• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1323-1332
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• 2018

The purpose of this study is to analyze the level of Media Information Literacy of international students in K-university, who attend the courses in which the classes are delivered only in English. A survey was carried out to find out the level of media information literacy. In order to verify the validity and reliability of the measurement result gathered from the responses, an item analysis was carried out with SPSS21.0, a statistics analysis software, and the diversity of utilizing media information literacy was also measured according to the factors of each analysand group. The analysis result gathered through ${\chi}^2-test$, a frequency analysis tool, shows that international students use domestic media information literacy mainly for daily life activities such as the internet shopping and the bank transaction.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.131-143
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• 2022

Focusing on FinTech keywords, this study is analyzing newspaper articles and Twitter data by using text mining methodology in order to understand trends in the industry of domestic digital financial service. In the growth of FinTech lifecycle, the frequency analysis has been performed by four important points: Mobile Payment Service, Internet Primary Bank, Data 3 Act, MyData Businesses. Utilizing frequency analysis, which combines the keywords 'China', 'USA', and 'Future' with the 'FinTech', has been predicting the FinTech industry regarding of the current and future position. Next, sentiment analysis was conducted on Twitter to quantify consumers' expectations and concerns about FinTech services. Therefore, this study is able to share meaningful perspective in that it presented strategic directions that the government and companies can use to understanding future FinTech market by combining frequency analysis and sentiment analysis.

• Journal of Korea Technology Innovation Society
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• v.20 no.2
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• pp.368-386
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• 2017

The purpose of this study is to present the technology value model based on profit approach and IITP practical guide for Ethernet network technology, which is the core technology of autonomous vehicles and connected cars in the hyper-connected industry. In-vehicle network, Ethernet technology, Ethernet port count, port pricing, and application data for technology assessment are sources of global market research organizations. The data on the company's COGS (Cost of Goods Sold), operating capital requirement, capital expenditure, and income statement data are used by the Bank of Korea's Business Analysis Report. According to the results of the study, the product market size was estimated to be US $470.3 billion and the technology market size was $52.1 billion over the seven years of economic life cycle of technology. The market value of the technology was estimated to be $260 million reflecting the possibility of entry into the market. In the case of the corporate management analysis report, the average value of the IITP and the top 25% were $0.7 million and $40.2 million, respectively. -27.8 million, and -73.6 million dollars respectively. This implies that government support for policy support is needed when conducting corporate R&D with high cost-to-sales ratio. The results of this study can be used as a reference for the evaluation of technology demand based ICT R&D technology in the industrial internet market in the fourth industrial revolution era.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2C
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• pp.209-216
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• 2009

The repeater for wireless broadband internet (Wibro) system using OFDM demands the short processing delay to eliminate inter-symbol interference resulted from the time delay greater than the guard time. Towards this, the total system delay of repeater is expected to be minimized as possible as it can without distorting signal quality. In general, the FIR-type of filter is commonly deployed as a channelization filter, but due to its large amount of coefficients for producing prerequisite filter response the excessive large time delay occurs. To withstand this problem, the paper proposes the method for designing IIR filter whose response almost identical to that of the original filter. Moreover, in order to linearize the phase response of the designed IIR filter, this paper also introduce the way of designing the all-pass filter to be cascaded works for linearizing phase response of the channelization as well as the de-channelization filter. To achieve the further improvement in linearization of the phase response and reduction of the overall complexity, this paper tries to transform the integrated IIR filter group into the structure in polyphase style. The computer simulation verifies that the integrated IIR filter group designed in this paper reveals the relatively short processing delay without harming the acceptible signal quality.

