• Title/Summary/Keyword: Urban Mining

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Evaluation on Utilization of the Health Care Service in One Urban Area in Korea (일개지역의 보건의료서비스 이용 평가;Y지역의 대학병원과 보건소 데이터베이스를 통하여)

  • Lee, Byung-Wha;Ahn, Sung-Hee
    • Journal of Korean Academy of Nursing Administration
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    • v.11 no.4
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    • pp.401-414
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    • 2005
  • Purpose: This study was to evaluate the utilization of health care service and to provide supportive data for health care policy making in one urban area in Korea. Method: This study tested the significance of public health service using the database of an university hospital and public health center from Feb. 2000 to Dec. 2004. Data were analyzed by multidimensional analysis and data mining technique and produced the information on the classification of utilization characteristics by main disease and the total cost of use and disease association with the users of the public health center. Results: The Results were as follows: 1) Top 10 diseases in the area accounted for 22.4% of total frequency for the most recent 5 years in university hospital, while 59.0% in public health center. 2) There were significant correlations between university hospital and public health center user's insurance type and place of residence: It showed higher use of public health center for free service beneficiaries residing in Seoul than residents in nearby or local area. The medical insurance types for hospital users were more various than those for public health center users. 3) The use of hospital for patients of hypertension, diabetes mellitus and hyperlipidemia was tended to concentrate in mostly autumn and winter since August 2000, while the cost of using public health center for those patients has been steadily reduced since July 2000. 4) As a result of cluster analysis, there were classified into three homogeneous groups according to the total cost of using public health service, age, and the frequency of use. 5) The association analysis on patients with chronic disease in public health center produced a detailed information on accompanying diseases related to the incidence rate of disease of high frequency due to aging, information on drug abuse and immune disease. Conclusion: The health care policy for local community should be evaluated continuously. And the policy to build an integrated data warehousing by public health indicator system and to enhance the faithfulness of data is required.

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Status and Strategy on Recycling of Domestic Used Chemical Catalysts (국내 사용 후 화학촉매제품의 재자원화 현황 및 향후 방향)

  • Kim, Young-Chun;Kang, Hong-Yoon
    • Resources Recycling
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    • v.26 no.3
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    • pp.3-16
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    • 2017
  • Chemical catalyst products are applied to various fields such as petrochemical process, air pollution prevention facility and automobile exhaust gas purifier. The domestic and overseas chemical catalyst market is increasing every year, and the amount of waste catalyst generated thereby is also increasing. Most of the used chemical catalyst products, such as desulfurized waste catalysts and automobile waste catalysts containing valuable metals are important recyclable resources from a substitute resource point of view. The recycling processes for recovering valuable metals have been commercialized through some urban mining companies, and SCR denitration catalysts have been recycled through some remanufacturing companies. In this paper, the amount of domestic production and recycling of major catalyst products have thus been investigated and analyzed so as to be used as basic data for establishing industrial support policy for recycling of used chemical catalyst products. Also tasks for promoting the recycling of used chemical catalyst products are suggested.

Analysis of Commercial Recycling Technology and Research Trend of Printed Circuit Boards in Korea (국내 인쇄회로기판의 재활용 상용화 기술 및 연구동향 분석)

  • An, HyeLan;Kang, Leeseung;Lee, Chan-Gi
    • Resources Recycling
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    • v.26 no.4
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    • pp.9-18
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    • 2017
  • Recently, the amount of electronic scrap is rapidly increasing due to the rapid growth of the electronics industry. Among the components of electronic scrap, the printed circuit board(PCB) is an important recycling target which includes common metals, precious metals, and rare metals such as gold, silver, copper, tin, nickel and so on. In Korea, however, PCB recycling technologies are mainly commercialized by some major companies, and other process quantities are not accurately counted. According to present situation, several urban mining companies, research institutes, and universities are conducting research on recovery of valuable metals from PCBs and/or reusing them as raw materials that is different from existing commercialization process developed by major companies. In this study, we analyzed not only current status of collection/disposal process and recycling of waste PCBs in Korea but also the trend of recycling technologies in order to help resource circulation from waste PCBs become more active.

