This study analyzed the ground characteristics region by designating 3 research areas, Anrim-dong in Chungju City, Busa-dong in Daejeon Metropolitan City and Sinan-dong in Andong City out of the areas subject to concentrated management to prepare for sediment disaster in downtown areas. The correlation between ground characteristics were observed by using characteristics (crown density, root cohesion, rainfall characteristics, soil characteristics) and the risk areas were predicted through sediment disaster prediction modeling. Landslide MAPping (LSMAP), Stability Index MAPping (SINMAP) and Landslide Hazard MAP (LHMAP) were used for the comparative analysis of the hazard prediction model for sediment disaster. As a result of predicting the sediment disaster danger, in case of SINMAP which was generally used, excessive range was predicted as a hazardous area and in case of the Korea Forest Service's landslide hazard map (LHMAP), the smallest prediction area was assessed. LSMAP predicted a medium range of SINMAP and LHMAP as hazardous area. The difference of the prediction results is that the analysis parameters of LSMAP is more diverse and engineering than two comparative models, and it is found that more precise prediction is possible.
Recently, the spatiotemporal patterns of flood disasters have become more complex and unpredictable due to climate change. Flood hazard map including information on flood risk level has been widely used as an unstructured measure against flooding damages. In order to product a high-precision flood hazard map by combination of hydrologic and hydraulic modeling, huge digital information such as topography, geology, climate, landuse and various database related to social economic are required. However, in some areas, especially in developing countries, flood hazard mapping is difficult or impossible and its accuracy is insufficient because such data is lacking or inaccessible. Therefore, this study suggests a method to delineate large scale flood-prone area based on topographic factors produced by linear binary classifier and ROC (Receiver Operation Characteristics) using globally-available geographic data such as ASTER or SRTM. We applied the proposed methodology to five different countries: North Korea Bangladesh, Indonesia, Thailand and Myanmar. The results show that model performances on flood area detection ranges from 38% (Bangladesh) to 78% (Thailand). The flood-prone area detection based on the topographical factors has a great advantage in order to easily distinguish the large-scale inundation-potent area using only digital elevation model (DEM) for ungauged watersheds.
Although the demand of ready-to-eat (RTE) foods such as Kimbab is growing, large quantities and wide distribution of these foods is difficult due to their short shelf-life, exposed packaging with hygienic risk, and decreased quality at refrigerator temperatures. This study was undertaken to develop preservation and storage methods to extend the shelf-life of RTE rice products using microwave and packaging methods such as vacuum and modified atmosphere packages. RTE rice ball samples inoculated with Escherichia coli, Salmonella Typhimurium, Listeria monocytogenes, Staphylococcus aureus or Bacillus cereus were microwave treated for 0, 30, 60, 90 and 120 seconds. Populations of pathogens on the rice balls were significantly reduced with an increase in treatment time. There were more than 5 log reductions of all pathogens when the samples were microwave treated for 60 seconds. RTE rice balls inoculated with two pathogens (S. aureus and B. cereus) were packaged via air, vacuum, $N_2$ gas, and $CO_2$ gas following microwave treatment for 90 seconds. The initial S. aureus and B. cereus concentration before treatment was 7.60 and 6.59 log CFU/g, and these levels were reduced by 3.37 and 2.18 log CFU/g after microwave treatment. The levels of pathogens were significantly increased during storage time at room temperature. $CO_2$ packaging was the most effective at inhibiting microbial growth among the tested packaging methods. The levels of total mesophilic count, S. aureus and B. cereus after 5 days of storage were 7.7, 8.8 and 9.3 log CFU/g in air packaged samples and 2.4, 3.2 and 8.3 log CFU/g in $CO_2$ gas packaged samples, respectively. However, after 3 days of storage higher levels of B. cereus were observed in all samples, indicating that the samples were not safe to be consumed. Base on these results, microwave treatment and MAP packaging methods using $CO_2$ gas could be used as a potential method for extending the shelf-life of RTE foods.
