Sharif Digital Repository

Autoregressive models are among the most successful neural network methods for estimating a distribution from a set of samples. However, these models, such as other neural methods, need large data sets to provide good estimations. We believe that knowing structural information about the data can improve their performance on small data sets. Masked autoencoder for distribution estimation (MADE) is a well-structured density estimator, which alters a simple autoencoder by setting a set of masks on its connections to satisfy the autoregressive condition. Nevertheless, this model does not benefit from extra information that we might know about the structure of the data. This information can... 

Autoregressive models are among the most successful neural network methods for estimating a distribution from a set of samples. However, these models, such as other neural methods, need large data sets to provide good estimations. We believe that knowing structural information about the data can improve their performance on small data sets. Masked autoencoder for distribution estimation (MADE) is a well-structured density estimator, which alters a simple autoencoder by setting a set of masks on its connections to satisfy the autoregressive condition. Nevertheless, this model does not benefit from extra information that we might know about the structure of the data. This information can... 

We consider the problem of learning a density function from observations of an unknown underlying model in a distributed setting, where the observations are partitioned into different sites. Applying commonly used density estimation methods such as Gaussian Mixture Model (GMM) or Kernel Density Estimation (KDE) to distributed data leads to an extensive amount of communication. A familiar approach to address this issue is to sample a small subset of data and collect them into a central node to run the density estimation algorithms on them. In this paper, we follow an alternative to the sub-sampling approach by proposing the nested Log-Poly model. This model provides an accurate density... 

This paper presents a robust tracking approach to handle challenges such as occlusion and appearance change. Here, the target is partitioned into a number of patches. Then, the appearance of each patch is modeled using a dictionary composed of corresponding target patches in previous frames. In each frame, the target is found among a set of candidates generated by a particle filter, via a likelihood measure that is shown to be proportional to the sum of patch-reconstruction errors of each candidate. Since the target's appearance often changes slowly in a video sequence, it is assumed that the target in the current frame and the best candidates of a small number of previous frames, belong to... 

We study the optimal pricing strategy for profit maximization in presence of network externalities where a decision to buy a product depends on the price offered to the buyer and also on the set of her friends who have already bought that product. We model the network influences by a weighted graph where the utility of each buyer is the sum of her initial value on the product, and the linearly additive influence from her friends. We assume that the buyers arrive online and the seller should offer a price to each buyer when she enters the market. We also take into account the manufacturing cost. In this paper, we first assume that the monopolist defines a unique price for the product and... 

The heat transfer Magnetohydrodynamics flows have been potentially used to enhance the thermal characteristics of several systems such as heat exchangers, electromagnetic casting, adjusting blood flow, X-rays, magnetic drug treatment, cooling of nuclear reactors, and magnetic devices for cell separation. Our concern in this article is to numerically investigate the flow of an incompressible Magnetohydrodynamics micropolar fluid with heat transportation through a channel having porous walls. By employing the suitable dimensionless coordinates, the flow model equations are converted into a nonlinear system of dimensionless ordinary differential equations, which are then numerically treated for... 

The purpose of the paper is to develop a mathematical foundation for exploring the complex interaction of Coriolis and Lorentz forces with the electromagnetohydrodynamic (EMHD) flow of a power-law fluid inside a microchannel with wall slip condition. Both the Lorentz and Coriolis forces act orthogonally to each other. Mathematical modeling of the problem is based on a set of classical Maxwell and Navier–Stokes equations, which are subsequently solved numerically by employing an implicit finite difference methodology. The numerical solution thus obtained has been found to be in an excellent agreement correlation with the ones reported in the scientific literature, for some limiting cases. A... 

Nano-fluids have considerable importance in the field of thermal development that relates to several industrial systems. There are some key applications in recent construction systems flow, as well as microscale cooling gadgets and microstructure electric gadgets for thermal migration. The current investigation concludes the study of electrically conducting nano-fluid flow and heat transfer analysis in two-dimensional boundary layer flow over a curved extending surface in the coexisting of magnetic field, heat generation and thermal radiation. The small sized particles of copper (Cu) are taken as nanoparticles and water is assumed to be the base fluid. We used quasi-linearization and central... 

Vortices grab the attention of many scientists while analyzing any flow model due to their importance in interpreting fluid mixing and mass transport phenomena. Since vortices exist in the natural environment, so researchers need to investigate them whenever they are encountered. Solar collectors, automobile cooling, engine applications, thermal management, and machine cutting, are just a few of the major areas in which most hybrid nanofluids could help to improve overall performance. The goal of this study is to demonstrate the highly complex dynamics of a Lorentz force, which governs the rotation of nanoparticles and the composition of the complex configuration of eddies inside the fluid... 

This work addresses the preparation of self-flowing lightweight aggregate foamed concrete (LAFC) resulting from the mixing of stable foam, expanded clay aggregate (ECA) and silica fume (SF) as main raw materials. Formulated LAFC mixtures were tested for the mechanical, thermal, sorption and high-temperature resistance properties. Results showed that the increase in the volume of foam from 0% to 20% considerably improved the flowability of LAFC and LAFC mixtures were categorized into high stable visual stability index. Compressive strength of LAFC mixtures was reduced from 24.75 MPa to 21.10, 15.95 and 12.05 MPa respectively when foam volume was increased from 0% to 10, 15 and 20%. Thermal...