Competitive learning/reflected residual vector quantization for coding angiogram images by Mourn, W.A.H.

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

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Predicting Compression Modes and Split Decisions for HEVC Video Coding Using Machine Learning Techniques by Hassan, Mahitab Alaaeldin

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Deep Learning-Based Coding Strategy for Improved Cochlear Implant Speech Perception in Noisy Environments by Billel Essaid (22047578)

LNCRI: Long Non-Coding RNA Identifier in Multiple Species by Saleh Musleh (15279190)

“…To overcome these challenges we developed LNCRI (Long Non-Coding RNA Identifier), a novel machine learning (ML)-based tool for the identification of lncRNA transcripts. …”

Large language models for code completion: A systematic literature review by Rasha Ahmad Husein (19744756)

“…Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. …”

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

Enhancing Healthcare Systems With Deep Reinforcement Learning: Insights Into D2D Communications and Remote Monitoring by Zina Chkirbene (16869987)

“…By formulating the video resource allocation challenge as a multi-objective optimization problem, the framework aims to minimize network delays while respecting node capacity limitations. The core of DRLLVT is its novel algorithm that leverages Deep Reinforcement Learning (DRL) to dynamically adapt to changing environmental conditions, facilitating real-time decisions that consider node capacities, latency, and the overall network dynamics. …”

UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data by Behrouz Ahadzadeh (19757022)

“…UniBFS exploits the inherent characteristic of binary algorithms-binary coding-to search the entire problem space for identifying relevant features while avoiding irrelevant ones. …”

Optimum Partition of Power Networks Using Singular Value Decomposition and Affinity Propagation by Maymouna Ez Eddin (21633650)

A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models by Azar, Danielle

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Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts by ALSHAMSI, SUROUR

“…So far none addresses the use of Threat Intelligence (IT) data in Ensemble Learning algorithms to improve the detection process, nor does it work as a function of time, that is, taking into account what happens on the network in a limited time interval. …”
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Benchmarking Concept Drift Detectors for Online Machine Learning by Mahgoub, Mahmoud

“…Upon drift detection, the classifica tion algorithm may reset its model or concurrently grow a new learning model. …”
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FarmTech: Regulating the use of digital technologies in the agricultural sector by Imad Antoine Ibrahim (14158998)

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

Analysis of Using Machine Learning to Enhance the Efficiency of Facilities Management in the UAE by ULLAH, SAAD

“…Seasonal thresholds are set for sensor values, and the algorithm detects hazardous trends when values exceed safe limits, correlating them with related sensors to generate combined variables and error codes. …”
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Recent advances on artificial intelligence and learning techniques in cognitive radio networks by Abbas, Nadine

“…The literature survey is organized based on different artificial intelligence techniques such as fuzzy logic, genetic algorithms, neural networks, game theory, reinforcement learning, support vector machine, case-based reasoning, entropy, Bayesian, Markov model, multi-agent systems, and artificial bee colony algorithm. …”
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Nonlinear analysis of shell structures using image processing and machine learning by M.S. Nashed (16392961)

“…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …”

Reinforcement R-learning model for time scheduling of on-demand fog placement by Farhat, Peter

“…On the fly deployment of fog nodes near users provides the flexibility of pushing services anywhere and whenever needed. …”
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Unsupervised Deep Learning for Classification Of Bats Calls Using Acoustic Data by Arshad, Muhammad Arbab

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