• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.1
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• pp.69-76
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• 2015

In this paper, we propose and analyze a M-ary transmission scheme in time hopping ultra-wide band(UWB) system using mutually orthogonal modified Hermite polynomial(MHP) pulses. The proposed M-ary transmission scheme employs the orthogonal property between different ordered pulses and N data bits make the M-ary signals by linear combination of M MHP pluses. The theoretical analysis and simulation results show that the proposed system has better performance and higher data rate than conventional M-ary UWB system. We derive the general form of correlation function for MHP pulses and analyze bit error rate(BER) performance over additive white Gaussian noise(AWGN) with the presence of timing jitter. We show that the proposed system has the improved BER performance and robustness to timing jitter and low power spectrum density compared with conventional M-ary UWB system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.3965-3982
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• 2015

Event detection is one of the key issues in many wireless sensor network (WSN) applications. The uncertainties that are derived from the instability of sensor node, measurement noise and incomplete sampling would influence the performance of event detection to a large degree. Many of the present researches described the sensor readings with crisp values, which cannot adequately handle the uncertainties inhered in the imprecise sensor readings. In this paper, a fault-tolerant event detection algorithm is proposed based on Dempster-Shafer (D-S) theory (also called evidence theory). Instead of crisp values, all possible states of the event are represented by the Basic Probability Assignment (BPA) functions, with which the output of each sensor node are characterized as weighted evidences. The combination rule was subsequently applied on each sensor node to fuse the evidences gathered from the neighboring nodes to make the final decision on whether the event occurs. Simulation results show that even 20% nodes are faulty, the accuracy of the proposed algorithm is around 80% for event region detection. Moreover, 97% of the error readings have been corrected, and an improved detection capability at the boundary of the event region is gained by 75%. The proposed algorithm can enhance the detection accuracy of the event region even in high error-rate environment, which reflects good reliability and robustness. The proposed algorithm is also applicable to boundary detection as it performs well at the boundary of the event.

• Journal of Korea Multimedia Society
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• v.11 no.4
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• pp.434-442
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• 2008

The parallel beam SPECT acquires projection data by using parallel hole collimators in conjunction with photon detectors. Those projection data of the parallel beam SPECT are, however, contaminated by the distance dependent blurring because of the inaccuracy of the point response function of the collimator that is used to define the range of directions where photons can be detected. Thus an efficient aperture correction is required. In this paper we propose a distance dependent backprojection method to overcome the time limitation of iterative aperture correction methods and the performance limitation of Fourier-Distance Relation based method. The proposed method achieves aperture correction and fast image reconstruction by replacing the distance independent backprojection of the direct image reconstruction with the distance dependent one. We conducted several simulations to compare the performance of the proposed method with that of the conventional Fourier-Distance Relation based method. The simulation result shows that the proposed method outperforms the Fourier-Distance Relation based method in spatial resolution and robustness against noise.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.107-113
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• 2019

This paper proposes the Hybrid-CRMMA adaptive equalization algorithm that is possible to improves the performance of CR-MMA based on adaptive modulus and adaptive stepsize. The 16-QAM nonconstant modulus signal is reduced to 4-QAM constant modulus signal, and the error signal were obtained based on the fixed statistic modulus of transmitted signal. It is possible to improving the currently MMA adaptive equalization performance. The proposed Hybrid-CRMMA composed of adaptive modulus which is propotional to the power of equalizer output and adaptive stepsize which is function of the nonlinearties of error signal, and its improved equalization performance were confirmed by computer simulation. For this purpose, the output signal constellation, the residual isi and maximum distortion and MSE that is for the convergence characteristics, the SER that is meaning the robustness of external noise of algorithm were used. As a result of computer simulation, it was confirmed that the proposed Hybrid-CRMMA has more superior performance in every index compared to currently CR-MMA.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.79-84
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• 2019

This paper compare the performance of CM-MMA (Constellation Matching-MMA) and RMMA (Region-based MMA) blind equalization algorithm for improve the QoS by minimizing the intersymbol interference that is occurred in nonlinear communication channel when transmitting the QAM signal. In the tap coefficient update for adaptive, CM-MMA use the error of nonconstant modulus signal adding the current MMA cost fuction and constellation matching error terms of sinusoidal power function, and the RMMA use the error by transfoms the nonconstant modulus signal of equalizer output constellation to 4-QAM constant modulus signal. They has different equalization performance by these error signal, it were compared in this paper by simulation, and performance index such as output signal constellation of equalizer, residual isi, maximum distortion, SER curves are applied for this. As a result of computer simulation, the RMMA has more better performance in the every performance index, convergence speed, residual value, noise robustness compared to CM-MMA.

