• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.238-240
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• 2018

Recently, healthcare services have been developed and studied using various bio-signal analysis tools. Most bio-signal analysis studies utilize Matlab and R Programming. However, in order to apply the algorithm developed by Matlab and R Programming to the system, it is necessary to convert the source code. This paper proposes a smart interface that can skip source code conversion.

• Journal of the military operations research society of Korea
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• v.2 no.1
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• pp.111-125
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• 1976

This paper is to explore technological forecasting methodologies and their application to military R&D programming. Among a number of forecasting methodologies, eight frequently used methods are explained. They are; Delphi method, analogy, growth curve, trend extrapolation, analytical model, breakthrough, normative method, and combined method. Due to the characteristic situation of a developing country, the application of technological forecasting to the Korean military R&D programming is limited. Therefore, only two forecasting methods such as Delphi and normative method are utilized in the development of a decision model for the military R&D programming. The model consists of a dynamic programming using decision tree model, which optimizes the total cost to equip a certain military item under a given range of risk during a given period. Some pitfalls in forecasting methodologies and of the model are discussed.

• Journal of applied mathematics & informatics
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• v.32 no.1_2
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• pp.99-111
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• 2014

In this paper, we have taken step in the direction to establish weak, strong and strict converse duality theorems for three types of dual models related to multiojective fractional programming problems involving ($H_p$, r)-invex functions.

• Management Science and Financial Engineering
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• v.14 no.2
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• pp.25-44
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• 2008

This paper concentrates on reduction of a Quadratic Fractional Integer Programming Problem (QFIP) to a 0-1 Mixed Linear Programming Problem (0-1 MLP). The solution technique is based on converting the integer variables to binary variables and then the resulting Quadratic Fractional 0-1 Programming Problem is linearized to a 0-1 Mixed Linear Programming problem. It is illustrated with the help of a numerical example and is solved using the LINDO software.

• The Journal of Korean Association of Computer Education
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• v.18 no.3
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• pp.59-68
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• 2015

The purpose of this study is to analyze the learner's characteristics, and relationship between learning styles and achievements in online programming learning environment. For the analysis, after performing the inspection of learning styles of Grasha-Reichmann for 104 middle and high school students, online programming learning were performed for 12 weeks. First, according to learner's variable, boy was higher than girls in dependent learning style. Middle school student higher than high school student in competitive and avoid learning styles. Independent and participant learning styles show a significant difference in achievement level. Analysis of the relationship between learning styles and achievements show that independent(r=.253, p<.01) and participant(r=.303, p<.01) have the positive correlations. As a result, independent and participant learning styles are confirmed to be related with achievements. In addition, we analyzed each learning style characteristics by writing survey of the impression of the learners by main learning styles, through which we could derive teaching and learning strategies for the online programming by learning styles.

• Electronics and Telecommunications Trends
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• v.28 no.1
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• pp.42-51
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• 2013

The R language is an open source programming language and a software environment for statistical computing and data visualization. The R language is widely used among a lot of statisticians and data scientists to develop statistical software and data analysis. The R language provides a variety of statistical and graphical techniques, including basic descriptive statistics, linear or nonlinear modeling, conventional or advanced statistical tests, time series analysis, clustering, simulation, and others. In this paper, we first introduce the R language and investigate its features as a data analytics tool. As results, we may explore the application possibility of the R language in the field of data analytics.

• Korean Management Science Review
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• v.16 no.1
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• pp.63-74
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• 1999

This paper presents a R&D investment model for the Information and telecommunications(l&T) technology using multiple objective linear programming(MOLP). The MOLP model involves the simultaneous maximization of three linear objective functions associated with three criteria, which are social, technological, and economic criterion. This model is different from the traditional one which only involves the maximization of economic criterion. It yields a suitable R&D investment ratio to each technology field. Its application to the National R&D Project in l&t Industry is also presented. In this application, the Analytic Hierarchy Process(AHP) is proposed to estimate the weights, which used as the coefficients in each objective function of the MOLP model. Then the problem is solved using the interactive method STEM. It is showed that with the aid of STEM, the MOLP model can be useful decision aid in formulation R&D investment plan in l&t industry. It is expected that the MOLP model works as the basis for planning R&D investment strategy in l&T industry.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.156-156
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• 2015

최근 화석연료의 사용으로 인한 지구온난화 등 환경파괴가 점점 증가하는 추세이며 이로 인해 신재생에너지 중 하나인 수력발전이 주목받고 있다. 수력발전은 물의 위치에너지를 기계에너지로 이를 다시 전기에너지로 변환하는 친환경적인 방식으로 운영된다. 수력발전량은 우리나라 전체 발전량의 1.5% 정도로 적은 양의 발전량을 생산하지만 가동시간이 짧아 전력수요가 급변하는 상황에 대비 가능하기 때문에 수력발전은 필수적이다. 기후변화의 영향으로 연평균강수량은 증가하는 양상을 보이나 연 강수일수는 줄어드는 등 수자원의 불확실성이 증가하고 있는 실정이다. 따라서 미래 불확실한 수자원 공급에 대비할 수 있는 수자원의 효율적 활용에 대한 연구가 필요하다. 본 연구에서는 하천의 유량이 계절에 따라 변동 폭이 크다는 점을 고려하며 월별 발전량을 최대화하기 위해 선형계획법을 적용하는 모형을 구축하였다. 선형계획법은 목적함수와 제약조건식 모두 1차식으로 비선형항을 포함할 수 없으나 초기 해가 불필요하고 최적해가 보장된다는 장점을 가진다. 일부 목적함수나 제약조건식에 비선형항이 포함되어 있을 경우 Successive Linear Programming(SLP), Piecewise Linear Programming(PLP), Taylor Expansion 등의 방법을 이용하여 선형화할 수 있다. 본 연구에서 비선형 제약조건은 Taylor Expansion을 이용하여 선형화하였으며 한강수계 9개 댐의 월간 발전량을 최대화시키는 장기 운영 모형을 구축하였다. 개발 환경은 Linux-CentOS이며 사용프로그램은 통계 분석에 많이 활용되는 R programming이다. R programming은 패키지를 이용한 개발이 용이하고 Windows 뿐만 아니라 Linux, Mac, Unix 등의 운영체제에서도 호환 가능하다는 장점이 있다.

• Journal of applied mathematics & informatics
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• v.24 no.1_2
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• pp.449-460
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• 2007

Several fuzzy approaches can be considered for solving multi-objective transportation problem. This paper presents a fuzzy goal programming approach to determine an optimal compromise solution for the multiobjective transportation problem. We assume that each objective function has a fuzzy goal. Also we assign a special type of nonlinear (hyperbolic) membership function to each objective function to describe each fuzzy goal. The approach focuses on minimizing the negative deviation variables from 1 to obtain a compromise solution of the multiobjective transportation problem. We show that the proposed method and the fuzzy programming method are equivalent. In addition, the proposed approach can be applied to solve other multiobjective mathematical programming problems. A numerical example is given to illustrate the efficiency of the proposed approach.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.4
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• pp.19-31
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• 2014

We study parallel processing techniques for the R programming language of high performance computing technology. In this study, we used massively parallel computing system which has 25,408 cpu cores. We conducted a performance evaluation of a distributed memory system using MPI and of a the shared memory system using OpenMP. Our findings are summarized as follows. First, For some particular algorithms, parallel processing is about 150 times faster than serial processing in R. Second, the distributed memory system gets faster as the number of nodes increases while shared memory system is limited in the improvement of performance, due to the limit of the number of cpus in a single system.