• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.427-441
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• 2021

Purpose: This study proposes a method for developing a model that predicts the probability of traffic accidents in advance to prevent the most frequent traffic accidents in the military. Method: For this purpose, CRISP-DM (Cross Industry Standard Process for Data Mining) was applied in this study. The CRISP-DM process consists of 6 stages, and each stage is not unidirectional like the Waterfall Model, but improves the level of completeness through feedback between stages. Results: As a result of modeling the same data set as the previously constructed accident investigation data for the entire group, when the classification criterion was 0.5, Significant results were derived from the accuracy, specificity, sensitivity, and AUC of the model for predicting traffic accidents. Conclusion: In the process of designing the prediction model, it was confirmed that it was difficult to obtain a meaningful prediction value due to the lack of data. The methodology for designing a predictive model using the data set was proposed by reorganizing and expanding a data set capable of rational inference to solve the data shortage.

• Journal of The Korean Association of Information Education
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• v.22 no.6
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• pp.711-721
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• 2018

The development of artificial intelligence technology and the shift to a software-driven society are raising the need for digital literacy education on how to access, understand, use, create and share new open content in a variety of sustainable open content. At this point in time, this paper defines the digital literacy as the subliteracy concept for data, tools, and device elements. It is defined as a concept that includes cognitive and non-cognitive abilities and is stratified by computer literacy, ICT literacy, and information literacy. Open content is also defined as teaching-learning materials that can be used and shared freely by anyone, such as the Open Education Resource (OER) and the Open Access movement. Based on the two definitions, a three-step strategy for digital literacy education was developed to select open content in the digital environment, followed by a digital literacy education plan, and finally, an education frame to foster digital literacy capabilities.

• Journal of Convergence for Information Technology
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• v.11 no.1
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• pp.28-33
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• 2021

Since the stock price is a measure of the future value of the company, when analyzing the stock price, the company's growth potential, such as sales and profits, is considered and invested in stocks. In order to set the criteria for selecting stocks, institutional investors look at current industry trends and macroeconomic indicators, first select relevant fields that can grow, then select related companies, analyze them, set a target price, then buy, and sell when the target price is reached. Stock trading is carried out in the same way. However, general individual investors do not have any knowledge of investment, and invest in items recommended by experts or acquaintances without analysis of financial statements or growth potential of the company, which is lower in terms of return than institutional investors and foreign investors. Therefore, in this study, we propose a research method to select undervalued stocks by analyzing ROE, an indicator that considers the growth potential of a company, such as sales and profits, and predict the stock price flow of the selected stock through deep learning algorithms. This study is conducted to help with investment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.99-105
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• 2021

In addition to the OTT video production service represented by Nexflix and YouTube, a personalized recommendation system for content with artificial intelligence has become common. YouTube's personalized recommendation service system consists of two neural networks, one neural network consisting of a recommendation candidate generation model and the other consisting of a ranking network. Netflix's video recommendation system consists of two data classification systems, divided into content-based filtering and collaborative filtering. As the online platform-led content production is activated by the Corona Pandemic, the field of virtual influencers using artificial intelligence is emerging. Virtual influencers are produced with GAN (Generative Adversarial Networks) artificial intelligence, and are unsupervised learning algorithms in which two opposing systems compete with each other. This study also researched the possibility of developing AI platform based on individual recommendation and virtual influencer (metabus) as a core content of OTT in the future.

• Journal of Platform Technology
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• v.9 no.4
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• pp.90-96
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• 2021

Most of the vehicles currently under development and in operation are equipped with various IoT sensors, but some of the factors that cause car accidents are relatively difficult to detect. One of the major risk factors among these factors is black ice. Black ice is one of the factors most likely to cause major accidents, as it can affect all vehicles passing through areas covered with black ice. Therefore, black ice detection technique is essential to prevent major accidents. For this purpose, some studies have been carried out in the past, but unrealistic factors have been reflected in some parts, so research to supplement this is needed. In this paper, we tried to detect black ice by analyzing color images using the CNN technique, and we succeeded in detecting black ice to a certain level. However, there were differences from previous studies, and the reason was analyzed.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1317-1322
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• 2021

Software in the era of the Fourth Industrial Revolution is becoming a key foundation in an intelligent information society. Therefore, it is necessary to study the new direction of manpower training and education that can cope with the times. To this end, the Ministry of Education reorganized the curriculum and is implementing software education based on a logical problem-solving process based on computing thinking skills rather than acquiring general ICT knowledge. However, there is a lack of securing high-quality educational content for software education, and there is also a lack of teaching aids that can be taught in connection with advanced IT technologies. To overcome this, this paper proposes the development of external expansion devices to expand educational content and functions capable of convergent software education such as artificial intelligence using coding robots for software education. Through this, effective software education is possible by improving the curriculum of the existing simple problem-solving method and developing various learning materials.

