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

Single channel speech denoising by DDPG reinforcement learning agent حسب Sania Gul (18272227)

"…The noisy speech is first converted from the time domain to the time–frequency (TF) domain by taking its short-time Fourier transform (STFT), and then two separate DDPG agents are trained on the magnitude and phase components of the STFT. The reward function used for training these agents is the relative perceptual quality score of speech. …"

Random vector functional link network: Recent developments, applications, and future directions حسب A.K. Malik (16003193)

"…<p>Neural networks have been successfully employed in various domains such as classification, regression and clustering, etc. Generally, the back propagation (BP) based iterative approaches are used to train the neural networks, however, it results in the issues of local minima, sensitivity to learning rate and slow convergence. …"

Particle swarm optimization based algorithm for protein structure prediction in the 3D HP model. (c2008) حسب Kanj, Fatima Hassan

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A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models حسب Osama Bassam J. Rabie (21323741)

"…<p dir="ltr">The Internet of Things (IoT) is extensively used in modern-day life, such as in smart homes, intelligent transportation, etc. However, the present security measures cannot fully protect the IoT due to its vulnerability to malicious assaults. …"

Rate Adaptation in Dynamic Adaptive Video Streaming Over HTTP حسب Abdelhafez, Nada

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Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle حسب Reza Jafari (3494018)

"…A tailored multi-term reward function is structured to penalize excessive yaw rate error, sideslip angle, tire slip deviations beyond peak grip regions, and power losses based on a realistic electric machine efficiency map. …"

Integration of nonparametric fuzzy classification with an evolutionary-developmental framework to perform music sentiment-based analysis and composition حسب Abboud, Ralph

"…Unlike existing solutions, MUSEC is: (i) a hybrid crossover between supervised learning (SL, to learn sentiments from music) and evolutionary computation (for music composition, MC), where SL serves at the fitness function of MC to compose music that expresses target sentiments, (ii) extensible in the panel of emotions it can convey, producing pieces that reflect a target crisp sentiment (e.g., love) or a collection of fuzzy sentiments (e.g., 65% happy, 20% sad, and 15% angry), compared with crisp-only or two-dimensional (valence/arousal) sentiment models used in existing solutions, (iii) adopts the evolutionary-developmental model, using an extensive set of specially designed music-theoretic mutation operators (trille, staccato, repeat, compress, etc.), stochastically orchestrated to add atomic (individual chord-level) and thematic (chord pattern-level) variability to the composed polyphonic pieces, compared with traditional evolutionary solutions producing monophonic and non-thematic music. …"
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A novel method for the detection and classification of multiple diseases using transfer learning-based deep learning techniques with improved performance حسب Krishnamoorthy Natarajan (22047464)

"…<p dir="ltr">A disease is a distinct abnormal state that significantly affects the functioning of all or part of an individual and is not caused by external harm. …"

FoGMatch حسب Arisdakessian, Sarhad

"…Our solution consists of (1) two optimization problems, one for the IoT devices and one for the fog nodes, (2) preference functions for both the IoT and fog layers to help them rank each other on the basis of several criteria such latency and resource utilization, and (3) centralized and distributed intelligent scheduling algorithms that consider the preferences of both the fog and IoT layers to improve the performance of the overall IoT ecosystem. …"
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DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins حسب Samir Brahim, Belhaouari

"…Unlike standard machine learning approaches such as PCA, LDA, SVM, RF, GBM etc, DeepRaman functions independently, requiring no human interaction, and can be used to much smaller datasets than traditional CNNs. …"
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