• Journal of Aerospace System Engineering
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• v.18 no.1
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• pp.99-107
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• 2024

This paper introduces an emergency response system in urban air mobility scenarios. A biometric responsive smartwatch was designed to monitor passengers' real-time heart rates. When an anomaly was detected, the system would send an alert via Morse code vibration and voice notification. It was integrated with the assumed control system of the ROS environment and communicates to implement a system for generating the shortest path for emergency landing to a nearby vertical port during urban air mobility operations. System stability was verified through high-fidelity simulation environments and testing based on actual geographic locations. Our technology improved the reliability and convenience of urban air mobility, demonstrating its effectiveness through simulations and tests in real-world scenarios.

• Journal of Drive and Control
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• v.21 no.1
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• pp.46-52
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• 2024

The advancement of autonomous driving technology has heightened the importance of Autonomous Mobile Robotics (AMR) within smart factories. Notably, in tasks involving the transportation of heavy objects, the consideration of weight in route optimization and path planning has become crucial. There is ongoing research on local path planning, such as Dijkstra, A^*, and RRT^*, focusing on minimizing travel time and distance within smart factory warehouses. Additionally, there are ongoing simultaneous studies on route optimization, including TSP algorithms for various path explorations and on minimizing energy consumption in mobile robotics operations. However, previous studies have often overlooked the weight of the objects being transported, emphasizing only minimal travel time or distance. Therefore, this research proposes route planning that accounts for the maximum payload capacity of mobile robotics and offers load-optimized path planning for multi-destination transportation. Considering the load, a genetic algorithm with the objectives of minimizing both travel time and distance, as well as energy consumption is employed. This approach is expected to enhance the efficiency of mobility within smart factories.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.17-34
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• 2022

This paper develops a model for dynamic station assignment to optimize the Demand Responsive Transit (DRT) operation. In the process of optimization, we use the bus travel time as a variable for DRT management. In addition, walking time, waiting time, and delay due to detour to take other passengers (detour time) are added as optimization variables and entered for each DRT passenger. Based on a network around Anaheim, California, reserved origins and destinations of passengers are assigned to each demand responsive bus, using K-means clustering. We create a model for selecting the dynamic station and bus route and use Non-dominated Sorting Genetic Algorithm-III to analyze seven scenarios composed combination of the variables. The result of the study concluded that if the DRT operation is optimized for the DRT management, then the bus travel time and waiting time should be considered in the optimization. Moreover, it was concluded that the bus travel time, walking time, and detour time are required for the passenger.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.1B
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• pp.40-52
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• 2007

Mobile IP allows mobile end-systems to maintain on-going connections while moving to other links. Based on the Internet Protocol Version 6 (IPv6), mobile IPv6 provides a set of new mobility functions such as route optimization in addition to the functions in mobile IPv4. This paper describes the hardware-based mobile IPv6 implementation which provides all the mobility functionalities in hardware. The hardware-based mobile IPv6 provides faster mobility support than software-based implementation as well as it reduces the number of packet losses which can be caused during the movement. In end-systems equipped with hardware-based mobility support, the CPU can concentrate more on running application programs without wasting its effort for mobility support, and hence it is expected the overall performance improvement.

• Journal of Appropriate Technology
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• v.7 no.2
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• pp.127-135
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• 2021

To respond to the threat of global warming, countries around the world are promoting the spread of renewable energy and reduction of carbon emissions. In accordance with the United Nation's Sustainable Development Goal to combat climate change and its impacts, global automakers are pushing for a full transition to electric vehicles within the next 10 years. Electric vehicles can be a useful means for reducing carbon emissions, but in order to reduce carbon generated in the stage of producing electricity for charging, a power generation system using eco-friendly renewable energy is required. In this study, we propose a smart electric mobility operating system integrated with off-grid solar power plants established in Tanzania, Africa. By applying smart monitoring and communication functions based on Arduino-based computing devices, information such as remaining battery capacity, battery status, location, speed, altitude, and road conditions of an electric vehicle or electric motorcycle is monitored. In addition, we present a scenario that communicates with the surrounding independent solar power plant infrastructure to predict the drivable distance and optimize the charging schedule and route to the destination. The feasibility of the proposed system was verified through test runs of electric motorcycles. In considering local environmental characteristics in Tanzania for the operation of the electric mobility system, factors such as eco-friendliness, economic feasibility, ease of operation, and compatibility should be weighed. The smart electric mobility operating system proposed in this study can be an important basis for implementing the SDGs' climate change response.

• Journal of the Korean Institute of Gas
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• v.27 no.3
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• pp.1-10
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• 2023

Due to the development of the industrial revolution, regulations on exhaust emissions have been continuously strengthened to reduce the rapidly increasing greenhouse gas emissions. The use of environmentally friendly fuels is essential to meet these regulations. Hydrogen has been attracting attention as a future environmentally friendly fuel, but due to its material properties, it faces significant challenges in handling and storage. As an alternative, ammonia has been proposed. Ammonia can be easily liquefied at room temperature compared to hydrogen and has a high energy density. In order to examine the applicability of ammonia as an engine fuel, experiments were conducted to investigate the effects of changes in combustion control parameters in a direct injection ammonia combustion engine. The experiments were conducted by varying two variables: spark timing and excessive air ratio. Observations were made on combustion stability and the trends of exhaust emissions such as nitrogen oxides and unburned ammonia under the conditions of an engine speed of 1,500 rpm and medium to high loads (brake torque of 200 Nm). By optimizing the combustion control parameters, conditions for stable combustion even when using ammonia as the sole fuel were identified, and plans are underway to apply strategies for future expansion of the operating range.

• 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.

• Journal of Navigation and Port Research
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• v.46 no.6
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• pp.570-575
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• 2022

The MX-S2X, utilizing high-frequency broadband communication technology, provides a reliable connection between land, ship, and facilities. This technology is expected to be effectively utilized as a future maritime communication infrastructure in the upcoming mixed navigational situation among autonomous and manned and/or unmanned ships. Following the physical layer design and M&S-based performance analysis of the MX-S2X system to overcome maritime multipath fading, this paper confirms the optimized and detailed design of physical layer hardware and implemented it to verify the performance. The PER(Packet Error Rate) performance was then measured by configuring a test environment to verify the implemented hardware. The results showed that the performance degradation was 0.2 dB in the AWGN environment and 1.2 dB in the Multi-path Fading on Sea Environment, thus confirming the successful implementation of the physical layer.