Stochastic beam dynamics in storage rings
International Nuclear Information System (INIS)
Pauluhn, A.
1993-12-01
In this thesis several approaches to stochastic dynamics in storage rings are investigated. In the first part the theory of stochastic differential equations and Fokker-Planck equations is used to describe the processes which have been assumed to be Markov processes. The mathematical theory of Markov processes is well known. Nevertheless, analytical solutions can be found only in special cases and numerical algorithms are required. Several numerical integration schemes for stochastic differential equations will therefore be tested in analytical solvable examples and then applied to examples from accelerator physics. In particular the stochastically perturbed synchrotron motion is treated. For the special case of a double rf system several perturbation theoretical methods for deriving the Fokker-Planck equation in the action variable are used and compared with numerical results. The second part is concerned with the dynamics of electron storage rings. Due to the synchrotron radiation the electron motion is influenced by damping and exciting forces. An algorithm for the computation of the density function in the phase space of such a dissipative stochastically excited system is introduced. The density function contains all information of a process, e.g. it determines the beam dimensions and the lifetime of a stored electron beam. The new algorithm consists in calculating a time propagator for the density function. By means of this propagator the time evolution of the density is modelled very computing time efficient. The method is applied to simple models of the beam-beam interaction (one-dimensional, round beams) and the results of the density calculations are compared with results obtained from multiparticle tracking. Furthermore some modifications of the algorithm are introduced to improve its efficiency concerning computing time and storage requirements. Finally, extensions to two-dimensional beam-beam models are described. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Ramirez, A; Mcnab, W; Hao, Y; White, D; Johnson, J
2011-04-14
During the last months of this project, our project activities have concentrated on four areas: (1) performing a stochastic inversion of pattern 16 seismic data to deduce reservoir bulk/shear moduli and density; the need for this inversion was not anticipated in the original scope of work, (2) performing a stochastic inversion of pattern 16 seismic data to deduce reservoir porosity and permeability, (3) complete the software needed to perform geochemical inversions and (4) use the software to perform stochastic inversion of aqueous chemistry data to deduce mineral volume fractions. This report builds on work described in progress reports previously submitted (Ramirez et al., 2009, 2010, 2011 - reports fulfilled the requirements of deliverables D1-D4) and fulfills deliverable D5: Field-based single-pattern simulations work product. The main challenge with our stochastic inversion approach is its large computational expense, even for single reservoir patterns. We dedicated a significant level of effort to improve computational efficiency but inversions involving multiple patterns were still intractable by project's end. As a result, we were unable to fulfill Deliverable D6: Field-based multi-pattern simulations work product.
Stochastic volatility of volatility in continuous time
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole; Veraart, Almut
This paper introduces the concept of stochastic volatility of volatility in continuous time and, hence, extends standard stochastic volatility (SV) models to allow for an additional source of randomness associated with greater variability in the data. We discuss how stochastic volatility...... of volatility can be defined both non-parametrically, where we link it to the quadratic variation of the stochastic variance process, and parametrically, where we propose two new SV models which allow for stochastic volatility of volatility. In addition, we show that volatility of volatility can be estimated...
Space-time-modulated stochastic processes
Giona, Massimiliano
2017-10-01
Starting from the physical problem associated with the Lorentzian transformation of a Poisson-Kac process in inertial frames, the concept of space-time-modulated stochastic processes is introduced for processes possessing finite propagation velocity. This class of stochastic processes provides a two-way coupling between the stochastic perturbation acting on a physical observable and the evolution of the physical observable itself, which in turn influences the statistical properties of the stochastic perturbation during its evolution. The definition of space-time-modulated processes requires the introduction of two functions: a nonlinear amplitude modulation, controlling the intensity of the stochastic perturbation, and a time-horizon function, which modulates its statistical properties, providing irreducible feedback between the stochastic perturbation and the physical observable influenced by it. The latter property is the peculiar fingerprint of this class of models that makes them suitable for extension to generic curved-space times. Considering Poisson-Kac processes as prototypical examples of stochastic processes possessing finite propagation velocity, the balance equations for the probability density functions associated with their space-time modulations are derived. Several examples highlighting the peculiarities of space-time-modulated processes are thoroughly analyzed.
Electricity price modeling with stochastic time change
International Nuclear Information System (INIS)
Borovkova, Svetlana; Schmeck, Maren Diane
2017-01-01
In this paper, we develop a novel approach to electricity price modeling, based on the powerful technique of stochastic time change. This technique allows us to incorporate the characteristic features of electricity prices (such as seasonal volatility, time varying mean reversion and seasonally occurring price spikes) into the model in an elegant and economically justifiable way. The stochastic time change introduces stochastic as well as deterministic (e.g., seasonal) features in the price process' volatility and in the jump component. We specify the base process as a mean reverting jump diffusion and the time change as an absolutely continuous stochastic process with seasonal component. The activity rate of the stochastic time change can be related to the factors that influence supply and demand. Here we use the temperature as a proxy for the demand and hence, as the driving factor of the stochastic time change, and show that this choice leads to realistic price paths. We derive properties of the resulting price process and develop the model calibration procedure. We calibrate the model to the historical EEX power prices and apply it to generating realistic price paths by Monte Carlo simulations. We show that the simulated price process matches the distributional characteristics of the observed electricity prices in periods of both high and low demand. - Highlights: • We develop a novel approach to electricity price modeling, based on the powerful technique of stochastic time change. • We incorporate the characteristic features of electricity prices, such as seasonal volatility and spikes into the model. • We use the temperature as a proxy for the demand and hence, as the driving factor of the stochastic time change • We derive properties of the resulting price process and develop the model calibration procedure. • We calibrate the model to the historical EEX power prices and apply it to generating realistic price paths.
Stochastic Sizing of Energy Storage Systems for Wind Integration
Directory of Open Access Journals (Sweden)
D. D. Le
2018-06-01
Full Text Available In this paper, we present an optimal capacity decision model for energy storage systems (ESSs in combined operation with wind energy in power systems. We use a two-stage stochastic programming approach to take into account both wind and load uncertainties. The planning problem is formulated as an AC optimal power flow (OPF model with the objective of minimizing ESS installation cost and system operation cost. Stochastic wind and load inputs for the model are generated from historical data using clustering technique. The model is tested on the IEEE 39-bus system.
Stochastic space-time and quantum theory
International Nuclear Information System (INIS)
Frederick, C.
1976-01-01
Much of quantum mechanics may be derived if one adopts a very strong form of Mach's principle such that in the absence of mass, space-time becomes not flat, but stochastic. This is manifested in the metric tensor which is considered to be a collection of stochastic variables. The stochastic-metric assumption is sufficient to generate the spread of the wave packet in empty space. If one further notes that all observations of dynamical variables in the laboratory frame are contravariant components of tensors, and if one assumes that a Lagrangian can be constructed, then one can obtain an explanation of conjugate variables and also a derivation of the uncertainty principle. Finally the superposition of stochastic metrics and the identification of root -g in the four-dimensional invariant volume element root -g dV as the indicator of relative probability yields the phenomenon of interference as will be described for the two-slit experiment
Stochastic time scale for the Universe
International Nuclear Information System (INIS)
Szydlowski, M.; Golda, Z.
1986-01-01
An intrinsic time scale is naturally defined within stochastic gradient dynamical systems. It should be interpreted as a ''relaxation time'' to a local potential minimum after the system has been randomly perturbed. It is shown that for a flat Friedman-like cosmological model this time scale is of order of the age of the Universe. 7 refs. (author)
Importance Sampling for Stochastic Timed Automata
DEFF Research Database (Denmark)
Jegourel, Cyrille; Larsen, Kim Guldstrand; Legay, Axel
2016-01-01
We present an importance sampling framework that combines symbolic analysis and simulation to estimate the probability of rare reachability properties in stochastic timed automata. By means of symbolic exploration, our framework first identifies states that cannot reach the goal. A state-wise cha......We present an importance sampling framework that combines symbolic analysis and simulation to estimate the probability of rare reachability properties in stochastic timed automata. By means of symbolic exploration, our framework first identifies states that cannot reach the goal. A state...
Stochastic models for time series
Doukhan, Paul
2018-01-01
This book presents essential tools for modelling non-linear time series. The first part of the book describes the main standard tools of probability and statistics that directly apply to the time series context to obtain a wide range of modelling possibilities. Functional estimation and bootstrap are discussed, and stationarity is reviewed. The second part describes a number of tools from Gaussian chaos and proposes a tour of linear time series models. It goes on to address nonlinearity from polynomial or chaotic models for which explicit expansions are available, then turns to Markov and non-Markov linear models and discusses Bernoulli shifts time series models. Finally, the volume focuses on the limit theory, starting with the ergodic theorem, which is seen as the first step for statistics of time series. It defines the distributional range to obtain generic tools for limit theory under long or short-range dependences (LRD/SRD) and explains examples of LRD behaviours. More general techniques (central limit ...
Beam life-time with intrabeam scattering and stochastic cooling
International Nuclear Information System (INIS)
Wei, J.; Ruggiero, A.G.
1991-01-01
A transport equation has been derived in terms of the longitudinal action variable to describe the time evolution of the longitudinal density distribution of a bunched hadron beam in the presence of intrabeam scattering and stochastic cooling. A computer program has been developed to numerically solve this equation. Both beam loss and bunch-shape evolution have been investigated for the 197 Au 79+ beams during the 10-hour storage in the Relativistic Heavy Ion Collider currently under construction at the Brookhaven National Laboratory. 9 refs., 1 fig
Stochastic nature of series of waiting times
Anvari, Mehrnaz; Aghamohammadi, Cina; Dashti-Naserabadi, H.; Salehi, E.; Behjat, E.; Qorbani, M.; Khazaei Nezhad, M.; Zirak, M.; Hadjihosseini, Ali; Peinke, Joachim; Tabar, M. Reza Rahimi
2013-06-01
Although fluctuations in the waiting time series have been studied for a long time, some important issues such as its long-range memory and its stochastic features in the presence of nonstationarity have so far remained unstudied. Here we find that the “waiting times” series for a given increment level have long-range correlations with Hurst exponents belonging to the interval 1/2
Quantum mechanics, stochasticity and space-time
International Nuclear Information System (INIS)
Ramanathan, R.
1986-04-01
An extended and more rigorous version of a recent proposal for an objective stochastic formulation of quantum mechanics along with its extension to the relativistic case without spin is presented. The relativistic Klein-Gordon equation is shown to be a particular form of the relativistic Kolmogorov-Fokker-Planck equation which is derived from a covariant formulation of the Chapman-Kolmogorov condition. Complexification of probability amplitudes is again achieved only through a conformal rotation of Minkowski space-time M 4 . (author)
A compositional Translation of Stochastic Automata into Timed Automata
d' Argenio, P.R.
We present a translation from stochastic automata [17, 16] into timed automata with deadlines [37, 13]. The translation preserves traces when the stochastic characteristics, namely the probability measures, are abstracted from the original stochastic automaton. Moreover, we show that the translation
Reducing storage of global wind ensembles with stochastic generators
Jeong, Jaehong
2018-03-09
Wind has the potential to make a significant contribution to future energy resources. Locating the sources of this renewable energy on a global scale is however extremely challenging, given the difficulty to store very large data sets generated by modern computer models. We propose a statistical model that aims at reproducing the data-generating mechanism of an ensemble of runs via a Stochastic Generator (SG) of global annual wind data. We introduce an evolutionary spectrum approach with spatially varying parameters based on large-scale geographical descriptors such as altitude to better account for different regimes across the Earth’s orography. We consider a multi-step conditional likelihood approach to estimate the parameters that explicitly accounts for nonstationary features while also balancing memory storage and distributed computation. We apply the proposed model to more than 18 million points of yearly global wind speed. The proposed SG requires orders of magnitude less storage for generating surrogate ensemble members from wind than does creating additional wind fields from the climate model, even if an effective lossy data compression algorithm is applied to the simulation output.
Reducing storage of global wind ensembles with stochastic generators
Jeong, Jaehong; Castruccio, Stefano; Crippa, Paola; Genton, Marc G.
2018-01-01
Wind has the potential to make a significant contribution to future energy resources. Locating the sources of this renewable energy on a global scale is however extremely challenging, given the difficulty to store very large data sets generated by modern computer models. We propose a statistical model that aims at reproducing the data-generating mechanism of an ensemble of runs via a Stochastic Generator (SG) of global annual wind data. We introduce an evolutionary spectrum approach with spatially varying parameters based on large-scale geographical descriptors such as altitude to better account for different regimes across the Earth’s orography. We consider a multi-step conditional likelihood approach to estimate the parameters that explicitly accounts for nonstationary features while also balancing memory storage and distributed computation. We apply the proposed model to more than 18 million points of yearly global wind speed. The proposed SG requires orders of magnitude less storage for generating surrogate ensemble members from wind than does creating additional wind fields from the climate model, even if an effective lossy data compression algorithm is applied to the simulation output.
Vehicle routing with stochastic time-dependent travel times
Lecluyse, C.; Woensel, van T.; Peremans, H.
2009-01-01
Assigning and scheduling vehicle routes in a stochastic time-dependent environment is a crucial management problem. The assumption that in a real-life environment everything goes according to an a priori determined static schedule is unrealistic. Our methodology builds on earlier work in which the
Vehicle routing with stochastic time-dependent travel times
Lecluyse, C.; Woensel, van T.; Peremans, H.
2007-01-01
Assigning and scheduling vehicle routes in a stochastic time-dependent environment is a crucial management problem. The assumption that in a real-life environment everything goes according to an a priori determined static schedule is unrealistic. Our methodology builds on earlier work in which the
Stochastic first passage time accelerated with CUDA
Pierro, Vincenzo; Troiano, Luigi; Mejuto, Elena; Filatrella, Giovanni
2018-05-01
The numerical integration of stochastic trajectories to estimate the time to pass a threshold is an interesting physical quantity, for instance in Josephson junctions and atomic force microscopy, where the full trajectory is not accessible. We propose an algorithm suitable for efficient implementation on graphical processing unit in CUDA environment. The proposed approach for well balanced loads achieves almost perfect scaling with the number of available threads and processors, and allows an acceleration of about 400× with a GPU GTX980 respect to standard multicore CPU. This method allows with off the shell GPU to challenge problems that are otherwise prohibitive, as thermal activation in slowly tilted potentials. In particular, we demonstrate that it is possible to simulate the switching currents distributions of Josephson junctions in the timescale of actual experiments.
Multimodal Network Equilibrium with Stochastic Travel Times
Directory of Open Access Journals (Sweden)
M. Meng
2014-01-01
Full Text Available The private car, unlike public traffic modes (e.g., subway, trolley running along dedicated track-ways, is invariably subject to various uncertainties resulting in travel time variation. A multimodal network equilibrium model is formulated that explicitly considers stochastic link capacity variability in the road network. The travel time of combined-mode trips is accumulated based on the concept of the mean excess travel time (METT which is a summation of estimated buffer time and tardy time. The problem is characterized by an equivalent VI (variational inequality formulation where the mode choice is expressed in a hierarchical logit structure. Specifically, the supernetwork theory and expansion technique are used herein to represent the multimodal transportation network, which completely represents the combined-mode trips as constituting multiple modes within a trip. The method of successive weighted average is adopted for problem solutions. The model and solution method are further applied to study the trip distribution and METT variations caused by the different levels of the road conditions. Results of numerical examples show that travelers prefer to choose the combined travel mode as road capacity decreases. Travelers with different attitudes towards risk are shown to exhibit significant differences when making travel choice decisions.
Time-ordered product expansions for computational stochastic system biology
International Nuclear Information System (INIS)
Mjolsness, Eric
2013-01-01
The time-ordered product framework of quantum field theory can also be used to understand salient phenomena in stochastic biochemical networks. It is used here to derive Gillespie’s stochastic simulation algorithm (SSA) for chemical reaction networks; consequently, the SSA can be interpreted in terms of Feynman diagrams. It is also used here to derive other, more general simulation and parameter-learning algorithms including simulation algorithms for networks of stochastic reaction-like processes operating on parameterized objects, and also hybrid stochastic reaction/differential equation models in which systems of ordinary differential equations evolve the parameters of objects that can also undergo stochastic reactions. Thus, the time-ordered product expansion can be used systematically to derive simulation and parameter-fitting algorithms for stochastic systems. (paper)
Real-Time Demand Side Management Algorithm Using Stochastic Optimization
Directory of Open Access Journals (Sweden)
Moses Amoasi Acquah
2018-05-01
Full Text Available A demand side management technique is deployed along with battery energy-storage systems (BESS to lower the electricity cost by mitigating the peak load of a building. Most of the existing methods rely on manual operation of the BESS, or even an elaborate building energy-management system resorting to a deterministic method that is susceptible to unforeseen growth in demand. In this study, we propose a real-time optimal operating strategy for BESS based on density demand forecast and stochastic optimization. This method takes into consideration uncertainties in demand when accounting for an optimal BESS schedule, making it robust compared to the deterministic case. The proposed method is verified and tested against existing algorithms. Data obtained from a real site in South Korea is used for verification and testing. The results show that the proposed method is effective, even for the cases where the forecasted demand deviates from the observed demand.
Factors influencing lysis time stochasticity in bacteriophage λ
Directory of Open Access Journals (Sweden)
Dennehy John J
2011-08-01
Full Text Available Abstract Background Despite identical genotypes and seemingly uniform environments, stochastic gene expression and other dynamic intracellular processes can produce considerable phenotypic diversity within clonal microbes. One trait that provides a good model to explore the molecular basis of stochastic variation is the timing of host lysis by bacteriophage (phage. Results Individual lysis events of thermally-inducible λ lysogens were observed using a temperature-controlled perfusion chamber mounted on an inverted microscope. Both mean lysis time (MLT and its associated standard deviation (SD were estimated. Using the SD as a measure of lysis time stochasticity, we showed that lysogenic cells in controlled environments varied widely in lysis times, and that the level of lysis time stochasticity depended on allelic variation in the holin sequence, late promoter (pR' activity, and host growth rate. In general, the MLT was positively correlated with the SD. Both lower pR' activities and lower host growth rates resulted in larger SDs. Results from premature lysis, induced by adding KCN at different time points after lysogen induction, showed a negative correlation between the timing of KCN addition and lysis time stochasticity. Conclusions Taken together with results published by others, we conclude that a large fraction of λ lysis time stochasticity is the result of random events following the expression and diffusion of the holin protein. Consequently, factors influencing the timing of reaching critical holin concentrations in the cell membrane, such as holin production rate, strongly influence the mean lysis time and the lysis time stochasticity.
On the small-time behavior of stochastic logistic models
Directory of Open Access Journals (Sweden)
Dung Tien Nguyen
2017-09-01
Full Text Available In this paper we investigate the small-time behaviors of the solution to a stochastic logistic model. The obtained results allow us to estimate the number of individuals in the population and can be used to study stochastic prey-predator systems.
Ranking shortest paths in Stochastic time-denpendent networks
DEFF Research Database (Denmark)
Nielsen, Lars Relund; Andersen, Kim Allan; Pretolani, Daniele
A substantial amount of research has been devoted to the shortest path problem in networks where travel times are stochastic or (deterministic and) time-dependent. More recently, a growing interest has been attracted by networks that are both stochastic and time-dependent. In these networks, the ...... present a computational comparison of time-adaptive and a priori route choices, pointing out the effect of travel time and cost distributions. The reported results show that, under realistic distributions, our solution methods are effective.......A substantial amount of research has been devoted to the shortest path problem in networks where travel times are stochastic or (deterministic and) time-dependent. More recently, a growing interest has been attracted by networks that are both stochastic and time-dependent. In these networks...
K shortest paths in stochastic time-dependent networks
DEFF Research Database (Denmark)
Nielsen, Lars Relund; Pretolani, Daniele; Andersen, Kim Allan
2004-01-01
A substantial amount of research has been devoted to the shortest path problem in networks where travel times are stochastic or (deterministic and) time-dependent. More recently, a growing interest has been attracted by networks that are both stochastic and time-dependent. In these networks, the ...... present a computational comparison of time-adaptive and a priori route choices, pointing out the effect of travel time and cost distributions. The reported results show that, under realistic distributions, our solution methods are effective.......A substantial amount of research has been devoted to the shortest path problem in networks where travel times are stochastic or (deterministic and) time-dependent. More recently, a growing interest has been attracted by networks that are both stochastic and time-dependent. In these networks...
Stochastic time series analysis of hydrology data for water resources
Sathish, S.; Khadar Babu, S. K.
2017-11-01
The prediction to current publication of stochastic time series analysis in hydrology and seasonal stage. The different statistical tests for predicting the hydrology time series on Thomas-Fiering model. The hydrology time series of flood flow have accept a great deal of consideration worldwide. The concentration of stochastic process areas of time series analysis method are expanding with develop concerns about seasonal periods and global warming. The recent trend by the researchers for testing seasonal periods in the hydrologic flowseries using stochastic process on Thomas-Fiering model. The present article proposed to predict the seasonal periods in hydrology using Thomas-Fiering model.
Computer Aided Continuous Time Stochastic Process Modelling
DEFF Research Database (Denmark)
Kristensen, N.R.; Madsen, Henrik; Jørgensen, Sten Bay
2001-01-01
A grey-box approach to process modelling that combines deterministic and stochastic modelling is advocated for identification of models for model-based control of batch and semi-batch processes. A computer-aided tool designed for supporting decision-making within the corresponding modelling cycle...
On Stochastic Finite-Time Control of Discrete-Time Fuzzy Systems with Packet Dropout
Directory of Open Access Journals (Sweden)
Yingqi Zhang
2012-01-01
Full Text Available This paper is concerned with the stochastic finite-time stability and stochastic finite-time boundedness problems for one family of fuzzy discrete-time systems over networks with packet dropout, parametric uncertainties, and time-varying norm-bounded disturbance. Firstly, we present the dynamic model description studied, in which the discrete-time fuzzy T-S systems with packet loss can be described by one class of fuzzy Markovian jump systems. Then, the concepts of stochastic finite-time stability and stochastic finite-time boundedness and problem formulation are given. Based on Lyapunov function approach, sufficient conditions on stochastic finite-time stability and stochastic finite-time boundedness are established for the resulting closed-loop fuzzy discrete-time system with Markovian jumps, and state-feedback controllers are designed to ensure stochastic finite-time stability and stochastic finite-time boundedness of the class of fuzzy systems. The stochastic finite-time stability and stochastic finite-time boundedness criteria can be tackled in the form of linear matrix inequalities with a fixed parameter. As an auxiliary result, we also give sufficient conditions on the stochastic stability of the class of fuzzy T-S systems with packet loss. Finally, two illustrative examples are presented to show the validity of the developed methodology.
Evoking prescribed spike times in stochastic neurons
Doose, Jens; Lindner, Benjamin
2017-09-01
Single cell stimulation in vivo is a powerful tool to investigate the properties of single neurons and their functionality in neural networks. We present a method to determine a cell-specific stimulus that reliably evokes a prescribed spike train with high temporal precision of action potentials. We test the performance of this stimulus in simulations for two different stochastic neuron models. For a broad range of parameters and a neuron firing with intermediate firing rates (20-40 Hz) the reliability in evoking the prescribed spike train is close to its theoretical maximum that is mainly determined by the level of intrinsic noise.
Wu, Xiaohua; Hu, Xiaosong; Moura, Scott; Yin, Xiaofeng; Pickert, Volker
2016-11-01
Energy management strategies are instrumental in the performance and economy of smart homes integrating renewable energy and energy storage. This article focuses on stochastic energy management of a smart home with PEV (plug-in electric vehicle) energy storage and photovoltaic (PV) array. It is motivated by the challenges associated with sustainable energy supplies and the local energy storage opportunity provided by vehicle electrification. This paper seeks to minimize a consumer's energy charges under a time-of-use tariff, while satisfying home power demand and PEV charging requirements, and accommodating the variability of solar power. First, the random-variable models are developed, including Markov Chain model of PEV mobility, as well as predictive models of home power demand and PV power supply. Second, a stochastic optimal control problem is mathematically formulated for managing the power flow among energy sources in the smart home. Finally, based on time-varying electricity price, we systematically examine the performance of the proposed control strategy. As a result, the electric cost is 493.6% less for a Tesla Model S with optimal stochastic dynamic programming (SDP) control relative to the no optimal control case, and it is by 175.89% for a Nissan Leaf.
Ranking paths in stochastic time-dependent networks
DEFF Research Database (Denmark)
Nielsen, Lars Relund; Andersen, Kim Allan; Pretolani, Daniele D.
2014-01-01
In this paper we address optimal routing problems in networks where travel times are both stochastic and time-dependent. In these networks, the best route choice is not necessarily a path, but rather a time-adaptive strategy that assigns successors to nodes as a function of time. Nevertheless, in...
Long-time correlations in the stochastic regime
International Nuclear Information System (INIS)
Karney, C.F.F.
1982-11-01
The phase space for Hamiltonians of two degrees of freedom is usually divided into stochastic and integrable components. Even when well into the stochastic regime, integrable orbits may surround small stable regions or islands. The effect of these islands on the correlation function for the stochastic trajectories is examined. Depending on the value of the parameter describing the rotation number for the elliptic fixed point at the center of the island, the long-time correlation function may decay as t -5 or exponentially, but more commonly it decays much more slowly (roughly as t -1 ). As a consequence these small islands may have a profound effect on the properties such as the diffusion coefficient, of the stochastic orbits
International Nuclear Information System (INIS)
Gomes, I.L.R.; Pousinho, H.M.I.; Melício, R.; Mendes, V.M.F.
2017-01-01
This paper presents an optimal bid submission in a day-ahead electricity market for the problem of joint operation of wind with photovoltaic power systems having an energy storage device. Uncertainty not only due to the electricity market price, but also due to wind and photovoltaic powers is one of the main characteristics of this submission. The problem is formulated as a two-stage stochastic programming problem. The optimal bids and the energy flow in the batteries are the first-stage variables and the energy deviation is the second stage variable of the problem. Energy storage is a way to harness renewable energy conversion, allowing the store and discharge of energy at conveniently market prices. A case study with data from the Iberian day-ahead electricity market is presented and a comparison between joint and disjoint operations is discussed. - • Joint wind and PV systems with energy storage. • Electricity markets. • Stochastic optimization. • Day-ahead market.
