人事档案中出生时间和参加工作时间准确性刍议

本文指出了目前人事档案存在出生时间和参加工作时间互不一致的现象 ,及其此现象对组织人事工作的正常进行造成被动 ,并影响职工的个人利益 ,同时提出为避免这种现象的出现而采取的措施及对既成现象的应对办法。     

Classifying Data Sets Using Support Vector Machines Based on Geometric Distance

Support vector machines (SVMs) are not as favored for large-scale data mining as for pattern recognition and machine learning because the training complexity of SVMs is highly dependent on the size of data set. This paper presents a geometric distance-based SVM (GDB-SVM). It takes the distance between a point and classified hyperplane as classification rule, and is designed on the basis of theoretical analysis and geometric intuition. Experimental code is derived from LibSVM with Microsoft Visual C 6.0 as system of translating and editing. Four predicted results of five of GDB-SVM are better than those of the method of one against all (OAA). Three predicted results of five of GDB-SVM are better than those of the method of one against one (OAO). Experiments on real data sets show that GDB-SVM is not only superior to the methods of OAA and OAO, but highly scalable for large data sets while generating high classification accuracy.     

闭环系统的过采样辨识方法及其估计精度分析

A new identification method for a linear discrete-time closed-loop system is proposed based on an output over-sampling scheme. When the system outputs are over-sampled the new output sequences would contain more information about the plant structure. Using general least squares method （GLS） the plant over-sampled model should be recognized. Then the original plant model should be obtained by its relationship with the over-sampled model. Compared with conventional approaches the advantage of the new method is that even if the ordinary identifiability conditions are not satisfied, a close-loop system can be identified by using the oversampled output without utilizing any external test signal. Accuracy analysis shows the relationship between the estimation error and the over-sampling rate. Numerical simulation illnstrates its effectiveness.     

对络合滴定中滴定速度的探讨

该文选择络合滴定法,在不同滴定速度下对水硬度进行了实验测定,并就滴定结果对滴定速度的影响进行了分析和讨论．     

几种高精度差分格式的比较试验

具体比较了三种含基架网点少的高精度格式：紧致平方守恒格式、特征保形格式和特征Ｈｅｒｍｉｔｅ插值格式．实例表明前两种格式计算效果较好,第三种格式有明显位相差．     

求解泊松方程的高精度紧致差分方法

基于Kreiss[1]所建立的紧致差分逼近公式,提出一种数值求解二维泊极方程的高精度紧致差分方法．该方法是矩形网络下九结点差分近似,其推导过程简单,且具有四阶精度．最后给出了误差估计和数值结果．     

冬季两项队员射击准确性“三调”要求的系统化

为优化冬季两项国家队员射击环节的程序行为,提高其射击准确性,对动静转换下的队员射击自我调节行为进行了研究.对运动员射击过程提出"三调"要求,分别从调姿、调息、调意的角度系统分析队员训练和竞赛表现,认为动态下运动员生理、心理对竞赛的高负荷的适应、技术行为程序的优化及心理活动指向的正确发展相互影响,并共同作用于"射击准".建议在"三调"的系统要求下,使队员在超越竞赛难度的训练情景中建立正确的射击认知和思维模式,做到在相对稳的情况下迅速击发,相对快的基础上果断击发.     

图像分割算法在零件图像测量中的应用研究

通过分析图像测量系统的组成,说明了图像分割算法在零件图像测量中的重要地位,综合阐述了目前常用的图像分割算法的特点。针对零件图像测量的实际应用情况,提出了一种新的图像分割算法,实现了对目标边缘的准确检测。在此基础上设计了边缘检测的亚像素细分算法,对目标边缘进行亚像素精确定位,并用实例说明了本算法的可行性。     

Validity of Self-Reported Pedometer Steps per Day in College Students

The purpose of this article was to examine the validity of self-reported pedometer steps/day. Forty-seven participants were provided a New Lifestyles NL-2000 (NL-2000; Lees Summit, MO, USA) pedometer and a physical activity (PA) diary for 3 weeks, but not informed of the data-storing capabilities. For weeks 2 and 3, each participant was given a step goal of 3,000 steps/day above week 1 average. A 2 × 3 repeated measures analysis of variance (ANOVA) was used to examine differences between reported steps/day. Bland–Altman plots assessed the mean bias and limits of agreement between reporting methods. Mean self-reported and NL-2000 steps/day were 9,264 ± 3,555 and 8,971 ± 3,590 steps/day (n = 26, p > .05). Mean biases were 216 ± 1,753 (week 1), –506 ± 1,355 (week 2), and –590 ± 1,360 (week 3) steps/day. Negative mean bias values indicate higher self-reported steps/day. Mean steps/day were similar between recording methods, but large differences were observed among individuals, suggesting self-reported steps/day may be valid for PA research at the population level, but not the individual level.     

体操运动员前臂运动特征及其发展特点的研究

采用直观半圆仪,对我国441名体操运动员和563名青少年儿童的前臂屈伸复制运动误差值作了测定和比较分析等研究,结果发现,就这个非专业性的和极为普通的动作——前臂屈伸运动的准确性来讲,在运动等级不同的体操运动员之间以及体操运动员与同年龄的普通人之间,都存在明显的差别。而且,这种运动准确性较高者,学习基本体操动作的成效优于准确性较低者。这种运动的准确性在7～11岁期间提高最快,12～22岁时呈波浪式的发展状态;在体操运动训练的作用下,这种运动的准确性,在9～13岁加速提高,而且,随后的波浪式变化明显减小。