• The Korean Journal of Pain
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• v.34 no.3
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• pp.322-331
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• 2021

Background: The present study employed National Health Insurance Data to explore complex regional pain syndrome (CRPS) updated epidemiology in a Korean context. Methods: A CRPS cohort for the period 2009-2016 was created based on Korean Standard Classification of Diseases codes alongside the national registry. The general CRPS incidence rate and the yearly incidence rate trend for every CRPS type were respectively the primary and secondary outcomes. Among the analyzed risk factors were age, sex, region, and hospital level for the yearly trend of the incidence rate for every CRPS. Statistical analysis was performed via the chi-square test and the linear and logistic linear regression tests. Results: Over the research period, the number of registered patients was 122,210. The general CRPS incidence rate was 15.83 per 100,000, with 19.5 for type 1 and 12.1 for type 2. The condition exhibited a declining trend according to its overall occurrence, particularly in the case of type 2 (P < 0.001). On the other hand, registration was more pervasive among type 1 compared to type 2 patients (61.7% vs. 38.3%), while both types affected female individuals to a greater extent. Regarding age, individuals older than 60 years of age were associated with the highest prevalence in both types, regardless of sex (P < 0.001). Conclusions: CRPS displayed an overall incidence of 15.83 per 100,000 in Korea and a declining trend for every age group which showed a negative association with the aging shift phenomenon.

• Journal of the Korea Fashion and Costume Design Association
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• v.23 no.2
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• pp.133-146
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• 2021

It is important to conduct an anthropometric study to develop garment patterns to accommodate the changes found in the body size and type of men in their 30s, to effectively address fit dissatisfaction. Thus, this study aims to explore changes in the lower body sizes and body types of men in their 30s, and provide basic measurements for designing pants patterns. For this purpose, key anthropometric dimensions for the lower body of men in their 30s, which were acquired by the 6th (2010) and 7th (2015) survey conducted by Size Korea, were analyzed using SPSS 24.0 for Windows. Independent sample t-tests were conducted on major lower body sizes to track changes over time. Factor and cluster analyses were used to classify lower body types. From the comparison of the 6th (2010) and 7th (2015) surveys, it was found that the overall lower body size of men in their 30s were increasing in the height-related aspects, circumference, thickness, and width-as well as body weight and BMI. The five factors were derived to determine the typical lower body types of men in their 30s and the body types were classified into three categories through cluster analysis: (1) those with the largest body size, body volume, and obesity, (2) those with smallest body size, lower body volume, and obesity degree, visually the most skinny type, (3) those with BMI and weight that are the smallest, like Type 2, but the main circumference of the lower body is lower. In order to visually look at the statistical analysis, results were presented by producing a avatar based on the main lower body values.

• Geomechanics and Engineering
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• v.24 no.5
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• pp.471-478
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• 2021

Water damage is one of the five disasters that affect the safety of coal mine production. The erosion of rocks by water is a very important link in the process of water inrush induced by fault activation. Through the observation and experiment of fault filling samples, according to the existing rock classification standards, fault sediments are divided into breccia, dynamic metamorphic schist and mudstone. Similar materials are developed with the characteristics of particle size distribution, cementation strength and water rationality, and then relevant tests and analyses are carried out. The experimental results show that the water-rock interaction mainly reduces the compressive strength, mechanical strength, cohesion and friction Angle of similar materials, and cracks or deformations are easy to occur under uniaxial load, which may be an important process of water inrush induced by fault activation. Mechanical experiment of similar material specimen can not only save time and cost of large scale experiment, but also master the direction and method of the experiment. The research provides a new idea for the failure process of rock structure in fault activation water inrush.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.25-34
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• 2022

