• Health Policy and Management
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• v.26 no.3
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• pp.185-194
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• 2016

Background: The purpose of this study is to forecast changes in the prevalence of chronic diseases and health expenditure by age group. Methods: Based on the Future Elderly Model, this study projects the size of Korean population, the prevalence of chronic diseases, and health expenditure over the 2014-2040 period using two waves (2012, 2013) of the Korea Health Panel and National Health Insurance Service database. Results: First, the prevalence of chronic diseases increases by 2040. The population with hypertension increases 2.04 times; the diabetes increases 2.43 times; and the cancer increases 3.38 times. Second, health expenditure on chronic diseases increases as well. Health expenditure on hypertension increases 4.33 times (1,098,753 million won in 2014 to 4,760,811 million won in 2040); diabetes increases 5.34 times (792,444 million won in 2014 to 4,232,714 million won in 2040); and cancer increases 6.09 times (4,396,223 million won in 2014 to 26,776,724 million won in 2040). Third, men and women who belong to the early middle-aged group (44-55 years old) as of 2014, have the highest increase rate in health spending. Conclusion: Most Korean literature on health expenditure estimation employs a macro-simulation approach and does not fully take into account personal characteristics and behaviors. Thus, this study aims to benefit medical administrators and policy makers to frame effective and targeted health policies by analyzing personal-level data with a microsimulation model and providing health expenditure projections by age group.

• The Plant Pathology Journal
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• v.32 no.1
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• pp.1-7
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• 2016

Responses of Botryosphaeria dothidea to interrupted wetness periods were investigated under in vivo and in vitro conditions. Conidia of B. dothidea were allowed to germinate on apple fruits under wetting condition at $25^{\circ}C$ for 5 hr. They were air-dried for 0, 1, 2 or 4 hr, and then rewetted at $25^{\circ}C$ for 5 hr. Following an initial wetness period of 5 hr, 83% of the conidia germinated. The percent conidial germination increased to 96% when wetting was extended continuously another 5 hr. However, no further conidial germination was observed when wetting was interrupted by dry periods of 1, 2 and 4 hr, resulting in 83, 81 and 82%, respectively. The mean length of the germ tubes was $37{\mu}m$ after 5 hr of wetting and elongated to $157{\mu}m$ after 10 hr of continuous wetting. On the other hand, interruption of wetting by a dry period of 1 hr or longer after the 5 hr of initial wetting arrested the germ tube elongation at approximately $42{\mu}m$ long. Prolonged rewetting up to 40 hr did not restore germ tube elongation on slide glasses under substrate treatments. Model simulation using weather data sets revealed that ending infection periods by a dry period of at least 1 hr decreased the daily infection periods, avoiding the overestimation of infection warning. This information can be incorporated into infection models for scheduling fungicide sprays to control apple white rot with fewer fungicide applications.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.3
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• pp.156-162
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• 2001

In order to monitor local climatic information, twelve automated weather stations (AWS) were installed in alpine area by the Alpine Agricultural Experiment Station, Rural Development Administration (RDA), at the field of major crop located in around highland area, and collected data from 1993 to 2000. Hourly measurements of air and soil temperature (underground 10 cm,20 cm), relative humidity, wind speed and direction, precipitation, solar radiation and leaf wetness were automatically performed and the data could be collected through a public phone line. Datalogger was selected as CR10X (Campbell scientific, LTD, USA) out of consideration for sensers' compatibility, economics, endurance and conveniences. All AWS in alpine area were combined for net work and daily climatic data were analyzed in text and graphic file by program (Chumsungdae, LTD) on 1 km $\times$ 1 km grid tell basis. In this analysis system, important multi-functionalities, monitoring and analysis of local climatic information in alpine area was emphasized. The first objective was to obtain the output of a real time data from AWS. Secondly, daily climatic normals for each grid tell were calculated from geo-statistical relationships based on the climatic records of existing weather stations as well as their topographical informations. On 1 km $\times$ 1 km grid cell basis, real time climatic data from the automated weather stations and daily climatic normals were analyzed and graphed. In the future, if several simulation models were developed and connected with this system it would be possible to precisely forecast crop growth and yield or plant disease and pest by using climatic information in alpine area.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.131-138
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• 2022

