• Journal of the Korean Society of Physical Medicine
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• v.18 no.4
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• pp.109-119
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• 2023

PURPOSE: The definition and scope of biofeedback are broad and lack a clear framework. Therefore, efforts are needed to clearly understand the exact range and definition of biofeedback based on the research and development conducted to date. Thus, the purpose of this study was to arrive at the definition and scope of biofeedback through a literature review and analysis of its application methods. METHODS: This study is a systematic literature review conducted to understand the various types and effects of biofeedback. International databases such as Google Scholar and PubMed were used. Domestic databases utilized for keyword searches included the Research Information Sharing Service (RISS) and the National Digital Science Library (NDSL). Quality assessment of the selected studies in the selection process was done using the Cochrane risk of bias, and the research was analyzed according to the population, intervention, control, and outcomes (PICO) format. RESULTS: Studies conducted between 2019 and 2021 were selected, with 4 papers falling under physiological classifications and 7 under biomechanical classifications. The quality assessment results showed that random sequence generation, allocation concealment, performance bias, and reporting bias were unclear. Detection bias was moderate, and attrition bias and other biases were low. Out of the 11 papers, 9 dealt with physical function outcomes, 5 with daily life activities, and 3 with mental functions. CONCLUSION: Physiological biofeedback tended to influence psychological factors more than physical functions, while biomechanical biofeedback tended to have a positive impact on physical functions.

• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.441-449
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• 2021

With advances in autonomous vehicles, there is a growing demand for more accurate position estimation. Especially, this is a case for a moving robot for the indoor operation which necessitates the higher accuracy in position estimation when the robot is required to execute the task at a predestined location. Thus, a method for improving the position estimation which is applicable to both the fixed and the moving object is proposed. The proposed method exploits the initial position estimation from Bluetooth beacon signals as observation signals. Then, it estimates the gravitational acceleration applied to each axis in an inertial frame coordinate through computing roll and pitch angles and combining them with magnetometer measurements to compute yaw angle. Finally, it refines the control inputs for an object with motion dynamics by computing acceleration on each axis, which is used for improving the performance of Kalman filter. The experimental assessment of the proposed algorithm shows that it improves the position estimation accuracy in comparison to a conventional Kalman filter in terms of average error distance at both the fixed and moving states.

• Journal of Drive and Control
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• v.21 no.1
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• pp.22-30
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• 2024

Gearboxes designed for reciprocating motion operating mechanisms operate under conditions where both the load and speed undergo continuous variations. When conducting durability tests on gearboxes designed for such applications, operating the target gearbox under conditions similar to the intended usage is essential. The gearbox must be operated for the required number of cycles to validate its durability under conditions mirroring its intended usage. This study devised an accelerated test method for gearboxes, which reduces operating angles and operational strokes. The reliability of the accelerated test was verified by comparing the stresses imposed on the gears under general and acceleration conditions through multi-body dynamic simulations. The results confirmed that the maximum contact stress levels under normal and accelerated conditions were within a 0.1% error range, indicating a minimal difference in the gear damage rates. However, a difference in the maximum contact stress results between the normal and accelerated conditions was observed when inertial forces acted on the output shaft due to the operational acceleration of the gearbox. Therefore, when conducting this acceleration test, caution should be exercised to ensure that the operational load on the gearbox, which affects inertia, does not significantly deviate from the conditions observed under normal operating conditions.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.10
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• pp.738-746
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• 2019

Instead of hydraulic actuation systems, an electromechanical actuation system is more efficient in terms of weight, cost, and test evaluation in the thrust vector control of the 7-ton gimbal engine used in the Korea Space Launch Vehicle-II(KSLV-II) $3^{rd}$ stage. The electromechanical actuator is a kind of servo actuator with position feedback and uses a BLDC motor that can operate at high vacuum. In the case of the gimballed rocket engine, a synthetic resonance phenomenon may occur due to a combination of a vibration mode of the actuator itself, a bending mode of the launcher structure, and an inertial load of the gimbals engine. When the synthetic resonance occurs, the control of the rocket attitude becomes unstable. Therefore, the requirements for the stiffness have been applied in consideration of the gimbal engine characteristics, the support structure, and the actuating system. For the 7-ton gimbal engine of the KSLV-II $3^{rd}$ stage, the stiffness requirement of the actuation system is $3.94{\times}10^7N/m$, and the direct drive type electromechanical actuator is designed to satisfy this requirement. In this paper, an equivalent stiffness analysis model of a direct drive electromechanical actuator designed based on the stiffness requirements is proposed and verified by experimental results.

• Journal of Ocean Engineering and Technology
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• v.33 no.2
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• pp.168-177
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• 2019

KRISO (Korea Research Institute of Ship & Ocean Engineering) started a project to develop the core algorithms for autonomous intervention using an underwater robot in 2017. This paper introduces the development of the robot platform for the core algorithms, which is an ROV (Remotely Operated Vehicle) type with one 7-function manipulator. Before the detailed design of the robot platform, the 7E-MINI arm of the ECA Group was selected as the manipulator. It is an electrical type, with a weight of 51 kg in air (30 kg in water) and a full reach of 1.4 m. To design a platform with a small size and light weight to fit in a water tank, the medium-size manipulator was placed on the center of platform, and the structural analysis of the body frame was conducted by ABAQUS. The robot had an IMU (Inertial Measurement Unit), a DVL (Doppler Velocity Log), and a depth sensor for measuring the underwater position and attitude. To control the robot motion, eight thrusters were installed, four for vertical and the rest for horizontal motion. The operation system was composed of an on-board control station and operation S/W. The former included devices such as a 300 VDC power supplier, Fiber-Optic (F/O) to Ethernet communication converter, and main control PC. The latter was developed using an ROS (Robot Operation System) based on Linux. The basic performance of the manufactured robot platform was verified through a water tank test, where the robot was manually operated using a joystick, and the robot motion and attitude variation that resulted from the manipulator movement were closely observed.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.1
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• pp.13-21
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• 2018

AGVS (Automated Guided Vehicle System) is a core technology of logistics automation which automatically moves specific objects or goods within a certain work space. Conventional AGVS generally requires the in-door localization system and each AGV equips expensive sensors such as laser, magnetic, inertial sensors for the route recognition and automatic navigation. thus the high installation cost is inevitable and there are many restrictions on route(path) modification or expansion. To address this issue, in this paper, we propose a cost-effective and scalable AGV based on a light-weight pattern recognition technique. The proposed pattern recognition technology not only enables autonomous driving by recognizing the route(path), but also provides a technique for figuring out the loc ation of AGV itself by recognizing the simple patterns(bar-code like) installed on the route. This significantly reduces the cost of implementing AGVS as well as benefiting from route modification and expansion. In order to verify the effectiveness of the proposed technique, we first implement a pattern recognition algorithm on a light-weight MCU(Micro Control Unit), and then verify the results by implementing an MCU_controlled AGV prototype.