• Korean Journal of Construction Engineering and Management
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• v.20 no.3
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• pp.54-63
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• 2019

Corporate Sustainability Management (CSM) is management approach and strategies that have grown in importance in recent years. and it is becoming increasingly important to organizations in every industry including the construction industry as well. It is important to establish and continuously manage and improve the strategies at the industrial and enterprise level and also to understand their trend. The most practical way to understand the overall sustainability management strategies and trend of construction companies is to analyze the sustainability management report of representative construction companies and to derive keywords for sustainability management, and then analyzed them using big data. The objective of the study is to analyze the trend of CSM strategies of Korean contractors in terms of key characteristics and implications by big data analysis employing keywords identified in the CSM reports of five major contractors in the Korean construction industry. Understanding the sustainable management strategy trend of construction companies has important significance in terms of being able to find out the issues that the construction industry and construction companies should focus on in order to pro-actively prepare for the future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.1100-1118
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• 2021

In a wide range of ML applications, the training data contains privacy-sensitive information that should be kept secure. Training the ML systems by privacy-sensitive data makes the ML model inherent to the data. As the structure of the model has been fine-tuned by training data, the model can be abused for accessing the data by the estimation in a reverse process called model inversion attack (MIA). Although, MIA has been applied to shallow neural network models of recognizers in literature and its threat in privacy violation has been approved, in the case of a deep learning (DL) model, its efficiency was under question. It was due to the complexity of a DL model structure, big number of DL model parameters, the huge size of training data, big number of registered users to a DL model and thereof big number of class labels. This research work first analyses the possibility of MIA on a deep learning model of a recognition system, namely a face recognizer. Second, despite the conventional MIA under the white box scenario of having partial access to the users' non-sensitive information in addition to the model structure, the MIA is implemented on a deep face recognition system by just having the model structure and parameters but not any user information. In this aspect, it is under a semi-white box scenario or in other words a gray-box scenario. The experimental results in targeting five registered users of a CNN-based face recognition system approve the possibility of regeneration of users' face images even for a deep model by MIA under a gray box scenario. Although, for some images the evaluation recognition score is low and the generated images are not easily recognizable, but for some other images the score is high and facial features of the targeted identities are observable. The objective and subjective evaluations demonstrate that privacy cyber-attack by MIA on a deep recognition system not only is feasible but also is a serious threat with increasing alert state in the future as there is considerable potential for integration more advanced ML techniques to MIA.

• Journal of Korea Entertainment Industry Association
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• v.13 no.4
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• pp.173-184
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• 2019

The data processing of this study is based on the word data search in social media through textom and the big data analysis is carried out and three areas (2019 Gwangju World Swimming Championships, 2019 Gwangju World Swimming Masters Competition, 2019 World Swimming Championships Problem) was consistently handled through data collection and refinement in the web environment. We applied the collected words to the program of Ucinet6, visualized them, and conducted a CONCOR analysis to grasp the similar relationship of words and to identify the cluster of common factors. As a result of the analysis, the clusters related to the 2019 Gwangju World Swimming Championships mainly consisted of four major areas of recognition and perception, mainly searching for operational aspects related to the swimming championship, and the community related to the 2019 Gwangju World Swimming Masters Competition Is mainly searched for the promotion of the Masters Competition and the aspect of the competition divided into two areas of major recognition and peripheral recognition. The cluster related to the problems of the 2019 Gwangju World Swimming Championships is divided into five areas, And they are mainly searching for the place, operation, institution, event, etc. of the problem of the swimming championship.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.29-42
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• 2023

In this paper, we propose a method to enhance the prediction accuracy of solar irradiance for three major South Korean cities: Seoul, Busan, and Incheon. Our method entails the development of five generative models-vanilla GAN, CTGAN, Copula GAN, WGANGP, and TVAE-to generate independent variables that mimic the patterns of existing training data. To mitigate the bias in model training, we derive values for the dependent variables using random forests and deep neural networks, enriching the training datasets. These datasets are integrated with existing data to form comprehensive solar irradiance prediction models. The experimentation revealed that the augmented datasets led to significantly improved model performance compared to those trained solely on the original data. Specifically, CTGAN showed outstanding results due to its sophisticated mechanism for handling the intricacies of multivariate data relationships, ensuring that the generated data are diverse and closely aligned with the real-world variability of solar irradiance. The proposed method is expected to address the issue of data scarcity by augmenting the training data with high-quality synthetic data, thereby contributing to the operation of solar power systems for sustainable development.

