Sharif Digital Repository

Signature verification (SV) is one of the common methods for identity verification in banking, where for security reasons, it is very important to have an accurate method for automatic SV (ASV). ASV is usually addressed by comparing the test signature with the enrolment signature(s) signed by the individual whose identity is claimed in two manners: online and offline. In this study, a new method based on the i-vector is proposed for online SV. In the proposed method, a fixed-length vector, called i-vector, is extracted from each signature and then this vector is used for template making. Several techniques such as nuisance attribute projection (NAP) and within-class covariance normalisation... 

This paper will first describe the Linear-Quadratic-Gaussian (LQG) and Lead-Compensator when the Proportional-Integral-Derivative (PID) controllers are inactive for procedures that have large delay time (LDT) in transfer stage. Therefore in those states, LQG and Lead Compensator perform better than the PID controllers. The constrained LQG is optimal and stabilizing. The solution algorithm is guaranteed to terminate in finite time with a computational cost that has a reasonable upper bound compared to the minimal cost for computing the optimal solution. In this work all actual working area condition for instance noises and disturbances are considered. Eventually, LQG and Lead Compensator have... 

Coupled continuous quadratic knapsack problems (CCK) are introduced in the present study. The solution of a CCK problem is equivalent to the projection of an arbitrary point onto the volume constrained Gibbs N-simplex, which has a wide range of applications in computational science and engineering. Three algorithms have been developed in the present study to solve large scale CCK problems. According to the numerical experiments of this study, the computational costs of presented algorithms scale linearly with the problem size, when it is sufficiently large. Moreover, they show competitive or even superior computational performance compared to the advanced QP solvers. The ease of... 

An unconditionally stable fully explicit finite difference method for solution of conduction dominated phase-change problems is presented. This method is based on an asymmetric stable finite difference scheme for approximation of diffusion terms and application of the temperature recovery method as a phase-change modeling method. The computational cost of the presented method is the same as the explicit method per time-step, while it is free from time-step limitation due to stability criteria. It robustly handles isothermal and nonisothermal phase-change problems and is very efficient when the global temperature field is desirable (not accurate front position). The robustness, stability,... 

An uncertain economic order quantity (UEOQ) model with payment in advance is developed to purchase high-price raw materials. A joint policy of replenishments and pre-payments is employed to supply the materials. The rate of demand is considered LR-fuzzy variables, lead-time is taken to be constant, and it is assumed that shortage does not occur in the cycles. The cycle is divided into three parts; the first part is the time between the previous replenishment-time to the next order-time (t0), the second part is the period between t0 to a payment-time (tk), and the third part is the period between tk to the next replenishment-time. At the start of the second part (t0), α% of the purchasing... 

Landmark extraction is used as the first step of many vision tasks such as tracking, image registration, localization, image matching and recognition. Furthermore, landmarks are used to reduce the data flow and consequently the computational costs. In this paper we extracted landmarks from echocardiography sequence, our algorithm is based on corner extraction, and then we evaluate our algorithm with applying some test. For this purpose, we evaluated the detectors according to their repeatability, stability and landmark localization under changes in noise. © 2009 IEEE  

Special superelements are often used to improve the computational efficiency and improve accuracy of finite element modeling. Structures with tapered and spherical geometry exist in many engineering problems. In this work, special tapered and spherical superelements are presented that can be used for modeling of tapered and spherical bodies in thermo mechanical analyses with computational efficiency. The performance of these superelements under thermal and structural loads is demonstrated by presenting several examples and comparing the results with those from conventional 3D brick elements, which shows high accuracy at reduced computational cost  

This paper proposes an inverse isogeometric analysis to estimate the blank and predict the strain distribution in sheet metal forming processes. In this study, the same NURBS basis functions are used for drawing a final part and analysis of the forming process. In other words, this approach requires only one modeling and analysis representation, in contrast to inverse FEM. This model deals with minimization of potential energy, deformation theory of plasticity, and infinitesimal deformation relations with considering a new non-uniform friction model. One advantage of the presented methodology is that the governing equations are solved in two-dimensional space without concerning about... 

Three-dimensional thermo-hydrodynamic analysis of gas turbine combustion chambers is of great importance in the power generation industry to achieve higher efficiency and reduced emissions. However, it is prohibitive to use a comprehensive full-detailed mechanism in their simulation algorithms because of the huge CPU time and memory space requirements. Many reduction approaches are available in the literature to remedy this problem. Here a new approach is presented to reduce large detailed or skeletal mechanisms of oxidation of hydrocarbon fuels to a low-cost skeletal mechanism. The method involves an integrated procedure including a Sensitivity Analysis (SA) and a procedure of Gradual... 

