• Interdisciplinary Bio Central
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• 제4권4호
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• pp.14.1-14.6
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• 2012

Splice site prediction in DNA sequence is a basic search problem for finding exon/intron and intron/exon boundaries. Removing introns and then joining the exons together forms the mRNA sequence. These sequences are the input of the translation process. It is a necessary step in the central dogma of molecular biology. The main task of splice site prediction is to find out the exact GT and AG ended sequences. Then it identifies the true and false GT and AG ended sequences among those candidate sequences. In this paper, we survey research works on splice site prediction based on support vector machine (SVM). The basic difference between these research works is nucleotide encoding technique and SVM kernel selection. Some methods encode the DNA sequence in a sparse way whereas others encode in a probabilistic manner. The encoded sequences serve as input of SVM. The task of SVM is to classify them using its learning model. The accuracy of classification largely depends on the proper kernel selection for sequence data as well as a selection of kernel parameter. We observe each encoding technique and classify them according to their similarity. Then we discuss about kernel and their parameter selection. Our survey paper provides a basic understanding of encoding approaches and proper kernel selection of SVM for splice site prediction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권11호
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• pp.5631-5652
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• 2019

The existing defense strategy selection methods based on game theory basically select the optimal defense strategy in the form of mixed strategy. However, it is hard for network managers to understand and implement the defense strategy in this way. To address this problem, we constructed the incomplete information stochastic game model for the dynamic analysis to predict multi-stage attack-defense process by combining Bayesian game theory and the Markov decision-making method. In addition, the payoffs are quantified from the impact value of attack-defense actions. Based on previous statements, we designed an optimal defense strategy selection method. The optimal defense strategy is selected, which regards defense effectiveness as the criterion. The proposed method is feasibly verified via a representative experiment. Compared to the classical strategy selection methods based on the game theory, the proposed method can select the optimal strategy of the multi-stage attack-defense process in the form of pure strategy, which has been proved more operable than the compared ones.

• 대한산업공학회지
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• 제43권1호
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• pp.49-61
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• 2017

This paper proposes an R&D project selection methodology for green technology centered on developing country-oriented technology commercialization. Eight selection criteria are derived from the R&BD logic model : technology needs of developing countries, effectiveness of green technology, technological potentials, domestic technological capability, commercialization feasibility, economic benefits, business feasibility, and spillover effects of developing countries. 21 qualitative and quantitative indicators are then defined for each criterion. The analytic hierarchy process is conducted to produce relative importance of evaluation indicators and to set final priority scores of R&D project candidates. The working of the proposed methodology is provided with the help of a case study example of Green Technology Center. The proposed methodology is expected to be effectively utilized for policy practices of R&D project selection in the field of green technology.

• Korean Journal of Geomatics
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• 제1권1호
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• pp.95-101
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• 2001

In a route plan, the route selection is a complicated problem to consider the spatial distribution and influence through overall related data and objective analysis on the social, economic and technical condition. The developed system in this study was compared and estimated by deciding a practical section for its validity and efficiency. Using Geographic Information System (GIS), the various information required for route selections in database was constructed, the characteristics of subject area by executing three-dimensional terrain analysis was grasped effectively, and the control point through buffering, overlay and location operation was extracted. An optimum route was selected by calculating the sum of alternatives to the sub-criteria weight, and from this result, there is a difference between real route and proposed route according to the prioritization of decision criteria based on the importance. This research could be constructed and applied geospatial information to the reasonable route plan and an optimum route selection efficiently using GIS. Therefore, the applications are presented by applying Analytic Hierarchy Process (AHP) to the decision-making of information needed in route selection.

• 정보처리학회논문지D
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• 제11D권2호
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• pp.381-386
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• 2004

인터넷 사용자의 급속한 증가로 여러 종류의 인기 웹사이트들이 생겨나고 있으나, 웹사이트의 품질을 사용자 관점에서 종합적이고 체계적으로 비교 및 평가하는 선정기법에 대한 연구는 미약한 상황이다. 일반적으로 웹사이트 품질을 평가하는 관점은 블랙박스, 화이트박스, 그레이박스 관점으로 구분할 수 있다. 본 논문에서는 최적의 웹사이트를 선정하기 위해 사용자 입장에서 블랙박스 관점으로 AHP(Analysis Hierarchy Process)기법을 사용하였고, 웹사이트의 품질은 국제표준 IS0/1EC 9126에서 규정하고 있는 6가지 소프트웨어 품질 특성 중에서 효율성, 사용성, 호환성을 고려하였다. 현재 인터넷상에서 운영하고 있는 웹사이트들에 대한 실증적 분석을 통하여, 본 논문에서 제시한 웹사이트 선정기법 및 품질 평가에 관한 연구가 최적의 웹사이트를 선택하는데 적용 가능한 것임을 보여준다

• 한국콘텐츠학회논문지
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• 제11권5호
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• pp.384-392
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• 2011

