• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.9
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• pp.782-791
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• 2013

This paper proposes the location estimation techniques of distributed targets with the multi-sensor data perceived through IR sensors of the military robots. In order to match up targets with measured azimuths, we apply the maximum likelihood (ML), depth-first, and breadth-first tree search algorithms, in which we use the measured azimuths and the number of pixels on IR screen for pruning branches and selecting candidates. After matching up targets with azimuths, we estimate the coordinate of each target by obtaining the intersection point of the azimuths with the least square error (LSE) algorithm. The experimental results show the probability of missing target, mean of the number of calculating nodes, and mean error of the estimated coordinates of the proposed algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.3B
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• pp.453-461
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• 2010

A critical issue in wireless sensor networks is an energy-efficiency since the sensor batteries have limited energy power and, in most cases, are not rechargeable. The most practical manner relate to this issue is to use a node wake-up scheduling protocol that some sensor nodes stay active to provide sensing service, while the others are inactive for conserving their energy. Especially, CTC (Connected Target Coverage) problem has been considered as a representative energy-efficiency problem considering connectivity as well as target coverage. In this paper, we propose a new energy consumption model considering multiple-targets and create a new problem, CMTC (Connected Multiple-Target Coverage) problem, of which objective is to maximize the network lifetime based on the energy consumption model. Also, we present SPT (Shortest Path based on Targets)-Greedy algorithm to solve the problem. Our simulation results show that SPT-Greedy algorithm performs much better than previous algorithm in terms of the network lifetime.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.741-747
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• 2012

In this paper, we propose a fast and robust framework for detecting and tracking multiple targets. The proposed system includes two modules: object detection module and object tracking module. In the detection module, we preprocess the input images frame by frame, such as gray and binarization. Next after extracting the foreground object from the input images, morphology technology is used to reduce noises in foreground images. We also use a block-based histogram analysis method to distinguish human and other objects. In the tracking module, color-based tracking algorithm and Kalman filter are used. After converting the RGB images into HSV images, the color-based tracking algorithm to track the multiple targets is used. Also, Kalman filter is proposed to track the object and to judge the occlusion of different objects. Finally, we show the effectiveness and the applicability of the proposed method through experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.5
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• pp.445-453
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• 2001

The multiple targets tracking problem has been one of the main issues in the radar applications area in the last decade. Besides the standard Kalman filtering, various methods including the variable dimen-sion filter, input estimation filter, interacting multiple model(IMM) filter, dederated variable dimension filter with input estimation, etc., have proposed to address the tracking and sensor fusion issues. In this pa- per, two existing tracking algorithm, i.e, the IMM filter and the variable dimension filter with input estima-tion(VDIE), are combined for the purpose of improving the tracking performance for maneuvering targets. To evaluate the tracking performance of the proposed algorithm, three typical maneuvering patterns, i.e., waver, pop-up, and high-diver motions, are defined and are applied to the modified IMM filter as well as the standard IMM filter. The smaller RMS tracking errors, in position and velocity, of the modified IMM filter than the standard IMM filter are demonstrated though computer simulations.

• Transactions on Electrical and Electronic Materials
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• v.14 no.4
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• pp.187-192
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• 2013

Because of the importance of small target detection in infrared images, many studies have been carried out in this area. Using a Kalman filter and mean shift algorithm, this study proposes an algorithm to track multiple small moving targets even in cases of target disappearance and appearance in serial infrared images in an environment with many noises. Difference images, which highlight the background images estimated with a background estimation filter from the original images, have a relatively very bright value, which becomes a candidate target area. Multiple target tracking consists of a Kalman filter section (target position prediction) and candidate target classification section (target selection). The system removes error detection from the detection results of candidate targets in still images and associates targets in serial images. The final target detection locations were revised with the mean shift algorithm to have comparatively low tracking location errors and allow for continuous tracking with standard model updating. In the experiment with actual marine infrared serial images, the proposed system was compared with the Kalman filter method and mean shift algorithm. As a result, the proposed system recorded the lowest tracking location errors and ensured stable tracking with no tracking location diffusion.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.12
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• pp.77-84
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• 2004

We design and implement the DSP module for automotive radar using FMCW. The designed parameters are based on 77GHz FMCW radar, and show the resolution of 0.4m and 0.67km/h in distance and velocity, respectively. For detecting multiple targets, we discuss the relationship between fb's and targets. In addition, we show that the detection of multiple targets is very simple when the range of $f_r$ is sufficiently larger than that of $f_b$. In the front of ADC, the 2nd order differentiator is applied for reducing the effects of path-loss so that the ADC bits are reduced to 8 bits. The designed block is simulated in Matlab and implemented with DSP and micro-processor.

• Journal of the Korean institute of surface engineering
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• v.49 no.4
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• pp.368-375
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• 2016

MoN-Cu thin films were prepared to achieve appropriate properties of high hardness and low friction coefficient, which could be applied to automobile engine parts for reducing energy consumption as well as solving wear problems. Composite thin films of MoN-Cu have been deposited by various processes using multiple targets such as Mo and Cu. However, those deposition with multiple targets revealed demerits such as difficulties in exact control of composition and homogeneous deposition. This study is aiming for suggesting an appropriate process to solve those problems. A single alloying target of Mo-Cu (10 at%) was prepared by powder metallurgy methods of mechanical alloying (MA) and spar plasma sintering (SPS). Thin film of MoN-Cu was then deposited by magnetron sputtering using the single alloying target of Mo-Cu (10 at%). Properties of the resulting MoN-Cu thin film were examined and compared to those of MoN-Cu thin films prepared with double targets of Mo and Cu.

• Development and Reproduction
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• v.16 no.3
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• pp.169-175
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• 2012

Angelman syndrome (AS) is a neurodevelopmental disorder characterized by intellectual disability and autism. The genetic cause is the absence of UBE3A, an E3 ubiquitin ligase, from the maternal chromosome which can arise from multiple origins. Recently discovered targets of Ube3a are important for activity dependent changes in synaptic transmission and spine morphology. Plasticity studies in an AS mouse model is important for basic plasticity research with regard to understanding protein homeostasis as well as the search for therapeutic targets for the patients. The progress on synaptic plasticity from this unique disorder is reviewed.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.6
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• pp.186-197
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• 1996

A multiple target tracking (MTT) problem is to track a number of targets in clusttered environment, where measurements may contain uncertainties of measurement origin due to clutter, missed detection, or other targets, as well as measurement noise errors. Hence, an MTT filter should be introduced to resolve this problem. In this paper, a neural network is rpoposed as an MTT filter.

• Korean Journal of Child Studies
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• v.15 no.2
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• pp.141-152
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• 1994

The purpose of this study was to investigate the goal and strategy differences in the Social Problem Solving (SPS) according to ages and interaction targets of children. The subjects were 48 children between the ages of 3, 4 and 5 years. Their SPS behavior was observed as it occurred naturally in free play interactions. The data were analysed by one-way ANOVA, Duncan's multiple range, repeated measures, and t-test. The results showed that there were significant goal and strategy differences in SPS behavior according to age and interaction targets of children.