Mathematical Modelling

The Mathematical Modeling Research Group serves as a dynamic platform for versatile researchers who thrive on developing mathematical models for implementation in cutting-edge science and engineering fields, including the realm of data science. This community provides a collaborative space for individuals passionate about leveraging mathematical frameworks to address complex challenges and advance the frontiers of scientific and engineering knowledge. Members of this group are not only enthusiastic about theoretical modeling but also actively engage in applying these models to real-world scenarios, contributing to the ongoing evolution of state-of-the-art practices in science, engineering, and data science.

INTEREST(S)

Machine LearningEducationPublic HealthData Science DemographyNatural Language Processing Blockchain Technology

MISSION

The mission of Mathematical Modeling Research Group is to apply advanced mathematical models to unravel intricate real-world phenomena, offering predictive insights and innovative solutions. Focused on interdisciplinary collaboration, innovation, and ethical practices, we strive to impact diverse fields globally, fostering a dynamic research environment that contributes to societal well-being and scientific advancement.

VISION

Pioneering a future where our mathematical modeling research group transforms complex real-world challenges into precise, innovative solutions. We envision cross-disciplinary impact, global recognition, and a commitment to ethical and sustainable practices, pushing the boundaries of mathematical modeling for the betterment of society and the advancement of knowledge.

Current Trends and Future Trajectories: Polymer-Modified Concrete in the Context of Bangladesh

Polymer-modified concrete (PMC) presents itself as a novel way to improve the characteristics of conventional concrete, tackling a variety of issues in the building industry. This paper explores the p...

Quantifying Climate Change Effects on Standard Minimum and Maximum Average Temperature Extremes in Bangladesh: A Machine Learning Regression Analysis from Past to Present

The impact of climate change on temperature extremes is particularly significant in regions like Bangladesh, and it is a pressing global concern. To quantify the effects of climate change on Banglades...

A Hybrid Deep Learning Framework for Detecting Human Stress from Multimodal Physiological Data

Stress is a widespread aspect of daily life that individuals often encounter in different situations. But prolonged or intense stress can compromise our well-being and disrupt our routines. When indiv...

Vibration control of a cable structure via a flexible piezoelectric damper and energy harvesting

A piezoelectric damper has been designed to control the vibration of a straight single cable structure, tuned with the shunt circuits. The optimal placement of the damper, and optimization of geometri...

An effective technique for the enhancement of images

This paper proposes a straightforward, effective, and time-efficient fuzzy technique for image contrast enhancement (ICE) with vagueness reduction, entropy conservation, and mean brightness preservati...

XMLPD: Explainable Ensemble Machine Learning Approach for Parkinson Disease Prediction at Early stage

Parkinson's disease is the primary cause of global mortality connected to the brain. Timely identification and diagnosis of Parkinson's disease can significantly enhance the likelihood of patient surv...

Statistical Perspectives on the Multidimensional Environmental Decline in Bangladesh

This study uses a statistical method to analyze the complex interactions between environmental elements that affect Bangladesh in order to address the various issues brought about by environmental de...

From Detection to Disruption: Leveraging NLP Insights to Proactively Combat Cybercrime in Bangladesh

In an era marked by the escalating prevalence and sophistication of cyber threats, the imperative for robust cybersecurity measures has reached a critical juncture, especially for nations in developme...

Singular value decomposition-base fuzzy method for enhancing visual quality of images captured in poor illumination environment

This research proposes an SVD and fuzzy-based method for poorly illuminated image contrast enhancement. First, it fuzzifies an image with a fuzzifier. Next, it defuzzifies the fuzzified image with a d...

A compendious study on histogram equalization for natural image contrast enhancement

Contrast enhancement plays a vital role in highlighting the visual features of contrast-distorted images. Histogram equalization is a popular CE method, although it fails to maintain the natural appea...