• Journal of the Korean Society of Clothing and Textiles
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• v.40 no.6
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• pp.1034-1044
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• 2016

This study seeks a method to objectively evaluate sensibility based on Big Data in the field of design. In order to do so, this study examined the sensibility responses on design factors for the public through a network analysis of texts displayed in social media. 'Hanbok', a formal clothing that represents Korea, was selected as the subject for the research methodology. We then collected 47,677 keywords related to Hanbok from 12,000 posts on Naver blogs from January $1^{st}$ to December $31^{st}$ 2015 and that analyzed using social matrix (a Big Data analysis software) rather than using previous survey methods. We also derived 56 key-words related to design elements and sensibility responses of Hanbok. Centrality analysis and CONCOR analysis were conducted using Ucinet6. The visualization of the network text analysis allowed the categorization of the main design factors of Hanbok with evaluation terms that mean positive, negative, and neutral sensibility responses. We also derived key evaluation factors for Hanbok as fitting, rationality, trend, and uniqueness. The evaluation terms extracted based on natural language processing technologies of atypical data have validity as a scale for evaluation and are expected to be suitable for utilization in an index for sensibility evaluation that supplements the limits of previous surveys and statistical analysis methods. The network text analysis method used in this study provides new guidelines for the use of Big Data involving sensibility evaluation methods in the field of design.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2026-2033
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• 2023

Due to Thailand's nuclear energy public acceptance problem, the understanding of nuclear energy public perception was the key factor affecting to re-consideration of the nuclear energy program. Thailand Institute of Nuclear Technology and its alliances together developed the classification model for the nuclear energy public perception from the big data comments on social media using Facebook using deep transfer learning. The objective was to insight into the Thailand nuclear energy public perception on Facebook social media platform using sentiment analysis. The supervised learning was used to generate up-to-date classification model with more than 80% accuracy to classify the public perception on nuclear power plant news on Facebook from 2009 to 2022. The majority of neutral sentiments (80%) represented the opportunity for Thailand to convince people to receive a better nuclear perception. Negative sentiments (14%) showed support for other alternative energies due to nuclear accident concerns while positive sentiments (6%) expressed support for innovative nuclear technologies.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.29-42
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• 2021

As the low fertility intensifies in Korea, this study investigated fundamental differences between the government's low fertility policy and public perception of it. To this end, we selected four times 'Aging Society and Population Policy' documents and news comments for two weeks immediately after announcement of the third and fourth Policy as analysis targets. Then we conducted word frequency analysis, co-occurrence analysis and CONCOR analysis. As a result of analyses, first, direct childcare support during the first and second periods, and a social structural approach during third and fourth periods were noticeable. Second, it was revealed that both policies and comments aim for the work-family compatibility in 'parenting'. Lastly it was showed public interest in environment of raising children and the critical mind to effectiveness of the policy. This study is meaningful in that it confirmed the public perception using big data analysis, and it will help improve the direction for the future low fertility policy.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.32 no.3
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• pp.268-278
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• 2022

Objectives: This study aimed to establish a control group based on the big data from National Health Insurance Service. We also presented presented the number of incidences for each cancer, and analyzed the cancer incidence rate among Korean workers. Methods: The cohort definition was separated by 'baseline cohort', 'dynamic cohort', and 'fixed- industry cohort' according to the definition. Cancer incidence was calculated based on the Korean Standard Classification of Disease code. Incidence rate was calculated among the group of all workers and public officials. Based on the study subjects and each cohort definition, the number of observations, incidences, and the incidence rate according to sex and age groups was calculated. The incidence rate was estimated based on the incidence per 100,000 person-year, and 95% confidence intervals calculated according to the Poisson distribution. Results: The result shows that the number of cancer cases in the all-worker group decreases after the age of 55, but the incidence rate tends to increase, which is attributed to the retirement of workers over 55 years old. Despite the specific characteristics of the workers, the trend and figures of cancer incidence revealed in this study are similar to those reported in previous studies of the overall South Korean population. When comparing the incidence rates of all workers and the control group of public officials, the incidence rate of public officials is generally observed to be higher in the age group under the age of 55. On the other hand, for workers aged 60 or older, the incidence rates were 1,065.4 per 100,000 person-year for all workers and 1,023.7 per 100,000 person-year for civil servants. Conclusions: This study analyzed through health insurance data including all workers in Korea, and analyzed the incidence of cancer of workers by sex and age. In addition, further in-depth researches are needed to determine the incidence of cancer by industry.

