• Proceedings of the PSK Conference
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• 2002.10a
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• pp.181-182
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• 2002

Recentadvancesin '-omics ' technologies enable us to discover more diverse disease- relevant target proteins, which encourages us to find out more target-specific novel lead compounds as new drug candidates. Therefore, high-throughput screening (HTS) becomes an essential tool in this area. Among many HTS tools, in silico HTS is a very fast and cost-effective tool to try to derive a new lead compound for any new targets, especially when the target protein structures are known or readily modeled. (omitted)

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.312-320
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• 2021

Increase in computational cost and exhaustive search can lead to more complexity and computational energy. Thus, there is need for effective and efficient scheme to reduce the complexity to achieve optimal energy utilization. This will improve the energy efficiency and enhance the proficiency in terms of the resources needed to achieve convergence. This paper primarily focuses on the development of hybrid swarm intelligence scheme for reducing the computational complexity in binary optimization. In order to reduce the complexity, both artificial bee colony (ABC) and particle swarm optimization (PSO) have been employed to effectively minimize the exhaustive search and increase convergence. First, a new approach using ABC and PSO has been proposed and developed to solve the binary optimization problem. Second, the scout for good quality food sources is accomplished through the deployment of PSO in order to optimally search and explore the best source. Extensive experimental simulations conducted have demonstrate that the proposed scheme outperforms the ABC approaches for reducing complexity and energy consumption in terms of convergence, search and error minimization performance measures.

• Bulletin of the Korean Chemical Society
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• v.28 no.4
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• pp.561-566
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• 2007

Adenosine kinase (AK) is a ubiquitous intracellular enzyme, which catalyzes the phosphorylation of adenosine (ADO) to adenosine monophosphate (AMP). AK inhibitors have therapeutic potential as analgesic and antiinflammatory agents. A chemical feature based pharmacophore model has been generated from known AK inhibitors (26 training set compounds) by HypoGen module implemented in CATALYST software. The top ranked hypothesis (Hypo1) contained four features of two hydrogen-bond acceptors (HBA) and two hydrophobic aromatics (Z). Hypo1 was validated by 124 test set molecules with a correlation coefficient of 0.905 between experimental and estimated activity. It was also validated by CatScramble method. Thus, the Hypo1 was exploited for searching new lead compounds over 238,819 chemical compounds in NCI database and then the selected compounds were screened based on restriction estimated activity and Lipinski's rules to evaluate their drug-like properties. Finally we could obtain 72 new lead candidates and the two best compound structures from them were posted.

• Korean Journal of Human Ecology
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• v.18 no.2
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• pp.465-476
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• 2009

The purpose of this study is to investigate recognition degree and acceptability of fashion trends of new consumers who live in digital era, and to determine how these factors have influence on their use of fashion trend information. The study was conducted with 696 people from 15 to 34 years old. A self-administrated questionnaire based on the results of previous researches was developed. The data were analyzed with statistical analyses such as frequency analysis, mean, factor analysis, t-test, ANOVA, correlation and regression analysis. The results are as follows: first, new digital consumer's recognition degree (RD) of fashion trends is 7.85 on the average, given that the top of scale is 20.0, it is quite low. Of fashion trend RD, fashion item RD is the highest. The female subjects recognize fashion trends better than the male subjects. Second, fashion trend acceptance of new digital generation is classified into 5 factors: 'search acceptance', 'lead acceptance', 'follow acceptance', 'non-acceptance', and 'delay acceptance'. The female subjects show higher degree in the factors of 'search acceptance', 'lead acceptance' and 'follow acceptance' of fashion trend than the males; hence it means that the females have more positive attitudes in fashion trend acceptance than the males. Third, there are significant differences between genders in the fashion information utilization. Compared to the males, the females more use fashion information on style, fabrics and color. Concludingly, their fashion trend recognition degree and acceptance made an influence in part on their utilization of fashion information.

