• Journal of the Earthquake Engineering Society of Korea
• /
• v.27 no.5
• /
• pp.213-220
• /
• 2023

Seismic fragility curves play a crucial role in assessing potential seismic losses and predicting structural damage caused by earthquakes. This study compares non-sampling-based methods of seismic fragility curve derivation, particularly the probabilistic seismic demand model (PSDM) and finite element reliability analysis (FERA), both of which require employing sophisticated finite element analysis to evaluate and predict structural damage caused by earthquakes. In this study, a three-dimensional finite element model of API 5L X65, a buried gas pipeline widely used in Korea, is constructed to derive seismic fragility curves. Its seismic vulnerability is assessed using nonlinear time-history analysis. PSDM and a FERA are employed to derive seismic fragility curves for comparison purposes, and the results are verified through a comparison with those from the Monte Carlo Simulation (MCS). It is observed that the fragility curves obtained from PSDM are relatively conservative, which is attributed to the assumption introduced to consider the uncertainty factors. In addition, this study provides a comprehensive comparison of seismic fragility curve derivation methods based on sophisticated finite element analysis, which may contribute to developing more accurate and efficient seismic fragility analysis.

• Journal of Information Technology Services
• /
• v.22 no.4
• /
• pp.97-110
• /
• 2023

In this study, we propose a technique to automatically generate transfer documents using sensor data from livestock manure transfer systems. The research involves analyzing sensor data and applying machine learning techniques to derive optimized outcomes for livestock manure transfer documents. By comparing and contrasting with existing documents, we present a method for automatic document generation. Specifically, we propose the utilization of Gradient Boosting, a machine learning algorithm. The objective of this research is to enhance the efficiency of livestock manure and liquid byproduct management. Currently, stakeholders including producers, transporters, and processors manually input data into the livestock manure transfer management system during the disposal of manure and liquid byproducts. This manual process consumes additional labor, leads to data inconsistency, and complicates the management of distribution and treatment. Therefore, the aim of this study is to leverage data to automatically generate transfer documents, thereby increasing the efficiency of livestock manure and liquid byproduct management. By utilizing sensor data from livestock manure and liquid byproduct transport vehicles and employing machine learning algorithms, we establish a system that automates the validation of transfer documents, reducing the burden on producers, transporters, and processors. This efficient management system is anticipated to create a transparent environment for the distribution and treatment of livestock manure and liquid byproducts.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.16 no.4
• /
• pp.210-219
• /
• 2023

The decline in the rural populace and an aging workforce have led to fatalities due to worsening environments and hazards within vinyl greenhouses. Therefore, it is necessary to automate crop cultivation and disease detection system in greenhouses to prevent labor loss. In this paper, an object detection-based model is used to detect diseased crop in greenhouses. In addition, the system proposed configures the environment of the artificial intelligence model in the cloud to ensure stability. The system captures images taken inside the vinyl greenhouse and stores them in a database, and then downloads the images to the cloud to perform inference based on Yolo-v4 for detection, generating JSON files for the results. Analyze this file and send it to the database for storage. From the experimental results, it was confirmed that disease detection through object detection showed high performance in real environments like vinyl greenhouses. It was also verified that efficient monitoring is possible through the database

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.4
• /
• pp.1123-1146
• /
• 2023

In South Korea, there have been many studies on efficient building-energy management using renewable energy facilities in single zero-energy houses or buildings. However, such management was limited due to spatial and economic problems. To realize a smart zero-energy city, studying efficient energy integration for the entire city, not just for a single house or building, is necessary. Therefore, this study was conducted in the eco-friendly energy town of Chungbuk Innovation City. Chungbuk successfully realized energy independence by converging new and renewable energy facilities for the first time in South Korea. This study analyzes energy data collected from public buildings in that town every minute for a year. We propose a smart city building-energy management model based on the results that combine various renewable energy sources with grid power. Supervised learning can determine when it is best to sell surplus electricity, or unsupervised learning can be used if there is a particular pattern or rule for energy use. However, it is more appropriate to use reinforcement learning to maximize rewards in an environment with numerous variables that change every moment. Therefore, we propose a power distribution algorithm based on reinforcement learning that considers the sales of Energy Storage System power from surplus renewable energy. Finally, we confirm through economic analysis that a 10% saving is possible from this efficiency.

