• 한국식물병리학회:학술대회논문집
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• 한국식물병리학회 2003년도 정기총회 및 추계학술발표회
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• pp.108.2-109
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• 2003

The Gyeonggi-do Agricultural Research and Extension Services has developed a web-site (www.epilove.com) in collaboration with EPINET to provide information on agricultural weather and rice disease and insect pest management in Gyeonggi-do. Weather information includes near real-time weather data monitored by automated weather stations (AWS) installed at rice paddy fields of 11 Agricultural Technology Centers (ATC) in Gyeonggi-do, and weekly weather forecast by Korea Meteorological Administration (KMA). Map images of hourly air temperature and rainfall are also generated at 309m x 309m resolution using hourly data obtained from AWS installed at 191 locations by KMA. Based on near real-time weather data from 11 ATC, hourly infection risks of rice blast, sheath blight, and bacterial grain rot for individual districts are estimated by disease forecasting models, BLAST, SHBLIGHT, and GRAINROT. Users can diagnose various diseases and insects of rice and find their information in detail by browsing thumbnail images of them. A database on agrochemicals is linked to the system for disease and insect diagnosis to help users search for appropriate agrochemicals to control diseases and insect pests.

• Journal of Preventive Medicine and Public Health
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• 제53권6호
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• pp.387-396
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• 2020

Objectives: The lack of advance planning in a public health emergency can lead to wasted resources and inadvertent loss of lives. This study is aimed at forecasting the needs for healthcare resources following the expansion of the coronavirus disease 2019 (COVID-19) outbreak in the Republic of Kazakhstan, focusing on hospital beds, equipment, and the professional workforce in light of the developing epidemiological situation and the data on resources currently available. Methods: We constructed a forecast model of the epidemiological scenario via the classic susceptible-exposed-infected-removed (SEIR) approach. The World Health Organization's COVID-19 Essential Supplies Forecasting Tool was used to evaluate the healthcare resources needed for the next 12 weeks. Results: Over the forecast period, there will be 104 713.7 hospital admissions due to severe disease and 34 904.5 hospital admissions due to critical disease. This will require 47 247.7 beds for severe disease and 1929.9 beds for critical disease at the peak of the COVID-19 outbreak. There will also be high needs for all categories of healthcare workers and for both diagnostic and treatment equipment. Thus, Republic of Kazakhstan faces the need for a rapid increase in available healthcare resources and/or for finding ways to redistribute resources effectively. Conclusions: Republic of Kazakhstan will be able to reduce the rates of infections and deaths among its population by developing and following a consistent strategy targeting COVID-19 in a number of inter-related directions.

• 한국식물병리학회:학술대회논문집
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• 한국식물병리학회 2003년도 정기총회 및 추계학술발표회
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• pp.24-24
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• 2003

Since Rice bacterial grain rot (RGBR) was reported at 1986 in Korea, it has been severely occurred in 1994, 1995, 1998, and especially around 16,609 ha in 2000, and became a major disease in rice cultivation field. This study was focused on investigation of ecology of RGBR, weather conditions that affect development of epidemics, and development of an effective RGBR forecast system based on weather conditions during the rice heading period.(중략)

• 한국농림기상학회:학술대회논문집
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• 한국농림기상학회 2003년도 춘계 학술발표논문집
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• pp.87-87
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• 2003

The Gyeonggi-do Agricultural Research and Extension Services has developed a web-site (http://www.epilove.com) in collaboration with EPINET to provide information on agricultural weather and rice disease and insect pest management in Gyeonggi-do. Weather information includes near real-time weather data monitored by automated weather stations (AWS) installed at rice paddy fields of 11 Agricultural Technology Centers (ATC) in Gyeonggi-do, and weekly weather forecast by Korea Meteorological Administration (KMA).(omitted)

• International Journal of Contents
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• 제17권3호
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• pp.1-14
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• 2021

Since the outbreak of the coronavirus disease 2019 (COVID-19) pandemic, a lot of efforts have been made in the field of data science to help combat against this disease. Among them, forecasting the number of cases of infection is a crucial problem to predict the development of the pandemic. Many deep learning-based models can be applied to solve this type of time series problem. In this research, we would like to take a step forward to incorporate spatial data (geography) with time series data to forecast the cases of region-level infection simultaneously. Specifically, we model a single spatio-temporal graph, in which nodes represent the geographic regions, spatial edges represent the distance between each pair of regions, and temporal edges indicate the node features through time. We evaluate this approach in COVID-19 in a Korean dataset, and we show a decrease of approximately 10% in both RMSE and MAE, and a significant boost to the training speed compared to the baseline models. Moreover, the training efficiency allows this approach to be extended for a large-scale spatio-temporal dataset.

• ALGAE
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• 제39권3호
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• pp.177-186
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• 2024

Red rot disease is one of the notorious algal diseases that threaten the cultivation of Pyropia in China, and two Pythium pathogens, i.e., Pythium porphyrae and P. chondricola, have been reported as causative agents. To monitor the pathogens, a fluorescent quantitative polymerase chain reaction (PCR) method was developed to quantitatively detect their abundance. Using overlapping PCR and pathogen-specific primer pairs, two pathogen-specific fragments were concatenated to construct an internal standard plasmid, which was used for quantification. For zoospores of known numbers, the results showed that this method can detect as less as 100 and 10 zoospores mL^-1 in a 200 mL solution for P. porphyrae and P. chondricola, respectively. Using monthly collected seawater at 10 sites in Haizhou Bay, a typical aquaculture farm in China, a significantly higher temperature and a significantly lower salinity were determined in December 2021. P. porphyrae was determined to be more abundant than P. chondricola, though with similar temporal distribution patterns from December 2021 to February 2022. When a red rot disease occurred in December 2021, the two pathogens were significantly more abundant at two infected sub-sites than the uninfected sub-site within both seawater and sediment, though they were all significantly more enriched in sediment than in seawater. The present method provides the capability to quantify and compare the abundance of two pathogens and also has the potential to forecast the occurrence of red rot disease, which is of much significance in managing and controlling the disease.

