Poonpakdee, Pasu

Preferred name

Poonpakdee, Pasu

Alternative Name

Poonpakdee, P.

Main Affiliation

School of Engineering

pasu.po@kmitl.ac.th

Now showing 1 - 7 of 7

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Interpretable ANN-Based Computer Vision System for Mangosteen Ripeness Detection for Export Markets
(2026-01-21)
Lapcharoensuk, Ravipat
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Tosribunjerd, Naphon
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Poonpakdee, Pasu
Mangosteen is a high-value tropical fruit widely consumed and exported from Thailand. Mangosteen ripeness classification is crucial for export quality control, but manual grading leads to inconsistency and inefficiency. This study presents a computer vision system using an Artificial neural network to classify mangosteen into ripe, semi-ripe, and unripe stages based on peel color. A dataset of 378 images was collected and processed to extract 40 color-based features across multiple color spaces. Principal Component Analysis demonstrated non-linear separability among the ripeness classes. SMOTE and Gaussian noise augmentation were used to tackle data imbalance and enhance generalizability. The model reached a 95% accuracy rate and displayed flawless precision and recall for the ripe class. Integrated Gradients analysis highlighted the importance of the red-green color component (CIELAB a*) in the classification process. The proposed method demonstrates a low-cost, interpretable, and efficient solution suitable for real-world application in the mangosteen export industry.
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Decentralized Network Building Change in Large Manufacturing Companies towards Industry 4.0
(2017-01-01)
Poonpakdee, P.
;
Koiwanit, J.
;
Yuangyai, C.
In complex industrial ecosystems together with an increasing global competition, success depends on a complete value chain transformation. The use of Industry 4.0 standards is therefore gradually emerging in many industries to ensure significantly higher factory productivity, flexibility, and efficiency. However, selected methodology and results are required to be studied to fully understand the digital transformation as well as its characteristics. This research presents a system conversion study, from centralized to decentralized systems, using epidemic membership protocols on a large manufacturing company towards Industry 4.0. The system conversion shows that the epidemic membership protocols provide an ability to rewrite the structure of the overlay topology. The experimental results are presented in two categories: (1) convergence speed and (2) accuracy of the epidemic applications. These provide the information for the performance guarantee of the global aggregate computation. The expectation of this paper is to present a preliminary study focusing on the system conversion methodology in the context of Industry 4.0. There are several recent publications based on Industry 4.0; however, nothing has been done to address any methodologies applied in Industry 4.0 or their simulation results.
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Epidemic Algorithms on Distributed Systems Towards Industry 4.0
(2018-08-21)
Poonpakdee, Pasu
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Koiwanit, Jarotwan
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Yuangyai, Chumpol
In today changing world, with the advent of technology and a challenging competition, reliable information methodologies and tools are required to collaborate big data and various components in both vertical and horizontal integrations over the value chain. Cyber-Physical System or CPS is one of available technologies serving industries' needs and desires. However, its important properties are required to be investigated to fully understand its characteristics and performance. This study present an epidemic-based communication and the results show that the base station could obtain the higher accuracy of the information while the method was adopted.
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Epidemic System Conversion on Industry 4.0's Perspective under Dynamic Network Condition
(2019-09-25)
Poonpakdee, Pasu
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Koiwanit, Jarotwan
;
Yuangyai, Chumpol
In large-scale manufacturing operations with increasing global competition, success depends on a reliable network system to complete a value chain transformation. The use of the Industry 4.0 paradigm is increasingly evolving in many areas of different industries to ensure significant increases in factory productivity, flexibility, and efficiency. Consequently, the system transformation requires a shift from single automated node to a fully integrated system. However, selected methodology and results require study to fully understand the digital transformation as well as its characteristics. This investigation presents a system conversion study, between centralized and decentralized systems, using the concept of epidemic membership protocols in the context of Industry 4.0. This paper proposes the method based on membership protocols focusing on the system conversion methodology under dynamic network condition. The experimental results show that the proposed method provides an ability to rewrite the structure of the network topology with optimal accuracy of epidemic application.
