• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.29-37
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• 2019

Synthetic Aperture Radar (SAR) observations are powerful tools to monitor surface's displacement very accurately, induced by earthquake, volcano, ground subsidence, glacier movement, etc. Especially, radar interferometry (InSAR) which utilizes phase information related to distance from sensor to target, can generate displacement map in line-of-sight direction with accuracy of a few cm or mm. Due to decorrelation effect, however, degradation of coherence in the InSAR application often prohibit from construction of differential interferogram. Offset tracking method is an alternative approach to make a two-dimensional displacement map using intensity information instead of the phase. However, there is limitation in that the offset tracking requires very intensive computation power and time. In this paper, efficiency of parallel computing has been investigated using high performance computer for estimation of glacier velocity. Two TanDEM-X SAR observations which were acquired on September 15, 2013 and September 26, 2013 over the Narsap Sermia in Southwestern Greenland were collected. Atotal of 56 of 2.4 GHz Intel Xeon processors(28 physical processors with hyperthreading) by operating with linux environment were utilized. The Gamma software was used for application of offset tracking by adjustment of the number of processors for the OpenMP parallel computing. The processing times of the offset tracking at the 256 by 256 pixels of window patch size at single and 56 cores are; 26,344 sec and 2,055 sec, respectively. It is impressive that the processing time could be reduced significantly about thirteen times (12.81) at the 56 cores usage. However, the parallel computing using all the processors prevent other background operations or functions. Except the offset tracking processing, optimum number of processors need to be evaluated for computing efficiency.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.1
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• pp.17-25
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• 2023

As the range of use of urban unmanned aerial vehicles (UAV) expands, it is necessary to operate UAVs efficiently because of its limited battery capacity. For this, it is required to find the optimal flight profile with various simulations. Therefore, it is important to predict the power and energy consumption of the UAV battery. In this paper, we analyzed the relationship between the speed and acceleration of the UAV and power consumption during the flight. Then, we derived a linear model, which is easily utilized. In addition, we also derived an accurate power consumption model based on deep neural network learning. To find the efficient model, we used learning data as 1) the GPS 3-axis velocity and acceleration data, 2) the IMU 3-axis velocity only, and 3) the IMU 3-axis velocity and acceleration data. The final model shows 5.86% error rate for power consumption and 1.50% error rate for the cumulative energy consumption.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.189-192
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• 2021

This study applies a deep learning-based long short-term memory(LSTM) model to track tracking technology. In the case of existing track tracking technology, the weight of constant velocity, constant acceleration, stiff turn, and circular(3D) flight is automatically changed when tracking track in real time using LMIPDA based on Kalman filter according to flight characteristics of an aircraft such as constant velocity, constant acceleration, stiff turn, and circular(3D) flight. In this process, it is necessary to improve performance of changing flight characteristic weight, because changing flight characteristics such as stiff turn flight during constant velocity flight could incur the loss of track and decreasing of the tracking performance. This study is for improving track tracking performance by predicting the change of flight characteristics in advance and changing flight characteristic weigh rapidly. To get this result, this study makes deep learning-based Long Short-Term Memory(LSTM) model study the plot and target of simulator applied with radar error model, and compares the flight tracking results of using Kalman filter with those of deep learning-based Long Short-Term memory(LSTM) model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.285-288
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• 2022

Objectives : This study aimed to determine whether Variability of Walking Environment Training can improve gait and balance in stroke patients. Methods : Twenty-four stroke patients are randomly assigned to experimental group 1 (n=8), experimental group 2 (n=8) and control group (n=8). Experimental group 1 performed unexpected obstacle walking training, experimental group 2 performed fixed obstacle walking training and control group performed non obstacle walking training for 12 minutes per session, 5 times a week for 4 weeks. The gait analyzer G-walk were evaluated using gait cadence, gait velocity, and stride length, balance was evaluated using FES-K and BBS. Results : In within-group comparison of gait cadence, gait velocity and stride length of change, the experimental 1,2 groups showed significant improvements post intervention (p<.05) but control group showed no significant improvement. In between-groups comparison there was significant difference in the change of gait cadence, gait velocity and stride length pre and post intervention. In within-group comparison of FES-K and BBS scores, the experimental 1,2 groups showed significant improvements post intervention (p<.05) but control group showed no significant improvement. In between-groups comparison there was significant difference in the change of FES-K and BBS scores pre and post intervention (p<.05).