With the development of online services, the ripple effect of negative comments is increasing, and the damage of cyber violence is rising. Various methods such as filtering based on forbidden words and reporting systems prevent this, but it is challenging to eradicate negative comments. Therefore, this study aimed to increase the accuracy of the classification of negative comments using deep learning and blur the parts corresponding to profanity. Two different conditional training helped decide the number of deep learning layers and filters. The accuracy of 88% confirmed with 90% of the dataset for training and 10% for tests. In addition, Grad-CAM enabled us to find and blur the location of swear words in negative comments. Although the accuracy of classifying comments based on simple forbidden words was 56%, it was found that blurring negative comments through the deep learning model was more effective.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1224-1248
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• 2022

In various sensor network applications, such as climate observation organizations, sensor nodes need to collect information from time to time and pass it on to the recipient of information through multiple bounces. According to field tests, this information corresponds to most of the energy use of the sensor hub. Decreasing the measurement of information transmission in sensor networks becomes an important issue.Compression sensing (CS) can reduce the amount of information delivered to the network and reduce traffic load. However, the total number of classification of information delivered using pure CS is still enormous. The hybrid technique for utilizing CS was proposed to diminish the quantity of transmissions in sensor networks.Further the energy productivity is a test task for the sensor nodes. However, in previous studies, a clustering approach using hybrid CS for a sensor network and an explanatory model was used to investigate the relationship between beam size and number of transmissions of hybrid CS technology. It uses efficient data integration techniques for large networks, but leads to clone attacks or attacks. Here, a new algorithm called SBEA (Snowball Endurance Algorithm) was proposed and tested with a bow. Thus, you can extend the battery life of your WSN by running effective copy detection. Often, multiple nodes, called observers, are selected to verify the reliability of the nodes within the network. Personal data from the source centre (e.g. personality and geographical data) is provided to the observer at the optional witness stage. The trust and reputation system is used to find the reliability of data aggregation across the cluster head and cluster nodes. It is also possible to obtain a mechanism to perform sleep and standby procedures to improve the life of the sensor node. The sniffers have been implemented to monitor the energy of the sensor nodes periodically in the sink. The proposed algorithm SBEA (Snowball Endurance Algorithm) is a combination of ERCD protocol and a combined mobility and routing algorithm that can identify the cluster head and adjacent cluster head nodes.This algorithm is used to yield the network life time and the performance of the sensor nodes can be increased.

• Journal of the Korean Chemical Society
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• v.67 no.5
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• pp.362-377
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• 2023

The purpose of this study was to investigate the effect of semantic mapping as a science text reading strategy on high school students' inferential understanding. For this purpose, eight science text reading classes were conducted a reading strategy using semantic mapping for 46 students in two science-focused classes in the third grade of a high school. To investigate the effects of semantic mapping reading strategy on students' inferential comprehension, students' pre- and post-reading ability tests results were analyzed. In order to find out the change in inferential comprehension, the level of the inferential comprehension was analyzed using the analysis framework for developed in this study. For the classification of inferential comprehension, the levels of the inferential comprehension were converted into scores. The results of the analysis of changes in students' inferential comprehension showed that semantic mapping reading strategy classes influenced the changes in high school students' inference, especially bridge inference and elaborative inference among sub-elements of inferential comprehension.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.126-142
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• 2023

The purpose of this study is to develop unmanned traffic enforcement equipment and standard specifications for the prevention of traffic accidents and violations of the two-wheeled vehicle laws. To this end, we conducted a review of the problems and new technologies of the currently operating unmanned traffic enforcement equipment on two-wheeled vehicles. And through a survey, the feasibility of introducing unmanned traffic enforcement equipment for two-wheeled vehicles and the current status of technology were investigated. In addition, the two-wheeled vehicle enforcement function was implemented through field tests of the development equipment, and the addition of enforcement targets and the number recognition rate were improved through performance improvement. Based on the results of field experiments and performance evaluation, performance standards for unmanned two-wheeled vehicle traffic enforcement equipment were prepared, and in the communication protocol, two-wheeled vehicle-related matters were newly composed in the vehicle classification code and violation items to develop standards.