International Nuclear Information System (INIS)
Kitapbayev, Yerkin; Moriarty, John; Mancarella, Pierluigi
2015-01-01
Highlights: • We calculate the real option value of flexibility from CHP-thermal storage. • Stochastic optimal feedback control problem is solved under uncertain market prices. • Efficient real-time numerical solutions combine simulation, regression and recursion. • Clear, interpretable feedback control maps are produced for each hour of the day. • We give a realistic UK case study using projected market gas and electricity prices. - Abstract: In district energy systems powered by Combined Heat and Power (CHP) plants, thermal storage can significantly increase CHP flexibility to respond to real time market signals and therefore improve the business case of such demand response schemes in a Smart Grid environment. However, main challenges remain as to what is the optimal way to control inter-temporal storage operation in the presence of uncertain market prices, and then how to value the investment into storage as flexibility enabler. In this outlook, the aim of this paper is to propose a model for optimal and dynamic control and long term valuation of CHP-thermal storage in the presence of uncertain market prices. The proposed model is formulated as a stochastic control problem and numerically solved through Least Squares Monte Carlo regression analysis, with integrated investment and operational timescale analysis equivalent to real options valuation models encountered in finance. Outputs are represented by clear and interpretable feedback control strategy maps for each hour of the day, thus suitable for real time demand response under uncertainty. Numerical applications to a realistic UK case study with projected market gas and electricity prices exemplify the proposed approach and quantify the robustness of the selected storage solutions
Investment timing under hybrid stochastic and local volatility
International Nuclear Information System (INIS)
Kim, Jeong-Hoon; Lee, Min-Ku; Sohn, So Young
2014-01-01
Highlights: • The effects of hybrid stochastic volatility on real option prices are studied. • The stochastic volatility consists of a fast mean-reverting component and a CEV type one. • A fast mean-reverting factor lowers real option prices and investment thresholds. • The increase of elasticity raises real option prices and investment thresholds. • The effects of the addition of a slowly varying factor depend upon the project value. - Abstract: We consider an investment timing problem under a real option model where the instantaneous volatility of the project value is given by a combination of a hidden stochastic process and the project value itself. The stochastic volatility part is given by a function of a fast mean-reverting process as well as a slowly varying process and the local volatility part is a power (the elasticity parameter) of the project value itself. The elasticity parameter controls directly the correlation between the project value and the volatility. Knowing that the project value represents the market price of a real asset in many applications and the value of the elasticity parameter depends on the asset, the elasticity parameter should be treated with caution for investment decision problems. Based on the hybrid structure of volatility, we investigate the simultaneous impact of the elasticity and the stochastic volatility on the real option value as well as the investment threshold
Time-Weighted Balanced Stochastic Model Reduction
DEFF Research Database (Denmark)
Tahavori, Maryamsadat; Shaker, Hamid Reza
2011-01-01
A new relative error model reduction technique for linear time invariant (LTI) systems is proposed in this paper. Both continuous and discrete time systems can be reduced within this framework. The proposed model reduction method is mainly based upon time-weighted balanced truncation and a recently...
Stochastic Approach to Determine CO2 Hydrate Induction Time in Clay Mineral Suspensions
Lee, K.; Lee, S.; Lee, W.
2008-12-01
A large number of induction time data for carbon dioxide hydrate formation were obtained from a batch reactor consisting of four independent reaction cells. Using resistance temperature detector(RTD)s and a digital microscope, we successfully monitored the whole process of hydrate formation (i.e., nucleation and crystal growth) and detected the induction time. The experiments were carried out in kaolinite and montmorillonite suspensions at temperatures between 274 and 277 K and pressures ranging from 3.0 to 4.0 MPa. Each set of data was analyzed beforehand whether to be treated by stochastic manner or not. Geochemical factors potentially influencing the hydrate induction time under different experimental conditions were investigated by stochastic analyses. We observed that clay mineral type, pressure, and temperature significantly affect the stochastic behavior of the induction times for CO2 hydrate formation in this study. The hydrate formation kinetics along with stochastic analyses can provide basic understanding for CO2 hydrate storage in deep-sea sediment and geologic formation, securing its stability under the environments.
Single-molecule stochastic times in a reversible bimolecular reaction
Keller, Peter; Valleriani, Angelo
2012-08-01
In this work, we consider the reversible reaction between reactants of species A and B to form the product C. We consider this reaction as a prototype of many pseudobiomolecular reactions in biology, such as for instance molecular motors. We derive the exact probability density for the stochastic waiting time that a molecule of species A needs until the reaction with a molecule of species B takes place. We perform this computation taking fully into account the stochastic fluctuations in the number of molecules of species B. We show that at low numbers of participating molecules, the exact probability density differs from the exponential density derived by assuming the law of mass action. Finally, we discuss the condition of detailed balance in the exact stochastic and in the approximate treatment.
Stochastic calculus for uncoupled continuous-time random walks.
Germano, Guido; Politi, Mauro; Scalas, Enrico; Schilling, René L
2009-06-01
The continuous-time random walk (CTRW) is a pure-jump stochastic process with several applications not only in physics but also in insurance, finance, and economics. A definition is given for a class of stochastic integrals driven by a CTRW, which includes the Itō and Stratonovich cases. An uncoupled CTRW with zero-mean jumps is a martingale. It is proved that, as a consequence of the martingale transform theorem, if the CTRW is a martingale, the Itō integral is a martingale too. It is shown how the definition of the stochastic integrals can be used to easily compute them by Monte Carlo simulation. The relations between a CTRW, its quadratic variation, its Stratonovich integral, and its Itō integral are highlighted by numerical calculations when the jumps in space of the CTRW have a symmetric Lévy alpha -stable distribution and its waiting times have a one-parameter Mittag-Leffler distribution. Remarkably, these distributions have fat tails and an unbounded quadratic variation. In the diffusive limit of vanishing scale parameters, the probability density of this kind of CTRW satisfies the space-time fractional diffusion equation (FDE) or more in general the fractional Fokker-Planck equation, which generalizes the standard diffusion equation, solved by the probability density of the Wiener process, and thus provides a phenomenologic model of anomalous diffusion. We also provide an analytic expression for the quadratic variation of the stochastic process described by the FDE and check it by Monte Carlo.
Expectation propagation for continuous time stochastic processes
International Nuclear Information System (INIS)
Cseke, Botond; Schnoerr, David; Sanguinetti, Guido; Opper, Manfred
2016-01-01
We consider the inverse problem of reconstructing the posterior measure over the trajectories of a diffusion process from discrete time observations and continuous time constraints. We cast the problem in a Bayesian framework and derive approximations to the posterior distributions of single time marginals using variational approximate inference, giving rise to an expectation propagation type algorithm. For non-linear diffusion processes, this is achieved by leveraging moment closure approximations. We then show how the approximation can be extended to a wide class of discrete-state Markov jump processes by making use of the chemical Langevin equation. Our empirical results show that the proposed method is computationally efficient and provides good approximations for these classes of inverse problems. (paper)
A Dynamic Momentum Compaction Factor Lattice for Improvements to Stochastic Cooling in Storage Rings
Energy Technology Data Exchange (ETDEWEB)
Olivieri, David Nicholas [Massachusetts U., Amherst
1996-01-01
A dynamic momentum compaction factor, also referred to as a dynamic $\\Delta \\gamma \\tau$, lattice for the FNAL Antiproton Source Debuncher Storage Ring is studied, both theoretically and experimentally, for the purpose of improving stochastic precooling, and hence, improving the global antiproton production and stacking performance. A dynamic $\\Delta \\gamma \\tau$ lattice is proposed due to the competing requirements inherent within the Debuncher storage ring upon $\\gamma \\tau$· Specifically, the Debuncher storage ring performs two disparate functions, $(i)$ accepting and debunching a large number of $\\overline{p}$s/pulse at the outset of the production cycle, which would perform ideally with a large value of $\\gamma\\tau$, and $(ii)$ subsequently employing stochastic cooling throughout the remainder of the $\\overline{p}$ production cycle for improved transfer and stacking efficiency into the Accumulator, for which a small value $\\gamma \\tau$ is ideal in order to reduce the diffusive heating caused by the mixing factor. In the initial design of the Debuncher optical lattice, an intermediate value of $\\gamma \\tau$ was chosen as a compromise between the two functional requirements. The goal of the thesis is to improve stochastic precooling by changing $\\gamma \\tau$ between two desired values during each p production cycle. In particular, the dynamic $\\Delta \\gamma \\tau$ lattice accomplishes a reduction in $\\gamma \\tau$, and hence the mixing factor, through an uniform increase to the dispersion throughout the arc sections of the storage ring. Experimental measurements of cooling rates and system performance parameters, with the implementation of the dynamic $\\Delta \\gamma \\tau$ lattice, are in agreement with theoretical predictions based upon a detailed integration of the stochastic cooling Fokker Planck equations. Based upon the consistency between theory and experiment, predictions of cooling rates are presented for future operational
International Nuclear Information System (INIS)
Wang, Zhaoqiang; Hu, Changhua; Wang, Wenbin; Zhou, Zhijie; Si, Xiaosheng
2014-01-01
Some systems may spend most of their time in storage, but once needed, must be fully functional. Slow degradation occurs when the system is in storage, so to ensure the functionality of these systems, condition monitoring is usually conducted periodically to check the condition of the system. However, taking the condition monitoring data may require putting the system under real testing situation which may accelerate the degradation, and therefore, shorten the storage life of the system. This paper presents a case study of condition-based remaining storage life prediction for gyros in the inertial navigation system on the basis of the condition monitoring data and the influence of the condition monitoring data taking process. A stochastic-filtering-based degradation model is developed to incorporate both into the prediction of the remaining storage life distribution. This makes the predicted remaining storage life depend on not only the condition monitoring data but also the testing process of taking the condition monitoring data, which the existing prognostic techniques and algorithms did not consider. The presented model is fitted to the real condition monitoring data of gyros testing using the maximum likelihood estimation method for parameter estimation. Comparisons are made with the model without considering the process of taking the condition monitoring data, and the results clearly demonstrate the superiority of the newly proposed model
Tomczewski, Andrzej
2014-01-01
The paper presents the issues of a wind turbine-flywheel energy storage system (WT-FESS) operation under real conditions. Stochastic changes of wind energy in time cause significant fluctuations of the system output power and as a result have a negative impact on the quality of the generated electrical energy. In the author's opinion it is possible to reduce the aforementioned effects by using an energy storage of an appropriate type and capacity. It was assumed that based on the technical parameters of a wind turbine-energy storage system and its geographical location one can determine the boundary capacity of the storage, which helps prevent power cuts to the grid at the assumed probability. Flywheel energy storage was selected due to its characteristics and technical parameters. The storage capacity was determined based on an empirical relationship using the results of the proposed statistical and energetic analysis of the measured wind velocity courses. A detailed algorithm of the WT-FESS with the power grid system was developed, eliminating short-term breaks in the turbine operation and periods when the wind turbine power was below the assumed level.
Stochastic inflation as a time-dependent random walk
International Nuclear Information System (INIS)
Kandrup, H.E.
1989-01-01
This paper exploits the ''stochastic inflation'' paradigm introduced by Starobinskii to study the evolution of long-wavelength modes for a free scalar field Phi in an inflationary Universe. By relaxing the assumption of a ''slow roll,'' it becomes obvious that the well-known late-time infrared divergence of the vacuum for a massless field in de Sitter space may be viewed as a consequence of the fluctuation-dissipation theorem. This stochastic model is also extended to allow for nonvacuum states and power-law inflation, situations where the fluctuation-dissipation theorem no longer holds. One recovers the correct late-time form for the expectation value 2 > in these cases as well, corroborating thereby the intuitive picture that, quite generally, the long-wavelength modes of the field evolve in a thermal ''bath'' provided by the shorter-wavelength modes
Energy Technology Data Exchange (ETDEWEB)
Lutaif, N.A. [Departamento de Clínica Médica, Faculdade de Ciências Médicas, Universidade Estadual de Campinas, Campinas, SP (Brazil); Palazzo, R. Jr [Departamento de Telemática, Faculdade de Engenharia Elétrica e Computação, Universidade Estadual de Campinas, Campinas, SP (Brazil); Gontijo, J.A.R. [Departamento de Clínica Médica, Faculdade de Ciências Médicas, Universidade Estadual de Campinas, Campinas, SP (Brazil)
2014-01-17
Maintenance of thermal homeostasis in rats fed a high-fat diet (HFD) is associated with changes in their thermal balance. The thermodynamic relationship between heat dissipation and energy storage is altered by the ingestion of high-energy diet content. Observation of thermal registers of core temperature behavior, in humans and rodents, permits identification of some characteristics of time series, such as autoreference and stationarity that fit adequately to a stochastic analysis. To identify this change, we used, for the first time, a stochastic autoregressive model, the concepts of which match those associated with physiological systems involved and applied in male HFD rats compared with their appropriate standard food intake age-matched male controls (n=7 per group). By analyzing a recorded temperature time series, we were able to identify when thermal homeostasis would be affected by a new diet. The autoregressive time series model (AR model) was used to predict the occurrence of thermal homeostasis, and this model proved to be very effective in distinguishing such a physiological disorder. Thus, we infer from the results of our study that maximum entropy distribution as a means for stochastic characterization of temperature time series registers may be established as an important and early tool to aid in the diagnosis and prevention of metabolic diseases due to their ability to detect small variations in thermal profile.
International Nuclear Information System (INIS)
Lutaif, N.A.; Palazzo, R. Jr; Gontijo, J.A.R.
2014-01-01
Maintenance of thermal homeostasis in rats fed a high-fat diet (HFD) is associated with changes in their thermal balance. The thermodynamic relationship between heat dissipation and energy storage is altered by the ingestion of high-energy diet content. Observation of thermal registers of core temperature behavior, in humans and rodents, permits identification of some characteristics of time series, such as autoreference and stationarity that fit adequately to a stochastic analysis. To identify this change, we used, for the first time, a stochastic autoregressive model, the concepts of which match those associated with physiological systems involved and applied in male HFD rats compared with their appropriate standard food intake age-matched male controls (n=7 per group). By analyzing a recorded temperature time series, we were able to identify when thermal homeostasis would be affected by a new diet. The autoregressive time series model (AR model) was used to predict the occurrence of thermal homeostasis, and this model proved to be very effective in distinguishing such a physiological disorder. Thus, we infer from the results of our study that maximum entropy distribution as a means for stochastic characterization of temperature time series registers may be established as an important and early tool to aid in the diagnosis and prevention of metabolic diseases due to their ability to detect small variations in thermal profile
A General Theory of Markovian Time Inconsistent Stochastic Control Problems
DEFF Research Database (Denmark)
Björk, Tomas; Murgochi, Agatha
We develop a theory for stochastic control problems which, in various ways, are time inconsistent in the sense that they do not admit a Bellman optimality principle. We attach these problems by viewing them within a game theoretic framework, and we look for Nash subgame perfect equilibrium points...... examples of time inconsistency in the literature are easily seen to be special cases of the present theory. We also prove that for every time inconsistent problem, there exists an associated time consistent problem such that the optimal control and the optimal value function for the consistent problem...
Stochastic ℋ∞ Finite-Time Control of Discrete-Time Systems with Packet Loss
Directory of Open Access Journals (Sweden)
Yingqi Zhang
2012-01-01
Full Text Available This paper investigates the stochastic finite-time stabilization and ℋ∞ control problem for one family of linear discrete-time systems over networks with packet loss, parametric uncertainties, and time-varying norm-bounded disturbance. Firstly, the dynamic model description studied is given, which, if the packet dropout is assumed to be a discrete-time homogenous Markov process, the class of discrete-time linear systems with packet loss can be regarded as Markovian jump systems. Based on Lyapunov function approach, sufficient conditions are established for the resulting closed-loop discrete-time system with Markovian jumps to be stochastic ℋ∞ finite-time boundedness and then state feedback controllers are designed to guarantee stochastic ℋ∞ finite-time stabilization of the class of stochastic systems. The stochastic ℋ∞ finite-time boundedness criteria can be tackled in the form of linear matrix inequalities with a fixed parameter. As an auxiliary result, we also give sufficient conditions on the robust stochastic stabilization of the class of linear systems with packet loss. Finally, simulation examples are presented to illustrate the validity of the developed scheme.
Quantum dynamical time evolutions as stochastic flows on phase space
International Nuclear Information System (INIS)
Combe, P.; Rodriguez, R.; Guerra, F.; Sirigue, M.; Sirigue-Collin, M.
1984-01-01
We are mainly interested in describing the time development of the Wigner functions by means of stochastic processes. In the second section we recall the main properties of the Wigner functions as well as those of their Fourier transform. In the next one we derive the evolution equation of these functions for a class of Hamiltonians and we give a probabilistic expression for the solution of these equations by means of a stochastic flow in phase space which reminds of the classical flows. In the last section we remark that the previously defined flow can be extended to the bounded continuous functions on phase space and that this flow conserves the cone generated by the Wigner functions. (orig./HSI)
Jumps and stochastic volatility in oil prices: Time series evidence
International Nuclear Information System (INIS)
Larsson, Karl; Nossman, Marcus
2011-01-01
In this paper we examine the empirical performance of affine jump diffusion models with stochastic volatility in a time series study of crude oil prices. We compare four different models and estimate them using the Markov Chain Monte Carlo method. The support for a stochastic volatility model including jumps in both prices and volatility is strong and the model clearly outperforms the others in terms of a superior fit to data. Our estimation method allows us to obtain a detailed study of oil prices during two periods of extreme market stress included in our sample; the Gulf war and the recent financial crisis. We also address the economic significance of model choice in two option pricing applications. The implied volatilities generated by the different estimated models are compared and we price a real option to develop an oil field. Our findings indicate that model choice can have a material effect on the option values.
Stochastic lag time in nucleated linear self-assembly
Energy Technology Data Exchange (ETDEWEB)
Tiwari, Nitin S. [Group Theory of Polymers and Soft Matter, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven (Netherlands); Schoot, Paul van der [Group Theory of Polymers and Soft Matter, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven (Netherlands); Institute for Theoretical Physics, Utrecht University, Leuvenlaan 4, 3584 CE Utrecht (Netherlands)
2016-06-21
Protein aggregation is of great importance in biology, e.g., in amyloid fibrillation. The aggregation processes that occur at the cellular scale must be highly stochastic in nature because of the statistical number fluctuations that arise on account of the small system size at the cellular scale. We study the nucleated reversible self-assembly of monomeric building blocks into polymer-like aggregates using the method of kinetic Monte Carlo. Kinetic Monte Carlo, being inherently stochastic, allows us to study the impact of fluctuations on the polymerization reactions. One of the most important characteristic features in this kind of problem is the existence of a lag phase before self-assembly takes off, which is what we focus attention on. We study the associated lag time as a function of system size and kinetic pathway. We find that the leading order stochastic contribution to the lag time before polymerization commences is inversely proportional to the system volume for large-enough system size for all nine reaction pathways tested. Finite-size corrections to this do depend on the kinetic pathway.
Infinite time interval backward stochastic differential equations with continuous coefficients.
Zong, Zhaojun; Hu, Feng
2016-01-01
In this paper, we study the existence theorem for [Formula: see text] [Formula: see text] solutions to a class of 1-dimensional infinite time interval backward stochastic differential equations (BSDEs) under the conditions that the coefficients are continuous and have linear growths. We also obtain the existence of a minimal solution. Furthermore, we study the existence and uniqueness theorem for [Formula: see text] [Formula: see text] solutions of infinite time interval BSDEs with non-uniformly Lipschitz coefficients. It should be pointed out that the assumptions of this result is weaker than that of Theorem 3.1 in Zong (Turkish J Math 37:704-718, 2013).
Investment timing decisions in a stochastic duopoly model
Energy Technology Data Exchange (ETDEWEB)
Marseguerra, Giovanni [Istituto di Econometria e CRANEC, Universita Cattolica del Sacro Cuore di Milan (Italy)]. E-mail: giovanni.marseguerra@unicatt.it; Cortelezzi, Flavia [Dipartimento di Diritto ed Economia delle Persone e delle Imprese, Universita dell' Insubria (Italy)]. E-mail: flavia.cortelezzi@uninsubria.it; Dominioni, Armando [CORE-Catholique de Louvain la Neuve (Belgium)]. E-mail: dominioni@core.ucl.ac.be
2006-08-15
We investigate the role of strategic considerations on the optimal timing of investment when firms compete for a new market (e.g., the provision of an innovative product) under demand uncertainty. Within a continuous time model of stochastic oligopoly, we show that strategic considerations are likely to be of limited impact when the new product is radically innovative whilst the fear of a rival's entry may deeply affect firms' decisions whenever innovation is to some extent limited. The welfare analysis shows surprisingly that the desirability of the different market structures considered does not depend on the fixed entry cost.
Investment timing decisions in a stochastic duopoly model
International Nuclear Information System (INIS)
Marseguerra, Giovanni; Cortelezzi, Flavia; Dominioni, Armando
2006-01-01
We investigate the role of strategic considerations on the optimal timing of investment when firms compete for a new market (e.g., the provision of an innovative product) under demand uncertainty. Within a continuous time model of stochastic oligopoly, we show that strategic considerations are likely to be of limited impact when the new product is radically innovative whilst the fear of a rival's entry may deeply affect firms' decisions whenever innovation is to some extent limited. The welfare analysis shows surprisingly that the desirability of the different market structures considered does not depend on the fixed entry cost
Time-variant reliability assessment through equivalent stochastic process transformation
International Nuclear Information System (INIS)
Wang, Zequn; Chen, Wei
2016-01-01
Time-variant reliability measures the probability that an engineering system successfully performs intended functions over a certain period of time under various sources of uncertainty. In practice, it is computationally prohibitive to propagate uncertainty in time-variant reliability assessment based on expensive or complex numerical models. This paper presents an equivalent stochastic process transformation approach for cost-effective prediction of reliability deterioration over the life cycle of an engineering system. To reduce the high dimensionality, a time-independent reliability model is developed by translating random processes and time parameters into random parameters in order to equivalently cover all potential failures that may occur during the time interval of interest. With the time-independent reliability model, an instantaneous failure surface is attained by using a Kriging-based surrogate model to identify all potential failure events. To enhance the efficacy of failure surface identification, a maximum confidence enhancement method is utilized to update the Kriging model sequentially. Then, the time-variant reliability is approximated using Monte Carlo simulations of the Kriging model where system failures over a time interval are predicted by the instantaneous failure surface. The results of two case studies demonstrate that the proposed approach is able to accurately predict the time evolution of system reliability while requiring much less computational efforts compared with the existing analytical approach. - Highlights: • Developed a new approach for time-variant reliability analysis. • Proposed a novel stochastic process transformation procedure to reduce the dimensionality. • Employed Kriging models with confidence-based adaptive sampling scheme to enhance computational efficiency. • The approach is effective for handling random process in time-variant reliability analysis. • Two case studies are used to demonstrate the efficacy
Time Series, Stochastic Processes and Completeness of Quantum Theory
International Nuclear Information System (INIS)
Kupczynski, Marian
2011-01-01
Most of physical experiments are usually described as repeated measurements of some random variables. Experimental data registered by on-line computers form time series of outcomes. The frequencies of different outcomes are compared with the probabilities provided by the algorithms of quantum theory (QT). In spite of statistical predictions of QT a claim was made that it provided the most complete description of the data and of the underlying physical phenomena. This claim could be easily rejected if some fine structures, averaged out in the standard descriptive statistical analysis, were found in time series of experimental data. To search for these structures one has to use more subtle statistical tools which were developed to study time series produced by various stochastic processes. In this talk we review some of these tools. As an example we show how the standard descriptive statistical analysis of the data is unable to reveal a fine structure in a simulated sample of AR (2) stochastic process. We emphasize once again that the violation of Bell inequalities gives no information on the completeness or the non locality of QT. The appropriate way to test the completeness of quantum theory is to search for fine structures in time series of the experimental data by means of the purity tests or by studying the autocorrelation and partial autocorrelation functions.
Stochastic quantization of geometrodynamic curved space-time
International Nuclear Information System (INIS)
Prugovecki, E.
1981-01-01
It is proposed that quantum rather than classical test particles be used in recent operational definitions of space-time. In the resulting quantum space-time the role of test particle trajectories is taken over by propagators. The introduced co-ordinate values are stochastic rather than deterministic, the afore-mentioned propagators providing probability amplitudes describing fluctuations of measured co-ordinates around their mean values. It is shown that, if a geometrodynamic point of view based on 3 + 1 foliations of space-time is adopted, self-consistent families of propagators for quantum test particles in free fall can be constructed. The resulting formalism for quantum space-time is outlined and the quantization of spatially flat Robertson-Walker space-times is provided as an illustration. (author)
Stochastic Landau equation with time-dependent drift
International Nuclear Information System (INIS)
Swift, J.B.; Hohenberg, P.C.; Ahlers, G.
1991-01-01
The stochastic differential equation τ 0 ∂ tA =ε(t)A-g 3 A 3 +bar f(t), where bar f(t) is Gaussian white noise, is studied for arbitrary time dependence of ε(t). In particular, cases are considered where ε(t) goes through the bifurcation of the deterministic system, which occurs at ε=0. In the limit of weak noise an approximate analytic expression generalizing earlier work of Suzuki [Phys. Lett. A 67, 339 (1978); Prog. Theor. Phys. (Kyoto) Suppl. 64, 402 (1978)] is obtained for the time-dependent distribution function P(A,t). The results compare favorably with a numerical simulation of the stochastic equation for the case of a linear ramp (both increasing and decreasing) and for a periodic time dependence of ε(t). The procedure can be generalized to an arbitrary deterministic part ∂ tA =D(A,t)+bar f(t), but the deterministic equation may then have to be solved numerically
Directory of Open Access Journals (Sweden)
Xueling Jiang
2014-01-01
Full Text Available The problem of adaptive asymptotical synchronization is discussed for the stochastic complex dynamical networks with time-delay and Markovian switching. By applying the stochastic analysis approach and the M-matrix method for stochastic complex networks, several sufficient conditions to ensure adaptive asymptotical synchronization for stochastic complex networks are derived. Through the adaptive feedback control techniques, some suitable parameters update laws are obtained. Simulation result is provided to substantiate the effectiveness and characteristics of the proposed approach.
