• Journal of Integrative Natural Science
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• v.3 no.1
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• pp.49-53
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• 2010

Molecular docking is a critical event which mostly forms Van der waals complex in molecular recognition. Since the majority of developed drugs are small molecules, docking them into proteins has been a prime concern in drug discovery community. Since the binding pose space is too vast to cover completely, many search algorithms such as genetic algorithm, Monte Carlo, simulated annealing, distance geometry have been developed. Proper evaluation of the quality of binding is an essential problem. Scoring functions derived from force fields handle the ligand binding prediction with the use of potential energies and sometimes in combination with solvation and entropy contributions. Knowledge-based scoring functions are based on atom pair potentials derived from structural databases. Forces and potentials are collected from known protein-ligand complexes to get a score for their binding affinities (e.g. PME). Empirical scoring functions are derived from training sets of protein-ligand complexes with determined affinity data. Because non of any single scoring function performs generally better than others, some other approaches have been tried. Although numerous scoring functions have been developed to locate the correct binding poses, it still remains a major hurdle to derive an accurate scoring function for general targets. Recently, consensus scoring functions and target specific scoring functions have been studied to overcome the current limitations.

• Journal of Information Processing Systems
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• v.11 no.2
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• pp.173-183
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• 2015

At present, it is simple to the electronic commerce credit scoring model, as a brush credit phenomenon in E-commerce has emerged. This phenomenon affects the judgment of consumers and hinders the rapid development of E-commerce. In this paper, that E-commerce credit evaluation model that uses a Gaussian density function is put forward by density test and the analysis for the anomalies of E-commerce credit rating, it can be fond out the abnormal point in credit scoring, these points were calculated by nonlinear credit scoring algorithm, thus it can effectively improve the current E-commerce credit score, and enhance the accuracy of E-commerce credit score.

• Bioinformatics and Biosystems
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• v.1 no.2
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• pp.103-108
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• 2006

Computational prediction of protein-ligand binding has been widely used as a tool to discover lead compounds fur new drugs. Prediction accuracy is determined in part by the scoring function used in docking calculations. Diverse scoring functions are available, and these can be classified into force-field based, empirical, and knowledge-based functions depending upon the basic assumptions made in development. Among these, force-field based functions consider physical interactions the most in detail. However, the force-field based functions have the drawback of not including the entropic effect while considering only the energy contribution such as dispersion or electrostatic forces. In this article, a method to take into account of the entropic effect using the colony energy is suggested when force-field based scoring functions is used by extracting conformational information obtained from the pre-existing docking program. An improved result for decoy discrimination is illustrated when the method is applied to the DOCK scoring function, and this implies that more accurate docking calculation is possible.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.2
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• pp.204-213
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• 2016

A differential game theory based approach is used to develop an automated maneuver generation algorithm for Within Visual Range (WVR) air-to-air combat of unmanned combat aerial vehicles (UCAVs). The algorithm follows hierarchical decisionmaking structure and performs scoring function matrix calculation based on differential game theory to find the optimal maneuvers against dynamic and challenging combat situation. The score, implying how much air superiority the UCAV has, is computed from the predicted relative geometry, relative distance and velocity of two aircrafts. Security strategy is applied at the decision-making step. Additionally, a barrier function is implemented to keep the airplanes above the altitude lower bound. To shorten the simulation time to make the algorithm more real-time, a moving horizon method is implemented. An F-16 pseudo 6-DOF model is used for realistic simulation. The combat maneuver generation algorithm is verified through three dimensional simulations.

• International Journal of Aeronautical and Space Sciences
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• v.13 no.1
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• pp.99-105
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• 2012

Track-before-detect techniques based on dynamic programming have provided solutions for detecting targets from a sequence of images. In its application to airborne threat detection, dynamic programming solutions should take into account the distinguishable properties of objects in a collision course. This paper describes the development of a new track scoring function that accumulates scores for airborne targets in Bayesian framework. Numerical results show that the proposed scoring function has slightly better detection capabilities.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.489-503
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• 2000

Data mining means data analysis and model selection using various types of data in order to explore useful information and knowledge for making decisions. Examples of data mining include scoring for credit analysis of a new customer and scoring for churn management, where the customers with high scores are given special attention. In this paper, scoring is interpreted as a modeling process of the conditional probability and polyclass scoring method is described. German credit data, a PC communication company data and a mobile communication company data are used to compare the performance of polyclass scoring method with that of the scoring method based on a tree model.

