• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.37 no.3
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• pp.231-240
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• 2024

Titanium dioxide (TiO₂) holds significant scientific and technological relevance as a key photocatalyst and resistive random-access memory, demonstrating unique physicochemical properties and serving as an n-type semiconductor. Understanding the density and arrangement of oxygen vacancies (VOs) is crucial for tailoring TiO₂'s properties to diverse technological needs, driving increased interest in exploring oxygen vacancy complexes and superstructures. In this mini review, we summarize the recent understandings of the fundamental properties of oxygen vacancies in bulk rutile (R-TiO₂) and anatase (A-TiO₂) based on DFT and beyond method. We specifically focus on the excess electrons and their spatial arrangement of disordered single VO in bulk R and A-TiO₂, aligned with the experimental findings. We also highlight the theoretical works on investigating the geometries and stabilities of ordered VOs complexes in bulk TiO₂. This comprehensive review provides insights into the fundamental properties of excess electrons in reduced TiO₂, offering valuable perspectives for future research and technological advancements in TiO₂-based devices.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.197-205
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• 2024

Development of AI and big data-based algorithms to advance and optimize the recognition and detection performance of various static/dynamic vehicles in front and around the vehicle at a time when securing driving safety is the most important point in the development and commercialization of autonomous vehicles. etc. are being studied. However, there are many research cases for recognizing the same vehicle by using the unique advantages of radar and camera, but deep learning image processing technology is not used, or only a short distance is detected as the same target due to radar performance problems. Therefore, there is a need for a convergence-based vehicle recognition method that configures a dataset that can be collected from radar equipment and camera equipment, calculates the error of the dataset, and recognizes it as the same target. In this paper, we aim to develop a technology that can link location information according to the installation location because data errors occur because it is judged as the same object depending on the installation location of the radar and CCTV (video).

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.3
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• pp.563-570
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• 2024

This paper proposes a method to recognize and track drivable lane areas to assist the driver. The main topic is designing a deep-based network that predicts drivable road areas using computer vision and deep learning technology based on images acquired in real time through a camera installed in the center of the windshield inside the vehicle. This study aims to develop a new model trained with data directly obtained from cameras using the YOLO algorithm. It is expected to play a role in assisting the driver's driving by visualizing the exact location of the vehicle on the actual road consistent with the actual image and displaying and tracking the drivable lane area. As a result of the experiment, it was possible to track the drivable road area in most cases, but in bad weather such as heavy rain at night, there were cases where lanes were not accurately recognized, so improvement in model performance is needed to solve this problem.

• Korean Journal of Radiology
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• v.24 no.6
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• pp.564-573
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• 2023

Objective: To investigate the feasibility of assessing the viscoelastic properties of the brain using magnetic resonance elastography (MRE) and a novel MRE transducer to determine the relationship between the viscoelastic properties and glymphatic function in neurologically normal individuals. Materials and Methods: This prospective study included 47 neurologically normal individuals aged 23-74 years (male-to-female ratio, 21:26). The MRE was acquired using a gravitational transducer based on a rotational eccentric mass as the driving system. The magnitude of the complex shear modulus |G^*| and the phase angle 𝛗 were measured in the centrum semiovale area. To evaluate glymphatic function, the Diffusion Tensor Image Analysis Along the Perivascular Space (DTI-ALPS) method was utilized and the ALPS index was calculated. Univariable and multivariable (variables with P < 0.2 from the univariable analysis) linear regression analyses were performed for |G^*| and 𝛗 and included sex, age, normalized white matter hyperintensity (WMH) volume, brain parenchymal volume, and ALPS index as covariates. Results: In the univariable analysis for |G^*|, age (P = 0.005), brain parenchymal volume (P = 0.152), normalized WMH volume (P = 0.011), and ALPS index (P = 0.005) were identified as candidates with P < 0.2. In the multivariable analysis, only the ALPS index was independently associated with |G^*|, showing a positive relationship (β = 0.300, P = 0.029). For 𝛗, normalized WMH volume (P = 0.128) and ALPS index (P = 0.015) were identified as candidates for multivariable analysis, and only the ALPS index was independently associated with 𝛗 (β = 0.057, P = 0.039). Conclusion: Brain MRE using a gravitational transducer is feasible in neurologically normal individuals over a wide age range. The significant correlation between the viscoelastic properties of the brain and glymphatic function suggests that a more organized or preserved microenvironment of the brain parenchyma is associated with a more unimpeded glymphatic fluid flow.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.93-100
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• 2024

