• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.3
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• pp.395-405
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• 2024

This study provides a thorough examination of Unmanned Ground Vehicles(UGVs), focusing on crucial technologies and trends across major global markets. It includes an in-depth patent analysis revealing the dominant positions of the United States and the European Union in this field. Additionally, it underscores substantial advancements made by China, Japan, and Korea since 2010. Using Latent Dirichlet Allocation(LDA)-based patent text mining, the study identified key technology areas in UGV development, such as advanced control systems, navigation technologies, power supply mechanisms, and sensing and communication tools. Through linear regression analysis, the study predicted the future paths of these technology areas, offering important insights into the evolving world of UGV technology. The findings can provide strategic guidance for stakeholders in the defense, commercial, and academic sectors, pointing out the future directions in UGV advancements.

• Journal of the Korean Society of Clothing and Textiles
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• v.48 no.5
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• pp.883-899
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• 2024

The aim of this study was to investigate fashion firms' environmental, social, and governance (ESG) information disclosure. A total of 25 fashion firms (e.g., Adidas, Burberry Group, Nike, Ralph Lauren Corp.) were selected, including eight luxury brands and eight athleisure brands. Thus, three groups were formed for analysis: the entire group (N = 25), luxury brands (N = 8), and athleisure brands (N = 8). Based on the ESG information disclosed on the firms' official web pages, 1128 valid words were extracted. The top keywords for each brand group were identified based on the frequency and term frequency-inverse document frequency (TF-IDF), and semantic network analysis and convergence of iterated correlations (CONCOR) analysis were performed. The results revealed that several keywords and clusters emerged with respect to unique attributes of the fashion industry, and they also revealed inconsistent ESG clusters according to brand type. The findings have significant academic and managerial implications.

• Journal of the Korean Society for information Management
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• v.19 no.4
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• pp.384-399
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• 2002

The ownership of scholarly communication, i.e. copyright is very important to solve the problem of access to many academic journals in network environment. The purpose of this article is to give a conceptual model for the open access based scholarly communication. The main point of this model is for the authors of research paper to retain copyright on their works and to license the work whenever it is reproduced or redistributed for non-profit use with academic purpose. And library have to construct full text journal databases under this open access license.

• Journal of Korean Library and Information Science Society
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• v.32 no.4
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• pp.419-447
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• 2001

This study is to analyze a cost-benefit and a cost-effectiveness on the basis of number full-text downloaded from IDEAL in the electronic journals consortium of Y University Library during 2000. The result of this study shows that Y University Library used more the combined print and electronic journals than only electronic journals, and in the case of the analysis on the cost-benefit, there was no benefit, but the cost-effectiveness was very high. Based upon the result of this study, it suggests that academic libraries request a trial from the information agency and carry out user instruction analysis of varied use statistics, user satisfaction survey so as to promote use of electronic journals.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.8-17
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• 2019

The main purpose of this study isto explore the potential of affective computing (AC) platforms in education through two phases ofresearch: Phase I - platform analysis and Phase II - classification of academic emotions. In Phase I, the results indicate that the existing affective analysis platforms can be largely classified into four types according to the emotion detecting methods: (a) facial expression-based platforms, (b) biometric-based platforms, (c) text/verbal tone-based platforms, and (c) mixed methods platforms. In Phase II, we conducted an in-depth analysis of the emotional experience that a learner encounters in online video-based learning in order to establish the basis for a new classification system of online learner's emotions. Overall, positive emotions were shown more frequently and longer than negative emotions. We categorized positive emotions into three groups based on the facial expression data: (a) confidence; (b) excitement, enjoyment, and pleasure; and (c) aspiration, enthusiasm, and expectation. The same method was used to categorize negative emotions into four groups: (a) fear and anxiety, (b) embarrassment and shame, (c) frustration and alienation, and (d) boredom. Drawn from the results, we proposed a new classification scheme that can be used to measure and analyze how learners in online learning environments experience various positive and negative emotions with the indicators of facial expressions.

• Journal of the Korean Society for information Management
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• v.38 no.1
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• pp.221-242
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• 2021

This study applied reference metadata recognition using bidirectional GRU-CRF model based on pre-trained language model. The experimental group consists of 161,315 references extracted by 53,562 academic documents in PDF format collected from 40 journals published in 2018 based on rules. In order to construct an experiment set. This study was conducted to automatically extract the references from academic literature in PDF format. Through this study, the language model with the highest performance was identified, and additional experiments were conducted on the model to compare the recognition performance according to the size of the training set. Finally, the performance of each metadata was confirmed.