Detecting stochastic backgrounds of gravitational waves with pulsar timing arrays
Siemens, Xavier
2016-03-01
For the past decade the North American Nanohertz Observatory for Gravitational Waves (NANOGrav) has been using the Green Bank Telescope and the Arecibo Observatory to monitor millisecond pulsars. NANOGrav, along with two other international collaborations, the European Pulsar Timing Array and the Parkes Pulsar Timing Array in Australia, form a consortium of consortia: the International Pulsar Timing Array (IPTA). The goal of the IPTA is to directly detect low-frequency gravitational waves which cause small changes to the times of arrival of radio pulses from millisecond pulsars. In this talk I will discuss the work of NANOGrav and the IPTA, as well as our sensitivity to stochastic backgrounds of gravitational waves. I will show that a detection of the background produced by supermassive black hole binaries is possible by the end of the decade. Supported by the NANOGrav Physics Frontiers Center.
A stochastic surplus production model in continuous time
DEFF Research Database (Denmark)
Pedersen, Martin Wæver; Berg, Casper Willestofte
2017-01-01
surplus production model in continuous time (SPiCT), which in addition to stock dynamics also models the dynamics of the fisheries. This enables error in the catch process to be reflected in the uncertainty of estimated model parameters and management quantities. Benefits of the continuous-time state......Surplus production modelling has a long history as a method for managing data-limited fish stocks. Recent advancements have cast surplus production models as state-space models that separate random variability of stock dynamics from error in observed indices of biomass. We present a stochastic......-space model formulation include the ability to provide estimates of exploitable biomass and fishing mortality at any point in time from data sampled at arbitrary and possibly irregular intervals. We show in a simulation that the ability to analyse subannual data can increase the effective sample size...
Fixation and escape times in stochastic game learning
International Nuclear Information System (INIS)
Realpe-Gomez, John; Szczesny, Bartosz; Galla, Tobias; Dall’Asta, Luca
2012-01-01
Evolutionary dynamics in finite populations is known to fixate eventually in the absence of mutation. We here show that a similar phenomenon can be found in stochastic game dynamical batch learning, and investigate fixation in learning processes in a simple 2×2 game, for two-player games with cyclic interaction, and in the context of the best-shot network game. The analogues of finite populations in evolution are here finite batches of observations between strategy updates. We study when and how such fixation can occur, and present results on the average time-to-fixation from numerical simulations. Simple cases are also amenable to analytical approaches and we provide estimates of the behaviour of so-called escape times as a function of the batch size. The differences and similarities with escape and fixation in evolutionary dynamics are discussed. (paper)
Extensions of Statecharts with probability, time, and stochastic timing
Jansen, D.N.
2003-01-01
Statecharts are a graphical language to describe the behaviour of a (computer) system. Statecharts are, among others, used as a part of the UML (Unified Modelling Language). This thesis describes three extensions related to statecharts. One of them is a real-time property language that fits well
Time-adaptive and history-adaptive multicriterion routing in stochastic, time-dependent networks
DEFF Research Database (Denmark)
Pretolani, Daniele; Nielsen, Lars Relund; Andersen, Kim Allan
2009-01-01
We compare two different models for multicriterion routing in stochastic time-dependent networks: the classic "time-adaptive'' model and the more flexible "history-adaptive'' one. We point out several properties of the sets of efficient solutions found under the two models. We also devise a method...
A theory of Markovian time-inconsistent stochastic control in discrete time
DEFF Research Database (Denmark)
Bjork, Tomas; Murgoci, Agatha
2014-01-01
We develop a theory for a general class of discrete-time stochastic control problems that, in various ways, are time-inconsistent in the sense that they do not admit a Bellman optimality principle. We attack these problems by viewing them within a game theoretic framework, and we look for subgame...
Johnson, Paul; Howell, Sydney; Duck, Peter
2017-08-13
A mixed financial/physical partial differential equation (PDE) can optimize the joint earnings of a single wind power generator (WPG) and a generic energy storage device (ESD). Physically, the PDE includes constraints on the ESD's capacity, efficiency and maximum speeds of charge and discharge. There is a mean-reverting daily stochastic cycle for WPG power output. Physically, energy can only be produced or delivered at finite rates. All suppliers must commit hourly to a finite rate of delivery C , which is a continuous control variable that is changed hourly. Financially, we assume heavy 'system balancing' penalties in continuous time, for deviations of output rate from the commitment C Also, the electricity spot price follows a mean-reverting stochastic cycle with a strong evening peak, when system balancing penalties also peak. Hence the economic goal of the WPG plus ESD, at each decision point, is to maximize expected net present value (NPV) of all earnings (arbitrage) minus the NPV of all expected system balancing penalties, along all financially/physically feasible future paths through state space. Given the capital costs for the various combinations of the physical parameters, the design and operating rules for a WPG plus ESD in a finite market may be jointly optimizable.This article is part of the themed issue 'Energy management: flexibility, risk and optimization'. © 2017 The Author(s).
Liu, Hongjian; Wang, Zidong; Shen, Bo; Alsaadi, Fuad E.
2016-07-01
This paper deals with the robust H∞ state estimation problem for a class of memristive recurrent neural networks with stochastic time-delays. The stochastic time-delays under consideration are governed by a Bernoulli-distributed stochastic sequence. The purpose of the addressed problem is to design the robust state estimator such that the dynamics of the estimation error is exponentially stable in the mean square, and the prescribed ? performance constraint is met. By utilizing the difference inclusion theory and choosing a proper Lyapunov-Krasovskii functional, the existence condition of the desired estimator is derived. Based on it, the explicit expression of the estimator gain is given in terms of the solution to a linear matrix inequality. Finally, a numerical example is employed to demonstrate the effectiveness and applicability of the proposed estimation approach.
Stochastic analysis of epidemics on adaptive time varying networks
Kotnis, Bhushan; Kuri, Joy
2013-06-01
Many studies investigating the effect of human social connectivity structures (networks) and human behavioral adaptations on the spread of infectious diseases have assumed either a static connectivity structure or a network which adapts itself in response to the epidemic (adaptive networks). However, human social connections are inherently dynamic or time varying. Furthermore, the spread of many infectious diseases occur on a time scale comparable to the time scale of the evolving network structure. Here we aim to quantify the effect of human behavioral adaptations on the spread of asymptomatic infectious diseases on time varying networks. We perform a full stochastic analysis using a continuous time Markov chain approach for calculating the outbreak probability, mean epidemic duration, epidemic reemergence probability, etc. Additionally, we use mean-field theory for calculating epidemic thresholds. Theoretical predictions are verified using extensive simulations. Our studies have uncovered the existence of an “adaptive threshold,” i.e., when the ratio of susceptibility (or infectivity) rate to recovery rate is below the threshold value, adaptive behavior can prevent the epidemic. However, if it is above the threshold, no amount of behavioral adaptations can prevent the epidemic. Our analyses suggest that the interaction patterns of the infected population play a major role in sustaining the epidemic. Our results have implications on epidemic containment policies, as awareness campaigns and human behavioral responses can be effective only if the interaction levels of the infected populace are kept in check.
A one-time truncate and encode multiresolution stochastic framework
Energy Technology Data Exchange (ETDEWEB)
Abgrall, R.; Congedo, P.M.; Geraci, G., E-mail: gianluca.geraci@inria.fr
2014-01-15
In this work a novel adaptive strategy for stochastic problems, inspired from the classical Harten's framework, is presented. The proposed algorithm allows building, in a very general manner, stochastic numerical schemes starting from a whatever type of deterministic schemes and handling a large class of problems, from unsteady to discontinuous solutions. Its formulations permits to recover the same results concerning the interpolation theory of the classical multiresolution approach, but with an extension to uncertainty quantification problems. The present strategy permits to build numerical scheme with a higher accuracy with respect to other classical uncertainty quantification techniques, but with a strong reduction of the numerical cost and memory requirements. Moreover, the flexibility of the proposed approach allows to employ any kind of probability density function, even discontinuous and time varying, without introducing further complications in the algorithm. The advantages of the present strategy are demonstrated by performing several numerical problems where different forms of uncertainty distributions are taken into account, such as discontinuous and unsteady custom-defined probability density functions. In addition to algebraic and ordinary differential equations, numerical results for the challenging 1D Kraichnan–Orszag are reported in terms of accuracy and convergence. Finally, a two degree-of-freedom aeroelastic model for a subsonic case is presented. Though quite simple, the model allows recovering some physical key aspect, on the fluid/structure interaction, thanks to the quasi-steady aerodynamic approximation employed. The injection of an uncertainty is chosen in order to obtain a complete parameterization of the mass matrix. All the numerical results are compared with respect to classical Monte Carlo solution and with a non-intrusive Polynomial Chaos method.
International Nuclear Information System (INIS)
Ghalelou, Afshin Najafi; Fakhri, Alireza Pashaei; Nojavan, Sayyad; Majidi, Majid; Hatami, Hojat
2016-01-01
Highlights: • Optimal stochastic energy management of renewable energy sources (RESs) is proposed. • The compressed air energy storage (CAES) besides RESs is used in the presence of DRP. • Determination charge and discharge of CAES in order to reduce the expected operation cost. • Moreover, demand response program (DRP) is proposed to minimize the operation cost. • The uncertainty modeling of input data are considered in the proposed stochastic framework. - Abstract: In this paper, a stochastic self-scheduling of renewable energy sources (RESs) considering compressed air energy storage (CAES) in the presence of a demand response program (DRP) is proposed. RESs include wind turbine (WT) and photovoltaic (PV) system. Other energy sources are thermal units and CAES. The time-of-use (TOU) rate of DRP is considered in this paper. This DRP shifts the percentage of load from the expensive period to the cheap one in order to flatten the load curve and minimize the operation cost, consequently. The proposed objective function includes minimizing the operation costs of thermal unit and CAES, considering technical and physical constraints. The proposed model is formulated as mixed integer linear programming (MILP) and it is been solved using General Algebraic Modeling System (GAMS) optimization package. Furthermore, CAES and DRP are incorporated in the stochastic self-scheduling problem by a decision maker to reduce the expected operation cost. Meanwhile, the uncertainty models of market price, load, wind speed, temperature and irradiance are considered in the formulation. Finally, to assess the effects of DRP and CAES on self-scheduling problem, four case studies are utilized, and significant results were obtained, which indicate the validity of the proposed stochastic program.
Long-time data storage: relevant time scales
Elwenspoek, Michael Curt
2011-01-01
Dynamic processes relevant for long-time storage of information about human kind are discussed, ranging from biological and geological processes to the lifecycle of stars and the expansion of the universe. Major results are that life will end ultimately and the remaining time that the earth is
International Nuclear Information System (INIS)
Bisognano, J.; Leemann, C.
1982-03-01
Stochastic cooling is the damping of betatron oscillations and momentum spread of a particle beam by a feedback system. In its simplest form, a pickup electrode detects the transverse positions or momenta of particles in a storage ring, and the signal produced is amplified and applied downstream to a kicker. The time delay of the cable and electronics is designed to match the transit time of particles along the arc of the storage ring between the pickup and kicker so that an individual particle receives the amplified version of the signal it produced at the pick-up. If there were only a single particle in the ring, it is obvious that betatron oscillations and momentum offset could be damped. However, in addition to its own signal, a particle receives signals from other beam particles. In the limit of an infinite number of particles, no damping could be achieved; we have Liouville's theorem with constant density of the phase space fluid. For a finite, albeit large number of particles, there remains a residue of the single particle damping which is of practical use in accumulating low phase space density beams of particles such as antiprotons. It was the realization of this fact that led to the invention of stochastic cooling by S. van der Meer in 1968. Since its conception, stochastic cooling has been the subject of much theoretical and experimental work. The earliest experiments were performed at the ISR in 1974, with the subsequent ICE studies firmly establishing the stochastic cooling technique. This work directly led to the design and construction of the Antiproton Accumulator at CERN and the beginnings of p anti p colliding beam physics at the SPS. Experiments in stochastic cooling have been performed at Fermilab in collaboration with LBL, and a design is currently under development for a anti p accumulator for the Tevatron
Time to rethink nuclear waste storage
International Nuclear Information System (INIS)
Flynn, J.; Kasperson, R.; Kunreuther, H.; Slovic, P.
1992-01-01
The authors feel that given the levels of public opposition and distrust, congress should scrap the current nuclear waste storage program and reconsider the options. They observe that no compelling reason currently exists for siting a permanent repository at an early date. Technology developed in the past decade, especially dry-cask storage, provides assurance that wastes from commercial reactors can be stored safely for a lengthy period at current sites. In the longer term, reprocessing may reduce the volume of high-level wastes; storage elsewhere than in a geological repository may prove attractive; and experimental techniques such as transmutation - aimed at radically reducing the amount of time that wastes remain highly radioactive - could help solve the problem. In the meantime, the authors suggest that the US must begin a long-term effort to engage the public in a process of active collaboration. In doing so, the US has much to learn from other countries, where innovative approaches and techniques have began to establish public confidence
Optimal investment models with stochastic volatility: the time ...
African Journals Online (AJOL)
Therefore, a transform is primordial to express the value function in terms of a semilinear PDE with quadratic growth on the derivative term. Some proofs for the existence of smooth solution to this equation have been provided for this equation by Pham [11]. In that paper they illustrated some common stochastic volatility ...
Directory of Open Access Journals (Sweden)
Mingzhu Song
2016-01-01
Full Text Available We address the problem of globally asymptotic stability for a class of stochastic nonlinear systems with time-varying delays. By the backstepping method and Lyapunov theory, we design a linear output feedback controller recursively based on the observable linearization for a class of stochastic nonlinear systems with time-varying delays to guarantee that the closed-loop system is globally asymptotically stable in probability. In particular, we extend the deterministic nonlinear system to stochastic nonlinear systems with time-varying delays. Finally, an example and its simulations are given to illustrate the theoretical results.
Mean Square Exponential Stability of Stochastic Switched System with Interval Time-Varying Delays
Directory of Open Access Journals (Sweden)
Manlika Rajchakit
2012-01-01
Full Text Available This paper is concerned with mean square exponential stability of switched stochastic system with interval time-varying delays. The time delay is any continuous function belonging to a given interval, but not necessary to be differentiable. By constructing a suitable augmented Lyapunov-Krasovskii functional combined with Leibniz-Newton’s formula, a switching rule for the mean square exponential stability of switched stochastic system with interval time-varying delays and new delay-dependent sufficient conditions for the mean square exponential stability of the switched stochastic system are first established in terms of LMIs. Numerical example is given to show the effectiveness of the obtained result.
Robustness Analysis of Hybrid Stochastic Neural Networks with Neutral Terms and Time-Varying Delays
Directory of Open Access Journals (Sweden)
Chunmei Wu
2015-01-01
Full Text Available We analyze the robustness of global exponential stability of hybrid stochastic neural networks subject to neutral terms and time-varying delays simultaneously. Given globally exponentially stable hybrid stochastic neural networks, we characterize the upper bounds of contraction coefficients of neutral terms and time-varying delays by using the transcendental equation. Moreover, we prove theoretically that, for any globally exponentially stable hybrid stochastic neural networks, if additive neutral terms and time-varying delays are smaller than the upper bounds arrived, then the perturbed neural networks are guaranteed to also be globally exponentially stable. Finally, a numerical simulation example is given to illustrate the presented criteria.
International Nuclear Information System (INIS)
Chen, Feng; Han, Yuecai
2013-01-01
The existence of time-periodic stochastic motions of an incompressible fluid is obtained. Here the fluid is subject to a time-periodic body force and an additional time-periodic stochastic force that is produced by a rigid body moves periodically stochastically with the same period in the fluid
Energy Technology Data Exchange (ETDEWEB)
Chen, Feng, E-mail: chenfengmath@163.com, E-mail: hanyc@jlu.edu.cn; Han, Yuecai, E-mail: chenfengmath@163.com, E-mail: hanyc@jlu.edu.cn [School of Mathematics, Jilin University, Changchun 130012 (China)
2013-12-15
The existence of time-periodic stochastic motions of an incompressible fluid is obtained. Here the fluid is subject to a time-periodic body force and an additional time-periodic stochastic force that is produced by a rigid body moves periodically stochastically with the same period in the fluid.
Kozel, Tomas; Stary, Milos
2017-12-01
The main advantage of stochastic forecasting is fan of possible value whose deterministic method of forecasting could not give us. Future development of random process is described better by stochastic then deterministic forecasting. Discharge in measurement profile could be categorized as random process. Content of article is construction and application of forecasting model for managed large open water reservoir with supply function. Model is based on neural networks (NS) and zone models, which forecasting values of average monthly flow from inputs values of average monthly flow, learned neural network and random numbers. Part of data was sorted to one moving zone. The zone is created around last measurement average monthly flow. Matrix of correlation was assembled only from data belonging to zone. The model was compiled for forecast of 1 to 12 month with using backward month flows (NS inputs) from 2 to 11 months for model construction. Data was got ridded of asymmetry with help of Box-Cox rule (Box, Cox, 1964), value r was found by optimization. In next step were data transform to standard normal distribution. The data were with monthly step and forecast is not recurring. 90 years long real flow series was used for compile of the model. First 75 years were used for calibration of model (matrix input-output relationship), last 15 years were used only for validation. Outputs of model were compared with real flow series. For comparison between real flow series (100% successfully of forecast) and forecasts, was used application to management of artificially made reservoir. Course of water reservoir management using Genetic algorithm (GE) + real flow series was compared with Fuzzy model (Fuzzy) + forecast made by Moving zone model. During evaluation process was founding the best size of zone. Results show that the highest number of input did not give the best results and ideal size of zone is in interval from 25 to 35, when course of management was almost same for
Partial Finite-Time Synchronization of Switched Stochastic Chua's Circuits via Sliding-Mode Control
Directory of Open Access Journals (Sweden)
Zhang-Lin Wan
2011-01-01
Full Text Available This paper considers the problem of partial finite-time synchronization between switched stochastic Chua's circuits accompanied by a time-driven switching law. Based on the Ito formula and Lyapunov stability theory, a sliding-mode controller is developed to guarantee the synchronization of switched stochastic master-slave Chua's circuits and for the mean of error states to obtain the partial finite-time stability. Numerical simulations demonstrate the effectiveness of the proposed methods.
Stochastic resonance in a time-delayed asymmetric bistable system with mixed periodic signal
International Nuclear Information System (INIS)
Yong-Feng, Guo; Wei, Xu; Liang, Wang
2010-01-01
This paper studies the phenomenon of stochastic resonance in an asymmetric bistable system with time-delayed feedback and mixed periodic signal by using the theory of signal-to-noise ratio in the adiabatic limit. A general approximate Fokker–Planck equation and the expression of the signal-to-noise ratio are derived through the small time delay approximation at both fundamental harmonics and mixed harmonics. The effects of the additive noise intensity Q, multiplicative noise intensity D, static asymmetry r and delay time τ on the signal-to-noise ratio are discussed. It is found that the higher mixed harmonics and the static asymmetry r can restrain stochastic resonance, and the delay time τ can enhance stochastic resonance. Moreover, the longer the delay time τ is, the larger the additive noise intensity Q and the multiplicative noise intensity D are, when the stochastic resonance appears. (general)
Robust stability for uncertain stochastic fuzzy BAM neural networks with time-varying delays
Syed Ali, M.; Balasubramaniam, P.
2008-07-01
In this Letter, by utilizing the Lyapunov functional and combining with the linear matrix inequality (LMI) approach, we analyze the global asymptotic stability of uncertain stochastic fuzzy Bidirectional Associative Memory (BAM) neural networks with time-varying delays which are represented by the Takagi-Sugeno (TS) fuzzy models. A new class of uncertain stochastic fuzzy BAM neural networks with time varying delays has been studied and sufficient conditions have been derived to obtain conservative result in stochastic settings. The developed results are more general than those reported in the earlier literatures. In addition, the numerical examples are provided to illustrate the applicability of the result using LMI toolbox in MATLAB.
Robust stability for uncertain stochastic fuzzy BAM neural networks with time-varying delays
International Nuclear Information System (INIS)
Syed Ali, M.; Balasubramaniam, P.
2008-01-01
In this Letter, by utilizing the Lyapunov functional and combining with the linear matrix inequality (LMI) approach, we analyze the global asymptotic stability of uncertain stochastic fuzzy Bidirectional Associative Memory (BAM) neural networks with time-varying delays which are represented by the Takagi-Sugeno (TS) fuzzy models. A new class of uncertain stochastic fuzzy BAM neural networks with time varying delays has been studied and sufficient conditions have been derived to obtain conservative result in stochastic settings. The developed results are more general than those reported in the earlier literatures. In addition, the numerical examples are provided to illustrate the applicability of the result using LMI toolbox in MATLAB
TIME-DEPENDENT STOCHASTIC ACCELERATION MODEL FOR FERMI BUBBLES
Energy Technology Data Exchange (ETDEWEB)
Sasaki, Kento; Asano, Katsuaki; Terasawa, Toshio, E-mail: kentos@icrr.u-tokyo.ac.jp, E-mail: asanok@icrr.u-tokyo.ac.jp, E-mail: terasawa@icrr.u-tokyo.ac.jp [Institute for Cosmic Ray Research, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8582 (Japan)
2015-12-01
We study stochastic acceleration models for the Fermi bubbles. Turbulence is excited just behind the shock front via Kelvin–Helmholtz, Rayleigh–Taylor, or Richtmyer–Meshkov instabilities, and plasma particles are continuously accelerated by the interaction with the turbulence. The turbulence gradually decays as it goes away from the shock fronts. Adopting a phenomenological model for the stochastic acceleration, we explicitly solve the temporal evolution of the particle energy distribution in the turbulence. Our results show that the spatial distribution of high-energy particles is different from those for a steady solution. We also show that the contribution of electrons that escaped from the acceleration regions significantly softens the photon spectrum. The photon spectrum and surface brightness profile are reproduced by our models. If the escape efficiency is very high, the radio flux from the escaped low-energy electrons can be comparable to that of the WMAP haze. We also demonstrate hadronic models with the stochastic acceleration, but they are unlikely in the viewpoint of the energy budget.
Quantum mechanics and stochastic mechanics for compatible observables at different times
International Nuclear Information System (INIS)
Correggi, M.; Morchio, G.
2002-01-01
Bohm mechanics and Nelson stochastic mechanics are confronted with quantum mechanics in the presence of noninteracting subsystems. In both cases, it is shown that correlations at different times of compatible position observables on stationary states agree with quantum mechanics only in the case of product wave functions. By appropriate Bell-like inequalities it is shown that no classical theory, in particular no stochastic process, can reproduce the quantum mechanical correlations of position variables of noninteracting systems at different times
Effects of stochastic time-delayed feedback on a dynamical system modeling a chemical oscillator
González Ochoa, Héctor O.; Perales, Gualberto Solís; Epstein, Irving R.; Femat, Ricardo
2018-05-01
We examine how stochastic time-delayed negative feedback affects the dynamical behavior of a model oscillatory reaction. We apply constant and stochastic time-delayed negative feedbacks to a point Field-Körös-Noyes photosensitive oscillator and compare their effects. Negative feedback is applied in the form of simulated inhibitory electromagnetic radiation with an intensity proportional to the concentration of oxidized light-sensitive catalyst in the oscillator. We first characterize the system under nondelayed inhibitory feedback; then we explore and compare the effects of constant (deterministic) versus stochastic time-delayed feedback. We find that the oscillatory amplitude, frequency, and waveform are essentially preserved when low-dispersion stochastic delayed feedback is used, whereas small but measurable changes appear when a large dispersion is applied.
Susceptibility of optimal train schedules to stochastic disturbances of process times
DEFF Research Database (Denmark)
Larsen, Rune; Pranzo, Marco; D’Ariano, Andrea
2013-01-01
study, an advanced branch and bound algorithm, on average, outperforms a First In First Out scheduling rule both in deterministic and stochastic traffic scenarios. However, the characteristic of the stochastic processes and the way a stochastic instance is handled turn out to have a serious impact...... and dwell times). In fact, the objective of railway traffic management is to reduce delay propagation and to increase disturbance robustness of train schedules at a network scale. We present a quantitative study of traffic disturbances and their effects on the schedules computed by simple and advanced...
Exponential stability of uncertain stochastic neural networks with mixed time-delays
International Nuclear Information System (INIS)
Wang Zidong; Lauria, Stanislao; Fang Jian'an; Liu Xiaohui
2007-01-01
This paper is concerned with the global exponential stability analysis problem for a class of stochastic neural networks with mixed time-delays and parameter uncertainties. The mixed delays comprise discrete and distributed time-delays, the parameter uncertainties are norm-bounded, and the neural networks are subjected to stochastic disturbances described in terms of a Brownian motion. The purpose of the stability analysis problem is to derive easy-to-test criteria under which the delayed stochastic neural network is globally, robustly, exponentially stable in the mean square for all admissible parameter uncertainties. By resorting to the Lyapunov-Krasovskii stability theory and the stochastic analysis tools, sufficient stability conditions are established by using an efficient linear matrix inequality (LMI) approach. The proposed criteria can be checked readily by using recently developed numerical packages, where no tuning of parameters is required. An example is provided to demonstrate the usefulness of the proposed criteria
H∞ state estimation of stochastic memristor-based neural networks with time-varying delays.
Bao, Haibo; Cao, Jinde; Kurths, Jürgen; Alsaedi, Ahmed; Ahmad, Bashir
2018-03-01
This paper addresses the problem of H ∞ state estimation for a class of stochastic memristor-based neural networks with time-varying delays. Under the framework of Filippov solution, the stochastic memristor-based neural networks are transformed into systems with interval parameters. The present paper is the first to investigate the H ∞ state estimation problem for continuous-time Itô-type stochastic memristor-based neural networks. By means of Lyapunov functionals and some stochastic technique, sufficient conditions are derived to ensure that the estimation error system is asymptotically stable in the mean square with a prescribed H ∞ performance. An explicit expression of the state estimator gain is given in terms of linear matrix inequalities (LMIs). Compared with other results, our results reduce control gain and control cost effectively. Finally, numerical simulations are provided to demonstrate the efficiency of the theoretical results. Copyright © 2018 Elsevier Ltd. All rights reserved.
