• Journal of Soil and Groundwater Environment
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• v.12 no.1
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• pp.87-96
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• 2007

Risk assessment was carried out in order to improve the remediation and management strategy on a contaminated gunnery site, where a flood control reservoir is under construction nearby. Six chemicals, including explosive chemicals and heavy metals, which were suspected to possess risk to humans by leaching events from the site were the target pollutants for the assessment. A site-specific conceptual site model was constructed based on effective, reasonable exposure pathways to avoid any overestimation of the risk. Also, conservative default values were adapted to prevent underestimation of the risk when site-specific values were not available. The risks of the six contaminants were calculated by API's Decision Support System for Exposure and Risk Assessment with several assumptions. In the crater-formed-area(Ac), the non-carcinogenic risks(i.e., HI values) of TNT(Tri-Nitro-Toluene) and Cd were slightly larger than 1, and for RDX(Royal Demolition Explosives), over 50. The total non-carcinogenic risk of the whole gunnery range calculated to a significantly high value of 62.5. Carcinogenicity of Cd was estimated to be about $10^{-3}$, while that of Pb was about $5\;{\times}\;10^{-4}$, which greatly exceeded the generally acceptable carcinogenic risk level of $10^{-4}{\sim}10^{-6}$. The risk assessment results suggest that an immediate remediation practice for both carcinogens and non-carcinogens are required before the reservoir construction. However, for more accurate risk assessment, more specific estimations on condition shifts due to the construction of the reservoir are required, and more over, the effects of the pollutants to the ecosystem is also necessary to be evaluated.

• Economic and Environmental Geology
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• v.52 no.5
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• pp.499-508
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• 2019

Based on the preliminary surveys for the occurrences of the Muwellut chrome-nickel mineralized zone ($800km^2$) in northwestern Myanmar, Bophivum area was selected as the detailed exploration area after considering data source, geological potential, metallogenic province, necessity of resource development on target mineral, exploration activity, grade, ore deposit type, nearby operating mine, infrastructure and exploration prediction effect. From 2013 to 2016, KIGAM and DGSE carried out geological and geochemical survey with 1:1,000 scale, magnetic survey(areal extent, $1.672km^2$), trench survey(19 trench, total length 392 m), pitting survey(18 pit, total depth 42.6m), exploration drilling(6holes 600m, 2015; 13holes 617.4m). We analyzed Cr and Ni contents of 77 drill cores with specific gravity in Yangon DGSE analytical center. Considering surface geological survey, geochemical exploration, magnetic survey, trench survey and drilling data, we divided Bophivum area into 8 blocks. Resource estimation are divided into measured and indicated resources. Measured resource is about 9,790t and indicated resource is about 12,080t with the average grade of Cr 11.8% and Ni 0.34%. In case of Bophivum area, if we develop by tying up Webula chrome mineralized zone in the south, it will be possible to upgrade the medium-scale mine. Geologically, the ophiolite belt are distributed in the western and eastern part in Myanmar. So, the exploration technology obtained from exploation in Bophivum area will be helpful to discover the hidden chromitite ore body in Myanmar ophiolite belt in the future.

• Journal of Environmental Impact Assessment
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• v.27 no.6
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• pp.562-581
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• 2018

This study was designed to predict the changes in species richness of plants under the climate change in South Korea. The target species were selected based on the Plants Adaptable to Climate Change in the Korean Peninsula. Altogether, 89 species including 23 native plants, 30 northern plants, and 36 southern plants. We used the Species Distribution Model to predict the potential habitat of individual species under the climate change. We applied ten single-model algorithms and the pre-evaluation weighted ensemble method. And then, species richness was derived from the results of individual species. Two representative concentration pathways (RCP 4.5 and RCP 8.5) were used to simulate the species richness of plants in 2050 and 2070. The current species richness was predicted to be high in the national parks located in the Baekdudaegan mountain range in Gangwon Province and islands of the South Sea. The future species richness was predicted to be lower in the national park and the Baekdudaegan mountain range in Gangwon Province and to be higher for southern coastal regions. The average value of the current species richness showed that the national park area was higher than the whole area of South Korea. However, predicted species richness were not the difference between the national park area and the whole area of South Korea. The difference between current and future species richness of plants could be the disappearance of a large number of native and northern plants from South Korea. The additional reason could be the expansion of potential habitat of southern plants under climate change. However, if species dispersal to a suitable habitat was not achieved, the species richness will be reduced drastically. The results were different depending on whether species were dispersed or not. This study will be useful for the conservation planning, establishment of the protected area, restoration of biological species and strategies for adaptation of climate change.

