• The Journal of the Korea Contents Association
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• v.22 no.6
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• pp.35-44
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• 2022

In this study, we tried to confirm the characteristics of books published on the topic of international cooperation, what kind of international cooperation-related research is being conducted through this book, and what are the main contents of international cooperation. In order to achieve this research purpose, we conducted data construction, statistical analysis, and text mining based on textom in international research cooperation at home and abroad. As a result of the study, it can be seen that there has been a particularly high interest in international research and international cooperation since the 2010s. Through this, it was found that he is interested in development, economy, technology, development, region, and relations and wants to promote development. In addition, topics such as environment, trade, education, and society appeared, and interest in international research cooperation centered on environment, trade, and education was high, was found to have a high influence on society as a whole. Through this study, we find the research significance in that it can serve as a basic research to confirm the characteristics of some national and public research institutes participating in international research cooperation, and that it confirms the trend of participating in international research cooperation in a relatively specific type of institution. can see.

• Journal of Korean Home Economics Education Association
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• v.34 no.1
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• pp.151-165
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• 2022

The aim of this study is to examine the effectiveness of non-face-to-face classes conducted due to the COVID-19 crisis. In order to achieve this goal, a non-face-to-face class with flipped learning was applied in one subject of clothing major held at 'S' University in Cheongju, Korea. In addition, this study tried to analyze the differences between pre- and post-non-face-to-face classes in problem analysis ability, resource/information/technology literacy, convergent thinking ability as core competencies, and overall learning satisfaction. As a result, after participating in the non-face-to-face class in which the flipped learning was applied, the students recognized that their abilities improved in the three problem-solving competency sub-areas, and their overall learning satisfaction also increased. The effectiveness of non-face-to-face classes in the field of clothing and fashion has been mainly measured in fashion design and clothing construction courses. However, based on the results of this study, it can be suggested that non-face-to-face classes in a theory-oriented lecture-type class can be effective methods for improving students' core competencies such as problem-solving skills if teaching-learning methods such as flipped learning are applied. Therefore, the results of this study will be useful data for designing differentiated non-face-to-face class strategies in a theory-oriented lecture-type class to improve the core competencies of college students.

• Korean Journal of Ecology and Environment
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• v.55 no.4
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• pp.352-359
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• 2022

Recently, with the development of genetic technology, interest in environmental DNA (eDNA) to study biodiversity according to molecular biological approaches is increasing. Environmental DNA has many advantages over traditional research methods for biological communities distributed in the environment but highly depends on the established base sequence database. This study conducted a comprehensive analysis of the habitat status and classification at the genus level, which is mainly used in eDNA (12S rRNA, 16S rRNA, 18S rRNA, COI, and CYTB), focusing on Korean registration taxon groups (phytoplankton, zooplankton, macroinvertebrates, and fish). As a result, phytoplankton and zooplankton showed the highest taxa proportion in 18S rRNA, and macroinvertebrates observed the highest ratio in the nucleotide sequence database in COI. In fish, all genes except 18S rRNA showed a high taxon ratio. Based on the Korean registration taxon group, the gene construction of the top 20 genera according to bio density observed that most of the phytoplankton were registered in 18S rRNA, and the most significant number of COI nucleotide sequences were established in macroinvertebrates. In addition, it was confirmed that there is a nucleotide sequence for the top 20 genera in 12S rRNA, 16S rRNA, and CYTB in fish. These results provided comprehensive information on the genes suitable for eDNA research for each taxon group.

• Journal of Convergence for Information Technology
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• v.12 no.3
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• pp.85-107
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• 2022

This study is to analyze the induced effect, network connectivity, and network visualization of the water transportation industry on the overall economy in relation to all industries. For this, various inducement coefficients of the water transportation industry are analyzed using industry linkage analysis and unit structure matrix, and network visualization analysis is performed using network connectivity and NetDraw using Ucinet 6 that utilizes unit structure matrix and inverse matrix function. As a result of the study, analysis results of input coefficient, production inducement coefficient, value-added inducement coefficient, and inter-industry chain effect were presented as various inducement coefficients in the water transportation industry. content was presented. Through this study, the current position and status of the water transportation industry and its relationship with all industries were confirmed, and the strategic relationship with which industries it should be presented was presented. In the future, it is necessary to further analyze the current status and trends of various induced effects, connectivity (centrality), and network visualization analysis using industry-related analysis published since the 2000s.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.236-244
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• 2023

