• Title/Summary/Keyword: classification property

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A Study on Anthropomorphic Animal Characters Search System Visualization for UX Design

  • Lee, Young-Suk
    • Journal of Korea Multimedia Society
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    • v.17 no.12
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    • pp.1521-1527
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    • 2014
  • This paper presents to design User eXperience(UX) of anthropomorphic animal characters search system (hereinafter, AACSS) for efficient user search. To this end, meta data were utilized herein to elevate the search efficiency of multimedia information and text information. Anthropomorphic animal characters require the human elements and the animal elements, thus this paper extracted the key elements of meta data as below; phenotypic element in animal system classification (Morphologic property elements, Ecological property elements, Behavioral property elements), emotion classification, which is the trait of personification and the Step of Anthropomorphic Animal Characters.

Preliminary Study of Bioinformatics Patents and Their Classifications Registered in the KIPRIS Database

  • Park, Hyun-Seok
    • Genomics & Informatics
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    • v.10 no.4
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    • pp.271-274
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    • 2012
  • Whereas a vast amount of new information on bioinformatics is made available to the public through patents, only a small set of patents are cited in academic papers. A detailed analysis of registered bioinformatics patents, using the existing patent search system, can provide valuable information links between science and technology. However, it is extremely difficult to select keywords to capture bioinformatics patents, reflecting the convergence of several underlying technologies. No single word or even several words are sufficient to identify such patents. The analysis of patent subclasses can provide valuable information. In this paper, I did a preliminary study of the current status of bioinformatics patents and their International Patent Classification (IPC) groups registered in the Korea Intellectual Property Rights Information Service (KIPRIS) database.

A Video Smoke Detection Algorithm Based on Cascade Classification and Deep Learning

  • Nguyen, Manh Dung;Kim, Dongkeun;Ro, Soonghwan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.12
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    • pp.6018-6033
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    • 2018
  • Fires are a common cause of catastrophic personal injuries and devastating property damage. Every year, many fires occur and threaten human lives and property around the world. Providing early important sign for early fire detection, and therefore the detection of smoke is always the first step in fire-alarm systems. In this paper we propose an automatic smoke detection system built on camera surveillance and image processing technologies. The key features used in our algorithm are to detect and track smoke as moving objects and distinguish smoke from non-smoke objects using a convolutional neural network (CNN) model for cascade classification. The results of our experiment, in comparison with those of some earlier studies, show that the proposed algorithm is very effective not only in detecting smoke, but also in reducing false positives.

Type of Classification Criterion and Characteristic of Classification Strategy That Appear in Pre-Service Elementary Teachers' Classification Activity (예비 초등 교사들의 분류 활동에서 나타난 분류 기준의 유형과 분류 전략의 특징)

  • Yang, Il-Ho;Choi, Hyun-Dong
    • Journal of Korean Elementary Science Education
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    • v.27 no.1
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    • pp.9-22
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    • 2008
  • The purpose of this study was to investigate the type of classification criterion and the characteristic of classification strategy that appear in pre-service elementary teachers' classification activity. The 4 tasks were developed for classification activity; button as a real things that attribute is prominent, shell as a real things that attribute is less prominent, snow flake as a picture cards that attribute is prominent, and galaxy as a picture cards that attribute is less prominent. The 5 college students who major in elementary education were selected. Data were collected by interview with participants, participants' classification recording paper, investigator's observation of participants' action observation, and videotaped that record participants' subject classification process. Result proved in this study is as following. First, pre-service elementary teachers used 4 qualitative classification criterion of feature, random field, image and secondary property, and used 2 dimension classification criterion of space and quantity. They used single quality classification criterion or combining dimension classification criterion in classification activity. Second, pre-service elementary teachers have classification strategy that apply each various classification criterion, and also classification strategy are different according to subject, but discussed that "anchor" and "priming effect" are important for effective classification. Result of this study is expected to contribute classification research and classification teaching program development.

