A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network by Xiaofang Pan (1895950)

“…In order to address this issue, in this paper, we propose a novel hybrid approach with both convolutional and recurrent neural networks combined, which is based on the long short-term memory module. Featuring the capability of learning the correlations of time-series data, the proposed deep learning method is well-suited for extracting the valuable transient feature contained in the very beginning of the response curve. …”

Teaching–learning-based optimization algorithm: analysis study and its application by Abualigah, Laith

Subjects: “…Teaching–learning-based optimization algorithm…”
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Deep Learning-Based Coding Strategy for Improved Cochlear Implant Speech Perception in Noisy Environments by Billel Essaid (22047578)

“…This paper presents a novel deep learning (DL)-based technique that leverages attention mechanisms to improve speech intelligibility through noise suppression. …”

Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms by Arafat Rahman (8065562)

“…We also developed a binary template matching-based algorithm, which gives 93.64% accuracy 6X faster. …”

Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology by Senyuk, Mihail

“…In this study, the emergency control algorithms based on ensemble machine learning algorithms (XGBoost and Random Forest) were developed for a low-inertia power system. …”
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Using machine learning algorithm for detection of cyber-attacks in cyber physical systems by Almajed, Rasha

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Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering by Abu Zitar, Raed

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AI and IoT-based concrete column base cover localization and degradation detection algorithm using deep learning techniques by Khalid, Naji

“…This paper proposes a novel automated algorithm for the health monitoring of concrete column base cover degradation based on IoT and the state-of-the-art deep learning framework, Convolutional Neural Network (CNN). …”
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Modified Elite Opposition-Based Artificial Hummingbird Algorithm for Designing FOPID Controlled Cruise Control System by Abualigah, Laith

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A Novel Genetic Algorithm Optimized Adversarial Attack in Federated Learning for Android-Based Mobile Systems by Faria Nawshin (21841598)

“…<p dir="ltr">Federated Learning (FL) is gaining traction in Android-based consumer electronics, enabling collaborative model training across decentralized devices while preserving data privacy. …”

Web Based Online Hybrid Teaching Method of Network Music Course by Abu Zitar, Raed

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A Multiprocessing-Based Sensitivity Analysis of Machine Learning Algorithms for Load Forecasting of Electric Power Distribution System by Ameema Zainab (16864263)

A systematic review of text classification research based on deep learning models in Arabic language by Wahdan, Ahlam

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CNN and HEVC Video Coding Features for Static Video Summarization by Issa, Obada

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Novel algorithms for accurate DNA base-calling by Mohammed, Omniyah Gul

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Predicting Patient ICU Readmission Using Recurrent Neural Networks With Long Short-Term Memory by Nadia Rasheed (22997257)

Cluster-based anonymity model and algorithm for 1:1 dataset with a single sensitive attribute using machine learning technique by J. Jayapradha (21323774)

Optimal selection of the forgetting matrix into an iterative learning control algorithm by Saab, Samer S.

“…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the optimal forgetting matrix and the learning gain matrix of a P-type iterative learning control (ILC) for linear discrete-time varying systems with arbitrary relative degree. …”
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Exploring Semi-Supervised Learning Algorithms for Camera Trap Images by Sajun, Ali Reza

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TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection by Zina Chkirbene (16869987)

“…TIDCS reduces the number of features in the input data based on a new algorithm for feature selection. Initially, the features are grouped randomly to increase the probability of making them participating in the generation of different groups, and sorted based on their accuracy scores. …”