• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.4
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• pp.385-392
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• 2015

Open city information model can increase the understanding of the situation, enable the effective reuse of information due to access the semantic and relational conditions of objects, and support the reliable decision-making through linking with external references. The city information model focused on terrain and buildings was implemented based on the actual data. In addition, a process for flooding simulation was proposed using hydraulic analysis data and the city information model. The deaths and damages were estimated by flooding simulation. The availabilities were examined by detailed queries and responses based on model data of the city information model, hydraulic analysis data and the estimated damages.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.04a
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• pp.217-224
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• 2004

Open-coast storm surge computations are of value in planning and constructing engineering works, especially in coastal regions. Prediction of typhoon surge elevations is based primarily on the use of a numerical model in this study, since it is difficult to study these events in real time or with use of physical models. A simple quasi-two dimensional numerical model for storm surge is considered. In order to understand the model's underlying assumptions, range of validity, and application, we discussed several aspects of typhoons and the physical factors governing storm generation processes. We also followed the basic governing equation, together with the assumption generally taken in their development, to see the principle characteristics of the model from a physical as well as a mathematical point of view. The equations consistent with the model described here are reduced forms of the basic equations and their effects on the resulting numerical scheme are discussed. Finally we applied the model discussed above to a storm surge problem at Masan Bay, the south coast of Korea Effects of astronomical tide, initial water level, and atmospheric pressure setup are considered. We then analyzed the flood at the coastal city and proposed a reasonable way of flood control.

• Journal of Internet of Things and Convergence
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• v.2 no.3
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• pp.1-6
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• 2016

This paper aims to present the physical computing learning model applicable in teaching the information and communication technology for technology and engineering education. This model is based on the physical computing and deals with the information creation and information transfer in one framework, thus provides students with the total understanding and practice opportunity about information and communication. The proposed learning models are classified into the client-server based model and the web based model. In the implemented learning model, the acquirement and control of information is performed by sketch on Arduino and the communication of information is performed by the Python socket on Raspberry Pi well known as an education platform. Our proposed learning model can be used for teaching students to understand the concept of Internet of Things (IoT), which provides us with world wide control and communication of information.

• Journal of Educational Research in Mathematics
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• v.27 no.4
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• pp.791-810
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• 2017

This study explored the possibility of using visual models in teaching proportional reasoning based on the review of previous studies. Many studies on proportional reasoning emphasize that students tend to simply apply formal procedures without understanding the meaning behind them and that using visual models may be an alternative to help students develop informal strategies and proportional reasoning. Given these, we re-constructed and implemented the unit of a textbook to teach sixth graders proportional reasoning with ratio table, double number line, and double tape diagram. The results of this study showed that such visual models helped students understand the meaning of proportion, explore the properties of proportion, and solve proportional problems. However, several difficulties that students experienced in using the visual models led us to suggest cautionary notes when to teach proportional reasoning with visual models. As such, this study is expected to provide empirical information for textbook developers and teachers who teach proportional reasoning with visual models.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.305-311
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• 2013

The size of the market as the economy continues to evolve, in order to make the right decisions to accurately predict the economic problems the market has emerged as an important issues. To express the modern economic system, the largest of the various economic indicators, pillars stock indicators analysis and decision-making with a proper understanding of the problem for the application of the model is suitable for time-series data concealment HMM. Based on this time series model and the calculation of the time and cost savings dimension decrease techniques for the estimation and prediction of the model was applied to the problem was to verify the validity. As a result, the model predictions in both the short term rather than long-term predictions of the model estimates the optimal predictive value similar pattern very similar to both the actual data and was able to confirm that.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.5
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• pp.51-68
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• 2024

To safely operate lithium-ion batteries that power mobile electronic devices, it is crucial to accurately predict the remaining useful life (RUL) of the battery. Recently, with the advancement of machine learning technologies, artificial intelligence (AI)-based RUL prediction models for batteries have been actively researched. However, existing models have limitations as the reasoning process within the models is not transparent, making it difficult to fully trust and utilize the predicted values derived from machine learning. To address this issue, various explainable AI techniques have been proposed, but these techniques typically visualize results in the form of graphs, requiring users to manually analyze the graphs. In this paper, we propose an explainable RUL prediction method for lithium-ion batteries that interprets the reasoning process of the prediction model in textual form using SHAP analysis based on large language models (LLMs). Experimental results using publicly available lithium-ion battery datasets demonstrated that the LLM-based SHAP analysis enabled us to concretely understand the model's prediction rationale in textual form.

