Sharif Digital Repository

In this paper a fuzzy controller is developed for automatic landing of fixed wing Unmanned Aerial Vehicles (UAVs). It is assumed that the vehicle has a built in vision system which provides the runway relative position and orientation to be used in the designed tracking system. The stability of the controller was analyzed through vector field diagrams, and the system performance is tested through a complete 6DOF computer simulation. The results show a satisfactory performance of the controller all through the automatic landing phase. ©2009 IEEE  

Tight unmanned aerial vehicle (UAV) autonomous missions such as formation flight (FF) and aerial refueling (AR) require an active controller that works in conjunction with a precise sensor that is able to identify an in-front aircraft and to estimate its relative position and orientation. Among possible choices vision sensors are of interest because they are passive in nature and do not require the cooperation of the in-front aircraft in any way. In this paper new vision-based estimation and navigation algorithms based on neural networks is developed. The accuracy and robustness of the proposed algorithm have been validated via a detailed modeling and a complete virtual environment based on... 

The quality of service in Wireless Multimedia Sensor Networks (WMSN) is related to congestion in network. Recently different studies have been done on developing efficient protocols in the transport layer for controlling packet loss in WMSN. However, all of these protocols are independent of the characteristics of multimedia content. In this paper, a novel transport layer protocol, called Energy Efficient Congestion Avoidance (EECA), is proposed to minimize the packet loss ratio in WMSN by predicting congestion in network, and adjusting the source nodes output rate before congestion happening. EECA adjusts the output video quality in source nodes to adjust the source nodes video quality. The... 

We explore the dictionary learning problem for sparse representation when the signals are dependent. In this paper, a first-order Markovian model is considered for dependency of the signals, that has many applications especially in medical signals. It is shown that the considered dependency among the signals can degrade the performance of the existing dictionary learning algorithms. Hence, we propose a method using the Maximum Log-likelihood Estimator (MLE) and the Expectation Minimization (EM) algorithm to learn the dictionary from the signals generated under the first-order Markovian model. Simulation results show the efficiency of the proposed method in comparison with the... 

Localization and quantification of structural damage and estimating the failure probability are key outputs in the reliability assessment of structures. In this study, an Artificial Neural Network (ANN) is used to reduce the computational effort required for reliability analysis and damage detection. Toward this end, one demonstrative structure is modeled and then several damage scenarios are defined. These scenarios are considered as training data sets for establishing an ANN model. In this regard, the relationship between structural response (input) and structural stiffness (output) is established using ANN models. The established ANN is more economical and achieves reasonable accuracy in... 

Tight unmanned aerial vehicle (UAV) autonomous missions such as formation flight and aerial refueling (AR) requires an active controller that works in conjunction with a precise vision-based sensor that is able to extract In-front aircraft relative position and orientation from captured images. A key point in implementing such a sensor is its robustness in the presence of noises and other uncertainties. In this paper, a new vision-based algorithm that uses neural networks to estimate the In-front aircraft relative orientation and position is developed. The accuracy and robustness of the proposed algorithm has been validated via a detailed modeling and a complete virtual environment based on... 

Image matching plays an important role in many aspects of computer vision. Our proposed method is based on Scale Invariant Feature Transform (SIFT) which is one of the popular image matching methods. The main ideas behind our method are removing the excess keypoints, adding oriented patterns to descriptor, and decreasing the size of the descriptors. By doing these changes to SIFT, we would have oriented patterns of keypoints. In addition, the numbers of keypoints have been reduced and the places of keypoints would be selected more accurately, and also the size of the descriptors has been reduced  

Developing internet usage and services urged play strong role for social network. Social networks are environment which uses internet as interface to provide relations between people, in the other word to interchange data and information between persons. Email and Instant Messengers are popular examples of them. Whereas these environments are continuously and instantly developing, revising and viewing by humans, they are good places for mining. In this paper, the topic of exchanged information between users in this type of networks will be our target. Our method is to use a hierarchical dictionary of semantically related topics and words that is mapped to a graph. Then extracted keywords... 

Performance of Friction Stir Welding (FSW) as a solid-state process is approved in several engineering applications, especially aluminum industries. Identification of mechanical behavior of the associated welded zone is necessary due to these extensive applications of FSW. In this study, considering the effect of rotational and forward speed of welding tool on the mechanical properties of welded region, a hybrid optimization method based on combination of Genetic Algorithm (GA) and Response Surface Method (RSM) named here as GA-RSM is proposed to achieve maximum tensile and ultimate strength. The results of GA-RSM are validated by per-forming necessary experimental tests on two wide-used... 

