MATLAB在粗差探测中的应用

测量工作中,观测数据可能会带有粗差,从而给数据处理带来困难,因此必须及时的发现并剔除观测数据中的粗差。基于粗差检验的原理,利用MATLAB强大的计算能力用于粗差探测中,通过对实例从整体和局部进行假设检验分析,结果表明是有效的,可行的。     

语言测试理论与大学英语测试

依据Bachman和Palmer的语言测试原则,对浙江大学英语专业学生和非英语专业学生同时进行两份试卷测试。测试结果表明:CET和TEM无论对英语专业学生和非英语专业学生而言都具有区分度;非英语专业的学生并不绝对地比英语专业学生英语能力差。这两套试卷测试相关度很高,表明用统一的考试机制更能客观地反映各类学生的英语实际水平。     

基于网格部署的RFID阅读器失效预警算法研究

针对RFID阅读器网络中阅读器部署效率低、收敛慢等特征,提出了基于网格划分机制的静态RFID阅读器的部署方法,实现了二维平面结构和三维立体结构中阅读器的部署。并提出了当网络中RFID阅读器失效的距离向量失效预警算法。本文中提出的网格划分部署机制简单、高效、部署周期短,距离向量失效预警算法预警迅速、准确。     

辐射场的量子化哈密顿正则法

对光学问题进行全量子化处理,必须对辐射场进行量子化.文章用矢势和哈密顿正则方程的方法,将辐射场量子化.     

关于单参数正态分布族的双边假设检验问题的讨论

讨论单参数正态分布族的双边假设检验问题,是基于考虑在第一类错误的概率为α的检验类中如何求取一个第二类错误概率最小的检验。     

浅谈英语听力能力和应试技巧的提高

随着我国对外开放的不断深入,国际交往日益频繁,提高外语听力能力势必变得更为迫切,社会上各种英语考试对英语听力能力的要求也越来越高。本文试从听力学习中存在的问题和对策入手,对英语听力能力的培养和应试技巧进行探讨。     

曲线拟合的极小极大法

曲线拟合被应用于许多领域.文章提出了曲线拟合的极小极大法,通过研究极小极大剩余向量的计算方法,将问题转化为求解相容方程组问题.     

参量匹配滤波器和向量自回归滤波器的等价性

分析了自适应匹配滤波器和向量自回归(VAR)时域白化滤波器. 结果表明,通过最小化用误差平方之和估计的均方误差得到的参量滤波器系数和通过相同阶数的多通道最小二乘法得到的VAR滤波器系数是等价的. 此外,还分析了VAR滤波器最小二乘估计器的渐进性能,分析了滤波器的运算量和杂波抑制性能.     

药学专业有机化学实验考核方法的研究与实施

根据药学专业有机化学的基本要求,本文明确了有机化学考核目标,建立了考核方法和考核标准。教学实践结果表明,该考核方法和标准具有较强的可操作性,且能够调动学生实验的积极性和主动性,基本上能全面客观地评价学生的实验学习成绩。     

Latent Variable Modeling and Adaptive Testing for Experimental Cognitive Psychopathology Research

The adaptation of experimental cognitive tasks into measures that can be used to quantify neurocognitive outcomes in translational studies and clinical trials has become a key component of the strategy to address psychiatric and neurological disorders. Unfortunately, while most experimental cognitive tests have strong theoretical bases, they can have poor psychometric properties, leaving them vulnerable to measurement challenges that undermine their use in applied settings. Item response theory–based computerized adaptive testing has been proposed as a solution but has been limited in experimental and translational research due to its large sample requirements. We present a generalized latent variable model that, when combined with strong parametric assumptions based on mathematical cognitive models, permits the use of adaptive testing without large samples or the need to precalibrate item parameters. The approach is demonstrated using data from a common measure of working memory—the N-back task—collected across a diverse sample of participants. After evaluating dimensionality and model fit, we conducted a simulation study to compare adaptive versus nonadaptive testing. Computerized adaptive testing either made the task 36% more efficient or score estimates 23% more precise, when compared to nonadaptive testing. This proof-of-concept study demonstrates that latent variable modeling and adaptive testing can be used in experimental cognitive testing even with relatively small samples. Adaptive testing has the potential to improve the impact and replicability of findings from translational studies and clinical trials that use experimental cognitive tasks as outcome measures.