Predicting Plasma Vitamin C Using Machine Learning by Daniel Kirk (17302798)

“…The NHANES dataset was used to predict plasma vitamin C in a cohort of 2952 American adults using regression algorithms and clustering in a way that a hypothetical health application might. …”

Modeling and thermoeconomic analysis of new polygeneration system based on geothermal energy with sea water desalination and hydrogen production by Wulaer Shaersaikai (21436652)

“…With strong R-squared values and high predictive accuracy, the Random Forest machine learning model predicts exergy efficiency, freshwater production, unit specific product cost (USPC), net present value (NPV), and environmental impact. …”

Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification by Rajendra Babu Chikkala (22330876)

“…<p dir="ltr">In recent years, deep learning methods have dramatically improved medical image analysis, though earlier models faced difficulties in capturing intricate spatial and contextual details. …”

Enhanced Deep Belief Network Based on Ensemble Learning and Tree-Structured of Parzen Estimators: An Optimal Photovoltaic Power Forecasting Method by Mohamed Massaoudi (16888710)

“…The proposed forecasting tool incorporates a base model and meta-model layers. The first-layer base learner combines extreme learning machines, extremely randomized trees, k-nearest neighbor, and mondrian forest models. …”

Software-Defined-Networking-Based One-versus-Rest Strategy for Detecting and Mitigating Distributed Denial-of-Service Attacks in Smart Home Internet of Things Devices by Neder Karmous (19743430)

“…We employed an ML method based on Random Forest (RF), Logistic Regression (LR), k-Nearest Neighbors (kNN), and Naive Bayes (NB) with a One-versus-Rest (OvR) strategy and then compared our work to other related works. …”

Personalization in Real-Time Physical Activity Coaching Using Mobile Applications: A Scoping Review by Francisco Monteiro-Guerra (16864122)

Corona power loss computation in bundled bipolar conductors by Al-Hamouz, Z.M.

“…In this paper, a finite element (FE) based algorithm devoted for the computation of the corona current and hence the corona power loss associated with bundled bipolar high voltage direct current (HVDC) conductors is presented. …”
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Isolating Physical Replacement of Identical IoT Devices Using Machine and Deep Learning Approaches by Mohammad, Areej Osama

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Newton-Raphson based adaptive inverse control scheme for tracking of nonlinear dynamic plants by Shafiq, M.

“…The U-model is utilized to design an adaptive inverse controller by using a simple root-solving algorithm of Newton-Raphson. The synergy of U-model with AIC structure has provided an effective and straight forward method for adaptive tracking of nonlinear plants. …”
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Face Recognition in Uncontrolled Indoor Environment by Abuqaaud, Kamal Adel

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Simulations of the penetration of 6061-T6511 aluminum targets by spherical-nosed VAR 4340 steel projectiles by Warren, Thomas

“…In the context of an analysis code, this approximation eliminates the need for discretizing the target as well as the need for a contact algorithm. Thus, this method substantially reduces the computer time and memory requirements. …”
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A Fully Optical Laser Based System for Damage Detection and Localization in Rail Tracks Using Ultrasonic Rayleigh Waves: A Numerical and Experimental Study by Masurkar, Faeez

“…Further, As the quality of received signals differs at different sensing points as a result of the surface conditions of the specimen, the Self Adaptive Smart Algorithm (SASA) method was adopted to filter out the noise and accurately pinpoint the defect reflected wave packet which ultimately aids in better detection and localization. …”
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Vibration suppression in a cantilever beam using a string-type vibration absorber by Issa, Jimmy S.

“…The string is rigidly connected to the fixed end of the beam and through a spring and damper to a second point on the beam. The finite element method is used to model the system and a reduced order model is obtained through modal reduction performed on both the string and the beam. …”
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Application of Metastructures for Targeted Low-Frequency Vibration Suppression in Plates by Ratiba F. Ghachi (14152455)

“…The thin plate and the zigzag cutouts are modelled using the finite element method, and the optimal location and optimal tip mass of the zigzag cutouts are obtained using genetic algorithms through iterative simulations. …”

A Full-System Approach of the Elastohydrodynamic Line/Point Contact Problem by Habchi, Wassim

“…The use of the finite element method allows the use of variable unstructured meshing and different types of elements within the same model which leads to a reduced size of the problem. …”
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Predicting the Impact of Data Poisoning Attacks in Blockchain-Enabled Supply Chain Networks by Javed Butt , Usman

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Predicting Android Malware Using Evolution Networks by Chahine, Joy

“…We combine this model with genetic algorithms to optimize its parameters and return the best state transition probabilities, and we predict future malware accordingly. …”
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A FeedForward–Convolutional Neural Network to Detect Low-Rate DoS in IoT by Harun Surej Ilango (17545728)

“…The performance of FFCNN is compared to the machine learning algorithms-J48, Random Forest, Random Tree, REP Tree, SVM, and Multi-Layer Perceptron (MLP). …”

Communications in electronic textile systems by Nakad, Z.

“…Abstract- Electronic textiles (e-textiles) are emerging as a novel method for constructing electronic systems in wearable and large area applications. …”
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Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features by Mariam Bahameish (19255789)

“…This study employed supervised learning algorithms to classify stress and relaxation states using HRV measures. …”