Graph signal processing (GSP) have found many applications in different domains. The underlying graph may not be available in all applications, and it should be learned from the data. There exist complicated data, where the graph changes over time. Hence, it is necessary to estimate the dynamic graph. In this paper, a new dynamic graph learning algorithm, called dynamic K-graphs, is proposed. This algorithm is capable of both estimating the time-varying graph and clustering the temporal graph signals. Numerical experiments demonstrate the high performance of this algorithm compared with other algorithms. © 2021 European Signal Processing Conference, EUSIPCO. All rights reserved  

In this paper, we consider the nonlinear Blind Source Separation BSS and independent component analysis (ICA) problems, and especially uniqueness issues, presenting some new results. A fundamental difficulty in the nonlinear BSS problem and even more so in the nonlinear ICA problem is that they are nonunique without a suitable regularization. In this paper, we mainly discuss three different ways for regularizing the solutions, that have been recently explored. © 2003 Elsevier B.V. All rights reserved  

Motivated by the bus escape routing problem in printed circuit boards, we study the following rectangle escape problem: given a set S of n axis-aligned rectangles inside an axis-aligned rectangular region R, extend each rectangle in S toward one of the four borders of R so that the maximum density over the region R is minimized. The density of each point p∈R is defined as the number of extended rectangles containing p. We show that the problem is hard to approximate to within a factor better than 3/2 in general. When the optimal density is sufficiently large, we provide a randomized algorithm that achieves an approximation factor of 1+ε with high probability improving over the current best... 

Error control is an important mechanism for providing robust multimedia communication in wireless sensor networks. Although there have been several research works in analysis of error control mechanisms in wireless multimedia networks and wireless sensor networks, but none of them are directly applicable to the wireless multimedia sensor networks (WMSNs) which has resource and performance constraints of WSNs as well as QoS requirements of multimedia communications. In this paper, we comprehensively evaluate the performance of several error control mechanisms in WMSNs. The results of our analysis provide an extensive comparison between automatic repeat request (ARQ), forward error correction... 

In this paper a new method for face virtual pose generation is presented. The proposed method uses subspace image representation. The general problem of blurring is addressed by introducing a multi resolution time-frequency analysis to subspace image representation. The training gallery contains face images in two different poses. Undecimated Wavelet Transform is applied on all training face images in first pose and the corresponding images in the second pose to produce image subbands. Then, a new subspace is constructed for each subband in both poses. The mapping between two corresponding subbands of two poses is learnt using linear regression. The resulted mapping matrix is used to... 

This paper is concerned about islanding of network and observability of these islands in power system restoration. It is assumed that a black out happened on a system which have minimum PMUs (phasor measurement units) for measuring network's parameters. To restore this system an algorithm of islanding that keeps all islands observable to make the restoration process shorter is introduced and developed step by step on the IEEE 14 bus system and it is applied to the New England 39 bus system to show the result for a bigger system  

This paper proposes a fuzzy-based speed controller for the doubly fed induction generator (DFIG)-based wind turbines with the rotor speed and wind speed inputs. The controller parameters are optimized using the particle swarm optimization algorithm. To accelerate tracking the maximum power point trajectory, the conventional controller is augmented with a feed-forward compensator, which uses the wind speed input and includes a high-pass filter. The proposed combined speed controller is robust against wind measurement errors and as the accuracy of anemometers increases the speed regulation tends toward the ideal controller. The cutoff frequency of the applied filter is determined considering a... 

Motivated by the bus escape routing problem in printed circuit boards, we revisit the following problem: given a set of n axis-parallel rectangles inside a rectangular region R, find the maximum number of rectangles that can be extended toward the boundary of R, without overlapping each other. We provide an efficient algorithm for solving this problem in O(n2 log3 n log log n) time, improving over the current best O(n3)-time algorithm available for the problem  

Laccase production by indigenous fungus, Phanerochaete chrysosporium, requires solving optimal problems to determine the maximum production of the enzyme within a definite time period and conditions specified in the solid-state fermentation process. For this purpose, parallel to response surface methodology, an analytical approach has been proposed based on the advanced concepts of Poisson geometry and Lie groups, which lead to a system of the Hamiltonian equations. Despite the dating of the Hamiltonian approach to solving biological problems, the novelty of this paper is based on the expression of a Hamiltonian system in notions of Poisson geometry, Lie algebras and symmetry groups and... 

The emerging multimedia applications of Wireless Sensor Network (WSNs) impose new challenges in design of algorithms and communication protocols for such networks. In the view of these challenges, error control is an important mechanism that enables us to provide robust multimedia communication and maintain Quality of Service (QoS). Despite the existence of some good research works on error control analysis in WSNs, none of them provides a thorough study of error control schemes for multimedia delivery. In this paper, a comprehensive performance evaluation of Automatic Repeat Request (ARQ), Forward Error Correction (FEC), Erasure Coding (EC), link-layer hybrid FEC/ARQ, and cross-layer hybrid... 

Photovoltaic (PV) arrays are composed of PV cells which have a nonlinear power-voltage characteristic. To extract maximum amount of energy from a PV array, it is essential to track maximum power point (MPP). When all PV cells are subject to the same solar energy, MPP is found easily. However, in some ambient conditions, PV cells are partially or completely shadowed. Under partial shading conditions (PSCs), overall power-voltage curve will have several peaks. This paper presents a novel approach for MPP tracking, utilizing configuration of PV cells in series and parallel that may deliver maximum power in shading conditions. As such, instead of blindly searching for the global MPP among local...