• Journal of Korean Medicine Rehabilitation
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• v.31 no.2
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• pp.49-55
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• 2021

Objectives The impact of social and economic losses on society due to the occurrence of osteoporosis patients is serious. The purpose of this study is to identify the types and effects of herbal medicine for osteoporosis and osteopenia. Methods We will investigate 8 online databases (MEDLINE/PubMed, Cochrane library, EMbase, China National Knowledge Infrastructure [CNKI], J-stage, National Digital Science Library [NDSL], Research Information Sharing Service [RISS], Koreanstudies Information Service System [KISS]) without language, publication date limitation for the clinical study of herbal medicine for osteoporosis and osteopenia published between the start of the database and 2021. The frequency, duration and pattern of the any type of herbal medicine utilization will be analyzed. Results Randomized controlled trials about herbal medicine or herbal medicine extracts for osteoporosis and osteopenia should be included in the study. Cochrane risk in bias tools will be used to evaluate the methodological quality of the study. A risk ratio or mean difference with a 95% confidence interval will show the effects of herbal medicine or herbal medicine extracts for osteoporosis and osteopenia. Conclusions The results of the systematic review will reflect the current status of herbal medicine treatment for osteoporosis and osteopenia, and it can be expected to verify the validity of the effectiveness, and provide it as a basic data for the use of herbal medicine in clinical utilization.

• Journal of the Korea Society of Computer and Information
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• v.26 no.11
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• pp.67-74
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• 2021

This paper intends to analyze the role expansion of characters, which was an important factor in setting the worldview in storytelling. With the development of media, the way of setting the worldview began to change. At the center of these changes are 'Transmedia' and 'Metaverse', which have recently been receiving attention. With the development of trans media, where the intersection and convergence of media is actively attempted, characters are breaking free from their innate limitations, crossing various media, and performing various activities in new stories. In addition, in the metaverse, an extended concept of the real world, avatars play a role in constructing and expanding the metaverse world as users and creators. By analyzing these changes, we would like to deal with the phenomenon in which character setting, which was used as an element in orthodox world view setting, replaces the world view.

• Knowledge Management Research
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• v.20 no.2
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• pp.25-42
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• 2019

AI speakers which are wireless speakers with smart features have released from many manufacturers and adopted by many customers. Though smart features including voice recognition, controlling connected devices and providing information are embedded in many mobile phones, AI speakers are sitting in home and has a role of the central en-tertainment and information provider. Many surveys have investigated the important factors to adopt AI speakers and influ-encing factors on satisfaction. Though most surveys on AI speakers are cross sectional, we can track customer attitude toward AI speakers longitudinally by analyzing customer reviews on AI speakers. However, there is not much research on the change of customer attitude toward AI speaker. Therefore, in this study, we try to grasp how the attitude of AI speaker changes with time by applying text mining-based analysis. We collected the customer reviews on Amazon Echo which has the highest share of AI speakers in the global market from Amazon.com. Since Amazon Echo already have two generations, we can analyze the characteristics of reviews and compare the attitude ac-cording to the adoption time. We identified all sub topics of customer reviews and specified the topics for smart features. And we analyzed how the share of topics varied with time and analyzed diverse meta data for comparisons. The proportions of the topics for general satisfaction and satisfaction on music were increasing while the proportions of the topics for music quality, speakers and wireless speakers were decreasing over time. Though the proportions of topics for smart fea-tures were similar according to time, the share of the topics in positive reviews and importance metrics were reduced in the 2nd generation of Amazon Echo. Even though smart features were mentioned similarly in the reviews, the influential effect on satisfac-tion were reduced over time and especially in the 2nd generation of Amazon Echo.

• The Journal of Information Systems
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• v.30 no.1
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• pp.65-84
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• 2021

Purpose Based on the development of artificial intelligence and big data technologies, the RegTech has been emerged to reduce regulatory costs and to enable efficient supervision by regulatory bodies. The word RegTech is a combination of regulation and technology, which means using the technological methods to facilitate the implementation of regulations and to make efficient surveillance and supervision of regulations. The purpose of this study is to describe the recent adoption of RegTech and to provide basic examples of applying RegTech to capital market regulations. Design/methodology/approach English-based ontology and deep learning technologies are quite developed in practice, and it will not be difficult to expand it to European or Latin American languages that are grammatically similar to English. However, it is not easy to use it in most Asian languages such as Korean, which have different grammatical rules. In addition, in the early stages of adoption, companies, financial institutions and regulators will not be familiar with this machine-based reporting system. There is a need to establish an ecosystem which facilitates the adoption of RegTech by consulting and supporting the stakeholders. In this paper, we provide a simple example that shows a procedure of applying RegTech to recognize and interpret Korean language-based capital market regulations. Specifically, we present the process of converting sentences in regulations into a meta-language through the morpheme analyses. We next conduct deep learning analyses to determine whether a regulatory sentence exists in each regulatory paragraph. Findings This study illustrates the applicability of RegTech-based ontology and deep learning technologies in Korean-based capital market regulations.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.2
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• pp.227-261
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• 2021

This study aims to analyze the current status of school library assessment and generate discussion points for the development directions of the assessment. Surveys, consulting, and evaluations related to school libraries conducted by the Office of Education, the Ministry of Education, the Ministry of Culture, Sports and Tourism were analyzed using meta-evaluations and in-depth interviews with the school librarians. The analysis revealed problems such as duplication of evaluation by various institutions, no reflection of the national school library development plan, low participation rate due to voluntary nature of the assessment, and lack of the educational evaluation index. The solution to the problem was a school libraries' operation evaluation improvement plan. The plan included the legal evaluation agent specification, the national school library development plan incorporation, inter-agency evaluation network & the case sharing system establishment, and the Office of Education's investigation and consulting cooperation.