• Korean Journal of Culture and Social Issue
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• v.15 no.1
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• pp.169-186
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• 2009

This study aims to investigate the relationship between personality, especially temperament and subjective well-being. The participants were 681 college students (211 males and 470 females), whose ages ranged from 17 to 37 (M=20.91, SD=2.36). The instruments utilized in the present study were Korean Version of BAS/BIS Scale, The Big Five Locator, Satisfaction with Life Scale, Life Satisfaction Motivation Scale, Life Satisfaction Expectancy Scale, Emotion Frequency Test, and Subjective Happiness Scale. Result indicated that women expected more positive future than men did, while no gender differences were found in any other well-being variables. Correlational analyses revealed that emotional stability and extroversion were closely associated with life satisfaction, happiness, positive and negative emotion, whereas behavioral activation system (BAS) and behavioral inhibition system (BIS) were more closely associated with motivation to live and expectancy of satisfactory life. There was close relationship between conscientiousness and subjective well-being, because they were college students. As a internal factor, personality was better predictor for subjective well-being of female students. For instance, it accounted for around 35% variance of female's subjective happiness. The present findings reiterate the role of personality in quality of life, and it was discussed with characteristics of subjects, situational factors, and previous studies.

• Information Systems Review
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• v.23 no.3
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• pp.51-75
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• 2021

Global e-commerce websites offer personalized recommendation services to gain sustainable competitiveness. Existing studies have offered personalized recommendation services using quantitative preferences such as ratings. However, offering personalized recommendation services using only quantitative data has raised the problem of decreasing recommendation performance. For example, a user gave a five-star rating but wrote a review that the user was unsatisfied with hotel service and cleanliness. In such cases, has problems where quantitative and qualitative preferences are inconsistent. Recently, a growing number of studies have considered review data simultaneously to improve the limitations of existing personalized recommendation service studies. Therefore, in this study, we identify review and rating mismatches and build a new user profile to offer personalized recommendation services. To this end, we use deep learning algorithms such as CNN, LSTM, CNN + LSTM, which have been widely used in sentiment analysis studies. And extract sentiment features from reviews and compare with quantitative preferences. To evaluate the performance of the proposed methodology in this study, we collect user preference information using real-world hotel data from the world's largest travel platform TripAdvisor. Experiments show that the proposed methodology in this study outperforms the existing other methodologies, using only existing quantitative preferences.

• Journal of Korean Society of Rural Planning
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• v.30 no.2
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• pp.13-24
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• 2024

This study conducts an analysis of social media big data pertaining to island tourism resources, aiming to discern the diverse forms and categories of island tourism favored by consumers, ascertain predominant resources, and facilitate objective decision-making grounded in scientific methodologies. To achieve this objective, an examination of blog posts published on Naver from 2022 to 2023 was undertaken, utilizing keywords such as 'Island tourism', 'Island travel', and 'Island backpacking' as focal points for analysis. Text mining techniques were applied to sift through the data. Among the resources identified, the port emerged as a significant asset, serving as a pivotal conduit linking the island and mainland and holding substantial importance as a focal point and resource for tourist access to the island. Furthermore, an analysis of the disparity between existing island tourism resources and those acknowledged by tourists who actively engage with and appreciate island destinations led to the identification of 186 newly emerging resources. These nascent resources predominantly clustered within five regions: Incheon Metropolitan City, Tongyeong/Geoje City, Jeju Island, Ulleung-gun, and Shinan-gun. A scrutiny of these resources, categorized according to the tourism resource classification system, revealed a notable presence of new resources, chiefly in the domains of 'rural landscape', 'tourist resort/training facility', 'transportation facility', and 'natural resource'. Notably, many of these emerging resources were previously overlooked in official management targets or resource inventories pertaining to existing island tourism resources. Noteworthy examples include ports, beaches, and mountains, which, despite constituting a substantial proportion of the newly identified tourist resources, were not accorded prominence in spatial information datasets. This study holds significance in its ability to unearth novel tourism resources recognized by island tourism consumers through a gap analysis approach that juxtaposes the existing status of island tourism resource data with techniques utilizing social media big data. Furthermore, the methodology delineated in this research offers a valuable framework for domestic local governments to gauge local tourism demand and embark on initiatives for tourism development or regional revitalization.

