• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.207-212
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• 2024

The importance of hydrogen fuel cells continues to be emphasized, and there is a growing demand for education and training in this field. Among various educational environments, metaverse education is opening a new era of change in the global education industry, especially to adapt to remote learning. The most significant change that the metaverse has brought to education is the shift from one-way, instructor-centered, and static teaching approaches to multi-directional and dynamic ones. It is expected that the metaverse can be effectively utilized in hydrogen fuel cell engineer education, not only enhancing the effectiveness of education by enabling learning and training anytime, anywhere but also reducing costs associated with engineering education.In this research, inspired by these ideas, we are designing a fuel cell education platform. We have created a platform that combines theoretical and practical training using the metaverse. Key aspects of this research include the development of educational training content to increase learner engagement, the configuration of user interfaces for improved usability, the creation of environments for interacting with objects in the virtual world, and support for convergence services in the form of digital twins.

• The Transactions of the Korea Information Processing Society
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• v.13 no.3
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• pp.91-101
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• 2024

The utilization of container virtualization technology ensures the consistency and portability of data-intensive and memory volatile workflows. Kubernetes serves as the de facto standard for orchestrating these container applications. Cloud users often overprovision container applications to avoid container restarts caused by resource shortages. However, overprovisioning results in decreased CPU and memory resource utilization. To address this issue, oversubscription of container resources is commonly employed, although excessive oversubscription of memory resources can lead to a cascade of container restarts due to node memory scarcity. Container restarts can reset operations and impose substantial overhead on containers with high memory volatility that include numerous stateful applications. This paper proposes a technique to mitigate container restarts in a memory oversubscription environment based on Kubernetes. The proposed technique involves identifying containers that are likely to request memory allocation on nodes experiencing high memory usage and temporarily pausing these containers. By significantly reducing the CPU usage of containers, an effect similar to a paused state is achieved. The suspension of the identified containers is released once it is determined that the corresponding node's memory usage has been reduced. The average number of container restarts was reduced by an average of 40% and a maximum of 58% when executing a high memory volatile workflow in a Kubernetes environment with the proposed method compared to its absence. Furthermore, the total execution time of a container workflow is decreased by an average of 7% and a maximum of 13% due to the reduced frequency of container restarts.

• Progress in Medical Physics
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• v.14 no.1
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• pp.34-42
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• 2003

In medical imaging, three-dimensional (3D) display using Virtual Reality Modeling Language (VRML) as a portable file format can give intuitive information more efficiently on the World Wide Web (WWW). The web-based 3D visualization of functional images combined with anatomical images has not studied much in systematic ways. The goal of this study was to achieve a simultaneous observation of 3D anatomic and functional models with planar images on the WWW, providing their locational information in 3D space with a measuring implement using VRML. MRI and ictal-interictal SPECT images were obtained from one epileptic patient. Subtraction ictal SPECT co-registered to MRI (SISCOM) was performed to improve identification of a seizure focus. SISCOM image volumes were held by thresholds above one standard deviation (1-SD) and two standard deviations (2-SD). SISCOM foci and boundaries of gray matter, white matter, and cerebrospinal fluid (CSF) in the MRI volume were segmented and rendered to VRML polygonal surfaces by marching cube algorithm. Line profiles of x and y-axis that represent real lengths on an image were acquired and their maximum lengths were the same as 211.67 mm. The real size vs. the rendered VRML surface size was approximately the ratio of 1 to 605.9. A VRML measuring tool was made and merged with previous VRML surfaces. User interface tools were embedded with Java Script routines to display MRI planar images as cross sections of 3D surface models and to set transparencies of 3D surface models. When transparencies of 3D surface models were properly controlled, a fused display of the brain geometry with 3D distributions of focal activated regions provided intuitively spatial correlations among three 3D surface models. The epileptic seizure focus was in the right temporal lobe of the brain. The real position of the seizure focus could be verified by the VRML measuring tool and the anatomy corresponding to the seizure focus could be confirmed by MRI planar images crossing 3D surface models. The VRML application developed in this study may have several advantages. Firstly, 3D fused display and control of anatomic and functional image were achieved on the m. Secondly, the vector analysis of a 3D surface model was defined by the VRML measuring tool based on the real size. Finally, the anatomy corresponding to the seizure focus was intuitively detected by correlations with MRI images. Our web based visualization of 3-D fusion image and its localization will be a help to online research and education in diagnostic radiology, therapeutic radiology, and surgery applications.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.177-192
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• 2012

