• Journal of Soil and Groundwater Environment
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• v.12 no.1
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• pp.97-102
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• 2007

An environmental survey from three abandoned metal mine areas was undertaken on to assess the risk of adverse health effects on human exposure to heavy metals influenced by past mining activities. Tailings contained high concentrations of heavy metals may have a impact on soils and waters around the tailing piles. In order to perform the human risk assessment, chemical analysis data of soils, rice grains and waters for As, Cd, Cu and Pb have been used. The HQ values for heavy metals via the rice consumption were significantly higher compared with other exposure pathways in all metal mine areas. The resulting HI values in three mine areas were higher than 9.0, and their toxic risk due to rice ingestion was strong in these mine areas. The cancer risk of being exposed to As by the rice consumption from the A, B and C mine areas was $5.1\;{\times}\;10^{-3}$, $6.8\;{\times}\;10^{-3}$ and $3.1\;{\times}\;10^{-3}$, respectively. The As cancer risk via the exposure pathway of rice ingestion from these mine areas exceeds the acceptable risk of 1 in 10,000 set for regulatory purposes. Thus, the daily intakes of rice by the local residents from these mine areas can pose a potential health threat if exposed by long-term As exposure.

• Journal of Korean Society of Forest Science
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• v.108 no.4
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• pp.540-551
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• 2019

This study was conducted to provide basic data for classifying patterns of land creep in 37 areas in South Korea using geological and soil property analyses. Geological time, as it relates to land creep areas in South Korea, had been most impactful for the Gyeongsang Supergroup and its sedimentary bedrock during the Cretaceous period. In this area, perfect ridge cliffs in land creeping areas included 20 plots (approximately 54.0%), while tension cracking areas with ambiguous ridge cliff characteristics included 17 plots (approximately 46.0%). Hesitant slide slope types included 20 plots (approximately 54.0%) within theslide slope of an incident pattern (slide slope figure) in land creeping areas. Colluvial debris types among land creep patterns were the most frequent and included 25 plots (approximately 68.0%). The direct causes of land creep were cutting of foothills, quarrying, land-clearing in mountains, mining exploration, and the creation of burial grounds, all of which added to geological impacts. Among land creeping areas, 27 plots (approximately 73.0%) were the result of man-made activities, and 10 plots (approximately 27.0%) were derived via natural causes such as earthquakes, heavy rainfall, and caving.

• Journal of the Korean Society of Mineral and Energy Resources Engineers
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• v.55 no.6
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• pp.588-595
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• 2018

This study has focused on evaluation of heavy metal contamination in seepage from 23 mine waste dumping sites in Korea. Seepage samples from the sites were taken and analyzed for heavy metals. The maximum levels (mg/L) in the samples were Al 53.98, As 16.19, Cd 1.15 Cu 37.30, Fe 28.64, Mn 39.00, Ni 0.097, Pb 0.750, and Zn 80.18. Among the sites, six mines were selected as continuous monitoring sites. As results of three months' monitoring of the sites, over the water guidelines for As, Cd, Cu, Fe, Mn, Zn and Al in seepage samples were found at two abandoned Au-Ag mines, Cd, Mn, Zn and Al at two Pb-Zn mines, and As, Fe and Mn at two other Fe-W mines. Therefore, those six mines need continuous monitoring on contamination assessment of seepage due to mining activities.

• Journal of Korean Library and Information Science Society
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• v.52 no.2
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• pp.25-44
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• 2021

In a situation where OA papers are increasing, POI, which indexes how open the research activities of individual researchers are, is drawing attention. This study investigated the existence of OA papers and the OA method published in international academic journals by domestic LIS researchers, and derived the researchers' POI based on this. In addition, by examining the relationship between the POI index and the researcher's amount of research papers, the research sub field, and the foreign co-authors, it was analyzed whether these factors are relevant to the researcher's POI. As a result, there were 492 papers by 82 researchers whose OA status and method were normally identified through Unpaywall. Second, only 20.7% of papers published in international journals were open accessed, and almost cases were gold and green methods. Third, there were many papers in text mining in medical journals, and the papers opened in the green method are open in institutional repositories of foreign co-authors or transnational subject repositories such as PMC. Third, the POI index was relatively higher for researchers in the field of informetrics, machine learning than other fields. In addition, it was analyzed that the presence or absence of overseas co-authors is related to OA.

• Economic and Environmental Geology
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• v.55 no.6
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• pp.717-726
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• 2022

This study was conducted to assess the geochemical contamination degree of As, Cd, Cu, Pb, Sb, and Zn in the soil and water samples from an abandoned gold mine. Enrichment Factor (EF), Geoaccumulation Index (Igeo), and Pollution Load Index (PLI) were carried out to assess the geochemical contamination degree of the soil samples. Variations of sulfate and heavy metals concentration in water samples were determined to identify the geochemical distribution with respect to the distance from the mine tailing dam. Geochemical pollution indices indicated significant contaminated with As, Cd, Pb, and Zn in the soil samples that areas close to the mine tailing dam, while, Sb showed similar indices in all soil samples. These results indicated that the As, Cd, Pb, and Zn dispersion has occurred via anthropogenic sources, such as mining activities. In terms of water samples, anomalies in the concentrations of As, Cd, Zn, and SO₄^2- was determined at specific area, in addition, the concentrations of the elements gradually decreased with distance. This result implies the heavy metals distribution in water has carried out by the weathering of sulfide minerals in the mine tailing and soil. The study area has been conducted the remediation of contaminated soil in the past, however, the geochemical dispersion of heavy metals was supposed to be occurred from the potential contamination source. Therefore, continuous monitoring of the soil and water is necessary after the completion of remediation.