• Journal of Korean Dental Hygiene Science
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• v.6 no.2
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• pp.101-114
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• 2023

Background: This study aimed to explore the overall perception of pit and fissure sealants and suggest methods to revitalize their current stagnation. Methods: To determine the social perception of the change in coverage policy for pit and fissure sealants, we categorized them into five time periods. The first period (December 1, 2009 to November 30, 2010), the second period (December 1, 2010 to September 30, 2012), the third period (October 1, 2012 to May 5, 2013), the fourth period (May 6, 2013 to September 30, 2017), and the fifth period (October 1, 2017 to December 31, 2022). We utilized text mining, an unstructured big data analysis method. Keywords were collected and analyzed using Textom, and the frequency analysis of the top 30 keywords, structural features of the semantic network, centrality analysis, QAP correlation analysis, and co-occurrence analysis were conducted. Results: The frequency analysis showed that the top keywords for each time period were 'Cavities', 'Treatment', and 'Children'. In the structural features of the semantic network of pit and fissure sealants by time period, the density index was found to be around 1.00 for all time periods. The QAP correlation analysis showed the highest correlation between the first and second periods and the fourth and fifth periods with a correlation coefficient of 0.834. The co-occurrence analysis showed that 'cavities' and 'prevention were the top two words across all time periods. Conclusion: This study showed that pit and fissure sealants are well accepted by the society as a preventive treatment for caries. However, the awareness of health education related to these sealants was found to be low. Efforts to revitalize stagnant pit and fissure sealants need to be strengthened with effective education.

• 보존과학연구
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• s.25
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• pp.171-195
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• 2004

This research presents an evaluation of the weathering and deterioration state of the Wanggung-ri five-storied stone pagoda in the Iksan (National Treasure No. 289) and suggests conservational schemes. A deterioration map of the pagoda was drawn from the aspects of petrological, physical, chemical, biological, structural and artificial weathering.The rock properties consisting of the pagoda were medium-grained biotite granite that had leucocratic phenocryst developed in parts. The body of each story suffered severely from the secondary contamination that turned the colors into light grey, pitch dark, yellowish brown, and reddish brown as well as granular decomposition, exfoliation and peel-off. The roof stones were heavy exfoliated or peeled off in most of the cases. In addition to the fine cracks, there were layered cracks on the corners. The roof stones of the3rd and 4th story in the north and west side had some stones fall-off, while those of the 2ndstory in the north side had steel reinforcement filled for a fixing purpose. Those of the 5th story showed big gaps that must have originated from cracks and were easily subject to granular decomposition and rainfall. The inside clay filler was missing in the lower part of the roof stones of the 4th and 5th story and the supporting stones, which were thus covered by light grey or pitch dark sediments. The contact area of the materials was about 70 % in the parts where there was a space due to the filler missing and washigher than 90 % in the lower parts of the pagoda. About 90 % or more of the roof stones surface of each story were covered by aerial plants that formed a thick biological mat. Thus it seemed necessary to come up with the conservational measures to remove the plans living on the surface of the stone materials, with the plans to prevent rain from falling inside, and with the water repellent and hardening treatments to postpone the surface weathering of the rock properties. All those measures and plans must be based on the results of long-term monitoring and thorough detail investigations.

• The Journal of Korean Academy of Sensory Integration
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• v.1 no.1
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• pp.9-16
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• 2003

Objective : The experiment consists of measuring functional grasp ability of a child suffering from sensory defense disability of the hands as the child is treated with sensory integration therapy. Methods : We treated two-year-old child with developmental disability to set up the reversal design(ABAB design). We used treatment equipments, free activities, and toys for sensory integration therapy. Results : A child's functional grasp ability did not show anything before the sensory integration therapy, however, after the sensory integration was applied during the first treatment(Treatment 1), the five minutes before the treatment, it averaged 1.87 times(ranges=0 to 5 times), the five minutes after the treatment, it averaged 1.25 times(ranges=0 to 8 times) showing an increased. After ending the sensory integration therapy, the functional grasp ability averaged 2.5 times before the therapy and 4 times after the therapy, which showed a totally different tendency, when we reapplied the treatment during the second treatment(Treatment 2), it averaged 2.4 times(ranges=1 to 4 times) before the treatment, and it averaged 5.3 times(ranges=4 to 6 times) after the treatment, which showed a big improvement. Conclusion : The sensory integration therapy brought an increase in functional grasp ability along with improvement in daily life functions of the child. For this result, there should be more research to see more effects and results to help those in need.