• Title/Summary/Keyword: full factorial

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The Effect of Garment Formality, Yin-Yang Level, and Body Type on Impression Formation (Part I) (아동의 의복과 체형이 인상형성에 미치는 영향(제 1 보) -국민학교 1학년 담임교사를 중심으로-)

  • 이미숙;김재숙
    • Journal of the Korean Society of Clothing and Textiles
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    • v.19 no.6
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    • pp.1017-1026
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    • 1995
  • The purpose of the study was to 1) extend the cognitive categorization theory in an attempt to explain the effect of garment formality, Yin-Yang, and body type of children on impression formation, and 2) to understand teacher's attitudes toward children's school outfits. The experimental design was a $2^3$_full factorial design by 3 independent variables. The stimuli consisted of 8 color photographs and the semantic differential response scale was used to analyze the responses of 267 teachers of elementary school. The data were analyzed by factor analysis, ANOVA, Duncan' test and content analysis. Four factors emerged to account for dimensions of first impressions. These were sociability, potency, dynamics, and cooperation. Garment formality effected on impression of cooperation dimension. Garment Yin-Yang and children's body type effected on impression of social and dynamics dimensions.

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A Study on Precision Infeed Grinding for the Silicon Wafer (실리콘 웨이퍼의 고정밀 단면 연삭에 관한 연구)

  • Ahn D.K.;Hwang J.Y.;Choi S.J.;Kwak C.Y.;Ha S.B.
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2005.06a
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    • pp.1-5
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    • 2005
  • The grinding process is replacing lapping and etching process because significant cost savings and performance improvemnets is possible. This paper presents the experimental results of wafer grinding. A three-variable two-level full factorial design was employed to reveal the main effects as well as the interaction effects of three process parameters such as wheel rotational speed, chuck table rotational speed and feed rate on TTV and STIR of wafers. The chuck table rotaional speed was a significant factor and the interaction effects was significant. The ground wafer shape was affected by surface shape of chuck table.

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조절된 코팅구조상에서 옵셋인쇄광택의 발현: Part 2

  • Jeon, Seong-Jae
    • Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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    • 2003.11a
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    • pp.121-134
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    • 2003
  • 최근의 많은 연구로부터 인쇄광택에 대한 코팅구조의 영향이 보고되고, 거론되고 있다. 그러나, 다각적이고, 다양한 잉크량 범위에서 인쇄광택의 개별적 인자에 대한 독립적 영향은 보고된 바 없다. 본 고에서는 다양한 코팅재료와 이어진 캘린더링 공정을 조합하여 Full-factorial실험설계에 준한 모델시료를 제작하고, 특성화하였다. 더불어 공극이 없지만 넓은 범위의 거칠음 수준을 가진 필름을 포함하였다. 통계도구를 사용하여 각 인자의 독립적인 영향을 추출하므로써, 각 구조인자의 함수로서 인쇄광택의 정량적인 반응도를 얻을 수 있었다. 결과는 60도와 75도 광택으로 표현하였다. 잉크공급량의 증가는 코팅층 거칠음의 영향을 약화는 시키되 배제시킬 수는 없었다. Matte급의 코팅층에 대한 인쇄광택은 코팅거칠음이 가장 큰 영향인자로 나타났다. 이는, 잉크필름의 Leveling을 저해하는, 큰 잉크필름의 분열형태와 코팅면을 따라 흐르며 형성되는 잉크필름 때문으로 생각되었다. 공극구조의 영향은 전반적으로 높은 잉크량과 백지광택수준에서 가장 크게 나타났다. 전체적으로는 코팅거칠음이 인쇄광택에 가장 강한 인자였으며, 공극크기, 공극부피가 뒤를 이었다. 그러나, 광택지 영역에서는 공극크기가 가장 강한 영향인자로 구분되었으며, 거칠음, 공극부피가 뒤를 이었다. 이러한 결과는 인쇄품질 측면에서 코팅을 최적화하는데 활용될 수 있을 것이다.

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A Study on Functionally Graded Material Spacer and Electrodes Shape in Gas Insulated Switchgear for the Improvement of Insulation Performance (절연성능 향상을 위한 가스절연 개폐장치에서의 경사 기능성 재료 스페이서 및 전극 형상 연구)

  • Ju, Heung-Jin;Kim, Bong-Seok;Ko, Kwang-Cheol
    • Proceedings of the KIEE Conference
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    • 2009.07a
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    • pp.1358_1359
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    • 2009
  • 가스 절연 개폐장치(Gas Insulated Switchgear : GIS)의 고체 스페이서에 경사기능성 재료(Functionally Graded Material : FGM)를 적용할 때, 전계의 완화를 예상할 수 있다. 특히, 균일 유전율 분포를 가지는 스페이서에서 양극 근처에 집중된 높은 전계가 FGM 스페이서를 사용할 때, 스페이서와 $SF_6$ 가스의 접촉부로 옮겨지며, 그 크기가 완화됨을 확인할 수 있었다[1]. 본 연구에서는 상용 고체 스페이서의 양극 부근에서의 전계 집중을 감소시키기 위해 전극 형상의 최적화를 수행하였다. 최적화 기법으로는 완전계승계획법(Full Factorial Design : FFD)과 결합된 반응표면법(Response Surface Method : RSM)을 이용하였으며, 균일 유전율 스페이서에서 양극 형상을 최적화하였다. 또한 타원형 유전율 분포를 가지는 FGM 스페이서를 이용함으로써, 상용 GIS 모델에 비해 최대 전계가 크게 완화될 수 있음을 확인하였으며, 상용 GIS의 외함부의 크기를 줄여 실제 소형화 가능 여부를 확인하였다.

