In this study, shear and peel stress distributions in the viscoelastic adhesive layer of a single-lap joint (SLJ) with functionally graded (FG) adherends are investigated. The study focuses on the effect of different adherend profiles and material composition on the time-dependent stress concentration/distribution in balanced and unbalanced SLJs. For this purpose, the Reddy model is applied to ...

We present a model for dihadron fragmentation functions, describing the fragmentation of a quark into two unpolarized hadrons. We tune the parameters of our model to the output of the PYTHIA event generator for two-hadron semi-inclusive production in deep inelastic scattering at HERMES. Once the parameters of the model are fixed, we make predictions for other unknown fragmentation functions and...

A recent trend in plasma etching of semi-conductors has been the move towards discharge operation at low pressures of 2-20 mTorr. At these conditions the electron distribution functions shows modest but signi cant deviations from a fully nonlocal distribution. We have developed a model which addresses this regime of modest deviations from the nonlocal case with an efcient numerical scheme to so...

The form postponement (FP) strategy is an important strategy for manufacturing firms to utilize to achieve a quick response to customer needs while keeping low inventory levels of finished products. It is an important and difficult task to design a supply chain that uses FP strategy to mitigate the conflict between inventory level and service level. To this end, we develop a two-stage tandem qu...

Although many studies have been conducted to improve the clustering efficiency, most of the state-of-art schemes suffer from the lack of robustness and stability. This paper is aimed at proposing an efficient approach to elicit prior knowledge in terms of must-link and cannot-link from the estimated distribution of raw data in order to convert a blind clustering problem into a semi-supervised o...

In this paper I propose to estimate densities with possibly restricted support semi-nonparametrically via semi-nonparametric (SNP) estimation of densities on the unit interval. The latter will be done similarly to the approach of Gallant and Nychka (1987), but instead of using Hermite polynomials I propose to use orthonormal Legendre polynomials on the unit interval. This approach will be appli...

In this paper we present a graph-based semisupervised method for solving regression problem. In our method, we first build an adjacent graph on all labeled and unlabeled data, and then incorporate the graph prior with the standard Gaussian process prior to infer the training model and prediction distribution for semi-supervised Gaussian process regression. Additionally, to further boost the lea...

Improving phoneme recognition has attracted the attention of many researchers due to its applications in various fields of speech processing. Recent research achievements show that using deep neural network (DNN) in speech recognition systems significantly improves the performance of these systems. There are two phases in DNN-based phoneme recognition systems including training and testing. Mos...

Consider the semi-parametric linear regression model Y = ′X+ , where has an unknown distribution F0. The semi-parametric MLE
̃ of under this set-up is called the generalized semi-parametric MLE(GSMLE).Although the GSML estimation of the linear regression model is statistically appealing, it has never been attempted due to difficulties with obtaining the GSML estimates of and F until recent work...