Sharif Digital Repository

We have derived an analytical equation of state (EOS) based on the soft-core statistical mechanical perturbation theory for fluids, using the Weeks-Chandler-Andersen (WCA) theory recently developed by Ben-Amotz-Stell (BAS) for the choice of the hard-sphere diameter, but with a new algorithm for calculation of the pair and many-body interactions. We have used Carnahan-Starling expression with the Boltzmann factor criterion (BFC) as an effective hard-sphere diameter for the reference system, and also decomposed the perturbed pair potential to symmetric and asymmetric terms. The former term is due to the many-body interactions at high densities as was used in the linear isotherm regularity... 

Weibull distributions play an important role in reliability studies and have many applications in engineering. It normally appears in the statistical scripts as having two parameters, making it easy to estimate its parameters. However, once you go beyond the two parameter distribution, things become complicated. For example, estimating the parameters of a three-parameter Weibull distribution has historically been a complicated and sometimes contentious line of research since classical estimation procedures such as Maximum Likelihood Estimation (MLE) have become almost too complicated to implement. In this paper, we will discuss an approach that takes advantage of Artificial Neural Networks... 

We present a model of fractures based on the idea that the elastic free energy due to the fracture density follows a Boltzmann distribution. The resulting expression for the spatial correlation in the displacement of fractures is used as an objective function in a simulated annealing algorithm to generate realizations of correlated fracture networks. This approach determines the appropriate statistical distribution for the fractures (e.g., length distribution) rather than imposing them as is done conventionally. The model consists of two families of parallel fractures which are perpendicular under isotropic conditions. There also exists a positive correlation between the position of... 

The absolute free energy of solvation of methane (CH4) and its fluorinated forms (CH3F, CH2F2, CHF3 and CF4) have been computed via statistical perturbation theory (SPT) in the NPT ensemble at four thermodynamical states (whitin liquid and supercritical regions), in the context of Monte Carlo Simulations. Thermodynamical interpretation of the observed trend in the absolute free energy of solvation in different states reveals an exothermic solvation with ΔSslv < 0 (entropically unfavorable solvation) that the intermolecular interactions play an important role in the solvation process. The fluorinated methanes are confirmed to control the mutual arrangement of neighboring CO2 molecules and the... 

Grammar induction, also known as grammar inference, is one of the most important research areas in the domain of natural language processing. Availability of large corpora has encouraged many researchers to use statistical methods for grammar induction. This problem can be divided into three different categories of supervised, semi-supervised, and unsupervised, based on type of the required data set for the training phase. Most current inductive methods are supervised, which need a bracketed data set for their training phase; but the lack of this kind of data set in many languages, encouraged us to focus on unsupervised approaches. Here, we introduce a novel approach, which we call... 

The change of gait pattern and muscular activity following amputation is thought to be responsible for the higher incidence of joint degenerative disorders observed in amputees. Considering the lack of consistent data in the literature, the purpose of the present study was to measure and analyze the spatio-temporal variables, the kinematics and, particularly, the net joint moments of the intact and prosthetic limbs of above knee amputee subjects during walking and to compare the results with those of normals. The gait characteristics of five transfemoral amputees and five normal subjects were measured using videography and a force platform. The human body was modeled as a 2-D sagittal plane... 

This paper presents a scalp electroencephalogram (EEG) rhythmic pattern detection scheme based on neural networks. Rhythmic discharges detection is applicable to the majority of seizures seen in newborns, and is listed as detecting 90% of all the seizures. In this approach some features based on various methods are extracted and compared by a modified multilayer neural network in order to find rhythmic discharges. Statistical performance comparison with seizure detection schemes of Gotman et al. and Liu et al. is performed. © 2006 IEEE  

In this paper a new approach to accurately classify ECG arrhythmias through a combination of the wavelet transform and artificial neural network is presented. Three kinds of features in a very computationally efficient manner are computed as follows: 1-Joint time-frequency features (discrete wavelet transform coefficients). 2-Time domain features (R-R intervals). 3-Statistical feature (form factor). Using these features, the limitations of other methods in classifying multiple kinds of arrhythmia with high accuracy for all of them at once are overcome. Finally, a cascade classifier including two ANNs has been designed. Considering the whole MIT-BIH arrhythmia database, 10 kinds of arrhythmia... 

