• 한국IT서비스학회지
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• 제12권3호
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• pp.311-321
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• 2013

In the community of software engineering, diverse modeling languages are used for representing all relevant information in the form of models. Also many different models such as business model, business process model, product models, interface models etc. are generated through software life cycles. In this situation, models need to be integrated for enterprise integration and enhancement of software productivity. Researchers propose rebuilding models by a specific modeling language, using a intemediate modeling language and using common reference for model integration. However, in the current approach it requires a lot of cost and time to integrate models. Also it is difficult to identify common objects from several models and to update objects in the repository of common model objects. This paper proposes software model integration using metadata model based on Linked data. We verify the effectiveness of the proposed approach through a case study.

• Structural Engineering and Mechanics
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• 제58권3호
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• pp.475-514
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• 2016

Various models have been proposed by several researchers for predicting the exterior RC beam-column joint shear strength. Most of these models were calibrated and verified with some limited experimental database. From the models it has been identified that the joint shear strength majorly depends on ten governing parameters. In the present paper, detailed investigation of twelve analytical models for predicting shear strength of exterior beam-column joint has been carried out. The study shows the effect of each governing parameter on joint shear strength predicted by various models. It has been observed that the consensus on effect of few of the governing parameters amongst the considered analytical models has not been attained. Moreover, the predicted joint strength by different models varies significantly. Further, the prediction of joint shear strength by these analytical models has also been compared with a set of 200 experimental results from the literature. It has been observed that none of the twelve models are capable of predicting joint shear strength with sufficient accuracy for the complete range of experimental results. The research community has to reconsider the effect of each parameters based on larger set of test results and new improved analytical models should be proposed.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2004년도 춘계학술대회 논문집
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• pp.1327-1331
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• 2004

In this paper constant power models for electric trains have been used to analyze the steady states of the AT feeding systems. There are some previous studies utilizing constant impedance models or constant current models. These mentioned models are easy to use, but even so they don't yield exact results because of the innate restraints of the models since linear models cannot represent the characteristic of constant power in inverter-driven trains. It is reasonable that the train be considered as a constant load model when it drives or as a constant source model when it applies regenerative brake. Nonlinear equations which reflect constant power model for train have been developed by considering mutual impedances between wires and AT's turn-ratio of 1:1, then these equations have been solved by N-R iterative method. The proposed method doesn't need any specific assumptions through either the process of developing equations or the process of acquiring solutions, so it can be said to be stricter than other conventional methods.

• Communications for Statistical Applications and Methods
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• 제10권2호
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• pp.585-594
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• 2003

It has been generally recognized that conventional binomial or Poisson model provides poor fits to the actual correlated binary data due to the extra-binomial variation. A number of generalized statistical models have been proposed to account for this additional variation. Among them, beta-binomial, correlated-binomial, and modified-binomial models are binomial-related models which are frequently used in modeling the sum of n correlated binary data. In many situations, it is reasonable to assume that n correlated binary data are exchangeable, which is a special case of correlated binary data. The sum of n exchangeable correlated binary data is modeled relatively well when the above three binomial-related models are applied. But the estimation results of correlation coefficient turn to be quite different. Hence, it is important to identify which model provides better estimates of model parameters(success probability, correlation coefficient). For this purpose, a small-scale simulation study is performed to compare the behavior of above three models.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.578-581
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• 2006

Usually to achieve precise geolocation of satellite images, we need to get GCPs (Ground control points) from individual scenes. This requirement greatly increases the cost and processing time for satellite mapping. In this article, we focus on finding appropriate sensor models for entire image strips composing of several adjacent scenes. We tested the feasibility of modelling whole satellite image strips by establishing sensor models of one scene with GCPs and by applying the models to neighboring scenes without GCPs. For this, we developed two types of sensor models: collinearity-based type and orbit-based type and tested them using different sets of unknowns. Results indicated that although the performance of two types was very similar, for modelling individual scenes, it was not for modelling the whole strips. Moreover, the performance of sensor models was remarkably sensitive to different sets of unknowns. It was found that the orbit-based model using attitude biases as unknowns can be used to model SPOT image strips of 420 Km in length.