The purpose of this study was to examine the economic feasibility of providing services according to the nationwide expansion of early warning services. The net present value method, one of the cost-benefit analysis methods, was applied to the analysis. As a benefit item that constituted the net present value, the damage reduction amount using crop insurance data and the willingness to pay for the use of early warning services were used. The cost items included system construction and maintenance costs, and text transmission costs. As a result of the analysis, it was found that the nationwide expansion of early warning services had economic feasibility, and its economic effect varied depending on the level of text message use (10 % to 40 %, 10 %p interval) of participating farmers. In the future, the economic effect of early warning services is expected to increase further due to the increase in the number of farmers participating in early warning services and the increase in crop damage caused by climate change. It is necessary to further enhance the economic effect of early warning services by actively utilizing information delivery means through apps or the web as well as text messages.

• Journal of the Korean Chemical Society
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• v.67 no.6
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• pp.441-461
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• 2023

This study explore characteristics of teaching orientation and pck of science teachers in online-offline mixed learning environment. Data consisted of open-ended survey, semi-structured interview, class observation, field notes from 12 science teachers. We categorized teaching orientation considering both science education goals and science teaching·learning orientation. There were 8 different teaching orientations such as 'understanding science concepts-lecture centered' 'constructing science concepts-inquiry based' 'applying science concepts and inquiry-inquiry based' 'applying science concepts and inquiry-lectured centered' 'analyzing and judging science information-inquiry based' 'developing scientific attitude-inquiry based' 'developing scientific attitude-lecture centered' and 'developing perception of interrelationships among science, technology, and society-inquiry based'. Teachers with inquiry based teaching·learning orientation seemed to have knowledge of science curriculum specific to online learning environment for student inquiry. While teachers with 'understanding science concepts-lecture centered' teaching orientation appeared to have questioning strategy of checking student understanding and strategy of repeating a lecture, teachers with 'constructing science concepts-inquiry based' teaching orientation appeared to have knowledge of instructional strategies to perform online group activities targeting student construction of knowledge and to replace face-to-face group activities with virtual experiments and individual experiments. While teachers with 'understanding science concepts-lecture centered' teaching orientation did not show knowledge of student science learning, teachers with 'constructing science concepts-inquiry based' teaching orientation appeared to have knowledge of student difficulties in inquiry based learning.

• Journal of Navigation and Port Research
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• v.47 no.6
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• pp.437-447
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• 2023

By actively adopting technologies from the Fourth Industrial Revolution, the port industry is trending toward new types of ports, such as automated and smart ports. However, behind the development of these ports, there is an increasing risk of cyber security incidents and threats within ports and container terminals, including information leakage through cargo handling equipment and ransomware attacks leading to disruptions in terminal operations. Despite the necessity of research to enhance cyber security within ports, there is a lack of such studies in the domestic context. This study focuses on Busan Port, a representative port in South Korea that actively incorporates technology from the Fourth Industrial Revolution, in order to discover variables for improving cyber security in container terminals. The research results categorized factors for enhancing cyber security in Busan Port's container terminals into network construction and policy support, standardization of education and personnel training, and legal and regulatory factors. Subsequently, multiple regression analysis was conducted based on these factors, leading to the identification of detailed factors for securing and enhancing safety, reliability, performance, and satisfaction in Busan Port's container terminals. The significance of this study lies in providing direction for enhancing cyber security in Busan Port's container terminals and addressing the increasing incidents of cyber security attacks within ports and container terminals.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.161-177
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• 2015

