• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.1
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• pp.8-15
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• 2011

This paper presents an effective method for detecting vehicles in front of the camera-assisted car during nighttime driving. The proposed method detects vehicles based on detecting vehicle headlights and taillights using techniques of image segmentation and clustering. First, in order to effectively extract spotlight of interest, a pre-signal-processing process based on camera lens filter and labeling method is applied on road-scene images. Second, to spatial clustering vehicle of detecting lamps, a grouping process use light tracking method and locating vehicle lighting patterns. For simulation, we are implemented through Da-vinci 7437 DSP board with visible light mono-camera and tested it in urban and rural roads. Through the test, classification performances are above 89% of precision rate and 94% of recall rate evaluated on real-time environment.

• Smart Media Journal
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• v.13 no.1
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• pp.45-51
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• 2024

Long Range Wide Area Network (LoRaWAN) is a widely adopted Internet of Things (IoT) protocol due to its high range and lower energy consumption. LoRaWAN utilizes Adaptive Data Rate (ADR) for efficient resource (e.g., spreading factor and transmission power) management. The ADR manages these two resource parameters on the network server side and end device side. This paper focuses on analyzing the ADR and Gaussian ADR performance of LoRaWAN. We have performed NS3 simulation under a static scenario by varying the antenna height. The simulation results showed that antenna height has a significant impact on the packet delivery ratio. Higher antenna height (e.g., 50 m) has shown an improved packet success ratio when compared with lower antenna height (e.g., 10 m) in static and mobility scenarios. Based on the results, it is suggested to use the antenna at higher allevation for successful packet delivery.

• Journal of Broadcast Engineering
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• v.23 no.1
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• pp.104-114
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• 2018

Recently, as HTTP-based video streaming traffic continues to increase, Dynamic Adaptive Streaming over HTTP(DASH), which is one of the HTTP-based adaptive streaming(HAS) technologies, is receiving attention. Accordingly, many video quality control techniques have been proposed to provide a high quality of experience(QoE) to clients in a DASH environment. In this paper, we propose a new quality control method using ANFIS(Adaptive Network based Fuzzy Inference System) which is one of the neuro-fuzzy system structure. By using ANFIS, the proposed scheme can find fuzzy parameters that selects the appropriate segment bitrate for clients. Also, considering the characteristic of VBR video, the next segment download time can be more accurately predicted using the actual size of the segment. And, by using this, it adjusts video quality appropriately in the time-varying network. In the simulation using NS-3, we show that the proposed scheme shows higher average segment bitrate and lower number of bitrate-switching than the existing methods and provides improved QoE to the clients.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12A
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• pp.1182-1188
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• 2006

Adaptive OFDM(Orthogonal Frequency Division Multiplexing) improves data capacity and system performance over multipath fading by adaptively changing modulation schemes according to channel state information(CSI). To achieve a good performance in adaptive OFDM systems, CSI should be transmitted from receiver to transmitter in real time through feedback channel. However, practically, the CSI feedback delay d which is the sum of the data processing delay and the propagation delay is not negligible and damages to the reliability of CSI such that the performance of adaptive OFDM is degraded. This paper presents an adaptive OFDM system with a multistep predictor on the frequency axis to effectively compensate the multiple feedback delays $d(\geq2)$. Via computer simulation we compare the proposed scheme and existing adaptive OFDM schemes with respect to data capacity and system performance.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.97-105
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• 2015

Content-adaptive steganography methods embed secret messages in hard-to-model regions of covers such as complicated texture or noisy area. Content-adaptive steganalysis methods often need high dimensional features to capture more subtle relationships of local dependencies among adjacent pixels. However, these methods require many computational complexity and depend on the location of hidden message and the exploited distortion metrics. In this paper, we propose an improved steganalysis method for content-adaptive steganography to enhance detection rate with small number features. We first show that the features form the difference between DCT coefficients are useful for analyzing the content-adaptive steganography methods, and present feature extraction mehtod using first-order Markov probability for the the difference between DCT coefficients. The extracted features are used as input of ensemble classifier. Experimental results show that the proposed method outperforms previous schemes in terms of detection rates and accuracy in spite of a small number features in various content-adaptive stego images.

