• Proceedings of the Korean Information Science Society Conference
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• 2007.10b
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• pp.17-21
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• 2007

Drug discovery is a long process with a low rate of successful new therapeutic discovery regardless of the advances in information technologies. Identification of candidate proteins is an essential step for the drug discovery and it usually requires considerable time and efforts in the drug discovery. The drug discovery is not a logical, but a fortuitous process. Nevertheless, considerable amount of information on drugs are accumulated in UniProt, NCBI, or DrugBank. As a result, it has become possible to try to devise new computational methods classifying drug target candidates extracting the common features of known drug target proteins. In this paper, we devise a method for drug target protein classification by using weighted feature summation and Support Vector Machine. According to our evaluation, the method is revealed to show moderate accuracy $85{\sim}90%$. This indicates that if the devised method is used appropriately, it can contribute in reducing the time and cost of the drug discovery process, particularly in identifying new drug target proteins.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10a
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• pp.169-170
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• 2007

• Journal of Ocean Engineering and Technology
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• v.34 no.3
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• pp.227-236
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• 2020

Underwater acoustics, which is the domain that addresses phenomena related to the generation, propagation, and reception of sound waves in water, has been applied mainly in the research on the use of sound navigation and ranging (SONAR) systems for underwater communication, target detection, investigation of marine resources and environment mapping, and measurement and analysis of sound sources in water. The main objective of remote sensing based on underwater acoustics is to indirectly acquire information on underwater targets of interest using acoustic data. Meanwhile, highly advanced data-driven machine-learning techniques are being used in various ways in the processes of acquiring information from acoustic data. The related theoretical background is introduced in the first part of this paper (Yang et al., 2020). This paper reviews machine-learning applications in passive SONAR signal-processing tasks including target detection/identification and localization.

• International Journal of Contents
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• v.7 no.3
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• pp.1-5
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• 2011

It has been an interesting challenge to find a good classifier for imbalanced data, since it is pervasive but a difficult problem to solve. However, classifiers developed with the assumption of well-balanced class distributions show poor classification performance for the imbalanced data. Among many approaches to the imbalanced data problems, the algorithmic level approach is attractive because it can be applied to the other approaches such as data level or ensemble approaches. Especially, the error back-propagation algorithm using the target node method, which can change the amount of weight-updating with regards to the target node of each class, attains good performances in the imbalanced data problems. In this paper, we analyze the relationship between two optimal outputs of neural network classifier trained with the target node method. Also, the optimal relationship is compared with those of the other error function methods such as mean-squared error and the n-th order extension of cross-entropy error. The analyses are verified through simulations on a thyroid data set.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.1657-1667
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• 2007

This study propose a model for railway safety evaluation with which the safety of whole railway system can be evaluated. The evaluation model is to generate a safety index which quantitatively represent the degree of railway safety. Safety index is proposed a function of three indexes; an accident index, safety management index, and safety culture index. This paper describes the first result from the study on the safety target which will be a key starting point toward the development of safety evaluation model. It is recommended that the safety target be composed of several sub-targets that are apportioned to constituent components. It is concluded that the classification of safety target influence on deciding components or attributes that constitute each sub-indexes; an accident index, safety management index, and safety culture index. Based on this study, a railway safety evaluation model will be developed in the next study.

• International Journal of Railway
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• v.5 no.4
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• pp.175-181
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• 2012

This study proposes a model for railway safety assessment with which the safety of whole railway system can be evaluated. The purpose of the assessment model is to generate safety indicators which quantitatively represent the degree of railway safety. Safety indicators were proposed as three indicators according to their functions; accident indicators, safety management indicators, and safety culture indicators. This paper describes the first result on the safety target which will be a key starting point toward the development of safety assessment model. It is recommended that the safety target to be composed of several sub-targets are apportioned to constituent components. It is concluded that the classification of safety target has influence on deciding components or attributes that constitute each sub-indicators; accident indicators, safety management indicators, and safety culture indicators. Based on this study, a railway safety assessment model will be developed in the following study.

• Journal of the Semiconductor & Display Technology
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• v.10 no.1
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• pp.113-118
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• 2011

This paper proposes computer visual inspection algorithms for PCB defects which are found in a manufacturing process. The proposed method can detect open circuit and short circuit on bare PCB without using any reference images. It performs adaptive threshold processing for the ROI (Region of Interest) of a target image, median filtering to remove noises, and then analyzes connected components of the binary image. In this paper, the connected components of circuit pattern are defined as 6 types. The proposed method classifies the connected components of the target image into 6 types, and determines an unclassified component as a defect of the circuit. The analysis of the original target image detects open circuits, while the analysis of the complement image finds short circuits. The machine vision inspection system is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiment results show that the proposed algorithms are quite successful.

• The Research Journal of the Costume Culture
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• v.12 no.1
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• pp.182-198
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• 2004

The purpose of this study was to analyze the previous make-up studies. A number of publications and journals were reviewed and analyzed carefully. The results of review and analysis were as follows: There were many different subjects in make-up studies and They can be divided into ten types : cosmetics purchase behavior, change of make-up culture and comparison, make-up trend by era, cosmetics industry's standing of today and strategy, art trend in make-up, brand preference of cosmetics, make up attitude, recognition about imported cosmetics and purchase behavior, color preference of cosmetics, the relationship between self-concept and make-up. In general, the cosmetic purchase behavior studies are conducted most actively. According to result that analyze existent study, special duality of cosmetics purchase action appears very variously according to standard of classification of study target and study target. But, study target and method of study are not various, and purchase behavior study collected with make-un and clothes is yew lacking. Therefore, in this study, wished to discover problem of virtue study because analyzes studies about previous make-up and present forward study direction.

• The Journal of the Acoustical Society of Korea
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• v.13 no.2
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• pp.30-37
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• 1994

Since the morden targets are of high speed and getting quiet in both active and passive mode, the necessities of developing advanced SONAR system capable of performing target motion analysis (TMA) and target classification are evident. In order to develop such a system, the scattering mechanism of complex bodies needs to be, some extent, fully understood and modeled. In this paper, MOving Spread Target(MOST) signal simulation model is presented and discussed. The model is based on the highlight distribution method, and simulates pulse elongation of spread target, doppler effect due to kinematics of the target as well as SONAR platform, and distribution target strength of each highlight point (HL) with directivity. The model can be used in developing and evaluating advanced SONAR system through system simulation, and can also be used in the development of target state estimation algorithm.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.1150-1155
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• 2009

In the information society, the amount of information have been increased by technological development. It is not easy to deal with information for fast data processing because of increasing of the complexity and diversity of data. So this paper will confirm the fact that the color plays the role of the classification of complex information and can make data processing fast. Experiment 1 shows that the searching time of target(line name) is more faster when the color of a subway line is equal to the color of station`s name. Experiment 2 using the task for classification of word mixed in various categories shows that color category processing is more faster rather than semantic category processing and the effect of this task is far better when color difference is more clear.