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. …"

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%). …"

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). …"

SemIndex: Semantic-Aware Inverted Index حسب Chbeir, Richard

"…We also provide an extended query model and related processing algorithms with the help of SemIndex. …"
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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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A Full-System Approach of the Elastohydrodynamic Line/Point Contact Problem حسب Habchi, Wassim

"…Up to now, most of the numerical works dealing with the modeling of the isothermal EHL problem were based on a weak coupling resolution of the Reynolds and elasticity equations (semi-system approach). …"
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Traffic Offloading with Channel Allocation in Cache-Enabled Ultra-Dense Wireless Networks حسب Abbas, Nadine

"…We also propose efficient sub-optimal hierarchical tree-based algorithms that operate in real time with dynamic and fast solutions for ultra dense networks. …"
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Cyberbullying Detection in Arabic Text using Deep Learning حسب ALBAYARI, REEM RAMADAN SA’ID

"…As a result of the models’ evaluation, a hybrid DL model is proposed that combines the best characteristics of the baseline models CNN, BLSTM and GRU for identifying cyberbullying. …"
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Design and Analysis of Lightweight Authentication Protocol for Securing IoD حسب Saeed Ullah Jan (9079260)

"…We proposed a hash message authentication code/secure hash algorithmic (HMACSHA1) based robust, improved and lightweight authentication protocol for securing IoD. …"

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.…"

Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis حسب Hassan, Ali

"…Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …"
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Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis حسب Hassan Ali (3348749)

"…<p>Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …"