• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.443-451
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• 2005

The studied in this paper is a new algorithm for searching the maximum likelihood estimate(MLE) in which probability density function is not explicitly expressed. Newton-Raphson's root-finding routine and a nonlinear numerical optimization algorithm with constraint (so-called feasible sequential quadratic programming) are used. This algorithm is applied to the Wakeby distribution which is importantly used in hydrology and water resource research for analysis of extreme rainfall. The performance comparison between maximum likelihood estimates and method of L-moment estimates (L-ME) is studied by Monte-carlo simulation. The recommended methods are L-ME for up to 300 observations and MLE for over the sample size, respectively. Methods for speeding up the algorithm and for computing variances of estimates are discussed.

• Structural Engineering and Mechanics
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• v.88 no.6
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• pp.535-549
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• 2023

Deep extreme learning machine (DELM) and multi-verse optimization algorithms (MVO) are hybridized for designing an optimal and adaptive control framework for uncertain buildings. In this approach, first, a robust model predictive control (RMPC) scheme is developed to handle the problem uncertainty. The optimality and adaptivity of the proposed controller are provided by the optimal determination of the tunning weights of the linear programming (LP) cost function for clustered external loads using the MVO. The final control policy is achieved by collecting the clustered data and training them by DELM. The efficiency of the introduced control scheme is demonstrated by the numerical simulation of a ten-story benchmark building subjected to earthquake excitations. The results represent the capability of the proposed framework compared to robust MPC (RMPC), conventional MPC (CMPC), and conventional DELM algorithms in structural motion control.

• Journal of the Korea Society of Computer and Information
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• v.10 no.1 s.33
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• pp.15-26
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• 2005

As one of the lightweight software development methodology, the XP (Extreme Programming) is the practical means to improve the productivity and qualify of software through the pursuit of 4 values - communication, simplicity, feedback, and courage. It appears, however, the TDD (Test Driven Development). one of the practices of in. has a problem. which is the unavailability of the test driven development in case of the prolonged period of testing or the failure of securing the independency of the test cases. This results in the emphasis on the importance of the Mock Objects recently. The Mock Objects, the one imitating the faulty real code, has the fundamentals of simplicity allowing even manual script but. due to the inefficiency of manual script of the Mock Objects in a real life, it is implemented the Mock Objects Generator such as Mockotjects, EasyMock in Java. It Is found difficult, however to apply the Mock Objects in C language due to its object -oriented Premise as well as the absence of mock objects generators for C language. Therefore, in this Paper it is presented the CMock, a Mock Objects generator fer C language which allows the easy creation of the Mock Objects, and the study is performed to verify the efficiency accordingly.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.53-56
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• 2000

The problem ( Ρ ) of optimizing a linear function d$\^$T/x over the set of efficient set for a multiple objective linear program ( Μ ) is difficult because the efficient set is nonconvex. There some interesting properties between the objective linear vector ｄ and the matrix of multiple objectives C and those properties lead us to establish criteria to solve ( Ρ ) with a linear program. In this paper we investigate a system of the linear equations C$\^$T/${\alpha}$=d and construct two linearly independent positive vectors ${\mu}$, ν such that ${\alpha}$=${\mu}$-ν. From those vectors ${\mu}$, ν, solving an weighted sum linear program for finding an efficient extreme point for the ( Μ ) is a way to get an optimal solution ( Ρ ). Therefore our theory gives an easy way of solving nonconvex program ( Ρ ) with a weighted sum linear program.

• Journal of Korea Water Resources Association
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• v.35 no.1
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• pp.37-49
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• 2002

The application of conventional method for optimizing firm water supply and hydro-electric power generation has some limitation during abnormal or extreme drought periods. Hashimoto et al. (1982) suggested there risk evaluation criteria such as reliability, resilience, and vulnerability. These three criteria have been incorporated into a mixed-integer programming model for evaluating the possible performance of water- supply reservoir (Moy et al., 1986; Srinivasan et al., 1999). However, till now, these kind of researches have been conducted only for water-supply reservoir. Therefore there have been no other study for multi-purpose dam including hydro-electric power generation. This study presents an improved formulation of the previous model for evaluating a multi-purpose reservoir system operation considering water supply and hydro-electric power generation. The modified model was applied to the Daechung multi-purpose reservoir system in the Keum river basin to demonstrate the efficiency of the improved formulation.

• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.2
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• pp.13-29
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• 1997

This paper considers a new routing problem, successive max-min connection ratio problem (SMCRP), arised in circuit telecommunication networks such as SONET and WDM optical transport network. An optimization model for SMCRP is established based on link-flow formulation. It's first optimization process is an integral version of maximum concurrent flow problem. Integer condition does not give the same connection-ratio of each node-pair at an optimal solution any more. It is also an integral multi-commodity flow problem with fairness restriction. In order to guarantee fairness to every node-pair the minimum of connection ratios to demand is maximized. NP- hardness of SMCRP is proved and a heuristic algorithm with polynomial-time bound is developed for the problem. Augmenting path and rerouting flow are used for the algorithm. The heuristic algorithm is implemented and tested for networks of different sizes. The results are compared with those given by GAMS/OSL, a popular commercial solver for integer programming problem.n among ferrite-pearlite matrix, the increase in spheroidal ratio with increasing fatigue limitation, 90% had the highest, 14.3% increasing more then 70%, distribution range of fatigue.
ife was small in same stress level. (2) $\sqrt{area}_{max}$ of graphite can be used to predict fatigue limit of Ductile Cast Iron. The Statistical distribution of extreme values of $\sqrt{area}_{max}$ may be used as a guideline for the control of inclusion size in the steelmaking.

