• Animal Bioscience
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• v.35 no.2_spc
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• pp.332-346
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• 2022

Shortage of protein feed resources is the major challenge to the world farm animal industry. Insects are known as an alternative protein source for poultry. A wide range of insects are available for use in poultry diets. Insect larvae thrive in manure, and organic waste, and produce antimicrobial peptides to protect themselves from microbial infections, and additionally these peptides might also be functional in poultry feed. The feed containing antimicrobial peptides can improve the growth performance, nutrient digestibility, intestinal health, and immune function in poultry. Insect meal contains a higher amount of essential amino acids compared to conventional feedstuffs. Black soldier fly, mealworm, housefly, cricket/Grasshopper/Locust (Orthoptera), silkworm, and earthworm are the commonly used insect meals in broiler and laying hen diets. This paper summarizes the nutrient profiles of the insect meals and reviews their efficacy when included in poultry diets. Due to the differences in insect meal products, and breeds of poultry, inconsistent results were noticed among studies. The main challenge for proper utilization, and the promising prospect of insect meal in poultry diet are also addressed in the paper. To fully exploit insect meal as an alternative protein resource, and exert their functional effects, modes of action need to be understood. With the emergence of more accurate and reliable studies, insect meals will undoubtedly play more important role in poultry feed industry.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.9
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• pp.305-316
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• 2022

With the flood of digital data owing to the Internet of Things and big data, cloud service providers that process and store vast amount of data from multiple users can apply duplicate data elimination technique for efficient data management. The user experience can be improved as the notion of edge computing paradigm is introduced as an extension of the cloud computing to improve problems such as network congestion to a central cloud server and reduced computational efficiency. However, the addition of a new edge device that is not entirely reliable in the edge computing may cause increase in the computational complexity for additional cryptographic operations to preserve data privacy in duplicate identification and elimination process. In this paper, we propose an efficiency-improved duplicate data elimination protocol while preserving data privacy with an optimized user-edge-cloud communication framework by utilizing a trusted execution environment. Direct sharing of secret information between the user and the central cloud server can minimize the computational complexity in edge devices and enables the use of efficient encryption algorithms at the side of cloud service providers. Users also improve the user experience by offloading data to edge devices, enabling duplicate elimination and independent activity. Through experiments, efficiency of the proposed scheme has been analyzed such as up to 78x improvements in computation during data outsourcing process compared to the previous study which does not exploit trusted execution environment in edge computing architecture.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.40 no.3
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• pp.351-358
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• 1995

Since summer growth depression of forage crops limits hay production in Korea, it is important to exploit natural resources which are suitable as forage. In the preliminary experiment it was found that Panicum dichotomiflorum Michx. might be utilized as soiling and hay crop. Effects of seed stratificaion, planting date and number of harvestings on fresh and dry yields of Panicum dichotomiflorum Michx. were investigated in 1993 and 1994. Stratification of seed promoted emergence, while seed age decreased emergence. Although fresh yield was closely related with number of plants estabilished per unit area, effect of number of plants per unit area on yield was less at the later stage of growth. Higher cutting height decreased fresh and dry yield at th early stage, but final yields were not influenced by cutting height. Panicum dichotomiflorum Michx. could be harvested 3~4 times beginning 40~50 days after planting and fresh and dry yields were 9~10 tons /10a and 1.4~1.8 tons /10a, respectively. Fresh and dry yields were significantly influenced by growth duration or accumulated temperature between cuttings. Leaf blade ratio was higher at earlier planting and / or harvesting. Contens of crude protein, crude fat and crude ash were 16.32, 24.01 and 11.59%, respectively.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.197-216
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• 2022

With the development of Internet and mobile technology and the spread of social media, a large amount of information is being generated and distributed online. Some of them are useful information for the public, but others are misleading information. The misleading information, so-called 'fake news', has been causing great harm to our society in recent years. Since the global spread of COVID-19 in 2020, much of fake news has been distributed online. Unlike other fake news, fake news related to COVID-19 can threaten people's health and even their lives. Therefore, intelligent technology that automatically detects and prevents fake news related to COVID-19 is a meaningful research topic to improve social health. Fake news related to COVID-19 has spread rapidly through social media, however, there have been few studies in Korea that proposed intelligent fake news detection using the information about how the fake news spreads through social media. Under this background, we propose a novel model that uses Graph2vec, one of the graph embedding methods, to effectively detect fake news related to COVID-19. The mainstream approaches of fake news detection have focused on news content, i.e., characteristics of the text, but the proposed model in this study can exploit information transmission relationships in social engagement networks when detecting fake news related to COVID-19. Experiments using a real-world data set have shown that our proposed model outperforms traditional models from the perspectives of prediction accuracy.

