• 제목/요약/키워드: Line-Clustering

검색결과 207건 처리시간 0.03초

블러와 조명 변화에 강인한 k-means 클러스터링 기반 고속 바코드 정보 추출 방법 (Robust k-means Clustering-based High-speed Barcode Decoding Method to Blur and Illumination Variation)

  • 김근준;조호상;강봉순
    • 한국정보통신학회논문지
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    • 제20권1호
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    • pp.58-64
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    • 2016
  • 본 논문에서는 블러와 조명 변화에 강인한 바코드 디코딩 방법을 제안한다. 제안하는 디코딩 방법은 블러에 강인 디코딩과 빠른 연산속도를 위해 블러 영역과 비블러영역을 나누어 임계값을 연산하는 부분 지역 임계값 이진화 방법을 사용하였다. 또한 노이즈 데이터에 의한 인식 실패를 막기 위해서 동일한 엘리먼트 개수를 가지는 라인의 픽셀 너비를 모두 합한 면적 데이터를 이용하여 군집분류를 수행하는 k-means 알고리즘 기반의 디코더를 구현하였다. 다양한 악조건 환경에서 촬영된 샘플을 이용하여 실험 결과, 평균 98.47%로 높은 성공률을 보였으며 3개의 비교 프로그램 보다 성공률이 높았다.

모터 보호, 고장진단 및 제어를 위한 디지털 보호계전기 활용 전력감시제어 시스템 설계 (A Design of Power Management and Control System using Digital Protective Relay for Motor Protection, Fault Diagnosis and Control)

  • 이성환;안인석
    • 대한전기학회논문지:전력기술부문A
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    • 제49권10호
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    • pp.516-523
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    • 2000
  • In this paper, intelligent methods using digital protective relay in power supervisory control system is developed in order to protect power systems by means of timely fault detection and diagnosis during operation for induction motor which has various load environments and capacities in power systems. The spectrum pattern of input currents was used to monitor to state of induction motors, and by clustering the spectrum pattern of input currents, the newly occurrence of spectrums pattern caused by faults were detected. For diagnosis of the fault detected, the fuzzy fault tree was derived, and the fuzzy relation equation representing the relation between an induction motor fault and each fault type, was solved. The solution of the fuzzy relation equation shows the possibility of each fault's occurring. The results obtained are summarized as follows: 1) The test result on the basis of KEMC1120 and IEC60255, show that the operation time error of the digital motor protective relay is improved within ${\pm}5%$. 2) Using clustering algorithm by unsupervisory learning, an on-line fault detection method, not affected by the characteristics of loads and rates, was implemented, and the degree of dependency by experts during fault detection was reduced. 3) With the fuzzy fault tree, fault diagnosis process became systematic and expandable to the whole system, and the diagnosis for sub-systems can be made as an object-oriented module.

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Defect Diagnosis of Cable Insulating Materials by Partial Discharge Statistical Analysis

  • Shin, Jong-Yeol;Park, Hee-Doo;Lee, Jong-Yong;Hong, Jin-Woong
    • Transactions on Electrical and Electronic Materials
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    • 제11권1호
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    • pp.42-47
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    • 2010
  • Polymer insulating materials such as cross linked polyethylene (XLPE) are employed in electric cables used for extra high voltage. These materials can degrade due to chemical, mechanical and electric stress, possibly caused by voids, the presence of extrinsic materials and protrusions. Therefore, this study measured discharge patterns, discharge phase angle, quantity and occurrence frequency as well as changes in XLPE under different temperatures and applied voltages. To quantitatively analyze the irregular partial discharge patterns measured, the discharge patterns were examined using a statistical program. A three layer sample was fabricated, wherein the upper and lower layers were composed of non-void XLPE, while the middle layer was composed of an air void and copper particles. After heating to room temperature and $50^{\circ}C$ and $80^{\circ}C$ in silicone oil, partial discharge characteristics were studied by increasing the voltage from the inception voltage to the breakdown voltage. Partial discharge statistical analysis showed that when the K-means clustering was carried out at 9 kV to determine the void discharge characteristics, the amount discharged at low temperatures was small but when the temperature was increased to $80^{\circ}C$, the discharge amount increased to be 5.7 times more than that at room temperature because electric charge injection became easier. An analysis of the kurtosis and the skewness confirmed that positive and negative polarity had counterclockwise and clockwise clustering distribution, respectively. When 5 kV was applied to copper particles, the K-means was conducted as the temperature changed from $50^{\circ}C$ to $80^{\circ}C$. The amount of charge at a positive polarity increased 20.3% and the amount of charge at a negative polarity increased 54.9%. The clustering distribution of a positive polarity and negative polarity showed a straight line in the kurtosis and skewness analyses.