Grigoryeva, Lyudmila; Henriques, Julie; Larger, Laurent; Ortega, Juan-Pablo
2014-07-01
Reservoir computing is a recently introduced machine learning paradigm that has already shown excellent performances in the processing of empirical data. We study a particular kind of reservoir computers called time-delay reservoirs that are constructed out of the sampling of the solution of a time-delay differential equation and show their good performance in the forecasting of the conditional covariances associated to multivariate discrete-time nonlinear stochastic processes of VEC-GARCH type as well as in the prediction of factual daily market realized volatilities computed with intraday quotes, using as training input daily log-return series of moderate size. We tackle some problems associated to the lack of task-universality for individually operating reservoirs and propose a solution based on the use of parallel arrays of time-delay reservoirs. Copyright © 2014 Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Wang Bo; Song Ruili
2009-01-01
We consider a more general wealth process with a drift coefficient which is Lipschitz continuous and the portfolio process with convex constraint. We convert the problem of hedging American contingent claims into the problem of minimal solution of backward stochastic differential equation with stopping time. We adopt the penalization method for constructing the minimal solution of stochastic differential equations and obtain the upper hedging price of American contingent claims.
International Nuclear Information System (INIS)
Zare Oskouei, Morteza; Sadeghi Yazdankhah, Ahmad
2015-01-01
Highlights: • Two-stage objective function is proposed for optimization problem. • Hourly-based optimal contractual agreement is calculated. • Scenario-based stochastic optimization problem is solved. • Improvement of system frequency by utilizing PSH unit. - Abstract: This paper proposes the operating strategy of a micro grid connected wind farm, photovoltaic and pump-storage hybrid system. The strategy consists of two stages. In the first stage, the optimal hourly contractual agreement is determined. The second stage corresponds to maximizing its profit by adapting energy management strategy of wind and photovoltaic in coordination with optimum operating schedule of storage device under frequency based pricing for a day ahead electricity market. The pump-storage hydro plant is utilized to minimize unscheduled interchange flow and maximize the system benefit by participating in frequency control based on energy price. Because of uncertainties in power generation of renewable sources and market prices, generation scheduling is modeled by a stochastic optimization problem. Uncertainties of parameters are modeled by scenario generation and scenario reduction method. A powerful optimization algorithm is proposed using by General Algebraic Modeling System (GAMS)/CPLEX. In order to verify the efficiency of the method, the algorithm is applied to various scenarios with different wind and photovoltaic power productions in a day ahead electricity market. The numerical results demonstrate the effectiveness of the proposed approach.
Long-Time Data Storage: Relevant Time Scales
Directory of Open Access Journals (Sweden)
Miko C. Elwenspoek
2011-02-01
Full Text Available Dynamic processes relevant for long-time storage of information about human kind are discussed, ranging from biological and geological processes to the lifecycle of stars and the expansion of the universe. Major results are that life will end ultimately and the remaining time that the earth is habitable for complex life is about half a billion years. A system retrieved within the next million years will be read by beings very closely related to Homo sapiens. During this time the surface of the earth will change making it risky to place a small number of large memory systems on earth; the option to place it on the moon might be more favorable. For much longer timescales both options do not seem feasible because of geological processes on the earth and the flux of small meteorites to the moon.
Event-Triggered Faults Tolerant Control for Stochastic Systems with Time Delays
Directory of Open Access Journals (Sweden)
Ling Huang
2016-01-01
Full Text Available This paper is concerned with the state-feedback controller design for stochastic networked control systems (NCSs with random actuator failures and transmission delays. Firstly, an event-triggered scheme is introduced to optimize the performance of the stochastic NCSs. Secondly, stochastic NCSs under event-triggered scheme are modeled as stochastic time-delay systems. Thirdly, some less conservative delay-dependent stability criteria in terms of linear matrix inequalities for the codesign of both the controller gain and the trigger parameters are obtained by using delay-decomposition technique and convex combination approach. Finally, a numerical example is provided to show the less sampled data transmission and less conservatism of the proposed theory.
Continuous-Time Mean-Variance Portfolio Selection: A Stochastic LQ Framework
International Nuclear Information System (INIS)
Zhou, X.Y.; Li, D.
2000-01-01
This paper is concerned with a continuous-time mean-variance portfolio selection model that is formulated as a bicriteria optimization problem. The objective is to maximize the expected terminal return and minimize the variance of the terminal wealth. By putting weights on the two criteria one obtains a single objective stochastic control problem which is however not in the standard form due to the variance term involved. It is shown that this nonstandard problem can be 'embedded' into a class of auxiliary stochastic linear-quadratic (LQ) problems. The stochastic LQ control model proves to be an appropriate and effective framework to study the mean-variance problem in light of the recent development on general stochastic LQ problems with indefinite control weighting matrices. This gives rise to the efficient frontier in a closed form for the original portfolio selection problem
Dar, Zamiyad
The prices in the electricity market change every five minutes. The prices in peak demand hours can be four or five times more than the prices in normal off peak hours. Renewable energy such as wind power has zero marginal cost and a large percentage of wind energy in a power grid can reduce the price significantly. The variability of wind power prevents it from being constantly available in peak hours. The price differentials between off-peak and on-peak hours due to wind power variations provide an opportunity for a storage device owner to buy energy at a low price and sell it in high price hours. In a large and complex power grid, there are many locations for installation of a storage device. Storage device owners prefer to install their device at locations that allow them to maximize profit. Market participants do not possess much information about the system operator's dispatch, power grid, competing generators and transmission system. The publicly available data from the system operator usually consists of Locational Marginal Prices (LMP), load, reserve prices and regulation prices. In this thesis, we develop a method to find the optimum location of a storage device without using the grid, transmission or generator data. We formulate and solve an optimization problem to find the most profitable location for a storage device using only the publicly available market pricing data such as LMPs, and reserve prices. We consider constraints arising due to storage device operation limitations in our objective function. We use binary optimization and branch and bound method to optimize the operation of a storage device at a given location to earn maximum profit. We use two different versions of our method and optimize the profitability of a storage unit at each location in a 36 bus model of north eastern United States and south eastern Canada for four representative days representing four seasons in a year. Finally, we compare our results from the two versions of our
Keren, Baruch; Pliskin, Joseph S
2011-12-01
The optimal timing for performing radical medical procedures as joint (e.g., hip) replacement must be seriously considered. In this paper we show that under deterministic assumptions the optimal timing for joint replacement is a solution of a mathematical programming problem, and under stochastic assumptions the optimal timing can be formulated as a stochastic programming problem. We formulate deterministic and stochastic models that can serve as decision support tools. The results show that the benefit from joint replacement surgery is heavily dependent on timing. Moreover, for a special case where the patient's remaining life is normally distributed along with a normally distributed survival of the new joint, the expected benefit function from surgery is completely solved. This enables practitioners to draw the expected benefit graph, to find the optimal timing, to evaluate the benefit for each patient, to set priorities among patients and to decide if joint replacement should be performed and when.
Stochastic simulation of power systems with integrated renewable and utility-scale storage resources
Degeilh, Yannick
The push for a more sustainable electric supply has led various countries to adopt policies advocating the integration of renewable yet variable energy resources, such as wind and solar, into the grid. The challenges of integrating such time-varying, intermittent resources has in turn sparked a growing interest in the implementation of utility-scale energy storage resources ( ESRs), with MWweek storage capability. Indeed, storage devices provide flexibility to facilitate the management of power system operations in the presence of uncertain, highly time-varying and intermittent renewable resources. The ability to exploit the potential synergies between renewable and ESRs hinges on developing appropriate models, methodologies, tools and policy initiatives. We report on the development of a comprehensive simulation methodology that provides the capability to quantify the impacts of integrated renewable and ESRs on the economics, reliability and emission variable effects of power systems operating in a market environment. We model the uncertainty in the demands, the available capacity of conventional generation resources and the time-varying, intermittent renewable resources, with their temporal and spatial correlations, as discrete-time random processes. We deploy models of the ESRs to emulate their scheduling and operations in the transmission-constrained hourly day-ahead markets. To this end, we formulate a scheduling optimization problem (SOP) whose solutions determine the operational schedule of the controllable ESRs in coordination with the demands and the conventional/renewable resources. As such, the SOP serves the dual purpose of emulating the clearing of the transmission-constrained day-ahead markets (DAMs ) and scheduling the energy storage resource operations. We also represent the need for system operators to impose stricter ramping requirements on the conventional generating units so as to maintain the system capability to perform "load following'', i
International Nuclear Information System (INIS)
Frank, T.D.
2006-01-01
First-order approximations of time-dependent solutions are determined for stochastic systems perturbed by time-delayed feedback forces. To this end, the theory of delay Fokker-Planck equations is applied in combination with Bayes' theorem. Applications to a time-delayed Ornstein-Uhlenbeck process and the geometric Brownian walk of financial physics are discussed
Capasso, Vincenzo
2015-01-01
This textbook, now in its third edition, offers a rigorous and self-contained introduction to the theory of continuous-time stochastic processes, stochastic integrals, and stochastic differential equations. Expertly balancing theory and applications, the work features concrete examples of modeling real-world problems from biology, medicine, industrial applications, finance, and insurance using stochastic methods. No previous knowledge of stochastic processes is required. Key topics include: * Markov processes * Stochastic differential equations * Arbitrage-free markets and financial derivatives * Insurance risk * Population dynamics, and epidemics * Agent-based models New to the Third Edition: * Infinitely divisible distributions * Random measures * Levy processes * Fractional Brownian motion * Ergodic theory * Karhunen-Loeve expansion * Additional applications * Additional exercises * Smoluchowski approximation of Langevin systems An Introduction to Continuous-Time Stochastic Processes, Third Editio...
Adaptive logical stochastic resonance in time-delayed synthetic genetic networks
Zhang, Lei; Zheng, Wenbin; Song, Aiguo
2018-04-01
In the paper, the concept of logical stochastic resonance is applied to implement logic operation and latch operation in time-delayed synthetic genetic networks derived from a bacteriophage λ. Clear logic operation and latch operation can be obtained when the network is tuned by modulated periodic force and time-delay. In contrast with the previous synthetic genetic networks based on logical stochastic resonance, the proposed system has two advantages. On one hand, adding modulated periodic force to the background noise can increase the length of the optimal noise plateau of obtaining desired logic response and make the system adapt to varying noise intensity. On the other hand, tuning time-delay can extend the optimal noise plateau to larger range. The result provides possible help for designing new genetic regulatory networks paradigm based on logical stochastic resonance.
Calculating Higher-Order Moments of Phylogenetic Stochastic Mapping Summaries in Linear Time
Dhar, Amrit
2017-01-01
Abstract Stochastic mapping is a simulation-based method for probabilistically mapping substitution histories onto phylogenies according to continuous-time Markov models of evolution. This technique can be used to infer properties of the evolutionary process on the phylogeny and, unlike parsimony-based mapping, conditions on the observed data to randomly draw substitution mappings that do not necessarily require the minimum number of events on a tree. Most stochastic mapping applications simulate substitution mappings only to estimate the mean and/or variance of two commonly used mapping summaries: the number of particular types of substitutions (labeled substitution counts) and the time spent in a particular group of states (labeled dwelling times) on the tree. Fast, simulation-free algorithms for calculating the mean of stochastic mapping summaries exist. Importantly, these algorithms scale linearly in the number of tips/leaves of the phylogenetic tree. However, to our knowledge, no such algorithm exists for calculating higher-order moments of stochastic mapping summaries. We present one such simulation-free dynamic programming algorithm that calculates prior and posterior mapping variances and scales linearly in the number of phylogeny tips. Our procedure suggests a general framework that can be used to efficiently compute higher-order moments of stochastic mapping summaries without simulations. We demonstrate the usefulness of our algorithm by extending previously developed statistical tests for rate variation across sites and for detecting evolutionarily conserved regions in genomic sequences. PMID:28177780
Xiao-Li Ding; Juan J. Nieto
2018-01-01
In this paper, we investigate analytical solutions of multi-time scale fractional stochastic differential equations driven by fractional Brownian motions. We firstly decompose homogeneous multi-time scale fractional stochastic differential equations driven by fractional Brownian motions into independent differential subequations, and give their analytical solutions. Then, we use the variation of constant parameters to obtain the solutions of nonhomogeneous multi-time scale fractional stochast...
Exact norm-conserving stochastic time-dependent Hartree-Fock
International Nuclear Information System (INIS)
Tessieri, Luca; Wilkie, Joshua; Cetinbas, Murat
2005-01-01
We derive an exact single-body decomposition of the time-dependent Schroedinger equation for N pairwise interacting fermions. Each fermion obeys a stochastic time-dependent norm-preserving wave equation. As a first test of the method, we calculate the low energy spectrum of helium. An extension of the method to bosons is outlined
GCSRL - A Logic for Stochastic Reward Models with Timed and Untimed Behaviour
Kuntz, Matthias; Haverkort, Boudewijn R.; Cloth, L.
In this paper we define the logic GCSRL (generalised continuous stochastic reward logic) that provides means to reason about systems that have states which sojourn times are either greater zero, in which case this sojourn time is exponentially distributed (tangible states), or zero (vanishing
International Nuclear Information System (INIS)
Fu, Jin; Wu, Sheng; Li, Hong; Petzold, Linda R.
2014-01-01
The inhomogeneous stochastic simulation algorithm (ISSA) is a fundamental method for spatial stochastic simulation. However, when diffusion events occur more frequently than reaction events, simulating the diffusion events by ISSA is quite costly. To reduce this cost, we propose to use the time dependent propensity function in each step. In this way we can avoid simulating individual diffusion events, and use the time interval between two adjacent reaction events as the simulation stepsize. We demonstrate that the new algorithm can achieve orders of magnitude efficiency gains over widely-used exact algorithms, scales well with increasing grid resolution, and maintains a high level of accuracy
Mashhoon, B.
1982-01-01
The influence of a stochastic and isotropic background of gravitational radiation on timing measurements of pulsars is investigated, and it is shown that pulsar timing noise may be used to establish a significant upper limit of about 10 to the -10th on the total energy density of very long-wavelength stochastic gravitational waves. This places restriction on the strength of very long wavelength gravitational waves in the Friedmann model, and such a background is expected to have no significant effect on the approximately 3 K electromagnetic background radiation or on the dynamics of a cluster of galaxies.
Doubly stochastic Poisson process models for precipitation at fine time-scales
Ramesh, Nadarajah I.; Onof, Christian; Xie, Dichao
2012-09-01
This paper considers a class of stochastic point process models, based on doubly stochastic Poisson processes, in the modelling of rainfall. We examine the application of this class of models, a neglected alternative to the widely-known Poisson cluster models, in the analysis of fine time-scale rainfall intensity. These models are mainly used to analyse tipping-bucket raingauge data from a single site but an extension to multiple sites is illustrated which reveals the potential of this class of models to study the temporal and spatial variability of precipitation at fine time-scales.
Guo, Feng; Wang, Xue-Yuan; Zhu, Cheng-Yin; Cheng, Xiao-Feng; Zhang, Zheng-Yu; Huang, Xu-Hui
2017-12-01
The stochastic resonance for a fractional oscillator with time-delayed kernel and quadratic trichotomous noise is investigated. Applying linear system theory and Laplace transform, the system output amplitude (SPA) for the fractional oscillator is obtained. It is found that the SPA is a periodical function of the kernel delayed-time. Stochastic multiplicative phenomenon appears on the SPA versus the driving frequency, versus the noise amplitude, and versus the fractional exponent. The non-monotonous dependence of the SPA on the system parameters is also discussed.
Stochasticity, decoherence and an arrow of time from the ...
Indian Academy of Sciences (India)
Certain intriguing consequences of the discreteness of time on the time evolution of dynamical systems are discussed. In the discrete-time classical mechanics proposed here, there is an arrow of time that follows from the fact that the replacement of the time derivative by the backward difference operator alone can preserve ...
Continuous-Time Public Good Contribution Under Uncertainty: A Stochastic Control Approach
International Nuclear Information System (INIS)
Ferrari, Giorgio; Riedel, Frank; Steg, Jan-Henrik
2017-01-01
In this paper we study continuous-time stochastic control problems with both monotone and classical controls motivated by the so-called public good contribution problem. That is the problem of n economic agents aiming to maximize their expected utility allocating initial wealth over a given time period between private consumption and irreversible contributions to increase the level of some public good. We investigate the corresponding social planner problem and the case of strategic interaction between the agents, i.e. the public good contribution game. We show existence and uniqueness of the social planner’s optimal policy, we characterize it by necessary and sufficient stochastic Kuhn–Tucker conditions and we provide its expression in terms of the unique optional solution of a stochastic backward equation. Similar stochastic first order conditions prove to be very useful for studying any Nash equilibria of the public good contribution game. In the symmetric case they allow us to prove (qualitative) uniqueness of the Nash equilibrium, which we again construct as the unique optional solution of a stochastic backward equation. We finally also provide a detailed analysis of the so-called free rider effect.
Continuous-Time Public Good Contribution Under Uncertainty: A Stochastic Control Approach
Energy Technology Data Exchange (ETDEWEB)
Ferrari, Giorgio, E-mail: giorgio.ferrari@uni-bielefeld.de; Riedel, Frank, E-mail: frank.riedel@uni-bielefeld.de; Steg, Jan-Henrik, E-mail: jsteg@uni-bielefeld.de [Bielefeld University, Center for Mathematical Economics (Germany)
2017-06-15
In this paper we study continuous-time stochastic control problems with both monotone and classical controls motivated by the so-called public good contribution problem. That is the problem of n economic agents aiming to maximize their expected utility allocating initial wealth over a given time period between private consumption and irreversible contributions to increase the level of some public good. We investigate the corresponding social planner problem and the case of strategic interaction between the agents, i.e. the public good contribution game. We show existence and uniqueness of the social planner’s optimal policy, we characterize it by necessary and sufficient stochastic Kuhn–Tucker conditions and we provide its expression in terms of the unique optional solution of a stochastic backward equation. Similar stochastic first order conditions prove to be very useful for studying any Nash equilibria of the public good contribution game. In the symmetric case they allow us to prove (qualitative) uniqueness of the Nash equilibrium, which we again construct as the unique optional solution of a stochastic backward equation. We finally also provide a detailed analysis of the so-called free rider effect.
Stochastic Power Control for Time-Varying Long-Term Fading Wireless Networks
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Charalambous Charalambos D
2006-01-01
Full Text Available A new time-varying (TV long-term fading (LTF channel model which captures both the space and time variations of wireless systems is developed. The proposed TV LTF model is based on a stochastic differential equation driven by Brownian motion. This model is more realistic than the static models usually encountered in the literature. It allows viewing the wireless channel as a dynamical system, thus enabling well-developed tools of adaptive and nonadaptive estimation and identification techniques to be applied to this class of problems. In contrast with the traditional models, the statistics of the proposed model are shown to be TV, but converge in steady state to their static counterparts. Moreover, optimal power control algorithms (PCAs based on the new model are proposed. A centralized PCA is shown to reduce to a simple linear programming problem if predictable power control strategies (PPCS are used. In addition, an iterative distributed stochastic PCA is used to solve for the optimization problem using stochastic approximations. The latter solely requires each mobile to know its received signal-to-interference ratio. Generalizations of the power control problem based on convex optimization techniques are provided if PPCS are not assumed. Numerical results show that there are potentially large gains to be achieved by using TV stochastic models, and the distributed stochastic PCA provides better power stability and consumption than the distributed deterministic PCA.
Fuji apple storage time rapid determination method using Vis/NIR spectroscopy
Liu, Fuqi; Tang, Xuxiang
2015-01-01
Fuji apple storage time rapid determination method using visible/near-infrared (Vis/NIR) spectroscopy was studied in this paper. Vis/NIR diffuse reflection spectroscopy responses to samples were measured for 6 days. Spectroscopy data were processed by stochastic resonance (SR). Principal component analysis (PCA) was utilized to analyze original spectroscopy data and SNR eigen value. Results demonstrated that PCA could not totally discriminate Fuji apples using original spectroscopy data. Signal-to-noise ratio (SNR) spectrum clearly classified all apple samples. PCA using SNR spectrum successfully discriminated apple samples. Therefore, Vis/NIR spectroscopy was effective for Fuji apple storage time rapid discrimination. The proposed method is also promising in condition safety control and management for food and environmental laboratories. PMID:25874818
Kitapbayev, Yerkin; Moriarty, John; Mancarella, Pierluigi
2014-01-01
In district energy systems powered by Combined Heat and Power (CHP) plants, thermal storage can significantly increase CHP flexibility to respond to real time market signals and therefore improve the business case of such demand response schemes in a Smart Grid environment. However, main challenges remain as to what is the optimal way to control inter-temporal storage operation in the presence of uncertain market prices, and then how to value the investment into storage as flexibility enabler...
Stochastic time-dependent vehicle routing problem: Mathematical models and ant colony algorithm
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Zhengyu Duan
2015-11-01
Full Text Available This article addresses the stochastic time-dependent vehicle routing problem. Two mathematical models named robust optimal schedule time model and minimum expected schedule time model are proposed for stochastic time-dependent vehicle routing problem, which can guarantee delivery within the time windows of customers. The robust optimal schedule time model only requires the variation range of link travel time, which can be conveniently derived from historical traffic data. In addition, the robust optimal schedule time model based on robust optimization method can be converted into a time-dependent vehicle routing problem. Moreover, an ant colony optimization algorithm is designed to solve stochastic time-dependent vehicle routing problem. As the improvements in initial solution and transition probability, ant colony optimization algorithm has a good performance in convergence. Through computational instances and Monte Carlo simulation tests, robust optimal schedule time model is proved to be better than minimum expected schedule time model in computational efficiency and coping with the travel time fluctuations. Therefore, robust optimal schedule time model is applicable in real road network.
Stochastic skyline route planning under time-varying uncertainty
DEFF Research Database (Denmark)
Yang, Bin; Guo, Chenjuan; Jensen, Christian S.
2014-01-01
Different uses of a road network call for the consideration of different travel costs: in route planning, travel time and distance are typically considered, and green house gas (GHG) emissions are increasingly being considered. Further, travel costs such as travel time and GHG emissions are time...
Modeling stochastic lead times in multi-echelon systems
Diks, E.B.; Heijden, van der M.C.
1996-01-01
In many multi-echelon inventory systems the lead times are random variables. A common and reasonable assumption in most models is that replenishment orders do not cross, which implies that successive lead times are correlated. However, the process which generates such lead times is usually not
Modeling stochastic lead times in multi-echelon systems
Diks, E.B.; van der Heijden, M.C.
1997-01-01
In many multi-echelon inventory systems, the lead times are random variables. A common and reasonable assumption in most models is that replenishment orders do not cross, which implies that successive lead times are correlated. However, the process that generates such lead times is usually not well
Directory of Open Access Journals (Sweden)
Yajun Li
2015-01-01
Full Text Available This paper deals with the robust H∞ filter design problem for a class of uncertain neutral stochastic systems with Markovian jumping parameters and time delay. Based on the Lyapunov-Krasovskii theory and generalized Finsler Lemma, a delay-dependent stability condition is proposed to ensure not only that the filter error system is robustly stochastically stable but also that a prescribed H∞ performance level is satisfied for all admissible uncertainties. All obtained results are expressed in terms of linear matrix inequalities which can be easily solved by MATLAB LMI toolbox. Numerical examples are given to show that the results obtained are both less conservative and less complicated in computation.
Adaptive control of chaotic systems with stochastic time varying unknown parameters
Energy Technology Data Exchange (ETDEWEB)
Salarieh, Hassan [Center of Excellence in Design, Robotics and Automation, Department of Mechanical Engineering, Sharif University of Technology, P.O. Box 11365-9567, Azadi Avenue, Tehran (Iran, Islamic Republic of)], E-mail: salarieh@mech.sharif.edu; Alasty, Aria [Center of Excellence in Design, Robotics and Automation, Department of Mechanical Engineering, Sharif University of Technology, P.O. Box 11365-9567, Azadi Avenue, Tehran (Iran, Islamic Republic of)], E-mail: aalasti@sharif.edu
2008-10-15
In this paper based on the Lyapunov stability theorem, an adaptive control scheme is proposed for stabilizing the unstable periodic orbits (UPO) of chaotic systems. It is assumed that the chaotic system has some linearly dependent unknown parameters which are stochastically time varying. The stochastic parameters are modeled through the Weiner process derivative. To demonstrate the effectiveness of the proposed technique it has been applied to the Lorenz, Chen and Rossler dynamical systems, as some case studies. Simulation results indicate that the proposed adaptive controller has a high performance in stabilizing the UPO of chaotic systems in noisy environment.
Effects of demographic stochasticity on biological community assembly on evolutionary time scales
Murase, Yohsuke
2010-04-13
We study the effects of demographic stochasticity on the long-term dynamics of biological coevolution models of community assembly. The noise is induced in order to check the validity of deterministic population dynamics. While mutualistic communities show little dependence on the stochastic population fluctuations, predator-prey models show strong dependence on the stochasticity, indicating the relevance of the finiteness of the populations. For a predator-prey model, the noise causes drastic decreases in diversity and total population size. The communities that emerge under influence of the noise consist of species strongly coupled with each other and have stronger linear stability around the fixed-point populations than the corresponding noiseless model. The dynamics on evolutionary time scales for the predator-prey model are also altered by the noise. Approximate 1/f fluctuations are observed with noise, while 1/ f2 fluctuations are found for the model without demographic noise. © 2010 The American Physical Society.
Effects of demographic stochasticity on biological community assembly on evolutionary time scales
Murase, Yohsuke; Shimada, Takashi; Ito, Nobuyasu; Rikvold, Per Arne
2010-01-01
We study the effects of demographic stochasticity on the long-term dynamics of biological coevolution models of community assembly. The noise is induced in order to check the validity of deterministic population dynamics. While mutualistic communities show little dependence on the stochastic population fluctuations, predator-prey models show strong dependence on the stochasticity, indicating the relevance of the finiteness of the populations. For a predator-prey model, the noise causes drastic decreases in diversity and total population size. The communities that emerge under influence of the noise consist of species strongly coupled with each other and have stronger linear stability around the fixed-point populations than the corresponding noiseless model. The dynamics on evolutionary time scales for the predator-prey model are also altered by the noise. Approximate 1/f fluctuations are observed with noise, while 1/ f2 fluctuations are found for the model without demographic noise. © 2010 The American Physical Society.
