Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort by Sergio Márquez-Sánchez (19437985)

“…However, these BEMSs often suffer from a critical limitation—they are primarily trained on building energy data alone, disregarding crucial elements such as occupant comfort and preferences. …”

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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General Inspection Plan For Critical Multicharacteristic Components by Duffuaa, S. O.

“…A decent type algorithm is proposed to determine the optimal number of repeat inspections and sequence characteristics for inspection that minimizes the expected total cost. …”
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Spatiotemporal Mapping and Monitoring of Mangrove Forests Changes From 1990 to 2019 in the Northern Emirates, UAE Using Random Forest, Kernel Logistic Regression and Naive Bayes Tr... by Elmahdy, Samy

“…The approach was developed based on random forest (RF), Kernel logistic regression (KLR), and Naive Bayes Tree machine learning algorithms which use multitemporal Landsat images. …”
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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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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.…”

A reduced model for phase-change problems with radiation using simplified PN approximations by Belhamadia, Youssef

“…In the present study, we develop a class of efficient reduced models for phase-change problems accounting for grey thermal radiation. …”
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LNCRI: Long Non-Coding RNA Identifier in Multiple Species by Saleh Musleh (15279190)

“…However, the cost and time-consuming nature of transcriptomics verification techniques barred the research community from focusing on lncRNA identification. …”

An Optimal Repeat Inspection Plan With Several Classifications by Duffuaa, S. O.

“…A mathematical model that depicts the plan is developed. An algorithm is proposed for finding the optimal number of repeat inspections and the sequence of characteristics for inspection that minimizes expected total cost per accepted component. …”
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A hybrid model for the optimum integration of renewable technologies in power generation systems by Poullikkas, Andreas

“…The optimization model developed uses a genetic algorithm (GA) technique for the calculation of both the additional cost of electricity due to the penetration of RES-E technologies as well as the required RES-E levy in the electricity bills in order to fund this RES-E penetration. …”
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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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Establishing Autonomous AUS-Quadrotor by Al Younes, Younes

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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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