• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.280-283
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• 2022

This study aims to identify problems with existing e-learning content and non-face-to-face class methods, improve students' concentration, improve class achievement and educational effectiveness, and propose an artificial intelligence class system design using a web server. By using the function of face and eye tracking using OpenCV to identify attendance and concentration, and by inducing feedback through voice or message to questions asked by the instructor in the middle of class, learners relieve boredom caused by online classes and test by runner If the score is not reached, we propose an artificial intelligence education program system design that can bridge the academic gap and improve academic achievement by providing educational materials and videos for the wrong problem.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.761-768
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• 2023

In the 4th Industrial Revolution, AI(Artificial Intelligence) and IoT(Internet of Things) technologies are being applied to across various fields, with particularly prominence in asset management, disaster management, and meteorological observation. In these fields, it is necessary to accurately determine the real-time and precise tracking of the object's location and status, and to collect various data even in situations that are difficult to detect with existing sensors. In order to address these demands, the use of GNSS(Global Navigation Satellite System) is essential, and this technology enables the efficient management of assets, disaster prevent and response, and accurate weather forecasting. In this paper, we provide the investigated results for the latest trends in the application of GNSS in the fields of asset management, disaster management, and weather observation, among various fields incorporating AI and IoT and analyze them.

• Journal of Korean Academy of Nursing
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• v.54 no.1
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• pp.1-17
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• 2024

Purpose: The significance of the healthcare industry has grown exponentially in recent years due to the impact of the fourth industrial revolution and the ongoing pandemic. Accordingly, this study aimed to examine domestic healthcare-related patents comprehensively. Big data analysis was used to present the trend and status of patents filed in nursing. Methods: The descriptive review was conducted based on Grant and Booth's descriptive review framework. Patents related to nursing was searched in the Korea Intellectual Property Rights Information Service between January 2016 to December 2020. Data analysis included descriptive statistics, phi-coefficient for correlations, and network analysis using the R program (version 4.2.2). Results: Among 37,824 patents initially searched, 1,574 were selected based on the inclusion criteria. Nursing-related patents did not specify subjects, and many patents (41.4%) were related to treatment in the healthcare delivery phase. Furthermore, most patents (56.1%) were designed to increase effectiveness. The words frequently used in the titles of nursing-related patents were, in order, "artificial intelligence," "health management," and "medical information," and the main terms with high connection centrality were "artificial intelligence" and "therapeutic system." Conclusion: The industrialization of nursing is the best solution for developing the healthcare industry and national health promotion. Collaborations in education, research, and policy will help the nursing industry become a healthcare industry of the future. This will prime the enhancement of the national economy and public health.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.5
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• pp.509-515
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• 2022

As the 4th industrial revolution based on ICT is progressing in the manufacturing field, interest in building smart factories that can be flexible and customized according to customer demand is increasing. To this end, it is necessary to maximize the efficiency of factory by performing an automated process in real time through a network communication between engineers and equipment to be able to link the established IT system. It is also necessary to collect and store real-time data from heterogeneous facilities and to analyze and visualize a vast amount of data to utilize necessary information. Therefore, in this study, four types of controllers such as PLC, Arduino, Raspberry Pi, and embedded system, which are generally used to build a smart factory that can connect technologies such as artificial intelligence (AI), Internet of Things (IoT), and big data, are configured. This study was conducted for the development of a program that can collect and store data in real time to visualize and manage information. For communication verification by controller, data communication was implemented and verified with the data log in the program, and 3D monitoring was implemented and verified to check the process status such as planned quantity for each controller, actual quantity, production progress, operation rate, and defect rate.

• Journal of Practical Engineering Education
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• v.14 no.1
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• pp.11-18
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• 2022

As the need for software development manpower increases, various educational programs appear and the popularity of bootcamp style education program for software development increases. However, despite the operations and forms of bootcamp education programs are completely different from the existing software development education programs, there is a lack of research in understanding bootcamp as a software education program. Therefore, this study tried to derive the core elements of the education program through a case study on bootcamp software developer education program. After conducting interviews of 7 members who have completed a series of bootcamp software developer education program X, seven characteristics of bootcamp-type software development education program were derived: intensive theory education, sense of growth and achievement, team project-based learning, community characteristics, peer pressure, stress and fatigue due to short-term learning, and contact-free specialty. Based on the derived characteristics, the advantages and improvements of bootcamp-type education were described, and the direction of the bootcamp-type education program for software developer was discussed.

