• Title/Summary/Keyword: 특징행렬

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The Study on the Deadlock Avoidance using the DAPN and the Adjacency Matrix (DAPN과 인접행렬을 이용한 교착상태 회피에 대한 연구)

  • Song, Yu-Jin;Lee, Jong-Kun
    • Journal of the Korea Society for Simulation
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    • v.15 no.1
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    • pp.1-10
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    • 2006
  • The Flexible Management System (FMS) consists of parallel and concurrent machines, pieces of equipment, and carrying systems classified as buffers, tools, and routers, respectively. The concurrent flow of multiple productions in a system is competed with one another for resources and this resulting competition can cause a deadlock in FMS. Since a deadlock is a condition in which the excessive demand for the resources being used by others causes activities to stop, it is very important to detect and prevent a deadlock. Herein a new algorithm has been studied in order to detect and prevent deadlocks, after defining a relationship between the general places and resource share places in Petri nets like as DAPN: Deadlock Avoidance Petri Net. For presenting the results, the suggested algorithms were also adapted to the models that demonstrated FMS features.

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Measure of similarity by toll theory and matching using fuzzy relation matrix - focused on 3-dimensional images (톨이론에 의한 유사도 계산과 퍼지 관계 행렬을 이용한 정합과정의 수행 - 3차원 영상을 중심으로)

  • 조동욱;한길성;조용환
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.22 no.8
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    • pp.1698-1706
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    • 1997
  • In this paper, we envisioned a multimedia object recognition system processing and combinig information from all available sources, such as 2-D, 3-D, color and sound data. Out of the overall system, we proposed 3-D information extraction and object recognition methods. Firstly, surfaces are classified by z-gradient from the range data, surface features are extracted using the intersection of normal vectors. Also feature relationship such as intersection angle and distance is established between the surfaces. Secondly, recognition is accomplished by matching process which is improtant step in the image understanding systems. Matching process is very improtant procedures because of more general and more efficient method is needed in the field of multimedia sytem. Therefore, we focused the proposal of matching process and in this article, first of all, we deal with the matching process of the 3-D object. Similarity measures are calculated.

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Real-Time Textile Dimension Inspection System Using Zone-Crossing Method, Distortion Angle Classifier and Gray-Level Co-occurrence Matrix Features (영역교차법, 왜곡각 분류자 및 명암도 상관행렬 특징자를 이용한 실시간 섬유 성량 검사 시스템)

  • 이응주;이철희
    • Journal of Korea Multimedia Society
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    • v.3 no.2
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    • pp.112-120
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    • 2000
  • In this paper, we implement a real-time textile dimension inspection system. It can detect various types of real defects which determine the quality of fabric product, defect positions of textile, classify the distortion angel of moving textile and the density. In the implemented system, we measure the density of textile using zone-crossing method with optical lens to solve the noise and real-time problems. And we compensate distortion angel of textile with the classification of distortion types using gaussian gradient and mean gradient features. And also, it detecs real defects of textile and its positions using gray level co-occurrence matrix features. The implemented texile demension inspection systemcan inspect textile dimensions such as density, distortion angle, defect of textile and defect position at real-time. In the implemented proposed texitile dimension inspection system, It is possible to calculate density and detect default of textile at real-time dimension inspection system, it is possible to calculate density and detect default of textile at textile states throughout at all the significant working process such as dyeing, manufacturing, and other texitle processing.

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Machine-printed Numeral Recognition using Weighted Template Matching (가중 원형 정합을 이용한 인쇄체 숫자 인식)

  • Jung, Min-Chul
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.10 no.3
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    • pp.554-559
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    • 2009
  • This paper proposes a new method of weighted template matching fur machine-printed numeral recognition. The proposed weighted template matching, which emphasizes the feature of a pattern using adaptive Hamming distance on local feature areas, improves the recognition rate while template matching processes an input image as one global feature. The experiment compares confusion matrices of the template matching, error back propagation neural network classifier, and the proposed weighted template matching respectively. The result shows that the proposed method improves fairly the recognition rate of the machine-printed numerals.

Derivation of a Confidence Matrix for Orientation Components in the ICP Algorithm (ICP 알고리즘의 회전 성분 신뢰도 행렬 유도)

  • Lee, Byung-Uk;Kim, Chul-Min;Park, Rae-Hong
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.12
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    • pp.69-76
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    • 1998
  • This paper proposes a matrix which represents the confidence in the rotation components of the Iterative Closest Point (ICP) algorithm is image registratiion, The reliability of the ICP algorithm depends on the shape of the object. For example, an object with more complex features shows higher reliablility than the one with rotation symmetry such as a cylinder. We show that the reliablity of the ICP algorithm can be estimated when the input range data has additive noise. Finally, we demonstrate that the proposed reliability formula is in good agreement with the computer simulation.

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Document Clustering using Clustering and Wikipedi (군집과 위키피디아를 이용한 문서군집)

  • Park, Sun;Lee, Seong Ho;Park, Hee Man;Kim, Won Ju;Kim, Dong Jin;Chandra, Abel;Lee, Seong Ro
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2012.10a
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    • pp.392-393
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    • 2012
  • This paper proposes a new document clustering method using clustering and Wikipedia. The proposed method can well represent the concept of cluster topics by means of NMF. It can solve the problem of "bags of words" to be not considered the meaningful relationships between documents and clusters, which expands the important terms of cluster by using of the synonyms of Wikipedia. The experimental results demonstrate that the proposed method achieves better performance than other document clustering methods.

