• Management & Information Systems Review
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• v.37 no.4
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• pp.41-62
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• 2018

As the volume of unstructured data increases through various social media, Internet news articles, and blogs, the importance of text analysis and the studies are increasing. Since text analysis is mostly performed on a specific domain or topic, the importance of constructing and applying a domain-specific dictionary has been increased. The quality of dictionary has a direct impact on the results of the unstructured data analysis and it is much more important since it present a perspective of analysis. In the literature, most studies on text analysis has emphasized the importance of dictionaries to acquire clean and high quality results. However, unfortunately, a rigorous verification of the effects of dictionaries has not been studied, even if it is already known as the most essential factor of text analysis. In this paper, we generate three dictionaries in various ways from 39,800 news articles and analyze and verify the effect each dictionary on the accuracy of document classification by defining the concept of Intrinsic Rate. 1) A batch construction method which is building a dictionary based on the frequency of terms in the entire documents 2) A method of extracting the terms by category and integrating the terms 3) A method of extracting the features according to each category and integrating them. We compared accuracy of three artificial neural network-based document classifiers to evaluate the quality of dictionaries. As a result of the experiment, the accuracy tend to increase when the "Intrinsic Rate" is high and we found the possibility to improve accuracy of document classification by increasing the intrinsic rate of the dictionary.

• Journal of the Korean Society of Mineral and Energy Resources Engineers
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• v.55 no.6
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• pp.553-563
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• 2018

In this study, the location conditions and optimal technologies required for creating urban municipalities that can utilize the space in an abandoned mine area, where there is no infrastructure related to recycling wastes and valuable metals, are investigated. The urban mining industry deals with mineral resources through the processing of high value-added industrial by-products and wastes, and it is a useful linkage industry for the development of mineral resources and prevention of mining hazards. Urban mining technologies targeted at the abandoned mine area constitute screening, extraction, and smelting for recycling waste products. By analyzing the technologies available, an industrial network can be developed for recycling waste batteries and catalysts, which are promising raw materials. It is also important to establish an appropriate location for related industries that can generate value-added resources, rather than the resource supply and demand conditions seen in general urban mines. In order to overcome the accessibility and infrastructure limitations, the economic foundation of the abandoned mine area should consider the linkage of raw material supply, key technologies for recycling useful mineral resources that are derived from urban mines, spatial and site conditions, and industrial characteristics.

• Economic and Environmental Geology
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• v.54 no.1
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• pp.127-136
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• 2021

This study was carried out to understand China's earthquake governance and role-sharing, and to strategically use it for research cooperation in related fields with China. The characteristics of China's national earthquake governance and role-sharing are detailed in this study. First, unlike Korea, China's geoscience and earthquake research fields are separate, and are clearly distinguished from other fields of science and technology. They hold a higher status compared to other fields in China. Second, China's provincial earthquake agencies simultaneously carry out related tasks under the dual supervisory management system of the central and provincial governments. Third, the China Earthquake Administration (CEA) has the authority to do research and development, manpower training, and degree conferment, which are centered on directly affiliated institutions. Fourth, China carries out similar functions in directly affiliated institutions of the CEA and the China Geological Survey (CGS), and affiliated institutions of the Chinese Academy of Sciences (CAS), respectively. Fifth, the CEA is continuously expanding the seismic observation network that connects the vast land of the country. Sixth, China is considered to have detailed structures of earthquake-related laws and regulations. Given China's earthquake governance and role-sharing, it is considered that the possibility of success in research cooperation is high if Korea first determines whether it is under the jurisdiction of the CGS, CEA, and CAS, depending on the specific field.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.651-658
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• 2021

Because bolts with anti-loosening coatings are used mainly for joining safety-related components in automobiles, accurate automatic screening of these coatings is essential to detect defects efficiently. The performance of the convolutional neural network (CNN) used in a previous study [Identification of bolt coating defects using CNN and Grad-CAM] increased with increasing number of data for the analysis of image patterns and characteristics. On the other hand, obtaining the necessary amount of data for coated bolts is difficult, making training time-consuming. In this paper, resorting to the same VGG16 model as in a previous study, transfer learning was applied to decrease the training time and achieve the same or better accuracy with fewer data. The classifier was trained, considering the number of training data for this study and its similarity with ImageNet data. In conjunction with the fully connected layer, the highest accuracy was achieved (95%). To enhance the performance further, the last convolution layer and the classifier were fine-tuned, which resulted in a 2% increase in accuracy (97%). This shows that the learning time can be reduced by transfer learning and fine-tuning while maintaining a high screening accuracy.

• Korean journal of applied entomology
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• v.60 no.1
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• pp.79-90
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• 2021

Landscape composition and structure are important factors determining biological diversity including pests and natural enemires in agricultural ecosystem. This study was conducted to indentify effect of landscape composition on occurrence of lepidopteran pest population in Geochang, Gyoungdnam. For this, orchard characteristics and management practices were surveyed in 80 conventional apple orchards in Geochang, Korea, along with the monitoring of pest population densities. The landscape features of each surveyed orchard also obtained by extracting information from the public-service map. Grapholita molesta was the most dominat and damaging pest followed by Phyllonorycter ringoniella and Carposina sasakii in trap catches. Adoxophyes paraorana occurrences were low. Farmers spray insecticides and fungicides ap. 12.4 times per year respectively while acaricides were sprayed 2.4 times. Major landscape features such as surrounding apple orchard or paddy field did not influence the pest populations but presence of plum, peach, wild peach, graph, and even abandoned orchards significantly resulted in higher pest population mostly on G. molesta. C. sasakii population was higher in orchards with grape, peach, and P. ringoniella with peach, grape, abandoned orchards and jujube. Results highlight the need of landscape management not only for the rural amenity but also for increasing functional diversity of agroecosystem as well as reducing pest population.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.1
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• pp.1-8
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• 2021

