this paper surveys parallel scheduling problems and metrics correlated to and then applys metrics to make decision in comparison to other policy schedulers. parallel processing is new trend in computer science especially in embedded and multicore systems whereas needs more power consumption to reach speed up. the qos requirement for users is to have good responsiveness and for service providers...

SUMMARY In biological assays, clinical trials, life-testing problems, reliability and survival analysis, and a variety of applied fields ranging from agrometry to biodivrersity to zodiacal sciences, generalized linear models covering usual linear, transformed linear, log-linear and nonlinear regression models, multi-nomial and logistic regression models, as well as some semiparametric ones, are...

objectives: the purpose of this study was to investigate the relation of personality traits with depression in active and non – active elderly women in tehran city. methods & materials: the present research is descriptive–correlation. for this purpose, 188 elderly women (94 active and 94 non - active elders) in the age range of 63-82 in tehran city availably selected as statistical sample. meas...

Non-linear regression is a fundamental and yet under-developing methodology in solving many problems in Artificial Intelligence. The canonical control and predictions mostly utilize linear models or multi-linear models. However, due to the high non-linearity of the systems, those linear prediction models cannot fully cover the complexity of the problems. In this paper, we propose a robust two-s...

Statistical models have been used to estimate the refractive index of 72 imidazolium-based ionic liquids using the electronic polarisability of their ions as the data for two different mathematical approaches: artificial neural networks, in the form of multi-layer perceptrons, and multiple linear regression models. Although the artificial neural networks and linear models have been able to acco...

The mode of a distribution provides an important summary of data and is often estimated based on some non-parametric kernel density estimator. This article develops a new data analysis tool called modal linear regression in order to explore highdimensional data. Modal linear regression models the conditional mode of a response Y given a set of predictors x as a linear function of x. Modal linea...