The Role of Artificial Intelligence in Decoding Speech from EEG Signals: A Scoping Review by Uzair Shah (15740699)

“…The study selection process was carried out in three phases: study identification, study selection, and data extraction. …”

Crashworthiness optimization of composite hexagonal ring system using random forest classification and artificial neural network by Monzure-Khoda Kazi (17191207)

“…The ultimate target is to develop a robust multi-modal machine learning method to predict the optimum geometry (i.e., hexagonal ring angle) and suitable in-plane crushing arrangements of the hexagonal ring system for targeted crashworthiness parameters. …”

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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Improving Rule Set Based Software Quality Prediction by Azar, Danielle

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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

“…Feature selection (FS) is the activity of defining the most contributing feature subset among all used features to improve the superiority of datasets with a large number of dimensions by selecting significant features and eliminating redundant and irrelevant ones. Therefore, this process can be seen as an optimization process. The primary goals of feature selection are to decrease the number of dimensions and enhance classification accuracy in many domains, such as text classification, large-scale data analysis, and pattern recognition. …”
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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.…”

Towards a self-powering greenhouse using semi-transparent PV: Utilizing hybrid BESS-hydrogen energy storage system by Gholami, Mohammadreza

“…Second, by employing a comprehensive approach with the GBO algorithm, the research examines various scenarios as a multi-objective optimization problem, balancing economic considerations such as net present value (NPV) and energy dependency (ED). …”
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Towards a self-powering greenhouse using semi-transparent PV: Utilizing hybrid BESS-hydrogen energy storage system by Mohammadreza Gholami (17032317)

“…Second, by employing a comprehensive approach with the GBO algorithm, the research examines various scenarios as a multi-objective optimization problem, balancing economic considerations such as net present value (NPV) and energy dependency (ED). …”

Predicting the Heats of Fusion of Ionic Liquids via Group Contribution Modeling and Machine Learning by Zeinab, Samira Jihad

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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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Lagrangian tracking in stochastic fields with application to an ensemble of velocity fields in the Red Sea by Issa, Leila

“…Lagrangian tracking of passive tracers in a stochastic velocity field within a sequential ensemble data assimilation framework is challenging due to the exponential growth in the number of particles. …”
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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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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. …”

Scheduling and allocation in high-level synthesis using stochastic techniques by Sait, Sadiq M.

“…High-level synthesis is the process of automatically translating abstract behavioral models of digital systems to implementable hardware. …”
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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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Modelling of pollutant transport in compound open channels by Chatila, Jean Georges

“…The numerical computation of open-channel flows requires preparing and processing larger volumes of boundary and bathymetry data for computer inputs and the development of numerical algorithms for treating complex boundary condition, channel properties, and free surface effects. …”
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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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Anomaly Detection Based Framework for Profile Monitoring by Al-Rahim, Nour Al-Huda Z. Al-Abed

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Reconstruction and simulation of neocortical microcircuitry by Khazen, Georges

“…The reconstruction uses cellular and synaptic organizing principles to algorithmically reconstruct detailed anatomy and physiology from sparse experimental data. …”
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An Artificial Intelligence Approach for Predictive Maintenance in Electronic Toll Collection System by Alkhatib, Osama

“…Despite having different performance results on predicting failures, most of the models produced close outcomes. Meaning no “perfect” machine learning algorithm that will produce good results at particular problem, in fact for each type of problem a specific algorithm is suited and might achieves good outcome, while another algorithm fails heavily. …”
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