Sharif Digital Repository

In this paper, the application of Endurance Time (ET) method to the seismic analysis of bridges is elaborated. ET method is a novel seismic analysis method based on time history analysis in which a structure is subjected to a predefined intensifying acceleration function. First, six concrete bridges were modeled in this study. Three Endurance Time Acceleration Functions (ETAFs) were applied to the models, and the average of responses was calculated. Next, the time history analysis was conducted using seven real accelerograms that are scaled using the method recommended by Federal Highway Administration (FHWA) to be compatible with the design spectrum of American Association of State Highway... 

Given the increasing need for the creation and development of automated systems, the problem of detecting and identifying the faces of people in the images has been considered by the researchers. In recent years, the sparse representation based classification has been of great interest to researchers. The goal of this investigation is to provide a quick and effective way to identify faces based on the sparse representation. Since the basis of sparse representation is to calculate it through L1-norm optimization for high dimensional dictionary with high computational volume, a smoothed L0-norm optimization-based method was introduced. At the time of obtaining the sparse representation using... 

this paper presents two new methods for power flow calculation of power systems in presence of Dynamic Flow Controller (DFC), which is a new member of FACTS controllers. In first method A new steady state model of DFC is introduced for the implementation of the device in the conventional Newton-Raphson power flow algorithm. The impact of DFC on power flow is accommodated by adding new entries and modifying some existing ones in the linearized Jacobian equations of the same system without DFC. The focus of second method is on the discrete nature of the DFC and including its effects on power flow. This method is based on Nabavi model for FACTS devices. A case study on a power system located in... 

In this paper the surface effects in 3D complex parts are investigated via classical FEM and the modified boundary Cauchy-Born method, which are continuum based theories, and the results are compared with molecular dynamics simulations. The boundary Cauchy-Born covers the weakness of the surface Cauchy-Born in modeling edge and corner elements, so the results are in better agreement with molecular dynamics simulations. Using super convergent patch recovery method, MBCB shows more precise results in comparison with BCB as it can model acute and obtuse angles which cannot be modeled via BCB. The flexibility of MBCB in modeling 3D complex and non-right angle geometries are utilized to model... 

In this paper we introduce and propose novel signaling methods and receiver structures based on advanced binary optical logic gates for fiber-optic code division multiple access (FO-CDMA) systems using all-optical signal processing. In the proposed system the users of the network are categorized into multiple classes. Users of each class transmit at the same power level but different from the levels of the other classes' users. Using a combination of optical OR, AND and XNOR logic gates for the receiver structure we show that such a network not only takes the full advantages of all-optical signal processing but also demonstrates a considerable throughput efficiency when compared to ordinary... 

It is a great challenge for the universities to present undergraduate students the fundamental knowledge needed to develop intelligent unstable robots. Due to the inherent instability and nonholonomic constraints, the problem of two-wheeled inverted pendulum (TWIP) mobile robot is appealing and challenging case in control and dynamic systems. In this paper, an approach is presented to introduce undergraduate students of the control engineering, the principle of developing a. TWIP mobile robot. For this purpose, a. conceptual design algorithm for TWIP robots is contributed and based on the algorithm and the design criteria, a. prototype of the robot is constructed. In the construction... 

Ta0.8Hf0.2C ceramic has the highest melting point among the known materials (4000°C). Spark plasma sintering is a new route for consolidation of materials, specially ultra high temperature ceramics (UHTCs), which are difficult to be sintered at temperatures lower than 2000°C.The purpose of this study is to consolidate Ta0.8Hf0.2C by spark plasma sintering at low temperature using MoSi2 and TaSi2 as sintering aid. In this regard, effect of different amounts of sintering aids and carbides ratio on densification behavior and mechanical properties of Ta1-xHfxC were investigated.Fully consolidation of Ta0.8Hf0.2C was achieved in presence of 12vol.% sintering aid after sintering at 1650°C for 5min... 

There was a mistake in the author mane. The right fifth author is “K. Motaghed A.” There was a mistake in the first keyword. The keyword is “Two-wheeled inverted pendulum(TWIP).” The original article can be found online at https://doi.org/10.3103/S0025654419040162. © 2019, Allerton Press, Inc  

Similarity measure is an important key in image registration. Most traditional intensity-based similarity measures (e.g. sum-of-squared-differences, correlation coefficient, mutual information and correlation ratio) assume a stationary image and pixel-by-pixel independence. These similarity measures ignore the correlation among pixel intensities; hence, a perfect image registration cannot be achieved especially in the presence of spatially varying intensity distortions and outlier objects that appear in one image but not in the other. It is supposed here that non-stationary intensity distortion (such as bias field) has a sparse representation in the transformation domain. Based on this... 

