• 한국정보컨버전스학회:학술대회논문집
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• 2008.06a
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• pp.191-194
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• 2008

SNP(Single Nucleotide Polymorphism) refers to the difference in a base pair existed in DNAs of individuals. Each of it appears per 1,000 bases in human genome and it enables each gene to defer in junctions, interacts with each other to make different shapes of humans, and produces different disease sensitivities. In this paper, we propose a system to forecast lung cancer sensitivities using SNP data related with the lung cancer. A lung cancer sensitivity forecasting model is also constructed through analysis of genetic and non-genetic factors for squamous cell carcinomas, adeno carcinomas, and small cell carcinomas that may frequently appear in Korean. The proposed system with the model gives the probabilities of the onset of lung cancers in the experimental subjects.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.11-20
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• 2017

In this paper, we introduced linear spatial time series (space-time autoregressive and moving average model) and nonlinear spatial time series (space-time bilinear model). Also we estimated the parameters by Kalman Filter method and made comparative studies of power of forecast in the final model. We proposed several weight matrices such as equal proportion allocation, reciprocal proportion between distances, and proportion of population sizes. For applications, we collected Mumps data at Korea Center for Disease Control and Prevention from January 2001 until August 2008. We compared three approaches of weight matrices using the Mumps data. Finally, we also decided the most effective model based on sum of square forecast error.

• Journal of Preventive Medicine and Public Health
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• v.35 no.1
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• pp.65-71
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• 2002

Objective : To estimate the status of HIV infection and AIDS incidence using a back-calculation model in Korea. Methods : Back-calculation is a method for estimating the past infection rate using AIDS incidence data. The method has been useful for obtaining short-term projections of AIDS incidence and estimating previous HIV prevalence. If the density of the incubation periods is known, together with the AIDS incidence, we can estimate historical HIV infections and forecast AIDS incidence in any time period up to time t. In this paper, we estimated the number of HIV infections and AIDS incidence according to the distribution of various incubation periods Results : The cumulative numbers of HIV infection from 1991 to 1996 were $708{\sim}1,426$ in Weibull distribution and $918{\sim}1,980$ in Gamma distribution. The projected AIDS incidence in 1997 was $16{\sim}25$ in Weibull distribution and $13{\sim}26$ in Gamma distribution. Conclusions : The estimated cumulative HIV infections from 1991 to 1996 were $1.4{\sim}4.0$ times more than notified cumulative HIV infections. Additionally, the projected AIDS incidence in 1997 was less than the notified AIDS cases. The reason for this underestimation derives from the very low level of HIV prevalence in Korea, further research is required for the distribution of the incubation period of HIV infection in Korea, particularly for the effects of combination treatments.

• Research in Plant Disease
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• v.21 no.2
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• pp.67-73
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• 2015

Bacterial blossom blight of kiwifruit (Actinidia deliciosa) caused by Pseudomonas syringae pv. syringae is known to be largely affected by weather conditions during the blooming period. While there have been many studies that investigated scientific relations between weather conditions and the epidemics of bacterial blossom blight of kiwifruit, no forecasting models have been developed thus far. In this study, we collected all the relevant information on the epidemiology of the blossom blight in relation to weather variables, and developed the Pss-KBB Risk Model that is based on the Maryblyt model for the fire blight of apple and pear. Subsequent model validation was conducted using 10 years of ground truth data from kiwifruit orchards in Haenam, Korea. As a result, it was shown that the Pss-KBB Risk Model resulted in better performance in estimating the disease severity compared with other two simple models using either temperature or precipitation information only. Overall, we concluded that by utilizing the Pss-KBB Risk Model and weather forecast information, potential infection risk of the bacterial blossom blight of kiwifruit can be accurately predicted, which will eventually lead kiwifruit growers to utilize the best practices related to spraying chemicals at the most effective time.

