• Korean Journal of Optics and Photonics
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• v.35 no.5
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• pp.228-234
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• 2024

Modern infrared-guided weapons detect and destroy targets by seeking and tracking the infrared radiation emitted by the target. By covering the target with a material that has low infrared emissivity, the infrared signal can be reduced to evade tracking. However, this method is effective only when the target is hotter than the background. Since the temperature of the background varies significantly between day and night, target signals with low emissivity at night can be captured by the optical systems of guided weapons due to signal contrast, as they are smaller than the background signals. In this study, the optimal emissivity for implementing infrared stealth for ground targets is calculated based on the temperature and emissivity of the background, as well as the temperature of the target. The size of the signal received by the optical systems of guided weapons, the contrast value of the image, and the lock-on range were calculated for target signals that vary depending on the emissivity of the target. The effectiveness of the optimal emissivity was demonstrated by thermal imaging computer simulations using COMSOL Multiphysics software.

• International Journal of Quality Innovation
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• v.8 no.1
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• pp.99-119
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• 2007

This research probes into the execution of small and medium-sized enterprises' value creativities by a difference analysis with different classifications, different capital, different turnover, different employees, and different established years. This study develop a questionnaire about value creativity with five dimensions and thirty-five items according to "Valuation" by McKinsey and Company, Inc. and Copeland et al., such as: "Aspiration and target," "Portfolio management," "Organization design," "Process management," and "Business and individual performance management." The results are as follows: (1) Most small and medium-sized enterprises (SMEs) have executed value creativities; (2) There is a difference in the execution of value creativities between the livelihood industry and the chemical industry; the execution of value creativities by livelihood industry is better than the chemical industry; (3) For value creativities of the execution of different capital and turnover for SMEs, bigger entities are better than smaller ones; (4) For the value creativities of the execution of different numbers of staff in SMEs, those with more staff are better than those with fewer staff; (5) For the value creativities of the execution of different established years for SMEs, those established longer are better than those established shorter.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.39 no.3
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• pp.239-248
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• 2003

This paper was conducted as an attempt in order to construct the data bank of target strength for acoustic estimation of fish length in the coastal waters of Korea. The fish length dependence of acoustic target strength for 13 large yellow croakers (Pseudosciaena crocea) at 75 kHz was investigated and the prediction of the target strength by using the Kirchhoff-Ray Mode model (KRM model) was compared with target strength measurements. The results obtained are summarized as follows; 1. In the averaged target strength pattern for 13 large yellow croakers the maximum target strength was -35.13 dB at $-13.35^{\circ}$ on a tilted angle. 2. The relationship between fork length(L, cm) and averaged target strength(TS, dB) was expressed as follows; TS=23. 76log (L) -73.45 (r=0.47) TS=20log(L) -67.35 From this result, the conversion coefficient was -73.45 dB and 6.1 dB lower than the coefficient -67.35 dB where the value of the slope of the regression equation is forced to be 20. 3. Averaged target strength and a length conversion coefficient derived from a target strength histogram for 13 large yellow croakers of mean length 25.59 cm were -41.23 dB, -69.72 dB, respectively. 4. In the range of $$2;{\ll} L (fish length /{\lambda}(wave length);{\ll}40$$, the prediction of the averaged target strength by the KRM model increased gradually with the increasing of $L/{\lambda}$ and was lower than the measured target strength.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.1166-1179
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• 2013

In wireless sensor network (WSN) environments, environmental noises are generated by, for example, small passing animals, crickets chirping or foliage blowing and will interfere target detection if the noises are higher than the sensor threshold value. For accurate tracking by acoustic WSNs, these environmental noises should be filtered out before initiating track. This paper presents the effect of environmental noises on target tracking and proposes a new algorithm for the noise mitigation in acoustic WSNs. We find that our noise mitigation algorithm works well even for targets with sensing range shorter than the sensor separation as well as with longer sensing ranges. It is also found that noise duration at each sensor affects the performance of the algorithm. A detection algorithm is also presented to account for the Doppler effect which is an important consideration for tracking higher-speed ground targets. For tracking, we use the weighted sensor position centroid to represent the target position measurement and use the Kalman filter (KF) for tracking.