• Journal of Industrial Convergence
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• v.20 no.5
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• pp.39-59
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• 2022

We analyze the perceptions and requirements of early childhood teachers for artificial intelligence(AI) education to develop an AI education program for 5-year-olds. As for the research methodology, we conducted a survey and an in-depth interview to extract the AI educational elements centering on the analysis stage, the first stage of the ADDIE model. The research result is that first, it is necessary to design a curriculum that combines the contents of early childhood education and AI education to be naturally accepted as AI education for 5-year-olds. Second, an evaluation tool for AI education that can showcase the teacher's reflection should be developed systematically. Third, it is necessary to support a play-centered AI education support and environment for early childhood teachers. Lastly, it is essential to establish a system that can be continuously operated in the field of early childhood education in consideration of AI education in the non-curricular curriculum. It is expected that in the future, a play-oriented AI education program for 5-year-olds will be developed to spread awareness of AI education for infants and present an AI education approach for each age and stage of learners.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.95-103
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• 2023

This paper proposes an artificial intelligence convergence education program for teaching the main concept and principle of Support Vector Machines(SVM) at elementary schools. The developed program, based on Jeju's natural environment theme, explains the decision boundary and margin of SVM by vertical and parallel from 4th grade mathematics curriculum. As a result of applying the developed program to 3rd and 5th graders, most students intuitively inferred the location of the decision boundary. The overall performance accuracy and rate of reasonable inference of 5th graders were higher. However, in the self-evaluation of understanding, the average value was higher in the 3rd grade, contrary to the actual understanding. This was due to the fact that junior learners had a greater tendency to feel satisfaction and achievement. On the other hand, senior learners presented more meaningful post-class questions based on their motivation for further exploration. We would like to find effective ways for artificial intelligence convergence education for elementary school students.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.681-687
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• 2023

The selection technique for optimal operation position selection technique is used to present the initial bow and stern draft with minimum resistance, for achievingthat is, the optimal fuel consumption efficiency at a given operating displacement and speed. The main purpose of this studypaper is to develop a program to select the optimal operating position with maximum energy efficiency under given operating conditions based on the effective power data of the target ship. This program was written as a Python-based GUI (Graphic User Interface) usingbased on artificial intelligence techniques sucho that ship owners could easily use the GUIit. In the process, tThe introduction of the target ship, the collection of effective power data through computational fluid dynamics (CFD), the learning method of the effective power model using deep learning, and the program for presenting the optimal operation position using the deep neural network (DNN) model were specifically explained. Ships are loaded and unloaded for each operation, which changes the cargo load and changes the displacement. The shipowners wants to know the optimal operating position with minimum resistance, that is, maximum energy efficiency, according to the given speed of each displacement. The developed GUI can be installed on the ship's tablet PC and application and used to determineselect the optimal operating position.

• Journal of KIBIM
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• v.14 no.2
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• pp.25-34
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• 2024

This study proposes a new methodology to increase the flexibility and efficiency of the design data evaluation system by combining Building Information Modeling (BIM) technology in the architectural industry, OpenAI's interactive artificial intelligence, and ChatGPT. BIM technology plays an important role in digitally modeling and managing architectural information. Since architectural information is included, research and development are underway to review and evaluate BIM data according to conditions through program development. However, in the process of reviewing BIM design data, if the review criteria or evaluation criteria according to design change occur frequently, it is necessary to update the program anew. In order for designers or reviewers to apply the changed criteria, requesting a program developer will delay time. This problem was studied by using ChatGPT to modify and update the design data evaluation program code in real time. In this study, it is aimed to improve the changing standards and accuracy by enabling programming non-professionals to change the design regulations and calculation standards of the BIM evaluation program system using ChatGPT. In this study, in the BIM-based design certification automation evaluation program, a program in which the automation evaluation method is being studied based on the design certification evaluation manual was first used. In the design certification automation evaluation program, the programming non-majors checked the automation evaluation code by linking ChatGPT, and the changed calculation criteria were created and modified interactively. As a result of the evaluation, the change in the calculation standard was explained to ChatGPT and the applied result was confirmed.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1283-1285
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• 2002

This study is developed vehicle information detector using loop and piezo sensors. This study would analyze the over all problems concerning our road conditions, environmental matters and unique features of our traffic matters; moreover, with these it would develope the hardware, software, car classification algorithm applied by artificial intelligence and traffic monitoring program which can be easily fixed. This can be divided into traffic detecting algorithm and car classification algorithm. Especially, we have developed the car classification algorithm used by C-means Fuzzy Clustering method.