Sharif Digital Repository

A specific structure of doped graphene with substituted silicon impurity is introduced and ab initio density-functional approach is applied for the energy band structure calculation of the proposed structure. Using the band structure calculation for different silicon sites in the host graphene, the effect of silicon concentration and unit cell geometry on the bandgap of the proposed structure is also investigated. Chemically, silicon-doped graphene results in an energy gap as large as 2eV according to density-functional theory calculations. As the authors will show, in contrast to previous bandgap engineering methods, such structure has significant advantages including wide gap tuning... 

TiO 2 -rGO nanocomposite coatings were obtained by electrophoretic deposition (EPD) technique of TiO 2 nanoparticles and graphene oxide (GO) on stainless steel substrate. First, GO particles were synthesized using a modified Hummers' method. GO was reduced electrochemically to form a coating in the presence of nano-sized TiO 2 particles. The influences of different parameters such as GO concentration, coupling co-electro-deposition parameters (electrophoretic duration and voltage) on thickness, surface morphology and, corrosion behavior of the as-synthesized TiO 2 -rGO nanocomposite coatings were systematically surveyed. The morphology and microstructure were investigated by field emission... 

Nonspecific low back pain (NSLBP) constitutes a critical health challenge that impacts millions of people worldwide with devastating health and socioeconomic consequences. In today’s clinical settings, practitioners continue to follow conventional guidelines to categorize NSLBP patients based on subjective approaches, such as the STarT Back Screening Tool (SBST). This study aimed to develop a sensor-based machine learning model to classify NSLBP patients into different subgroups according to quantitative kinematic data, i.e., trunk motion and balance-related measures, in conjunction with STarT output. Specifically, inertial measurement units (IMU) were attached to the trunks of ninety-four... 

This article introduces a methodology to integrate fuzzy multiattribute decision making (FMADM) and fuzzy simulation. According to this method, a fuzzy simulation method is applied to study the effect of different alternative on system's performance and decision criteria taking into account fuzzy inputs. Using a fuzzy analytical hierarchy process (FAHP) and the results of fuzzy simulation, a FMADM is conducted to select the best alternative. This article introduces how to incorporate fuzzy set theory with discrete-event simulation in order to model uncertain activity duration in simulating a realworld system, especially when insufficient or no sample data are available. A case study is... 

This paper introduces how to incorporate fuzzy set theory with discrete-event simulation in order to model uncertain activity duration in simulating a real-world system, especially when insufficient or no sample data are available. A case study is developed to apply this method to select a scenario to implement the maintenance program in a constant work in process (CONWIP) system. The maintenance activities directly or indirectly affect on production system performance such as response time production costs and etc. so we used the fuzzy simulation to determine the maintenance affects on the system performance. Finally we used the fuzzy simulation result to develop a fuzzy multi attribute... 

A flexible meta modelling approach is presented to predictive control of a drying process using Adaptive Neuro-Fuzzy Inference System (ANFIS), Artificial Neural Network (ANN) and Partial Least Squares (PLS) analysis. In the proposed approach, the PLS analysis is used to pre-process actual data and to provide the necessary background to apply ANN and ANFIS approaches. A reasonable section of this study is assigned to the modelling with aim at predicting the granule particle size and executing by ANFIS and ANN. ANN hold the promise of being capable of producing non-linear models, being able to work under noise conditions and being fault tolerant to the loss of neurons or connections. Also, the... 

Anti-reflection and self-cleaning coatings on the glass substrate are used to improve the performance of solar systems. TiO2 are one of the most used semiconductors for this application. In this research meso-porous TiO2 coatings (that synthesized by the sol-gel process) with the various extent of porosity (using different concentrations of Pluronic F127, as pore-forming agent) have been investigated. The coating's thickness and porosity and anti-reflective properties were studied by FE-SEM and UV/VIS spectrometer (transmission spectra test), respectively. It was found that the use of F127 leads to the formation of pores smaller than 30 nm and increases the surface roughness from 1.5 (for... 

This paper presents the scheduling optimisation of cargo trains by hybrid computer simulation (CS) and genetic algorithm. Scheduling cargo trains is based on the timetable of passenger trains that have priority in relation to cargo trains. System modelling is accomplished by Visual SLAM by considering time limitations, queue priority and limited station lines. Time limitations define that a cargo train is permitted to travel from station i to j if scheduled passenger trains have completed the travel from station i to j. Queue priority means that passenger trains have priority over cargo trains. In addition, each station has a limited storage track. In addition, all repair, maintenance,... 

