Modelling Prediction Of Cities Real Estate Price Trend Using Recurrent Neural Network: A Case Of Dar Es Salaam City,
2023
1Department of Computer Science and Engineering, College of Information and Communication Technologies, University of Dar es Salaam
Modelling Prediction Of Cities Real Estate Price Trend Using Recurrent Neural Network: A Case Of Dar Es Salaam City, Ellen Kalinga
Tanzania Journal of Engineering and Technology (TJET)
Real estate refers to a class of real property such as land and its associated infrastructure. The prediction of real estate prices in cities, which is affected by a number of parameters, is an open research problem. The lack of reliable and effective tools for price forecasting in real estate, especially in residential housing, can adversely affect investment flows and the growth of the real estate sector. Taking Tanzania as an example, the price prediction practices rely on human suggestions that are prone to personal bias and subjective to price hysteria for personal gain and impact consumer expectations. To address …
Utilizing Non-Negative Least Squares For Data-Driven Discovery Of Dynamics,
2023
George Mason University
Utilizing Non-Negative Least Squares For Data-Driven Discovery Of Dynamics, Tracey G. Oellerich
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Computational Modeling Using A Novel Continuum Approach Coupled With Pathway-Informed Neural Networks To Optimize Dynein-Mediated Centrosome Positioning In Polarized Cells,
2023
George Mason University
Computational Modeling Using A Novel Continuum Approach Coupled With Pathway-Informed Neural Networks To Optimize Dynein-Mediated Centrosome Positioning In Polarized Cells, Arkaprovo Ghosal, Padmanabhan Seshaiyar Dr., Adriana Dawes Dr., General Genomics Inc.
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Understanding Impact Of Educational Awareness And Vaccines As Optimal Control Mechanisms For Changing Human Behavior In Disease Epidemics,
2023
George Mason University
Understanding Impact Of Educational Awareness And Vaccines As Optimal Control Mechanisms For Changing Human Behavior In Disease Epidemics, Manal Badgaish, Dr. Padmanabhan Seshaiyer
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Parameter Estimation In Epidemiological And Climate Models Using Ensemble Smoothing With Multiple Data Assimilation,
2023
George Mason University
Parameter Estimation In Epidemiological And Climate Models Using Ensemble Smoothing With Multiple Data Assimilation, Emmanuel Fleurantin
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Thoracoabdominal Asynchrony In A Virtual Preterm Infant: Computational Modeling And Analysis,
2023
Virginia Commonwealth University
Thoracoabdominal Asynchrony In A Virtual Preterm Infant: Computational Modeling And Analysis, Richard R. Foster, Bradford Smith, Laura Ellwein Fix
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Modeling Single And Multiple Pacemaker Interaction In Jellyfish Locomotion,
2023
Illinois State University
Modeling Single And Multiple Pacemaker Interaction In Jellyfish Locomotion, Alexander Hoover
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Minimization Of Diet For Optimum Consumption Using Linear Programming,
2023
Texas A&M University-Commerce
Minimization Of Diet For Optimum Consumption Using Linear Programming, Nita Ngozi Ezekwem, Aditi Ghosh
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Lnksc Method On Pde-Constrained Optimization For Mcf-7 Breast Cancer Cell Growth Predictions And Treatment Response With Gold Nanoparticles,
2023
Jarvis Christian College
Lnksc Method On Pde-Constrained Optimization For Mcf-7 Breast Cancer Cell Growth Predictions And Treatment Response With Gold Nanoparticles, Widodo Samyono, Shakhawat Bhuiyan
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Helices In Fluids And Applications To Modeling In Biology,
2023
James Madison University
Helices In Fluids And Applications To Modeling In Biology, Eva M. Strawbridge
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Disease Informed Neural Network And Mathematical Modeling Of Covid-19 With Human Behavior Modification,
2023
George Mason University
Disease Informed Neural Network And Mathematical Modeling Of Covid-19 With Human Behavior Modification, Alonso Gabriel Ogueda, Jeremis Morales-Morales, Carmen Caiseda, Padmanabhan Seshaiyer
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Physics-Informed Neural Networks For Agent-Based Epidemiological Model Calibration,
2023
Harvard University
Physics-Informed Neural Networks For Agent-Based Epidemiological Model Calibration, Alvan C. Arulandu, Padmanabhan Seshaiyer
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Modeling The Communication Dynamics In Human-Autonomy Teams: Insights From Search And Rescue Scenarios,
2023
Arizona State University at the Tempe Campus
Modeling The Communication Dynamics In Human-Autonomy Teams: Insights From Search And Rescue Scenarios, Carlos E. Bustamante Orellana, Lucero Rodriguez Rodriguez, Yun Kang
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Mathematical Modeling Of The Impact Of Lobbying On Climate Policy,
2023
Jack M Barrack Hebrew Academy
Mathematical Modeling Of The Impact Of Lobbying On Climate Policy, Andrew Jacoby, Claire Hannah, James Hutchinson, Jasmine Narehood, Aditi Ghosh, Padmanabhan Seshaiyer
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Convolutional Neural Network-Based Gene Prediction Using Buffalograss As A Model System,
2023
University of Nebraska-Lincoln
Convolutional Neural Network-Based Gene Prediction Using Buffalograss As A Model System, Michael Morikone
Complex Biosystems Program: Dissertations and Student Research