• The Korean Journal of Applied Statistics
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• v.18 no.3
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• pp.543-553
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• 2005

Linear logistic regression is one of the most widely used method for credit scoring in credit risk management. This paper deals with credit scoring using splines based on Logistic regression. Linear splines and an automatic basis selection algorithm are adopted. The final model is an example of the generalized additive model. A simulation using a real data set is used to illustrate the performance of the spline method.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.279-286
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• 2005

The objective of this study is to suggest a credit scoring model of a capital company's customers by integration of multiple classifiers using genetic algorithm. For this purpose , an integrated model is derived in two phases. In first phase, three types of classifiers MLP (Multi-Layered Perceptron), RBF (Radial Basis Function) and linear models - are trained, in which each type has three ones respectively so htat we have nine classifiers totally. In second phase, genetic algorithm is applied twice for integration of classifiers. That is, after htree models are derived from each group, a final one is from these three, In result, our suggested model shows a superior accuracy to any single ones.

• Bulletin of the Korean Chemical Society
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• v.29 no.5
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• pp.921-927
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• 2008

Discovery of $\alpha$-glucosidase inhibitors has been actively pursued with the aim to develop therapeutics for the treatment of diabetes and the other carbohydrate mediated diseases. As a method for the discovery of new novel inhibitors of $\alpha$-glucosidase, we have addressed the performance of the computer-aided drug design protocol involving the homology modeling of $\alpha$-glucosidase and the structure-based virtual screening with the two docking tools: FlexX and the automated and improved AutoDock implementing the effects of ligand solvation in the scoring function. The homology modeling of $\alpha$-glucosidase from baker’s yeast provides a high-quality 3-D structure enabling the structure-based inhibitor design. Of the two docking programs under consideration, AutoDock is found to be more accurate than FlexX in terms of scoring putative ligands to the extent of 5-fold enhancement of hit rate in database screening when 1% of database coverage is used as a cutoff. A detailed binding mode analysis of the known inhibitors shows that they can be stabilized in the active site of $\alpha$- glucosidase through the simultaneous establishment of the multiple hydrogen bond and hydrophobic interactions. The present study demonstrates the usefulness of the automated AutoDock program with the improved scoring function as a docking tool for virtual screening of new $\alpha$-glucosidase inhibitors as well as for binding mode analysis to elucidate the activities of known inhibitors.

• Clinics in Shoulder and Elbow
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• v.4 no.2
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• pp.173-180
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• 2001

Aim: To evaluate validity and responsiveness of four shoulder scoring systems. Material and Method: Twenty-five cases of shoulder instability(22 traumatic, 3 non-traumatic) and twenty-three cases of rotator cuff tear(12 small or medium, 10 large or massive) treated surgically were evaluated with the Shoulder Function Score of the University of Pennsylvania(Penn FS), Constant Score, UCLA Shoulder Rating Scale and Simple Shouler Test(SST), preoperatively and at final follow-up. The average follow-up was 16.0 months in instability group and 17.5 months in rotator cuff tear group. Using the SPSS program, Pearson linear correlation coefficiency(PLCC) between the scores were calculated. And to assess the construct validity, PLCC between patients' satisfaction and the scores were also calculated. Responsiveness was measured by the standardized response mean(SRM). Result: In instability group, correlation between the scoring systems was low preoperatively except between Constant and SST, but high after operation. Patients' satisfaction with the scores showed low PLCC preoperativley, but high PLCC postoperatively. SRM was high in PENN and UCLA, but when the satisfaction segment of the score was eliminated from UCLA, the SRM was the lowest. In rotator cuff tear group, there was high correlation between the scores not only preoperatively but postoperatively. And the patients' satisfaction matched well with the scores. SRM was particularly high in UCLA and SST. Even when satisfaction segment was eliminated from UCLA, the SRM was still the highest. Conclusion : Evaluation by the 4 scoring systems investigated in the study showed less consistency in instability than rotator cuff tear in terms of correlation and validity. Responsiveness was generally higher in rotator cuff tear group than in instability group except for Pennsylvania Shoulder Function Score. Therefore it is construed that use of any among the four scoring systems doesn't make difference in evaluation of rotator cuff lesions. However in instability group, care is needed because different result may be obtained according to the selection of a scoring system.