• Korean Journal of Poultry Science
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• v.46 no.1
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• pp.31-37
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• 2019

A chicken clathrin-associated adaptor protein $3-{\delta}$ subunit 2 (AP3S2) is a subunit of AP3, which is involved in cargo protein trafficking to target membrane with clathrin-coated vesicles. AP3S2 may play a role in virus entry into host cells through clathrin-dependent endocytosis. AP3S2 is also known to participate in metabolic disease developments of progressions, such as liver fibrosis with hepatitis C virus infection and type 2 diabetes mellitus. Chicken AP3S2 (chAP3S2) gene was originally identified as one of the differentially expressed genes (DEGs) in chicken kidney which was fed with different calcium doses. This study aims to characterize the molecular characteristics, gene expression patterns, and transcriptional regulation of chAP3S2 in response to the stimulation of Toll-like receptor 3 (TLR3) to understand the involvement of chAP3S2 in metabolic disease in chicken. As a result, the structure prediction of chAP3S2 gene revealed that the gene is highly conserved among AP3S2 orthologs from other species. Evolutionarily, it was suggested that chAP3S2 is relatively closely related to zebrafish, and fairly far from mammal AP3S2. The transcriptional profile revealed that chAP3S2 gene was highly expressed in chicken lung and spleen tissues, and under the stimulation of poly (I:C), the chAP3S2 expression was down-regulated in DF-1 cells (P<0.05). However, the presence of the transcriptional inhibitors, BAY 11-7085 (Bay) as an inhibitor for nuclear factor ${\kappa}B$ ($NF{\kappa}B$) or Tanshinone IIA (Tan-II) as an inhibitor for activated protein 1 (AP-1), did not affect the expressional level of chAP3S2, suggesting that these transcription factors might be dispensable for TLR3 mediated repression. These results suggest that chAP3S2 gene may play a significant role against viral infection and be involved in TLR3 signaling pathway. Further study about the transcriptional regulation of chAP3S2 in TLR3 pathways and the mechanism of chAP3S2 upon virus entry shall be needed.

• The Journal of Engineering Geology
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• v.30 no.4
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• pp.457-468
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• 2020

Problems arising during pile design works for plant construction, civil and architecture work are mostly come from uncertainty of geotechnical characteristics. In particular, obtaining the N-value measured through the Standard Penetration Test (SPT) is the most important data. However, it is difficult to obtain N-value by drilling investigation throughout the all target area. There are many constraints such as licensing, time, cost, equipment access and residential complaints etc. it is impossible to obtain geotechnical characteristics through drilling investigation within a short bidding period in overseas. The geotechnical characteristics at non-drilling investigation points are usually determined by the engineer's empirical judgment, which can leads to errors in pile design and quantity calculation causing construction delay and cost increase. It would be possible to overcome this problem if N-value could be predicted at the non-drilling investigation points using limited minimum drilling investigation data. This study was conducted to predicted the N-value using an Artificial Neural Network (ANN) which one of the Artificial intelligence (AI) method. An Artificial Neural Network treats a limited amount of geotechnical characteristics as a biological logic process, providing more reliable results for input variables. The purpose of this study is to predict N-value at the non-drilling investigation points through patterns which is studied by multi-layer perceptron and error back-propagation algorithms using the minimum geotechnical data. It has been reviewed the reliability of the values that predicted by AI method compared to the measured values, and we were able to confirm the high reliability as a result. To solving geotechnical uncertainty, we will perform sensitivity analysis of input variables to increase learning effect in next steps and it may need some technical update of program. We hope that our study will be helpful to design works in the future.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.23-48
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• 2021

