Cutting‐edge technologies for detecting and controlling fish diseases: Current status, outlook, and challenges حسب Sk Injamamul Islam (14111241)

"…Here, we highlighted the potential of machine learning algorithms in early pathogen detection and the possibilities of intelligent aquaculture in controlling disease outbreaks at the farm level. …"

Exploring the System Dynamics of Covid-19 in Emergency Medical Services حسب Ali, Muhammad

"…The predictive analysis yielded a model of response times for emergency missions through machine learning, specifically using a random forest algorithm. …"
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Multi-class subarachnoid hemorrhage severity prediction: addressing challenges in predicting rare outcomes حسب Muhammad Mohsin Khan (22150360)

"…In the first stage, we performed binary classification, grouping SAH severity into “Good Outcome” (class 0), which includes MRS levels 0, 1, 2, and 3, and “Poor Outcome” (class 1), encompassing levels 4, 5, and 6. …"

Artificial intelligence models for predicting the mode of delivery in maternal care حسب Rawan AlSaad (14159019)

"…The dataset included 12,639 vaginal deliveries and 4012 unplanned cesarean deliveries, with 92 variables recorded for each patient. Five machine learning algorithms were evaluated: XGBoost, AdaBoost, random forest, decision tree, and multi-layer perceptron (MLP) classifier. …"

Peripheral inflammatory and metabolic markers as potential biomarkers in treatment-resistant schizophrenia: Insights from a Qatari Cohort حسب Mohamed Adil Shah Khoodoruth (14589828)

"…The Random Forest model, a supervised machine learning algorithm, efficiently differentiated between cases and controls and between TRS and NTRS, with accuracies of 86.87 % and 88.41 %, respectively. …"

Extremely boosted neural network for more accurate multi-stage Cyber attack prediction in cloud computing environment حسب Surjeet Dalal (4906894)

"…This paper demonstrated the results of executing various machine learning algorithms and proposed an enormously boosted neural network. …"

Diabetic Sensorimotor Polyneuropathy Severity Classification Using Adaptive Neuro Fuzzy Inference System حسب Fahmida Haque (16896489)

"…The model accuracy was validated with the results from different machine learning algorithms. The Accuracy, sensitivity, and specificity of the ANFIS model are 91.17±1.18%, 92±2.26%, 96.72±0.93%, respectively. …"

Recursive Parameter Identification Of A Class Of Nonlinear Systems From Noisy Measurements حسب Emara-Shabaik, Husam

"…The model structure is made up of two linear dynamic elements separated by a nonlinear static one. The nonlinear element is assumed to be of the polynomial type with known order; The identification is based on input/output data where the output is contaminated with measurement noise. …"
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Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information حسب M. Ghoniem, Rania

"…This basically follows either a feature-level or decision-level strategy. In all likelihood, while features from several modalities may enhance the classification performance, they might exhibit high dimensionality and make the learning process complex for the most used machine learning algorithms. …"
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A hybrid approach for XML similarity حسب Tekli, Joe

"…Various algorithms for comparing hierarchically structured data, e.g. …"
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On the complexity of multi-parameterized cluster editing حسب Abu-Khzam, Faisal

"…In other words, Cluster Editing can be solved efficiently when the number of false positives/negatives per single data element is expected to be small compared to the minimum cluster size. …"
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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 حسب Masurkar, Faeez

"…Finally, a 3D Finite Element simulation was conducted to validate the findings and each observation resulting from the experiments. …"
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Estimating Bridge Deterioration Age Using Artificial Neural Networks حسب AL HUSSEIN, ASEEL

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An Alternating Projection Framework for Elementwise Masked Nonlinear Matrix Decomposition حسب Kulathil, Muhammed Noshin Poovan

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An Artificial Intelligence Approach for Predictive Maintenance in Electronic Toll Collection System حسب Alkhatib, Osama

"…Historical data of Dubai Toll Collection System is utilized to investigate multiple machine learning algorithms. …"
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Smart non-intrusive appliance identification using a novel local power histogramming descriptor with an improved k-nearest neighbors classifier حسب Yassine Himeur (14158821)

"…Specifically, short local histograms are drawn to represent individual appliance consumption signatures and robustly extract appliance-level data from the aggregated power signal. Furthermore, an improved k-nearest neighbors (IKNN) algorithm is presented to reduce the learning computation time and improve the classification performance. …"

Application of Data Mining to Predict and Diagnose Diabetic Retinopathy حسب Haniyeh, Maryam

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Crashworthiness optimization of composite hexagonal ring system using random forest classification and artificial neural network حسب Monzure-Khoda Kazi (17191207)

"…Advanced machine learning algorithms are used in this study to figure out the complicated relationship between the crashworthiness parameters of the hexagonal composite ring specimens under lateral compressive, energy absorption, and failure modes. …"

Integration of nonparametric fuzzy classification with an evolutionary-developmental framework to perform music sentiment-based analysis and composition حسب Abboud, Ralph

"…Unlike existing solutions, MUSEC is: (i) a hybrid crossover between supervised learning (SL, to learn sentiments from music) and evolutionary computation (for music composition, MC), where SL serves at the fitness function of MC to compose music that expresses target sentiments, (ii) extensible in the panel of emotions it can convey, producing pieces that reflect a target crisp sentiment (e.g., love) or a collection of fuzzy sentiments (e.g., 65% happy, 20% sad, and 15% angry), compared with crisp-only or two-dimensional (valence/arousal) sentiment models used in existing solutions, (iii) adopts the evolutionary-developmental model, using an extensive set of specially designed music-theoretic mutation operators (trille, staccato, repeat, compress, etc.), stochastically orchestrated to add atomic (individual chord-level) and thematic (chord pattern-level) variability to the composed polyphonic pieces, compared with traditional evolutionary solutions producing monophonic and non-thematic music. …"
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Exploratory risk prediction of type II diabetes with isolation forests and novel biomarkers حسب Yousef, Hibba

"…In this study, we developed an interpretable machine learning model leveraging baseline levels of biomarkers of oxidative stress (OS), inflammation, and mitochondrial dysfunction (MD) for identifying individuals at risk of developing T2DM. …"
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