• Journal of Korean Public Health Nursing
• /
• v.37 no.1
• /
• pp.5-24
• /
• 2023

Purpose: The objective of this review was to identify the research trends in Information and Communication Technology (ICT)-based health-related intervention studies for children and adolescents published in South Korea over the past 10 years. Methods: A scoping review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) and the system classification framework for digital health intervention 1.0 of the World Health Organization (WHO) was applied to analyze how technology was being used to support the needs of the health system. Results: A total of 18 studies were included in the final analysis. The participants were mainly children with a variety of diseases. No studies had used innovative technology platforms such as artificial intelligence (AI), the Internet of Things (IoT), and robotics. In addition, the scope of application of the WHO classification criteria was quite limited. Finally, no intervention study considered technical operational indicators, such as the number of website visits and streaming as outcome measurements. Conclusions: Researchers should introduce advanced technology-based strategies to provide customized and professional healthcare services to children and adolescents in South Korea and continue efforts to integrate innovative ICT for various research purposes, subjects, and environments.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.19 no.2
• /
• pp.135-145
• /
• 2023

ChatGPT is an artificial intelligence-based conversation agent developed by OpenAI using natural language processing technology. In this study, an empirical study was conducted on incumbent teachers on the intention to use the newly emerged Chat GPT. First, we studied how accuracy, entertainment, system accessibility, perceived usefulness, and perceived ease of use affect ChatGPT's acceptance intention. In addition, we analyzed whether perceived usefulness and perceived ease of use differ in the intention to accept depending on the digital technology of teachers. As a result of the study, the suitability of the structural equation model was generally good. Accuracy and entertainment were found to have a significant effect on perceived usefulness, and system accessibility was found to have a significant effect on perceived ease of use. In the analysis of teachers' digital technology control effects, it was found that perceived usefulness and perceived ease of use had a control effect between acceptance intentions. It was found that the group with high digital skills of teachers was strongly intended to accept the service regardless of perceived usefulness and ease of use. In the group with low digital skills of teachers, it is thought that ChatGPT's service shows the acceptance intention only when the perceived usefulness and ease of use are high. Therefore, in the group with low digital technology, it is necessary to seek teaching activities such as the development of instructional models using ChatGPT.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.22 no.6
• /
• pp.51-56
• /
• 2022

With the development of industrialization, the amount of food and waste is rapidly increasing. Accordingly, the government is aware of the seriousness and is making efforts in various ways to reduce it. As a part of that, the volume-based food system was introduced, and although there were several trials and errors at the beginning of the introduction, it shows a reduction effect of 20 to 30%. These results suggest that the volume-based food system is being established. However, the waste is caused by foreign substances in the process of recycling resources by collecting them from the 1st collection to the 2nd collection process. Therefore, in this study, to solve these problems fundamentally, artificial intelligence is applied to classify foreign substances and improve them. Due to the nature of food waste, there is a limit to obtaining many images, so we compare several models based on CNNs and classify them as abnormal data, that is, CNN-based models are trained on various types of foreign substances, and then models with high accuracy are selected. We intend to prepare improvement measures for maintenance, such as manpower input to protect equipment and classify foreign substances by applying it.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.17 no.2
• /
• pp.333-342
• /
• 2022

Cellular Automata (CA) is a discrete and abstract computational model that is being applied in various fields. Applicable as an excellent pseudo-random sequence generator, CA has recently developed into a basic element of cryptographic systems. Several studies on CA-based stream ciphers have been conducted and it has been observed that the encryption strength increases when the radius of a CA's neighbor is increased when appropriate CA rules are used. In this paper, among CAs that can be applied as a one-dimensional pseudo-random number sequence generator (PRNG), one-dimensional 5-neighbor CAs are classified according to the connection state of their neighbors, and the ignition relationship of the characteristic polynomial is obtained. Also this paper propose a synthesis algorithm for an asymmetric 1-D linear 5-neighbor MLCA in which the radius of the neighbor is increased by 2 using the one-dimensional 3-neighbor 90/150 CA state transition matrix.

• 한국정보교육학회:학술대회논문집
• /
• 2021.08a
• /
• pp.261-267
• /
• 2021

This study examines the purpose and goals of ICT education, compares them with current software and artificial intelligence-oriented information curriculum, analyzes foreign SW curriculum, extracts learning topics and elements, and analyzes whether the current information curriculum is presented effectively. As a result of the analysis, the number of information-related courses in Korea is currently lower than in other countries, which has reduced the number of basic computer applications and underlying software applications such as presentations and spreadsheets covered in ICT training in the past. In addition, compared to Korea's curriculum where information education begins in the fifth grade of elementary school, other countries are introducing information education from the first grade to the third grade of elementary school. Therefore, active discussions on the expansion of the number of information education, the timing of introduction of information education, and the utilization of basic computers are needed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.328-329
• /
• 2021

Newly, the fourth industrial revolution is a way of describing the blurring of boundaries between the physical, digital, and biological worlds. It's a fusion of advances in AI (artificial intelligence), robotics, the IoT (Internet of Things), 3d printing, genetic engineering, quantum computing, and other technologies. At the world economic forum in Davos, switzerland, in january 2016, chairman professor klaus schwab proposed the fourth industrial revolution for the first time. In order to apply the AHP (analytic hierarchy process) analysis method, the first stage factors were designed as Natural, Water, Earth and Atom energy. In addition, the second stage factors were organized into 9 detailed energies presented in the conceptual model. Thus, we present the theoretical and practical implications of these results.