Sharif Digital Repository

Stochastic activity networks (SANs) are a powerful and flexible extension of Petri nets. Modeling and analysis with Petri nets and their extensions need a software tool to help to construct and analyze the models. The original definition of SANs has been used as a modeling formalism in several tools. In this paper, we introduce a modeling tool called SharifSAN, which is based on a new definition of SANs. This modeling tool is useful for both the verification and performance evaluation of systems. The functional aspects of a system are verified by model checking branching temporal logic formulas, whereas its performance aspects are evaluated using some analytic and simulative methods. The... 

Stochastic Activity Networks (SANs) are a stochastic generalization of Petri nets which have been defined for the modeling and analysis of distributed real-time systems. In this paper, a new definiton for these models is presented. This definition is based on a unified view of the system in three settings: nondeterministic, probabilistic and stochastic. Some general properties of these models are also investigated  

Using the cross-correlation of the wavelet transformation, we propose a general method of studying the scale dependence of the direction of coupling for coupled time series. The method is first demonstrated by applying it to coupled van der Pol forced oscillators and coupled nonlinear stochastic equations. We then apply the method to the analysis of the log-return time series of the stock values of the IBM and General Electric (GE) companies. Our analysis indicates that, on average, IBM stocks react earlier to possible common sector price movements than those of GE  

Jumps are discontinuous variations in time series and one expects that the higher jump activity will cause higher uncertainty in the stochastic behavior of measured time series. Here we study jump events in beat-to-beat fluctuations in the heart rates of healthy subjects, as well as those with congestive heart failure (CHF). The analysis shows that the interbeat time series belong to the class of non-continuous stochastic processes. The estimated drift and diffusion coefficients and jump characteristics of healthy and CHF subjects reveal the distinguishability of two subjects. © 2019 IOP Publishing Ltd and SISSA Medialab srl  

In this research, nickel thin films have been deposited on Si (1 0 0) substrate using the dc sputtering method. Then, the deposited layers were annealed in different temperatures to oxidize and crystallize the as prepared layers. Scanning electron microscopy (SEM) analysis indicated that the nanorod shape of the nickel oxides has grown on the substrate and x-ray photoelectron spectroscopy determined the formation of stoichiometric NiO on the surface. Field emission (FE) measurements of the NiO nanorods exhibited the lowest turn-on electric field at about 3.8 V μm-1 in the 300 μm vacuum gap. Moreover, the field enhancement factor (β) was measured of about 4109 for this sample. The FE... 

We introduce a method by which stochastic processes are mapped onto complex networks. As examples, we construct the networks for such time series as those for free-jet and low-temperature helium turbulence, the German stock market index (the DAX), and white noise. The networks are further studied by contrasting their geometrical properties, such as the mean length, diameter, clustering, and average number of connections per node. By comparing the network properties of the original time series investigated with those for the shuffled and surrogate series, we are able to quantify the effect of the long-range correlations and the fatness of the probability distribution functions of the series... 

Urban rail planning is extremely complex, mainly because it is a decision problem under different uncertainties. In practice, travel demand is generally uncertain, and therefore, the timetabling decisions must be based on accurate estimation. This research addresses the optimization of train timetable at public transit terminals of an urban rail in a stochastic setting. To cope with stochastic fluctuation of arrival rates, a two-stage stochastic programming model is developed. The objective is to construct a daily train schedule that minimizes the expected waiting time of passengers. Due to the high computational cost of evaluating the expected value objective, the sample average... 

Analysis of flow in fluidized beds, a common chemical reactor, is of much current interest due to its fundamental as well as industrial importance. Experimental data for the successive increments of the pressure fluctuations time series in a fluidized bed are analyzed by computing a multiscale probability density function (PDF) of the increments. The results demonstrate the evolution of the shape of the PDF from the short to long time scales. The deformation of the PDF across time scales may be modeled by the log-normal cascade model. The results are also in contrast to the previously proposed PDFs for the pressure fluctuations that include a Gaussian distribution and a PDF with a power-law... 

We employ the horizontal visibility algorithm to map the velocity and acceleration time series in turbulent flows with different Reynolds numbers, onto complex networks. The universal nature of velocity fluctuations in high Reynolds turbulent Helium flow is found to be inherited in the corresponding network topology. The degree distributions of the acceleration series are shown to have stretched exponential forms with the Reynolds number dependent fitting parameter. Furthermore, for acceleration time series, we find a transitional behavior in terms of the Reynolds number in all network features which is in agreement with recent empirical studies  

Social networks are getting closer to our real physical world. People share the exact location and time of their check-ins and are influenced by their friends. Modeling the spatio-temporal behavior of users in social networks is of great importance for predicting the future behavior of users, controlling the users’ movements, and finding the latent influence network. It is observed that users have periodic patterns in their movements. Also, they are influenced by the locations that their close friends recently visited. Leveraging these two observations, we propose a probabilistic model based on a doubly stochastic point process with a periodic-decaying kernel for the time of check-ins and a... 

