Sharif Digital Repository

Continuity and reliability of electricity supply in a country are vital to the operational continuity of the critical infrastructure and government. High levels of cyber security are required to achieve such key measures in the electricity industry. We propose solutions and models on how to improve the cyber security using the maturity model in order to achieve continuity of electricity supplies. Maturity levels start from the relative level (level 1) and continue to the adaptive level (level 4). A total of 10 domains are defined in the model. The practices of cyber security are clustered into domains. The model is used for assessment of the strength and weakness factors for the... 

In this paper, a multiple metric learning scheme for human pose estimation from a single image is proposed. Here, we focused on a big challenge of this problem which is; different 3D poses might correspond to similar inputs. To address this ambiguity, some Euclidean distance based approaches use prior knowledge or pose model that can work properly, provided that the model parameters are being estimated accurately. In the proposed method, the manifold of data is divided into several clusters and then, we learn a new metric for each partition by utilizing not only input features, but also their corresponding poses. The manifold clustering allows the decomposition of multiple manifolds into a... 

In this paper, we have focused on finding an error resilient method for discontinuity-less transmission of speech signals in the internet. Our proposed method creates artificial correlation between speech samples that pre-distorts the speech signal. The receiver uses this correlation to reconstruct the lost speech packets. A discrete Fourier transform (DFT)-based speech enhancement technique is designed for the reduction of the processing error in the recovered speech caused by the speech codecs. The SegSNR results show the superiority of our proposed method over a recently proposed speech enhancement technique. ©2007 IEEE  

In this paper, we present a novel multilinear algebra based feature extraction approach for face recognition which preserves some implicit structural or locally-spatial information among elements of the original images. We call this method three-dimensional modular discriminant analysis (3DMDA). Our approach uses a new data model called third-order tensor model (3TM) for representing the face images. In this model, each image is partitioned into the several equal size local blocks, and the local blocks are combined to represent the image as a third-order tensor. Then, a new optimization algorithm called direct mode (d-mode) is introduced for learning three optimal projection axes. Extensive... 

One limitation of vector-based LDA and its matrix-based extension is that they cannot deal with heteroscedastic data. In this paper, we present a novel two-dimensional feature extraction technique for face recognition which is capable of handling the heteroscedastic data in the dataset. The technique is a general form of two-dimensional linear discriminant analysis. It generalizes the interclass scatter matrix of two-dimensional LDA by applying the Chernoff distance as a measure of separation of every pair of clusters with the same index in different classes. By employing the new distance, our method can capture the discriminatory information presented in the difference of covariance... 

Motivated by the fact that in computer vision data samples are matrices, in this paper, we propose a matrix-variate probabilistic model for canonical correlation analysis (CCA). Unlike probabilistic CCA which converts the image samples into the vectors, our method uses the original image matrices for data representation. We show that the maximum likelihood parameter estimation of the model leads to the two-dimensional canonical correlation directions. This model helps for better understanding of two-dimensional Canonical Correlation Analysis (2DCCA), and for further extending the method into more complex probabilistic model. In addition, we show that two-dimensional Linear Discriminant... 

To evaluate the performance of the distributed medium access control layer of the emerging ultrawideband and 60-GHz millimeter wave (mmWave) wireless personal area networks based on ECMA-368 and ECMA-387 standards, the first step is to determine the beacon period length (BPL) of the superframe in a given network. In this paper, we provide an analytical model for the probability mass function (PMF) of the BPL as a function of the network dimensions, number of beaconing devices, antenna beamwidth, and the transmission range of the devices. To enable devices with steerable directional antennas in the ECMA-387 standard to have simultaneous communications with neighbors in their different antenna... 

A probabilistic method is developed here to model the beacon period length (BPL) defined in the ECMA-368 and ECMA-387 standards for the distributed reservation protocol. The model computes the probability mass function (PMF) of the BPL in a superframe which will be used in modeling of throughput, delay, fairness, power and other major distributed medium access control layer parameters of the emerging ultra wideband and 60- GHz millimeter wave wireless personal area networks. The model relates the PMF of the BPL to the network density, antenna beamwidth, and the transmission range of the devices assuming that the devices are distributed in an outdoor environment based on Two-dimensional... 

There is a growing attention in subspace learning using tensor-based approaches in high dimensional spaces. In this paper we first indicate that these methods suffer from the Heteroscedastic problem and then propose a new approach called Heteroscedastic Multilinear Discriminant Analysis (HMDA). Our method can solve this problem by utilizing the pairwise chernoff distance between every pair of clusters with the same index in different classes. We also show that our method is a general form of Multilinear Discriminant Analysis (MDA) approach. Experimental results on CMU-PIE, AR and AT&T face databases demonstrate that the proposed method always perform better than MDA in term of classification... 

This paper presents a new approach based on Artificial Potential Fields (APF) which provides real-time and very effective methodology for practical motion planners in unknown dynamic environments. The Maxwell's equations are exploited to define Artificial Magnetoquasistatic Fields (AMF) as an extension of APF, which provides a predictive, intelligent, and natural behavior in contrast with other approaches. The essential aim of the AMF is dealing with moving obstacles, as well as static ones. The main idea is to consider an electrical current in the direction of each moving obstacle which induces magnetic field around it. These moving obstacles could be arbitrary in shape, size, and number.... 

