• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.2
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• pp.95-101
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• 2023

Globally, the importance of utilization and management of marine spatial information is being maximized, and analyzing such data is emerging as a major driving force for R&D. In Korea, it is expected that collecting marine data from the past to the present and extracting its value will play an important role in the development of science in Korea in the future. In particular, marine static data constitutes a huge big database, and it is necessary to store and store the collected data without loss as high data collection costs and high-level observation techniques are required. In addition, the Disaster Safety Intelligence Convergence Center's "Marine Digital Twin Establishment and Utilization-Based Technology Research" task requires collection and analysis of marine data, so this paper conducts a current status survey of static marine data. And we present a series of algorithms that collect and store them in a database.

• Coupled systems mechanics
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• v.11 no.6
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• pp.505-524
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• 2022

Floods represent extreme hydrological phenomena that affect populations, environment, social, political, and ecological systems. After the catastrophic floods that have hit Europe and the World in recent decades, the flood problem has become more current. At the EU level, a legal framework has been put in place with the entry into force of Directive 2007/60/EC on Flood Risk Assessment and Management (Flood Directive). Two years after the entry into force of the Floods Directive, Bosnia and Herzegovina (B&H), has adopted a Regulation on the types and content of water protection plans, which takes key steps and activities under the Floods Directive. The "Methodology for developing flood hazard and risk maps" (Methodology) was developed for the territory of Bosnia and Herzegovina, following the methodology used in the majority of EU member states, but with certain modifications to the country's characteristics. Accordingly, activities for the preparation of the Preliminary Flood Risk Assessment for each river basin district were completed in 2015 for the territory of Bosnia and Herzegovina. Activities on the production of hazard maps and flood risk maps are in progress. The results of probable climate change impact model forecasts should be included in the preparation of the Flood Risk Management Plans, which is the subsequent phase of implementing the Flood Directive. By the foregoing, the paper will give an example of the development of the hydrodynamic model of the Zujevina River, as well as the development of hazard and risk maps. Hazard and risk maps have been prepared for medium probability floods of 1/100 as well as for high probability floods of 1/20. The results of LiDAR (Light Detection and Ranging) recording were used to create a digital terrain model (DMR). It was noticed that there are big differences between the flood maps obtained by recording LiDAR techniques in relation to the previous flood maps obtained using georeferenced topographic maps. Particular attention is given to explaining the Methodology applied in Bosnia and Herzegovina.

• Imaging Science in Dentistry
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• v.52 no.4
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• pp.383-391
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• 2022

Purpose: Periodontitis, the most prevalent chronic inflammatory condition affecting teeth-supporting tissues, is diagnosed and classified through clinical and radiographic examinations. The staging of periodontitis using panoramic radiographs provides information for designing computer-assisted diagnostic systems. Performing image segmentation in periodontitis is required for image processing in diagnostic applications. This study evaluated image segmentation for periodontitis staging based on deep learning approaches. Materials and Methods: Multi-Label U-Net and Mask R-CNN models were compared for image segmentation to detect periodontitis using 100 digital panoramic radiographs. Normal conditions and 4 stages of periodontitis were annotated on these panoramic radiographs. A total of 1100 original and augmented images were then randomly divided into a training (75%) dataset to produce segmentation models and a testing (25%) dataset to determine the evaluation metrics of the segmentation models. Results: The performance of the segmentation models against the radiographic diagnosis of periodontitis conducted by a dentist was described by evaluation metrics(i.e., dice coefficient and intersection-over-union [IoU] score). MultiLabel U-Net achieved a dice coefficient of 0.96 and an IoU score of 0.97. Meanwhile, Mask R-CNN attained a dice coefficient of 0.87 and an IoU score of 0.74. U-Net showed the characteristic of semantic segmentation, and Mask R-CNN performed instance segmentation with accuracy, precision, recall, and F1-score values of 95%, 85.6%, 88.2%, and 86.6%, respectively. Conclusion: Multi-Label U-Net produced superior image segmentation to that of Mask R-CNN. The authors recommend integrating it with other techniques to develop hybrid models for automatic periodontitis detection.