• Journal of Home Health Care Nursing
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• v.31 no.1
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• pp.66-76
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• 2024

Purpose: This study aimed to develop and evaluate an integrated management program to enhance self-efficacy, compliance with sick-role behaviors, symptom management, and biomarker indication in hemodialysis patients. Methods: The integrated management program was developed through a systematic review of literature, analysis of relevant online data, and expert validation. It comprised 480 min of video-based education delivered eight times over four weeks, supplemented by weekly phone consultations and text message support from a nurse. To evaluate the program's effectiveness, it was administered to 44 patients with hemodialysis in a single group in a pre-post test experimental study. Changes in self-efficacy, sick-role behavior compliance, dialysis symptom index, and biomarkers were assessed. Results: The program yielded statistically significant improvements in self-efficacy (t=-7.13, p<.001), sick-role behavioral compliance (t=-7.35, p<.001), dialysis symptom index (t=4.32, p<.001), and blood urea nitrogen levels (t=2.55, p=.014) among the participants. Conclusion: The integrated management program is an effective intervention for improving hemodialysis patients' self-efficacy, compliance with sick-role behaviors, and experience of symptoms. Additionally, it is considered an intervention with high clinical applicability and efficiency through video reproducibility.

• Convergence Security Journal
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• v.19 no.4
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• pp.23-34
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• 2019

This study utilized big data, one of the new technologies of the Fourth Industrial Revolution as a policy direction study related to the military security of the Army. By utilizing Text mining and analyzing military security trends in domestic and foreign papers, it will be able to set policy directions and reduce trial and error. In this study, we found differences in domestic and international studies on military sucurity. At first, Domestic research has shown that in the course of the fourth industrial revolution, there is a strong interest in technological security, such as IT technology in security and cyber security in North Korea. On the other hand, Foreign research confirmed that policies are being studied in such a way that military sucurity is needed at the level of cooperation between countries and that it can contribute to world peace. Various academic policy studies have been underway in terms of determining world peace and security levels, not just security levels. It contrasted in our immediate confrontation with North Korea for decades but suggest complementary measures that cannot be overlooked from a grand perspective. Conclusionally, the direction of academic research in domestic and foreign should be done in macro perspective under national network cooperation, not just technology sucurity research, recognizing that military security is a policy product that should be studied in a security system between countries.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.3
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• pp.13-24
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• 2018

For government and public institutions, civil complaints containing direct requirements of citizens can be utilized as important data in developing policies. However, it is difficult to draw accurate requirements using text mining methods since the nature of the complaint text is unstructured. In this study, a new method is proposed that draws the exact requirements of citizens, improving the previous text mining in analyzing the data of civil complaints. The new text-mining method is based on the principle of Co-Occurrences Structure Map, and it is structured by two-step association analysis, so that it consists of the first-order related word and a second-order related word based on the core subject word. For the analysis, 3,004 cases posted on the electronic bulletin board of Busan City for the year 2016 are used. This study's academic contribution suggests a method deriving the requirements of citizens from the civil affairs data. As a practical contribution, it also enables policy development using civil service data.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.97-107
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• 2020

This study aims to conduct a comprehensive meta-study from the perspective of content analysis to explore trends in Korean academic research on the sharing economy by using the big data analytics. Comprehensive meta-analysis methodology can examine the entire set of research results historically and wholly to illuminate the tendency or properties of the overall research trend. Academic research related to the sharing economy first appeared in the year in which Professor Lawrence Lessig introduced the concept of the sharing economy to the world in 2008, but research began in earnest in 2013. In particular, between 2006 and 2008, research improved dramatically. In order to grasp the overall flow of domestic academic research of trends, 8 years of papers from 2013 to the present have been selected as target analysis papers, focusing on titles, keywords, and abstracts using database of electronic journals. Big data analysis was performed in the order of cleaning, analysis, and visualization of the collected data to derive research trends and insights by year and type of literature. We used Python3.7 and Textom analysis tools for data preprocessing, text mining, and metrics frequency analysis for key word extraction, and N-gram chart, centrality and social network analysis and CONCOR clustering visualization based on UCINET6/NetDraw, Textom program, the keywords clustered into 8 groups were used to derive the typologies of each research trend. The outcomes of this study will provide useful theoretical insights and guideline to future studies.