• 전기학회논문지
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• 제66권7호
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• pp.1053-1058
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• 2017

In this paper, the design of iron loss minimization of 600W was performed by using Quasi-Newton method. Stator shoe, the width of stator teeth and yoke, and the length of d-axis flux path were selected as design parameters, and the output characteristics according to each design variable were considered. The objective function was set to minimize iron loss. Using the Quasi-Newton method, the variables converged to the target value while changing simultaneously and multiple times. As the algorithm advanced optimization, the correlation with the behavior of each variable was compared and analyzed.

• Korean Journal of Hydrosciences
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• 제7권
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• pp.61-75
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• 1996

The purpose of this study is to develop an efficient model for the least cost design of multi-site detention systems. The IDP (Incremental Dynamic Programming) model for optimal design is composed of two sub-models : hydrologic-hydraulic model and optimization model. The objective function of IDP is the sum of costs ; acquisition cost of the land, construction cost of detention basin and pumping system. Model inputs include channel characteristics, hydrologic parameters, design storm, and cost function. The model is applied to the Jung-Rang Cheon basin in Seoul, a watershed with cetention basins in multiple branching channels. The application results show that the detention system can be designed reasonably for various conditions and the model can be applied to multi-site detention system design.

• 디지털융복합연구
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• 제12권6호
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• pp.509-517
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• 2014

본 연구의 목적은 간호대학생들의 대인관계 증진 프로그램을 위한 기초자료로, 간호대학생들의 대인관계 및 관련요인을 파악하기 위해 시행되었다. 연구설계는 서술적 상관관계연구로, 연구기간은 2013년 6월 5일부터 6월 20일까지였으며 연구대상은 경상남도 G시에 소재하는 K대학교 간호학과 학생 306명이었다. 수집된 자료는 SPSS 프로그램을 이용하여 빈도, 백분율, t-test, ANOVA, Pearson's correlation coefficient, 다중회귀분석으로 분석하였으며, 결과는 다음과 같다. 대상자의 대인관계, 가족기능, 자아분화 및 의사결정유형간의 상관관계를 검정한 결과, 간호대학생들의 대인관계는 가족기능, 자아분화와 유의한 양의 상관관계를 나타내었다. 또한 대상자의 대인관계에 영향을 미치는 관련변인은 자아분화, 가족기능이었다. 결론적으로 자아분화와 가족기능은 간호대학생들의 대인관계에 영향을 미치는 중요한 요인임이 확인되었다.

• 한국의류학회지
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• 제22권1호
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• pp.18-28
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• 1998

The objective of the study was to observe the difference of moving function of lower-limb in relation to the length 8t silouutte of tight skirt. Four types of tight skirts (2 lengths$\times$2 silhouettes) were made for the experiment. The surface E.M.S in four different locations of leg muscles (Rectos femoris, Semitendinosus, Tibalis anterior, Gastrocnemius) were recorded. The sensory test to decide how to be fatigued after longtime wearing of skirt were examined two times per a day. The fatigue sensory test was scored a Likert-type scale (1= no fatigue, 5=heavy fatigue). Data were analyzed by the repeated ANOVA ann Duncan's multiple range test with use of SAS Package. The main results of this study were as follows: 1. As a result of analysis of E.M.S., in case of walking on the floor there was significant difference in the moving function according to length of skirt and in case of stepping there was significant differnce in three ways (length silhouette, length, silhouette). 2. From the record of walking the step-length, stride-length, step-width were found affected by garments, but foot-angle was not affected. The moving function of slim type was lower than that of semi type and that of ankle-length skirt was lower than that of knee-length skirt. 3. The results of the sensory test agreed with that of E.M.G and Footprints.

• International Journal of Fluid Machinery and Systems
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• 제9권3호
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• pp.265-276
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• 2016

Energy systems working coherently in different conditions may not have a specific design which can provide optimal performance. A system working for a longer period at lower efficiency implies higher energy consumption. In this effort, a methodology demonstrated by a jet pump design and optimization via numerical modeling for fluid dynamics and implementation of an evolutionary algorithm for the optimization shows a reduction in computational costs. The jet pump inherently has a low efficiency because of improper mixing of primary and secondary fluids, and multiple momentum and energy transfer phenomena associated with it. The high fidelity solutions were obtained through a validated numerical model to construct an approximate function through surrogate analysis. Pareto-optimal solutions for two objective functions, i.e., secondary fluid pressure head and primary fluid pressure-drop, were generated through a multi-objective genetic algorithm. For the jet pump geometry, a design space of several design variables was discretized using the Latin hypercube sampling method for the optimization. The performance analysis of the surrogate models shows that the combined surrogates perform better than a single surrogate and the optimized jet pump shows a higher performance. The approach can be implemented in other energy systems to find a better design.

