Sharif Digital Repository

SAPO-34 zeolite-like particles were successfully synthesized at high temperature environment. An L9 orthogonal array of the Taguchi method was implemented to investigate the effects of experimental conditions to prepare SAPO-34 with respect to crystallinity of the final product phase. The results showed that the favorable phase crystallinity was improved by increasing the hydrothermal synthesis temperature and organic template content, whereas increasing the water content in synthesis mixture decreased the crystallinity. No significant changes in crystallinity of the final products were observed by increasing the synthesis duration. In addition, zeolite SAPO-5, which was formed as the... 

Decreasing particle size results in larger increase of external surface area and shorter diffusion path, both reducing mass and heat transfer resistances in catalysis and sorption. A rapid high-temperature hydrothermal synthesis method was developed to synthesize uniform nanoparticles of SAPO-34 zeolite with high crystallinity. To investigate the effects of temperature and synthesis time on purity and crystallinity of the final products, the crystallization temperature was increased from 468 to 673 K while the synthesis time was decreased from 24 h to 45 min. The products were characterized by XRD and SEM techniques. It was found that high temperature and short synthesis time reduce the... 

Connected and Autonomous Vehicles (CAVs) are introduced to improve individuals' quality of life by offering a wide range of services. They collect a huge amount of data and exchange them with each other and the infrastructure. The collected data usually includes sensitive information about the users and the surrounding environment. Therefore, data security and privacy are among the main challenges in this industry. Blockchain, an emerging distributed ledger, has been considered by the research community as a potential solution for enhancing data security, integrity, and transparency in Intelligent Transportation Systems (ITS). However, despite the emphasis of governments on the transparency... 

In this paper, we design a dimming compatible visible light communication (VLC) system in a standard office room according to illumination standards under channel constraints. We use overlapping pulse position modulation (OPPM) to support dimming control by changing the code weights. The system parameters such as a valid interval for dimming together with an upper bound for bit rate according to the channel delay spread are investigated. Moreover, considering the dispersive VLC channel and using Monte Carlo (MC) simulations, a method is proposed to determine the minimum code length in different dimming levels in order to achieve a valid bit error rate (BER). Finally, trellis coded modulation... 

In this paper, we design a dimming compatible visible light communication (VLC) system with asynchronous and optimum indoor positioning method in a standard office room in combination with asynchronous and optimum indoor positioning method according to illumination standards under channel constraints. We use overlapping pulse position modulation (OPPM) to support dimming control by changing the code weights. The system parameters such as a valid interval for dimming together with an upper bound for bit rate according to the channel delay spread are investigated. Moreover, considering the dispersive VLC channel and using Monte Carlo (MC) simulations, a method is proposed to determine the... 

We theoretically study a Kitaev chain with a quasiperiodic potential, where the quasiperiodicity is introduced by a Fibonacci sequence. Based on an analysis of the Majorana zero-energy mode, we find the critical p-wave superconducting pairing potential separating a topological phase and a non-topological phase. The topological phase diagram with respect to Fibonacci potentials follow a self-similar fractal structure characterized by the box-counting dimension, which is an example of the interplay of fractal and topology like the Hofstadter's butterfly in quantum Hall insulators. © 2017 The Physical Society of Japan  

Transferring large models in federated learning (FL) networks is often hindered by clients' limited bandwidth. We propose $ extsf {FedAA}$ , an FL algorithm which achieves fast convergence by exploiting the regularized Anderson acceleration (AA) on the global level. First, we demonstrate that FL can benefit from acceleration methods in numerical analysis. Second, $ extsf {FedAA}$ improves the convergence rate for quadratic losses and improves the empirical performance for smooth and strongly convex objectives, compared to FedAvg, an FL algorithm using gradient descent (GD) local updates. Experimental results demonstrate that employing AA can significantly improve the performance of FedAvg,... 

Natural convection in a porous enclosure in the presence of thermal dispersion is investigated. The Fourier–Galerkin (FG) spectral element method is adapted to solve the coupled equations of Darcy’s flow and heat transfer with a full velocity-dependent dispersion tensor, employing the stream function formulation. A sound implementation of the FG method is developed to obtain accurate solutions within affordable computational costs. In the spectral space, the stream function is expressed analytically in terms of temperature, and the spectral system is solved using temperature as the primary unknown. The FG method is compared to finite element solutions obtained using an in-house code... 