• Journal of Industrial Convergence
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• v.21 no.5
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• pp.1-13
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• 2023

Carbon neutrality is the concept of reducing greenhouse gases emitted by human activities and making actual emissions zero through removal of remaining gases. It is also called "Net-Zero" and "carbon zero". Korea has declared a "2050 Carbon Neutrality policy" to cope with the climate change crisis. Various carbon reduction legislative processes are underway. Since carbon neutrality requires changes in industrial technology, it is important to prepare a system for carbon zero. This paper aims to understand the status and trends of global carbon neutrality technology. Therefore, ROK's web platform "www.naver.com." was selected as the data collection scope. Korean online articles related to carbon neutrality were collected. Carbon neutrality technology trends were analyzed by future signal methodology and Word2Vec algorithm which is a neural network deep learning technology. As a result, technology advancement in the steel and petrochemical sectors, which are carbon over-release industries, was required. Investment feasibility in the electric vehicle sector and technology advancement were on the rise. It seems that the government's support for carbon neutrality and the creation of global technology infrastructure should be supported. In addition, it is urgent to cultivate human resources, and possible to confirm the need to prepare support policies for carbon neutrality.

• Journal of Practical Engineering Education
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• v.15 no.3
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• pp.539-547
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• 2023

In recent years, university education has emphasized a learner-centered education model with a change in educational paradigm. This study aims to explore students' diverse opinions and improve the quality of education by analyzing the open-ended responses of university lecture evaluations using topic modeling. To this end, a total of 45,001 open-ended responses based on the results of lecture evaluations from 2017 to 2022 in non-metropolitan universities were divided into majors and liberal arts, and a short-form optimized Biterm Topic Modeling (BTM) analysis was conducted. As a result of the analysis, major lectures were divided into "attitude toward non-face-to-face classroom experience", "attitude toward questions and discussions", "attitude toward attendance and grading", "attitude toward practical activities and presentations", and "attitude toward communication and collaboration", while liberal arts lectures were divided into "attitude toward non-face-to-face classroom experience", "attitude toward grades and evaluations", "attitude toward attendance and syllabus", "attitude toward academic knowledge and interest", and "attitude toward communication and questions". The results of this study, which analyzed various feedback from students, provide insights that can be used to compare the characteristics of majors and liberal arts courses and improve teaching and learning experiences.

• Journal of Navigation and Port Research
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• v.48 no.1
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• pp.34-48
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• 2024

As global supply chain risks proliferate unpredictably, the high interdependence of port and logistics industry intensifies the risk burden. This study conducted fundamental research to explore diverse safety issues in domestic ports. Utilizing news article data about Busan Port, we employed LDA topic modeling and time-series linear regression to understand key safety trends. Over the past 30 years, Busan Port faced nine major safety issues-maritime safety, import cargo inspection, labor strikes, and natural disasters emerged cyclically. Major port safety issues in Busan Port are primarily characterized by an unpredictable nature, falling under socio-environmental and natural phenomena types, indicating a significant impact of global uncertainty. Therefore, systematic policies need to be formulated based on identified port safety issues to enhance port safety in Busan Port. Additionally, there is a need to strengthen the resilience of port safety for unpredictable risk situations. In conclusion, advanced research activities are necessary to promote port safety enhancement in response to dynamically changing social conditions.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.171-183
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• 2012