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Fuzzy Cognitive Map-Based A, pp.oach to Causal Knowledge Base Construction and Bi-Directional Inference Method -A, pp.ications to Stock Market Analysis- (퍼지인식도에 기초한 인과관계 지식베이스 구축과 양방향 추론방식에 관한 연구 -주식시장 분석에의 적용을 중심으로-)

  • 이건창;주석진;김현수
    • Journal of Intelligence and Information Systems
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    • v.1 no.1
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    • pp.1-22
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    • 1995
  • 본 연구에서 퍼지인식도(Fuzzy Cognitive Map) 개념을 기초로 하여 (1) 특정 문제영역에 대한 전문가의 인과관계 지식(causal knowledge)을 추출하는 알고리즘을 제시하고, (2) 이 알고리즘에 기초하여 작성된 해당 문제영역에 대한 여러 전문가들의 인과관계 지식을 계층별로 분해하여, (3) 해당 계층간의 양방향 추론이 가능한 추론메카니즘을 제시하고자 한다. 특정 문제영역에 있어서의 인과관계 지식이란 해당 문제를 구성하는 여러 개념간에 존재하는 인과관계를 표현한 지식을 의미한다. 이러한 인과관계 지식은 기존의 IF-THEN 형태의 규칙과는 달리 행렬형태로 표현되기 때문에 수학적인 연산이 가능하다. 특정 문제영역에 대한 전문가의 인과관계 지식을 추출하는 알고리즘은 집합연산에 의거하여 개발되었으며, 특히 상반된 의견을 보이는 전문가들의 의견을 통합하여 하나의 통합된 인과관계 지식베이스를 구축하는데 유용하다. 그러나, 주어진 문제가 복잡하여 다양한 개념들이 수반되면, 자연히 인과관계 지식베이스의 규모도 커지게 되므로 이를 다루는데 비효율성이 개재되기 마련이다. 따라서 이러한 비효율성을 해소하기 위하여 주어진 문제를 여러계측(Hierarchy)으로 분해하여, 해당 계층별로 인과관계 지식베이스를 구축하고 각 계층별 인과관계 지식베이스를 연결하여 추론하는 메카니즘을 개발하면 효과적인 추론이 가능하다. 이러한 계층별 분해는 행렬의 분해와 같은 개념으로도 이해될 수 있다는 특징이 있어 그 연산이 간단명료하다는 장점이 있다. 이와같이 분해된 인과관계 지식베이스는 계층간의 추론메카니즘을 통하여 서로 연결된다. 이를 위하여 본 연구에서는 상향 또는 하향방식이 추론이 가능한 양방향 추론방식을 제시하여 주식시장에서의 투자분석 문제에 적용하여 그 효율성을 검증하였다.

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Comparison of deep learning-based autoencoders for recommender systems (오토인코더를 이용한 딥러닝 기반 추천시스템 모형의 비교 연구)

  • Lee, Hyo Jin;Jung, Yoonsuh
    • The Korean Journal of Applied Statistics
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    • v.34 no.3
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    • pp.329-345
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    • 2021
  • Recommender systems use data from customers to suggest personalized products. The recommender systems can be categorized into three cases; collaborative filtering, contents-based filtering, and hybrid recommender system that combines the first two filtering methods. In this work, we introduce and compare deep learning-based recommender system using autoencoder. Autoencoder is an unsupervised deep learning that can effective solve the problem of sparsity in the data matrix. Five versions of autoencoder-based deep learning models are compared via three real data sets. The first three methods are collaborative filtering and the others are hybrid methods. The data sets are composed of customers' ratings having integer values from one to five. The three data sets are sparse data matrix with many zeroes due to non-responses.

Realtime Facial Expression Control of 3D Avatar by PCA Projection of Motion Data (모션 데이터의 PCA투영에 의한 3차원 아바타의 실시간 표정 제어)

  • Kim Sung-Ho
    • Journal of Korea Multimedia Society
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    • v.7 no.10
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    • pp.1478-1484
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    • 2004
  • This paper presents a method that controls facial expression in realtime of 3D avatar by having the user select a sequence of facial expressions in the space of facial expressions. The space of expression is created from about 2400 frames of facial expressions. To represent the state of each expression, we use the distance matrix that represents the distances between pairs of feature points on the face. The set of distance matrices is used as the space of expressions. Facial expression of 3D avatar is controled in real time as the user navigates the space. To help this process, we visualized the space of expressions in 2D space by using the Principal Component Analysis(PCA) projection. To see how effective this system is, we had users control facial expressions of 3D avatar by using the system. This paper evaluates the results.

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Color Laser Printer Forensics through Wiener Filter and Gray Level Co-occurrence Matrix (위너 필터와 명암도 동시발생 행렬을 통한 컬러 레이저프린터 포렌식 기술)

  • Lee, Hae-Yeoun;Baek, Ji-Yeoun;Kong, Seung-Gyu;Lee, Heung-Su;Choi, Jung-Ho
    • Journal of KIISE:Software and Applications
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    • v.37 no.8
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    • pp.599-610
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    • 2010
  • Color laser printers are nowadays abused to print or forge official documents and bills. Identifying color laser printers will be a step for media forensics. This paper presents a new method to identify color laser printers with printed color images. Since different printer companies use their own printing process, each of printed papers from different printers has a little different invisible noise. After the wiener-filter is used to analyze the invisible noises from each printer, we extract some features from these noises by calculating a gray level co-occurrence matrix. Then, these features are applied to train and classify the support vector machine for identifying the color laser printer. In the experiment, we use total 2,597 images from 7 color laser printers. The results prove that the presented identification method performs well using the noise features of color printed images.