• The Journal of Korean Academy of Orthopedic Manual Physical Therapy
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• v.29 no.2
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• pp.31-38
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• 2023

Background: The aim of this study was to compare the effects of taping techniques on menstrual pain, body temperature, and menstrual symptoms in women of reproductive age. Methods: This study targeted 40 female students enrolled at G university with menstrual pain rated above 5 on the visual analog scale (VAS). The participants were randomly assigned to four groups: the Kinesio taping, spiral taping, non-steroidal anti-inflammatory drug, and control groups. The intervention was applied one day after the onset of menstruation, and menstrual pain, menstrual symptoms, and body temperature were measured before the intervention and 24 hours after the intervention application. We measured menstrual pain using the VAS. Additionally, we evaluated menstrual symptoms using the menstruation symptom scale and measured body temperature of the abdomen and feet using digital infrared thermal imaging. Results: After the intervention, all three experimental groups showed significant improvement in menstrual pain and menstrual symptoms compared to the control group, and there was no significant difference among the three groups. After applying Kinesio taping, there was a slight decrease in the temperature difference between the abdomen and feet, but no statistically significant difference was observed. Conclusion: The results of this study demonstrated that kisesio and spiral taping have similar effects as with anti-inflammatory medication in relieving menstrual pain and menstrual symptoms. Taping can be considered as an effective method to replace medications in order to alleviate menstrual pain.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.127-135
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• 2023

Nowadays, the number of patients committing suicide due to depression and stress is rapidly increasing. In addition, if stress and depression last for a long time, they are dangerous factors that can cause heart disease, brain disease, and high blood pressure. However, no matter how modern medicine has developed, it is a very difficult situation for patients with depression and heart disease without special drugs or treatments. Therefore, in many countries around the world, studies are being actively conducted to determine patients at risk of depression and patients at risk of suicide at an early stage using electrocardiogram, oxygen saturation, and brain wave analysis functions. In this paper, in order to analyze these problems, a computer simulation was performed to determine heart disease risk patients by establishing heart disease hypothesis data. In particular, in order to improve the predictive rate of heart disease by more than 10%, a simulation using fuzzy inference was performed.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.755-761
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• 2023

As digital transformation accelerates, the proportion of non-face-to-face services in financial services is also increasing. Recently, user experience has emerged to secure competitiveness in mobile services, and analysis techniques to improve user experience have emerged. User review data, one of the data used for quantitative evaluation, contains a lot of unnecessary information, which is time-consuming to derive improvement directions. Therefore, this study aims to develop a UX analysis system based on the hierarchy of UX needs by using a cosine similarity algorithm and analyze user review data of Kookmin Bank, Woori Bank, Kakao Bank, and Toss for verification. This study proved that the developed UX analysis system is a system that can effectively analyze UX through the analysis of user review data. The system of this study is expected to be easily used to identify improvement plans for the hierarchy of UX needs in an agile organization that needs to quickly reflect customer feedback.

• Journal of Auto-vehicle Safety Association
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• v.14 no.1
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• pp.26-31
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• 2022

Changwon City has the second highest accident rate with 79.6 according to the city bus accident rate. In fact, 250,000 people use the city bus a day in Changwon, The number of accidents is increasing gradually. In addition, a recent fire accident occurred in the engine room of a city bus (CNG) in Changwon, which has gradually expanded the public's anxiety. In the case of business vehicles, the government conducts inspections with a short inspection cycle for the purpose of periodic safety inspections, etc., but it is not in the monitoring stage. In the case of city buses, the operation records are monitored using Digital Tacho Graph (DTG). As such, driving records, methods, etc. are continuously monitored, but inspections are conducted every six months to ascertain the safety and performance of automobiles. It is difficult to identify real-time information on automobile safety. Therefore, in this study, individual automobile management solutions are presented through machine learning techniques of inspection results based on driving records or habits by linking DTG data and Vehicle Inspection Management System (VIMS) data for city buses in Changwon from 2019 to 2020.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.246-248
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• 2021

