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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Journal of Robotics and Control (JRC)
Riasat Khan
North South University
Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Mechanical Engineering

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Masters and Doctor of Philosophy admission prediction of Bangladeshi students into different classes of universities Md Naimul Islam Suvon; Sadman Chowdhury Siam; Mehebuba Ferdous; Mahabub Alam; Riasat Khan
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 11, No 4: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v11.i4.pp%p

Abstract

Many Bangladeshi students intend to pursue higher studies abroad after completing their undergraduate degrees every year. Choosing a university for higher education is a challenging task for students. Especially, the students with average and lower academic credentials (undergraduate grades, English proficiency test scores, job, and research experiences) can hardly choose the universities that could match their profile. In this paper, we have analyzed some real unique data of Bangladeshi students who had been accepted admissions at different universities worldwide for higher studies. Finally, we have produced prediction models based on random forest (RF) and decision tree (DT) techniques, which can predict appropriate universities of specific classes for students according to their past academic performances. Two separate models have been studied in this paper, one for Masters (MS) students and another for Doctor of Philosophy (PhD) students. According to the Quacquarelli Symonds (QS) World University Rankings, the universities where the students got admitted have been divided into 9 classes for MS students and 8 classes for PhD students. Accuracy, precision, recall and F1-Score have been studied for the two machine learning algorithms. Numerical results show that both the algorithm DT and RF have the same accuracy of 89% for PhD student data and 86% for MS student data.
Semi Wireless Underwater Rescue Drone with Robotic Arm Ishrat Jacy Meem; Safwat Osman; Khadem Md Habibul Bashar; Nazrul Islam Tushar; Riasat Khan
Journal of Robotics and Control (JRC) Vol 3, No 4 (2022): July
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v3i4.14867

Abstract

Wireless communication with underwater drones plays a vital role in rescuing an after-ship accident, and it is considered one of the most challenging technologies nowadays. The wireless underwater drone also contributes significantly to navy, gas and oil companies, underwater infrastructure, aquaculture industry, commercial diving, and deep archeological investigations. Bangladesh, a developing country with many rivers and seashores used by many water transport vehicles, faces boat and ship accidents as a typical scenario every year. Many lives, dead bodies, ships, boats, and valuable objects do not get rescued because of the lifetime risk of the divers or the rescue team. The rescue operation is exceptionally troublesome because of the absence of wireless underwater drone technology at the cheapest cost, whose innovation and function are very challenging for Bangladesh. Considering these problematic situations, in this paper, we have proposed a prototype of a semi wireless underwater drone designed and structured with the best quality PVC pipe of 6mm diameter, considering the weight as lowest as possible, maintaining its buoyancy properly. In this prototype, we have used three propellers, each connected with three servo motors, to move it up, down, back, and forth. A robotic arm is also utilized to rescue objects from under the water, and a 4K HD EKEN camera and two waterproof fog lights to search and visualize underwater objects on the mobile screen from the land. For wireless communication between the controller and the drone, we have used two nRF24L01 modules; one is for the controller, and the other is for the drone’s receiver to send and obtain the signals from the controller to the drone. 12V and 24V lithium-ion batteries are employed as power sources for the controller and receiver, respectively. Finally, real experimental tests of the proposed underwater device were performed in a swimming pool facility.
Co-Authors Ishrat Jacy Meem Khadem Md Habibul Bashar Mahabub Alam Md Naimul Islam Suvon Mehebuba Ferdous Nazrul Islam Tushar Sadman Chowdhury Siam Safwat Osman