ANT-colony optimization-direct torque control for a doubly fed induction motor : An experimental validation حسب Said Mahfoud (17150968)

"…The new combined ACO-DTC strategy has been studied for optimizing the gains of the PID controller by using a cost function such as Integral Square Error (ISE). …"

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). The CFD model of a battery module is developed to train an ultra-fast metamodel for battery geometry optimisation. …"

Performance Modeling of Rooftop PV Systems in Arid Climate, a Case Study for Qatar: Impact of Soiling Losses and Albedo Using PVsyst and SAM حسب Sachin Jain (19161721)

"…The optimized approach reduced the root mean square error (RMSE) of predicted soiling ratios from 7.30 to 1.93 and improved the agreement between simulated and measured monthly energy yields for 2024, achieving normalized RMSE values of 4.66% in SAM and 4.86% in PVsyst. The findings demonstrate that coupling data-driven soiling optimization with refined albedo representation modernizes the predictive capabilities of PVsyst and SAM, yielding more reliable performance forecasts. …"

Extremity Ischemia After Jellyfish Envenomation: A Case Report and Systematic Review of the Literature حسب Saif Badran (16888785)

"…In the literature, 15 different pharmacologic classes have been used to manage these presentations. Only IV infusions of prostaglandin derivatives and intra-arterial thrombolytics have been found to improve the clinical picture and avoid the need for surgical fasciotomy and debridement in some cases. …"

Heuristics. (c2006) حسب Kallab, Chadi

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A MIMO Sampling-Rate-Dependent Controller حسب Saab, Samer S.

"…A proportional-integral-derivative (PID) controller is a special case of the proposed controller. …"
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Humanizing AI in medical training: ethical framework for responsible design حسب Mohammed Tahri Sqalli (18420840)

"…<p dir="ltr">The increasing use of artificial intelligence (AI) in healthcare has brought about numerous ethical considerations that push for reflection. …"

Blood Glucose Regulation Modelling and Intelligent Control حسب Nasar, Nabeel

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A Comprehensive Overview of the COVID-19 Literature: Machine Learning–Based Bibliometric Analysis حسب Alaa Abd-Alrazaq (17430900)

"…Publishers should avoid noise in the data by developing a way to trace the evolution of individual publications and unique authors.…"

Developing a resilient framework for electric vehicle charging stations harnessing solar energy, standby batteries and grid integration with advanced control mechanisms حسب Debabrata Mazumdar (18560506)

"…Consequently, this article presents and evaluates a system that utilizes a proportional‐integral‐derivative controller, a neural network‐equipped grid and a charging station utilizing a Dragon Fly Optimization Algorithm to generate power and a maximum power point tracking controller. …"

AI-Based Methods for Predicting Required Insulin Doses for Diabetic Patients حسب Azar, Danielle

"…This results in an enormous amount of data. Endocrinologists need to find a certain pattern in this data that would help them determine the optimal dosage of insulin to administer to each patient. …"
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Detecting Arabic Cyberbullying Tweets in Arabic Social Using Deep Learning حسب ALFALASI, FARIS Jr

"…The data needs to be initially prepared so that deep learning algorithms may be trained on it before cyberbullying analysis can be done. …"
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Single-Cell Transcriptome Analysis Revealed Heterogeneity and Identified Novel Therapeutic Targets for Breast Cancer Subtypes حسب Radhakrishnan Vishnubalaji (3563306)

"…In the current study, we employed computational algorithms to decipher the cellular composition of estrogen receptor-positive (ER⁺), HER2⁺, ER⁺HER2⁺, and triple-negative BC (TNBC) subtypes from a total of 49,899 single cells’ publicly available transcriptomic data derived from 26 BC patients. …"

Predicting insulin dosage for diabetic patients to reach optimal glucose levels. (c2012) حسب Bitar, Mandy

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Machine Learning Model for a Sustainable Drilling Process حسب Alsaidi, Ola

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Real-Time Social Robot’s Responses to Undesired Interactions Between Children and their Surroundings حسب Ahmad Yaser Alhaddad (7017434)

"…Experiments with features showed that acceleration data were the most contributing factor on the prediction compared to gyroscope data and that combined data of raw and extracted features provided a better overall performance. …"

Predicting and Interpreting Student Performance Using Machine Learning in Blended Learning Environments in a Jordanian School Context حسب SALIM, MAHA JAWDAT

"…These platforms enhance academic performance by fostering collaborative learning environments and generating extensive data from every user interaction. Machine learning algorithms can process large and complex datasets to identify patterns and trends that may not be immediately apparent. …"
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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.…"

An enhanced binary Rat Swarm Optimizer based on local-best concepts of PSO and collaborative crossover operators for feature selection حسب Abu Zitar, Raed

"…In this paper, an enhanced binary version of the Rat Swarm Optimizer (RSO) is proposed to deal with Feature Selection (FS) problems. FS is an important data reduction step in data mining which finds the most representative features from the entire data. …"

Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort حسب Sergio Márquez-Sánchez (19437985)

"…However, these BEMSs often suffer from a critical limitation—they are primarily trained on building energy data alone, disregarding crucial elements such as occupant comfort and preferences. …"