7. Hemodynamical behavior analysis of anemic, diabetic, and healthy blood flow in the carotid artery
Authors - Hashnayne Ahmed*, Chinmayee Podder
10.1016/j.heliyon.2024.e26622 - February 2024 - Open Access Link
Journal: Heliyon
Publisher: Cell Press
Abstract
The influence of blood rheology on hemodynamic parameters is investigated using Computational Fluid Dynamics on blood flow through the human carotid artery. We performed three-dimensional modeling and simulation to study blood flow through the carotid artery, which is divided into internal and exterior parts with a decreased radius. The blood flow was classified as basic pulsatile to simulate the human heart's rhythmic pulses. For hemodynamic modeling viscosity of the fluid, the Carreau model was utilized with four distinct blood instances: Anemic, diabetic, and two healthy blood types. The boundary conditions with Carreau viscosity were applied using the Ansys Fluent simulator, and the governing equations were solved using the finite volume technique. Different time steps were tested for their impact on wall deformation, strain rate, blood velocity, pressure, wall shear, and skin friction coefficient. The hemodynamical parameters were calculated using many cross-sectional planes along the artery. Finally, the impact of the four types of blood cases listed above was investigated, and we discovered that each blood case has a substantial impact on blood velocity, pressure, wall shear, and strain rate along the artery.
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6. Mathematical Modeling for Launch Vessel Operators at Internal Waterways Transportation in Bangladesh
Authors - Tanzila Yeasmin Nilu, Hashnayne Ahmed, Shek Ahmed
10.3329/gubjse.v6i1.52050 - October 2020 - Open Access Link
Journal: GUB Journal of Science and Engineering
Publisher: Green University Press
Abstract
Launch-based water vessel transportation has been growing in Bangladesh as an easier and cheaper transportation system. The shipping liners introducing more launches in different routes because of their growing demands. However, this trade sector is imbalanced in terms of profits in several service categories and uncertainties are a common issue faced by the liner operators. In this paper, we consider the launch vessel operators' profit scenarios to give a broad idea by considering different stochastic parameters to meet the customer's demand over time and maximize the profit. We need to make the decision about building launches as per demand categories and also to maximize the profit. We show how scenario-based stochastic optimization could be applied in this perspective and discuss some solving techniques with modification as required. Finally, we conduct a numerical case study to evaluate the value of the stochastic scenario-based model over some uncertain issues according to the model.
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5. Analysis of Diet Choice towards a Proper Nutrition Plan by Linear Programming
Authors - Tanzila Yeasmin Nilu*, Shek Ahmed, Hashnayne Ahmed
10.11648/j.sjams.20200805.12 - September 2020 - Open Access Link
Journal: Science Journal of Applied Mathematics and Statistics
Publisher: SciencePG
Abstract
Linear Programming is an optimization technique to attain the most effective outcome or optimize the objective function (like maximum profit or lowest cost) in a mathematical model whose requirements are represented by linear relationships called constraints. In this paper, we have discussed fundamental and detailed techniques for formulating LP models in various real-life decision problems, decisions, works, etc. In the human body, an unhealthy diet can cause a lot of nutrition-related diseases. Sometimes, having a proper diet costs beyond one’s limit and it affects us to develop a diet-based budget-friendly nutrition model. Our goal is to minimize the total cost considering the required amount of nutrition values required. To construct the study we took some standard values of nutrition ingredients to compute the budget-friendly values. It's quite hard to resolve most of the real-life models with a large number of decision variables & constraints by hand calculations implying the use of AMPL (A Mathematical Programming Language) coding to get the optimal result. The number of variables & constraints doesn't matter in any respect for the computer techniques used in this study. This study results in some standard values of diet plans for optimizing the nutrition for a particular person with limited costs.
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4. A Proposed Linear Programming-Based Algorithm to Solve Arc Routing Problems
Author - Hashnayne Ahmed*
10.5815/ijmsc.2020.02.03 - April 2020 - Open Access Link
Journal: International Journal of Mathematical Sciences and Computing
Publisher: MECS Press
Abstract
A new linear programming-based algorithm has been demonstrated to find the best arc routing method. In most arc routing problems, the main goal is to minimize the total cost of the lane. To find the minimum cost-giving lane, the existing algorithms find the smallest possible sum of weights by ticking the shortest paths. The proposed computer-based algorithm is based on focusing on the minimized total cost with some constraint criteria of fixed values. The routes are marked with a series of variables that may differ according to the lane choice and more accurately estimate the exact total cost considering the remaining weight. Finally, a stochastic model for private company vehicle transport has been discussed with some possible solution expectations.