Novel Coronavirus (COVID-19) is viewed as one of the main general wellbeing theaters on the worldwide level all over the planet. Because of the abrupt idea of the flare-up and the irresistible force of the infection, it causes individuals tension, melancholy, and other pressure responses. The avoidance and control of the novel Covid pneumonia have moved into an imperative stage. It is fundamental to early foresee and figure of infection episode during this troublesome opportunity to control of its grimness and mortality. The entire world is investing unimaginable amounts of energy to fight against the spread of this lethal infection. In this paper, we utilized machine learning and deep learning techniques for analyzing what is going on utilizing countries shared information and for detecting the climate factors that effect on spreading Covid-19, such as humidity, sunny hours, temperature and wind speed for understanding its regular dramatic way of behaving alongside the forecast of future reachability of the COVID-2019 around the world. We utilized data collected and produced by Kaggle and the Johns Hopkins Center for Systems Science. The dataset has 25 attributes and 9566 objects. Our Experiment consists of two phases. In phase one, we preprocessed dataset for DL model and features were decreased to four features humidity, sunny hours, temperature and wind speed by utilized the Pearson Correlation Coefficient technique (correlation attributes feature selection). In phase two, we utilized the traditional famous six machine learning techniques for numerical datasets, and Dense Net deep learning model to predict and detect the climatic factor that aide to disease outbreak. We validated the model by using confusion matrix (CM) and measured the performance by four different metrics: accuracy, f-measure, recall, and precision.

• Genomics & Informatics
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• v.21 no.4
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• pp.50.1-50.9
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• 2023

Vaccine development is one of the key efforts to control the spread of coronavirus disease 2019 (COVID-19). However, it has become apparent that the immunity acquired through vaccination is not permanent, known as the waning effect. Therefore, monitoring the proportion of the population with immunity is essential to improve the forecasting of future waves of the pandemic. Despite this, the impact of the waning effect on forecasting accuracies has not been extensively studied. We proposed a method for the estimation of the effective immunity (EI) rate which represents the waning effect by integrating the second and booster doses of COVID-19 vaccines. The EI rate, with different periods to the onset of the waning effect, was incorporated into three statistical models and two machine learning models. Stringency Index, omicron variant BA.5 rate (BA.5 rate), booster shot rate (BSR), and the EI rate were used as covariates and the best covariate combination was selected using prediction error. Among the prediction results, Generalized Additive Model showed the best improvement (decreasing 86% test error) with the EI rate. Furthermore, we confirmed that South Korea's decision to recommend booster shots after 90 days is reasonable since the waning effect onsets 90 days after the last dose of vaccine which improves the prediction of confirmed cases and deaths. Substituting BSR with EI rate in statistical models not only results in better predictions but also makes it possible to forecast a potential wave and help the local community react proactively to a rapid increase in confirmed cases.

• Journal of Acupuncture Research
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• v.21 no.1
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• pp.1-20
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• 2004

Pulse-feeling took its origin from making a diagnosis along meridians in the course of discovering and forming meridians and for a long time its meaning was mixed with meridians in the course of recognizing "The Pulse" then was separated from meridians in the early days of Western Han Dynasty. Ancient pulse-feeling methods are pulse-feeling method by the twelve regular meridians, pulse-feeling method by three regions and nine modes, pulse-feeling method by Inyeong(人迎) and Chon-gu(寸口), etc. Pulse-feeling was changed in proportion to diagnostic purpose and method of treating and if method and region of pulse-feeling is arranged, we will infer correlation between meridians and pulse-feeling and will infer transitional system of past pulse-feeling and will forecast transition of future pulse-feeling. As the result that I study the transition of the above three pulse-feeling methods of meridians diagnosis: 1. Three pulse-feeling methods of meridians diagnosis flowed into diagnostic method by taking pulse of setting six region for Chon(寸), Gwan(關) and Cheok(尺), i.e. the Chon[寸] spot pulse of $\ll$Nan-gyeong$\gg$ and were changed into diagnostic method being fit for use of five Su points, The Front-Mo points and Back-Su points that grasp the pathology of mutual internal organs and treat the disease. 2. Today it is suggesting the transition of another pulse-feeling method that do not apply diagnostic method by taking pulse of setting six region for Chon(寸), Gwan(關) and Cheok(尺), i.e. the Chon[寸] spot pulse of $\ll$Nan-gyeong$\gg$ to 19C Sasang(四象) Constitutional Medicine or 20C Eight Constitutional Medicine.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.294-297
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• 2015