In the political field of news articles, there are polarized and biased characteristics such as conservative and liberal, which is called political bias. We constructed keyword-based dataset to classify bias of news articles. Most embedding researches represent a sentence with sequence of morphemes. In our work, we expect that the number of unknown tokens will be reduced if the sentences are constituted by subwords that are segmented by the language model. We propose a document embedding model with subword tokenization and apply this model to SVM and feedforward neural network structure to classify the political bias. As a result of comparing the performance of the document embedding model with morphological analysis, the document embedding model with subwords showed the highest accuracy at 78.22%. It was confirmed that the number of unknown tokens was reduced by subword tokenization. Using the best performance embedding model in our bias classification task, we extract the keywords based on politicians. The bias of keywords was verified by the average similarity with the vector of politicians from each political tendency.

• The Southeast Asian review
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• v.28 no.1
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• pp.173-218
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• 2018

This study focuses on the healthcare sector in Vietnam which is promoting universal health insurance for the achievement of Universal Health Coverage (UHC) under Sustainable Development Goals (SDGs). The purpose of this study is to examine the characteristics of the reform process of the health care system and the law on health insurance through the historical and cultural contexts and its implications from the perspective of development. Based on the three dimensions of UHC - extension of protection for population, provision of various medical services, and financial protection, the current status of the Vietnam healthcare sector is summarized respectively as follows. First, according to the revised Health Insurance law which came into effect in 2015, the mandatory health insurance premiums are calculated based on household units. Second, there is a medical network that can provide preventive and healthcare services centered on primary health care facilities, for example commune health stations (trạm y $t{\hat{e}}$ $X{\tilde{a}}$). Third, out-of-pocket expenditure is still a large proportion although public spending has increased and private spending has decreased since the enforcement of the health insurance law and various schemes. Vietnam is currently striving towards a universal health care system. The development of institutions and systems should be designed in a way that is appropriate for the members of the society rather than efficiency. This article findings shed light on the role of social values, family culture, and informal institutions.

• Korean Journal of Acupuncture
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• v.37 no.4
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• pp.209-230
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• 2020

Objectives : Practice-Based Research Networks (PBRNs), collaborations of practitioners and academic researchers, have provided platforms for conducting research to address clinical questions generated from daily routine care. This review aimed to critically analyse articles from PBRNs that are related to complementary and integrative medicine (CIM) and to suggest future directions for a PBRN which is appropriate for Korean Medicine (KM). Methods : PubMed, PBRN registries in Agency for Healthcare Research and Quality and relevant PBRN websites were searched up to November 2019 for research articles from PBRNs that focused on CIM regardless of study design. Methodological quality of the included studies was assessed. The included studies were read in full, classified and summarised according to their topics. Results : A total of 51 articles published from 1998 through 2020 were included in this review. They were categorised into three principal themes based on research questions and findings: health services research (embracing researches examining characteristics of patients and CIM practitioners/practices, and communication between patients and practitioners); effectiveness and safety of CIM practices/interventions; and feasibility studies of instruments and interventions in PBRN settings. The study designs varied including surveys (n=30), prospective observational studies (n=6), 2ndary analyses of existing studies (n=7), protocols (n=7), retrospective chart review (n=1) and qualitative study (n=1). Quality of the included studies greatly varied. Conclusions : PBRNs can serve as a feasible platform for conducting practice-relevant research on KM and CIM. Considering growing demands on evidence-base for routine practice of KM amid various stakeholders, a PBRN in KM community and further researches nested within PBRN designs are warranted.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.225-232
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• 2021

Nowadays, opinion leaders influence the formation of public opinion on various issues in social network services. There has been a lack of research on the personal characteristics that inspire users to interact with opinion leaders and show intent to act. This paper verifies how the disposition of Facebook users' self-identity affects the quasi-social interaction with opinion leaders on Facebook and the intention to share information. As the perception and behavior of users on social media platforms differ depending on the type of issue, an online survey was conducted by classifying issue types into life culture and political sectors. Research found that personal identity had a significant positive effect on quasi-social interactions in the life culture and politics sectors, while group identity negatively affected quasi-social interactions. In addition, the intention to share information was confirmed to have a significant effect only in the life and culture areas of self-identity (social and group identity). Quasi-social interaction was confirmed to have a significant positive effect on all issue areas. The results of this study suggest the need to consider variations in opinion leader marketing strategies based on the types of self-identity of Facebook users in the future. In addition, the study shows that raising the level of quasi-social interaction at the corporate level without distinction of issue types can lead to effective results.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.561-566
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• 2021

Schools are highly feared to spread widely in the event of an infectious disease, and systematic management and prompt response are needed as it can undermine students' health and learning rights. This study was conducted to identify the current status of infectious diseases common to elementary, middle and high school students and to provide basic data to protect students and faculty from the threat of infectious diseases and maintain normal school functions. Sejong City was selected for investigation. The three major infectious diseases are influenza, chickenpox and aquarium, all of which are classified as acute viral infectious diseases and have fast propagation speed and strong propagation power, which can have fatal consequences for students living in groups. The research data were analyzed using the 2019 infectious disease report data from the Education Ministry's Education Administration Information Network (NEIS), and the current status data reported by elementary, middle and high schools nationwide were analyzed. The research method was to compare the current status of infectious diseases across the country and Sejong City, compare the status of issuance by each school level, compare the status of infectious diseases by item, and analyze the status of infectious diseases by time. The results of the survey on the status of the three major infectious diseases are expected to be used as basic data for managing infectious diseases not only in Sejong City but also in the nation, so that they can be used to establish measures to manage student infectious diseases in the future.