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All Journal IAES International Journal of Robotics and Automation (IJRA) International Journal of Reconfigurable and Embedded Systems (IJRES) Bulletin of Electrical Engineering and Informatics International Journal of Accounting and Management Information Systems
Kashem, Mohammod Abul
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Automotive Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering

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A holistic approach of stability using material parameters of manipulators Mustary, Shabnom; Kashem, Mohammod Abul; Chowdhury, Mohammad Asaduzzaman; Uddin, Jia
IAES International Journal of Robotics and Automation (IJRA) Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v13i4.pp380-390

Abstract

The demand for a comprehensive method to assess stability using manipulator material parameters is high. Various material parameters, such as the Young modulus, which represents stiffness, damping, and deflection, influence the material of the robot manipulator. The correlation between robot stability and these characteristics remains unclear, as prior studies have not yet examined the collective impact of these parameters on robot manipulators. This work considers two sophisticated manipulators, namely ABB and FANUC. The main objective of this research is to construct a stability model that considers the material properties of stiffness, damping, and deflection to assess the manipulator’s stability level, which may be categorized as low, medium, or high. Furthermore, the presented stability model examines and employs numerous modified and conventional formulas for material properties to determine the level of stability. The findings show that stiffness significantly influences the stability of robot manipulators, a relationship that applies to all the examined manipulators. We also emphasize that the choice of manipulator materials significantly impacts stability maintenance. These findings are expected to enhance the design and advancement of novel robot manipulators within the industry.
A cost-effective ECG monitoring in rural areas: leveraging artificial neural networks for efficient healthcare solutions Rahaman, Md Obaidur; Kashem, Mohammod Abul
Bulletin of Electrical Engineering and Informatics Vol 13, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i3.6866

Abstract

Cardiovascular diseases engender serious public health concerns in developing nations since access to specialized medical equipment is often limited and standard treatment expenses can be prohibitive. This study proposes an efficient and relatively affordable electrocardiogram (ECG) monitoring system that reads and analyzes a person's electrocardiogram data to provide affordable and quality healthcare solutions. The device initially extracts features from electrocardiogram records by reading electrical signals in the heart. Extracted data are then analyzed by a trained deep learning model to determine precisely if the heart is in a healthy state or undergoing complexities. Experimental results showed that the fine-tuned ANN architecture outperformed the state-of-the-art architectures in this field with an accuracy of 98.95%. The data can also be sent to specialists through an MQTT server if necessary, allowing for remote diagnosis and treatment. The system is intended to be deployed in countries where rural regions lack access to specialized healthcare equipment and professionals. Additionally, the device is inexpensive and, hence can be made accessible to people with limited affordability.
Algorithm-driven development of a simulation tool for industrial manipulator stability analysis Mustary, Shabnom; Kashem, Mohammod Abul; Chowdhury, Mohammad Asaduzzaman; Uddin, Jia
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 14, No 1: March 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v14.i1.pp69-78

Abstract

Industrial manipulators are essential to many manufacturing processes because they increase efficiency and productivity dramatically. However, maintaining operational safety and averting potential risks in industrial environments requires that these manipulators be stable. The development and implementation of an entirely algorithm-driven novel simulation tool intended to assess industrial manipulators’ stability in-depth are presented in this research. The suggested tool combines sophisticated mathematical models with the material properties of the manipulator, such as deflection, stiffness, and damping. To analyses the dynamic behaviour of manipulators under various operating situations, a hypothetical simulation technique to assess the stability of robot manipulators combined with material properties is taken into consideration. The simulation tool offers vital insights into the stability characteristics of manipulators, allowing engineers and designers to enhance their performance and guarantee operational safety. The simulation tool’s usefulness is showcased through case studies and comparative evaluations, emphasizing its capacity to improve the design and implementation of industrial manipulators in practical situations. In summary, this research enhances the field of industrial automation by offering a strong framework for assessing and upgrading the stability of manipulator systems. This, in turn, improves productivity and safety in industrial settings.
Maternal healthcare using IoT-based integrated medical device: Bangladesh perspective Kashem, Mohammod Abul; Ahmed, Marzia; Mohammad, Naderuzzaman
International Journal of Accounting and Management Information Systems Vol. 3 No. 2 (2025): August
Publisher : Goodwood Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/ijamis.v3i2.3288

Abstract

Purpose: The main purpose of this study was to develop a low-cost integrated medical device. This device will help investigate the risk levels of pregnant patients and reduce the cost of medical diagnosis for poor countries such as Bangladesh, where maternal healthcare is a great concern. Research Methodology: A device equipped with multiple sensors was developed to collect raw data from pregnant patients. This data is transmitted to the cloud, where open-source algorithms process and analyze it to identify patient risk levels. Results: We developed the system, collected raw data from patients, and uploaded these data to our cloud system. The data were processed in the cloud, and the resultant data were presented in the form of graphs. From these graphs, the risk levels were determined. Conclusion: The IoT-based integrated device showed approximately 93% accuracy compared with conventional methods. It is a cost-effective, scalable, and adaptable solution that is suitable for maternal healthcare in developing countries. Features such as plug-and-play sensors, real-time cloud processing, and machine learning-based diagnostics make it a promising innovation for reducing maternal and infant mortality rates. Limitations: The device is designed solely for use in pregnant patients and requires authorization from health regulators. Some high-cost sensors were excluded to ensure affordability.. Contribution: The main contribution of this study is to minimize the costs involved in maternal healthcare in poor countries such as Bangladesh. This, in turn, controls the death of mothers and children by improving maternal healthcare facilities.
Co-Authors Ahmed, Marzia Chowdhury, Mohammad Asaduzzaman Mohammad, Naderuzzaman Mustary, Shabnom Rahaman, Md Obaidur Uddin, Jia