• Journal of The Korean Association of Information Education
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• v.23 no.2
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• pp.149-157
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• 2019

The fourth industrial revolution era calls for the ability to solve problems creatively based on basic literacy for technology. These capabilities can be enhanced through the maker education linked to SW education STEM convergence education. Meanwhile, one of the tasks that must be set prior to the maker education is to take an educational approach rather than a tech-centric approach and consider ways to stimulate interest and motivation of the participants. For this purpose, this study developed and applied an engineering-oriented Reading & Maker education program to prospective teachers so that they could participate in active making activities on their own with interest and sympathy rather than simply guiding maker activities. As a result of the study, the results of the maker education recognition survey after the application of the program showed a statistically significant improvement(p<.000).

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.673-681
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• 2021

This study is a case study of artificial intelligence education subjects in the graduate school of education. The main educational contents consisted of understanding and practice of machine learning, data analysis, actual artificial intelligence using Entries, artificial intelligence and physical computing. As a result of the survey on the educational effect after the application of the curriculum, it was found that the students preferred the use of the Entry AI block and the use of the Blacksmith board as a physical computing tool as the priority applied to the elementary education field. In addition, the data analysis area is effective in linking math data and graph education. As a physical computing tool, Husky Lens is useful for scalability by using image processing functions for self-driving car maker education. Suggestions for desirable AI education include training courses by level and reinforcement of data collection and analysis education.

• Journal of The Korean Society of Integrative Medicine
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• v.9 no.4
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• pp.49-58
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• 2021

Purpose : This study investigates the effects of the application of traditional occupational therapy and the korean computerized cognition training system on the cognitive function and performance of daily activities of stroke patients with cognitive impairment. Methods : From inpatients referred for rehabilitation treatment at L Rehabilitation Hospital located in Busan, 20 patients diagnosed with stroke from April 05. 2021 to May 02. 2021 (study period) were selected, They were divided into two, an experimental group consisting of 10 subjects who underwent a computerized cognitive rehabilitation program and traditional occupational therapy in combination and a control group of 10 subjects who underwent traditional occupational therapy alone. In order to measure the cognitive function of the subjects before the intervention, two assessment tests were conducted: a Neurobehavioral Cognitive Status Examination (NCSE), which evaluates stroke-related cognitive ability, and a Functional Independence Measure (FIM) test, which evaluates life activities. Then, both groups received a total of 20 training sessions at 30 minutes per session, five times a week for four weeks. Results : A statistically significant difference was found in cognitive function between before and after the cognitive training for both the experimental group and the control group. For the FIM scores, statistically significant differences were observed after intervention in the categories of handling personal matters and social cognition, and in the total score. The average scores of the remaining items also improved. Conclusion : The results of this study showed that both the computerized cognition rehabilitation program and the traditional occupational therapy had a positive effect on the improvement of cognitive function in stroke patients.

• Journal of the Society of Disaster Information
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• v.16 no.4
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• pp.682-690
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• 2020

Purpose: This study builds a database by collecting and refining disaster occurrence data and real-time weather and atmospheric data. In conjunction with the public data provided by the API, we propose a service model for the Big Data-based Urban Safety Index. Method: The plan is to provide a way to collect various information related to disaster occurrence by utilizing public data and SNS, and to identify and cope with disaster situations in areas of interest by real-time dashboards. Result: Compared with the prediction model by extracting the characteristics of the local safety index and weather and air relationship by area, the regional safety index in the area of traffic accidents confirmed that there is a significant correlation with weather and atmospheric data. Conclusion: It proposed a system that generates a prediction model for safety index based on machine learning algorithm and displays safety index by sector on a map in areas of interest to users.