• Research in Plant Disease
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• v.30 no.3
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• pp.256-267
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• 2024

We have developed FBcastS (Fire Blight Forecasting System), a cloud-based information system that leverages the K-Maryblyt forecasting model. The FBcastS provides an optimal timing for spraying antibiotics to prevent flower infection caused by Erwinia amylovora and forecasts the onset of disease symptoms to assist in scheduling field scouting activities. FBcastS comprises four discrete subsystems tailored to specific functionalities: meteorological data acquisition and processing, execution of the K-Maryblyt model, distribution of web-based information, and dissemination of spray timing notifications. The meteorological data acquisition subsystem gathers both observed and forecasted weather data from 1,583 sites across South Korea, including 761 apple or pear orchards where automated weather stations are installed for fire blight forecast. This subsystem also performs post-processing tasks such as quality control and data conversion. The model execution subsystem operates the K-Maryblyt model and stores its results in a database. The web-based service subsystem offers an array of internet-based services, including weather monitoring, mobile services for forecasting fire blight infection and symptoms, and nationwide fire blight monitoring. The final subsystem issues timely notifications of fire blight spray timing alert to growers based on forecasts from the K-Maryblyt model, blossom status, pesticide types, and field conditions, following guidelines set by the Rural Development Administration. FBcastS epitomizes a smart agriculture internet of things (IoT) by utilizing densely collected data with a spatial resolution of approximately 4.25 km to improve the accuracy of fire blight forecasts. The system's internet-based services ensure high accessibility and utility, making it a vital tool in data-driven smart agricultural practices.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.2
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• pp.65-73
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• 2016

We estimated the averaged maximum incidences of bacterial canker at suitable sites for kiwifruit cultivation in 2020s and 2050s using D-PSA-K model with RCP4.5 and RCP8.5 climate change scenarios. Though there was a little difference between the estimation using RCP4.5 and that using RCP8.5, the estimated maximum disease incidences were more than 75% at all the suitable sites in Korea except for some southern coastal areas and Jeju island under the assumption that there are a plenty of infections to cause the symptoms. We also analyzed the intermediate and final outputs of D-PSA-K model to find out the trends on the change in disease incidence affected by climate change. Whereas increase of damage to kiwifruit canes in a non-frozen environment caused by bacterial canker was estimated at almost all the suitable sites in both the climate change scenarios, rate of necrosis increase caused by the bacterial canker pathogen in a frozen environment during the last overwintering season was predicted to be reduced at almost all the suitable sites in both the climate change scenarios. Directions of change in estimated maximum incidence varied with sites and scenarios. Whereas the maximum disease incidence at 3.14% of suitable sites for kiwifruit cultivation in 2020s under RCP4.5 scenario was estimated to increase by 10% or more in 2050s, the maximum disease incidence at 25.41% of the suitable sites under RCP8.5 scenario was estimated so.

• Journal of Korean Society of Rural Planning
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• v.19 no.4
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• pp.137-147
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• 2013

Most of livestock houses are concentrated in certain area with mass rearing system resulting in rapid spread of infectious diseases such as HPAI (highly pathogenic avian influenza). The livestock-related vehicles which frequently travel between farms could be a major factor for disease spread by means of transmission of airborne aerosol including pathogens. This study was focused on the quantitative measurement of aerosol concentration by field experiment while vehicles were passing through the road. The TSP (total suspended particle) and PM10 (particle matter) were measured using air sampler with teflon filter installed downward the road with consideration of weather forecast and the direction of road. And aerosol spectrometer and video recorders were also used to measure the real-time distribution of aerosol concentration by its size. The results showed that PM2.5 was not considerable for transmission of airborne aerosol from the livestock-related vehicle. The mass generated from the road during the vehicle movement was measured and calculated to 241.4 ${\mu}g/m^3$ by means of the difference between TSP and PM2.5. The dispersion distance was predicted by 79.6 m from the trend curve.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.3
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• pp.234-239
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• 2012