The Korean economy has achieved continuous economic growth for the past several decades thanks to the government's export strategy policy. This increase in exports is playing a leading role in driving Korea's economic growth by improving economic efficiency, creating jobs, and promoting technology development. Traditionally, the main factors affecting Korea's exports can be found from two perspectives: economic factors and industrial structural factors. First, economic factors are related to exchange rates and global economic fluctuations. The impact of the exchange rate on Korea's exports depends on the exchange rate level and exchange rate volatility. Global economic fluctuations affect global import demand, which is an absolute factor influencing Korea's exports. Second, industrial structural factors are unique characteristics that occur depending on industries or products, such as slow international division of labor, increased domestic substitution of certain imported goods by China, and changes in overseas production patterns of major export industries. Looking at the most recent studies related to global exchanges, several literatures show the importance of cultural aspects as well as economic and industrial structural factors. Therefore, this study attempted to develop a forecasting model by considering cultural factors along with economic and industrial structural factors in calculating the import volume of each country from Korea. In particular, this study approaches the influence of cultural factors on imports of Korean products from the perspective of PUSH-PULL framework. The PUSH dimension is a perspective that Korea develops and actively promotes its own brand and can be defined as the degree of interest in each country for Korean brands represented by K-POP, K-FOOD, and K-CULTURE. In addition, the PULL dimension is a perspective centered on the cultural and psychological characteristics of the people of each country. This can be defined as how much they are inclined to accept Korean Flow as each country's cultural code represented by the country's governance system, masculinity, risk avoidance, and short-term/long-term orientation. The unique feature of this study is that the proposed final prediction model can be selected based on Design Principles. The design principles we presented are as follows. 1) A model was developed to reflect interest in Korea and cultural characteristics through newly added data sources. 2) It was designed in a practical and convenient way so that the forecast value can be immediately recalled by inputting changes in economic factors, item code and country code. 3) In order to derive theoretically meaningful results, an algorithm was selected that can interpret the relationship between the input and the target variable. This study can suggest meaningful implications from the technical, economic and policy aspects, and is expected to make a meaningful contribution to the export support strategies of small and medium-sized enterprises by using the import forecasting model.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.99-112
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• 2021

This study was performed to predict spatial change of future forestland area in South Korea at regional level for supporting forest-related plans established by local governments. In the study, land use was classified to three types which are forestland, agricultural land, and urban and other lands. A logistic regression model was developed using transitional interaction between each land use type and topographical factors, land use restriction factors, socioeconomic indices, and development infrastructures. In this model, change probability from a target land use type to other land use types was estimated using raster dataset(30m×30m) for each variable. With priority order map based on the probability of land use change, the total annual amount of land use change was allocated to the cells in the order of the highest transition potential for the spatial analysis. In results, it was found that slope degree and slope standard value by the local government were the main factors affecting the probability of change from forestland to urban and other land. Also, forestland was more likely to change to urban and other land in the conditions of a more gentle slope, lower slope criterion allowed to developed, and higher land price and population density. Consequently, it was predicted that forestland area would decrease by 2027 due to the change from forestland to urban and others, especially in metropolitan and major cities, and that forestland area would increase between 2028 and 2050 in the most local provincial cities except Seoul, Gyeonggi-do, and Jeju Island due to locality extinction with decline in population. Thus, local government is required to set an adequate forestland use criterion for balanced development, reasonable use and conservation, and to establish the regional forest strategies and policies considering the future land use change trends.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.694-709
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• 2021

Purpose: In this study, earthquake-induced landslide risk assessment was conducted to provide basic data for efficient and preemptive damage prevention by selecting the erosion control work before the earthquake and the prediction and restoration priorities of the damaged area after the earthquake. Method: The study analyzed the previous studies abroad to examine the evaluation methodology and to derive the evaluation factors, and examine the utilization of the landslide hazard map currently used in Korea. In addition, the earthquake-induced landslide hazard map was also established on a pilot basis based on the fault zone and epicenter of Pohang using seismic attenuation. Result: The earthquake-induced landslide risk assessment study showed that China ranked 44%, Italy 16%, the U.S. 15%, Japan 10%, and Taiwan 8%. As for the evaluation method, the statistical model was the most common at 59%, and the physical model was found at 23%. The factors frequently used in the statistical model were altitude, distance from the fault, gradient, slope aspect, country rock, and topographic curvature. Since Korea's landslide hazard map reflects topography, geology, and forest floor conditions, it has been shown that it is reasonable to evaluate the risk of earthquake-induced landslides using it. As a result of evaluating the risk of landslides based on the fault zone and epicenter in the Pohang area, the risk grade was changed to reflect the impact of the earthquake. Conclusion: It is effective to use the landslide hazard map to evaluate the risk of earthquake-induced landslides at the regional scale. The risk map based on the fault zone is effective when used in the selection of a target site for preventive erosion control work to prevent damage from earthquake-induced landslides. In addition, the risk map based on the epicenter can be used for efficient follow-up management in order to prioritize damage prevention measures, such as to investigate the current status of landslide damage after an earthquake, or to restore the damaged area.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.101-114
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• 2023

