• 제목/요약/키워드: Environmental of Big Data

검색결과 399건 처리시간 0.03초

Artificial-Neural-Network-based Night Crime Prediction Model Considering Environmental Factors

  • Lee, Juwon;Jeong, Yongwook;Jung, Sungwon
    • Architectural research
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    • 제24권1호
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    • pp.1-11
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    • 2022
  • As the occurrence of a crime is dependent on different factors, their correlations are beyond the ordinary cognitive range. Owing to this limitation, systems face difficulty in correlating various factors, thereby requiring the assistance of artificial intelligence (AI) to overcome such limitations. Therefore, AI has become indispensable for crime prediction. Crimes can cause severe and irrevocable damage to a society. Recently, big data has been introduced for developing highly accurate models for crime prediction. Prediction of night crimes should be given significant consideration, because crimes primarily occur during nights, when the spatiotemporal characteristics become vulnerable to crimes. Many environmental factors that influence crime rate are applied for crime prediction, and their influence on crime rate may differ based on temporal characteristics and the nature of crime. This study aims to identify the environmental factors that influence sex and theft crimes occurring at night and proposes an artificial neural network (ANN) model to predict sex and theft crimes at night in random areas. The crime data of A district in Seoul for 12 years (2004-2015) was used, and environmental factors that influence sex and theft crimes were derived through multiple regression analysis. Two types of crime prediction models were developed: Type A using all environmental factors as input data; Type B with only the significant factors (obtained from regression analysis) as input data. The Type B model exhibited a greater accuracy than Type A, by 3.26 and 9.47 % higher for theft and sex crimes, respectively.

IoT 도시빅데이터를 활용한 도로교통특성과 유해환경요인 간 영향관계 분석 (Impact of Road Traffic Characteristics on Environmental Factors Using IoT Urban Big Data)

  • 박병훈;유다영;박동주;홍정열
    • 한국ITS학회 논문지
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    • 제20권5호
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    • pp.130-145
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    • 2021
  • 스마트 서울 정책의 일환으로 도시 빅데이터 활용의 중요성이 부각되고 있으며, 미세먼지, 소음과 같이 교통과 관련된 도시환경 요소가 시민들의 삶의 질에 미치는 영향에 대한 사회적 관심이 증가하고 있다. 본 연구에서는 IoT 도시 빅데이터와 교통 빅데이터를 매칭하여 통합 DB를 구축하고, 이를 활용하여 특정 공간이 도로 영향권 내에 포함되는지 여부에 따라 미세먼지, 소음 피해에 유의한 차이가 있는지 분석하였다. 또한 시계열 클러스터링을 통하여 도로교통특성 및 환경요인들이 유사한 특성을 가지는 공간 단위들을 군집화하였으며, 이 결과를 통하여 미세먼지 또는 초미세먼지 hot-spot, 소음 hot-spot 등 도시공간 단위의 환경위험 관리를 체계적으로 구축하는 기반을 마련하고자 하였다.

Age or environmental radiation dose rate: Which is more correlated with cancer incidence rates in the Republic of Korea?

  • Joo, Han Young;Kim, Jae Wook;Jeong, So Yun;Choi, Jin Sik;Moon, Joo Hyun
    • Nuclear Engineering and Technology
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    • 제54권9호
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    • pp.3452-3458
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    • 2022
  • Our study adopted a big data analysis approach to determine whether there was a significant relationship between environmental radiation dose rates or age and cancer incidence rates in the Republic of Korea. The data for this analysis included environmental radiation dose rates, number of cancer patients, and age distributions of the residents from 2009 to 2016 in the administrative districts where environmental radiation monitoring posts were located. For this analysis, the environmental radiation dose rates were obtained from 171 monitoring posts located in 113 elementary administrative districts in the Republic of Korea. The number of cancer patients and the age distributions were obtained from the Central Cancer Information Center of the National Cancer Center of Korea and the Ministry of the Interior and Safety, respectively. Our findings indicated that there was no statistically significant relationship between the environmental radiation dose rate and the cancer incidence rate. However, age had a considerable influence on the cancer incidence rate of the monitored regions.

