• Food Engineering Progress
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• v.13 no.1
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• pp.38-43
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• 2009

In this research, the contents of capsaicin and dihydrocapsaicin in various species of red pepper produced in the Goesan-gun County were determined by GC-MS. Further, the contents of capsaicin and dihydrocapsaicin in powdered red pepper products with very hot, hot, normal and mild taste were analyzed to present the degree of hot taste in their products based on contents of capsaicin. The contents of capsaicin in each species of red pepper were from 25.18 mg%(Daetong) to 123.62 mg%(Cheongyang). In the powdered red pepper sold in the market, the contents (mg%) of capsaicin in very hot, hot, normal and mild taste products were 101.98, 67.63, 37.74, and 14.73, respectively. Based on this result, the classification of hot taste by contents of capsaicin was presented in the 7 grades. Namely, the products currently sold in the market were classified into very hot, hot, normal and mild taste. In this research, the degree of hot taste was classified based on contents of capsaicin into 1st grade over 120 mg%, 2nd grade in 100-120 mg%, 3rd grade in 80-100 mg%, 4th grade in 60-80 mg%, 5th grade in 40-60 mg%, 6th grade in 20-40 mg% and 7th grade below 20 mg%. Thus, it is expected that the problem which arises when preparing the products such as kimchi, gochujang and seasoning sauces by using powdered red pepper, namely, the inconsistency of hot taste can be improved and maintained.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.29 no.2
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• pp.251-258
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• 2019

Objective: Chronic obstructive pulmonary disease(COPD) is characterized by persistent airflow limitations associated with chronic inflammatory response due to noxious particles or gases in the lung. Inflammation and oxidative stress are associated with COPD. The aim of this study was to evaluate the relationship among inflammation, oxidative stress, and airflow limitation severity in retired miners with COPD. Methods: The levels of serum high-sensitivity C-reactive protein(hsCRP) as a biomarker for inflammation, degree of reactive oxygen metabolites(dROMs) and biological antioxidants potential(BAP) in plasma as biomarkers for oxidative stress were measured in 211 male subjects with COPD. Degree of airflow limitation severity as determined by spirometry was divided into three grades grouped according to the classification of the Global Initiatives for Obstructive Lung Disease(GOLD)(1, mild; 2, moderate; $3{\leq}$, severe or more) using a fixed ratio, post- bronchodilator $FEV_1/FVC$ < 0.7. Results: Mean levels of dROMs significantly increased in relation to airflow limitation severity(GOLD 1, 317.8 U.CARR vs. GOLD 2, 320.3 U.CARR vs. GOLD $3{\leq}$, 350.9 U.CARR, p=0.047) and dROMs levels were correlated with serum hsCRP levels(r=0.514, p<0.001). Mean levels of hsCRP were higher in current smokers(non-smoker, 1.47 mg/L vs. smoker, 2.34 mg/L, p=0.006), and tended to increase with degree of airflow limitation severity(p=0.071). Mean levels of BAP were lower in current smokers(non-smoker, $1873{\mu}mol/L$ vs. smoker, $1754{\mu}mol/L$, p=0.006). Conclusions: These results suggest that inflammation and oxidative stress are related to airflow limitation severity in retired miners with COPD, and there was a correlation between inflammation and oxidative stress.

• Management & Information Systems Review
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• v.38 no.3
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• pp.55-80
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• 2019

Recently, many companies improving their management performance by building a powerful brand value which is recognized for trademark rights. However, as growing up the size of online commerce market, the infringement of trademark rights is increasing. According to various studies and reports, cases of foreign and domestic companies infringing on their trademark rights are increased. As the manpower and the cost required for the protection of trademark are enormous, small and medium enterprises(SMEs) could not conduct preliminary investigations to protect their trademark rights. Besides, due to the trademark image search service does not exist, many domestic companies have a problem that investigating huge amounts of trademarks manually when conducting preliminary investigations to protect their rights of trademark. Therefore, we develop an intelligent similar trademark search model to reduce the manpower and cost for preliminary investigation. To measure the performance of the model which is developed in this study, test data selected by intellectual property experts was used, and the performance of ResNet V1 101 was the highest. The significance of this study is as follows. The experimental results empirically demonstrate that the image classification algorithm shows high performance not only object recognition but also image retrieval. Since the model that developed in this study was learned through actual trademark image data, it is expected that it can be applied in the real industrial environment.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.5
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• pp.493-498
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• 2019

