• Interdisciplinary Bio Central
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• v.4 no.4
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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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• v.13 no.11
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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.

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.1
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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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• v.1 no.1
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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.

• The KIPS Transactions:PartD
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• v.11D no.2
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• pp.381-386
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• 2004

Because of rapid increase of internet user, numerous popular web sites have been made on the internet but it is hard to find out a systematic technique for the selection of qualified web site in consumer position. Generally, there are black box, white box and gray box viewpoint for evaluating web site. In this paper present evaluation criteria based on AHP(Analysis Hierarchy Process) technique of black box viewpoint for optimal web site selection in consumer position. We considered usability, efficiency, compatibility based on ISO/IEC 9126 for quality measurement of web site and executed practical analysis about web site in internet. This paper show that the proposed selection technique is applicable to optimal web site selection.

• The Journal of the Korea Contents Association
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• v.11 no.5
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• pp.384-392
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• 2011

Recruitment and selection are separate but mutually reinforcing processes. The goal of recruitment is to attract the largest number of applicants possible to apply to the agency, and selection is the process of weeding out unqualified candidates and identifying qualified candidates. In this context, the recruitment and selection system of police officials is an important issue because it affects their future performance as police officers on the job, especially their policing skills, perception of society, occupational ethics. This study suggested the characteristics of U. S. recruitment and selection system of police officials. In the U. S, each police agency sets up its own recruitment and selection standards and procedures. However, recruitment and selection process follows a certain sequence : receiving application, psychological examination, background check, polygraph test, drug screening, interview, physical agility, and medical test. Special characteristic of American police system regarding recruitment and selection is that many law enforcement agencies use a polygraph test to ensure the integrity of the candidates. Another interesting screening process is a drug test because many Americans abuse illegal drugs. A candidate officer must submit urine or a hair sample for screening test. Police human resources specialists should continually identify the most innovative tests and approaches recruit and select police officers. Recruitment and selection strategies should increasingly attract and retain those officers who have the attributes to work in a community-oriented policing environment.

• The Journal of Society for e-Business Studies
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• v.18 no.4
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• pp.327-338
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• 2013

Effective and efficient selection of IT projects is crucial for company's competitiveness. The selection of IT projects usually involves consideration of budget constraints but existing IT project selection models often neglect budget constraints. This paper presents an IT project selection model which considers budget constraints. AHP(Analytic Hierarchy Process) and Knapsack problem model have been combined to develop the proposed model, AHP-K model, where AHP is used to estimate weights of selection criteria and, then, a knapsack problem model is utilized to optimize selection of IT project while meeting the budget constraints. In this paper, a case study is provided to validate the effectiveness of the proposed AHP-K model. It has been shown that the proposed AHP-K model is better than the AHP model in terms of total utility of projects and investment efficiency.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.28 no.3
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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.

• IE interfaces
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• v.13 no.3
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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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• v.24 no.4
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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.