参数Kleene系统中广义三-I算法的变化

介绍了参数K leene系统和参数K leene系统的三-I算法,并将它们在运算方法随参数值的变化进行比较.把K leene系统三-I算法归入到逻辑演算意义下,有助于在系统Kp中研究模糊推理.     

数控切削中粗车循环参数确定初探

介绍了G71循环加工指令的格式、各参数的含义及其确定方法,并给出了编程实例,以提高编程质量和加工效率．     

基于SIMPLIS软件的功率MOSFET寄生参数仿真研究

针对功率MOSFET关断时寄生参数对死区时间的影响问题,基于SIMPLIS仿真软件和MOSFET的特点,建立MOSFET的仿真分析模型,并研究MOSFET寄生参数与电路中米勒平台及关断时间的关系。建立MOSFET的寄生电容分段线性模型,应用Matlab软件实现参数的对比分析,根据内部器件的工作原理确定其转移特性和输出特性,利用图像数据获取MOSFET的等效模型,采用MOSFET搭建LLC谐振变换器电路,通过不同条件下的仿真实验,得到寄生参数的影响规律。一系列的仿真训练能够有效提高学生的仿真实践能力。     

Bond graph models of structured parameter uncertainties

Taking into account uncertainties in model parameter values is a crucial point for studying robustness in modeling and in control. This paper proposes to construct in a systematic and graphical procedure two forms of the linear state equation usually found in the literature for dealing with the robustness problem in the case of structured uncertainties on parameters. It is shown how to model uncertainties in a bond graph approach, in the case of additive or multiplicative parametric variations.     

含持久生存数据模型的识别问题

混合和非混合模型被广泛地用于拟合含有持久生存者的生存数据．当添加有协变量时,这两类模型却都不具有比例危险率(PH)结构．“不正确”比例危险率模型能克服上述缺点．本文研究此模型的识别问题．同时也考虑“不正确”的可加危险率(AH)模型的识别问题．本文的结果对模型的参数估计有重要意义．     

MATLAB在说话人识别算法中的应用

Matlab作为目前最流行的功能强大的软件,可用于说话人识别。在介绍说话人识别基本概念和原理的基础上,通过一个具体实例,说明如何用matlab的simulink工具箱提取特征参数、通过编程来进行对说话人识别的过程。最后给出了识别结果。     

贡蕉胚性细胞悬浮培养过程中几个参数的变化

以贡蕉（Musa acuminata cv．Mas）未成熟雄花序来源的胚性愈伤组织为材料建立了贡蕉胚性细胞悬浮系（Embryogenic cell suspensions,ECS）,测定了其培养过程中培养物的鲜重、干重及培养液的PH值、阿拉伯半乳糖蛋白（Arabinogala ctan proteins,AGPs）含量等生长参数在培养过程中的变化动态．结果表明：在培养周期内,培养物的鲜重在继代后第24d达到高峰,干重在继代后第21d达到高峰;培养液中的pH值表现为先下降,第3d下降到最低,随后开始升高;培养液中AGPs含量随培养天数而增加,在第14d含量达到最高,随后保持稳定状态．     

Spark作业性能建模及参数优化

Apache Spark分布式大数据计算框架应用广泛,但是其配置参数繁多导致使用难度较大,且不合理的配置将严重影响作业执行性能,研究Spark参数对性能的影响并进一步对参数进行自动优化具有重要意义。该文分析了Spark作业中影响系统行为的关键参数,建立了性能模型,并进一步探索了Spark参数自动优化的方法和策略。通过提取作业执行过程中对性能有影响的参数,对主流的19种回归模型进行了对比测试,获得通用性和拟合效果都比较好的6种回归模型,并针对不同类型的Spark任务在特定集群上建立性能模型,最后依据建立的性能模型在参数空间中利用改进的多起点爬山搜索算法寻找最优的参数组合。实验证明经参数优化后Spark作业性能有较大提升。     

Parameter Estimation Accuracy of the Effort-Moderated Item Response Theory Model Under Multiple Assumption Violations

As low-stakes testing contexts increase, low test-taking effort may serve as a serious validity threat. One common solution to this problem is to identify noneffortful responses and treat them as missing during parameter estimation via the effort-moderated item response theory (EM-IRT) model. Although this model has been shown to outperform traditional IRT models (e.g., two-parameter logistic [2PL]) in parameter estimation under simulated conditions, prior research has failed to examine its performance under violations to the model’s assumptions. Therefore, the objective of this simulation study was to examine item and mean ability parameter recovery when violating the assumptions that noneffortful responding occurs randomly (Assumption 1) and is unrelated to the underlying ability of examinees (Assumption 2). Results demonstrated that, across conditions, the EM-IRT model provided robust item parameter estimates to violations of Assumption 1. However, bias values greater than 0.20 SDs were observed for the EM-IRT model when violating Assumption 2; nonetheless, these values were still lower than the 2PL model. In terms of mean ability estimates, model results indicated equal performance between the EM-IRT and 2PL models across conditions. Across both models, mean ability estimates were found to be biased by more than 0.25 SDs when violating Assumption 2. However, our accompanying empirical study suggested that this biasing occurred under extreme conditions that may not be present in some operational settings. Overall, these results suggest that the EM-IRT model provides superior item and equal mean ability parameter estimates in the presence of model violations under realistic conditions when compared with the 2PL model.     

化工仪表及自动化课程改革初探

本论述了化工仪表及自动化课程改革的指导思想．提出了对化工仪表及自动化课程改革的具体措施和尝试，即增加应用和创新内容，培养学生应用技能和分析解决问题的能力。