In the development of technologies, the exhibition industry has received much attention from governments and companies as an important way of marketing activities. Also, the exhibitors have considered the exhibition as new channels of marketing activities. However, the growing size of exhibitions for net square feet and the number of visitors naturally creates the competitive environment for them. Therefore, to make use of the effective marketing tools in these environments, they have planned and implemented many promotion technics. Especially, through smart environment which makes them provide real-time information for visitors, they can implement various kinds of promotion. However, promotions ignoring visitors' various needs and preferences can lose the original purposes and functions of them. That is, as indiscriminate promotions make visitors feel like spam, they can't achieve their purposes. Therefore, they need an approach using STP strategy which segments visitors through right evidences (Segmentation), selects the target visitors (Targeting), and give proper services to them (Positioning). For using STP Strategy in the smart exhibition environment, we consider these characteristics of it. First, an exhibition is defined as market events of a specific duration, which are held at intervals. According to this, exhibitors who plan some promotions should different events and promotions in each exhibition. Therefore, when they adopt traditional STP strategies, a system can provide services using insufficient information and of existing visitors, and should guarantee the performance of it. Second, to segment automatically, cluster analysis which is generally used as data mining technology can be adopted. In the smart exhibition environment, information of visitors can be acquired in real-time. At the same time, services using this information should be also provided in real-time. However, many clustering algorithms have scalability problem which they hardly work on a large database and require for domain knowledge to determine input parameters. Therefore, through selecting a suitable methodology and fitting, it should provide real-time services. Finally, it is needed to make use of data in the smart exhibition environment. As there are useful data such as booth visit records and participation records for events, the STP strategy for the smart exhibition is based on not only demographical segmentation but also behavioral segmentation. Therefore, in this study, we analyze a case of the promotion methodology which exhibitors can provide a differentiated service to segmented visitors in the smart exhibition environment. First, considering characteristics of the smart exhibition environment, we draw evidences of segmentation and fit the clustering methodology for providing real-time services. There are many studies for classify visitors, but we adopt a segmentation methodology based on visitors' behavioral traits. Through the direct observation, Veron and Levasseur classify visitors into four groups to liken visitors' traits to animals (Butterfly, fish, grasshopper, and ant). Especially, because variables of their classification like the number of visits and the average time of a visit can estimate in the smart exhibition environment, it can provide theoretical and practical background for our system. Next, we construct a pilot system which automatically selects suitable visitors along the objectives of promotions and instantly provide promotion messages to them. That is, based on the segmentation of our methodology, our system automatically selects suitable visitors along the characteristics of promotions. We adopt this system to real exhibition environment, and analyze data from results of adaptation. As a result, as we classify visitors into four types through their behavioral pattern in the exhibition, we provide some insights for researchers who build the smart exhibition environment and can gain promotion strategies fitting each cluster. First, visitors of ANT type show high response rate for promotion messages except experience promotion. So they are fascinated by actual profits in exhibition area, and dislike promotions requiring a long time. Contrastively, visitors of GRASSHOPPER type show high response rate only for experience promotion. Second, visitors of FISH type appear favors to coupon and contents promotions. That is, although they don't look in detail, they prefer to obtain further information such as brochure. Especially, exhibitors that want to give much information for limited time should give attention to visitors of this type. Consequently, these promotion strategies are expected to give exhibitors some insights when they plan and organize their activities, and grow the performance of them.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.149-169
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• 2020

"The Urban Renewal New Deal project", one of the government's major national projects, is about developing underdeveloped areas by investing 50 trillion won in 100 locations on the first year and 500 over the next four years. This project is drawing keen attention from the media and local governments. However, the project model which fails to reflect the original characteristics of the area as it divides project area into five categories: "Our Neighborhood Restoration, Housing Maintenance Support Type, General Neighborhood Type, Central Urban Type, and Economic Base Type," According to keywords for successful urban regeneration in Korea, "resident participation," "regional specialization," "ministerial cooperation" and "public-private cooperation", when local governments propose urban regeneration projects to the government, they can see that it is most important to accurately understand the characteristics of the city and push ahead with the projects in a way that suits the characteristics of the city with the help of local residents and private companies. In addition, considering the gentrification problem, which is one of the side effects of urban regeneration projects, it is important to select and implement urban regeneration types suitable for the characteristics of the area. In order to supplement the limitations of the 'Urban Regeneration New Deal Project' methodology, this study aims to propose a system that recommends urban regeneration types suitable for urban regeneration sites by utilizing various machine learning algorithms, referring to the urban regeneration types of the '2025 Seoul Metropolitan Government Urban Regeneration Strategy Plan' promoted based on regional characteristics. There are four types of urban regeneration in Seoul: "Low-use Low-Level Development, Abandonment, Deteriorated Housing, and Specialization of Historical and Cultural Resources" (Shon and Park, 2017). In order to identify regional characteristics, approximately 100,000 text data were collected for 22 regions where the project was carried out for a total of four types of urban regeneration. Using the collected data, we drew key keywords for each region according to the type of urban regeneration and conducted topic modeling to explore whether there were differences between types. As a result, it was confirmed that a number of topics related to real estate and economy appeared in old residential areas, and in the case of declining and underdeveloped areas, topics reflecting the characteristics of areas where industrial activities were active in the past appeared. In the case of the historical and cultural resource area, since it is an area that contains traces of the past, many keywords related to the government appeared. Therefore, it was possible to confirm political topics and cultural topics resulting from various events. Finally, in the case of low-use and under-developed areas, many topics on real estate and accessibility are emerging, so accessibility is good. It mainly had the characteristics of a region where development is planned or is likely to be developed. Furthermore, a model was implemented that proposes urban regeneration types tailored to regional characteristics for regions other than Seoul. Machine learning technology was used to implement the model, and training data and test data were randomly extracted at an 8:2 ratio and used. In order to compare the performance between various models, the input variables are set in two ways: Count Vector and TF-IDF Vector, and as Classifier, there are 5 types of SVM (Support Vector Machine), Decision Tree, Random Forest, Logistic Regression, and Gradient Boosting. By applying it, performance comparison for a total of 10 models was conducted. The model with the highest performance was the Gradient Boosting method using TF-IDF Vector input data, and the accuracy was 97%. Therefore, the recommendation system proposed in this study is expected to recommend urban regeneration types based on the regional characteristics of new business sites in the process of carrying out urban regeneration projects."