This study deals with the analysis of the technology association rules between CPC codes of the Internet of Things(IoT) patent, the core of the Fourth Industrial Revolution ICT-based technology. The association rules between CPC codes were extracted using R, an open source for data mining. To this end, we analyzed 369 of the 605 patents related to the Internet of Things filed with the Patent Office until July 2019, with a complex CPC code, up to the subclass-level. As a result of the technology association rules, CPC codes with high support were [H04W ${\rightarrow}$ H04L](18.2%), [H04L ${\rightarrow}$ H04W](18.2%), [G06Q ${\rightarrow}$ H04L](17.3%), [H04L ${\rightarrow}$ G06Q](17.3%), [H04W ${\rightarrow}$ G06Q](9.8%), [G06Q ${\rightarrow}$ H04W](9.8%), [G06F ${\rightarrow}$ H04L](7.9%), [H04L ${\rightarrow}$ G06F](7.9%), [G06F ${\rightarrow}$ G06Q](6.2%), [G06Q ${\rightarrow}$ G06F](6.2%). After analyzing the technology interconnection network, the core CPC codes related to technology association rules are G06Q and H04L. The results of this study can be used to predict future patent trends.

• The Journal of Society for e-Business Studies
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• v.24 no.3
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• pp.35-51
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• 2019

The two main goals of this study are to derive independent factors affecting the success rate of crowdfunding and to empirically analyze the variation of independent factors' effects on the success of crowdfunding by industry (Internet, culture/art, manufacturing/distribution), and funding type (stock type, bond type). To identify the success factors of crowdfunding for invigoration and strategic utilization, first, several variables were refined after interviews with experts and platform operators with investment experiences in numerous crowdfunding projects. Then, independent factors affecting project involvement were categorized as follows: a characteristic of project, participant activity, and enterprise. Also, the results derived from the influence of independent variables on crowdfunding after moderating effects were driven. Selected independent factors in this study are as follows: crowdfunding period, target amount, visual contents, minimum account money, number of comments, number of SNS followers, level of interest, financial Statement disclosure, investment attraction, venture company, intellectual property rights disclosure, and business operation period. Selected moderating factors in this study are as follows: industry (Internet, culture/art, manufacturing/distribution), and funding type (stock type, bond type). In conclusion, a discussion of the academical and practical implications and a suggestion of directions for further research are explained.

• Health Policy and Management
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• v.30 no.4
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• pp.438-443
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• 2020

The digital treatment technology industry is one of the core fostering industries of the Moon Jae-in government along with the global trend. The purpose of this study is to compare and analyze the investment and economic ripple effect on the related industries. To this end, we used the industry-related table, which is the actual measurement data for 2015 that the Bank of Korea actually measured and released every 5 years in 2019. The digital treatment technology industry was not clearly classified within Korea's industrial classification system, so the contents of the industry-related survey were analyzed, and the digital treatment technology industry was reclassified and then analyzed. As a result of the analysis, it was analyzed that the production induction effect of the digital treatment technology-related industry in 2015 was 1.770, the value-added induction effect was 0.875, and the employment induction effect was 19.128, which was higher than that of other industries in Korea. As a result of the analysis of the economic ripple effect (scenario 1), the production inducing effect was about 370 billion won, the added value inducing effect was about 185 billion won, and the employment inducing effect was 4,044 people. The results of this study are expected to play a large role in economic revitalization as the effect of inducing production, increasing employment, and creating added value through fostering the digital treatment technology industry is expected to play a large role in activating the economy. It is expected to play a large role in providing central medical services. Therefore, it is expected that policy support for revitalizing the digital treatment technology industry through active investment support and tax benefits from the government to foster the digital treatment technology industry is necessary.