To evaluate the performance of distributed mediumaccess control (MAC) layer of emerging ultra wideband (UWB) and 60-GHz millimeter wave (mmWave) wireless personal area networks (WPANs) based on distributed reservation protocol (DRP) of ECMA-368 and ECMA-387 standards, we provide an analytical model for the probability distribution of steady state throughput as a function of the network dimensions size, number of devices, antenna beamwidth, transmission range, bit error rate (BER), antenna disturbance rate (ADR), aggregation length, payload size, and incoming frame rate. Using this model, the optimal payload size is computed as an example of optimization problem.We also propose a formula for... 

In the internet telephony, loss of IP packets causes instantaneous discontinuities in the received speech. In this paper, we have focused on finding an error resilient method for this problem. Our proposed method creates artificial correlation between speech samples that pre-distorts the speech signal. The receiver uses this correlation to reconstruct the lost speech packets. An appropriate speech enhancement technique is designed for the reduction of the processing error in the recovered speech caused by the speech codecs. The SegSNR results show the superiority of our proposed speech enhancement method over a recently proposed one. © 2007 IEEE  

A set of small battery-operated sensors with low-power transceivers that can automatically form a network and collect some desired physical characteristics of the environment is called a wireless sensor network. The communications must be designed to conserve the limited energy resources of the sensors [14].By clustering sensors we can save energy. In this paper, we introduce a new concept called "Center of Energy Mass" which is a combination of both energy level and location of the nodes which is used to form the new factor of "distance of the nodes to the CEM ".Distance of the nodes to the CEM is used together with Probability Density Function of the normal distribution in optimizing... 

This paper presents a new approach based on Artificial Potential Fields (APF) method which provides simple and effective motion planners for practical path planning in fully dynamic environments. We have exploited the fuzzy modeling to define Fuzzy Artificial Potential Fields (FAPF) which provides a real-time and flexible path planning, in contrast with classical approaches which make use of analytic harmonic functions to solve the navigation problem. It is shown that FAPF paves a way to merge both global and local path planning strategies. In this particular application, the proposed fuzzy system is used to obtain the gradient of the harmonic functions via weighting the membership functions... 

Proposing a proper method for face recognition is still a challenging subject in biometric and computer vision applications. Although some reliable systems were introduced under relatively controlled conditions, their recognition rate is not satisfactory in the general settings. This is especially true when there are variations in pose, illumination, and facial expression. To alleviate these problems, a hybrid face recognition system is proposed which benefits from the superiority of both convolutional neural network (CNN) and support vector machine (SVM). To this end, first a genetic algorithm is employed to find the optimum structure of CNN. Then, the performance of the system is improved... 

In this paper we describe two differential fault attack techniques against Advanced Encryption Standard (AES). We propose two models for fault occurrence; we could find all 128 bits of key using one of them and only 6 faulty ciphertexts. We need approximately 1500 faulty ciphertexts to discover the key with the other fault model. Union of these models covers all faults that can occur in the 9th round of encryption algorithm of AES-128 cryptosystem, One of main advantage of proposed fault models is that any fault in the AES encryption from start (AddRoundKey with the main key before the first round) to MixColumns function of 9th round can be modeled with one of our fault models. These models... 

Face recognition has been an important topic in computer vision for the last two decades. While many algorithms have been developed to address this issue, one of the major challenges faced by them is variation in pose. One of the possible solutions is to find invariant features among different poses of a single person. In this paper a geometry mapping between a frontal face and its rotated pose is used to find invariant features for pose robust face recognition. This mapping is solely based on the angle of rotation and indicates mutual regions between a frontal view of a person and its rotated image. Invariant features based on the low frequency coefficients of these mutual regions are then... 

During the last years several logic styles have been proposed to counteract power analysis attacks. This article starts with a brief review of four different logic styles namely RSL, MDLP, DRSL, and TDPL. This discussion continues to examine the effect of the number of fanouts in power consumption of a CMOS inverter. Moreover, it is shown that insertion of delay elements in typical CMOS circuits is not adequate to prevent the glitches and information leakage unless the fanouts of input signals are balanced. Whereas enable signals have to be classified according to the depth of combinational circuits implemented using pre-charge logic styles, we show that the number of fanouts of enable... 

In this paper a novel method called Extended Two-Dimensional PCA (E2DPCA) is proposed which is an extension to the original 2DPCA. We state that the covariance matrix of 2DPCA is equivalent to the average of the main diagonal of the covariance matrix of PCA. This implies that 2DPCA eliminates some covariance information that can be useful for recognition. E2DPCA instead of just using the main diagonal considers a radius of r diagonals around it and expands the averaging so as to include the covariance information within those diagonals. The parameter r unifies PCA and 2DPCA. r=1 produces the covariance of 2DPCA, r=n that of PCA. Hence, by controlling r it is possible to control the...