Article Per Year (5 Year)
p-Index From 2021 - 2026
0.817
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This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics Journal of Applied Engineering and Technological Science (JAETS)
Duc-Tan Tran
Phenikaa University
Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering

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Develop algorithms to determine the status of car drivers using built-in accelerometer and GBDT Thi Thu Nguyen; Phuc Thinh Doan; Anh-Ngoc Le; Kolla Bhanu Prakash; Subrata Chowdhury; Duc-Nghia Tran; Duc-Tan Tran
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 1: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i1.pp785-792

Abstract

In this paper, we introduce a mobile application called CarSafe, in which data from the acceleration sensor integrated on smartphones is exploited to come up with an efficient classification algorithm. Two statuses, "Driving" or "Not driving," are monitored in the real-time manner. It enables automatic actions to help the driver safer. Also, from these data, our software can detect the crash situation. The software will then automatically send messages with the user's location to their emergency departments for timely assistance. The application will also issue the same alert if it detects a driver of a vehicle driving too long. The algorithm's quality is assessed through an average accuracy of 96.5%, which is better than the previous work (i.e., 93%).
Improvements on the performance of subcarrier multiplexing/wavelength division multiplexing based radio over fiber system Duc-Tan Tran; Ninh Trung Bui
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i2.pp1439-1449

Abstract

Radio over fiber (RoF) techniques are good candidates to create the backbone of the next generation of wireless networks. Many parameters affect RoF communications such as amplified spontaneous emission noise (ASE), four-wave mixing nonlinearity (FWM), the modulation, channel spacing, switching voltage, and phase shifter. In this paper, we propose an improved model of RoF communication systems using subcarrier multiplexing/wavelength division multiplexing (SCM/WDM) technique with unequal channel spacing and 1-km Erbium-doped fiber amplifier (EDFA). Simulation results confirmed that we could obtain the lowest bit error rate and noises when the EDFA is placed at 1 km from the transmitter by using optical single-sideband (OSSB) modulation at frequencies 193.1 THz, 193.2 THz, 193.35 THz, and 193.6 THz.
A study on agricultural engineering equipment in South Tamilnadu using linear regression Chandrakumar Thangavel; Ramya Thangavel; Karthik Chandran; Gunnam Suryanarayana; Subrata Chowdhury; Nguyen Duc Uyen; Thi-Thu Nguyen; Duc-Tan Tran
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3325

Abstract

Economic growth in India purely depends on the Indian agricultural sector. In developing countries, the mechanization of agriculture plays a vital role in productivity. The research focuses on identifying which farmers in South Tamilnadu mostly use agricultural machinery. In this paper, we have taken farmer names and mobile numbers, choice of implement requirement into consideration by collecting the real data through DBT portal (https://agrimachinery.nic.in). This research work deals with five southern districts in Tamilnadu, namely Dindigul, Madurai, Theni, Ramnad, and Virudhunagar, in which we have predicted which machinery is suitable for that area. The linear regression model was used in this research by testing and training the dataset in all five data frames to get efficient results. Prediction of each data frame reveals the efficient working of the particular machinery for that specific area due to the different geographical features.
Students’ Activeness Measure in Moodle Learning Management System Using Machine Learning Chandrakumar Thangavel; Valliammai S E; Amritha P. P; Karthik Chandran; Subrata Chowdhury; Nguyen Thi Thu; Bo Quoc Bao; Duc-Tan Tran; Duc-Nghia Tran; Do Quang Trang
Journal of Applied Engineering and Technological Science (JAETS) Vol. 6 No. 1 (2024): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v6i1.6128

Abstract

Due to COVID-19, the need for online education has increased worldwide, prompting students to shift from traditional learning methods to online platforms as guided by higher education departments. Higher learning institutes are focused on developing constructive online learning platforms. This research aims to measure students’ academic performance on an online learning platform – Moodle Learning Management System (LMS) – using machine learning techniques. Moodle LMS, a popular free and open-source system, has seen significant growth since the COVID-19 lockdown. Many researchers have analyzed student performance in online learning, yet there remains a need to predict academic outcomes effectively. In this study, data were collected from a higher learning institute in Tamil Nadu, and linear regression was applied to predict students' final course outcomes. The analysis, based on students' activity in Moodle LMS across both theory and laboratory courses, helps faculty identify students at risk of failing and adjust instructional methods and assignments accordingly. This approach aims to reduce failure rates by providing timely warnings and encouraging students to improve their engagement with LMS resources.
Co-Authors Amritha P. P Anh-Ngoc Le Bo Quoc Bao Chandrakumar Thangavel Chandrakumar Thangavel Do Quang Trang Duc-Nghia Tran Duc-Nghia Tran Gunnam Suryanarayana Karthik Chandran Kolla Bhanu Prakash Nguyen Duc Uyen Nguyen Thi Thu Ninh Trung Bui Phuc Thinh Doan Ramya Thangavel Subrata Chowdhury Subrata Chowdhury Subrata Chowdhury Thi Thu Nguyen Thi-Thu Nguyen Valliammai S E