• 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.

• Proceedings of KOSOMES biannual meeting
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• 2009.06a
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• pp.71-75
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• 2009

This paper proposes an evaluation to Target Factor Values of Port State Control Inspections(PSCITFV) using AHP because PSCITFV is very simple methode, This AHP is the more rational and objective methode than existing TFV methode. AHP is relative measurement., but, weights should be re-calculation whenever alternative plan add. To this solve, therefore, this paper, used an absolute measurement and involved an marine casualty factor in PSCITFV, that IMO go ahead with it., Also, accomplished with evaluation some ships for the practice.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.3
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• pp.23-36
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• 2016

We consider a model that minimizes the total cost incurred by assigning available weapons to existing targets in order to reduce enemy threats, which is called the weapon target assignment problem (WTAP). This study addresses the stochastic versions of WTAP, in which data, such as the probability of destroying a target, are given randomly (i.e., data are identified with certain probability distributions). For each type of random data or parameter, we provide a stochastic optimization model on the basis of the expected value or scenario enumeration. In particular, when the probabilities of destroying targets depending on weapons are stochastic, we present a stochastic programming formulation with a simple recourse. We show that the stochastic model can be transformed into a deterministic equivalent mixed integer programming model under a certain discrete probability distribution of randomness. We solve the stochastic model to obtain an optimal solution via the mixed integer programming model and compare this solution with that of the deterministic model.

• International Journal of Aeronautical and Space Sciences
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• v.15 no.2
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• pp.163-172
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• 2014

This paper proposes a novel guidance law based on the block backstepping sliding mode control and extended state observer (ESO), which also takes into account the autopilot dynamic characteristics of the near space interceptor (NSI), and the impact angle constraint of attacking the maneuvering target. Based on the backstepping control approach, the target maneuvers and the parameter uncertainties of the autopilot are regarded as disturbances of the outer loop and inner loop, respectively. Then, the ESO is constructed to estimate the target acceleration and the inner loop disturbance, and the block backstepping sliding model guidance law is employed, based on the estimated disturbance value. Furthermore, in order to avoid the "explosion of complexity" problem, first-order low-pass filters are also introduced, to obtain differentiations of the virtual control variables. The stability of the closed-loop guidance system is also proven, based on the Lyapunov theory. Finally, simulation results demonstrate that the proposed guidance law can not only overcome the influence of the autopilot dynamic delay and target maneuvers, but also obtain a small miss distance.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.3 s.357
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• pp.12-19
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• 2007

This paper proposes the enhanced auto-focus algorithm detecting several objects and selecting the target object. Proposed algorithm first detects some objects distributed in the image using focus measure operator and multi-window and then selects the target object through fuzzy reasoning with three fuzzy membership functions. Implementation can be simple because it only needs image sensor instead of infrared or ultrasonic equipment. Experimental result shows that the proposed algorithm can improve the quality of image by focusing to the target object.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.2302-2316
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• 2015

We propose an efficient method of extracting targets within a region of interest in non-homogeneous infrared images by using a principal component analysis (PCA) plane and adaptive Gaussian kernel. Existing approaches for extracting targets have been limited to using only the intensity values of the pixels in a target region. However, it is difficult to extract the target regions effectively because the intensity values of the target region are mixed with the background intensity values. To overcome this problem, we propose a novel PCA based approach consisting of three steps. In the first step, we apply a PCA technique minimizing the total least-square errors of an IR image. In the second step, we generate a binary image that consists of pixels with higher values than the plane, and then calculate the second derivative of the sum of the square errors (SDSSE). In the final step, an iteration is performed until the convergence criteria is met, including the SDSSE, angle and labeling value. Therefore, a Gaussian kernel is weighted in addition to the PCA plane with the non-removed data from the previous step. Experimental results show that the proposed method achieves better segmentation performance than the existing method.