• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.4
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• pp.30-37
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• 2007

In this paper, Water Entry Point Selection Algorithm(WEPSA) for selecting an optimal Water Entry Point of anti-submarine missiles which maximizes Detection Probability about a given target was investigated. WEPSA is a method which decides the position of an optimal Water Entry Point with calculating the target Detection Probability of a torpedo in the whole domain which centered by the target, performing the Monte-Carlo Simulations which include errors for the target informations and for weapon delivery. We can decide an optimal Water Entry Point of anti-submarine missiles which maximizes Detection Probability about a given target with WEPSA, if we get target informations about target range, target bearing, target speed and target course from Combat Systems.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.4
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• pp.684-695
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• 1987

In this paper, an improved matching method using subtemplate of moving region and 3-step search algorithm is proposed. It reduces heavy computational load of the conventional method and also can continuously track the target even with occlusion. The proposed method is applied to an automatic target tracker using high speed 16bit microprocessor in order to track one moving target in real time. Experimental results show that the proposed method has better performance over the conventional method in spite of greately reducing the computational load, even in case with complex background and/or with occlusion.

• Ocean and Polar Research
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• v.34 no.1
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• pp.85-91
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• 2012

Physical properties such as sound speed contrast (h) and density contrast (g) of the interested target are key parameters to understand acoustic characteristics by using theoretical scattering models. The density and sound speed of moon jellyfish (common jellyfish, Aurelia aurita s.l.) were measured. Sound speed contrast (h) was measured from travel time difference (time-of-flight method) of an acoustic signal in a water tank for APOP studies (Acoustic Properties Of zooplankton). Density contrast (g) was measured by the displacement volume and wet weight (dual-density method). The sound speed remained almost constant as the moon jellyfish increased in bell length. The mean values${\pm}$standard deviation of h and g were $1.0005{\pm}0.0012$ and $0.9808{\pm}0.0195$), respectively. These results will provide important input for use in theoretical scattering models for estimating the acoustic target strength of jellyfish.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.8
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• pp.1777-1783
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• 2013

We do research on the simulation of Doppler effect from a target's moving under the sea by Transmission Line Matrix modeling which is one of numerical methods on time domain. To implement the effect, the input signal was entered at a moving node according to a moving target's moving speed. The result had maximum 2.47% error compared with the theoretical value. And from simulation results with speed control of a moving target, we could also obtain resonable results within 0.63% error range.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.1
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• pp.108-114
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• 2014

This paper describes a method to set an intensity-based initial validation gate for tracking filter while preserves the ability of tracking a target with maximum speed. First, we collected real data set of signal versus distance of an airplane target. And at each data point, we computed maximum distance the target can move. And a function is modeled to expect the maximum moving pixels on the lateral direction based on the intensity of the detected target in IR image sequence. The initial prediction error covariance can be computed using this function to decide the size of the initial validation gate. The simulation results show the proposed method can set the appropriate initial validation gates to track the targets with the maximum speed.

• Investigative Magnetic Resonance Imaging
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• v.25 no.1
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• pp.10-22
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• 2021

Purpose: To overcome the difficulty in building a large data set with a high-quality in medical imaging, a concept of 'blended-transfer learning' (BTL) using a combination of both source data and target data is proposed for the target task. Materials and Methods: Source and target tasks were defined as training of the source and target networks to reconstruct cardiac CINE images from undersampled data, respectively. In transfer learning (TL), the entire neural network (NN) or some parts of the NN after conducting a source task using an open data set was adopted in the target network as the initial network to improve the learning speed and the performance of the target task. Using BTL, an NN effectively learned the target data while preserving knowledge from the source data to the maximum extent possible. The ratio of the source data to the target data was reduced stepwise from 1 in the initial stage to 0 in the final stage. Results: NN that performed BTL showed an improved performance compared to those that performed TL or standalone learning (SL). Generalization of NN was also better achieved. The learning curve was evaluated using normalized mean square error (NMSE) of reconstructed images for both target data and source data. BTL reduced the learning time by 1.25 to 100 times and provided better image quality. Its NMSE was 3% to 8% lower than with SL. Conclusion: The NN that performed the proposed BTL showed the best performance in terms of learning speed and learning curve. It also showed the highest reconstructed-image quality with the lowest NMSE for the test data set. Thus, BTL is an effective way of learning for NNs in the medical-imaging domain where both quality and quantity of data are always limited.

