• Journal of the Korean Society for information Management
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• v.39 no.2
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• pp.203-232
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• 2022

Drug addiction or substance use disorder is continuously observed worldwide for its risks and prevalence. In this context, numerous studies have been conducted regarding this issue. However, bibliometric analysis related to drug addiction is insufficient. In particular, it is difficult to find research that utilizes a macro-level bibliographic approach that comprehensively reflects various characteristics related to drug addiction. In this study, to reflect the multidimensional features of drug addiction, research trends in drug addiction in social science, natural science, and multidisciplinary studies were compared and analyzed. This study collected drug addiction research articles from 2002 to 2021 by searching from the Web of Science, and classified academic disciplines based on SCI(E) and SSCI information. Author keyword co-occurrence analysis was also conducted, which provided confirmation that natural science mainly studied psychoactive substances and the reward system in the brain, while drug addiction studies reflecting demographic characteristics were conducted in the domain of social science. In the multidisciplinary field, all of the above topics were covered. Author co-citation analysis was also employed, which showed that there are superstars (i.e., authors who receive a rigorous amount of citation) in the field of natural science, while in the social science domain, authors were highly cited not only at the individual level but also at the institutional level.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.185-207
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• 2022

Recently, with the development of deep learning technology, researches to apply a deep learning algorithm to analyze unstructured data such as text and images are being actively conducted. Text classification has been studied for a long time in academia and industry, and various attempts are being performed to utilize data characteristics to improve classification performance. In particular, a hierarchical relationship of labels has been utilized for hierarchical classification. However, the top-down approach mainly used for hierarchical classification has a limitation that misclassification at a higher level blocks the opportunity for correct classification at a lower level. Therefore, in this study, we propose a methodology for classifying hierarchical data using the autoencoder-based deeply supervised network that high-level classification does not block the low-level classification while considering the hierarchical relationship of labels. The proposed methodology adds a main classifier that predicts a low-level label to the autoencoder's latent variable and an auxiliary classifier that predicts a high-level label to the hidden layer of the autoencoder. As a result of experiments on 22,512 academic papers to evaluate the performance of the proposed methodology, it was confirmed that the proposed model showed superior classification accuracy and F1-score compared to the traditional supervised autoencoder and DNN model.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.81-103
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• 2022

It recognizes the importance of mental health and well-being worldwide and consistently records public happiness figures through the World Happiness Report. COVID-19, which occurred in China in 2019, has changed people's daily lives a lot. The accumulation of stress caused by the prolonged epidemic is affecting people's happiness. The present research has revealed negative mental health effects such as "depression" and "anxiety" after the pandemic. In this regard, it was revealed that the happiness index was also lowered numerically. It is insufficient to analyze specific issues about changes in the issue of happiness felt by the public in Korean society after the epidemic. Therefore, this study aims to identify changes in the happiness issue of Koreans after COVID-19 and find ways to improve happiness. Data were collected from various aspects by searching 32 sub keywords based on ERG theory by dividing the period before and after COVID-19. The results of topic modeling before and after COVID-19 were classified into seven areas of happiness index 2.0 published by the National Assembly Future Research Institute and compared and analyzed. Based on the results of comparing the results of the before and after topic from the perspective of each area, a plan to improve happiness was presented. The academic implications of this paper are that the research on psychological changes caused by COVID-19 was expanded by mining the opinions of the actual public on 'happiness'. In addition, it has practical implications in that it specifically presented measures to promote happiness by utilizing the area of objective happiness indicators based on the existing research on ways to reduce happiness promotion unhappiness.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.223-231
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• 2022

