• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.1
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• pp.231-243
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• 1994

A stochastic programming model for river water quality management was developed. River water quality, river flow, quality and flowrate of the wastewater treatment plant inflow were treated as random variables in the model. Withdrawal for water supply and submerged weir reaeration were included in the model itself. A probabilistic model was formulated to compute the expectation and variance of water quality using Streeter-Phelps equation. Chance constraints of the optimization problem were converted to deterministic equivalents by chance constrained method. Objective function was total annual treatment cost of all wastewater treatment plants in the region. Construction cost function and O & M cost function were derived in the form of nonlinear equations that are functions of treatment efficiency and capacity of treatment plant. The optimization problem was solved by nonlinear programming. This model was applied to the lower Han River. The results show that the reliability to meet the DO standards of the year 1996 is about 50% when the treatment level of four wastewater treatment plants in Seoul is secondary treatment, and BOD load from the tributary inflows is the same as present time. And when BOD load from Tanchon, Jungrangchon, and Anyangchon is decreased to 50%, the reliability to meet the DO standards of the year 1996 is above 60%. This results indicated that for the sake of the water quality conservation of the lower Han River, water quality of the tributaries must be improved, and at least secondary level of treatment is required in the wastewater treatment plants.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.359-366
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• 2005

Most engineering optimization are based on numerical linear and nonlinear programming methods that require substantial gradient information and usually seek to improve the solution in the neighborhood of a starting point. These algorithm, however, reveal a limited approach to complicated real-world optimization problems. If there is more than one local optimum in the problem, the result may depend on the selection of an initial point, and the obtained optimal solution may not necessarily be the global optimum. This paper describes a new harmony search(HS) meta-heuristic algorithm-based approach for structural size optimization problems with continuous design variables. This recently developed HS algorithm is conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search so that derivative information is unnecessary. Two classical space truss optimization problems are presented to demonstrate the effectiveness and robustness of the HS algorithm. The results indicate that the proposed approach is a powerful search and optimization technique that may yield better solutions to structural engineering problems than those obtained using current algorithms.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.4 s.175
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• pp.894-900
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• 2000

Optimization of chassis frame is performed according to the minimization of eleven responses representing one total frame weight, three natural frequencies and seven strength limits of chassis frame that are analyzed by using each response surface model from D-optimal design of experiments. After each response surface model is constructed form D-optimal design and random orthogonal array, the main effect and sensitivity analyses are successfully carried out by using this approximated regression model and the optimal solutions are obtained by using a nonlinear programming method. The response surface models and the optimization algorithms are used together to obtain the optimal design of chassis frame. The eleven-polynomial response surface models of the thirteen frame members (design factors) are constructed by using D-optimal Design and the multi-disciplinary design optimization is also performed by applying dual response analysis.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.287-293
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• 2005

Predicting RNA secondary structure as accurately as possible is very important in functional analysis of RNA molecules. However, different prediction methods and related parameters including terminal GU pair of helices, minimum length of helices, and free energy systems often give different prediction results for the same RNA sequence. Then, which structure is more important than the others? i.e. which combinations of the methods and related parameters are the optimal? In order to investigate above problems, first, three prediction methods, namely, random stacking of helical regions (RS), helical regions distribution (HD), and Zuker's minimum free energy algorithm (ZMFE) were compared by taking 1139 tRNA sequences from Rfam database as the samples with different combinations of parameters. The optimal parameters are derived. Second, Zuker's dynamic programming method for prediction of RNA secondary structure was revised using the above optimal parameters and related software BJRNAFold was developed. Third, the effects of short-range interaction were studied. The results indicated that the prediction accuracy would be improved much if proper short-range factor were introduced. But the optimal short-range factor was difficult to determine. A user-adjustable parameter for short-range factor was introduced in BJRNAFold software.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.3
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• pp.95-102
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• 2018

The objective of this research is to explore the diverse challenges faced by the customer as well transport providers through the selected modes of transportation of the second most populous country in the world - India. Two separate well-structured questionnaires administered to garner the opinions on different challenges. A random sample of 100 equally selected from the customers of 3 modes of transportation along with 30 transport providers. The collected data was analyzed in Microsoft Excel and R Studio platforms using Percentile Rank Tool and R Programming Language for Chi-square test respectively. Traffic congestion coupled with parking is the major problem in case of roadways while Safety and cleanliness in railways are the first amongst the problems to reckon with. High fares and lack of trained employees are the biggest challenges faced by aviation industry. The research is concentrated only in the states of Andhra Pradesh and Telangana in India with most widely used three modes of transportation viz., Road, Rail and Airways. This research paper is first of its kind which has collected the opinions of both customers as well transport providers on the problems faced. This research proffers information about the challenges faced by the customers which there will be an enormous possibility to review their strategies and plans.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.48
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• pp.37-52
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• 1998

In many distribution systems important cost reductions and/or service improvements may be achieved by adopting an efficient inventory policy and proper selection of facilities. These efficiency improvements and service enhancements clearly require an integrated approach towards various logistical planning functions. The areas of inventory control and transportation planning need to be closely coordinated. The purpose of this paper is to construct an integrated model that can minimize the total cost of the transportation and inventory systems between multiple origin and destination points, where in origin point i has the supply of commodities and in destination point j requires the commodities. In this case, demands of the destination points are assumed random variables which have a known probability distribution. Using the lot-size reorder-point policy and the safety stock level that minimize total cost we find optimal distribution centers which transport the commodities to the destination points and suggest an optimal inventory policy to the selected distribution center. We also show if a demand greater than one unit will occur at a particular time, we describe the approximate optional replenishment policy from computational results of this lot-size reorder-point policy. This model is formulated as a 0-1 nonlinear integer programming problem. To solve the problem, this paper proposes heuristic computational procedures and a computer program with UNIX C language. In the usefulness review, we show the meaning and validity of the proposed model and exhibit the results of a comparison between our approach and the traditional approach, respectively.

