Tooprakai, Sirapop

Preferred name

Tooprakai, Sirapop

Alternative Name

Tooprakai, Siraphop

Main Affiliation

School of Engineering

sirapop.to@kmitl.ac.th

Now showing 1 - 7 of 7

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Current-Mode Active Filter Using EX-CCCII
(2024-06-01)
Kumngern, Montree
;
Khateb, Fabian
;
Kulej, Tomasz
;
Tooprakai, Siraphop
This paper presents a novel multiple-input and multiple-output current-mode universal analog filter with electronic tuning capability. The proposed circuit uses a single second-generation current-controlled current conveyor with extra-X terminals (EX-CCCII) and two grounded capacitors. The filter can offer five standard filtering functions, namely low-pass, high-pass, band-pass, band-stop, all-pass responses, in the same circuit without changing the internal configuration of the filter by selecting appropriate input and output signals. To obtain the five standard filtering functions, inverted input signal and input matching conditions are absent. The natural frequency of all filter responses can be electronically controlled. The proposed circuit was simulated by SPICE using 0.18 μm CMOS process from Taiwan Semiconductor Manufacturing Company (TSMC). The results of experiments using the integrated circuit operational amplifier AD844 confirm the functionality of the new filter.
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Estimation of Protection Distance between Digital TV Signals in Adjacent Channel on Terrestrial Television
(2025-01-01)
Chomsuk, Kinupong
;
Tooprakai, Siraphop
The Office of the National Broadcasting and Telecommunication Commission (NBTC) of Thailand initiated the transition to digital broadcasting. The implementation process requires a broadcasting license and digital transmission testing, which was carried out on channel 29 and channel 30 - adjacent channels. Due to the 20 MHz spacing between these signals, adjacent channel interference is inevitable. This study experimentally evaluates the degradation caused by interference between digital television signals operating on adjacent channels in terrestrial television broadcasting.A novel aspect of this research is the use of field strength measurements to assess the impact of adjacent channel interference on digital TV signals within urban areas. The results demonstrate that most measured protection ratios (PR) align with the ITU-R recommended value of -11 dB. This confirms that the power ratio is affected by spectrum overlap rather than the distance from the trasmitter station.
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Maintenance Decision Modeling for Solar Photovoltaic Performance Prediction Using RMSE and MAPE Methods
(2025-01-01)
Aree, Sompong
;
Tooprakai, Siraphop
This study evaluates the efficiency and degradation of a 999.50 kWp photovoltaic (PV) system in Thailand under clear sky conditions. It found that the system efficiency ratio significantly decreased, 10% below the design threshold. Thus, a feasible and optimal model can be identified to support better maintenance decisions. In addition, a real-time performance monitoring approach is proposed to enable building operators to make informed decisions about mechanical maintenance or cleaning maintenance. This method involves comparing the actual power generation data with the efficiency prediction based on linear regression modeling. In addition, the impact of dirt accumulation on the efficiency of the PV modules is evaluated. The preliminary results indicate that the output power decreases to 213.74 kW, and the corresponding efficiency ratio is 46.76%. A linear regression-based warning mechanism is adopted to issue an alarm when the efficiency drops below a threshold of 50% ± 10 or when the power drops below 300 kW ± 50. The results show that using this prediction approach can improve the system efficiency ratio by up to 70% and increase the output power by more than 355.53 kW. The accuracy of the model is verified with a mean square error(RMSE) of 18.86% or more than 81.14% and a mean absolute percentage error(MAPE) of 4.56%. The study concludes that the prediction simulation can effectively guide maintenance interventions, which can improve both power generation and system efficiency. Future work may incorporate AI-driven predictive analysis to further optimize the PV system and maintenance strategies.
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Recognition of Marijuana Plant Leaf Diseases Based on Deep Learning
(2025-01-01)
Kong, Qingye
;
Tooprakai, Siraphop
