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Impact of Active learning model and prior knowledge on discovery time of elusive relevant papers: a simulation study
Software that employs screening prioritization through active learning (AL) has accelerated the screening process significantly by ranking an...
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The power of news data in forecasting tail risk: evidence from China
This study investigates whether the inclusion of news information can help predict tail risk in the Chinese market. To quantify information from...
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Improved robust price bounds for multi-asset derivatives under market-implied dependence information
We show how inter-asset dependence information derived from market prices of options can lead to improved model-free price bounds for multi-asset...
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Image classification for sub-surface crack identification in concrete dam based on borehole CCTV images using deep dense hybrid model
The research investigates the significance of identifying structure discontinuities, such as cracks, in concrete dams to ensure dam safety and...
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Automation of takeoff data for aviation services using self-supervised LSTM approaches with time-series prediction
Landing and takeoff are the most crucial phases of any flight; in particular, the takeoff configuration of an aircraft is a delicate balance between...
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Physical activity, gut microbiota and the nexuses of metabolic and psychological disorders in children and adolescents
The burden of health issues surrounding the children and adolescents (ChAds) population is of great concern. From metabolic disorders such as...
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Epidemiological modeling of Romanization and Christianization in Ancient Greece
The spread of culture has been often paralleled with epidemic contagion. We propose to use models of this type to analyze Romanization and...
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Community health promotion and medical provision and impact on neonates (CHAMPION2) and support to rural India’s public education system and impact on numeracy and literacy scores (STRIPES2): an update to the study protocol (v 11) for a cluster randomised trial in Madhya Pradesh, India
BackgroundThis update outlines amendments to the CHAMPION2/STRIPES2 cluster randomised trial protocol primarily made due to the COVID-19 pandemic and...
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Unlocking Online Insights: LSTM Exploration and Transfer Learning Prospects
Machine learning algorithms can improve the time series data analysis as compared to the traditional methods such as moving averages or...
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A spatio-temporal model for binary data and its application in analyzing the direction of COVID-19 spread
It is often of primary interest to analyze and forecast the levels of a continuous phenomenon as a categorical variable. In this paper, we propose a...
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Antiplatelet therapy to prevent ischemic events in giant cell arteritis: protocol for a systematic review and meta-analysis
BackgroundGiant cell arteritis (GCA) is the most common systemic vasculitis in adults. Presenting features include new-onset headaches,...
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Assessment and prediction of water quality indices by machine learning-genetic algorithm and response surface methodology
Conventional techniques for determining water adequacy are generally expensive because they take into account a variety of factors. Thus, the problem...
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Automation of systematic reviews of biomedical literature: a sco** review of studies indexed in PubMed
BackgroundThe demand for high-quality systematic literature reviews (SRs) for evidence-based medical decision-making is growing. SRs are costly and...
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Drinkers Voice Recognition Intelligent System: An Ensemble Stacking Machine Learning Approach
Alcohol's dehydrating effects can cause vocal cords to dry out, potentially causing temporary voice changes and increasing the risk of vocal strain...
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Ensemble Machine Learning and Predicted Properties Promote Antimicrobial Peptide Identification
AbstractThe emergence of antibiotic-resistant microbes raises a pressing demand for novel alternative treatments. One promising alternative is the...
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Business-Cycle Analysis and Zero-Crossings of Time Series: A Generalized Forecast Approach
We propose an extension of classic time series approaches to business-cycle measurement called Simple Sign Accuracy (SSA), which addresses...
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Functional Principal Component Analysis for Multiple Variables on Different Riemannian Manifolds
Functional principal component analysis (FPCA) is a very important dimension reduction tool for functional data analysis. The conventional FPCA...
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A Comparison of Estimation Methods for Shared Gamma Frailty Models
This paper compares six different estimation methods for shared frailty models via a series of simulation studies. A shared frailty model is a...
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Functional Causal Inference with Time-to-Event Data
Functional data analysis has proven to be a powerful tool for capturing and analyzing complex patterns and relationships in a variety of fields,...
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Downscaling crop production data to fine scale estimates with geostatistics and remote sensing: a case study in map** cotton fibre quality
PurposeA generalised approach to downscale areal observations of crop production data is illustrated using cotton yield and fibre quality (length and...
