• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.12
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• pp.62-69
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• 2020

The demand for industrial robots is proliferating with production automation. Industrial robots are used in various fields, such as logistics, welding, and assembly. Generally, six degrees of freedom are required to move freely in space. However, the palletizing robot used for material management and logistics systems typically has four degrees of freedom. In designing such robots, their main parts, such as motors and reducers, need to be adequately selected while satisfying payload requirements and speed. Hence, this study proposes a practical method for selecting the major parts based on dynamic analysis using ADAMS. First, the acceleration torques for the robot motion were found from the analysis, and then the friction torques were evaluated. This study introduces a constant-speed torque constant instead of friction coefficient. The RMS torque and maximum power of each motor were found considering the above torques. After that, this study recommends the major specifications of all motors and reducers. The proposed method was applied to a palletizing robot to verify the suitability of the pre-selected main parts. The verification result shows that the proposed method can be successfully applied to the early design stage of industrial robots.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.163-173
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• 2021

In the era of digital transformation, the transportation underprivileged remains as an underprivileged class without the benefits of technological advances. Electric assist devices for the People with disability are inadequate to provide services suitable for the current traffic environment, although the mobility of the People with disability is improved. In this paper, we develop IoT smart mobility by deriving essential elements through user satisfaction surveys to efficiently move physical distances based on the experience of users using existing electric assistive devices. Based on the data collected through user satisfaction survey, quantitative analysis using TF-IFD and qualitative analysis based on QFD are performed to determine the importance of user requirements. For the evaluation of IoT smart mobility design results reflecting essential functions, usability verification is conducted by forming an expert evaluation team in various fields. In the future, we plan to conduct a service design study that can improve mobility convenience and provide mobility service solutions by designing to provide efficient public services by utilizing IoT smart mobility to the People with disability.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.1
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• pp.541-565
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• 2021

The study is aimed at designing an effective edutech platform based on online remote classes, and clarifying the effect of empathy competence of youths through the operation linked with the empathic reading program focusing on reading. To this end, after constructing the environment for education and drawing a class model based on components of edutech for remote classes on the basis of previous studies and elaborating the empathic reading education program, this study has been conducted for one semester for 107 students in 4 classes in their 1st grade at S middle school, Gyeonggi-do in order to apply them to fields. As a result of the study, the empathy reading program that a remote class model was applied has shown a meaningful difference among groups in cognitive empathy and emotional empathy, and it was found that there was a statistically meaningful difference between the two groups in total scores. Besides, the effect and meaning of adolescents' empathy competence have been verified through the remote empathy reading education and the empirical analysis, and the direction to develop the empathy reading program has been suggested for a solution to settle differences in students' learning due to COVID-19.

• Fashion & Textile Research Journal
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• v.23 no.1
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• pp.106-117
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• 2021

This study proposes a design process for an upper limb assistive wearable soft robot that will enable the development of a clothing product for an upper limb assistive soft robot. A soft robot made of a flexible and soft material that compensates for the shortcomings of existing upper limb muscle strength assistive devices is being developed. Consequently, a clothing process of the upper limb assistive soft robot is required to increase the possibility of wearing such a device. The design process of the upper limb auxiliary soft robot is presented as follows. User analysis and required performance deduction-Soft robot design-upper limb assistive wearable soft robot prototype design and production-evaluation. After designing the clothing according to the design process, the design was revised and supplemented repeatedly according to the results of the clothing evaluation. In the post-production evaluation stage, the first and second prototypes were attached to actual subjects, and the second prototype showed better results. The developed soft robot evaluated if the functionality as a clothing function and the functionality as the utility of the device were harmonized. The convergence study utilized a process of reducing friction conducted through an understanding and cooperation between research fields. The results of this study can be used as basic data to establish the direction of prototype development in fusion research.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.8
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• pp.1060-1066
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• 2021

Recently, researches for quantum computers have been carried out in various fields. Quantum computers performs calculations by utilizing various phenomena and characteristics of quantum mechanics such as quantum entanglement and quantum superposition, thus it is a very complex calculation process compared to classical computers used in the past. In order to simulate a quantum computer, many factors and parameters of a quantum computer need to be analyzed, for example, error verification, optimization, and reliability verification. Therefore, it is necessary to visualize circuits that can intuitively simulate the configuration of the quantum computer components. In this paper, we present a novel visualization method for designing complex quantum computer system, and attempt to create a 3D visualization toolkit to deploy large circuits, provide help a new way to design large-scale quantum computing systems that can be built into future computing systems.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.371-380
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• 2021

