Sharif Digital Repository

In an electronic warfare environment, an electronic support system receives signals emitted by different radars. One of the key tasks in an electronic support system is PRI estimation tracking Pulse Trains using Pulse Repetition Interval (PRI) of these signals. In this paper we present a simple method for PRI estimation and tracking radar pulse trains with complex PRI Modulations. This method uses nonlinear least square, Pisarenko and innovative methods for PRI estimation and tracking pulse train. Simulation results show high robustness of the proposed method against noise (spurious and missing pulses)  

We consider a multi-facility location problem in the presence of a line barrier with the starting point of the barrier uniformly distributed. The objective is to locate n new facilities among m existing facilities minimising the summation of the weighted expected rectilinear barrier distances of the locations of new facilities and new and existing facilities. The proposed problem is designed as a mixed-integer nonlinear programming model, conveniently transformed into a mixed-integer quadratic programming model. The computational results show that the LINGO 9.0 software package is effective in solving problems with small sizes. For large problems, we propose two meta-heuristic algorithms,... 

Watermarking is a suitable approach for digital image authentication. Robustness regarding attacks that aim to remove the watermark is one of the most important challenges in watermarking, in general. Several different attacks are reported that aim to make it difficult or impossible for the real owner of the digital watermarked image to extract the watermark. Some of such common attacks are noise addition, compression, scaling, rotation, clipping, cropping, etc. In this paper we address the issue of print and scan attack by introducing a method to model the scanner and printer. Then we will simulate the print and scan attack on the digital images to evaluate its robustness. In addition, we... 

Robustness against attacks is an important requirement in image watermarking. This paper presents a robust watermarking algorithm in wavelet transform domain. Firstly, original image is decomposed into its subbands using three level wavelet transform, then, significant coefficients with the same position in HL, LH and HH subbands of the last level are extracted to make a triplet. To embed a watermark bit into a triplet, the standard deviation of triplet coefficients magnitude is set to zero for zero bit or increased for a one bit. Three constant are used to increase the standard deviations of a triplet coefficients. The value of these constants affects the robustness of algorithm and the... 

This paper concentrates on the target localization problem in a distributed multiple-input multiple-output radar system using the bistatic range (BR) measurements. By linearizing the BR measurements and considering the relationship between the nuisance parameter and the target position, a constrained weighted least squares (CWLS) problem is formulated, which is an indefinite quadratically constrained quadratic programming problem. Since the constraint is non-convex, it is a nontrivial task to find the global solution. For this purpose, an improved Newton's method is applied to the CWLS problem to estimate the target position. Numerical simulations are included to examine the algorithm's... 

In this paper, we focus on the moving target localization problem in a multiple-input multiple-output radar with widely separated antennas. By exploiting jointly different types of information including time delay, Doppler shift and azimuth and elevation angles of arrival, we develop an algebraic closed-form two-stage weighted least squares solution for the problem. The proposed algorithm is shown analytically to attain the CramerRao lower bound accuracy under the small Gaussian noise assumption. Numerical simulations are included to examine the algorithm's performance and corroborate the theoretical developments  

This article proposes a blind discrete wavelet transform-discrete cosine transform (DWT-DCT) composite watermarking scheme that is robust against print and scan distortions. First, two-dimensional DWT is applied to the original image to obtain the mid-frequency subbands. Then, a one-dimensional DCT is applied to the selected mid-frequency subbands to extract the final coefficients for embedding the watermark. To specify watermarking parameters, we utilize a Genetic Algorithm to achieve a predefined image quality after watermark insertion. Suitable locations for watermarking are determined by analyzing the effect of a modeling algorithm. This model simulates noise and nonlinear attacks in... 

Image annotation approaches need an annotated dataset to learn a model for the relation between images and words. Unfortunately, preparing a labeled dataset is highly time consuming and expensive. In this work, we describe the development of an annotation system in semi-supervised learning framework which by incorporating unlabeled images into training phase reduces the system demand to labeled images. Our approach constructs a generative model for each semantic class in two main steps. First, based on Gamma distribution, a generative model is constructed for each semantic class using labeled images in that class. The second step incorporates the unlabeled images by using a modified EM... 

We present a competitive algorithm to minimize a locally Lipschitz function constrained with locally Lipschitz constraints. The approach is to use an ℓ1 nonsmooth penalty function. The method generates second order descent directions to minimize the ℓ1 penalty function. We introduce a new criterion to decide upon acceptability of a Goldstein subdifferential approximation. We show that the new criterion leads to an improvement of the Goldstein subdifferential approximation, as introduced by Mahdavi-Amiri and Yousefpour. Also, making use of our proposed line search strategy, the method always moves on differentiable points. Furthermore, the method has an adaptive behaviour in the sense that,... 

Different types of visual features provide multi-modal representation for images in the annotation task. Conventional graph-based image annotation methods integrate various features into a single descriptor and consider one node for each descriptor on the learning graph. However, this graph does not capture the information of individual features, making it unsuitable for propagating the labels of annotated images. In this paper, we address this issue by proposing an approach for fusing the visual features such that a specific subgraph is constructed for each visual modality and then subgraphs are connected to form a supergraph. As the size of supergraph grows linearly with the number of... 