• 동의생리병리학회지
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• 제21권1호
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• pp.1-9
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• 2007

${\ulcorner}$Hamsansachon Dongyi Suse Bowon Gabogubon${\lrcorner}$ , discovered in 2000, can give very precious information in order to study the formation and development process of ${\ulcorner}$Dongyi Suse Bowon${\lrcorner}$ ${\ulcorner}$The Dircourse on the Constitutional Symptoms and Disease${\lrcorner}$ . I examined, by comparison, changes in understanding pathology explained in ${\ulcorner}$Dongyi Suse Bowon${\lrcorner}$ ${\ulcorner}$The Discourse on the Constitutional Symptoms and Disease${\lrcorner}$ of Gabobon and Sinchukbon, and consequently tried to define the concept of Dispositional Symptom(Dispositional disease) as below, in a point of view that ‘Dispositional Symptom(Dispositional disease)’ should be the key word in explaining the changes in understanding of pathology. Dispositional Symptom(dispositional disease) is a new concept that was first troduced in the Kyongjabon, not found in the Gabobon, and that played a key role in editing ${\ulcorner}$Dongyi Suse Bowon${\lrcorner}$ ${\ulcorner}$The Discourse on the Constitutional Symptom and Disease${\lrcorner}$ . Dispositional Symptom(dispositional disease) means an innate temperament or a pathological tendency, which is already constructed in the system of an individual, prior to expression of specific diseases and symptoms, and can be a primary basis to tell the susceptibility and developing pattern of a certain disease, to decide how to treat and forecast the prognosis. Sinchukbon inductively categorized symptoms of the dispositional symptom (dispositional disease) into the concept of ‘Eight principles’, or eight standards of diagnosis, such as superficies-interior, cold-heat, and weakness-strength.

• 한국지리정보학회지
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• 제13권1호
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• pp.28-34
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• 2010

소나무재선충병 피해의 공간적 분포 특성은 고사목 단목 중심의 점상 발생을 보이기 때문에 신속한 피해지 파악과 정확한 확산예측에 어려움이 있다. 따라서 피해발생 조기예찰 및 분석, 감시 감독이 매우 중요하다. 그러나 기존의 예찰방법인 도로나 민가 주변 중심의 지상 육안예찰은 누락된 지역이 많고 고산지역, 급경사, 절벽등의 위험지역 예찰이 불가능하기 때문에 본 연구에서는 이러한 단점들을 보완하기 위하여 체계적이고 과학적인 GIS, GPS와 헬기를 이용한 항공정밀예찰 기법을 개발하였으며, 2005년 전국 32개 시 군(약 $28,810km^2$) 피해지역의 349지점 972본의 고사목 위치좌표를 취득하여 소나무재선충병 방제에 활용하였다. 따라서 항공정밀예찰기법 개발은 소나무재선충병 발생 우려지역에 대한 고사목 색출 및 고사원인 규명, 매개충 산란처 제거 등의 효과를 얻을 수 있을 것이다.

• International Journal of Computer Science & Network Security
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• 제22권1호
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• pp.225-233
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• 2022

The recent outbreak of corona virus (COVID-19) infectious disease had made its forecasting critical cornerstones in most scientific studies. This study adopts a machine learning based time series model - Auto Regressive Integrated Moving Average (ARIMA) model to forecast COVID-19 confirmed cases in Botswana over 60 days period. Findings of the study show that COVID-19 confirmed cases in Botswana are steadily rising in a steep upward trend with random fluctuations. This trend can also be described effectively using an additive model when scrutinized in Seasonal Trend Decomposition method by Loess. In selecting the best fit ARIMA model, a Grid Search Algorithm was developed with python language and was used to optimize an Akaike Information Criterion (AIC) metric. The best fit ARIMA model was determined at ARIMA (5, 1, 1), which depicted the least AIC score of 3885.091. Results of the study proved that ARIMA model can be useful in generating reliable and volatile forecasts that can used to guide on understanding of the future spread of infectious diseases or pandemics. Most significantly, findings of the study are expected to raise social awareness to disease monitoring institutions and government regulatory bodies where it can be used to support strategic health decisions and initiate policy improvement for better management of the COVID-19 pandemic.

• 한국멀티미디어학회논문지
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• 제18권6호
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• pp.772-779
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• 2015

Advancing information technology have rapidly changed our service environment of life, culture, and industry. Computer information communication system is applied in medical, health, distribution, and business transaction. Smart is using new information by combining ability of computer and information. Although agriculture is labor intensive industry that requires a lot of hands, agriculture is becoming knowledge-based industry today. In agriculture field, computer communication system is applied on facilities farming and machinery Agricultural. In this paper, we designed and implemented application that provides personalized agriculture related information at the actual farming field. Also, this provides farmer a system that they can directly auction or sell their produced crops. We designed and implemented a system that parsing information of each seasonal, weather condition, market price, region based, crop, and disease and insects through individual setup on ubiquitous environment using location-based sensor network and processing data.