FoGMatch by Arisdakessian, Sarhad

“…Our solution consists of (1) two optimization problems, one for the IoT devices and one for the fog nodes, (2) preference functions for both the IoT and fog layers to help them rank each other on the basis of several criteria such latency and resource utilization, and (3) centralized and distributed intelligent scheduling algorithms that consider the preferences of both the fog and IoT layers to improve the performance of the overall IoT ecosystem. …”
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Improving the Resilience of Smart Distribution Networks against Cyber Attacks by ElYamani, Mohamed ElHusseiny Mohamed

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Nouveaux points de coupure et primitives pour les préoccupations de renforcement de sécurité by Mourad, Azzam

“…The two proposed primitives are called exportParameter and importParameter and are used to pass parameters between two pointcuts. They allow to analyze a program’s call graph in order to determine how to change function signatures for the passing of parameters associated with a given security hardening. …”
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Optimized 3D Deployment of UAV-Mounted Cloudlets to Support Latency-Sensitive Services in IoT Networks by Islambouli, Rania

“…The performance of the meta-heuristic solution is evaluated and compared to the optimal solution as a function of various system parameters and for different application use cases. …”
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On-demand deployment of multiple aerial base stations for traffic offloading and network recovery by Sharafeddine, Sanaa

“…We present performance results for the proposed algorithm as a function of various system parameters and demonstrate its effectiveness compared to the close-to-optimal greedy approach and its superiority compared to recent related work from the literature.…”
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Optimized provisioning of edge computing resources with heterogeneous workload in IoT networks by Kherraf, Nouha

“…We analyze the effectiveness of the proposed algorithm through extensive simulations and highlight valuable performance trends and trade-offs as a function of various system parameters.…”
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Blood Glucose Regulation Modelling and Intelligent Control by Nasar, Nabeel

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Particle swarm optimization approach for protein structure prediction in the 3D HP model by Mansour, Nashat

“…In this paper, we present a particle swarm optimization (PSO) based algorithm for predicting protein structures in the 3D hydrophobic polar model. …”
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Guidance, Control and Trajectory Tracking of Small Fixed Wing Unmanned Aerial Vehicles (UAV's) by Al-Radaideh, Amer

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Enhanced Microgrid Reliability Through Optimal Battery Energy Storage System Type and Sizing by Mohammadreza Gholami (17032317)

“…To determine the optimized size, a firefly optimization algorithm is used as an efficient meta-heuristic approach. …”

Data-driven robust model predictive control for greenhouse temperature control and energy utilisation assessment by Farhat Mahmood (15468854)

“…A robust model predictive control strategy, based on the minimax objective function and particle swarm optimisation algorithm, is developed to handle the uncertainties in the system. …”

Design and performance analysis of hybrid MPPT controllers for fuel cell fed DC-DC converter systems by Shaik Rafikiran (15838929)

“…The studied MPPT controllers are Adaptive Adjustable Step-based Perturb and Observe (AASP&O) controllers, Variable Step Value-Radial Basis Function Controller (VSV-RBFC), Adaptive Step Hill Climb (ASHC) based fuzzy technique, Variable P&O with Particle Swarm Optimization (VP&O-PSO), and Variable Step Grey Wolf Algorithm (VSGWA) based fuzzy logic controller. …”

Design and performance analysis of hybrid MPPT controllers for fuel cell fed DC-DC converter systems by Shaik, Rafikiran

“…The studied MPPT controllers are Adaptive Adjustable Step-based Perturb and Observe (AAS-P&O) controllers, Variable Step Value-Radial Basis Function Controller (VSV-RBFC), Adaptive Step Hill Climb (ASHC) based fuzzy technique, Variable P&O with Particle Swarm Optimization (VP&O-PSO), and Variable Step Grey Wolf Algorithm (VSGWA) based fuzzy logic controller. …”
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Iterative heuristics for multiobjective VLSI standard cellplacement by Sait, Sadiq M.

“…Fuzzy rules are incorporated in order to design a multiobjective cost function that integrates the costs of three objectives in a single overall cost value. …”
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EVOLUTIONARY HEURISTICS FOR MULTIOBJECTIVE VLSI NETLIST BI-PARTITIONING by Sait, Sadiq M.

“…Fuzzy rules are incorporated in order to design a multiobjective cost function. Both the techniques are applied to ISCAS-85/89 benchmark circuits and experimental results are reported and compared.…”
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General iterative heuristics for VLSI multiobjective partitioning by Sait, Sadiq M.

“…These heuristics are based on Genetic Algorithms (GAs) and Tabu Search (TS) and incorporate fuzzy rules in order to handle the multiobjective cost function. …”
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Phased Array Technique for Brain Source Localization by Zarghami, Tahereh

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Integration of nonparametric fuzzy classification with an evolutionary-developmental framework to perform music sentiment-based analysis and composition by Abboud, Ralph

“…Unlike existing solutions, MUSEC is: (i) a hybrid crossover between supervised learning (SL, to learn sentiments from music) and evolutionary computation (for music composition, MC), where SL serves at the fitness function of MC to compose music that expresses target sentiments, (ii) extensible in the panel of emotions it can convey, producing pieces that reflect a target crisp sentiment (e.g., love) or a collection of fuzzy sentiments (e.g., 65% happy, 20% sad, and 15% angry), compared with crisp-only or two-dimensional (valence/arousal) sentiment models used in existing solutions, (iii) adopts the evolutionary-developmental model, using an extensive set of specially designed music-theoretic mutation operators (trille, staccato, repeat, compress, etc.), stochastically orchestrated to add atomic (individual chord-level) and thematic (chord pattern-level) variability to the composed polyphonic pieces, compared with traditional evolutionary solutions producing monophonic and non-thematic music. …”
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Scatter search for homology modeling by Mansour, Nashat

“…The metaheuristic optimizes the initial poor alignments and uses fitness functions. We assess our algorithm on a number of proteins whose structures are present in the Protein Data Bank and which have been used in previous literature. …”
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An Introduction to the Special Issue “Protein Glycation in Food, Nutrition, Health and Disease” by Naila Rabbani (291722)

“…The keynote speaker was Lasker Laureate Professor Kazutoshi Mori, speaking on the unfolded protein response, and there were sessions on: glycation in obesity, diabetes, and diabetic complications; glycation in food; glycation through the life course—from maternal bonding to aging; glycation in plants—physiology, function, and food security; glycation in the COVID-19 response; glycation analytics and chemistry; glycation in kidney disease, cancer, and mental health; glycation-related imaging, diagnostic algorithms, and therapeutics; and methods and models in glycation research. …”