This paper presents a hybrid adaptive network based fuzzy inference system (ANFIS), computer simulation and time series algorithm to estimate and predict electricity consumption estimation. The difficulty with electricity consumption estimation modeling approach such as time series is the reason for proposing the hybrid approach of this study. The algorithm is ideal for uncertain, ambiguous and complex estimation and forecasting. Computer simulation is developed to generate random variables for monthly electricity consumption. Various structures of ANFIS are examined and the preferred model is selected for estimation by the proposed algorithm. Finally, the preferred ANFIS and time series... 

In this paper, a single-inductor dual-output (SIDO) DC/DC converter is proposed. The significant feature of the proposed converter is feeding a constant power load in low voltage side (LVS) port, where even feeding a variable load at LVS doesn't have any cross regulation to high voltage side port with the desired approximation. Magnificently, both merits are obtained in open-loop manner which is an outstanding characteristic in comparison with existed converters. In this paper, soft commutation and soft switching of switches and diodes are investigated along with the aforementioned main novelty. Moreover, detailed theoretical analyses of the proposed SIDO DC/DC converter in continuous... 

Design of an Ultra-Wideband 3-dB quadrature (90°) Hybrid using ADS and HFSS softwares plus Measurement report are presented. Simultaneous Use of these two softwares lead to fast and accurate design procedure. The coupler is realized in broadside stripline and with the connection of coupled regions in tandem structure. The measured data agrees well with the expected values from simulations, and shows a good ultra wide bandwidth response over the frequency range of 1-10 GHz. Measurements showed an amplitude unbalance of ±1.5 dB, a phase unbalance of 90°±7° , and an isolation and a return loss characteristics of more than 14 dB over the frequency of 1 to 10 GHz  

The Ni-base superalloy GTD-111 is employed in high-power stationary gas turbines because of its high temperature strength and oxidation resistance. The temperature dependence of the tensile behavior of GTD-111 has been studied by tensile tests in the temperature range of 25-900°C with a constant strain rate of 10-4s-1. The results showed an abnormal tensile property variation with increasing temperature. The yield strength decreased slightly with temperature up to about 650°C and then increased between 650 and 750°C. Above 750°C, a rapid decrease in the yield strength was found. The tensile strength showed a similar behavior except for its maximum that occurred at 650°C. The elongation... 

The challenge of finding an optimized and reliable path dates back to emersion of mobile robots. Several approaches have been developed that have partially answered this need. Satisfying results in previous implementations has led to an increased utilization of sampling-based motion planning algorithms in recent years, especially in high degrees of freedom (DOF), fast evolving environments. Another advantage of these algorithms is their probabilistic completeness that guarantees delivery of a path in sufficient time, if one exists. On the other hand, sampling based motion planners leave no comment on safety of the planned path. This paper suggests biasing the Rapidly-exploring Random Trees... 

This paper applies a novel adaptive approach consisting of Artificial Neural Network (ANN) and Fuzzy Linear Regression (FLR) to improve car ownership forecasting in complex, ambiguous, and uncertain environments. This integrated approach is applied to forecast car ownership in Iran from 1930 to 2007. In this study, the level of car ownership is viewed as the result of demographic, politico-social, and urban structure factors including average family size, total population density, urban population density, urbanization rate, gross national product per capita, gasoline price, and total road length. To capture the potential complexity, uncertainty, and linearity relation between the car... 

In this paper, we address global non-fragile control and synchronization of a new fractional order chaotic system. First we inspect the chaotic behavior of the fractional order system under study and also find the lowest order (2.49) for the introduced dynamics to remain chaotic. Then, a necessary and sufficient condition which can be easily extended to other fractional-order systems is proposed in terms of Linear Matrix Inequality (LMI) to check whether the candidate state feedback controller with parameter uncertainty can guarantee zero convergence of error or not. In addition, the proposed method provides a global zero attraction of error that guarantees stability around all existing... 

While the differentiation factors have been widely used to differentiate mesenchymal stem cells (MSCs) into various cell types, they can cause harm at the same time. Therefore, it is beneficial to propose methods to differentiate MSCs without factors. Herein, magnetoelectric (ME) nanofibers were synthesized as the scaffold for the growth of MSCs and their differentiation into neural cells without factors. This nanocomposite takes the advantage of the synergies of the magnetostrictive filler, CoFe 2 O 4 nanoparticles (CFO), and piezoelectric polymer, polyvinylidene difluoride (PVDF). Graphene oxide nanosheets were decorated with CFO nanoparticles for a proper dispersion in the polymer through... 

Grid computing is a type of parallel and distributed system that provides the possibility of sharing, choosing and collecting the autonomous resources (such as computer, software, databases, and equipments) that are distributed geographically. Resource discovery is one of the key subjects in distributed systems and especially Grids. We should consider that Grid consists of different applications that each of them consist of different hardware and software resources, therefore recognizing these resources is important in a Grid system. Classical approaches to Grid resource discovery are either centralized or hierarchical [1] (and will maybe prove inefficient as the scale of Grid systems...