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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Scrambled Prime Key Encryption by Haraty, Ramzi A.

“…To enhance data security different cryptographic algorithms are used. …”
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Predicting insulin dosage for diabetic patients to reach optimal glucose levels. (c2012) by Bitar, Mandy

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From Collatz Conjecture to chaos and hash function by Masrat Rasool (17807813)

“…This paper aims to introduce a novel approach to addressing current security challenges by utilizing our generalized Collatz process to create a chaos-based hash function. By leveraging the unpredictable behaviour of the Collatz sequence, the proposed hash function aims to enhance ergodicity and entropy properties, thereby making it well-suited for cryptographic applications. …”

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. …”

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.…”

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). The design makes use of projective coordinates together with scalable Montgomery multipliers for data size of up to 256-bits. …”
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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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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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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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Applications of fast fourier transform in the integrity evaluation of deep foundations by Abi Shdid, Caesar

“…The method is developed and validated using experimental data, and is based on applying the fast Fourier transform mapping algorithm on data obtained from cross-hole sonic logging. …”
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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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Privacy-preserving energy optimization via multi-stage federated learning for micro-moment recommendations by Md Mosarrof Hossen (21399056)

“…<p>Human behavior significantly impacts domestic energy consumption, making it essential to monitor and improve these consumption patterns. …”

A comprehensive review of deep reinforcement learning applications from centralized power generation to modern energy internet frameworks by Sakib Mahmud (15302404)

“…Deep reinforcement learning (DRL) offers a data-driven alternative that couples perception with sequential decision-making. …”

Modeling and Control of a Thermally Driven MEMS Actuator for RF Applications by Estahbanati, Shahabeddin Vamegh

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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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