Features of geological lineaments generally play an important role at the data interpretation concerned geological processes, mineral exploration or natural hazard risk estimation. However, there are intrinsically discordances between lineaments-related features extracted from surficial geological syrvey and those from satellite imagery;nevertheless, any data set contained those information should not be considred as less meaningful within their own task. For the purpose of effective utilization task of extracted lineaments, the mathematical scheme, based on fuzzy set theory, for practical integration of various types of rasterized data sets is studied. As a real application, the geological map named Homyeong sheet(1:50,000) and the Landset TM imageries covering same area were used, and then lineaments-related data sets such as lineaments on the geological map, lineaments extracted from a false-color image composite satellite, and major drainage pattern were utilized. For data fusion process, fuzzy membership functions of pixel values in each data set were experimentally assigned by percentile, and then fuzzy algebraic sum operator was tested. As a result, integrated lineaments by this well-known operator are regarded as newly-generated reasonable ones. Conclusively, it was thought that the implementation within available GISs, or the stand-alone module for general applications of this simple scheme can be utilized as an effective scheme can be utilized as an effective scheme for further studies for spatial integration task for providing decision-supporting information, or as a kind of spatial reasoning scheme.
Proceedings of the Korean Institute of Navigation and Port Research Conference
/
2023.05a
/
pp.100-103
/
2023
Recently, development of maritime autonomoust surface ships and eco-friendly ships, production and evaluation research considering various marine environments is needed in the field of optimal routes as the demand for accurate and detailed real-time marine environment prediction information expands. An algorithm that can calculate the optimal route while reducing the risk of the marine environment and uncertainty in energy consumption in smart ships was developed in 2 stages. In the first stage, a profile was created by combining marine environmental information with ship location and status information within the Automatic Ship Identification System(AIS). In the second stage, a model was developed that could define the marine environment energy map using the configured profile results, A regression equation was generated by applying Random Forest among machine learning techniques to reflect about 600,000 data. The Random Forest coefficient of determination (R2) was 0.89, showing very high reliability. The Dijikstra shortest path algorithm was applied to the marine environment prediction at June 1 to 3, 2021, and to calculate the optimal safety route and express it on the map. The route calculated by the random forest regression model was streamlined, and the route was derived considering the state of the marine environment prediction information. The concept of route calculation based on real-time marine environment prediction information in this study is expected to be able to calculate a realistic and safe route that reflects the movement tendency of ships, and to be expanded to a range of economic, safety, and eco-friendliness evaluation models in the future.
Recently, soil erosion have been thickening from heavy rainfall according to climate change. These soil erosion is main reason to cause landslide, the water quality, agricultural counterproductivity and so on. Therefore, it is important to find out the main source area to cause soil erosion using geospatial data including DEM, soil map and land cover those are very sensitive to soil erosion modeling. This study evaluated soil erosion using RUSLE model. Hyoja 4-Dong and Pyonghwa 2-Dong among Wansan-Gu showed high as 10,869 ton/yr and 10,477 ton/yr respectively and Ua 2-Dong of Deokjin-Gu showed high as 17,603 ton/yr in soil erosion. And Hyoja 1-Dong and Pyonghwa 1-Dong among Wansan-Gu showed high as $1,485.7ton/km^2$ and $1,297.0ton/km^2$ respectively and Inhu 3-Dong of Deokjin-Gu showed high as $2,557.7ton/km^2$ in unit soil erosion that was applied to the evaluation of soil erosion potential. It is anticipated that achievement of this study can apply to forecast and prepare the risk of soil erosion and debris flow in urban area.
Shahdoust, Maryam;Hajizadeh, Ebrahim;Mozdarani, Hossein;Chehrei, Ali
Asian Pacific Journal of Cancer Prevention
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v.14
no.1
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pp.111-116
/
2013
Background: Cigarette smoking is the major risk factor for development of lung cancer. Identification of effects of tobacco on airway gene expression may provide insight into the causes. This research aimed to compare gene expression of large airway epithelium cells in normal smokers (n=13) and non-smokers (n=9) in order to find genes which discriminate the two groups and assess cigarette smoking effects on large airway epithelium cells.Materials and Methods: Genes discriminating smokers from non-smokers were identified by applying a neural network clustering method, growing self-organizing maps (GSOM), to microarray data according to class discrimination scores. An index was computed based on differentiation between each mean of gene expression in the two groups. This clustering approach provided the possibility of comparing thousands of genes simultaneously. Results: The applied approach compared the mean of 7,129 genes in smokers and non-smokers simultaneously and classified the genes of large airway epithelium cells which had differently expressed in smokers comparing with non-smokers. Seven genes were identified which had the highest different expression in smokers compared with the non-smokers group: NQO1, H19, ALDH3A1, AKR1C1, ABHD2, GPX2 and ADH7. Most (NQO1, ALDH3A1, AKR1C1, H19 and GPX2) are known to be clinically notable in lung cancer studies. Furthermore, statistical discriminate analysis showed that these genes could classify samples in smokers and non-smokers correctly with 100% accuracy. With the performed GSOM map, other nodes with high average discriminate scores included genes with alterations strongly related to the lung cancer such as AKR1C3, CYP1B1, UCHL1 and AKR1B10. Conclusions: This clustering by comparing expression of thousands of genes at the same time revealed alteration in normal smokers. Most of the identified genes were strongly relevant to lung cancer in the existing literature. The genes may be utilized to identify smokers with increased risk for lung cancer. A large sample study is now recommended to determine relations between the genes ABHD2 and ADH7 and smoking.
