• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.15 no.5
• /
• pp.116-124
• /
• 2016

This paper proposes a medium access control protocol for collision detection and resolution when a large number of sensor nodes transmits data in vehicle. The proposed protocol selects a random collision detection (CD) slot after data transmission, suspends its transmission and senses the channel to check whether a collision occurs by the detection of both energy level and jam signal. The proposed scheme uses multiple CD phases and in each CD phase, colliding stations are filtered and only surviving stations compete again in the next CD phase; thus, the collision resolution probability significantly increases. Simulation results show that the proposed protocol using the multiple CD phases has significantly better throughput than the conventional protocol. In addition, according to the number of CD phases and the number of CD slots per phase, the throughput aspect of the proposed scheme is investigated and the optimal parameters are derived.

• Journal of IKEEE
• /
• v.24 no.1
• /
• pp.147-153
• /
• 2020

Conventional lane detection algorithms have problems in that the detection rate is lowered in road environments having a large change in curvature and illumination. The probabilistic Hough transform method has low lane detection rate since it exploits edges and restrictive angles. On the other hand, the method using a sliding window can detect a curved lane as the lane is detected by dividing the image into windows. However, the detection rate of this method is affected by road slopes because it uses affine transformation. In order to detect lanes robustly and avoid obstacles, we propose driving assist system using semantic segmentation based on deep learning. The architecture for segmentation is SegNet based on VGG-16. The semantic image segmentation feature can be used to calculate safety space and predict collisions so that we control a vehicle using adaptive-MPC to avoid objects and keep lanes. Simulation results with CARLA show that the proposed algorithm detects lanes robustly and avoids unknown obstacles in front of vehicle.

• The Journal of Korean Institute of Information Technology
• /
• v.16 no.11
• /
• pp.97-103
• /
• 2018

In this paper, the estimation method for the power signal harmonics is proposed by using the time-varying optimal finite impulse response (FIR) filter. To estimate the magnitude and phase-angle of the harmonic components, the time-varying optimal FIR filter is designed for the state space representation of the noisy power signal which the magnitude and phase is considered as a stochastic process. Since the time-varying optimal FIR filter used in the proposed method does not use any priori information of the initial condition and has FIR structure, the proposed method could overcome the demerits of Kalman filter based method such as poor estimation and divergence problem. Due to the FIR structure, the proposed method is more robust against to the model uncertainty than the Kalman filter. Moreover, the proposed method gives more general solution than the time-invariant optimal FIR filter based harmonic estimation method. To verify the performance and robustness of the proposed method, the proposed method is compared with time-varying Kalman filter based method through simulation.

• The Journal of the Acoustical Society of Korea
• /
• v.28 no.4
• /
• pp.401-407
• /
• 2009

In this paper, we propose a novel method for the cross-correlation based double-talk detection (DTD), which employing the Gaussian Mixture Model (GMM) in the frequency domain. The proposed algorithm transforms the cross correlation coefficient used in the time domain into 16 channels in the frequency domain using the discrete fourier transform (DFT). The channels are then selected into seven feature vectors for GMM and we identify three different regions such as far-end, double-talk and near-end speech using the likelihood comparison based on those feature vectors. The presented DTD algorithm detects efficiently the double-talk regions without Voice Activity Detector which has been used in conventional cross correlation based double-talk detection. The performance of the proposed algorithm is evaluated under various conditions and yields better results compared with the conventional schemes. especially, show the robustness against detection errors resulting from the background noises or echo path change which one of the key issues in practical DTD.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.24 no.7B
• /
• pp.1351-1360
• /
• 1999

In frequency selective channels, conventional PN code acquisition schemes are not ideal candidates. This is because they are primarily designed for the AWGN channel. In this paper, a direct-sequence spread-spectrum(DSSS) PN code acquisition system based on digital matched filtering (DMF) with automatic threshold control(ATC) algorithm is presented and analyzed with regards to probability of detection and probability of false alarm. These two important probabilities, the probability of detection ($P_D$) and the probability of false alarm ($P_{FA}$) are derived and analyzed in considering Doppler shift, sampling rate, mean acquisition time, and PN chip rate in frequency selective Rayleigh fading channel when using serial-search method as detection technique. From computer simulation results of a DMF acquisition system model, it is shown that the performance of the acquisition system using ATC algorithm is better than that of constant threshold system.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.17 no.3
• /
• pp.162-173
• /
• 1997