Plant pests and diseases are a common problem in agricultural production, and if not handled properly, they can seriously affect crop yield and quality. The era of the Internet of Things has arrived, and modern monitoring methods have also been applied to the growth monitoring of some crops, achieving good results. However, the cultivation of marijuana still relies mainly on traditional manual monitoring and modern methods have not yet been widely used. At the same time, the prevention of diseases and pests in marijuana is the focus, and if problems are not detected early, the losses can often be severe. This article proposes using machine learning to screen for abnormal leaves and confirm whether the leaves are healthy. After repeated training, the system can compare and classify different images of marijuana leaves and identify abnormal parts. The system is designed based on Python. The test results indicate that this technology can be applied to distinguish marijuana leaves to ensure early detection of diseases and pests, and to minimize agricultural losses caused by untimely remedial measures.
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Cannabis Greenhouse Management System with IOT Technology
(2024-01-01)
Tooprakai, Siraphop
;
Panaworn, Rujiphat Thanbumrung Pimlaphat
;
Samrit, Peerawit
This paper presents the cannabis greenhouse management system with IOT technology. The cannabis cultivation control system consists of 2 parts: controlling the environment inside the greenhouse and displaying various statuses in the greenhouse such as temperature, humidity and light, etc.
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Designing Appropriate Sensor Values for Surface Forest Fire Alarm Systems Using IoT
(2024-01-01)
Ruengtham, Jiratt
;
Tooprakai, Siraphop
Forest fire are a common problem today, causing serious damage to people's lives and property safety. It also has a huge impact on the ecological balance and economy of the country. Therefore forest fires are an issue that should be prioritized. Thailand is another country facing this problem, despite being used in the era of modernization of the Internet of Things to help alert forest fires. But one of the reasons for such significant losses is IoT technology. The forest fire alarm is installed in an inappropriate location and delays the alarm, causing serious damage. This paper focuses on using IoT technology to design appropriate sensor values for surface forest fire alarm systems. Since surface fires are the most common type of fires in Thailand, researchers designed an experiment using microcontrollers to work with different sensors for detect surface fire. The system consists of microcontroller, DHT 22 humidity and temperature sensor, MQ-2 gas detection sensor and IR Infrared detector flame sensor. The researchers simulated the surface fire, and then measured the parameters of each sensor under different conditions, and determined the best parameters suitable for the forest fire alarm system based on the Internet of Things, and the result was the optimal temperature value 28.2°c and humidity value is 66.9%. The optimal smoke value is 300 and IR Infrared Detector can detect fire at a distance of up to 1 meter. This result is an initial test. The experimental results will be collected as specified in the next step.
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EX-CCCII with Controlled Current Gain and Its Applications
(2026-04-01)
Tooprakai, Siraphop
;
Khateb, Fabian
;
Kulej, Tomasz
;
Nonthaputha, Thanat
;
Vavra, Jiri
This paper presents a novel extra-X second-generation current-controlled conveyor (EX-CCCII) with controllable current gain. Unlike the conventional EX-CCCII, the proposed EX-CCCII provides a controllable current gain between the (Formula presented.) - and (Formula presented.) -terminals. To demonstrate the advantages of the EX-CCCII with the controllable current gain, the proposed EX-CCCII is employed to realize a universal current-mode filter and a three-phase current-mode oscillator. The universal filter can realize five standard filtering responses (low-pass, high-pass, band-pass, band-stop, and all-pass) using the same topology. The current gains of these filters can be controlled through the current gain of the EX-CCCII, while the natural frequency of the universal filter can be electronically tuned via the intrinsic resistance at the x-terminal. When the proposed EX-CCCII is used to implement the three-phase oscillator, the condition of oscillation can be adjusted through the current gain of the EX-CCCII, whereas the oscillation frequency can be tuned using the parasitic resistance of the x-terminals. The proposed EX-CCCII and its applications were verified through SPICE simulations using the transistor model parameters NR100N (NPN) and PR100N (PNP) of the bipolar array ALA400-CBIC-R from AT&T to confirm the functionality and feasibility of the proposed topologies. Furthermore, experimental verification of the EX-CCCII and its integration into a three-phase oscillator further substantiates the proposed concept and demonstrates its practical viability.

Tooprakai, Sirapop

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