Multi-scale materials modeling combines existing and emerging methods from diverse scientific disciplines to bridge the wide range of time and length scales that are inherent in a number of essential phenomena and processes in materials science and engineering. In this contribution we demonstrate how novel developments have changed the field in recent years from a descriptive to a predictive ap...

 Biodiesel production from non edible oil through transesterification in batch reactor is highly effective technique for kinetic analysis. Temperature, molar ratio, mixing intensity and catalyst influenced the biodiesel production and kinetic. Alkaline catalysts are more efficient in nature as compare to acid and base catalyst. This paper particularly focuses on the impact of NaOH catalyst o...

With the results of version 2.1 a consistent set of performance measurements of the NAS Parallel Benchmarks (NPB) are available. Unchanged portable MPI code was used for this set of 269 single measurements. In this study we investigate how this amount of information can be condensed. We present a methodology for analyzing performance data not requiring detailed knowledge of the codes. For this ...

One of the major issues in signed networks is to use network structure to predict the missing sign of an edge. In this paper, we introduce a novel probabilistic approach for the sign prediction problem. The main characteristic of the proposed models is their ability to adapt to the sparsity level of an input network. The sparsity of networks is one of the major reasons for the poor performance ...

In this paper we construct a modeling for detection of banks which are experiencing serious problems. Sample and variable set of the study contains 30 banks of Iran during 2006-2014 and their financial ratios. Well known multivariate statistical technique (principal component analysis) was used to explore the basic financial characteristics of the banks, and discriminant Logit and Probit models ...

This paper discusses the improvement of the statistical model that was developed in [6] by adding a new weather variable called sunshine. We also took into account other weather factors such as ambient temperature, humidity, wind speed, and sky cover as well as time factors such as the day of the week and the hour of the day. We developed a statistical model that describes the electric power de...

When solving machine learning problems, there is currently little automated support for easily experimenting with alternative statistical models or solution strategies. This is because this activity often requires expertise from several different fields (e.g., statistics, optimization, linear algebra), and the level of formalism required for automation is much higher than for a human solving pr...

This lab is about two topics in modeling. Interaction refers to a particular way of structuring models; it is a concept that applies to a wide variety of models. Logistic Regression is a form of nonlinear modeling that is particularly useful when the response variable is binomial, e.g., yes or no, alive or dead, success or failure. The two concepts are brought together in this lab only because ...