The potential of using GIS in analyzing pest surveillance data was explored. The Spatial Analysis System (SPANS) was used to construct a spatial data base to study pest distributions using pest surveillance data collected from 152 stations in South Korea. The annual spatIal distributions of the striped rice borer(SRB), Chdo suppressalis, showed that high densities started to expand in the early 1980s, reaching a peak in 1988. The pattern change appears to be related to cultivation of japonica and indica-japonica hybrid varieties in South Korea. Japo7l!ca varieties have longer duration resulting in the SRB haVlng more time to mature and hibernate in wmter. The locus of SRB spread appears to be located in the mid-west region near lri, Chun~ Buk Province. High brown planthopper (BPH) populations in South Korea are often related to the early immigration and temperature. The simulated distribution of PPH densities in September using these two factors was compared with the actual distribution obtained using 1990 data. The two density maps corresponded closely excepL for differences in the south eastern valley. By overlaying the simulated map layer with the elevation and rice area maps, more specific BPH risk zones could be identified.
Korean Journal of Agricultural and Forest Meteorology
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v.6
no.3
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pp.170-176
/
2004
This study was carried out to establish a spatial decision support system for evaluating climatic aspects of a given geographic location in complex terrains with respect to the quality apple production. Monthly climate data from S6 synoptic stations across South Korea were collected for 1971-2000. A digital elevation model (DEM) with a 10-m cell spacing was used to spatially interpolate daily maximum and minimum temperatures based on relevant topoclimatological models applied to Jangsoo county in Korea. For daily minimum temperature, a spatial interpolation scheme accommodating the potential influences of cold air accumulation and the temperature inversion was used. For daily maximum temperature estimation, a spatial interpolation model loaded with the overheating index was used. Freezing risk in January was estimated under the recurrence intervals of 30 years. Frost risk at bud-burst and blossom was also estimated. Fruit quality was evaluated for soluble solids, anthocyanin content, Hunter L and A values, and LID ratio, which were expressed as empirical functions of temperature based on long-term field observations. AU themes were prepared as ArcGlS Grids with a 10-m cell spacing. Analysis showed that 11 percent of the whole land area of Jangsoo county might be suitable for quality 'Fuji' apple production. A computer program (MAPLE) was written to help utilize the results in decision-making for site-selection of new orchards in this region.
Korean Journal of Agricultural and Forest Meteorology
/
v.19
no.1
/
pp.10-18
/
2017
Korean Red Pine (Pinus densiflora) has been protected and used as the most ecologically and socio-culturally important tree species in Korea. However, as dieback of Korean red pines has occurred in the protected area of the forest genetic resources. The aims of this study is to identify causes for dieback of pine tree by investigating topographical characteristics of pine tree dieback and its correlation to meteorological factors. We extracted the dead trees from the time series aerial images and analyzed geomorphological characteristics of dead tree concentration area. As a result, 1,956 dead pine trees were extracted in the study region of 2,600 ha. Dieback of pine trees was found mostly in the areas with high altitude, high solar radiation, low topographic wetness index, south and south-west slopes, ridgelines, and high wind exposure compared to other living pine forest area. These areas are classified as high temperature and high drought stress regions due to micro-climatic characteristics affected by topographic factors. As high temperature and drought stress are generally increasing with climate change, we can evaluated that a risk of pine tree dieback is also increasing. Based on these geomorphological characteristics, we developed a pine tree dieback risk map using Maximum Entropy Model (MaxEnt), and it can be useful for establishing Korean red pine protection and management strategies.
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