Benchmarking Concept Drift Detectors for Online Machine Learning by Mahgoub, Mahmoud

“…The main task is to detect changes in data distribution that might cause changes in the decision bound aries for a classification algorithm. …”
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High-order parametrization of the hypergeometric-Meijer approximants by Abouzeid M. Shalaby (16329062)

“…To solve this problem, we formulate an equivalent (order by order) linear set of equations which is easy to solve in an appropriate time using normal PCs. 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. …”

Phased Array Technique for Brain Source Localization by Zarghami, Tahereh

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

“…A system architecture is designed for a cloud-based IoT framework to implement the proposed algorithm efficiently. The performance evaluation using standard datasets demonstrates that the proposed model provides an accuracy of up to 99.99%.…”
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Edge intelligence for network intrusion prevention in IoT ecosystem by Mansura Habiba (17808302)

“…A system architecture is designed for a cloud-based IoT framework to implement the proposed algorithm efficiently. The performance evaluation using standard datasets demonstrates that the proposed model provides an accuracy of up to 99.99%.…”

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. …”

Adaptive controlled superconducting magnetic energy storage devices for performance enhancement of wind energy systems by Rania A., Turky

“…It depends mainly on the actuating error signal, and it has a variable step size of the CMPN. The detailed modeling of the whole system is presented, including measured wind speed data, detailed switching techniques, a drive train model of the turbine, and real SMESD. …”
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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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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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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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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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DNA Base-Calling Techniques by Odeh, Fadi

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Establishing Autonomous AUS-Quadrotor by Al Younes, Younes

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Positive Unlabelled Learning to Recognize Dishes as Named Entity by TAREK, AIMAN

“…I work with Yelp dataset, going through each text review, using each noun as a candidate, label the positive samples using the aforementioned lookup table, then using Positive Unlabelled learning techniques to recognise more entities within the unlabelled data, by predicting the probability for each candidate. …”
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A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security by S. Shitharth (12017480)

“…Moreover, the Reconciliate Multi-Agent Markov Learning (RMML) based classification algorithm is used to predict the intrusion with its appropriate classes. …”

Cross entropy error function in neural networks by Nasr, G.E.

“…To forecast gasoline consumption (GC), the ANN uses previous GC data and its determinants in a training data set. …”
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Neural network-based failure rate prediction for De Havilland Dash-8 tires by Al-Garni, Ahmed Z.

“…The inputs to the neural network are independent variables and the output is the failure rate of the tires. Six years of data are used for model building and validation. …”
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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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