Stochastic behavior of panels in supersonic flow is investigated to assess the significance of including the damping caused by the strains resulting from axial extension of the panel. The governing equations of motion are based on the Von Karman's large deflection equation and are considered with Kelvin's model of structural damping. The panel under study is two dimensional and simply supported for which the first order piston theory is used to account for the unsteady aerodynamic loading. Transformation of the governing partial differential equation to a set of ordinary differential equations is performed through the Galerkin averaging technique. The statistical response moment equations... 

In many applications, the requirements of static data and large computation times are still major concerns. This paper presents a practical equivalent model of a small area in a large scale system which needs less statistical data of system equipments with acceptable level of accuracy. The proposed technique is designated as the Branch-Cutting Method in which tie lines between the area of interest (AI) and the other parts of the network are cut and the network behavior is modeled with some load and generating units in marginal load points. The load at marginal load points is represented as a multi state load model with the associated state probability. Load uncertainty is modeled using the... 

This paper investigates the problem of maneuvering target tracking by using hybrid (intelligent/classical) methods. The adaptive capability of filters is known to be increased by incorporating a neural network into the filtering procedure. The proposed algorithm is implemented with two second-order Gaussian filters based on the current statistical model and a multilayer feedforward neural network. The two filters, which use the noise corrupted measurements of the target line of sight (LOS) angle, track the same maneuvering target in parallel. The neural network automatically considers all the state information of the two filters and adaptively adjusts the process variance of one of them to... 

Although the prevention of Distributed Denial of Service (DDoS) attacks is not possible, detection of such attacks plays main role in preventing their progress. In the flooding attacks, especially new sophisticated DDoS, the attacker floods the network traffic toward the target computer by sending pseudo-normal packets. Therefore, multi-purpose IDSs do not offer a good performance (and accuracy) in detecting such kinds of attacks. In this paper, a novel method for detection of DDoS attacks has been introduced based on a statistical pre-processor and an unsupervised artificial neural net. In addition, SPUNNID system has been designed based on the proposed method. The statistical... 

Screening analysis is a useful guideline that helps us with proper field selection for different enhanced oil recovery processes. In this work, reservoir simulation is combined with experimental design to estimate the effect of reservoir rock and fluid properties on performance of immiscible nitrogen injection. Reservoir dip, thickness, and horizontal permeability are found to be the most influential parameters. Possible interactions of parameters are also discussed to increase reliability and robustness of screening results. Finally, significance of both main effects and interactions are evaluated by employing a statistical inference approach (hypothesis testing) and results are compared to... 

Most of industrial applications of statistical process control involve more than one quality characteristics to be monitored. These characteristics are usually correlated, causing challenges for the monitoring methods. These challenges are resolved using multivariate quality control charts that have been widely developed in recent years. Nonetheless, multivariate process monitoring methods encounter a problem when the quality characteristics are of the attribute type and follow nonnormal distributions such as multivariate binomial or multivariate Poisson. Since the data analysis in the latter case is not as easy as the normal case, more complexities are involved to monitor multiattribute... 

Functional quality in the mechanical products is governed mainly by the degree of satisfaction of the design requirements, which itself depends on the variations in the effective variables. The functional parameters cannot be easily measured in mass production, and thus, are not usually considered as a direct inspection objective. Process capability indices are useful tools for evaluating the ability of a process to produce the dependent variables of a product that meet certain specifications. In this paper, the conventional process capability concept is extended to develop a computational tool for analysis of the functional quality of a mechanical product. Through defining new proper... 

Ubiquitous power-law as a fingerprint of Self-Organized Criticality (SOC) is used for describing catastrophic events in different fields. In this paper, by investigating the prerequisites of SOC, we show that SOC-like dynamics drive a correlation among disturbances in Iranian bulk power systems. The existence of power-law regions in probability distribution is discussed for empirical data using maximum likelihood estimation. To verify the results, long time correlation is evaluated in terms of Hurst exponents, by means of statistical analysis of time series, including Rescaled Range (R/S) and Scaled Windowed Variance (SWV) analysis. Also, sensitivity analysis showed that for correct...