This study aims to design a tunnel part model for underpass and subway lines that correspond to tunnel sector among the underground facilities(structure types) covered in the integrated map of underground spaces. For this purpose, we compared and reviewed the characteristics of international standards related to tunnel data models. As a result, it was found that CityGML 3.0 - Tunnel module was the most suitable for designing a 3D tunnel data model. Afterwards we reviewed the legal and institutional regulations to derive the standard elements of the 3D tunnel data model. Then we conducted a demand survey targeting experts in related fields to derive standard elements for addition and extension of underpasses and subway lines. Based on the above process, we designed and presented a 3D tunnel data model using UML. This study is expected to be meaningful as a basic study to improve the utilization of tunnel model in the integrated map of underground spaces.

• The Journal of the Korea Contents Association
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• v.22 no.9
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• pp.339-348
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• 2022

Blended Learning is one of the most popular methods in education for encouraging active learning and improving student learning effectiveness, and it is regarded as one of the most effective methods for universities to attract students. Based on the cultural dimension theory, this paper examined blended learning research trends in both South Korea and China, which are culturally similar but also differ. The research methods include keyword analysis and visualization. Academic papers on blended learning indexed by WoS, KISS, and CNKI from 1990 to June 2022 were collected and analyzed. According to the findings, since the outbreak of COVID-19, the common research topic of blended learning has been subdivided by forming clusters in various research fields. Korea and China exhibit similarities to global research trends while exhibiting differences based on cultural background. The cultural dimension theory-based analysis reveals a common pattern that is especially long-term oriented. The findings can suggest significant implications for designing what role national culture plays in forming patterns of education and research and for developing blended learning with effective impacts in a multicultural educational environment.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.105-111
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• 2022

Multiple-choice survey types have been mainly performed to analyze students' needs for online classes. However, in order to analyze the exact needs of students, unstructured data analysis by answer for essay question is required. Big data is applied in various fields because it is possible to analyze unstructured data. This study aims to investigate and analyze what students want subjects or topics for software lecture in general education that process on non-face-to-face online teaching methods. As for the experimental method, keyword analysis and association analysis of big data were performed with unstructured data by giving a subjective questionnaire to students. By the result, we are able to know the keyword what the students want for software lecture, so it will be an important data for planning and designing software lecture of liberal arts in the future as students can grasp the topics they want to learn.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.6
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• pp.1127-1137
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• 2022

Cryptographic analysis and decryption technology utilizing the parallel operation of GPU has been studied in the direction of shortening the computation time of the password analysis system. These studies focus on optimizing the code to improve the speed of cryptographic analysis operations on a single GPU or simply increasing the number of GPUs to enhance parallel operations. However, using a large number of GPUs without optimization for data transmission causes longer data transmission latency than using a single GPU and increases the overall computation time of the cryptographic analysis system. In this paper, we investigate GPUDirect RDMA and related technologies for high-performance data processing in deep learning or HPC research fields in GPU clustering environments. In addition, we present a method of designing a high-performance cryptanalysis system using the relevant technologies. Furthermore, based on the suggested system topology, we present a method of implementing a cryptanalysis system using password cracking and GPU reduction. Finally, the performance evaluation results are presented according to demonstration of high-performance technology is applied to the implemented cryptanalysis system, and the expected effects of the proposed system design are shown.

• Journal of Digital Policy
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• v.1 no.1
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• pp.15-20
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• 2022

Recently, the healthcare field is trying to develop a model that can improve service quality by reflecting the requirements of various industrial fields. In this paper, we propose an Internet of Behavior (IoB) environment model that can process users' healthcare information in real time in a 5G environment to improve healthcare services. The purpose of the proposed model is to analyze the user's healthcare information through deep learning and then check the health status in real time. In this case, the biometric information of the user is transmitted through communication equipment attached to the portable medical equipment, and user authentication is performed through information previously input to the attached IoB device. The difference from the existing IoT healthcare service is that it analyzes the user's habits and behavior patterns and converts them into digital data, and it can induce user-specific behaviors to improve the user's healthcare service based on the collected data.