KSCE Journal of Civil and Environmental Engineering Research
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v.43
no.6
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pp.883-896
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2023
As human activities in Korea are spread throughout the mountains, forest fires often affect residential areas, infrastructure, and other facilities. Hence, it is necessary to detect fire-damaged areas quickly to enable support and recovery. Remote sensing is the most efficient tool for this purpose. Fire damage detection experiments were conducted on the east coast of Korea. Because this area comprises a mixture of forest and artificial land cover, data with low resolution are not suitable. We used Sentinel-2 multispectral instrument (MSI) data, which provide adequate temporal and spatial resolution, and the k-nearest neighbor (kNN) algorithm in this study. Six bands of Sentinel-2 MSI and two indices of normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as features for kNN classification. The kNN classifier was trained using 2,000 randomly selected samples in the fire-damaged and undamaged areas. Outliers were removed and a forest type map was used to improve classification performance. Numerous experiments for various neighbors for kNN and feature combinations have been conducted using bi-temporal and uni-temporal approaches. The bi-temporal classification performed better than the uni-temporal classification. However, the uni-temporal classification was able to detect severely damaged areas.
This study speculates on responses to the nuclear threats of North Korea and mutual assistance and cooperation between South Korea, the U.S. and China for the unification of the Korean Peninsula. As for the North Koreas nuclear issue and unification of the Korean Peninsula, South Korea is the subject of national division, the U.S. is a responsible country in international issues and does not have diplomatic ties with North Korea. China is a traditional socialist nation and a supporter of North Korea. As North Korea's strategic weapons including nuclear weapons and ballistic missiles are international issues, to defend against Kim Jung-Eun's unexpected acts, the three countries should actively cooperate with each other and develop countermeasures. However, with respect to the road map of the North Koreas issue, there are subtle differences between the U.S. and China in recognition of and sanctions against North Korea as a resolution of the U..N. Security Council. The U.S. has continued a deterrence policy and sanctions against North Korea based on joint threats between South Korea and the U.S. while China has showed a negative position in the process of solving the North Korean nuclear issue because of the unstable security derived from the U.S. 's intervention in the Korean peninsula. North Korea should change its diplomatic policy in a more concrete way towards world peace although it has continued trade of strategic weapons with Middle Eastern countries to maintain its political system. For example, to restart the summit talks and open multilateral security channels. Although the issue of unification of the Korean peninsula should be resolved by South and North Korea themselves, it is strange that South and North Korea depend on the logic of powerful countries for the resolution of a national problem. As for North Koreas nuclear and the Unification issues, peaceful solutions presented by South Korea seem more persuasive than the solution presented by North Korea which did not secure any international support. However, South Korea, the U.S. and China need to develop uni-directional two-tract strategies for sanctions against North Korea and talks with North Korea for peace on the Korean peninsula, and should continue to support the economic independence of North Korea.
In South Korea with forest as a major land cover class (over 60% of the country), many wildfires occur every year. Wildfires weaken the shear strength of the soil, forming a layer of soil that is vulnerable to landslides. It is important to identify the severity of a wildfire as well as the burned area to sustainably manage the forest. Although satellite remote sensing has been widely used to map wildfire severity, it is often difficult to determine the severity using only the temporal change of satellite-derived indices such as Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR). In this study, we proposed an approach for determining wildfire severity based on machine learning through the synergistic use of Sentinel-1A Synthetic Aperture Radar-C data and Sentinel-2A Multi Spectral Instrument data. Three wildfire cases-Samcheok in May 2017, Gangreung·Donghae in April 2019, and Gosung·Sokcho in April 2019-were used for developing wildfire severity mapping models with three machine learning algorithms (i.e., Random Forest, Logistic Regression, and Support Vector Machine). The results showed that the random forest model yielded the best performance, resulting in an overall accuracy of 82.3%. The cross-site validation to examine the spatiotemporal transferability of the machine learning models showed that the models were highly sensitive to temporal differences between the training and validation sites, especially in the early growing season. This implies that a more robust model with high spatiotemporal transferability can be developed when more wildfire cases with different seasons and areas are added in the future.
Journal of the Economic Geographical Society of Korea
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v.25
no.1
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pp.109-130
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2022
The Vietnamese government has proposed contract farming through a new type of cooperative as an institutional innovation which aims to restructure the agricultural sector. However, policy changes often impact farmers, who bear the primary effects of the transition process. Understanding households' strategies for land use and livelihood is crucial for policymaking in the agricultural development field. This study was conducted in the rural Binh Dao commune in Central Vietnam. We analyzed household members' labor force changes and their livelihood behaviors after their participation in a contract farming scheme using qualitative analysis methods combined with geographic information system (GIS) support, based on secondary data and in-depth interviews of 190 farmers. Simultaneously, we created a digital map of the cooperative's production area to investigate changes in land use and production activities. The findings show that contract farming shaped the vertical coordination of the value chain from the farmers to the cooperative and agricultural product trading companies. Subsequently, it encouraged land use and labor efficiency due to mechanical support. In addition, it also increased productivity and protected farmers from market risks. However, despite its positive effects on agricultural productivity in this case, the contract farming scheme could not achieve the restructuring of the rural labor force toward non-agricultural sectors. Ironically, farmers in the Binh Dao commune tended to increase cultivable land during the agricultural restructuring program, rather than switching their labor forces to non-agricultural sectors. The lack of stable non-farming job opportunities in rural Vietnam results in challenges to the efficiency of agricultural restructuring programs. Consequently, farmers in the Binh Dao commune are still smallholder farmers, depending on the family labor force.
