A comprehensive review of deep reinforcement learning applications from centralized power generation to modern energy internet frameworks by Sakib Mahmud (15302404)

“…We present a structured taxonomy covering value-based, policy-based, actor-critic, model-based, and advanced multi-agent and multi-objective approaches, and link algorithms to tasks such as dispatch, microgrid coordination, real-time pricing, load balancing, and demand–response. …”

Single-channel speech denoising by masking the colored spectrograms by Sania Gul (18272227)

“…With a slightly reduced PESQ score (by 0.58 points), the proposed model offers an improvement of 2 % in STOI, and 4375 and 1135 times reduction respectively in the required number of training epochs and network parameters when compared to a GAN-based model augmented by WavLM; a large-scale self-supervised learning model. …”

Nonlinear Friction Identification of A Linear Voice Coil DC Motor by Takrouri, Mohannad Hashem

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Efficient XML Structural Similarity Detection using Sub-tree Commonalities by Tekli, Joe

“…Various algorithms for comparing hierarchically structured data, e.g. …”
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Comprehensive whole genome sequence analyses yields novel genetic and structural insights for Intellectual Disability by Farah R. Zahir (18892108)

“…The <i>de novo</i> assembly resulted in unmasking hidden genome instability that was missed by standard re-alignment based algorithms. We also interrogated regulatory sequence variation for known and hypothesized ID genes and present useful strategies for WGS data analyses for non-coding variation.…”

Diabetic Sensorimotor Polyneuropathy Severity Classification Using Adaptive Neuro Fuzzy Inference System by Fahmida Haque (16896489)

“…Patients have been classified into four classes: Absent, Mild, Moderate, and Severe. The model accuracy was validated with the results from different machine learning algorithms. …”

Machine Learning Techniques for Pharmaceutical Bioinformatics by SULTAN, AHMED ATTA AHMED

“…The study integrates knowledge visualization, analysis, as well as development of a predictive model based on the Drug-Drug Interactions (DDIs) as a complex network. …”
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Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying by Tekli, Joe

“…Dedicated weighting functions and various search algorithms have been developed for that purpose and will be presented here. …”
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Dynamic Cyber Resilience of Interdependent Critical Information Infrastructures by JUMA, MAZEN GHAZI

“…The technology stack was also enhanced with three new algorithms and five protocols. The proposed solution was optimized using the iterative four-objective cycle based on previous primary phase results. …”
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Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE by Ben Romdhane, Haifa

“…The validation of these results was performed using previous archaeological works as well as geological and geomorphological field surveys. The modelling and prediction accuracies are expected to improve with the insertion of a neural network and backpropagation algorithms based on the performed cluster groups following more recent field surveys. …”
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LDSVM: Leukemia Cancer Classification Using Machine Learning by Abdul Karim (417009)

“…The main aim was to predict the initial leukemia disease. Machine learning algorithms such as decision tree (DT), naive bayes (NB), random forest (RF), gradient boosting machine (GBM), linear regression (LinR), support vector machine (SVM), and novel approach based on the combination of Logistic Regression (LR), DT and SVM named as ensemble LDSVM model. …”

Four quadrant robust quick response optimally efficient inverterfed induction motor drive by Islam, S.M.

“…An optimal efficiency calculator provides optimum flux and torque producing current, while a supervisory control eliminates the intricate boot-strap effect of the flux-torque loop. A model reference-based adaptive speed controller guarantees quick speed response and robustness of the drive system. …”
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Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE by Ben-Romdhane, Haïfa

“…The validation of these results was performed using previous archaeological works as well as geological and geomorphological field surveys. The modelling and prediction accuracies are expected to improve with the insertion of a neural network and backpropagation algorithms based on the performed cluster groups following more recent field surveys. …”
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Condenser capacity and hyperbolic perimeterImage 1 by Mohamed M.S., Nasser

“…We study the conformal capacity by using novel computational algorithms based on implementations of the fast multipole method, and analytic techniques. …”
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A family of minimum curvature variable-methods for unconstrained optimization. (c1998) by Obeid, Samir Y.

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Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms by Marwan Dhuheir (19170898)

“…Our approach is tested on CNN networks and benchmarked against state-of-the-art conventional reinforcement learning algorithms. Extensive simulations show that our model outperforms competitive methods by around 29% in terms of latency and around 23% in terms of transmission power improvements while delivering results comparable to the traditional LDTP optimization solution by around 9% in terms of latency.…”

Decision-level Gait Fusion for Human Identification at a Distance by Al-Tayyan, Amer

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Towards secure private and trustworthy human-centric embedded machine learning: An emotion-aware facial recognition case study by Muhammad Atif Butt (10849980)

“…Since the success of AI is to be measured ultimately in terms of how it benefits human beings, and that the data driving the deep learning-based edge AI algorithms are intricately and intimately tied to humans, it is important to look at these AI technologies through a human-centric lens. …”

A fine-grained XML structural comparison approach by Tekli, Joe

“…Our approach consists of two main algorithms for discovering the structural commonality between sub-trees and computing tree-based edit operations costs. …”
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Condenser capacity and hyperbolic perimeter by Mohamed M.S. Nasser (16931772)

“…<p dir="ltr">We study the conformal capacity by using novel computational algorithms based on implementations of the fast multipole method, and analytic techniques. …”