• Korea Trade Review
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• v.42 no.1
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• pp.165-188
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• 2017

Foreign direct investment is the means for companies to enter the overseas market and strengthen their competitiveness. The holding of intellectual properties, representing advantages of firms, may affect foreign direct investment. By expanding previous studies, we define intellectual properties as including trademarks and design as well as patents. Using a random-effect panel data model, we examine the effects of both intellectual properties of Korea and host countries on Korea's foreign direct investment in 128 countries from 1981 to 2014. The results are as follow. First, the coefficients of Korea's intellectual properties, patent, trademark, and design are significantly positive. This implies that Korean firms may invest abroad to take their advantages of technologies, brand value, and the capability of product differentiation. Second, except for patents, intellectual properties of host countries have a positive impact on foreign direct investment. In other words, foreign direct investment to acquire the ability of branding or product design from host countries may occur. Third, the coefficients of Korea's intellectual properties are significantly greater than those of host countries' properties. Foreign direct investment to take advantages of the firms' capabilities overseas is greater than one to acquire knowledge of host countries. Finally, Korea's intellectual properties have a greater positive impact on foreign direct investment in high growth countries than in low growth countries. It is interpreted that Korean firms are more motivated to exploit their intellectual properties in developing countries with a high growth than developed countries. Overall, it is confirmed that Korea's foreign direct investment not only to utilize some advantages but also to seek the brand value or product differentiation ability from host countries can occur. Our findings provide the contribution that some innovative activities in firms and R&D investments policies which encourage the possession of intellectual properties can improve foreign direct investment.

• Korea Trade Review
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• v.43 no.5
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• pp.203-232
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• 2018

Gobizkorea is an online B2B matching platform operated by the Small & Medium Business Corporation. Gobizkorea provides an opportunity for resource-poor SMEs to promote their products and exploit new market opportunities at low cost. The successful operation of Gobizkorea will contribute to the increased exports of Korean SMEs. Accordingly, the present study examined determinants of foreign buyer loyalty toward Gobizkorea.com focusing on country image, e-service quality, and satisfaction. One hundred two survey questionnaires were collected from U.S. buyers registered with Gobizkorea.com. Exploratory and confirmatory factor analysis confirmed three dimensions of e-service quality including information & efficiency, reliability & privacy, and prompt communication & delivery. The path analysis results showed that the country image of Korea significantly and positively affected these three dimensions of e-service quality. Information & efficiency and reliability & privacy positively influenced buyer satisfaction. Reliability & privacy and satisfaction had a positive impact on buyer loyalty. This study enhances the understanding of the foreign buyers use of the domestic e-market platform by examining of determinants of U.S. buyer loyalty toward Gobizkorea.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.5
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• pp.303-314
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• 2018

In the past few years, government agencies and corporations have succumbed to stealthy, tailored cyberattacks designed to exploit vulnerabilities, disrupt operations and steal valuable information. Security Information and Event Management (SIEM) is useful tool for cyberattacks. SIEM solutions are available in the market but they are too expensive and difficult to use. Then we implemented basic SIEM functions to research and development for future security solutions. We focus on collection, aggregation and analysis of real-time logs from host. This tool allows parsing and search of log data for forensics. Beyond just log management it uses intrusion detection and prioritize of security events inform and support alerting to user. We select Elastic Stack to process and visualization of these security informations. Elastic Stack is a very useful tool for finding information from large data, identifying correlations and creating rich visualizations for monitoring. We suggested using vulnerability check results on our SIEM. We have attacked to the host and got real time user activity for monitoring, alerting and security auditing based this security information management.