Document classification based on emotional polarity has become a welcomed emerging task owing to the great explosion of data on the Web. In the big data age, there are too many information sources to refer to when making decisions. For example, when considering travel to a city, a person may search reviews from a search engine such as Google or social networking services (SNSs) such as blogs, Twitter, and Facebook. The emotional polarity of positive and negative reviews helps a user decide on whether or not to make a trip. Sentiment analysis of customer reviews has become an important research topic as datamining technology is widely accepted for text mining of the Web. Sentiment analysis has been used to classify documents through machine learning techniques, such as the decision tree, neural networks, and support vector machines (SVMs). is used to determine the attitude, position, and sensibility of people who write articles about various topics that are published on the Web. Regardless of the polarity of customer reviews, emotional reviews are very helpful materials for analyzing the opinions of customers through their reviews. Sentiment analysis helps with understanding what customers really want instantly through the help of automated text mining techniques. Sensitivity analysis utilizes text mining techniques on text on the Web to extract subjective information in the text for text analysis. Sensitivity analysis is utilized to determine the attitudes or positions of the person who wrote the article and presented their opinion about a particular topic. In this study, we developed a model that selects a hot topic from user posts at China's online stock forum by using the k-means algorithm and self-organizing map (SOM). In addition, we developed a detecting model to predict a hot topic by using machine learning techniques such as logit, the decision tree, and SVM. We employed sensitivity analysis to develop our model for the selection and detection of hot topics from China's online stock forum. The sensitivity analysis calculates a sentimental value from a document based on contrast and classification according to the polarity sentimental dictionary (positive or negative). The online stock forum was an attractive site because of its information about stock investment. Users post numerous texts about stock movement by analyzing the market according to government policy announcements, market reports, reports from research institutes on the economy, and even rumors. We divided the online forum's topics into 21 categories to utilize sentiment analysis. One hundred forty-four topics were selected among 21 categories at online forums about stock. The posts were crawled to build a positive and negative text database. We ultimately obtained 21,141 posts on 88 topics by preprocessing the text from March 2013 to February 2015. The interest index was defined to select the hot topics, and the k-means algorithm and SOM presented equivalent results with this data. We developed a decision tree model to detect hot topics with three algorithms: CHAID, CART, and C4.5. The results of CHAID were subpar compared to the others. We also employed SVM to detect the hot topics from negative data. The SVM models were trained with the radial basis function (RBF) kernel function by a grid search to detect the hot topics. The detection of hot topics by using sentiment analysis provides the latest trends and hot topics in the stock forum for investors so that they no longer need to search the vast amounts of information on the Web. Our proposed model is also helpful to rapidly determine customers' signals or attitudes towards government policy and firms' products and services.
Korean Peninsula is surrounded by ocean on three sides. Because of this geographical quality over 97% of export and import volumes are exchange by sea. Foreign ship and international passenger vessels carries foreign tourist and globalization and internationalization increases this trends. Leisure population grows with national income increase and interest of ocean. And accidents and incidents rates are also increases. Korea Coast Guard's jurisdiction area is 4.5 times bigger than our country. The length of coastline is 14,963km including islands. One patrol vessel is responsible for 24,068km and one coast guard substation is responsible for 94km. Efficient patrol activities can not be provided. This research focus on this problem. Analyze the status and trends of maritime crime and suggest efficient patrol activities. To deal with increasing maritime crime rate this study suggest to use geographical profile method which developed early 1900s in USA. This geographical profile analyse the spatial characteristic and mapping this result. With this result potential crime zone can be predicted. One of the result is hot spot management which gives data about habitual crime zone. In Korea National Police Agency adopt this method in 2008 and apply on patrol and crime prevention activity by analysis of different criteria. Korea National Police Agency analyse the crime rate with crime type, crime zone and potential crime zone, and hourly, regionally criteria. Korea Coast Guard need to adopt this method and apply on maritime to make maritime crime map, which shows type of crime with regional, periodical result. With this geographical profiling we can set a Criminal Point which shows the place where the crime often occurs. The Criminal Points are set with the data of numerous rates such as homicide, robbery, burglary, missing, collision which happened in ocean. Set this crime as the major crime and manage the data more thoroughly. I expect to enhance the reinforcement of marine crime using this Criminal Points. Because this points will give us efficient way to prevent the maritime crime by placing the patrol vessel where they needed most.