Awareness, attitude, and behavior of global and Korean consumers towards vegan fashion consumption - A social big data analysis -

  • Yeong-Hyeon Choi;Sungchan Yeom
    • 복식문화연구
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    • 제32권1호
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    • pp.38-57
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    • 2024
  • This study utilizes social big data to investigate the factors influencing the awareness, attitude, and behavior toward vegan fashion consumption among global and Korean consumers. Social media posts containing the keyword "vegan fashion" were gathered, and meaningful discourse patterns were identified using semantic network analysis and sentiment analysis. The study revealed that diverse factors guide the purchase of vegan fashion products within global consumer groups, while among Korean consumers, the predominant discourse involved the concepts of veganism and ethics, indicating a heightened awareness of vegan fashion. The research then delved into the factors underpinning awareness (comprehension of animal exploitation, environmental concerns, and alternative materials), attitudes (both positive and negative), and behaviors (exploration, rejection, advocacy, purchase decisions, recommendations, utilization, and disposal). Global consumers placed great significance on product-related information, whereas Korean consumers prioritized ethical integrity and reasonable pricing. In addition, environmental issues stemming from synthetic fibers emerged as a significant factor influencing the awareness, attitude, and behavior regarding vegan fashion consumption. Further, this study confirmed the potential presence of cultural disparities influencing overall awareness, attitude, and behavior concerning the acceptance of vegan fashion, and offers insights into vegan fashion marketing strategies tailored to specific cultures, aiming to provide vegan fashion companies and brands with a deeper understanding of their consumer base.

Riding a Bike Not Owned by Me in Bad Air: Big Data Analysis on Bike Sharing

  • Taekyung Kim
    • Asia pacific journal of information systems
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    • 제29권3호
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    • pp.414-427
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    • 2019
  • The sharing economy has significantly changed the way of living for years. The emergence and expansion of sharing economy empowered by the mobile information technologies and intellectual algorithms reconfigure how people use transportation means. In this paper, the bike sharing phenomenon is highlighted. Combining a big data set provided by the Seoul government about user logs and air quality data set, the empirical findings reveal that temperature change is tightly associated bike sharing activities. Also, the concentration of particulate matter is weakly related to bike sharing, but the trend should be carefully examined. By considering external environmental factors to bike sharing businesses, this work is differentiated. To further understand empirical data, data mining methods and econometric approaches were adopted.

공공기록관리분야의 빅데이터 활용 방법과 시사점 제안 (Big Data Utilization and Policy Suggestions in Public Records Management)

  • 홍덕용
    • 한국기록관리학회지
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    • 제21권4호
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    • pp.1-18
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    • 2021
  • 본 연구에서는 오늘날 기록관리는 정보통신 기술의 발전과 업무환경이 급변하고 정부의 규모와 여러 기능들이 확대되면서 행정업무에서 발생하는 기록과 그에 따른 데이터 생산량이 대폭 증가함에 따라 관리에 대한 중요도가 커졌다. 빅데이터의 특성을 가진 공공기록물의 개념과 빅데이터 특징을 연계하여 사례로 설명한다. 빅데이터 발생 환경에 따른 사회적, 기술적, 환경적, 경제적, 정치적 영역으로 살펴보기 위해 'STEEP'분석을 실시하였다. 공공기록관리분야에서 빅데이터 기술 적용 적절함과 필요성을 알아보고 활용이 가능한 업무 분석을 통해 공공기록관리 업무의 최우선 적용 가능한 프레임워크를 도식하고 업무 시사점을 제시하였다. 첫째, 공공기록관리 절차와 표준에 '분석' 단계를 넣고 기록관과 기록물관리전문요원들에 의해 빅데이터 분석기술을 적용할 수 있는 신규 조직과 추가연구와 시도가 필요하다. 둘째, 많은 양의 데이터 속에 비구조화 되어있고 숨겨져 있는 패턴을 발견할 수 있도록 통합적 사고와 관련이 있는 '빅데이터 분석 자격'을 갖춘 기록물관리전문요원을 양성하여야 한다. 셋째, 공공기록분야에 빅데이터기술과 인공지능을 결합하여 자가 학습 시킨 후, 맥락을 분석하고 이를 통해 공공기관의 사회 현상과 환경을 분석하고 예측 되도록 하여야 한다.