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.33-38
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• 1989

This paper is about construction of Data Acquisition System for Gyro-System which obtains the information such as position, velocity, acceleration and attitude etc of Dynamic Vehicle System. We made up the Data Acquisition System using IBM-PC and in connection with CYBER 180-830 based on rate table, controller and IEEE 488 Interface etc.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2002.06a
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• pp.161-165
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• 2002

This paper describe a trajectory generation method for a soccer robot using cubic Bezier curve. It is proposed that the method to determine the location of control points. The control points are determined by the distance and the velocity parameters of start and target positions. Simulation results show its traceability of the trajectory of mobile robot.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.173-182
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• 2005

In this paper, a target tracking algorithm for tracking maneuvering vehicles is presented. The overall algorithm belongs to the category of an interacting multiple-model (IMM) algorithm used to detect multiple targets using fused information from multiple sensors. First, two kinematic models are derived: a constant velocity model for linear motions, and a constant-speed turn model for curvilinear motions. Fpr the constant-speed turn model, a nonlinear information filter is used in place of the extended Kalman filter. Being equivalent to the Kalman filter (KF) algebraically, the information filter is extended to N-sensor distributed dynamic systems. The model-matched filter used in multi-sensor environments takes the form of a federated nonlinear information filter. In multi-sensor environments, the information-based filter is easier to decentralize, initialize, and fuse than a KF-based filter. In this paper, the structural features and information sharing principle of the federated information filter are discussed. The performance of the suggested algorithm using a Monte Carlo simulation under the two patterns is evaluated.

• Journal of Navigation and Port Research
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• v.31 no.3 s.119
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• pp.223-228
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• 2007

In recent trends of the enlargement and specialization, container ship, LNCG, PCC and passenger ship which have relatively large hull and superstructure above the water line, are already being operated in the world It is very important information for the safety operation of these vessels to estimate the ship's performance under the specific wind condition while berthing, unberthing or low-speed sailing. In this paper, the effect of wind force and moment acting on the training ship HANNARA is investigated by using the numerical calculations. The results of drift angle and counter rudder angle with the relative wind direction and force, the critical wind velocity with the ratio of wind velocity and ship's speed and maximum heeling angle with the wind velocity are shown The presented results can be applied directly to T/S HANNARA in berthing maneuver and avoiding typhoons, and utilized as an educational materials.

• Geophysics and Geophysical Exploration
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• v.8 no.4
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• pp.237-242
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• 2005

A seismic refraction study in estimation of depth to the bedrock demonstrates that 1) the average velocity in the medium is about 250 m/s in the surface layer (< 4 m), 2,500 m/s in the weathered formation, and greater than 3,000 m/s in the bedrock, 2) the depth to the deepest reflector assumed to be the bedrock is about 17 m; however, according to the cores collected in a borehole in study area, the bedrock (granite) occurred at depth 25 m, 3) according to the density and velocity logging, at depth 17 m, a measurable velocity and density increase are observed, and 4) the velocity of the weathered formation is relatively high and therefore, the acquisition offsets ($70{\sim}80m$) are turned out not to be long enough to record the refracted signal from the bedrock at depth 25 m as first arrivals.

• Journal of Biosystems Engineering
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• v.15 no.1
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• pp.1-13
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• 1990

Aerodynamic property is the most important factor in designing the pneumatic separator and handling equipment for grains and seeds. Particularly the correct information about the terminal velocities of the corresponding grains and seeds is indispensible. However, a few studies with relation to the terminal velocities of grains and seeds were conducted in this country, even though the terminal velocities of the domestic grains and seeds are required to design those equiments which can be used for the domestic grains and seeds having specific aerodynamic properties. In this study, the terminal velocities for four varieties of varley and six varieties of paddy were investigated by means of two different methods, the suspension method and the drop method in an upward current of air. For measuring the terminal velocities, the vertical wind tunnel which had been examined about the uniform air flow in the previous study was used. In addition, the effect of the size of grains and the moisture content of grain kernel on the terminal velocity was examined. The following conclusions were derived from the study : 1. The different terminal velocities of grains are resulted from the different measuring methods. The terminal velocity measured by the drop method is smaller than that by the suspension method. It is considered that the difference in the terminal velocities is caused by the difference in the projection area of grain which is faced to the air stream. 2. The terminal velocity of grain increases as the size and the moisture content of the kernel increase. 3. The linear regression equations for the terminal velocities of grains were derived in terms of the moisture content of grains by the variety of grains and the measuring method. Also, the linear regression equations for the terminal velocity, based on the weighted size of grains, were derived in terms of the moisture contents of granis.