• 제목/요약/키워드: Input information

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품질기능전개에서 입력정보의 불확실성에 대한 고찰 (Consideration of Uncertainty in input information of QFD)

  • 김덕환;김광재;민대기
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
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    • pp.566-573
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    • 2005
  • Quality function deployment (QFD) is a useful tool for ensuring quality throughout each stage of the product development and production process. Since the focus of QFD is placed on the early stage, the uncertainty in the input information of QFD is inevitable. If the uncertainty is neglected, the QFD analysis results are likely to be misleading. This paper classifies the sources of uncertainty in QFD, and proposes a new approach to model and analyze the effects of uncertainty in QFD.

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Convergence Control of Moving Object using Opto-Digital Algorithm in the 3D Robot Vision System

  • Ko, Jung-Hwan;Kim, Eun-Soo
    • Journal of Information Display
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    • 제3권2호
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    • pp.19-25
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    • 2002
  • In this paper, a new target extraction algorithm is proposed, in which the coordinates of target are obtained adaptively by using the difference image information and the optical BPEJTC(binary phase extraction joint transform correlator) with which the target object can be segmented from the input image and background noises are removed in the stereo vision system. First, the proposed algorithm extracts the target object by removing the background noises through the difference image information of the sequential left images and then controlls the pan/tilt and convergence angle of the stereo camera by using the coordinates of the target position obtained from the optical BPEJTC between the extracted target image and the input image. From some experimental results, it is found that the proposed algorithm can extract the target object from the input image with background noises and then, effectively track the target object in real time. Finally, a possibility of implementation of the adaptive stereo object tracking system by using the proposed algorithm is also suggested.

자기조직화 교사 학습에 의한 패턴인식에 관한 연구 (A Study on Pattern Recognition with Self-Organized Supervised Learning)

  • 박찬호
    • 정보학연구
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    • 제5권2호
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    • pp.17-26
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    • 2002
  • 본 연구에서는 자기조직화 교사학습 신경망인 SOSL(Self-Organized Superised Learning)과 이 신경망의 구조를 제안한다. SOSL신경망은 하이브리드 형태의 신경망으로써 다수 개의 컴포넌트 에러 역전파 신경망들과 수정된 PCA신경망으로 구성된다. CBP신경망은 군집화되고 복잡한 입력패턴에 대하여 교사학습을 병렬적으로 수행한다. 수정된 PCA신경망은 군집화 및 지역투영에 의하여 원 입력패턴을 보다 작은 차원으로 변환시키기 위하여 사용된다. 제안된 SOSL은 많은 입력패턴을 가짐으로써 큰 네트워크 크기를 가지게 되는 신경망에 효과적으로 적용이 가능하다.

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우리나라의 권역별 농산업 클러스터 분석: 6개 권역간 산업연관모형희 적용 (An Analysis of Korean Regional Agricultural and Agri-Manufacturing Clusters Using Multi-Regional Input-Output Model)

  • 윤민경;최명섭;김의준
    • 농촌계획
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    • 제16권1호
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    • pp.9-20
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    • 2010
  • The aim of this paper is to identify Korean agricultural and agri-manufacturing cluster using a multi-regional input-output model. This paper derives a representative set of five agricultural and agri-manufacturing clusters in Korea in terms of spatial and industrial interdependency. The results show that agriculture and agri-manufacturing clusters agglomerated in Seoul Metropolitan Area and Chungcheong Area are linked both production and manufacture functions, whereas Gangwon Area is more focused on production and Jeolla Area is more concentrated on manufacture.

랜덤 패턴 인증 방식의 개발을 위한 우도 기반 방향입력 최적화 (Likelihood-based Directional Optimization for Development of Random Pattern Authentication System)

  • 최연재;이현규;이상철
    • 한국멀티미디어학회논문지
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    • 제18권1호
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    • pp.71-80
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    • 2015
  • Many researches have been studied to overcome the weak points in authentication schemes of mobile devices such as pattern-authentication that is vulnerable for smudge-attack. Since random-pattern-lock authenticates users by drawing figure of predefined-shape, it can be a method for robust security. However, the authentication performance of random-pattern-lock is influenced by input noise and individual characteristics sign pattern. We introduce an optimization method of user input direction to increase the authentication accuracy of random-pattern-lock. The method uses the likelihood of each direction given an data which is angles of line drawing by user. We adjusted recognition range for each direction and achieved the authentication rate of 95.60%.