Recently, big data analysis which is based on machine learning has been gained a lot of attentions in various fields. Especially, agriculture is considered as one promising field that machine learning algorithm can be efficiently utilized and accordingly, lots of works have been done so far. However, most of the researches are focusing on the forecast of weather or analysis of genome, and machine learning algorithm for livestock management, especially which uses individual data of livestocks, e.g., temperature and movement, are not properly investigated yet. In this work, we propose fast abnormal livestock detection algorithm based on machine learning, more specifically expectation maximization, such that livestock which has problem can be efficiently and promptly found. In our proposed scheme, livestocks are divided into two clusters using expectation maximization based on their bionic data and the abnormal livestock can be detected by comparing the size of two clusters. Especially, we divide the case in which single livestock has problem and the case in which livestocks have epidemic such that fast response is enabled when epidemic case. Moreover, our algorithm does not need statistical information.

• Journal of Food Hygiene and Safety
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• v.27 no.4
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• pp.339-348
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• 2012

The purpose of this study is to predict the economic size of foods-for-elderly market, which will be valuable information for establishing related policy and backup system. After setting the scope of related industry, detailed information for current market situation was investigated and a systematic forecast for market changes in the future was performed. Economic growth, changes in consumer expenditure and economic status of the elderly, current subscription of medical insurance and saving for pension were reflected. In addition, a survey toward related firms was completed and changes in aged population and incidence of chronic disease in the elderly were taken into account. Results show that the annual growth rate of the market was predicted to be the minimum 4.54% through the maximum 8.32% from 2010 to 2025 and its market size was forecasted to be the minimum 7,073 ten million won through the maximum 10,976 ten million won. It is expected that the market of foods-for-elderly will grow rapidly with development of foods technology and fast increase of aged population. Especially, growth of health functional foods and foods for special dietary uses for elderly will be distinguished. However, it seems that related firms are on the hedge, watching current trend of the related industry. This may results in insufficient supply against the demand. Therefore, policy for foods-for-elderly should be introduced and systematically administered, including R&D support, standardization and authentication for foods-for-elderly, construction of related database system.

• The Journal of Korean Medical History
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• v.18 no.2
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• pp.197-227
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• 2005

