• KIPS Transactions on Computer and Communication Systems
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• v.12 no.2
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• pp.77-84
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• 2023

Dengue virus transmission is a viral infection disease between humans and Aedes mosquitoes. Dengue is ubiquitous throughout the tropics and subtropical zones, where 1/3 of the global population live. The weather in Korea is also changing to subtropical weather, resulting in increased vulnerable Korean population to dengue virus transmission. It is important to control and prevent the dengue risk with track-recording & monitoring system. It is also required to have the control system to treat and monitor dengue patients with various cases such as regions, ages, genders according to the track-record of the disease. In this paper, we developed a Dengue Control & Prevention System, which can monitor and control dengue outbreaks in real-time with in-vitro diagnostic devices. Dengue Control & Prevention System is composed of in-vitro diagnostic device, which is a fluorescent immunoassay, and real-time monitoring system. In the future, we expect that our Dengue Control & Prevention System can be upgraded to have various disease information from Korea Disease Control and Prevention Agency for government policies and diseases control in Korea.

• Journal of Korean Society of Forest Science
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• v.109 no.3
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• pp.259-270
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• 2020

Extreme weather events, such as heat and drought, have occurred frequently over the past two decades. This has led to continuous reports of cases of forest damage due to physiological stress, not pest damage. In 2014, pine trees were collectively damaged in the forest genetic resources reserve of Sogwang-ri, Uljin, South Korea. An investigation was launched to determine the causes of the dieback, so that a forest management plan could be prepared to deal with the current dieback, and to prevent future damage. This study aimedto 1) understand the topographic and structural characteristics of the area which experienced pine tree dieback, 2) identify the main causes of the dieback, and 3) predict future risk areas through the use of machine-learning techniques. A model for identifying risk areas was developed using 14 explanatory variables, including location, elevation, slope, and age class. When three machine-learning techniques-Decision Tree, Random Forest (RF), and Support Vector Machine (SVM) were applied to the model, RF and SVM showed higher predictability scores, with accuracies over 93%. Our analysis of the variable set showed that the topographical areas most vulnerable to pine dieback were those with high altitudes, high daily solar radiation, and limited water availability. We also found that, when it came to forest stand characteristics, pine trees with high vertical stand densities (5-15 m high) and higher age classes experienced a higher risk of dieback. The RF and SVM models predicted that 9.5% or 115 ha of the Geumgang Pine Forest are at high risk for pine dieback. Our study suggests the need for further investigation into the vulnerable areas of the Geumgang Pine Forest, and also for climate change adaptive forest management steps to protect those areas which remain undamaged.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.1
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• pp.1-12
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• 2014

Crown fire, the main propagation type of large forest fire, has caused extreme damage with the fast spread rate and the high flame intensity. In this paper, we developed the probability equation to predict the crown fires using the spatial features of topography, fuel and weather in damaged area by crown fire. Eighteen variables were collected and then classified by burn severity utilizing geographic information system and remote sensing. Crown fire ratio and logistic regression model were used to select related variables and to estimate the weights for the classes of each variables. As a results, elevation, forest type, elevation relief ratio, folded aspect, plan curvature and solar insolation were related to the crown fire propagation. The crown fire propagation probability equation may can be applied to the priority setting of fuel treatment and suppression resources allocation for forest fire.

• International Journal of Highway Engineering
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• v.18 no.6
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• pp.77-85
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• 2016

OBJECTIVES : A fog generated field test was conducted to analyze the relationship between the luminance of variable speed-limit signs and the legibility distance under various fog density conditions. By using this study, appropriate luminance values can be selected depending on the density of fog. METHODS : An actual tunnel was selected as the area to conduct the test, as other places cannot maintain the fog condition because of rapid air current. Ninety-two subjects were recruited for this test, which took place during the course of three days. Visibility-distance detecting sensor was used to measure the visibility distance due to the fog density time, simultaneously with the evaluation of legibility distance by subjects. RESULTS : The test results show the relationship between luminance values and the legibility distance corresponding to the visibility distance due to fog. According to the technical test results, lower luminance value such as $7000cd/m^2$ corresponds to less legibility distance compared to higher values such as $20000cd/m^2$ or $40000cd/m^2$. However, the amount of difference between $20000cd/m^2$ and $40000cd/m^2$ is negligible in our test. CONCLUSIONS : The results of this study can be used to select appropriate luminance of valuable speed signs under fog conditions. Hence, drivers can expect to have more room to respond to adverse weather conditions, thereby reducing the risk of accidents.

• Journal of Preventive Medicine and Public Health
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• v.34 no.3
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• pp.253-261
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• 2001

Objectives : To evaluate the hypothesis that air pollution could increase emergency room visits for respiratory diseases, and if so, to quantify the strength of association between those. Methods : We compiled daily records of hospital emergency room visits for respiratory diseases in Seoul, from November 1. 1955 to October 31. 1996, by using medical utilization data of unscheduled visits. In addition, air quality and weather data for the same period was collected. And a case-crossover design was applied by adopting conditional logistic regression analysis to determine the relationship between air pollutants and emergency room visits for respiratory diseases. In particular, the control periods were chosen by a bidirectional paired matching technique 7, 14, and 21 days before and after the case periods. Results : Only ozone was associated with the increased number of emergency room visits for respiratory diseases. The relative risk according to a 30ppb increase of ozone concentration (24hr mean, lagged 1day) was 1.91(95% confidence interval = 1.78-2.05). Conclusion : There was a statistically significant association between the ambient ozone and daily emergency room visits for respiratory diseases.

