• 제목/요약/키워드: Improved Methods

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Kano 품질속성 평가방법론들의 실증적 비교분석 (An Empirical Comparative Analysis Between Kano and Improved Kano Methods)

  • 윤재욱;이희영
    • 품질경영학회지
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    • 제37권4호
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    • pp.31-42
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    • 2009
  • Various studies have been undertaken in order to effectively understand customer requirements. Kano proposed a dualistic approach, physical fulfillment and customer satisfaction, to differentiate Attractive, Must-be, One-dimensional quality attributes. As there were a few limitations on the Kano's method, researchers have proposed improved methods. However, there have been few empirical evidences that the improved methods are superior to the original Kano's method for identifying relevant quality attributes. The objective of this study is to provide a comparative study on Kano and improved Kanomethods based on empirical analysis of quality attributes on University services. For the analysis of the questionnaire formats, the Kano's original 5 scale questionnaire is more effective than improved methods, direct and 3 scale questionnaire. For the analysis of evaluation methods, the original Kano and Timko's method using the evaluation table are more effective than quantifying methods, Domouchel and Lim's methods.

개선된 검출 마스크를 이용한 에지추출 방법들에 관한 연구 (The Study of Edge Extract Methods Using Improved Detect Mask)

  • 신충호
    • 한국멀티미디어학회논문지
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    • 제12권2호
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    • pp.191-199
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    • 2009
  • 본 논문에서 에지를 검출하기 위해 개선된 에지 검출 방법들이 제안되었으며, 정확하고 빠른 검출을 위해서 임계값을 사용한 이진화 영상들이 실험에 사용되었다. 각 방법들의 실험적인 분석을 위해서 기존방법들과 개선된 방법들을 비교 분석하였다. 여기에서 기존방법들은 소벨, 로버트, 프리위트방법들이다. 그리고 개선된 방법들은 기존 방법들의 마스크 변위를 적용하였다. 개선된 방법들의 장점은 에지들의 침식이 많이 발생하지 않았고, 명확하게 에지를 검출할 수 있었다. 특히, 실험적인 분석을 위해서 의료영상에 그레이 영상을 사용하였고, 명확한 에지를 검출하기 위해서 결과영상에 대해서 임계값을 적용하였다. 각 방법들의 정량화 된 분석을 위해서 의료영상에 대해서 히스토그램을 적용하였다. 결론적으로, 기존 방법들과 개선된 방법들을 다수의 의료영상들의 분석적인 그래프에 적용시켜서 개선된 방법들의 장점을 증명하였다.

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협력적 필터링 추천 시스템의 정확도 향상 (Accuracy improvement of a collaborative filtering recommender system)

  • 이석환;박승현
    • 대한안전경영과학회지
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    • 제12권1호
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    • pp.127-136
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    • 2010
  • In this paper, the author proposed following two methods to improve the accuracy of the recommender system. First, in order to classify the users more accurately, the author used a EMC(Expanded Moving Center) heuristic algorithm which improved clustering accuracy. Second, the author proposed the Neighborhood-oriented preference prediction method that improved the conventional preference prediction methods, so the accuracy of the recommender system is improved. The test result of the recommender system which adapted the above two methods suggested in this paper was improved the accuracy than the conventional recommendation methods.

Vibration analysis of high nonlinear oscillators using accurate approximate methods

  • Pakar, I.;Bayat, M.
    • Structural Engineering and Mechanics
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    • 제46권1호
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    • pp.137-151
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    • 2013
  • In this paper, two new methods called Improved Amplitude-Frequency Formulation (IAFF) and Energy Balance Method (EBM) are applied to solve high nonlinear oscillators. Two cases are given to illustrate the effectiveness and the convenience of these methods. The results of Improved Amplitude-Frequency Formulation are compared with those of EBM. The comparison of the results obtained using these methods reveal that IAFF and EBM are very accurate and can therefore be found widely applicable in engineering and other science. Finally, to demonstrate the validity of the proposed methods, the response of the oscillators, which were obtained from analytical solutions, have been shown graphically and compared with each other.

