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
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.
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.
MEMBER(S)
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...
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...
Utilizing Clustering Techniques to Analyze Climate and Environmental Factors Impacting Dengue Incidence in Bangladesh
This study explores the link between climatic factors and dengue fever in Bangladesh (2008–2018) using machine learning clustering techniques: K-means, DBSCAN, and Affinity Propagation (AP). Rainfall ...
Exploring Dengue Dynamics Through Simulation and Stochastic Modeling.
This study investigates the complex patterns of dengue disease transmission using simulation techniques and stochastic modeling. By capturing the inherent randomness and variability in disease dynami...
Optimal Control Strategies for Managing Marburg Virus Infections.
Optimal control strategies are designed using Pontryagin’s Maximum Principle to minimize the spread of infection. The study examines how individuals with robust immune systems influence the spread of ...
Effects of Short-Form Content on Attention and Social Interaction
This study examines the impact of short-form content consumption on attention span, cognitive performance, and social interactions among individuals aged 18–25. Participants were categorized based on ...
Weighted Residual Approximations of the System of Lane Emden Equations
Weighted residual approximations are numerical techniques used to model chemical reaction systems, particularly when solving complex reaction-diffusion equations. This method approximate the solution ...
PD_EBM: An Integrated Boosting Approach Based on Selective Features for Unveiling Parkinson's Disease Diagnosis with Global and Local Explanations
Early detection and characterization play a vital role in the treatment and management of Parkinson’s disease (PD). The rising prevalence of PD, along with its profound impact on motor neurons in the ...
Stability Analysis of Nipah Virus Using Immune System Enhancement as Control Strategy.
This study investigates the stability dynamics of Nipah virus transmission and examines how immune-system–enhancing control strategies can effectively reduce infection levels and promote long-term dis...
Modeling the Dynamics of Deforestation, Afforestation, and the Effects of Reforestation on Forests
We discuss the causes and detrimental effects of deforestation. We create mathematical models of afforestation and deforestation. We work on stability analysis and equilibrium points. Utilizing data, the models are solved numerically. To stop deforestation, we develop a mathematical model with reforestation conditions.
Prosocial behavior guided by an intervention game approach can restrain the rapid transmission of Covid-19.
This study explores how prosocial behavior, influenced by strategic intervention games, can effectively control the rapid spread of COVID-19. Leveraging mathematical modeling and game theory, it examines the impact of cooperative actions such as social distancing, mask-wearing, and vaccination on disease transmission dynamics. The intervention game approach simulates interactions among individuals, emphasizing the role of incentives and penalties in promoting behaviors that benefit public health.
The apparent incompatibility of the law of propagation of light with the Principal of relativity.
In this research, we initiate by Friedmann equation and work with Raychaudhuri equation for comparing of propagation of light and principal of Relativity
The significance of aspiration dynamics and imitative behavior in interim defense tactics to prevent the spread of epidemic diseases
Starting with the SIR compartmental model, we employ the mean-field approximation (MFA) methodology. We make use of strategy-based risk assessment (SB-RA) and master equations for the strategy updating rule. We then analyze this master equation for preference levels and aspirations that change throughout time. Intermediate defense measures are essential for curbing the spread of epidemics, preventing their escalation, and safeguarding public health and well-being
Dynamic Stochastic Adaptive Bio-Economic Model of Nile Tilapia Aquaculture
Developed a Dynamic Stochastic Adaptive Bioeconomic Model (DSABM) specifically for Nile Tilapia Aquaculture. Modeled the dynamic interactions between biological factors (growth rates, mortality rates) and economic variables (costs, prices) over time.
Analysis of the dual vaccine epidemic model with vaccination-age structures
A model of epidemic dynamics is proposed, which includes continuous variables for vaccination ages. The model examines vaccine effectiveness according to vaccination age. The age at which a person receives vaccinations affects their immunity to infection.