• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.3194-3210
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• 2022

Wall obstruction is the main factor leading to the non-line of sight (NLoS) error of indoor localization based on received signal strength indicator (RSSI). Modeling and correcting the path loss of the signals through the wall will improve the accuracy of RSSI localization. Based on electromagnetic wave propagation theory, the reflection and transmission process of wireless signals propagation through the wall is analyzed. The path loss of signals through wall is deduced based on power loss and RSSI definition, and the theoretical model of path loss of signals through wall is proposed. In view of electromagnetic characteristic parameters of the theoretical model usually cannot be accurately obtained, the statistical model of NLoS error caused by the signals through the wall is presented based on the log-distance path loss model to solve the parameters. Combining the statistical model and theoretical model, a hybrid model of path loss of signals through wall is proposed. Based on the empirical values of electromagnetic characteristic parameters of the concrete wall, the effect of each electromagnetic characteristic parameters on path loss is analyzed, and the theoretical model of regional path loss of signals through the wall is established. The statistical model and hybrid model of regional path loss of signals through wall are established by RSSI observation experiments, respectively. The hybrid model can solve the problem of path loss when the material of wall is unknown. The results show that the hybrid model can better express the actual trend of the regional path loss and maintain the pass loss continuity of adjacent areas. The validity of the hybrid model is verified by inverse computation of the RSSI of the extended region, and the calculated RSSI is basically consistent with the measured RSSI. The hybrid model can be used to forecast regional path loss of signals through the wall.

• International journal of advanced smart convergence
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• v.10 no.1
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• pp.56-61
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• 2021

Neighbor path selection is to pre-select alternate routes in case geographically correlated failures occur simultaneously on the communication network. Conventional heuristic-based algorithms no longer improve solutions because they cannot sufficiently utilize historical failure information. We present a novel solution model for neighbor path selection by using machine learning technique. Our proposed machine learning neighbor path selection (ML-NPS) model is composed of five modules- random graph generation, data set creation, machine learning modeling, neighbor path prediction, and path information acquisition. It is implemented by Python with Keras on Tensorflow and executed on the tiny computer, Raspberry PI 4B. Performance evaluations via numerical simulation show that the neighbor path communication success probability of our model is better than that of the conventional heuristic by 26% on the average.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.1
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• pp.139-147
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• 2001

In this study a path control scheme of simulation models of various vehicles to evaluate their handling characteristic is developed. Based on the forward target method, path deviation error is estimated and the required steering effort to reduce the error is computed by Ziegler-Nichols PID control rule. Velocity control model is also included in the proposed path control scheme to achieve the desired velocity. The path control scheme is implemented on a full vehicle model to perform ISO test procedures, such as steady state cornering, lane change, and sinusoidal input, etc. Through the simulations of ISO test procedures and comparison with actual tests, effectiveness and validity of the path control model is demonstrated.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1111-1117
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• 2003

NURBS (Non Uniform Rational B-Spline) is widely used in CAD system and NC data for high speed machining. Conventional CAM system changes NURBS surface to tessellated meshes or Z-map model, and produces linear tool path. The linear tool path is not good for precise machining and high speed machining. In this paper, an algorithm to change linear tool path to NURBS one was studied, and the machining result of NURBS tool path was compared with that of linear tool path. The N-post, post-processing and virtual machining software was developed. The N-Post post-processes linear tool path to NURBS tool path and quickly shades machined product on OpenGL view and compares a machined product with original CAD surface. A virtual machined model of original tool path and post-processed tool path was compared to original CAD model. The machining error of post-processed NURBS tool path was reduced to 43%. The original tool path and NURBS tool path was used to machine general model using same machine tool and machining condition. The machining time of post-processed NURBS tool path was reduced up to 38%.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.3
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• pp.194-198
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• 2011

In this paper, we obtained the path loss characteristics in the 850 MHz for Russia area by using the free space path loss model and Okumura-Hata path loss model. In order to extract the additional path loss model parameter from the new Russian regional properties, the mean square error technique is used to obtain the correction factor. According to the obtained correction factor, the differences for the free space and Hata path loss model are 17, 6 dB in the 5 ~ 10 Km, 28, 14 dB in the 10 ~ 15 Km, and 35, 18 dB in the 15 ~ 20 Km. By applying the correction factors, the appropriate partial path loss models for the measured Russain area are proposed.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.24 no.1
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• pp.1-9
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• 2016