경상남도 천연기념물 노거수의 생육환경 연구 (Growth Conditions of Natural Monument Old Big Trees in Gyeongsangnamdo, Korea)

  • 김효정
    • 한국환경복원기술학회지
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    • 제14권5호
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    • pp.103-112
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    • 2011
  • Old big tree transcends the simple meaning of trees as they are the natural monuments that embody the people's history and culture of this land. The Cultural Heritage Administration of Korea(CHA) defines and protects old big tree based not only on the size of the tree but also on its definitive cultural and natural factors such as value, implications, and originality. This research aims to identify and analyze the growth conditions, soil conditions and location character of 20 old big tree in Gyeongsangnamdo korea. The research examined the soundness of the arboreal form, the degree of damage on the bark, as well as the quantity of leafs levels to evaluate the overall condition of growth and development. Also, 9 elements such as soil texture, nitrogen and organic matter content, soil pH, phosphoric acid and EC were further analyzed The research analyzed in correlation of Growth condition and soil. Tree health related positivity that total nitrogen and organic matter. The result which analyzes location character, With natural monument old big trees raising a hand the area where is contiguous appeared with the fact that the farming village style where the rice field and the arable land of field etc. This research aimed at generating some foundational reference data for the analysis of the habitation and management conditions of natural monument old big tree within the Gyeongsangnamdo korea.

토픽 모델링을 활용한 '수돗물 유충' 뉴스 빅데이터 분석 (News Big Data Analysis of 'Tap Water Larvae' Using Topic Modeling Analysis)

  • 이수연;김태종
    • 한국콘텐츠학회논문지
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    • 제20권11호
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    • pp.28-37
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    • 2020
  • 본 연구는 '수돗물 유충' 사태의 뉴스 빅데이터를 분석함으로써, '수돗물 유충'과 관련된 주요 키워드와 토픽을 파악하여, 환경문제에 대한 위기 대응력 제고방안을 제안하기 위해 수행되었다. 2020년 7월 13일부터 8월 31일까지 보도된 1,975건의 '수돗물 유충' 뉴스를 토픽 모델링 기법으로 분석하였다. 그 결과 언론에서 나타난 '수돗물 유충' 사태가 발생기, 확산기, 수습기로 구분되며, 각 5개의 토픽을 선정하여, 환경문제의 발생과 추진 과정을 확인할 수 있었다. 분석 결과를 바탕으로 환경문제에 대한 위기 대응 방안을 다음과 같이 제언하였다. 첫째, '수돗물 유충' 사건을 중심으로 얽혀있는 다양한 맥락을 탐구하고 통합적인 안목을 형성하는 교육으로 환경문제에 대한 대응력을 기를 수 있도록 해야 한다. 둘째, 인터넷 커뮤니티를 활용한 시민참여의 환경정보 공유와 환경감시 역할 부여가 필요하다. 셋째, 신속하고 정확한 환경정보 제공과 소통을 담당하는 환경 커뮤니케이터의 양성 및 배치가 필요하다. 본 연구는 '수돗물 유충' 관련 뉴스 빅데이터를 기반으로 국내에서 처음으로 토픽 모델링 분석기법을 활용하여 분석한 연구로서, 비정형 데이터로 나타나는 환경 관련 이슈를 실증적이고 체계적으로 분석했다는 학술적 의의와 환경교육 및 커뮤니케이션 개선 방안을 제시했다는 정책적 의의를 지닌다.

Stochastics and Artificial Intelligence-based Analytics of Wastewater Plant Operation

  • Sung-Hyun Kwon;Daechul Cho
    • 청정기술
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    • 제29권2호
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    • pp.145-150
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    • 2023
  • Tele-metering systems have been useful tools for managing domestic wastewater treatment plants (WWTP) over the last decade. They mostly generate water quality data for discharged water to ensure that it complies with mandatory regulations and they may be able to produce every operation parameter and additional measurements in the near future. A sub-big data group, comprised of about 150,000 data points from four domestic WWTPs, was ready to be classified and also analyzed to optimize the WWTP process. We used the Statistical Product and Service Solutions (SPSS) 25 package in order to statistically treat the data with linear regression and correlation analysis. The major independent variables for analysis were water temperature, sludge recycle rate, electricity used, and water quality of the influent while the dependent variables representing the water quality of the effluent included the total nitrogen, which is the most emphasized index for discharged flow in plants. The water temperature and consumed electricity showed a strong correlation with the total nitrogen but the other indices' mutual correlations with other variables were found to be fuzzy due to the large errors involved. In addition, a multilayer perceptron analysis method was applied to TMS data along with root mean square error (RMSE) analysis. This study showed that the RMSE in the SS, T-N, and TOC predictions were in the range of 10% to 20%.