A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network حسب Xiaofang Pan (1895950)

CNN and HEVC Video Coding Features for Static Video Summarization حسب Issa, Obada

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Novel algorithms for accurate DNA base-calling حسب Mohammed, Omniyah Gul

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Predicting Patient ICU Readmission Using Recurrent Neural Networks With Long Short-Term Memory حسب Nadia Rasheed (22997257)

Deep Learning-Based Coding Strategy for Improved Cochlear Implant Speech Perception in Noisy Environments حسب Billel Essaid (22047578)

Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices حسب Khawam, Yahya Bader

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Competitive learning/reflected residual vector quantization for coding angiogram images حسب Mourn, W.A.H.

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Automatic Video Summarization Using HEVC and CNN Features حسب Issa, Obada

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A new multiobjective evolutionary algorithm forenvironmental/economic power dispatch حسب Abido, A.A.

"…In this paper, a new multiobjective evolutionary algorithm for environmental/economic power dispatch (EED) optimization problem is presented. …"
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Environmental/economic power dispatch using multiobjective evolutionary algorithms: a comparative study حسب Abido, M.A.

"…A comparative study of newly developed Pareto-based multiobjective evolutionary algorithms (MOEA) applied to a nonlinear power system multiobjective optimization problem is presented in this paper. …"
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TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection حسب Zina Chkirbene (16869987)

"…TIDCS reduces the number of features in the input data based on a new algorithm for feature selection. Initially, the features are grouped randomly to increase the probability of making them participating in the generation of different groups, and sorted based on their accuracy scores. …"

Nonlinear analysis of shell structures using image processing and machine learning حسب M.S. Nashed (16392961)

Face Recognition in Uncontrolled Indoor Environment حسب Abuqaaud, Kamal Adel

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A new bi-objective model of the urban public transportation hub network design under uncertainty حسب Firoozeh Kaveh (14150877)

"…For medium and large-sized problems, a meta-heuristic algorithm, namely multi-objective particle swarm optimization is applied and its performance is compared with results from the non-dominated sorting genetic algorithm. …"

An Efficient Prediction System for Diabetes Disease Based on Deep Neural Network حسب Tawfik Beghriche (19563184)

"…A performance comparison between the DNN algorithm and some well‐known machine learning techniques as well as the state‐of‐the‐art methods is presented. …"

Combined cycle gas turbine system optimization for extended range electric vehicles حسب Barakat, Aya A.

"…The two-steps methodology consists of conducting first an exergo-technological analysis using a Non-dominated Sorting Genetic Algorithm to identify the best suitable combined cycle configuration for integration in a series hybrid powertrain. …"
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Cohen syndrome and early-onset epileptic encephalopathy in male triplets: two disease-causing mutations in VPS13B and NAPB حسب Alice AbdelAleem (17753799)

"…Sanger sequencing verified the segregation of the two recessive gene variants with the phenotype in family members. The prediction algorithms support the pathogenicity of these variants. …"

Oversampling techniques for imbalanced data in regression حسب Samir Brahim Belhaouari (9427347)

"…For tabular data, we also present the Auto-Inflater neural network, utilizing an exponential loss function for Autoencoders. …"

A Literature Review on System Dynamics Modeling for Sustainable Management of Water Supply and Demand حسب Khawar Naeem (17984062)

"…The solution approaches included the genetic algorithm (GA), particle swarm optimization (PSO), and the non-dominated sorting genetic algorithm (NSGA-II). …"

An Artificial Intelligence Approach for Predictive Maintenance in Electronic Toll Collection System حسب Alkhatib, Osama

"…Historical data of Dubai Toll Collection System is utilized to investigate multiple machine learning algorithms. Experiment is performed using Azure Machine Learning (ML) platform to test and assess the most efficient model that would predict the failure of system elements and predict the abnormality of the operation. …"
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