함수근사와 규칙추출을 위한 클러스터링을 이용한 강화학습 (Reinforcement Learning with Clustering for Function Approximation and Rule Extraction)

  • 이영아;홍석미;정태충
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제30권11호
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    • pp.1054-1061
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    • 2003
  • 강화학습의 대표적인 알고리즘인 Q-Learning은 상태공간의 모든 상태-행동 쌍(state-action pairs)의 평가값이 수렴할 때까지 반복해서 경험하여 최적의 전략(policy)을 얻는다. 상태공간을 구성하는 요소(feature)들이 많거나 요소의 데이타 형태가 연속형(continuous)인 경우, 상태공간은 지수적으로 증가하게 되어, 모든 상태들을 반복해서 경험해야 하고 모든 상태-행동 쌍의 Q값을 저장하는 것은 시간과 메모리에 있어서 어려운 문제이다. 본 논문에서는 온라인으로 학습을 진행하면서 비슷한 상황의 상태들을 클러스터링(clustering)하고 새로운 경험에 적응해서 클러스터(cluster)의 수정(update)을 반복하여, 분류된 최적의 전략(policy)을 얻는 새로운 함수근사(function approximation)방법인 Q-Map을 소개한다. 클러스터링으로 인해 정교한 제어가 필요한 상태(state)는 규칙(rule)으로 추출하여 보완하였다. 미로환경과 마운틴 카 문제를 제안한 Q-Map으로 실험한 결과 분류된 지식을 얻을 수 있었으며 가시화된(explicit) 지식의 형태인 규칙(rule)으로도 쉽게 변환할 수 있었다.

몬테칼로 시뮬레이션 기반의 다수 지상 연성표적에 대한 최적 조준점 산출 (Monte Carlo Simulation based Optimal Aiming Point Computation Against Multiple Soft Targets on Ground)

  • 김종환;안남수
    • 한국시뮬레이션학회논문지
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    • 제29권1호
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    • pp.47-55
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    • 2020
  • 본 논문은 드론봇 전투체계를 운용하여 전투전단의 적 보병부대 위치정보를 수집하였을 시, 지휘관이 요구하는 적 부대 피해수준을 충족하면서 적 보병부대를 신속하고 정확하게 타격하기 위하여, 보유한 화력체계의 살상범위를 기초로 최적의 사격발수 및 조준점 위치를 실시간 자동으로 산출하는 인공지능 알고리즘 연구이다. 이를 위해, 100m×200m 크기의 야지 전장환경에서 증강된 소대급 규모의 적 보병부대를 임의로 전개 및 모의하고, 약 15m의 살상범위를 갖는 가상의 화력체계에 대한 모델링을 수행하였으며, 각개 적병사의 무피해/경상 및 중상/사망 등의 피해유형 및 임무수행 가능여부를 모의하기 위하여 연성표적의 피해효과에 적용되는 칼튼피해함수를 적용하고 전장의 불확실성을 모의하기 위하여 몬테칼로 시뮬레이션을 수행하였다. 또한, 지휘관 의도에 부합된 적부대의 피해수준을 달성하기 위하여, 반복적인 모의 및 비지도학습의 k-mean clustering 기법을 적용하여 최적의 사격발수 및 조준점 위치를 0.4초 이내로 산출하였다. 본 연구에서 제안하는 방법은 드론봇 전투체계를 운용하는 대대급 규모의 전투부대에서 '탐지-결심-타격' 의사결정시간의 단축에 기여할 것으로 판단된다.

Support Vector Machine을 이용한 선에코 특성 분석 및 탐지 방법 (Analysis and Detection Method for Line-shaped Echoes using Support Vector Machine)

  • 이한수;김은경;김성신
    • 한국지능시스템학회논문지
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    • 제24권6호
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    • pp.665-670
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    • 2014
  • SVM은 학습 데이터를 두 개의 집단으로 분리시키는 최적의 초평면을 찾는 이진 분류기로서 우수한 성능 때문에 다양한 분야에서 귀납 추론, 이진 분류, 예측 등을 목적으로 사용되는 알고리즘이다. 또한 대표적인 블랙박스 모델 중 하나이기 때문에 학습 후 생성되는 SVM의 해석에 대한 연구도 활발히 진행되고 있다. 본 논문에서는 SVM 알고리즘을 이용하여 기상 레이더의 데이터 내에 비교적 높은 빈도로 발생하여 기상 예보의 정확도를 감소시키는 비강수에코 중 하나인 선에코를 자동으로 탐지하는 방법에 대한 연구를 수행하였다. 학습 데이터로는 평균 반사도, 크기, 발생 형태, 중심 고도 등과 같은 특성을 활용하였는데, 이는 기상 레이더 데이터에 저장된 다양한 데이터 중 반사도 값을 선택한 후 클러스터링 기법을 통해 추출한 것이다. 이와 같이 학습된 SVM 분류기를 실제 사례를 바탕으로 하여 검증하였으며, Decision Tree 알고리즘을 적용하여 생성한 분류기의 해석을 수행하였다.

