Equations of state are useful for description of fluid properties such as pressure-volumetemperature (PVT). However, the success estimation of such correlations depends mainly on the range of data which have originated. Therefore new models are highly required. In this work a new method is proposed based on Artificial Neural Network (ANN) for estimation of PVT properties of compounds. The data ...

Congestion has become part of everyday urban life, and resilience is very crucial to traffic vulnerability sustainable mobility. This research employed a neural network as an adaptive artificially-intelligent application study the complex domains transport system in Nigerian cities (Kano Lagos). The input criteria train check models for are demographic variables, geospatial data, parameters, in...

Finland’s Slot Machine Association (RAY) has recently undergone a major transformation from a steady operator of slot machines to an agile innovator of new games and concepts. As a key part of this transformation, agile methods used in product development teams have been scaled up to the organizational level using Scaled Agile Framework (SAFe). To help analyze the development in the organizatio...

Nanotechnology, shortened to nanotech, is the study of the controlling of matter on an atomic and molecular scale. Generally, nanotechnology deals with structures sized between 1 to 100 nanometer in at least one dimension and involves developing materials or devices within that size. The use of nanotechnology in the field of pharmaceutics and drug delivery has grown over the last few years, so ...

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 ...

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...