• Title/Summary/Keyword: Individual Paper

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Automatic Individual Tooth Region Separation using Accurate Tooth Curve Detection for Orthodontic Treatment Planning

  • Lee, Chan-woo;Chae, Ok-sam
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.4
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    • pp.57-64
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    • 2018
  • In this paper, we propose the automatic detection method for individual region separation using panorama image. Finding areas that contain individual teeth is one of the most important tasks in automating 3D models through individual tooth separation. In the conventional method, the maxillary and mandibular teeth regions are separated using a straight line or a specific CT slide, and the tooth regions are separated using a straight line in the vertical direction. In the conventional method, since the teeth are arranged in a curved shape, there is a problem that each tooth region is incorrectly detected in order to generate an accurate tooth region. This is a major obstacle to automating the creation of individual tooth models. In this study, we propose a method to find the correct tooth curve by using the jawbone curve which is very similar to the tooth curve in order to overcome the problem of finding the area containing the existing tooth. We have proposed a new method to accurately set individual tooth regions using the feature that individual teeth are arranged in a direction similar to the normal direction of the tooth alignment curve. In the proposed method, the maxillary and mandibular teeth can be more precisely separated than the conventional method, and the area including the individual teeth can be accurately set. Experiments using real dental CT images demonstrate the superiority of the proposed method.

A Feasibility Study on Adopting Individual Information Cognitive Processing as Criteria of Categorization on Apple iTunes Store

  • Zhang, Chao;Wan, Lili
    • The Journal of Information Systems
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    • v.27 no.2
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    • pp.1-28
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    • 2018
  • Purpose More than 7.6 million mobile apps could be approved on both Apple iTunes Store and Google Play. For managing those existed Apps, Apple Inc. established twenty-four primary categories, as well as Google Play had thirty-three primary categories. However, all of their categorizations have appeared more and more problems in managing and classifying numerous apps, such as app miscategorized, cross-attribution problems, lack of categorization keywords index, etc. The purpose of this study focused on introducing individual information cognitive processing as the classification criteria to update the current categorization on Apple iTunes Store. Meanwhile, we tried to observe the effectiveness of the new criteria from a classification process on Apple iTunes Store. Design/Methodology/Approach A research approach with four research stages were performed and a series of mixed methods was developed to identify the feasibility of adopting individual information cognitive processing as categorization criteria. By using machine-learning techniques with Term Frequency-Inverse Document Frequency and Singular Value Decomposition, keyword lists were extracted. By using the prior research results related to car app's categorization, we developed individual information cognitive processing. Further keywords extracting process from the extracted keyword lists was performed. Findings By TF-IDF and SVD, keyword lists from more than five thousand apps were extracted. Furthermore, we developed individual information cognitive processing that included a categorization teaching process and learning process. Three top three keywords for each category were extracted. By comparing the extracted results with prior studies, the inter-rater reliability for two different methods shows significant reliable, which proved the individual information cognitive processing to be reliable as criteria of categorization on Apple iTunes Store. The updating suggestions for Apple iTunes Store were discussed in this paper and the results of this paper may be useful for app store hosts to improve the current categorizations on app stores as well as increasing the efficiency of app discovering and locating process for both app developers and users.

Systematic Analysis of Periodic Variation in Paper Structure

  • Sung, Yong-Joo;Keller, D.Steven
    • Journal of Korea Technical Association of The Pulp and Paper Industry
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    • v.41 no.5
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    • pp.50-58
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    • 2009
  • Periodic variation of local paper structure was evaluated using two-dimensional fast Fourier transform (FFT) and spectral analysis. Since the periodic variation could originate from various sources and have different magnitudes and patterns depending on the origins, a complete analysis of local paper structure properties such as local grammage, local thickness, local apparent density and surface topography was proposed in this study. For a commercial copy paper, the individual periodic patterns for each local structural property were identified by using inverse FFT spectrums of the filtered spectrum. The spectral analysis of newsprint sample provided the period of variation quantitatively, which was useful in comparing the origins of the individual periodic patterns of the local structural properties.

INDIVIDUAL AND SOCIAL INCENTIVES VERSUS R&D NETWORK RESTRICTION

  • ALGHAMDI, MOHAMAD
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.23 no.4
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    • pp.329-350
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    • 2019
  • This paper examines individual and social strategies to form profitable cooperation networks. These two types of strategies measure network stability and efficiency that may not meet in a single network. We apply restrictions on knowledge flows (R&D spillovers) and links formation to integrate these benefits into structures that ensure high outcomes for both strategies. The results suggest that linking the spillovers to the firms' positions and restricting cooperation contribute to reducing the conflict between the individual and social strategies in the development of cooperative networks.

