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1
Deep random vector functional link transformer network with multiple output layers for significant wave height forecasting
Published 2025“…This paper introduces a novel random vector functional link transformer (RFT) and ensemble deep random vector functional link transformer (edRFT) networks to capture the dynamic characteristics of significant wave heights. …”
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2
An Efficient Test Vector Compression Technique Based on Geometric Shapes
Published 2001“…The proposed scheme is based on ordering the test vectors in such a way that enables the generation of geometric shapes that can be highly compressed via perfect lossless compression. …”
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3
Differential Flatness-Based Performance Enhancement of a Vector Controlled VSC With an LCL-Filter for Weak Grids
Published 2021“…<p>In this paper, a novel single-loop flatness-based controller (FBC) is proposed to control the grid-side current in a shunt converter connected to a weak grid through an LCL-filter. …”
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4
On Test Vector Reordering for Combinational Circuits
Published 2004“…In this paper, we propose an efficient test vector reordering technique that significantly reduces both the time and memory complexities of reordering procedures based on fault simulation without dropping. …”
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5
On test vector reordering for combinational circuits
Published 2004“…In this paper, we propose an efficient test vector reordering technique that significantly reduces both the time and memory complexities of reordering procedures based on fault simulation without dropping. …”
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6
Ensemble Deep Random Vector Functional Link Neural Network for Regression
Published 2022“…<p dir="ltr">Inspired by the ensemble strategy of machine learning, deep random vector functional link (dRVFL), and ensemble dRVFL (edRVFL) has shown state-of-the-art results on different datasets. …”
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7
Board changes and CEO turnover
Published 2014“…For firms that decrease independence, the CEO turnover performance sensitivity significantly decreases following SOX. …”
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A slow but steady nanoLuc: R162A mutation results in a decreased, but stable, nanoLuc activity
Published 2024“…<p dir="ltr">NanoLuc (NLuc) <u>luciferase</u> has found extensive application in designing a range of <u>biologica</u><u>l</u><u> assays,</u> including <u>gene expression analysis</u>, protein-protein interaction, and protein conformational changes due to its enhanced brightness and small size. …”
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9
An enhanced ensemble deep random vector functional link network for driver fatigue recognition
Published 2023“…<p>This work investigated the use of an ensemble deep random vector functional link (edRVFL) network for electroencephalogram (EEG)-based driver fatigue recognition. …”
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10
SARS‐CoV‐2 infection triggers more potent antibody‐dependent cellular cytotoxicity (ADCC) responses than mRNA‐, vector‐, and inactivated virus‐based COVID‐19 vaccines
Published 2024“…We analyzed ADCC activity targeting SARS‐CoV‐2 spike (S) and nucleocapsid (N) proteins in convalescent sera following WT SARS‐CoV‐2‐infection (<i>n</i> = 91), including symptomatic and asymptomatic infections, omicron‐infection (<i>n</i> = 8), COVID‐19 vaccination with messenger RNA‐ (mRNA)‐ (BNT162b2 or mRNA‐1273, <i>n</i> = 77), adenovirus vector‐ (<i>n</i> = 41), and inactivated virus‐ (<i>n</i> = 46) based vaccines, as well as post‐mRNA vaccination BTI caused by omicron (<i>n</i> = 28). …”
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11
Notch Signaling Inhibition by LY411575 Attenuates Osteoblast Differentiation and Decreased Ectopic Bone Formation Capacity of Human Skeletal (Mesenchymal) Stem Cells
Published 2019“…Global gene expression profiling of LY411575-treated cells revealed changes in multiple signaling pathways, including focal adhesion, insulin, TGFβ, IL6, and Notch signaling, and decreased the expression of genes associated with functional categories of tissue development. …”
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12
Vocal Changes in Patients With Polycystic Ovary Syndrome
Published 2011“…There was no statistically significant difference in the acoustic parameters except for an increase in the relative average perturbation (P value = 0.035) and a decrease in maximum phonation time (P value = 0.001) in patients with PCOS. …”
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Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test
Published 2019“…Data generated from an oral glucose tolerance test (OGTT) was used to develop a predictive model based on the support vector machine (SVM). We trained and validated the models using the OGTT and demographic data of 1,492 healthy individuals collected during the San Antonio Heart Study. …”
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15
Interval-Valued SVM Based ABO for Fault Detection and Diagnosis of Wind Energy Conversion Systems
Published 2022“…The developed techniques are based on Support Vector Machine (SVM) model to improve the diagnosis of WEC systems. …”
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16
Essays on the effect of excess compensation and governance changes on firm value
Published 2012“…This dissertation consists of three essays on the effect of excess compensation and corporate governance changes on the firm’s performance. The first paper utilizes a cost minimization stochastic frontier approach to investigate the efficiency of director total compensation. …”
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17
Hyperspectral-physiological based predictive model for transpiration in greenhouses under CO<sub>2</sub> enrichment
Published 2023“…The results demonstrated the inclusion of hyperspectral-based vegetation indices significantly increased the performance of the three machine learning models in predicting transpiration. …”
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Metabolomics of Dynamic Changes in Insulin Resistance Before and After Exercise in PCOS
Published 2019“…While compering within the groups, no significant changes in the amino acid levels before and after exercise were observed. …”
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A Multi-Feature Based Approach Incorporating Variable Thresholds for Detecting Price Spikes in the National Electricity Market of Australia
Published 2021“…These features are employed as inputs to a support vector machine to classify electricity prices as spikes or non-spikes. …”
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Kernel-Ridge-Regression-Based Randomized Network for Brain Age Classification and Estimation
Published 2024“…In this study, a brain age classification and estimation framework is proposed using structural magnetic resonance imaging (sMRI) scans, a 3-D convolutional neural network (3-D-CNN), and a kernel ridge regression-based random vector functional link (KRR-RVFL) network. …”