• Journal of the Korean Society of Physical Medicine
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• v.19 no.2
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• pp.55-64
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• 2024

PURPOSE: This study evaluated the effects of robot-assisted gait training combined with virtual reality training on balance and gait ability in stroke patients. METHODS: Thirty-one stroke patients were allocated randomly into one of two groups: robot-assisted gait training combined virtual reality training group (RGVR group; n = 16) and control group (n = 15). The RGVR group received 30 minutes of robot-assisted gait training combined with virtual reality training. Robot-assisted gait training was conducted in parallel using a virtual reality device. In the Control group, neurodevelopmental therapy was performed according to the function of chronic stroke patients. Both groups underwent training for 30 minutes, three times per week for eight weeks. The balance assessment system (BioRescue, Marseille, France), BBS, and TUG were used to evaluate the balance ability. The OptoGait (Microgate Srl, Bolzano, Italy) and 10 mWT were measured to evaluate the gait ability. The measurements were performed before and after the eight-week intervention period. RESULTS: Both groups showed significant improvement in their balance and gait ability during the intervention. RGVR showed significant differences in balance and gait ability compared to the control group groups (p < .05). These results showed that RGVR was more effective on balance and gait ability in patients with chronic stroke. CONCLUSION: RGVR can improve balance and gait ability, highlighting the benefits of RGVR. This study provides intervention data for recovering the balance and gait ability of chronic stroke patients.

• Composites Research
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• v.37 no.2
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• pp.132-138
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• 2024

In this study, a molecular dynamics simulation study was performed to investigate the size-dependent electroelastic properties of single-walled boron nitride nanotubes(BNNT). To describe the elasticity and polarization of BNNT under mechanical loading, the Tersoff potential model and rigid ion approximation were adopted. For the prediction of piezoelectric constants and Young's modulus of BNNTs, piezoelectric constitutive equations based on the Maxwell's equation were used to calculate the strain-electric displacement and strain-stress relationships. It was found that the piezoelectric constants of BNNTs gradually decreases as the radius of the tubes increases showing a nonnegligible size effect. On the other hand, the elastic constants of the BNNTs showed opposites trends according to the equivalent geometrical assumption of the tubular structures. To establish the structure-property relationships, localized configurational change of the primarily bonded B-N bonded topology was investigated in detail to elucidate the BNNT curvature dependent elasticity.

• Journal of the Korea Fashion and Costume Design Association
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• v.26 no.2
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• pp.115-127
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• 2024

This study was initiated by focusing on the characteristics of 3D virtual clothing utilized by fashion brands aiming for sustainability. The purpose of this study is to analyze the characteristics of fashion brands that utilize 3D virtual imagery to mitigate environmental pollution caused by the fashion industry from the perspective of green design. The research methodology draws on green design literature and analyzes three hypothetical cases. These include experiential immersive design, design that rewards engagement, and design that delivers economic benefits that were utilized by fashion brands from 2019 to 2023. The findings and conclusions are as follow. First, the for the commercialization of virtual clothing, offline stores are reproduced in the digital world to provide an immersive shopping experience, similar to reality. These promote fashion products in a virtual space without the constraints of space and time, and creates profits and sustainable value. Second, virtual clothing promotes playfulness. Games and events utilize branded virtual worlds and characters to attract users. Rewards are given for achieving goals, and it is a practice of green marketing that uses virtual items to express products and minimize resource waste. Third, virtual clothing is affordable and can reduce the financial burden on consumers by digitally reproducing expensive products as physical brand collections at an acceptable price point. This reduces environmental pollution, saves physical resources, and increases the utilization of virtual clothing by providing a convenient way to purchase. This study is a basic study that examines the current status and characteristics of fashion brands' use of 3D virtual imagery from the perspective of green design based on literature and case analysis, and follow-up studies are expected on empirical virtual imagery activation measures through interviews or surveys with users for each case.

• Journal of Information Technology Services
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• v.23 no.3
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• pp.55-63
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• 2024

To grasp the structure of an industry and monitor its changes, it is essential to utilize relevant statistics. Various statistics are being compiled regarding the software (SW) industry, presenting diverse numerical values. However, without a precise understanding of the scope and measurement methods inherent to each statistic, gaining a rigorous understanding of the industry's structure and evolving trends becomes challenging. Moreover, significant discrepancies between similar statistics often lead to confusion among users. In the software (SW) industry, key statistics commonly used include SW production value and SW market size. As of 2022, the annual domestic SW production value is reported as 77.4 trillion KRW (based on ICT Survey), while the SW market size for the same year is stated as 38.5 trillion KRW (according to IDC data). Although production value and market size may seem conceptually similar, there is approximately a twofold difference between the figures provided. Without understanding the meanings of each statistic and the differences between them, there are limitations in utilizing these statistics effectively. While statistics are utilized for various purposes such as policy development or causal analysis of policy using statistical raw data, research that presents and analyzes the precise meanings and limitations of each SW-related statistic is virtually non-existent. Thus, this study aims to compare and analyze the methodologies and differences among key statistics used to represent the SW industry: SW production value, SW market size, and SW GDP statistics. Through this analysis, the goal is to contribute to a better understanding of the SW industry's structure and enable more accurate and rigorous utilization of relevant statistics.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.1
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• pp.183-192
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• 2008