Real-Time Pipe Fault Detection System Using Computer Vision

  • Kim Hyoung-Seok;Lee Byung-Ryong
    • International Journal of Precision Engineering and Manufacturing
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    • 제7권1호
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    • pp.30-34
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    • 2006
  • Recently, there has been an increasing demand for computer-vision-based inspection and/or measurement system as a part of factory automation equipment. In general, it is almost impossible to check the fault of all parts, coming from part-feeding system, with only manual inspection because of time limitation. Therefore, most of manual inspection is applied to specific samples, not all coming parts, and manual inspection neither guarantee consistent measuring accuracy nor decrease working time. Thus, in order to improve the measuring speed and accuracy of the inspection, a computer-aided measuring and analysis method is highly needed. In this paper, a computer-vision-based pipe inspection system is proposed, where the front and side-view profiles of three different kinds of pipes, coming from a forming line, are acquired by computer vision. And the edge detection is processed by using Laplace operator. To reduce the vision processing time, modified Hough transform is used with clustering method for straight line detection. And the center points and diameters of inner and outer circle are found to determine eccentricity of the parts. Also, an inspection system has been built so that the data and images of faulted parts are stored as files and transferred to the server.

검침데이터를 이용한 전력설비 시공간 부하분석모델 (Spatio-temporal Load Analysis Model for Power Facilities using Meter Reading Data)

  • 신진호;김영일;이봉재;양일권;류근호
    • 전기학회논문지
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    • 제57권11호
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    • pp.1910-1915
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    • 2008
  • The load analysis for the distribution system and facilities has relied on measurement equipment. Moreover, load monitoring incurs huge costs in terms of installation and maintenance. This paper presents a new model to analyze wherein facilities load under a feeder every 15 minutes using meter reading data that can be obtained from a power consumer every 15 minute or a month even without setting up any measuring equipment. After the data warehouse is constructed by interfacing the legacy system required for the load calculation, the relationship between the distribution system and the power consumer is established. Once the load pattern is forecasted by applying clustering and classification algorithm of temporal data mining techniques for the power customer who is not involved in Automatic Meter Reading(AMR), a single-line diagram per feeder is created, and power flow calculation is executed. The calculation result is analyzed using various temporal and spatial analysis methods such as Internet Geographic Information System(GIS), single-line diagram, and Online Analytical Processing (OLAP).

A Fast Contingency Screening Algorithm for On-line Transient Security Assessment Based on Stability Index

  • Nam, Hae-Kon;Kim, Yong-Hak;Song, Sung-Geun;Kim, Yong-Gu
    • KIEE International Transactions on Power Engineering
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    • 제2A권4호
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    • pp.131-135
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    • 2002
  • This paper describes a new ultra-fast contingency screening algorithm for on-line TSA without time simulation. All machines are represented in a classical model and the stability index is defined as the ratio between acceleration power during a fault and deceleration power after clearing the fault. Critical clustering of machines is done based on the stability index, and the power-angle curve of the critical machines is drawn assuming that the angles of the critical machines increase uniformly, while those of the non-critical ones remain constant. Finally, the critical clearing time (CCT) is computed using the power-angle curve. The proposed algorithm is tested on the KEPCO system comprised of 900-bus and 230-machines. The CCT values computed with the screening algorithm are in good agreement with those computed using the detailed model and the SIME method. The computation time for screening about 270 contingencies is 17 seconds with 1.2 GHz PC.

남성 재킷 패턴 설계를 위한 30-44세 남성의 상반신 체형 및 유형별 사이즈 연구 (A study on the upper body type and size of men aged 30-44 for men jacket pattern design)

  • 권동국
    • 복식문화연구
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    • 제29권6호
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    • pp.881-903
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    • 2021
  • This study aimed to analyze adult men's body sizes and shapes and suggest size specifications to provide preliminary data to academia and industries. A total of 814 adult men aged 30-44 were selected from the 7th Size Korea data, and 55 direct upper body measurement and calculation items were analyzed using SPSS 25.0. In individual Individual differences, thickness, circumference, and width were high, and height and length were low. Height above the waist base line and shoulder dimension decreased in early 40s age group, while height below the waist base line declined as age increased. In addition, buttocks shape changes were found in early 40s age group. According to factor analysis, 'upper body and upper-extremity horizontal size', 'torso height and upper extremity length', 'shoulder dimension', 'upper body length' and 'shoulder angle' were derived. Using clustering analysis, four different body types were classified: i) big abdomen with flat chest, ii) slender with big, raised shoulders, iii) dwarfish with small, droopy shoulders, and iv) obese with large shoulders. 'Slender with big, raised shoulders' was a typical body shape among men aged 30-44. In older participants, the 'big abdomen with flat chest' ratio was low, while 'obese with large shoulders' was more common. This study proposed size specifications by body type considering the above characteristics.