• Smart Media Journal
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• v.12 no.3
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• pp.120-128
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• 2023

There are various ICT technologies continuously being developed to reduce damage by industrial accidents. And research is being conducted to minimize damage in case of industrial accidents by utilizing sensors, IoT, big data, machine learning and artificial intelligence. In this paper, we propose a design method for a smart device capable of multilateral communication between devices and smart repeater in the communication shaded Areas such as closed areas of industrial sites, mountains, oceans, and coal mines. The proposed device collects worker's information such as worker location and movement speed, and environmental information such as terrain, wind direction, temperature, and humidity, and secures a safe distance between workers to warn in case of a dangerous situation and is designed to be attached to a helmet. For this, we proposed functional requirements for smart devices and design methods for implementing each requirement using sensors and modules in smart device. And we derived evaluation items for performance evaluation of the smart device and proposed an evaluation environment for performance evaluation in mountainous area.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.77-84
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• 2024

In this paper, we propose a method for accurately and rapidly detecting defects in wire harnesses by utilizing computer vision to calculate six crucial measurement values: the length of crimped terminals, the dimensions (width) of terminal ends, and the width of crimped sections (wire and core portions). We employ Harris corner detection to locate object positions from two types of data. Additionally, we generate reference points for extracting measurement values by utilizing features specific to each measurement area and exploiting the contrast in shading between the background and objects, thus reflecting the slope of each sample. Subsequently, we introduce a method using the Euclidean distance and correction coefficients to predict values, allowing for the prediction of measurements regardless of changes in the wire's position. We achieve high accuracy for each measurement type, 99.1%, 98.7%, 92.6%, 92.5%, 99.9%, and 99.7%, achieving outstanding overall average accuracy of 97% across all measurements. This inspection method not only addresses the limitations of conventional visual inspections but also yields excellent results with a small amount of data. Moreover, relying solely on image processing, it is expected to be more cost-effective and applicable with less data compared to deep learning methods.

• Science of Emotion and Sensibility
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• v.24 no.1
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• pp.37-44
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• 2021

A study was conducted on the effects of improving concentration by obscuring the peripheral vision using a blindfold that only covers the left and right sides of the field of view. The blindfold was trapezoidal in shape (5 × 4.8 cm in length and width) and was fixed to the left and right sides of the glasses with fixing clips. The material was a black-colored polypropylene (PP) and weighed 2.3 g including the clip. Qualitative and quantitative evaluations were performed on 50 healthy college students during the 15 days of using a blindfold. The qualitative analysis was performed utilizing a questionnaire regarding the improvement of concentration and the structure of the blindfold. EEG was measured while watching a learning video that required attention for quantitative analysis, and signal power and ERD/S analyses were performed for the mid β band (15-20 Hz) at the F4 position, which was the frontal lobe. The results showed that 40 of the 50 people reported improved concentration when they wore a vision shield, and 80% of the total subjects found it to be effective. From the quantitative evaluation, the ERS peak (p = 0.023) and the ERD + ERS peak value showed a significant difference (p = 0.017). In conclusion, concentration still improved even if only the left and right visual fields were used. Thus, it is expected that blindfolding could be used in various environments that require concentration.

• Journal of The Korean Association of Information Education
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• v.15 no.3
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• pp.413-423
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• 2011

Programming education has the favorable influence on creative logical thinking and problem-solving ability of students. However programming has not been actively taught at the elementary schools. One of the causes is the lack of systematic curriculum. In this paper, we design the curriculum for 'Understanding of Information Processing' in revised ICT educational guidelines using the educational programming language Scratch. We propose curriculum that consists of 4 lessons for 1st and 2nd graders, 5 lessons for 3rd and 4th graders, and 6 lessons for 5th and 6th graders to lesson the cognitive load, and present the instruction plans. Selected group of experts verified our proposed curriculum and instruction plans. According to verification results, we can conclude that almost the area including the targets, educational factors, learning content, amount of learning, instruction plans are appropriate. The curriculum proposed in this paper can help the elementary students learn programming efficiently, and develop their logical thinking, problem-solving ability, creativity, and information processing ability.