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Applying epidemic algorithm for financial service based on blockchain technology
(2018-08-13)
Poonpakdee, Pasu
;
Koiwanit, Jarotwan
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Yuangyai, Chumpol
;
Chatwiriya, Watchara
Our global market is emerging transformation strategy that can make the difference between success and failure. Smart contract systems through developments of technological innovations are increasingly seen as alternative technologies to impact transactional processes significantly. Blockchain is a smart contract protocol with trust offering the potential for creating new transaction platforms and thus shows a radical change of the current core value creation in third parties. These results in enormous cost and time savings and the reduced risk for the parties. This study proposed a method to improve the efficiency of distributed consensus in blockchains using epidemic algorithm. The results showed that epidemic protocols can distribute the information similar to blockchain.
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Global Convergence Detection in Decentralized IoT Networks based on Epidemic Approach
(2024-01-01)
Poonpakdee, Pasu
;
Pongnukrohsiri, Ananyalux
;
Santangjai, Chaiyaporn
The concept of decentralization has involved in the varieties of the research area including computer science, management, politics. Bitcoin is the first cryptocurrency that indicates the power of decentralization from blockchain, the emergence of blockchain has established a new solution to solve the problem in centralization. The technology avoids the centralized controller and creates a trusted network in which all participants have a right to verify the information that flows all over the network. Considering the network layer of system architecture, an important aspect of any decentralized distributed systems including blockchain is the epidemic (gossip-based) protocols which maintain the network consistency properties namely, robustness, scalability, convergence speed, and accuracy, across the distributed systems. Epidemic protocols are bio-inspired paradigm that provides randomized communication and computation for extreme-scale networked systems. However, one of the drawback of Epidemic protocol is that each node receives multiple duplicated data with high traffic in the data transmission of data can cause high bandwidth in the network. The ability to extract relevant data from an enormous amount of data which is distributed in the network is necessary. In previous research, local convergence detection is proposed to detect global convergence for a given approximation error of the aggregation estimation. This work adapts the concept of local convergence detection to epidemic aggregation protocols to the scenario of decentralized IoT network architecture and evaluates with the standard benchmark. The results show that the adapted protocols can adjust themselves to be capable of dynamic conditions regarding global convergence.
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Experimental Verification of Control Strategies for Satellite Magnetic-Based Attitude Control System Under a Three-Axis Helmholtz Cage Environment
(2023-01-01)
Panyalert, Thanayuth
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Manuthasna, Shariff
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Chaisakulsurin, Jormpon
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Masri, Tanawish
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Palee, Kritsada
During satellite mission planning and operation, the main function of the satellite's attitude determination and control subsystem (ADCS) is to gather information about the satellite's orientation relative to the inertial reference frame. Additionally, this subsystem generates control actions that produce the required torques for adjusting the satellite's orientation, particularly in the context of the Low-Earth Orbit (LEO) regime. This paper focuses on the satellite three-axis attitude control problem for a de-tumbling mode of spacecraft using only magnetorquers as actuators under the presence of noise and investigates their performance through Hardware-in-the-Loop simulation (HiLs) tests, which consisted of a relative Earth's magnetic field generator along with the SGP-4-based satellite orbital propagator high-level control software. The design, development, and verification of proposed satellite attitude control system (ACS) strategies are presented. In detail, as an example of experimentation, the classical B-dot control algorithm is used for the de-tumbling mode to stabilize and reduce the angular rate, along with the pointing algorithm for orienting the satellite to the desired attitude. Then, a cascade Proportional-Integral-Derivative (PID) is implemented to generate enough torque through the three-axis magnetorquers on the frictionless air-bearing platform to verify the performance of the controller using an onboard computer. Finally, the effectiveness of the co-simulation tested as the primary experiment was confirmed through the integrated simulation process.

Poonpakdee, Pasu

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