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。     

并联混合动力汽车动力源参数设计及模糊控制策略的建模仿真分析

根据汽车道路行驶的数学模型计算并联混合动力汽车驱动电机和发动机的各项参数,设计模糊控制策略控制驱动电机和发动机协调工作,使用Matllab/Simulink软件和Advisor汽车仿真软件联合建模仿真。在建模过程中,将上述计算结果输入Advisor汽车模型中,设置汽车的行驶工况、最高车速、加速时间和爬坡能力4个计算任务,并运行计算任务。仿真结果表明:汽车驱动电机和发动机的参数能匹配汽车整车参数、性能要求,模糊控制策略能在保证汽车整车性能要求的前提下进一步减少燃油消耗和尾气排放物,表明本驱动电机和发动机参数匹配设计方法、模糊控制策略均可行。     

整数规划中精确罚函数的一般形式

In this paper, the general exact penalty functions in integer programming were studied. The conditions which ensure the exact penalty property for the general penalty function with one penalty parameter were given and a general penalty function with two parameters was proposed.     

微波杀菌处理牛肉干效果研究

本文对微波杀菌处理牛肉干的应用效果进行研究,通过对影响牛肉干杀菌效果的主要因素,即微波处理机的阳极电流、传送链速、牛肉干的厚度三个因素进行正交试验,并对主要因素影响杀菌效果的实质原因进行探讨.结果表明:对于牛肉干两种品牌的杀菌最佳工艺参数分别为:阳极电流0.2A、0.4A,传送链速1100r/d、1100r/d,牛肉干厚度20mm、20 mm.     

多变量系统的结构辩识和参数估计

将单输入 单输出 (SISO)系统的递推辩识算法推广到多变量的情形 ,这种最小二乘类型的算法结构简洁且可同时给出具有良好数值性质的模型结构和参数辩识。证明了多变量输入 输出差分方程模型与其对应的标准状态空间模型可以经变换而由一种模型得到另一种模型。该算法与对应的最小二乘递推算法比较更易于理解和实现     

非光滑半无限规划调节熵函数法

对一类非光滑半无限规划,利用调节熵函数性质,得到两种算法,并分别讨论了它们的收敛性·     

基于2PLM项目参数估计的病态矩阵控制

病态矩阵是IRT理论中项目参数估计必然面对的问题．本文以2PLM参数估计为例．推导出参数估计迭代公式，系统阐述了三种病态控制方法的原理及在编程中数据处理的技巧。     

Using the United States Census Data to Introduce Differential Equations

Abstract

This article describes a method for using the United States Census data to open a differential equations course. The question of finding a model for the United States population data gives students a first experience with creating a model using differential equations, and also understanding derivatives, what they mean, and how to calculate them in the context of real data. This model-building start motivates further exploration in many of the standard differential equations topics: the method of separation of variables, slope fields, autonomous equations, equilibria, and stability.