• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.50 no.4
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• pp.427-434
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• 2014

Although ex situ target strength (TS) measurements using dual- and split-beam systems have become the primary approach of estimating fish abundance, theoretical model estimation is a powerful tool for verifying the measurements, as well as for providing values when making direct measurements is difficult. TS values for 20 samples of live bambooleaf wrasse (Pseudolabrus japonicus) whose target length (TL) ranged between 13.7 and 21.3 cm were estimated theoretically using the Kirchhoff-ray mode model, and the TS values for 18 live fish samples were additionally measured at ${\sim}0^{\circ}$ tilt angle to the swimming aspect using a tethered method at a frequency of 120 kHz to verify the theoretical values. The digitizing intervals used to extract the fish body and swim bladder morphology in the X-ray photographs significantly affected the calculated TS patterns, but variations based on the speed of sound and density ratio values for the general range of fish flesh were relatively small (within 1 dB). Close agreement was observed between the measured and theoretical TS values, and the correlation between the average TS and body length of the fish could be calculated accurately as <$TS_{120kHz}$>= 20logTL (cm) -71.6 using the theoretical method.

• Journal of applied mathematics & informatics
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• v.26 no.3_4
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• pp.661-672
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• 2008

In this paper an algorithm, based on extracting a certain target of an image, is proposed that is capable of performing bilevel thresholding of image with multimodal distribution. Each pixel in the image has a membership value which is used to denote the characteristic relationship between the pixel and its belonging region (i.e. the object or background). Using the membership values of image set, a new measurement, which simultaneously measures the measure of fuzziness and the conditional entropy of the image, is calculated. Then, thresholds are found by optimally minimizing calculated measurement. In addition, a fuzzy range is defined to improve the threshold values. The experimental results demonstrate that the proposed approach can select the thresholds automatically and effectively extract the meaningful target from the input image. The resulting image can preserve the object region we target very well.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.14-19
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• 1998

In this paper, a target approachable force-guided control with adaptive accommodation for the complex assembly is presented. The complex assembly (CA) is defined as a task which deals with complex shaped parts including concavity or whose environment is so complex that unexpected contacts occur frequently during insertion. CA tasks are encountered frequently in the field of the manufacturing automation and various robot applications. To make CA successful, both the bounded wrench condition and the target approachability condition should be satisfied simultaneously during insertion. By applying the convex optimization technique, an optimum target approaching twist can be determined at each instantaneous contact state as a global minimum solution. Incorporated with an admissible perturbation method, a new CA algorithm using only the sensed resultant wrench and the target twist is developed without motion planning nor contact analysis which requires the geometry of the part and the environment. Finally, a VME-bus based real-time control system is built to experiment various CA task. T-insertion task as a planar CA and double-peg assembly task as a spacial assembly were successfully executed by implementing the new force-guided control with adaptive accommodation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2094-2112
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• 2019

Focusing on the issue that the conventional Kernel Correlation Filter (KCF) algorithm has poor performance in handling scale change and obscured objects, this paper proposes an anti-occlusion and scale adaptive tracking algorithm in the basis of KCF. The average Peak-to Correlation Energy and the peak value of correlation filtering response are used as the confidence indexes to determine whether the target is obscured. In the case of non-occlusion, we modify the searching scheme of the KCF. Instead of searching for a target with a fixed sample size, we search for the target area with multiple scales and then resize it into the sample size to compare with the learnt model. The scale factor with the maximum filter response is the best target scaling and is updated as the optimal scale for the following tracking. Once occlusion is detected, the model updating and scale updating are stopped. Experiments have been conducted on the OTB benchmark video sequences for compassion with other state-of-the-art tracking methods. The results demonstrate the proposed method can effectively improve the tracking success rate and the accuracy in the cases of scale change and occlusion, and meanwhile ensure a real-time performance.