Recently data has been transformed into a data economy and society that acts as a catalyst for the development of all industries and the creation of new value, and COVID-19 is accelerating digital transformation. In the upcoming intelligent Internet of Things era, the availability of decentralized systems such as blockchain and mixnet is emerging to solve the security problems of centralized systems that makes it difficult to utilize data safely and efficiently. Blockchain manages data in a transparent and decentralized manner and guarantees the reliability and integrity of the data through agreements between participants, but the transparency of the data threatens the privacy of users. On the other hand, mixed net technology for protecting privacy protects privacy in distributed networks, but due to inefficient power consumption efficiency and processing speed issues, low cost, light weight, low power consumption Internet Hard to use. In this paper, we analyze the limitations of conventional mixed-net technology and propose a mixed-net technology method for low power consumption, high speed, and the Internet of things.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.67-77
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• 2023

This study represents an innovative research conducted in the smart farm environment, developing a deep learning-based disease and pest detection model and applying it to the Intelligent Internet of Things (IoT) platform to explore new possibilities in the implementation of digital agricultural environments. The core of the research was the integration of the latest ImageNet models such as Pseudo-Labeling, RegNet, EfficientNet, and preprocessing methods to detect various diseases and pests in complex agricultural environments with high accuracy. To this end, ensemble learning techniques were applied to maximize the accuracy and stability of the model, and the model was evaluated using various performance indicators such as mean Average Precision (mAP), precision, recall, accuracy, and box loss. Additionally, the SHAP framework was utilized to gain a deeper understanding of the model's prediction criteria, making the decision-making process more transparent. This analysis provided significant insights into how the model considers various variables to detect diseases and pests.

• Journal of The Korean Astronomical Society
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• v.56 no.1
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• pp.59-73
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• 2023

The second generation of stars in the globular clusters (GCs) of the Milky Way (MW) exhibit unusually high N, Na, or Al, compared to typical Galactic halo stars at similar metallicities. The halo field stars enhanced with such elements are believed to have originated in disrupted GCs or escaped from existing GCs. We identify such stars in the metallicity range -3.0 < [Fe/H] < 0.0 from a sample of ~36,800 giant stars observed in the Sloan Digital Sky Survey and Large Sky Area Multi-Object Fiber Spectroscopic Telescope survey, and present their dynamical properties. The N-rich population (NRP) and N-normal population (NNP) among our giant sample do not exhibit similarities in either in their metallicity distribution function (MDF) or dynamical properties. We find that, even though the MDF of the NRP looks similar to that of the MW's GCs in the range of [Fe/H] < -1.0, our analysis of the dynamical properties does not indicate similarities between them in the same metallicity range, implying that the escaped members from existing GCs may account for a small fraction of our N-rich stars, or the orbits of the present GCs have been altered by the dynamical friction of the MW. We also find a significant increase in the fraction of N-rich stars in the halo field in the very metal-poor (VMP; [Fe/H] < -2.0) regime, comprising up to ~20% of the fraction of the N-rich stars below [Fe/H] = -2.5, hinting that partially or fully destroyed VMP GCs may have in some degree contributed to the Galactic halo. A more detailed dynamical analysis of the NRP reveals that our sample of N-rich stars do not share a single common origin. Although a substantial fraction of the N-rich stars seem to originate from the GCs formed in situ, more than 60% of them are not associated with those of typical Galactic populations, but probably have extragalactic origins associated with Gaia Sausage/Enceladus, Sequoia, and Sagittarius dwarf galaxies, as well as with presently unrecognized progenitors.