GATS: A Novel Hybrid Algorithm for Multiobjective Cell Placement in VLSI Circuit Design by Sait, Sadiq M.

“…This paper addresses the optimization of cell placement step in VLSI circuit design [1]. A novel hybrid algorithm is proposed for performance and low power driven VLSI standard cell placement. …”
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Timing influenced general-cell genetic floorplanner by Sait, Sadiq M.

“…In this paper we present a timing-influenced floorplanner for general cell IC design. …”
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Adaptive Time-Varying Brain Source Localization by Al-Momani, Sajedah A.

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New Fast Arctangent Approximation Algorithm for Generic Real-Time Embedded Applications by Mohieddine Benammar (18103039)

“…A new 2nd order rational approximation formula is introduced for the first time in this work and benchmarked against existing alternatives as it improves the new algorithm performance. …”

A parallel tabu search algorithm for VLSI standard-cell placement by Suit, S.M.

“…VLSI standard-cell placement is an NP-hard problem to which various heuristics have been applied. …”
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Time-varying volatility model equipped with regime switching factor: valuation of option price written on energy futures by Leduc, Guillaume

“…We develop a semi-analytical method to determine the price of European options on these energy futures, involving the derivation of the characteristic function for the energy futures' dynamics. To determine the parameters of the regime switching model and identify when economic states change, we employ the EM algorithm, utilizing real gas futures price data. …”
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Logarithmic spiral search based arithmetic optimization algorithm with selective mechanism and its application to functional electrical stimulation system control by Abu Zitar, Raed

“…The constructed Ls-AOA algorithm was then proposed to design a proportional-integral-derivative (PID) controller employed in a functional electrical stimulation (FES) system for the first time. …”

Guaranteed Cost Control Of A Markov Jump Linear Uncertain System UsingA Time-Multiplied Cost Function by Boukas, EK

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Guaranteed Cost Control Of A Markov Jump Linear Uncertain System Using A Time-Multiplied Cost Function by Boukas, EK

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Guaranteed Cost Control Of A Markov Jump Linear Uncertain System Using A Time-Multiplied Cost Function by Boukas, EK

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Efficient Algorithms for Constructing Preset Distinguishing Sequences for Nondeterministic Finite State Machines by Haddad, Abdul Rahim

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Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids by Khayata, Mohammad Tarek

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STEM: spatial speech separation using twin-delayed DDPG reinforcement learning and expectation maximization by Muhammad Salman Khan (7202543)

Real-Time Implementation of High Performance Control Scheme for Grid-Tied PV System for Power Quality Enhancement Based on MPPC-SVM Optimized by PSO Algorithm by Abdelbasset Krama (16870008)

“…<p dir="ltr">This paper proposes a high performance control scheme for a double function grid-tied double-stage PV system. It is based on model predictive power control with space vector modulation. …”

Optimization of Commercially Off the Shelf (COTS) Electric Propulsion System for Low Speed Fuel Cell UAV by Zulkifli, Muhammad

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Single channel speech denoising by DDPG reinforcement learning agent by Sania Gul (18272227)

“…<p dir="ltr">Speech denoising (SD) covers the algorithms that suppress the background noise from the contaminated speech and improve its clarity. …”

BUC algorithm for iceberg cubes by Nasr, George E.

“…In this paper, we implement the Bottom-Up Computation (BUC) algorithm for computing Iceberg cubes and conduct a sensitivity analysis of BUC with respect to the probability density function of the data. …”
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High-Accurate Parameter Identification of PEMFC Using Advanced Multi-Trial Vector-Based Sine Cosine Meta-Heuristic Algorithm by Badreddine Kanouni (23073244)

“…The trigonometric function-based sine cosine algorithm (SCA) may solve such problems, but it traps in local optima, making it inappropriate for larger optimization tasks. …”

Cross entropy error function in neural networks by Nasr, G.E.

“…The ANN is implemented using the cross entropy error function in the training stage. The cross entropy function is proven to accelerate the backpropagation algorithm and to provide good overall network performance with relatively short stagnation periods. …”
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Development of an Optimization Scheme for A Fixed-Wing UAV Long Endurance with PEMFC and Battery by Al Rayes, Zaid

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