Sharif Digital Repository

Recent evaluations of mapping systems show that lack of background knowledge, most often domain specific knowledge, is one of the key problems of mapping systems these days. In fact, at present, most state of the art systems, for the tasks of mapping large ontologies, perform not with such high values of recall (~ 30%), because they mainly rely on label and structure based similarity measures. Disregarding context knowledge in ontology mapping is another drawback that almost all current approaches suffer from. In this paper we use the semantic web as background knowledge and introduce a novel approach for capturing context knowledge from the ontology for improving mapping results. We have... 

The remediation of nonaqueous phase liquids (NAPLs) enhanced by surfactant and nanoparticles (NP) has been investigated in numerous studies. However, the role of NP-assisted surfactants in the dissolution process is still not well discussed. Besides, there is a lack of empirical dissolution models considering the effects of initial residual saturation Strap, NAPL distribution, and surfactant concentration in NAPL-aqueous phase systems. In this work, micromodel experiments are conducted to quantify mass transfer coefficients for different injected aqueous phases including deionized water, SDS surfactant solutions, and NP-assisted solutions with different levels of concentrations and flow... 

Taxonomy learning is a prerequisite step for ontology learning. In order to create a taxonomy, first of all, existing 'is-a' relations between words should be extracted. A known way to extract 'is-a' relations is finding lexicosyntactic patterns in large text corpus. Although this approach produces results with high precision but it suffers from low values of recall. Furthermore developing a comprehensive set of patterns is tedious and cumbersome. In this paper, firstly, we introduce an approach for developing lexico-syntactic patterns automatically using the snippets of search engine results and then, challenge the law recall of this approach using a combined model, which is based on... 

The creation of surfaces with various super nonwetting properties is an ongoing challenge. We report diverse modifications of novel synthesized zirconia-ceria nanocomposites by different low surface energy agents to fabricate nanofluids capable of regulating surface wettability of mineral substrates to achieve selective superhydrophobic, superoleophobic-superhydrophilic, and superamphiphobic conditions. Surfaces treated with these nanofluids offer self-cleaning properties and effortless rolling-off behavior with sliding angles ≤7° for several liquids with surface tensions between 26 and 72.1 mN/m. The superamphiphobic nanofluid coating imparts nonstick properties to a solid surface whereby... 

Vapour extraction (VAPEX), a newly developed heavy oil recoveiy (HOR) method, has been extensively studied, both theoretically and experimentally, in conventional sandstone models. However, the applicability of this process to naturally fractured reservoirs has not yet been addressed. The objective of this work is to evaluate the effects of fractures' geometrical properties, such as orientation, length of extension, discontinuity in both the upper well region (UWR) and the far well region (FWR) and vertical fracture location on VAPEX performance. Additionally, the effects of horizontal and vertical fracture dispersion in various density, dispersion scheme and networking on the performance of... 

Accurate determination of relative permeability (kr) curves and their hysteresis is needed for reliable prediction of the performance of oil and gas reservoirs. A few options (e.g., Carlson, Killough and Jargon models) are available in commercial reservoir simulators to account for hysteresis in kr curves under two-phase flow. Two-phase kr curves are also needed for estimating kr hysteresis under three-phase flow during water-alternating-gas (WAG) injection. Although, most oil reservoirs are mixed-wet, the existing hysteresis predictive approaches have been developed based on water-wet conditions. Experimentally measured data are needed to assess the performance of these methodologies under... 

Slow-gamma (35-45 Hz) phase synchronization and the coupling between slow-gamma and low-frequency theta oscillations (4–8 Hz) are closely related to memory retrieval and cognitive functions. In this pilot study, we assess the Phase Amplitude Coupling (PAC) between theta and slow-gamma oscillatory bands and the quality of synchronization in slow-gamma oscillations using Phase Locking Value (PLV) on EEG data from healthy individuals and patients diagnosed with amnestic Mild Cognitive Impairment (aMCI) and Alzheimer's Disease (AD) during an oddball olfactory task. Our study indicates noticeable differences between the PLV and PAC values corresponding to olfactory stimulation in the three groups... 

The critical micelle concentration (CMC) of a set of 58 alkylsulfates, alkylsulfonates, alkyltrimethyl ammonium and alkylpyridinium salts were predicted using an artificial neural network (ANN). The multiple linear regression (MLR) technique was used to select the important descriptors that act as inputs for artificial neural network. These descriptors are Balaban index, heat of formation, maximum distance between the atoms in the molecule, Randic index and volume of the molecule. Designed artificial neural network is a fully connected back-propagation network that has a 5-5-1 architecture. The results obtained using neural network were compared with those obtained using MLR technique.... 

In this paper, genetic algorithm (GA) and stepwise multiple regression variable selection methods were used as a feature-selection tools and neural network was employed for feature mapping. To provide an extended test of these hybrid methods, a data set consists of the bioconcentration factors (BCF) for 53 molecules were selected. Suitable set of molecular descriptors were calculated and the important descriptors were selected by genetic algorithm and stepwise multiple regression methods. These variables serve as inputs to generated neural networks. After optimization and training of the networks, they were used for the calculation of bioconcentration factors for the prediction set.... 

We present a sampling theory for a class of binary images with finite rate of innovation (FRI). Every image in our model is the restriction of 1{p le; 0} to the image plane, where 1 denotes the indicator function and p is some real bivariate polynomial. This particularly means that the boundaries in the image form a subset of an algebraic curve with the implicit polynomial p. We show that the image parameters - i.e., the polynomial coefficients'satisfy a set of linear annihilation equations with the coefficients being the image moments. The inherent sensitivity of the moments to noise makes the reconstruction process numerically unstable and narrows the choice of the sampling kernels to... 

