control of production processes in an industrial environment needs the correct setting of input factors, so that output products with desirable characteristics will be resulted at minimum cost. moreover, such systems havetomeetset of qualitycharacteristicstosatisfycustomer requirements.identifyingthemosteffectivefactorsindesignoftheprocesswhichsupportcontinuousandcontinualimprovement isrecently...

We are addressing two fundamental problems in authorship verification (AV): Topic variability and miscalibration. Variations the topic of disputed texts a major cause error for most AV systems. In addition, it is observed that underlying probability estimates produced by deep learning mechanisms oftentimes do not match actual case counts respective training data. As such, poorly calibrated. exp...

The aim of domain adaptation algorithms is to establish a learner, trained on labeled data from a source domain, that can classify samples from a target domain, in which few or no labeled data are available for training. Covariate shift, a primary assumption in several works on domain adaptation, assumes that the labeling functions of source and target domains are identical. We present a domain...

To determine the genetic etiology of complex diseases, a common study design is to recruit affected sib/relative pairs (ASP/ARP) and evaluate their genome-wide distribution of identical by descent (IBD)-sharing using a set of highly polymorphic markers. Other attributes or environmental exposures of the ASP/ARP, which are thought to affect liability to disease, are sometimes collected. Conceiva...

To determine the genetic etiology of complex diseases, a common study design is to recruit affected sib/relative pairs (ASP/ARP) and evaluate their genome-wide distribution of identical by descent (IBD) sharing using a set of highly polymorphic markers. Other attributes or environmental exposures of the ASP/ARP, which are thought to affect liability to disease, are sometimes collected. Conceiva...

We present a semiparametric statistical model for the probabilistic index which can be defined as P .Y Y Å/, where Y and Y Å are independent random response variables associated with covariate patterns X and XÅ respectively. A link function defines the relationship between the probabilistic index and a linear predictor. Asymptotic normality of the estimators and consistency of the covariance ma...

Synopsis: The average expenditure related to development of a drug candidate has doubled over the last decade. Each day that informed decisions about a drug candidate are delayed carries with it opportunity costs, tangible costs, and patient risk. Adaptive trial design is a clinical methodology that is receiving significant attention from pharmaceutical companies and regulatory agencies because...

We present a model for estimating a probabilistic map of ecological habitats using species presence/absence data and environmental covariate data observed at the sites where species presence data were collected. The model is notable because it treats spatially varying patterns of species distributions as the principle defining characteristic of habitats. The model also permits inference about t...

The Mann-Whitney U test is frequently used to evaluate treatment effects in randomized experiments with skewed outcome distributions or small sample sizes. It may lack power, however, because it ignores the auxiliary baseline covariate information that is routinely collected. Wald and score tests in so-called probabilistic index models generalize the Mann-Whitney U test to enable adjustment for...