• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.638-644
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• 2019

In this study, the fluid flow and heat transfer characteristics within sandwich panels are investigated using computational fluid dynamics. Within the sandwich panels having periodic cellular cores, air can freely move inside the core section so that the structure is able to perform multi-functional roles such as simultaneous load bearing and heat dissipation. Thus, there needs to examine the thermal and flow analysis with respect to design variables and various conditions. In this regard, ANSYS Fluent was utilized to explore the flow and heat transfer within the pyramidal truss sandwich structures by varying the truss angle and inlet velocity. Without the entry effect in the first unitcell, the constant rate of pressure and the constant rate of Nusselt number was observed. As a result, it was demonstrated that Nusselt number increases and friction factor decreases as the inlet velocity increases. Moreover, the rate of Nusselt number and friction factor was appreciable in the range of V=1-5m/s due to the transition from laminar to turbulent flow. Regarding the effect of design variable, the variation of truss angle did not significantly influence the characteristics.

• Journal of Korea Entertainment Industry Association
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• v.14 no.1
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• pp.117-124
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• 2020

Chinese youth films fall into the dilemma of continuous development after experiencing rapid development from 2013 to 2017. How to update the creative ideas and methods of the films, arouse the audience's interest in watching and stimulate a new aesthetic experience has become a focal point for the creators who concern about the Chinese film market. "Us and Them" is a successful youth film in 2018. Its creative practice proves that defamiliarization can provide theoretical and methodological basis for the creation of Chinese youth films. Therefore, taking the current situation of Chinese youth film as the research background, treating "Us and Them" as the research object, the defamiliarization of narrative discourse and narrative content used in the film are analyzed. First, the defamiliarization of narrative discourse composed of scenes, characters and plots makes the film "stand out" from the real world. Second, the defamiliarization of narrative content composed of metropolis adoration, self-identity and hometown affection makes the film "stand out" from the existing context. These methods of creation not only meet the needs of the contemporary, but also provide an effective reference for the creation of other youth films. Research will be needed to utilize the elements of defamiliarization through the analysis of the successful case in spite of the time change.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.33-56
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• 2017

As Internet usage is becoming more common worldwide and smartphone become necessity in daily life, technologies and applications related to mobile Internet are developing rapidly. The results of the Internet usage patterns of consumers around the world imply that there are many potential new business opportunities for mobile Internet technologies and applications. The location-based service (LBS) is a service based on the location information of the mobile device. LBS has recently gotten much attention among many mobile applications and various LBSs are rapidly developing in numerous categories. However, even with the development of LBS related technologies and services, there is still a lack of empirical research on the intention to use LBS. The application of previous researches is limited because they focused on the effect of one particular factor and had not shown the direct relationship on the intention to use LBS. Therefore, this study presents a research model of factors that affect the intention to use and actual use of LBS whose market is expected to grow rapidly, and tested it by conducting a questionnaire survey of 330 users. The results of data analysis showed that service customization, service quality, and personal innovativeness have a positive effect on the intention to use LBS and the intention to use LBS has a positive effect on the actual use of LBS. These results implies that LBS providers can enhance the user's intention to use LBS by offering service customization through the provision of various LBSs based on users' needs, improving information service qualities such as accuracy, timeliness, sensitivity, and reliability, and encouraging personal innovativeness. However, privacy concerns in the context of LBS are not significantly affected by service customization and personal innovativeness and privacy concerns do not significantly affect the intention to use LBS. In fact, the information related to users' location collected by LBS is less sensitive when compared with the information that is used to perform financial transactions. Therefore, such outcomes on privacy concern are revealed. In addition, the advantages of using LBS are more important than the sensitivity of privacy protection to the users who use LBS than to the users who use information systems such as electronic commerce that involves financial transactions. Therefore, LBS are recommended to be treated differently from other information systems. This study is significant in the theoretical point of contribution that it proposed factors affecting the intention to use LBS in a multi-faceted perspective, proved the proposed research model empirically, brought new insights on LBS, and broadens understanding of the intention to use and actual use of LBS. Also, the empirical results of the customization of LBS affecting the user's intention to use the LBS suggest that the provision of customized LBS services based on the usage data analysis through utilizing technologies such as artificial intelligence can enhance the user's intention to use. In a practical point of view, the results of this study are expected to help LBS providers to develop a competitive strategy for responding to LBS users effectively and lead to the LBS market grows. We expect that there will be differences in using LBSs depending on some factors such as types of LBS, whether it is free of charge or not, privacy policies related to LBS, the levels of reliability related application and technology, the frequency of use, etc. Therefore, if we can make comparative studies with those factors, it will contribute to the development of the research areas of LBS. We hope this study can inspire many researchers and initiate many great researches in LBS fields.