Covid-19, which has made a huge difference in our daily lives, has also brought major changes to our college education. As the class was changed from the traditional face-to-face class to a non face-to-face class, both teachers and students had difficulties in adapting, and problems such as the occurrence of academic achievement gaps due to non face-to-face classes were also raised. Therefore, this study aims to find out what attitudes students have toward non-face-to-face classes at universities caused by Covid-19. Accordingly, this study tried to identify the types of subjective perceptions college students have toward non-face-to-face classes by applying the Q methodology, and to suggest points for reference in the development and improvement of non-face-to-face classes in the future. Five types were found as a result of analysis using 30 P samples and 34 Q samples. First, learning efficiency-oriented type, second, class participation and communication-oriented type, third, non-face-to-face class active acceptance and utilization type, fourth, dissatisfaction type due to remote system and equipment operation errors, fifth, passive response type according to the situation to be. From the results of this study, it seems that it is necessary to develop an educational method for effective non-face-to-face class considering the characteristics of each type, and the merits of non-face-to-face classes, especially recorded lectures, in terms of learning efficiency, are evident. Therefore, even if face-to-face classes are conducted entirely at universities, it is believed that providing video-recorded lectures in class will be of great help to students' learning.

• The Journal of Korean Medicine
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• v.42 no.3
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• pp.153-164
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• 2021

Objectives: The aim of this study is to investigate the effect of Heat-sensitive Moxibustion on Benign Prostatic Hyperplasia Methods: We searched articles from Academic Journals(CAJ) online databases, Oriental Medicine Advanced Searching Integrated System (OASIS), Searching key words were '前列腺增生', '熱敏灸' and '열민구', '전립선비대'. The search range included randomized controlled trials (RCTs). Among the articles published to 2020, 10 articles were found. After review the title, abstract and original, 3 articles were selected finally to rule out treatment combined with completely different treatments. Result: The Heat-sensitive moxibustion at acupoints in the treatment of Benign prostatic hyperplasia were significantly superior to control group after treatment in the symptoms of patients, IPSS, QOL, PVR and Qmax(P<0.05). The Heat-sensitive moxibustion can significantly reduce the incidence of temporary urinary incontinence after Transurethral resection of the prostate(TURP) and improve life quality and satisfaction of patients(P<0.05). The individualized desensitization saturated time and amount of Heat-sensitive moxibustion is superior effective to general amount and time of traditional moxibustion in the total effective rate, IPSS, Ru and Qmax(P<0.01) for Benign prostatic hyperplasia. Conclusion: Heat sensitive moxibustion directly transfer heat to the source of a disease. So it can be considered as a good treatment for Benign prostate hypertrophy. It was also shown a better effect on BPH compared to traditional moxibustion, According to the thermo principles of tumor, if the tumor cell's death temperature of 43℃ is reached, that can cause tumor degeneration. Therefore I think Heat sensitive moxibustion can be applied to various tumor disease. The results of this study could be applied to clinical treatment of BPH. However, additional large-scale clinical researches should be conducted.

• The Journal of the Korea Contents Association
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• v.22 no.2
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• pp.529-544
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• 2022

With the global pandemic in the era of the 4th industrial revolution, the business environment of companies was engulfed by rapid volatility and uncertainty. In particular, in order for an organization to have high competitiveness due to the spread of the flexible work system, relationship management with members of the organization and self-directed job crafting are recognized as important key resources. This study aims to investigate how relational energy and resilience within a corporate organization affect job crafting and to verify the effect of job crafting on individual job performance. For empirical research, 400 valid responses to employees of general companies were analyzed by SPSS 26.0 and Smart PLS 3.0. As a result of the analysis, first, it was confirmed that relational energy did not have a positive (+) effect on task crafting. Second, it was found that relational energy had a positive (+) effect on relational crafting and cognitive crafting, respectively. Third, it was found that resilience had a positive (+) effect on both task crafting, relationship crafting, and cognitive crafting that constitute job crafting. Fourth, it was found that job crafting had a positive (+) effect on individual job performance. Based on these research results, we intend to derive academic and practical implications and provide practical help to follow-up researchers and stakeholders.