The Analysis of Research Trends in Technology to the Fourth Industrial Revolution using SNA (소셜 네트워크 분석을 이용한 4차 산업혁명 기술 분야의 연구 동향 분석)

  • Kim, Hong-Gwang;Ahn, Jong-Wook
    • Journal of Cadastre & Land InformatiX
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    • v.49 no.1
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    • pp.113-121
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    • 2019
  • The fourth industrial revolution technology focused on the fusion of infrastructure and various advanced technologies related city. Therefore, technical cooperation in various fields of research is essential. In order to activating the fourth industrial revolution technologies, it is necessary to research the state of technology in various fields. Consequently, this paper aims to analysis of domestic and foreign research trends on technology to the fourth industrial revolution using SNA and text mining for web site. We collected text, date data of research paper and report in web site for five years, that is, from January 1st in 2014 to December 31st in 2018. Next, we have deduced the major keywords in public data through analyzing the morphemes. Then we have analyzed the core and related keyword lists through an SNA. In Korea, the focus is on R&D and legal/institutional solution in relation to the fourth industrial revolution technology. On the other hand, in the case of foreign, there was focus on practical technologies for urban services in detail aspects.

Suggestion of Urban Regeneration Type Recommendation System Based on Local Characteristics Using Text Mining (텍스트 마이닝을 활용한 지역 특성 기반 도시재생 유형 추천 시스템 제안)

  • Kim, Ikjun;Lee, Junho;Kim, Hyomin;Kang, Juyoung
    • 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."

Heavy Metal Pollution in Sub-Saharan Africa and Possible Implications in Cancer Epidemiology

  • Fasinu, Pius Sedowhe;Orisakwe, Orish Ebere
    • Asian Pacific Journal of Cancer Prevention
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    • v.14 no.6
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    • pp.3393-3402
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    • 2013
  • The increasing scourge of cancer epidemiology is a global concern. With WHO emphasizing that 40% of all cancer cases are preventable, exposure to known and suspected carcinogens must be discouraged. The battle with communicable diseases and other third world challenges has greatly de-emphasized anti-cancer campaigns in sub-Saharan Africa. The abundant deposit of mineral resources in sub-Saharan Africa has attracted high mining activity with its negative environmental aftermath. Poor regulatory mechanisms have led to environmental contamination by products of mining including heavy metals. In addition to poor urban planning, the springing up of settlements in industrial areas has led to generation and exposure to more hazardous wastes consequent on poor disposal systems. Studies establishing close association between exposure to heavy metals and cancer epidemiology in sub-Saharan Africa are increasing. The current review assesses the level of environmental pollution by heavy metals in sub-Saharan Africa, and brings to the fore available evidence implicating such in the increasing cancer epidemiology in the sub-continent.

Appropriate Technologies for Municipal Solid Waste Management in Bantayan Island, Philippines

  • Yu, Kwang Sun;Thriveni, Thenepalli;Jang, Changsun;Whan, Ahn Ji
    • Journal of Energy Engineering
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    • v.26 no.1
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    • pp.54-61
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    • 2017
  • In general, solid waste arises from lots of human activities such as domestic, agricultural, industrial, commercial, waste water treatment, construction, and mining activities etc. If the waste is not properly disposal and treated, it will have a negative impact to the environment, and hygienic conditions in urban areas and pollute the air with greenhouse gases (GHG), ground water, as well as the soil and crops. In this paper, the Carbon Resources Recycling Appropriate Technology Center feasibility studies are reported at Bantayan Island, Philippines on the municipal solid waste management. The present objective of our study is to characterize the municipal solid waste incineration (MSWI) bottom ash and case study of MSWI production status in Bantayan, Philippines. Currently, wide variety of smart technologies available for MSWI management in developed countries. Recycling is the other major alternative process for MSWI landfill issues. In this paper, the feasibility studies of applied appropriate technologies for the municipal solid waste generation in Bantayan Island, Philippines are reported.

