• The Journal of the Acoustical Society of Korea
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• v.38 no.3
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• pp.302-307
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• 2019

In modern Anti-Submarine Warfare, there are various ways to locate a submarine in a two-dimensional space. For more effective tracking and attack against a submarine the depth of the target is a critical factor. However, it has been difficult to find out the depth of a submarine until now. In this paper a possible solution to the depth estimation of submarines is proposed utilizing DIFAR (Directional Frequency Analysis and Recording) sonobuoy information such as contact bearings at or prior to CPA (Closest Point of Approach) and the target's Doppler signals. The relative depth of the target is determined by applying the Pythagorean theorem to the slant range and horizontal range between the target and the hydrophone of a DIFAR sonobuoy. The slant range is calculated using the Doppler shift and the target's velocity. the horizontal range can be obtained by applying a simple trigonometric function for two consecutive contact bearings and the travel distance of the target. The simulation results show that the algorithm is subject to an elevation angle, which is determined by the relative depth and horizontal distance between the sonobuoy and target, and that a precise measurement of the Doppler shift is crucial.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1424-1436
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• 2020

Although huge progress has been made in current image segmentation work, there are still no efficient segmentation strategies for tree image which is taken from natural environment and contains complex background. To improve those problems, we propose a method for tree image segmentation combining adaptive mean shifting with image abstraction. Our approach perform better than others because it focuses mainly on the background of image and characteristics of the tree itself. First, we abstract the original tree image using bilateral filtering and image pyramid from multiple perspectives, which can reduce the influence of the background and tree canopy gaps on clustering. Spatial location and gray scale features are obtained by step detection and the insertion rule method, respectively. Bandwidths calculated by spatial location and gray scale features are then used to determine the size of the Gaussian kernel function and in the mean shift clustering. Furthermore, the flood fill method is employed to fill the results of clustering and highlight the region of interest. To prove the effectiveness of tree image abstractions on image clustering, we compared different abstraction levels and achieved the optimal clustering results. For our algorithm, the average segmentation accuracy (SA), over-segmentation rate (OR), and under-segmentation rate (UR) of the crown are 91.21%, 3.54%, and 9.85%, respectively. The average values of the trunk are 92.78%, 8.16%, and 7.93%, respectively. Comparing the results of our method experimentally with other popular tree image segmentation methods, our segmentation method get rid of human interaction and shows higher SA. Meanwhile, this work shows a promising application prospect on visual reconstruction and factors measurement of tree.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.2
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• pp.73-78
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• 2023

The dining philosophers problem(DPP) is that five philosophers sit around a round table and eat spaghetti(or noodles) together, where they must have a pair of chopsticks(two) on both sides of them to eat, and if all philosophers have one chopstick on the right, no one can eat because the deadlock occurs. Deadlocks are a problem that frequently occur in parallel systems, and most current operating systems(OS) cannot prevent it. This paper proposes a silver bullet that causes no deadlock in an OS where all processors of 2≤n≤∞ have multiple parallel processing capabilities. The proposed method is a group round-robin method in which ⌊n/2⌋ odd processors form a group and perform simultaneously, and shift right to the next processor when execution ends. The proposed method is to perform two times for even processors, three times for odd processors per one round-robin. If the proposed method is performed n times, even-numbered processors perform n/2 times and odd-numbered processors perform (n-1)/2-times.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.1-8
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• 2023

An Orthogonal Frequency Division Multiplexing (OFDM) based wireless communication system has drawn wide attention for its high transmission rate and high spectrum efficiency in not only radio but also Underwater Acoustic (UWA) applications. Because of the narrow sub-carrier spacing of OFDM, orthogonality between sub-carriers is easily affected by Doppler effect caused by the movement of transmitter or receiver. Previously, Doppler compensation signal processing algorithm for Desired propagation path was proposed. However, other Doppler shifts caused by delayed Undesired signal arriving from different directions cannot be perfectly compensated. Then Receiver Bit Error Rate (BER) is degraded by Inter-Carrier-Interference (ICI) caused in the case of Multi-path Doppler channel. To mitigate the ICI effect, a modified Delay and Doppler Profiler (mDDP), which estimates not only attenuation, relative delay and Doppler shift but also sampling clock shift of each multi-path component, is proposed. Based on the outputs of mDDP, an ICI canceling multi-tap equalizer is also proposed. Computer simulated performances of one-tap equalizer with the conventional Time domain linear interpolated Channel Transfer Function (CTF) estimator, multi-tap equalizer based on mDDP are compared. According to the simulation results, BER improvement has been observed. Especially, in the condition of 16QAM modulation, transmitting vessel speed of 6m/s, two-path multipath channel with direct path and ocean surface reflection path; more than one order of magnitude BER reduction has been observed at CNR=30dB.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.4C
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• pp.215-222
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• 2005

