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Author: search.filters.author.La-Inchua, Jaraspat

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    Variable to variable crossover in GA to solve PAPR reduction in OFDM systems
    (2014-02-12)
    U-Thong, Sutud
    ;
    Pradabpet, Chusit
    ;
    La-Inchua, Jaraspat
    ;
    Chivapreecha, Sorawat
    ;
    Soontornwong, Parinya
    The hybrid of partial transmit sequences (PTS) and cascade adaptive peak power reduction (CAPPR) methods have been used to reduce peak to average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) system. When number of sub-block increases, PAPR is getting small. However, the calculation cost of its selection must be considerably large. We introduce variable to variable crossover in GA, the total calculation cost becomes drastically reduced. The parameter for simulation used standard WLAN in IEEE 802.11a system. In simulation results, the proposed method shows the improvement performance PAPR and bit error rate (BER) of an OFDM system.
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    Fuzzy logic-based traffic incident detection system with discrete wavelet transform
    (2014-01-01)
    La-Inchua, Jaraspat
    ;
    Chivapreecha, Sorawat
    ;
    Thajchayapong, Suttipong
    This paper presents a fuzzy logic-based traffic incident detection system to detect a lane-blocking traffic incident that usually causes of traffic congestion. The proposed system uses fuzzy logic to identify traffic status as normal and abnormal. Macroscopic and microscopic traffic variables, namely, mean speed and standard deviation of inter-arrival time are used as inputs to the fuzzy inference system (FIS). As traffic variables have many fluctuations which are considered as noisy signals, discrete wavelet transform (DWT) as used for de-noising and also extracting features from noisy signals. It is found that the proposed system that uses DWT can give higher detection rate when compared with the system without DWT. Furthermore, the majority voting is also applied to the outputs of FIS in order to increase detection rate. Finally, based on simulation results, the performance of the proposed detection system for lane-blocking traffic incidents will be shown. © 2014 IEEE.
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    A new system for traffic incident detection using fuzzy logic and majority voting
    (2013-09-02)
    La-Inchua, Jaraspat
    ;
    Chivapreecha, Sorawat
    ;
    Thajchayapong, Suttipong
    This paper presents a system to detect lane-blocking traffic incidents which are amongst major causes of traffic jam. The proposed system uses fuzzy logic to identify traffic status as normal and abnormal. Mean speed and standard deviation of inter-arrival time are used as inputs to the fuzzy inference system (FIS), and then, the majority voting is applied to the outputs of FIS to improve detection rate and mean time to detection. Furthermore, based on simulation results, we show that the proposed lane-blocking detection system is very suitable for real-time implementation. © 2013 IEEE.