• Research in Mathematical Education
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• v.5 no.1
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• pp.13-24
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• 2001

Using computer technology in teaching school mathematics creates new instructional environments. The emphases on the use of computer technology in the classrooms and in particular the use of computer-based exploration as a context of mathematics instruction have been reflected in the recommendation of the NCTM (Curriculum and Evaluation Standards for School Mathematics, 1989). Although the power of using computer technology in the exploration of mathematical problems has been recognized and stressed by many educators, we do not have many research studies on mathematics in computer-based explorations. Especially research has failed to clarify how computer technology can contribute to the construction of procedural and conceptual knowledge of mathematics. Up to now most researches on procedural and conceptual knowledge in computer environments have only focused on classifying programming languages which program language has more random access and rich interrelationship characteristic in relation to conceptual knowledge in humans, and which computer language has more characteristic flavor of procedural knowledge. How computer-based explorations affect the knowledge construction of mathematics, therefore, emerges as an issue of research on teacher education program for theoretical framework. This situation leads to do research on the effectiveness of using computer explorations in pre-service teacher education in terms of procedural and conceptual knowledge construction.

• Proceedings of the Korean Vacuum Society Conference
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• 2011.08a
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• pp.285-285
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• 2011

최근 반도체 소자의 미세화에 따라, 단채널 효과에 의한 누설전류 및 소비전력의 증가 등이 문제되고 있다. 대표적인 휘발성 메모리인 dynammic random access memory (DRAM)의 경우, 소자의 집적화가 진행됨에 따라 저장되는 정보의 양을 유지하기 위해 캐패시터영역의 복잡한 공정을 요구하게 된다. 하나의 캐패시터와 하나의 트랜지스터로 이루어진 기존의 DRAM과 달리, single transistor (1T) DRAM은 silicon-on-insulator (SOI) 기술을 기반으로 하여, 하나의 트랜지스터로 DRAM 동작을 구현한다. 이러한 구조적인 이점 이외에도, 우수한 전기적 절연 특성과 기생 정전용량 및 소비 전력의 감소 등의 장점을 가지고 있다. 또한 strained-Si 층을 적용한 strained-Silicon-On-Insulator (sSOI) 기술을 이용하여, 전기적 특성 및 메모리 특성의 향상을 기대 할 수 있다. 본 연구에서는 sSOI 기판위에 1T-DRAM을 구현하였으며, impact ionization과 gate induced-drain-leakage (GIDL) 전류에 의한 메모리 구동 방법을 통해 sSOI 1T-DRAM의 메모리 특성을 평가하였다. 그 결과 strain 효과에 의한 전기적 특성의 향상을 확인하였으며, GIDL 전류를 이용한 메모리 구동 방법을 사용했을 경우 낮은 소비 전력과 개선된 메모리 윈도우를 확인하였다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.105-116
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• 2018

In this study, we consider the assembly line balancing (ALB) problem which is known as an very important decision dealing with the optimal design of assembly lines. We consider ALB problems with soft constraints which are expected to be fulfilled, however they are not necessarily to be satisfied always and they are difficult to be presented in exact quantitative forms. In previous studies, most researches have dealt with hard constraints which should be satisfied at all time in ALB problems. In this study, we modify the mixed integer programming model of the problem introduced in the existing study where the problem was first considered. Based on the modified model, we propose a new algorithm using the genetic algorithm (GA). In the algorithm, new features like, a mixed initial population selection method composed of the random selection method and the elite solutions of the simple ALB problem, a fitness evaluation method based on achievement ratio are applied. In addition, we select the genetic operators and parameters which are appropriate for the soft assignment constraints through the preliminary tests. From the results of the computational experiments, it is shown that the proposed algorithm generated the solutions with the high achievement ratio of the soft constraints.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.11
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• pp.209-218
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• 2004

The purpose of this paper is to suggest a practical and simple method for the identification of the joint mechanical properties and to apply it to human knee joints. The passive moment at a joint was modeled by three mechanical parts, that is, a gravity term, a linear damper term and a nonlinear spring term. Passive pendulum tests were performed in 5 fat and 5 thin men. The data of pendulum test were used to identify the mechanical properties of joints through sequential quadratic programming (SQP) with random initial values. The identification was successful where the normalized root-mean-squared (RMS) errors between the simulated and experimental joint angle trajectories were less than 10％. The parameter values of mechanical properties obtained in this study agreed with literature. The inertia, gravity and the damping constant were greater at fat men, which indicates more resistance to body movement and more energy consumption fer fat men. The suggested method is noninvasive and requires simple setup and short measurement time. It is expected to be useful in the evaluation of joint pathologies.