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normalization » organization (Expand Search), localization (Expand Search), realization (Expand Search)
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Toward RDF normalization
Published 2017Get full text
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Numerical simulation of large deformations of amorphous polymer with finite element method: Application to normal impact test
Published 2015“…The implementation of the model was verified on a compressive test. Next a normal impact test was simulated in order to validate the predictive capabilities of the model. …”
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Electric Behavior Modeling and Evaluation of New Lightweight Conductive Concrete
Published 2016Get full text
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The Digital Transformation in Teaching Methods as the New Normal in Abu Dhabi Private Schools
Published 2022“…The results also showed a positive teachers’ perception of Digital learning, which school leaders believe will continue with us as the new normal. Meanwhile, they found the blended or hybrid learning model as the most successful teaching, and learning model during and post Covid-19.…”
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The Effect of New Normal Leadership and Workplace Flexibility on Employee Burnout and Work-Life Balance During COVID-19 Era
Published 2022“…The proposed relationships were supported by the findings generated by PLS-SEM equation modeling.…”
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Application of human RNase P normalization for the realistic estimation of SARS-CoV-2 viral load in wastewater: A perspective from Qatar wastewater surveillance
Published 2022“…This study evaluates the use of a new normalization approach using human RNase P for the logic estimation of SARS-CoV-2 viral load in wastewater. …”
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Biallelic variants in WARS1 cause a highly variable neurodevelopmental syndrome and implicate a critical exon for normal auditory function
Published 2022“…variant as potentially impacting an exon critical for normal hearing. Together, our findings provide consolidating evidence for biallelic disruption of WARS1 as causal for an autosomal recessive neurodevelopmental syndrome and present a vertebrate model that recapitulates key phenotypes observed in patients.…”
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Prediction of minimum factor of safety against slope failure in clayey soils using artificial neural network
Published 2015“…It is observed that both ANN predictions are very close to the FS calculated by each of the corresponding four methods, separately. However, the ANN model with the scaled down number of input parameters showed better performance and the best one has a normalized mean square error of 0.0073, mean absolute percent error (MAPE) of 1.52 % and correlation coefficient (r) of 0.9966. …”
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Perinatal outcomes in women with class IV obesity compared to women in the normal or overweight body mass index categories: A population‐based cohort study in Qatar
Published 2023“…Adjusted odds ratios (aOR) with 95% confidence intervals (95% CI) were determined using multivariable logistic regression models.</p><h3>Results</h3><p dir="ltr">A total of 247 women with class IV obesity were compared with 6797 normal/overweight women. …”
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Estimation of Above-Ground Carbon-Stocks for Urban Greeneries in Arid Areas: Case Study for Doha and FIFA World Cup Qatar 2022
Published 2021“…Linear and non-linear regression models are established between AGC and five vegetative spectral indices (VIs) derived from the Landsat 8 Operational Land Imager (OLI). …”
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Enhanced Deadbeat Control Approach for Grid-Tied Multilevel Flying Capacitors Inverter
Published 2022“…The proposed controller has the following advantages: 1) Improved current tracking quality even at zero crossing instants by using a weighted state-space model, 2) Superior steady-state performance (lower current THD) compared to other prediction-based control techniques such as Finite-Control-Set Model Predictive Control, 3) The generated duty cycles are normalized to the common base when the desired state is out of reach within the sampling time, 4) Voltage Ride-Through (VRT) capability, and 5) Robustness to parameters variation. …”
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Partial least squares path modelling (PLSPM)
Published 2013“…This article highlights the main differences between CBSEM and PLSPM and describes the advantages of PLSPM with regard to (1) testing theories and analyzing structural relationships among latent constructs; (2) dealing with sample size limitations and non-normal data; (3) analyzing complex models that have 'formative' and 'reflective' latent constructs; and (4) analyzing models with higher-order molar and molecular constructs. …”
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Modeling the influence of daily temperature and precipitation extreme indices on vegetation dynamics in Katsina State using statistical downscaling model (SDM)
Published 2023“…This study aims to derive a simulation model of vegetation conditions concerning daily temperature and extreme precipitation indices in Katsina State, Nigeria. …”
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Scalable Behavioral Models and Predistorters for Broad Band Power Amplifiers
Published 2023Get full text
doctoralThesis -
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Modeling the influence of daily temperature and precipitation extreme indices on vegetation dynamics in Katsina State using statistical downscaling model (SDM)
Published 2023“…This study aims to derive a simulation model of vegetation conditions concerning daily temperature and extreme precipitation indices in Katsina State, Nigeria. …”