Sharif Digital Repository

Estimation of physical parameters in dynamical systems driven by linear partial differential equations is an important problem. In this paper, we introduce the least costly experiment design framework for these systems. It enables parameter estimation with an accuracy that is specified by the experimenter prior to the identification experiment, while at the same time minimising the cost of the experiment. We show how to adapt the classical framework for these systems and take into account scaling and stability issues. We also introduce a progressive subdivision algorithm that further generalises the experiment design framework in the sense that it returns the lowest cost by finding the... 

This paper considers Pressure Oscillation (PO) experiments for which we find the minimum experiment time that guarantees user-imposed parameter variance upper bounds and honours actuator limits. The parameters permeability and porosity are estimated with a classical least-squares estimation method for which an expression of the covariance matrix of the estimates is calculated. This expression is used to tackle the optimization problem. We study the Dynamic Darcy Cell experiment set-up (Heller et al., 2002) and focus on data generation using square wave actuator signals, which, as we shall prove, deliver shorter experiment times than sinusoidal ones. Parameter identification is achieved using... 

Classic identifiability analysis of flow barriers in incompressible single-phase flow reveals that it is not possible to identify the location and permeability of low-permeability barriers from production data (wellbore pressures and rates), and that only averaged reservoir properties in between wells can be identified. We extend the classic analysis by including compressibility effects. We use two approaches: a twin experiment with synthetic production data for use with a time-domain parameter-estimation technique, and a transfer-function formalism in the form of bilaterally coupled four-ports allowing for an analysis in the frequency domain. We investigate the identifiability, from noisy... 

This study presents a novel perspective on pressure-transient analysis (PTA) of downhole-pressure and flow-rate data by use of system-identification (SI) techniques as widely used in advanced process engineering. Key features of the paper are that it considers the classic PTA process from a system-theoretical perspective; derives the causal structure of the flow dynamics; proposes a method to deal with continuously varying pressure and flow-rate signals contaminated with correlated noise, which estimates physical reservoir parameters through a systematic matching procedure in the frequency domain; and can cope with arbitrary (i.e., not necessarily piecewise constant) flow-rate signals. To... 

Diffuse reflectance near-infrared (NIR) data (908–1676 nm) of chicken breast fillets was recorded in a non-destructive way using a portable miniaturised NIR spectrometer. The NIR data was used to discriminate between fresh and thawed breast fillets and to determine the birds’ growth conditions. NIR data was recorded of 153 commercial supermarket chicken fillet samples by applying the NIR device equipped with the standard issue collar on the samples in three different ways: (i) directly on the meat (ii) through the top foil of the package (i.e. with an air pocket between the foil and the breast fillet), and (iii) through the top foil with the packaging turned bottom up (i.e. no air pocket... 

Decision-making is challenging for agents operating in partially observable environments. In such environments, agents’ observation is often based on incomplete, ambiguous, and noisy sensed data, which may lead to perceptual aliasing. This means there might be distinctive states of the environment that appear the same to the agents, and agents fail to take suitable actions. Currently, machine learning, collaboration, and practical reasoning techniques are used to improve agents’ observation and their performance in such environments. However, their long exploration and negotiation periods make them incapable of reacting in real time and making decisions on the fly. The Ontology-based... 

By combining portable, handheld near-infrared (NIR) spectroscopy with state-of-the-art classification algorithms, we developed a powerful method to test chicken meat authenticity. The research presented shows that it is both possible to discriminate fresh from thawed meat, based on NIR spectra, as well as to correctly classify chicken fillets according to the growth conditions of the chickens with good accuracy. In all cases, the random subspace discriminant ensemble (RSDE) method significantly outperformed other common classification methods such as partial least squares-discriminant analysis (PLS-DA), artificial neural network (ANN) and support vector machine (SVM) with classification... 

Identifying clusters is an important aspect of analyzing large datasets. Clustering algorithms classically require access to the complete dataset. However, as huge amounts of data are increasingly originating from multiple, dispersed sources in distributed systems, alternative solutions are required. Furthermore, data and network dynamicity in a distributed setting demand adaptable clustering solutions that offer accurate clustering models at a reasonable pace. In this paper, we propose GoScan, a fully decentralized density-based clustering algorithm which is capable of clustering dynamic and distributed datasets without requiring central control or message flooding. We identify two major... 

Cloud manufacturing is an emerging service-oriented manufacturing paradigm that integrates and manages distributed manufacturing resources through which complex manufacturing demands with a high degree of customization can be fulfilled. The process of service selection optimization and scheduling (SSOS) is an important issue for practical implementation of cloud manufacturing. In this paper, we propose new mixed-integer programming (MIP) models for solving the SSOS problem with basic composition structures (i.e., sequential, parallel, loop, and selective). Through incorporation of the proposed MIP models, the SSOS with a mixed composition structure can be tackled. As transportation is... 

