Sharif Digital Repository

This paper proposes an image watermarking scheme for copyright protection based on Independent Component Analysis (ICA). In the suggested scheme, we divide the original image into blocks and use the ICA to project the image into a basis with its components as statistically independent as possible. The data embedding is carried out in cumulative form in the ICA basis and also the ICA is used for watermark extraction. The extraction process could be either non-blind, through a straightforward procedure, or blind, via a tricky method we propose. Experimental results show that the new method outperforms some well-known image watermarking methods [1], [2], [3] in spatial or frequency domain and... 

Independent Component Analysis (ICA) can be used to decompose functional Magnetic Resonance Imaging (fMRI) data into a set of statistically independent images which are likely to be the sources of fMRI data. After applying ICA, a set of independent components are produced, and then, a "meaningful" subset from these components must be identified, because a large majority of components are non-interesting. So, interpreting the components is an important and also difficult task. In this paper, we propose a criterion based on the entropy of time courses to automatically select the components of interest. This method does not require to know the stimulus pattern of the experiment  

Focusing on aspects during early stages of the software development lifecycle has received special attention by many researchers, leading to the advent of numerous Aspect-Oriented Software Development (AOSD) methods. This has consequently given a relatively high level of maturity to aspect-oriented processes. Process patterns, on the other hand, have been adopted as suitable mechanisms for defining or tailoring processes to fit specific organizational/project requirements. Process patterns, which essentially are reusable process components extracted from successful processes and practices, can be used to engineer new software development methodologies or to enhance existing ones. We propose... 

As the electricity market undergoes continuous evolutions, along with the outdated nature of the grid, system operators would have to be able to more effectively manage the operation costs since waves of maintenance costs and equipment investments would be anticipated in the years to come. Strategic implementation of cost-effective reliability centered maintenance (RCM) approaches seems to be a key solution. This paper proposes an efficient method to assess the component criticality for the system overall reliability and further maintenance focuses. A solution concept of game theory, called Shapely Value, that is able to fairly identify the contribution of each single equipment to the system... 

In this study, a transformer model is proposed to simulate the behaviour of a real transformer, under presence ofdifferent types of defects which contribute to partial discharge (PD) generation, as closely as possible. Five different typesof defects (scratch on winding insulation, bubble in oil, moisture in insulation paper, very small free metal particle intransformer tank and fixed sharp metal point on transformer tank) are implemented artificially into these transformermodels to investigate the resultant PD current signal magnitude and characteristics. Time-domain PD currentwaveforms are recorded on those transformer models which have one type of those defects. The resultant statisticalPD... 

Suppose that a solution x to an underdetermined linear system b=Ax is given. x is approximately sparse meaning that it has a few large components compared to other small entries. However, the total number of nonzero components of x is large enough to violate any condition for the uniqueness of the sparsest solution. On the other hand, if only the dominant components are considered, then it will satisfy the uniqueness conditions. One intuitively expects that x should not be far from the true sparse solution x0. It was already shown that this intuition is the case by providing upper bounds on ||x-x0|| which are functions of the magnitudes of small components of x but independent from x0. In... 

Abdominal recordings of fetal ECG (fECG) have lower signal-to-noise ratio (SNR) as compared with invasive procedures. In this paper we have combined two previously proposed methods, one for extracting fECG, called πCA and the other, a transformation based on Hilbert transform to enhance the R-peaks. The combination of these methods seems to work well in situations of noisy data and fetal repositioning. Also a comparison is done by using ICA in order to extract the fetal signals. Performance of both methods is studied separately. Results show that applying the transformation on the components extracted with the use of πCA (after maternal ECG cancellation), had a very good performance. Also,... 

In this paper, we consider to seek vulnerabilities and we conduct possible attacks on the crucial and essential parts of Android OSs architecture including the framework and the Android kernel layers. As a regard, we explain the Binder component of Android OS from security point of view. Then, we demonstrate how to penetrate into the Binder and control data exchange mechanism in Android OS by proposing a kernel level attack model based on the hooking method. As a result, by implementing the attack model, it is illustrated that the Android processes are detectable and the data can be extracted from any process and system calls. © 2016 IEEE  

In this paper the Unsupervised Active Learning Method (UALM), a novel clustering method based on the Active Learning Method (ALM) is introduced. ALM is an adaptive recursive fuzzy learning algorithm inspired by some behavioral features of human brain functionality. UALM is a density-based clustering algorithm that relies on discovering densely connected components of data, where it can find clusters of arbitrary shapes. This approach is a noise-robust clustering method. The algorithm first blurs the data points as ink drop patterns, then summarizes the effects of all data points, and finally puts a threshold on the resulting pattern. It uses the connected-component algorithm for finding... 

Hierarchical reinforcement learning facilitates learning in large and complex domains by exploiting subtasks and creating hierarchical structures using these subtasks. Subtasks are usually defined through finding subgoals of the problem. Providing mechanisms for autonomous subgoal discovery and skill acquisition is a challenging issue in reinforcement learning. Among the proposed algorithms, a few of them are successful both in performance and also efficiency in terms of the running time of the algorithm. In this paper, we study four methods for subgoal discovery which are based on graph partitioning. The idea behind the methods proposed in this paper is that if we partition the transition... 