In the wartime, aircraft carrying out a mission to strike the enemy deep in the depth are exposed to the risk of being shoot down. As a key combat force in mordern warfare, it takes a lot of time, effot and national budget to train military flight personnel who operate high-tech weapon systems. Therefore, this study studied the path problem of predicting the route of emergency escape from enemy territory to the target point to avoid obstacles, and through this, the possibility of safe recovery of emergency escape military flight personnel was increased. based problem, transforming the problem into a TSP, VRP, and Dijkstra algorithm, and approaching it with an optimization technique. However, if this problem is approached in a network problem, it is difficult to reflect the dynamic factors and uncertainties of the battlefield environment that military flight personnel in distress will face. So, MDP suitable for modeling dynamic environments was applied and studied. In addition, GIS was used to obtain topographic information data, and in the process of designing the reward structure of MDP, topographic information was reflected in more detail so that the model could be more realistic than previous studies. In this study, value iteration algorithms and deterministic methods were used to derive a path that allows the military flight personnel in distress to move to the shortest distance while making the most of the topographical advantages. In addition, it was intended to add the reality of the model by adding actual topographic information and obstacles that the military flight personnel in distress can meet in the process of escape and escape. Through this, it was possible to predict through which route the military flight personnel would escape and escape in the actual situation. The model presented in this study can be applied to various operational situations through redesign of the reward structure. In actual situations, decision support based on scientific techniques that reflect various factors in predicting the escape route of the military flight personnel in distress and conducting combat search and rescue operations will be possible.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.57-77
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• 2013

Social media has become one of the most popular media in web and mobile application. In 2011, social networks and blogs are still the top destination of online users, according to a study from Nielsen Company. In their studies, nearly 4 in 5active users visit social network and blog. Social Networks and Blogs sites rule Americans' Internet time, accounting to 23 percent of time spent online. Facebook is the main social network that the U.S internet users spend time more than the other social network services such as Yahoo, Google, AOL Media Network, Twitter, Linked In and so on. In recent trend, most of the companies promote their products in the Facebook by creating the "Facebook Page" that refers to specific product. The "Like" option allows user to subscribed and received updates their interested on from the page. The film makers which produce a lot of films around the world also take part to market and promote their films by exploiting the advantages of using the "Facebook Page". In addition, a great number of streaming service providers allows users to subscribe their service to watch and enjoy movies and TV program. They can instantly watch movies and TV program over the internet to PCs, Macs and TVs. Netflix alone as the world's leading subscription service have more than 30 million streaming members in the United States, Latin America, the United Kingdom and the Nordics. As the matter of facts, a million of movies and TV program with different of genres are offered to the subscriber. In contrast, users need spend a lot time to find the right movies which are related to their interest genre. Recent years there are many researchers who have been propose a method to improve prediction the rating or preference that would give the most related items such as books, music or movies to the garget user or the group of users that have the same interest in the particular items. One of the most popular methods to build recommendation system is traditional Collaborative Filtering (CF). The method compute the similarity of the target user and other users, which then are cluster in the same interest on items according which items that users have been rated. The method then predicts other items from the same group of users to recommend to a group of users. Moreover, There are many items that need to study for suggesting to users such as books, music, movies, news, videos and so on. However, in this paper we only focus on movie as item to recommend to users. In addition, there are many challenges for CF task. Firstly, the "sparsity problem"; it occurs when user information preference is not enough. The recommendation accuracies result is lower compared to the neighbor who composed with a large amount of ratings. The second problem is "cold-start problem"; it occurs whenever new users or items are added into the system, which each has norating or a few rating. For instance, no personalized predictions can be made for a new user without any ratings on the record. In this research we propose a clustering method according to the users' genre interest extracted from social network service (SNS) and user's movies rating information system to solve the "cold-start problem." Our proposed method will clusters the target user together with the other users by combining the user genre interest and the rating information. It is important to realize a huge amount of interesting and useful user's information from Facebook Graph, we can extract information from the "Facebook Page" which "Like" by them. Moreover, we use the Internet Movie Database(IMDb) as the main dataset. The IMDbis online databases that consist of a large amount of information related to movies, TV programs and including actors. This dataset not only used to provide movie information in our Movie Rating Systems, but also as resources to provide movie genre information which extracted from the "Facebook Page". Formerly, the user must login with their Facebook account to login to the Movie Rating System, at the same time our system will collect the genre interest from the "Facebook Page". We conduct many experiments with other methods to see how our method performs and we also compare to the other methods. First, we compared our proposed method in the case of the normal recommendation to see how our system improves the recommendation result. Then we experiment method in case of cold-start problem. Our experiment show that our method is outperform than the other methods. In these two cases of our experimentation, we see that our proposed method produces better result in case both cases.