• Journal of the Korean Geographical Society
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• v.29 no.4
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• pp.402-419
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• 1994

Telecommunication and intormation technology have been conceived as crucial as well as revolutionary elements for recent and future social and economic development, and their development have led to a spatial reorganization and locational change of economic activities. Information technology has resulted in important changes in the organization structure and location of firm. This study draws attention to the understanding of the relationship between the diffusion of information technology and changes in firm activities with the special reference to the service industry of the United States. Information technology has had a significant impact on the growth and changes of the service industry of the United States through changes in the organizational and employment structure, market structure, and locational changes. The impact of information technology on location changes of the service industry shows two opposite patterns, concentration and decentralization. Among these patterns, the location change in the service industry of the United States reveals predominantly the decentralization tendency such as suburbanization and transfer to lower ranking cities rather than concentration. In case of Korea, however, it is anticipated that the rapid development of information technology may lead to the concentration of the service industry in Seoul and Capital region.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.29 no.1
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• pp.28-41
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• 2024

The carbon balance serves as a valuable indicator of a plant's physiological status under diverse environmental conditions. We investigated the photosynthetic and respiratory responses of the Asian surfgrass Phyllospadix iwatensis along the northeast coast of the Korean peninsula in response to changing water temperature (ranging from 5℃ to 30℃) to estimate the seasonal whole-plant carbon balance through a series of incubation experiments. The maximum gross photosynthetic rate (P_max) showed a significant difference among the temperature treatments, while there was no significant difference in photosynthetic efficiency (α). The maximum gross photosynthetic rate of P. iwatensis reached its peaks at 20℃ treatment (101.65 μmol O₂ g^-1 DW h^-1) but decreased rapidly at 30℃. The saturation irradiance (I_k), compensation irradiance (I_c), and respiration rate (R) of P. iwatensis exhibited significant differences among the temperature treatments. The saturation irradiance increased up to 20-25℃ (121.59-124.50 μmol photons m^-2 s^-1) and sharply decreased at 30℃. The compensation irradiance and respiration rate increased steadily with rising water temperature. The ratio of P_max to R (P_max:R ratio) was the highest at 5℃ but dramatically decreased at 30℃. The whole-plant carbon balance, calculated based on photosynthetic parameters, respiration rates, and biomass, exhibited distinct seasonal variation, increasing during winter and spring and decreasing during summer and fall, which is consistent with the highest in situ growth in spring and severely limited growth at the highest water temperature conditions. Phyllospadix iwatensis displayed a negative carbon balance during late summer, fall, and winter, but demonstrated a positive carbon balance during spring and early summer. Our findings suggest that the rising seawater temperatures associated with climate change may lead to significant alterations in the seagrass ecosystem functioning along the rocky shores of the Korean east coast.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Cartoon and Animation Studies
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• s.38
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• pp.53-70
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• 2015

In industrialized societies throughout the 19th and 20th centuries, Over Produced and Mass consumption images were constantly shown to people via Mass-Media as means to provoke one's desire. Frank Mouris, the American independent animator, captured and showed the infinite nesting of industrialized image with his autobiographical story through his work (1973) and made it as an intense visual flow. This innovative art animation has broke the traditional form of narrative animation and won the Annecy Animation Festival Grand Prix and the Academy Awards in 1974. This was also selected for preservation in the United States National Film Registry by the Library of Congress as being culturally, historically, or aesthetically significant in 1996. This study explores and shows that how these a-half million images to express Franks Mouris's autobiographical story in could be analyzed by the concept of Walter Benjamin's 'dialectical images'. Typically, the term 'dialectic' need to be formed by contradiction or opposite concept in the basic principles, but a dialectical image of Benjamin could be formed without any opposite concept while maintaining the uniqueness of each new relationship of the past. Benjamin's dialectical images are no longer stay in the historical past, It always meets with the present when someone realizes the past in the present moment. I suggest three different aspect according to Benjamin's point of view to analyse this animated film such as 'Historical-dialectical imaging of private/collective memory', 'Reconfiguring of present through analysing the relationship between the image flows and its own time/space', and 'Old future over the existing fragment and the presence of fragment. has the great value not only to present the experimental and innovative aesthetics of animated film, but also to show an analysis of contemporary culture and social aspect in mid-20th century. This study is to explore the diversity of animation representation, aesthetics, and also to suggest a new aspect of animation studies.

• Journal of Energy Engineering
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• v.23 no.4
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• pp.61-72
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• 2014

This paper analyzed transition pathways toward a low carbon society in Korea to meet global $2^{\circ}C$ climate target. Lower economic growth, industrial structure change, enhance of energy demand management, decarbonization of power sector, and replacement of low carbon fuel could reduce greenhouse gas (GHG) emission from fuel combustion in 2050 by 67% against in 2011, or by 74% against in BAU (Business-As-Usual). Lower economic growth contributes to 13% of cumulative emission reduction relative to BAU, industrial structure change 9%, enhance of energy demand management 72%, decarbonization of power sector 5% and replacement of low carbon fuel 1% respectively. Final energy consumption in 2050 needs to be reduced to 50% relative to 2011, or to 41% relative to BAU. Nuclear, coal and renewable energy represent 31%, 40%, 2% respectively among electricity generation in 2011, but 38%, 2%, 32% in 2050. CCS represents 23% of total generation in 2050. Emission intensity of electricity in 2050 was decreased to 19% relative to 2011, or to 24% relative to BAU. Primary energy in 2050 was decreased to 64% compared to 2011, or to 44% compared to BAU. Final energy consumption, primary energy supply and GHG emission from fuel combustion from 1990 to 2011 increased by 176%, 197%, 146%. Radical change from historical trend is required to transit toward a low carbon society by 2050. Appropriate economic growth, structural change to non-energy intensive industries, energy technology research, development and deployment (RD&D) in terms of enhancement of energy efficiency and low carbon energy supply technologies, and fuel change to electricity and renewable energy are key instruments.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.97-121
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• 2013

