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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  

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,... 

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 high-integrity systems, certain quality requirements have gained utmost significance in such a way that failing to satisfy them at a particular level may result in the loss of the entire system, endangerment of human life, peril to the organization's existence, or serious damage to the environment. High-integrity computer systems should incorporate top-quality software in order to adequately address their stringent quality requirements. The methodologies used for developing high-integrity software must possess special characteristics in order to ensure successful realization of the requirements. Software Process patterns represent empirically proven methods of software development that... 

A Real-Time Optimization (RTO) strategy incorporating the fuzzy sets theory is developed, where the problem constraints obtained from process considerations are treated in fuzzy environment. Furthermore, the objective function is penalized by a fuzzified form of the key process constraints. To enable using conventional optimization techniques, the resulting fuzzy optimization problem is then reformulated into a crisp programming problem. The crisp programming problem is solved using both Sequential Quadratic Programming (SQP) and Heuristic Random Optimization (HRO) techniques for comparison purposes. The proposed fuzzy RTO strategy is demonstrated via the Tennessee Eastman benchmark process,... 

In this paper, an integrated software environment is demonstrated for computational simulation of powder forming processes. The powder compaction software, PCS_SUT, is designed in both popularity and functionality with the development of user-friendly pre- and post-processing software. Pre-processing software is used to create the model, generate an appropriate finite element grid, apply the appropriate boundary conditions, and view the total model. Post-processing provides visualization of the computed results. In PCS_SUT, a numerical model is developed based on a Lagrangian finite element formulation for large deformations, a cap plasticity theory for non-linear behaviour of material, and... 

As product complexity increases and economic constraints result in a demand for greater efficiency, industry must invest in new innovative ways to assist design and manufacture. As a first step in the long-term development of such a system, a computer software environment has been developed for pre- and post-processing for unstructured grid-based computational simulation. This paper describes the powder compaction software (PCS_SUT), which is designed for pre- and post-processing for computational simulation of the compaction of powder. Pre-processing software is used to create the model, generate an appropriate finite element grid, apply the appropriate boundary conditions, and view the... 

Using the Markovian method, we study the stochastic nature of electrical discharge current fluctuations in the Helium plasma. Sinusoidal trends are extracted from the data set by the Fourier-Detrended Fluctuation analysis and consequently cleaned data is retrieved. We determine the Markov time scale of the detrended data set by using likelihood analysis. We also estimate the Kramers-Moyal's coefficients of the discharge current fluctuations and derive the corresponding Fokker-Planck equation. In addition, the obtained Langevin equation enables us to reconstruct discharge time series with similar statistical properties compared with the observed in the experiment. We also provide an exact... 

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... 

Pseudomonas aeoroginosa B-3556 was grown on soy flour based semi-solid media for lipase production. The effect of different factors including medium composition, pH, temperature, mixing intensity and substrate particle size on lipase productivity was analyzed using the Taguchi method in three steps. Based on these analyses the optimum concentrations of soy flour, (NH4)2HPO4, K2HPO4 and MgSO4.7H2O were found be 3%, 3%, 0.5% and 0.21% respectively. Furthermore, optimum values for temperature, pH and the shaking speed were determined as 30°C, 7.1 and 150 rpm. As for the substrate particle size, the best result was achieved when the soy flour had a mesh size cut of 60-70. The influence of the... 

In this paper, a new on-line handwritten signature verification system using Hidden Markov Model (HMM) is presented. The proposed system segments each signature based on its perceptually important points and then computes for each segment a number of features that are scale and displacement invariant. The resulted sequence is then used for training an HMM to achieve signature verification. Our database includes 622 genuine signatures and 1010 forgery signatures that were collected from a population of 69 human subjects. Our verification system has achieved a false acceptance rate (FAR) of 4% and a false rejection rate (FRR) of 12%. © 2003 IEEE  

Business process reengineering (BPR) can help organisations to identify and improve their business processes. A major problem is the high volume of business process datasets with characteristics such as high dimensionality, noise, uncertainty in process datasets and complicated interactions among process variables. Data mining (DM) techniques facilitate the identification and analysis of business processes, and improve their performance by extracting the hidden knowledge in business process datasets. In this paper, we present the application of DM to BPR, based on two novel approaches. By a literature review, the first approach proposes DMbBPR model, mainly focuses on the applications of... 

In this chapter we present three examples of the Langevin dynamics, namely, the Anderson–Kubo, Ornstein–Uhlenbeck, and Black–Scholes processes. We will use the Itô interpretation that provides us with a powerful tool for dealing with such linear and nonlinear stochastic processes analytically. © 2019, Springer Nature Switzerland AG  

In this chapter we provide mathematical tools to study the stochastic process from the physical point of view. © 2019, Springer Nature Switzerland AG  

In this chapter we present three examples of the Langevin dynamics, namely, the Anderson–Kubo, Ornstein–Uhlenbeck, and Black–Scholes processes. We will use the Itô interpretation that provides us with a powerful tool for dealing with such linear and nonlinear stochastic processes analytically. © 2019, Springer Nature Switzerland AG  

In this chapter we provide mathematical tools to study the stochastic process from the physical point of view. © 2019, Springer Nature Switzerland AG  

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... 

Process-centered Software Engineering Environments, or PSEEs, are intended for the definition, modification, and enactment of software process models, they thus bring software development processes into effect. Even though research efforts in process-centered software engineering abound, PSEE technology has not received the attention that it deserves. In order to create a concise but effective and practically applicable evaluation framework for PSEEs, this paper first presents a survey of PSEEs and highlights the current state of the art of the technology. The PSEEs which have been reviewed herein have been regarded as software systems, and as such, have been characterized in terms of their...