Purahong, Boonchana

Preferred name

Purahong, Boonchana

Alternative Name

Purahong, B.

Main Affiliation

School of Engineering

boonchana.pu@kmitl.ac.th

Now showing 1 - 10 of 45

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Approximation of the maximally flat filter by using Bézier curve with an exponential function
(2020-02-24)
Purahong, B.
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Kanjanasurat, I.
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Sithiyopasakul, P.
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Chutchavong, V.
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Pintavirooj, C.
This paper presents a design of filter by using Bézier curve with an exponential function. This paper used the advantage of The Bézier curve which had ability for approximation and an exponential function which had the adaptable parameters of the polynomial. It can adjust the characteristic of frequency response for the best performance. The simulation results of various setting show the frequency response, step response. The comparison of response between the Bernstein filter and Butterworth filter in order two show that the rise time of Bernstein filter better than Butterworth filter and Bézier curve filter has not overshoot. Furthermore, the stability Nyquist criterion has been used to guarantee the stability of the transfer function.
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Blood Vessel Extraction and Optic Disk Localization for Diabetic Retinopathy
(2020-09-15)
Kanjanasurat, Isoon
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Purahong, Boonchana
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Pintavirooj, Chuchart
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Satayarak, Nitjaree
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Benjangkaprasert, Chawalit
This paper presents methods of vascular extraction and optic disk localization in the retinal images. Our approach begins with preprocessing to improve the quality of blood vessels. In the next step, a matrix filter was applied to express blood vessels. Finally, the blood vessel structure was used to estimate the location of the optic disk. The proposed method was tested on all different forty retinal images from the DRIVE database, which public retinal image dataset. The results of vessel extraction were compared with the ground truth image. The error of vascular extraction showed that the average sensitivity and accuracy were 79.81% and 94.98%, respectively. The optic disk localization achieved 97.5%.
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Student development towards innovation in the information engineering curriculum of faculty of engineering, KMITL
(2020-11-04)
Archevapanich, Tuanjai
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Sithiyopasakul, Jiran
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Purahong, Boonchana
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Sithiyopasakul, Jirayus
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Sithiyopasakul, Paisan
This article presents the student development towards creative works of innovation in the Information Engineering curriculum of the Faculty of Engineering, King Mongkut's Institute of Technology Ladkrabang by using the theory of cognition in wisdom, skill range, and mental range. Enlighten students have knowledge and skills in creating innovative inventions. The satisfaction survey results in the integration of teaching and learning. The criteria were at a high level (4.03), which is 80.76 percent and the achievement of students' creative innovation works is at a high level (4.16), representing 83.31 percent.
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Automated resource management system based on kubernetes technology
(2021-05-19)
Sithiyopasakul, Jirayus
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Archevapanich, Tuanjai
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Purahong, Boonchana
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Sithiyopasakul, Paisan
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Benjangkaprasert, Chawalit
The purpose of this research is intended to study and analyze the Kubernetes technology using the processes of performance evaluation by inspecting how many requests and responses could the server handle. According to the ability of Kubernetes technology, there is no systematic measure of performance despite the Kubernetes is currently in use broadly. Therefore, this paper proposed to test out the system by measuring the effectiveness according to a structured process by studying such measurement variables including the number of requests per second, number of responses to requests, and resource extension period with Kubernetes technology. Which from the testing and analysis of all three variables as mentioned, it is possible to know the efficiency of the Kubernetes technology in such a similar environment. Moreover, the testing experiment could display a piece of information on the dashboard for visualization and analytic purposes.
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INTERNET OF THINGS BASED PRACTICAL SMART ENVIRONMENTAL MONITORING SYSTEM FOR POULTRY FARM
(2026-01-01)
Anuwongpinit, Thanavit
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Manthawornsiri, Chananont
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Archevapanich, Tuanjai
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Purahong, Boonchana
In this article, we propose developing digital innovation of smart monitoring systems in the poultry farm using the Internet of Things (IoT) technology. This work aimed to design and develop a monitoring system based on an IoT system that transforms a traditional farm that uses a manual management system to apply an IoT system for environmental monitoring in a poultry farm. The main components include a hardware component that was designed and implemented to gather data of the poultry houses. Temperature and humidity sensor nodes are applied to monitoring the environment of poultry houses. The LoRa communication module in the sensor node will forward data to the gateway. The second principal component is the cloud server for data acquisition from the gateway. The cloud will be responsible for back-end processing and a web-based dashboard displaying mechanism. This system can work as an alarm notification system using LINE notify API for the LINE application that is the most popular communication application in Thailand. The system was implemented practically in one of the poultry farms in Prachinburi province, Thailand. The results indicate that the proposed system provides significant advantages, including enhanced monitoring accuracy, reduced energy consumption, and improved real-time environmental tracking for poultry farms.
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Information Engineering Course Management in Faculty of Engineering, KMITL towards excellence
(2021-01-01)
Purahong, Punyaruethai
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Archevapanich, Tuanjai
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Chaowalittawin, Vasutorn
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Punthang, Donnaporn
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Millerteacher, Gregory P.
