Phasukkit, Pattarapong

Preferred name

Alternative Name

Phasukkit, P.

Main Affiliation

School of Engineering

pattarapong.ph@kmitl.ac.th

Now showing 1 - 10 of 96

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Analysis of heat sink effect in hepatic cancer treatment near arterial for microwave ablation by using finite element method
(2012-12-01)
Yhamyindee, P.
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Phasukkit, P.
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Tungjitkusolmon, S.
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Sanpanich, A.
This paper presents an analysis of heat sink effect in hepatic cancer treatment near arterial vessel for microwave ablation by using finite element method. We analyze the temperature distribution, Specific Absorbtion Rate (SAR) and coagulation area in two models. The first is hepatic tissue without artery and the second is hepatic tissue with artery. In the second model, we specify distance between antenna and artery at 10 mm. The initial condition is set as power at 50 watts, temperature at 37°C and blood perfusion rate is varied at 6.4 × 10-10, 6.4 × 10-3 and 6.4 × 104 l/s. The simulation results by using three-dimensional finite element analysis show that the temperature distribution in case of hepatic tissue with no artery is larger than the case with artery. We also found that blood perfusion rate affects to the temperature distribution in hepatic tissue. Higher blood perfusion rate, higher heat sink effect occur. ©2012 IEEE.
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Recurrent neural network based underground object detection using a-scan ground penetrating radar
(2021-05-19)
Choochim, Poomsak
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Kasjarun, Panut
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Phasukkit, Pattarapong
Ground penetrating radar is a highly effective tool to find objects buried underground. But there are still some limitations that prevent it from being applied to a wider variety of applications. The complexity of processing and the opportunity to collect the signal. This work is applied GPR with AI to reduce the processing steps and displayed your object's features immediately. Based on the time series model in Bidirectional Neural Network as RNN in bidirectional format. Because it possible to predict the position and shape of the object simultaneously. The object was buried under a sandbox with a depth of 10 - 50 centimeters and used two antennas to receive and transmit the signal as a GPR machine in this experiment. Found that the accuracy is at 92.8 % and also measured by F1-score in each target positions as well, when using the results of this work to add features and extend it to work with multiple functions, it will be possible to use the GPR used with Neural Network model can be used in the actual situation.
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Image Enhancement by using Triple Filter and Histogram Equalization for Organ Segmentation
(2019-11-01)
Thitivirut, Mongkol
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Leekitviwat, Jirayuts
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Pathomsathit, Carat
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Phasukkit, Pattarapong
Convolution filters are used for blurring and sharpening to modifying image when combined with the Histogram equalization for enhancing medical image by adjusting the contrast of the image. Then, the image will be optimized. So, use morphological for segmentation. This research has been designed the filtering in a part of the convolution filter by using the triple filter to adjust the threshold of morphological and normalization value. The results of this experiment are presented that the accuracy of segmentation is increasing and detecting the multiple organs. Nevertheless, we also found that each algorithm can be used for each organ.
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Computational analysis of blood parameters separate by centrifuge technique
(2017-03-23)
Wangboon, Anon
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Phasukkit, Pattarapong
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Keawbumrung, Mongkol
This article is purpose of the computational fluid dynamic (CFD) simulation for blood parameters separated by centrifuge machine which has different spinning velocities. The structure of the machine, as a fixed tube at 30 degrees from the base is used to prove that the precipitate of the blood's 2 parameters, such as blood cell and plasma, by using the simulation from computer In three dimensional (3D) symmetry modeling to study the change of the precipitate in centrifuge at different velocity of spinning. At 2000 rpm, 3000 rpm, 4000 rpm and 5000 rpm(round per minute) the result of this simulation showed the density of blood as low density in the top of the blood it's mean plasma and high density at the bottom of the tube it's mean blood cell. From the model in centrifuge can prove that in each different level of the density from velocity of spinning that useful for study to improvement of blood parameters separated by used computer simulation.
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Airflow effect on microwave ablation in lung model
(2016-02-04)
Phairoh, C.
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Sanpanich, A.
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Kajornpredanon, Y.
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Petsarb, K.
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Sroykham, W.
Pulmonary microwave ablation has been trailed and became dramatically recognized as an alternative surgical method for lung cancer treatment due to its minimal invasive technique and destroyable only a small part of malignant tissue. Even though, lung is realized as a porous tissue in which filled of humid air and a capillary network that rather difficult to control an ablation region, then a prediction of lung destructive region by using MWA simulation seem to be a reliable investigation and numerical tool for supporting this medical maneuver. In this paper, we propose a simulation of microwave thermal ablation for lung cancer treatment in a simple lung model. Microwave applicator was designed as an opened-tip coaxial antenna of 2.45 GHz at 10 Watts. To study an effect of air flow in pulmonary bronchus, a small tube with air flow was also placed close to the microwave applicator then a temperature distribution and coagulation volume at 60 °c were analyzed. The in silico results show a predictable ablation shape which affected by a convection heat transfer of a humid air. However, before a real ablation with swine tissue, an amount of pulmonary blood flow in small blood vessel should be also included in the next investigation inorder to obtain more reasonable results.
