• Journal of dental hygiene science
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• v.12 no.6
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• pp.696-701
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• 2012

The purpose of this study was to determine pH value of some alcoholic drinks sold in Korea and to provide the basic information which can cause dental erosion. Alcoholic drinks commercially sold were purchased from various big markets in Korea. The sorts of drinks tested in this study consisted of 5 brands of beers, 24 brands of makgeollis, 9 brands of wines and 12 brands of sojus. The test groups were selected randomly and the pH of each beverage was determined using a pH meter he each pH was measured. For statistical data, Mann-Whitney test was used to analyze difference for red wine and white wine and Kruskal-Wallis test was used to compare the pH of each test group. The result of this study was as followings: the mean pH of 5 brands of beers was 4.21, that of 24 brands of makgeollis 3.88, of 9 brands of wines 3.34 and of 12 brans of sojus 7.86. Each test group was significantly different (p<0.05). Except for soju groups, the test groups had a low pH value which can cause dental erosion. In terms of comparing between pH value of red wine and white wine, the result of this study represented that the mean pH of red wine was 3.45 and that of white wine was 3.21. This result showed the pH of two kinds of wine had a low pH which can lead to dental erosion and the difference of two wine were significantly different (p<0.05). As a result, some drinks sold in Korea have a high erosive potential on teeth since they have a comparatively low pH expect soju. Hence, when we consume some kinds of alcoholic drinks, we make sure to remember that the alcoholics which had a low pH, can have an effect on dental erosion that mean we should avoid to drink some alcoholic drinks with low pH for long time.

• Journal of agriculture & life science
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• v.43 no.1
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• pp.9-16
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• 2009

A survey which was to find out visitor's behavior and their satisfaction on nature trails in Mt. Jiri National Park was conducted to provide basic information and management methods. According to the survey, major visitors were male with the age between 40 and 50, and the residents of Gyeongnam with relatively high academic background. The visitors had obtained information about natural trail mainly from other visitor, not from internet. The visitors were mainly composed of big group and family. The main purpose of visiting was to escape congested everyday in Yupyeong and Hadong district, and to enjoy mountain climbing in Jungsanri and Baekmudong district. Although there were differences among districts, most visitors were satisfied with natural interpretation program. About 40% were recognized optimum length of nature trails as 2km and less.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.204-204
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• 2016

Thailand had set the National Water Management Strategy which covered main six areas in the next 12 years, i.e., by priority: (1) water for household, (2) water for agricultural and industrial production, (3) water for flood and drought management, (4) water for quality issue, (5) water from forest conservation and soil erosion protection, (6) water resources management. However due to the climate change impact, there is a question for all strategies is whether to complete this mission under future climate change. If the impact affects our target, we have to clarify how to mitigate or to adapt with it. Vulnerability assessment was conducted under the framework of ADB's (with the parameters of exposure, sensitivity and adaptive capacity) and the assessments were classified into groups due to their different characteristic and the framework of the National Water Management Strategy, i.e., water supply (rural and urban), water for development (agriculture and others), water disasters (floods (flash, overflow), drought, water quality). The assessments identified the parameters concerned and weight factors used for each groups via expert group discussions and by using GIS mapping technology, the vulnerability maps were produced. The maps were verified with present water situation data (floods, drought, water quality). From the analysis result of this water resources management strategy, we found that 30% of all projects face the big impacts, 40% with low impact, and 30% for no impact. It is clear that water-related agencies have to carefully take care approximately 70% of future projects to meet water resources management strategy. It is recommended that additional issues should be addressed to mitigate the impact from climate risk on water resource management of the country, i.e., water resources management under new risk based on development scenarios, relationship with area-based problems, priority definition by viewpoints of risk, vulnerability (impact and occurrence probability in past and future), water management system in emergency case and water reserve system, use of information, knowledge and technology in management, network cooperation and exchange of experiences, knowledge, technique for sustainable development with mitigation and adaptation, education and communication systems in risk, new impact, and emergency-reserve system. These issues will be described and discussed.

• Journal of Digital Convergence
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• v.19 no.10
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• pp.241-246
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• 2021

Although there have been many studies on laws and systems for the proliferation of autonomous vehicles, studies on the activation of autonomous vehicles from a strategic perspective are insufficient. This study examines the issues and problem solving methods of autonomous vehicles. Based on this, plans to activate autonomous vehicles from a strategic point of view are proposed. In order to solve the issues and problems of autonomous vehicles, it is necessary to clearly establish legal and institutional standards based on the reinforcement of the safety of autonomous vehicles. In the event of a traffic accident, who is responsible for the accident and responsibility for compensation should be prioritized. Diffusion strategies are established according to the level of autonomous driving for the activation of autonomous vehicles in strategic perspective. In addition, governmental support policies should be used as triggers for initial activation, and marketing mix strategies should be implemented based on segmentation, targeting, and positioning strategies.

• Journal of Convergence for Information Technology
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• v.11 no.12
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• pp.22-29
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• 2021

COVID-19, which has spread around the world, is also affecting local economic industries such as the domestic tourism industry and the service industry. In particular, the quality of life is threatened as safety prevention rules related to infectious diseases such as social distancing have been regularized. The purpose of this study is to analyze the impact on safety quarantine on users of the summer festival at Songho Beach in Haenam, a summer resort. In addition, it protrudes through big data surveys, demographic analysis, and technology analysis on the management of users who have changed in the COVID-19 era. It is expected to be a reference material by utilizing practical data on users in the future. In addition, this study is significant that it has been reviewed for safety and satisfaction for tourists using the summer beach festival through quarantine management using ICT technology in the COVID-19 situation, and needs to be used as good guidelines and examples for this study in the future.

