• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.1
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• pp.306-310
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• 2012

Location tracking system represents position by searching objects and humans. In this paper I would like to write about RF chip support Zigbee which is called CC2420. In simulated network circumstance, we can get the information about mobile-node by sending it to sink-node. Position finding is in error by 3m at outdoor environment. The error scale is acceptable within easy range of naked eyes. It can be overcome by using GPS information and Google maps with the wireless networking background.

• The Journal of the Korea Contents Association
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• v.10 no.1
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• pp.87-93
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• 2010

This paper describes an improved location determination scheme based on the triangulation method calculating a target position. The proposed scheme uses coordinates of intersection points of three circles each generated by measurement of an observer. The target position obtained from the proposed scheme has higher accuracy not only at the vicinity, but also at the periphery of the observation area. The maximum error and the average error with the proposed scheme are reduced by 40.89% and 40.30%, respectively, with respect to conventional methods.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2002.03a
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• pp.219-227
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• 2002

In this paper, we designed neural network predictive PID controller to control sway happened in transfer of trolley for automatic travel control system. We include dynamic character of nonlinear system, and mathematical expression veny simple used neural network. When various establishment location and surrounding disturbance were approved based on mathematical modelling of crane, controller designed to become effective control location error and vibration angle of two control variables that simultaneously can predictive control. Neural network predictive PID controller produced parameter of PID controller using neural network self-tuner. Neural network self-tuner's input used crane's output and neural network predictive output. Neural network self-tuner using error back propagation algorithm. We analyzed control performance comparison through computer simulation when applied disturbance about sway of location and angle in transfer of crane. The results show that the proposed neural network predictive PID controller has better performances than general PID controller, neural network PID controller.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.266-268
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• 2003

This paper proposes the Fault Location Estimation Algorithm in the parallel transmission lines. These algorithm uses a variable data window method based on least square error method to estimate fault impedance quickly. And it selects the optimal equation according to the operation situation and usable fault data for minimizing the fault estimation error effected by the zero sequence mutual coupling. After simulation result, we can see that these algorithm estimates fault location more rapidly and exactly.

• Journal of Korea Multimedia Society
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• v.24 no.6
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• pp.796-804
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• 2021

In computer vision, visual tracking method addresses the problem of localizing an specific object in video sequence according to the bounding box. In this paper, we propose a tracking method by introducing the feature correlation comparison into the siamese network to increase its matching identification. We propose a way to compute location of object to improve matching performance by a correlation operation, which locates parts for solving the searching problem. The higher layer in the network can extract a lot of object information. The lower layer has many location information. To reduce error rate of the object center point, we built a siamese network that extracts the distribution and location information of target objects. As a result of the experiment, the average center error rate was less than 25%.

• Industrial Engineering and Management Systems
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• v.16 no.1
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• pp.92-102
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• 2017

In this paper, we consider a typical health care system via the help of Wireless Sensor Network (WSN) for wireless patient tracking. The wireless patient tracking module of this system performs localization out of samples of Received Signal Strength (RSS) variations and tracking through a Particle Filter (PF) for WSN assisted by multiple transmit-power information. We propose a modified PF, Kullback-Leibler Distance (KLD)-resampling PF, to ameliorate the effect of RSS variations by generating a sample set near the high-likelihood region for improving the wireless patient tracking. The key idea of this method is to approximate a discrete distribution with an upper bound error on the KLD for reducing both location error and the number of particles used. To determine this bound error, an optimal algorithm is proposed based on the maximum gap error between the proposal and Sampling Important Resampling (SIR) algorithms. By setting up these values, a number of simulations using the health care system's data sets which contains the real RSSI measurements to evaluate the location error in term of various power levels and density nodes for all methods. Finally, we point out the effect of different power levels vs. different density nodes for the wireless patient tracking.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.842-846
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• 2015

In this study, we propose an algorithm of the method of recovering quickly find the location of the error encountered during separate operations in the functional structure of complex digital circuits by mimicking the self-healing function of the cell. By the digital circuit was divided by 9 function block unit of function, proposes a method that It can quickly detect and recover the error position. It was the detection and recovery algorithms for the error location in the digital circuit of a complicated structure and could extended the number of function block for the $3{\times}3$ matrix structure on the digital circuit.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.11
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• pp.2745-2750
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• 2015

Abstract should be placed here In this study, we propose an algorithm of the method of recovering quickly find the location of the error encountered during separate operations in the functional structure of complex digital circuits by mimicking the self-healing function of the cell. By the digital circuit was divided by 9 function block unit of function, proposes a method that It can quickly detect and recover the error position. It was the detection and recovery algorithms for the error location in the digital circuit of a complicated structure and could extended the number of function block for the $3{\times}3$ matrix structure on the dital circuit.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.11
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• pp.1442-1447
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• 2018

Since the indoor location recognition system using RFID is a method for predicting the indoor position, an error occurs due to the surrounding environment such as an obstacle. In this paper, we plan to reduce errors using back propagation neural networks. The neural network adjusts and trains the connection values between the layers to reduce the error between the actual position of the object with the reader and the expected position of the object through the experiment. In this paper, we propose a method that uses the median method and the radiation method as input to the neural network. Among the two methods, we want to find out which method is more effective in recognizing the actual position in an environment with obstacles and reduce the error. Consequently, the method using the median has less error, and we confirmed that the more the number of data, the smaller the error.

• Proceedings of the Acoustical Society of Korea Conference
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• 1984.12a
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• pp.100-106
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• 1984

Traditional methods for estimating the location of underwater target, i.e. the triangulation method and the wavefront curvature method, have been utilized. The location of a target is defined by the range and the bearing, which estimates can be obtained by evaluating the time delay between neighboring sensors. Many components of error occur in estimating the target range, among which the error due to the fluctuation of heading angle is outstanding. In this paper, the wavefront curvature method was used. We considered the error due to the heading fluctuation as the $\beta$-density process, from which we analized the range estimates with $\beta$-density function exist in some finite limits, and its mean value and variation are depicted as a function of true range and heading fluctuation. Given heading angles and sensor separation, maximum estimated heading errors are presented as a function of true range.