Supnithi, Pornchai
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Supnithi, Pornchai
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Supnithi, P.
Supnithi, Pomchai
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pornchai.su@kmitl.ac.th
111 results
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Item type:Publication, A comparative study on reduced complexity 2-D detectors for bit patterned media(2011-12-01) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Effects of Equatorial Plasma Bubbles over Real-Time Kinematic Positioning in Low-Latitude Region(2023-01-01); ; ; Saito, SusumuEquatorial plasma bubbles (EPBs) refer to ionospheric irregularities in low-latitude regions, commonly observed after sunset. They originate at the magnetic equator and then potentially spread to mid-latitude region. As cm-level positioning techniques are increasingly important to various segments of society, the performance degradation of these systems due to EPB at low latitudes needs to be investigated. In this work, we analyze the EPB effects on the performances of real-time kinematic (RTK) positioning at the short, medium, and long baselines at low-latitude stations in Thailand. The low-latitudes local ionospheric disturbances such EPBs are shown to degrade the positioning accuracy of RTK in different seasons in 2022. It is found that the positioning errors are higher during the disturbance periods and more severe at the long baselines than the shorter ones, especially during the equinoctial months. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Comparative Analysis of Deep Learning Models for Daily Solar Indices Forecasting in Solar Cycle 25(2025-01-01); Accurate forecasting of solar activity indices, particularly the Sunspot Number (SSN) and the F10.7 solar radio flux index (F10.7), is essential for effective space weather monitoring, as severe solar and ionospheric disturbances can significantly impact satellite operations, radio communications, and navigation systems. This paper presents a comparative analysis of deep learning models - Long Short-Term Memory (LSTM), Temporal Convolutional Networks (TCN), and encoder-only Transformer architectures - for daily forecasting of SSN and F10.7 up to 14 days ahead based on past 27 days. Considering relatively simple model structures, both single-step and multi-step prediction strategies are explored to evaluate the models' capability in handling short-and long-term dependencies in time series data. Daily solar activity data spanning seven solar cycles (Cycles 19-25), obtained from the GFZ Helmholtz Centre for Geosciences, are used for model training and evaluation. Experimental results show that LSTM consistently achieves the best performance across most forecast horizons, particularly in short-to medium-term predictions. The Transformer model delivers competitive and stable results, while TCN performs relatively less effectively, indicating the need for more complex architecture and optimization strategies. These findings highlight the strengths and limitations of each architecture for solar activity forecasting applications. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A flexible KFCI compensation for head/media optimization in perpendicular magnetic recording systems(2010-12-01); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The variation of critical frequency of E layer over Chumphon, Thailand(2013-12-09); ; ; Noppanakeepong, SuthichaiIn this research paper presents the observed critical frequency of E layer (foE) over Chumphon, Thailand which is located at nearly the magnetic equator (lat. 10.72° long. 99.37° dip. 3°) during September 2004 to August 2005. The foE is one of essential parameters in the International Reference Ionsphere (IRI) model. We investigate the variation of the observed foE by comparing to the Sun spot number, ionospheric index, and 10.7 cm. flux. Due to essentially of accurate IRI model can be used to applied in communication such as it may be implied tendency of phenomena in E layer effect on high frequency communication over Chumphon, Thailand. © 2013 IEEE. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Reduced-complexity window decoding of spatially coupled LDPC codes for magnetic recording systems(2018-10-24); In channel coding theory, the performance of error correcting codes (ECCs) approaching the Shannon limit can be achieved through increasing code lengths. Unfortunately, the complexity of ECCs will be increased as the code length increases. Nowadays, the magnetic recording (MR) system takes advantage of powerful ECCs by using 4 Kbytes sector. Among the advanced ECCs, the spatially coupled LDPC (SC-LDPC) codes (also known as a LDPC convolutional code) [1] are shown to have the decoding latency and complexity lower than those of the underlying LDPC block codes (LDPC-BC). Moreover, the SC-LDPC codes with threshold decoding outperform the LDPC-BC codes [2]. Hence, the SC-LDPC codes are the strong candidate for the future MR systems, when the sector size is increased beyond 4 Kbytes. An SC-LDPC decoder can use sliding window decoding [3] whereby the received signals are decoded by sliding window along the bit sequence. The window decoder is called "uniform window decoding (U-WD)", when all variable nodes (VNs) within a window are updated. In order to reduce the complexity of window decoding, some researchers proposed the non-uniform window decoding (N-WD) [4], which do not update the VNs with no improvement in the bit error rate (BER). This approach provides about 35-50% reduction in complexity compared to U-WD. In this work, we consider the application of SC-LDPC codes in MR systems, whereby SC-LDPC decoder cooperates with BCJR detector to encounter inter-symbol interference (ISI). We propose the dynamic shifting of window decoding (DS-WD) to reduce the complexity of SC-LDPC codes. Herein, the number of shifted bits is defined according to their soft BERs which are estimated at each decoding position. In addition, we modify the N-WD [4] to reinforce our proposed algorithm called "dynamic-shifting non-uniform window decoding (DS-N-WD)." The DS-WD and DS-N-WD achieve the complexity reduction of 7% and 25% without any loss in performance compared to the N-WD algorithms. i - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Rain attenuation of satellite link in Ku-band at Bangkok(2005-12-01); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Prediction of foF2 using Neural Network at Thailand equatorial latitude station, Chumphon(2014-01-01) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Construction of punctured polar codes based on genetic algorithm(2021-05-19); In this work, we propose a new construction of punctured polar codes, which provides a good error-correcting performance at arbitrary code lengths and code rates. We exploit the density evolution to evaluate the error probability of punctured polar codes. Then, the puncturing pattern and frozen bit positions are selected by genetic algorithm to construct a punctured polar code with low error probability. The results show that the proposed technique provides superior block error rate performance than the quasi-uniform puncturing technique at a high code rate. At a low code rate, the proposed technique can show the better performance than the shortening technique. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Improvement of Kalman Filter for GNSS/IMU Data Fusion with Measurement Bias Compensation(2020-07-01); ; The ASEAN IVO project currently supports the research related to GNSS and ionospheric data products for disaster prevention and aviation in low-latitude regions. In vehicle navigation, Real Time Kinematic (RTK) positioning distorted from the environment often contaminates the measurement vectors (such as position or speed of a rover). In this situation, the conventional Kalman filter with a linear motion model could not reduce positioning errors sufficiently due to existing bias. Hence, the measurement bias compensation method based on the mean of residual vectors is proposed. We modify the conventional Kalman filter by including this compensation in the estimation step. We test the algorithm in both of the simulations and actual experiments. From the results, the proposed method outperforms the baseline method in terms of positioning error by 60% and 12% for the simulation test and the field test respectively.