• Architectural research
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• v.24 no.1
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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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.130-145
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• 2021

As part of the Smart Seoul policy, the importance of using big urban data is being highlighted. Furthermore interest in the impact of transportation-related urban environmental factors such as PM10 and noise on citizen's quality of life is steadily increasing. This study established the integrated DB by matching IoT big data with transportation data, including traffic volume and speed in the microscopic Spatio-temporal scope. This data analyzed the impact of a spatial unit in the road-effect zone on environmental risk level. In addition, spatial units with similar characteristics of road traffic and environmental factors were clustered. The results of this study can provide the basis for systematically establishing environmental risk management of urban spatial units such as PM10 or PM2.5 hot-spot and noise hot-spot.

• Nuclear Engineering and Technology
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• v.54 no.9
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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.

• The Research Journal of the Costume Culture
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• v.32 no.1
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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.

• Asia pacific journal of information systems
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• v.29 no.3
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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.

• Journal of Korean Society of Archives and Records Management
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• v.21 no.4
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• pp.1-18
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• 2021

Today, record management has become more important in management as records generated from administrative work and data production have increased significantly, and the development of information and communication technology, the working environment, and the size and various functions of the government have expanded. It is explained as an example in connection with the concept of public records with the characteristics of big data and big data characteristics. Social, Technological, Economical, Environmental and Political (STEEP) analysis was conducted to examine such areas according to the big data generation environment. The appropriateness and necessity of applying big data technology in the field of public record management were identified, and the top priority applicable framework for public record management work was schematized, and business implications were presented. First, a new organization, additional research, and attempts are needed to apply big data analysis technology to public record management procedures and standards and to record management experts. Second, it is necessary to train record management specialists with "big data analysis qualifications" related to integrated thinking so that unstructured and hidden patterns can be found in a large amount of data. Third, after self-learning by combining big data technology and artificial intelligence in the field of public records, the context should be analyzed, and the social phenomena and environment of public institutions should be analyzed and predicted.

• The Journal of the Korea Contents Association
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• v.20 no.11
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• pp.28-37
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• 2020

This study was conducted to propose measures to improve crisis response to environmental issues by analyzing the news big data on the 'tap water larvae' situation and identifying related major keywords and topics. To accomplish this, 1,975 cases of 'tap water larvae' reported between July 13 to August 31, 2020 were divided into three periods and analyzed using topical modeling techniques. The analysis output 15 topics for each period. According to the result, the 'tap water larvae' incident, as reported in the media, is divided into the occurrence, diffusion, and rectification stages. The government's response and civilian risk consciousness and reaction could also be seen. Based on the result, the following measures to respond to environment risk is proposed. First, it is necessary to explore the various intertwined context with the 'tap water larvae' incident at its core and develop responsiveness to environmental problems through education which forms integrated views. Second, a role to monitor the environment must be implemented and civilian-participated environmental information must be shared through the application of internet communities. Third, the cultivation and deployment of environmental communicators who provide and communicate fast and accurate environment information is required. This study, as the first in Korea to use the topic modeling analysis method based on big data related to 'tap water larvae', has academic significance in that it has empirically and systematically analyzed environmental issues which appear as unstructured data. It also political significance as it suggests ways to improve environmental education and communication.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.14 no.5
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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.

• Clean Technology
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• v.29 no.2
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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%.

• International journal of advanced smart convergence
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• v.13 no.3
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• pp.117-124
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• 2024

ESG is currently a global topic, meaning environmental, social, and governance, which are three important measures of socially responsible management. It is also having a great influence on improving competitiveness in the global market and enhancing corporate image. In this study, ESG in Korea was analyzed through big data, and four central keywords of ESG management in China based on Chinese data were derived. These four keywords are environment, management, corporate event, and quality certification. In addition, we want to understand the ESG perspective of China by studying ESG cases in China. Through this, we will be able to compare and analyze the differences between ESG approaches and key points between Korea and China.