• 제목/요약/키워드: Algorithm Judging

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알고리즘 자동평가 시스템의 개발 및 적용 : 프로그래밍 학습 효과 분석 (Development and application of algorithm judging system : analysis of effects on programming learning)

  • 장원영;김성식
    • 컴퓨터교육학회논문지
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    • 제17권4호
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    • pp.45-57
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    • 2014
  • 학습자가 주어진 문제를 해결하는 알고리즘을 작성한 후 그것이 정확한지, 그리고 시간 효율적인지를 확인할 수 있는 알고리즘 자동평가 시스템에 대한 연구가 최근 들어 활발히 진행 중이다. 그러나 기존에 연구되었던 시스템은 대부분 프로그래밍 콘테스트를 위한 Online Judge 방식으로 본 연구에서는 교수 학습 기능을 강화한 클라이언트-서버 기반의 시스템을 개발하였다. 특히, 문제해결력 증진을 위한 교수 학습 설계 모델 CRESST을 토대로 학습자의 메타인지와 동기가 활성화되도록 설계하였으며, 알고리즘 자동평가 시스템의 구성요소인 문제, 채점데이터 세트, 자동평가 프로그램, 사용자서비스 환경 등의 전체 시스템을 구현하였다. 본 시스템의 프로그래밍 학습 효과를 분석하기 위해 초 중 고 학생 39명에 대해서 비동질 통제집단 사전사후측정 실험을 실시하였고, 사후검사에 대한 독립표본 T-검정 결과, 실험집단(18명)의 평균점수가 통제집단(21명)보다 유의미하게 높은 것으로 확인되었다. 이것은 본 시스템을 사용한 교수 학습 방법이 전통적인 교수 학습 방법에 비해 프로그래밍 학습에 더 효과적임을 의미한다.

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Evaluation of Network Reliability Using Most Probable States

  • Oh, Dae-Ho;Park, Dong-Ho;Lee, Seung-Min
    • 한국신뢰성학회:학술대회논문집
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    • 한국신뢰성학회 2001년도 정기학술대회
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    • pp.463-469
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    • 2001
  • An algorithm is presenter for generating the most probable states in decreasing order of probability of each unit. The proposed new algorithm in this note is compared with the existing methods regarding memory requirement and execution time. Our method is simpler and, judging from the computing experiment, it requires less memory size than the previously known methods and takes comparable execution time to previous methods for an acceptable level of criterion.

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다중상태 유닛들의 망 신뢰도 근사 계산을 위한 알고리즘 (An Algorithm For Approximating The Reliability of Network with Multistate Units)

  • 오대호;염준근
    • 품질경영학회지
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    • 제30권1호
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    • pp.162-171
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    • 2002
  • A practical algorithm of generating most probable states in decreasing order of probability, given the probability of each unit\`s state, is suggested for approximating reliability(performability) evaluation of a network with multistate(multimode) units. Method of approximating network reliability for a given measure with most probable states is illustrated with a numerical example. The proposed method in this paper is compared with the previous method regarding memory requirement. Our method has some advantages for computation and achieves improvement with regard to memory requirement for a certain condition judging from the computation experiment.

뉴로-퍼지를 이용한 변압기 보호계전 알고리즘 (Protective Relaying Algorithm for Transformer Using Neuro-Fuzzy)

  • 이명윤;이종범;서재호
    • 대한전기학회논문지:전력기술부문A
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    • 제52권12호
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    • pp.722-730
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    • 2003
  • Current differential relay is commonly used to protect power transformer. However, current differential relay will be tripod by judging like internal fault during inrush occurring in transformer. To resolve such problem, this paper proposes a new protective relaying algorithm using Neuro-Fuzzy Inference. A variety of transformer transition states are simulated by BCTRAN and HYSDT of EMTP. Primary phase voltage and differential current are obtained from simulation. The target data which are used in Neuro-Fuzzy algorithm are obtained from transformed primary voltage and current. Then, these are trained by Neuro-Fuzzy algorithm. The trained Neuro-Fuzzy algorithm correctly distinguishes whether internal fault occurs or not, within 1/2 cycle after fault. Accordingly, it is evaluated that the proposed algorithm has good relaying characteristics.

Robust System Identification Algorithm Using Cross Correlation Function

  • Takeyasu, Kazuhiro;Amemiya, Takashi;Goto, Hiroyuki;Masuda, Shiro
    • Industrial Engineering and Management Systems
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    • 제1권1호
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    • pp.79-86
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    • 2002
  • This paper proposes a new algorithm for estimating ARMA model parameters. In estimating ARMA model parameters, several methods such as generalized least square method, instrumental variable method have been developed. Among these methods, the utilization of a bootstrap type algorithm is known as one of the effective approach for the estimation, but there are cases that it does not converge. Hence, in this paper, making use of a cross correlation function and utilizing the relation of structural a priori knowledge, a new bootstrap algorithm is developed. By introducing theoretical relations, it became possible to remove terms, which is liable to include much noise. Therefore, this leads to robust parameter estimation. It is shown by numerical examples that using this algorithm, all simulation cases converge while only half cases succeeded with the previous one. As for the calculation time, judging from the fact that we got converged solutions, our proposed method is said to be superior as a whole.

