• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.4
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• pp.271-282
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• 2022

In this paper, we propose a digital human content creation system. The digital human content creation system works with 3D AI modeling through whole-body scanning, and is produced with 3D modeling post-processing, texturing, rigging. By combining this with virtual reality(VR) content information, natural motion of the virtual model can be achieved in virtual reality, and digital human content can be efficiently created in one system. Therefore, there is an effect of enabling the creation of virtual reality-based digital human content that minimizes resources. In addition, it is intended to provide an automated pre-processing process that does not require a pre-processing process for 3D modeling and texturing by humans, and to provide a technology for efficiently managing various digital human contents. In particular, since the pre-processing process such as 3D modeling and texturing to construct a virtual model are automatically performed by artificial intelligence, so it has the advantage that rapid and efficient virtual model configuration can be achieved. In addition, it has the advantage of being able to easily organize and manage digital human contents through signature motion.

• Korean Journal of Construction Engineering and Management
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• v.23 no.3
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• pp.45-55
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• 2022

BIM models allow building spaces to be instantiated and recognized as unique objects independently of model elements. These instantiated spaces provide the required semantics that can be leveraged for building code checking, energy analysis, and evacuation route analysis. However, theses spaces or rooms need to be designated manually, which in practice, lead to errors and omissions. Thus, most BIM models today does not guarantee the semantic integrity of space designations, limiting their potential applicability. Recent studies have explored ways to automate space allocation in BIM models using artificial intelligence algorithms, but they are limited in their scope and relatively low classification accuracy. This study explored the use of Graph Convolutional Networks, an algorithm exclusively tailored for graph data structures. The goal was to utilize not only geometry information but also the semantic relational data between spaces and elements in the BIM model. Results of the study confirmed that the accuracy was improved by about 8% compared to algorithms that only used geometric distinctions of the individual spaces.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.1059-1066
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• 2021

In Korea, the importance of marine activities is great, and automatic weather observation facilities are operating on land to investigate abnormal weather phenomena caused by industrialization; however, the number of facilities at sea is insufficient. Marine survey ships are operated to establish marine safety information, but there are many places where marine survey ships are difficult to access and operating costs are high. Therefore, a small, unmanned vessel capable of marine surveys must be developed. The sail has a significant impact on the sailing performance, so much research has been conducted. In this study, the camber effect, which is a design variable of the twin curvy sail known to have higher aerodynamic performance than existing airfoil shapes, was investigated. Flow analysis results for five cases with different camber sizes show that the lift coefficient is highest when the camber size is 9%. Curvy twin sails had the highest lift coefficient at an angle of attack of 23° because of the interaction of the port and starboard sails. The port sail had the highest lift coef icient at an angle of attack of 20°, and the starboard sail had the lowest lift coef icient at an angle of attack of 15°. In addition, the curvy twin sail had a higher lift coefficient than NACA 0018 at all angles of attack.

• Korean Chemical Engineering Research
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• v.60 no.3
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• pp.363-370
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• 2022

In this paper, an estimation algorithm for state of charge (SOC) was applied using an equivalent circuit model (ECM) and an Extended Kalman Filter (EKF) to improve the estimation accuracy of the battery system states. In particular, an observer was designed to estimate SOC along with the aged capacity. In the case of the fresh battery, when SOC was estimated by Kalman Filter (KF), the mean absolute percentage error (MAPE) was 0.27% which was smaller than MAPE of 1.43% when the SOC was calculated by the model without the observer. In the driving mode of the vehicle, the general KF or EKF algorithm cannot be used to estimate both SOC and capacity. Considering that the battery aging does not occur in a short period of time, a strategy of periodically estimating the battery capacity during charging was proposed. In the charging mode, since the current is fixed at some intervals, a strategy for estimating the capacity along with the SOC in this situation was suggested. When the current was fixed, MAPE of SOC estimation was 0.54%, and the MAPE of capacity estimation was 2.24%. Since the current is fixed when charging, it is feasible to estimate the battery capacity and SOC simultaneously using the general EKF. This method can be used to periodically perform battery capacity correction when charging the battery. When driving, the SOC can be estimated using EKF with the corrected capacity.

• Journal of Advanced Navigation Technology
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• v.27 no.3
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• pp.306-313
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• 2023

Realistic and graphics-based virtual reality content is based on 360-degree videos, and viewport extraction through the viewer's intention or automatic recommendation function is essential. This paper designs a viewport extraction system based on multiple object tracking in 360-degree videos and proposes a parallel computing structure necessary for multiple viewport extraction. The viewport extraction process in 360-degree videos is parallelized by composing pixel-wise threads, through 3D spherical surface coordinate transformation from ERP coordinates and 2D coordinate transformation of 3D spherical surface coordinates within the viewport. The proposed structure evaluated the computation time for up to 30 viewport extraction processes in aerial 360-degree video sequences and confirmed up to 5240 times acceleration compared to the CPU-based computation time proportional to the number of viewports. When using high-speed I/O or memory buffers that can reduce ERP frame I/O time, viewport extraction time can be further accelerated by 7.82 times. The proposed parallelized viewport extraction structure can be applied to simultaneous multi-access services for 360-degree videos or virtual reality contents and video summarization services for individual users.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.11
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• pp.109-119
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• 2018

