Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information حسب M. Ghoniem, Rania

"…For classifying unimodal data of either speech or EEG, a hybrid fuzzy c-means-genetic algorithm-neural network model is proposed, where its fitness function finds the optimal fuzzy cluster number reducing the classification error. …"
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Enhanced PSO-Based NN for Failures Detection in Uncertain Wind Energy Systems حسب Khaled Dhibi (16891524)

"…First, a feature selection tool using PSO Algorithm is developed. Then, in order to maximize the diversity between data samples and improve the effectiveness of using PSO algorithm for feature selection, the Euclidean distance metric is used in order to reduce the data and maximize the diversity between data samples. …"

Wide area monitoring system operations in modern power grids: A median regression function-based state estimation approach towards cyber attacks حسب Haris M. Khalid (17017743)

"…The algorithm was stationed at each monitoring node using interacting multiple model (IMM)-based fusion architecture. …"

Scatter search metaheuristic for homology based protein structure prediction. (c2015) حسب Stamboulian, Mouses Hrag

"…We assess our algorithm on a total of 11 proteins whose structures are present in the Protein Data Bank (PDB) and which has been used in previous literature. …"
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Machine learning based approaches for intelligent adaptation and prediction in banking business processes. (c2018) حسب Tay, Bilal M.

"…Companies, nowadays, rely on systems and applications to automate their business processes and data management. In this context, the notion of integrating machine learning techniques in banking business processes has emerged, where trainable computational algorithms can be improved by learning. …"
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Frontiers and trends of supply chain optimization in the age of industry 4.0: an operations research perspective حسب Zhitao Xu (2426023)

"…Furthermore, we recommend four promising research avenues in this interplay: (1) incorporating new decisions relevant to data-enabled SC decisions, (2) developing data-enabled modeling approaches, (3) preprocessing parameters, and (4) developing data-enabled algorithms. …"

Automatic and Intelligent Stressor Identification Based on Photoplethysmography Analysis حسب Sami Elzeiny (16891521)

"…This work leverages the output of wearable technology to provide automatic stress and stressor identification model. In particular, this study proposes a novel algorithm that first detects instances of stress and then classifies the stressor type using photoplethysmography (PPG) data from wearable smartwatches. …"

Enhancing e-learning through AI: advanced techniques for optimizing student performance حسب Rund Mahafdah (21399854)

Interpreting patient-Specific risk prediction using contextual decomposition of BiLSTMs: application to children with asthma حسب Rawan AlSaad (14159019)

"…<h3>Background</h3><p dir="ltr">Predictive modeling with longitudinal electronic health record (EHR) data offers great promise for accelerating personalized medicine and better informs clinical decision-making. …"

VEGAWES: variational segmentation on whole exome sequencing for copy number detection حسب Samreen Anjum (19651882)

Artificial Intelligence (AI) based machine learning models predict glucose variability and hypoglycaemia risk in patients with type 2 diabetes on a multiple drug regimen who fast d... حسب Tarik Elhadd (5480393)

"…<h3>Objective</h3><p dir="ltr">To develop a machine-based algorithm from clinical and demographic data, physical activity and glucose variability to predict hyperglycaemic and hypoglycaemic excursions in patients with type 2 diabetes on multiple glucose lowering therapies who fast during Ramadan.…"

Multi-class subarachnoid hemorrhage severity prediction: addressing challenges in predicting rare outcomes حسب Muhammad Mohsin Khan (22150360)

"…Feature selection was done using a Random Forest algorithm to identify the top 20 features for the SAH severity prediction. …"

Transmission Line Fault Location Using Unsynchronized Measurements حسب Hussain, Shoaib

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Performance Analysis of Artificial Neural Networks in Forecasting Financial Time Series حسب Lasfer, Assia

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The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review حسب Zainab Jan (17306614)

"…We identified different machine learning models used in the selected studies, including classification models (18, 55%), regression models (5, 16%), model-based clustering methods (2, 6%), natural language processing (1, 3%), clustering algorithms (1, 3%), and deep learning–based models (3, 9%). …"

A multi-pretraining U-Net architecture for semantic segmentation حسب Cagla Copurkaya (22502042)

"…For the validation of the proposed model, we used data from 21,000 cell nuclei at a resolution of 1000 by 1000 pixels. …"

Prediction of biogas production from chemically treated co-digested agricultural waste using artificial neural network حسب Fares Almomani (12585685)

"…An Artificial neural network (ANN) algorithm was developed to model and optimize the cumulative methane production (CMP) from ASWs, CM, and their mixture under mesophilic and thermophilic conditions. …"

Ensemble Deep Random Vector Functional Link Neural Network for Regression حسب Minghui Hu (2457952)

"…The esc-edRVFL is identified as the best-performing algorithm through a comprehensive evaluation of 31 UCI datasets.…"

A Survey of Machine Learning Innovations in Ambulance Services: Allocation, Routing, and Demand Estimation حسب Reem Tluli (22282702)

"…By thoroughly reviewing the existing literature and methodologies, this paper provides a comprehensive overview of the approaches used in ambulance allocation, routing, demand estimation and simulation models. We discuss the challenges faced by these methods, emphasizing the need for innovative solutions that can adapt to real-time data and changing emergency patterns. …"

Framework for rapid design and optimisation of immersive battery cooling system حسب Ali Almshahy (23544823)

"…A conjugate heat transfer model for a 3S2P pouch cell module (20 Ah LiFePO₄) is developed and validated against experimental data (< 2% error). …"