Results for "Amirreza Khodadadian"

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An adaptive multilevel Monte Carlo algorithm for the stochastic drift-diffusion-Poisson systemApr 11 2019We present an adaptive multilevel Monte Carlo algorithm for solving the stochastic drift-diffusion-Poisson system with non-zero recombination rate. The a-posteriori error is estimated to enable goal-oriented adaptive mesh refinement for the spatial dimensions, ... More
Analysis of a Legendre spectral element method (LSEM) for the two-dimensional system of a nonlinear stochastic advection-reaction-diffusion modelsApr 12 2019In this work, we develop a Legendre spectral element method (LSEM) for solving the stochastic nonlinear system of advection-reaction-diffusion models. The used basis functions are based on a class of Legendre functions such that their mass and diffuse ... More
The optimal multilevel Monte-Carlo approximation of the stochastic drift-diffusion-Poisson systemOct 14 2016Existence and local-uniqueness theorems for weak solutions of a system consisting of the drift-diffusion-Poisson equations and the Poisson-Boltzmann equation, all with stochastic coefficients, are presented. For the numerical approximation of the expected ... More
Generalized moving least squares and moving kriging least squares approximations for solving the transport equation on the sphereApr 11 2019In this work, we apply two meshless methods for the numerical solution of the time-dependent transport equation defined on the sphere in spherical coordinates. The first technique, which was introduced by Mirzaei (BIT Numerical Mathematics, 54 (4) 1041-1063, ... More
Dynamic Transparent General Purpose Process Migration For LinuxJan 12 2013Process migration refers to the act of transferring a process in the middle of its execution from one machine to another in a network. In this paper, we proposed a process migration framework for Linux OS. It is a multilayer architecture to confine every ... More
Evaluation of Dedicated Lanes for Automated vehicles at Roundabouts with Various Flow PatternsApr 09 2019Autonomous vehicles (AVs) are about to be used in transportation systems in the near future. To increase the level of safety and throughput of these vehicles, dedicated lanes for AVs have been suggested in past studies as exclusive mobility infrastructure ... More
Local Similarities, Global Coding: An Algorithm for Feature Coding and its ApplicationsNov 24 2013Mar 05 2014Data coding as a building block of several image processing algorithms has been received great attention recently. Indeed, the importance of the locality assumption in coding approaches is studied in numerous works and several methods are proposed based ... More
A Predictive Model for Oil Market under Uncertainty: Data-Driven System Dynamics ApproachAug 13 2018In recent years, there have been a lot of sharp changes in the oil price. These rapid changes cause the traditional models to fail in predicting the price behavior. The main reason for the failure of the traditional models is that they consider the actual ... More
Positive Unknown Input Observer For Positive Linear SystemsJul 12 2015Aug 04 2015Positive systems are important class of dynamic systems with impressive properties. The response of such systems to positive initial conditions and positive inputs remain in the nonnegative orthant of the state space. Although positive observers have ... More
Effects of Demand Variation on Optimal Automated Demand Responsive Feeder Transit System Operation in Rural AreasApr 09 2019Improving accessibility is one of the major issues in rural and suburban transportation. With the recent technological improvement of automated vehicles, it is expected that automated demand responsive transit and automated demand responsive feeder transit ... More
Cascading Randomized Weighted Majority: A New Online Ensemble Learning AlgorithmMar 03 2014Feb 02 2015With the increasing volume of data in the world, the best approach for learning from this data is to exploit an online learning algorithm. Online ensemble methods are online algorithms which take advantage of an ensemble of classifiers to predict labels ... More
Testing fine-grained parallelism for the ADMM on a factor-graphMar 08 2016There is an ongoing effort to develop tools that apply distributed computational resources to tackle large problems or reduce the time to solve them. In this context, the Alternating Direction Method of Multipliers (ADMM) arises as a method that can exploit ... More
Deep Forward and Inverse Perceptual Models for Tracking and PredictionOct 31 2017May 20 2018We consider the problems of learning forward models that map state to high-dimensional images and inverse models that map high-dimensional images to state in robotics. Specifically, we present a perceptual model for generating video frames from state ... More
One-Shot Learning for Semantic SegmentationSep 11 2017Low-shot learning methods for image classification support learning from sparse data. We extend these techniques to support dense semantic image segmentation. Specifically, we train a network that, given a small set of annotated images, produces parameters ... More
Truncated Back-propagation for Bilevel OptimizationOct 25 2018Apr 05 2019Bilevel optimization has been recently revisited for designing and analyzing algorithms in hyperparameter tuning and meta learning tasks. However, due to its nested structure, evaluating exact gradients for high-dimensional problems is computationally ... More
Truncated Back-propagation for Bilevel OptimizationOct 25 2018Bilevel optimization has been recently revisited for designing and analyzing algorithms in hyperparameter tuning and meta learning tasks. However, due to its nested structure, evaluating exact gradients for high-dimensional problems is computationally ... More
An Evaluation of Coarse-Grained Locking for Multicore MicrokernelsSep 27 2016Sep 28 2016The trade-off between coarse- and fine-grained locking is a well understood issue in operating systems. Coarse-grained locking provides lower overhead under low contention, fine-grained locking provides higher scalability under contention, though at the ... More
Statistical model of the human RF exposure in Small cells environmentNov 06 2018Small cells are one of the solutions to face the imperative demand on increasing mobile data traffic. They are low-powered base stations installed close to the users to offer better network services and to deal with increased data traffic. In this paper, ... More
Bulk dipole contribution to second harmonic generation in diamond latticesMar 14 2012Jun 26 2012It is generally argued that material classes with inversion symmetry do not produce bulk dipole related second harmonic generation (SHG). So, SHG is then either ascribed to surface effects or bulk related electric quadrupole or magnetic dipole effects. ... More
Learning Clinical Outcomes from Heterogeneous Genomic Data SourcesApr 02 2019Translating the vast data generated by genomic platforms into reliable predictions of clinical outcomes remains a critical challenge in realizing the promise of genomic medicine largely due to small number of independent samples. In this paper, we show ... More
All One Needs to Know about Fog Computing and Related Edge Computing Paradigms: A Complete SurveyAug 15 2018Feb 13 2019With the Internet of Things (IoT) becoming part of our daily life and our environment, we expect rapid growth in the number of connected devices. IoT is expected to connect billions of devices and humans to bring promising advantages for us. With this ... More
Passivation-sensitive exciton finestructure produces excess Stokes shifts in colloidal quantum dotsAug 17 2016The excitonic finestructure of colloidal quantum dots (CQDs) is comprised of a manifold of transitions, of which only the lowest are populated and contribute to photoluminescence. This leads to a Stokes shift in emission relative to absorption. Here we ... More
Monolithic shape-programmable dielectric liquid crystal elastomer actuatorsApr 21 2019Macroscale robotic systems have demonstrated great capabilities of high speed, precise, and agile functions. However, the ability of soft robots to perform complex tasks, especially in centimeter and millimeter scale, remains limited due to the unavailability ... More