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Study on establish for unit of measure for Quality Feature (다구찌의 품질특성 측정에 대한 고찰과 사례 연구)

  • Park, No-Guk;Lee, Sang-Bok
    • Proceedings of the Safety Management and Science Conference
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    • 2013.04a
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    • pp.163-172
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    • 2013
  • In this Paper, We study on establish for unit of measure. Quality means abstract for customer needs. we surveyed unit of measurement of quality feature of Juran, Taguchi, 6 sigma method. We suggest unit of measurement of quality feature. Each enterprise can use defining own unit of measurement of quality feature. Effect is expected in enterprise that these proposals do quality control. There is meaning in direction that measuring mean of quality feature that propose in this treatise understands actuality to be deeply and reconcile exact point of theory.

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Study on establish for unit of measure for Quality Feature (품질 특성의 측정에 대한 분석 사례 연구)

  • Lee, Hui-Chun;Park, No-Guk;Lee, Sang-Bok
    • Proceedings of the Safety Management and Science Conference
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    • 2011.11a
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    • pp.157-165
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    • 2011
  • In this Paper, We study on establish for unit of measure. Quality means abstract for customer needs. we surveyed unit of measurement of quality feature of Juran, Taguchi, 6 sigma method. We suggest unit of measurement of quality feature. Each enterprise can use defining own unit of measurement of quality feature. Effect is expected in enterprise that these proposals do quality control. There is meaning in direction that measuring mean of quality feature that propose in this treatise understands actuality to be deeply and reconcile exact point of theory.

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Generative Process Planning through Feature Recognition (특징형상 인식을 통한 창성적 자동 공정계획 수립 - 복합특징형상 분류를 중심을 -)

  • 이현찬;이재현
    • Korean Journal of Computational Design and Engineering
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    • v.3 no.4
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    • pp.274-282
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    • 1998
  • A feature is a local shape of a product directly related to the manufacturing process. The feature plays a role of the bridge connecting CAD and CAM. In the process planning for he CAM, information on manufacturing is required. To get the a manufacturing information from CAD dat, we need to recognize features. Once features are recognized, they are used as an input for the process planning. In this paper, we thoroughly investigate the composite features, which are generated by interacting simple features. The simple features in the composite feature usually have precedence relation in terms of process sequence. Based on the reason for the precedence relation, we classify the composite features for the process planning. In addition to the precedence relation, approach direction is used as an input for the process planning. In the process planning, the number of set-up orientations are minimized whole process sequence for the features are generated. We propose a process planning algorithm based on the topological sort and breadth-first search of graphs. The algorithn is verified using sample products.

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Crease detection method using fingerprint image decomposition and composition (지문 영상의 분해 및 합성에 의한 주름선 검출방법)

  • Hwang, Woon-Joo;Park, Sung-Wook;Park, Jong-Kwan;Park, Jong-Wook
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.44 no.3
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    • pp.90-97
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    • 2007
  • For a highly reliable fingerprint recognition system, the precise and accurate feature extraction is indispensable. In this paper, We propose a highly efficient crease extraction method, which can improve the accuracy of feature extraction within the fingerprint image. The proposed method applies the 1-dimensional directional slit for each pixel in fingerprint image. And then it calculates the average grey level and variance to determine whether the current pixel composes the crease, and estimates the direction of crease. Once the direction of every pixel in crease candidate area is estimated, it is decomposed into 8 different images depending on their direction. From the 8 directional images, the crease clusters are estimated by utilizing the property of crease area. The proposed method finally extracts the crease from the crease clusters estimated from directional images. In conclusion, the proposed method highly improved the accuracy of overall feature extraction by accurate and precise extraction of the crease from fingerprint image.

Part Similarity Assessment Method Based on Hierarchical Feature Decomposition: Part 2 - Using Negative Feature Decomposition (계층적 특징형상 정보에 기반한 부품 유사성 평가 방법: Part 2 - 절삭가공 특징형상 분할방식 이용)

  • 김용세;강병구;정용희
    • Korean Journal of Computational Design and Engineering
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    • v.9 no.1
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    • pp.51-61
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    • 2004
  • Mechanical parts are often grouped into part families based on the similarity of their shapes, to support efficient manufacturing process planning and design modification. The 2-part sequence papers present similarity assessment techniques to support part family classification for machined parts. These exploit the multiple feature decompositions obtained by the feature recognition method using convex decomposition. Convex decomposition provides a hierarchical volumetric representation of a part, organized in an outside-in hierarchy. It provides local accessibility directions, which supports abstract and qualitative similarity assessment. It is converted to a Form Feature Decomposition (FFD), which represents a part using form features intrinsic to the shape of the part. This supports abstract and qualitative similarity assessment using positive feature volumes.. FFD is converted to Negative Feature Decomposition (NFD), which represents a part as a base component and negative machining features. This supports a detailed, quantitative similarity assessment technique that measures the similarity between machined parts and associated machining processes implied by two parts' NFDs. Features of the NFD are organized into branch groups to capture the NFD hierarchy and feature interrelations. Branch groups of two parts' NFDs are matched to obtain pairs, and then features within each pair of branch groups are compared, exploiting feature type, size, machining direction, and other information relevant to machining processes. This paper, the second one of the two companion papers, describes the similarity assessment method using NFD.