가정과 수업의 협동학습이 학생의 교과에 대한 흥미와 태도에 미치는 영향 (The Effect of Cooperative Learning method in Home Economics on students′Interest and Attitude about Subject matter)

  • 양정혜;신상옥
    • 한국가정과교육학회지
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    • 제10권1호
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    • pp.137-151
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    • 1998
  • The purpose of this study is (1)to develop the teaching plan based on Cooperative Learning approach and (2)to investigate the effect of students'Interest on Subject matter and Teaching method and Attitudes to others of the area of Foreign food in Home Economics class. Among those various types of Cooperative Learning's models, this study adopted 'Learning Together'developed by Johnsons. To investigate these purpose, subject matter were analyzed and reconstructed for Cooperative Learning. The tests were developed to evaluate the interest on the Subject matter and teaching methods, and the attitude to others of the students. 108 femail high school students were divided into two groups with 54 students-traditional learning condition, Cooperative Learning condition-and had a 5 session. The subject of the class was Foreign food including Western, Chinese, and Japanes food. Before and after the class, students were tested. The statistical methods used for the study methods used for the study were t-test. The research findings are as follows : When the students in the Cooperative Learning classes were compared before and after the test, (1)Interest on Subject matter were improved considerably(p〈.001) (2)Interest on Teaching methods were improved considerably(p〈.05) (3)Attitude to Others were improved considerably(p〈.001) Therefore when the teaching-learning model based on Cooperative Liarning was used in Home Economics class, their interest on the subject and teaching methods and attitude to others were improved.

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성토하부 개량된 연약지반의 측방이동에 관한 연구 (A Study on Lateral Movement of Improved Soft Ground under Embankment)

  • 홍원표;한중근;박재석;김영환
    • 한국지반공학회:학술대회논문집
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    • 한국지반공학회 2005년도 춘계 학술발표회 논문집
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    • pp.1094-1101
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    • 2005
  • The stability of embankment on the soft ground has included problems on stabilities of embanked body and soft soil, which related with vertical displacement and lateral movement of the soft ground especially. The judge methods for the potentialities of lateral movement have been used in order to stabilization assessment during and after construction of the embankment. In this study, the judge methods on the improved soft ground suggested, which compared with exist judge methods on lateral movement. It is due to recent trend using embanked structures on the soft ground most of improved.

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A New Method for Robust and Secure Image Hash Improved FJLT

  • ;김형중
    • 한국정보통신설비학회:학술대회논문집
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    • 한국정보통신설비학회 2009년도 정보통신설비 학술대회
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    • pp.143-146
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    • 2009
  • There are some image hash methods, in the paper four image hash methods have been compared: FJLT (Fast Johnson- Lindenstrauss Transform), SVD (Singular Value Decomposition), NMF (Non-Negative Matrix Factorization), FP (Feature Point). From the compared result, FJLT method can't be used in the online. the search time is very slow because of the KNN algorithm. So FJLT method has been improved in the paper.

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Evaluating and improving system reliability of bridge structure using gamma distribution

  • Mustaf, Abdelfattah;El-Desouky, Beih S.;Taha, Ahmed
    • International Journal of Reliability and Applications
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    • 제17권2호
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    • pp.121-135
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    • 2016
  • In this paper, we study a system of five components. One of them is a bridge network component. Each of these components is identical and has a failure rate as a function of time. The system components have non-constant failure rates. The given system is improved by using the reduction, hot duplication, and cold duplication methods. We derive the equivalence factors of the bridge structure system to be as another system improved according to these different methods. The ${\beta}-fractiles$ are obtained to compare the original system with these improved systems. Finally, we present numerical results to show the difference between these methods.

Subset selection in multiple linear regression: An improved Tabu search

  • Bae, Jaegug;Kim, Jung-Tae;Kim, Jae-Hwan
    • Journal of Advanced Marine Engineering and Technology
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    • 제40권2호
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    • pp.138-145
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    • 2016
  • This paper proposes an improved tabu search method for subset selection in multiple linear regression models. Variable selection is a vital combinatorial optimization problem in multivariate statistics. The selection of the optimal subset of variables is necessary in order to reliably construct a multiple linear regression model. Its applications widely range from machine learning, timeseries prediction, and multi-class classification to noise detection. Since this problem has NP-complete nature, it becomes more difficult to find the optimal solution as the number of variables increases. Two typical metaheuristic methods have been developed to tackle the problem: the tabu search algorithm and hybrid genetic and simulated annealing algorithm. However, these two methods have shortcomings. The tabu search method requires a large amount of computing time, and the hybrid algorithm produces a less accurate solution. To overcome the shortcomings of these methods, we propose an improved tabu search algorithm to reduce moves of the neighborhood and to adopt an effective move search strategy. To evaluate the performance of the proposed method, comparative studies are performed on small literature data sets and on large simulation data sets. Computational results show that the proposed method outperforms two metaheuristic methods in terms of the computing time and solution quality.