2007年世界女排大奖赛决赛中国队得失分比较分析

通过对2007年世界女排大奖赛总决赛中国队5场比赛中得失分情况的观察记录,运用分类统计、比较和分析等方法,探讨了中国队在一攻、防守、拦网和发球等方面的表现及与其他各队对抗时的优势和差距,得出结论为中国队发球的进攻性较强,前排的拦网,后排保护,一攻成功率高等方面较其它队稍强为主要得分点;而对强攻的防守被动以及技术上的不稳定和心理素质不稳定引起的失误多,为主要失分因素。     

VB上机操作题自动判分程序的设计

介绍了VB上机操作题的自动判分程序的主要算法，对上机操作题的评分标准格式进行了描述，阐述如何提取考生提交的答案并使用评分标：簋进行自动判分，并给出判分过程记录。     

多级评分的Bayes估计

对多级评分的测验题型,给出了其Bayes模型,把先验分布从无信息先验推广到了更一般的Dirichlet先验分布情形,求出了参数的Bayes估计,指出了其意义,并在不同样本条件下给出了先验分布超参数的估计.     

Enhancing the accuracy of virtual screening: molecular dynamics with quantum-refined force fields

Summary A methodology aimed at improving the accuracy of current docking–scoring procedures is proposed, and validated through detailed tests of its performance in predicting the activity of HIV-1 protease inhibitors. This methodology is based on molecular dynamics simulations using a force field whose effective charges are refined by means of a novel procedure that relies on quantum-mechanical calculations and preserves the internal consistency of the parameterization scheme.     

Bayesian networks applied to credit scoring

Email: kchang{at}gmu.eduEmail: RobertFung{at}Fairlsaac.comEmail: alan.lucas{at}hotmail.com^¶Email: BobOliver{at}Fairlsaac.com^||Email: NShikaloff{at}Fairlsaac.com The objectives of this paper are to apply the theory and numericalalgorithms of Bayesian networks to risk scoring, and comparethe results with traditional methods for computing scores andposterior predictions of performance variables. Model identification,inference, and prediction of random variables using Bayesiannetworks have been successfully applied in a number of areas,including medical diagnosis, equipment failure, informationretrieval, rare-event prediction, and pattern recognition. Theability to graphically represent conditional dependencies andindependencies among random variables may also be useful incredit scoring. Although several papers have already appearedin the literature which use graphical models for model identification,as far as we know there have been no explicit experimental resultsthat compare a traditionally computed risk score with predictionsbased on Bayesian learning algorithms. In this paper, we examine a database of credit-card applicantsand attempt to ‘learn’ the graphical structure ofthe characteristics or variables that make up the database.We identify representative Bayesian networks in a developmentsample as well as the associated Markov blankets and cliquestructures within the Markov blanket. Once we obtain the structureof the underlying conditional independencies, we are able toestimate the probabilities of each node conditional on its directpredecessor node(s). We then calculate the posterior probabilitiesand scores of a performance variable for the development sample.Finally, we calculate the receiver operating characteristic(ROC) curves and relative profitability of scorecards basedon these identifications. The results of the different modelsand methods are compared with both development and validationsamples. Finally, we report on a statistical entropy calculationthat measures the degree to which cliques identified in theBayesian network are independent of one another.     

山东高校体育招生考试标准理论依据的研究

考试标准的准确性、可靠性和合理性是依赖于评分方法的设计是否客观,是否符合考生的实际水平.本文就这一问题进行了研究与分析,提出了一套新颖的制定考试标准的数学模型.并在1988年,1989年山东体育招生考试中收到良好的效果.     

SKATE: A docking program that decouples systematic sampling from scoring

SKATE is a docking prototype that decouples systematic sampling from scoring. This novel approach removes any interdependence between sampling and scoring functions to achieve better sampling and, thus, improves docking accuracy. SKATE systematically samples a ligand's conformational, rotational and translational degrees of freedom, as constrained by a receptor pocket, to find sterically allowed poses. Efficient systematic sampling is achieved by pruning the combinatorial tree using aggregate assembly, discriminant analysis, adaptive sampling, radial sampling, and clustering. Because systematic sampling is decoupled from scoring, the poses generated by SKATE can be ranked by any published, or in‐house, scoring function. To test the performance of SKATE, ligands from the Asetex/CDCC set, the Surflex set, and the Vertex set, a total of 266 complexes, were redocked to their respective receptors. The results show that SKATE was able to sample poses within 2 Å RMSD of the native structure for 98, 95, and 98% of the cases in the Astex/CDCC, Surflex, and Vertex sets, respectively. Cross‐docking accuracy of SKATE was also assessed by docking 10 ligands to thymidine kinase and 73 ligands to cyclin‐dependent kinase. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010     

Drug efficiency indices for improvement of molecular docking scoring functions

A dataset of protein‐drug complexes with experimental binding energy and crystal structure were analyzed and the performance of different docking engines and scoring functions (as well as components of these) for predicting the free energy of binding and several ligand efficiency indices were compared. The aim was not to evaluate the best docking method, but to determine the effect of different efficiency indices on the experimental and predicted free energy. Some ligand efficiency indices, such as ΔG/W (Wiener index), ΔG/NoC (number of carbons), and ΔG/P (partition coefficient), improve the correlation between experimental and calculated values. This effect was shown to be valid across the different scoring functions and docking programs. It also removes the common bias of scoring functions in favor of larger ligands. For all scoring functions, the efficiency indices effectively normalize the free energy derived indices, to give values closer to experiment. Compound collection filtering can be done prior or after docking, using pharmacokinetic as well as pharmacodynamic profiles. Achieving these better correlations with experiment can improve the ability of docking scoring functions to predict active molecules in virtual screening. © 2009 Wiley Periodicals, Inc. J Comput Chem 2010