• Journal of Broadcast Engineering
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• v.26 no.1
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• pp.70-78
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• 2021

Estimating 3D information from a single image is one of the essential problems in numerous applications. Since a 2D image inherently might originate from an infinite number of different 3D scenes, thus 3D reconstruction from a single image is notoriously challenging. This challenge has been overcame by the advent of recent deep convolutional neural networks (CNNs), by modeling the mapping function between 2D image and 3D information. However, to train such deep CNNs, a massive training data is demanded, but such data is difficult to achieve or even impossible to build. Recent trends thus aim to present deep learning techniques that can be trained in a weakly-supervised manner, with a meta-data without relying on the ground-truth depth data. In this article, we introduce recent developments of weakly-supervised deep learning technique, especially categorized as scene 3D reconstruction and object 3D reconstruction, and discuss limitations and further directions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.9
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• pp.1193-1201
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• 2020

Cell planning, which determines the cell structure for location management of mobile terminals in mobile communications, has been dealt with as an important research task to determine network performance. Among the factors influencing the cell structure planning in mobile communication, the signal cost for location management plays the most important role. In this paper, we propose an optimization algorithm that minimizes the location management cost of all the cells used to plan the cell structure in the network with reporting cell structure in mobile communication. The proposed algorithm uses a Tabu search algorithm, which is a meta-heuristic algorithm, and the proposed algorithm proposes a new neighborhood generation method to obtain a result close to the optimal solution. In order to evaluate the performance of the proposed algorithm, the simulation was performed in terms of location management cost and algorithm execution time. The evaluation results show that the proposed algorithm outperforms the existing genetic algorithm and simulated annealing.

• Journal of Oriental Neuropsychiatry
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• v.32 no.1
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• pp.55-66
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• 2021

Objectives: The aim of this scoping review was to analyze research trends about mental health of nurses working in Korean medicine (KM) hospitals in Republic of Korea. Methods: Searches were conducted using four electronic databases including Oriental Medicine Advanced Searching Integrated System, Korean Studies Information Service System, Research Information Sharing Service, Korea Citation Index to collect relevant studies. The search date was March 4, 2021. All studies published up to the search date were considered. Observational studies reporting mental health outcomes of nurses working at KM Hospital were included. Results: A total of 11 cross-sectional observation studies were included. Four of them compared mental health of nurses working on KM and Western medicine (WM). Commonly reported outcomes related to mental health were job satisfaction, role conflict, and work stress. As a result of meta-analysis based on a 5-point Likert scale, the following factors were related to mental health of KM nurses: job satisfaction (2.844±0.067 points), role conflict (3.678±0.058 points), work stress (3.142±0.021 points), turnover intention (3.483±0.028 points), and burnout (3.180±0.033). Compared to WM nurses, KM nurses had significantly less work stress (p=0.000), role conflict (p=0.039), and job satisfaction (p=0.000). Conclusions: Mental health problems of nurses are known to be very common. Although improving them is an important social task, studies on mental health of KM nurses remain insufficient. Based on findings of this study, more cooperation between nurses and KM doctors should be made to improve the mental health of KM nurses, especially their job satisfaction in the future. The Korean Society of Oriental Neuropsychiatry needs to pay more attention to this topic.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.8
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• pp.1013-1018
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• 2021

Due to the recent accident caused by the automated vehicle, discussions on the ethical aspects of AI have been actively underway. This paper confirms that AI is inevitably connected to ethical components through the concepts and techniques related to robots-AI, and argues that ethical aspects are built-in, not post facto. Furthermore, this devises a solution to the trolley dilemma that can serve as a clue to ethical problems associated with automated vehicles. Preferentially, that process contains writing Bayesian networks. Next, only important and influential data are left after the pre-processing stage, and crowd-sourcing & extrapolation is used to calculate the exact figures of the networks. Through this process, this argues that humans' subjects are certainly included in implementing algorithms and models and discusses the necessity and direction of engineering liberal arts, especially education of ethics that distinguished from major education to prevent distortions and biases abouts AI systems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.43-52
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• 2021

In weapon assignment studies to defend against threats such as ballistic missiles and long range artillery, threat assessment was partially lacking in analysis of various threat attributes, and considering the threat characteristics of warheads, which are difficult to judge in the early flight stages, it is very important to apply more reliable optimal solutions than approximate solution using LP model, Meta heuristics Genetic Algorithm, Tabu search and Particle swarm optimization etc. Our studies suggest Generic Rule based threat evaluation and weapon assignment algorithm in the basis of various attributes of threats. First job of studies analyzes information on Various attributes such as the type of target, Flight trajectory and flight time, range and intercept altitude of the intercept system, etc. Second job of studies propose Rule based threat evaluation and weapon assignment algorithm were applied to obtain a more reliable solution by reflection the importance of the interception system. It analyzes ballistic missiles and long-range artillery was assigned to multiple intercept system by real time threat assessment reflecting various threat information. The results of this study are provided reliable solution for Weapon Assignment problem as well as considered to be applicable to establishing a missile and long range artillery defense system.