• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.4
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• pp.137-146
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• 2016

In recent years, business environment is faced with multi uncertainty that have not been suffered in the past. As supply chain is getting expanded and longer, the flow of information, material and production is also being complicated. It is well known that development service industry using application software has various uncertainty in random events such as supply and demand fluctuation of developer's capcity, project effective date after winning a contract, manpower cost (or revenue), subcontract cost (or purchase), and overrun due to developer's skill-level. This study intends to social contribution through attempts to optimize enterprise's goal by supply chain management platform to balance demand and supply and stochastic programming which is basically applied in order to solve uncertainty considering economical and operational risk at solution supplier. In Particular, this study emphasizes to determine allocation of internal and external manpower of developers using S&OP (Sales & Operations Planning) as monthly resource input has constraint on resource's capability that shared in industry or task. This study is to verify how Stochastic Programming such as Markowitz's MV (Mean Variance) model or 2-Stage Recourse Model is flexible and efficient than Deterministic Programming in software enterprise field by experiment with process and data from service industry which is manufacturing software and performing projects. In addition, this study is also to analysis how profit and labor input plan according to scope of uncertainty is changed based on Pareto Optimal, then lastly it is to enumerate limitation of the study extracted drawback which can be happened in real business environment and to contribute direction in future research considering another applicable methodology.

• Journal of The Korean Association of Information Education
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• v.19 no.4
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• pp.409-418
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• 2015

The purpose of this study is derived implications at software curriculum development utilizing the backward design model. In this study, we developed 'Algorithms and Programming' unit teaching plan based on backward design template. First, we have derived enduring understandings, essential questions, specific knowledge and skill on 'Algorithms and Programming' unit by considering the goal, content, achievement standard of Software education operating instructions. Second, we developed authentic tasks using GRASPS technic and holistic scoring rubrics. Third, we developed 7 lesson 14 WHERETO element for effective teaching in 'Algorithms and Programming' unit. Fourth, we investigated about the effectiveness of the development unit based on backward design. Backward design could be useful of developing curriculum unit and lesson plan at software education.

• Journal of Communications and Networks
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• v.17 no.2
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• pp.184-197
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• 2015

This paper builds on a recent method, chain routing with even energy consumption (CREEC), for designing a wireless sensor network with chain topology and for scheduling the communication to ensure even average energy consumption in the network. In here a new suboptimal design is proposed and compared with the CREEC design. The chain topology in CREEC is reconfigured after each group of n converge-casts with the goal of making the energy consumption along the new paths between the nodes in the chain as even as possible. The new method described in this paper designs a single near-optimal Hamiltonian circuit, used to obtain multiple chains having only the terminal nodes different at different converge-casts. The advantage of the new scheme is that for the whole life of the network most of the communication takes place between same pairs of nodes, therefore keeping topology reconfigurations at a minimum. The optimal scheduling of the communication between the network and base station in order to maximize network lifetime, given the chosen minimum length circuit, becomes a simple linear programming problem which needs to be solved only once, at the initialization stage. The maximum lifetime obtained when using any combination of chains is shown to be upper bounded by the solution of a suitable linear programming problem. The upper bounds show that the proposed method provides near-optimal solutions for several wireless sensor network parameter sets.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.12
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• pp.1793-1803
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• 2010

The weighting method and goal programming require weighting factors or target values to obtain a Pareto optimal solution. However, it is difficult to define these parameters, and a Pareto solution is not guaranteed when the choice of the parameters is incorrect. Recently, the Mahalanobis Taguchi System (MTS) has been introduced to minimize the Mahalanobis distance (MD). However, the MTS method cannot obtain a Pareto optimal solution. We propose a function called the skewed Mahalanobis distance (SMD) to obtain a Pareto optimal solution while retaining the advantages of the MD. The SMD is a new distance scale that multiplies the skewed value of a design point by the MD. The weighting factors are automatically reflected when the SMD is calculated. The SMD always gives a unique Pareto optimal solution. To verify the efficiency of the SMD, we present two numerical examples and show that the SMD can obtain a unique Pareto optimal solution without any additional information.

• Journal of the Korea Society of Computer and Information
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• v.3 no.2
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• pp.189-199
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• 1998

This study presents a FZOGP(fuzzified zero-one goal programming) model and a DHP (Delphic Hierarchy Process) that can be used to help information systems(IS) managers decides which IS projects should be selected. Delphic method is conducted prior to AHP so that not only can the objectives to be considered in analysis be determined, but the opinions of all decision makers can also be incorporated in problem formulation. While the DHP provides an ideal ranking process for the selection of IS Projects, it does not consider real constraints that exists in decision making process. Then this study intends to show how the DHP can be used to establish a priority structure for use within a FZOGP model. The advantages of FZOGP model are as follows: the imprecise aspiration level for each objective can be considered in FZOGP model. And, the common features between the new FZOGP and the GP models are that the objective functions in both models are minimized and the structure of their formulations are the same.

