• Journal of Internet Computing and Services
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• v.2 no.2
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• pp.71-93
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• 2001

Commonly to design a database system. a conceptual database has to be designed and then it is transformed into a logical database schema prior to building a target database system. This paper proposes a method which transforms a Temporal Entity-Relationship Model(TERM) into a Temporal Object-Oriented Model(TOOM) to build an efficient database schema. I formalize the time concept in view of object versioning and specify the constraints required during transformation procedure. The proposed transformation method contributes to getting the logical temporal data from the conceptual temporal events Without any loss of semantics, Compared to other approaches of supporting various properties, this approach is more general and efficient because it is the semantically seamless transformation method by using the orthogonality of types of objects, semantics of relationships and constraints over roles.

• Journal of the Korean Society for Railway
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• v.13 no.4
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• pp.382-388
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• 2010

This paper describes the standardized finite element model for carbody structures of railway vehicle made of sandwich composites. Recently, sandwich composites were widely used to railway vehicle due to the improvement of energy efficiency, high specific stiffness and strength, weight reduction and space saving in korea. Therefore, structural integrity should be verified using finite element analysis prior to the manufacture of composite railway vehicle. The standardized finite element model for composite carbody structures was introduced through comparing the results of real structural test under vertical, compressive, twisting load and natural frequency test of various railway vehicles in this study. The results show that the quadratic shell element is suitable to model the reinforced metal frame used to improve the flexural stiffness of sandwich panel compared to beam element, and layered shell and solid element are recommended to model the skin and honeycomb core of sandwich panel compared to sandwich shell element. Also, the proposed standard finite element model has the merit of being applied to crashworthiness problem without modifications of finite element model.

• Journal of Broadcast Engineering
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• v.26 no.5
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• pp.608-620
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• 2021

Recent deep learning-based face super-resolution (FSR) works showed significant performances by utilizing facial prior knowledge such as facial landmark and dictionary that reflects structural or semantic characteristics of the human face. However, most of these methods require additional processing time and memory. To solve this issue, this paper propose an efficient FSR models using knowledge distillation techniques. The intermediate features of teacher network which contains dictionary information based on major face regions are transferred to the student through adversarial multi-scale features distillation. Experimental results show that the proposed model is superior to other SR methods, and its effectiveness compare to teacher model.

• Journal of Digital Convergence
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• v.19 no.7
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• pp.199-208
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• 2021

Automatic Post Editing(APE) is the study that automatically correcting errors included in the machine translated sentences. The goal of APE task is to generate error correcting models that improve translation quality, regardless of the translation system. For training these models, source sentence, machine translation, and post edit, which is manually edited by human translator, are utilized. Especially in the recent APE research, multilingual pretrained language models are being adopted, prior to the training by APE data. This study deals with multilingual pretrained language models adopted to the latest APE researches, and the specific application method for each APE study. Furthermore, based on the current research trend, we propose future research directions utilizing translation model or mBART model.

• Land and Housing Review
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• v.14 no.1
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• pp.123-134
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• 2023

The BIM (Building Information Modeling) model created in the design stage can be used for prior review and schedule management for the construction stage. However, in the case of actual BIM application cases, additional work is required, such as creating a new model suitable for the construction stage, rather than using the 3D model in the design stage, due to the difference in the purpose of use between the design stage and the construction stage. Therefore, in this study, a division function of BIM model is proposed as a method of recycling it in the construction stage without a remodeling process. In addition, the application to the actual BIM model and the 4D CAD system linkage of the divided object and the comparison with the existing division method are used to verify the usability.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.43-50
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• 2024

This paper evaluates the Korean sentiment analysis performance of large language models like GPT-3.5 and GPT-4 using a zero-shot approach facilitated by the ChatGPT API, comparing them to pre-trained Korean models such as KoBERT. Through experiments utilizing various Korean sentiment analysis datasets in fields like movies, gaming, and shopping, the efficiency of these models is validated. The results reveal that the LMKor-ELECTRA model displayed the highest performance based on F1-score, while GPT-4 particularly achieved high accuracy and F1-scores in movie and shopping datasets. This indicates that large language models can perform effectively in Korean sentiment analysis without prior training on specific datasets, suggesting their potential in zero-shot learning. However, relatively lower performance in some datasets highlights the limitations of the zero-shot based methodology. This study explores the feasibility of using large language models for Korean sentiment analysis, providing significant implications for future research in this area.