Automatic on-line surface inspection systems have been applied for monitoring a quality of steel strip surfaces. One of the important issues in this application is the performance of on-line defect classifiers. Rule-based classification table methods which are conventionally used for this purpose have been suffered from their low performances. In this work, probabilistic neural networks and the enhanced classification tables which are newly proposed here are applied as alternative on-line classifiers to identify types of surface defects on cold rolled strips. Probabilistic neural networks have shown very excellent performance for classification of surface defects.

• Journal of Convergence for Information Technology
• /
• v.11 no.11
• /
• pp.31-37
• /
• 2021

In this paper, we propose an outlier detection algorithm called C-SCGP to prevent the degradation of localization performance based on RSS (Received Signal Strength) and AOA (Angle of Arrival) in the presence of outliers in wireless sensor networks. Since the accuracy of target estimation can significantly deteriorate due to various cause of outliers such as malfunction of sensor, jamming, and severe noise, it is important to detect and filter out all outliers. The single cluster graph partitioning (SCGP) algorithm has been widely used to remove such outliers. The proposed continuous-SCGP (C-SCGP) algorithm overcomes the weakness of the SCGP that requires the threshold and computing probability of outliers, which are impratical in many applications. The results of numerical simulations show that the performance of C-SCGP without setting threshold and probability computation is the same performance of SCGP.

• Proceedings of the KIEE Conference
• /
• 2011.07a
• /
• pp.2005-2006
• /
• 2011

Due to the advantages of small sizes, more I/O ports, etc., Ball Grid Array (BGA) has been used in the production of printed circuit board (PCB). However, BGA voids can degrade the performance of the board and cause failure. To automatically detect the voids in X-ray image, a novel blob filter that makes use of the local image gradient magnitude is proposed in this paper. The utilization of the local image gradient magnitude makes the proposed filter invariant to the image brightness, void shape, void position, and component interference. Furthermore, different sizes of box filters are employed to analyze the image in multi-scale, and as a result, the proposed blob filter is robust to void size. Experimental results show that the proposed method can obtain void detection accuracy up to 96.104% while keep low false ratio.

• The Journal of the Acoustical Society of Korea
• /
• v.26 no.8
• /
• pp.397-402
• /
• 2007

In this paper, we apply a support vector machine(SVM) that incorporates an optimized nonlinear decision rule over different sets of feature vectors to improve the performance of statistical model-based voice activity detection(VAD). Conventional method performs VAD through setting up statistical models for each case of speech absence and presence assumption and comparing the geometric mean of the likelihood ratio (LR) for the individual frequency band extracted from input signal with the given threshold. We propose a novel VAD technique based on SVM by treating the LRs computed in each frequency bin as the elements of feature vector to minimize classification error probability instead of the conventional decision rule using geometric mean. As a result of experiments, the performance of SVM-based VAD using the proposed feature has shown better results compared with those of reported VADs in various noise environments.

• The Journal of the Acoustical Society of Korea
• /
• v.26 no.1
• /
• pp.16-24
• /
• 2007

Voice activity detectors (VADs) are important in wireless communication and speech signal processing. In the conventional VAD methods. an expression for the likelihood ratio test (LRT) based on statistical models is derived. Then, speech or noise is decided by comparing the value of the expression with a threshold. We propose a new method with the modified decision rule based on the Gaussian distribution and the uniformly most power (UMP) test. This method requires the distribution of the absolute value of the incoming speech signal. Then we can obtain the final decision through the relation between the Rayleigh distributions. This VAD method can detect speech without a priori signal-to-noise ratio (SNR) which is required in the conventional VAD algorithms. Additionally, in the various VAD performance tests, the proposed VAD method is shown to be more effective than the traditional scheme.