• Korean Journal of Remote Sensing
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• v.35 no.2
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• pp.299-316
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• 2019

The purpose of this study was to analyze landslide susceptibility in the Pyeongchang area using Weight of Evidence (WOE) and Evidential Belief Function (EBF) as probability models and Artificial Neural Networks (ANN) as a machine learning model in a geographic information system (GIS). This study examined the widespread shallow landslides triggered by heavy rainfall during Typhoon Ewiniar in 2006, which caused serious property damage and significant loss of life. For the landslide susceptibility mapping, 3,955 landslide occurrences were detected using aerial photographs, and environmental spatial data such as terrain, geology, soil, forest, and land use were collected and constructed in a spatial database. Seventeen factors that could affect landsliding were extracted from the spatial database. All landslides were randomly separated into two datasets, a training set (50%) and validation set (50%), to establish and validate the EBF, WOE, and ANN models. According to the validation results of the area under the curve (AUC) method, the accuracy was 74.73%, 75.03%, and 70.87% for WOE, EBF, and ANN, respectively. The EBF model had the highest accuracy. However, all models had predictive accuracy exceeding 70%, the level that is effective for landslide susceptibility mapping. These models can be applied to predict landslide susceptibility in an area where landslides have not occurred previously based on the relationships between landslide and environmental factors. This susceptibility map can help reduce landslide risk, provide guidance for policy and land use development, and save time and expense for landslide hazard prevention. In the future, more generalized models should be developed by applying landslide susceptibility mapping in various areas.

• Spatial Information Research
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• v.17 no.2
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• pp.243-249
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• 2009

Damages from typhoon events have contributed more than 60 percent of total economic and social loss and the size of loss have been increased up to 800 million dollars per year in Korea, It is therefore necessary to make an effort to mitigate the loss of natural disasters. To facilitate the evaluation of damages in advance and to support the decision making to recover the damages, scientific methods have been adopted. With the effort, GIS data can provide various tools. Three components of hazard mapping are estimation of hazard, inventory for vulnerable features, and fragility of each feature. Vulnerability of natural disaster can be obtained by relation between loss and meteorological data such as precipitation and wind speed. Features can be categorized from other GIS data of public facilities and private properties, and then social and economic loss can be estimated. At this point, GIS data conversions for each model are required. In this study, we build a method to estimate typhoon risk based on GIS data such as DEM, land cover and land use map, facilities.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.12
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• pp.6175-6179
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• 2012

Intestinal parasitic infections (IPIs) are still important to the health of Thai rural residents. IPIs are the cause of many chronic diseases with, for example, opisthorchiasis resulting in progression to cholangiocarcinoma (CCA). This cross-sectional study in a prospective cohort study aimed to examine the prevalence and co-infection of intestinal parasites among Northeastern Thai rural residents, recruited into the Khon Kaen Cohort Study (KKCS), and who were residing in areas of high-risk for developing CCA. On recruitment, subjects had completed questionnaires and provided fecal samples for IPI testing using the formalin ethyl acetate concentration technique. Data on selected general characteristics and the results of the fecal tests were analysed. IPI test results were available for 18,900 of cohort subjects, and 38.50% were found to be positive for one or more types of intestinal parasite. The prevalence of Opisthorchis viverrini (O. viverrini) infection was the highest (45.7%), followed by intestinal flukes (31.9%), intestinal nematodes (17.7%), intestinal protozoa (3.02%), and intestinal cestodes (1.69%). The pattern of different infections was similar in all age groups. According to a mapping analysis, a higher CCA burden was correlated with a higher prevalence of O. viverrini and intestinal flukes and a greater intensity of O. viverrini. Both prevention and control programs against liver fluke and other intestinal parasites are needed and should be delivered simultaneously. We can anticipate that the design of future control and prevention programmes will accommodate a more community-orientated and participatory approach.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.14
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• pp.5669-5673
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• 2015

Background: Breast cancer is the most prevalent kind of cancer among women in Iran. Regarding the importance of cancer prevention and considerable variation of breast cancer incidence in different parts of the country, it is necessary to recognize regions with high incidence of breast cancer and evaluate the role of potential risk factors by use of advanced statistical models. The present study focussed on incidence of breast cancer in Iran at the province level and also explored the impact of some prominent covariates using Bayesian models. Materials and Methods: All patients diagnosed with breast cancer in Iran from 2005 to 2008 were included in the study. Smoking, fruit and vegetable intake, physical activity, obesity and the Human Development Index (HDI), measured at the province level, were considered as potential modulating factors. Gamma-Poisson, log normal and BYM models were used to estimate the relative risk of breast cancer in this ecological investigation with and without adjustment for the covariates. Results: The unadjusted BYM model had the best fit among applied models. Without adjustment, Isfahan, Yazd, and Tehran had the highest incidences and Sistan- Baluchestan and Chaharmahal-Bakhtiari had the lowest. With the adjusted model, Khorasan-Razavi, Lorestan and Hamedan had the highest and Ardebil and Kohgiluyeh-Boyerahmad the lowest incidences. A significantly direct association was found between breast cancer incidence and HDI. Conclusions: BYM model has better fit, because it contains parameters that allow including effects from neighbors. Since HDI is a significant variable, it is also recommended that HDI should be considered in future investigations. This study showed that Yazd, Isfahan and Tehran provinces feature the highest crude incidences of breast cancer.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.453-453
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• 2011

21세기에 들어 홍수의 규모가 대형화 되었고, 그 발생빈도 및 강도도 증가하고 있다. 최근에는 지구온난화가 지속화되면서 전 세계적으로 높은 강도의 기상이변들이 속출하고 있고, 이러한 이상기후에 따른 태풍, 집중호우 등의 대규모 호우로 인해 댐 및 제방 등의 수공구조물 붕괴와 같은 비상상황이 초래 될 수 있다. 이와 같은 피해들을 통해 홍수 침수 범위의 예측, 분석을 통한 홍수위험 및 다양한 홍수위험지도 작성의 필요성이 대두되었고, 실제로 국가 차원의 홍수위 험지도가 제작되고 있다. 특히, 홍수 위험도 분석에 있어서 홍수에 노출된 지역의 인구수, 홍수에 노출된 지역에서의 경제적 활동의 형태, 홍수가 발생했을 때 2차적 피해를 불러올 수 있는 설비 등을 나타내는 홍수 취약도(Flood Vulnerability)에 대한 정량적 평가는 홍수위험지표 및 홍수위험강도 등에 의한 Flood Risk 개념을 기반으로 한 홍수위험지도 제작을 위해 매우 중요한 사항이라 할 수 있다. 그러나 현재까지의 홍수취약도 산정방법은 방법론적인 면에 있어 다소 단순하고, 직관에 의한 위험도의 분류가 이루어지고 있는 실정이다. 또한 취약도 지표의 산정과정이 전문가의 의견에 의존하는 경우가 많아 홍수 취약도 선정과정과 가중치 결정과정에 전문가들의 주관이 개입되는 등 홍수위험지표의 정량화에 어려움을 겪는 경우가 많다. 본 연구에서는 위와 같은 문제를 극복하기 위해 Flood Risk Mapping 기술의 적용에 있어 중요한 요소인 홍수취약도를 다기준의사결정법에 의해 산정하고, 국내 낙동강 유역에 대해 행정구역별로 세분화된 홍수위험지도 제작을 위한 취약도 지표를 산정하고자 하였다. 이를 위해 다기준의사결정법중의 하나 인 PROMEETEE와 ELECTRE를 이용하여 민감도, 노출도, 저감성 지표를 낙동강 유역에 대해 정량화하여 도시하였다. 본 연구결과를 통해 홍수위험지표 및 지수들의 결합에 대한새로운 방법론을 제시하고, 그에 따른 지도화 기법을 확립할 수 있을 것으로 기대된다.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.4
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• pp.57-64
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• 2004

In order to decrease the area damaged by forest fires and to prevent the occurrence of forest fires, the forest fire danger rating system was developed to estimate forest fire risk by means of weather, topography, and forest type. Forest fires occurrence prediction needs to improve continually. Logistic regression and spatial analysis was used in developing the forest fire occurrence probability model. The forest fire danger index in accordance to the probability of forest fire occurrence was used in the classification of forest fire occurrence risk regions.

• Journal of Environmental Health Sciences
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• v.36 no.3
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• pp.182-190
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• 2010

We examined the association of particulate matter with an aerodynamic diameter < $10\;{\mu}m$ ($PM_{10}$) with asthma-related hospitalization, stratified by socioeconomic status (SES), among children less than 15 years of age in Seoul, Korea, between 2003 and 2005. In addition, we estimated the reduction in the number of asthma-related hospitalizations that would result from implementing the World Health Organization (WHO) guideline. SES was defined based on data concerning health insurance premium grades, and grouped into two levels: lower-income group and control group. The lower-income group was classified as having an accumulated income which did not exceed the 50th percentile of the median income. Time-series analysis was performed to evaluate the association between $PM_{10}$ and asthma-related hospitalization. The Environmental Benefits Mapping and Analysis Program was used to analyze the impact on children's health. Based upon an increase of $10\;{\mu}g/m^3$ of $PM_{10}$, the asthma-related hospitalization risk for the lower-income group was increased by 1.78% (95% confidence intervals (CI) = 0.79-2.78%), while the risk for the control group was increased by 0.83% (95% CI = 0.34-1.32%). Attaining the WHO guideline, relative to the concentration in 2007, would result in a reduction in asthma-related hospitalizations of 18 cases per 100,000 of the children population in the lower-income group, and 7 cases in the control group. The health benefits of improved air quality for children in the lower-income group were thus 2.5 times greater than for children in the control group. Our results show that the lower-income group is disproportionately burdened with asthma-related hospitalization arising from air pollution. Therefore, biologically- and socioeconomically-disadvantaged populations should be considered in public health interventions in order to protect the children's health.