With the advent of the Fourth Industrial Revolution, cutting-edge technologies such as artificial intelligence, big data, the Internet of Things, and cloud computing are driving innovation across industries. These technologies are generating massive amounts of data that many companies are leveraging. However, there is a notable reluctance among users to share sensitive information due to the privacy risks associated with collecting personal data. This is particularly evident in the healthcare sector, where the collection of sensitive information such as patients' medical conditions poses significant challenges, with privacy concerns hindering data collection and analysis. This research presents a novel technique for collecting and analyzing medical data that not only preserves privacy, but also effectively extracts statistical information. This method goes beyond basic data collection by incorporating a strategy to efficiently mine statistical data while maintaining privacy. Performance evaluations using real-world data have shown that the propose technique outperforms existing methods in extracting meaningful statistical insights.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.157-167
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• 2023

The use of big data for transportation often involves using data that includes personal information, such as the driver's driving routes and coordinates. This study explores the creation of a route choice prediction model using a large dataset from mobile navigation apps using federated learning. This privacy-focused method used distributed computing and individual device usage. This study established preprocessing and analysis methods for driver data that can be used in route choice modeling and compared the performance and characteristics of widely used learning methods with federated learning methods. The performance of the model through federated learning did not show significantly superior results compared to previous models, but there was no substantial difference in the prediction accuracy. In conclusion, federated learning-based prediction models can be utilized appropriately in areas sensitive to privacy without requiring relatively high predictive accuracy, such as a driver's preferred route choice.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.138-146
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• 2024

Purpose: The purpose of this study is to find cases of using information and communication technology and smart mobility technology in snow removal vehicles and equipment for rapid and efficient road snow removal in the event of a snowstorm, and to find ways to utilize them. Method: Cases of domestic and overseas snow removal methods are investigated, and snow removal operation methods incorporating new technologies are presented. Result: Most of the operation of snow removal equipment in Korea uses GPS, CCTV, and road traffic information systems, and in the case of overseas, road weather information systems and road snow removal monitoring systems are used. It is expected that snow removal technology using autonomous snow removal vehicles, which are smart mobility, will be developed in the future. Conclusion: The results of this study can contribute to the policy of using snow removal equipment and snow removal vehicles of local governments and related organizations.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.465-470
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• 2024

Kitchen cabinets are widely used for their spacious storage and efficient use of space, but their high installed location makes it difficult for the elderly and disabled to access. Therefore, in this paper, we propose a new height-adjustable kitchen cabinet that can be used more easily and safely. The lift-down range of cabinet was set considering the installation location of cabinet for efficient use of kitchen space and the maximum height accessible to the elderly and disabled, and the link geometry and driving method of the complex link mechanism were determined through the mechanism design procedure to ensure that the selected floor come down safely along the optimal descend path. In addition, the appropriate motor and control algorithm were added to allow the user to descend to the desired height with a simple button operation. It was confirmed through actual production that the proposed linkage mechanism performs the desired lift-down motion.

• The Journal of the Acoustical Society of Korea
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• v.43 no.4
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• pp.391-399
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• 2024

In order to analyze the distribution of sound fields radiating from a circular plate vibrated by a Langevin transducer, a theoretical analysis model was derived. The boundary conditions of the driving area and fixed boundary area were appropriately applied to the equation of motion of the vibrating plate, which was derived by L. Rayleigh. By calculating the vibration displacement distributed on the surface of the vibrating plate using the derived analysis model and then calculating the sound field formed by the ultrasonic waves radiating from it, it was confirmed that the radiation characteristics vary significantly depending on the area of the vibrating plate. For comparison, a simulation of the same system was performed using the COMSOL program, a finite element method, and showed good agreement with the theoretical calculation results, confirming the effectiveness of the theoretical analysis model derived in thisstudy. It is expected that the theoretical analysis model derived from this study can be used in the design and development of related devices, such as in the ultrasonic chemistry field.

• Journal of the Institute of Convergence Signal Processing
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• v.25 no.1
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• pp.33-38
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• 2024

The importance of connected technology that connects products or systems is increasing. Connected technology is a concept that can communicate with surrounding objects and connect to each other through a network to operate as one system. In particular, it can be implemented using wireless communication, and various conditions are required depending on the application system, such as communication distance and speed. In this study, we analyzed trends in communication technology for the implementation of connectivity between mobility devices such as self-driving cars, drones, UAVs, and shared mobility devices. The communication distance, speed, wired and wireless status, etc. of the latest communication methods currently commercialized or under development were investigated, with a particular focus on low-power operation. We identified the element technologies needed to build a low-power long-distance communication (LPWAN) system, and initially developed a plan for constructing a connected drone. The analysis results showed that it was possible to implement a connected system using the LoRa system, and an example configuration method was presented.