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3D finite element analysis of heat transfer efficiency in double wall infant incubator
(2012-12-01)
Wongkamhang, A.
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Phasukkit, P.
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Airphaiboon, S.
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Pintavirooj, C.
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Thongpance, N.
This paper presents a study of heat transfer efficiency in double wall infant incubator by using 3D finite element method. Double wall infant incubator was modeled by using general CAD program then FEM analysis was implemented based on heat transfer and fluid dynamic principle. Real temperature measurement also performed to validate our simulation by using a general infant incubator and an infant incubator analyzer. Real experimental data at each 4 monitoring points and simulation data provide a small difference in temperature. In the future work, infant model should be included into our incubator in order to estimate a heat source effect from newborn baby. ©2012 IEEE.
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Investigation of deep learning optimizer for water pipe leaking detection
(2019-07-01)
Arunsuriyasak, Peerachai
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Boonme, Phattraporn
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Phasukkit, Pattarapong
Nowadays, Deep learning plays an important role in complex problems. Thus, one of important algorithm part is an optimizer. This paper aims to improve algorithm using optimizers. Adam optimizer, a powerful and effective optimizer, was used to adjust parameters in Deep Neural Networks model. Which, object datasets consist leaking water pipe, non-leaking water pipe are used to classify 2 object labels. Nevertheless, RMSprop and Adadelta are alternative optimizers that can be used in Deep Neural Network. Other than that, this experiment has been shown Adam gave an accuracy at 98.973% for leaking water pipe and 97.466% for non-leaking water pipe. While, Adadelta gave 76.755% and 70.448%. And RMSprop gave 98.973% and 97.466%.
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A simple laboratory test of music therapy for insufficient sleep
(2016-02-04)
Phasukkit, Pattarapong
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Mahrozeh, Nurhayatee
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Kumngern, Montree
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Tungjitkusolmun, Supan
This article studies the behavior of human sleep found the insufficient sleep problem due to the brain performance. This experiment uses devices such as sleeptracker to save the results of a sleep and electroencephalogram (EEG) to detect brainwaves while enjoying music. However, this study considers only a general sleep and sleep event that a relaxed with the music. The findings indicated the music can help to reduce the problems of insufficient sleep. As a result, volunteers are developing the sleep as sufficiently and efficiently due to get the best quality of sleep in the life. It is also available to deploy to the general person in order to solve the problem of insufficient sleep.
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Classification of White blood cell using Deep Convolutional Neural Network
(2019-11-01)
Throngnumchai, Kan
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Lomvisai, Pitchayakorn
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Tantasirin, Chayanan
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Phasukkit, Pattarapong
White blood cells are the one of immune system that are involved in protecting the body against infection disease and foreign invaders. There are difference category of white blood cell and each category can indicate about the irregularity of body. Nowadays, White blood cell diagnosis is usually examined manually by doctor. This process consumes a lot time, cost and susceptible to error compare with automatic computerize process. An automatic classification technique for microscopic white blood cell images focusing on images from fresh blood smears[1] is proposed in this paper. The classification is conducted using a proposed method that consist of deep convolutional neural network (DCNN). 10, 000 Microscopic blood images were tested and the classification method obtain 93%
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Vertical speed prediction for the efficient landing of aircraft using GRU
(2020-11-04)
Pavitpok, Siwagorn
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Phasukkit, Pattarapong
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Pradabpet, Chusit
Air traffic management is currently the process of managing air traffic demand. For support the capacity to handle the amount of air traffic. Whether it is in the airspace sector or the airport area. There are many factors such as the ability of the air traffic providers, physical characteristics of airspace and airport terrain. The main goal of air traffic management is to manage air traffic control. Streamlined and demand-capacity balancing are safe and effective. Whether it is air traffic service providers or passengers. In this research, the experiment was carried out on specific aircraft model A-320. Traveling from Bangkok Suvarnabhumi Airport to Phuket International Airport. In which the landing airport has island terrain. Therefore, requires high security due to physical characteristics in the airspace which has many factors such as wind and wind direction and to provide safety and effective landing. Therefore, take the factors affecting the landing to predict the vertical speed. The epoch =2000, learning rate =0.01, accuracy more than 90% for training set and 90% for test set.

Phasukkit, Pattarapong

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