• Journal of Life Science
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• v.19 no.11
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• pp.1568-1574
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• 2009

The purpose of this study was to investigate whether group III muscle afferents play an important role eliciting abnormal blood pressure response mediated during passive muscle stretch in prehypertensive individuals. Eleven middle-aged prehypertensive men (average BP 133/80 mmHg) and nine middle-aged normotensive men (average BP 119/74 mmHg) participated in this study. After 1 min rest baseline data collection, the subject's foot was flexed (dorsiflexion) by an automated cybex for one minute. Systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial blood pressure (MAP), heart rate, stroke volume, cardiac output, and total peripheral resistance were continuously measured on a beat-by-beat basis from a finger via a Finapres device for 1 minute. To evaluate the role of mechanoreflex, a component of exercise pressor reflex, SBP, DBP, and MAP responses over the course of time were examined. The results showed that the pressor response mediated by the muscle mechanoreflex was faster in prehypertensive individuals compared to the normotensive individuals. The substantial pressor response was observed within mean 20 sec of the onset of passive stretch in prehypertension, while mean 45 sec in normotension (p<0.05). It is concluded that excessive pressor response produced during exercise in prehypertension may be due to the dysfunction of the mechano-receptors.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.7
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• pp.848-857
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• 2018

Recently, around the world, active development of new renewable energy sources including solar power, waves, and fuel cells, etc. has taken place. Particularly, floating offshore wind farms have been developed for saving costs through large scale production, using high-quality wind power and minimizing noise damage in the ocean area. The development of floating wind farms requires an evaluation of the Maritime Safety Audit Scheme under the Maritime Safety Act in Korea. Floating wind farms shall be assessed by applying the line and area concept for systematic development, management and utilization of specified sea water. The development of appropriate evaluation methods and standards is also required. In this study, proper standards for marine traffic surveys and assessments were established and a systemic treatment was studied for assessing marine spatial area. First, a marine traffic data collector using AIS or radar was designed to conduct marine traffic surveys. In addition, assessment methods were proposed such as historical tracks, traffic density and marine traffic pattern analysis applying the line and area concept. Marine traffic density can be evaluated by spatial and temporal means, with an adjusted grid-cell scale. Marine traffic pattern analysis was proposed for assessing ship movement patterns for transit or work in sea areas. Finally, conceptual design of a Marine Traffic and Safety Assessment Solution (MaTSAS) was competed that can be analyzed automatically to collect and assess the marine traffic data. It could be possible to minimize inaccurate estimation due to human errors such as data omission or misprints through automated and systematic collection, analysis and retrieval of marine traffic data. This study could provides reliable assessment results, reflecting the line and area concept, according to sea area usage.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.307-325
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• 2023

Due to the prolonged COVID-19 pandemic, the frequency of people who are tired of living indoors visiting nearby mountains and national parks to relieve depression and lethargy has exploded. There is a place where thousands of people who came out of nature stop walking and breathe and rest, that is the mineral spring. Even in mountains or national parks, there are about 600 mineral springs that can be found occasionally in neighboring parks or trails in the metropolitan area. However, due to irregular and manual water quality tests, people drink mineral water without knowing the test results in real time. Therefore, in this study, we intend to develop a model that can predict the quality of the spring water in real time by exploring the factors affecting the quality of the spring water and collecting data scattered in various places. After limiting the regions to Seoul and Gyeonggi-do due to the limitations of data collection, we obtained data on water quality tests from 2015 to 2020 for about 300 mineral springs in 18 cities where data management is well performed. A total of 10 factors were finally selected after two rounds of review among various factors that are considered to affect the suitability of the mineral spring water quality. Using AutoML, an automated machine learning technology that has recently been attracting attention, we derived the top 5 models based on prediction performance among about 20 machine learning methods. Among them, the catboost model has the highest performance with a prediction classification accuracy of 75.26%. In addition, as a result of examining the absolute influence of the variables used in the analysis through the SHAP method on the prediction, the most important factor was whether or not a water quality test was judged nonconforming in the previous water quality test. It was confirmed that the temperature on the day of the inspection and the altitude of the mineral spring had an influence on whether the water quality was unsuitable.