• Journal of the Institute of Convergence Signal Processing
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• v.1 no.1
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• pp.7-14
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• 2000

Recently, the technologies of adaptive noise cancellation(ANC) are developed fast and widely due to the highly sophisticated digital signal processing algorithms and the high-speed communication networks and devices. But, thousand numbers of the adaptive filter taps are required to obtain the satisfying results in the fields of the adaptive noise cancellation and echo cancellation. In the paper, performance comparisons based on the real-time processing between frequency domain adaptive filter(FDAF) and multi-delay frequency domain adaptive filter(MDF) are carried. Those algorithms provide us with the reductions of the computational burdens and the increase of the convergence rate for the lengthy Fill adaptive filters. The time delay due to the long taps of FDAF can be reduced by adopting the MDF algorithms. The conventional ANC and cross talks ANC using FDAF are implemented on the dSP ACE 1103 real-time signal processing board.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.8B
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• pp.1493-1498
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• 2000

In this paper, we introduce a modified interference cancellation scheme to overcome MAI in DS-CDMA. Among ICs(Interference Cancellers), PIC(Parallel IC) requires the more complexity, and SIC(Successive IC) faces the problems of the long delay time. Most of all, the adaptive detector achieves the good BER performance using the adaptive filter conducted iteration algorithm. so it requires many iterations. To resolve the problems of them, we propose an improved adaptive detector that the received signal removed MAI through the sorting scheme and the cancellation method are fed into the adaptive filter. Because the improved input signal is fed into the adaptive filter, it has the same BER performance only using smaller iterations than the conventional adaptive detector, and the proposed detector having adaptive filter requires less complexity than the other detectors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4A
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• pp.370-377
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• 2004

In this paper, we present an adaptive modulation technique for orthogonal frequency division multiplexing (OFDM) for broadband wireless communications. Also, using improved channel prediction, we enhance the performance of adaptive OFDM in high mobility environments. Adaptive modulation technique has been shown to achieve reliable high-rate data transmission over frequency-selective fading channel when OFDM is employed. This scheme requires the accurate channel information between two stations for a better performance. In an outdoor high mobility environment, most of adaptive OFDM systems have to be given the channel information transmitted from the receiver. Even if it is possible, there is some delay. Moreover, the channel impulse response between two stations is very rapidly varied. If the channel information is obsolete at the time of transmission, then poor system performance will result. In order to solve this problem, we propose adaptive OFDM with improved channel predictor. The proposed bit allocation algorithm has a lower complexity and the proposed scheme mitigates the effect of channel delay. Robust approach is less sensitive to outdated channel information. Performance results show that the proposed scheme can achieve considerable performance enhancement.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.1
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• pp.211-218
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• 2000

This paper describes the improvement of broadband radio channel characteristics using a MMSE adaptive equalization technique as a fundamental study of high transmission rates in indoor radio channel. First, the performance of 16-QAM system that employs a MMSE linear adaptive equalizer in Rayleigh fading channel is analyzed. Next, in order to improve broadband radio channel characteristics, we apply an adaptive equalization technique employing the MMSE algorithm to the radio channel measured by using circularly polarized antenna under indoor NLOS(non-line-of sight) environment. Consequently, for 16-QAM with adaptive equalizer, we can achieve the improvement of about 13 dB at $10^{-3}$ error rate as compared with general 16-QAM. Moreover, it was found that the adaptive equalization technique could improve broadband radio channel characteristics over the all measured areas. Also, it was found that the employing both adaptive equalization and polarization diversity technique together could improve broadband radio channel characteristics and reduce fading more effectively.

• The Transactions of the Korea Information Processing Society
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• v.6 no.2
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• pp.534-542
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• 1999

A sell-designed rate control strategy can improve overall picture quality for video transmission over a constant bit rate channel and the rate control method is not a normative part of MPEG-video standard, the performance of MPEG video codec can be quite different depends on how to implement the rate control scheme. The rate control scheme proposed in MPEG show good results when scene changes is not occurred. But it has weakness that it does not properly handle scene-changed pictures. Therefore picture quality after scene change is deteriorated, and possibility of overflow occurrence becomes high. In this paper, a new method for detection of scene change occurrence using local variance and a new determination scheme for adaptive quantization parameter, mqunt, which can consider local characteristic of an image by using previously computed the local variance from the scene change detection part are proposed. IN addition, and adaptive rate control scheme which can handles scene changed picture very efficiently by scene-changed picture is proposed. Computer simulations are performed to verify the performance of the proposed algorithm. The suggested detection algorithm precisely detected scene change. And the proposed rate control scheme shows better rate control performance as compared with that of the conventional MPEG scheme.