Part Similarity Assessment Method Based on Hierarchical Feature Decomposition: Part 1 - Using Convex Decomposition and Form Feature Decomposition (계층적 특징형상 정보에 기반한 부품 유사성 평가 방법: Part 1 - 볼록입체 분할방식 및 특징형상 분할방식 이용)

  • 김용세;강병구;정용희
    • Korean Journal of Computational Design and Engineering
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    • v.9 no.1
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    • pp.44-50
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    • 2004
  • Mechanical parts are often grouped into part families based on the similarity of their shapes, to support efficient manufacturing process planning and design modification. The 2-part sequence papers present similarity assessment techniques to support part family classification for machined parts. These exploit the multiple feature decompositions obtained by the feature recognition method using convex decomposition. Convex decomposition provides a hierarchical volumetric representation of a part, organized in an outside-in hierarchy. It provides local accessibility directions, which supports abstract and qualitative similarity assessment. It is converted to a Form Feature Decomposition (FFD), which represents a part using form features intrinsic to the shape of the part. This supports abstract and qualitative similarity assessment using positive feature volumes. FFD is converted to Negative Feature Decomposition (NFD), which represents a part as a base component and negative machining features. This supports a detailed, quantitative similarity assessment technique that measures the similarity between machined parts and associated machining processes implied by two parts' NFDs. Features of the NFD are organized into branch groups to capture the NFD hierarchy and feature interrelations. Branch groups of two parts' NFDs are matched to obtain pairs, and then features within each pair of branch groups are compared, exploiting feature type, size, machining direction, and other information relevant to machining processes. This paper, the first one of the two companion papers, describes the similarity assessment methods using convex decomposition and FFD.

A Feature of Stellar Density Distribution within Tidal Radius of Globular Cluster NGC 6626 in the Bulge Direction

  • Chun, Sang-Hyun;Lim, Dong-Wook;Kim, Myo-Jin;Sohn, Young-Jong
    • The Bulletin of The Korean Astronomical Society
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    • v.35 no.2
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    • pp.82.1-82.1
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    • 2010
  • We have investigated the spatial configuration of stars within the tidal radius of metal poor globular cluster NGC 6626 in the bulge direction. Data were obtained in near-IR J,H,Ks bands with wide-field ($20'\times20'$) detector, WIRCam at CFHT. To trace the stellar density around target cluster, we sorted cluster's member stars by using a mask filtering algorithm and weighting the stars on the color-magnitude diagram. From the weighted surface density map, we found that the stellar spatial distributions within the tidal radius appear asymmetric and distorted features. Especially, we found that more prominent over-density features are extending toward the direction of Galactic plane rather than toward the directions of the Galactic center and its orbital motion. This orientation of the stellar density distribution can be interpreted with result of disk-shock effect of the Galaxy that the cluster had been experienced. Indeed, this over-density feature are well represented in the radial surface density profile for different angular sections. As one of the metal poor globular clusters with extended horizontal branch (EHB) in the bulge direction, NGC 6626 is kinematically decoupled from the normal clusters and known to have disk motion of peculiar motion. Thus, our result will be able to add further constraints to understand the origin of this cluster and the formation of bulge region in early universe.

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Analysis of Face Direction and Hand Gestures for Recognition of Human Motion (인간의 행동 인식을 위한 얼굴 방향과 손 동작 해석)

  • Kim, Seong-Eun;Jo, Gang-Hyeon;Jeon, Hui-Seong;Choe, Won-Ho;Park, Gyeong-Seop
    • Journal of Institute of Control, Robotics and Systems
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    • v.7 no.4
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    • pp.309-318
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    • 2001
  • In this paper, we describe methods that analyze a human gesture. A human interface(HI) system for analyzing gesture extracts the head and hand regions after taking image sequence of and operators continuous behavior using CCD cameras. As gestures are accomplished with operators head and hands motion, we extract the head and hand regions to analyze gestures and calculate geometrical information of extracted skin regions. The analysis of head motion is possible by obtaining the face direction. We assume that head is ellipsoid with 3D coordinates to locate the face features likes eyes, nose and mouth on its surface. If was know the center of feature points, the angle of the center in the ellipsoid is the direction of the face. The hand region obtained from preprocessing is able to include hands as well as arms. For extracting only the hand region from preprocessing, we should find the wrist line to divide the hand and arm regions. After distinguishing the hand region by the wrist line, we model the hand region as an ellipse for the analysis of hand data. Also, the finger part is represented as a long and narrow shape. We extract hand information such as size, position, and shape.

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A New Image Enhancement Algorithm Based on Bidirectional Diffusion

  • Wang, Zhonghua;Huang, Xiaoming;Huang, Faliang
    • Journal of Information Processing Systems
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    • v.16 no.1
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    • pp.49-60
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    • 2020
  • To solve the edge ringing or block effect caused by the partial differential diffusion in image enhancement domain, a new image enhancement algorithm based on bidirectional diffusion, which smooths the flat region or isolated noise region and sharpens the edge region in different types of defect images on aviation composites, is presented. Taking the image pixel's neighborhood intensity and spatial characteristics as the attribute descriptor, the presented bidirectional diffusion model adaptively chooses different diffusion criteria in different defect image regions, which are elaborated are as follows. The forward diffusion is adopted to denoise along the pixel's gradient direction and edge direction in the pixel's smoothing area while the backward diffusion is used to sharpen along the pixel's gradient direction and the forward diffusion is used to smooth along the pixel's edge direction in the pixel's edge region. The comparison experiments were implemented in the delamination, inclusion, channel, shrinkage, blowhole and crack defect images, and the comparison results indicate that our algorithm not only preserves the image feature better but also improves the image contrast more obviously.