Sharif Digital Repository

In this work, a new approach is described for the calculation of the relaxation time and magnetic anisotropy energy of magnetic nanoparticles. Ferrofluids containing monodispersed magnetite nanoparticles were synthesized via hydrothermal method and then heated using the 10 kA/m external AC magnetic fields in three different frequencies: 10, 50 and 100 kHz. By measuring the temperature variations during the application of the magnetic field, the total magnetic time constant including both Brownian and Neel relaxation times can be calculated. By measuring the magnetic core size and hydrodynamic size of particles, the magnetic anisotropy can be calculated too. Synthesized ferrofluids were... 

In this study, some stabilized magnetite based ferrofluids were synthesized using Dextran as a stabilizing agent. In order to achieve optimum experimental conditions for synthesizing ferrofluids as MRI contrast agents, the Taguchi method was used. This approach was employed to design and minimize the number of required experiments. By using the Taguchi orthogonal (L16) array, four parameters including solution temperature and alkalinity, reaction temperature and stirring rate were selected at four predetermined levels for 16 experiments. Synthesizing processes established based on this set of experimental conditions were carried out and the obtained ferrofluids were characterized using PCS,... 

In this work, magnetite nanoparticles (mean particle size about 20 nm) were synthesized via coprecipitation method. In order to investigate the kinetics of nanoparticle formation, variation in the amount of reactants within the process was measured using pH-meter and atomic absorption spectroscopy (AAS) instruments. Results show that nanoparticle formation behavior can be described by Avrami equations. Transmission electron microscopy (TEM) and X-ray diffraction (XRD) were performed to study the chemical and morphological characterization of nanoparticles. Some simplifying assumptions were employed for estimating the nucleation and growth rate of magnetite nanoparticles  

We revisit the mathematical formulation of the famous Jaynes-Cummings-Paul Hamiltonian, which describes the interaction of a two-level atom with a single mode of an electromagnetic cavity reservoir. We rigorously show that under the condition of ultrastrong coupling between the atom and cavity in which the transition frequency is comparable to the coupling frequency, the bosonic field operators undergo non-sinusoidal time variations. As a result, the well-known solutions to the Jaynes-Cummings-Paul model are no longer valid, even when the rotating wave approximation is not used. We show how a correct mathematical solution could be found instead  

BACKGROUND AND OBJECTIVES: Road traffic noise is a matter of challenge for both people and policymakers. For instance, the price of lands/houses which are close to road traffic noise is reduced. The key objective of this study is to propose a conceptual model to illustrate details of a road traffic noise model along with its policy and societal relevance. The second objective is to consider the honking of horns in such a conceptual model, as honking is a remarkable traffic noise factor, however, it has been neglected in some noise abatement policies. METHODS: By the use of previously proposed traffic noise models, some attempts were made to figure out how the models were applicable in... 

Introduction: Physical air pollutants comprising noise, temperature, and humidity are among health risk factors that influence human well-being. No study has been carried out on how the three physical pollutants affect the psychological health. Therefore, the objectives of this research are to assess road traffic noise, temperature, and relative humidity in association with psychological health. Final objective is to propose a formula capable of computing psychological health index using the three above-mentioned risk factors. Methods: At the chosen sample points throughout Baharan Town situated in the city of Sanandaj in Iran, data of four independent variables encompassing age of the... 

Various parameters affect thermal conductivity of nanofluid; however, some of them are more influential such as temperature, size and type of nano particles and volumetric concentration. In this study, artificial neural network as well as least square support vector machine (LSSVM) are applied in order to predict thermal conductivity ratio of alumina/water nanofluid as a function of particle size, temperature and volumetric concentration. LSSVM, Self-Organizing Map and Levenberg-Marquardt Back Propagation algorithms are applied to predict thermal conductivity ratio. Obtained results indicated that these algorithms are appropriate tool for thermal conductivity ratio prediction. The... 

Large-scale simulation of spiking neural networks on hardware with a remarkable resemblance to their mathematical models is a key objective of the neuromorphic discipline. This issue is, however, considerably resource-intensive due to the presence of nonlinear terms in neuron models. This paper proposes a novel uniform piecewise linear segmentation approach for nonlinear function evaluations. Employing the proposed approach, we present a uniform-segmented adaptive exponential neuron model capable of accurately producing various responses exhibited by the original model and suitable for efficient large-scale implementation. In contrast to previous nonuniform-segmented neuron models, the... 

In the present study, a one step hydrothermal process was employed to synthesize magnetite nanoparticles using oleic acid as surfactant agent at 140 °C. Effects of reaction time and alkalinity were studied on particles size and morphology. By changing these parameters, some monodisperse spherical nanoparticles with mean particle size between 2.71 and 13.88 nm were synthesized and characterized via TEM, XRD, VSM, TGA and FT-IR techniques. Assuming the Avrami behavior of particles formation, a kinetics equation was proposed for the transformation rate at 140 °C. Using some simplifying assumptions, nucleation and growth rates were calculated for the hydrothermal formation of magnetite... 

The objective of this paper is to apply computational fluid dynamic (CFD) as a complementary tool for clinical tests to not only predict the present and future status of left coronary artery stenosis but also to evaluate some clinical hypotheses. In order to assess the present status of the coronary artery stenosis severity, and thereby selecting the most appropriate type of treatment for each patient, fractional flow reserve (FFR), instantaneous wave free-ratio (iFR), and coronary flow reserve (CFR) are calculated. To examine FFR, iFR, and CFR results, the effect of geometric features of stenoses, including diameter reduction (%), lesion length (LL), and minimum lumen diameter (MLD), is... 