• Industrial Engineering and Management Systems
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• 제3권1호
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• pp.78-84
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• 2004

To optimize movement of a multi-joint robot arm is known to be a difficult problem, because it is a kind of redundant system. Although the end-effector is set its position by each angle of the joints, the angle of each joint cannot be uniquely determined by the position of the end-effector. There exist the infinite number of different sets of joint angles which represent the same position of the end-effector. This paper describes how to manage the angle of each joint to move its end-effector preferably on an X-Y plane with obstacles in the end-effector’s reachable area, and how to optimize the movement of a multi-joint robot arm, evading obstacles. The definition of “preferable” movement depends upon a purpose of robot operation. First, we divide viewpoints of preference into two, 1) the standpoint of the end-effector, and 2) the standpoint of joints. Then, we define multiple objective functions, and formulate it into a multi-objective programming problem. Finally, we solve it using multi-purpose genetic algorithm, and obtain reasonable results. The method described here is possible to add appropriate objective function if necessary for the purpose.

• Asian-Australasian Journal of Animal Sciences
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• 제33권10호
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• pp.1633-1641
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• 2020

Objective: The objective of this study was to develop a model for estimating the carcass weight of Hanwoo cattle as a function of body measurements using three different modeling approaches: i) multiple regression analysis, ii) partial least square regression analysis, and iii) a neural network. Methods: Data from a total of 134 Hanwoo cattle were obtained from the National Institute of Animal Science in South Korea. Among the 372 variables in the raw data, 20 variables related to carcass weight and body measurements were extracted to use in multiple regression, partial least square regression, and an artificial neural network to estimate the cold carcass weight of Hanwoo cattle by any of seven body measurements significantly related to carcass weight or by all 19 body measurement variables. For developing and training the model, 100 data points were used, whereas the 34 remaining data points were used to test the model estimation. Results: The R² values from testing the developed models by multiple regression, partial least square regression, and an artificial neural network with seven significant variables were 0.91, 0.91, and 0.92, respectively, whereas all the methods exhibited similar R² values of approximately 0.93 with all 19 body measurement variables. In addition, relative errors were within 4%, suggesting that the developed model was reliable in estimating Hanwoo cattle carcass weight. The neural network exhibited the highest accuracy. Conclusion: The developed model was applicable for estimating Hanwoo cattle carcass weight using body measurements. Because the procedure and required variables could differ according to the type of model, it was necessary to select the best model suitable for the system with which to calculate the model.

• Advances in materials Research
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• 제5권2호
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• pp.67-80
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• 2016

The objective of the present work is to optimize process parameters namely, cutting speed, feed rate, and depth of cut in milling of AISI 304 stainless steel. In this work, experiments were carried out as per the Taguchi experimental design and an $L_{27}$ orthogonal array was used to study the influence of various combinations of process parameters on surface roughness (Ra) and material removal rate (MRR). As a dynamic approach, the multiple response optimization was carried out using grey relational analysis (GRA) and desirability function analysis (DFA) for simultaneous evaluation. These two methods are considered in optimization, as both are multiple criteria evaluation and not much complicated. The optimum process parameters found to be cutting speed at 63 m/min, feed rate at 600 mm/min, and depth of cut at 0.8 mm. Analysis of variance (ANOVA) was employed to classify the significant parameters affecting the responses. The results indicate that depth of cut is the most significant parameter affecting multiple response characteristics of GFRP composites followed by feed rate and cutting speed. The experimental results for the optimal setting show that there is considerable improvement in the process.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권10호
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• pp.3685-3707
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• 2021

In recent years, facial attribute editing has been successfully used to effectively change face images of various attributes based on generative adversarial networks and encoder-decoder models. However, existing models have a limitation in that they may change an unintended part in the process of changing an attribute or may generate an unnatural result. In this paper, we propose a model that improves the learning of the attention mask by adding a spatial attention mechanism based on the unified selective transfer network (referred to as STGAN) using semi-supervised learning. The proposed model can edit multiple attributes while preserving details independent of the attributes being edited. This study makes two main contributions to the literature. First, we propose an encoder-decoder model structure that learns and edits multiple facial attributes and suppresses distortion using an attention mask. Second, we define guide masks and propose a method and an objective function that use the guide masks for multiple facial attribute editing through semi-supervised learning. Through qualitative and quantitative evaluations of the experimental results, the proposed method was proven to yield improved results that preserve the image details by suppressing unintended changes than existing methods.

• 한국구조물진단유지관리공학회 논문집
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• 제24권3호
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• pp.26-38
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• 2020

자기 충전형 콘크리트의 배합물 설계는 전형적인 다기준의사결정의 과정이다. 본 연구에서는 실험설계법과 반응표면법을 이용하여 SCC 배합물 전산 설계가 가능하도록 재료성능 및 비용모델을 생성하고, 요구조건을 반영한 여러 성능 사이의 상대적 중요도를 산정하여 가중 다목적 설계문제로 정식화하여 수치최적해를 계산함으로써 비용효율을 고려한 SCC최적설계를 수행하였다. 실험비용과 시간을 고려하여 SCC의 수많은 요구성능 중 압축강도, 철근충전성, 재료분리저항성, 비용정보 등을 다목적 최적화의 목적함수로 설정하였다. 재료경제성을 최적재료설계프로세스에 합리적으로 반영함으로써 경제적 콘크리트배합설계를 수행할 수 있었으며, 본 연구 결과 실험점 계획에서부터 최적해 산출에 이르는 과정을 객관적인 프로세스로 구성함으로써 콘크리트 범용 최적재료설계기술 및 전산화를 기대할 수 있다.