• 제목/요약/키워드: Line classification

검색결과 593건 처리시간 0.041초

온라인 부분방전 감시 시스템 (On-Line System for Partial Monitoring Discharge)

  • 최용성;황종선;이경섭
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2008년도 제39회 하계학술대회
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    • pp.2114-2115
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    • 2008
  • We consider the relation between on-line monitoring and diagnostics on the one hand and high-voltage (HV) withstand and partial discharge (PD) on-site testing on the other. HV testing supplies the basic data (fingerprints) for diagnostics. In case of warnings by on-line diagnostic systems, off-line withstand and PD testing delivers the best possible information about defects and enables the classification of the risk. Frequency tuned resonant (ACRF) test systems are best adapted to on-site conditions. They can be simply combined with PD measuring equipment. The available ACRF test systems and their application to electric power equipment -from cable systems to power transformers is described.

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대중가요를 통한 바다경관 체험에 관한 연구 (A Study on an Experience of Seascape through Korean Popular Songs)

  • 채혜성;권차경;이동화;강영조
    • 한국조경학회지
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    • 제27권4호
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    • pp.73-79
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    • 1999
  • This study is on the production and the classification of a new appreciation methods of seascape through materials in the words of Korean popular songs. In advance, it is necessary to understand the popular songs as collective representation and the songs are analytic data. In this study, some essential elements of seascape in popular songs are analyzed and classified. They are; 1. visible elements-weather, time, season and object. 2. all senses-vision, audition, olfaction, tactile sense, and spatial sense. 3. the line of vision-static line of vision and dynamic line of vision. In this way data is produced, and then the result of this study makes appreciation methods of seascape developed. In this way, this study results in developed appreciation of seascape. This study on new understanding of appreciation methods of seascape is on the basis of a design method of water-front that is considered a visible scene, not a design of construction elements.

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선군집분할방식의 강판튜브 엑스선 영상에의 적용성 판별 (Applicability Discrimination for Line-clustering Segmental Approach to Steel-tube X-ray Image)

  • 황중원;황재호
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2007년도 하계종합학술대회 논문집
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    • pp.397-398
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    • 2007
  • In this paper, we have verified the applicability of the line-clustering segmentation method to steel-tube X-ray images. Image data is partitioned into three regions on the base of vertical line edge detection. Parameters for necessary condition, such as neighborlity, similarity and directional neighbor correlation coefficients, proposed in that method is calculated and applied to such selected regions separately Segmental features at each region is extracted statistically and functional classification is clustered by the point or space process. The analyzed data and experimental results show that the line-clustering segmentation method has a high applicability to X-ray image.

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전자상거래에서 지식탐사기법의 활용에 관한 연구 (An Application of Data Mining Techniques in Electronic Commerce)

  • 성태경;주석진;김중한;홍준석
    • 한국정보시스템학회지:정보시스템연구
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    • 제14권2호
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    • pp.277-292
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    • 2005
  • This paper uses a data mining approach to develop bankruptcy prediction models suitable for traditional (off-line) companies and electronic (on-line) companies. It observes the differences in the composition prediction models between these two types of companies and provides interpretation of bankruptcy classifications. The bankruptcy prediction models revealed the major variables in predicting bankruptcy to be 'cash flow to total assets' and 'gross value-added to net sales' for traditional off-line companies while 'cash flow to liabilities','gross value-added to net sales', and 'current ratio' for electronic companies. The accuracy rates of final prediction models for traditional off-line and electronic companies were found to be $84.7\%\;and\;82.4\%$, respectively. When the model for traditional off-line companies was applied for electronic companies, prediction accuracy dropped significantly in the case of bankruptcy classification (from $70.4\%\;to\;45.2\%$) at the level of a blind guess ($41.30\%$). Therefore, the need for different models for traditional off-line and electronic companies is justified.

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Vehicle Classification by Road Lane Detection and Model Fitting Using a Surveillance Camera

  • Shin, Wook-Sun;Song, Doo-Heon;Lee, Chang-Hun
    • Journal of Information Processing Systems
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    • 제2권1호
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    • pp.52-57
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    • 2006
  • One of the important functions of an Intelligent Transportation System (ITS) is to classify vehicle types using a vision system. We propose a method using machine-learning algorithms for this classification problem with 3-D object model fitting. It is also necessary to detect road lanes from a fixed traffic surveillance camera in preparation for model fitting. We apply a background mask and line analysis algorithm based on statistical measures to Hough Transform (HT) in order to remove noise and false positive road lanes. The results show that this method is quite efficient in terms of quality.

