Chivapreecha, Sorawat

Preferred name

Alternative Name

Chivapreecha, S.

Chivapreecha, Sorwat

Main Affiliation

School of Engineering

sorawat.ch@kmitl.ac.th

Now showing 1 - 10 of 86

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Morphology-based algorithm and application for mammographic masses segmentation
(2013-01-01)
Suapang, Piyamas
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Naruephai, Chadaporn
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Chivapreecha, Sorawat
Medical images segmentation is an important work for object recognition of the human organs and it is an important pre-processing step in medical image segmentation and 3D reconstruction. Conventionally, segmentation is detected according to some early brought forward algorithms such as gradient-based algorithm and template-based algorithm, but they are not so good for noise medical image segmentation. In this paper, basic morphological theory and operations are introduced at first, and then a novel morphological segmentation algorithm is proposed to detect the segment of mammographic masses with salt-And-pepper noise. The experimental results show that the proposed algorithm is more efficient for medical image denoising and segmentation than the usually used template-based segmentation algorithms and general morphological segmentation algorithms. Furthermore, the application is helpful for physician and doctors in diagnosis of the breast cancer in further steps.
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Generalized Pascal matrices, inverses, computations and properties using one-to-one rational polynomial s-z transformations
(2008-01-01)
Deng, Tian Bo
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Chivapreecha, Sorawat
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Dejhan, Kobchai
This paper proposes a one-to-one mapping between the coefficients of continuous-time (s-domain) and discrete-time (z-domain) IIR transfer functions such that the s-domain numerator/denominator coefficients can be uniquely mapped to the z-domain numerator/denominator coefficients. The one-to-one mapping provides a firm basis for proving the inverses of the so-called generalized Pascal matrices from various first-order s-z transformations. We also derive recurrence formulas for recursively determining the inner elements of the generalized Pascal matrices from their boundary ones. Consequently, all the elements of the whole generalized Pascal matrix can be easily generated through utilizing their neighbourhood, which can be exploited for further simplifying the Pascal matrix generations. Finally, we reveal and prove some interesting properties of the generalized Pascal matrices. © 2008 IEEE.
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An FPGA-based implementation of variable fractional delay filter
(2009-10-19)
Nithirochananont, Ussanai
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Chivapreecha, Sorawat
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Dejhan, Kobchai
A variable fractional delay (VFD) filter is widely used in applications such as symbol timing recovery, arbitrary sampling rate conversion and echo cancellation. This paper presents an implementation of variable fractional delay filter on FPGA. The implementation utilizes an efficient structure so called Taylor structure. The main advantage of this structure is to reduce number of multiplier and adder when compared with Farrow structure or modified Farrow structure. The result of implementation will be reported as throughput and area utilization. ©2009 IEEE.
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Real-Time Zero-Phase Digital Filter Using Recurrent Neural Network
(2023-01-01)
Sinjanakhom, Tantep
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Chivapreecha, Sorawat
This paper proposes a method to design and implement a zero-phase digital filter that can run in a real-time system. Generally, zero-phase filters are designed for non-causal systems only as the time-reversal operations are required. Thus, the typical usage of these filters is for offline applications. For this reason, we propose a real-time zero-phase digital filter that is designed based on a recurrent neural network model, particularly the gated recurrent units. The model learns to perform zero-phase filtering by using training data made from the filtered signals that are generated by using the conventionally designed zero-phase filter. The original digital filter used to create the dataset is an IIR filter performing forward-backward filtering. The best trained model yields the mean absolute loss values at approximately 0.001 and can process at least 30 times faster than real-time. Furthermore, the trained model was implemented as a 3-band zero-phase graphic equalizer to exhibit one of its applications.
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Wireless intelligent fall detection and movement classification using fuzzy logic
(2012-12-01)
Putchana, Wuttichai
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Chivapreecha, Sorawat
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Limpiti, Tulaya
Global population aging leads to increased interests in preventive healthcare technology. As falls are the most common cause of injury or death in old persons, fall detection and movement classification is one of the key topics in this research area. In this paper we propose a simple wireless intelligent system prototype for fall detection and movement classification for real-time monitoring of the elderly. The portable sensor unit acquires data from a triaxial accelerometer and sends the data wirelessly to a computer using Zigbee technology. Alternative to classic methods, the movement data is analyzed using a fuzzy inference system. The system is designed to distinguish between four movement types: standing, sitting, forward fall, and backward fall. Its classification accuracy is investigated using experimental data. It is observed that the system performs well with high sensitivity and excellent specificity. Additionally, the system is applicable for monitoring rehabilitative patients and is extendable to a larger class of movements and postures. ©2012 IEEE.