• Korean Journal of Construction Engineering and Management
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• v.23 no.3
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• pp.74-82
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• 2022

With the introduction of proptech, this study aims to find out the changes and necessity of introducing blockchain technology, one of the most popular technologies, in real estate electronic transactions. In addition, it is intended to develop evaluation indicators that classify newly created values within real estate electronic transactions and calculate the relative importance of each value area through technology application. To this end, the value that can be created when applying blockchain technology to real estate electronic transactions was classified according to the hierarchy, and considering that the evaluation criteria are complex and the importance can be measured differently depending on various factors, an analysis was conducted according to the AHP method for experts in practical and academic fields. As a result of the analysis, general value showed the highest importance in the first dimension, and digitalization of real estate information showed the highest importance in the second dimension.

• Journal of The Korean Association of Information Education
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• v.25 no.6
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• pp.907-915
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• 2021

In this study, in order to investigate the relationships between the self-efficacy, career maturity, and information subject achievement of information-specialized high school students according to information subject classes, their correlations were analyzed through a survey of 214 second and third year students enrolled in two information-specialized high schools in Seoul. The main results are as follows. First, in the analysis of differences in self-efficacy, career maturity, and information subject achievement according to demographic characteristics, there was no significant difference according to gender, grade, extracurricular or individual learning for information subjects. The more they recognized that their grades belonged to the upper group, the higher their sense of self-efficacy and information subject achievement were perceived, and the higher their career maturity. Second, the students' self-efficacy was analyzed to have a positive effect on their career maturity and information subject achievement. Finally, it was found that the students' career maturity had a positive effect on their information subject achievement. Based on the above results, we briefly present the development direction for the education system to improve students' self-efficacy, career maturity, and information subject achievement.

• Journal of Korean Library and Information Science Society
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• v.54 no.1
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• pp.45-68
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• 2023

This study aims to investigate the awareness and experiences of domestic researchers regarding data publishing, which has been recognized as a new channel of data sharing as scholarly communication evolves in the open science environment. A survey is conducted among researchers from five government-funded research institutes in the field of science and technology and members of the GeoAI Data Society to confirm the awareness of data publishing. As a result of the study, domestic researchers recognized providing explanations for data, stable access to data, citation, and quality assurance through peer review as the advantages of data journals. On the contrary, a low level of recognition for data paper as one of the research outputs was presented. With regard to the properties of data publication, the respondents answered that the data description, metadata description, and permanent identifiers are highly related, however, their recognition of the relation between the properties of data publication and the data submission to a repository and data peer review was relatively low. Finally, to expand the data publication, the need for the development of an editorial system that supports data paper peer review and cross-linking to a data repository as well as the development of a repository that supports data citation was identified. This study on the domestic researchers' experience and awareness of data publishing can provide insights for the implementation of data publishing services and infrastructure in the future.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.377-396
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• 2023

As the cryptocurrency market continues to grow, it has developed into a new financial market. The need for investment strategy research on the cryptocurrency market is also emerging. This study aims to conduct an empirical analysis on an investment methodology of cryptocurrency that combines short-term trading strategy and deep learning. Daily price data of the Ethereum was collected through the API of Upbit, the Korean cryptocurrency exchange. The investment performance of the experimental model was analyzed by finding the optimal parameters based on past data. The experimental model is a volatility breakout strategy(VBS), a Long Short Term Memory(LSTM) model, moving average cross strategy and a combined model. VBS is a short-term trading strategy that buys when volatility rises significantly on a daily basis and sells at the closing price of the day. LSTM is suitable for time series data among deep learning models, and the predicted closing price obtained through the prediction model was applied to the simple trading rule. The moving average cross strategy determines whether to buy or sell when the moving average crosses. The combined model is a trading rule made by using derived variables of the VBS and LSTM model using AND/OR for the buy conditions. The result shows that combined model is better investment performance than the single model. This study has academic significance in that it goes beyond simple deep learning-based cryptocurrency price prediction and improves investment performance by combining deep learning and short-term trading strategies, and has practical significance in that it shows the applicability in actual investment.