Empirical method to measure stochasticity and multifractality in nonlinear time series
Lin, Chih-Hao; Chang, Chia-Seng; Li, Sai-Ping
2013-12-01
An empirical algorithm is used here to study the stochastic and multifractal nature of nonlinear time series. A parameter can be defined to quantitatively measure the deviation of the time series from a Wiener process so that the stochasticity of different time series can be compared. The local volatility of the time series under study can be constructed using this algorithm, and the multifractal structure of the time series can be analyzed by using this local volatility. As an example, we employ this method to analyze financial time series from different stock markets. The result shows that while developed markets evolve very much like an Ito process, the emergent markets are far from efficient. Differences about the multifractal structures and leverage effects between developed and emergent markets are discussed. The algorithm used here can be applied in a similar fashion to study time series of other complex systems.
Approximation of itô integrals arising in stochastic time-delayed systems
Bagchi, Arunabha
1984-01-01
Likelihood functional for stochastic linear time-delayed systems involve Itô integrals with respect to the observed data. Since the Wiener process appearing in the standard observation process model for such systems is not realizable and the physically observed process is smooth, one needs to study
On the small time asymptotics of 3D stochastic primitive equations
Dong, Zhao; Zhang, Rangrang
2017-01-01
In this paper, we establish a small time large deviation principle for the strong solution of 3D stochastic primitive equations driven by multiplicative noise. Both the small noise and the small, but highly nonlinear, unbounded nonlinear terms should be taken into consideration.
Assessing and accounting for time heterogeneity in stochastic actor oriented models
Lospinoso, Joshua A.; Schweinberger, Michael; Snijders, Tom A. B.; Ripley, Ruth M.
This paper explores time heterogeneity in stochastic actor oriented models (SAOM) proposed by Snijders (Sociological methodology. Blackwell, Boston, pp 361-395, 2001) which are meant to study the evolution of networks. SAOMs model social networks as directed graphs with nodes representing people,
Zhang, Kemei; Zhao, Cong-Ran; Xie, Xue-Jun
2015-12-01
This paper considers the problem of output feedback stabilisation for stochastic high-order feedforward nonlinear systems with time-varying delay. By using the homogeneous domination theory and solving several troublesome obstacles in the design and analysis, an output feedback controller is constructed to drive the closed-loop system globally asymptotically stable in probability.
Bicriterion a priori route choice in stochastic time-dependent networks
DEFF Research Database (Denmark)
Nielsen, Lars Relund; Andersen, Kim Allan; Pretolani, Daniele
In recent years there has been a growing interest in using stochastic time-dependent (STD) networks as a modelling tool for a number of applications within such areas as transportation and telecommunications. It is known that an optimal routing policy does not necessarily correspond to a path...
Bicriterion a priori route choice in stochastic time-dependent networks
DEFF Research Database (Denmark)
Nielsen, Lars Relund; Pretolani, D; Andersen, K A
2006-01-01
In recent years there has been a growing interest in using stochastic time-dependent (STD) networks as a modelling tool for a number of applications within such areas as transportation and telecommunications. It is known that an optimal routing policy does not necessarily correspond to a path...
Statistical inference for discrete-time samples from affine stochastic delay differential equations
DEFF Research Database (Denmark)
Küchler, Uwe; Sørensen, Michael
2013-01-01
Statistical inference for discrete time observations of an affine stochastic delay differential equation is considered. The main focus is on maximum pseudo-likelihood estimators, which are easy to calculate in practice. A more general class of prediction-based estimating functions is investigated...
ON THE ANISOTROPIC NORM OF DISCRETE TIME STOCHASTIC SYSTEMS WITH STATE DEPENDENT NOISE
Directory of Open Access Journals (Sweden)
Isaac Yaesh
2013-01-01
Full Text Available The purpose of this paper is to determine conditions for the bound-edness of the anisotropic norm of discrete-time linear stochastic sys-tems with state dependent noise. It is proved that these conditions canbe expressed in terms of the feasibility of a specific system of matrixinequalities.
The Limit Behavior of a Stochastic Logistic Model with Individual Time-Dependent Rates
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Yilun Shang
2013-01-01
Full Text Available We investigate a variant of the stochastic logistic model that allows individual variation and time-dependent infection and recovery rates. The model is described as a heterogeneous density dependent Markov chain. We show that the process can be approximated by a deterministic process defined by an integral equation as the population size grows.
Control of photon storage time using phase locking.
Ham, Byoung S
2010-01-18
A photon echo storage-time extension protocol is presented by using a phase locking method in a three-level backward propagation scheme, where phase locking serves as a conditional stopper of the rephasing process in conventional two-pulse photon echoes. The backward propagation scheme solves the critical problems of extremely low retrieval efficiency and pi rephasing pulse-caused spontaneous emission noise in photon echo based quantum memories. The physics of the storage time extension lies in the imminent population transfer from the excited state to an auxiliary spin state by a phase locking control pulse. We numerically demonstrate that the storage time is lengthened by spin dephasing time.
Hopf Bifurcation Analysis for a Stochastic Discrete-Time Hyperchaotic System
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Jie Ran
2015-01-01
Full Text Available The dynamics of a discrete-time hyperchaotic system and the amplitude control of Hopf bifurcation for a stochastic discrete-time hyperchaotic system are investigated in this paper. Numerical simulations are presented to exhibit the complex dynamical behaviors in the discrete-time hyperchaotic system. Furthermore, the stochastic discrete-time hyperchaotic system with random parameters is transformed into its equivalent deterministic system with the orthogonal polynomial theory of discrete random function. In addition, the dynamical features of the discrete-time hyperchaotic system with random disturbances are obtained through its equivalent deterministic system. By using the Hopf bifurcation conditions of the deterministic discrete-time system, the specific conditions for the existence of Hopf bifurcation in the equivalent deterministic system are derived. And the amplitude control with random intensity is discussed in detail. Finally, the feasibility of the control method is demonstrated by numerical simulations.
Stochastic modeling of hourly rainfall times series in Campania (Italy)
Giorgio, M.; Greco, R.
2009-04-01
Occurrence of flowslides and floods in small catchments is uneasy to predict, since it is affected by a number of variables, such as mechanical and hydraulic soil properties, slope morphology, vegetation coverage, rainfall spatial and temporal variability. Consequently, landslide risk assessment procedures and early warning systems still rely on simple empirical models based on correlation between recorded rainfall data and observed landslides and/or river discharges. Effectiveness of such systems could be improved by reliable quantitative rainfall prediction, which can allow gaining larger lead-times. Analysis of on-site recorded rainfall height time series represents the most effective approach for a reliable prediction of local temporal evolution of rainfall. Hydrological time series analysis is a widely studied field in hydrology, often carried out by means of autoregressive models, such as AR, ARMA, ARX, ARMAX (e.g. Salas [1992]). Such models gave the best results when applied to the analysis of autocorrelated hydrological time series, like river flow or level time series. Conversely, they are not able to model the behaviour of intermittent time series, like point rainfall height series usually are, especially when recorded with short sampling time intervals. More useful for this issue are the so-called DRIP (Disaggregated Rectangular Intensity Pulse) and NSRP (Neymann-Scott Rectangular Pulse) model [Heneker et al., 2001; Cowpertwait et al., 2002], usually adopted to generate synthetic point rainfall series. In this paper, the DRIP model approach is adopted, in which the sequence of rain storms and dry intervals constituting the structure of rainfall time series is modeled as an alternating renewal process. Final aim of the study is to provide a useful tool to implement an early warning system for hydrogeological risk management. Model calibration has been carried out with hourly rainfall hieght data provided by the rain gauges of Campania Region civil
A stochastic space-time model for intermittent precipitation occurrences
Sun, Ying; Stein, Michael L.
2016-01-01
Modeling a precipitation field is challenging due to its intermittent and highly scale-dependent nature. Motivated by the features of high-frequency precipitation data from a network of rain gauges, we propose a threshold space-time t random field (tRF) model for 15-minute precipitation occurrences. This model is constructed through a space-time Gaussian random field (GRF) with random scaling varying along time or space and time. It can be viewed as a generalization of the purely spatial tRF, and has a hierarchical representation that allows for Bayesian interpretation. Developing appropriate tools for evaluating precipitation models is a crucial part of the model-building process, and we focus on evaluating whether models can produce the observed conditional dry and rain probabilities given that some set of neighboring sites all have rain or all have no rain. These conditional probabilities show that the proposed space-time model has noticeable improvements in some characteristics of joint rainfall occurrences for the data we have considered.
A stochastic space-time model for intermittent precipitation occurrences
Sun, Ying
2016-01-28
Modeling a precipitation field is challenging due to its intermittent and highly scale-dependent nature. Motivated by the features of high-frequency precipitation data from a network of rain gauges, we propose a threshold space-time t random field (tRF) model for 15-minute precipitation occurrences. This model is constructed through a space-time Gaussian random field (GRF) with random scaling varying along time or space and time. It can be viewed as a generalization of the purely spatial tRF, and has a hierarchical representation that allows for Bayesian interpretation. Developing appropriate tools for evaluating precipitation models is a crucial part of the model-building process, and we focus on evaluating whether models can produce the observed conditional dry and rain probabilities given that some set of neighboring sites all have rain or all have no rain. These conditional probabilities show that the proposed space-time model has noticeable improvements in some characteristics of joint rainfall occurrences for the data we have considered.
Introduction to Stopping Time in Stochastic Finance Theory. Part II
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Jaeger Peter
2017-12-01
Full Text Available We start proceeding with the stopping time theory in discrete time with the help of the Mizar system [1], [4]. We prove, that the expression for two stopping times k1 and k2 not always implies a stopping time (k1 + k2 (see Theorem 6 in this paper. If you want to get a stopping time, you have to cut the function e.g. (k1 + k2 ⋂ T (see [2, p. 283 Remark 6.14]. Next we introduce the stopping time in continuous time. We are focused on the intervals [0, r] where r ∈ ℝ. We prove, that for I = [0, r] or I = [0,+∞[ the set {A ⋂ I : A ∈ Borel-Sets} is a σ-algebra of I (see Definition 6 in this paper, and more general given in [3, p.12 1.8e]. The interval I can be considered as a timeline from now to some point in the future. This set is necessary to define our next lemma. We prove the existence of the σ-algebra of the τ -past, where τ is a stopping time (see Definition 11 in this paper and [6, p.187, Definition 9.19]. If τ1 and τ2 are stopping times with τ1 is smaller or equal than τ2 we can prove, that the σ-algebra of the τ1-past is a subset of the σ-algebra of the τ2-past (see Theorem 9 in this paper and [6, p.187 Lemma 9.21]. Suppose, that you want to use Lemma 9.21 with some events, that never occur, see as a comparison the paper [5] and the example for ST(1={+∞} in the Summary. We don’t have the element +1 in our above-mentioned time intervals [0, r[ and [0,+1[. This is only possible if we construct a new σ-algebra on ℝ {−∞,+∞}. This construction is similar to the Borel-Sets and we call this σ-algebra extended Borel sets (see Definition 13 in this paper and [3, p. 21]. It can be proved, that {+∞} is an Element of extended Borel sets (see Theorem 21 in this paper. Now we use the interval [0,+∞] as a basis. We construct a σ-algebra on [0,+∞] similar to the book ([3, p. 12 18e], see Definition 18 in this paper, and call it extended Borel subsets. We prove for stopping times with this given σ-algebra, that
International Nuclear Information System (INIS)
Bornapour, Mosayeb; Hooshmand, Rahmat-Allah; Khodabakhshian, Amin; Parastegari, Moein
2017-01-01
Highlights: •Stochastic model is proposed for coordinated scheduling of renewable energy sources. •The effect of combined heat and power is considered. •Hydrogen storage is considered for fuel cells. •Maximizing profits of micro grid is considered as objective function. •Considering the uncertainties of problem lead to profit increasing. -- Abstract: Nowadays, renewable energy sources and combined heat and power units are extremely used in micro grids, so it is necessary to schedule these units to improve the performance of the system. In this regard, a stochastic model is proposed in this paper to schedule proton exchange membrane fuel cell-combined heat and power, wind turbines, and photovoltaic units coordinately in a micro grid while considering hydrogen storage. Hydrogen storage strategy is considered for the operation of proton exchange membrane fuel cell-combined heat and power units. To consider stochastic generation of renewable energy source units in this paper, a scenario-based method is used. In this method, the uncertainties of electrical market price, the wind speed, and solar irradiance are considered. This stochastic scheduling problem is a mixed integer- nonlinear programming which considers the proposed objective function and variables of coordinated scheduling of PEMFC-CHP, wind turbines and photovoltaic units. It also considers hydrogen storage strategy and converts it to a mixed integer nonlinear problem. In this study a modified firefly algorithm is used to solve the problem. This method is examined on modified 33-bus distributed network as a MG for its performance.
Incomplete Continuous-time Securities Markets with Stochastic Income Volatility
DEFF Research Database (Denmark)
Christensen, Peter Ove; Larsen, Kasper
2014-01-01
We derive closed-form solutions for the equilibrium interest rate and market price of risk processes in an incomplete continuous-time market with uncertainty generated by Brownian motions. The economy has a finite number of heterogeneous exponential utility investors, who receive partially...
Stochastic Resonance and First Arrival Time for Excitable Systems
Duki, Solomon Fekade; Taye, Mesfin Asfaw
2018-06-01
We study the noise induced thermally activated barrier crossing of Brownian particles that hop in a piecewise linear potential. Using the exact analytic solutions and via numerical simulations not only we explore the dependence for the first passage time of a single particle but also we calculate the first arrival time for one particle out of N particles. The first arrival time decreases as the number of particles increases as expected. We then explore the thermally activated barrier crossing rate of the system in the presence of time varying signal. The dependence of signal to noise ratio SNR as well as the power amplification (η ) on model parameters is explored. η and SNR depict a pronounced peak at particular noise strength. In the presence of N particles, η is considerably amplified as N steps up showing the weak periodic signal plays a vital role in controlling the noise induced dynamics of the system. Moreover, for the sake of generality, the viscous friction γ is considered to decrease exponentially when the temperature T of the medium increases (γ =Be^{-A T}) as proposed originally by Reynolds (Philos Trans R Soc Lond 177:157, 1886).
Incomplete Continuous-Time Securities Markets with Stochastic Income Volatility
DEFF Research Database (Denmark)
Christensen, Peter Ove; Larsen, Kasper
In an incomplete continuous-time securities market governed by Brownian motions, we derive closed-form solutions for the equilibrium risk-free rate and equity premium processes. The economy has a finite number of heterogeneous exponential utility investors, who receive partially unspanned income ...
A fire management simulation model using stochastic arrival times
Eric L. Smith
1987-01-01
Fire management simulation models are used to predict the impact of changes in the fire management program on fire outcomes. As with all models, the goal is to abstract reality without seriously distorting relationships between variables of interest. One important variable of fire organization performance is the length of time it takes to get suppression units to the...
International Nuclear Information System (INIS)
Buon, J.
1988-10-01
A new semiclassical and stochastic model of spin diffusion is used to obtain numerical predictions for depolarization enhancement due to beam energy spread. It confirms the results of previous models for the synchrotron sidebands of isolated spin resonances. A satisfactory agreement is obtained with the width of a synchrotron satellite observed at SPEAR. For HERA and LEP, at Z 0 energy, the depolarization enhancement is of the order of a few units and increases very rapidly with the energy spread. Large reduction of polarization degree is expected in these rings
Stochastic generation of hourly wind speed time series
International Nuclear Information System (INIS)
Shamshad, A.; Wan Mohd Ali Wan Hussin; Bawadi, M.A.; Mohd Sanusi, S.A.
2006-01-01
In the present study hourly wind speed data of Kuala Terengganu in Peninsular Malaysia are simulated by using transition matrix approach of Markovian process. The wind speed time series is divided into various states based on certain criteria. The next wind speed states are selected based on the previous states. The cumulative probability transition matrix has been formed in which each row ends with 1. Using the uniform random numbers between 0 and 1, a series of future states is generated. These states have been converted to the corresponding wind speed values using another uniform random number generator. The accuracy of the model has been determined by comparing the statistical characteristics such as average, standard deviation, root mean square error, probability density function and autocorrelation function of the generated data to those of the original data. The generated wind speed time series data is capable to preserve the wind speed characteristics of the observed data
International Nuclear Information System (INIS)
Nikzad, Mehdi; Mozafari, Babak; Bashirvand, Mahdi; Solaymani, Soodabeh; Ranjbar, Ali Mohamad
2012-01-01
Recently in electricity markets, a massive focus has been made on setting up opportunities for participating demand side. Such opportunities, also known as demand response (DR) options, are triggered by either a grid reliability problem or high electricity prices. Two important challenges that market operators are facing are appropriate designing and reasonable pricing of DR options. In this paper, time-of-use program (TOU) as a prevalent time-varying program is modeled linearly based on own and cross elasticity definition. In order to decide on TOU rates, a stochastic model is proposed in which the optimum TOU rates are determined based on grid reliability index set by the operator. Expected Load Not Supplied (ELNS) is used to evaluate reliability of the power system in each hour. The proposed stochastic model is formulated as a two-stage stochastic mixed-integer linear programming (SMILP) problem and solved using CPLEX solver. The validity of the method is tested over the IEEE 24-bus test system. In this regard, the impact of the proposed pricing method on system load profile; operational costs and required capacity of up- and down-spinning reserve as well as improvement of load factor is demonstrated. Also the sensitivity of the results to elasticity coefficients is investigated. -- Highlights: ► Time-of-use demand response program is linearly modeled. ► A stochastic model is proposed to determine the optimum TOU rates based on ELNS index set by the operator. ► The model is formulated as a short-term two-stage stochastic mixed-integer linear programming problem.
Bridging time scales in cellular decision making with a stochastic bistable switch
Directory of Open Access Journals (Sweden)
Waldherr Steffen
2010-08-01
Full Text Available Abstract Background Cellular transformations which involve a significant phenotypical change of the cell's state use bistable biochemical switches as underlying decision systems. Some of these transformations act over a very long time scale on the cell population level, up to the entire lifespan of the organism. Results In this work, we aim at linking cellular decisions taking place on a time scale of years to decades with the biochemical dynamics in signal transduction and gene regulation, occuring on a time scale of minutes to hours. We show that a stochastic bistable switch forms a viable biochemical mechanism to implement decision processes on long time scales. As a case study, the mechanism is applied to model the initiation of follicle growth in mammalian ovaries, where the physiological time scale of follicle pool depletion is on the order of the organism's lifespan. We construct a simple mathematical model for this process based on experimental evidence for the involved genetic mechanisms. Conclusions Despite the underlying stochasticity, the proposed mechanism turns out to yield reliable behavior in large populations of cells subject to the considered decision process. Our model explains how the physiological time constant may emerge from the intrinsic stochasticity of the underlying gene regulatory network. Apart from ovarian follicles, the proposed mechanism may also be of relevance for other physiological systems where cells take binary decisions over a long time scale.
Theory of time-averaged neutral dynamics with environmental stochasticity
Danino, Matan; Shnerb, Nadav M.
2018-04-01
Competition is the main driver of population dynamics, which shapes the genetic composition of populations and the assembly of ecological communities. Neutral models assume that all the individuals are equivalent and that the dynamics is governed by demographic (shot) noise, with a steady state species abundance distribution (SAD) that reflects a mutation-extinction equilibrium. Recently, many empirical and theoretical studies emphasized the importance of environmental variations that affect coherently the relative fitness of entire populations. Here we consider two generic time-averaged neutral models; in both the relative fitness of each species fluctuates independently in time but its mean is zero. The first (model A) describes a system with local competition and linear fitness dependence of the birth-death rates, while in the second (model B) the competition is global and the fitness dependence is nonlinear. Due to this nonlinearity, model B admits a noise-induced stabilization mechanism that facilitates the invasion of new mutants. A self-consistent mean-field approach is used to reduce the multispecies problem to two-species dynamics, and the large-N asymptotics of the emerging set of Fokker-Planck equations is presented and solved. Our analytic expressions are shown to fit the SADs obtained from extensive Monte Carlo simulations and from numerical solutions of the corresponding master equations.
A unified nonlinear stochastic time series analysis for climate science.
Moon, Woosok; Wettlaufer, John S
2017-03-13
Earth's orbit and axial tilt imprint a strong seasonal cycle on climatological data. Climate variability is typically viewed in terms of fluctuations in the seasonal cycle induced by higher frequency processes. We can interpret this as a competition between the orbitally enforced monthly stability and the fluctuations/noise induced by weather. Here we introduce a new time-series method that determines these contributions from monthly-averaged data. We find that the spatio-temporal distribution of the monthly stability and the magnitude of the noise reveal key fingerprints of several important climate phenomena, including the evolution of the Arctic sea ice cover, the El Nio Southern Oscillation (ENSO), the Atlantic Nio and the Indian Dipole Mode. In analogy with the classical destabilising influence of the ice-albedo feedback on summertime sea ice, we find that during some time interval of the season a destabilising process operates in all of these climate phenomena. The interaction between the destabilisation and the accumulation of noise, which we term the memory effect, underlies phase locking to the seasonal cycle and the statistical nature of seasonal predictability.
Relative Error Model Reduction via Time-Weighted Balanced Stochastic Singular Perturbation
DEFF Research Database (Denmark)
Tahavori, Maryamsadat; Shaker, Hamid Reza
2012-01-01
A new mixed method for relative error model reduction of linear time invariant (LTI) systems is proposed in this paper. This order reduction technique is mainly based upon time-weighted balanced stochastic model reduction method and singular perturbation model reduction technique. Compared...... by using the concept and properties of the reciprocal systems. The results are further illustrated by two practical numerical examples: a model of CD player and a model of the atmospheric storm track....
Reconstructing the hidden states in time course data of stochastic models.
Zimmer, Christoph
2015-11-01
Parameter estimation is central for analyzing models in Systems Biology. The relevance of stochastic modeling in the field is increasing. Therefore, the need for tailored parameter estimation techniques is increasing as well. Challenges for parameter estimation are partial observability, measurement noise, and the computational complexity arising from the dimension of the parameter space. This article extends the multiple shooting for stochastic systems' method, developed for inference in intrinsic stochastic systems. The treatment of extrinsic noise and the estimation of the unobserved states is improved, by taking into account the correlation between unobserved and observed species. This article demonstrates the power of the method on different scenarios of a Lotka-Volterra model, including cases in which the prey population dies out or explodes, and a Calcium oscillation system. Besides showing how the new extension improves the accuracy of the parameter estimates, this article analyzes the accuracy of the state estimates. In contrast to previous approaches, the new approach is well able to estimate states and parameters for all the scenarios. As it does not need stochastic simulations, it is of the same order of speed as conventional least squares parameter estimation methods with respect to computational time. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
DEFF Research Database (Denmark)
Foddai, Alessandro; Enøe, Claes; Krogh, Kaspar
2014-01-01
A stochastic simulation model was developed to estimate the time from introduction ofBovine Viral Diarrhea Virus (BVDV) in a herd to detection of antibodies in bulk tank milk(BTM) samples using three ELISAs. We assumed that antibodies could be detected, after afixed threshold prevalence of seroco......A stochastic simulation model was developed to estimate the time from introduction ofBovine Viral Diarrhea Virus (BVDV) in a herd to detection of antibodies in bulk tank milk(BTM) samples using three ELISAs. We assumed that antibodies could be detected, after afixed threshold prevalence......, which was the most efficient ELISA, could detect antibodiesin the BTM of a large herd 280 days (95% prediction interval: 218; 568) after a transientlyinfected (TI) milking cow has been introduced into the herd. The estimated time to detectionafter introduction of one PI calf was 111 days (44; 605...
Exponential stability result for discrete-time stochastic fuzzy uncertain neural networks
International Nuclear Information System (INIS)
Mathiyalagan, K.; Sakthivel, R.; Marshal Anthoni, S.
2012-01-01
This Letter addresses the stability analysis problem for a class of uncertain discrete-time stochastic fuzzy neural networks (DSFNNs) with time-varying delays. By constructing a new Lyapunov–Krasovskii functional combined with the free weighting matrix technique, a new set of delay-dependent sufficient conditions for the robust exponential stability of the considered DSFNNs is established in terms of Linear Matrix Inequalities (LMIs). Finally, numerical examples with simulation results are provided to illustrate the applicability and usefulness of the obtained theory. -- Highlights: ► Applications of neural networks require the knowledge of dynamic behaviors. ► Exponential stability of discrete-time stochastic fuzzy neural networks is studied. ► Linear matrix inequality optimization approach is used to obtain the result. ► Delay-dependent stability criterion is established in terms of LMIs. ► Examples with simulation are provided to show the effectiveness of the result.
Yang, Xin; Zeng, Zhenxiang; Wang, Ruidong; Sun, Xueshan
2016-01-01
This paper presents a novel method on the optimization of bi-objective Flexible Job-shop Scheduling Problem (FJSP) under stochastic processing times. The robust counterpart model and the Non-dominated Sorting Genetic Algorithm II (NSGA-II) are used to solve the bi-objective FJSP with consideration of the completion time and the total energy consumption under stochastic processing times. The case study on GM Corporation verifies that the NSGA-II used in this paper is effective and has advantages to solve the proposed model comparing with HPSO and PSO+SA. The idea and method of the paper can be generalized widely in the manufacturing industry, because it can reduce the energy consumption of the energy-intensive manufacturing enterprise with less investment when the new approach is applied in existing systems.
International Nuclear Information System (INIS)
Olsson, Magnus; Perninge, Magnus; Soeder, Lennart
2010-01-01
The inclusion of wind power into power systems has a significant impact on the demand for real-time balancing power due to the stochastic nature of wind power production. The overall aim of this paper is to present probabilistic models of the impact of large-scale integration of wind power on the continuous demand in MW for real-time balancing power. This is important not only for system operators, but also for producers and consumers since they in most systems through various market solutions provide balancing power. Since there can occur situations where the wind power variations cancel out other types of deviations in the system, models on an hourly basis are not sufficient. Therefore the developed model is in continuous time and is based on stochastic differential equations (SDE). The model can be used within an analytical framework or in Monte Carlo simulations. (author)
Monte Carlo simulation of induction time and metastable zone width; stochastic or deterministic?