• Journal of Korean Society of Disaster and Security
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• v.12 no.3
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• pp.51-57
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• 2019

In recent years, the occurrence of localized torrential rain has increased due to the increase in heavy rainfall and massive typhoons caused by abnormal weather. As a result, the flow rate of small and medium-sized rivers in Korea is rapidly increasing, affecting the safety of bridges and increasing the risk of scour. However, the domestic bridge construction technology does not reflect the watershed characteristics of domestic rivers because the bridge scour depth calculation formula developed overseas is used to calculate the bridge scour depth. Therefore, this study is a basic study for prevention of bridge damage according to scouring phenomenon, and a comparative analysis was performed between the experimental data measured through hydraulic model test and the scour depth formulas applied in Korea. In addition, the statistical analysis between experimental data and scour depth formula shows that Coleman's (1971) formula estimates the best scour depth. The results of this study are expected to be used to calculate more accurate bridge scour depth in river design and bridge design.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.3
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• pp.299-309
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• 2006

In recent years, a large natural disasters have occurred due to worldwide abnormal weather and the amount of damage has been increased more resulting from high density population and a large-sized buildings of the urbanized area. In this study. we estimate the flooded area according to rainfall probability intensify and sea level in Woreong dong, Masan occurred flood damages by typhoon Maemi using SWMM, a dynamic rainfall-runoff simulation model in urban area, and then analyze the damage of flood expected area through connecting with GIS database. In result, we can predict accurately expected area of inundation according to the rainfall intensity and sea level rise through dividing the study area into sub-area and estimating a flooded area and height using SWMM. We provide also the shelter information available for urban planning and flood risk estimation by landuse in expected flood area. Further research for hazard management system construction linked with web or wireless communication technology expects to increase its application.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_1
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• pp.439-446
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• 2013

This paper is about assessment of soil loss in irrigation reservoir based on GIS. Natural disaster caused by soil loss whose natural incidence has been rapidly reduced due to successful tree planting campaign shows high potential risk, since the latest localized heavy rain resulted from extreme weather event and artificial land development acts as direct factors for land disaster. To prevent it, various techniques and technologies have been used to predict effect of soil loss. However, reliability of techniques and technologies to predict its effect precisely is relatively low so far because the natural disaster by soil loss is taken place by complicated interaction between possible factors and direct factors. Geospatial approach is essential to examine these interactions. In this regard, this study will provide detailed plan to improve prediction reliability for soil loss of irrigation reservoir, using GIS that has Hydrologic -Topographical parameter and digital map as its input parameters.

• The Plant Pathology Journal
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• v.33 no.5
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• pp.441-449
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• 2017

Citrus canker is an important bacterial disease of citrus in several regions of the world. Strains of Xanthomonas citri type-A (Xc-A) group are the primary pathogen where citrus canker occurs. After Xc-A entered the Northeast of Argentina in 1974, the disease spread rapidly from 1977 to 1980 and then slowed down and remained moving at slow pace until 1990 when it became endemic. Citrus canker was detected in Northwest Argentina in 2002. This paper presents the main steps in the fight of the disease and the management strategies that have been used to control citrus canker at this time. We think the process might be usefull to other countries with the same situation. Results from more than 40 years of research in Northeast (NE) Argentina indicate that we are at the limit of favorable environment for the disease. The severity of citrus canker is greatly affected by the environment and El $Ni{\tilde{n}}o$ Southern Oscillation (ENSO) phenomenon which causes cyclic fluctuations on the disease intensity in the NE region. Weather-based logistic regression models adjusted to quantify disease levels in field conditions showed that the environmental effect was strongly modulated by the distance from a windbreak. Production of healthy fruits in citrus canker endemic areas is possible knowing the dynamics of the disease. A voluntary Integrated Plan to Reduce the Risk of Canker has been in place since 1994 and it allows growers to export unsymptomatic, uninfested fresh fruit to countries which are free of the disease and require healthy, pathogen free fruits. The experience from Argentina can be replicated in other countries after appropriate trials.

• Research in Plant Disease
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• v.26 no.3
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• pp.121-133
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• 2020

Climate change, increased extreme weather and climate events, and rapidly changing socio-economic environment threaten agriculture and thus food security of our society. Therefore, it is urgent to shift from conventional farming to smart agriculture using big data and artificial intelligence to secure sustainable growth. In order to efficiently manage plant diseases through smart agriculture, agricultural big data that can be utilized with various advanced technologies must be secured first. In this review, we will first learn about agrometeorological big data consisted of meteorological, environmental, and agricultural data that the plant pathology communities can contribute for smart plant disease management. We will then present each sequential components of the smart plant disease management, which are prediction, monitoring and diagnosis, control, prevention and risk management of plant diseases. This review will give us an appraisal of where we are at the moment, what has been prepared so far, what is lacking, and how to move forward for the preparation of smart plant disease management.