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Parallel implementation of clique partitioning using artificial neural networks. (c2000)
Published 2000Get full text
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masterThesis -
103
A reduced model for phase-change problems with radiation using simplified PN approximations
Published 2025“…The integro-differential equation for the full radiative transfer is replaced by a set of differential equations which are independent of the angle variable and easy to solve using conventional computational methods. To solve the coupled equations, we implement a second-order implicit scheme for the time integration and a mixed finite element method for the space discretization. …”
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104
Brain Source Localization in the Presence of Leadfield Perturbations
Published 2015Get full text
doctoralThesis -
105
An Effective Hash Based Assessment and Recovery Algorithm for Healthcare Systems
Published 2019Get full text
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masterThesis -
106
A fast exact sequential algorithm for the partial digest problem
Published 2016“…Two types of simulated data, random and Zhang, are used to measure the efficiency of the algorithm. …”
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107
Forecasting the nearly unforecastable: why aren’t airline bookings adhering to the prediction algorithm?
Published 2021“…The Individual Behavior Framework theory provides insights into possibly explaining this inconsistency in evaluation outcomes. Research results indicate that algorithmic approaches in competitive industries must account for shifting customer preferences, changes to the travel environment, and confounding business effects rather than relying solely on historical data.…”
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Predicting Dropouts among a Homogeneous Population using a Data Mining Approach
Published 2019“…Our research reveals that the Gradient Boosted Trees is a robust algorithm that predicts dropouts with an accuracy of 79.31% and AUC of 88.4% using only pre-enrollment data. …”
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110
Methodology for Analyzing the Traditional Algorithms Performance of User Reviews Using Machine Learning Techniques
Published 2020“…Based on the semantics of reviews of the applications, the results of the reviews were classified negative, positive or neutral. In this research, different machine-learning algorithms such as logistic regression, random forest and naïve Bayes were tuned and tested. …”
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Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval
Published 2024“…Unfortunately, PCA’s reliability drops when data has nonlinear characteristics as industrial processes. …”
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Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study
Published 2024“…</p><h3>Methods</h3><p dir="ltr">We conducted an analysis to identify research gaps in COVID-19 literature using the COVID-19 Open Research (CORD-19) data set, which comprises 1,121,433 papers related to the COVID-19 pandemic. …”
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113
A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
Published 2022“…Due to a limited training dataset, an ML-based IDS generates a higher false detection ratio and encounters data imbalance issues. To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …”
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Monitoring Bone Density Using Microwave Tomography of Human Legs: A Numerical Feasibility Study
Published 2021“…This study was performed using an in-house finite-element method contrast source inversion algorithm (FEM-CSI). …”
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116
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Large-scale annotation dataset for fetal head biometry in ultrasound images
Published 2023“…Its detailed annotations, broad compatibility, and ethical compliance make it a highly reusable and adaptable tool for the development of algorithms aimed at improving maternal and Fetal health.…”
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118
A parallel ant colony optimization to globally optimize area in high-level synthesis. (c2011)
Published 2011Get full text
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masterThesis -
119
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