Superparamganetic iron oxide-based contrast agents in magnetic resonance imaging (MRI) have offered new possibility for early detection of lymph nodes and their metastases. According to important role of nanoparticle size in biodistribution, magnetite nanoparticles coated with different polyethylene glycol (PEG) concentrations up to 10/1 PEG/iron oxide weight ratio in an ex situ manner. To predict the PEG-coated nanoparticle behavior in biological media, such as blood stream or tissue, colloidal stability evaluation was performed to estimate the coating endurance in different conditions. Accordingly, optical absorbance measurements were conducted in solutions with different values of pH and... 

Active learning method (ALM) is a powerful fuzzy-based soft computing methodology suitable for various applications such as function modeling, control systems, clustering and classification. Despite considerable advantages, the main computational engine of ALM, ink drop spread (IDS), is memory-intensive, which imposes significant area overheads in the hardware realization of the ALM for real-time applications. In this paper, we propose a compressed model for ALM which greatly alleviates the storage limitations. The proposed approach employs a distinct inference algorithm, enabling a significant reduction in memory utilization from O(N2) to O(2N) for a multi-input single-output (MISO) system.... 

A theory is presented for the quantum radiation emitted from a single exciton in a quantum dot. We assume that the quantum dot is in strong coupling to a slab photonic crystal cavity. A dielectric function of spatial coordinates is used to explain the effects of the macroscopic medium. It has been proved that the electric field in such a medium can be described using the so-called K-function. We derive a formula for obtaining the frequency spectrum, and present an analytical result for the optical spectrum, which is dependent on the K-function. We also have considered a slab photonic crystal configuration with hexagonal structure containing a cavity to evaluate the frequency spectrum in such... 

Pulsating heat pipes are cooling devices that are partially filled with working fluid. Working fluid thermophysical properties affect the thermal performance of pulsating heat pipes. In this research, the effect of adding a Triton X-100 surfactant to pure water and using the mixture as a working fluid is investigated experimentally. The results indicate that adding surfactant leads to improvement in the thermal performance of the pulsating heat pipe. In particular, the maximum of the thermal resistance improvement is about 61%, which is attributed to 0.01% surfactant concentration. Higher heat transfer ability is attributed to lower surface tension and the contact angle of the mixture... 

The main purpose of this research is to predict the flow field of impinging turbulent jet with cylinder in a 3-d state. Nowadays, shear stress has multiple uses in the industry. The study has been conducted in both compressible and incompressible states with output velocities between 100 and 150 m/s, in different eccentricities of jet with respect to the first cylinder, and in various nozzle outlet orifice distances from front edge of the first cylinder. Pressure distribution and shear stress on cylinder surfaces have been determined and efficiency of jet in cleaning the heat exchangers pipes has been analyzed. Also, an experimental investigation has been conducted in order to verify the... 

Performance of polymer electrolyte membrane fuel cells (PEMFC) at high current densities is limited to transport reactants and products. Furthermore, large amounts of water are generated and may be condensed due to the low temperature of the PEMFC. Development of a two-phase flow model is necessary in order to predict water flooding and its effects on the PEMFC performance. In this paper, a multiphase mixture model (M2) is used, accurately, to model two-phase transport in porous media of a PEMFC. The cathode side, which includes channel, gas diffusion layer (GDL), microporous layer (MPL), and catalyst layer (CL), is considered as the computational domain. A multidomain approach has been used... 

We consider a production system with a single product and two classes of customers. Customers are segmented into two classes: 1) loyal and 2) occasional. Each class has a different shortage cost for the system. The demand of the customer classes is assumed to be stochastic and price sensitive, and distributed as a Poisson process. The objective is to determine the inventory rationing as well as pricing policies in order to maximise the profit function of the system. We formulate the problem as a Markov decision problem and characterise the optimal policies for pricing and inventory rationing. The joint pricing and rationing threshold policy is shown to be optimal. The performance of the... 

Increasing access to very large and non-stationary datasets in many real problems has made the classical data mining algorithms impractical and made it necessary to design new online classification algorithms. Online learning of data streams has some important features, such as sequential access to the data, limitation on time and space complexity and the occurrence of concept drift. The infinite nature of data streams makes it hard to label all observed instances. It seems that using the semi-supervised approaches have much more compatibility with the problem. So in this paper we present a new semi-supervised ensemble learning algorithm for data streams. This algorithm uses the majority... 

Increase of nonlinear loads has led to the rise of harmonic currents, voltage distortion and imbalance in power systems. IEEE Std. 1459 proposes new definitions for electric power in sinusoidal, nonsinusoidal, balanced and unbalanced conditions which can be used for compensation of nonsinusoidal and unbalanced systems. Among different definitions, IEEE Std. 1459 proposes the new concept of effective apparent power and power factor which is more related to the real losses in a power system. In this paper, by expansion of definitions of IEEE Std. 1459, instantaneous forms of effective parameters are defined. Then, a new control strategy for a Shunt Active Power Filters (SAPFs) is defined based... 

This paper considers dynamic pricing in a production system with a single product which is demanded by several customer classes. We seek the structure of the optimal policy assuming m available prices and n demand classes that differ based on the lost sales cost they impose on the system. The assumption of different available prices leads to dynamic pricing structure and the assumption of several demand classes leads to rationing which is proposed in the literature of revenue management. We found that an optimal policy structure exists for this combined problem. The optimal policy has a threshold form which lower thresholds are related to the rationing decision and upper thresholds are...