Multi-Person Tracking Using SURF and Background Subtraction for Surveillance

  • Yu, Juhee;Lee, Kyoung-Mi
    • Journal of Information Processing Systems
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    • 제15권2호
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    • pp.344-358
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    • 2019
  • Surveillance cameras have installed in many places because security and safety is becoming important in modern society. Through surveillance cameras installed, we can deal with troubles and prevent accidents. However, watching surveillance videos and judging the accidental situations is very labor-intensive. So now, the need for research to analyze surveillance videos is growing. This study proposes an algorithm to track multiple persons using SURF and background subtraction. While the SURF algorithm, as a person-tracking algorithm, is robust to scaling, rotating and different viewpoints, SURF makes tracking errors with sudden changes in videos. To resolve such tracking errors, we combined SURF with a background subtraction algorithm and showed that the proposed approach increased the tracking accuracy. In addition, the background subtraction algorithm can detect persons in videos, and SURF can initialize tracking targets with these detected persons, and thus the proposed algorithm can automatically detect the enter/exit of persons.

흉부 디지털 영상의 병변 유무 판단을 위한 딥러닝 모델 (A Deep Learning Model for Judging Presence or Absence of Lesions in the Chest X-ray Images)

  • 이종근;김선진;곽내정;김동우;안재형
    • 한국정보통신학회논문지
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    • 제24권2호
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    • pp.212-218
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    • 2020
  • 흉부 영상을 통해 진단 가능한 병변은 무기폐, 심비대, 덩어리, 기흉, 삼출 등 그 종류가 수십 가지에 이른다. 흉부 병변의 정확한 진단과 위치 및 크기를 판단하기 위해 일반적으로 전산화단층촬영(CT) 검사가 필요하지만, 전산화단층촬영은 검사 비용과 방사선 피폭 등의 단점이 있다. 따라서 본 논문에서는 흉부 병변 진단의 일차적 선별도구로서 방사선검사(X-ray) 영상에서 병변 유무 판단을 위한 딥러닝 알고리즘을 제안한다. 제안하는 알고리즘은 병변의 유무 판단에 최적화하기 위해 다양한 구성 방법들을 비교하여 설계하였다. 실험 결과, 기존 알고리즘보다 병변 유무 판단률이 약 1% 정도 향상되었다.

적응적 다단계 연속 제거 알고리즘 (An Adaptive Multilevel Successive Elimination Algorithm)

  • 안태경;문용호;김재호
    • 한국통신학회논문지
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    • 제29권1C호
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    • pp.111-118
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    • 2004
  • 본 논문에서는 고속 전역 탐색 알고리즘 가운데 좋은 성능을 나타내는 다단계 연속 제거 알고리즘을 개선시킨 적응적 다단계 연속 제거 알고리즘을 제안한다. 여러 레벨로 구성되어진 다단계 연속 제거 알고리즘에서 검사 시작 레벨을 적응적으로 선택함으로서 불필요한 레벨에서의 검사를 제거한다. 모의 실험 결과로부터 제안 알고리즘이 다단계 연속 제거 알고리즘보다 적은 계산량으로 최적의 움직임 벡터를 얻을 수 있음을 확인하였다.

A Regular Expression Matching Algorithm Based on High-Efficient Finite Automaton

  • Wang, Jianhua;Cheng, Lianglun;Liu, Jun
    • Journal of Computing Science and Engineering
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    • 제8권2호
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    • pp.78-86
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    • 2014
  • Aiming to solve the problems of high memory access and big storage space and long matching time in the regular expression matching of extended finite automaton (XFA), a new regular expression matching algorithm based on high-efficient finite automaton is presented in this paper. The basic idea of the new algorithm is that some extra judging instruments are added at the starting state in order to reduce any unnecessary transition paths as well as to eliminate any unnecessary state transitions. Consequently, the problems of high memory access consumption and big storage space and long matching time during the regular expression matching process of XFA can be efficiently improved. The simulation results convey that our proposed scheme can lower approximately 40% memory access, save about 45% storage space consumption, and reduce about 12% matching time during the same regular expression matching process compared with XFA, but without degrading the matching quality.

자연광의 색온도 주기 재현을 위한 슬라이딩 윈도우 기반 이상치 판정 알고리즘 (Algorithm for Judging Anomalies Using Sliding Window to Reproduce the Color Temperature Cycle of Natural Light)

  • 전건우;오승택;임재현
    • 한국멀티미디어학회논문지
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    • 제24권1호
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    • pp.30-39
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    • 2021
  • Research in the field of health lighting has continued to advance to reproduce the color temperature of natural light which periodically changes. However, most of this research could only reproduce a uniform circadian color temperature of natural light, therefore failing to realize the characteristics of the circadian cycle of color temperature difference by latitude and longitude. To reproduce the color temperature of natural light on which the characteristics of a region are reflected, the collection technology of real-time characteristics of natural light is needed. If the color temperatures which are not within a periodical pattern due to climate changes, etc., are measured, it will be difficult to judge the occurrence (presence) of the anomalies and to reproduce the circadian cycle of the color temperature of natural light. Therefore, this study proposes an algorithm for judging the anomalies in real time based on the sliding window to reproduce the color temperature of natural light. First, the natural light characteristics DB collected through the on-site measurement were analyzed, the differential values at a one-minute interval were calculated and examined, and then representative color temperature circadian patterns by solar terms were drawn. The anomalies were then detected by the application of the sliding window that calculated the deviation of the color temperature for the measured color temperature data set, which was collected through RGB sensors, while moving along the time sequence. In addition, the presence of anomalies was verified through the comparison study between the detection results and the representative circadian cycle of the color temperature by solar term. The judgment method for the anomalies from the measured color temperature of natural light was proposed for the first time, confirming that the proposed method was capable of detecting the anomalies with an average accuracy of 94.6%.