With the rapid evolution of technology, the size, number, and the type of databases has increased concomitantly, so data mining approaches face many challenging applications from databases. One such application is discovery of fraud patterns from agricultural product wholesale transaction instances. The agricultural product wholesale market in Korea is huge, and vast numbers of transactions have been made every day. The demand for agricultural products continues to grow, and the use of electronic auction systems raises the efficiency of operations of wholesale market. Certainly, the number of unusual transactions is also assumed to be increased in proportion to the trading amount, where an unusual transaction is often the first sign of fraud. However, it is very difficult to identify and detect these transactions and the corresponding fraud occurred in agricultural product wholesale market because the types of fraud are more intelligent than ever before. The fraud can be detected by verifying the overall transaction records manually, but it requires significant amount of human resources, and ultimately is not a practical approach. Frauds also can be revealed by victim's report or complaint. But there are usually no victims in the agricultural product wholesale frauds because they are committed by collusion of an auction company and an intermediary wholesaler. Nevertheless, it is required to monitor transaction records continuously and to make an effort to prevent any fraud, because the fraud not only disturbs the fair trade order of the market but also reduces the credibility of the market rapidly. Applying data mining to such an environment is very useful since it can discover unknown fraud patterns or features from a large volume of transaction data properly. The objective of this research is to empirically investigate the factors necessary to detect fraud transactions in an agricultural product wholesale market by developing a data mining based fraud detection model. One of major frauds is the phantom transaction, which is a colluding transaction by the seller(auction company or forwarder) and buyer(intermediary wholesaler) to commit the fraud transaction. They pretend to fulfill the transaction by recording false data in the online transaction processing system without actually selling products, and the seller receives money from the buyer. This leads to the overstatement of sales performance and illegal money transfers, which reduces the credibility of market. This paper reviews the environment of wholesale market such as types of transactions, roles of participants of the market, and various types and characteristics of frauds, and introduces the whole process of developing the phantom transaction detection model. The process consists of the following 4 modules: (1) Data cleaning and standardization (2) Statistical data analysis such as distribution and correlation analysis, (3) Construction of classification model using decision-tree induction approach, (4) Verification of the model in terms of hit ratio. We collected real data from 6 associations of agricultural producers in metropolitan markets. Final model with a decision-tree induction approach revealed that monthly average trading price of item offered by forwarders is a key variable in detecting the phantom transaction. The verification procedure also confirmed the suitability of the results. However, even though the performance of the results of this research is satisfactory, sensitive issues are still remained for improving classification accuracy and conciseness of rules. One such issue is the robustness of data mining model. Data mining is very much data-oriented, so data mining models tend to be very sensitive to changes of data or situations. Thus, it is evident that this non-robustness of data mining model requires continuous remodeling as data or situation changes. We hope that this paper suggest valuable guideline to organizations and companies that consider introducing or constructing a fraud detection model in the future.

• The Transactions of the Korea Information Processing Society
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• v.7 no.11S
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• pp.3651-3667
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• 2000

Recently, in the distributed multimedia environments based on internet, as radical growing technologies, the most of researchers focus on both streaming technology and distributed object thchnology, Specially, the studies which are tried to integrate the streaming services on the distributed object technology have been progressing. These technologies are applied to various stream service mamgements and protocols. However, the stream service management mexlels which are being proposed by the existing researches are insufficient for suporting the QoS of stream services. Besides, the existing models have the problems that cannot support the extensibility and the reusability, when the QoS-reiatedfunctions are being developed as a sub-module which is suited on the specific-purpose application services. For solving these problems, in this paper. we suggested a QoS Integrated platform which can extend and reuse using the distributed object technologies, and guarantee the QoS of the stream services. A structure of platform we suggested consists of three components such as User Control Module(UCM), QoS Management Module(QoSM) and Stream Object. Stream Object has Send/Receive operations for transmitting the RTP packets over TCP/IP. User Control ModuleI(UCM) controls Stream Objects via the COREA service objects. QoS Management Modulel(QoSM) has the functions which maintain the QoS of stream service between the UCMs in client and server. As QoS control methexlologies, procedures of resource monitoring, negotiation, and resource adaptation are executed via the interactions among these comiXments mentioned above. For constmcting this QoS integrated platform, we first implemented the modules mentioned above independently, and then, used IDL for defining interfaces among these mexlules so that can support platform independence, interoperability and portability base on COREA. This platform is constructed using OrbixWeb 3.1c following CORBA specification on Solaris 2.5/2.7, Java language, Java, Java Media Framework API 2.0, Mini-SQL1.0.16 and multimedia equipments. As results for verifying this platform functionally, we showed executing results of each module we mentioned above, and a numerical data obtained from QoS control procedures on client and server's GUI, while stream service is executing on our platform.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.167-194
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• 2019