• Korean Management Science Review
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• v.31 no.2
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• pp.33-48
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• 2014

It is important to maintain on operational availability of aircraft during wartime. The KF-16 fighter, the backbone of the ROKAF (Republic Of Korea Air Force), has a single engine. Therefore, the engine has a critical influence on operational availability. The purpose of this study is to estimate optimal levels of spare part inventories concerning both engines and modules. That is provided by linear programming methods utilizing a developed meta-model. For drawing out the meta-model, we develop a simulation model which can consider wartime demands. In the previous study, $2^k$ factorial design method is used to check the influence of each independent variable. That method requires relatively many scenarios because every extreme value combination of independent variables should be checked. However, this study adopts NOLH (Nearly Orthogonal Latin Hypercube) as an experimental design. By adopting NOLH, this study increases not only efficiency but also accuracy. That is proven by comparing the validity of the developed meta-model on both experimental designs. This study also utilizes the OptQuest simulation tool in ARENA to derive the optimal level of spare stocks. By comparing the result of OptQuest to that of the developed meta-model, the validity of this study is secured.

• The KIPS Transactions:PartA
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• v.16A no.6
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• pp.453-462
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• 2009

Studies on software plagiarism detection, prevention and judgement have become widespread due to the growing of interest and importance for the protection and authentication of software intellectual property. Many previous studies focused on comparing all pairs of submitted codes by using attribute counting, token pattern, program parse tree, and similarity measuring algorithm. It is important to provide a clear-cut model for distinguishing plagiarism and collaboration. This paper proposes a source code clustering algorithm using a probability model on extreme value distribution. First, we propose an asymmetric distance measure pdist($P_a$, $P_b$) to measure the similarity of $P_a$ and $P_b$ Then, we construct the Plagiarism Direction Graph (PDG) for a given program set using pdist($P_a$, $P_b$) as edge weights. And, we transform the PDG into a Gumbel Distance Graph (GDG) model, since we found that the pdist($P_a$, $P_b$) score distribution is similar to a well-known Gumbel distribution. Second, we newly define pseudo-plagiarism which is a sort of virtual plagiarism forced by a very strong functional requirement in the specification. We conducted experiments with 18 groups of programs (more than 700 source codes) collected from the ICPC (International Collegiate Programming Contest) and KOI (Korean Olympiad for Informatics) programming contests. The experiments showed that most plagiarized codes could be detected with high sensitivity and that our algorithm successfully separated real plagiarism from pseudo plagiarism.

• Journal of Internet Computing and Services
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• v.9 no.2
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• pp.107-118
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• 2008

The XP, the representative methodology of Agile software development, maximizes the effectiveness of the development by focusing on development itself and using primitive and basic process definition that can be easily implemented in the fields. However, the most of XP's practices came from those of engineering and the manogement practices of work product tend to be overlooked. The research on the implementation of those manogement practices has not been performed enough. Because of deficiency of processes that guide the change control over major baselines of work product and that describe proper continuous integration and refactoring in XP, the integrity of those work products is difficult to be guaranteed. To fulfill this work product integrity, CM(configuration manogement) should be hired and CMMI(Capability Maturity Model Integration) is considered to be the best references for that purpose, CMMI defines the required practices of CM and leave implementation details to the organization so that it could customize those practices based on the characteristics of its development methods. The CM process implementation guidelines based on CMMI could provides work product integrity with a way of keeping XP's agility that includes continuous integration, refactoring and small release. In this research, we selected CM process factors applicable to XP among CMMI's CM practices and based on them we developed the CM implementation guidelines.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.581-588
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• 2017

This study was conducted to determine which factors would predict metabolic syndrome (MetS) perception and exercise by applying a machine learning classifier, or Extreme Gradient Boosting algorithm (XGBoost) from July 2014 to December 2015. Data were obtained from the Korean Community Health Survey (KCHS), representing different community-dwelling Korean adults 19 years and older, from 2009 to 2013. The dataset includes 370,430 adults. Outcomes were categorized as follows based on the perception of MetS and physical activity (PA): Stage 1 (no perception, no PA), Stage 2 (perception, no PA), and Stage 3 (perception, PA). Features common to all questionnaires for the last 5 years were selected for modeling. Overall, there were 161 features, categorical except for age and the visual analogue scale (EQ-VAS). We used the Extreme Boosting algorithm in R programming for a model to predict factors and achieved prediction accuracy in 0.735 submissions. The top 10 predictive factors in Stage 3 were: age, education level, attempt to control weight, EQ mobility, nutrition label checks, private health insurance, EQ-5D usual activities, anti-smoking advertising, EQ-VAS, education in health centers for diabetes, and dental care. In conclusion, the results showed that XGBoost can be used to identify factors influencing disease prevention and management using healthcare bigdata.