• Korean Journal of Metals and Materials
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• v.49 no.3
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• pp.250-255
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• 2011

The basic properties and electrical characteristics of sputtering films deposited with a commercial cast target and Spark Plasma Sintering (SPS) were compared and analyzed. From the results, the Cu film prepared heating $60^{\circ}C/min$ (SPS process) showed a similar specific resistance compared to the commercial cast Cu film. Also, auording to the results of XRD, SIMS, and TEM. There was not much difference in the crystal structure and impurities between the two films. Consequently, the SPS Cu target was found to have quite similar properties with the commercial one and it is expected to be applied in futare research to the metal wiring material for semiconductor/display devices.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.5006-5022
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• 2017

Effect and robust detection of targets in infrared images has crucial meaning for many applications, such as infrared guidance, early warning, and video surveillance. However, it is not an easy task due to the special characteristics of the infrared images, in which the background clutters are severe and the targets are weak. The recent literature demonstrates that sparse representation can help handle the detection problem, however, the detection performance should be improved. To this end, in this text, a hybrid method based on local sparse representation and contrast is proposed, which can effectively and robustly detect the infrared targets. First, a residual image is calculated based on local sparse representation for the original image, in which the target can be effectively highlighted. Then, a local contrast based method is adopted to compute the target prediction image, in which the background clutters can be highly suppressed. Subsequently, the residual image and the target prediction image are combined together adaptively so as to accurately and robustly locate the targets. Based on a set of comprehensive experiments, our algorithm has demonstrated better performance than other existing alternatives.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.5
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• pp.904-912
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• 2011

In this paper, we have proposed a M&S tool for analyzing detection coverage and target localization in bistatic radar system. The detection coverage determined by radar parameters is meaningful when it satisfies the clear line-of-sight condition. We improved the method to find the minimum altitudes of transmitter and receiver for meeting the condition by considering three-dimensional coverage. Its computational burden is not problematic because the calculation is for maximizing the performance of the radar and does not demand a real-time operation. In addition, target localization on three-dimensional earth model based on the information of the height, longitude, and latitude is proposed instead of the previous unpractical calculation on two-dimensional bistatic plane. Its precalculated result can reduce its computation burden and it is suitable for real-time estimation of target location.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.1
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• pp.66-75
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• 2020

Enemy information has significant value when it comes to the process of military actions in battle field. Our Army now uses Battlefield Management Systems(BMSs) equipped in Ground Fighting Vehicles(GFVs) and we need to make research on what kind of role enemy information can play in such systems. Also, enemy information can be shared among GFVs and target information shall be extracted from it in view of KVMF scheme. Because KVMF becomes requisite standard in modern BMSs, we need to implement target information handling process in KVMF standard. In this article, we will focus on how target information and its sharing process can be managed efficiently without information conflicts. Also, situation map produced by it will be noted.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.1
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• pp.66-74
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• 2012

The virtual target signal generator was developed to verify the shipborne tracking radar performance. It was used to DRFM(Digital RF Memory) method to generate the virtual moving targets. The target signal includes Doppler shift and RCS according to the target motion. And the signal generator can make jamming signal and clutter to test shipborne radar performance at real environmental condition. This paper described the functional diagram and the hardware configuration items to meet the test requirements for the tracking radar. And it showed the critical design points for the sub-systems. The signal generator which was developed in this paper shared the operational information of the radar with the radar command and control part. To test the frequency agility of the radar, it had the local oscillator which could do high speed frequency switching according to radar information. By communicating between the signal generator and the radar command and control part, the local oscillator of signal generator could be controlled every pulse. It reduced the instantaneous bandwidth of signal generator and minimized the spurious. So it lowered the probability of generating wrong targets.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.3
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• pp.364-377
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• 2014

In this paper, we have developed a target recognition algorithm based on a template matching technique using Synthetic Aperture Radar (SAR) images. For efficient computations, Radon transform-based azimuth estimation algorithm was used with the template matching. MSTAR data set was divided into two groups according to the depression angles, which were a train set and a test set. Template data were generated by rotating and cropping chips which were from MSTAR train set using the azimuth estimation algorithm. Then the template matching process between test data and template data was performed under various conditions. Performance variation according to contrast enhancement preprocessing which is scarce in open literature was also presented. The analysis results show that the target recognition algorithm could be useful for the automatic target recognition using SAR images.