• Title/Summary/Keyword: Cross-over search

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Optimization Study of a Helicopter Rotor Blade Section Using EDISON Ksec2D and Grid Search Method (EDISON Ksec2D와 Grid Search 법을 이용한 헬리콥터 블레이드 단면의 형상 최적화)

  • Na, Deok-Hwan;Hahm, Jae-Joon;Bae, Jae-Seong
    • Proceeding of EDISON Challenge
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    • 2016.03a
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    • pp.183-189
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    • 2016
  • In this paper, an optimization study on a helicopter rotor blade cross-section was made. Generalization was made to the baseline cross-section to simplify the analysis. To have better performance in aeroelastic response, with the aerodynamic center being the origin of the baseline, the distance between aerodynamic center and shear center, and the distance between mass center and shear center of the blade were minimized. For efficient searching of optimum solutions over the design space, grid search method, which is a method of graphical search was used. Two design variables, radius of balancing weight at leading edge, and offset of the spar from leading edge were selected for the study. Cubic spline interpolation method was used to accommodate searching of the optimum solution. 2-Leveled searching system was devised in accordance with the interpolation method. Optimum solution was found to show 6% decrease in both distance between aerodynamic center and shear center, and mass center and shear center to the baseline.

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A Study on the Searching Behavior of OPAC Users (온라인 열람목록의 이용행태에 관한 연구)

  • Sakong Bok-Hee
    • Journal of the Korean Society for Library and Information Science
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    • v.31 no.3
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    • pp.165-208
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    • 1997
  • The purpose of this study is to evaluate the characteristics of user interface that affect the searching behavior of OPAC users. and then to propose how to design user-friendly interfaces of OPACS. An experiment was conducted on two systems with different interfaces to grasp the effect of user interface to search process and search outcome. A $2\times2$ cross-over design was used for the experiment. Sixty five searchers participated in the experiment. Several statistical techniques such as carry-over effect and system effect of a $2\times2$ cross-over design, $\chi^2$ test, t- test, McNemar test, test of marginal homogeneity through maximum likelihood method, factor analysis, regression analysis, and analysis of variance were applied according to the hypotheses tested and the data analyzed.

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Using a Grounded Theory Approach for Understanding Multichannel Users' Crossover Shopping Behavior (근거이론을 활용한 멀티채널 사용자의 크로스오버 쇼핑행동 이해 )

  • Sang-Cheol Park;Woong-Kyu Lee
    • Information Systems Review
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    • v.19 no.3
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    • pp.179-199
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    • 2017
  • As users' cross-over shopping behaviors become more popular, many studies have attempted to describe a theoretical mechanism in multichannel environments. Apart from explaining a simplified multichannel user behavior, relevant researchers must deeply understand the mechanism of users' cross-over shopping behavior, which cannot be discovered by employing either existing theories or traditional research methods. Thus, this study explores why, how, and when users conduct cross-over shopping behaviors in multichannel environments by employing a grounded theory approach. In this study, we have interviewed 25 participants who have prior experiences in cross-over shopping. By analyzing the interview manuscripts using the grounded theory approach, we have extracted 118 codes in the coding steps and ultimately presented 28 categories by incorporating similar concepts from those codes. In this qualitative grounded theory study, we have discussed why, how, and when users do cross-over shopping behavior based on our selected codes and categories as well as by listening to the stories of our interviewees. By grounding our proposed framework, which can capture both dynamic information search and purchasing behavior, this study provides an alternative research approach to explain user behavior, thereby bolstering our current understanding of the cross-over shopping behavior of users in multichannel environments.