• Knowledge Management Research
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• v.21 no.4
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• pp.129-156
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• 2020

The sharing economy is recognized as a new economic system based on the digital service platform, but the sharing economy has yet to be established in Korea due to a lack of social awareness and understanding. There is a need to enhance understanding and awareness of the sharing economy in positive perspective in order to make up business with advanced economies global and explore new markets. In this study, after collecting papers of the sharing economy over the past decade published by each academic field around the world, we reviewed them from academic lens and conducted a comprehensive analysis using meta analysis methodology. Then, we selected papers of MIS field and analyzed the trends of the MIS field research in these papers. As a result we identified the research trend of the sharing economy and the MIS research and drew the necessity of interdisciplinary research between the two studies by examining importance and relevance of MIS research in the sharing economy research. Therefore, we expect that this study contributes to promote interdisciplinary research with neighboring disciplines and to establish a positive social, economical and industrial position in Korea.

• Applied Chemistry for Engineering
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• v.32 no.4
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• pp.361-370
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• 2021

Carbon fiber reinforced polymer (CFRP) is one of the composite materials, which has a unique property that is lightweight but strong. The CFRPs are widely used in various industries where their unique characteristics are required. In particular, electric and unmanned aerial vehicles critically need lightweight parts and bodies with sufficient mechanical strengths. Vehicles using the battery as a power source should simultaneously meet two requirements that the battery has to be safely protected. The vehicle should be light of increasing the mileage. The CFRP has considered as the one that satisfies the requirements and is widely used as battery housing and other vehicle parts. On the other hand, in the battery area, carbon fibers are intensively tested as battery components such as electrodes and/or current collectors. Furthermore, using carbon fibers as both structure reinforcements and battery components to build a structural battery is intensively investigated in Sweden and the USA. This mini-review encompasses recent research trends that cover the classification of structural batteries in terms of functionality of carbon fibers and issues and efforts in the battery and discusses the prospect of structural batteries.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.3
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• pp.119-131
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• 2009

The world's widely used key exchange protocols are open cryptographic communication protocols, such as TLS/SSL, whereas in the financial field in Korea, key exchange protocols developed by industrial classification group have been used that are based on PKI(Public Key Infrastructure) which is suitable for the financial environments of Korea. However, the key exchange protocols are not only vulnerable to client impersonation attacks and known-key attacks, but also do not provide forward secrecy. Especially, an attacker with the private keys of the financial security server can easily get an old session-key that can decrypt the encrypted messages between the clients and the server. The exposure of the server's private keys by internal management problems, etc, results in a huge problem, such as exposure of a lot of private information and financial information of clients. In this paper, we analyze the weaknesses of the cryptographic communication protocols in use in Korea. We then propose two key exchange protocols which reduce the replacement cost of protocols and are also secure against client impersonation attacks and session-key and private key reveal attacks. The forward secrecy of the second protocol is reduced to the HDH(Hash Diffie-Hellman) problem.

• The Journal of Society for e-Business Studies
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• v.27 no.1
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• pp.15-28
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• 2022

Due to recent expansion of online market such as clothing, utilizing customer review has become a major marketing measure. User review has been used as a tool of analyzing sentiment of customers. Sentiment analysis can be largely classified with machine learning-based and lexicon-based method. Machine learning-based method is a learning classification model referring review and labels. As research of sentiment analysis has been developed, multi-modal models learned by images and video data in reviews has been studied. Characteristics of words in reviews are differentiated depending on products' and customers' categories. In this paper, sentiment is analyzed via considering review data and metadata of products and users. Gated Recurrent Unit (GRU), Long Short-Term Memory (LSTM), Self Attention-based Multi-head Attention models and Bidirectional Encoder Representation from Transformer (BERT) are used in this study. Same Multi-Layer Perceptron (MLP) model is used upon every products information. This paper suggests a multi-modal sentiment analysis model that simultaneously considers user reviews and product meta-information.