• Journal of Hydrogen and New Energy
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• v.29 no.1
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• pp.117-123
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• 2018

The long-term perception investigation of environment is needed for the persistence of each country's policy on climate change, which is greatly influenced by external factors. Long term data on perception and attitudes of people's thought can be a big data point for climate change and consistent policies can be implemented with the need for public demand. Information on the perception of the general public regarding the environment should be carried out as a basis for the national environmental policy.

• Journal of Engineering Education Research
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• v.25 no.3
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• pp.35-44
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• 2022

Artificial intelligence is a core technology in the era of digital transformation, and as the technology level is advanced and used in various industries, its influence is growing in various fields, including social, ethical and legal issues. Therefore, it is time to raise social awareness on ethics of artificial intelligence as a prevention measure as well as improvement of laws and institutional systems related to artificial intelligence development. In this study, we analyzed unstructured data, typically text, such as online news articles and comments to confirm the degree of social awareness on ethics of artificial intelligence development. The analysis showed that the public intended to concentrate on specific issues such as "Human," "Robot," and "President" in 2018 to 2019, while the public has been interested in the use of personal information and gender conflics in 2020 to 2021.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.107-117
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• 2020

With the recent development of autonomous vehicles, various sensors installed in vehicles have become common, and big data generated from those sensors is increasingly being used in the transportation field. In this study, we proposed a grid index method to efficiently process real-time vehicle sensing big data and public data such as road weather. The applicability and effect of the proposed grid space division method and grid ID generation method were analyzed. We created virtual data based on DTG data and mapped to the road link based on coordinates. As a result of analyzing the data processing speed in grid index method, the data processing performance improved by more than 2,400 times compared to the existing link unit processing method. In addition, in order to analyze the efficiency of the proposed technology, the virtually generated data was mapped and visualized.

• Journal of East Asia Management
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• v.4 no.1
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• pp.1-22
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• 2023

This study conducted a big data analysis study through text mining and semantic network analysis to explore the perception of defense reform 2.0. The collected data were analyzed with the top 70 keywords as the appropriate range for network visualization. Through word frequency analysis, connection centrality analysis, and an N-gram analysis, we identified issues that received much attention such as troop reduction, shortening of military service period, dismantling of the border area unit, and returning wartime operational control. In particular, the results of clustering words through CONCOR analysis showed that there was a great interest in pursuing the technical group, concerns about military capacity reduction, and reorganization of manpower structure. The results of the analysis through text mining techniques are as follows. First, it was found that there was a lack of awareness about measures to reinforce the reduced troops while receiving much attention to the reduction of troops in Defense Reform 2.0. Second, it was found that it is necessary to actively communicate with the local community due to the deconstruction and movement of the border area units, such as the decrease of the population of the region and the collapse of the local commercial area. Third, it was judged that it is necessary to show substantial results through the promotion of barracks culture and the defense industry, which showed that there was less interest than military structure and defense operation from the people and the introduction of active policies. Through this study, we analyzed the public's interest in defense reform 2.0, which is a representative defense policy, and suggested a plan to draw support for national policy.

• Korean Institute of Interior Design Journal
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• v.21 no.5
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• pp.390-398
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• 2012

The purpose of this study was to analyze the planning guideline of individual space size for public library. The 26 cases were selected from the data of outstanding libraries built after the year 2000. The paper focused on the comparison between the data from analysis and the guideline from manual book of public library. The result of this study was as followed ; The first, reference reading rooms were open-plan rather than segmented. The second, the percentages of reference reading spaces from the data were lower than the guidelines. It proved the fact that the role of public library expanded to cultural community space. The third, children's space retained sufficient numbers of book collections. It represented that people realized the importance of children's library in terms of cultural education. The fourth, the percentage of space size of cultural area showed high amount of numbers. It proved the fact that the public library as community center was required various cultural programs. The fifth, the percentages of preservation library were lower than the guideline in case of the big libraries, while the small libraries were higher. The book collections of detached annex libraries should be linked with the central libraries.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.2
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• pp.53.2-53.2
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• 2016

We present our experiences with open-source spatio-temporal database systems for managing and analyzing big astronomical data acquired by wide-field time-domain sky surveys. Considering performance, cost, difficulty, and scalability of the database systems, we conduct comparison studies of open-source spatio-temporal databases such as GeoMesa and PostGIS that are already being used for handling big geographical data. Our experiments include ingesting, indexing, and querying millions or billions of astronomical spatio-temporal data. We choose the public VVV (VISTA Variables in the Via Lactea) catalogs of billions measurements for hundreds of millions objects as the test data. We discuss issues of how these spatio-temporal database systems can be adopted in the astronomy community.