• 대한공업교육학회지
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• v.32 no.2
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• pp.87-103
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• 2007

The purpose of this study was to develop of the smoke flow visualization device of learning wind tunnel, teaching-learning materials in order to demonstrate air-flow around the fluid-flow field qualitatively and understand the resistance concepts of fluid-flow in secondary school. The contents of this study were consisted of the development and experiment of smoke flow visualization for learning wind tunnel. The main results of this study were as follows: First, this developed teaching-learning material here will help students understand the fundamental physical phenomena related with the resistance of fluid and the various patterns of air-flow in the field of transportation technology. Second, flow visualization has shown the same tendency in both of theoretical and experimental patterns. Third, the airfoil model has the smallest wake region meaning resistance against air-flow of circular cylinder and square rod model. Forth, flow separation point at leading edge and wide wake region began to show under the angle of attack of airfoil model ${\alpha}$ is $20^{\circ}$. Fifth, the wake width of the flow field behind a golf ball with dimple became slightly narrower than that without dimple. Sixth, the developed device was made to apply the teaching and learning materials for the experiment and practice in order to increase students' interest and attitude.

• Journal of the Korea Convergence Society
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• v.6 no.6
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• pp.17-26
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• 2015

Firms that have adopted internet technology have been confused by distorted market signals. It is natural to look at marketplace outcomes for guidance, when confronted with a new business phenomenon. However, market signals can be unreliable in the early states of any important new information technology. New technologies trigger rampant experimentation, and the experimentation is often unsustainable. As a result, market behavior is distorted and must be interpreted cautiously. In Chapter 1, we review a concept of business model and roles of strategies in a business model. In Chapter 2, we discuss a strategic auditing method for analyzing market/channel positioning, product/service positioning, value chain/value network positioning and external environmental factors. In chapter 3, we introduces major frameworks for understanding factors forming strategies. The strategic grid model categorizes four quadrants depending on the level of impacts of information technology on operation and strategy. The strategic alignment model presents a new method of assessing an alignment of information technology and business throughout all elements of a business model. In this research, we review the concept of a business model. This research introduces factors that shape strategies and new frameworks for understanding these factors. The research objective of this manuscript is to present a guidance for firms how to use information technology for attaining sustainable competitive advantages.

• Journal of the Korea Convergence Society
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• v.12 no.5
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• pp.127-138
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• 2021

The aim of this study is to demonstrate interaction as a describable field and tries to understand interaction from the perspective of attributes, thus building a theoretical to help interactive designer understand this field by common rule, rather than waste huge time and labor cost on iteration. Since the concept of interaction language has been brought out in 2000, there are varies of related academical studies, but all with defect such as proposed theoretical models are built on a non-uniform scale, or the analyzing perspective are mainly based on researcher's personal experience and being too unobjective. The value of this study is the clustered resource of research which mainly based on academical review. It collected 21 papers researched on interaction paradigm or interaction attributes published since 2000, extracting 19 interaction attribute models which contains 174 interaction attributes. Furthermore, these 174 attributes were re-clustered based on a more unified standard scale, and the two theoretical models summarized from it are respectively focuses on interaction control and interaction experience, both of which covered 6 independent attributes. The propose of this theoretical models and the analyzation of the cluster static will contribute on further revealing of the importance of interaction attribute, or the attention interaction attribute has been paid on. Also, in this regard, the interactive designer could reasonably allocate their energy during design process, and the future potential on various direction of interaction design could be discussed.

• Smart Media Journal
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• v.13 no.3
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• pp.9-17
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• 2024

Due to the recent pandemic and the development of ICT technology, the use of non-face-to-face and unmanned systems is expanding, and it is very important to understand emotions in communication in non-face-to-face situations. As emotion recognition methods for various facial expressions are required to understand emotions, artificial intelligence-based research is being conducted to improve facial expression emotion recognition in image data. However, existing research on facial expression emotion recognition requires high computing power and a lot of learning time because it utilizes a large amount of data to improve accuracy. To improve these limitations, this paper proposes a method of recognizing facial expressions using age and gender, which are image meta information, as a method of recognizing facial expressions with even a small amount of data. For facial expression emotion recognition, a face was detected using the Yolo Face model from the original image data, and age and gender were classified through the VGG model based on image meta information, and then seven emotions were recognized using the EfficientNet model. The accuracy of the proposed data classification learning model was higher as a result of comparing the meta-information-based data classification model with the model trained with all data.