• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.6
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• pp.792-798
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• 2021

In this paper, an algorithm for determining the coagulant input rate in the drug-injection tank during the process of the water purification plant was derived through big data analysis and prediction based on artificial intelligence. In addition, analysis of big data technology and AI algorithm application methods and existing academic and technical data were reviewed to analyze and review application cases in similar fields. Through this, the goal was to develop an algorithm for determining the coagulant input rate and to present the optimal input rate through autonomous driving simulator and pilot operation of the coagulant input process. Through this study, the coagulant injection rate, which is an output variable, is determined based on various input variables, and it is developed to simulate the relationship pattern between the input variable and the output variable and apply the learned pattern to the decision-making pattern of water plant operating workers.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.261-270
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• 2020

In this study, we identify promising technologies for Piggyback transportation system by analyzing the relevant patent information. In order for this, we first develop the patent database by extracting relevant technology keywords from the pioneering research papers for the Piggyback flactcar system. We then employed textmining to identify the frequently referred words from the patent database, and using these words, we applied the LDA (Latent Dirichlet Allocation) algorithm in order to identify "topics" that are corresponding to "key" technologies for the Piggyback system. Finally, we employ the ARIMA model to forecast the trends of these "key" technologies for technology forecasting, and identify the promising technologies for the Piggyback system. with keyword search method the patent analysis. The results show that data-driven integrated management system, operation planning system and special cargo (especially fluid and gas) handling/storage technologies are identified to be the "key" promising technolgies for the future of the Piggyback system, and data reception/analysis techniques must be developed in order to improve the system performance. The proposed procedure and analysis method provides useful insights to develop the R&D strategy and the technology roadmap for the Piggyback system.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.537-544
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• 2022

As the penetration of electric vehicles and development of new models, user experience factors are getting more important in designing connectivity systems for car infotainment services. The primary object of this study is to identify commonalities and differences by comparing user experience factors in the Korean and US electric vehicle markets. This study derived connectivity keywords by text mining the vehicle introduction on the market in each country, and performed centrality, cluster analysis and visualization mapping using the semantic network analysis. As a result, the Korean new electric vehicle connectivity service mainly focused on driving functions such as driving, parking assistance, and charging, while US focused on device connection, convenience function control, app use, entertainment viewing. Based on the analysis, this study presented the practical implications in marketing, system design, and HMI design.

• Korean Journal of Construction Engineering and Management
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• v.23 no.2
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• pp.24-32
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• 2022

In Korea, the productivity of the construction industry is evaluated at a very low level, and the utilization of the elemental technology of the Fourth Industrial Revolution is also very low compared to other industries. In order to solve this problematic situation, it is necessary to identify the demand for technology improvement in the specialty construction industry that is directly in charge of construction in projects. Therefore, this study aims to investigate improving construction competitiveness and the demand for technology improvement in Korea's specialty construction industry. First, the concept and status of classification of the specialized construction industry were identified, and a questionnaire was organized. Second, a survey was conducted on experts construction experts, and the demand for technical improvement of the specialty construction industry was derived by applying AHP and cluster analysis. The results of this study will serve as a practical reference for policy development, R&D direction, and technology development roadmap to enhance construction competitiveness in the future, and ultimately will help to present directions to improve the construction competitiveness of the construction industry.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.157-164
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• 2022

This study was to analyze consumer confidence, satisfaction and repurchase intention after categorizing food-related lifestyle among 488 consumers who had experience purchasing convenience store lunch boxes. The data were analyzed with PASW 18.0 using frequency analysis, k-means cluster analysis, crosstabs analysis and one-way ANOVA. According to findings, first of all, types of food-related lifestyle are divided into 4 groups: a type of eating out(11.7%), a type of convenience seeking(18.3%), a type of food indifference(15%), a type of dietary interest(55%). Secondly, the types of food-related lifestyle showed statistically significant difference gender, age, marital status, education, monthly average household income, monthly average allowance, job, monthly average number of lunch box buying, lunch box purchase time zone and average one cost of lunch box buying of socio-economic variables. Thirdly, convenience seeking and dietary interest type showed the highest in consumer confidence and dietary interest type showed the highest level of satisfaction and repurchase intention.