• Journal of The Korean Association For Science Education
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• v.33 no.5
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• pp.893-910
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• 2013

The purpose of this study was to identify changes in mental models of students in the elementary school about causes of seasonal changes. During a total of eight sessions, eight sixth graders were asked to describe the causes of seasonal changes through pictures, writing and thinking aloud by using microgenetic research methods, and the changes in mental models were examined. When the research was conducted, linguistic and behavioral factors and contents of interviews of participants were recorded on video. Moreover, a variety of materials such as field observation chart were written by a researcher and mental models records were written by a student. The protocol was written by integration of collected results, and it was repeated to read and was inductively categorized. The results of this study were as follows: First, participants' mental models about causes of seasonal changes were changed in various paths within and across sessions. Participants' mental models that had been more changed in various ways were closer to the scientific model. In addition, like rotation and revolution, students who correctly established the preconceptions related to seasonal changes formed the mental models consistent with scientific concept based on new information. On the other hand, students who did not correctly establish the preconceptions did not deviate from non-scientific mental models. Second, prior knowledge, experience and information which participants held in advance, accuracy of prior knowledge, resolution of inconsistency between new knowledge and existing mental models, activation of mental models through operation of models and drawing an picture affected the changes of mental models. Teachers should provide to learners with sufficient experience which can be configured to various mental models in order to form the scientific concepts. And they need to let learners feel the doubt and resolve it through presentation of new teaching material which is inconsistent with the existing mental models.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.1
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• pp.145-151
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• 2014

This paper proposes an image haze removal algorithm for a single image. The conventional Dark Channel Prior(DCP) algorithm estimates a transmission map using the dark information in an image, and the haze regions are then detected using a matting algorithm. However, since the DCP algorithm uses block-based processing, block artifacts are invariably formed in the transmission map. To solve this problem, the proposed algorithm generates a modified transmission map using a Hidden Markov Random Field(HMRF) and Expectation-Maximization(EM) algorithm. Experimental results confirm that the proposed algorithm is superior to conventional algorithms in image haze removal.

• Korean Business Review
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• v.18 no.2
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• pp.61-81
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• 2005

As to the research method for this study, it examines the conceptional understanding of organizational politics along with existing theories, prior research and prior models on the perception of organizational politics. Empirical analysis concerning the six hypothesis of the research, is carried out based upon returned questionnaires. The subjects of the survey were more than sergeant executive of 51 units R.O.K Army. Out of the 350 copies of the questionnaire, 323 copies were returned of which 294 were used for analysis. Results indicated that perceptions of organizational politics were negatively related to job attitudes(eg. job satisfaction, organizational commitment, organizational citizenship behavior). The relationship between perceptions of organizational politics and organizational citizenship behavior was moderated by trust in supervisor. Finally, implications and future research suggestions are discussed.

• Journal of Environmental Science International
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• v.20 no.12
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• pp.1541-1551
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• 2011

This study applied the Bayesian method for the quantification of the parameter uncertainty of spatial linear mixed model in the estimation of the spatial distribution of probability rainfall. In the application of Bayesian method, the prior sensitivity analysis was implemented by using the priors normally selected in the existing studies which applied the Bayesian method for the puppose of assessing the influence which the selection of the priors of model parameters had on posteriors. As a result, the posteriors of parameters were differently estimated which priors were selected, and then in the case of the prior combination, F-S-E, the sizes of uncertainty intervals were minimum and the modes, means and medians of the posteriors were similar to the estimates using the existing classical methods. From the comparitive analysis between Bayesian and plug-in spatial predictions, we could find that the uncertainty of plug-in prediction could be slightly underestimated than that of Bayesian prediction.