• Journal of Digital Convergence
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• v.15 no.3
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• pp.55-64
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• 2017

This study identified the important categories and items about evaluation criteria of e-learning quality assurance by comparing evaluation criteria between Korea and France case. For deriving the conclusion, this research analyzed the Korea quality assurance case which is consist of success or failure for evaluation of quality assurance, and built the generic quality model of e-learning evaluation criteria. A generic model about evaluation criteria, categories, and item of e-learning quality assurance, which should be reflected on French quality criteria, were developed based on statistical approach. This research suggests a evaluation criteria which can be applied to African and Asian countries, that are related to AUF, as well as Korea. The result of this study can be applied to all organizations around the world which prepare for e-learning quality assurance, and at the same time it will be a valuable resource for companies or institutions which want to be evaluated e-learning quality assurance.

• The Transactions of the Korea Information Processing Society
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• v.1 no.2
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• pp.225-236
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• 1994

Many research result conducted by neural network researchers claimed that the degree of generalization of the neural network system is higher or at least equal to that of statistical methods. However, those successful results could be brought only if the neural network was trained by appropriately sound data, having a little of noisy data and being large enough to control noisy data. Real data used in a lot of fields, especially business fields, were not so sound that the network have frequently failed to obtain satisfactory prediction accuracy, the degree of generalization. Enhancing the degree of generalization with noisy data is discussed in this study. The suggestion, which was obtained through a series of experiments, to enhance the degree of generalization is to remove inconsistent data by checking overlapping and inconsistencies. Furthermore, the previous conclusion by other reports is also confirmed that the learning mechanism of neural network takes average value of two inconsistent data included in training set［2］. The interim results of on-going research project are reported in this paper These are ann architecture of the neural network adopted in this project and the whole idea of developing on-line credit evaluation system,being intergration of the expert(resoning)system and the neural network(learning system.Another definite result is corroborated through this study that quickprop,being agopted as a learing algorithm, also has more speedy learning process than does back propagation even in very noisy environment.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.2
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• pp.244-253
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• 2022

Recently, installation projects of structures such as offshore wind farms have been increasing, and the installation of such marine obstacles could affect ships that pass nearby. Therefore, the purpose of this study was to quantitatively evaluate the risk posed to passing ships due to obstacles in their passage. Hence, parameters that affected the risk were selected, and scenarios were set based on the parameters. The scenarios were evaluated through the ES model, which is a risk assessment model, and we confirmed that the risk ratio increased as the size of the obstacle increased, the safe distance from the obstacle increased, the speed of ship decreased, and the traffic volume increased. Additionally, we found that when the traffic flow direction was designated, the risk ratio was lower than that of general traffic flow. In this study, we proposed a generalization model based on the results of the performed scenarios, applied it to the Dadaepo offshore wind farm, and demonstrated that the estimation of the approximate risk ratio was possible through the generalization model. Finally, we judged that the generalization model proposed in this study could be used as a preliminary reference for the installation of marine obstacles.

• Journal of Korean Society of Transportation
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• v.11 no.1
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• pp.55-66
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• 1993

본 논문에서는 최근에 소개된 일반화중력모형(Generalized Gravity Model)파라메터의 최우추정치(Maximum Likelihood Estimates) 계산을 위한 새로운 알고리즘을 이론적으로 도출하였다. 개발된 알고리즘은 첫째 계산속도, 둘째 정밀도, 셋째 모형변수(예컨데 통행시간, 통행비용 등)들 간에 공선성(multicolinearity)이 존재할 경우의 계산능력, 넷째 대규모 스케일의 기.종점자료(large O-D Matrices)에 적용시의 계산능력, 다섯째 모형변수의 개수에 따른 계산능력의 평가기준에서 그 계산실적이 기존의 알고리즘과 비교 평가 되었다. 제안된 기법중에서 Modified Scoring 기법은 계산속도 및 정밀도등 앞서 나열한 계산능력의 평가기준 중 모든 부문에서 매우 탁월한 계산실적을 보이는 것으로 판명되었다. 따라서 최선의 추정치를 보장하는 최우추정기법이 대규모 스케일의 교통계획 적용에도 큰 비용(시간)부담없이 손쉽게 적용될 수 있게 되었다. 제안된 새로운 알고리즘의 적용시 교통계획분야에 가져올 수 있는 기대효과는 다음과 같다. 첫째, 최우추정법이 대규모 O-D 통행표에 쉽게 적용될 수 있고 또한 PC등 소형 컴퓨터에서도 처리가 쉽다. 둘째, 모형설명변수의 자유로운 선택등 통계적실험(experimentation)을 가능케 한다. 셋째, 중력모형이 내재되어 있는 결합모형(Combined Model)의 정산속도를 높인다. 넷째, IVHS(Intelligent Vehicle and Highway System)와 같은 분야에서 온라인(On-line)모형정산을 가능케 할 수 있다.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2010.06a
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• pp.308-308
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• 2010

실리콘 나이트라이드 박막의 굴절률과 lifetime을 유전자 알고리즘과 일반화된 회귀 신경망을 이용하여 모델링하였다. 종래의 모델링에서 평가한 Spread Range 범위보다 더 작은 0.04~1.0 범위에서 평가를 수행하였다. 통계적 실험계획법을 적용해서 수집한 데이터가 이용되었다. 평가결과 보다 낮은 spread range에서 보다 우수한 예측모델이 개발될 수 있음을 확인하였다.