This is a study of match-making systems that considers the mutual satisfaction of matching partners. Recently, recommendation systems have been applied to people recommendation, such as recommending new friends, employees, or dating partners. One of the prominent domain areas is match-making systems that recommend suitable dating partners to customers. A match-making system, however, is different from a product recommender system. First, a match-making system needs to satisfy the recommended partners as well as the customer, whereas a product recommender system only needs to satisfy the customer. Second, match-making systems need to include as many participants in a matching pool as possible for their recommendation results, even with unpopular customers. In other words, recommendations should not be focused only on a limited number of popular people; unpopular people should also be listed on someone else's matching results. In product recommender systems, it is acceptable to recommend the same popular items to many customers, since these items can easily be additionally supplied. However, in match-making systems, there are only a few popular people, and they may become overburdened with too many recommendations. Also, a successful match could cause a customer to drop out of the matching pool. Thus, match-making systems should provide recommendation services equally to all customers without favoring popular customers. The suggested match-making system, called Mutually Beneficial Matching (MBM), considers the reciprocal satisfaction of both the customer and the matched partner and also considers the number of customers who are excluded in the matching. A brief outline of the MBM method is as follows: First, it collects a customer's profile information, his/her preferable dating partner's profile information and the weights that he/she considers important when selecting dating partners. Then, it calculates the preference score of a customer to certain potential dating partners on the basis of the difference between them. The preference score of a certain partner to a customer is also calculated in this way. After that, the mutual preference score is produced by the two preference values calculated in the previous step using the proposed formula in this study. The proposed formula reflects the symmetry of preferences as well as their quantities. Finally, the MBM method recommends the top N partners having high mutual preference scores to a customer. The prototype of the suggested MBM system is implemented by JAVA and applied to an artificial dataset that is based on real survey results from major match-making companies in Korea. The results of the MBM method are compared with those of the other two conventional methods: Preference-Based Matching (PBM), which only considers a customer's preferences, and Arithmetic Mean-Based Matching (AMM), which considers the preferences of both the customer and the partner (although it does not reflect their symmetry in the matching results). We perform the comparisons in terms of criteria such as average preference of the matching partners, average symmetry, and the number of people who are excluded from the matching results by changing the number of recommendations to 5, 10, 15, 20, and 25. The results show that in many cases, the suggested MBM method produces average preferences and symmetries that are significantly higher than those of the PBM and AMM methods. Moreover, in every case, MBM produces a smaller pool of excluded people than those of the PBM method.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.157-173
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• 2021

