Using time and stochastic models for software reliability forecasting and analysis

Tämä työ luo katsauksen ajallisiin ja stokastisiin ohjelmien luotettavuus malleihin sekä tutkii muutamia malleja käytännössä. Työn teoriaosuus sisältää ohjelmien luotettavuuden kuvauksessa ja arvioinnissa käytetyt keskeiset määritelmät ja metriikan sekä varsinaiset mallien kuvaukset. Työssä esitellään kaksi ohjelmien luotettavuusryhmää. Ensimmäinen ryhmä ovat riskiin perustuvat mallit. Toinen ryhmä käsittää virheiden ”kylvöön” ja merkitsevyyteen perustuvat mallit. Työn empiirinen osa sisältää kokeiden kuvaukset ja tulokset. Kokeet suoritettiin käyttämällä kolmea ensimmäiseen ryhmään kuuluvaa mallia: Jelinski-Moranda mallia, ensimmäistä geometrista mallia sekä yksinkertaista eksponenttimallia. Kokeiden tarkoituksena oli tutkia, kuinka syötetyn datan distribuutio vaikuttaa mallien toimivuuteen sekä kuinka herkkiä mallit ovat syötetyn datan määrän muutoksille. Jelinski-Moranda malli osoittautui herkimmäksi distribuutiolle konvergaatio-ongelmien vuoksi, ensimmäinen geometrinen malli herkimmäksi datan määrän muutoksille.

Anticipating linear stochastic differential equations driven by a Lévy process

In this paper we study the existence of a unique solution for linear stochastic differential equations driven by a Lévy process, where the initial condition and the coefficients are random and not necessarily adapted to the underlying filtration. Towards this end, we extend the method based on Girsanov transformations on Wiener space and developped by Buckdahn [7] to the canonical Lévy space, which is introduced in [25].

INCLUDING RISK IN ECONOMIC FEASIBILITY ANALYSIS:A STOCHASTIC SIMULATION MODEL FOR BLUEBERRY INVESTMENT DECISIONS IN CHILE

ABSTRACT The traditional method of net present value (NPV) to analyze the economic profitability of an investment (based on a deterministic approach) does not adequately represent the implicit risk associated with different but correlated input variables. Using a stochastic simulation approach for evaluating the profitability of blueberry (Vaccinium corymbosum L.) production in Chile, the objective of this study is to illustrate the complexity of including risk in economic feasibility analysis when the project is subject to several but correlated risks. The results of the simulation analysis suggest that the non-inclusion of the intratemporal correlation between input variables underestimate the risk associated with investment decisions. The methodological contribution of this study illustrates the complexity of the interrelationships between uncertain variables and their impact on the convenience of carrying out this type of business in Chile. The steps for the analysis of economic viability were: First, adjusted probability distributions for stochastic input variables (SIV) were simulated and validated. Second, the random values of SIV were used to calculate random values of variables such as production, revenues, costs, depreciation, taxes and net cash flows. Third, the complete stochastic model was simulated with 10,000 iterations using random values for SIV. This result gave information to estimate the probability distributions of the stochastic output variables (SOV) such as the net present value, internal rate of return, value at risk, average cost of production, contribution margin and return on capital. Fourth, the complete stochastic model simulation results were used to analyze alternative scenarios and provide the results to decision makers in the form of probabilities, probability distributions, and for the SOV probabilistic forecasts. The main conclusion shown that this project is a profitable alternative investment in fruit trees in Chile.

Asymmetric stochastic switching driven by intrinsic molecular noise

Low-copy-number molecules are involved in many functions in cells. The intrinsic fluctuations of these numbers can enable stochastic switching between multiple steady states, inducing phenotypic variability. Herein we present a theoretical and computational study based on Master Equations and Fokker-Planck and Langevin descriptions of stochastic switching for a genetic circuit of autoactivation. We show that in this circuit the intrinsic fluctuations arising from low-copy numbers, which are inherently state-dependent, drive asymmetric switching. These theoretical results are consistent with experimental data that have been reported for the bistable system of the gallactose signaling network in yeast. Our study unravels that intrinsic fluctuations, while not required to describe bistability, are fundamental to understand stochastic switching and the dynamical relative stability of multiple states.

Monotonic continuous-time random walks with drift and stochastic reset events

In this paper we consider a stochastic process that may experience random reset events which suddenly bring the system to the starting value and analyze the relevant statistical magnitudes. We focus our attention on monotonic continuous-time random walks with a constant drift: The process increases between the reset events, either by the effect of the random jumps, or by the action of the deterministic drift. As a result of all these combined factors interesting properties emerge, like the existence (for any drift strength) of a stationary transition probability density function, or the faculty of the model to reproduce power-law-like behavior. General formulas for two extreme statistics, the survival probability, and the mean exit time, are also derived. To corroborate in an independent way the results of the paper, Monte Carlo methods were used. These numerical estimations are in full agreement with the analytical predictions.