This research starts from the four basic concepts of incentive incompatibility, limited information, myopia and decision variable which are confronted when making decisions in keyword bidding. In order to make these concept concrete, four framework approaches are designed as follows; Strategic approach for the incentive incompatibility, Statistical approach for the limited information, Alternative optimization for myopia, and New model approach for decision variable. The purpose of this research is to propose the statistical optimization model in constructing the portfolio of Sponsored Search Advertising (SSA) in the Sponsor's perspective through empirical tests which can be used in portfolio decision making. Previous research up to date formulates the CTR estimation model using CPC, Rank, Impression, CVR, etc., individually or collectively as the independent variables. However, many of the variables are not controllable in keyword bidding. Only CPC and Rank can be used as decision variables in the bidding system. Classical SSA model is designed on the basic assumption that the CPC is the decision variable and CTR is the response variable. However, this classical model has so many huddles in the estimation of CTR. The main problem is the uncertainty between CPC and Rank. In keyword bid, CPC is continuously fluctuating even at the same Rank. This uncertainty usually raises questions about the credibility of CTR, along with the practical management problems. Sponsors make decisions in keyword bids under the limited information, and the strategic portfolio approach based on statistical models is necessary. In order to solve the problem in Classical SSA model, the New SSA model frame is designed on the basic assumption that Rank is the decision variable. Rank is proposed as the best decision variable in predicting the CTR in many papers. Further, most of the search engine platforms provide the options and algorithms to make it possible to bid with Rank. Sponsors can participate in the keyword bidding with Rank. Therefore, this paper tries to test the validity of this new SSA model and the applicability to construct the optimal portfolio in keyword bidding. Research process is as follows; In order to perform the optimization analysis in constructing the keyword portfolio under the New SSA model, this study proposes the criteria for categorizing the keywords, selects the representing keywords for each category, shows the non-linearity relationship, screens the scenarios for CTR and CPC estimation, selects the best fit model through Goodness-of-Fit (GOF) test, formulates the optimization models, confirms the Spillover effects, and suggests the modified optimization model reflecting Spillover and some strategic recommendations. Tests of Optimization models using these CTR/CPC estimation models are empirically performed with the objective functions of (1) maximizing CTR (CTR optimization model) and of (2) maximizing expected profit reflecting CVR (namely, CVR optimization model). Both of the CTR and CVR optimization test result show that the suggested SSA model confirms the significant improvements and this model is valid in constructing the keyword portfolio using the CTR/CPC estimation models suggested in this study. However, one critical problem is found in the CVR optimization model. Important keywords are excluded from the keyword portfolio due to the myopia of the immediate low profit at present. In order to solve this problem, Markov Chain analysis is carried out and the concept of Core Transit Keyword (CTK) and Expected Opportunity Profit (EOP) are introduced. The Revised CVR Optimization model is proposed and is tested and shows validity in constructing the portfolio. Strategic guidelines and insights are as follows; Brand keywords are usually dominant in almost every aspects of CTR, CVR, the expected profit, etc. Now, it is found that the Generic keywords are the CTK and have the spillover potentials which might increase consumers awareness and lead them to Brand keyword. That's why the Generic keyword should be focused in the keyword bidding. The contribution of the thesis is to propose the novel SSA model based on Rank as decision variable, to propose to manage the keyword portfolio by categories according to the characteristics of keywords, to propose the statistical modelling and managing based on the Rank in constructing the keyword portfolio, and to perform empirical tests and propose a new strategic guidelines to focus on the CTK and to propose the modified CVR optimization objective function reflecting the spillover effect in stead of the previous expected profit models.