Heojun was the top scientist on Medicine in the 16th and 17th centuries and wrote the Dongeubogam describing the top-level medical theory and technology. So far, his outlook on nature has been disregarded even though his medicine is still effective. Through this study, I would like to know if his outlook on nature as well as his medicine is still effective. The conclusions are as follows: 1. According to his output, the origin of the universe started from the spinning of One Gi(一氣) which is quite different from Hawking's theory. Hawking assumed that the origin of the universe started from the Big-bang and will end to the Big-crunch. However, the current report on the origin of a star is quite similar to Heojun's theory and we acknowledge that his view on the origin of the universe is still effective. 2. According to his output, the universe repeats expanding and contracting forever while Hawking assumed it will come to the end, the Big-crunch, based on the expanding universe theory. Some scientists assists that Hawking's assumption should have some contradictions. Now, we acknowledge that Heojun's universal cycling theory which corresponds with modern physical theories is still effective, which would lead to a new environmental movement. 3. His view on the structure of the universe is quite different from the output of the current science, which results from his thought that the nature should be reviewed from the point of human's view. His view on the structure will be able to be updated based on the output of the current science. 4. The universe analogy started from the East Asian area as well as the Greek and Roman area in the ancient. The idea has disappeared since the scientific revolution era in the West while the idea has been deepened and abundant in the East and has become one of the major philosophical bases. Heojun emphasized its importance from the beginning of his book. 5. The nation analogy has been popular all times and places. According to his output, governing a country is like controlling one's body. 6. According to Needham's output, the universe analogy and the nation analogy were based on the ancient developed alchemy. And Harper assumed that Taiosm was based on the macrobiotic hygiene which was developed by the ancient developed alchemists. We acknowledge that xian(仙) cult, macrobiotic hygiene, medicine, alchemy and the ancient philosophy started from our ancients. Heojun's output restored our ancient tradition by combining the macrobiotic hygiene and philosophy with medicine. 7. Roughly predicting yearly weather would be unacceptable by the current scientist but Heojun's yearly weather forecast is still used in the clinic and seems effective to prepare from any epidemic disease. 8. 'Day and Night' and Four seasons are the most important factors to the macrobiotic hygiene according to the Dongeubogam. The new environmental movements should be based on the most important factors, otherwise the human beings as well as the environment would fail to survive. 9. Wind, Coldness, Heat, Humidity, Dryness and Fire represents weather. The six weather factors represent one of six phases of a year which is decided by the areal factors. Heojun preferred the six factors generated in the body itself to them from the outside. He thought a human being was a universe and the six factors generated in the body responded to the factors of the outside. 10. According to his output, Heat and Humidity are the most important factors which make a human being ill. 11. Life span, disease, food, and dwelling are dependent upon the geographical feature, according to Heojun's output. In addition, one's appearance and his five viscera and the six entrails depend on the food as well as the geographical feature. 12. Heath is related with the environment and they effects upon each other. If one is weak, he will be deeply effected by the nature. On the other hand, if one is strong, he will effect on the nature. That's why people live together. 13. According to Heojun's work, the society is an important factor comprising the environment. During a peaceful era, the society becomes stable and human beings are stable as well while they will be on fire during a chaotic era. 14. Medicine deals with human beings who live in the nature, so any medical book cannot be excellent unless it has any description on the nature. Heojun's outlook on the nature turned out to be logical and suitable even from the point of the current view and it is still effective as if his clinical knowledge and technology are still effective. Something unsuitable may be substituted with the output of the current science.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.4
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• pp.199-205
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• 2001

This study was conducted to figure out temperature profiles of a partially developed paddy rice canopy, which are necessary to run plant disease forecasting models. Air temperature over and within the developing rice canopy was monitored from one month after transplanting (June 29) to just before heading (August 24) in 1999 and 2001. During the study period, the temporal march of the within-canopy profile was analyzed and an empirical formula was developed for simulating the profile. A partially developed rice canopy temperature seemed to be controlled mainly by the ambient temperature above the canopy and the water temperature beneath the canopy, and to some extent by the solar altitude, resulting in alternating isothermal and inversion structures. On sunny days, air temperature at the height of maximum leafages was increased at the same rate as the ambient temperature above the canopy after sunrise. Below the height, the temperature increase was delayed until the solar noon. Air temperature near the water surface varied much less than those of the outer- and the upper-canopy, which kept increasing by the time of daily maximum temperature observed at the nearby synoptic station. After sunset, cooling rate is much less at the lower canopy, resulting in an isothermal profile at around the midnight. A fairly consistent drop in temperature at rice paddies compared with the nearby synoptic weather stations across geographic areas and time of day was found. According to this result, a cooling by 0.6 to 1.2$^{\circ}C$ is expected over paddy rice fields compared with the officially reported temperature during the summer months. An empirical equation for simulating the temperature profile was formulated from the field observations. Given the temperature estimates at 150 cm above the canopy and the maximum deviation at the lowest layer, air temperature at any height within the canopy can be predicted by this equation. As an application, temperature surfaces at several heights within rice fields were produced over the southwestern plains in Korea at a 1 km by 1km grid spacing, where rice paddies were identified by a satellite image analysis. The outer canopy temperature was prepared by a lapse rate corrected spatial interpolation of the synoptic temperature observations combined with the hourly cooling rate over the rice paddies.