• Journal of Korea Game Society
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• v.15 no.4
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• pp.179-188
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• 2015

The A* algorithm is a well-known pathfinding algorithm. However, if the information about obstacles is not exploited, the algorithm may collide with obstacles or lead into swamp areas unnecessarily. In this paper, we propose new heuristic functions using the information of obstacles to avoid them or swamp areas. It takes time to process the information of obstacles before starting pathfinding, but it may not cause any problems most of cases because it is not processed in real time. We showed that the proposed methods could reduce the search space effectively through experiments. Furthermore, we showed that heuristic functions using obstacle information could reduce the search space effectively without processing obstacle information at all.

• Journal of Integrative Natural Science
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• v.5 no.4
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• pp.229-232
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• 2012

The pharmaceutical industry has an ongoing need for new, safe medicines with genuine biomedical effects. Most of the candidate molecules are far from becomes a drug, because of their pharmacokinetic and pharmacodynamic properties. The introduction of bioisostere to improve properties of molecules and to obtain new class of compound is currently increased. Silicon substitution of carbon of existing drugs is an attractive strategy to search a new candidate with improved biological and physicochemical properties. The fundamental differences between carbon and silicon can lead to improved profile of the silicon containing candidate, and could be exploited to get further benefit in drug design process.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.4
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• pp.317-322
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• 2002

The major operations of Evolutionary Computation include crossover, mutation, competition and selection. Although selection does not create new individuals like crossover or mutation, a poor selection mechanism may lead to problems such as taking a long time to reach an optimal solution or even not finding it at all. In view of this, this paper proposes a hybrid Evolutionary Programming (EP) algorithm that exhibits a strong capability to move toward the global optimum even when stuck at a local minimum using a synergistic combination of the following three basic ideas. First, a "local selection" technique is used in conjunction with the normal tournament selection to help escape from a local minimum. Second, the mutation step has been improved with respect to the Fast Evolutionary Programming technique previously developed in our research group. Finally, the crossover and mutation operations of the Genetic Algorithm have been added as a parallel independent branch of the search operation of an EP to enhance search diversity.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.11
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• pp.520-527
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• 2001

This paper suggests a new methodology of evolutionary computations - an Adaptive Evolutionary Algorithm (AEA) for solving the Economic Load Dispatch (ELD) problem which has piecewise quadratic cost functions and prohibited operating zones with many local minima. AEA uses a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner in order to take merits of two different evolutionary computations: global search capability of GA and local search capability of ES. In the reproduction procedure, proportions of the population by GA and the population by ES are adaptively modulated according to the fitness. Case studies illustrate the superiority of the proposed methods to existing conventional methods in power generation cost and computation time. The results demonstrate that the AEA can be applied successfully in the solution of ELD with piecewise quadratic cost functions and prohibited operating zones

• Proceedings of the Korean Society of Applied Pharmacology
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• 1998.11a
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• pp.34-37
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• 1998

Combinatorial chemistry is one of the most interested topics in the area of drug discovery. One of the most important points is how to find a lead compound that gives the seed structure for designing of a combinatorial library. Natural products is suitable for searching a new bioactive compound with new structure. We have carried out systematic screening works to find natural products possessing the effects on inter-and intra-cellular signaling. Two hundreds extracts of medical plants and two thousands microbial culture broth samples have been tested for the induction and inhibition of IL-2 or IL-6 production (Fig. 1). ELISA is an efficient method for screenings from such a large number of samples. Now, we apply this method to search prion- binding agents.

• Proceedings of the Korea Society for Simulation Conference
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• 1999.10a
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• pp.75-80
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• 1999

This paper presents a new method to find a optimal solution for stochastic system. This method uses Genetic Algorithm(GA) and simulation. GA is used to search for new alternative and simulation is used to evaluate alternative. The stochastic system has one or more random variables as inputs. Random inputs lead to random outputs. Since the outputs are random, they can be considered only as estimates of the true characteristics of they system. These estimates could greatly differ from the corresponding real characteristics for the system. We need multiple replications to get reliable information on the system. And we have to analyze output data to get a optimal solution. It requires too much computation to be practical. We address the problem of reducing computation. The procedure on this paper use GA character, an iterative process, to reduce the number of replications. The same chromosomes could exit in post and present generation. Computation can be reduced by using the information of the same chromosomes which exist in post and present current generation.