Distributed Anchor Cross Over Switch Search Algorithm for Wireless ATM Handoff (무선 ATM 의 핸드오프에서 Distributed Anchor Cross Over Switch 탐색 알고리즘 제안)

  • 이형원;이홍기;송주석
    • Proceedings of the Korean Information Science Society Conference
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    • 1998.10a
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    • pp.252-254
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    • 1998
  • 유선에서 이용하는 능력으로 무선으로도멀티미디어 서비스를 이용하고자 연구된덧이 무선 ATM이다. 무선 ATM에서 핸드오프는 망 레벨과 무선 A레벨의 무선 핸드오프로 구분할 수 있다. 망 레벨의 핸드오프에서 CX의 선택은 빠르고 매끄러운 핸드오프를 지원해 주는데 중요한 역할을 한다. 망 관리에는 하나의 연결서버가 망의 연결관리를 해주는 중앙 집중 연결관리(Centralized Connection Management Scheme)와 각노드에서 연결을 관리하는 분산된 연결관리(Distributed Connection Management Scheme)로 나뉜다. 여기서 문제점은 중앙집중 연결관리에서는 전달지연시간(Propagation delay), 분산된, 연결관리에서는 시스템 오버헤드가 발생한다는 것이다. 이러한 중앙집중 연결관리의 지연시간과 분산된 연결관리의 오버헤드를 감소시키기 Distributed 위해 탐색알고리즘을 제안한다.

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Efficient Integer pel and Fractional pel Motion Estimation on H.264/AVC (H.264/AVC에서 효율적인 정화소.부화소 움직임 추정)

  • Yoon, Hyo-Sun;Kim, Hye-Suk;Jung, Mi-Gyoung;Kim, Mi-Young;Cho, Young-Joo;Kim, Gi-Hong;Lee, Guee-Sang
    • The KIPS Transactions:PartB
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    • v.16B no.2
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    • pp.123-130
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    • 2009
  • Motion estimation (ME) plays an important role in digital video compression. But it limits the performance of image quality and encoding speed and is computational demanding part of the encoder. To reduce computational time and maintain the image quality, integer pel and fractional pel ME methods are proposed in this paper. The proposed method for integer pel ME uses a hierarchical search strategy. This strategy method consists of symmetrical cross-X pattern, multi square grid pattern, diamond patterns. These search patterns places search points symmetrically and evenly that can cover the overall search area not to fall into the local minimum and to reduce the computational time. The proposed method for fractional pel uses full search pattern, center biased fractional pel search pattern and the proposed search pattern. According to block sizes, the proposed method for fractional pel decides the search pattern adaptively. Experiment results show that the speedup improvement of the proposed method over Unsymmetrical cross Multi Hexagon grid Search (UMHexagonS) and Full Search (FS) can be up to around $1.2{\sim}5.2$ times faster. Compared to image quality of FS, the proposed method shows an average PSNR drop of 0.01 dB while showing an average PSNR gain of 0.02 dB in comparison to that of UMHexagonS.

The Optimization of Sizing and Topology Design for Drilling Machine by Genetic Algorithms (유전자 알고리즘에 의한 드릴싱 머신의 설계 최적화 연구)

  • Baek, Woon-Tae;Seong, Hwal-Gyeong
    • Journal of the Korean Society for Precision Engineering
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    • v.14 no.12
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    • pp.24-29
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    • 1997
  • Recently, Genetic Algorithm(GA), which is a stochastic direct search strategy that mimics the process of genetic evolution, is widely adapted into a search procedure for structural optimization. Contrast to traditional optimal design techniques which use design sensitivity analysis results, GA is very simple in their algorithms and there is no need of continuity of functions(or functionals) any more in GA. So, they can be easily applicable to wide area of design optimization problems. Also, owing to multi-point search procedure, they have higher porbability of convergence to global optimum compared to traditional techniques which take one-point search method. The methods consist of three genetics opera- tions named selection, crossover and mutation. In this study, a method of finding the omtimum size and topology of drilling machine is proposed by using the GA, For rapid converge to optimum, elitist survival model,roulette wheel selection with limited candidates, and multi-point shuffle cross-over method are adapted. And pseudo object function, which is the combined form of object function and penalty function, is used to include constraints into fitness function. GA shows good results of weight reducing effect and convergency in optimal design of drilling machine.

