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. …"

Automatic Recognition of Poets for Arabic Poetry using Deep Learning Techniques (LSTM and Bi-LSTM) حسب AL SHOUBAKI, HAMZA YOUNIS

"…We also explore a range of algorithms, including traditional classifiers and deep learning models, to determine and select the most suitable and accurate models of identifying poets' names from the verses. …"
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Corrosion Monitoring Technologies for Reinforced Concrete Structures: A Review حسب SHEHADEH, KHADIJA

"…New technology, algorithms, data processing, and AI are new approaches to improving corrosion monitoring processes. …"
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An Infrastructure-Assisted Workload Scheduling for Computational Resources Exploitation in the Fog-Enabled Vehicular Network حسب Sorkhoh, Ibrahim

"…A Dantzig–Wolfe decomposition algorithm is proposed which yields to a master program solvable by the Barrier algorithm and subproblems solve...…"
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Precision nutrition: A systematic literature review حسب Daniel Kirk (17302798)

"…Therefore, we carried out a Systematic Literature Review (SLR) to provide an overview of where and how machine learning has been used in Precision Nutrition from various aspects, what such machine learning models use as input features, what the availability status of the data used in the literature is, and how the models are evaluated. …"

Reconstruction and simulation of neocortical microcircuitry حسب Khazen, Georges

"…The reconstruction uses cellular and synaptic organizing principles to algorithmically reconstruct detailed anatomy and physiology from sparse experimental data. …"
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Predicting COVID-19 cases using bidirectional LSTM on multivariate time series حسب Ahmed Ben Said (14158926)

"…Unlike other forecasting techniques, our proposed approach first groups the countries having similar demographic and socioeconomic aspects and health sector indicators using K-means clustering algorithm. The cumulative case data of the clustered countries enriched with data related to the lockdown measures are fed to the bidirectional LSTM to train the forecasting model. …"

Anonymizing multimedia documents حسب Haraty, Ramzi

"…We provide a sanitizing MD∗-algorithm to enforce de-linkability along with a utility function to evaluate the utility of multimedia documents that is preserved after the sanitizing process. …"
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Overview of Artificial Intelligence–Driven Wearable Devices for Diabetes: Scoping Review حسب Arfan Ahmed (17541309)

"…WDs coupled with artificial intelligence (AI) algorithms show promise to help understand and conclude meaningful information from the gathered data and provide advanced and clinically meaningful analytics.…"

Structural alignment. (c2006) حسب Kazma, Layal

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Identification of physically based models of residential air-conditioners for direct load control management حسب El-Ferik, S.

"…In this work, we address the problem of identifying the parameters of an aggregated elemental model representing a housing unit with an A/C system. …"
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Active distribution network type identification method of high proportion new energy power system based on source-load matching حسب Qinlin, Shi

"…Firstly, the typical daily output scenarios of DG are extracted by clustering method, and the generalized load curve model is solved by the optimization algorithm to obtain the source load operation data; Secondly, calculate the source-load matching indicators (including matching performance, matching degree, and matching rate) according to the source load data of each region, and identify the distribution network type according to the range of the index values; Finally, several indicators are introduced to quantify the characteristics of different types of distribution networks. …"
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An Infrastructure-Assisted Crowdsensing Approach for On-Demand Traffic Condition Estimation حسب Abdul Rahman, Sawsan

"…Our approach combines the strengths of mobile crowdsensing, with the support of the mobile infrastructure, a multi-criteria algorithm for the participants' selection, and a deductive rule-based model for traffic condition estimation. …"
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Machine Learning-Based Approach for EV Charging Behavior حسب Shahriar, Sakib

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Real-Time Implementation of GPS Aided Low Cost Strapdown Inertial Navigation System حسب Sahawneh, Laith Rasmi

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FPGA-Based Network Traffic Classification Using Machine Learning حسب Elnawawy, Mohammed

"…The performed experiments show that 60% of flow packets are a good compromise that ensures high performance in the least processing time. The results of the conducted experiments indicate that random forest outperforms other algorithms achieving a maximum accuracy of 98.5% and an F-score of 0.932. …"
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A Comprehensive Overview of the COVID-19 Literature: Machine Learning–Based Bibliometric Analysis حسب Alaa Abd-Alrazaq (17430900)

"…Publishers should avoid noise in the data by developing a way to trace the evolution of individual publications and unique authors.…"

Multi-Classifier Tree With Transient Features for Drift Compensation in Electronic Nose حسب Atiq Ur Rehman (8843024)

"…These electronic instruments rely on Machine Learning (ML) algorithms for recognizing the sensed odors. The effect of long-term drift influences the performance of ML algorithms and the models those are trained on drift free data fail to perform on the drifted data. …"

Inception voltage of corona in bipolar ionized fields-effect oncorona power loss حسب Al-Hamouz, Z.

"…In this paper, an iterative finite element based algorithm is presented as a numerical tool for the solution of the bipolar ionized field around high voltage direct current (HVDC) transmission lines. …"
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Generic metadata representation framework for social-based event detection, description, and linkage حسب Abebe, Minale A.

"…SEDDaL consists of four main modules for: i) describing social media objects in a generic Metadata Representation Space Model (MRSM) consisting of three composite dimensions: temporal, spatial, and semantic, ii) evaluating the similarity between social media objects’ descriptions following MRSM, iii) detecting events from similar social media objects using an adapted unsupervised learning algorithm, where events are represented as clusters of objects in MRSM, and iv) identifying directional, metric, and topological relationships between events following MRSM’s dimensions. …"
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