Kubota, Noriaki
2018-03-01
The induction time and metastable zone width (MSZW) measured for small samples (say 1 mL or less) both scatter widely. Thus, these two are observed as stochastic quantities. Whereas, for large samples (say 1000 mL or more), the induction time and MSZW are observed as deterministic quantities. The reason for such experimental differences is investigated with Monte Carlo simulation. In the simulation, the time (under isothermal condition) and supercooling (under polythermal condition) at which a first single crystal is detected are defined as the induction time t and the MSZW ΔT for small samples, respectively. The number of crystals just at the moment of t and ΔT is unity. A first crystal emerges at random due to the intrinsic nature of nucleation, accordingly t and ΔT become stochastic. For large samples, the time and supercooling at which the number density of crystals N/V reaches a detector sensitivity (N/V)det are defined as t and ΔT for isothermal and polythermal conditions, respectively. The points of t and ΔT are those of which a large number of crystals have accumulated. Consequently, t and ΔT become deterministic according to the law of large numbers. Whether t and ΔT may stochastic or deterministic in actual experiments should not be attributed to change in nucleation mechanisms in molecular level. It could be just a problem caused by differences in the experimental definition of t and ΔT.
Effects of time delay on stochastic resonance of the stock prices in financial system
International Nuclear Information System (INIS)
Li, Jiang-Cheng; Li, Chun; Mei, Dong-Cheng
2014-01-01
The effect of time delay on stochastic resonance of the stock prices in finance system was investigated. The time delay is introduced into the Heston model driven by the extrinsic and intrinsic periodic information for stock price. The signal power amplification (SPA) was calculated by numerical simulation. The results indicate that an optimal critical value of delay time maximally enhances the reverse-resonance in the behaviors of SPA as a function of long-run variance of volatility or cross correlation coefficient between noises for both cases of intrinsic and extrinsic periodic information. Moreover, in both cases, being a critical value in the delay time, when the delay time takes value below the critical value, reverse-resonance increases with the delay time increasing, however, when the delay time takes value above the critical value, the reverse-resonance decrease with the delay time increasing. - Highlights: • The effects of delay time on stochastic resonance of the stock prices was investigated. • There is an optimal critical value of delay time maximally enhances the reverse-resonance • The reverse-resonance increases with the delay time increasing as the delay time takes value below the critical value • The reverse-resonance decrease with the delay time increasing as the delay time takes value above the critical value
Effects of time delay on stochastic resonance of the stock prices in financial system
Energy Technology Data Exchange (ETDEWEB)
Li, Jiang-Cheng [Department of Physics, Yunnan University, Kunming, 650091 (China); Li, Chun [Department of Computer Science, Puer Teachers' College, Puer 665000 (China); Mei, Dong-Cheng, E-mail: meidch@ynu.edu.cn [Department of Physics, Yunnan University, Kunming, 650091 (China)
2014-06-13
The effect of time delay on stochastic resonance of the stock prices in finance system was investigated. The time delay is introduced into the Heston model driven by the extrinsic and intrinsic periodic information for stock price. The signal power amplification (SPA) was calculated by numerical simulation. The results indicate that an optimal critical value of delay time maximally enhances the reverse-resonance in the behaviors of SPA as a function of long-run variance of volatility or cross correlation coefficient between noises for both cases of intrinsic and extrinsic periodic information. Moreover, in both cases, being a critical value in the delay time, when the delay time takes value below the critical value, reverse-resonance increases with the delay time increasing, however, when the delay time takes value above the critical value, the reverse-resonance decrease with the delay time increasing. - Highlights: • The effects of delay time on stochastic resonance of the stock prices was investigated. • There is an optimal critical value of delay time maximally enhances the reverse-resonance • The reverse-resonance increases with the delay time increasing as the delay time takes value below the critical value • The reverse-resonance decrease with the delay time increasing as the delay time takes value above the critical value.
Directory of Open Access Journals (Sweden)
Pengfei Guo
2014-01-01
Full Text Available This paper deals with the fault detection problem for a class of discrete-time wireless networked control systems described by switching topology with uncertainties and disturbances. System states of each individual node are affected not only by its own measurements, but also by other nodes’ measurements according to a certain network topology. As the topology of system can be switched in a stochastic way, we aim to design H∞ fault detection observers for nodes in the dynamic time-delay systems. By using the Lyapunov method and stochastic analysis techniques, sufficient conditions are acquired to guarantee the existence of the filters satisfying the H∞ performance constraint, and observer gains are derived by solving linear matrix inequalities. Finally, an illustrated example is provided to verify the effectiveness of the theoretical results.
Absolute continuity under time shift of trajectories and related stochastic calculus
Löbus, Jörg-Uwe
2017-01-01
The text is concerned with a class of two-sided stochastic processes of the form X=W+A. Here W is a two-sided Brownian motion with random initial data at time zero and A\\equiv A(W) is a function of W. Elements of the related stochastic calculus are introduced. In particular, the calculus is adjusted to the case when A is a jump process. Absolute continuity of (X,P) under time shift of trajectories is investigated. For example under various conditions on the initial density with respect to the Lebesgue measure, m, and on A with A_0=0 we verify \\frac{P(dX_{\\cdot -t})}{P(dX_\\cdot)}=\\frac{m(X_{-t})}{m(X_0)}\\cdot \\prod_i\\left|\
Volatility Degree Forecasting of Stock Market by Stochastic Time Strength Neural Network
Directory of Open Access Journals (Sweden)
Haiyan Mo
2013-01-01
Full Text Available In view of the applications of artificial neural networks in economic and financial forecasting, a stochastic time strength function is introduced in the backpropagation neural network model to predict the fluctuations of stock price changes. In this model, stochastic time strength function gives a weight for each historical datum and makes the model have the effect of random movement, and then we investigate and forecast the behavior of volatility degrees of returns for the Chinese stock market indexes and some global market indexes. The empirical research is performed in testing the prediction effect of SSE, SZSE, HSI, DJIA, IXIC, and S&P 500 with different selected volatility degrees in the established model.
Sliding mode control-based linear functional observers for discrete-time stochastic systems
Singh, Satnesh; Janardhanan, Sivaramakrishnan
2017-11-01
Sliding mode control (SMC) is one of the most popular techniques to stabilise linear discrete-time stochastic systems. However, application of SMC becomes difficult when the system states are not available for feedback. This paper presents a new approach to design a SMC-based functional observer for discrete-time stochastic systems. The functional observer is based on the Kronecker product approach. Existence conditions and stability analysis of the proposed observer are given. The control input is estimated by a novel linear functional observer. This approach leads to a non-switching type of control, thereby eliminating the fundamental cause of chatter. Furthermore, the functional observer is designed in such a way that the effect of process and measurement noise is minimised. Simulation example is given to illustrate and validate the proposed design method.
Robust stability for stochastic bidirectional associative memory neural networks with time delays
Shu, H. S.; Lv, Z. W.; Wei, G. L.
2008-02-01
In this paper, the asymptotic stability is considered for a class of uncertain stochastic bidirectional associative memory neural networks with time delays and parameter uncertainties. The delays are time-invariant and the uncertainties are norm-bounded that enter into all network parameters. The aim of this paper is to establish easily verifiable conditions under which the delayed neural network is robustly asymptotically stable in the mean square for all admissible parameter uncertainties. By employing a Lyapunov-Krasovskii functional and conducting the stochastic analysis, a linear matrix inequality matrix inequality (LMI) approach is developed to derive the stability criteria. The proposed criteria can be easily checked by the Matlab LMI toolbox. A numerical example is given to demonstrate the usefulness of the proposed criteria.
Anderson, David F; Yuan, Chaojie
2018-04-18
A number of coupling strategies are presented for stochastically modeled biochemical processes with time-dependent parameters. In particular, the stacked coupling is introduced and is shown via a number of examples to provide an exceptionally low variance between the generated paths. This coupling will be useful in the numerical computation of parametric sensitivities and the fast estimation of expectations via multilevel Monte Carlo methods. We provide the requisite estimators in both cases.
A note on "Multicriteria adaptive paths in stochastic, time-varying networks"
DEFF Research Database (Denmark)
Pretolani, Daniele; Nielsen, Lars Relund; Andersen, Kim Allan
In a recent paper, Opasanon and Miller-Hooks study multicriteria adaptive paths in stochastic time-varying networks. They propose a label correcting algorithm for finding the full set of efficient strategies. In this note we show that their algorithm is not correct, since it is based on a property...... that does not hold in general. Opasanon and Miller-Hooks also propose an algorithm for solving a parametric problem. We give a simplified algorithm which is linear in the input size....
Improved result on stability analysis of discrete stochastic neural networks with time delay
International Nuclear Information System (INIS)
Wu Zhengguang; Su Hongye; Chu Jian; Zhou Wuneng
2009-01-01
This Letter investigates the problem of exponential stability for discrete stochastic time-delay neural networks. By defining a novel Lyapunov functional, an improved delay-dependent exponential stability criterion is established in terms of linear matrix inequality (LMI) approach. Meanwhile, the computational complexity of the newly established stability condition is reduced because less variables are involved. Numerical example is given to illustrate the effectiveness and the benefits of the proposed method.
International Nuclear Information System (INIS)
Bornapour, Mosayeb; Hooshmand, Rahmat-Allah; Khodabakhshian, Amin; Parastegari, Moein
2017-01-01
Highlights: • Stochastic model is proposed for coordinated scheduling of renewable energy sources. • The effect of combined heat and power is considered. • Uncertainties of wind speed, solar radiation and electricity market price are considered. • Profit maximization, emission and AENS minimization are considered as objective functions. • Modified firefly algorithm is employed to solve the problem. - Abstract: Nowadays the operation of renewable energy sources and combined heat and power (CHP) units is increased in micro grids; therefore, to reach optimal performance, optimal scheduling of these units is required. In this regard, in this paper a micro grid consisting of proton exchange membrane fuel cell-combined heat and power (PEMFC-CHP), wind turbines (WT) and photovoltaic (PV) units, is modeled to determine the optimal scheduling state of these units by considering uncertain behavior of renewable energy resources. For this purpose, a scenario-based method is used for modeling the uncertainties of electrical market price, the wind speed, and solar irradiance. It should be noted that the hydrogen storage strategy is also applied in this study for PEMFC-CHP units. Market profit, total emission production, and average energy not supplied (AENS) are the objective functions considered in this paper simultaneously. Consideration of the above-mentioned objective functions converts the proposed problem to a mixed integer nonlinear programming. To solve this problem, a multi-objective firefly algorithm is used. The uncertainties of parameters convert the mixed integer nonlinear programming problem to a stochastic mixed integer nonlinear programming problem. Moreover, optimal coordinated scheduling of renewable energy resources and thermal units in micro-grids improve the value of the objective functions. Simulation results obtained from a modified 33-bus distributed network as a micro grid illustrates the effectiveness of the proposed method.
Optimal Stochastic Management of Distributed Energy Storage Embedded with Wind Farms
Yanchi, Xiao; Vargas, Bruce; Hamdi, Mohammd
2018-01-01
Increasing wind turbines (WT) penetration and low carbon demand can potentially lead to two different flow peaks, generation and load, within distribution networks. This will not only constrain WT penetration but also pose serious threats to network reliability. This paper proposes energy storage (ES) to reduce system congestion cost caused by the two peaks by sending cost-reflective economic signals to affect ES operation in responding to network conditions. Firstly, a new charging and disch...
Directory of Open Access Journals (Sweden)
Xiao-Li Ding
2018-01-01
Full Text Available In this paper, we investigate analytical solutions of multi-time scale fractional stochastic differential equations driven by fractional Brownian motions. We firstly decompose homogeneous multi-time scale fractional stochastic differential equations driven by fractional Brownian motions into independent differential subequations, and give their analytical solutions. Then, we use the variation of constant parameters to obtain the solutions of nonhomogeneous multi-time scale fractional stochastic differential equations driven by fractional Brownian motions. Finally, we give three examples to demonstrate the applicability of our obtained results.
Moeeni, Hamid; Bonakdari, Hossein; Fatemi, Seyed Ehsan
2017-04-01
Because time series stationarization has a key role in stochastic modeling results, three methods are analyzed in this study. The methods are seasonal differencing, seasonal standardization and spectral analysis to eliminate the periodic effect on time series stationarity. First, six time series including 4 streamflow series and 2 water temperature series are stationarized. The stochastic term for these series obtained with ARIMA is subsequently modeled. For the analysis, 9228 models are introduced. It is observed that seasonal standardization and spectral analysis eliminate the periodic term completely, while seasonal differencing maintains seasonal correlation structures. The obtained results indicate that all three methods present acceptable performance overall. However, model accuracy in monthly streamflow prediction is higher with seasonal differencing than with the other two methods. Another advantage of seasonal differencing over the other methods is that the monthly streamflow is never estimated as negative. Standardization is the best method for predicting monthly water temperature although it is quite similar to seasonal differencing, while spectral analysis performed the weakest in all cases. It is concluded that for each monthly seasonal series, seasonal differencing is the best stationarization method in terms of periodic effect elimination. Moreover, the monthly water temperature is predicted with more accuracy than monthly streamflow. The criteria of the average stochastic term divided by the amplitude of the periodic term obtained for monthly streamflow and monthly water temperature were 0.19 and 0.30, 0.21 and 0.13, and 0.07 and 0.04 respectively. As a result, the periodic term is more dominant than the stochastic term for water temperature in the monthly water temperature series compared to streamflow series.
International Nuclear Information System (INIS)
Rougé, Charles; Mathias, Jean-Denis; Deffuant, Guillaume
2014-01-01
The goal of this paper is twofold: (1) to show that time-variant reliability and a branch of control theory called stochastic viability address similar problems with different points of view, and (2) to demonstrate the relevance of concepts and methods from stochastic viability in reliability problems. On the one hand, reliability aims at evaluating the probability of failure of a system subjected to uncertainty and stochasticity. On the other hand, viability aims at maintaining a controlled dynamical system within a survival set. When the dynamical system is stochastic, this work shows that a viability problem belongs to a specific class of design and maintenance problems in time-variant reliability. Dynamic programming, which is used for solving Markovian stochastic viability problems, then yields the set of design states for which there exists a maintenance strategy which guarantees reliability with a confidence level β for a given period of time T. Besides, it leads to a straightforward computation of the date of the first outcrossing, informing on when the system is most likely to fail. We illustrate this approach with a simple example of population dynamics, including a case where load increases with time. - Highlights: • Time-variant reliability tools cannot devise complex maintenance strategies. • Stochastic viability is a control theory that computes a probability of failure. • Some design and maintenance problems are stochastic viability problems. • Used in viability, dynamic programming can find reliable maintenance actions. • Confronting reliability and control theories such as viability is promising
Streeter, Lee
2017-07-01
Time-of-flight range imaging is analyzed using stochastic calculus. Through a series of interpretations and simplifications, the stochastic model leads to two methods for estimating linear radial velocity: maximum likelihood estimation on the transition probability distribution between measurements, and a new method based on analyzing the measured correlation waveform and its first derivative. The methods are tested in a simulated motion experiment from (-40)-(+40) m/s, with data from a camera imaging an object on a translation stage. In tests maximum likelihood is slow and unreliable, but when it works it estimates the linear velocity with standard deviation of 1 m/s or better. In comparison the new method is fast and reliable but works in a reduced velocity range of (-20)-(+20) m/s with standard deviation ranging from 3.5 m/s to 10 m/s.
Stochastic models for structured populations scaling limits and long time behavior
Meleard, Sylvie
2015-01-01
In this contribution, several probabilistic tools to study population dynamics are developed. The focus is on scaling limits of qualitatively different stochastic individual based models and the long time behavior of some classes of limiting processes. Structured population dynamics are modeled by measure-valued processes describing the individual behaviors and taking into account the demographic and mutational parameters, and possible interactions between individuals. Many quantitative parameters appear in these models and several relevant normalizations are considered, leading to infinite-dimensional deterministic or stochastic large-population approximations. Biologically relevant questions are considered, such as extinction criteria, the effect of large birth events, the impact of environmental catastrophes, the mutation-selection trade-off, recovery criteria in parasite infections, genealogical properties of a sample of individuals. These notes originated from a lecture series on Structured P...
Risk-sensitive control of stochastic hybrid systems on infinite time horizon
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Runolfsson Thordur
1999-01-01
Full Text Available A risk-sensitive optimal control problem is considered for a hybrid system that consists of continuous time diffusion process that depends on a discrete valued mode variable that is modeled as a Markov chain. Optimality conditions are presented and conditions for the existence of optimal controls are derived. It is shown that the optimal risk-sensitive control problem is equivalent to the upper value of an associated stochastic differential game, and insight into the contributions of the noise input and mode variable to the risk sensitivity of the cost functional is given. Furthermore, it is shown that due to the mode variable risk sensitivity, the equivalence relationship that has been observed between risk-sensitive and H ∞ control in the nonhybrid case does not hold for stochastic hybrid systems.
Directory of Open Access Journals (Sweden)
Ryota Mori
2015-01-01
Full Text Available Airport congestion, in particular congestion of departure aircraft, has already been discussed by other researches. Most solutions, though, fail to account for uncertainties. Since it is difficult to remove uncertainties of the operations in the real world, a strategy should be developed assuming such uncertainties exist. Therefore, this research develops a fast-time stochastic simulation model used to validate various methods in order to decrease airport congestion level under existing uncertainties. The surface movement data is analyzed first, and the uncertainty level is obtained. Next, based on the result of data analysis, the stochastic simulation model is developed. The model is validated statistically and the characteristics of airport operation under existing uncertainties are investigated.
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Noble Mark
2006-05-01
Full Text Available Abstract Background The purpose of this paper is two-fold. The first objective is to validate the assumptions behind a stochastic model developed earlier by these authors to describe oligodendrocyte generation in cell culture. The second is to generate time-lapse data that may help biomathematicians to build stochastic models of cell proliferation and differentiation under other experimental scenarios. Results Using time-lapse video recording it is possible to follow the individual evolutions of different cells within each clone. This experimental technique is very laborious and cannot replace model-based quantitative inference from clonal data. However, it is unrivalled in validating the structure of a stochastic model intended to describe cell proliferation and differentiation at the clonal level. In this paper, such data are reported and analyzed for oligodendrocyte precursor cells cultured in vitro. Conclusion The results strongly support the validity of the most basic assumptions underpinning the previously proposed model of oligodendrocyte development in cell culture. However, there are some discrepancies; the most important is that the contribution of progenitor cell death to cell kinetics in this experimental system has been underestimated.
International Nuclear Information System (INIS)
Wu, Fuke; Tian, Tianhai; Rawlings, James B.; Yin, George
2016-01-01
The frequently used reduction technique is based on the chemical master equation for stochastic chemical kinetics with two-time scales, which yields the modified stochastic simulation algorithm (SSA). For the chemical reaction processes involving a large number of molecular species and reactions, the collection of slow reactions may still include a large number of molecular species and reactions. Consequently, the SSA is still computationally expensive. Because the chemical Langevin equations (CLEs) can effectively work for a large number of molecular species and reactions, this paper develops a reduction method based on the CLE by the stochastic averaging principle developed in the work of Khasminskii and Yin [SIAM J. Appl. Math. 56, 1766–1793 (1996); ibid. 56, 1794–1819 (1996)] to average out the fast-reacting variables. This reduction method leads to a limit averaging system, which is an approximation of the slow reactions. Because in the stochastic chemical kinetics, the CLE is seen as the approximation of the SSA, the limit averaging system can be treated as the approximation of the slow reactions. As an application, we examine the reduction of computation complexity for the gene regulatory networks with two-time scales driven by intrinsic noise. For linear and nonlinear protein production functions, the simulations show that the sample average (expectation) of the limit averaging system is close to that of the slow-reaction process based on the SSA. It demonstrates that the limit averaging system is an efficient approximation of the slow-reaction process in the sense of the weak convergence.
Directory of Open Access Journals (Sweden)
Giorgos Minas
2017-07-01
Full Text Available In order to analyse large complex stochastic dynamical models such as those studied in systems biology there is currently a great need for both analytical tools and also algorithms for accurate and fast simulation and estimation. We present a new stochastic approximation of biological oscillators that addresses these needs. Our method, called phase-corrected LNA (pcLNA overcomes the main limitations of the standard Linear Noise Approximation (LNA to remain uniformly accurate for long times, still maintaining the speed and analytically tractability of the LNA. As part of this, we develop analytical expressions for key probability distributions and associated quantities, such as the Fisher Information Matrix and Kullback-Leibler divergence and we introduce a new approach to system-global sensitivity analysis. We also present algorithms for statistical inference and for long-term simulation of oscillating systems that are shown to be as accurate but much faster than leaping algorithms and algorithms for integration of diffusion equations. Stochastic versions of published models of the circadian clock and NF-κB system are used to illustrate our results.
The Ising Decision Maker: a binary stochastic network for choice response time.
Verdonck, Stijn; Tuerlinckx, Francis
2014-07-01
The Ising Decision Maker (IDM) is a new formal model for speeded two-choice decision making derived from the stochastic Hopfield network or dynamic Ising model. On a microscopic level, it consists of 2 pools of binary stochastic neurons with pairwise interactions. Inside each pool, neurons excite each other, whereas between pools, neurons inhibit each other. The perceptual input is represented by an external excitatory field. Using methods from statistical mechanics, the high-dimensional network of neurons (microscopic level) is reduced to a two-dimensional stochastic process, describing the evolution of the mean neural activity per pool (macroscopic level). The IDM can be seen as an abstract, analytically tractable multiple attractor network model of information accumulation. In this article, the properties of the IDM are studied, the relations to existing models are discussed, and it is shown that the most important basic aspects of two-choice response time data can be reproduced. In addition, the IDM is shown to predict a variety of observed psychophysical relations such as Piéron's law, the van der Molen-Keuss effect, and Weber's law. Using Bayesian methods, the model is fitted to both simulated and real data, and its performance is compared to the Ratcliff diffusion model. (c) 2014 APA, all rights reserved.
Stochastic behavior of a cold standby system with maximum repair time
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Ashish Kumar
2015-09-01
Full Text Available The main aim of the present paper is to analyze the stochastic behavior of a cold standby system with concept of preventive maintenance, priority and maximum repair time. For this purpose, a stochastic model is developed in which initially one unit is operative and other is kept as cold standby. There is a single server who visits the system immediately as and when required. The server takes the unit under preventive maintenance after a maximum operation time at normal mode if one standby unit is available for operation. If the repair of the failed unit is not possible up to a maximum repair time, failed unit is replaced by new one. The failure time, maximum operation time and maximum repair time distributions of the unit are considered as exponentially distributed while repair and maintenance time distributions are considered as arbitrary. All random variables are statistically independent and repairs are perfect. Various measures of system effectiveness are obtained by using the technique of semi-Markov process and RPT. To highlight the importance of the study numerical results are also obtained for MTSF, availability and profit function.
Critical spare parts ordering decisions using conditional reliability and stochastic lead time
International Nuclear Information System (INIS)
Godoy, David R.; Pascual, Rodrigo; Knights, Peter
2013-01-01
Asset-intensive companies face great pressure to reduce operation costs and increase utilization. This scenario often leads to over-stress on critical equipment and its spare parts associated, affecting availability, reliability, and system performance. As these resources impact considerably on financial and operational structures, the opportunity is given by demand for decision-making methods for the management of spare parts processes. We proposed an ordering decision-aid technique which uses a measurement of spare performance, based on the stress–strength interference theory; which we have called Condition-Based Service Level (CBSL). We focus on Condition Managed Critical Spares (CMS), namely, spares which are expensive, highly reliable, with higher lead times, and are not available in store. As a mitigation measure, CMS are under condition monitoring. The aim of the paper is orienting the decision time for CMS ordering or just continuing the operation. The paper presents a graphic technique which considers a rule for decision based on both condition-based reliability function and a stochastic/fixed lead time. For the stochastic lead time case, results show that technique is effective to determine the time when the system operation is reliable and can withstand the lead time variability, satisfying a desired service level. Additionally, for the constant lead time case, the technique helps to define insurance spares. In conclusion, presented ordering decision rule is useful to asset managers for enhancing the operational continuity affected by spare parts
International Nuclear Information System (INIS)
Ju, Liwei; Tan, Zhongfu; Yuan, Jinyun; Tan, Qingkun; Li, Huanhuan; Dong, Fugui
2016-01-01
Highlights: • Our research focuses on Virtual Power Plant (VPP). • Virtual Power Plant consists of WPP, PV, CGT, ESSs and DRPs. • Robust optimization theory is introduced to analyze uncertainties. • A bi-level stochastic scheduling optimization model is proposed for VPP. • Models are built to measure the impacts of ESSs and DERPs on VPP operation. - Abstract: To reduce the uncertain influence of wind power and solar photovoltaic power on virtual power plant (VPP) operation, robust optimization theory (ROT) is introduced to build a stochastic scheduling model for VPP considering the uncertainty, price-based demand response (PBDR) and incentive-based demand response (IBDR). First, the VPP components are described including the wind power plant (WPP), photovoltaic generators (PV), convention gas turbine (CGT), energy storage systems (ESSs) and demand resource providers (DRPs). Then, a scenario generation and reduction frame is proposed for analyzing and simulating output stochastics based on the interval method and the Kantorovich distance. Second, a bi-level robust scheduling model is proposed with a double robust coefficient for WPP and PV. In the upper layer model, the maximum VPP operation income is taken as the optimization objective for building the scheduling model with the day-ahead prediction output of WPP and PV. In the lower layer model, the day-ahead scheduling scheme is revised with the actual output of the WPP and PV under the objectives of the minimum system net load and the minimum system operation cost. Finally, the independent micro-grid in a coastal island in eastern China is used for the simulation analysis. The results illustrate that the model can overcome the influence of uncertainty on VPP operations and reduce the system power shortage cost by connecting the day-ahead scheduling with the real-time scheduling. ROT could provide a flexible decision tool for decision makers, effectively addressing system uncertainties. ESSs could
Identification of the structure parameters using short-time non-stationary stochastic excitation
Jarczewska, Kamila; Koszela, Piotr; Śniady, PaweŁ; Korzec, Aleksandra
2011-07-01
In this paper, we propose an approach to the flexural stiffness or eigenvalue frequency identification of a linear structure using a non-stationary stochastic excitation process. The idea of the proposed approach lies within time domain input-output methods. The proposed method is based on transforming the dynamical problem into a static one by integrating the input and the output signals. The output signal is the structure reaction, i.e. structure displacements due to the short-time, irregular load of random type. The systems with single and multiple degrees of freedom, as well as continuous systems are considered.
