• International journal of advanced smart convergence
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• v.8 no.2
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• pp.39-46
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• 2019

Human mobility estimation plays a key factor in a lot of promising applications including location-based recommendation systems, urban planning, and disease outbreak control. We study the human mobility estimation problem in the case where recent locations of a person-of-interest are unknown. Since matrix decomposition is used to perform latent semantic analysis of multi-dimensional data, we propose a human location estimation algorithm based on matrix factorization to reconstruct the human movement patterns through the use of information of persons with correlated movements. Specifically, the optimization problem which minimizes the difference between the reconstructed and actual movement data is first formulated. Then, the gradient descent algorithm is applied to adjust parameters which contribute to reconstructed mobility data. The experiment results show that the proposed framework can be used for the prediction of human location and achieves higher predictive accuracy than a baseline model.

• Archives of Craniofacial Surgery
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• v.20 no.4
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• pp.246-250
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• 2019

Recently, there is a growing interest of hyperbaric oxygen therapy in many fields of medicine. We had a 43-year-old female patient presented with severe necrosis of the nose, philtrum, and upper lip due to retrograde arterial occlusion after nasolabial fold hyaluronic acid filler injection. Our patient went through 43 sessions of systemic hyperbaric oxygen therapy from December 2, 2017 to January 18, 2018. We administered 2.8 atmosphere absolute (ATA) for 135 minutes in the first session and the remaining sessions consisted of 2.0 ATA for 110 minutes. In reporting this case, we wish to provide a warning regarding the latent risk of filler injections and share our experience about minimizing soft tissue damage in the early stages with systemic hyperbaric oxygen therapy.

• Journal of People, Plants, and Environment
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• v.24 no.6
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• pp.563-572
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• 2021

Background and objective: The ongoing COVID-19 pandemic restricted daily life, forcing people to spend time indoors. With the growing interest in mental health issues and residential environments, 'pet plants' have been receiving attention during the unprecedented social distancing measures. This study aims to analyze the change in trends of pet plants before and during the COVID-19 pandemic and provide basic data for studies related to pet plants and directions of future development. Methods: A total of 2,016 news articles using the keyword 'pet plants' were collected on Naver News from January 1, 2018 to August 15, 2019 (609 articles) and January 1, 2020 to August 15, 2021 (1,407 articles). The texts were tokenized into words using KoNLPy package, ultimately coming up with 63,597 words. The analyses included frequency of keywords and topic modeling based on Latent Dirichlet Allocation (LDA) to identify the inherent meanings of related words and each topic. Results: Topic modeling generated three topics in each period (before and during the COVID-19), and the results showed that pet plants in daily life have become the object of 'emotional support' and 'healing' during social distancing. In particular, pet plants, which had been distributed as a solution to prevent solitary deaths and depression among seniors living alone, are now expanded to help resolve the social isolation of the general public suffering from COVID-19. The new term 'plant butler' became a new trend, and there was a change in the trend in which people shared their hobbies and information about pet plants and communicated with others in online. Conclusion: Based on these findings, the trend data of pet plants before and after the outbreak of COVID-19 can provide the basis for activating research on pet plants and setting the direction for development of related industries considering the continuous popularity and trend of indoor gardening and green hobby.

• Journal of the Korea Society of Computer and Information
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• v.29 no.7
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• pp.73-80
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• 2024

In this paper, we proposes a method to improve the accuracy of predicting the Korea Composite Stock Price Index (KOSPI) by combining topic modeling and Long Short-Term Memory (LSTM) neural networks. In this paper, we use the Latent Dirichlet Allocation (LDA) technique to extract ten major topics related to interest rate increases and decreases from financial news data. The extracted topics, along with historical KOSPI index data, are input into an LSTM model to predict the KOSPI index. The proposed model has the characteristic of predicting the KOSPI index by combining the time series prediction method by inputting the historical KOSPI index into the LSTM model and the topic modeling method by inputting news data. To verify the performance of the proposed model, this paper designs four models (LSTM_K model, LSTM_KNS model, LDA_K model, LDA_KNS model) based on the types of input data for the LSTM and presents the predictive performance of each model. The comparison of prediction performance results shows that the LSTM model (LDA_K model), which uses financial news topic data and historical KOSPI index data as inputs, recorded the lowest RMSE (Root Mean Square Error), demonstrating the best predictive performance.

• Korean Journal of Culture and Social Issue
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• v.27 no.2
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• pp.167-189
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• 2021

The purpose of this study was to classify different profiles of grit (effort vs. interest) and passion mindset (fixed vs. growth) in university students and to understand whether there are differences in psychological characteristics (ie. depression, anxiety and happiness) and career adaptability between the profiles. To this end, we recruited 359 students aged 18 and 25 and applied a Latent Profile Analysis(LPA). The results revealed 4 distinct profiles : Profile1-a burgeoning type, Profile2-an ordinary type, Profile3-a fixed/limited type, Profile4-sprouting/drifting type. The profile1(LP1, 22.2%) had high levels of grit and passion growth mindset. The profile2(LP2, 63.8%) showed average levels in both grit and passion mindset. The profile3(LP3, 8.8%) had a low level of grit and a high level of passion fixed mindset. The profile4(LP4, 5.1%) showed a low level of grit and a high level of passion growth mindset. The four profiles were distinct in psychological characteristics and career adaptability. The burgeoning type(profile1) was most adaptive in comparison to the fixed/limited type(profile 3). These results suggest that grit has more powerful effects on psychological characteristics while passion growth mindset exerts stronger influencers in career adaptability. Putting the results together, our findings imply that both passion growth mindset and grit need to be considered together to enhance the individuals' comprehensive well-being and to increase the level of adaptation for career preparation.