A Time Series Analysis of Urban Park Behavior Using Big Data (빅데이터를 활용한 도시공원 이용행태 특성의 시계열 분석)

  • Woo, Kyung-Sook;Suh, Joo-Hwan
    • Journal of the Korean Institute of Landscape Architecture
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    • v.48 no.1
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    • pp.35-45
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    • 2020
  • This study focused on the park as a space to support the behavior of urban citizens in modern society. Modern city parks are not spaces that play a specific role but are used by many people, so their function and meaning may change depending on the user's behavior. In addition, current online data may determine the selection of parks to visit or the usage of parks. Therefore, this study analyzed the change of behavior in Yeouido Park, Yeouido Hangang Park, and Yangjae Citizen's Forest from 2000 to 2018 by utilizing a time series analysis. The analysis method used Big Data techniques such as text mining and social network analysis. The summary of the study is as follows. The usage behavior of Yeouido Park has changed over time to "Ride" (Dynamic Behavior) for the first period (I), "Take" (Information Communication Service Behavior) for the second period (II), "See" (Communicative Behavior) for the third period (III), and "Eat" (Energy Source Behavior) for the fourth period (IV). In the case of Yangjae Citizens' Forest, the usage behavior has changed over time to "Walk" (Dynamic Behavior) for the first, second, and third periods (I), (II), (III) and "Play" (Dynamic Behavior) for the fourth period (IV). Looking at the factors affecting behavior, Yeouido Park was had various factors related to sports, leisure, culture, art, and spare time compared to Yangjae Citizens' Forest. The differences in Yangjae Citizens' Forest that affected its main usage behavior were various elements of natural resources. Second, the behavior of the target areas was found to be focused on certain main behaviors over time and played a role in selecting or limiting future behaviors. These results indicate that the space and facilities of the target areas had not been utilized evenly, as various behaviors have not occurred, however, a certain main behavior has appeared in the target areas. This study has great significance in that it analyzes the usage of urban parks using Big Data techniques, and determined that urban parks are transformed into play spaces where consumption progressed beyond the role of rest and walking. The behavior occurring in modern urban parks is changing in quantity and content. Therefore, through various types of discussions based on the results of the behavior collected through Big Data, we can better understand how citizens are using city parks. This study found that the behavior associated with static behavior in both parks had a great impact on other behaviors.

Citizen Sentiment Analysis of the Social Disaster by Using Opinion Mining (오피니언 마이닝 기법을 이용한 사회적 재난의 시민 감성도 분석)

  • Seo, Min Song;Yoo, Hwan Hee
    • Journal of Korean Society for Geospatial Information Science
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    • v.25 no.1
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    • pp.37-46
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    • 2017
  • Recently, disaster caused by social factors is frequently occurring in Korea. Prediction about what crisis could happen is difficult, raising the citizen's concern. In this study, we developed a program to acquire tweet data by applying Python language based Tweepy plug-in, regarding social disasters such as 'Nonspecific motive crimes' and 'Oxy' products. These data were used to evaluate psychological trauma and anxiety of citizens through the text clustering analysis and the opinion mining analysis of the R Studio program after natural language processing. In the analysis of the 'Oxy' case, the accident of Sewol ferry, the continual sale of Oxy products of the Oxy had the highest similarity and 'Nonspecific motive crimes', the coping measures of the government against unexpected incidents such as the 'incident' of the screen door, the accident of Sewol ferry and 'Nonspecific motive crime' due to misogyny in Busan, had the highest similarity. In addition, the average index of the Citizens sentiment score in Nonspecific motive crimes was more negative than that in the Oxy case by 11.61%p. Therefore, it is expected that the findings will be utilized to predict the mental health of citizens to prevent future accidents.

Visualizing Spatial Information of Climate Change Impacts on Social Infrastructure using Text-Mining Method (텍스트마이닝 기법을 활용한 사회기반시설 기후변화 영향의 공간정보 표출)

  • Shin, Hana;Ryu, Jaena
    • Korean Journal of Remote Sensing
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    • v.33 no.5_3
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    • pp.773-786
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    • 2017
  • This study was to analyze data of climate change impacts on social infrastructure using text-mining methodology, and to visualize the spatial information by integrating those with regional data layers. First of all, the study identified that the following social infrastructure; power, oil and resource management, transport and urban, environment, and water supply infrastructures, were affected by five kinds of climate factors (heat wave, cold wave, heavy rain, heavy snow, strong wind). Climate change impacts on social infrastructure were then analyzed and visualized by regions. The analysis resulted that transport and urban infrastructures among all kinds of infrastructure were highly impacted by climate change, and the most severe factors of the climate impacts on social infrastructure were heavy rain and heavy snow. In addition, it found out that social infrastructure located in Seoul and Gangwon-do region were relatively largely affected by climate change. This study has significance that atypical data in media was used to analyze climate change impacts on social infrastructure and the results were translated into spatial information data to analyze and visualize the climate change impacts by regions.