STEM: spatial speech separation using twin-delayed DDPG reinforcement learning and expectation maximization حسب Muhammad Salman Khan (7202543)

"…In this paper, a novel speech separation algorithm is proposed that integrates the twin-delayed deep deterministic (TD3) policy gradient reinforcement learning (RL) agent with the expectation maximization (EM) algorithm for clustering the spatial cues of individual sources separated on azimuth. …"

Variable Selection in Data Analysis: A Synthetic Data Toolkit حسب Mitra, Rohan

"…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …"
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On the Optimization of Band Gaps in Periodic Waveguides حسب Jamil Renno (14070771)

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How can algorithms help in segmenting users and customers? A systematic review and research agenda for algorithmic customer segmentation حسب Joni Salminen (7434770)

Leveraging Machine and Deep Learning Algorithms for hERG Blocker Prediction حسب Syed Mohammad (21075689)

"…The application of machine learning (ML) and deep learning (DL) models in the field of toxicity has gained burgeoning interest. …"

A combined algorithm based on finite elements and a modified methodof characteristics for the analysis of the corona in wire-ductelectrostatic precipitators حسب Al-Hamouz, Z.M.

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A reduced model for phase-change problems with radiation using simplified PN approximations حسب Belhamadia, Youssef

"…The integro-differential equation for the full radiative transfer is replaced by a set of differential equations which are independent of the angle variable and easy to solve using conventional computational methods. To solve the coupled equations, we implement a second-order implicit scheme for the time integration and a mixed finite element method for the space discretization. …"
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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data حسب 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. …"

Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices حسب Khawam, Yahya Bader

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Brain Source Localization in the Presence of Leadfield Perturbations حسب Momin, Rabiya Nakhat

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Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification حسب Rajendra Babu Chikkala (22330876)

"…<p dir="ltr">In recent years, deep learning methods have dramatically improved medical image analysis, though earlier models faced difficulties in capturing intricate spatial and contextual details. …"

Monitoring Bone Density Using Microwave Tomography of Human Legs: A Numerical Feasibility Study حسب Alkhodari, Mohanad Ahmed

"…This study was performed using an in-house finite-element method contrast source inversion algorithm (FEM-CSI). …"
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Auto-indexing Arabic texts based on association rule data mining. (c2015) حسب Rouba G. Nasrallah

"…Our model denotes extracting new relevant words by relating those chosen by the previous classical methods, to new words using data mining rules. …"
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Estimating Construction Project Duration Using a Machine Learning Algorithm حسب Nasr, Joshua

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The Use of Microwave Tomography in Bone Healing Monitoring حسب Alkhodari, Mohanad Ahmed

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IntruSafe: a FCNN-LSTM hybrid IoMT intrusion detection system for both string and 2D-spatial data using sandwich architecture حسب Moutaz Alazab (17730060)

Design of acoustic absorbing metasurfaces using a data-driven approach حسب Hamza Baali (14603380)

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Design of adaptive arrays based on element position perturbations حسب Dawoud, M.M.

"…The main advantage of using this technique over the other commonly used methods is that the amplitudes and phases of the array elements can be used mainly to steer the main beam towards the desired signal. …"
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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. …"

A kernelization algorithm for d-Hitting Set حسب Abu-Khzam, Faisal N.

"…For 3-Hitting Set, an arbitrary instance is reduced into an equivalent one that contains at most 5k2+k elements. This kernelization is an improvement over previously known methods that guarantee cubic-order kernels. …"
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