• International Journal of Industrial Entomology and Biomaterials
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• v.14 no.1
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• pp.1-7
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• 2007

In order to find out the appropriate parents for the breeding programme, twelve bivoltine and three multivoltine silkworm breeds were evaluated on the basis of multivariate selection index and isozyme analysis. Of which, four [CSR2, D6 (P), SK3, SK4] bivoltine and two multivoltine (Nistari, Cambodge) breeds were selected and breeding initiated to develop higher survival bivoltine silkworm breed suitable for tropical conditions. Among two isozyme (Esterase and acid phosphatase) analyzed, only esterase exhibited polymorphism among the bivoltine breeds. No polymorphism was observed among multivoltine in respect of esterase as well as acid phosphatase.

• Convergence Security Journal
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• v.6 no.3
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• pp.87-95
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• 2006

An intrusion can be defined as any set of actors that attempt to compromise the integrity, confidentiality and availability of computer resource and destroy the security policy of computer system. The Intrusion Detection System that detects the intrusion consists of data collection, data reduction, analysis and detection, and report and response. It is important for feature selection to detect the intrusion efficiently after collecting the large set of data of Intrusion Detection System. In this paper, the feature selection method using Genetic Algorithm and Decision Tree is proposed. Also the method is verified by the simulation with KDD data.

• Journal of IKEEE
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• v.22 no.2
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• pp.402-407
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• 2018

Link selection strategy has been an important technical issues of relay network. In this paper, we introduce a link selection scheme in the bidirectional, buffer-aided relay network. Three kinds of information such as the states of the queue at the relay buffer, the qualities of the links, and the states of the queues at the user buffer are considered. Throughput and delay performance is evaluated under three cases with different available information.

• Journal of the Earthquake Engineering Society of Korea
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• v.21 no.4
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• pp.181-188
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• 2017

Current seismic design provisions such as ASCE 7-10 provide criteria for selecting ground motions for conducting response history analysis. This study is the sequel of a companion paper (I - Ground Motion Selection) for assessment of the ASCE 7-10 criteria. To assess of the ASCE 7-10 criteria, nonlinear response history analyses of twelve single degree of freedom (SDF) systems and one multi-degree of freedom (MDF) system are conducted in this study. The results show that the target seismic demands for SDF can be predicted using the mean seismic demands over seven and ten ground motions selected according to the proposed method within an error of 30% and 20%, respectively

• International Journal of Costume and Fashion
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• v.10 no.2
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• pp.51-59
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• 2010

This study regarded fashion selection criteria as clothing consumption value and desired fashion images, and examined selection differences according to regional subculture groups. Clothing consumption value is a direct value that people seek with clothing products and a perceived value which is divided into emotional, social, price, quality values. Fashion image which is a feeling communicated to others by wearing a certain fashion style is the most superficial value. Multivariate Analysis of Variance (MANOVA) was performed to test the differences between regional subculture groups in clothing consumption values and desired fashion images. We found some differences in clothing consumption value specifically in emotional value and social value. The group differences were remarkably significant in fashion image comparison. 'Kang-nam' group pursued 'lively', 'sophisticated', 'charming', feminine', 'gorgeous' image more than 'Kang-buk' group. While 'Kang-buk' group produced lower scores in ideal fashion images, the group had significant higher seeking in 'sportive' image compared to 'Kangnam' group.

• Korean Management Science Review
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• v.26 no.2
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• pp.19-35
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• 2009

This paper investigated performance of the Markowitz's portfolio selection model with applications to Korean stock market. We chose Samsung-Group-Funds and KOSPI index for performance comparison with the Markowitz's portfolio selection model. For the most recent one and a half year period between March 2007 and September 2008, KOSPI index almost remained the same with only 0.1% change, Samsung-Group-Funds showed 20.54% return, and Markowitz's model, which is composed of the same 17 Samsung group stocks, achieved 52% return. We performed sensitivity analysis on the duration of financial data and the frequency of portfolio change in order to maximize the return of portfolio. In conclusion, according to our empirical research results with Samsung-Group-Funds, investment by Markowitz's model, which periodically changes portfolio by using nonlinear programming with only financial data, outperformed investment by the fund managers who possess rich experiences on stock trading and actively change portfolio by the minute-by-minute market news and business information.

• Asia pacific journal of information systems
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• v.21 no.2
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• pp.43-58
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• 2011

Support vector machines (SVMs), a machine learning technique, has been applied to not only binary classification problems such as bankruptcy prediction but also multi-class problems such as corporate credit ratings. However, in general, the performance of SVMs can be easily worse than the best alternative model to SVMs according to the selection of predictors, even though SVMs has the distinguishing feature of successfully classifying and predicting in a lot of dichotomous or multi-class problems. For overcoming the weakness of SVMs, this study has proposed an approach for selecting features for multi-class SVMs that utilize the impurity measures of classification trees. For the selection of the input features, we employed the C4.5 and CART algorithms, including the stepwise method of discriminant analysis, which is a well-known method for selecting features. We have built a multi-class SVMs model for credit rating using the above method and presented experimental results with data regarding S&P 500 companies.

• Korean Medical Education Review
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• v.12 no.1
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• pp.3-8
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• 2010

This study is designed to evaluate the effectiveness of teaching or studying programs, and thus to overcome the selectionbias in studies. Selection-bias derived from unobservable characteristics in the course of participants selection of the teaching or studying programs, in the case of cross-section data instrumental variable(IV) method and two stage least square estimation were suggested as an analysis tool. Panel data were analyzed by using both fixed effect in which individual effects are captured by intercept terms and random effect estimation where an unobserved effect can be characterized as being randomly drawn from a given distribution.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.35
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• pp.147-178
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• 2007

This study clarified a study of relationship of strategic alliance structure factor, partner selection criteria and performance awareness on the container liners alliance. In order to obtain such objective of study existing literature variables suitable to the container liner were perused and extracted. Research models for research development and three study hypothesis were set out and scope of investigation and samples were chosen. The research hypothesis are followings. H1: The factors of strategic alliance motivation influence the performance awareness. H2: The strategic alliance structure factors influence the performance awareness. H3: The factors of partner selection criteria influence the performance awareness. In the result of the empirical study, the hypothesis 1, hypothesis 2 were supported completely and hypothesis 3 was partially supported.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.3
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• pp.164-175
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• 2010

In this study, we developed a genetic algorithm to find a near optimal solution of concurrent spare parts selection for the operational time period with limited information of weapon systems purchased from overseas. Through the analysis of time profiles related with system operations, we first define the optimization goal which maintains the expected system operating rate under the budget restrictions, and the number of failures and the lead time for each spare part are used to calculate the estimated total down time of the system. The genetic algorithm for CSP selection shows that the objective function minimizes the estimated total down time of systems with satisfying the restrictions. The method provided by this study can be applied to the generalized model of CSP selection for the systems purchased from overseas without provision of their full structure and adequate information.