• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.4
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• pp.95-105
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• 2021

Road surface damage detection is essential for a comfortable driving environment and the prevention of safety accidents. Road management institutes are using automated technology-based inspection equipment and systems. As one of these automation technologies, a sensor to detect road surface damage plays an important role. For this purpose, several studies on sensors using deep learning have been conducted in recent years. Road images and label images are needed to develop such deep learning algorithms. On the other hand, considerable time and labor will be needed to secure label images. In this paper, the adversarial learning method, one of the semi-supervised learning techniques, was proposed to solve this problem. For its implementation, a lightweight deep neural network model was trained using 5,327 road images and 1,327 label images. After experimenting with 400 road images, a model with a mean intersection over a union of 80.54% and an F1 score of 77.85% was developed. Through this, a technology that can improve recognition performance by adding only road images was developed to learning without label images and is expected to be used as a technology for road surface management in the future.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1323-1328
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• 2021

In this paper, we present a medical electric scooter sharing platform for the transportation vulnerable who are experiencing difficulties and inconveniences in moving. The proposed medical electric scooter sharing platform for the transportation vulnerable includes basic mobile rental, return, and functions that incorporate the IOT technology of the currently operating personal mobility sharing platform. The safety function has been strengthened. The medical electric scooter sharing platform for the transportation vulnerable stores driving data on the server in real time through GPS, and strengthens the alarm and call function in advance of an accident to enable rapid SOS processing. By making the quick contact and responding to the situation, people with disabilities can drive safely and comfortably.

• The Journal of the Acoustical Society of Korea
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• v.40 no.6
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• pp.571-577
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• 2021

This study is a study on System On Chip (SOC) that implements virtual engine sound in electric vehicles without engines, and realizes vivid engine sound by combining Adaptive Difference PCM (ADPCM) method and frequency modulation method for satisfaction of driver's needs and safety of pedestrians. In addition, by proposing an electronic sound synthesis algorithm applying Musical Instrument Didital Interface (MIDI), an engine sound synthesis method and a constitutive model of an engine sound generation system are presented. In order to satisfy both drivers and pedestrians, this study uses Controller Area Network (CAN) communication to receive information such as Revolution Per Minute (RPM), vehicle speed, accelerator pedal depressed amount, torque, etc., transmitted according to the driver's driving habits, and then modulates the frequency according to the appropriate preset parameters We implemented an interaction algorithm that accurately reflects the intention of the system and driver by using interpolation for the system, ADPCM algorithm for reducing the amount of information, and MIDI format information for making engine sound easier.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.3138-3151
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• 2022

Traffic safety and congestion are becoming more and more serious, especially the frequent occurrence of traffic accidents, which have caused great casualties and economic losses. Cellular Vehicle to Everything (C-V2X) can assist in safe driving and improve traffic efficiency through real-time information sharing and communication between vehicles. All vehicles communicate directly with Base Stations (BS), which will increase the base station load. And when the communicating vehicles are too far apart, too fast or there are obstacles in the communication path, the communication link can be unstable or even interrupted. Therefore, choosing an effective and reliable multi-hop relay-assisted Vehicle to Vehicle (V2V) communication can not only reduce the base station load and improve the system throughput but also expand the base station coverage and improve the communication quality of edge vehicles. Therefore, a communication area division scheme based on regular hexagon segmentation technology is proposed, a relay-assisted V2V communication mechanism is designed for the divided communication areas, and an efficient communication link is constructed by selecting the best relay node. Simulation results show that the scheme can improve the throughput of the system by nearly 55% and enhance the robustness of the V2V communication link.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.4_2
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• pp.655-662
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• 2022

Recently, with the increase in the use of UAV(unmanned aerial vehicles), research on horizontal maintenance stations that can take off and land in various environments has been actively conducted. These stations can safely land UAV through multiple DOF(degrees of freedom) or at least 2-DOF-based actuator actuation. Among them, many researchers are dealing with the multi-DOF stewart platform due to its high safety. However, the stewart platform requires high-precision control technology because it requires a lot of torque to actuate according to the load action. Therefore, in this paper, to solve the mentioned problem, a bevel gear-based 2-DOF horizontal maintenance station system is proposed. The proposed system is configured to prevent damage due to air resistance when maintaining ships and to install it in a small space. Also, in terms of system configuration, the bevel gear-based horizontal maintenance system has the main advantage of being able to take off and land UAVs of various sizes through the replacement of station pads. The driving of the system consists of a simple form that can control the motor by adjusting the rotation speed of the motor according to the sea waveform.