• International Journal of Advanced Culture Technology
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• 제11권3호
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• pp.310-314
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• 2023

The purpose of this study is to predict the remaining capacity of lithium-ion batteries and evaluate their performance using five artificial intelligence models, including linear regression analysis, decision tree, random forest, neural network, and ensemble model. We is in the study, measured Excel data from the CS2 lithium-ion battery was used, and the prediction accuracy of the model was measured using evaluation indicators such as mean square error, mean absolute error, coefficient of determination, and root mean square error. As a result of this study, the Root Mean Square Error(RMSE) of the linear regression model was 0.045, the decision tree model was 0.038, the random forest model was 0.034, the neural network model was 0.032, and the ensemble model was 0.030. The ensemble model had the best prediction performance, with the neural network model taking second place. The decision tree model and random forest model also performed quite well, and the linear regression model showed poor prediction performance compared to other models. Therefore, through this study, ensemble models and neural network models are most suitable for predicting the remaining capacity of lithium-ion batteries, and decision tree and random forest models also showed good performance. Linear regression models showed relatively poor predictive performance. Therefore, it was concluded that it is appropriate to prioritize ensemble models and neural network models in order to improve the efficiency of battery management and energy systems.

• Journal of Information Technology Applications and Management
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• 제9권4호
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• pp.35-63
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• 2002

The analysis on the relationships among SPI models and restructuring SPI models according to a common framework makes it possible to compare and integrate the numerous research results about the models. It also makes it possible to assess objectively and accurately the results and benefits of evaluating an organization which has been evaluated according to a partial SPI model according to a new and integrated SPI model.

• 벤처창업연구
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• 제18권2호
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• pp.53-66
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• 2023

롤 모델은 개인의 직업 혹은 경력선택에 영향을 주기도 한다고 알려져 있다. 창업을 선택함에 있어서 롤 모델의 긍정적 영향은 많은 연구를 통해 이미 밝혀진 바가 있다. 롤 모델로는 혈연으로 연결된 가족 구성원인 부모형제 및 친척뿐만 아니라 사회적 관계로 만난 지인을 롤 모델로 선정한다고 한다. 본 연구에서는 자기이외에 롤 모델이 없는 창업자들과 롤 모델이 있는 창업자들로 구분하였다. 그리고 롤 모델이 있는 창업자들과 롤 모델이 없는 창업자들 간에 개인속성, 기업가정신 요인들, 학습지향성의 차이를 검증하고자 하였다. 또, 부모형제 및 친척 롤 모델을 강한 유대의 롤 모델로 지인 롤 모델을 약한 유대의 롤 모델로 구분하였다. 강한 유대 롤 모델을 가진 창업자들과 약한 유대 롤 모델을 가진 창업자들 간에 개인속성, 혁신성, 진취성, 위험감수성, 학습지향성의 차이를 검증하고자 하였다. 이를 위해 요인분석, t-검증 및 로지스틱 회귀분석을 실시하였다. 본 연구를 통해 밝혀진 실증분석 결과는 다음과 같다. 첫째, 롤 모델이 없는 창업자들 중 여성의 비율이 높은 것으로 나타났다. 둘째, 약한 유대의 롤 모델을 가진 창업자들이 강한 유대의 롤 모델을 가진 창업자들에 비해 큰 규모의 창업기업을 운영한다는 것이 밝혀졌다. 셋째, 약한 유대의 롤 모델을 가진 창업자들이 강한 유대의 롤 모델을 가진 창업자들에 비해 학습지향성이 더 높은 것으로 나타났다. 넷째, 로지스틱 회귀분석을 통해 살펴본 결과 롤 모델의 유무에 대한 영향은 성별, 학습지향성, 위험감수성, 창업규모 순인 것으로 나타났다. 다섯째, 로지스틱 회귀분석 결과에서 롤 모델의 유형에 대한 영향은 학습지향성, 창업규모의 순인 것으로 나타났다.

• 품질경영학회지
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• 제7권2호
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• pp.17-21
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• 1979

There are many kinds of the mathematical models which are developed for choosing the economic inspection plan. The aim of this paper is to classify these mathematical models, and to examine their characteristics. The mathematical models for choosing the economic inspection plan can be classified into three groups. The first of it is the break-even analysis, the second group of the model is to choose the inspection plan so as to minimize total sampling inspection cost function, and the third group of it is the model to choose the inspection plan which maximize the profit function of the sampling inspection. As a result of examining the characteristics of this classified group of the models the model to choose the inspection plan which minimize total sampling inspection cost is more economical than the other models.

• Journal of Mechanical Science and Technology
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• 제15권9호
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• pp.1292-1301
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• 2001

The mean-line method using empirical models is the most practical method of predicting off-design performance. To gain insight into the empirical models, the influence of empirical models on the performance prediction results is investigated. We found that, in the two-zone model, the secondary flow mass fraction has a considerable effect at high mass flow-rates on the performance prediction curves. In the TEIS model, the first element changes the slope of the performance curves as well as the stable operating range. The second element makes the performance curves move up and down as it increases or decreases. It is also discovered that the slip factor affects pressure ratio, but it has little effect on efficiency. Finally, this study reveals that the skin friction coefficient has significant effect on both the pressure ratio curve and the efficiency curve. These results show the limitations of the present empirical models, and more resonable empirical models are reeded.