A Case Study on Practical Teaching Methods for Engineering Design Education - A Practical Teaching Case of Artificial Intelligence Courses for Juniors in Computer Engineering Major - (공학설계 교육을 위한 현실적 교수학습 방법론의 적용 연구 - 컴퓨터공학과 3학년 인공지능 교과진행 사례 -)

  • Kim, Jinil
    • Journal of Engineering Education Research
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    • v.21 no.6
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    • pp.74-80
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    • 2018
  • This paper proposes practical teaching methods for efficient progress of project-based learning in engineering design education. Engineering design courses consist of three categories; introductory, individual and capstone design courses. This study concentrates on the case of individual design courses. Individual design courses act as bridges between introductory and capstone design courses and deal with applicable projects based on theoretical frameworks. In this study, practical teaching methods are applied to Artificial Intelligence curriculum as an individual design course for Juniors in Computer Engineering Major. The results on application of practical teaching methods show relatively positive in all aspects.

Individual Factors Influence on Client Involvement: the Case Construction Projects in Saudi Arabia

  • Trigunarsyah, Bambang;Al-Solaiman, Sultan
    • International conference on construction engineering and project management
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    • 2015.10a
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    • pp.578-582
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    • 2015
  • Lack of client involvement in construction of public projects has been identified as the main cause of many operational problems. Clients need to perform their roles and responsibilities effectively and efficiently at the right time and through the use of correct methods in order to have the optimum involvement required during all the construction project phases, namely, the planning, design, construction, handover, and operation and maintenance phase. This paper investigates the influence of clients' individual factors on their involvement in construction project delivery. A questionnaire survey was distributed to various government agencies of the Kingdom of Saudi Arabia (KSA). Explanatory Factory Analysis was performed to group nineteen individual factors. The factor analysis result suggests that the individual factors that can involve clients' involvement in construction projects can be grouped into five, which are: adequacy of knowledge and experience for decision making in the early stage of design; ability to communicate clearly; job satisfaction; personal skills; and expertise in design and construction.

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Development of Individual Electronic Identification System Using the Inductive Transmission Method for Stockbreeding Management (개체관리를 위한 인덕터 전송방식의 개체인식 시스템 개발)

  • Ko, S.C.;Han, B.S.;Lee, J.;Kim, Y.J.;Lee, S.Y.
    • Journal of Biosystems Engineering
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    • v.27 no.5
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    • pp.451-458
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    • 2002
  • This paper introduces that livestock can be effectively managed by an individual electronic identification system. The proposed system was composed of the original code transmitter, receiver, personal computer, micro-processor, and RS485 telecommunications module. In the individual electronic identification system, the signal including encoded information of a milk-cow was transmitted from an original code transmitter to a micro-processor through RS485 telecommunications module. The transmitted signal can be successfully displayed in a personal computer. This system can be managed by 9999 individuals with a original code transmitter. The recognition rate of an individual electronic identification system was 98.5% and also auto-feeder operates very well. an individual electronic identification system was developed for automation of stockbreeding management. To automate the breeding management, it is necessary to obtain and analyze the individual information distinguished from others preferentially.

Metalevel Data Mining through Multiple Classifier Fusion (다수 분류기를 이용한 메타레벨 데이터마이닝)

  • 김형관;신성우
    • Proceedings of the Korean Information Science Society Conference
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    • 1999.10b
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    • pp.551-553
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    • 1999
  • This paper explores the utility of a new classifier fusion approach to discrimination. Multiple classifier fusion, a popular approach in the field of pattern recognition, uses estimates of each individual classifier's local accuracy on training data sets. In this paper we investigate the effectiveness of fusion methods compared to individual algorithms, including the artificial neural network and k-nearest neighbor techniques. Moreover, we propose an efficient meta-classifier architecture based on an approximation of the posterior Bayes probabilities for learning the oracle.

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NEW RECOGNITION AND IDENTIFICATION MERHOD FOR MICRO-ORGANISMS BY EXPERT SYSTEM DRIVEN IMAGE PROCESSING

  • Fukuda, Toshio;Hasegawa, Osamu
    • 제어로봇시스템학회:학술대회논문집
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    • 1989.10a
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    • pp.1005-1010
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    • 1989
  • A refined version of automatic micro-organism recognition and identification method, 'O.I.S.M.2' is proposed in this paper, using image processing based on an expert system. This proposed method is based on the segmentation of the organism image, characterizing segment features, which are independent of individual size and length. Complicated shapes of organisms are divided into basic shape segments defined in this paper such as lines, circles, ovals etc. Organisms can then be expressed simply in a set of segments, regardless their individual differences.

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LM Tests in Nested Serially Correlated Error Components Model with Panel Data

  • Song, Seuck-Heun;Jung, Byoung-Cheol;Myoungshic Jhun
    • Journal of the Korean Statistical Society
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    • v.30 no.4
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    • pp.541-550
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    • 2001
  • This paper considers a panel data regression model in which the disturbances follow a nested error components with serial correlation. Given this model, this paper derives several Lagrange Multiplier(LM) testis for the presence of serial correlation as well as random individual effects, nested effects, and for existence of serial correlation given random individual and nested effects.

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