• Information Systems Review
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• v.17 no.2
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• pp.219-238
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• 2015

As Internet and IT have been developed, people have been exposed to large amounts of information. So, many online information providers recommend relevant information to users to relieve an information overload. However, information recommendation which is based on the taste and preference of a user can lead to a problem of unbalanced information consumption. Prior research about online information has not investigated the side-effect of a recommendation function. This research suggests IT solutions for alleviating unbalanced information consumption behavior. Based on adaptation level theory and expectancy theory, we proposed self-reference point diagnosticity interface and social-reference point diagnosticity interface to help people to consume information following their own information consuming goal. We hypothesized positive impacts of these two interfaces on the self-awareness about information consuming pattern. And we predicted that self-awareness has a positive impact on the motivation and actual behavior to conform the ideal information consuming pattern which the user sets. Laboratory experiment was executed as a research method. As a result, the self-reference diagnosticity interface leaded to higher self-awareness and mitigated the unbalanced information consumption. But, the social-reference diagnosticity interface and the motivation to improve the information consuming behavior had no significant results. Academic and practical implications are discussed.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.1
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• pp.43-48
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• 2006

The educational system has been changed owing to Web, which is most actively used on internet and has the characteristics of providing suitable environments for implementing constructivism study theory. WBI(Web Based Instruction), web-mediated teaching form for students at a long distance, has the advantages of possible interact between instructors and learners, offering a great variety of learning materials, and overcome the spatiotemporal restriction. This paper focuces on the construction of learning surroundings where the learner-centered, active learning can be done by design and Implementation of web based instruct system providing a sham examination with an item pool system. The web based Self-directed Learning system for word processor qualifying exams on this paper, can be mentioned as a real item pool that the question is not setting each time by the instructors but can be reused by reference on item pool bank, designed the number of question. It helps the learner Self-directed Learning study with evaluation during the web based instruct process and immediate feedback. It also provides the chance to research some similar using keyword. To sum up, this system can amplify the efficiency of study.

• The Journal of Society for e-Business Studies
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• v.15 no.4
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• pp.285-301
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• 2010

Peer-to-peer (P2P) lending is an open marketplace for loans not from bank but from individuals online. Financial transactions are facilitated directly between individuals ("peers") without any intermediation of a traditional financial institution. A market study by renowned research company forecasts that P2P lending will grow very fast and a couple of P2P lending sites in Korea also are getting attentions by providing the alternative financial services. In P2P lending market, Lender will enjoy higher income generated from the loans in the form of interest than interest that can be earned by financial products provided by official financial institutions. Furthermore, lenders are able to decide who they would lend the money for themselves. Meanwhile, borrowers with low credit scores are able to finance their liquidity requirement with low cost and convenient access to the Internet. The objective of this paper is to introduce P2P lending and its issues of information asymmetry. We provide the insights from the case study of one of P2P lending sites in Korea and review the issues in P2P lending market as research topics. Specifically, information asymmetry issues in both traditional financial institutions and P2P lending are discussed.

• Economic Analysis
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• v.25 no.2
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• pp.54-95
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• 2019

The purpose of this study is to analyze quantitatively and qualitatively the effects of the increase in online shopping and its effects on real-world commercial outlets. The empirical analysis of this study is based on the results of "Census on Establishments" and "Online Shopping Survey" that cover 15 years, from 2002 to 2016. According to the results of this study, the increase in the number of online transactions affects the decrease in the number of stores in the real-world retail sector. However, non-specialized large stores and chain convenience stores showed an increase in the number of stores. In addition, the number of F&B stores increased the most in line with the increase in online transactions. This is because the increase in online transactions and in internet users led to the use of more delivery applications and the introduction of popular places on blogs or through social media. Street-level rents for medium and large-sized locations increased. In other words, it is seen that the demand for differentiated real-world stores that provide a good user experience increases, even though online transactions also increase. These results suggest that real-world stores should provide good user experiences in their physical locations with a certain size and assortment of goods.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.71-84
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• 2013