In this paper, we integrate three degree of freedom(3DOF) point-mass model for aircraft and three-dimensional path generation algorithms using dubins curve and nonlinear path tracking law. Through this integration, we apply the path generation algorithm to the path planning, and verify tracking performance and feasibility of using the aircraft 3DOF point-mass model for air traffic management. The accuracy of modeling 6DOF aircraft is more accurate than that of 3DOF model, but the complexity of the calculation would be raised, in turn the rate of computation is more likely to be slow due to the increase of degree of freedom. These obstacles make the 6DOF model difficult to be applied to simulation requiring real-time path planning. Therefore, the 3DOF point-mass model is also sufficient for simulation, and real-time path planning is possible because complexity can be reduced, compared to those of the 6DOF. Dubins curve used for generating the optimal path has advantage of being directly available to apply path planning. However, we use the algorithm which extends 2D path to 3D path since dubins curve handles the two dimensional path problems. Control law for the path tracking uses the nonlinear path tracking laws. Then we present these concomitant simulation results.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.4
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• pp.334-340
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• 2005

A mouse is an important input device that is used in most of all computer works. A mouse control time prediction model was proposed in this study. Especially, the model described the time of mouse control that made a cursor to move within path constraints. The model was developed by a laboratory experiment. Cursor movement times were measured in 36 task conditions; 3 levels of path length, 3 levels of path width and 4 levels of target's width. 12 subjects participated in all conditions. The time of cursor movement with path constraints could be better explained by the combination of Fitts' law with steering law($r^2=0.947$) than by the other models; Fitts' law($r^2=0.740$), Steering law($r^2=0.633$) and Crossman's model($r^2=0.897$). The proposed model is expected to be used in menu design or computer game design.

• The Journal of the Acoustical Society of Korea
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• v.22 no.1E
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• pp.33-42
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• 2003

Kuo et al proposed an on-line method for an adaptive prediction error filter for improving secondary path modeling performance in the modeling method of the secondary path. This method have some disadvantages, namely having to use additive noise with the result that noise control performance is not good since it is focused on the estimated performance of the secondary path. In this paper, we proposes a modified Kuo model using gain control parameter and delay. It uses a reference signal for additive noise to improve the problems in the existing Kuo model.

• Journal of the Semiconductor & Display Technology
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• v.20 no.4
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• pp.134-140
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• 2021

This study investigates the flow efficiency and temperature based on flow path shape. Five models are designed to the no flow path, one flow path, two flow path, three flow path, add inlet flow path and add interior space gradient. Results show that two flow model(add inlet flow path and add interior space gradient), It was confirmed that model(add inlet flow path) is the optimal shape for coolant heat transfer, and model(add interior space gradient) is the optimal shape for coolant flow, demonstrates optimal design among the five models. The results of this study can be utilized to efficiently control the coolant flow through various types of flow paths.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.399-399
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• 2000

In this paper, path generation using the sensor platform is proposed. The sensor platform is composed two electric motors which make panning and tilting motions. An algorithm fur a real path form and an obstacle length is realized using a scanning algorithm to rotating the sensors on the sensor platform. An ARV (Autonomous Robot Vehicle) is able to recognize the given path by adapting this algorithm. In order for the ARV to navigate the path flexibly, a kinematic model needed to be constructed. The kinematic model of the ARV was reformed around its body center through a relative velocity relationship to controllability, which derives from the nonholonomic characteristics. The optimal controller that is based on tile kinematic model is operated purposefully to track a reference vehicle's path. The path generation algorithm is composed of two parks. On e part is the generating path pattern, and the other is used to avoid an obstacle. The optimal controller is used for tracking the reference path which is generated by recognizing the path pattern. Results of simulation show that this algorithm for an ARV is sufficient for path generation by small number of sensors and for low cost controller.