This study investigates the effect of urban and architectural forms on the microclimate in urban areas. It applies urban and architectural elements such as urban form and tissue and building form and characteristics as the main influences on the microclimate within urban area. Among the 23 Automated Weather Stations (AWS) installed within Seoul city by the Korea Meteorological Administration, 6 sites were selected for the analysis, based on their different urban and architectural characteristics, and actual measurements were conducted in August 2017 using individual AWS equipment. Also, the measurements of microclimate and urban and architectural elements within a 500m radius of the AWS measurement points were collected and analyzed. The result of the analysis shows that the microclimate elements, such as wind speed, solar radiation, and temperature, were affected by the direction of the streets, the width, depth, and height of the buildings, the topographic elevation and direction and the traffic volume. This study is expected to contribute to mitigating urban heat island effect and setting the foundation for sustainable cities through development of urban management methods and techniques including the relationship between built environment elements and microclimate.

• Membrane Journal
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• v.33 no.3
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• pp.94-109
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• 2023

1,3-Dioxolane is an exciting material that has attracted widespread interest in the chemical, paint, and pharmaceutical industries as a solvent, electrolyte, and reagent because 1,3-dioxolane is not toxic, carcinogenic, explosive, auto-flammable, and multifunctional, and due to their excellent miscibility in most organic and aqueous solvent conditions. Recently, this material has received increasing attention as a CO₂-selective polymer precursor to separating CO₂ from flue gas and natural gas mixtures. Poly(1,3-dioxolane) (PDXL) possesses higher ether oxygen content than polyethylene oxide (PEO), which demonstrates superior membrane CO₂/N₂ separation properties owing to their polar ether oxygen groups exhibiting strong affinity toward CO₂. Thus, PDXL-based membranes displayed an outstanding CO₂ solubility selectivity over non-polar (N₂, H₂, and CH₄) gases. However, the polar groups of PDXL, like PEO, promote chain packing efficiency and cause polymer crystallization, thereby reducing its gas permeability, which should be improved. In this short review, we discuss the recent advancement and limitations of PDXL membranes in gas separation applications. To conclude, we provide future perspectives for inhibiting the limits of 1,3-dioxolane-based polymers in the CO₂ separation process.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.137-144
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• 2023

Cyberattack technology is evolving to an unpredictable degree, and it is a situation that can happen 'at any time' rather than 'someday'. Infrastructure that is becoming hyper-connected and global due to cloud computing and the Internet of Things is an environment where cyberattacks can be more damaging than ever, and cyberattacks are still ongoing. Even if damage occurs due to external influences such as cyberattacks or natural disasters, intelligent self-recovery must evolve from a cyber resilience perspective to minimize downtime of cyber assets (OS, WEB, WAS, DB). In this paper, we propose an intelligent self-recovery technology to ensure sustainable cyber resilience when cyber assets fail to function properly due to a cyberattack. The original and updated history of cyber assets is managed in real-time using timeslot design and snapshot backup technology. It is necessary to secure technology that can automatically detect damage situations in conjunction with a commercialized file integrity monitoring program and minimize downtime of cyber assets by analyzing the correlation of backup data to damaged files on an intelligent basis to self-recover to an optimal state. In the future, we plan to research a pilot system that applies the unique functions of self-recovery technology and an operating model that can learn and analyze self-recovery strategies appropriate for cyber assets in damaged states.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.126-133
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• 2023

In this study, electromyography was obtained in the six muscle areas that move the joints of the two legs, and by analyzing it, an exercise robot system capable of gait rehabilitation was proposed in consideration of the individual's muscle state. Through this, the system was constructed to prevent the effect of exercise from decreasing because the patient's will was not reflected when walking exercise was simply provided automatically. As a result of the evaluation of the developed system, it was confirmed that the pedestrian rehabilitation robot system manufactured through this study had performance suitable for the design requirements, and it was also confirmed that the usability evaluation was comprehensively satisfactory. The results of this study are thought to be of great help to patients who are having difficulty in gait rehabilitation, and are believed to be helpful in the development of electromyography signal-based gait robot systems.

• Journal of Navigation and Port Research
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• v.47 no.6
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• pp.367-375
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• 2023

This study developed a new distance metric for vessel trajectories, applicable to marine traffic control services in the Korean coastal waters. The proposed metric is designed through the weighted summation of the traditional Hausdorff distance, which measures the similarity between spatiotemporal data and incorporates the differences in the average Speed Over Ground (SOG) and the variance in Course Over Ground (COG) between two trajectories. To validate the effectiveness of this new metric, a comparative analysis was conducted using the actual Automatic Identification System (AIS) trajectory data, in conjunction with an agglomerative clustering algorithm. Data visualizations were used to confirm that the results of trajectory clustering, with the new metric, reflect geographical distances and the distribution of vessel behavioral characteristics more accurately, than conventional metrics such as the Hausdorff distance and Dynamic Time Warping distance. Quantitatively, based on the Davies-Bouldin index, the clustering results were found to be superior or comparable and demonstrated exceptional efficiency in computational distance calculation.