This study aims to investigate the role of fluid-fluid interactions during low salinity water flooding, using crude oil from an Iranian oil reservoir. To minimize the effects of mineral heterogeneity and wettability alteration, a synthetic sintered glass core was utilized and all coreflooding experiments were performed at low temperatures without any aging process. The effect of fluid-fluid interactions were investigated in both secondary and tertiary injection modes. pH measurements as well as UV-Vis spectroscopy and interfacial tension (IFT) analysis were performed on the effluent brine samples. Results: show that fluid-fluid interactions, mainly the dissolution of crude oil polar... 

Dynamic behavior of fluid-fluid interactions can potentially affect the performance of any enhanced oil recovery (EOR) process including low salinity water flooding. In this work, dynamic interfacial tension (IFT) of crude-oil/brine system is measured in a wide range of salinity of sea water (SW), from 50-time diluted sea water (SW50D) to 2-time concentrated sea water (SW2C). Contrary to the most of published IFT trends in the literature, for the system under investigation here, as the brine salinity increases the crude-oil/brine IFT reduces, which cannot be explained using the existing theories. The lack of a physical model to explain the observed phenomena was the motivation to develop a... 

Because of the complex nature of carbonate reservoirs, the required conditions for effective Low Salinity Water Flooding (LSWF) in these reservoirs need further and in depth investigation. In the present study, three calcite cores, i.e. Cal-1, Cal-2, and IL, with the same chemical composition are subjected to tertiary low salinity water flooding (LSWF), while the crude oil and composition of flooding brine kept the same. The experimental results show significant difference in the amount of enhanced oil recovery, as IL had the most additional oil recovery (20.8 % of IOIP), followed by Cal-2 (10.5 % of IOIP) and Cal-1 (3.9 % of IOIP). The results of contact angle, zeta potential, and effluent... 

Accurate determination of relative permeability curves and their hysteresis is vital for reliable prediction of the performance of oil and gas reservoirs under enhanced recovery processes. Two out of the three available approaches to simulate three-phase relative permeability hysteresis are based on two-phase hysteresis. A few options (e.g., Carlson, Killough and Jargon models) are available in commercial reservoir simulators to account for hysteresis in relative permeability curves under two-phase flow. These models are based on the assumptions of water-wet state of the rocks, while most of the reservoir rocks are mixed-wet. As a result the aim of the present work is to evaluate the... 

Landmark extraction is used as the first step of many vision tasks such as tracking, image registration, localization, image matching and recognition. Furthermore, landmarks are used to reduce the data flow and consequently the computational costs. In this paper we extracted landmarks from echocardiography sequence, our algorithm is based on corner extraction, and then we evaluate our algorithm with applying some test. For this purpose, we evaluated the detectors according to their repeatability, stability and landmark localization under changes in noise. © 2009 IEEE  

Landmark extraction is used as the first step of many vision tasks such as tracking, image registration, localization, image matching and recognition. Furthermore, landmarks are used to reduce the data flow and consequently the computational costs. In this paper we extracted landmarks from echocardiography sequence, our algorithm is based on corner extraction, and then we evaluate our algorithm with applying some test. For this purpose, we evaluated the detectors according to their repeatability, stability and landmark localization under changes in noise. © 2009 IEEE  

A multi-stage secret sharing (MSS) scheme is a method of sharing a number of secrets among a set of participants, such that any authorized subset of participants could recover one secret in every stage. The first MSS scheme was proposed by He and Dawson in 1994, based on Shamir's well-known secret sharing scheme and one-way functions. Several other schemes based on different methods have been proposed since then. In this paper, the authors propose an MSS scheme using All-Or-Nothing Transform (AONT) approach. An AONT is an invertible map with the property that having "almost all" bits of its output, one could not obtain any information about the input. This characteristic is employed in the... 

Air pollution in urban centers has become a key public concern around the world. Apart from its adverse health effects, air pollution could impact less visible outcomes like cognitive performance. Standardized tests are a fixture of all education settings that are susceptible to pollution shocks because they require high cognitive function. Given that test scores are widely used as signals by parents, employers, and education institutions, pollution shocks could render tests unfair and unreliable. In this paper, we combine pollution data with test scores from a large testing institution in Iran between 2012 and 2017 to quantify the impact of short-term exposure to air pollution on test... 

If an ideal membrane for gas separation is to be obtained, the following three characteristics should be considered: the membrane should be as thin as possible, be mechanically robust, and have welldefined pore sizes. These features will maximize its solvent flux, preserve it from fracture, and guarantee its selectivity. Graphene is made up of a hexagonal honeycomb lattice of carbon atoms with sp2 hybridization state forming a one-atom-thick sheet of graphite. Following conversion of the honeycomb lattices into nanopores with a specific geometry and size, a nanoporous graphene membrane that offers high efficiency as a separation membrane because of the ultrafast molecular permeation rate as... 

This study is focused on the development of a systematic computational approach which implements Genetic Algorithm (GA) to find the optimal rigorous kinetic models. A general Kinetic model for hydrogenolysis of dibenzothiophene (DBT) based on Langmuir Hinshelwood type has been obtained from open literature. This model consists of eight continuous parameters(e.g., Arrhenus and Van't Hoff parameters) and six discrete parameters representing the order of the reaction with respect to each concentration. The optimal value of these parameters have been obtained based on Genetic Algorithm. Furthermore, the best type of Genetic operators and their corresponding parameters for this type of problems...