• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.1
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• pp.26-41
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• 2024

To ensure safer road conditions, understanding the human factors influencing driving behavior is crucial. However, there are many difficulties in deriving the characteristics of individual human factors that affect actual driving behaviors. Therefore, this study analyzes self-reported dangerous-driving propensities in order to explore potential correlations with drivers' behaviors. The goal is to propose a method for assessing driving tendencies based on varying traffic scenarios. The study employed a questionnaire to gauge participants' propensity to drive dangerously, utilizing a simulator to analyze their driving behaviors. The aim is to determine any notable connections between dangerous-driving propensity and specific driving behaviors. Results indicate that individuals exhibiting a high propensity for reckless driving, as identified by the Korean DBQ, tend to drive at higher speeds and display more aggressive acceleration patterns. These findings contribute to a potential method for assessing reckless driving drivers.

• Journal of the Korea Society of Computer and Information
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• v.29 no.6
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• pp.31-38
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• 2024

This study proposes a novel approach to enhancing the social inclusion and participation of individuals with developmental disabilities. Utilizing cutting-edge virtual reality (VR) technology, we designed and developed a metaverse simulator that enables individuals with developmental disabilities to safely and conveniently experience indoor handicapped handball sports. This simulator provides an environment where individuals with disabilities can experience and practice handball matches. For the modeling and animation of handball players, we employed advanced modeling and motion capture technologies to accurately replicate the movements required in handball matches. Additionally, we ported various training programs, including basic drills, penalty throws, and target games, onto XR (Extended Reality) devices. Through this research, we have explored the development of immersive assistive tools that enable individuals with developmental disabilities to more easily participate in activities that may be challenging in real-life scenarios. This is anticipated to broaden the scope of social participation for individuals with developmental disabilities and enhance their overall quality of life.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.77-84
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• 2024

Over the past few years, IoT edges have begun to emerge based on new low-latency communication protocols such as 5G. However, IoT edges, despite their enormous advantages, pose new complementary threats, requiring new security solutions to address them. In this paper, we propose a cloud environment-based IoT edge architecture model that complements IoT systems. The proposed model acts on machine learning to prevent security threats in advance with network traffic data extracted from IoT edge devices. In addition, the proposed model ensures load and security in the access network (edge) by allocating some of the security data at the local node. The proposed model further reduces the load on the access network (edge) and secures the vulnerable part by allocating some functions of data processing and management to the local node among IoT edge environments. The proposed model virtualizes various IoT functions as a name service, and deploys hardware functions and sufficient computational resources to local nodes as needed.

• Journal of Soil and Groundwater Environment
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• v.29 no.1
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• pp.1-9
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• 2024

As part of monitoring technology aimed at verifying the stability of CO₂ geologic storage and mitigating concerns about leakage, a method for measuring the pH and alkalinity of high-pressure fluid samples was established to obtain practical technology. pH measurement for high-pressure samples utilized a high-pressure pH electrode, and alkalinity was measured using the Gran titration method for samples collected with a piston cylinder sampler (PCS). Experimental samples, referencing CO₂-rich water and CO₂ geologic storage studies, were prepared in the laboratory. The PCS controls the piston, preventing CO₂ degassing and maintaining fluid pressure, allowing mixing with KOH to fix dissolved CO₂. Results showed a 6.1% average error in high-pressure pH measurement. PCS use for sample collection maintained pressure, preventing CO₂ degassing. However, PCS-collected sample alkalinity measurements had larger errors than non-PCS measurements, limiting PCS practicality in monitoring field settings. Nevertheless, PCS could find utility in preprocessing for carbon isotope analysis and other applications. This research not only contributes to the field of CCS monitoring but also suggests potential applications in studies related to natural analogs of CCS, CO₂-rock interaction experiments, core flooding experiments, and beyond.

• Journal of The Korean Society of Integrative Medicine
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• v.12 no.1
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• pp.109-124
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• 2024

Purpose : The purpose of this study was to examine the effects of a virtual reality-based complex cognitive training program for depression, cognitive function, and digital divide reduction in the elderly who have not been diagnosed with dementia or MCI. Methods : We enrolled 16 participants who were over 65 years old and not been diagnosed with dementia or MCI. We randomly divided into three groups (A, B, C). Participants underwent an 8-week virtual reality-based complex cognitive training program (60 minutes each session, twice per week). At a baseline, all participants completed questionnaires on general features, depression and cognitive function. After four weeks, all participants completed questionnaires on depression and cognitive function. After the end of the last program, participants conducted questionnaires on depression, cognitive function, and usability evaluation. Results : At the 8-week follow-up, 16 participants completed the program. Compared to the baseline, the average score of cognitive function was increased (from 26.5 to 28.5), although it was not statistically significant (p<.061). There were no significant differences between baseline and post-training evaluations on depression scores. The average score of usability evaluation was 75.56, which corresponds to good. Conclusion : Even though the results showed no statistically significant findings in cognitive function and depression after the virtual reality-based complex cognitive training intervention, this pilot study proposed the possibility of utilizing the virtual reality program as a tool that provides active learning opportunities for the elderly and helps improve their cognitive function through multi-sensory components. Also, the findings of this study suggested a positive reevaluation of the elderly's digital access capabilities while reducing the digital divide. A virtual reality-based complex cognitive training program improved the social network of the elderly. We expect that it will expand in size and help with their social participation of the elderly.

