Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques by Fares, Samar

“…This paper presents two different methods for track-to-track fusion of drone tracks. …”
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Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier by Syed Ali Jafar Zaidi (19563178)

“…This study focuses on the future prediction of the effectiveness of the COVID-19 vaccine effectiveness which has been presented as a light in the dark. People bear several reservations, including concerns about the efficacy of the COVID-19 vaccine. …”

Local convexity preserving rational cubic spline curves by Sarfraz, M.

“…An algorithm is presented which constructs a curve by interpolating the given data points. …”
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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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Intelligent route to design efficient CO₂ reduction electrocatalysts using ANFIS optimized by GA and PSO by Majedeh Gheytanzadeh (17541927)

“…Accordingly, a dataset containg 258 data points was extracted from the DFT method to use in machine learning method. …”

Parallel processing by Mansour, Nashat

“…Parallel algorithms, based on simulated annealing, neural networks and genetic algorithms, for mapping irregular data to multicomputers are presented and compared. …”
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Decomposition-based wind power forecasting models and their boundary issue: An in-depth review and comprehensive discussion on potential solutions by Yinsong Chen (16685508)

“…Then, we systematically summarize commonly available boundary issue solutions into three categories, namely algorithm-based solutions, sampling-strategy-based solutions and iteration-based solutions. …”

Dynamic adaptation for video streaming over mobile devices. (c2013) by Jalloul, Rayan A.

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An Improved Genghis Khan Optimizer based on Enhanced Solution Quality Strategy for Global Optimization and Feature Selection Problems by Abdel-Salam, Mahmoud

“…It utilizes Quasi-opposite-based learning (QOBL) to enhance the best solution obtained and, consequently, the entire population. The algorithm presented aims to solve the FS problem and has been assessed using benchmark optimization problems from the CEC’2017 and CEC’2022. …”
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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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Lagrangian tracking in stochastic fields with application to an ensemble of velocity fields in the Red Sea by Issa, Leila

“…To this end, an efficient algorithm for forward and backward tracking of passive particles in stochastic flow-fields is presented. …”
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Growing hierarchical self-organizing map for filtering intrusion detection alarms by Mansour, Nashat

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A geographic information system method to generate long term regional solar radiation resource maps: enhancing decision-making by Sachin Jain (19161721)

“…The availability of solar radiation throughout the country has been mapped here using ground-based measurements and satellite data. The regression-kriging algorithm and its variants are used to calibrate satellite data, through interpolation of ground solar radiation data. …”

Innovative mobile E-healthcare systems by Haraty, Ramzi A.

“…Caching is one of the key methods in distributed computing environments to improve the performance of data retrieval. To find which item in the cache can be evicted and replaced, cache replacement algorithms are used. …”
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Efficient utilization of scalable multipliers in parallel to compute GF(p) elliptic curve cryptographic operations by Gutub, Adnan

“…This paper presents the design and implementation of an elliptic curve cryptographic core to realize point scalar multiplication operations used for the GF(p) elliptic curve encryption/decryption and the elliptic curve digital signature algorithm (ECDSA). …”
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Scheduling and allocation in high-level synthesis using stochastic techniques by Sait, Sadiq M.

“…Both genetic scheduling and allocation (GSA) and tabu scheduling and allocation (TSA) have been tested on various benchmarks and results obtained for data-oriented control-data flow graphs are compared with other implementations in the literature. …”
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Modelling Exchange Rates during Currency Crisis using Neural Networks by Nasr, G. E.

“…The models are built using the feedforward ANN structure trained by the backpropagation algorithm. Exchange rate data from the Lebanese currency crisis period of 1985-1992 is used for training, testing and evaluation of the models. …”
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Predicting insulin dosage for diabetic patients to reach optimal glucose levels. (c2012) by Bitar, Mandy

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Predicting COVID-19 cases using bidirectional LSTM on multivariate time series by Ahmed Ben Said (14158926)

“…Unlike other forecasting techniques, our proposed approach first groups the countries having similar demographic and socioeconomic aspects and health sector indicators using K-means clustering algorithm. The cumulative case data of the clustered countries enriched with data related to the lockdown measures are fed to the bidirectional LSTM to train the forecasting model. …”

Smart non-intrusive appliance identification using a novel local power histogramming descriptor with an improved k-nearest neighbors classifier by Yassine Himeur (14158821)

“…Specifically, short local histograms are drawn to represent individual appliance consumption signatures and robustly extract appliance-level data from the aggregated power signal. Furthermore, an improved k-nearest neighbors (IKNN) algorithm is presented to reduce the learning computation time and improve the classification performance. …”