경찰은 시민의 가장 가까운 곳에서 시민의 생명과 재산을 지키는 형사사법기관이다. 따라서, 다른 여타의 공무원들이나 직군에 비해서 높은 윤리성과 봉사성이 필요하다. 우리나라뿐만 아니라 세계 각국에서는 경찰공무원을 임용할 때, 무엇보다도 엄격하고 까다로운 기준과 절차를 통해서 선발한다. 이러한 맥락에서, 본 연구에서는 경찰 선진국인 미국 경찰관들의 모집 및 선발 실태를 분석하였다. 본 연구에서 제시한 미국 신임경찰관 채용 과정은 통상적으로 모집공고 및 활동, 지원서 접수, 필기 및 적성검사, 육체 민첩성 테스트, 심리 테스트, 구술고사, 신원조회, 거짓말 탐지기를 이용한 조사, 그리고 건강검진 등의 절차를 거치게 된다. 미국 경찰공무원 선발제도 중에서 가장 큰 특징은 많은 경찰조직에서 지원자의 정직성 및 도덕성을 검증하기 위하여 거짓말 탐지기를 활용한다는 점이다. 또한 미국은 불법적인 약물남용이 많기 때문에 지원자들은 반드시 약물 테스트를 위해 소변이나 머리카락을 제출해야 한다. 한국에서도 경찰관 선발시험은 지원자의 실력과 자격을 정확하게 파악할 수 있어야 하고, 아울러 현대사회가 요청하는 경찰공무원을 선발할 수 있도록 적성검사를 새롭게 구성해야 할 것이다. 또한 적성검사의 한계를 극복하는데 미국의 사례와 같이 거짓말탐지기 조사를 적극적으로 검토할 필요성이 제기된다.

• 한국전자거래학회지
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• 제18권4호
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• pp.327-338
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• 2013

IT프로젝트를 수행하는 기업은 정해진 예산범위 내에서 투자계획을 수립하고 실행하게 된다. 이 과정에서 IT프로젝트를 효과적, 효율적으로 선정하는 문제는 기업경쟁력과 직결되는 중요한 요소이다. 그동안 IT프로젝트의 선정을 위한 다양한 모형이 개발되었으나 예산제약을 고려한 효과적 프로젝트 선정에 대한 연구는 보고되지 않고 있다. 본 연구에서는 예산 제약을 고려하여 효과적으로 IT프로젝트를 선정하는 기법을 제시하였다. 본 연구에서 제안한 모델(AHP-K)에서는 AHP(Analytic Hierarchy Process : 계층분석법) 기법을 적용하여 평가 항목의 가중치와 프로젝트 후보군의 가중치를 산정한 후 배낭문제(Knapsack Problem)를 적용하여 예산 범위 내에서 프로젝트 효용을 최대화하는 선정안을 도출한다. 실제 적용단계에서 고려하는 대안이 많거나 신규대안이 추가되는 경우 쌍대비교의 수행이 어려운 점을 감안하여 대안 비교 단계에서 절대평가법을 적용하였다. 본 연구에서는 제시된 모델을 실제 사례에 적용하여 기존 AHP 모형과 비교 분석함으로써 효과성을 검증하였다.

• 한국항공운항학회지
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• 제28권3호
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• pp.74-83
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• 2020

Securing excellent pilots is not only directly linked to the military's improved combat capabilities, but also a way to minimize human and property losses from aircraft accidents. Therefore, a scientific method is needed to diagnose pilot aptitude from the pilot selection process and select those with high accident potential, those who are dropped out of the flight training process, and those who are not suitable for pilot life in advance. Developed countries have implemented pilot aptitude tests to solve these problems early on, but so far, the Korean Army has not introduced a pilot aptitude test system that uses diagnostic tools in the helicopter pilot selection process. Therefore, in this study, scientific diagnostic tools are developed for selecting helicopter pilots, and through this, it is predicted that the number of people who are likely to be dropped out of the training course and who have the potential for accidents will be selected in advance and eliminated in the selection process. In this context, prior research examined the key factors involved in the pilot aptitude test. Through this, the aptitude test items were developed and aptitude tests were conducted on student pilots currently in flight training, and the results of flight training were analyzed.

• 산업공학
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• 제13권3호
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• pp.296-305
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• 2000

In supply chains, coordination between a manufacturer and suppliers is regarded as the most important issue when partnership of organizations is considered. Since the suppliers are external to the manufacturer and poor coordination between them results in excessive delays and ultimately leads to poor customer service, manufacturers need a new methodology to select suppliers and to manage and enhance the partnership between manufacturer and suppliers. We suggest a methodology that extends knowledge obtained from the supplier selection process to the supplier management process. We reserved a word, the supplier selection and management system (SSMS) for this methodology. In this paper, we explain how the SSMS is applied to a real supply chain. The methodology identifies the managerial criteria using information derived from supplier selection process and makes use of them in the supplier management process. These managerial criteria include key criteria that are major criteria required by the manufacturer for the best quality of parts from suppliers according to the character of each part, and weak criteria that show the shortcomings of selected suppliers as compared with alternative suppliers with regard to each criterion. The effectiveness of supplier management with managerial criteria was verified by a t-test and a correlation analysis with data collected and hypothesized from a Korean air-conditioner manufacturer.

• Communications for Statistical Applications and Methods
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• 제24권4호
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• pp.383-396
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• 2017

The model in our approach assumes that computer responses are a realization of a Gaussian processes superimposed on a regression model called a Gaussian process regression model (GPRM). Selecting a subset of variables or building a good reduced model in classical regression is an important process to identify variables influential to responses and for further analysis such as prediction or classification. One reason to select some variables in the prediction aspect is to prevent the over-fitting or under-fitting to data. The same reasoning and approach can be applicable to GPRM. However, only a few works on the variable selection in GPRM were done. In this paper, we propose a new algorithm to build a good prediction model among some GPRMs. It is a post-work of the algorithm that includes the Welch method suggested by previous researchers. The proposed algorithms select some non-zero regression coefficients (${\beta}^{\prime}s$) using forward and backward methods along with the Lasso guided approach. During this process, the fixed were covariance parameters (${\theta}^{\prime}s$) that were pre-selected by the Welch algorithm. We illustrated the superiority of our proposed models over the Welch method and non-selection models using four test functions and one real data example. Future extensions are also discussed.