• Journal of Practical Engineering Education
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• v.16 no.1_spc
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• pp.1-9
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• 2024

The introduction of smart factory digital twins is a concept that has already been proposed to increase productivity in the manufacturing industry through CPS(Cyber Physics System), and has been applied to specific industrial process stages or partially introduced in stages where simulation is required. However, with the recent development of the 4th Industrial Revolution technology, it is receiving attention again along with XR (Extended Reality) technology. However, because there are not many effective cases, this study analyzed the devices, equipment, and technology of the manufacturing process to build a digital twin applying digital threads and synchronized signals and information to control, remote control, and produce intelligent process automation equipment. A platform capable of analyzing information was proposed and developed. Through this, we designed and built an XR content service platform that can support artificial intelligence and developed it to enable control, remote control, and analysis of production information. A possible platform was proposed and developed. We hope that this study will be helpful in conducting research on many cases, and in the future, expanded research on increasing productivity in each part of the process and production is needed through intelligent models.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.1
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• pp.41-47
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• 2024

This paper utilizes computational asymptotic analysis to compute the boundary layer solution for composite beams and validates the findings through a comparison with ANSYS results. The boundary layer solution, presented as a sum of the interior solution and pure boundary layer effects, necessitates a mathematically rigorous formalization for both interior and boundary layer aspects. Computational asymptotic analysis emerges as a robust technique for addressing such problems. However, the challenge lies in connecting the boundary layer and interior solutions. In this study, we systematically separate the principles of virtual work and the principles of Saint-Venant to tackle internal and boundary layer issues. The boundary layer solution is articulated by calculating the Papkovich-Fadle eigenfunctions, representing them as linear combinations of real and imaginary vectors. To address warping functions in the interior solutions, we employed a least squares method. The computed solutions exhibit excellent agreement with 2D finite element analysis results, both quantitatively and qualitatively. This validates the effectiveness and accuracy of the proposed approach in capturing the behavior of composite beams.

• The Journal of the Acoustical Society of Korea
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• v.26 no.5
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• pp.220-226
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• 2007

The two major objectives of acoustical measurements in a cavitation tunnel are measuring the noise levels generated by rotating propellers behind a hull and localizing possible noise sources in order to reduce noise levels. Propeller noise measurement experiments were performed in MOERI cavitation tunnel at December, 2006. In order to put the propeller into cavitating conditions, a wake-generating dummy body was devised. In addition, ten hydrophones are put inside a wing-shaped casing in order to minimize the unexpected flow induced self noise around hydrophone itself. After measuring both of the noises of the rotating propeller behind the dummy body and signals generated by a virtual source, respectively the data were matched field processed using the frequency incoherent Bartlett processor to localize noises on the propeller plane. In this paper, we presented the measured noise analysis and the localization results.

• The Journal of the Acoustical Society of Korea
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• v.28 no.6
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• pp.557-565
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• 2009

To perceive the direction and the distance of a sound, we always use a couple of information. Head Related Transfer Function (HRTF) contains the information that sound arrives from a sound source to the ears of the listener, like differences of level, phase and frequency spectrum. For a reproduction system using 2 channels, we apply HRTF to many algorithms which make 3d sound. But it causes a problem to localize a sound source around a certain places which is called the cone-of-confusion. In this paper, we proposed the new algorithm to reduce the confusion of sound image localization. The difference of frequency spectrum and psychoacoustics theory are used to boost the spectral cue among each directions. To confirm the performance of the algorithm, informal listening tests are carried out. As a result, we can make the improved 3d sound in 2 channel system based on a headphone. Also sound quality of improved 3d sound is much better than conventional methods.

• The Journal of the Acoustical Society of Korea
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• v.27 no.4
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• pp.207-214
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• 2008

To create 3D sound, we usually use two methods which are two channels or multichannel sound systems. Because of cost and space problems, we prefer two channel sound system to multi-channel. Using a headphone or two speakers, the most typical method to create 3D sound effects is a technology of head related transfer function (HRTF) which contains the information that sound arrives from a sound source to the ears of the listener. But it causes a problem to localize a sound source around a certain places which is called cone-of-confusion. In this paper, we proposed the new algorithm to reduce the confusion of sound image localization. HRTF grouping and psychoacoustics theory are used to boost the spectral cue with spectrum difference among each directions. Informal listening tests show that the proposed method improves the front-back sound localization characteristics much better than conventional methods.