Sharif Digital Repository

In this paper, we consider the problem of scheduling the power of a sensor when transmitting over an unknown Gilbert-Elliott (GE) channel for remote state estimation. The sensor supports two power modes, namely low power and high power, which are to be selected for transmission over the channel in order to minimize a cost on the error covariance, while satisfying the energy constraints. The remote estimator provides error-free acknowledgement/negative-acknowledgement (ACK/NACK) messages to the sensor only when low power is utilized. We first consider the Partially Observable Markov Decision Process (POMDP) problem for the case of known GE channels and derive conditions for optimality of a... 

Battery Electric Vehicles (BEVs) are a promising solution for reducing the impacts of passenger vehicles on the environment. However, their driving range is restricted due to the limitations of battery technologies. This range can be extended by adoption of multiple-speed transmissions. Most of the comparisons in the related studies are based on non-optimal designs or limited to modal driving cycles. Furthermore, the impact of Power-Split. Continuously Variable Transmission (PS-CVT) layout with type III power How on the power consumption of BEVs has never been examined. In this paper, single-, two-, and three-speed transmissions along with PS-C'VTs with type I and III power flows are... 

Battery Electric Vehicles (BEVs) are a promising solution for reducing the impacts of passenger vehicles on the environment. However, their driving range is restricted due to the limitations of battery technologies. This range can be extended by adoption of multiple-speed transmissions. Most of the comparisons in the related studies are based on non-optimal designs or limited to modal driving cycles. Furthermore, the impact of Power-Split. Continuously Variable Transmission (PS-CVT) layout with type III power How on the power consumption of BEVs has never been examined. In this paper, single-, two-, and three-speed transmissions along with PS-C'VTs with type I and III power flows are... 

We show with angle-resolved photoemission spectroscopy that a new energy band appears in the electronic structure of electron-doped hydrogenated monolayer graphene (H-graphene). Its occupation can be controlled with the hydrogen amount and allows for tuning of graphene's doping level. Our calculations of the electronic structure of H-graphene suggest that this state is largely composed of hydrogen 1s orbitals and remains extended for low H coverages despite the random chemisorption of H. Further evidence for the existence of a hydrogen state is provided by x-ray absorption studies of undoped H-graphene which are clearly showing the emergence of an additional state in the vicinity of the π*... 

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... 

Tailoring the electronic properties of graphene is of fundamental interest regarding its application in electronic devices. One of the key strategies is chemical functionalization which modifies the p-electron system and thus can induce band gaps. However, in order to control the degree of functionalization it is crucial to know the exact amount of the chemisorbed species. We show with angle-resolved photoemission spectroscopy (ARPES) the formation of a band gap in graphene and estimate the hydrogen coverage from the scattering rate. Using X-ray photoemission spectroscopy (XPS) we identify the chemical environments in hydrogenated graphene and determine the total hydrogen to carbon... 

Designers and manufacturers of cryptographic devices are always worried about the vulnerability of their implementations in the presence of power analysis attacks. This article can be categorized into two parts. In the first part, two parameters are proposed to improve the accuracy of the latest hypothetical power consumption model, so-called toggle-count model, which is used in power analysis attacks. Comparison between our proposed model and the toggle-count model demonstrates a great advance, i.e., 16%, in the similarity of hypothetical power values to the corresponding values obtained by an analog simulation. It is supposed that the attacker would be able to build such an accurate power... 

Partial discharge (PD) measurement and identification have great importance to condition monitoring of power transformers. In this paper a new method for recognition of single and multi-source of PD based on extraction of high level image features have been introduced. A database, involving 365 samples of phase-resolved PD (PRPD) data, is developed by measurement carried out on transformer artificial defect models (having different sizes of defect) under a specific applied voltage, to be used for proposed algorithm validation. In the first step, each set of PRPD data is converted into grayscale images to represent different PD defects. Two “image feature extraction” methods, the Local Binary... 

Transformers are the key component in power system transmission and distribution networks. Condition-based maintenance will increase their expected life, and online monitoring is essential to ensure operation reliability. In this paper, a new approach to transformer online monitoring is provided based on partial discharge (PD) measurement. Simultaneous measurements of PD using IEC60270 and radio frequency (RF) techniques are employed to explore new features that can be used to distinguish between internal PDs and external interference, as well as among different internal PD sources. Stream clustering based on the density grid method with only a few features required is used to categorize...