• The Journal of the Korea Contents Association
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• v.20 no.4
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• pp.25-37
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• 2020

As social costs of traffic congestion increase, various studies are underway to predict road speed. In order to improve the accuracy of road speed prediction, unexpected traffic situations need to be considered. In this paper, we propose a road speed prediction scheme considering traffic incidents affecting road speed. We use not only the speed data of the target road but also the speed data of the connected roads to reflect the impact of the connected roads. We also analyze the amount of speed change to predict the traffic congestion caused by traffic incidents. We use the speed data of connected roads and target road with input data to predict road speed in the first place. To reduce the prediction error caused by breaking the regular road flow due to traffic incidents, we predict the final road speed by applying event weights. It is shown through various performance evaluations that the proposed method outperforms the existing methods.

• Proceedings of the Korean Vacuum Society Conference
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• 2016.02a
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• pp.140.1-140.1
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• 2016

We have measured DNA translocation through a nanocapillary functionalized with probe DNA. These DNA-functionalized nanocapillaries selectively facilitate the translocation of target ssDNAs that are complementary to the probe ssDNAs. In addition, translocation of the complementary target ssDNA exhibits two tendencies to translocation speed, such as fast and slow translocation, whereas that of non-complementary target ssDNA yields only one tendency, fast translocation. These observations suggest that the complementary and non-complementary target ssDNAs may be discriminated due to different interaction strengths between target and probe ssDNAs. The temperature dependence measurements of DNA translocation show that slow translocation events are ascribed to the complementary interaction between probe and target ssDNA. This confirms that their dwell time is dependent on the base-pair binding strength. These results demonstrate that mere single-base different target DNA can be selectively detectable by using the probe DNA-functionalized nanocapillaries.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.550-553
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• 2005

To acquire radar target signature, various kinds of target are necessary. Measurement is one of the data acquiring method, but much time and high cost is required to get the target data from the real targets. Even if we can afford that, the targets we can access are very limited. To obtain target signatures avoiding these problems, we build the target CAD (Computer Aided Design) model for the calculation of target signatures. To speed up RCS calculation, we applied adaptive super-sampling and tested quite complex tank CAD model which is 1.4 hundred of thousands facet. We use calculated RCS data for ID range profile and 2D ISAR (Inverse Synthetic Aperture Radar) image formation. We adopted IFFT (Inverse Fast Fourier Transform) algorithm combined with polar formatting algorithm for the ISAR imaging. We could confirm the possibility of the construction of database from the images of CAD models for target classification applications.

• Journal of Sensor Science and Technology
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• v.28 no.6
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• pp.414-419
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• 2019

An ultrasonic based magnetostrictive position sensor (MPS) provides an indication of real target position. It determines the real target position by multiplying the propagation speed of ultrasonic wave and the time-of-flight between the receiving signals; one is the initial signal by an excitation current and the other is the reflection signal by the ultrasonic wave. The propagation speed of the ultrasonic wave depends on the temperature of the waveguide. Hence, the change of the propagation speed in various environments is a critical factor in terms of the positioning accuracy in the MPS. This means that the influence of the changes in the waveguide temperature needs to be compensated. In this paper, we presents a novel way to improve the positioning accuracy of MPSs using temperature compensation for waveguide. The proposed method used the inherent measurement blind area for the structure of the MPS, which can simultaneously measure the position of the moving target and the temperature of the waveguide without any additional devices. The average positional error was approximately -23.9 mm and -1.9 mm before and after compensation, respectively. It was confirmed that the positioning accuracy was improved by approximately 93%.