• Korean Business Review
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• v.15
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• pp.99-114
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• 2002

Recently several business models concerning e-Business has been introduced. But the different environment for each business requires the business model which is contingent to its specific situation. We, therefore, need to develop the e-Business models considering environment factors such as capital size, technology level, collection ability and amount of information, profit or target customers, etc. There can be several ways to create the value of an e-Business firm. A way among them is to develop limited area by focusing on core parts of the firm. This way leads for the firm to search the investment priority in order to solve the problem, which is to set a proper production and investment level for concentrating on competitively excellent areas of the firm. In this paper, we propose a method to decide the investment priority effectively when making a decision using fuzzy information. The method by our model is to minimize tolerances of given business fuzzy goals.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.267-277
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• 2022

Recently, the topics of SW liberal-arts education are diversifying, from 'Computational Thinking(CT)' to 'Programming, Data Analysis and Artificial Intelligence(AI)' in universities. We expect that the diversification of SW liberal-arts subjects does not just mean that the learning contents are different, but also differentiates the educational goals and educational effects of each subject. In this paper, we conducted a case study to analyze the educational effect according to the educational goals of two SW liberal-arts subjects, CT and Data Analysis Fundamentals(DA), for humanities college students. We confirmed that the educational effect of 'CT Efficacy' increased significantly in accordance with the common educational goal of 'Improving CT-based SW convergence competency' in both subjects. However, we also analyzed the difference in the educational effects of 'CT(the goal of basic SW education)' and 'DA(the goal of major-friendly SW education)', which have different subject goals. 'CT' mainly showed an educational effect on how to solve general daily problems, and 'DA' showed confidence in how to solve major problems along with general problems.

• Journal of the Korean Society of Safety
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• v.30 no.3
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• pp.32-37
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• 2015

In the fields of plant layout optimization, the main goal is to minimize the construction cost including pipelines as satisfying all constraints such as safety and operating issues. However, what is the lacking of considerations in previous researches is to consider proper safety and maintenance spaces for a complex plant. Based on the mathematical programming, MILP(Mixed Integer Linear Programming) problems including various constraints can be formulated to find the optimal solution which is to achieve the best economic benefits. The objective function of this problem is the sum of piping cost, pumping cost and area cost. In general, many conventional optimization solvers are used to find a MILP problem. However, it is really hard to solve this problem due to complex inequality and equality constraints, since it is impossible to use the derivatives of objective functions and constraints. To resolve this problem, the PSO (Particle Swarm Optimization), which is one of the representative sampling approaches and does not need to use derivatives of equations, is employed to find the optimal solution considering various complex constraints in this study. The EO (Ethylene Oxide) plant is tested to verify the efficacy of the proposed method.

• Journal of Power System Engineering
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• v.21 no.6
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• pp.56-61
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• 2017

The check valves are mechanical valves that permit fluids to flow in only one direction, preventing flow from reversing. It is classified as one way directional valves. There are various types of check valves that used in a marine application. A lift type check valve uses the disc to open and close the passage of fluid. The disc lift up from seat as pressure below the disc increases, while drop in pressure on the inlet side or a build up of pressure on the outlet side causes the valve to close. An important concept in check valves is the cracking pressure which is the minimum upstream pressure at which the valve will operate. On the other hand, optimization is a process of finding the best set of parameters to reach a goal while not violating certain constraints. The AMESim software provides NLPQL(Nonlinear Programming by Quadratic Lagrangian) and genetic algorithm(GA) for optimization. NLPQL is the implementation of a SQP(sequential quadratic programming) algorithm. SQP is a standard method, based on the use of a gradient of objective functions and constraints to solve a non-linear optimization problem. A characteristic of the NLPQL is that it stops as soon as it finds a local minimum. Thus, the simulation results may be highly dependent on the starting point which user give to the algorithm. In this paper, we carried out optimization design of the check valve with NLPQL algorithm.

• Journal of Electrical Engineering and Technology
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• v.11 no.1
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• pp.47-54
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• 2016

Microgrids offer several reliability benefits, such as the improvement of load-point reliability and the opportunity for reliability-differentiated services. The primary goal of this work is to investigate the impacts of operating condition on the reliability index for microgrid system. It relies on a component failure rate model which quantifies the relationship between component failure rate and state variables. Some parameters involved are characterized by subjective uncertainty. Thus, fuzzy numbers are introduced to represent such parameters, and an optimization model based on Fuzzy Chance Constrained Programming (FCCP) is established for reliability index calculation. In addition, we present a hybrid algorithm which combines scenario enumeration and fuzzy simulation as a solution tool. The simulations in a microgrid test system show that reliability indices without considering operating condition can often prove to be optimistic. We also investigate two groups of situations, which include the different penetration levels of microsource and different confidence levels. The results support the necessity of considering operating condition for achieving accurate reliability evaluation.