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decrease » increase (Expand Search)
predictions » prediction (Expand Search), predicting (Expand Search), predictors (Expand Search)
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101
Dynamic mechanical characterization and modelling of polypropylene based organoclay nanocomposite
Published 2015“…<p dir="ltr">In order to investigate the dynamic behaviour of polypropylene based organoclay nanocomposite, the polypropylene matrix and a master batch of polypropylene modified anhydrid maleic were mixed by means of melt mixing technique. …”
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102
Dietary Trichosporon mycotoxinivoron modulates ochratoxin-A induced altered performance, hepatic and renal antioxidant capacity and tissue injury in broiler chickens
Published 2021“…Dietary OTA at all the tested levels induced the hepatic and renal tissue injury as indicated by significant decreased total antioxidant capacity in these organs along with significant decreased (p ≤ 0.05) serum concentrations of total proteins and albumin. …”
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103
Calculation of Average Road Speed Based on Car-to-Car Messaging
Published 2019“…These predictions are mainly based on historical data. Systems that provide near real-time road condition updates, e.g. …”
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Competition vs cooperation: An agent based model for sustainable tomatoes’ import system
Published 2024“…Interactions between trade partners are modeled using two game theoretic approaches counting<u> Cournot</u><u> competition</u> and <u>Cartel</u> collusion. Based on the research findings, a competitive global market can bring economic benefits to Qatar as an importing nation, but this approach also entails substantial <u>water consumption</u> and results in significant environmental emissions. …”
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Kernel-Ridge-Regression-Based Randomized Network for Brain Age Classification and Estimation
Published 2024“…Moreover, the proposed algorithm demonstrated excellent prediction accuracy with a mean absolute error (MAE) of <b>3.89</b> years, <b>3.64 </b>years, and <b>4.49</b> years for GM, WM, and CSF regions, confirming that changes in WM volume are significantly associated with normal brain aging. …”
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Type 2 Diabetes Mellitus Automated Risk Detection Based on UAE National Health Survey Data: A Framework for the Construction and Optimization of Binary Classification Machine Learn...
Published 2020“…This research motivated by the unprecedented increase in diabetes and specifically Type 2 Diabetes Miletus (T2DM), proposes two significant contributions. The first is a comprehensive ML framework for the construction of diagnostic binary classification high accuracy models to predict T2DM in the United Arab Emirates based on STEPS style National Health Survey. …”
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Modeling of photovoltaic soiling loss as a function of environmental variables
Published 2017“…The ANN model performed significantly better in predicting daily ΔCIas well as cumulative CI than the linear model in term of R2 values and statistical error indexes. …”
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An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study
Published 2024“…The data were distributed for training (35%), testing (35%), and validation (30%) of the prediction model.</p><h3>Results</h3><p dir="ltr">In total, 70,623 records were collected in the data set from Ornge and land medical transport services to develop a prediction model. …”
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115
The utility of a deep learning-based approach in Her-2/neu assessment in breast cancer
Published 2023“…The framework consists of three phases: identification of tumor patches, scoring of tumor patches, and Her-2/neu score prediction for whole slide images (WSI) based on the distribution of each score. …”
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116
The utility of a deep learning-based approach in Her-2/neu assessment in breast cancer
Published 2024“…The framework consists of three phases: identification of tumor patches, scoring of tumor patches, and Her-2/neu score prediction for whole slide images (WSI) based on the distribution of each score. …”
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A machine learning-based optimization approach for pre-copy live virtual machine migration
Published 2023“…The experiment results show that our proposed model outperforms other machine learning models in terms of prediction accuracy and it significantly reduces downtime or service unavailability during the migration process.…”
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Deep transfer learning strategy in intelligent fault diagnosis of gas turbines based on the Koopman operator
Published 2024“…A <u>deep neural network</u>-based transfer learning framework is proposed for realizing a precise adaptive linear model called the deep transfer linear (DTL) model enabling reliable prediction of the system’s behavior in various situations and designing structured fault residuals. …”
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Mutations in L-type amino acid transporter-2 support SLC7A8 as a novel gene involved in age-related hearing loss
Published 2018“…Significant decreases in SLC7A8 transport activity was detected for patient’s variants (p.Val302Ile, p.Arg418His, p.Thr402Met and p.Val460Glu) further supporting a causative role for SLC7A8 in ARHL. …”