In this paper, we propose a fingerprint verification algorithm for the embedded system based on the minutia extracted using the image quality, the minutia structure, and the Sequency and the orientation of ridges. After the pre- and the post-processing, the true minutia are selected, thus it shows high reliability in the fingerprint verification. In matching process, we consider the errors caused by shift, rotation, and pressure when acquiring the fingerprint image and reduce the matching time by applying a local matching instead of a full matching to select the reference pair. The proposed algorithm has been designed and verified in Arm920T environment and various techniques for the realtime process have been applied. Time taken from the fingerprint registration through out the matching is 0.541 second that is relevant for the realtime applications. The FRR (False Reject Rate) and FAR (False Accept Rate) show 0.079 and 0.00005 respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.12A
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• pp.998-1005
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• 2009

In the uplink of OFDMA (Orthogonal Frequency Division Multiple Access) based M-WiMAX(Mobile-Worldwide Interoperability for Microwave Access) system, linear phase shift is caused by signals transmitted from multiuser with different delay time and thus, MAI (Multiple Access Interference) occurs. MAI degrades the performance of ranging code detection and delay time estimation in the uplink. Therefore, in this paper, we propose ranging algorithm, applying SIC (Successive Interference Cancellation) to the conventional ranging algorithm, to minimize MAI and to improve ranging performance. The proposed ranging algorithm is verified through the Monte Carlo simulation, which shows the improved performance of ranging code detection and delay time estimation compared to the conventional algorithms. Through compared with random access of the 3GPP LTE, we can know limit of ranging performance.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.101-106
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• 2020

This paper relates with the VS-QE-MMA (Varying Stepsize-Quantized Error-MMA) based on the varying stepsize for improving the equalization performance in the QE-MMA adaptive equalization algorithm that is possible to reducing the intersymbol interference occurred at channel. The SE-MMA use the high-order statistics of transmitted signal and sign of error signal. The QE-MMA was appeared for the H/W implementation easiness substitutes the multiplication and substraction into the shift and substraction in the updating the tap coefficient based on the power-of-two operation of error signal magnitude. The QE-MMA gives degradation of equalization performance due to the such simplification of arithmetic operation. For improving this problem, the propose algorithm, namely VS-QE-MMA, applies the varying stepsize of the nonlinear transformation of error signal. It was confirmed by simulation that the VS-QE-MMA gives better performance than current QE-MMA in the same channel and signal to noise ratio. As a result of simulation, the VS-QE-MMA has more better performance in the every performance index, and it was also confirmed that the varying stepsize effect can be obtained in the greater than 10dB of signal to noise ratio.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.142-145
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• 2005

Since the successful launch of FORMOSAT -2 satellite by National Space Organization of Taiwan in May 2004, the Remote Sensing Instrument (RSI) on- board the FORMOSAT -2 has continuously acquired images at one panchromatic and four multi-spectral bands (http://www.nspo.org.tw). In general, the RSI performs well and receives high quality images which proved to be very useful for various applications. However, some RSI panchromatic products exhibit obvious trembling artifact that must be removed. Preliminary study reveals that the trembling artifact is caused by the instability of the spacecraft attitude. Though the magnitude of this artifact is actually less than half of a pixel, it affects the applicability of panchromatic products. A procedure removing this artifact is therefore needed for providing image products of consistent quality. Due to the nature of trembling artifact, it is impossible to describe the trembling amount by employing an analytic model. Relied only on image itself, an algorithm determining trembling amount and removing accordingly the trembling artifact is proposed. The algorithm consists of 3 stages. First, a cross-correlation based scheme is used to measure the relative shift between adjacent scan lines. Follows, the trembling amount is estimated from the measured value. For this purpose, the Fourier transform is utilized to characterize random shifts in frequency domain. An adaptive estimation method is then applied to deduce the approximate trembling amount. In the subsequent stage, image re-sampling operation is applied to restore the trembling-free product. Experimental results show that by applying the proposed algorithm, the unpleasant trembling artifact is no longer evident.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.7
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• pp.560-570
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• 2017

Recently, well-known SAR imaging algorithms have been developed to form the focused SAR images for stationary targets. In general, the conventional methods exploit the range variation only defined by the motion of radar platform and SAR geometry. However, for SAR imaging of ground moving targets, the motion of the targets induces an additional range shift, yielding the blurred SAR images. To overcome the problem, in this paper we propose an effective motion compensation algorithm operated under a multi-channel SAR, named along-track interferometry(ATI) and phase unwrapping to directly estimate the motion parameters of the targets. In simulations, 50 Monte-Carlo simulation results show the effectiveness of the algorithm in the presence of noise.

• Journal of Advanced Navigation Technology
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• v.16 no.3
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• pp.545-552
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• 2012

In this paper, we propose Modified Multi CAMShift Algorithm based on Kalman filter and Weighted Search Windows(KWMCAMShift) that extracts skin color area and tracks several human body parts for real-time human tracking system. We propose modified CAMShift algorithm that generates background model, extracts skin area of hands and head, and tracks the body parts. Kalman filter stabilizes tracking search window of skin area due to changing skin area in consecutive frames. Each occlusion areas is avoided by using weighted window of non-search areas and main-search area. And shadows are eliminated from background model and intensity of shadow. The proposed KWMCAMShift algorithm can estimate human pose in real-time and achieves 96.82% accuracy even in the case of occlusions.