With the development of information technology, the amount of available information increases daily. However, having access to so much information makes it difficult for users to easily find the information they seek. Users want a visualized system that reduces information retrieval and learning time, saving them from personally reading and judging all available information. As a result, recommendation systems are an increasingly important technologies that are essential to the business. Collaborative filtering is used in various fields with excellent performance because recommendations are made based on similar user interests and preferences. However, limitations do exist. Sparsity occurs when user-item preference information is insufficient, and is the main limitation of collaborative filtering. The evaluation value of the user item matrix may be distorted by the data depending on the popularity of the product, or there may be new users who have not yet evaluated the value. The lack of historical data to identify consumer preferences is referred to as data sparsity, and various methods have been studied to address these problems. However, most attempts to solve the sparsity problem are not optimal because they can only be applied when additional data such as users' personal information, social networks, or characteristics of items are included. Another problem is that real-world score data are mostly biased to high scores, resulting in severe imbalances. One cause of this imbalance distribution is the purchasing bias, in which only users with high product ratings purchase products, so those with low ratings are less likely to purchase products and thus do not leave negative product reviews. Due to these characteristics, unlike most users' actual preferences, reviews by users who purchase products are more likely to be positive. Therefore, the actual rating data is over-learned in many classes with high incidence due to its biased characteristics, distorting the market. Applying collaborative filtering to these imbalanced data leads to poor recommendation performance due to excessive learning of biased classes. Traditional oversampling techniques to address this problem are likely to cause overfitting because they repeat the same data, which acts as noise in learning, reducing recommendation performance. In addition, pre-processing methods for most existing data imbalance problems are designed and used for binary classes. Binary class imbalance techniques are difficult to apply to multi-class problems because they cannot model multi-class problems, such as objects at cross-class boundaries or objects overlapping multiple classes. To solve this problem, research has been conducted to convert and apply multi-class problems to binary class problems. However, simplification of multi-class problems can cause potential classification errors when combined with the results of classifiers learned from other sub-problems, resulting in loss of important information about relationships beyond the selected items. Therefore, it is necessary to develop more effective methods to address multi-class imbalance problems. We propose a collaborative filtering model using CGAN to generate realistic virtual data to populate the empty user-item matrix. Conditional vector y identify distributions for minority classes and generate data reflecting their characteristics. Collaborative filtering then maximizes the performance of the recommendation system via hyperparameter tuning. This process should improve the accuracy of the model by addressing the sparsity problem of collaborative filtering implementations while mitigating data imbalances arising from real data. Our model has superior recommendation performance over existing oversampling techniques and existing real-world data with data sparsity. SMOTE, Borderline SMOTE, SVM-SMOTE, ADASYN, and GAN were used as comparative models and we demonstrate the highest prediction accuracy on the RMSE and MAE evaluation scales. Through this study, oversampling based on deep learning will be able to further refine the performance of recommendation systems using actual data and be used to build business recommendation systems.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.195-211
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• 2014

Cloud computing services provide IT resources as services on demand. This is considered a key concept, which will lead a shift from an ownership-based paradigm to a new pay-for-use paradigm, which can reduce the fixed cost for IT resources, and improve flexibility and scalability. As IT services, cloud services have evolved from early similar computing concepts such as network computing, utility computing, server-based computing, and grid computing. So research into cloud computing is highly related to and combined with various relevant computing research areas. To seek promising research issues and topics in cloud computing, it is necessary to understand the research trends in cloud computing more comprehensively. In this study, we collect bibliographic information and citation information for cloud computing related research papers published in major international journals from 1994 to 2012, and analyzes macroscopic trends and network changes to citation relationships among papers and the co-occurrence relationships of key words by utilizing social network analysis measures. Through the analysis, we can identify the relationships and connections among research topics in cloud computing related areas, and highlight new potential research topics. In addition, we visualize dynamic changes of research topics relating to cloud computing using a proposed cloud computing "research trend map." A research trend map visualizes positions of research topics in two-dimensional space. Frequencies of key words (X-axis) and the rates of increase in the degree centrality of key words (Y-axis) are used as the two dimensions of the research trend map. Based on the values of the two dimensions, the two dimensional space of a research map is divided into four areas: maturation, growth, promising, and decline. An area with high keyword frequency, but low rates of increase of degree centrality is defined as a mature technology area; the area where both keyword frequency and the increase rate of degree centrality are high is defined as a growth technology area; the area where the keyword frequency is low, but the rate of increase in the degree centrality is high is defined as a promising technology area; and the area where both keyword frequency and the rate of degree centrality are low is defined as a declining technology area. Based on this method, cloud computing research trend maps make it possible to easily grasp the main research trends in cloud computing, and to explain the evolution of research topics. According to the results of an analysis of citation relationships, research papers on security, distributed processing, and optical networking for cloud computing are on the top based on the page-rank measure. From the analysis of key words in research papers, cloud computing and grid computing showed high centrality in 2009, and key words dealing with main elemental technologies such as data outsourcing, error detection methods, and infrastructure construction showed high centrality in 2010~2011. In 2012, security, virtualization, and resource management showed high centrality. Moreover, it was found that the interest in the technical issues of cloud computing increases gradually. From annual cloud computing research trend maps, it was verified that security is located in the promising area, virtualization has moved from the promising area to the growth area, and grid computing and distributed system has moved to the declining area. The study results indicate that distributed systems and grid computing received a lot of attention as similar computing paradigms in the early stage of cloud computing research. The early stage of cloud computing was a period focused on understanding and investigating cloud computing as an emergent technology, linking to relevant established computing concepts. After the early stage, security and virtualization technologies became main issues in cloud computing, which is reflected in the movement of security and virtualization technologies from the promising area to the growth area in the cloud computing research trend maps. Moreover, this study revealed that current research in cloud computing has rapidly transferred from a focus on technical issues to for a focus on application issues, such as SLAs (Service Level Agreements).