• Journal of Korean Neurosurgical Society
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• v.66 no.4
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• pp.456-464
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• 2023

Objective : This study aims to investigate the incidence of vestibular schwannoma (VS) and demographic characteristics in Korea using population-based National Health Insurance Service data. Methods : This study analyzed Korean National Health Insurance Service data from 2005 to 2020, based on the International Classification of Diseases, 10th version, Clinical Modification codes D333 and D431. Only those patients who had undergone magnetic resonance imaging and audiologic tests were considered definitive cases. Demographic variables included age, sex, treatment modality, hypertension, diabetics, dyslipidemia, smoking history, alcohol history, and income status. Results : The total number of VS patients was 5751. The average incidence rate was 0.71 per 100000 from 2005 to 2020, and the annual incidence rate increased from 0.33 in 2005 to 1.32 in 2019 but decreased to 0.80 in 2020. Incidence was highest in those aged 60-69 years (1.791) and lowest in those younger than 20 years (0.041). Incidence was higher in females, and the number of patients who received radiosurgery (46.64%) was largest compared to the wait and scan group (37.96%), microsurgery group (12.85%), or the group who received both (2.56%). Diabetes, dyslipidemia, and alcohol consumption increased the risk of VS, while cigarette smoking reduced the risk of VS. Conclusion : The incidence of VS exhibited an increasing trend from 2005 to 2019. Radiosurgery (46.64%) was the most common treatment modality. Diabetes, dyslipidemia, and alcohol consumption increased the risk of VS, while cigarette smoking reduced the risk of VS.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.53-63
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• 2023

This study developed a cognitive impairment predictive model as one of the screening tests for preventing dementia in the elderly by using Automated Machine Learning(AutoML). We used 'Wearable lifelog data for high-risk dementia patients' of National Information Society Agency, then conducted using PyCaret 3.0.0 in the Google Colaboratory environment. This study analysis steps are as follows; first, selecting five models demonstrating excellent classification performance for the model development and lifelog data analysis. Next, using ensemble learning to integrate these models and assess their performance. It was found that Voting Classifier, Gradient Boosting Classifier, Extreme Gradient Boosting, Light Gradient Boosting Machine, Extra Trees Classifier, and Random Forest Classifier model showed high predictive performance in that order. This study findings, furthermore, emphasized on the the crucial importance of 'Average respiration per minute during sleep' and 'Average heart rate per minute during sleep' as the most critical feature variables for accurate predictions. Finally, these study results suggest that consideration of the possibility of using machine learning and lifelog as a means to more effectively manage and prevent cognitive impairment in the elderly.

• Restorative Dentistry and Endodontics
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• v.49 no.1
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• pp.4.1-4.9
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• 2024

Objectives: This study aims to correlate caries-causing microorganism load, lactic acid estimation, and blood groups to high caries risk in diabetic and non-diabetic individuals and low caries risk in healthy individuals. Materials and Methods: This study includes 30 participants divided into 3 groups: Group A, High-risk caries diabetic individuals; Group B, High-risk caries non-diabetic individuals; and Group C, Low-risk caries individuals. The medical condition, oral hygiene, and caries risk assessment (American Dental Association classification and International Caries Detection and Assessment System scoring) were documented. Each individual's 3 mL of saliva was analyzed for microbial load and lactic acid as follows: Part I: 2 mL for microbial quantity estimation using nutrient agar and blood agar medium, biochemical investigation, and carbohydrate fermentation tests; Part II: 0.5 mL for lactic acid estimation using spectrophotometric analysis. Among the selected individuals, blood group correlation was assessed. The χ² test, Kruskal-Wallis test, and post hoc analysis were done using Dunn's test (p < 0.05). Results: Group A had the highest microbial load and lactic acid concentration, followed by Groups B and C. The predominant bacteria were Lactobacilli (63.00 ± 15.49) and Streptococcus mutans (76.00 ± 13.90) in saliva. Blood Group B is prevalent in diabetic and non-diabetic high-risk caries patients but statistically insignificant. Conclusions: Diabetic individuals are more susceptible to dental caries due to high microbial loads and increased lactic acid production. These factors also lower the executing tendency of neutrophils, which accelerates microbial accumulation and increases the risk of caries in diabetic individuals.