This article represents the management of Information Engineering course in faculty of Engineering, KMITL towards excellence. Sample group is the parental units of who registered since 2017 until 2020 for 15 people, by purposive sampling. The researcher later presenting the Information Engineering course management. Then make a parental satisfaction assessment form about the Information Engineering course management in faculty of Engineering, King Mongkut's Institute of Technology Ladkrabang, towards excellence of 7 subject. The conclude of assessment says that the parental units are having a good level of satisfaction and the arithmetic mean is 4.72 and the standard deviation is 0.56 (\overline{X} =4.27, S.D. = 0.56)
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IoT-based Water Quality Monitoring Station and Forecasting System with Machine Learning
(2025-01-01)
Jomjaiekachorn, Thanart
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Anuwongpinit, Thanavit
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Purahong, Boonchana
This paper presents an IoT-based water quality monitoring and forecasting system designed for real-time and continuous assessment of water resources. The system integrates Siemens SIMATIC IOT2050 as an Industrial IoT Gateway, which collects data from sensors measuring conductivity, pH, dissolved oxygen, and temperature using RS485 Modbus RTU communication. Data processing occurs at the edge using Node-RED and is transmitted to AWS Cloud via MQTT for storage and visualization on a dashboard. Predictive analysis employs machine learning models, including XGBoost with Optuna parameter tuning and Long Short-Term Memory (LSTM) networks, for water quality forecasting. Results indicate superior performance of LSTM for most parameters, while XGBoost excels in pH prediction. This system demonstrates scalability, reliability, and potential for enhanced water quality management in diverse environments.
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DDoS Detection Using a Hybrid CNN–RNN Model Enhanced with Multi-Head Attention for Cloud Infrastructure
(2025-11-01)
Sathaporn, Posathip
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Krungseanmuang, Woranidtha
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Chaowalittawin, Vasutorn
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Benjangkaprasert, Chawalit
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Purahong, Boonchana
Cloud infrastructure supports modern services across different sectors, such as business, education, lifestyle, government and so on. With the high demand for cloud computing, the security of network communication is also an important consideration. Distributed denial-of-service (DDoS) attacks pose a significant threat. Therefore, detection and mitigation are critically important for reliable operation of cloud-based systems. Intrusion detection systems (IDS) play a vital role in detecting and preventing attacks to avoid damage to reliability. This article presents DDoS detection using a convolutional neural network (CNN) and recurrent neural network (RNN) model enhancement with a multi-head attention mechanism for cloud infrastructure protection enhances the contextual relevance and accuracy of the DDoS detection. Preprocessing techniques were applied to optimize model performance, such as information gained to identify important features, normalization, and synthetic minority oversampling technique (SMOTE) to address class imbalance issues. The results were evaluated using confusion metrics. Based on the performance indicators, our proposed method achieves an accuracy of 97.78%, precision of 98.66%, recall of 94.53%, and F1-score of 96.49%. The hybrid model with multi-head attention achieved the best results among the other deep learning models. The model parameter size was moderately lightweight at 413,057 parameters with an inference time in a cloud environment of less than 6 milliseconds, making it suitable for application to cloud infrastructure.
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Optimized Gaussian Pulse Design for UWB System Using Particle Swarm Optimization Based-on Generalized Bessel Polynomials
(2022-01-01)
Chutchavong, Vanvisa
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Anuwongpinit, Thanavit
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Purahong, Boonchana
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Archevapanich, Tuanjai
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Janchitrapongvej, Kanok
The ultrawideband system operates a very short pulse with enormous bandwidth to provide high data rates for data transmission. To design the UWB pulse, considering the pulse shape is very necessary, and a spectral emission mask of the designed pulse should meet the FCC spectral mask requirement between frequency range 3.1 GHz to 10.6 GHz. The traditional UWB pulse design is based on the Gaussian derivative. However, the frequency spectrum is not satisfied the FCC spectral mask requirement. In this study, the Gaussian pulse can be designed from the mathematical characteristic of the generalized Bessel polynomial. The spectral efficiency of the proposed pulse can be improved by the combination of the derivative of Gaussian pulse with a weight coefficient optimization with particle swarm optimization (PSO). PSO is a population-based optimization algorithm inspired by animal behavior. PSO is applied with generalized Bessel polynomial transfer function to gain the best weight coefficient, we proposed to optimize its weight vector to design a pulse that exceeds to FCC spectral mask. The results were found in MATLAB software show that generalized Bessel polynomials can approximate the proposed pulse with combination method and PSO. The spectral efficiency is improved to 89.30% and the spectrum is greater close to the FCC spectral mask requirement. To confirm an improved spectral efficiency compared to the previous works.
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Hybrid facial features with application in person identification
(2020-08-14)
Purahong, Boonchana
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Chutchavong, Vanvisa
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Aoyama, Hisayuki
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Pintavirooj, Chuchart
This paper presents the hybrid facial feature with identification and verification based on facial images. A query facial image had been taken under different conditions of the facial image of the same person (as the query). The query facial image database was constructed. We have used the technique of three-dimensional (3D) Dlib facial landmarks using a direct linear transform technique. A set of absolute affine invariance had been constructed from a series of the 3D landmark quadruplets, which make the facial identification robust to affine geometric transformation. These 3D facial features serve as a coarse feature depending on each individual facial structure. The construct of the 2D detail features represents the edge facial image confined between the 2D Dlib landmarks. The similarity of the 2D feature is achieved by aligning the 2D query edge image against that of the reference edge image. The geometric transformation matrix is estimated from the 2D Dlib landmarks, where correspondence is well established. An identification/verification cost function using a combination of local 2D facial features and global 3D facial features is utilized to verify and identify a query facial image against a candidate facial image(s). The performance of the algorithm yielding an area of 99.97% perfect classification is represented as a value under the receiver operating characteristic (ROC) curve.

Purahong, Boonchana

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