• Asia Marketing Journal
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• v.16 no.1
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• pp.35-69
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• 2014

The impact of competition on pricing has been studied in the context of counterfactual merger analyses where expected optimal prices in a hypothetical monopoly are compared with observed prices in an oligopolistic market. Such analyses would typically assume static decision making by consumers and firms and thus have been applied mostly to data obtained from consumer packed goods such as cereal and soft drinks. However such static modeling approach is not suitable when decision makers are forward looking. When it comes to the markets for durable products with indirect network effects, consumer purchase decisions and firm pricing decisions are inherently dynamic as they take into account future states when making purchase and pricing decisions. Researchers need to take into account the dynamic aspects of decision making both in the consumer side and in the supplier side for such markets. Firms in a two-sided market typically subsidize one side of the market to exploit the indirect network effect. Such pricing behaviors would be more prevalent in competitive markets where firms would try to win over the battle for standard. While such qualitative expectation on the relationship between pricing behaviors and competitive structures could be easily formed, little empirical studies have measured the extent to which the distinct pricing structure in two-sided markets depends on the competitive structure of the market. This paper develops an empirical model to measure the impact of competition on optimal pricing of durable products under indirect network effects. In order to measure the impact of exogenously determined competition among firms on pricing, we compare the equilibrium prices in the observed oligopoly market to those in a hypothetical monopoly market. In computing the equilibrium prices, we account for the forward looking behaviors of consumers and supplier. We first estimate a demand function that accounts for consumers' forward-looking behaviors and indirect network effects. And then, for the supply side, the pricing equation is obtained as an outcome of the Markov Perfect Nash Equilibrium in pricing. In doing so, we utilize numerical dynamic programming techniques. We apply our model to a data set obtained from the U.S. video game console market. The video game console market is considered a prototypical case of two-sided markets in which the platform typically subsidizes one side of market to expand the installed base anticipating larger revenues in the other side of market resulting from the expanded installed base. The data consist of monthly observations of price, hardware unit sales and the number of compatible software titles for Sony PlayStation and Nintendo 64 from September 1996 to August 2002. Sony PlayStation was released to the market a year before Nintendo 64 was launched. We compute the expected equilibrium price path for Nintendo 64 and Playstation for both oligopoly and for monopoly. Our analysis reveals that the price level differs significantly between two competition structures. The merged monopoly is expected to set prices higher by 14.8% for Sony PlayStation and 21.8% for Nintendo 64 on average than the independent firms in an oligopoly would do. And such removal of competition would result in a reduction in consumer value by 43.1%. Higher prices are expected for the hypothetical monopoly because the merged firm does not need to engage in the battle for industry standard. This result is attributed to the distinct property of a two-sided market that competing firms tend to set low prices particularly at the initial period to attract consumers at the introductory stage and to reinforce their own networks and eventually finally to dominate the market.

• Information Systems Review
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• v.21 no.1
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• pp.23-38
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• 2019

The social network service (SNS) is one of the important marketing channels, so many companies actively exploit SNSs by posting SNS messages with appropriate content and style for their customers. In this paper, we focused on the psychological distances embedded in the SNS messages and developed a method to measure the psychological distance in SNS message by mixing a traditional content analysis, natural language processing (NLP), and machine learning. Through a traditional content analysis by human coding, the psychological distance was extracted from the SNS message, and these coding results were used for input data for NLP and machine learning. With NLP, word embedding was executed and Bag of Word was created. The Support Vector Machine, one of machine learning techniques was performed to train and test the psychological distance in SNS message. As a result, sensitivity and precision of SVM prediction were significantly low because of the extreme skewness of dataset. We improved the performance of SVM by balancing the ratio of data by upsampling technique and using data coded with the same value in first content analysis. All performance index was more than 70%, which showed that psychological distance can be measured well.

• The Journal of the Acoustical Society of Korea
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• v.43 no.3
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• pp.361-367
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• 2024

Ultrasound in the air is widely used in industry as a measurement technique to prevent abnormalities in the machinery. Recently, the use of airborne ultrasound imaging techniques, which can find the location of abnormalities using an array transducers, is increasing. A beamforming method that uses the phase difference for each sensor is used to visualize the location of the ultrasonic sound source. We exploit a random sparse ultrasonic array and obtain beamforming power distribution on the source in a certain distance away from the array. Conventional beamforming methods inevitably have limited spatial resolution depending on the number of sensors used and the aperture size. A high-resolution ultrasound imaging technique was implemented by applying functional beamforming as a method to overcome the geometric constraints of the array. The functional beamforming method can be expressed as a generalized beam forming method mathematically, and has the advantage of being able to obtain high-resolution imaging by reducing main-lobe width and side lobes. As a result of observation through computer simulation, it was verified that the resolution of the ultrasonic source in the air was successfully increased by functional beamforming using the ultrasonic sparse array.