Resources Allocation for Drones Tracking Utilizing Agent-Based Proximity Policy Optimization by De Rochechouart, Maxence

“…The learned system can apply sensor allocation online, works in real-time, and selects one radar and one camera at a time without having to reevaluate a cost function at every time step. …”
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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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Morphology for Planar Hexagonal Modular Self-Reconfigurable Robotic Systems by Sadjadi, Hossein

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Energy-Efficient Computation Offloading in Vehicular Edge Cloud Computing by Xin Li (51274)

“…Subsequently, we propose a method to measure the cost-effectiveness of allocated resources and energy savings, named value density function. …”

Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management by Alhusin, Mohammed Omer Alamin

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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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Software defect prediction. (c2019) by Moussa, Rebecca

“…This is normally measured at the level of a module. A module is a class in the object-oriented design or a function in the procedural design. …”
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Prediction of biogas production from chemically treated co-digested agricultural waste using artificial neural network by Fares Almomani (12585685)

“…The developed model can be used to forecast the CMP as a function of operating temperature, the substrate composition, and chemical dose, and can be used for scaling-up and cost analysis purposes.…”

Improving the Resilience of Smart Distribution Networks against Cyber Attacks by ElYamani, Mohamed ElHusseiny Mohamed

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Small-Signal Stability Analysis and Parameters Optimization of Virtual Synchronous Generator for Low-Inertia Power System by Alaa Altawallbeh (22565837)

“…Through systematic eigenvalue analysis and parameter sensitivity studies, complemented by time-domain verification in MATLAB/SIMULINK, we demonstrate the decisive influence of VSG control parameters on low-frequency oscillation (LFO) damping characteristics, transient frequency stability metrics, including the rate of change of frequency (ROCOF), maximum frequency deviation (<i>fnadir</i>), overshoot, and settling time. We further propose a hybrid Particle Swarm Optimization (PSO) algorithm with a multi-objective cost function to optimize VSG controller gains. …”

Multidimensional Gains for Stochastic Approximation by Saab, Samer S.

“…This paper deals with iterative Jacobian-based recursion technique for the root-finding problem of the vector-valued function, whose evaluations are contaminated by noise. …”
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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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Power system output feedback stabilizer design via geneticalgorithms by Abdel-Magid, Y.L.

“…In the second method, the problem of selecting the output feedback gains is converted to a simple optimization problem with an eigenvalue based objective function, which is solved by a genetic algorithm. …”
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Intelligent route to design efficient CO₂ reduction electrocatalysts using ANFIS optimized by GA and PSO by Majedeh Gheytanzadeh (17541927)

“…The development of such technology is strongly depended upon tuning the surface properties of the applied electrocatalysts. Considering the high cost and time-consuming experimental investigations, computational methods, particularly machine learning algorithms, can be the appropriate approach for efficiently screening the metal alloys as the electrocatalysts. …”

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

“…</p><h2>Other Information</h2><p dir="ltr">Published in: Composites Part C: Open Access<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.jcomc.2024.100440" target="_blank">https://dx.doi.org/10.1016/j.jcomc.2024.100440</a></p>…”

Singularly perturbed nonlinear ODEs and interior point optimizationalgorithms by Ezzine, J.

“…In addition, this connection is used to show that the logarithmic barrier function is indeed, in some sense, optimum…”
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Autonomous Robot Navigation Based On Recurrent Neural Networks by Al-Sagban, Mariam Qusai

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AGEomics Biomarkers and Machine Learning—Realizing the Potential of Protein Glycation in Clinical Diagnostics by Naila Rabbani (291722)

“…The term AGEomics is defined as multiplexed quantitation of spontaneous modification of proteins damage and other usually low-level modifications associated with a change of structure and function—for example, citrullination and transglutamination. …”