A family of minimum curvature variable-methods for unconstrained optimization. (c1998) حسب Obeid, Samir Y.

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SPA & MLST typing as epidemiological tools for the study of MRSA & MSSA Isolates in Lebanon. (c2009) حسب Rizk, Mazen

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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. …"

Towards secure private and trustworthy human-centric embedded machine learning: An emotion-aware facial recognition case study حسب Muhammad Atif Butt (10849980)

"…Since the success of AI is to be measured ultimately in terms of how it benefits human beings, and that the data driving the deep learning-based edge AI algorithms are intricately and intimately tied to humans, it is important to look at these AI technologies through a human-centric lens. …"

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

"…These algorithms include random forest (RF) classification and artificial neural networks (ANN). …"

Condenser capacity and hyperbolic perimeterImage 1 حسب Mohamed M.S., Nasser

"…We study the conformal capacity by using novel computational algorithms based on implementations of the fast multipole method, and analytic techniques. …"
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Systems biology analysis reveals NFAT5 as a novel biomarker and master regulator of inflammatory breast cancer حسب Andrea Remo (447375)

"…</p><h3>Methods</h3><p dir="ltr">In-silico modeling and Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNe) on IBC/non-IBC (nIBC) gene expression data (n = 197) was employed to identify novel master regulators connected to the IBC phenotype. …"

Privacy-preserving energy optimization via multi-stage federated learning for micro-moment recommendations حسب Md Mosarrof Hossen (21399056)

"…To address this challenge, this study aims to optimize household energy consumption while preserving data privacy by proposing an innovative two-stage Federated Learning (FL) framework that delivers real-time micro-moment-based recommendations. Leveraging FL enables efficient model training across diverse end-user applications while preserving data privacy. …"

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. …"

Pre-training on Multi-modal for Improved Persona Detection Using Multi Datasets حسب Abdulla, Salwa

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Uplink Noma in UAV-Assisted IoT Networks حسب Mrad, Ali

"…The second device is then selected using a heuristic algorithm based on prioritizing devices with higher bit rate requirements and strict deadlines. …"
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Condenser capacity and hyperbolic perimeter حسب Mohamed M.S. Nasser (16931772)

"…<p dir="ltr">We study the conformal capacity by using novel computational algorithms based on implementations of the fast multipole method, and analytic techniques. …"

Tailoring motivational health messages for smoking cessation using an mHealth recommender system integrated with an electronic health record: a study protocol حسب Santiago Hors-Fraile (5950823)

"…Health recommender systems are information-filtering algorithms that can choose the most relevant health-related items—for instance, motivational messages aimed at smoking cessation—for each user based on his or her profile. …"

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%). …"

Application of Metastructures for Targeted Low-Frequency Vibration Suppression in Plates حسب 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. …"

Face Flow: Constrained Optical Flow Framework for Faces حسب Alkaddour, Muhannad

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Intelligent Bilateral Client Selection in Federated Learning Using Game Theory حسب Wehbi, Osama

"…Based on our simulation findings, our strategy surpasses the VanillaF selection approach in terms of maximizing both the revenues of the client devices and accuracy of the global federated learning model.…"
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A comparative analysis to forecast carbon dioxide emissions حسب Md. Omer Faruque (17545671)

"…Based on multivariate time series prediction, four deep learning algorithms are analyzed in this work, those are convolution neural network (CNN), CNN long short-term memory (CNN–LSTM), long short-term memory (LSTM), and dense neural network (DNN). …"

Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms حسب Marwan Dhuheir (19170898)

"…Our approach is tested on CNN networks and benchmarked against state-of-the-art conventional reinforcement learning algorithms. Extensive simulations show that our model outperforms competitive methods by around 29% in terms of latency and around 23% in terms of transmission power improvements while delivering results comparable to the traditional LDTP optimization solution by around 9% in terms of latency.…"

Decision-level Gait Fusion for Human Identification at a Distance حسب Al-Tayyan, Amer

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