분류나무를 활용한 군집분석의 입력특성 선택: 신용카드 고객세분화 사례 (Classification Tree-Based Feature-Selective Clustering Analysis: Case of Credit Card Customer Segmentation)

  • 윤한성
    • 디지털산업정보학회논문지
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    • 제19권4호
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    • pp.1-11
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    • 2023
  • Clustering analysis is used in various fields including customer segmentation and clustering methods such as k-means are actively applied in the credit card customer segmentation. In this paper, we summarized the input features selection method of k-means clustering for the case of the credit card customer segmentation problem, and evaluated its feasibility through the analysis results. By using the label values of k-means clustering results as target features of a decision tree classification, we composed a method for prioritizing input features using the information gain of the branch. It is not easy to determine effectiveness with the clustering effectiveness index, but in the case of the CH index, cluster effectiveness is improved evidently in the method presented in this paper compared to the case of randomly determining priorities. The suggested method can be used for effectiveness of actively used clustering analysis including k-means method.

직접학습제어를 이용한 가상 기준입력 생성 (Virtual Reference Input Generation Using Direct Learning Control)

  • 안현식;정구민
    • 전기학회논문지
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    • 제56권3호
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    • pp.611-614
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    • 2007
  • In this paper, a Direct Learning Control (DLC) method is presented to generate a virtual reference input for linear feedback systems to improve the output tracking performance. The original reference input is effectively modified by the DLC without any iterative learning process. The presented DLC is designed based on the information on the relative degree of a system and previously generated virtual reference inputs. It is illustrated by simulations that the virtual reference input generated by the proposed DLC can achieve high tracking performance, although the reference input cannot be appropriately shaped by using existing DLC methods.

Coded Single Input Channel for Color Pattern Recognition in Joint Transform Correlator

  • Jeong, Man-Ho
    • Journal of the Optical Society of Korea
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    • 제15권4호
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    • pp.335-339
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    • 2011
  • Recently, we reported a single input channel joint transform correlator for the color pattern recognition which decomposes the input color image into three R, G, and B gray components and adds those components into a single gray image in the input plane. This technique has the merit of a single input channel instead of three input channels. However, we found this technique has some problems with discrimination impossibility in the case of a simple primary color pattern which results in the same gray level through the addition process. Thus, we propose a modified coding technique which selectively recombines the decomposed three R, G, and B gray components instead of the simple adding process. Simulated results show that the modified coding technique can accurately discriminate a variety of kinds of color images.

불완전 디버깅 환경에서 Input Domain에 기초한 소프트웨어 신뢰성 성장 모델 (An Input Domain-Based Software Reliability Growth Model In Imperfect Debugging Environment)

  • Park, Joong-Yang;Kim, Young-Soon;Hwang, Yang-Sook
    • 정보처리학회논문지D
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    • 제9D권4호
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    • pp.659-666
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    • 2002
  • Park, Seo and Kim은 소프트웨어의 시험단계와 유지보수단계에 모두 적용할 수 있는 입력 영역 기반 소프트웨어 신뢰성 성장 모델을 개발하였다. 이들의 모형은 완전디버깅의 가정 하에서 개발되어졌다. 입력 영역 기반 소프트웨어 신뢰성 성장 모델이 현실적이기 위해서는 이러한 가정은 개선되어야 한다. 본 논문에서는 불완전 디버깅 하에서 사용할 수 있는 입력 영역 기반 소프트웨어 신뢰성 성장 모델을 제안하고 그 통계적 특성을 조사한다.

육각형 입력제약 공간을 이용한 무정전 전원장치의 모델예측제어 (Model Predictive Control of Three-Phase Inverter for Uninterruptible Power Supply Applications under a Hexagonal Input Constraint Region)

  • 김석균;김정수;이영일
    • 제어로봇시스템학회논문지
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    • 제20권2호
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    • pp.163-169
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    • 2014
  • Using the classical cascade voltage control strategy, this paper proposes an analytical solution to an MPC (Model Predictive Control) problem with a hexagonal input constraint set for the inner-loop to regulate the output voltage of the UPS (Uninterruptible Power Supply). Focus is placed on how to deal with the hexagonal input constraint set without any approximation. Following the conventional cascade voltage control strategy, the PI (Proportional-Integral) controller is used in the outer-loop in order to regulate the output voltage. The simulation results illustrate that the capacitor voltage rapidly goes to its reference in a satisfactory manner while keeping other state variables bounded under an unexpected load changes.