황사(Asian dust storm, ADS)란 중국이나 몽골 등 중앙아시아 지역의 사막 지대의 작은 모래나 황토 또는 먼지가 하늘에 떠다니다가 상층풍을 타고 멀리까지 날아가 떨어지는 현상을 말하며, 주로 봄철에 우리나라를 비롯한 동아시아 지역에 영향을 준다. 이와 같은 황사에 영향을 받는 지역에서는 거주민들의 건강에 부정적인 영향을 미치는 것으로 알려져 있다. 본 연구는 2005년도에서 2008년도까지 4년간 서울지역 거주민들 사이에서 황사현상이 천식질환에 미치는 영향을 분석하고자 한다. 이를 위해 황사발생일(기준일 또는 index day)과 기준일 대비 7일 전후(비교일 또는 comparison day) 황사가 발생하지 않은 날에 병의원에서 진료를 받은 천식환자 수를 황사예보의 정확도에 따라 비교 분석하였다. 그 결과 24시간 전 제공된 황사예보가 황사발생을 정확히 예측한 경우라 하더라도 비교일 대비 기준일의 천식환자 수가 여전히 더 많다는 사실을 알 수 있었다. 다만, 증가 정도는 통계적으로 유의한 수준은 아니었다는 점에서 정확한 황사예보가 최소한 어느 정도는 천식질환 발생을 저감시키는 효과는 분명히 가지고 있다고 판단할 수 있다. 반면에 24시간 전 황사예보가 황사발생을 정확하게 예측하지 못한 경우에는 비교일 대비 기준일에서 5~6일 후에 진료 받은 천식환자 수가 통계적으로 유의할 수준까지 높게 나타났다. 하지만, 기준일 및 기준일 다음 날의 경우에는 오히려 천식환자 수가 감소하는 경향을 보였다. 본 연구를 통해 황사예보 및 황사발생의 다양한 경우에 따라 천식환자 수의 일정한 변화패턴이 발견되었으며, 이와 같은 연구결과는 황사 관련 의료서비스 체계를 보다 효율적으로 설계하는데 활용될 수 있을 것으로 기대된다.

• Health Policy and Management
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• v.28 no.4
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• pp.352-359
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• 2018

Background: The purpose of this study is to propose an analysis of trends and characteristics of high-cost patients who take over 40% of total national health insurance medical expenses. Methods: It has been analyzed the tendency of high-cost patients by open data based on the medical history information of 1 million people among national health insurance subscriber from 2002 to 2015. To conduct detailed study of characteristics of high-cost patients, multiple regression has been performed by sex, age, residence, main provider, and admission status based on the top 5% group. Results: The amount of medical expenses and the number of high-cost patients have gradually increased in decades. The number of high-cost patients for Korean won (KRW) 5,000,000 category has increased by 7.6 times, KRW 10,000,000 category has increased by 14.1 times in comparing of year 2002 and 2015. Top 5% medical expenses have increased by 4.6 times. In consideration of the characteristics of patients, the incidence of high medical expenses has been higher in female patients than male ones, the older patients than in the younger. Patients residence in Gyeonsang or Jeonla province have had a high incidence of medical expenses than other area. The disease including dementia, cerebral infarction, and cerebrovascular disease for high-cost patients has been also increased. Conclusion: The major increase factor for high medical expenses is the aging of population. The elderly population receiving inpatient care residing in the province that increases high medical costs have to management. There is an urgent need to develop a mechanism for predicting and managing the cost of high-cost medical expenses for patients who have a heavy financial burden.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.224-232
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• 2016

The methodology to visualize the shape of blood vessel and its blood flow have been attracting as a very interesting problem to forecast and examinate a disease in thrombus precursor protein. May previous visualization researches have been appeared for designing the blood vessel and also modeling the blood flow using a doppler imaging technique which is one of nondestructive testing techniques. General visualization methods are to depict the blood flow obtained from doppler effects with fragmentary stream lines and also visualize the blood flow model using volume rendering. However, these visualizeation techniques have the disadvantage which a set of small line segments does not give the overall observation of blood flows. Therefore, we propose a visualization system which reconstruct the continuity of the blood flow obtained from doppler effects and also visualize the blood flow with the vector field of blood particles. This system will use doppler phase difference from medical equipments such as OCT with low penetration and reconstruct the blood flow by the curvature estimation from vector field of each blood particle.