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Multi-objective optimal design of laminate composite shells and stiffened shells

  • Lakshmi, K.;Rama Mohan Rao, A.
    • Structural Engineering and Mechanics
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    • v.43 no.6
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    • pp.771-794
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    • 2012
  • This paper presents a multi-objective evolutionary algorithm for combinatorial optimisation and applied for design optimisation of fiber reinforced composite structures. The proposed algorithm closely follows the implementation of Pareto Archive Evolutionary strategy (PAES) proposed in the literature. The modifications suggested include a customized neighbourhood search algorithm in place of mutation operator to improve intensification mechanism and a cross over operator to improve diversification mechanism. Further, an external archive is maintained to collect the historical Pareto optimal solutions. The design constraints are handled in this paper by treating them as additional objectives. Numerical studies have been carried out by solving a hybrid fiber reinforced laminate composite cylindrical shell, stiffened composite cylindrical shell and pressure vessel with varied number of design objectives. The studies presented in this paper clearly indicate that well spread Pareto optimal solutions can be obtained employing the proposed algorithm.

A Study on the STN International (STN International 온라인 정보검색(情報檢索) 시스템)

  • Jeong, Hye-Soon
    • Journal of Information Management
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    • v.23 no.3
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    • pp.45-73
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    • 1992
  • STN International is operated in North America by CAS, a division of the American Chemical Society;by FIZ Karlsruhe in Eruope ; and by JICST in Japan. All three are not-for-profit scientific organizations. This paper describes Messenger software that is designed for fast and efficient information retrieval, the advanced front-end STN Express software that saves time and effort, and databases in STN.

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Effective Harmony Search-Based Optimization of Cost-Sensitive Boosting for Improving the Performance of Cross-Project Defect Prediction (교차 프로젝트 결함 예측 성능 향상을 위한 효과적인 하모니 검색 기반 비용 민감 부스팅 최적화)

  • Ryu, Duksan;Baik, Jongmoon
    • KIPS Transactions on Software and Data Engineering
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    • v.7 no.3
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    • pp.77-90
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    • 2018
  • Software Defect Prediction (SDP) is a field of study that identifies defective modules. With insufficient local data, a company can exploit Cross-Project Defect Prediction (CPDP), a way to build a classifier using dataset collected from other companies. Most machine learning algorithms for SDP have used more than one parameter that significantly affects prediction performance depending on different values. The objective of this study is to propose a parameter selection technique to enhance the performance of CPDP. Using a Harmony Search algorithm (HS), our approach tunes parameters of cost-sensitive boosting, a method to tackle class imbalance causing the difficulty of prediction. According to distributional characteristics, parameter ranges and constraint rules between parameters are defined and applied to HS. The proposed approach is compared with three CPDP methods and a Within-Project Defect Prediction (WPDP) method over fifteen target projects. The experimental results indicate that the proposed model outperforms the other CPDP methods in the context of class imbalance. Unlike the previous researches showing high probability of false alarm or low probability of detection, our approach provides acceptable high PD and low PF while providing high overall performance. It also provides similar performance compared with WPDP.

A study on the optimal sizing and topology design for Truss/Beam structures using a genetic algorithm (유전자 알고리듬을 이용한 트러스/보 구조물의 기하학적 치수 및 토폴로지 최적설계에 관한 연구)

  • 박종권;성활경
    • Journal of the Korean Society for Precision Engineering
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    • v.14 no.3
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    • pp.89-97
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    • 1997
  • A genetic algorithm (GA) is a stochastic direct search strategy that mimics the process of genetic evolution. The GA applied herein works on a population of structural designs at any one time, and uses a structured information exchange based on the principles of natural selection and wurvival of the fittest to recombine the most desirable features of the designs over a sequence of generations until the process converges to a "maximum fitness" design. Principles of genetics are adapted into a search procedure for structural optimization. The methods consist of three genetics operations mainly named selection, cross- over and mutation. In this study, a method of finding the optimum topology of truss/beam structure is pro- posed by using the GA. In order to use GA in the optimum topology problem, chromosomes to FEM elements are assigned, and a penalty function is used to include constraints into fitness function. The results show that the GA has the potential to be an effective tool for the optimal design of structures accounting for sizing, geometrical and topological variables.variables.

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