Random decision making in genetic switches can be modeled as tossing a biased coin. In other word, each genetic switch can be considered as a game in which the reactive elements compete with each other to increase their molecular concentrations. The existence of a very small number of reactive element molecules has caused the neglect of effects of noise to be inevitable. Noise can lead to undesirable cell fate in cellular differentiation processes. In this paper, we study the robustness to noise in genetic switches by considering another switch to have a new gene regulatory network (GRN) in which both switches have been affected by the same noise and for this purpose, we will use Parrondo's... 

In this paper, we investigate the statistical and scaling properties of the California earthquakes' inter-events over a period of the recent 40 years. To detect long-term correlations behavior, we apply detrended fluctuation analysis (DFA), which can systematically detect and overcome nonstationarities in the data set at all time scales. We calculate for various earthquakes with magnitudes larger than a given M. The results indicate that the Hurst exponent decreases with increasing M; characterized by a Hurst exponent, which is given by, H = 0:34 + 1:53/M, indicating that for events with very large magnitudes M, the Hurst exponent decreases to 0:50, which is for independent events. © Versita... 

The substantial presence of different uncertainties in energy systems highlights the need for probabilistic analysis of operational and planning studies. Motivated by this fact, a new stochastic planning framework for energy hubs (EHs) is presented in this study based on the probability transformation concept. In the proposed framework, a measure of relative-likelihood impact is developed to estimate the importance of uncertainty sources in the studies, which, in turn, can remarkably reduce the overall complexity of stochastic problems. Step-by-step algorithm for implementation of the proposed framework on planning studies of an EH is also addressed in this study. Three different case... 

We have investigated different algorithms for the simulation of kinetics of small systems. We have simulated the first order reversible reaction with the Gillespie, Gibson and Brack time simulation as a function of Poisson distribution and compared the results of three algorithms. We have also simulated intracellular viral kinetics for a genome with Gillespie and Poisson distribution algorithms  

In this paper, we consider acyclic networks of queues as a model to support the design of a dynamic production system. Each service station in the network represents a manufacturing or assembly operation. Only one type of product is produced by the system, but there exist several distinct production processes for manufacturing this product, each one corresponding with a directed path in the network of queues. In each network node, the number of servers in the corresponding service station is either one or infinity. The service time in each station is either exponentially distributed or belongs to a special class of Coxian distribution. Only in the source node, the service system may be... 

A limiting problem for a stochastic evolution equation is studied in the paper. In the equation, the linear operator is non-positive with a pure point spectrum, the non-linearity is monotone, and the Brownian motion is cylindrical. It is shown that, in the limit, the mild solution to the evolution equation tends to the solution of an ordinary Ito equation. Copyright © Taylor & Francis, Inc  

Voltage sags, also known as dips, are important to industrial reliability. This paper presents a Monte Carlo based approach to evaluate the maximum voltage sag magnitudes as well as the voltage unbalance ratio in transmission systems. In this context, investigations have been conducted on a system model taking into consideration the uncertainty in several factors associated with the practical operation of a power system. MATLAB is used in the simulation studies. © 2003 IEEE  

In this paper, we apply the stochastic dynamic programming to find the dynamic shortest path from the source node to the sink node in stochastic dynamic networks, in which the arc lengths are independent random variables with exponential distributions. In each node there is an environmental variable, which evolves in accordance with a continuous time Markov process. The parameter of the exponential distribution of the transition time of each arc is also a function of the state of the environmental variable of its initiative node. Upon arriving at each node, we can move toward the sink node through the best outgoing arc or wait. At the beginning, it is assumed that upon arriving at each node,... 

We prove an inequality for the pth power of the norm of a stochastic convolution integral in a Hilbert space. The inequality is stronger than analogous inequalities in the literature in the sense that it is pathwise and not in expectation  

Semilinear stochastic evolution equations with multiplicative Poisson noise and monotone nonlinear drift in Hilbert spaces are considered. The coefficients are assumed to have linear growth. We do not impose coercivity conditions on coefficients. A novel method of proof for establishing existence and uniqueness of the mild solution is proposed. Examples on stochastic partial differential equations and stochastic delay differential equations are provided to demonstrate the theory developed. © 2017 Iranian Mathematical Society