A5101477766- Robotics and Automated Systems
- Mobile Ad Hoc Networks
- Second Language Learning and Teaching
- Innovation in Digital Healthcare Systems
- Elevator Systems and Control
- Network Traffic and Congestion Control
- Municipal Solid Waste Management
- High-Temperature Coating Behaviors
- Astronomical Observations and Instrumentation
- Kruppel-like factors research
- Epigenetics and DNA Methylation
- Astronomy and Astrophysical Research
- Seismology and Earthquake Studies
- Subtitles and Audiovisual Media
- Healthcare and Environmental Waste Management
- Solar Radiation and Photovoltaics
- Economic Growth and Development
- Engineering Applied Research
- Material Properties and Applications
- Tribology and Wear Analysis
- Inertial Sensor and Navigation
- Industrial Vision Systems and Defect Detection
- Safety Systems Engineering in Autonomy
- Healthcare Technology and Patient Monitoring
- Energy Efficient Wireless Sensor Networks
University of Rajshahi
2025
Islamic University
2022-2024
Daffodil International University
2022
Prime University
2020
This research empirically examined the effect of internal and external factors on economic growth Bangladesh using annual data from 1976 to 2019. ARDL bounds tests were used detect cointegration understand dynamic effect. study mainly identified positive negative casualties because remittance export have a significant role, FDI has an adverse role in process. Furthermore, this recommends that government take appropriate steps increase export, inflow achieve long-run growth, considering...
Near-Earth asteroids (NEAs) are celestial bodies that orbit within close to Earth, offering valuable insights into the early solar system's formation and posing potential hazards due impact events. This work presents a comprehensive overview of NEAs, encompassing their historical significance, characteristics, hazards, prospects. The study outlines NASA Asteroids Classification Dataset discusses its importance for research on asteroid classification risk assessment. Furthermore, methodology...
Quality control in metal product manufacturing relies heavily on accurately detecting and classifying surface defects through visual inspection. Recently, convolutional neural networks (CNNs) have shown promising results automating this process with high accuracy. This research paper proposes a new (experimental version) Lite Convolutional Neural Network (LCNN) designed to analyze image data detect classify metallic surfaces. Our model was trained dataset comprising 1800 images of six...
Composite materials have emerged as a cornerstone of aerospace engineering due to their exceptional properties, such high strength-to-weight ratios, corrosion resistance, and superior mechanical performance. This research paper provides an in-depth analysis recent advancements in synthesizing composite tailored for applications. We review cutting-edge manufacturing techniques, explore the integration nanomaterials sustainable biocomposites, highlight five case studies illustrating practical...
In modern life, with the ability to perform tasks, virtual assistant (VA) can make our lives easier and smart. The as a librarian, very smartly, effectively. We build VA Raspberry Pi Alexa Voice Service. As result, few discussions that occur in library environments such find books, short review university notice are accurately performed. common way of communication used by people day life is through speech. If system be heard customer for handle affairs, then grant right reply, it will much...
Proper garbage classification is essential for effective waste management and environmental sustainability. This research paper presents a comprehensive study of using Convolutional Neural Networks (CNNs). The objective to develop an accurate automated system leveraging the power deep learning. proposed CNN model achieves impressive accuracy 98.45%, demonstrating its efficacy in classifying different categories. encompasses data collection, preprocessing, architecture, training methodology,...
This research comprehensively reviews the historical trajectory of exoplanet discovery. Delving into significant milestones, we highlight pivotal role in shaping our understanding exoplanetary systems. Building upon this foundation, propose an innovative approach employing a Lite Convolutional Neural Networks (LCNN) model for detection utilizing Kepler Dataset. By fusing advancements machine learning, particularly CNNs, with rich domain studies, represents stride towards automated,...
Gravitational waves are related to the concept of vibration space-time curvature. When body heavy masses lies on four-dimensional and changes their position with turbulence motion then actually they create a disturbance in space. The travels outward from origin having light velocity is known as gravitational waves. Laser Interferometer Gravitational-Wave Observatory (LIGO) scientific teamwork declared identification these In this paper, we review waves, Detection deep learning for...
Background: Cardiovascular disease is leading cause of mortality and morbidity in developed developing countries. Metabolic syndrome (MS) a risk factor for coronary artery (CAD). Objective: The aim this study to evaluate the angiographic severity patients with NSTEMI by Gensini score \Vessel score. Methods: This cross-sectional observational was done at National Institute Diseases (NICVD), Dhaka. A total 100 underwent angiography were included study. Coronary angiogram during index hospital...