With the growing importance of knowledge for sustainable competitive advantages and innovation in a volatile environment, many researches on knowledge sharing have been conducted. However, previous researches have mostly relied on the questionnaire survey which has inherent perceptive errors of respondents. The current research has drawn the relationship among primary participant behaviors towards the participation level in knowledge sharing, basically from online user behaviors on Wikipedia, a representative community for online knowledge collaboration. Without users' participation in knowledge sharing, knowledge collaboration for creating knowledge cannot be successful. By the way, the editing patterns of Wikipedia users are diverse, resulting in different revisiting periods for the same number of edits, and thus varying results of shared knowledge. Therefore, we illuminated the participation level of knowledge sharing from two different angles of number of edits and revisiting period. The behavioral dimensions affecting the level of participation in knowledge sharing includes the article talk for public discussion and user talk for private messaging, and community registration, which are observable on Wiki platform. Public discussion is being progressed on article talk pages arranged for exchanging ideas about each article topic. An article talk page is often divided into several sections which mainly address specific type of issues raised during the article development procedure. From the diverse opinions about the relatively trivial things such as what text, link, or images should be added or removed and how they should be restructured to the profound professional insights are shared, negotiated, and improved over the course of discussion. Wikipedia also provides personal user talk pages as a private messaging tool. On these pages, diverse personal messages such as casual greetings, stories about activities on Wikipedia, and ordinary affairs of life are exchanged. If anyone wants to communicate with another person, he or she visits the person's user talk page and leaves a message. Wikipedia articles are assessed according to seven quality grades, of which the featured article level is the highest. The dataset includes participants' behavioral data related with 2,978 articles, which have reached the featured article level, with editing histories of articles, their article talk histories, and user talk histories extracted from user talk pages for each article. The time period for analysis is from the initiation of articles until their promotion to the featured article level. The number of edits represents the total number of participation in the editing of an article, and the revisiting period is the time difference between the first and last edits. At first, the participation levels of each user category classified according to behavioral dimensions have been analyzed and compared. And then, robust regressions have been conducted on the relationships among independent variables reflecting the degree of behavioral characteristics and the dependent variable representing the participation level. Especially, through adopting a motivational theory adequate for online environment in setting up research hypotheses, this work suggests a theoretical framework for the participation level of online knowledge sharing. Consequently, this work reached the following practical behavioral results besides some theoretical implications. First, both public discussion and private messaging positively affect the participation level in knowledge sharing. Second, public discussion exerts greater influence than private messaging on the participation level. Third, a synergy effect of public discussion and private messaging on the number of edits was found, whereas a pretty weak negative interaction effect of them on the revisiting period was observed. Fourth, community registration has a significant impact on the revisiting period, whereas being insignificant on the number of edits. Fifth, when it comes to the relation generated from private messaging, the frequency or depth of relation is shown to be more critical than the scope of relation for the participation level.

• The Mathematical Education
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• v.62 no.3
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• pp.435-455
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• 2023

This study primarily focused on the development of an Explainable Artificial Intelligence (XAI) model to discern and analyze papers with significant impact in the field of mathematics education. To achieve this, meta-information from 29 domestic and international mathematics education journals was utilized to construct a comprehensive academic research network in mathematics education. This academic network was built by integrating five sub-networks: 'paper and its citation network', 'paper and author network', 'paper and journal network', 'co-authorship network', and 'author and affiliation network'. The Random Forest machine learning model was employed to evaluate the impact of individual papers within the mathematics education research network. The SHAP, an XAI model, was used to analyze the reasons behind the AI's assessment of impactful papers. Key features identified for determining impactful papers in the field of mathematics education through the XAI included 'paper network PageRank', 'changes in citations per paper', 'total citations', 'changes in the author's h-index', and 'citations per paper of the journal'. It became evident that papers, authors, and journals play significant roles when evaluating individual papers. When analyzing and comparing domestic and international mathematics education research, variations in these discernment patterns were observed. Notably, the significance of 'co-authorship network PageRank' was emphasized in domestic mathematics education research. The XAI model proposed in this study serves as a tool for determining the impact of papers using AI, providing researchers with strategic direction when writing papers. For instance, expanding the paper network, presenting at academic conferences, and activating the author network through co-authorship were identified as major elements enhancing the impact of a paper. Based on these findings, researchers can have a clear understanding of how their work is perceived and evaluated in academia and identify the key factors influencing these evaluations. This study offers a novel approach to evaluating the impact of mathematics education papers using an explainable AI model, traditionally a process that consumed significant time and resources. This approach not only presents a new paradigm that can be applied to evaluations in various academic fields beyond mathematics education but also is expected to substantially enhance the efficiency and effectiveness of research activities.