• KNOM Review
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• v.23 no.1
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• pp.43-50
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• 2020

As General Purpose Graphics Processing Unit (GPGPU) recently plays an essential role in high-performance computing, several cloud service providers offer GPU service. Most cluster orchestration platforms in a cloud environment using containers allocate the integer number of GPU to jobs and do not allow a node shared with other jobs. In this case, resource utilization of a GPU node might be low if a job does not intensively require either many cores or large size of memory in GPU. GPU virtualization brings opportunities to realize kernel concurrency and share resources. However, performance may vary depending on characteristics of applications running concurrently and interference among them due to resource contention on a node. This paper proposes GPU container co-execution framework with multiple server creation and execution based on Kubernetes, container orchestration platform for measuring interference which may be occurred by sharing GPU resources. Performance changes according to scheduling policies were investigated by executing several jobs on GPU. The result shows that optimal scheduling is not possible only considering GPU memory and computing resource usage. Interference caused by co-execution among applications is measured using the framework.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.9
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• pp.381-390
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• 2022

Influenced by a culture that prefers non-face-to-face activity during the COVID-19 pandemic, chatbot usage is accelerating. Chatbots have been used for various purposes, not only for customer service in businesses and social conversations for fun but also for mental health. Chatbots are a platform where users can easily talk about their depressed moods because anonymity is guaranteed. However, most relevant research has been on social media data, especially Twitter data, and few studies have analyzed the commercially used chatbots data. In this study, we identified the characteristics of depressive discourse in user-chatbot interaction data by analyzing the chats, including the word 'depress,' using the topic modeling algorithm and the text-mining technique. Moreover, we compared its characteristics with those of the depressive moods in the Twitter data. Finally, we draw several design guidelines and suggest avenues for future research based on the study findings.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.351-356
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• 2022

The era of the 4th industrial revolution is being built on the digital revolution. In order to understand and properly utilize these technological advances, digital literacy education is emphasized. This study investigated the components of digital literacy and proposed a curriculum & teaching and learning method improvement plan, and instructor digital literacy cultivation method. In order to improve the curriculum, it is necessary to improve the curriculum by expanding the ability to solve digital problems. As a plan to improve teaching and learning methods, it is necessary to present a linkage and convergence educational model based on communication, collaboration, and sharing between instructors and learners through the establishment of an interactive platform. In order to improve the digital literacy of instructors, it is very important to improve the educational environment that can easily design a learner-centered educational model. This study is meaningful in that it presented basic data for creating an educational environment based on communication and collaboration through digital literacy in an environment connected with digital technology.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.107-114
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• 2022

In this paper, proposes a delivery robot that can be autonomous driving learning. The proposed robot is designed to be used in park-type apartments without ground parking facilities. Compared to the existing apartments with complex ground and underground routes, park-type apartments have a standardized movement path, allowing the robot to run stably, making it suitable for students' initial education environment. The delivery robot is configured to enable delivery of parcels through machine learning technology for route learning and autonomous driving using cameras and LiDAR sensors. In addition, the control MCU was designed by separating it into three parts to enable learning by level, and it was confirmed that it can be used as a delivery robot for learning through operation tests such as autonomous driving and obstacle recognition. In the future, we plan to develop it into an educational delivery robot for various delivery services by linking with the precision indoor location information recognition technology and the public technology platform of the apartment.

• Asia-Pacific Journal of Business
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• v.12 no.2
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• pp.205-222
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• 2021

Purpose - Due to the Covic-19 pandemic, the perceived value of video conferencing platforms has been increased drastically. However, there is little guidance on how service providers can improve video conferencing platforms. The purpose of this study is to investigate the factors that influence the users' perceived value of video conferencing services based on the heuristic-systematic model and the value-based adoption model. Design/Methodology/Approach - In this paper, we theoretically explore the relationship of the antecedents of perceived value(credibility, expertise, attractiveness, economic feasibility, security, and interactivity) and its outcomes (perceived usefulness, perceived risk and perceived value). The outcomes of this research is a conceptualization of antecedents of perceived value supported by research hypothesis based on the existing literature. A total of 100 valid questionnaires were collected to empirically test the research model. Findings - The analysis results showed that credibility, economic feasibility, and interactivity positively influenced perceived usefulness. On the other hand, credibility, professionalism and interactivity negatively influenced perceived risk. Perceived usefulness positively affects perceived value and perceived risk has a negative effect on perceived value. The brand image as a moderating variable was found to decrease the effect of perceived risk on perceived value. Research Implications - The contribution of this study is significant for video conferencing providers as follows. First, a service provider can actively utilize influencers or referees with high credibility and expertise to maximize the perceived usefulness of users. Second, economic feasibility should be ensured in respect of users through various alliance discount strategies. Third, a video conferencing service company needs to build a positive brand image in order to increase users' perceived value.