• The Journal of the Korea Contents Association
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• v.22 no.2
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• pp.770-781
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• 2022

Korea's aging population is rapidly increasing, but there has been little research into senior-friendly foods. Therefore, this study aimed to provide basic data for the development of senior-friendly Home Meal Replacement(HMR) foods by conducting a survey among elderly and middle-aged persons highly likely to purchase senior-friendly foods in the near future. Study findings showed that the level of HMR purchase was higher among the middle-aged, many subjects preferred products requiring simple cooking, and a higher proportion of subjects purchased them offline. Five HMR selection attributes were identified, and dietary lifestyles were classified into four categories. Through a cluster analysis, 3 groups based on level of involvement were identified: high-level, mid-level, and low-level. Napping^® analysis showed that subjects classified food products into HMR and meal kits, and into products with a clear broth and products with a thicker broth. The study findings are expected to help suggest a differentiating approach in developing senior-friendly HMR foods.

• Korean Journal of Environment and Ecology
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• v.36 no.1
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• pp.56-71
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• 2022

This study was conducted to build basic terrestrial insect data for the management of the persimmon plantations in the Sangju dried persimmon agricultural area. The survey identified terrestrial insect species were 7 orders, 77 families, and 1,925 individuals of 177 species. And the number of species that appeared in each village was in the order of Seoman II Village in Naeseo Township > Seoman I Village in Naeseo Township > Soeun Village in Oenam Township. Hemiptera and Coleoptera predominated throughout the site due to the characteristics of the cultivated land. The special species were 13 Korean endemic species, 2 vulnerable (VU) species, 22 least concern (LC) species, 42 not-evaluated (NE) species on the national red list, and 2 species of ecosystem disturbance wildlife. A result of the cluster analysis identified the Ectmetopterus micantulusas the dominant species and Ceutorhynchus albosuturalisas the subdominant species. The species diversity (H') was 1.1636-1.6022, evenness (J') was 0.6748-0.7611, and dominance (D) was in the range of 0.2389-0.3252.

• Journal of Environmental Impact Assessment
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• v.31 no.6
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• pp.369-377
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• 2022

The purpose of this study is to explore whether open spaces with land use characteristics of forest green areas can have different influence on the urban heat reduction depending on the location distribution, through the case of Gangneung-si downtown area. As a research method, the InVest Urban Cooling Model, which is a thermal phenomenon analysis model, is employed based on the most recent data available in 2018. In order to focus on the effect of location distribution of open space in the city, the downtown area is set as the observation area, not the entire city. The analysis of the land use location distribution scenarios shows that large-scale forests or clustered forests are more effective in reducing atmospheric heat in the region than several small-scale forests.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.1-10
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• 2021

This paper aimed to look at the awareness of foreign workers in social platforms by using text mining, one of the big data techniques and draw suggestions for foreign workers. To achieve this purpose, data collection was conducted with search keyword 'Foreign Worker' from Jan. 1, to Dec. 31, 2020, and frequency analysis, TF-IDF analysis, and degree centrality analysis and 100 parent keywords were drawn for comparison. Furthermore, Ucinet6.0 and Netdraw were used to analyze semantic networks, and through CONCOR analysis, data were clustered into the following eight groups: foreigner policy issue, regional community issue, business owner's perspective issue, employment issue, working environment issue, legal issue, immigration issue, and human rights issue. Based on such analyzed results, it identified national awareness of foreign workers and main issues and provided the basic data on policy proposals for foreign workers and related researches.

• Journal of The Korean Association of Information Education
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• v.25 no.6
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• pp.935-945
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• 2021

The purpose of this study is to analyze the social perception of Arduino lecture using big data analysis method. For this purpose, data from January 2012 to May 2021 were collected using the Textom website as a keyword searched for 'arduino + lecture' in blogs, cafes, and news channels of NAVER website. The collected data was refined using the Textom website, and text mining analysis and semantic network analysis were performed by opening the Textom website, Ucinet 6, and Netdraw programs. As a result of text mining analysis such as frequency analysis, TF-IDF analysis, and degree centrality it was confirmed that 'education' and 'coding' were the top keywords. As a result of CONCOR analysis for semantic network analysis, four clusters can be identified: 'Arduino-related education', 'Physical computing-related lecture', 'Arduino special lecture', and 'GUI programming'. Through this study, it was possible to confirm various meaningful social perceptions of the general public in relation to Arduino lecture on the Internet. The results of this study will be used as data that provides meaningful implications for instructors preparing for Arduino lectures, researchers studying the subject, and policy makers who establish software education or coding education and related policies.