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C-3PA: Streaming Conformance, Confidence and Completeness in Prefix-Alignments
Published 2023“…The aim of streaming conformance checking is to find dis crepancies between process executions on streaming data and the refer ence process model. …”
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TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection
Published 2020“…TIDCS reduces the number of features in the input data based on a new algorithm for feature selection. …”
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Diagnostic structure of visual robotic inundated systems with fuzzy clustering membership correlation
Published 2023“…<p dir="ltr">The process of using robotic technology to examine underwater systems is still a difficult undertaking because the majority of automated activities lack network connectivity. …”
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Design of an innovative and self-adaptive-smart algorithm to investigate the structural integrity of a rail track using Rayleigh waves emitted and sensed by a fully non-contact las...
Published 2020“…In view of this, an innovative signal processing technique called a self-adaptive-smart algorithm (SASA) was designed and developed. …”
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A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security
Published 2023“…Moreover, the Reconciliate Multi-Agent Markov Learning (RMML) based classification algorithm is used to predict the intrusion with its appropriate classes. …”
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Defining quantitative rules for identifying influential researchers: Insights from mathematics domain
Published 2024“…Within each categorical grouping, we meticulously selected the five most pivotal parameters. This selection process was guided by an importance score, that was derived after assessing its influence on the model's performance in the classification of data pertaining to both awardees and non awardees. …”
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Oversampling techniques for imbalanced data in regression
Published 2024“…We adapt K-Nearest Neighbor Oversampling-Regression (KNNOR-Reg), originally for imbalanced classification, to address imbalanced regression in low population datasets, evolving to KNNOR-Deep Regression (KNNOR-DeepReg) for high-population datasets. …”
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Type 2 Diabetes Mellitus Automated Risk Detection Based on UAE National Health Survey Data: A Framework for the Construction and Optimization of Binary Classification Machine Learn...
Published 2020“…A special consideration was given to data pre-processing and dimensionality reduction such Chi Squared (CS) and Recursive Feature Elimination (RFE) to improve progressively the proposed models performance. …”
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311
Investigation of Forming a Framework to shortlist contractors in the tendering phase
Published 2022“…After obtaining the weights of the decision factors, a model using Machine Learning algorithm on Google Colab was written using the Python language. …”
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312
Novel Multi Center and Threshold Ternary Pattern Based Method for Disease Detection Method Using Voice
Published 2020“…The artificial neural network (ANN), support vector machine (SVM) and deep learning models, especially the convolutional neural network (CNN), are the most commonly used machine learning approaches where they proved to be performance in most cases. …”
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IoT-Based Sustainable Parking Lot
Published 2023“…Moreover, a carbon emissions sensor at the gate is used to detect the generated emission rates by vehicles entering the parking lot. Furthermore, deep learning neural network was used to predict the congestion of the parking lot at any day or time. …”
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Wearable wrist to finger photoplethysmogram translation through restoration using super operational neural networks based 1D-CycleGAN for enhancing cardiovascular monitoring
Published 2024“…<h3>Background and Motivations</h3><p dir="ltr">Physiological signals, such as the Photoplethysmogram (PPG) collected through wearable devices, consistently encounter significant motion artifacts. Current signal processing techniques, and even state-of-the-art machine learning algorithms, frequently struggle to effectively restore the inherent bodily signals amidst the array of randomly generated distortions. …”
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Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts
Published 2022“…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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318
Can AI Help in Screening Viral and COVID-19 Pneumonia?
Published 2020“…The aim of this paper is to propose a robust technique for automatic detection of COVID-19 pneumonia from digital chest X-ray images applying pre-trained deep-learning algorithms while maximizing the detection accuracy. …”
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Cooperative Caching Policy in Fog Computing for Connected Vehicles
Published 2023“…In this thesis, we implemented cooperation between a Deep Reinforcement Learning (DRL) model and Federated Learning to improve caching in Connected Vehicles connected to fog nodes. …”
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masterThesis -
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Evolution Of Activation Functions for Neural Architecture Search
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masterThesis