain on which a procedure must be tested a subset of the procedure’s input domain, and the latter makes testers stand more chance to find out the faults that are more likely to show their presence in the use of the program under consideration. Our test frame updating method preserves the effectiveness of CPM testing with respect to the detection of faults we care. The test case generation from the updated set of test frames is also discussed. In order to show the applicability of our method an approximation call patterns semantics is proposed, and the test frame updating on the semantics is illustrated by an example.

Utilize bootstrap in small data set learning for pilot run modeling of manufacturing systems

If the production process, production equipment, or material changes, it becomes necessary to execute pilot runs before mass production in manufacturing systems. Using the limited data obtained from pilot runs to shorten the lead time to predict future production is this worthy of study. Although, artificial neural networks are widely utilized to extract management knowledge from acquired data, sufficient training data is the fundamental assumption. Unfortunately, this is often not achievable for pilot runs because there are few data obtained during trial stages and theoretically this means that the knowledge obtained is fragile. The purpose of this research is to utilize bootstrap to generate virtual samples to fill the information gaps of sparse data. The results of this research indicate that the prediction error rate can be significantly decreased by applying the proposed method to a very small data set.     

城市轨道交通电力监控系统测试的研究及应用

针对电力监控系统具有实时性、可靠性、硬件依赖等特点,为了保证电力监控系统的可靠、安全和稳定性。提出了适用于该系统的测试方法。根据系统的特点制定了相应的测试策略,并进行了测试的总体设计和测试用例的设计。最后通过对测试环境的分析,开发了相应的模拟器。通过模拟器和测试用例实现了测试的自动化。根据测试的过程和结果表明,采用正确的测试设计方法能够有效的发现系统中存在的问题,保证系统的质量。     

民政低保系统中基于XML的数据交换浅析

该文主要介绍电子政务在我国的发展,低保信息系统概述,重点阐述低保信息系统中面临的数据交换问题,并对基于XML的数据交换平台的构建进行分析。     

基于DS18B20的温度测量系统

以温度的采集处理和显示为目的,研究了基于AT89S51单片机的温度检测及显示的设计方法,给出了硬件和软件系统设计,包括温度传感器芯片的选取、单片机与温度传感器的接口设计以及实现温度采集和数据传输的软件设计。该系统结构简单,成本较低,体积小,测温范围为-55℃～125℃,可以应用在很多温度检测领域。     

一种分布式拒绝服务攻击的检测方法

该文提出和实现了一种基于网络异常流量特征的检测模型。通过将多条链路或多个流的流量信号作为一个整体进行研究,构建了网络异常流量监控的系统模型。该模型包括了数据采集、分析、异常判断和警告等功能,并综合了异常信息融合及警告信息关联性分析技术。通过实验证明,该套系统模型对短时间段内的突发流量能提供有效的检测和报警服务。     

高职院校计算机专业现状分析及对策——以黄冈职业技术学院计算机专业为例

该文也就高职院校计算机专业改革进行若干的设想,从课程体系、学生结构、教师知识结构等方面的改革进行分析总结。     

运输车辆安全体系评价的研究

该文通过对车辆安全因数的分析、得出子危险集。在分析评价方法特征技术上应用了选用模糊推理模型(FIS)的评价方法对车辆的危险度进行评价与仿真,其结果是可信的。实现了对车辆安全进行量态和动态的评价体系。