Panel Data Stochastic Convergence Analysis of the Mexican Regions

The stochastic convergence amongst Mexican Federal entities is analyzed in panel data framework. The joint consideration of cross-section dependence and multiple structural breaks is required to ensure that the statistical inference is based on statistics with good statistical properties. Once these features are accounted for, evidence in favour of stochastic convergence is found. Since stochastic convergence is a necessary, yet insufficient condition for convergence as predicted by economic growth models, the paper also investigates whether-convergence process has taken place. We found that the Mexican states have followed either heterogeneous convergence patterns or divergence process throughout the analyzed period.

Asymptotic analysis of stock price densities and implied volatilities in mixed stochastic models

In this paper, we obtain sharp asymptotic formulas with error estimates for the Mellin con- volution of functions de ned on (0;1), and use these formulas to characterize the asymptotic behavior of marginal distribution densities of stock price processes in mixed stochastic models. Special examples of mixed models are jump-di usion models and stochastic volatility models with jumps. We apply our general results to the Heston model with double exponential jumps, and make a detailed analysis of the asymptotic behavior of the stock price density, the call option pricing function, and the implied volatility in this model. We also obtain similar results for the Heston model with jumps distributed according to the NIG law.

Performance Improvement of Centrifugal Compressor Stage with Pinched Geometry or Vaned Diffuser

Centrifugal compressors are widely used for example in refrigeration processes, the oil and gas industry, superchargers, and waste water treatment. In this work, five different vaneless diffusers and six different vaned diffusers are investigated numerically. The vaneless diffusers vary only by their diffuser width, so that four of the geometries have pinch implemented to them. Pinch means a decrease in the diffuser width. Four of the vaned diffusers have the same vane turning angle and a different number of vanes, and two have different vane turning angles. The flow solver used to solve the flow fields is Finflo, which is a Navier-Stokes solver. All the cases are modeled with the Chien's k – έ- turbulence model, and selected cases are modeled also with the k – ώ-SST turbulence model. All five vaneless diffusers and three vaned diffusers are investigated also experimentally. For each construction, the compressor operating map is measured according to relevant standards. In addition to this, the flow fields before and after the diffuser are measured with static and total pressure, flow angle and total temperature measurements. When comparing the computational results to the measured results, it is evident that the k – ώ-SST turbulence model predicts the flow fields better. The simulation results indicate that it is possible to improve the efficiency with the pinch, and according to the numerical results, the two best geometries are the ones with most pinch at the shroud. These geometries have approximately 4 percentage points higher efficiency than the unpinched vaneless diffusers. The hub pinch does not seem to have any major benefits. In general, the pinches make the flow fields before and after the diffuser more uniform. The pinch also seems to improve the impeller efficiency. This is down to two reasons. The major reason is that the pinch decreases the size of slow flow and possible backflow region located near the shroud after the impeller. Secondly, the pinches decrease the flow velocity in the tip clearance, leading to a smaller tip leakage flow and therefore slightly better impeller efficiency. Also some of the vaned diffusers improve the efficiency, the increment being 1...3 percentage points, when compared to the vaneless unpinched geometry. The measurement results confirm that the pinch is beneficial to the performance of the compressor. The flow fields are more uniform with the pinched cases, and the slow flow regions are smaller. The peak efficiency is approximately 2 percentage points and the design point efficiency approximately 4 percentage points higher with the pinched geometries than with the un- pinched geometry. According to the measurements, the two best geometries are the ones with the most pinch at the shroud, the case with the pinch only at the shroud being slightly better of the two. The vaned diffusers also have better efficiency than the vaneless unpinched geometries. However, the pinched cases have even better efficiencies. The vaned diffusers narrow the operating range considerably, whilst the pinch has no significant effect on the operating range.

Heteropentámeros (etanol)4-agua: estudio estructural y termodinámico

Stochastic exploration of the potential energy surface of (ethanol)4-water heteropentamers through simulated annealing calculations was used to find probable structures of these clusters. Subsequent geometry optimization with the B3LYP/6-31+G(d) approach of these initial structures led to 13 stable heteropentamers. The strength of the hydrogen bonds of the type O"H-O (primary) and their spatial arrangements seem to be responsible for the geometric preferences and the high stability of these heteropentamers. This result is a consequence of the presence of the cooperative effects among such interactions. There is no significant influence of the secondary hydrogen bonds (C"H-O) on the stability of the heteropentamers.

PRACTICAL STOCHASTIC MODEL FOR CHEMICAL KINETICS

The Practical Stochastic Model is a simple and robust method to describe coupled chemical reactions. The connection between this stochastic method and a deterministic method was initially established to understand how the parameters and variables that describe the concentration in both methods were related. It was necessary to define two main concepts to make this connection: the filling of compartments or dilutions and the rate of reaction enhancement. The parameters, variables, and the time of the stochastic methods were scaled with the size of the compartment and were compared with a deterministic method. The deterministic approach was employed as an initial reference to achieve a consistent stochastic result. Finally, an independent robust stochastic method was obtained. This method could be compared with the Stochastic Simulation Algorithm developed by Gillespie, 1977. The Practical Stochastic Model produced absolute values that were essential to describe non-linear chemical reactions with a simple structure, and allowed for a correct description of the chemical kinetics.