In this paper, a two-component Lattice Boltzmann Method (LBM) has been utilized to simulate the natural convection of TiO2-water nanofluid in a curved geometry. The main purpose of this research is to study the effect of nanoparticle size and also boundary conditions on the thermal characteristics of the nanofluid. Furthermore, the effect of Rayleigh number (Ra) and volume fraction of nanoparticles (ϕ) on the average Nusselt number (Nuave) have been investigated. Two different thermal boundary conditions, namely adiabatic and constant temperature, have been considered in the current work for the curved boundaries. The Rayleigh number varies from 103 to 109. Four different sizes, namely 10,... 

Hierarchical reinforcement learning (HRL) has had a vast range of applications in recent years. Preparing mechanisms for autonomous acquisition of skills has been a main topic of research in this area. While different methods have been proposed to achieve this goal, few methods have been shown to be successful both in performance and also efficiency in terms of time complexity of the algorithm. In this paper, a linear time algorithm is proposed to find subgoal states of the environment in early episodes of learning. Having subgoals available in early phases of a learning task, results in building skills that dramatically increase the convergence rate of the learning process. © 2009 Springer... 

Reo is a coordination language for modeling component connectors of component-based computing systems. Constraint automaton, as an extension of finite automaton, has been proposed as the operational semantics of Reo. In this paper, we introduce an extended definition of constraint automaton by which, every constraint automaton can be considered as a labeled transition system and each labeled transition system can be translated into a constraint automaton. We show that failure-based equivalences CFFD and NDFD are congruences with respect to composition of constraint automata using their join (production) and hiding operators. Based on these congruency results and by considering the temporal... 

Hole-transporter-free perovskite solar cells carrying a carbon back contact electrode provide the possibility of making full printable low cost and stable devices, even though their efficiency is substantially lower than those made in the standard configuration. The present work searched for simple and easy routes for constructing such devices, demonstrating that organic components do enhance device efficiency but only to a level that is not worth the trouble nor the cost. Devices based on a triple mesoporous layer of titania/zirconia/carbon with perovskite infiltration gave an efficiency of 10.7%. After 180 days of storing under ambient conditions, a small loss of efficiency has been... 

Demand response programs can be regarded as a risk management approach for retailers in electricity market. In case of high wholesale electricity price, implementation of demand response will reduce the economic risk exposure of the retailer. Realization of demand response requires investment in various sectors, and therefore, there is a need for economic valuation in order to determine the economic profit gained. This paper attempts to evaluate the economic value of demand response programs by the use of real option valuation method. In this regard, at first demand response programs are converted to option contracts. Then, the profit of retailer resulting from the demand response is... 

This paper models the cyber-social system as a cyber-network of agents monitoring states of individuals in a social network. The state of each individual is represented by a social node, and the interactions among individuals are represented by a social link. In the cyber-network, each node represents an agent, and the links represent information sharing among agents. The agents make an observation of social states and perform distributed inference. In this direction, the contribution of this paper is threefold: First, a novel distributed inference protocol is proposed that makes no assumption on the rank of the underlying social system. This is significant as most protocols in the... 

In this paper, a new sensitivity-based model updating method is presented based on the changes of principal components (PCs) of frequency response function (FRF). Structural damage estimation, identification of damage location and severity, is conducted by an innovative sensitivity relation. The sensitivity relation is derived by incorporating PC analysis (PCA) data obtained from the incomplete measured structural responses in a mathematical formulation and is then solved by the least square method. In order to demonstrate the performance of the proposed method, it is applied to a truss and a frame model. The results prove the ability of the method as a robust damage detection algorithm in... 

absectionBackground Three types of sources can be considered in the analysis of multi-subject datasets: (i) joint sources which are common among all subjects, (ii) partially-joint sources which are common only among a subset of subjects, and (iii) individual sources which belong to each subject and represent the specific conditions of that subject. Extracting spatial and temporal joint, partially-joint, and individual sources of multi-subject datasets is of significant importance to analyze common and cross information of multiple subjects. New method: We present a new framework to extract these three types of spatial and temporal sources in multi-subject functional magnetic resonance... 

In this paper, a new algorithm for source recovery in under-determined Sparse Component Analysis (SCA) or atomic decomposition on over-complete dictionaries is presented in the noisy case. The algorithm is essentially a method for obtaining sufficiently sparse solutions of under-determined systems of linear equations with additive Gaussian noise. The method is based on iterative Expectation-Maximization of a Maximum A Posteriori estimation of sources (EM-MAP) and a new steepest-descent method is introduced for the optimization in the Mstep. The solution obtained by the proposed algorithm is compared to the minimum ℓ1-norm solution achieved by Linear Programming (LP). It is experimentally... 

Heave plates are structural components used for reducing the vibrations caused by environmental forces on marine and offshore structures by changing the hydrodynamic properties. The fact that the added mass increase via heave plates does not always lead to the structural response reduction underscores the role of damping in maintaining the vibration amplitude within allowable limits. In the present experimental study, a novel combined rigid-elastic design is used to improve the damping through the velocity increase in the elastic part and added mass creation in the central rigid part. The desired percentage of total added mass and damping can be adjusted by changing the rigid-to-elastic...