信息论与编码的混合式教学设计与实践

混合式教学将线上教学与传统课堂相融合,有效地提升了教学质量和学习效果。本文基于信息论与编码的课程特点和学情分析,设计了具有普适性的混合式教学模式,包括课前自主学习、课中深化学习、课后拓展学习的教学过程。通过实践证明该方案具有较好的应用效果,能更好地培养学生的自主学习、独立思考、实践创新的能力,并通过面对面高效互动,实现了个性化指导和因材施教的目的,对高校专业课程教学改革的推广和运用有指导性意义。     

GaN基高电子迁移率晶体管器件的可靠性及退化机制研究进展

GaN基高电子迁移率晶体管（high electron mobility transistor,HEMT）器件在航天、通讯、雷达、电动汽车等领域具有广泛的应用,近年来成为电力电子器件的研究热点。在实际应用中,GaN基HEMT器件随着使用时间的延长会发生退化甚至失效的情况,器件的可靠性问题仍是进一步提高HEMT器件应用的绊脚石。因此,研究器件的可靠性及退化机制对于进一步优化器件性能具有极其重要的意义。将从影响器件可靠性的几个关键因素如高电场应力、高温存储、高温电场和重离子辐照等进行阐述,主要对近几年文献里报道的几种失效机制及相应的失效现象进行了综述和总结,最后讨论了进一步优化器件可靠性的措施,对进一步提高HEMT器件的应用起促进作用。     

General and efficient parallel approach of finite element-boundary integral-multilevel fast multipole algorithm

A general and efficient parallel approach is proposed for the first time to parallelize the hybrid finiteelement-boundary-integral-multi-level fast multipole algorithm （FE-BI-MLFMA）. Among many algorithms of FE-BI-MLFMA, the decomposition algorithm （DA） is chosen as a basis for the parallelization of FE-BI-MLFMA because of its distinct numerical characteristics suitable for parallelization. On the basis of the DA, the parallelization of FE-BI-MLFMA is carried out by employing the parallelized multi-frontal method for the matrix from the finiteelement method and the parallelized MLFMA for the matrix from the boundary integral method respectively. The programming and numerical experiments of the proposed parallel approach are carried out in the high perfor- mance computing platform CEMS-Liuhui. Numerical experiments demonstrate that FE-BI-MLFMA is efficiently parallelized and its computational capacity is greatly improved without losing accuracy, efficiency, and generality.     

Adaptive SPC monitoring scheme for DOE-based APC

Automatic process control （APC） based on design of experiment （DOE） is a cost-efficient approach for variation reduction. The process changes both in mean and variance owing to online parameter adjustment make it hard to apply traditional SPC charts in such DOE-based APC applied process. An adaptive SPC scheme is developed, which can better track the process transitions and achieve the possible SPC run cost reduction when the process is stable. The control law of SPC parameters is designed by fully utilizing the estimation properties of the process model instead of traditionally using the data collected from the production line. An example is provided to illustrate the proposed adaptive SPC design approach.     

基于目标导向的多属性决策属性价值公度方法

MACBETH方法在多个属性维度上确定出的一组属性Good值(或Neutral值)并不能真地具有保证属性价值公度的完全相同的偏好涵义.为克服该方法缺陷,基于包容性属性价值函数,通过引入数据包络分析技术和马尔可夫理论给出了以目标参照方案为导向的目标导向属性价值函数和多属性决策属性价值公度的方法程序.相比于具有较大随意性确定属性Good值和Neutral值的MACBETH方法,依赖目标导向属性价值函数的多属性决策属性价值公度程序具有更明显的科学合理性,因此具有发展MACBETH方法,推动实际决策应用该方法及相关多属性偏好关联决策模型的创新价值.基于决策实验的应用分析直接验证了多属性决策属性价值公度方法程序的科学有效性,间接验证了包容性属性价值函数和目标导向属性价值函数的科学理性.     

Optimal bundling and pricing decisions for complementary products in a two-layer supply chain

This article explores bundling and pricing decisions for two complementary products in a two-layer supply chain consisting of a multi-product manufacturer and a retailer. We establish four different pricing models under cases of decentralized decision, while considering different portfolio-bundling strategies of the manufacturer and the retailer. A game-theoretical method is used to characterize the corresponding equilibrium outcomes in each scenario. By further analyzing and comparing the maximum profits of all four possible scenarios, optimal bundling and pricing decisions for the manufacturer and the retailer are obtained, respectively. Model extensions and numerical examples are enriched to highlight the factors affecting optimal decision-making. Finally, valuable and interesting managerial insights are summarized. Results show that the upstream manufacturer always profits more when he sells complementary products separately. However, the optimal bundling decision of the downstream retailer is jointly determined by product complementarity (as a major factor) and the difference of product profitability (as a secondary factor). Market power cannot exert an influence on both optimal bundling decisions, but it can partly affect pricing decisions.     

基于广义出行成本的出行方案优化

为了使出行成本更加符合出行者的认知规律,运用结构方程建模方法模拟出行成本,个体特征及出行决策之间的影响关系.引入敏感系数调整服务属性在出行成本中的贡献率,利用出行意愿调查数据对敏感系数进行标定.考虑出行者对抵达时刻的选择偏好,假设行程时间服从正态分布条件下,对最佳出发时刻及期望出行成本进行寻优求解,结果表明它取决于期望到达时刻,行程时间的期望值及方差,出行者对早到损失及晚到延误损失时间成本的相对大小.研究成果可为制定个性化及最优化出行决策方案提供依据.     

一种基于工作流网的游戏作弊检测系统

游戏作弊对网络游戏危害很大,目前反作弊技术的瓶颈是效率低并且过多依赖于签名匹配。提出一种高效且不依赖于签名匹配的游戏作弊检测系统,用工作流网对作弊行为建模,通过流程树对作弊行为模型进行融合,在不影响检测结果的前提下节省存储空间。用热门网游的作弊软件对系统进行实验,存储空间降低率达到约60%,证明了该系统框架是可行、有效的。     

修正AHP中判断矩阵一致性的加速遗传算法

作为系统工程中典型的定性定量综合集成方法,层次分析法(AHP)在各种复杂系统综合评价和多目标决策中具有广泛的应用价值.为修正AHP中判断矩阵的一致性,提出了用加速遗传算法同时修正判断矩阵一致性和计算AHP中各要素的排序权值的新方法(AGA-CAHP).理论分析和实例分析的初步结果说明:AGA-CAHP法直观、实用,计算结果稳定、精度高,在系统工程中具有推广应用价值.     

一类仓库作业优化问题的混合遗传算法研究

针对自动化立体仓库固定货架系统中拣选作业优化问题的特点, 分析并设计了一种新型高效混合遗传算法。提出了多起点2-最近点搜索算法进行初始种群的构造,采用了一种新的自适应启发式变异方法,显著改善了原有遗传算法的搜索能力。仿真结果表明该算法从执行时间和优化效果两方面均能够很好地满足作业要求。