• Design & Manufacturing
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• v.14 no.4
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• pp.71-77
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• 2020

Various manufacturing technologies, including over-molding and insert-injection molding, are used to produce hybrid plastics and metals. However, there are disadvantages to these technologies, as they require several steps in manufacturing and are limited to what can be reasonably achieved within the complexities of part geometry. This study aims to determine a practical approach for producing metal/plastic hybrid components by combining plastic injection molding and metal die casting to create a new hybrid metal/plastic molding process. The integrated metal/plastic hybrid injection molding process developed in this study uses the proven method of multi-component technology as a basis to combine plastic injection molding with metal die casting into one integrated process. In this study, the electrical conductivity and ampacity were verified to qualify the new process for the production of parts used in electronic devices. The electrical conductivity was measured, contacting both sides of the test sample with constant pressure, and the resistivity was measured using a micro ohmmeter. Also, the specific conductivity was subsequently calculated from the resistivity and contact surface of the conductor path. The ampacity defines the maximum amount of current a conductive path can carry before sustaining immediate or progressive deterioration. The manufactured hybrid multi-components were loaded with increasing currents, while the temperature was recorded with an infrared camera. To compare the measured infrared images, an electro-thermal simulation was conducted using commercial CAE software to predict the maximum temperature of the power loaded parts. Overall, during the injection molding process, it was demonstrated that multifunctional parts can be produced for electric and electronic applications.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.107-112
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• 2021

This study aims to analyze a cafe built by reflecting the characteristics of Jeju among the cafes in Jeju. This is to provide practical help to prospective prep entrepreneurs who want to start a cafe in Jeju. The cafe reflecting the characteristics of Jeju maintains its own competitiveness and constant interest of tourists by securing differentiation and uniqueness. In addition, by looking at the characteristics of Jeju applied to cafe architecture, the academic foundation for understanding the Jeju and applicable characteristics of Jeju were summarized. The study was conducted in parallel with literature analysis and on-site analysis, and as a result, the following contents were found. First, it is a reflection of Jeju's phenomenal materiality. Second, it is a reflection of Jeju's interpretive everyday life. Third, it is a reflection of Jeju's materiality time. In this regard, if prep entrepreneurs start a cafe that reflects the characteristics of Jeju, they can create a cafe with very specific characteristics if they integrate the three characteristics above.

• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.453-462
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• 2020

With the development of artificial intelligence, a lot of platforms have emerged that enable anyone to easily access and learn about artificial intelligence or create artificial intelligence models. Therefore, in this study, we analyzed various artificial intelligence education platforms and developed and proposed a SW education class plan using a framework-based artificial intelligence education platform for activating artificial intelligence based SW education. The artificial intelligence-based SW education framework aims to cultivate artificial intelligence literacy on the basis of computational thinking. In addition, a learner-centered project class was formed to include elements that could be fused with real life contexts or other subjects. Using this, with the theme of creating an artificial intelligence program to help separate garbage collection, a six-hour project-based class was developed and proposed using practical arts, social studies, and creative experiential activities. This project class was organized using a platform that is not difficult, such as AI Oceans and Entry.

• Journal of Information Technology Services
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• v.19 no.6
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• pp.131-144
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• 2020

As the blockchain technology attracts attention, interest in cryptocurrency that is received as a reward is also increasing. Currently, investments and transactions are continuing with the expectation and increasing value of cryptocurrency. Accordingly, prediction for cryptocurrency price has been attempted through artificial intelligence technology and social sentiment analysis. The purpose of this paper is to develop a deep learning ensemble model for predicting the price fluctuations and one-day lag price of cryptocurrency based on the design science research method. This paper intends to perform predictive modeling on Ethereum among cryptocurrencies to make predictions more efficiently and accurately than existing models. Therefore, it collects data for five years related to Ethereum price and performs pre-processing through customized functions. In the model development stage, four LSTM models, which are efficient for time series data processing, are utilized to build an ensemble model with the optimal combination of hyperparameters found in the experimental process. Then, based on the performance evaluation scale, the superiority of the model is evaluated through comparison with other deep learning models. The results of this paper have a practical contribution that can be used as a model that shows high performance and predictive rate for cryptocurrency price prediction and price fluctuations. Besides, it shows academic contribution in that it improves the quality of research by following scientific design research procedures that solve scientific problems and create and evaluate new and innovative products in the field of information systems.

• Journal of The Korean Association of Information Education
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• v.26 no.1
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• pp.65-73
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• 2022

In this study, by using Entry text model learning, educational contents for artificial intelligence education of elementary school students are developed and applied to actual classes. Based on the elementary and secondary artificial intelligence content table, the achievement standards of practical software education and artificial intelligence education will be reconstructed.. Among text, images, and sounds capable of machine learning, "production of emotion recognition programs using text model learning" will be selected as the educational content, which can be easily understood while reducing data preparation time for elementary school students. Entry artificial intelligence is selected as an education platform to develop artificial intelligence education contents that create emotion recognition programs using text model learning and apply them to actual elementary school classes. Based on the contents of this study, As a result of class application, students showed positive responses and interest in the entry AI class. it is suggested that quantitative research on the effectiveness of classes for elementary school students is necessary as a follow-up study.

• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.279-285
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• 2022

In this paper, as a liberal arts course for non-majors, we developed a basic practice case for convolutional neural networks, which is essential for designing a basic convolutional neural network course curriculum. The developed practice case focuses on understanding the working principle of the convolutional neural network and uses a spreadsheet to check the entire visualized process. The developed practice case consisted of generating supervised learning method image training data, implementing the input layer, convolution layer (convolutional layer), pooling layer, and output layer sequentially, and testing the performance of the convolutional neural network on new data. By extending the practice cases developed in this paper, the number of images to be recognized can be expanded, or basic practice cases can be made to create a convolutional neural network that increases the compression rate for high-quality images. Therefore, it can be said that the utility of this convolutional neural network basic practice case is high.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1644-1652
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• 2022

In the case of safety training where practical training is impossible due to risk problems, training contents using realistic media such as virtual reality or augmented reality are becoming a new alternative. In this paper, we propose a smoke modeling method that can be applied to safety-training contents implemented with realistic media technology. When an accident occurs in a hazardous area such as a petrochemical plant, visibility is not secured due to gas leakage and fire. In order to create such a situation, it is important to realistically express smoke. The proposed method is a smoke model implementation technique that can be effectively applied to the background of complex passages and devices such as petrochemical plants. In the proposed method, the smoke is expressed using volumetric rendering in the post-processing stage for the resulting image of scene rendering. Implementation results in the background of the factory show that the proposed method produces models that can express the smoke realistically.

• Structural Engineering and Mechanics
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• v.82 no.1
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• pp.107-120
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• 2022

The bracing members capable of active control against seismic loads to reduce earthquake damage have been widely utilized in construction projects. Effectively reducing the structural damage caused by earthquake events, bracing systems equipped with retrofitting damper devices, which take advantage of the energy dissipation and impact absorption, have been widely used in practical construction sites. Shape Memory Alloys (SMAs) are a new generation of smart materials with the capability of recovering their predefined shape after experiencing a large strain. This is mainly due to the shape memory effects and the superelasticity of SMA. These properties make SMA an excellent alternative to be used in passive, semi-active, and active control systems in civil engineering applications. In this research, a new system in diagonal braces with slit damper combined with SMA is investigated. The diagonal element under the effect of tensile and compressive force turns to shear force in the slit damper and creates tension in the SMA. Therefore, by creating shear forces in the damper, it leads to yield and increases the energy absorption capacity of the system. The purpose of using SMA, in addition to increasing the stiffness and strength of the system, is to create reversibility for the system. According to the results, the highest capacity is related to the case where the ratio of the width of the middle section to the width of the end section (b₁/b) is 1.0 and the ratio of the height of the middle part to the total height of the damper (h₁/h) is 0.1. This is mainly because in this case, the damper section has the highest cross-section. In contrast, the lowest capacity is related to the case where b₁/b=0.1 and the ratio h₁/h=0.8.

• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.305-312
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• 2022

In this paper, we focused on training to create and optimize a basic data prediction model. And we proposed a gradient descent training method of machine learning that is widely used to optimize data prediction models. It visually shows the entire operation process of gradient descent used in the process of optimizing parameter values required for data prediction models by applying the differential method and teaches the effective use of mathematical differentiation in machine learning. In order to visually explain the entire operation process of gradient descent, we implement gradient descent SW in a spreadsheet. In this paper, first, a two-variable gradient descent training method is presented, and the accuracy of the two-variable data prediction model is verified by comparison with the error least squares method. Second, a three-variable gradient descent training method is presented and the accuracy of a three-variable data prediction model is verified. Afterwards, the direction of the optimization practice for gradient descent was presented, and the educational effect of the proposed gradient descent method was analyzed through the results of satisfaction with education for non-majors.

• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.377-385
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• 2022

As a kind of industry-university cooperation, the contract-based department for nurturing the employers that meets the needs of industrial society has started for about 20 years. In particular, interest in contract departments as part of the SMEs' human resource development support is increasing with the newly starting government, so it is expecting that the number of new contract departments will increase for the time being. The purpose of this study is to identify the characteristics of each contract department according to the learner type and contract method, and to suggest procedures and considerations for the establishment of re-education-type and third party contract-type contract departments suitable for SMEs. In particular, the authors would like to present the case of K University for how to design the curriculum to create a virtuous cycle by harmoniously reflecting the position of the operating institution as a supplier and the requirements of many companies as consumers.