Ryu, Ji Myung;Hong, Kwang Pyo;Park, J.M. Sungil;Choi, Young Hyeon;Lee, Kye Hong
Journal of Radiation Protection and Research
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v.39
no.1
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pp.21-29
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2014
A new cold neutron triple-axis spectrometer (Cold-TAS) was recently constructed at the 30 MWth research reactor, HANARO. The spectrometer, which is composed of neutron optical components and radiation shield, required a redesign of the segmented monochromator shield due to the lack of adequate support of its weight. To shed some weight, lowering the height of the segmented shield was suggested while adding more radiation shield to the top cover of the monochromator chamber. To investigate the radiological effect of such change, we performed MCNPX simulations of a few different configurations of the Cold-TAS monochromator shield and obtained neutron and photon intensities at 5 reference points just outside the shield. Reducing the 35% of the height of the segmented shield and locating lead 10 cm from the bottom of the top cover made of polyethylene was shown to perform just as well as the original configuration as radiation shield excepting gamma flux at two points. Using gamma map by MCNPX, it was checked that is distribution of gamma. Increased flux had direction to the top and it had longer distance from top of segmented shield. However, because of reducing the 35% of the height, height of dissipated gamma was lower than original geometry. Reducing the 35% of the height of the segmented shield and locating lead 10cm from the bottom of the top cover was selected. After changing geometry, radiation dose was measured by TLD for confirming tester's safety at any condition. Neutron(0.21 ${\mu}Svhr^{-1}$) and gamma(3.69 ${\mu}Svhr^{-1}$) radiation dose were satisfied standard(6.25 ${\mu}Svhr^{-1}$).
Kim, He Min;Song, Ji Eun;Lee, Soon Min;Park, Min Soo;Park, Kook In;Namgung, Ran;Lee, Chul
Clinical and Experimental Pediatrics
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v.52
no.2
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pp.181-186
/
2009
Purpose : Inflammation plays a potential role in the pathogenesis of bronchopulmonary dysplasia (BPD). Strategies for preventing BPD include respiratory management, antioxidants, nutritional treatment, and others such as anti-inflammatory agents. We aimed to assess the safety, tolerability, and efficacy of montelukast (MK), a cysteinyl leukotriene 1 receptor antagonist, as an add-on therapy in BPD. Methods : In addition to currently available standard measures such as oxygen supplementation, bronchodilators, nutritional support, and/or diuretics, montelukast was administered to 15 preterm infants with BPD. MK was given orally (1 mg/kg/d) for a mean period of 12 weeks. We compared safety and efficacy parameters with historical controls. Results : All 15 patients survived, and no differences were found in the incidence of adverse reactions between the 2 groups. The ventilation index was significantly improved after 2 weeks in MK group compared with historical controls. There were no significant differences in other respiratory parameters (MAP, oxygen dependency, and ventilator dependency) between the groups, but the MK group showed trends of greater improvement. Conclusion : Administration of MK 1 mg/kg/d was well tolerated in preterm BPD patients as an add-on therapy. We demonstrated that after 2 weeks of MK administration of 1 mg/kg/d, MK had beneficial therapeutic effects on BPD patients as an add-on to the standard therapy. Further multicenter randomized controlled clinical trials are needed to confirm the efficacy and safety of MK as a useful supplement to standard therapy for BPD patients.
A cultural ecosystem service(CES), which is non-material benefit that human gains from ecosystem, has been recently further recognized as gross national income increases. Previous researches proposed to quantify the value of CES, which still remains as a challenging issue today due to its social and cultural subjectivity. This study proposes new way of assessing CES which is called Cultural Service Opportunity Spectrum(CSOS). CSOS is accessibility based CES assessment methodology for regional scale and it is designed to be applicable for any regions in Korea for supporting decision making process. CSOS employed public spatial data which are road network and population density map. In addition, the results of 'Rapid Assessment of Natural Assets' implemented by National Institute of Ecology, Korea were used as a complementary data. CSOS was applied to Namyangju-si and the methodology resulted in revealing specific areas with great accessibility to 'Natural Assets' in the region. Based on the results, the advantages and limitations of the methodology were discussed with regard to weighting three main factors and in contrast to Scenic Quality model and Recreation model of InVEST which have been commonly used for assessing CES today due to its convenience today.
As the internet technologies develop, the geographic information system environment is changing to the web-based service. Since geospatial information of the existing Web-GIS services were developed independently, there is no interoperability to support diverse map formats. In spite of the same geospatial information object it can be used for various proposes that is duplicated in GIS separately. It needs intelligent strategies for optimal replica selection, which is identification of replication geospatial information objects. And for management of replication objects, OMG, GLOBE and GRID computing suggested related frameworks. But these researches are not thorough going enough in case of geospatial information object. This paper presents a model of location service, which is supported for optimal selection among replication and management of replication objects. It is consist of tree main services. The first is binding service which can save names and properties of object defined by users according to service offers and enable clients to search them on the service of offers. The second is location service which can manage location information with contact records. And obtains performance information by the Load Sharing Facility on system independently with contact address. The third is intelligent selection service which can obtain basic/performance information from the binding service/location service and provide both faster access and better performance characteristics by rules as intelligent model based on rough sets. For the validity of location service model, this research presents the processes of location service execution with Graphic User Interface.
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