On time-dependent diffusion coefficients arising from stochastic processes with memory
Carpio-Bernido, M. Victoria; Barredo, Wilson I.; Bernido, Christopher C.
2017-08-01
Time-dependent diffusion coefficients arise from anomalous diffusion encountered in many physical systems such as protein transport in cells. We compare these coefficients with those arising from analysis of stochastic processes with memory that go beyond fractional Brownian motion. Facilitated by the Hida white noise functional integral approach, diffusion propagators or probability density functions (pdf) are obtained and shown to be solutions of modified diffusion equations with time-dependent diffusion coefficients. This should be useful in the study of complex transport processes.
Eco-reliable path finding in time-variant and stochastic networks
International Nuclear Information System (INIS)
Li, Wenjie; Yang, Lixing; Wang, Li; Zhou, Xuesong; Liu, Ronghui; Gao, Ziyou
2017-01-01
This paper addresses a route guidance problem for finding the most eco-reliable path in time-variant and stochastic networks such that travelers can arrive at the destination with the maximum on-time probability while meeting vehicle emission standards imposed by government regulators. To characterize the dynamics and randomness of transportation networks, the link travel times and emissions are assumed to be time-variant random variables correlated over the entire network. A 0–1 integer mathematical programming model is formulated to minimize the probability of late arrival by simultaneously considering the least expected emission constraint. Using the Lagrangian relaxation approach, the primal model is relaxed into a dualized model which is further decomposed into two simple sub-problems. A sub-gradient method is developed to reduce gaps between upper and lower bounds. Three sets of numerical experiments are tested to demonstrate the efficiency and performance of our proposed model and algorithm. - Highlights: • The most eco-reliable path is defined in time-variant and stochastic networks. • The model is developed with on-time arrival probability and emission constraints. • The sub-gradient and label correcting algorithm are integrated to solve the model. • Numerical experiments demonstrate the effectiveness of developed approaches.
International Nuclear Information System (INIS)
De-Yi, Chen; Li, Zhang
2009-01-01
This paper investigates the phenomenon of stochastic resonance in a single-mode laser driven by time-modulated correlated coloured noise sources. The power spectrum and signal-to-noise ratio R of the laser intensity are calculated by the linear approximation. The effects caused by noise self-correlation time τ 1 , τ 2 and cross-correlated time τ 3 for stochastic resonance are analysed in two ways: τ 1 , τ 2 and τ 3 are taken to be the independent variables and the parameters respectively. The effects of the gain coefficient Γ and loss coefficient K on the stochastic resonance are also discussed. It is found that besides the presence of the standard form and the broad sense of stochastic resonance, the number of extrema in the curve of R versus K is reduced with the increase of the gain coefficient Γ
Contribution to the stochastically studies of space-time dependable hydrological processes
International Nuclear Information System (INIS)
Kjaevski, Ivancho
2002-12-01
One of the fundaments of today's planning and water economy is Science of Hydrology. Science of Hydrology through the history had followed the development of the water management systems. Water management systems, during the time from single-approach evolved to complex and multi purpose systems. The dynamic and development of the today's society contributed for increasing the demand of clean water, and in the same time, the resources of clean water in the nature are reduced. In this kind of conditions, water management systems should resolve problems that are more complicated during managing of water sources. Solving the problems in water management, enable development and applying new methods and technologies in planning and management with water resources and water management systems like: systematical analyses, operational research, hierarchy decisions, expert systems, computer technology etc. Planning and management of water sources needs historical measured data for hydro metrological processes. In our country there are data of hydro metrological processes in period of 50-70, but in some Europe countries there are data more than 100 years. Water economy trends follow the hydro metrological trend research. The basic statistic techniques like sampling, probability distribution function, correlation and regression, are used about one intended and simple water management problems. Solving new problems about water management needs using of space-time stochastic technique, modem mathematical and statistical techniques during simulation and optimization of complex water systems. We need tree phases of development of the techniques to get secure hydrological models: i) Estimate the quality of hydro meteorological data, analyzing of their consistency, and homogeneous; ii) Structural analyze of hydro meteorological processes; iii) Mathematical models for modeling hydro meteorological processes. Very often, the third phase is applied for analyzing and modeling of hydro
International Nuclear Information System (INIS)
Vecherin, Sergey N; Ostashev, Vladimir E; Wilson, D Keith; Ziemann, A
2008-01-01
Time-dependent stochastic inversion (TDSI) was recently developed for acoustic travel-time tomography of the atmosphere. This type of tomography allows reconstruction of temperature and wind-velocity fields given the location of sound sources and receivers and the travel times between all source–receiver pairs. The quality of reconstruction provided by TDSI depends on the geometry of the transducer array. However, TDSI has not been studied for the geometry with reciprocal sound transmission. This paper is focused on three aspects of TDSI. First, the use of TDSI in reciprocal sound transmission arrays is studied in numerical and physical experiments. Second, efficiency of time-dependent and ordinary stochastic inversion (SI) algorithms is studied in numerical experiments. Third, a new model of noise in the input data for TDSI is developed that accounts for systematic errors in transducer positions. It is shown that (i) a separation of the travel times into temperature and wind-velocity components in tomography with reciprocal transmission does not improve the reconstruction, (ii) TDSI yields a better reconstruction than SI and (iii) the developed model of noise yields an accurate reconstruction of turbulent fields and estimation of errors in the reconstruction
A stochastic fractional dynamics model of space-time variability of rain
Kundu, Prasun K.; Travis, James E.
2013-09-01
varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, which allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and time scales. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and on the Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to fit the second moment statistics of radar data at the smaller spatiotemporal scales. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well at these scales without any further adjustment.
Directory of Open Access Journals (Sweden)
Shichao Sun
2015-01-01
Full Text Available This paper addressed the vehicle routing problem (VRP in large-scale urban transportation networks with stochastic time-dependent (STD travel times. The subproblem which is how to find the optimal path connecting any pair of customer nodes in a STD network was solved through a robust approach without requiring the probability distributions of link travel times. Based on that, the proposed STD-VRP model can be converted into solving a normal time-dependent VRP (TD-VRP, and algorithms for such TD-VRPs can also be introduced to obtain the solution. Numerical experiments were conducted to address STD-VRPTW of practical sizes on a real world urban network, demonstrated here on the road network of Shenzhen, China. The stochastic time-dependent link travel times of the network were calibrated by historical floating car data. A route construction algorithm was applied to solve the STD problem in 4 delivery scenarios efficiently. The computational results showed that the proposed STD-VRPTW model can improve the level of customer service by satisfying the time-window constraint under any circumstances. The improvement can be very significant especially for large-scale network delivery tasks with no more increase in cost and environmental impacts.
DEFF Research Database (Denmark)
Lund, K.E.; Nielsen, Henrik Hauch
2001-01-01
Changes in free amino acids (FAAs), small peptides and myofibrillar proteins were investigated in salmon (Salmo salar) muscle stored at OC for up to 23 days and after the stored salmon was smoked. Storage time and smoking process did not increase the formation of FAAs and small peptides indicating...
Strategic WIP Inventory Positioning for Make-to-Order Production with Stochastic Processing Times
Directory of Open Access Journals (Sweden)
Jingjing Jiang
2017-01-01
Full Text Available It is vital for make-to-order manufacturers to shorten the lead time to meet the customers’ requirements. Holding work-in-process (WIP inventory at more stations can reduce the lead time, but it also brings about higher inventory holding cost. Therefore, it is important to seek out the optimal set of stations to hold WIP inventory to minimize the total inventory holding cost, while meeting the required due date for the final product at the same time. Since the problem with deterministic processing times at the stations has been addressed, as a natural extension, in this study, we address the problem with stochastic processing times, which is more realistic in the manufacturing environment. Assuming that the processing times follow normal distributions, we propose a solution procedure using genetic algorithm.
Schilde, M; Doerner, K F; Hartl, R F
2014-10-01
In urban areas, logistic transportation operations often run into problems because travel speeds change, depending on the current traffic situation. If not accounted for, time-dependent and stochastic travel speeds frequently lead to missed time windows and thus poorer service. Especially in the case of passenger transportation, it often leads to excessive passenger ride times as well. Therefore, time-dependent and stochastic influences on travel speeds are relevant for finding feasible and reliable solutions. This study considers the effect of exploiting statistical information available about historical accidents, using stochastic solution approaches for the dynamic dial-a-ride problem (dynamic DARP). The authors propose two pairs of metaheuristic solution approaches, each consisting of a deterministic method (average time-dependent travel speeds for planning) and its corresponding stochastic version (exploiting stochastic information while planning). The results, using test instances with up to 762 requests based on a real-world road network, show that in certain conditions, exploiting stochastic information about travel speeds leads to significant improvements over deterministic approaches.
Effect of liquid nitrogen storage time on the survival and ...
African Journals Online (AJOL)
Investigations were undertaken on the effect of liquid nitrogen (LN) storage time on survival and regeneration of somatic embryos of cocoa (Theobroma cacao l.). Somatic embryos from different cocoa genotypes (AMAZ 3-2, AMAZ 10-1, AMAZ 12, SIAL 93, and IMC 14) at 15.45% moisture content were cryopreserved in LN ...
Influence of different storage times and temperatures on blood gas ...
African Journals Online (AJOL)
The present study was designed to investigate the effects of storage temperature and time on blood gas and acid-base balance of ovine venous blood. Ten clinically healthy sheep were used in this study. A total number of 30 blood samples, were divided into three different groups, and were stored in a refrigerator adjusted ...
40 CFR 273.53 - Storage time limits.
2010-07-01
...) STANDARDS FOR UNIVERSAL WASTE MANAGEMENT Standards for Universal Waste Transporters § 273.53 Storage time limits. (a) A universal waste transporter may only store the universal waste at a universal waste transfer facility for ten days or less. (b) If a universal waste transporter stores universal waste for...
A comparison of the stochastic and machine learning approaches in hydrologic time series forecasting
Kim, T.; Joo, K.; Seo, J.; Heo, J. H.
2016-12-01
Hydrologic time series forecasting is an essential task in water resources management and it becomes more difficult due to the complexity of runoff process. Traditional stochastic models such as ARIMA family has been used as a standard approach in time series modeling and forecasting of hydrological variables. Due to the nonlinearity in hydrologic time series data, machine learning approaches has been studied with the advantage of discovering relevant features in a nonlinear relation among variables. This study aims to compare the predictability between the traditional stochastic model and the machine learning approach. Seasonal ARIMA model was used as the traditional time series model, and Random Forest model which consists of decision tree and ensemble method using multiple predictor approach was applied as the machine learning approach. In the application, monthly inflow data from 1986 to 2015 of Chungju dam in South Korea were used for modeling and forecasting. In order to evaluate the performances of the used models, one step ahead and multi-step ahead forecasting was applied. Root mean squared error and mean absolute error of two models were compared.
Energy Technology Data Exchange (ETDEWEB)
Chorošajev, Vladimir [Department of Theoretical Physics, Faculty of Physics, Vilnius University, Sauletekio 9-III, 10222 Vilnius (Lithuania); Gelzinis, Andrius; Valkunas, Leonas [Department of Theoretical Physics, Faculty of Physics, Vilnius University, Sauletekio 9-III, 10222 Vilnius (Lithuania); Department of Molecular Compound Physics, Center for Physical Sciences and Technology, Sauletekio 3, 10222 Vilnius (Lithuania); Abramavicius, Darius, E-mail: darius.abramavicius@ff.vu.lt [Department of Theoretical Physics, Faculty of Physics, Vilnius University, Sauletekio 9-III, 10222 Vilnius (Lithuania)
2016-12-20
Highlights: • The Davydov ansatze can be used for finite temperature simulations with an extension. • The accuracy is high if the system is strongly coupled to the environmental phonons. • The approach can simulate time-resolved fluorescence spectra. - Abstract: Time dependent variational approach is a convenient method to characterize the excitation dynamics in molecular aggregates for different strengths of system-bath interaction a, which does not require any additional perturbative schemes. Until recently, however, this method was only applicable in zero temperature case. It has become possible to extend this method for finite temperatures with the introduction of stochastic time dependent variational approach. Here we present a comparison between this approach and the exact hierarchical equations of motion approach for describing excitation dynamics in a broad range of temperatures. We calculate electronic population evolution, absorption and auxiliary time resolved fluorescence spectra in different regimes and find that the stochastic approach shows excellent agreement with the exact approach when the system-bath coupling is sufficiently large and temperatures are high. The differences between the two methods are larger, when temperatures are lower or the system-bath coupling is small.
Extinction time of a stochastic predator-prey model by the generalized cell mapping method
Han, Qun; Xu, Wei; Hu, Bing; Huang, Dongmei; Sun, Jian-Qiao
2018-03-01
The stochastic response and extinction time of a predator-prey model with Gaussian white noise excitations are studied by the generalized cell mapping (GCM) method based on the short-time Gaussian approximation (STGA). The methods for stochastic response probability density functions (PDFs) and extinction time statistics are developed. The Taylor expansion is used to deal with non-polynomial nonlinear terms of the model for deriving the moment equations with Gaussian closure, which are needed for the STGA in order to compute the one-step transition probabilities. The work is validated with direct Monte Carlo simulations. We have presented the transient responses showing the evolution from a Gaussian initial distribution to a non-Gaussian steady-state one. The effects of the model parameter and noise intensities on the steady-state PDFs are discussed. It is also found that the effects of noise intensities on the extinction time statistics are opposite to the effects on the limit probability distributions of the survival species.
Lipan, Ovidiu; Ferwerda, Cameron
2018-02-01
The deterministic Hill function depends only on the average values of molecule numbers. To account for the fluctuations in the molecule numbers, the argument of the Hill function needs to contain the means, the standard deviations, and the correlations. Here we present a method that allows for stochastic Hill functions to be constructed from the dynamical evolution of stochastic biocircuits with specific topologies. These stochastic Hill functions are presented in a closed analytical form so that they can be easily incorporated in models for large genetic regulatory networks. Using a repressive biocircuit as an example, we show by Monte Carlo simulations that the traditional deterministic Hill function inaccurately predicts time of repression by an order of two magnitudes. However, the stochastic Hill function was able to capture the fluctuations and thus accurately predicted the time of repression.
Digital Repository Service at National Institute of Oceanography (India)
Haris, K.; Chakraborty, B.
Nonlin. Processes Geophys., 21, 101–113, 2014 www.nonlin-processes-geophys.net/21/101/2014/ doi:10.5194/npg-21-101-2014 © Author(s) 2014. CC Attribution 3.0 License. Nonlinear Processes in Geophysics O pen A ccess Stochastic formalism-based seafloor... shifted in time to align with the selected feature (Fig. 2). The aligned echo envelopes were averaged to obtain stable acoustic signals to Nonlin. Processes Geophys., 21, 101–113, 2014 www.nonlin-processes-geophys.net/21/101/2014/ K. Haris and B...
The stochastic versus the Euclidean approach to quantum fields on a static space-time
International Nuclear Information System (INIS)
De Angelis, G.F.; de Falco, D.
1986-01-01
Equations are presented which modify the definition of the Gaussian field in the Rindler chart in order to make contact with the Wightman state, the Hartle-Hawking state, and the Euclidean field. By taking Ornstein-Uhlenbeck processes the authors have chosen, in the sense of stochastic mechanics, to place precisely the Fulling modes in their harmonic oscillator ground state. In this respect, together with the periodicity of Minkowski space-time, the authors observe that the covariance of the Ornstein-Uhlenbeck process can be obtained by analytical continuation of the Wightman function of the harmonic oscillator at zero temperature
Elliott, Thomas J.; Gu, Mile
2018-03-01
Continuous-time stochastic processes pervade everyday experience, and the simulation of models of these processes is of great utility. Classical models of systems operating in continuous-time must typically track an unbounded amount of information about past behaviour, even for relatively simple models, enforcing limits on precision due to the finite memory of the machine. However, quantum machines can require less information about the past than even their optimal classical counterparts to simulate the future of discrete-time processes, and we demonstrate that this advantage extends to the continuous-time regime. Moreover, we show that this reduction in the memory requirement can be unboundedly large, allowing for arbitrary precision even with a finite quantum memory. We provide a systematic method for finding superior quantum constructions, and a protocol for analogue simulation of continuous-time renewal processes with a quantum machine.
FAME Storage Time in an Optimized Natural Antioxidant Mixture
Directory of Open Access Journals (Sweden)
Rodolfo Lopes Coppo
2013-01-01
Full Text Available The study of B100 biodiesel oxidation stability, and its conservation, is extremely important to control its quality, especially regarding storage. Many spices have shown antioxidant effect and are the targets of study. Knowing the oxidation process in greater detail allows a reliable storage period to be stipulated for the biodiesel without its degradation until the time of use. Results have shown that according to the accelerated stove method, the optimal mixture, composed of 100% of oregano extract, can confer a 535-day shelf life to biodiesel without evident oxidation. According to the results obtained by the Rancimat method, the ideal mixture consists of 100% rosemary, resulting in 483 days of storage. The application of the process variable showed that the accelerated stove method was more suitable to determine oxidative stability of biodiesel.
International Nuclear Information System (INIS)
Zhang Min-Min; Mei Dong-Cheng; Wang Can-Jun
2011-01-01
The effects of the time delay on the upper bound of the time derivative of information entropy are investigated in a time-delayed dynamical system driven by correlated noise. Using the Markov approximation of the stochastic delay differential equations and the Schwartz inequality principle, we obtain an analytical expression for the upper bound U B (t) of the time derivative of the information entropy. The results show that there is a critical value of τ (delay time), and U B (t) presents opposite behaviours on difference sides of the critical value. For the case of the weak additive noise, τ can induce a reentrance transition. Delay time τ also causes a reversal behaviour in U B (t)-λ plot, where λ denotes the degree of the correlation between the two noises. (general)
Analyzing a stochastic time series obeying a second-order differential equation.
Lehle, B; Peinke, J
2015-06-01
The stochastic properties of a Langevin-type Markov process can be extracted from a given time series by a Markov analysis. Also processes that obey a stochastically forced second-order differential equation can be analyzed this way by employing a particular embedding approach: To obtain a Markovian process in 2N dimensions from a non-Markovian signal in N dimensions, the system is described in a phase space that is extended by the temporal derivative of the signal. For a discrete time series, however, this derivative can only be calculated by a differencing scheme, which introduces an error. If the effects of this error are not accounted for, this leads to systematic errors in the estimation of the drift and diffusion functions of the process. In this paper we will analyze these errors and we will propose an approach that correctly accounts for them. This approach allows an accurate parameter estimation and, additionally, is able to cope with weak measurement noise, which may be superimposed to a given time series.
Stochastic Dynamics of a Time-Delayed Ecosystem Driven by Poisson White Noise Excitation
Directory of Open Access Journals (Sweden)
Wantao Jia
2018-02-01
Full Text Available We investigate the stochastic dynamics of a prey-predator type ecosystem with time delay and the discrete random environmental fluctuations. In this model, the delay effect is represented by a time delay parameter and the effect of the environmental randomness is modeled as Poisson white noise. The stochastic averaging method and the perturbation method are applied to calculate the approximate stationary probability density functions for both predator and prey populations. The influences of system parameters and the Poisson white noises are investigated in detail based on the approximate stationary probability density functions. It is found that, increasing time delay parameter as well as the mean arrival rate and the variance of the amplitude of the Poisson white noise will enhance the fluctuations of the prey and predator population. While the larger value of self-competition parameter will reduce the fluctuation of the system. Furthermore, the results from Monte Carlo simulation are also obtained to show the effectiveness of the results from averaging method.
Zhang, Wei; Wang, Jun
2017-09-01
In attempt to reproduce price dynamics of financial markets, a stochastic agent-based financial price model is proposed and investigated by stochastic exclusion process. The exclusion process, one of interacting particle systems, is usually thought of as modeling particle motion (with the conserved number of particles) in a continuous time Markov process. In this work, the process is utilized to imitate the trading interactions among the investing agents, in order to explain some stylized facts found in financial time series dynamics. To better understand the correlation behaviors of the proposed model, a new time-dependent intrinsic detrended cross-correlation (TDI-DCC) is introduced and performed, also, the autocorrelation analyses are applied in the empirical research. Furthermore, to verify the rationality of the financial price model, the actual return series are also considered to be comparatively studied with the simulation ones. The comparison results of return behaviors reveal that this financial price dynamics model can reproduce some correlation features of actual stock markets.
Mansø, Mads; Petersen, Anne Ugleholdt; Wang, Zhihang; Erhart, Paul; Nielsen, Mogens Brøndsted; Moth-Poulsen, Kasper
2018-05-16
Molecular photoswitches can be used for solar thermal energy storage by photoisomerization into high-energy, meta-stable isomers; we present a molecular design strategy leading to photoswitches with high energy densities and long storage times. High measured energy densities of up to 559 kJ kg -1 (155 Wh kg -1 ), long storage lifetimes up to 48.5 days, and high quantum yields of conversion of up to 94% per subunit are demonstrated in norbornadiene/quadricyclane (NBD/QC) photo-/thermoswitch couples incorporated into dimeric and trimeric structures. By changing the linker unit between the NBD units, we can at the same time fine-tune light-harvesting and energy densities of the dimers and trimers so that they exceed those of their monomeric analogs. These new oligomers thereby meet several of the criteria to be met for an optimum molecule to ultimately enter actual devices being able to undergo closed cycles of solar light-harvesting, energy storage, and heat release.
Liu, Hongjian; Wang, Zidong; Shen, Bo; Huang, Tingwen; Alsaadi, Fuad E
2018-06-01
This paper is concerned with the globally exponential stability problem for a class of discrete-time stochastic memristive neural networks (DSMNNs) with both leakage delays as well as probabilistic time-varying delays. For the probabilistic delays, a sequence of Bernoulli distributed random variables is utilized to determine within which intervals the time-varying delays fall at certain time instant. The sector-bounded activation function is considered in the addressed DSMNN. By taking into account the state-dependent characteristics of the network parameters and choosing an appropriate Lyapunov-Krasovskii functional, some sufficient conditions are established under which the underlying DSMNN is globally exponentially stable in the mean square. The derived conditions are made dependent on both the leakage and the probabilistic delays, and are therefore less conservative than the traditional delay-independent criteria. A simulation example is given to show the effectiveness of the proposed stability criterion. Copyright © 2018 Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Li Jianlong; Zeng Lingzao
2010-01-01
We discuss in detail the effects of the multi-time-delayed feedback driven by an aperiodic signal on the output of a stochastic resonance (SR) system. The effective potential function and dynamical probability density function (PDF) are derived. To measure the performance of the SR system in the presence of a binary random signal, the bit error rate (BER) defined by the dynamical PDF is employed, as is commonly used in digital communications. We find that the delay time, strength of the feedback, and number of time-delayed terms can change the effective potential function and the effective amplitude of the signal, and then affect the BER of the SR system. The numerical simulations strongly support the theoretical results. The goal of this investigation is to explore the effects of the multi-time-delayed feedback on SR and give a guidance to nonlinear systems in the application of information processing.
Directory of Open Access Journals (Sweden)
Yingwei Li
2014-01-01
Full Text Available The exponential synchronization issue for stochastic neural networks (SNNs with mixed time delays and Markovian jump parameters using sampled-data controller is investigated. Based on a novel Lyapunov-Krasovskii functional, stochastic analysis theory, and linear matrix inequality (LMI approach, we derived some novel sufficient conditions that guarantee that the master systems exponentially synchronize with the slave systems. The design method of the desired sampled-data controller is also proposed. To reflect the most dynamical behaviors of the system, both Markovian jump parameters and stochastic disturbance are considered, where stochastic disturbances are given in the form of a Brownian motion. The results obtained in this paper are a little conservative comparing the previous results in the literature. Finally, two numerical examples are given to illustrate the effectiveness of the proposed methods.
Geological storage of CO2 : time frames, monitoring and verification
International Nuclear Information System (INIS)
Chalaturnyk, R.; Gunter, W.D.
2005-01-01
In order to ensure that carbon dioxide (CO 2 ) injection and storage occurs in an environmentally sound and safe manner, many organizations pursuing the development of a CO 2 geological storage industry are initiating monitoring programs that include operational monitoring; verification monitoring; and environmental monitoring. Each represents an increase in the level of technology used and the intensity and duration of monitoring. For each potential site, the project conditions must be defined, the mechanisms that control the fluid flow must be predicted and technical questions must be addressed. This paper reviewed some of the relevant issues in establishing a monitoring framework for geological storage and defined terms that indicate the fate of injected CO 2 . Migration refers to movement of fluids within the injection formation, while leakage refers to movement of fluids outside the injection formation, and seepage refers to movement of fluids from the geosphere to the biosphere. Currently, regulatory agencies focus mostly on the time period approved for waste fluid injection, including CO 2 , into depleted hydrocarbon reservoirs or deep saline aquifers, which is in the order of 25 years. The lifetime of the injection operation is limited by reservoir capacity and the injection rate. Monitoring periods can be divided into periods based on risk during injection-operation (10 to 25 years), at the beginning of the storage period during pressure equilibration (up to 100 years), and over the long-term (from 100 to 1000 years). The 42 commercial acid gas injection projects currently in operation in western Canada can be used to validate the technology for the short term, while validation of long-term storage can be based on natural geological analogues. It was concluded that a monitored decision framework recognizes uncertainties in the geological storage system and allows design decisions to be made with the knowledge that planned long-term observations and their
Rullan, Marc; Benzinger, Dirk; Schmidt, Gregor W; Milias-Argeitis, Andreas; Khammash, Mustafa
2018-05-17
Transcription is a highly regulated and inherently stochastic process. The complexity of signal transduction and gene regulation makes it challenging to analyze how the dynamic activity of transcriptional regulators affects stochastic transcription. By combining a fast-acting, photo-regulatable transcription factor with nascent RNA quantification in live cells and an experimental setup for precise spatiotemporal delivery of light inputs, we constructed a platform for the real-time, single-cell interrogation of transcription in Saccharomyces cerevisiae. We show that transcriptional activation and deactivation are fast and memoryless. By analyzing the temporal activity of individual cells, we found that transcription occurs in bursts, whose duration and timing are modulated by transcription factor activity. Using our platform, we regulated transcription via light-driven feedback loops at the single-cell level. Feedback markedly reduced cell-to-cell variability and led to qualitative differences in cellular transcriptional dynamics. Our platform establishes a flexible method for studying transcriptional dynamics in single cells. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
Stochastic modeling for time series InSAR: with emphasis on atmospheric effects
Cao, Yunmeng; Li, Zhiwei; Wei, Jianchao; Hu, Jun; Duan, Meng; Feng, Guangcai
2018-02-01
Despite the many applications of time series interferometric synthetic aperture radar (TS-InSAR) techniques in geophysical problems, error analysis and assessment have been largely overlooked. Tropospheric propagation error is still the dominant error source of InSAR observations. However, the spatiotemporal variation of atmospheric effects is seldom considered in the present standard TS-InSAR techniques, such as persistent scatterer interferometry and small baseline subset interferometry. The failure to consider the stochastic properties of atmospheric effects not only affects the accuracy of the estimators, but also makes it difficult to assess the uncertainty of the final geophysical results. To address this issue, this paper proposes a network-based variance-covariance estimation method to model the spatiotemporal variation of tropospheric signals, and to estimate the temporal variance-covariance matrix of TS-InSAR observations. The constructed stochastic model is then incorporated into the TS-InSAR estimators both for parameters (e.g., deformation velocity, topography residual) estimation and uncertainty assessment. It is an incremental and positive improvement to the traditional weighted least squares methods to solve the multitemporal InSAR time series. The performance of the proposed method is validated by using both simulated and real datasets.