Generally, application of steel pipe pile as deep foundation member needs special requirement for the connection method between steel pipe pile and concrete footing. Even though two types of connection method are suggested in the korea highway bridge code, type-B method is prevalent. In this study, vertical, lateral, and tension loading test are done for two types of type B connection to review stress concentration, formation and behavior of imaginary RC column in the footing. Welding type and hook type as the connection method are considered in this study. Test results show that welding type have the more reserve capacity than hook type and the specimens connected by the welding type behave as the imaginary RC column in the footing. However, the specimens connected by the hook type did not behave as the imaginary RC column in the footing but behave as the hinge.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.2
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• pp.153-165
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• 2006

A damage in a structure changes its dynamic characteristics such as natural frequencies, damping ratios, and the mode shapes. In this paper the effort has been spent in obtaining the characteristics of the reduction ratio in natural frequencies and the damage detection is performed using the reduction ratios. Most of the emphasis has been on using the artificial neural network to determine the location and the extent of the damage as well as the existence of the damage. The data for learning and verifying neural network were obtained from the analytical analysis. The data have no errors. Considering the real measurements the data including errors which are difference this study between other studies also were used for neural network. The position and extent of the damage can be detected using the neural network trained by reduction ratios of natural frequencies.

• Journal of the Korea Society of Computer and Information
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• v.29 no.8
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• pp.23-32
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• 2024

NVS (Novel View Synthesis) is a field in computer vision that reconstructs new views of a scene from a set of input views. Real-time rendering and high performance are essential for NVS technology to be effectively utilized in various applications. Recently, 3D-GS (3D Gaussian Splatting) has gained popularity due to its faster training and inference times compared to those of NeRF (Neural Radiance Fields)-based methodologies. However, since 3D-GS reconstructs a 3D (Three-Dimensional) scene by splitting and cloning (Density Control) Gaussian points, the number of Gaussian points continuously increases, causing the model to become heavier as training progresses. To address this issue, we propose two methodologies: 1) Gaussian blending, an improved density control methodology that removes unnecessary Gaussian points, and 2) a performance enhancement methodology using a depth estimation model to minimize the loss in representation caused by the blending of Gaussian points. Experiments on the Tanks and Temples Dataset show that the proposed methodologies reduce the number of Gaussian points by up to 4% while maintaining performance.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.109-123
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• 2024

Research into vision-based end-to-end autonomous driving systems utilizing deep learning and reinforcement learning has been steadily increasing. These systems typically encode continuous and high-dimensional vehicle states, such as location, velocity, orientation, and sensor data, into latent features, which are then decoded into a vehicular control policy. The complexity of urban driving environments necessitates the use of state representation learning through networks like Variational Autoencoders (VAEs) or Convolutional Neural Networks (CNNs). This paper analyzes the impact of different image state encoding methods on reinforcement learning performance in autonomous driving. Experiments were conducted in the CARLA simulator using RGB images and semantically segmented images captured by the vehicle's front camera. These images were encoded using VAE and Vision Transformer (ViT) networks. The study examines how these networks influence the agents' learning outcomes and experimentally demonstrates the role of each state representation technique in enhancing the learning efficiency and decision- making capabilities of autonomous driving systems.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.159-169
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• 2024

This paper proposes a new real-time fire monitoring and evacuation navigation system by integrating Augmented Reality (AR) technology with Internet of Things (IoT) technology. The proposed system collects temperature data through IoT temperature measurement devices installed in buildings and automatically transmits it to a MySQL cloud database via an IoT platform, enabling real-time and accurate data monitoring. Subsequently, the real-time IoT data is visualized on a 3D building model generated through Building Information Modeling (BIM), and the model is represented in the real world using AR technology, allowing intuitive identification of the fire origin. Furthermore, by utilizing Vuforia engine's Device Tracking and Area Targets features, the system tracks the user's real-time location and employs an enhanced A^* algorithm to find the optimal evacuation route among multiple exits. The paper evaluates the proposed system's practicality and demonstrates its effectiveness in rapid and safe evacuation through user experiments based on various virtual fire scenarios.

• Journal of the Society of Disaster Information
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• v.20 no.3
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• pp.663-671
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• 2024

Purpose: The purpose of this study is to examine the risks and criminal progress of pig murder fraud crimes in the absence of related research and statistics amid a surge in pig murder fraud damage in Korea, and to approach the methods, problems, and countermeasures that can be prevented in Korea through foreign cases. Method: In order to classify the types of pig murder fraud crimes, the progress was analyzed through related reports and statistics, and various damage cases. Result: The crime of pig murder fraud can be seen as an organized crime that organically combines simple romance scams, investment fraud, and human trafficking. In the case of victims, unlike simple fraud, psychological problems such as suicide impulse and panic disorder were found, and in the case of cryptocurrency acquired through fraud, a path was found to flow back into the criminal organization through money laundering. Conclusion: In the case of pig murder fraud crimes that have been detected as a danger worldwide, the scale will be even wider. Therefore, various institutional supplements and policies should be prepared through crime type analysis in Korea for crime prevention and countermeasures.