Artificial Intelligence for the Prediction and Early Diagnosis of Pancreatic Cancer: Scoping Review حسب Zainab Jan (17306614)

"…Most of the included articles used data sets with a size of <1000 samples (11/30, 37%). Deep learning models were the most prominent branch of AI used for pancreatic cancer diagnosis in the studies, and the convolutional neural network was the most used algorithm (18/30, 60%). …"

The Assessment and Allocation of Public Private Partnership Risks in the UAE حسب Shaban, Mazhd

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Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier حسب Syed Ali Jafar Zaidi (19563178)

"…Specifically, this study exhibits people’s predilection toward the COVID-19 vaccine and its results based on the reviews. Five models, e.g., random forest (RF), a support vector machine (SVM), decision tree (DT), K-nearest neighbor (KNN), and an artificial neural network (ANN), were used for forecasting the overall predilection toward the COVID-19 vaccine. …"

Optimization of Commercially Off the Shelf (COTS) Electric Propulsion System for Low Speed Fuel Cell UAV حسب Zulkifli, Muhammad

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A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass حسب Uzma Nawaz (21980708)

"…By synthesizing findings across various data sources and model architectures, we offer critical insights into the selection of context-aware algorithms and identify key research gaps, an essential step for advancing the reliability and applicability of AI-driven seagrass conservation efforts.…"

LungVision: X-ray Imagery Classification for On-Edge Diagnosis Applications حسب Aldamani, Raghad

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An Intelligent and Low-Cost Eye-Tracking System for Motorized Wheelchair Control حسب Mahmoud Dahmani (18810247)

"…The first three techniques were automatic, employ correlation, and were variants of template matching, whereas the last one uses convolutional neural networks (CNNs). Different metrics to quantitatively evaluate the performance of each algorithm in terms of accuracy and latency were computed and overall comparison is presented. …"

Dynamic performance evaluation and machine learning-assisted optimization of a solar-driven system integrated with PCM-based thermal energy storage: A case study approach حسب Haitham Osman (11737057)

"…A comprehensive techno-economic analysis is conducted, supported by a machine learning-assisted optimization framework that combines artificial neural networks with genetic algorithms. Considering optimum conditions, the system attains an exergetic efficiency of 30.13 % and a power generation of 7.24 MW, with a cost rate of 232.06 $/h and a payback period of 4.09 years. …"

Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods حسب Sivakavi Naga Venkata Bramareswara Rao (15944992)

"…From the results, it is found that the Levenberg–Marquardt optimization algorithm-based ANN model gives the best electrical load forecasting results.…"

Determining the Factors Affecting the Boiling Heat Transfer Coefficient of Sintered Coated Porous Surfaces حسب Uzair Sajjad (19646296)

"…In this regard, two Bayesian optimization algorithms including Gaussian process regression (GPR) and gradient boosting regression trees (GBRT) are used for tuning the hyper-parameters (number of input and dense nodes, number of dense layers, activation function, batch size, Adam decay, and learning rate) of the deep neural network. …"

MAESTRO: Orchestrating Computational Offloading to Multiple FemtoClouds in Various Communication Environments حسب Hend Gedawy (23275984)

"…<p dir="ltr">Many novel IoT-based applications demand low latency, large compute resources, and high privacy. …"

ThoraX-PriorNet: A Novel Attention-Based Architecture Using Anatomical Prior Probability Maps for Thoracic Disease Classification حسب Md. Iqbal Hossain (723299)

MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network حسب Sakib Mahmud (15302404)

"…Because the diagnosis of many neurological diseases is heavily reliant on clean EEG data, it is critical to eliminate motion artifacts from motion-corrupted EEG signals using reliable and robust algorithms. Although a few deep learning-based models have been proposed for the removal of ocular, muscle, and cardiac artifacts from EEG data to the best of our knowledge, there is no attempt has been made in removing motion artifacts from motion-corrupted EEG signals: In this paper, a novel 1D convolutional neural network (CNN) called multi-layer multi-resolution spatially pooled (MLMRS) network for signal reconstruction is proposed for EEG motion artifact removal. …"

Fast Transient Stability Assessment of Power Systems Using Optimized Temporal Convolutional Networks حسب Mohamed Massaoudi (16888710)

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. …"

Inferential sensing techniques in industrial applications حسب Shakil,, Muhammad

"…System delays are obtained by approximating the model by a linear model. Genetic algorithm, which is a heuristic optimization technique, is used to ¯nd the system delays of the linear model, which are used in dynamical neural network model. …"
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A novel technique for fast multiplication حسب Sait, Sadiq M.

"…The algorithm is modelled in a hardware description language and its VLSI chip implemented. …"
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A novel technique for fast multiplication حسب Sait, Sadiq M.

"…In this algorithm the partial products of the multiplicand and three bits of the multiplier are pre-calculated using only hardwired shifts. …"
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Establishing Autonomous AUS-Quadrotor حسب Al Younes, Younes

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Optimizing ADWIN for Steady Streams حسب Moharram, Hassan

"…However, the drift detection accuracy of these variants was not compared with the original algorithm. Moreover, there is no study concerning the memory consumption of the variants and the origi nal algorithm. …"
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