• Archives of design research
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• v.17 no.2
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• pp.335-350
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• 2004

Design takes concrete form from the things which are not yet exist to the molded reality. Creation of value which is accompanied by the rational value could be possible only through the searching examination of the basic concept. All designs are under circumstances because the results and the character of the problems are different under the given conditions and circumstances which are the characteristic of the design. The aim of this study is searching for the differential design conce- pt which is the most appropriate and reasonable in the basic design process in which the phase of the analysis, synthesis and evaluation of the problem. First of all the pursuit value of the times and the change of the view point of value of the product design. How the pursuit value of times were searched and analyzed. Analyze the successful product design realization of the typical trend of the modern design which are 3-2. function-focused design, 3-3. emotion-centered design, 3-4. image communicative design through the metaphor, 3-5. environmental affinity design. On the base of the case analysis how to apply the differential design concept which is coming as a trend in the future society which are sustainable developing society was examined closely. The outcome through the analysis of the success cases are as follows, \circled1 the value of the spirit of the times should be emphasized as the design image, \circled2 environmental appropriateness should be taken into consideration as the first primary factor, \circled3 the realization of value of the fulfillment of differential consumer's needs, \circled4 lead to prolong the life cycle of the product, \circled5 promote the sustaining growth of enterprise, \circled6 user-centered product value should be the first consideration. \circled7 It is necessary to overcome the cultural andinguistic barriers and to reflect the metaphor which people remember well. \circled8 The application of human's true character should be decided beforehand. It is the commonness of values of times and customs. \circled9 The differentiated design concept which meets our mental satisfaction, not material one, will be required. In addition to this the creative and differentiated design concepts which are accompanied by the good design factor under the base of product could achieve the emotional consensus from the consumers. That is, the value of all designs should be estimated by the base of the humanism ' The human beings are the barometer of all things".ngs".uot;.

• Progress in Medical Physics
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• v.19 no.4
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• pp.231-240
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• 2008

We developed a user-friendly program to independently verify monitor units (MUs) calculated by radiation treatment planning systems (RTPS), as well as to manage beam database in clinic. The off-axis factor, beam hardening effect, inhomogeneity correction, and the different depth correction were incorporated into the program algorithm to improve the accuracy in calculated MUs. A beam database in the program was supposed to use measured data from routine quality assurance (QA) processes for timely update. To enhance user's convenience, a graphic user interface (GUI) was developed by using Visual Basic for Application. In order to evaluate the accuracy of the program for various treatment conditions, the MU comparisons were made for 213 cases of phantom and for 108 cases of 17 patients treated by 3D conformal radiation therapy. The MUs calculated by the program and calculated by the RTPS showed a fair agreement within ${\pm}3%$ for the phantom and ${\pm}5%$ for the patient, except for the cases of extreme inhomogeneity. By using Visual Basic for Application and Microsoft Excel worksheet interface, the program can automatically generate beam data book for clinical reference and the comparison template for the beam data management. The program developed in this study can be used to verify the accuracy of RTPS for various treatment conditions and thus can be used as a tool of routine RTPS QA, as well as independent MU checks. In addition, its beam database management interface can update beam data periodically and thus can be used to monitor multiple beam databases efficiently.