LCC 분석을 이용한 효과적인 신호 설비 분류에 관한 연구 (A Study on The Effective Classification of Signal Facilities using LCC Analysis)

  • 김두석;김영훈;안찬기;장성용
    • 한국철도학회:학술대회논문집
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    • 한국철도학회 2011년도 정기총회 및 추계학술대회 논문집
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    • pp.2711-2717
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    • 2011
  • This paper presents the classification scheme of the signal facilities on the railroad considering the construction costs and maintenance costs in a low population area. The construction costs of the new signal facility system can be compare with the costs of the present signal facilities as the classification scheme. The signal facilities on the railroad were classified as the railroad security regulations and then the scheme is considered through the LCC analysis. In order to test this research, the costs of signal facilities obtained from ones on TAEBACK railroad line. The costs categorized the construction costs, the labor cost and the maintenance costs can be effectively applied to the LCC analysis. The scheme is very useful to make a decision whether the new signal facilities on railroad in low population area is build or not in terms of the costs.

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Study on Forest Vegetation Classification with Remote Sensing

  • Yuan, Jinguo;Long, Limin
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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    • pp.250-255
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    • 2002
  • This paper describes the study methods of identifying forest vegetation types, based on this study, forest vegetation classification method based on vegetation index is proposed. According to reflectance data of vegetation canopy and soil line equation NIR=1.506R+0.0076 in Jingyuetan, Changchun, China, many vegetation index are calculated and analyzed. The relationships between vegetation index and vegetation types are that PVI identifies broadleaf forest and conifer forest the most easily, the next is TSAVI and MSAVI, but their calculation is complex. RVI values of different conifer trees vary obviously, so RVI can classify conifer trees. In a word, combination of PVI and RVI is evaluated to classify different vegetation types.

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Efficient Classification of High Resolution Imagery for Urban Area

  • Lee, Sang-Hoon
    • 대한원격탐사학회지
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    • 제27권6호
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    • pp.717-728
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    • 2011
  • An efficient method for the unsupervised classification of high resolution imagery is suggested in this paper. It employs pixel-linking and merging based on the adjacency graph. The proposed algorithm uses the neighbor lines of 8 directions to include information in spatial proximity. Two approaches are suggested to employ neighbor lines in the linking. One is to compute the dissimilarity measure for the pixel-linking using information from the best lines with the smallest non. The other is to select the best directions for the dissimilarity measure by comparing the non-homogeneity of each line in the same direction of two adjacent pixels. The resultant partition of pixel-linking is segmented and classified by the merging based on the regional and spectral adjacency graphs. This study performed extensive experiments using simulation data and a real high resolution data of IKONOS. The experimental results show that the new approach proposed in this study is quite effective to provide segments of high quality for object-based analysis and proper land-cover map for high resolution imagery of urban area.

필기체 한글의 오프라인 인식을 위한 효과적인 두 단계 패턴 정합 방법 (Efficient two-step pattern matching method for off-line recognition of handwritten Hangul)

  • 박정선;이성환
    • 전자공학회논문지B
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    • 제31B권4호
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    • pp.1-8
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    • 1994
  • In this paper, we propose an efficient two-step pattern matching method which promises shape distortion-tolerant recognition of handwritten of handwritten Hangul syllables. In the first step, nonlinear shape normalization is carried out to compensate for global shape distortions in handwritten characters, then a preliminary classification based on simple pattern matching is performed. In the next step, nonlinear pattern matching which achieves best matching between input and reference pattern is carried out to compensate for local shape distortions, then detailed classification which determines the final result of classification is performed. As the performance of recognition systems based on pattern matching methods is greatly effected by the quality of reference patterns. we construct reference patterns by combining the proposed nonlinear pattern matching method with a well-known averaging techniques. Experimental results reveal that recognition performance is greatly improved by the proposed two-step pattern matching method and the reference pattern construction scheme.

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Neuro-fuzzy network을 이용한 고장 검출 및 판별 알고리즘에 관한 연구 (A Novel Algorithm for Fault Classification in Transmission Lines using a Combined Adaptive Network-based Fuzzy Inference System)

  • 여상민;김철환;채영무;최재덕
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2001년도 하계학술대회 논문집 A
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    • pp.252-254
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    • 2001
  • Accurate detection and classification of faults on transmission lines is vitally important. High impedance faults(HIF) in particular pose difficulties for the commonly employed conventional overcurrent and distance relays, and if not detected, can cause damage to expensive equipment, threaten life and cause fire hazards. Although HIFs are far less common than LIFs, it is imperative that any protection device should be able to satisfactorily deal with both HIFs and LIFs. This paper proposes an algorithm for fault detection and classification for both LIFs and HIFs using Adaptive Network-based Fuzzy Inference System(ANFIS). The performance of the proposed algorithm is tested on a typical 154[kV] Korean transmission line system under various fault conditions. Test results show that the ANFIS can detect and classify faults including (LIFs and HIFs) accurately within half a cycle.

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