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Evaluation of transfer functions for punctured turbo codes
Published 2000“…A modified algorithm for evaluating transfer functions of turbo codes with punctured systematic bits is presented. …”
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Attacking ElGamal based cryptographic algorithms using Pollard's rho algorithm
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An enhanced binary Rat Swarm Optimizer based on local-best concepts of PSO and collaborative crossover operators for feature selection
Published 2022“…The binary enhanced RSO is built based on three successive modifications: i) an S-shape transfer function is used to develop binary RSO algorithms; ii) the local search paradigm of particle swarm optimization is used with the iterative loop of RSO to boost its local exploitation; iii) three crossover mechanisms are used and controlled by a switch probability to improve the diversity. …”
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Determining the Factors Affecting the Boiling Heat Transfer Coefficient of Sintered Coated Porous Surfaces
Published 2021“…In this regard, two Bayesian optimization algorithms including Gaussian process regression (GPR) and gradient boosting regression trees (GBRT) are used for tuning the hyper-parameters (number of input and dense nodes, number of dense layers, activation function, batch size, Adam decay, and learning rate) of the deep neural network. …”
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Design Optimization of Inductive Power Transfer Systems Considering Bifurcation and Equivalent AC Resistance for Spiral Coils
Published 2020“…<p>This paper presents a design optimization algorithm for series-series compensated Inductive Power Transfer (IPT) system based on flat spiral coils, considering bifurcation phenomenon and AC equivalent resistance of the coils. …”
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A novel method for the detection and classification of multiple diseases using transfer learning-based deep learning techniques with improved performance
Published 2024“…Chest X-rays, MRI scans, CT scans, and skin lesions are used to diagnose the mentioned diseases. Transfer learning algorithms, such as VGG16, VGG19, ResNet, InceptionV3, and EfficientNetB4, are utilized to categorize various diseases. …”
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Impact of fuzzy volume fraction on unsteady stagnation-point flow and heat transfer of a third-grade fuzzy hybrid nanofluid over a permeable shrinking/stretching sheet
Published 2024“…Also, the comparison of Al<sub>2</sub>O<sub>3</sub>/SA, Cu/SA and Al<sub>2</sub>O<sub>3</sub> +Cu/SA through the fuzzy membership functions (MFs). The fuzzy MFs show that the hybrid nanofluid (Al<sub>2</sub>O<sub>3</sub> +Cu/SA) in terms of rate of heat transfer is better than both Cu/SA and Al<sub>2</sub>O<sub>3</sub>/SA nanofluids.…”
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A hybrid of clustering and meta-heuristic algorithms to solve a p-mobile hub location–allocation problem with the depreciation cost of hub facilities
Published 2021“…<p dir="ltr">Hubs act as intermediate points for the transfer of materials in the transportation system. …”
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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT
Published 2023“…We utilised a CNN to determine the best-transferring strategy and the most efficient partitioning of a specific task. …”
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Brain Source Localization in the Presence of Leadfield Perturbations
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A Quasi-Oppositional Method for Output Tracking Control by Swarm-Based MPID Controller on AC/HVDC Interconnected Systems With Virtual Inertia Emulation
Published 2021“…Also the proposed fitness function, as deviation characteristics of the step response in MIMO transfer function in virtual inertia emulation based HVDC model, is compared with integral time absolute error (ITAE), as the standard performance index in the optimization process. …”
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Performance Analysis of Artificial Neural Networks in Forecasting Financial Time Series
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Gas pipeline modelling and control
Published 2015“…The pipeline input–output, transfer function, pressure and volume flow representations are formulated. …”
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A lightweight adaptive compression scheme for energy-efficient mobile-to-mobile file sharing applications
Published 2011“…The proposed scheme monitors the signal strength level during the file transfer process and compresses data blocks on-the-fly only whenever energy reduction gain is expected. …”
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Automatic image quality evaluation in digital radiography using a modified version of the IAEA radiography phantom allowing multiple detection tasks
Published 2025“…</p><h3>Results</h3><p dir="ltr">The IQ‐metric values calculated using the modified IAEA phantom images can be radically different between raw and clinical images, and between different manufacturers, irrespectively whether only the standard or all the different Al‐target thicknesses are considered. The modulation transfer function (MTF) and the signal‐to‐noise‐ratio (SNR) dependence on exposure conditions and post‐processing algorithms do not always follow the same trends for raw and clinical images and/or different manufacturers, while the signal‐difference‐to‐noise‐ratio (SDNR) and the detectability index (d′), despite their differences, seem more appropriate to characterize IQ. …”