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A Study on the System Improvement of Registered Cultural Properties for the Preservation of Modern and Contemporary Landscape Heritage (근현대 조경유산 보존을 위한 등록문화재 제도개선 방안 연구)

  • KWON Yeji;KIM Minseon;KIM Choongsik
    • Korean Journal of Heritage: History & Science
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    • v.56 no.2
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    • pp.282-294
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    • 2023
  • Efforts are being made internationally to pay attention to the landscape value of modern and contemporary heritage and to pass it on. However, in Korea, the registration of modern and contemporary landscape heritage as registered cultural properties is insignificant. There has also been little discussion on ways to improve the system in this regard. This study sought ways to improve the registration criteria and classification system of the registered cultural property system so that modern and contemporary landscaping heritage could be protected. Currently, the registration criteria for registered cultural properties are not stipulated for each type of heritage, but are stipulated as a single comprehensive standard. Registration criteria should be separately prepared so that the landscape value of the heritage can be reviewed. First, the registration criteria have an important value in understanding the development of landscape culture. Second, well-preserved landscaping reflects or characterizes the times. Lastly, it should be defined as related to the works of major artists or important figures or historical events. The classification system must match the studied building cultural property classification system, and the detailed types of modern and contemporary landscape heritage should be specified. The major classification follows the building cultural property classification system, but parks and green spaces, squares, and gardens, which can be called a single landscape heritage, should be added to the middle classification. Landscaping heritage, such as gardens combined with building heritage, shall be specified in the subcategory based on building use.

Entropy Coders Based on Binary Forword Classification for Image Compression (영상 압축을 위한 이진 순방향 분류 기반 엔트로피 부호기)

  • Yoo, Hoon;Jeong, Je-Chang
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.4B
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    • pp.755-762
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    • 2000
  • Entropy coders as a noiseless compression method are widely used as end-point compression for images so there have been many contributions to increase of entropy coder performance and to reduction of entropy coder complexity. In this paper, we propose some entropy coders based on binary forward classification (BFC). BFC requires overhead of classification but there is no change between the amount of input information and that of classified output information, which we prove this property in this paper. And using the proved property, we propose entropy coders which are Golomb-Rice coder after BFC (BFC+GR) and arithmetic coder with BFC(BFC+A). The proposed entropy decoders do not have further complexity Son BFC. Simulation results also show better performance than other entropy coders which have similar complexity to proposed coders.

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Metric Defined by Wavelets and Integra-Normalizer (웨이브렛과 인테그라-노말라이저를 이용한 메트릭)

  • Kim, Sung-Soo;Park, Byoung-Seob
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.50 no.7
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    • pp.350-353
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    • 2001
  • In general, the Least Square Error method is used for signal classification to measure distance in the $l^2$ metric or the $L^2$ metric space. A defect of the Least Square Error method is that it does not classify properly some waveforms, which is due to the property of the Least Square Error method: the global analysis. This paper proposes a new linear operator, the Integra-Normalizer, that removes the problem. The Integra-Normalizer possesses excellent property that measures the degree of relative similarity between signals by expanding the functional space with removing the restriction on the functional space inherited by the Least Square Error method. The Integra-Normalizer shows superiority to the Least Square Error method in measuring the relative similarity among one dimensional waveforms.

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A Design of Design Pattern Retrieval System using Pattern Information (패턴정보를 이용한 디자인패턴 검색 시스템 설계)

  • Kim, Gui-Jung
    • Proceedings of the Korea Contents Association Conference
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    • 2006.05a
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    • pp.440-443
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    • 2006
  • In this paper, we implemented design pattern retrieval system for efficient management and reusability of design patterns. Pattern is consisted of property information and meta information. Property information is used for similarity measurement on classification and retrieval of patterns. Meta information is used for UML modeling of patterns. We classified design patterns with the empirical scope in addition to Gamma's basic classification.

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Vehicle Face Recognition Algorithm Based on Weighted Nonnegative Matrix Factorization with Double Regularization Terms

  • Shi, Chunhe;Wu, Chengdong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.5
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    • pp.2171-2185
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    • 2020
  • In order to judge that whether the vehicles in different images which are captured by surveillance cameras represent the same vehicle or not, we proposed a novel vehicle face recognition algorithm based on improved Nonnegative Matrix Factorization (NMF), different from traditional vehicle recognition algorithms, there are fewer effective features in vehicle face image than in whole vehicle image in general, which brings certain difficulty to recognition. The innovations mainly include the following two aspects: 1) we proposed a novel idea that the vehicle type can be determined by a few key regions of the vehicle face such as logo, grille and so on; 2) Through adding weight, sparseness and classification property constraints to the NMF model, we can acquire the effective feature bases that represent the key regions of vehicle face image. Experimental results show that the proposed algorithm not only achieve a high correct recognition rate, but also has a strong robustness to some non-cooperative factors such as illumination variation.