• Journal of Preventive Medicine and Public Health
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• v.54 no.5
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• pp.293-300
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• 2021

The study aims to examine the current status and differences in the burden of disease in Korea during 2008-2018. We calculated the burden of disease for Koreans from 2008 to 2018 using an incidence-based approach. Disability adjusted life years (DALYs) were expressed in units per 100 000 population by adding years of life lost (YLLs) and years lived with disability (YLDs). DALY calculation results were presented by gender, age group, disease, region, and income level. To explore differences in DALYs by region and income level, we used administrative district and insurance premium information from the National Health Insurance Service claims data. The burden of disease among Koreans showed an increasing trend from 2008 to 2018. By 2017, the burden of disease among men was higher than that among women. Diabetes mellitus, low back pain, and chronic lower respiratory disease were ranked high in the burden of disease; the sum of DALY rates for these diseases accounted for 18.4% of the total burden of disease among Koreans in 2018. The top leading causes associated with a high burden of disease differed slightly according to gender, age group, and income level. In this study, we measured the health status of Koreans and differences in the population health level according to gender, age group, region, and income level. This data can be used as an indicator of health equity, and the results derived from this study can be used to guide community-centered (or customized) health promotion policies and projects, and for setting national health policy goals.

• Journal of the Society of Disaster Information
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• v.16 no.4
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• pp.842-848
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• 2020

Purpose: It is important to operate safely and economically in obsolescent power plant facilities. Economical operation is related in the balance of the supply and demand. Safety operation predicts the possible risks in the facilities and then, takes measures to the facilities. For the monitoring of the power plant facilities, we needs several kinds of the sensing system. From the sensors data, we can predict the possible risk. Method: We installed the acoustic, vibration, electric and smoke sensors in the power plant facilities. Using the data, we developed 3 kinds of prediction models, such as, demand prediction, plant engine abnormal prediction model, and risk prediction model. Results: Accuracy of the demand prediction model is over 90%. The other models make a stable operation of the system. Conclusion: For the sustainable operation of the obsolescent power plant, we developed 3 kinds of AI prediction models. The model apply to JB company's power plant facilities.

• Neurospine
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• v.15 no.4
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• pp.329-337
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• 2018

Objective: Machine learning algorithms excel at leveraging big data to identify complex patterns that can be used to aid in clinical decision-making. The objective of this study is to demonstrate the performance of machine learning models in predicting postoperative complications following anterior cervical discectomy and fusion (ACDF). Methods: Artificial neural network (ANN), logistic regression (LR), support vector machine (SVM), and random forest decision tree (RF) models were trained on a multicenter data set of patients undergoing ACDF to predict surgical complications based on readily available patient data. Following training, these models were compared to the predictive capability of American Society of Anesthesiologists (ASA) physical status classification. Results: A total of 20,879 patients were identified as having undergone ACDF. Following exclusion criteria, patients were divided into 14,615 patients for training and 6,264 for testing data sets. ANN and LR consistently outperformed ASA physical status classification in predicting every complication (p < 0.05). The ANN outperformed LR in predicting venous thromboembolism, wound complication, and mortality (p < 0.05). The SVM and RF models were no better than random chance at predicting any of the postoperative complications (p < 0.05). Conclusion: ANN and LR algorithms outperform ASA physical status classification for predicting individual postoperative complications. Additionally, neural networks have greater sensitivity than LR when predicting mortality and wound complications. With the growing size of medical data, the training of machine learning on these large datasets promises to improve risk prognostication, with the ability of continuously learning making them excellent tools in complex clinical scenarios.

• Journal of Convergence for Information Technology
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• v.8 no.6
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• pp.165-171
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• 2018

The most threatening attack that has become a hot topic of recent IT security is APT Attack.. So far, there is no way to respond to APT attacks except by using artificial intelligence techniques. Here, we have implemented a machine learning algorithm for analyzing cyber threat data using machine learning method, using a data set that collects cyber attack cases using Scikit Learn, a big data machine learning framework. The result showed an attack classification accuracy close to 70%. This result can be developed into the algorithm of the security control system in the future.

• Journal of Convergence for Information Technology
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• v.9 no.3
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• pp.16-21
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• 2019

Small and medium-sized Korean companies are currently changing their industrial structure faster than in the past due to various environmental factors (such as securing competitiveness and developing excellent products). In particular, the importance of collecting and utilizing data produced in smart factory environments is increasing as diverse devices related to artificial intelligence are put into manufacturing sites. This paper proposes an artificial intelligence-based smart factory model to improve the process of products produced at the manufacturing site with the recent smart factory. The proposed model aims to ensure the increasingly competitive manufacturing environment and minimize production costs. The proposed model is managed by considering not only information on products produced at the site of smart factory based on artificial intelligence, but also labour force consumed in the production of products, working hours and operating plant machinery. In addition, data produced in the proposed model can be linked with similar companies and share information, enabling strategic cooperation between enterprises in manufacturing site operations.