Multiscale entropy (MSE) analysis [1, 2] is a new method of measuring the complexity of finite length time series. This computational tool can be applied both to physical and physiologic data sets, and can be used with a variety of measures of entropy. We have developed and applied MSE for the analysis of physiologic time series, for which we prefer to estimate entropy using the sample entropy ...

This article has been compiled to identify the best model of housing price forecasting using machine learning methods with maximum accuracy and minimum error. Five important machine learning algorithms are used to predict housing prices, including Nearest Neighbor Regression Algorithm (KNNR), Support Vector Regression Algorithm (SVR), Random Forest Regression Algorithm (RFR), Extreme Gradient B...

The purpose of this research is to analyze data and perform machine learning modeling predict the energy efficiency rating air conditioning (AC) units using a labeled AC dataset from Directorate General New, Renewable Energy Conservation (EBTKE). consists Power, Cooling Capacity, Efficiency, Annual Consumption, Electricity Cost. visualized box plots linear regression examine relationship betwee...

Introduction Multivariate Fay–Herriot models for estimating small area indicators are introduced. Among the available procedures for fitting linear mixed models, the residual maximum likelihood (REML) is employed. The empirical best predictor (EBLUP) of the vector of area means is derived. An approximation to the matrix of mean squared crossed prediction errors (MSE) is given and four MSE estim...

We present the first bioluminescence tomography algorithm that makes use of the PDEconstrained concept, which has shown to lead to significant savings in computation times in similar applications. Implementing a sequential quadratic programming (SQP) method, we solve the forward and inverse problems simultaneously. Using numerical results we show that the PDEconstrained SQP approach leads to ~1...

or more than 50 years, the mean-squared error (MSE) has been the dominant quantitative performance metric in the field of signal processing. It remains the standard criterion for the assessment of signal quality and fidelity; it is the method of choice for comparing competing signal processing methods and systems, and, perhaps most importantly, it is the nearly ubiquitous preference of design e...

The Ndt80 protein of the yeast Saccharomyces cerevisiae is the founding member of a new sub-family of proteins in the Ig-fold superfamily of transcription factors. The crystal structure of Ndt80 bound to DNA shows that it makes contacts through several loops on one side of the protein that connect beta-strands which form the beta-sandwich fold common to proteins in this superfamily. However, th...

PURPOSE To investigate the efficacy of distributed compressed sensing (CS) to accelerate free-breathing, electrocardiogram (ECG)-triggered noncontrast pulmonary vein (PV) magnetic resonance angiography (MRA). MATERIALS AND METHODS Fully sampled ECG-triggered noncontrast PV MRA, using a spatially selective slab inversion preparation sequence, was acquired on seven healthy adult subjects (27 ± ...