• Journal of Convergence for Information Technology
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• v.9 no.10
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• pp.9-15
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• 2019

Recently, in the field of next-generation e-commerce and finance, interest in blockchain-based technologies such as Bitcoin and Ethereum is great. Although the security of blockchain technology is known to be secure, hacking incidents / accidents related to cryptocurrencies are being issued. The main causes were vulnerabilities in the external environment, such as taking over login sessions on cryptocurrency wallets, exposing private keys due to malware infection, and using simple passwords. However, private key management recommends general methods such as utilizing a dedicated application or local backup and physical archiving through document printing. In this paper, we propose a white box password-based private key protection scheme. As a result of safety and performance analysis, we strengthened the security against vulnerability of private key exposure and proved the processing efficiency of existing protocol.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.19-27
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• 2021

With the development of information and communication technology and the increasing use of smart devices, universities are using an electronic attendance-absence management system using smart devices to facilitate efficient attendance management. Currently, the electronic attendance-absence management system has the disadvantage of causing an error in attendance when the Wi-Fi connection is not well established because the student's smartphone independently conducts electronic attendance, and it is difficult to manage attendance because the real-time push message transmission function is excluded. In this paper, we propose an electronic attendance-absence management system to prevent irregular attendance, provide real-time attendance results, and solve delays in attendance processing due to Wi-Fi connection problems. The proposed system can prevent delays in attendance processing as a result of irregular attendance because the instructor's smartphone processes proposed system using the Bluetooth communication function of the instructor's smartphone and the students' smartphone. In addition, it has the advantage of being able to notice management result in real time with the push message server.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.259-267
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• 2020

The purpose of this study is to analyze the effects of computational thinking class using ARCS model to increase students' learning motivation. Then, this study designed the detailed instruction strategy according to each motivation factor(Attention, Relevance, Confidence, Satisfaction) of ARCS through the previous study on computational thinking education and ARCS model. The results of the ARCS test were compared between the experimental group to which the ARCS model was applied and the control group to which the general class was conducted. As a result, students in the experimental group showed significantly higher motivation for learning about computational thinking. In particular, the learning motivation of computer-related majors was significantly higher than that of the control group. In addition, majors were found to have high relevance(R) and non-majors had high satisfaction(S). Therefore, based on these findings, this study suggests an improvement for effective computational thinking class in liberal arts education.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1687-1692
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• 2019

In the era of the fourth industrial revolution, advanced technologies such as the Internet of Things(IoT) and big data are emerging. However, the level of application of IoT to indoor environment is very weak. Therefore, it is necessary to develop a system for analyzing air pollutants or indoor air quality through real-time monitoring using the IoT. This paper implements a system that measures indoor environmental values using Arduino and various sensors, and stores the information obtained from various sensors into a database of server. The information stored in the server was built as a database and utilized in the ventilation system or air cleaner installed in the home or company's room. In the proposed system, it is possible to check the immediate indoor environmental condition through the LED status display of the monitoring sensor module while reducing the cost of the sensor used to implement IoT technology.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1520-1527
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• 2019

Superpixel methods are widely used in the preprocessing stage as a method to reduce computational complexity by simplifying images while maintaining the characteristics of images in the field of computer vision. It is common to generate superpixels with a regular size and form based on the pixel values rather than considering the characteristics of the image. In this paper, we propose a method to generate superpixels considering the characteristics of an image according to the application. The proposed method consists of two steps, and the first step is to oversegment an image so that the boundary information of the image is well preserved. In the second step, superpixels are merged based on similarity to produce the desired number of superpixels, where the form of superpixels are controlled by limiting the maximum size of superpixels. Experimental results show that the proposed method preserves the boundaries of an image more accurately than the existing method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.172-178
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• 2020

In order to recommend contents, the company generally uses collaborative filtering that takes into account both user preferences and video (item) similarities. Such services are primarily intended to facilitate user convenience by leveraging personal preferences such as user search keywords and viewing time. It will also be ranked around the keywords specified in the video. However, there is a limit to analyzing video similarities using limited keywords. In such cases, the problem becomes serious if the specified keyword does not properly reflect the item. In this paper, I would like to propose a system that identifies the characteristics of a video as it is by the system without human intervention, and analyzes and recommends similarities between videos. The proposed system analyzes similarities by taking into account all words (keywords) that have different meanings from training videos, and in such cases, the methods handled by big data clusters are applied because of the large scale of data and operations.