基于Perron—Frobenius特征值的传感器组网效能评估方法

随着当前各种类型的传感器不断涌现,将各类不同的传感器组网探测必将是今后的发展趋势,对传感器组网效能的分析自然成为重中之重。然而,当前对该问题的研究尚缺乏合适的网络模型和方法对其进行描述。基于此,构建了传感器网络环模型,并提出求取与该传感器网络相对应的邻接矩阵Perron—Frobenius特征值（PFE）的方法,同时通过算例分析了该传感器网络的组网效能,结果证明该方法结构明晰,简单可行,能较好的反映实际,适用于对各种传感器组网的网络化效能分析。     

Apriori算法在学生成绩管理中的应用

介绍了关联规则的基本概念及Apriori算法,提出了成绩预警模型,并利用Apriori算法进行了求解。所得到不及格课程之间的关联规则,可以为教师的教学管理及学生学习提供一定的指导和参考。     

模糊控制在磁悬浮球系统实时控制中的应用

在磁悬浮球系统中采用PID控制时,动态性能较差,控制效果不理想.为了获得控制效果较好的控制器,根据模糊控制原理,设计磁悬浮模糊控制器.根据PID实时控制中的经验,确定模糊控制器的输入输出变量模糊化范围,建立合理的模糊规则表.在Matlab/Simulink中组建实时控制模块,并分别对磁悬浮球系统在无干扰和有干扰下进行实时控制.对控制效果进行分析讨论,证明模糊控制器具有良好的鲁棒性和在非线性系统控制中的有效性.     

An experimental investigation of personality types impact on pair effectiveness in pair programming

In this paper, pair programming is empirically investigated from the perspective of developer personalities and temperaments and how they affect pair effectiveness. A controlled experiment was conducted to investigate the impact of developer personalities and temperaments on communication, pair performance and pair viability-collaboration. The experiment involved 70 undergraduate students and the objective was to compare pairs of heterogeneous developer personalities and temperaments with pairs of homogeneous personalities and temperaments, in terms of pair effectiveness. Pair effectiveness is expressed in terms of pair performance, measured by communication, velocity, design correctness and passed acceptance tests, and pair collaboration-viability measured by developers’ satisfaction, knowledge acquisition and participation. The results have shown that there is important difference between the two groups, indicating better communication, pair performance and pair collaboration-viability for the pairs with heterogeneous personalities and temperaments. In order to provide an objective assessment of the differences between the two groups of pairs, a number of statistical tests and stepwise Discriminant Analysis were used.

On guiding the augmentation of an automated test suite via mutation analysis

Mutation testing has traditionally been used as a defect injection technique to assess the effectiveness of a test suite as represented by a “mutation score.” Recently, mutation testing tools have become more efficient, and industrial usage of mutation analysis is experiencing growth. Mutation analysis entails adding or modifying test cases until the test suite is sufficient to detect as many mutants as possible and the mutation score is satisfactory. The augmented test suite resulting from mutation analysis may reveal latent faults and provides a stronger test suite to detect future errors which might be injected. Software engineers often look for guidance on how to augment their test suite using information provided by line and/or branch coverage tools. As the use of mutation analysis grows, software engineers will want to know how the emerging technique compares with and/or complements coverage analysis for guiding the augmentation of an automated test suite. Additionally, software engineers can benefit from an enhanced understanding of efficient mutation analysis techniques. To address these needs for additional information about mutation analysis, we conducted an empirical study of the use of mutation analysis on two open source projects. Our results indicate that a focused effort on increasing mutation score leads to a corresponding increase in line and branch coverage to the point that line coverage, branch coverage and mutation score reach a maximum but leave some types of code structures uncovered. Mutation analysis guides the creation of additional “common programmer error” tests beyond those written to increase line and branch coverage. We also found that 74% of our chosen set of mutation operators is useful, on average, for producing new tests. The remaining 26% of mutation operators did not produce new test cases because their mutants were immediately detected by the initial test suite, indirectly detected by test suites we added to detect other mutants, or were not able to be detected by any test.

可见光波段虚拟伪装场景的创建

提出基于Vue和Python的可见光波段虚拟伪装场景概念,重点阐述了不同探测方位、不同天气时段的虚拟伪装场景和动态虚拟伪装场景的创建流程,分析了该方法存在的问题并对下一步的工作进行了展望.基于Vue和Python的虚拟伪装场景在可见光波段伪装效果评估方面具有较好的应用前景和推广价值.     

基于网格的一种新的动态演化算法

近年来,越来越多的演化计算研究者对动态优化问题产生了很大的兴趣,并产生了很多解决动态优化问题的方法。提出一种新的动态演化算法,与传统的演化算法有所不同,它是建立在划分网格基础上的,故而称它为网格优化算法。通过测试典型的动态优化问题,并与经典的SOS算法进行比较,证明了算法的有效性。     

基于MSP430单片机的智能多功能电流测试仪

针对现有电源设备在测试电容和压敏电阻等元件的故障电流时,存在检测精度低、实时性差、电路复杂等问题,设计了一种基于MSP430F449单片机的新型智能多功能电流测试仪。该电流测试仪具有电路简单、灵敏度高、响应时间短、功耗低等特点,有推广应用价值。     

基于正负理想点的导弹武器系统作战效能评估

讨论了目前导弹武器系统作战效能评估中的几点不足,提出用正负理想点法来评估导弹武器系统的作战效能.首先给出评估模型.其次,通过对具有典型意义的5种空舰导弹武器系统作战效能进行分析,给出应用示例,并对评估效果进行分析,得出结论.     

基于领域知识的预警规则发现研究

预警有助于及时预防和解决隐患,具有重要的应用价值,受到了广泛的关注。提出了一种新的预警机制,以领域相关的预警知识为基础构建预警系统,重点研究了以实际数据为资源,基于背景领域知识挖掘出预警规则,使得预警系统中的预警知识更丰富、更完备、更具有实际应用价值。将上述研究应用于高校教学教务系统的学生成绩预警,实验结果表明所提出的预警机制和方法是有效的。