Given a social network modeled as a weighted graph GG, the influence maximization problem seeks kk vertices to become initially influenced, to maximize the expected number of influenced nodes under a particular diffusion model. The influence maximization problem has been proven to be NP-hard, and most proposed solutions to the problem are approximate greedy algorithms, which can guarantee a tunable approximation ratio for their results with respect to the optimal solution. The state-of-the-art algorithms are based on Reverse Influence Sampling (RIS) technique, which can offer both computational efficiency and non-trivial (1-1/e-ϵ)-approximation ratio guarantee for any epsilon >0ϵ>0.... 

Constructing an accurate geological model of the reservoir is a preliminary to make any reliable prediction of a reservoir's performance. Afterward, one needs to simulate the flow to predict the reservoir's dynamic behaviour. This process usually is associated with high computational costs. Therefore, alternative methods such as the percolation approach for rapid estimation of reservoir efficiency are quite desirable. This study tries to address the Well Testing (WT) interpretation of heterogeneous reservoirs, constructed from two extreme permeabilities, 0 and K. In particular, we simulated a drawdown test on typical site percolation mediums, occupied to fraction "p"at a constant rate Q/h,... 

In 2003, Wu and Chieu proposed a user friendly remote authentication scheme using smart cards. Later, Yang and Wang pointed out that Wu and Chieu's scheme is vulnerable to the password guessing and forgery attacks. Recently, Lee et al. proposed an improved authentication scheme and claimed that their scheme is secure against forgery attack. However, in this paper, we illustrate that Lee et al.'s scheme is still vulnerable to the forgery attack. We also propose an enhancement of the scheme to resist such that attack. © 2010  

Smart grid plays an important role in managing demand response management in modern smart city using Information and Communication Technologies (ICTs). In smart grid environment, sensors are widely used for surveillance. These are deployed on the high tension power supply lines which help to share the information to control center about line breakage or any other flaw. Besides the cyber-attacks, sensors may also experience physical attacks as they are deployed on high-tension power lines in an open environment. Moreover, an attacker can also impersonate the information exchanged between sensors, gateways and control centers. Therefore, the most indispensable requirement is to prevent these... 

Realistic simulation of tool-tissue interactions can help to develop more effective surgical training systems and simulators. This study uses a finite element and meshless modeling approach to simulate the grasping procedure of a large intra-abdominal organ, i.e. a kidney, during laparoscopic surgery. Results indicate that the accuracy of the meshless method is comparable with that of the finite element method, with root mean square errors in the range of 0.8 to 2.3 mm in different directions. For the model presented in this study, the computational cost of the meshless method was much less than that of the finite element model  

Although Face detection is not a recent activity in the field of image processing, it is still an open area for research. The greatest step in this field is the work reported by Viola and the recent analogous one is proposed by Huang et al. Both of them use similar features and also similar training process. The former is just for detecting upright faces, but the latter can detect multi-view faces in still grayscale images using new features called 'sparse feature'. Finding these features is very time consuming and inefficient by proposed methods. Here, we propose a new approach for finding sparse features using a genetic algorithm system. This method requires less computational cost and... 

Kinetic theory based numerical scheme such as direct simulation Monte Carlo (DSMC) and information preservation (IP) schemes properly solve micro-nano flow problems in transition and free molecular regimes. However, the high computational cost of these methods encourages the researchers toward extending the applicability of the continuumbased equations beyond the slip flow regime. In addition to correct velocity profile, the continuum-based equations should predict accurate mass flow rate magnitude. The secondorder velocity slip models derived from the kinetic theory provide accurate velocity profiles up to Kn=0.5; however, they yield erroneous mass flow rate magnitudes because the basic... 

The kinetic-theory-based numerical schemes, such as direct simulation Monte Carlo (DSMC) and information preservation (IP), can be readily used to solve transition flow regimes. However, their high computational cost still promotes the researchers to extend the Navier-Stokes (NS) equations beyond the slip flow and to the transition regime applications. Evidently, a suitable extension would accurately predict both the local velocity profiles and the mass flow rate magnitude as well as the streamwise pressure distribution. The second-order slip velocity model derived from kinetic theory can provide relatively accurate velocity profiles up to a Knudsen (Kn) number of around 0.5; however, its... 

The current study aims at introducing a 2D and fast-running code for the issues pertinent to design, analysis and safety in modular high temperature reactors. While the porous media approach is only applied to pebble bed type, the analysis in this paper covers both pebble bed and prismatic reactor. A time-dependent mass equation along with energy conservation equation for the cooling gas and a time-dependent energy conservation equation for the solid was solved. Appropriate series of constitutive equations (e.g. heat transfer coefficient, effective heat conductivity of solid, heat transfer coefficient, pressure drop etc.) has been recruited as well. In addition a finite-volume method is... 

Pretrained representations have recently gained attention in various machine learning applications. Nonetheless, the high computational costs associated with training these models have motivated alternative approaches for representation learning. Herein we introduce TripletProt, a new approach for protein representation learning based on the Siamese neural networks. Representation learning of biological entities which capture essential features can alleviate many of the challenges associated with supervised learning in bioinformatics. The most important distinction of our proposed method is relying on the protein-protein interaction (PPI) network. The computational cost of the generated...