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Modeling and simulation in passive bistatic radar for detecting target range and velocity application to USRP B-210 SDR
(2019-07-01)
Chunsangnetr, Thongterm
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Chivapreecha, Sorawat
The propose of this paper is to improve the performance of Passive Bistatic Radar. The process of developed model has three steps. Firstly, the integration of the designed Passive Bistatic Radar algorithm such as coherent receiver USRP B-210, Least Mean Square (LMS) adaptive filter for noise cancellation, cross correlation for comparing similarity of two series signals and the result display on time scope for range and velocity of the targets. Secondly, the test on the overall system with the simulation targets in real time environment. Thirdly, the evaluation on the result of simulation for the range and velocity of the targets. The result of this experiment is more stable because of better synchronization receiver, noise cancellation in designed LMS which is close to the LMS simulink block, range and velocity from cross correlation for comparing similarity of the signals appear correctly. Conclusion, the simulations show that the proposed algorithms improve the performance of Passive Bistatic Radar.
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A transient-free structure for Lagrange-type variable fractional-delay digital filter
(2014-01-01)
Soontornwong, Parinya
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Chivapreecha, Sorawat
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Pradabpet, Chusit
This paper presents a new structure for Lagrange-type variable fractional-delay (VFD) filter. A new structure is formulated from discrete Pascal transform (DPT) and its Pascal interpolation. The computational complexity which obtained from proposed structure is linear function of VFD filter order as same as the so-called Taylor's series structure and also be modular structure. Unfortunately, Taylor's series structure is suffered from transient error that caused from changing delay parameter but the proposed structure can online adjust delay parameter without transient error. Therefore, a transient-free structure will be the new choice for Lagrange-type VFD filters structure which is suitable for real-time application such as sampling rate conversion (SRC) and timing recovery in digital receiver. © 2014 IEEE.
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Fuzzy logic-based traffic incident detection system with discrete wavelet transform
(2014-01-01)
La-Inchua, Jaraspat
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Chivapreecha, Sorawat
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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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Internet network in space for small satellites: Concept and experiments
(2018-01-01)
Techavijit, Pirada
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Sukchalerm, Polkit
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Wongphuangfuthaworn, Natthapong
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Plodpai, Aniwat
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Manuthasna, Shariff
Currently, no wireless network service is being offered in space. This fact has caused satellite developers to establish their own wireless network with a low coverage area that does not function very well. These problems can be resolved by setting up an effective wireless network that can be offered as a service to satellites in orbit. This study is focused on designing a high-quality wireless-in-space network to connect satellites in orbit to the Internet. Such a network would enable satellites to be controlled through the Internet from the Earth without having their own ground stations. In this paper, various aspects of the design of a network setup standard are discussed. These aspects include appropriate wireless communication and the construction of a model satellite that can be connected to the network from space. The work also included testing the design by setting up the Internet network for use above Thailand's territory and launching the original model satellite for the demonstration of the principle. The sensor data was then transmitted in real time to audiences from all over the country and used to design an Internet network in space with global coverage, which is a target for further development.
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Adaptive equalization architecture using distributed arithmetic for partial response channels
(2006-12-01)
Chivapreecha, Sorawat
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Jaruvarakul, Aungkana
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Jaruvarakul, Nivat
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Dejhan, Kobchai
This paper proposes a design and implementation of transversal adaptive digital filter using LMS (Least Mean Squares) adaptive algorithm. The filter structure is based on Distributed Arithmetic (DA), which is able to calculate the inner product by shifting, and accumulating of partial products and storing in look-up table, also the desired adaptive digital filter will be multiplierless filter. In addition, the hardware implementation uses VHDL (Very high-speed integrated circuit Hardware Description Language) and synthesis using FLEX10K Altera FPGA (Field Programmable Gate Array) as target technology and uses Leonardo Spectrum and MAX+plusII program for overall development. The results of this design are shown that the speed performance and used area of FPGA. The experimental results are presented to demonstrate the feasibility of the desired adaptive digital filter.. © 2006 IEEE.

Chivapreecha, Sorawat

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