We present a competitive algorithm to minimize a locally Lipschitz function constrained with locally Lipschitz constraints. The approach is to use an ℓ1 nonsmooth penalty function. The method generates second order descent directions to minimize the ℓ1 penalty function. We introduce a new criterion to decide upon acceptability of a Goldstein subdifferential approximation. We show that the new criterion leads to an improvement of the Goldstein subdifferential approximation, as introduced by Mahdavi-Amiri and Yousefpour. Also, making use of our proposed line search strategy, the method always moves on differentiable points. Furthermore, the method has an adaptive behaviour in the sense that,... 

We present an algorithm for minimizing locally Lipschitz functions being continuously differentiable in an open dense subset of Rn. The function may be nonsmooth and/or nonconvex. The method makes use of a gradient sampling method along with a conjugate gradient scheme. To find search directions, we make use of a sequence of positive definite approximate Hessians based on conjugate gradient matrices. The algorithm benefits from a restart procedure to improve upon poor search directions or to make sure that the approximate Hessians remain bounded. The global convergence of the algorithm is established. An implementation of the algorithm is executed on a collection of well-known test problems.... 

Considering each of the visual features as one modality in image annotation task, efficient fusion of different modalities is essential in graph-based learning. Traditional graph-based methods consider one node for each image and combine its visual features into a single descriptor before constructing the graph. In this paper, we propose an approach that constructs a subgraph for each modality in such a way that edges of subgraph are determined using a search-based approach that handles class-imbalance challenge in the annotation datasets. Multiple subgraphs are then connected to each other to have a supergraph. This follows by introducing a learning framework to infer the tags of... 

Aerodynamically alleviated marine vehicle (AAMV) is a high speed craft equipped with aerodynamic surfaces that operating in ground effect zone provides this craft with the ability to achieve much higher cruising speeds. Reducing the take-off mode of an AAMV is highly desirable. Additionally, it is seen where there is a considerable reserve thrust take-off can occur in the lower get-away speeds that shorten the take-off run and, therefore, is favourable. Accordingly, in this study an attempt has been made to develop a nonlinear mathematical model for an AAMV to simulate accelerations in take-off and landing phases, using semi-empirical equations mainly proposed for mono-hull high-speed craft,... 

This work presents a complete framework of an integrated aerial virtual environment (IAVE), which could effectively help implementing MonoSLAM (single-camera simultaneous localization and mapping) on an aerial vehicle. The developed system allows investigating different flight conditions without using any preloaded maps or predefined features. A 3D graphical engine integrated with a full 6 DOF aircraft dynamic simulator together with its trajectory generator completes the package. The 3D engine generates and accumulates real-time images of a general camera installed on the aerial vehicle. We effectively exploit C++ to develop the 3D graphics engine (3DGE) and all its associated visual... 

This work describes the essential tools and architecture of a simulation environment, which could help enhance general aviation training as well as safety issues, especially while dealing with flights over unfamiliar environments. It also describes how the authors could effectively generate any desired flight path and its associated surrounding images through implementing a virtual single camera with simultaneous localization and mapping (monocular simultaneous localization and mapping) techniques. The overall package enjoys an aerial three-dimensional (3D)/graphical engine integrated with a full six-degrees-of-freedom aircraft dynamics, which serves as its trajectory generator, together... 

Purpose: The aim of this research is to propose a buffer sizing and buffer controlling algorithm (BSCA) as a heuristic algorithm for calculating project buffer and feeding buffers as well as dynamic controlling of buffer consumption in different phases of a wind power plant project in order to achieve a more realistic project duration. Design/methodology/approach: The BSCA algorithm has two main phases of planning and buffer sizing and construction and buffer consumption. Project buffer and feeding buffers are determined in the planning and buffer sizing phase, and their consumption is controlled in the construction and buffer consumption phase. The heuristic algorithm was coded and run in... 

The present paper developed and validated a numerical procedure for the calculation of turbulent combustive flows in converging and diverging ducts. Through simulation of the heat transfer processes, the amounts of production and spread of NOx pollutants were measured. Also, this paper reported the results of a numerical investigation of the effects of the fuel Molecular Weight on NOx emissions in converging and diverging ducts. The fuels which were examined were methane, naphtha, and kerosene. The differential equations in the Von-Misses coordinate system were transformed to a cross-stream coordinate system in order to concentrate more grid lines near wall boundaries. A marching integration... 

We present a structured algorithm for solving constrained nonlinear least squares problems, and establish its local two-step Q-superlinear convergence. The approach is based on an adaptive structured scheme due to Mahdavi-Amiri and Bartels of the exact penalty method of Coleman and Conn for nonlinearly constrained optimization problems. The structured adaptation also makes use of the ideas of Nocedal and Overton for handling quasi-Newton updates of projected Hessians. We discuss the comparative results of the testing of our programs and three nonlinear programming codes from KNITRO on some randomly generated test problems due to Bartels and Mahdavi-Amiri. The results indeed confirm the... 

We have recently proposed a structured algorithm for solving constrained nonlinear least-squares problems and established its local two-step Q-superlinear convergence rate. The approach is based on an earlier adaptive structured scheme due to Mahdavi-Amiri and Bartels of the exact penalty method. The structured adaptation makes use of the ideas of Nocedal and Overton for handling quasi-Newton updates of projected Hessians and adapts a structuring scheme due to Engels and Martinez. For robustness, we have employed a specific nonsmooth line search strategy, taking account of the least-squares objective. Numerical results also confirm the practical relevance of our special considerations for...