• Structural Monitoring and Maintenance
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• v.2 no.3
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• pp.283-300
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• 2015

Visual condition inspections remain paramount to assessing the current deterioration status of a bridge and assigning remediation or maintenance tasks so as to ensure the ongoing serviceability of the structure. However, in recent years, there has been an increasing backlog of maintenance activities. Existing research reveals that this is attributable to the labour-intensive, subjective and disruptive nature of the current bridge inspection method. Current processes ultimately require lane closures, traffic guidance schemes and inspection equipment. This not only increases the whole-of-life costs of the bridge, but also increases the risk to the travelling public as issues affecting the structural integrity may go unaddressed. As a tool for bridge condition inspections, Unmanned Aerial Vehicles (UAVs) or, drones, offer considerable potential, allowing a bridge to be visually assessed without the need for inspectors to walk across the deck or utilise under-bridge inspection units. With current inspection processes placing additional strain on the existing bridge maintenance resources, the technology has the potential to significantly reduce the overall inspection costs and disruption caused to the travelling public. In addition to this, the use of automated aerial image capture enables engineers to better understand a situation through the 3D spatial context offered by UAV systems. However, the use of UAV for bridge inspection involves a number of critical issues to be resolved, including stability and accuracy of control, and safety to people. SLAM (Simultaneous Localisation and Mapping) is a technique that could be used by a UAV to build a map of the bridge underneath, while simultaneously determining its location on the constructed map. While there are considerable economic and risk-related benefits created through introducing entirely new ways of inspecting bridges and visualising information, there also remain hindrances to the wider deployment of UAVs. This study is to provide a context for use of UAVs for conducting visual bridge inspections, in addition to addressing the obstacles that are required to be overcome in order for the technology to be integrated into current practice.

• Journal of Breast Cancer
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• v.21 no.4
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• pp.447-452
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• 2018

Purpose: The recent trend in breast cancer treatment is to minimize axillary dissection. However, no pattern of axillary metastasis has been precisely established. The purpose of this study was to evaluate the metastatic lymphatic pattern using near-infrared fluorescence imaging with indocyanine green (ICG) in breast cancer with cytologically proven axillary metastasis. Methods: This was a prospective single-center study. We evaluated 147 patients with breast cancer involving cytologically proven axillary metastasis, and compared physiological and nonphysiological lymphatic metastasis. Results: We performed lymphatic mapping for 64 patients who exhibited level II lymphatic flow on near-infrared fluorescence imaging with ICG, and found that all had axillary metastasis: 51 patients who did not receive neoadjuvant chemotherapy (NAC) and 13 patients post-NAC. Of patients who did not receive NAC, 32 had physiological lymphatic metastasis and 19 had nonphysiological lymphatic metastasis. The risk factors for nonphysiological lymphatic metastasis were age ${\geq}55$ years, high Ki-67 index (>20%), and perinodal extension in both univariate and multivariate analysis (p<0.05). Conclusion: Patients with identified risk factors in cytologically-proven axillary metastasis who did not receive NAC may have nonphysiological lymphatic metastasis.

• Geomechanics and Engineering
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• v.34 no.3
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• pp.267-284
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• 2023

Landslides are one of the most dangerous phenomena and natural disasters. Landslides cause many human and financial losses in most parts of the world, especially in mountainous areas. Due to the climatic conditions and topography, people in the northern and western regions of Iran live with the risk of landslides. One of the measures that can effectively reduce the possible risks of landslides and their crisis management is to identify potential areas prone to landslides through multi-criteria modeling approach. This research aims to model landslide potential area in the Oshvand watershed using a support vector machine algorithm. For this purpose, evidence maps of seven effective factors in the occurrence of landslides namely slope, slope direction, height, distance from the fault, the density of waterways, rainfall, and geology, were prepared. The maps were generated and weighted using the continuous fuzzification method and logistic functions, resulting values in zero and one range as weights. The weighted maps were then combined using the support vector machine algorithm. For the training and testing of the machine, 81 slippery ground points and 81 non-sliding points were used. Modeling procedure was done using four linear, polynomial, Gaussian, and sigmoid kernels. The efficiency of each model was compared using the area under the receiver operating characteristic curve; the root means square error, and the correlation coefficient . Finally, the landslide potential model that was obtained using Gaussian's kernel was selected as the best one for susceptibility of landslides in the Oshvand watershed.