Background and purpose: To protect against any potential adverse effects to human health from localised exposure to radio frequency (100 kHz–3 GHz) electromagnetic fields (RF EMF), international health organisations have defined basic restrictions on specific absorption rate (SAR) in tissues. These exposure restrictions incorporate safety factors which are generally conservative so that exposures that exceed the basic restrictions are not necessarily harmful. The magnitude of safety margin for various exposure scenarios is unknown. This shortcoming becomes more critical for medical applications where the safety guidelines are required to be relaxed. The purpose of this study was to quantify... 

Human error including driving misbehavior contributes to over 90 percent of road vehicle accidents, and speeding is considered to be risky. Smart technologies, such as Connected Vehicle System (CVS) are among the interesting technical options to improve driving behavior, and Pay-As-You-Speed (PAYS) is an effective economic incentive to reduce speed violations. We investigated the acceptability of CVS with and without the presence of economic incentives, such as PAYS, in the context of a middle-income country: Iran. We used a Zero-Inflated Ordered Probit model (ZIOP) to estimate drivers’ willingness to pay for a CVS, and a hazard-based model for predicting the incentive level needed for... 

Cloud manufacturing is an emerging service-oriented manufacturing paradigm that integrates and manages distributed manufacturing resources through which complex manufacturing demands with a high degree of customization can be fulfilled. The process of service selection optimization and scheduling (SSOS) is an important issue for practical implementation of cloud manufacturing. In this paper, we propose new mixed-integer programming (MIP) models for solving the SSOS problem with basic composition structures (i.e., sequential, parallel, loop, and selective). Through incorporation of the proposed MIP models, the SSOS with a mixed composition structure can be tackled. As transportation is... 

IC 1613 is a Local Group dwarf irregular galaxy at a distance of 750 kpc. In this work, we present an analysis of the star formation history (SFH) of a field of ~200 arcmin 2 in the central part of the galaxy. To this aim, we use a novel method based on the resolved population of more highly evolved stars. We identify 53 such stars, eight of which are supergiants and the remainder are long-period variables, large-amplitude variables, or extreme asymptotic giant branch (x-AGB) stars. Using stellar evolution models, we find the age and birth mass of these stars and thus reconstruct the SFH. The average rate of star formation during the last Gyr is ~3 × 10 -4 M ⊙ yr -1 kpc -2. The absence of a... 

The Sun is located inside an enormous local cavity filled with a million degree, ionized hydrogen gas and surrounded by a wall of dense and cold gas, this cavity is known as the Local Bubble (LB). Since the tempreture of Local Bubble is high, the typical singly-ionized atoms or molecules can not survive at this high tempreture. To overcome this problem we should probe the Local Bubble using species which survive under this condition so we have done a whole sky survey in north hemisphere by observing absorptions in the Diffuse Interstellar Bands (DIBs) for sight-lines with distance >300 pc. We have done 30 nights observation and have observed 473 bright stars. We found that the correlations... 

Hough transform based object detectors divide an object into a number of patches and combine them using a shape model. For efficient combination of patches into the shape model, the individual patches are assumed to be independent of one another. Although this independence assumption is key for fast inference, it requires the individual patches to have a high discriminative power in predicting the class and location of objects. In this paper, we argue that the sparsity of the appearance of a patch in its neighborhood can be a very powerful measure to increase the discriminative power of a local patch and incorporate it as a sparsity potential for object detection. Further, we show that this... 

Atomic emission detection (AED) is a sensitive as well as a selective detection technique for gas chromatography (GC) and provides element-specific information. A rapidly increasing number of applications in many different areas illustrates the versatility and analytical power of the technique - especially when complex samples have to be analysed. The complementary use of GC-AED and GC with mass-spectrometric detection often yields the most rewarding results. © 2002 Published by Elsevier Science B.V. All rights reserved  

This article proposes a control strategy to stabilize the axial-torsional dynamics of a distributed drill-string system. An infinite-dimensional model for the vibrational dynamics of the drill string is used as a basis for controller design. In this article, both the cutting process and frictional contact effects are considered in the bit-rock interaction model. Moreover, models for the top-side boundary conditions regarding axial and torsional actuation are considered. The resulting model is formulated in terms of neutral-type delay differential equations that involve constant state delays, state-dependent state delays, and constant input delays arising from the distributed nature of the... 

Recent progress in the development of bismuth vanadate (BiVO4) photoanodes has firmly established it as a promising material for solar water splitting applications. Performance limitations due to intrinsically poor catalytic activity and slow electron transport have been successfully addressed through the application of water oxidation co-catalysts and novel doping strategies. The next bottleneck to tackle is the modest optical absorption in BiVO4, particularly close to its absorption edge of 2.4 eV. Here, we explore the modification of the BiVO4 surface with Ag@SiO2 core-shell plasmonic nanoparticles. A photocurrent enhancement by a factor of ∼2.5 is found under 1 sun illumination (AM1.5)....