• The Journal of Korea Robotics Society
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• v.4 no.3
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• pp.201-209
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• 2009

In this paper, we deal with the performance evaluation method of user identification and user tracking for intelligent robots using face images. This paper shows general approaches for standard evaluation methods to improve intelligent robot systems as well as their algorithms. The evaluation methods proposed in this paper can be combined with the evaluation methods for detection algorithms of face region and facial components to measure the overall performance of face recognition in intelligent robots.

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.1
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• pp.289-299
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• 2016

The purpose of the study was to develop evaluation methods which would measure student achievement and progress without traditional paper-pencil tests such as mid-term and final examinations. More specifically, the main research focus were to establish general directions of student assessment during free semester, to build evaluation models supporting student's participation and learning, and to report and record various student evaluation results. As research results, we found that student evaluation of free semester should be organized to improve a) experience learning activity, self-regulatory and collaboratory study, b) high-order thinking ability and character-building, and c) teacher-student-parent cooperation. Since traditional paper-pencil tests were restricted in free semester, student achievement should be provided by a way of performance descriptions on transcripts rather than quantitative grade points. Student performance descriptions had to show not only subject knowledge but also students efforts, motivation, and participation. These multiple and educationally meaningful information would be collected by teacher-student-parent communication and collaboration.

• Journal of Korean Society for Quality Management
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• v.33 no.2
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• pp.1-12
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• 2005

An extensive literature review has been made in this paper to build the evaluation hierarchy structure for the certification of electronic commerce services. In building the evaluation hierarchy structure, major candidate evaluation factors are selected by bench marking the various certification practices, including the Malcolm Baldrige award, ISO9000, and BSC(balanced scorecard) techniques. This paper deployed principal component analysis and factor analysis techniques to develop a statistically solid and systematic evaluation model. The final evaluation model, as presented in this paper as a model for the certification of electronic commerce services, produces a numeric score on the 100% scale, which can be served as a metric for the certification decision. The AHP technique was used in converting the various qualitative and quantitative evaluation values into a single measure for the certification decision.

• The Journal of Korean Association of Computer Education
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• v.21 no.5
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• pp.61-68
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• 2018

Collaborative filtering is a fundamental technique implemented in many commercial recommender systems and provides a successful service to online users. This technique recommends items by referring to other users who have similar rating records to the current user. Hence, similarity measures critically affect the system performance. This study addresses problems of previous similarity measures and suggests a new similarity measure. The proposed measure reflects the subjectivity or vagueness of user ratings and the users' rating behavior by using fuzzy logic. We conduct experimental studies for performance evaluation, whose results show that the proposed measure demonstrates outstanding performance improvements in terms of prediction accuracy and recommendation accuracy.

• Journal of KIISE:Software and Applications
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• v.26 no.11
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• pp.1372-1380
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• 1999

본 논문에서는 자연언어 문장의 객관적 정량적인 질 측정 방법의 구축에 대해 설명하고, 이를 문장 퇴고 시스템의 사례에 적용해 본다. 문장의 질을 평가한다는 것은 본질적으로 주관적이고 정량화가 어려운 작업이기 때문에, 이 과정에서 질의 객관적 계량화가 가능한지 여부가 가장 중요한 문제가 된다. 이 논문에서는 이러한 문제를 해결하기 위해 유전자 알고리즘을 이용한 진화적 접근 방법을 통해 객관적이고 정량적인 질의 측정 공식을 유도하는 방법론을 제시하였다. 이 논문에서 제시한 방법론의 핵심은 간단히 말해서 사람이 행하는 정성적인 판단을, 이에 가장 근접하는 정량적 측정 체계로 전환시키는 것이라고 보면 된다. 이것을 위해 정량화 문제를 문장의 단순 언어 특징들의 변화값을 이용한 최적화 문제로 환원시키고, 다시 이 최적화 문제를 유전자 알고리즘을 이용해 해결함으로써 문제를 효과적으로 해결할 수 있었다. 실험 결과를 보면, 본 논문에서 제시한 최적화 방법은 주어진 훈련용 예제와 검증용 예제 중 각각 99.84%, 99.88%를 만족시키는 해를 찾아내었으므로 정량적 질 평가 공식의 유도에 매우 효과적임을 알 수 있었다. 또한 도출된 측정 공식을 이용해서 실제 퇴고 시스템 평가에 적용한 결과 문장 질의 측정에 매우 유용하게 이용될 수 있음을 알 수 있었다. 이와 같이 질의 정량적 평가가 가능하다는 사실이 갖는 또 한가지 중요한 의미는 최종 사용자의 구매 의사나 개발자의 공학적 의사 결정을 위한 객관적 성능 평가 자료의 제공에 이 방법이 유용하게 사용될 수 있다는 점이다.Abstract This paper describes a method of building a quantitative measure of the quality of natural language sentences, particularly produced by document revision systems. Evaluating the quality of natural language sentences is intrinsically subjective, so what is most important as to the evaluation is whether the quality can be measured objectively. To solve such problem of objective measurability, genetic algorithm, an evolutionary learning method, is employed in this paper. The underlying standpoint of this approach is that building the quality measures is a task of constructing a formulae that produces as close results as can to the qualitative decisions made by humans. For doing this, the problem of measurability has been simply reduced to an optimization problem using the change of the values of simple linguistic parameters found in sentences, and the reduced problem has been solved effectively by the genetic algorithm. Experimental result shows that the optimization task satisfied 99.84% and 99.88% of the given objectives for training and validation samples, respectively, which means the method is quite effective in constructing the quantitative measure of the quality of natural language sentences. The actual evaluation result of a revision system shows that the measure is useful to quantize the quality of sentences. Another important contribution of this measure would be to provide an objective performance evaluation data of natural language systems on a basis of which end-users and developers can make their decision to fit their own needs.