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A Taguchi Approach to Parameter Setting in a Genetic Algorithm for General Job Shop Scheduling Problem

  • Sun, Ji Ung
    • Industrial Engineering and Management Systems
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    • v.6 no.2
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    • pp.119-124
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    • 2007
  • The most difficult and time-intensive issue in the successful implementation of genetic algorithms is to find good parameter setting, one of the most popular subjects of current research in genetic algorithms. In this study, we present a new efficient experimental design method for parameter optimization in a genetic algorithm for general job shop scheduling problem using the Taguchi method. Four genetic parameters including the population size, the crossover rate, the mutation rate, and the stopping condition are treated as design factors. For the performance characteristic, makespan is adopted. The number of jobs, the number of operations required to be processed in each job, and the number of machines are considered as noise factors in generating various job shop environments. A robust design experiment with inner and outer orthogonal arrays is conducted by computer simulation, and the optimal parameter setting is presented which consists of a combination of the level of each design factor. The validity of the optimal parameter setting is investigated by comparing its SN ratios with those obtained by an experiment with full factorial designs.

A Plasma-Etching Process Modeling Via a Polynomial Neural Network

  • Kim, Dong-Won;Kim, Byung-Whan;Park, Gwi-Tae
    • ETRI Journal
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    • v.26 no.4
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    • pp.297-306
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    • 2004
  • A plasma is a collection of charged particles and on average is electrically neutral. In fabricating integrated circuits, plasma etching is a key means to transfer a photoresist pattern into an underlayer material. To construct a predictive model of plasma-etching processes, a polynomial neural network (PNN) is applied. This process was characterized by a full factorial experiment, and two attributes modeled are its etch rate and DC bias. According to the number of input variables and type of polynomials to each node, the prediction performance of the PNN was optimized. The various performances of the PNN in diverse environments were compared to three types of statistical regression models and the adaptive network fuzzy inference system (ANFIS). As the demonstrated high-prediction ability in the simulation results shows, the PNN is efficient and much more accurate from the point of view of approximation and prediction abilities.

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Performance Optimization of the Two-Stage Gas Gun Based on Experimental Result (2-단계 기포(氣砲)의 성능 최적화에 관한 연구)

  • 이진호;배기준;전권수;변영환;이재우;허철준
    • Proceedings of the Korean Society of Propulsion Engineers Conference
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    • 2003.10a
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    • pp.145-150
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    • 2003
  • The present study aims to optimize the performance of the Two-Stage Gas Gun by using the experimentally obtained data. RSM(Response Surface Method) was adopted in the optimization process to find the operating parameter than can maximize the projectile speed with the minimum number of tests. To decide the test points which results can consist of the response surface, 3$^{k}$ full factorial method was used, and the design variables were chosen with piston mass and 2$^{nd}$ driver fill pressure. The response surface was composed by nine test results and consequently the optimization was done with GENOCOP III, inherently GA code, in order to seek the optimal test point. The optimal test condition from the response surface was verified by the experiment. Results showed that the optimization process with response surface can successfully predict the test results fairly well. This study shows the possibility of performance optimization for the experimental facilities using numerical optimization algorithm.

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Statistical Factor Analysis of Scanning Electron Microscope (주사전자 현미경의 통계적 인자 해석)

  • Kwon, Sang-Hee;Kim, Byung-Whan
    • Proceedings of the IEEK Conference
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    • 2009.05a
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    • pp.335-337
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    • 2009
  • A scanning electron microscope(SEM) is a system that visualizes complex surface features. The resolution of SEM is affected by each of equipment components. In this study, we examined the effects of the four factors including the beam current, magnification, voltage and working distance. A statistical analysis was conducted to investigate the main and interaction effects. For a systematic characterization, a $2^4$ full factorial experiment was conducted. The $R^2$ of constructed statistical model was 88.9%. The main effect revealed that the current and working distance are dominant factors. Of the interactions, those between the current and voltage yielded the highest interaction. 3D plots generated from the model were used to explore various parameter effects.

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Structural Design for 2kW Class Wind Turbine Blade by using Design of Experiment (실험계획법을 이용한 2kW급 풍력발전용 블레이드에 대한 구조설계)

  • Lee, Seung-Pyo;Kang, Ki-Weon;Chang, Se-Myong;Lee, Jang-Ho
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.20 no.1
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    • pp.28-33
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    • 2011
  • In this paper, structural design for 2kW class composite blade is performed by using design of experiment(DOE). A full factorial design is applied to meet the design specifications at the manufacturing process. The analysis of variance(ANOVA) is made in order to determine the significance of effects in an analysis. Structural analysis by using of commercial software ABAQUS is performed to compute the displacement and safety factor of filament wound composite blade. The results show that the proposed method is suitable to analyze the factors at the design of wind turbine blade.

Performance Optimization of Hypervelocity Launcher System using Experimental Data

  • Huh, Choul-Jun;Lee, Jin-Ho;Bae, Ki-Joon;Jeon, Kwon-Su;Byun, Yung-Hwan;Lee, Jae-Woo;Lee, Chang-Jin
    • Journal of Mechanical Science and Technology
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    • v.18 no.10
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    • pp.1829-1836
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    • 2004
  • This study presents the performance optimization of hypervelocity launcher system by using the experimentall data. During the optimization, the RSM (Response Surface Method) is adopted to find the operating parameters that could maximize the projectile speed. To construct a reliable response surface model, 3 full factorial method is used with the selected design variables, such as piston mass and 2 driver fill pressure. Nine test data could successfully construct the reasonable response surface, which used to yield the optimal operational conditions of the system using the genetic algorithm. The optimization results are confirmed by the experimental test with a good accuracy. Thus, the optimization can improve the performance of the facility.