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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Classification automatique et stratégie d'annotation appliquées à un concept philosophique: la dimension psychologique du concept de LANGAGE dans l'oeuvre de Bergson 1 by Alrahabi, Al Moatasem

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

“…Broadband stimulation signals are injected from distributed generators and their effects are measured at various locations in the grid. To process and evaluate this data, a novel aggregation method based on weighed least squares will be proposed in this study. …”
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ISSP by Zouein, P.P.

“…Many decision-support tools were developed to assist planners in space scheduling but these were limited to providing the user with a platform that ties spatial and temporal data in the project and left it up to the user to decide on positions of resources and schedule adjustments to solve spatial conflicts that may arise in the process of constructing site layouts over time.The ISSP system, presented here, provides a graphical user-interactive interface with underlying layout and scheduling algorithms that construct feasible layout and schedule solutions under 2-dimensional spatial constraints between resources. …”
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Benchmark on a large cohort for sleep-wake classification with machine learning techniques by Joao Palotti (8479842)

“…However, the largest experiments conducted to date, have had only hundreds of participants. In this work, we processed the data of the recently published Multi-Ethnic Study of Atherosclerosis (MESA) Sleep study to have both PSG and actigraphy data synchronized. …”

Improving Rule Set Based Software Quality Prediction by Azar, Danielle

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A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass by Uzma Nawaz (21980708)

“…By synthesizing findings across various data sources and model architectures, we offer critical insights into the selection of context-aware algorithms and identify key research gaps, an essential step for advancing the reliability and applicability of AI-driven seagrass conservation efforts.…”

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

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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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Identification of the Uncertainty Structure to Estimate the Acoustic Release of Chemotherapeutics From Polymeric Micelles by Wadi, Ali

“…The identified a priori knowledge is used to implement an optimal Kalman filter, a multi-hypothesis Kalman filter, and a variant of the full information estimator (moving horizon estimator) to the problem at hand. The proposed algorithms are initially deployed in a simulation environment, and then the experimental data sets are fed into the algorithms to validate their performance. …”
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Establishing Autonomous AUS-Quadrotor by Al Younes, Younes

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Corrosion Monitoring Technologies for Reinforced Concrete Structures: A Review by SHEHADEH, KHADIJA

“…New technology, algorithms, data processing, and AI are new approaches to improving corrosion monitoring processes. …”
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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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Positive Unlabelled Learning to Recognize Dishes as Named Entity by TAREK, AIMAN

“…With the lack of labelled data, I try to overcome the cold start and avoid manual labelling by building a lookup table from a dictionary. …”
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Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier by Syed Ali Jafar Zaidi (19563178)

“…Multiple ML algorithms are used to improve decision-making at different aspects after forecasting. …”

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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Modeling and Bias-Robust Estimation of the Acoustic Release of Chemotherapeutics from Liposomes by Wadi, Ali

“…Optimality is guaranteed by accurately identifying the underlying statistical noise characteristics in experimental data. The estimator also quantifies the bias in the release, exhibited by the experimental data. …”
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Anonymizing multimedia documents by Haraty, Ramzi

“…We provide a sanitizing MD∗-algorithm to enforce de-linkability along with a utility function to evaluate the utility of multimedia documents that is preserved after the sanitizing process. …”
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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. …”