A hybrid neuro-fuzzy power system stabilizer for multimachine powersystems by Abido, M.A.

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IMPROVING BER PERFORMANCE OF LDPC CODES BASED ON INTERMEDIATE DECODING RESULTS by Alghonaim, Esa

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Fragment based protein structure prediction. (c2013) by Terzian, Meghrig Ohanes

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The Use of Enumerative Techniques in Topological Optimization of Computer Networks Subject to Fault Tolerance and Reliability by Abd-El-barr, Mostafa

“…Experimental results obtained from a set of randomly generated networks using the proposed algorithms are presented and compared to those obtained using the existing techniques [1], [2]. …”
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Metaheuristic Optimization‐Based Sliding Mode Control With Modified Perturb and Observe for Controlling MPPT of a PV Interfaced Grid Connected System by Anupama Ganguly (22502969)

“…These two performance figures for various transition instances demonstrate that the suggested MPPT algorithm can determine the global MPP for the new shading pattern (SP) when it shifts from a uniform state to a partially shaded condition at 4s (middle of the <i>x</i>‐axis).…”

Coordinated design of robust excitation and TCSC-based damping controllers by Abido, M.A.

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Power system stability enhancement via coordinated design of a PSS and an SVC-based controller by Abido, M.A.

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Anonymizing multimedia documents by Haraty, Ramzi

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Development and Implementation of a Hybrid Intelligent Controller for Interior Permanent Magnet Synchronous Motor Drives by Nasir Uddin, M.

“…At each operating condition a genetic algorithm is used to optimize the PI controller parameters in a closed-loop vector control scheme. …”
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Optimizing Aircraft Pitch Control Systems: A Novel Approach Integrating Artificial Rabbits Optimizer with PID-F Controller by Abualigah, Laith

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Simulations of the penetration of 6061-T6511 aluminum targets by spherical-nosed VAR 4340 steel projectiles by Warren, Thomas

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Effective solutions for the capacitated vehicle routing problem and for the split delivery vehicle routing problem with time windows. (c2013) by Hilal, Nathalie

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HPTS: heterogeneous parallel tabu search for VLSI placement by Al-Yamani, A.

“…Two parallelization strategies, i.e., functional decomposition and multi-search thread strategies are integrated. …”
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Online Control and Optimization of Directional Drilling by unknown

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Single-Cell Transcriptome Analysis Highlights a Role for Neutrophils and Inflammatory Macrophages in the Pathogenesis of Severe COVID-19 by Hibah Shaath (5599658)

“…Interferon signaling, FCγ receptor-mediated phagocytosis, IL17, and Tec kinase canonical pathways were enriched in patients with severe COVID-19, while PD-1 and PDL-1 pathways were suppressed. …”

The maximum common subgraph problem by Abu-Khzam, Faisal N.

“…The result is an algorithm whose run time is bounded by a function exponential in the order of the smaller cover rather than in the order of the smaller graph.…”
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Prediction of biogas production from chemically treated co-digested agricultural waste using artificial neural network by Fares Almomani (12585685)

“…An ANN model consists of three layers, 15 neutrons and 260 <i>epochs</i> accurately predict the CMP with 99.1% of data within ±10% deviation of the mean experimental value. …”

Regression testing web services-based applications by Tarhini, Abbas

“…We discuss three situations for applying this algorithm: (1) connecting to a newly established web service that fulfills a composed web service, (2) adding or removing an operation in any of the composed web services, (3) modifying the specification of the web application. …”
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Entire hypergeometric approximants for the ground state energy perturbation series of the quartic, sextic and octic anharmonic oscillators by I.S. Elkamash (16810689)

“…Besides, in literature, we barely can find a resummation algorithm for which the convergence is faster for stronglydivergent ( Gevrey − k , k > 1) series than a divergent one ( Gevrey − 1 ). …”

Reinforcement Learning-Based School Energy Management System by Yassine Chemingui (18891757)

“…In recent years, the Deep Reinforcement Learning algorithm, applying neural networks for function approximation, shows promising results in handling such complex problems. …”