Control charts are useful tools of monitoring quality characteristics. One of the problems of employing a control chart is that the time it alarms is not synchronic with the time when assignable cause manifests itself in the process. This makes difficult to search and find assignable causes. Knowing the real time of manifestation of assignable cause (change point) helps to find assignable cause(s) sooner and eases corrective actions to be taken. In this paper, a probabilistic neural network (PNN)-based procedure was developed to estimate the variance change point of a normally distributed quality characteristic. The PNN was selected based on trial and error among different types of... 

Object-oriented frameworks are widely used to develop new applications. They provide reusable concepts that are instantiated in application code through potentially complex implementation steps such as subclassing, implementing interfaces, and calling framework operations. Unfortunately, many modern frameworks are difficult to use because of their large and complex APIs and frequently incomplete user documentation. To cope with these problems, developers often use existing framework applications as a guide. However, locating concept implementations in those sample applications is typically challenging due to code tangling and scattering. To address this challenge, we introduce the notion of... 

This paper studies the energy-limited performance of multi-relay networks. Taking the properties of the power amplifiers (PAs) into account, we derive closed-form expressions for the optimal power allocation, the outage probability and the throughput in the cases with a sum consumed energy constraint. Moreover, we analyze the diversity and the multiplexing gains of the PA-aware systems. Finally, we investigate the performance of large-scale multi-relay networks and develop efficient multi-relay systems with low cooperation overhead. The numerical and the analytical results show that the inefficiency of the PAs affects the outage probability and the throughput of the multi-relay systems... 

Rapid assessment of structural safety and performance right after the occurrence of significant earthquake shaking is crucial for building owners and decision-makers to make informed risk management decisions. Hence, it is vital to develop online and pseudo-online health monitoring methods to quantify the health of the building right after significant earthquake shaking. Many Bayesian inference–based methods have been developed in the past which allow the users to estimate the unknown states and parameters. However, one of the most challenging part of the Bayesian inference–based methods is the determination of the parameter noise covariance matrix. It is especially difficult when the number... 

Online selection of the appropriate model and identifying its parameters based on measured vibrational data are among the challenging issues in dynamic system identification. After a severe earthquake, quick monitoring and assessment of structural health status play a crucial role in effective critical risk management for the building owners and decision-makers. The Bayesian multiple modeling approach is a suitable tool for optimal model class selection, which is used in this article mainly for improving data fitting precision, decreasing dimensions of structural unknown vector through removing unnecessary parameters, detecting the occurrence and type of predominant phenomenon related to... 

Online selection of the appropriate model and identifying its parameters based on measured vibrational data are among the challenging issues in dynamic system identification. After a severe earthquake, quick monitoring and assessment of structural health status play a crucial role in effective critical risk management for the building owners and decision-makers. The Bayesian multiple modeling approach is a suitable tool for optimal model class selection, which is used in this article mainly for improving data fitting precision, decreasing dimensions of structural unknown vector through removing unnecessary parameters, detecting the occurrence and type of predominant phenomenon related to... 

Rapid assessment of structural safety and performance right after the occurrence of significant earthquake shaking is crucial for building owners and decision-makers to make informed risk management decisions. Hence, it is vital to develop online and pseudo-online health monitoring methods to quantify the health of the building right after significant earthquake shaking. Many Bayesian inference–based methods have been developed in the past which allow the users to estimate the unknown states and parameters. However, one of the most challenging part of the Bayesian inference–based methods is the determination of the parameter noise covariance matrix. It is especially difficult when the number... 

We address the noninvasive temperature estimation from pulse-echo radio frequency signals from standard diagnostic ultrasound imaging equipment. In particular, we investigate the use of a high-resolution spectral estimation method for tracking frequency shifts at two or more harmonic frequencies associated with temperature change. The new approach, employing generalized second-order statistics, is shown to produce superior frequency shift estimates when compared to conventional high-resolution spectral estimation methods Seip and Ebbini (1995). Furthermore, temperature estimates from the new algorithm are compared with results from the more commonly used echo shift method described in Simon...