• Journal of Korean Port Research
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• v.12 no.1
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• pp.9-17
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• 1998

The evaluation structure of complex problems is composed of multi-attributes and hierarchy. A many studies were existed on this problems, but that based on the assumption that the evaluation elements were independent. The actual evaluation problems have the complexity, ambiguity and interlinkage among the elements. In this situation, the fuzzy evaluation process is very effective in settling the complex problems. For evaluation of large scale hierarchical MADM problem, the fuzzy evaluation algorithm is developed in this paper, and that is centering on the identification of fuzzy measures. In this study, we newly identified the weight and interaction among the evaluation attributes. The results of this study are as follows: we can identified the hierarchical structure of the evaluation problem which is composed of the evaluation structure, function and hierarchy; we improved the existed weighting method which could be accomplished by normalizing process, considering the uncertainty and new weight integrating method which come from Dempster-Shafer theory. And we take into account the interaction properties among more than 3 evaluation attributes, which can be compared with the existed studies in which only 2 evaluation attributes taked into account.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.1
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• pp.104-111
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• 2012

In this paper, we propose a novel method to improve the performance of the improved minima controlled recursive averaging (IMCRA). From an examination for various noise environment, it is shown that the IMCRA has a fundamental drawback for the noise power estimate at the offset region of continuity speech signals. Espectially, it is difficult to obtain the robust estimates of the noise power in non-stationary noisy environments that is rapidly changed the spectral characteristics such as babble noise. To overcome the drawback, we apply the global speech absence probability (GSAP) conditioned on both a priori SNR and a posteriori SNR to the speech detection algorithm of IMCRA. With the performance criteria of the ITU-T P.862 perceptual evaluation of speech quality (PESQ) and a composite measure test, we show that the proposed algorithm yields better results compared to the conventional IMCRA-based scheme under various noise environments. In particular, in the case of babble 5 dB, the proposed method produced a remarkable improvement compared to the IMCRA ( PESQ = 0.026, composite measure = 0.029 ).

• Journal of the Korean Data and Information Science Society
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• v.24 no.2
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• pp.257-265
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• 2013

As evaluating the health literacy is getting important, various measures for evaluation are being developed. Nevertheless, discussions about developing proper measures in Korean are still inactive. Therefore in this paper, we proposed Korean REALM (rapid estimate of adult literacy in medicine) measure that is composed of five point scale and investigated about its validity. As a result, we could find that Korean REALM measure which is composed of five point scale has high reliability, and that it formed one dimension as a result of factor analysis. Positive responses were lower than two point scale and correlation coefficient with NVS (the newest vital sign) appeared statistically significant. Therefore, we could conclude that Korean REALM measure that is composed of five point scale is a valid measurement. Furthermore, there were statistically significant differences between general students and department of nursing students about health literacy.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.3
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• pp.138-144
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• 2019

In a modern society, people are concerned seriously about their travel destinations depending on time, economic problem. In this paper, we propose an non-hierarchical clustering based hybrid recommendation using context knowledge. The proposed method is personalized way of recommended knowledge about preferred travel places according to the user's location, place, and weather. Based on 14 attributes from the data collected through the survey, users with similar characteristics are grouped using a non-hierarchical clustering based hybrid recommendation. This makes more accurate recommendation by weighting implicit and explicit data. The users can be recommended a preferred travel destination without spending unnecessary time. The performance evaluation uses accuracy, recall, F-measure. The evaluation result was shown 0.636 accuracy, 0.723 recall, and 0.676 F-measure.

• The Mathematical Education
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• v.45 no.2 s.113
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• pp.205-215
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• 2006

One of the most important concepts in the 7th curriculum of Korea is the student-centered education. Since educational evaluation has significant influence on the whole curriculum, if we realize the importance of the student-center education on the curriculum we should establish the student-centered educational evaluation system. Educational evaluation is defined by the theory of information to permit information users to identify, to measure, to manipulate and to communicate useful educational information concerning an educational curriculum for making decisions. If we accept the above definitions, the demands of information users are significant in the light of conceptual framework of educational evaluation. The purpose of this study is to analyze the conceptual framework of educational evaluation from information users' perspectives and to investigate the qualitative characteristics which satisfy information users' need for making decisions. We also show that students aren't provided sufficient evaluation results information to decide for their study plans by analyzing an evaluation study of the 7th primary curriculum. Finally, this study suggests how to improve an evaluation system for students in mathematics.