Log data, which record the multitude of information created when operating computer systems, are utilized in many processes, from carrying out computer system inspection and process optimization to providing customized user optimization. In this paper, we propose a MongoDB-based unstructured log processing system in a cloud environment for processing the massive amount of log data of banks. Most of the log data generated during banking operations come from handling a client's business. Therefore, in order to gather, store, categorize, and analyze the log data generated while processing the client's business, a separate log data processing system needs to be established. However, the realization of flexible storage expansion functions for processing a massive amount of unstructured log data and executing a considerable number of functions to categorize and analyze the stored unstructured log data is difficult in existing computer environments. Thus, in this study, we use cloud computing technology to realize a cloud-based log data processing system for processing unstructured log data that are difficult to process using the existing computing infrastructure's analysis tools and management system. The proposed system uses the IaaS (Infrastructure as a Service) cloud environment to provide a flexible expansion of computing resources and includes the ability to flexibly expand resources such as storage space and memory under conditions such as extended storage or rapid increase in log data. Moreover, to overcome the processing limits of the existing analysis tool when a real-time analysis of the aggregated unstructured log data is required, the proposed system includes a Hadoop-based analysis module for quick and reliable parallel-distributed processing of the massive amount of log data. Furthermore, because the HDFS (Hadoop Distributed File System) stores data by generating copies of the block units of the aggregated log data, the proposed system offers automatic restore functions for the system to continually operate after it recovers from a malfunction. Finally, by establishing a distributed database using the NoSQL-based Mongo DB, the proposed system provides methods of effectively processing unstructured log data. Relational databases such as the MySQL databases have complex schemas that are inappropriate for processing unstructured log data. Further, strict schemas like those of relational databases cannot expand nodes in the case wherein the stored data are distributed to various nodes when the amount of data rapidly increases. NoSQL does not provide the complex computations that relational databases may provide but can easily expand the database through node dispersion when the amount of data increases rapidly; it is a non-relational database with an appropriate structure for processing unstructured data. The data models of the NoSQL are usually classified as Key-Value, column-oriented, and document-oriented types. Of these, the representative document-oriented data model, MongoDB, which has a free schema structure, is used in the proposed system. MongoDB is introduced to the proposed system because it makes it easy to process unstructured log data through a flexible schema structure, facilitates flexible node expansion when the amount of data is rapidly increasing, and provides an Auto-Sharding function that automatically expands storage. The proposed system is composed of a log collector module, a log graph generator module, a MongoDB module, a Hadoop-based analysis module, and a MySQL module. When the log data generated over the entire client business process of each bank are sent to the cloud server, the log collector module collects and classifies data according to the type of log data and distributes it to the MongoDB module and the MySQL module. The log graph generator module generates the results of the log analysis of the MongoDB module, Hadoop-based analysis module, and the MySQL module per analysis time and type of the aggregated log data, and provides them to the user through a web interface. Log data that require a real-time log data analysis are stored in the MySQL module and provided real-time by the log graph generator module. The aggregated log data per unit time are stored in the MongoDB module and plotted in a graph according to the user's various analysis conditions. The aggregated log data in the MongoDB module are parallel-distributed and processed by the Hadoop-based analysis module. A comparative evaluation is carried out against a log data processing system that uses only MySQL for inserting log data and estimating query performance; this evaluation proves the proposed system's superiority. Moreover, an optimal chunk size is confirmed through the log data insert performance evaluation of MongoDB for various chunk sizes.

• Journal of Food Hygiene and Safety
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• v.28 no.1
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• pp.50-55
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• 2013

Since 1 June 2012, it is prohibited to sell oilfish as a food material but there are still many illegal cases of selling oilfish as if it is tuna or grilled Patagonian toothfish. So it is absolutely crucial to construct the system to distinguish the real food material from oilfish. There are two sorts of oil fish called Ruvettus pretiosus and Lepidocybirium flavobrunneum involved in Percifomes order and Gempylidae class. 16S DNA gene region in mitochondria was selected to design the specific primers. For design species-specific primer, the theoretical experiment were performed for the sequences of R. pretiosus, L. flavobrunneum, Thunnus thynnus, Thunnus albacores, Makaira mitsukurii and Xiphias gladius, registered at the Gene bank from the National Centre for Biotechnology Information, using BioEdit 7.0.9.0. program. Through the analysis of the result from experiments, it was possible to design the 4 kinds of primers to distinguish R. pretiosus and L. flavobrunneum. As a comparison group, 3 kinds of tuna and 4 kinds of billfishes were selected and experimental verification was performed. As a result, for R. pretiosus and L. flavobrunneum, R.P-16S-006-F/R.P-16S-008-R and L.F-16S-004-F/L.F-16S-006-R primers were selected eventually and PCR condition was established. In addition, 178bp and 238bp of PCR products were confirmed from the established condition and non-specific band was not amplified among similar species. Therefore, the species-specific primers developed in this study would be very useful and used in various ways such as internet shopping mall and illegal distributions with fast and scientific results.