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code algorithm » cosine algorithm (Expand Search), rd algorithm (Expand Search), colony algorithm (Expand Search)
mean algorithm » deer algorithm (Expand Search), search algorithm (Expand Search)
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A Novel Internal Model Control Scheme for Adaptive Tracking of Nonlinear Dynamic Plants
Published 2006“…The U-model utilizes only past data for plant modelling and standard root solving algorithm for control law formulation. …”
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Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands
Published 2020“…This would make it possible to extract out the standard deviation value of the uncertain parameters and reflect their impacts on the microgrid operation problem through the limited concentration points. A novel evolving solution based on flower pollination algorithm is also proposed to solve the problem optimally. …”
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Joint energy-distortion aware algorithms for cooperative video streaming over LTE networks
Published 2013“…Videos with single description coding (SDC), multiple description coding (MDC), and scalable video coding (SVC) are considered. …”
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K Nearest Neighbor OveRsampling approach: An open source python package for data augmentation
Published 2022“…This paper introduces K Nearest Neighbor OveRsampling (KNNOR) Algorithm — a novel data augmentation technique that considers the distribution of data and takes into account the k nearest neighbors while generating artificial data points. …”
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Comprehensive whole genome sequence analyses yields novel genetic and structural insights for Intellectual Disability
Published 2017“…The <i>de novo</i> assembly resulted in unmasking hidden genome instability that was missed by standard re-alignment based algorithms. We also interrogated regulatory sequence variation for known and hypothesized ID genes and present useful strategies for WGS data analyses for non-coding variation.…”
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Parameter identification of PV solar cells and modules using bio dynamics grasshopper optimization algorithm
Published 2024“…However, accurate modelling and identification of PV cell parameters pose challenges, prompting the adoption of meta‐heuristic optimization algorithms. This work explores the limitations of existing algorithms and introduces a novel approach, the bio‐dynamics grasshopper optimization algorithm (BDGOA). …”
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Single-Cell Transcriptome Analysis Revealed Heterogeneity and Identified Novel Therapeutic Targets for Breast Cancer Subtypes
Published 2023“…Taken together, our data are the first to unravel the unique gene signatures and to identify novel dependencies and therapeutic vulnerabilities for each BC molecular subtype, thus setting the foundation for the future development of more effective targeted therapies for BC.…”
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Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators
Published 2021“…The outcomes of the DNA microarray is a table/matrix, called gene expression data. Pattern recognition algorithms are widely applied to gene expression data to differentiate between health and cancerous patient samples. …”
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A novel few shot learning derived architecture for long-term HbA1c prediction
Published 2024“…For the first time in the literature, this work proposes a novel FSL-derived algorithm for the long-term prediction of clinical HbA1c measures. …”
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Systems biology analysis reveals NFAT5 as a novel biomarker and master regulator of inflammatory breast cancer
Published 2015“…</p><h3>Methods</h3><p dir="ltr">In-silico modeling and Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNe) on IBC/non-IBC (nIBC) gene expression data (n = 197) was employed to identify novel master regulators connected to the IBC phenotype. …”
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Autonomous 3D Deployment of Aerial Base Stations in Wireless Networks with User Mobility
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Smart non-intrusive appliance identification using a novel local power histogramming descriptor with an improved k-nearest neighbors classifier
Published 2021“…Specifically, short local histograms are drawn to represent individual appliance consumption signatures and robustly extract appliance-level data from the aggregated power signal. Furthermore, an improved k-nearest neighbors (IKNN) algorithm is presented to reduce the learning computation time and improve the classification performance. …”