• Journal of the Korean Data and Information Science Society
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• v.27 no.2
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• pp.395-407
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• 2016

This study aims to apply the G-theory for estimation of reliability of evaluation scores between raters on Taekwondo Poomsae rating categories. Selecting a number of game days and raters as multiple error sources, we analyzed the error sources caused by relative magnitude of error variances of interaction between the factors and proceeded with D-study based on the results of G-study for optimal determination of measurement condition. The results showed below. The estimated outcomes of variance component for accuracy among the Taekwondo Poomsae categories with G-theory showed that impact of error was the biggest influence factor in raters conditions and in order of interaction in subjects and between subjects, also impact of variance component estimation error on expression category was the major influence factor in interaction and in order of the between subjects and raters. Finally, the result of generalizability coefficient estimation via D-study showed that measurement condition of optimal level depend on the number of raters was 8 persons of raters on accuracy category, and stable reliability on expression category was gained when the raters were 7 persons.

• The Journal of Society for e-Business Studies
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• v.22 no.4
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• pp.159-173
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• 2017

In order to provide technical financial support to small and medium-sized venture companies based on technology, the government implemented the TCB evaluation, which is a kind of technology rating evaluation, from the Kibo and a qualified private TCB. In this paper, we briefly review the current state of TCB evaluation and available indicators related to technology evaluation accumulated in the Korea Credit Information Services (TDB), and then use indicators that have a significant effect on the technology rating score. Multiple regression techniques will be explored. And the relative importance and classification accuracy of the indicators were calculated by applying the key indicators as independent features applied to the generalized boosting model, which is a representative machine learning classifier, as the class influence and the fitness of each model. As a result of the analysis, it was analyzed that the relative importance between the two models was not significantly different. However, GBM model had more weight on the InnoBiz certification, R&D department, patent registration and venture confirmation indicators than regression model.

• School Mathematics
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• v.10 no.1
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• pp.23-42
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• 2008

The purpose of this study was to describe characteristics of thinking in elementary gifted students' solutions to algebraic tasks. Especially, this paper was focused on the students' strategies to develop generalization while problem solving, the justifications on the generalization and metacognitive thinking emerged in stildents' problem solving process. To find these issues, a case study was conducted. The subjects of this study were four 6th graders in elementary school-they were all receiving education for the gifted in an academy for the gifted attached to a university. Major findings of this study are as follows: First, during the process of the task solving, the students varied in their use of generalization strategies and utilized more than one generalization strategy, and the students also moved from one strategy toward other strategies, trying to reach generalization. In addition, there are some differences of appling the same type of strategy between students. In a case of reaching a generalization, students were asked to justify their generalization. Students' justification types were different in level. However, there were some potential abilities that lead to higher level although students' justification level was in empirical step. Second, the students utilized their various knowledges to solve the challengeable and difficult tasks. Some knowledges helped students, on the contrary some knowledges made students struggled. Specially, metacognitive knowledges of task were noticeably. Metacognitive skills; 'monitoring', 'evaluating', 'control' were emerged at any time. These metacognitive skills played a key role in their task solving process, led to students justify their generalization, made students keep their task solving process by changing and adjusting their strategies.

• (The)Korea Educational Review
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• v.24 no.3
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• pp.167-189
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• 2018

Using the 1st to 5th wave data from Gyeonggi Education Panel Study(GEPS), this study analyzed the change of school effectiveness of middle schools by innovation school expansion in Gyeonggi province. For this purpose, the analysis employed difference-in-difference model with repeated cross-sectional data and the dependent variable was comprised of academic achievement, school satisfaction, creativity, and sense of community. Results showed that the effectiveness of innovation schools had not significantly different from general schools before innovation school expansion but significantly improved in academic achievement and school satisfaction compared to general schools after the policy applied. On the other hand, the school effectiveness in creativity and sense of community not significantly different between innovation and general schools in both before and after. As time passes, the effectiveness of existing innovation schools in the academic achievement was improved and the school satisfaction was maintained. In addition, the effectiveness in satisfaction of the schools was improved as general schools with high effectiveness in academic achievement were transformed into innovation schools. Based on the results, the policy for innovation school expansion was evaluated and the issues related to this policy were discussed.

• The Journal of the Acoustical Society of Korea
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• v.14 no.3
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• pp.37-48
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• 1995

This paper presents an sstimation of ARMA coefficients of noisy ARMA system using generalized total least square (GTLS) method. GTLS problem for ARMA system is defined as minimizing the errors between the noisy output vectors and estimated noisy-free output. The GTLS problem is solved in closed form by eigen-problem and the perturbation analysis of GTLS is presented. Also its recursive solution (recursive GTLS) is proposed using the power method and the covariance formula of the projected output error vector into the input vector space. The simulation results show that GTLS ARMA coefficients estimator is an unbiased estimator and that recursive GTLS achieves fast convergence.