The task of gene prediction has been largely stagnant in algorithmic improvements compared to when algorithms were first developed for predicting genes thirty years ago. Rather than iteratively improving the underlying algorithms in gene prediction tools by utilizing better performing models, most current approaches update existing tools through incorporating increasing amounts of extrinsic data to improve gene prediction performance. The traditional method of predicting genes is done using Hidden Markov Models (HMMs). These HMMs are constrained by having strict assumptions made about the independence of genes that do not always hold true. To address this, a Convolutional Neural Network (CNN) …
Rigid Body Constrained Motion Optimization And Control On Lie Groups And Their Tangent Bundles,
2023
Embry-Riddle Aeronautical University
Rigid Body Constrained Motion Optimization And Control On Lie Groups And Their Tangent Bundles, Brennan S. Mccann
Doctoral Dissertations and Master's Theses
Rigid body motion requires formulations where rotational and translational motion are accounted for appropriately. Two Lie groups, the special orthogonal group SO(3) and the space of quaternions H, are commonly used to represent attitude. When considering rigid body pose, that is spacecraft position and attitude, the special Euclidean group SE(3) and the space of dual quaternions DH are frequently utilized. All these groups are Lie groups and Riemannian manifolds, and these identifications have profound implications for dynamics and controls. The trajectory optimization and optimal control problem on Riemannian manifolds presents significant opportunities for theoretical development. Riemannian optimization is an attractive …
A Multitask Learning Framework For Pilot Decontamination In 5g Massive Mimo,
2023
University of Dodoma, Dodoma
A Multitask Learning Framework For Pilot Decontamination In 5g Massive Mimo, Crallet Victor
Tanzania Journal of Engineering and Technology (TJET)
Reference signals enable the acquisition of channel state information (CSI) for purposes such as channel estimation, beam selection, precoding, and symbol detection in 5G massive multiple-input multiple output (MAMIMO) systems. Eventually, as more and more users and cells are added, orthogonal reference signals become few which leads to pilot contamination. Pilot contamination limits the performance and occurs when non-orthogonal reference signals occupy time-frequency resources that are alike. Learning-based techniques have been proposed to alleviate it. However, each can only learn to perform a single task namely pilot assignment, power allocation, pilot design, or de-noising for pilot decontamination. In addition, each …
Modeling Nonsegmented Negative-Strand Rna Virus (Nnsv) Transcription With Ejective Polymerase Collisions And Biased Diffusion,
2023
Baylor College of Medicine
Modeling Nonsegmented Negative-Strand Rna Virus (Nnsv) Transcription With Ejective Polymerase Collisions And Biased Diffusion, Felipe-Andres Piedra
Research Symposium
Background: The textbook model of NNSV transcription predicts a gene expression gradient. However, multiple studies show non-gradient gene expression patterns or data inconsistent with a simple gradient. Regarding the latter, several studies show a dramatic decrease in gene expression over the last two genes of the respiratory syncytial virus (RSV) genome (a highly studied NNSV). The textbook model cannot explain these phenomena.
Methods: Computational models of RSV and vesicular stomatitis virus (VSV – another highly studied NNSV) transcription were written in the Python programming language using the Scientific Python Development Environment. The model code is freely available on GitHub: …
An Implementation Of The Method Of Moments On Chemical Systems With Constant And Time-Dependent Rates,
2023
University of Alabama, Tuscaloosa
An Implementation Of The Method Of Moments On Chemical Systems With Constant And Time-Dependent Rates, Emmanuel O. Adara, Roger B. Sidje
Northeast Journal of Complex Systems (NEJCS)
Among numerical techniques used to facilitate the analysis of biochemical reactions, we can use the method of moments to directly approximate statistics such as the mean numbers of molecules. The method is computationally viable in time and memory, compared to solving the chemical master equation (CME) which is notoriously expensive. In this study, we apply the method of moments to a chemical system with a constant rate representing a vascular endothelial growth factor (VEGF) model, as well as another system with time-dependent propensities representing the susceptible, infected, and recovered (SIR) model with periodic contact rate. We assess the accuracy of …
Boundary Integral Equation Methods For Superhydrophobic Flow And Integrated Photonics,
2023
New Jersey Institute of Technology
Boundary Integral Equation Methods For Superhydrophobic Flow And Integrated Photonics, Kosuke Sugita
Dissertations
This dissertation presents fast integral equation methods (FIEMs) for solving two important problems encountered in practical engineering applications.
The first problem involves the mixed boundary value problem in two-dimensional Stokes flow, which appears commonly in computational fluid mechanics. This problem is particularly relevant to the design of microfluidic devices, especially those involving superhydrophobic (SH) flows over surfaces made of composite solid materials with alternating solid portions, grooves, or air pockets, leading to enhanced slip.
The second problem addresses waveguide devices in two dimensions, governed by the Helmholtz equation with Dirichlet conditions imposed on the boundary. This problem serves as a …