• Structural Engineering and Mechanics
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• v.71 no.4
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• pp.391-405
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• 2019

Compared to the ambient vibration test mainly identifying the structural modal parameters, such as frequency, damping and mode shapes, the impact testing, which benefits from measuring both impacting forces and structural responses, has the merit to identify not only the structural modal parameters but also more detailed structural parameters, in particular flexibility. However, in traditional impact tests, an impacting hammer or artificial excitation device is employed, which restricts the efficiency of tests on various bridge structures. To resolve this problem, we propose a new method whereby a moving vehicle is taken as a continuous exciter and develop a corresponding flexibility identification theory, in which the continuous wheel forces induced by the moving vehicle is considered as structural input and the acceleration response of the bridge as the output, thus a structural flexibility matrix can be identified and then structural deflections of the bridge under arbitrary static loads can be predicted. The proposed method is more convenient, time-saving and cost-effective compared with traditional impact tests. However, because the proposed test produces a spatially continuous force while classical impact forces are spatially discrete, a new flexibility identification theory is required, and a novel structural identification method involving with equivalent load distribution, the enhanced Frequency Response Function (eFRFs) construction and modal scaling factor identification is proposed to make use of the continuous excitation force to identify the basic modal parameters as well as the structural flexibility. Laboratory and numerical examples are given, which validate the effectiveness of the proposed method. Furthermore, parametric analysis including road roughness, vehicle speed, vehicle weight, vehicle's stiffness and damping are conducted and the results obtained demonstrate that the developed method has strong robustness except that the relative error increases with the increase of measurement noise.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.143-151
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• 2021

The enormous prevalence of transferring official confidential digital documents via the Internet shows the urgent need to deliver confidential messages to the recipient without letting any unauthorized person to know contents of the secret messages or detect there existence . Several Steganography techniques such as the least significant Bit (LSB), Secure Cover Selection (SCS), Discrete Cosine Transform (DCT) and Palette Based (PB) were applied to prevent any intruder from analyzing and getting the secret transferred message. The utilized steganography methods should defiance the challenges of Steganalysis techniques in term of analysis and detection. This paper presents a novel and robust framework for color image steganography that combines Linear Congruential Generator (LCG), simulated annealing (SA), Cesar cryptography and LSB substitution method in one system in order to reduce the objection of Steganalysis and deliver data securely to their destination. SA with the support of LCG finds out the optimal minimum sniffing path inside a cover color image (RGB) then the confidential message will be encrypt and embedded within the RGB image path as a host medium by using Cesar and LSB procedures. Embedding and extraction processes of secret message require a common knowledge between sender and receiver; that knowledge are represented by SA initialization parameters, LCG seed, Cesar key agreement and secret message length. Steganalysis intruder will not understand or detect the secret message inside the host image without the correct knowledge about the manipulation process. The constructed system satisfies the main requirements of image steganography in term of robustness against confidential message extraction, high quality visual appearance, little mean square error (MSE) and high peak signal noise ratio (PSNR).

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.27-34
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• 2021

In this paper, we propose a copyright protection scheme for real-time streaming of HEVC(High Efficiency Video Coding) based realistic content. Previous research uses encryption and modular operation for copyright pre-protection and copyright post-protection, which causes delays in ultra high resolution video. The proposed scheme maximizes parallelism by using thread pool based DRM(Digital Rights Management) packaging with only HEVC's CABAC(Context Adaptive Binary Arithmetic Coding) codec and GPU based high-speed bit operation(XOR), thus enabling real-time copyright protection. As a result of comparing this scheme with previous research at three resolutions, PSNR showed an average of 8 times higher performance, and the process speed showed an average of 18 times difference. In addition, as a result of comparing the robustness of the forensic mark, the filter and noise attack, which showed the largest and smallest difference, with a 27-fold difference in recompression attacks, showed an 8-fold difference.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.313-330
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• 2021

In an autonomous driving system equipped with a camera and lidar, depth completion techniques enable dense depth estimation. In particular, using self-supervised learning it is possible to train the depth completion network even without ground truth. In actual autonomous driving, such depth completion should have very short latency as it is the input of other algorithms. So, rather than complicate the network structure to increase the accuracy like previous studies, this paper focuses on network latency. We design a U-Net type network with RegNet encoders optimized for GPU computation. Instead, this paper presents several techniques that can increase accuracy during the process of self-supervised learning. The proposed techniques increase the robustness to unreliable lidar inputs. Also, they improve the depth quality for edge and sky regions based on the semantic information extracted in advance. Our experiments confirm that our model is very lightweight (2.42 ms at 1280x480) but resistant to noise and has qualities close to the latest studies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4292-4307
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• 2021

For the research field of night infrared surveillance video, the target imaging in the video is easily affected by the light due to the characteristics of the active infrared camera and the classical ViBe algorithm has some problems for moving target extraction because of background misjudgment, noise interference, ghost shadow and so on. Therefore, an improved ViBe algorithm (I-ViBe) for moving target extraction in night infrared surveillance video is proposed in this paper. Firstly, the video frames are sampled and judged by the degree of light influence, and the video frame is divided into three situations: no light change, small light change, and severe light change. Secondly, the ViBe algorithm is extracted the moving target when there is no light change. The segmentation factor of the ViBe algorithm is adaptively changed to reduce the impact of the light on the ViBe algorithm when the light change is small. The moving target is extracted using the region growing algorithm improved by the image entropy in the differential image of the current frame and the background model when the illumination changes drastically. Based on the results of the simulation, the I-ViBe algorithm proposed has better robustness to the influence of illumination. When extracting moving targets at night the I-ViBe algorithm can make target extraction more accurate and provide more effective data for further night behavior recognition and target tracking.