The registration of images is a fundamental task in numerous applications in medical image processing. Similarity measure is an important key in intensity based image registration. Here, we propose correntropy measure as similarity measure in mono modal setting. Correntropy is a important measure between two random variables based on information theoretic learning and kernel methods. This measure is useful in non-Gaussian signal processing. In this paper, this measure is used in image registration. Here, we analytically illustrate that this measure is robust in presence of spiky noise (impulsive noise). The experimental results show that the proposed similarity has better performance than... 

Similarity measure is an important key in image registration. Most traditional intensity-based similarity measures (e.g., SSD, CC, MI, and CR) assume stationary image and pixel by pixel independence. Hence, perfect image registration cannot be achieved especially in presence of spatially-varying intensity distortions and outlier objects that appear in one image but not in the other. Here, we suppose that non stationary intensity distortion (such as Bias field or Outlier) has sparse representation in transformation domain. Based on this as-sumption, the zero norm (ℓ0)of the residual image between two registered images in transform domain is introduced as a new similarity measure in presence... 

Similarity measure is an important block in image registration. Most traditional intensity-based similarity measures (e.g., sum-of-squared-difference, correlation coefficient, and mutual information) assume a stationary image and pixel-by-pixel independence. These similarity measures ignore the correlation between pixel intensities; hence, perfect image registration cannot be achieved, especially in the presence of spatially varying intensity distortions. Here, we assume that spatially varying intensity distortion (such as bias field) is a low-rank matrix. Based on this assumption, we formulate the image registration problem as a nonlinear and low-rank matrix decomposition (NLLRMD).... 

Similarity measure is an important part of image registration. The main challenge of similarity measure is lack of robustness to different distortions. A well-known distortion is spatially-varying intensity distortion. Its main characteristic is correlation among pixels. Most traditional intensity based similarity measures (e.g., SSD, MI) assume stationary image and pixel to pixel independence. Hence, these similarity measures are not robust against spatially-varying intensity distortion. Here, we suppose that non-stationary intensity distortion has a sparse representation in transform domain, i.e. its distribution has high peak at origin and a long tail. We use two viewpoints of Maximum... 

In this paper, we propose the Object Pursuing based Efficient Routing Algorithm (OPERA) suitable for vehicular ad hoc networks (VANETs), esp. in sparse situations. The proposed algorithm is applicable for both moving and fixed destinations. It is based on considering static nodes at each intersection. In this algorithm, we optimize the decision making at intersections, with respect to the connectivity and feasibilty of the roads. To this end, we consider the average delay of each road as the connectivity metric, and the vehicle availability in the transmission range of the intersection as the feasibility metric. By exploiting the related metrics, we select the next road to forward the packet... 

Similarity measure is a main core of image registration algorithms. Spatially varying intensity distortion is an important challenge, which affects the performance of similarity measures. Correlation among the pixels is the main characteristic of this distortion. Similarity measures such as sum-of-squared-differences (SSD) and mutual information ignore this correlation; hence, perfect registration cannot be achieved in the presence of this distortion. In this paper, we model this correlation with the aid of the low rank matrix theory. Based on this model, we compensate this distortion analytically and introduce rank-regularized SSD (RRSSD). This new similarity measure is a modified SSD based... 

We show that multiple Abelian sectors with Stückelberg mass-mixing simply break supersymmetry via Fayet-Iliopoulos D-terms and straightforwardly mediate it to the other sectors. This mechanism naturally realizes a split supersymmetry spectrum for soft parameters. Scalar squared-masses (holomorphic and non-holomorphic) are induced through sizable portals and are not suppressed. Gaugino masses, a-terms and a μ-like term are generated by higher-dimensional operators and are suppressed. The hypercharge is mixed with extra U(1)'s, it's D-term in non-vanishing and supersymmetry is broken in the visible sector too. Scalar tachyonic directions are removed by unsuppressed interactions and hypercharge... 

We present a constant-time randomized distributed algorithms in the congested clique model that computes an O(α)-vertex-coloring, with high probability. Here, α denotes the arboricity of the graph, which is, roughly speaking, the edge-density of the densest subgraph. Congested clique is a well-studied model of synchronous message passing for distributed computing with all-to-all communication: per round each node can send one O(log n)-bit message algorithm to each other node. Our O(1)-round algorithm settles the randomized round complexity of the O(α)-coloring problem. We also explain that a similar method can provide a constant-time randomized algorithm for decomposing the graph into O(α)...