• Informatization Policy
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• v.28 no.4
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• pp.3-18
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• 2021

The 'digital divide' is regarded as a latent dysfunction that impedes the intrinsic role of information to contribute to social equality. Therefore, it has drawn great attention inside and outside of academia. The growing interest in the digital divide has been driven by the realization that it can create a serious crisis that threatens a social system compounded by existing economic, social, and cultural inequality, rather than being limited to an uneven distribution of information. In this paper (1) studies on the digital divide published since 1970 are reviewed, (2) studies noteworthy of discussion are selected to assess their academic significance, and (3) the tasks and prospects of digital divide research are explored. Although meaningful achievements have been amassed through continuous interest and efforts of the academic community, two limitations are raised; the gap between pure research and policy research that hinders the working of synthetic imagination, and the intellectual lag falling behind a rapidly changing society. In addition, it is suggested that the operation, curation, and augmentation gaps would emerge as new agenda for digital divide research in the intelligent information age.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.6
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• pp.205-220
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• 2023

This study aimed to analyze the needs and interests of the public on endangered wildlife using complaint big data. We collected 1,203 complaints and their corresponding text data on endangered wildlife, pre-processed them, and constructed a document-term matrix for 1,739 text data. We performed LDA (Latent Dirichlet Allocation) topic modeling and network analysis. The results revealed that the complaints on endangered wildlife peaked in June-August, and the interest shifted from insects to various endangered wildlife in the living area, such as mammals, birds, and amphibians. In addition, the complaints on endangered wildlife could be categorized into 8 topics and 5 clusters, such as discovery report, habitat protection and response request, information inquiry, investigation and action request, and consultation request. The co-occurrence network analysis for each topic showed that the keywords reflecting the call center reporting procedure, such as photo, send, and take, had high centrality in common, and other keywords such as dung beetle, know, absence and think played an important role in the network. Through this analysis, we identified the main keywords and their relationships within each topic and derived the main issues for each topic. This study confirmed the increasing and diversifying public interest and complaints on endangered wildlife and highlighted the need for professional response. We also suggested developing and extending participatory conservation plans that align with the public's preferences and demands. This study demonstrated the feasibility of using complaint big data on endangered wildlife and its implications for policy decision-making and public promotion on endangered wildlife.

• The Korean Journal of Cytopathology
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• v.7 no.1
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• pp.38-43
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• 1996

Epstein-Barr virus(EBV) is associated with a wide spectrum of benign and malignant disorders including leukoplakia, Hodgkln's lymphoma, central nervous system lymphoma, peripheral T cell lymphoma and nasopharyngeal undifferentiated carcinoma. There are several distinctive aspects of biology of the virus that are important in investigation of virus in clinical specimens. The abundant expression of the EBER mRNA transcripts makes possible the sensitive detection of latent expression in EBV-associated tumors. Although there has been a dramatic increased interest in the direct characterization of EBV in clinical specimens, there have been few studios about the effective and reliable positive controls in performing in situ hybridization technique for EBV, especially on paraffin-em bedded tissue. We applied Burkitts lymphoma ceil line as positive control in EBV in situ hydridization using Oncor Kit. The cell block of Burkitt lymphoma cell line(CCL85 EB-3) showed strong and specific positivity for EBER in situ in nuclei of EBV infected cells.

• Journal of the Korean Society of Food Culture
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• v.35 no.5
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• pp.417-425
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• 2020

There is a growing global interest in food choices that could affect health. Consumer food choices are dictated by numerous factors such as attitudes, beliefs, desires and preferences stemming from psychological and physiological attributes. The present study aimed to understand consumers' internal perceptions about cream soup, cream sauce, and tomato sauce using ZMET (Zaltman's Metaphor Elicitation Technique). The 9 step ZMET interview process was conducted for a sample of 36 consumers (12 consumers for each sauce). A content analysis of the survey results was carried out. From this, 56 concepts of cream soup were derived, and 15 constructs that met with the agreement of more than one-third of the total sample consumers were extracted. These 15 constructs included 'Soft', 'Recollection', 'Familiar', 'Warm', 'Comfortable', etc. Similarly, for cream sauce, 67 concepts and 20 constructs 'Silky', 'Warm', 'Restaurant', 'Family', 'Memory', etc. were deduced. A total of 66 concepts and 20 constructs for tomato sauce 'Sourness', 'Sauce Bottle', 'Pleasant', 'Ingredient', 'Cooking', etc. were derived. The analysis of consumers' consensus maps through this study provides a deep and useful understanding of consumers and their latent needs. Also, the results of this study indicate that exploring consumers' internal perceptions is critical to understanding their healthy food choices. This can be used as basic data for formulating marketing strategies.

• Journal of Korea Technology Innovation Society
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• v.9 no.3
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• pp.538-557
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• 2006

The interest in performance evaluation of public R&D has been dramatically increased. Many tries have been made to measure and to evaluate the quality of research performance. Quantitative indicators are considered increasingly important for this purpose. The most widely used are the number of research articles, citations and Impact Factors. However, such indicators are strongly discipline-dependent, and hence they should be used with careful attention. In this study we tried to provide quantitative evidence on the latent problems of discipline-dependent indicators. We also tried to provide a set of quantitative indicators for evaluating publications as a result of research activities. We put our focus on the quantitative indicators reflecting the characteristics on disciplines and provided several indicators with guideline on their usage.