• Asia pacific journal of information systems
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• v.19 no.1
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• pp.147-165
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• 2009

Virtual community(VC) will increasingly be organized as commercial enterprises, with the objective of earning an attractive financial return by providing members with valuable resources and environment. For example, Cyworld.com in Korea uses several community services to enable customers of Cyworld to take control of their own value as potential purchasers of products and services. Although initial adoption is important for online network service success, it does not necessarily result in the desired managerial performance unless the initial usage is continuously related to the continuous usage and purchase. Particularly, the customer who receives relevant online services and is well equipped with online network services, will trust the online service provider and perceive less risk and experience more activities such as continuous usage and purchase. Thus, how to promote continued online service usage or, alternatively, how to prevent discontinuance is a critical issue for VC service providers to consider. By aggregating a wide range of information and online environments for customers and providing trust to its members, the service providers of virtual communities help to reduce the perceived risk of continuous usage and purchase. Drill down, online service managers realize that achieving strong and sustained customers who continuously use online service and purchase on it is crucial. Therefore, the research into this online service continuance will identify the relationship between the initial usage and the continuous usage and purchase. The research of continuous usage or post adoption has recently emerged as an important issue in the IS literature. Individuals' information systems(IS) continuous usage decisions are congruent with consumers' repeat purchase decisions. The TAM(Technology Acceptance Model) paradigm has been strongly confirmed across a wide range from product purchase on EC to online service usage contexts. The analysis of IS usage based on TAM has proven to be successful across almost online service contexts. However, most of previous studies have focused on only an area (i.e., VC or EC). Just little research has tried to analyze the relationship between VC and EC. The effect of some factors on user intention, captured through several theories such as TAM, has been demonstrated. Yet, few studies have explored the salient relationships of VC users' EC acceptance. To fill this gap between VC and EC research, this paper attempts to develop a research model that extends the TAM perspective in view of the additional contributions of trust in the service provider and trust in members on some factors that affect EC and VC adoption. In this extension, we applied the TAM-to-TAM(T2T) model, and analyzed the transfer effect of trust between these two TAMs. The research model was empirically tested on the context of a social network service. The model was to extend TAM with the trust concept for the virtual community environment from the perspective of tasks. By building an extended model of TAM and examining the relationships between trust and the existing variables of TAM, it is aimed to explain a user's continuous intention to use VC and purchase on EC. The unit of analysis in this paper is an individual user of a virtual community. The population of interest is the individual with the experiences in virtual community. The data for this paper was made available via a Web survey of VC users. In total, 281 cases were gathered for about one week, but there were some missing values in the sample and there were some inappropriate cases. Thus, only 248 cases were finally analyzed. We chose the structural equation analysis to test the hypotheses and it is better suited for explaining complex relationships than the other methods. In this test, AMOS was used to test the Structural Equation Model (SEM). Noticeable results have been found in the T2T model regarding the factors affecting the intention to use of virtual community and loyalty. Our result showed that trust transfer plays a key role in forming the two adoption beliefs. Overall, this study preliminarily confirms the salience of trust transfer in online service.

• Cartoon and Animation Studies
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• s.45
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• pp.397-415
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• 2016

This paper will investigate how animated practice can be a research form as practice-led research in an ethnography approach. This practice-led research will explore the issue of the construction of contemporary identities (based on the strange case of Dr. Jekyll and Mr. Hyde) and in particular, the Korean youth culture and identity, exemplified, for example, creation of 'avatars' in the virtual characters of animated online games such as Massively Multiplayer Online Role-playing Games (MMORPGs). In this proposed discussion, I will argue that the sudden period of change in contemporary Korea bears some resemblance to the Victorian era as explored in gothic fiction (e.g. Jekyll and Hyde). In this sense, my animation investigates the connection between the fictional Jekyll and Hyde and a real murder incident by a young Korean boy, which actually happened on the 16th November 2010, in SouthKorea.I will, therefore, construct this practice-led research to obtain the primary data consisted of online and offline practices in 'social ethnography'. These practices engage with specific Korean youth identity, comparing the 'avatar' with the real lives of participants. However, this paper will only focus on the (ethnographic) research process and strategy, using animated (visual) practices, rather than giving the meaning of the specific case of 'Korean-ness'. Eventually, I will explore the four different animated representations as it presents the distinctive animated realties or documentaries by online and offline practices. My intention is to visually interpret the issue of 'Korean-ness' within its socio-cultural context, adapting the convention and code of Jekyll and Hyde concept into an animated documentary in the 'virtual' world (auto-animated documentary by recording avatar interviews and online game footages) and the 'real' world (self-created animated documentary, based on real people and events).