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3. A Comparative Study on Harvesting Plan Predicting Insurance with Two-Stage Stochastic Analysis
Authors - Hashnayne Ahmed*, Shek Ahmed
10.11648/j.ijdst.20190504.12 - December 2019 - Open Access Link
Journal: International Journal on Data Science and Technology
Publisher: SciencePG
Abstract
The exception of considering uncertainty could be very detrimental to the outcomes of any systems or phenomena in the long run. The stochastic Process describes the way of considering uncertainty in different sectors of our life. We use Linear Programming for planning at its best. It is also considered the best optimization technique for making decisions or planning. But this planning tool disappoints us in optimization for unexpected risk or stochasticity. Consideration of stochasticity for a farmer to devote land to different crops for harvesting could be some insurance for the farmer with the best possible outcomes. Stochastic Programming studies these types of optimization techniques with risk consideration for better decisions at every step of our lives. In this paper, we described the early starting of uncertainty calculation or stochastic approach and the evolution of stochastic optimization fields. Stochastic optimization is rather important in uncertainty calculation than sensitivity analysis and works through data gained from experience. We also present a stochastic model with some uncertainty issues in harvesting to make better outcomes. Some application areas are also discussed.
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2. Formulation of Two-Stage Stochastic Programming with Fixed Recourse
Author - Hashnayne Ahmed*
10.33258/bioex.v1i1.23 - August 2019 - Open Access Link
Journal: Britain International of Exact Sciences (BIoEx) Journal
Publisher: BIAR Publisher
Abstract
Stochastic Programming is an asset for the next world researchers due to its uncertainty calculations, which have been skipped in deterministic world experiments as it includes complicated calculations. Two-stage stochastic programming concerns two time period decisions based on some random parameters obtained from experience or some sort of survey. The objective function for formulating two-stage stochastic programming with fixed recourse includes first-stage forecast and second-stage fixed decisions based on the experiment results. The constraints are similar to the normal optimization techniques rather than some adjustments of requirements and technology assets. The fixed recourse decisions are sort of decisions from the deterministic world. Formulation techniques of two-stage stochastic programming with fixed recourse may be used for further complications that arise in stochastic programming like complete recourse problems, multi-stage problems, etc. And that’s why Two-stage stochastic programming with fixed recourse is called the primary model for stochastic programming.
[Indexed by CrossRef, Publons (Clarivate Analytics)] [Google Scholar Citations]
1. Graph Routing Problem Using Euler's Theorem and Its Applications
Author - Hashnayne Ahmed*
10.11648/j.engmath.20190301.11 - June 2019 - Open Access Link
Journal: Engineering Mathematics
Publisher: SciencePG
Abstract
In this modern era, time and cases related to time are very important to us. For shortening time, the Eulerian Circuit can open a new dimension. In computer science, social science, and natural science, graph theory is a stimulating space for the study of proof techniques. Graphs are also effective in modeling a variety of optimization cases like routing protocols, network management, stochastic approaches, street mapping, etc. Konigsberg Bridge Problem has seven bridges linked with four islands detached by a river in such a way that one can't walk through each of the bridges exactly once and return to the starting point. Leonard Euler solved it in 1735 which is the foundation of modern graph theory. Euler's solution for the Konigsberg Bridge Problem is considered as the first theorem of Graph Theory which gives the idea of the Eulerian circuit. It can be used in several cases for shortening any path. From the Konigsberg Bridge Problem to the ongoing DNA fragmentation problem, it has its applications. Aiming to build such a dimension using Euler's theorem and the Konigsberg Bridge Problem, this paper presents the history of the remarkable Konigsberg Bridge Problem, Euler's Explanation of it, an alternative explanation, and some applications to the Eulerian Circuit using graph routing and Fortran Coding of it.
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