Sharif Digital Repository

Time of concentration (TC) of surface flow in watersheds depends on the coupled response of hillslopes and stream networks. The important point in this background is to study the effects of the geometry and the shape of complex hillslopes on the time of concentration considering the degree of flow convergence (convergent, parallel or divergent) as well as the profile curvature (concave, straight or convex). In this research, the shape factor of complex hillslopes as introduced by Agnese et al. (2007) is generalized and linked to the TC. A new model for calculating TC of complex hillslopes is presented, which depends on the plan shape, the type and degree of profile curvature, the Manning... 

The travel time of subsurface flow in complex hillslopes (hillslopes with different plan shape and profile curvature) is an important parameter in predicting the subsurface flow in catchments. This time depends on the hillslopes geometry (plan shape and profile curvature), soil properties and climate conditions. The saturation capacity of hillslopes affect the travel time of subsurface flow. The saturation capacity, and subsurface travel time of compound hillslopes depend on parameters such as soil depth, porosity, soil hydraulic conductivity, plan shape (convergent, parallel or divergent), hillslope length, profile curvature (concave, straight or convex) and recharge rate to the groundwater... 

In the present study, we aimed to quantify the effects of COVID-19 restrictions and speech treatment approaches during lockdowns on autistic children using CBCL and neuro-fuzzy artificial intelligence method. In this regard, a survey including CBCL questionnaire is prepared using online forms. In total, 87 children with diagnosed Autism spectrum disorders (ASD) participated in the survey. The influences of three treatment approaches of in-person, telehealth and public services along with no-treatment condition during lockdown were the main factors of the investigation. The main output factors were internalized and externalized problems in general and their eight subcategory syndromes. We... 

In this work, the mesoporous magnetic heterogeneous catalyst was synthesized by anchoring copper (II) onto the nitrogen-rich poly (melamine) Schiff base networks magnetic nanocomposite. First, MNP (Fe3O4@SiO2) was functionalized with chlorosilane (CPTS). Then, the chlorine of these functionalized magnetic nanoparticles could react with the –NH2 groups of the melamine through a nucleophilic substitution reaction. Simultaneously, the condensation polymerization of melamine and benzene-1, 3, 5-tricarbaldehyde was carried out in the presence of surface-modified magnetic nanoparticles. Later, Fourier-transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), thermogravimetric analysis... 

In recent years there has been potential increase in the use of alkaline protease as industrial catalysts. Many major industrial and commercial applications, such as food and textile industries, and medical diagnoses, are highly dependent on the protease enzyme. In the cell immobilization technique, the free movement of microorganisms is restricted in the process, and a continuous system of fermentation can be used. In the present work, this technique has been used for alkaline protease production using different carriers, such as chitosan, corn cob and corn tassel. Enzyme activity before immobilization (72 h) was 78.3 U/ml. Corn cob, with 65% immobilization capacity and the highest enzyme... 

The simultaneous control of the molecular weight, separation, and purification of polyvinyl acetate was achieved using a cobalt-mediated radical polymerization (CMRP) in a packed column with silica gel particles (PC-CMRP). The controlled radical polymerization of VAc in the packed columns was evaluated from the linear time dependence of Ln[M]0/[M], linear increase of molecular weight with the increase in conversion, and narrow molecular weight distribution. PC-CMRP method was used to produce high-purity polymers with controlled molecular weight and narrow molecular weight distribution without requiring additional purification steps. The high ability of silica gel particles to adsorb free... 

The microstructure evaluation and phase transformation of multi-pass friction stir-processed (FSP) commercially pure titanium were investigated using optical microscopy, scanning electron microscopy equipped with a backscatter detector, and electron backscatter diffractometer. The microstructure characterization shows that the grain refinement mechanism changed with the increasing number of passes. The equiaxed α grains in the untreated sample changed to lath-shaped grains surrounded by serrated grain boundaries, and produced Widmanstätten morphology during the cooling cycle of FSP. The higher micro-hardness values and bio-corrosion resistances of the FSP-treated samples are due to their... 

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...