• Journal of Ocean Engineering and Technology
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• v.36 no.5
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• pp.313-325
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• 2022

Recently around the world, coastal erosion is paying attention as a social issue. Various constructions using low-crested and submerged structures are being performed to deal with the problems. In addition, a prediction study was researched using machine learning techniques to determine the wave attenuation characteristics of low crested structure to develop prediction matrix for wave attenuation coefficient prediction matrix consisting of weights and biases for ease access of engineers. In this study, a deep neural network model was constructed to predict the wave height transmission rate of low crested structures using Tensor flow, an open source platform. The neural network model shows a reliable prediction performance and is expected to be applied to a wide range of practical application in the field of coastal engineering. As a result of predicting the wave height transmission coefficient of the low crested structure depends on various input variable combinations, the combination of 5 condition showed relatively high accuracy with a small number of input variables defined as 0.961. In terms of the time cost of the model, it is considered that the method using the combination 5 conditions can be a good alternative. As a result of predicting the wave transmission rate of the trained deep neural network model, MSE was 1.3×10^-3, I was 0.995, SI was 0.078, and I was 0.979, which have very good prediction accuracy. It is judged that the proposed model can be used as a design tool by engineers and scientists to predict the wave transmission coefficient behind the low crested structure.

• International Journal of Computer Science & Network Security
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• v.23 no.2
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• pp.111-125
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• 2023

Due to the car's central role in modern life, the industry has become more fiercely competitive, with each manufacturer doing everything it can to attract buyers with features like plush interiors, comprehensive warranties, and helpful customer service departments. Customers may not have the luxury of buying a new car, so they will have to buy a used car. Nevertheless, in most cases, the customer (car driver) may be deceived about the vehicle information and history and thus will be confused in making his/her decision to purchase. In addition, after all attempts to obtain vehicle information (plate number, model, year of manufacture, number of maintenance times, accidents, etc.), the customer's many attempts may fail. In general, the government records and verifies the information of all cars, even those that pass through their borders. However, there might still be some trouble in obtaining this information. From this standpoint, we will design a website that makes it easier for car drivers, car companies and governments to carry out all the above-mentioned processes. It will also allow users, whether a driver or a car company, to inquire about all vehicle information through detailed and integrated reports on its condition since its entry into the Kingdom of Saudi Arabia until the present time, in addition to information supported by numbers and statistics to ensure the integrity and reliability of the information. This platform will save the trouble of searching for car information for drivers and car companies. It will also help governments keep track of the information of all cars entering and leaving the Kingdom of Saudi Arabia, which will contribute to facilitating the process of viewing the history of any car that has previously entered the Kingdom's borders.

• Human Ecology Research
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• v.60 no.4
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• pp.549-564
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• 2022

This study aimed to develop an e-mentoring youth financial education program and verify its effectiveness for promoting financial empowerment and establishing financial capabilities among independent consumers. A four-session, eight-hour "Youth Financial Empowerment Mentoring Program" was developed. This program dealt with financial literacy and financial psychology factors in an integrated fashion. We used the nonequivalent control group pretest-posttest design to evaluate the program's effectiveness. Specifically, by using Zoom, a virtual conference platform, four mentors of college students were trained for four sessions over two weeks. Meanwhile, four groups were formed with four mentors and 18 high school mentees to implement a four-week e-mentoring program. As a result of the analysis of covariance, significant differences were found between the two groups in all financial psychology factors and financial literacy variables. In addition, the score of the experimental group was higher than that of the control group. As a result of qualitative evaluation through FGI for mentees and mentors, mentees experienced positive changes in financial behavior, beliefs, attitudes, and personal relationships, as well as increased financial knowledge. Meanwhile, mentors experienced positive changes in their introspection into financial behavior and consumption. Considering these results, we can conclude that this program effectively induces participants to learn and reflect on their initiative, which is in line with the original goal of "improving financial empowerment".

• Journal of the International Relations & Interdisciplinary Education
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• v.3 no.1
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• pp.29-50
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• 2023

This study selected college students in Anhui Province as the research subjects and used a questionnaire survey method to understand the current implementation status of the integration of innovation and entrepreneurship education and professional education. The survey results indicate that college students have insufficient awareness of innovation and entrepreneurship; Poor integration of curriculum construction. This study analyzes the reasons for the problems from four aspects: the government, enterprises, and universities, as well as the subjective will of students. Based on qualitative and quantitative research, the following countermeasures and suggestions are proposed: firstly, strengthen top-level design; Secondly, promote the integration of curriculum construction; Thirdly, expand the teaching staff; Fourthly, a practical platform for school enterprise co creation; Fifth, cultivate students' innovative awareness and guide innovative practice.

• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.4
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• pp.711-728
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• 2023

This study aims to validate the user experience associated with the personalized recommendation systems of fashion vertical platforms. The investigation focused on women aged 18 to 30 with prior experience using personalized fashion recommendation systems. The collected data were analyzed using SPSS 26.0 and AMOS 26.0, and the outcomes can be summarized as follows. Firstly, the diversity and usefulness of information quality exerted a positive effect on use satisfaction. Secondly, the affirmative impact of the reliability of system quality on user satisfaction was established, although stability was not confirmed. Thirdly, the study identified a favorable connection between ease-of-use of service quality and user satisfaction, while the influence of tangibles was unsubstantiated. Fourthly, the degree of self-reference was found to have a positive effect on user satisfaction. Fifthly, a constructive relationship emerged between user satisfaction and both continuous-use intention and recommendation intention. Lastly, there was a significant difference in the magnitude of the effect of ease-of-use on satisfaction according to self-regulatory focus. The findings of this study hold the potential to enhance the explanatory and predictive power of the field of consumer behavior within the novel shopping landscape of fashion vertical platforms.