• Journal of Trauma and Injury
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• v.35 no.1
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• pp.3-11
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• 2022

Purpose: The increasing use of electric personal mobility devices (ePMDs) has been accompanied by an increasing incidence of associated accidents. This study aimed to investigate the characteristics of ePMD-related injuries and their associated factors. Methods: This cross-sectional study was conducted using data from the Emergency Department-based Injury In-depth Surveillance database from 2014 to 2018. All patients who were injured while operating an ePMD were eligible. The primary outcome was the rate of severe injury, defined as an excess mortality ratio-adjusted Injury Severity Score of ≥25. We calculated the adjusted odds ratios (AORs) of outcomes associated with ePMD-related injuries. Results: Of 1,391,980 injured patients, 684 (0.05%) were eligible for inclusion in this study. Their median age was 28 years old, and most injuries were sustained by men (68.0%). The rate of ePMD-related injuries increased from 3.1 injuries per 100,000 population in 2014 to 100.3 per 100,000 population in 2018. A majority of the injuries occurred on the street (32.7%). The most commonly injured area was the head and face (49.6%), and the most common diagnosis was superficial injuries or contusions (32.9%). Being aged 55 years or older (AOR, 3.88; 95% confidence interval, 1.33-11.36) and operating an ePMD while intoxicated (AOR, 2.78; 95% confidence interval, 1.52-5.08) were associated with severe injuries. Conclusions: The number of emergency room visits due to ePMD-related injuries is increasing. Old age and drunk driving are both associated with serious injuries. Active traffic enforcement and safety regulations regarding ePMDs should be implemented to prevent severe injuries caused by ePMD-related accidents.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.2
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• pp.95-101
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• 2023

Globally, the importance of utilization and management of marine spatial information is being maximized, and analyzing such data is emerging as a major driving force for R&D. In Korea, it is expected that collecting marine data from the past to the present and extracting its value will play an important role in the development of science in Korea in the future. In particular, marine static data constitutes a huge big database, and it is necessary to store and store the collected data without loss as high data collection costs and high-level observation techniques are required. In addition, the Disaster Safety Intelligence Convergence Center's "Marine Digital Twin Establishment and Utilization-Based Technology Research" task requires collection and analysis of marine data, so this paper conducts a current status survey of static marine data. And we present a series of algorithms that collect and store them in a database.

• Membrane Journal
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• v.32 no.6
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• pp.401-410
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• 2022

Demand for lithium hydroxide (LiOH) is annually increasing due to its efficiency and safety for the environment in comparison to its current alternatives. Lithium can be found in different salty and brine lakes which later synthesized to produce LiOH for various applications. Different methods are used to separate and recover lithium ions, the most common of which is electrodialysis (ED). ED is a membrane-based separation technique which works on potential difference of its layers as a driving force to push ions from one side to another. The ion exchange membrane (IEM) in ED makes the process efficient because of the perm selectivity of different ions vary depending on their hydrodynamic volume. In this review, the different alteration strategies of both ED and IEM, to enhance the recovery of lithium ions are discussed.

• Journal of Korean Port Research
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• v.12 no.1
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• pp.55-64
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• 1998

Directed graphic algorithm was applied to an empirical analysis of traffic occupant fatalities based on a model by Crandall. In this paper, Crandall's data on U.S. traffic fatalities for the period 1947-1981 are focused and extended to include 1982-1993. Based on the 1947-1981 annual data, the directed graph algorithms reveal that occupant traffic deaths are directly caused by income, vehicle miles, and safety devices. Vehicle mileage is caused by income and rural driving. The estimation is conducted using three stage least squares regression. Those results show a difference between the traditional regression methodology and causal graphical analysis. It is also found that forecasts from the directed graph based model outperform forecasts from the regression-based models, in terms of mean squared forecasts error. Furthermore, it is demonstrates that there exists some latent variables between all explanatory variables and occupant deaths.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.265-275
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• 2023

The purpose of this paper is to devise an optimal route allocation algorithm for automated vehicle(AV) in monitoring quality of road infrastructure to support the road safety. The tasks of an AV in this paper include visiting node-links at least once during its operation and checking status of road infrastructure, and coming back to its depot.. In selecting optimal route, its priority goal is visiting the node-links with higher risks while reducing costs caused by operation. To deal with the problem, authors devised reward maximizing algorithm for AVs. To check its validity, the authors developed simple toy network that mimic node-link networks and assigned costs and rewards for each node-link. With the toy network, the reward maximizing algorithm worked well as it visited the node-link with higher risks earlier then chinese postman route algorithm (Eiselt, Gendreau, Laporte, 1995). For further research, the reward maximizing algorithm should be tested its validity in a more complex network that mimic the real-life.