High-order parametrization of the hypergeometric-Meijer approximants by Abouzeid M. Shalaby (16329062)

“…We also show that such extension of the hypergeometric resummation algorithm is able to employ non-perturbative information like strong-coupling and large-order asymptotic data which are always used to accelerate the convergence. …”

Edge intelligence for network intrusion prevention in IoT ecosystem by Mansura, Habiba

“…This paper proposes a deep learning-based algorithm to protect the network against Distributed Denial-of-Service (DDoS) attacks, insecure data flow, and similar network intrusions. …”
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Computation of conformal invariants by Mohamed M.S., Nasser

“…We compare the performance and accuracy to previous results in the cases when numerical data is available and also in the case of several model problems where exact results are available.…”
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STEM: spatial speech separation using twin-delayed DDPG reinforcement learning and expectation maximization by Muhammad Salman Khan (7202543)

“…For stationary sources, the proposed system gives satisfactory performance in terms of quality, intelligibility, and separation speed, and generalizes well with the test data from a mismatched speech corpus. Its perceptual evaluation of speech quality (PESQ) score is 0.55 points better than a self-supervised learning (SSL) model and almost equivalent to the diffusion models at computational cost and training data which is many folds lesser than required by these algorithms. …”

Phased Array Technique for Brain Source Localization by Zarghami, Tahereh

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A novel hybrid methodology for fault diagnosis of wind energy conversion systems by Khaled Dhibi (16891524)

“…Therefore, a hybrid feature selection based diagnosis technique, that can preserve the advantages of wrapper and filter algorithms as well as RF model, is proposed. In the first phase, the neighborhood component analysis (NCA) filter algorithm is used to reduce and select only the pertinent features from the original raw data. …”

Edge intelligence for network intrusion prevention in IoT ecosystem by Mansura Habiba (17808302)

“…This paper proposes a deep learning-based algorithm to protect the network against Distributed Denial-of-Service (DDoS) attacks, insecure data flow, and similar network intrusions. …”

Student advising decision to predict student's future GPA based on Genetic Fuzzimetric Technique (GFT) by Kouatli, Issam

“…Decision making and/or Decision Support Systems (DSS) using intelligent techniques like Genetic Algorithm and fuzzy logic is becoming popular in many new applications. …”
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Neural network-based failure rate prediction for De Havilland Dash-8 tires by Al-Garni, Ahmed Z.

“…An artificial neural network (ANN) model for predicting the failure rate of De Havilland Dash-8 airplane tires utilizing the twolayered feed-forward back-propagation algorithm as a learning rule is developed. …”
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Computation of conformal invariants by Mohamed M.S. Nasser (16931772)

“…We compare the performance and accuracy to previous results in the cases when numerical data is available and also in the case of several model problems where exact results are available.…”

On sensor selection in mobile devices based on energy, application accuracy, and context metrics by Taleb, Sireen

“…We use this algorithm to build a sensor selection model to choose among location sensors. …”
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Solar power forecasting beneath diverse weather conditions using GD and LM-artificial neural networks by Sharma, Neetan

“…A case study has been done in the Peer Panjal region. The data collected for four months with various parameters have been applied randomly as input data using GD and LM type of artificial neural network compared to actual solar energy data. …”
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DNA Base-Calling Techniques by Odeh, Fadi

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Failure-Rate Prediction for De Havilland Dash-8 Tires Employing Neural-Network Technique by Al-Garni, Ahmed Z.

“…An artificial neural-network model for predicting the failure rate of De Havilland Dash-8 airplane tires utilizing the two-layered feedforward back-propagation algorithm as a learning rule is developed. …”
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Soft Sensor for NOx Emission using Dynamical Neural Network by Shakil, M.

“…Neural network model is trained using real data logs of an industrial boiler. …”
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FAILURE RATE ANALYSIS OF BOEING 737 BRAKES EMPLOYING NEURAL NETWORK by Al-Garni, Ahmed Z.

“…Three years of data are used for model building and validation. …”
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Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management by Alhusin, Mohammed Omer Alamin

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Enhanced DC Microgrid Protection: a Neural Network and Wavelet Transform Approach by El Gohary, Youssef Hesham

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Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort by Sergio Márquez-Sánchez (19437985)

“…However, these BEMSs often suffer from a critical limitation—they are primarily trained on building energy data alone, disregarding crucial elements such as occupant comfort and preferences. …”

Topology and parameter estimation in power systems through inverter-based broadband stimulations by Margossian, Harag

“…This study describes a method for identifying parameters associated with the power system model. In particular, the proposed algorithm in this study addresses the line parameter and topology identification task in the scope of state estimation. …”
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