Time to reach a given level of number of neutrons is stochastic analog of reactor period
International Nuclear Information System (INIS)
Ryazanov, V.V.
2012-01-01
In theory and in practice the operation of nuclear reactors to control the safety of the reactor is widely used deterministic value - the period of the reactor. It is proposed along with the period of the reactor using a stochastic analogue of this magnitude - a random amount of time to achieve a given level of a random process for the number of neutrons in the reactor. The paper discusses various features of the behavior of the mean and variance of time to achieve a specified level. This kind of features can be associated with impaired behavior of the reactor system. Introduced the value of time required to reach the level can be used to monitor and improve the safety of nuclear power plants
Robust stability analysis of uncertain stochastic neural networks with interval time-varying delay
International Nuclear Information System (INIS)
Feng Wei; Yang, Simon X.; Fu Wei; Wu Haixia
2009-01-01
This paper addresses the stability analysis problem for uncertain stochastic neural networks with interval time-varying delays. The parameter uncertainties are assumed to be norm bounded, and the delay factor is assumed to be time-varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. A sufficient condition is derived such that for all admissible uncertainties, the considered neural network is robustly, globally, asymptotically stable in the mean square. Some stability criteria are formulated by means of the feasibility of a linear matrix inequality (LMI), which can be effectively solved by some standard numerical packages. Finally, numerical examples are provided to demonstrate the usefulness of the proposed criteria.
Liu, Xiaomei; Li, Shengtao; Zhang, Kanjian
2017-08-01
In this paper, we solve an optimal control problem for a class of time-invariant switched stochastic systems with multi-switching times, where the objective is to minimise a cost functional with different costs defined on the states. In particular, we focus on problems in which a pre-specified sequence of active subsystems is given and the switching times are the only control variables. Based on the calculus of variation, we derive the gradient of the cost functional with respect to the switching times on an especially simple form, which can be directly used in gradient descent algorithms to locate the optimal switching instants. Finally, a numerical example is given, highlighting the validity of the proposed methodology.
Zhang, Wanli; Li, Chuandong; Huang, Tingwen; Huang, Junjian
2018-02-01
This paper investigates the fixed-time synchronization of complex networks (CNs) with nonidentical nodes and stochastic noise perturbations. By designing new controllers, constructing Lyapunov functions and using the properties of Weiner process, different synchronization criteria are derived according to whether the node systems in the CNs or the goal system satisfies the corresponding conditions. Moreover, the role of the designed controllers is analyzed in great detail by constructing a suitable comparison system and a new method is presented to estimate the settling time by utilizing the comparison system. Results of this paper can be applied to both directed and undirected weighted networks. Numerical simulations are offered to verify the effectiveness of our new results.
An approach to the drone fleet survivability assessment based on a stochastic continues-time model
Kharchenko, Vyacheslav; Fesenko, Herman; Doukas, Nikos
2017-09-01
An approach and the algorithm to the drone fleet survivability assessment based on a stochastic continues-time model are proposed. The input data are the number of the drones, the drone fleet redundancy coefficient, the drone stability and restoration rate, the limit deviation from the norms of the drone fleet recovery, the drone fleet operational availability coefficient, the probability of the drone failure-free operation, time needed for performing the required tasks by the drone fleet. The ways for improving the recoverable drone fleet survivability taking into account amazing factors of system accident are suggested. Dependencies of the drone fleet survivability rate both on the drone stability and the number of the drones are analysed.
Supply Chain Model with Stochastic Lead Time, Trade-Credit Financing, and Transportation Discounts
Directory of Open Access Journals (Sweden)
Sung Jun Kim
2017-01-01
Full Text Available This model extends a two-echelon supply chain model by considering the trade-credit policy, transportations discount to make a coordination mechanism between transportation discounts, trade-credit financing, number of shipments, quality improvement of products, and reduced setup cost in such a way that the total cost of the whole system can be reduced, where the supplier offers trade-credit-period to the buyer. For buyer, the backorder rate is considered as variable. There are two investments to reduce setup cost and to improve quality of products. The model assumes lead time-dependent backorder rate, where the lead time is stochastic in nature. By using the trade-credit policy, the model gives how the credit-period would be determined to achieve the win-win outcome. An iterative algorithm is designed to obtain the global optimum results. Numerical example and sensitivity analysis are given to illustrate the model.
Stochastic Simulation and Forecast of Hydrologic Time Series Based on Probabilistic Chaos Expansion
Li, Z.; Ghaith, M.
2017-12-01
Hydrological processes are characterized by many complex features, such as nonlinearity, dynamics and uncertainty. How to quantify and address such complexities and uncertainties has been a challenging task for water engineers and managers for decades. To support robust uncertainty analysis, an innovative approach for the stochastic simulation and forecast of hydrologic time series is developed is this study. Probabilistic Chaos Expansions (PCEs) are established through probabilistic collocation to tackle uncertainties associated with the parameters of traditional hydrological models. The uncertainties are quantified in model outputs as Hermite polynomials with regard to standard normal random variables. Sequentially, multivariate analysis techniques are used to analyze the complex nonlinear relationships between meteorological inputs (e.g., temperature, precipitation, evapotranspiration, etc.) and the coefficients of the Hermite polynomials. With the established relationships between model inputs and PCE coefficients, forecasts of hydrologic time series can be generated and the uncertainties in the future time series can be further tackled. The proposed approach is demonstrated using a case study in China and is compared to a traditional stochastic simulation technique, the Markov-Chain Monte-Carlo (MCMC) method. Results show that the proposed approach can serve as a reliable proxy to complicated hydrological models. It can provide probabilistic forecasting in a more computationally efficient manner, compared to the traditional MCMC method. This work provides technical support for addressing uncertainties associated with hydrological modeling and for enhancing the reliability of hydrological modeling results. Applications of the developed approach can be extended to many other complicated geophysical and environmental modeling systems to support the associated uncertainty quantification and risk analysis.
Stochastic models in the DORIS position time series: estimates for IDS contribution to ITRF2014
Klos, Anna; Bogusz, Janusz; Moreaux, Guilhem
2017-11-01
This paper focuses on the investigation of the deterministic and stochastic parts of the Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) weekly time series aligned to the newest release of ITRF2014. A set of 90 stations was divided into three groups depending on when the data were collected at an individual station. To reliably describe the DORIS time series, we employed a mathematical model that included the long-term nonlinear signal, linear trend, seasonal oscillations and a stochastic part, all being estimated with maximum likelihood estimation. We proved that the values of the parameters delivered for DORIS data are strictly correlated with the time span of the observations. The quality of the most recent data has significantly improved. Not only did the seasonal amplitudes decrease over the years, but also, and most importantly, the noise level and its type changed significantly. Among several tested models, the power-law process may be chosen as the preferred one for most of the DORIS data. Moreover, the preferred noise model has changed through the years from an autoregressive process to pure power-law noise with few stations characterised by a positive spectral index. For the latest observations, the medians of the velocity errors were equal to 0.3, 0.3 and 0.4 mm/year, respectively, for the North, East and Up components. In the best cases, a velocity uncertainty of DORIS sites of 0.1 mm/year is achievable when the appropriate coloured noise model is taken into consideration.
The Long Time Behavior of a Stochastic Logistic Model with Infinite Delay and Impulsive Perturbation
Lu, Chun; Wu, Kaining
2016-01-01
This paper considers a stochastic logistic model with infinite delay and impulsive perturbation. Firstly, with the space $C_{g}$ as phase space, the definition of solution to a stochastic functional differential equation with infinite delay and impulsive perturbation is established. According to this definition, we show that our model has an unique global positive solution. Then we establish the sufficient and necessary conditions for extinction and stochastic permanence of the...
Herath, Narmada; Del Vecchio, Domitilla
2018-03-01
Biochemical reaction networks often involve reactions that take place on different time scales, giving rise to "slow" and "fast" system variables. This property is widely used in the analysis of systems to obtain dynamical models with reduced dimensions. In this paper, we consider stochastic dynamics of biochemical reaction networks modeled using the Linear Noise Approximation (LNA). Under time-scale separation conditions, we obtain a reduced-order LNA that approximates both the slow and fast variables in the system. We mathematically prove that the first and second moments of this reduced-order model converge to those of the full system as the time-scale separation becomes large. These mathematical results, in particular, provide a rigorous justification to the accuracy of LNA models derived using the stochastic total quasi-steady state approximation (tQSSA). Since, in contrast to the stochastic tQSSA, our reduced-order model also provides approximations for the fast variable stochastic properties, we term our method the "stochastic tQSSA+". Finally, we demonstrate the application of our approach on two biochemical network motifs found in gene-regulatory and signal transduction networks.
Managing high-bandwidth real-time data storage
Energy Technology Data Exchange (ETDEWEB)
Bigelow, David D. [Los Alamos National Laboratory; Brandt, Scott A [Los Alamos National Laboratory; Bent, John M [Los Alamos National Laboratory; Chen, Hsing-Bung [Los Alamos National Laboratory
2009-09-23
There exist certain systems which generate real-time data at high bandwidth, but do not necessarily require the long-term retention of that data in normal conditions. In some cases, the data may not actually be useful, and in others, there may be too much data to permanently retain in long-term storage whether it is useful or not. However, certain portions of the data may be identified as being vitally important from time to time, and must therefore be retained for further analysis or permanent storage without interrupting the ongoing collection of new data. We have developed a system, Mahanaxar, intended to address this problem. It provides quality of service guarantees for incoming real-time data streams and simultaneous access to already-recorded data on a best-effort basis utilizing any spare bandwidth. It has built in mechanisms for reliability and indexing, can scale upwards to meet increasing bandwidth requirements, and handles both small and large data elements equally well. We will show that a prototype version of this system provides better performance than a flat file (traditional filesystem) based version, particularly with regard to quality of service guarantees and hard real-time requirements.
Sun, Ying; Ding, Derui; Zhang, Sunjie; Wei, Guoliang; Liu, Hongjian
2018-07-01
In this paper, the non-fragile ?-? control problem is investigated for a class of discrete-time stochastic nonlinear systems under event-triggered communication protocols, which determine whether the measurement output should be transmitted to the controller or not. The main purpose of the addressed problem is to design an event-based output feedback controller subject to gain variations guaranteeing the prescribed disturbance attenuation level described by the ?-? performance index. By utilizing the Lyapunov stability theory combined with S-procedure, a sufficient condition is established to guarantee both the exponential mean-square stability and the ?-? performance for the closed-loop system. In addition, with the help of the orthogonal decomposition, the desired controller parameter is obtained in terms of the solution to certain linear matrix inequalities. Finally, a simulation example is exploited to demonstrate the effectiveness of the proposed event-based controller design scheme.
Discrete-time state estimation for stochastic polynomial systems over polynomial observations
Hernandez-Gonzalez, M.; Basin, M.; Stepanov, O.
2018-07-01
This paper presents a solution to the mean-square state estimation problem for stochastic nonlinear polynomial systems over polynomial observations confused with additive white Gaussian noises. The solution is given in two steps: (a) computing the time-update equations and (b) computing the measurement-update equations for the state estimate and error covariance matrix. A closed form of this filter is obtained by expressing conditional expectations of polynomial terms as functions of the state estimate and error covariance. As a particular case, the mean-square filtering equations are derived for a third-degree polynomial system with second-degree polynomial measurements. Numerical simulations show effectiveness of the proposed filter compared to the extended Kalman filter.
Energy Technology Data Exchange (ETDEWEB)
Dong, Jing [ORNL; Mahmassani, Hani S. [Northwestern University, Evanston
2011-01-01
This paper proposes a methodology to produce random flow breakdown endogenously in a mesoscopic operational model, by capturing breakdown probability and duration. Based on previous research findings that probability of flow breakdown can be represented as a function of flow rate and the duration can be characterized by a hazard model. By generating random flow breakdown at various levels and capturing the traffic characteristics at the onset of the breakdown, the stochastic network simulation model provides a tool for evaluating travel time variability. The proposed model can be used for (1) providing reliability related traveler information; (2) designing ITS (intelligent transportation systems) strategies to improve reliability; and (3) evaluating reliability-related performance measures of the system.
Fast state estimation subject to random data loss in discrete-time nonlinear stochastic systems
Mahdi Alavi, S. M.; Saif, Mehrdad
2013-12-01
This paper focuses on the design of the standard observer in discrete-time nonlinear stochastic systems subject to random data loss. By the assumption that the system response is incrementally bounded, two sufficient conditions are subsequently derived that guarantee exponential mean-square stability and fast convergence of the estimation error for the problem at hand. An efficient algorithm is also presented to obtain the observer gain. Finally, the proposed methodology is employed for monitoring the Continuous Stirred Tank Reactor (CSTR) via a wireless communication network. The effectiveness of the designed observer is extensively assessed by using an experimental tested-bed that has been fabricated for performance evaluation of the over wireless-network estimation techniques under realistic radio channel conditions.
Fault Detection for Non-Gaussian Stochastic Systems with Time-Varying Delay
Directory of Open Access Journals (Sweden)
Tao Li
2013-01-01
Full Text Available Fault detection (FD for non-Gaussian stochastic systems with time-varying delay is studied. The available information for the addressed problem is the input and the measured output probability density functions (PDFs of the system. In this framework, firstly, by constructing an augmented Lyapunov functional, which involves some slack variables and a tuning parameter, a delay-dependent condition for the existence of FD observer is derived in terms of linear matrix inequality (LMI and the fault can be detected through a threshold. Secondly, in order to improve the detection sensitivity performance, the optimal algorithm is applied to minimize the threshold value. Finally, paper-making process example is given to demonstrate the applicability of the proposed approach.
The optimal replenishment policy for time-varying stochastic demand under vendor managed inventory
DEFF Research Database (Denmark)
Govindan, Kannan
2015-01-01
A Vendor Managed Inventory (VMI) partnership places the responsibility on the vendor (rather than on buyers) to schedule purchase orders for inventory replenishment in the supply chain system. In this research, the supply chain network considers the Silver-Meal heuristic with an augmentation...... quantity replenishment policy between both traditional and VMI systems. We consider time-varying stochastic demand in two-echelon (one vendor, multiple retailers) supply chains. This paper seeks to find the supply chain that minimizes system cost through comparing performance between traditional and VMI...... systems. A mathematical model is developed, and total supply chain cost is used as the measure of comparison. The models are applied in both traditional and VMI supply chains based on pharmaceutical industry data, and we focus on total cost difference compared through the use of Adjusted Silver-Meal (ASM...
Chen, Yonghong; Bressler, Steven L.; Knuth, Kevin H.; Truccolo, Wilson A.; Ding, Mingzhou
2006-06-01
In this article we consider the stochastic modeling of neurobiological time series from cognitive experiments. Our starting point is the variable-signal-plus-ongoing-activity model. From this model a differentially variable component analysis strategy is developed from a Bayesian perspective to estimate event-related signals on a single trial basis. After subtracting out the event-related signal from recorded single trial time series, the residual ongoing activity is treated as a piecewise stationary stochastic process and analyzed by an adaptive multivariate autoregressive modeling strategy which yields power, coherence, and Granger causality spectra. Results from applying these methods to local field potential recordings from monkeys performing cognitive tasks are presented.
International Nuclear Information System (INIS)
Yan-Mei, Kang; Yao-Lin, Jiang
2008-01-01
To explore the influence of anomalous diffusion on stochastic resonance (SR) more deeply and effectively, the method of moments is extended to subdiffusive overdamped bistable fractional Fokker-Planck systems for calculating the long-time linear dynamic response. It is found that the method of moments attains high accuracy with the truncation order N = 10, and in normal diffusion such obtained spectral amplification factor (SAF) of the first-order harmonic is also confirmed by stochastic simulation. Observing the SAF of the odd-order harmonics we find some interesting results, i.e. for smaller driving frequency the decrease of sub diffusion exponent inhibits the stochastic resonance (SR), while for larger driving frequency the decrease of sub diffusion exponent enhances the second SR peak, but the first one vanishes and a double SR is induced in the third-order harmonic at the same time. These observations suggest that the anomalous diffusion has important influence on the bistable dynamics
Stochastic approaches for time series forecasting of boron: a case study of Western Turkey.
Durdu, Omer Faruk
2010-10-01
In the present study, a seasonal and non-seasonal prediction of boron concentrations time series data for the period of 1996-2004 from Büyük Menderes river in western Turkey are addressed by means of linear stochastic models. The methodology presented here is to develop adequate linear stochastic models known as autoregressive integrated moving average (ARIMA) and multiplicative seasonal autoregressive integrated moving average (SARIMA) to predict boron content in the Büyük Menderes catchment. Initially, the Box-Whisker plots and Kendall's tau test are used to identify the trends during the study period. The measurements locations do not show significant overall trend in boron concentrations, though marginal increasing and decreasing trends are observed for certain periods at some locations. ARIMA modeling approach involves the following three steps: model identification, parameter estimation, and diagnostic checking. In the model identification step, considering the autocorrelation function (ACF) and partial autocorrelation function (PACF) results of boron data series, different ARIMA models are identified. The model gives the minimum Akaike information criterion (AIC) is selected as the best-fit model. The parameter estimation step indicates that the estimated model parameters are significantly different from zero. The diagnostic check step is applied to the residuals of the selected ARIMA models and the results indicate that the residuals are independent, normally distributed, and homoscadastic. For the model validation purposes, the predicted results using the best ARIMA models are compared to the observed data. The predicted data show reasonably good agreement with the actual data. The comparison of the mean and variance of 3-year (2002-2004) observed data vs predicted data from the selected best models show that the boron model from ARIMA modeling approaches could be used in a safe manner since the predicted values from these models preserve the basic
Cotter, C J; Gottwald, G A; Holm, D D
2017-09-01
In Holm (Holm 2015 Proc. R. Soc. A 471 , 20140963. (doi:10.1098/rspa.2014.0963)), stochastic fluid equations were derived by employing a variational principle with an assumed stochastic Lagrangian particle dynamics. Here we show that the same stochastic Lagrangian dynamics naturally arises in a multi-scale decomposition of the deterministic Lagrangian flow map into a slow large-scale mean and a rapidly fluctuating small-scale map. We employ homogenization theory to derive effective slow stochastic particle dynamics for the resolved mean part, thereby obtaining stochastic fluid partial equations in the Eulerian formulation. To justify the application of rigorous homogenization theory, we assume mildly chaotic fast small-scale dynamics, as well as a centring condition. The latter requires that the mean of the fluctuating deviations is small, when pulled back to the mean flow.
International Nuclear Information System (INIS)
Yu, Haitao; Guo, Xinmeng; Wang, Jiang; Deng, Bin; Wei, Xile
2014-01-01
The phenomenon of stochastic resonance in Newman-Watts small-world neuronal networks is investigated when the strength of synaptic connections between neurons is adaptively adjusted by spike-time-dependent plasticity (STDP). It is shown that irrespective of the synaptic connectivity is fixed or adaptive, the phenomenon of stochastic resonance occurs. The efficiency of network stochastic resonance can be largely enhanced by STDP in the coupling process. Particularly, the resonance for adaptive coupling can reach a much larger value than that for fixed one when the noise intensity is small or intermediate. STDP with dominant depression and small temporal window ratio is more efficient for the transmission of weak external signal in small-world neuronal networks. In addition, we demonstrate that the effect of stochastic resonance can be further improved via fine-tuning of the average coupling strength of the adaptive network. Furthermore, the small-world topology can significantly affect stochastic resonance of excitable neuronal networks. It is found that there exists an optimal probability of adding links by which the noise-induced transmission of weak periodic signal peaks
Energy Technology Data Exchange (ETDEWEB)
Yu, Haitao; Guo, Xinmeng; Wang, Jiang, E-mail: jiangwang@tju.edu.cn; Deng, Bin; Wei, Xile [School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China)
2014-09-01
The phenomenon of stochastic resonance in Newman-Watts small-world neuronal networks is investigated when the strength of synaptic connections between neurons is adaptively adjusted by spike-time-dependent plasticity (STDP). It is shown that irrespective of the synaptic connectivity is fixed or adaptive, the phenomenon of stochastic resonance occurs. The efficiency of network stochastic resonance can be largely enhanced by STDP in the coupling process. Particularly, the resonance for adaptive coupling can reach a much larger value than that for fixed one when the noise intensity is small or intermediate. STDP with dominant depression and small temporal window ratio is more efficient for the transmission of weak external signal in small-world neuronal networks. In addition, we demonstrate that the effect of stochastic resonance can be further improved via fine-tuning of the average coupling strength of the adaptive network. Furthermore, the small-world topology can significantly affect stochastic resonance of excitable neuronal networks. It is found that there exists an optimal probability of adding links by which the noise-induced transmission of weak periodic signal peaks.
Optimal routing of hazardous substances in time-varying, stochastic transportation networks
International Nuclear Information System (INIS)
Woods, A.L.; Miller-Hooks, E.; Mahmassani, H.S.
1998-07-01
This report is concerned with the selection of routes in a network along which to transport hazardous substances, taking into consideration several key factors pertaining to the cost of transport and the risk of population exposure in the event of an accident. Furthermore, the fact that travel time and the risk measures are not constant over time is explicitly recognized in the routing decisions. Existing approaches typically assume static conditions, possibly resulting in inefficient route selection and unnecessary risk exposure. The report described the application of recent advances in network analysis methodologies to the problem of routing hazardous substances. Several specific problem formulations are presented, reflecting different degrees of risk aversion on the part of the decision-maker, as well as different possible operational scenarios. All procedures explicitly consider travel times and travel costs (including risk measures) to be stochastic time-varying quantities. The procedures include both exact algorithms, which may require extensive computational effort in some situations, as well as more efficient heuristics that may not guarantee a Pareto-optimal solution. All procedures are systematically illustrated for an example application using the Texas highway network, for both normal and incident condition scenarios. The application illustrates the trade-offs between the information obtained in the solution and computational efficiency, and highlights the benefits of incorporating these procedures in a decision-support system for hazardous substance shipment routing decisions
Stochastic integrated vendor–buyer model with unstable lead time and setup cost
Directory of Open Access Journals (Sweden)
Chandra K. Jaggi
2011-01-01
Full Text Available This paper presents a new vendor-buyer system where there are different objectives for both sides. The proposed method of this paper is different from the other previously published works since it considers different objectives for both sides. In this paper, the vendor’s emphasis is on the crashing of the setup cost, which not only helps him compete in the market but also provides better services to his customers; and the buyer’s aim is to reduce the lead time, which not only facilitates the buyer to fulfill the customers’ demand on time but also enables him to earn a good reputation in the market or vice versa. In the light of the above stated facts, an integrated vendor-buyer stochastic inventory model is also developed. The propsed model considers two cases for demand during lead time: Case (i Complete demand information, Case (ii Partial demand information. The proposed model jointly optimizes the buyer’s ordered quantity and lead time along with vendor’s setup cost and the number of shipments. The results are demonstrated with the help of numerical examples.
A stochastic model of radiation carcinogenesis: Latent time distributions and their properties
International Nuclear Information System (INIS)
Klebanov, L.V.; Yakovlev, A.Yu.; Rachev, S.T.
1993-01-01
A stochastic model of radiation carcinogenesis is proposed that has much in common with the ideas suggested by M. Pike as early as 1966. The model allows one to obtain a parametric family of substochastic-type distributions for the time of tumor latency that provides a description of the rate of tumor development and the number of affected individuals. With this model it is possible to interpret data on tumor incidence in terms of promotion and progression processes. The basic model is developed for a prolonged irradiation at a constant dose rate and includes short-term irradiation as a special case. A limiting form of the latent time distribution for short-term irradiation at high doses is obtained. This distribution arises in the extreme value theory within the random minima framework. An estimate for the rate of convergence to a limiting distributions is given. Based on the proposed latent time distributions, long-term predictions of carcinogenic risk do not call for information about irradiation dose. As shown by computer simulation studies and real data analysis, the parametric estimation of carcinogenic risk appears to be robust to the loss of statistical information caused by the right-hand censoring of time-to-tumor observations. It seems likely that this property, although revealed by means of a purely empirical procedure, may be useful in selecting a model for the practical purpose of risk prediction. 44 refs., 3 figs., 1 tab
Wind power impacts and electricity storage - a time scale perspective
DEFF Research Database (Denmark)
Hedegaard, Karsten; Meibom, Peter
2012-01-01
Integrating large amounts of wind power in energy systems poses balancing challenges due to the variable and only partly predictable nature of wind. The challenges cover different time scales from intra-hour, intra-day/day-ahead to several days and seasonal level. Along with flexible electricity...... demand options, various electricity storage technologies are being discussed as candidates for contributing to large-scale wind power integration and these also differ in terms of the time scales at which they can operate. In this paper, using the case of Western Denmark in 2025 with an expected 57% wind...... power penetration, wind power impacts on different time scales are analysed. Results show consecutive negative and high net load period lengths indicating a significant potential for flexibility measures capable of charging/activating demand and discharging/inactivating demand in periods of 1 h to one...
D'Onofrio, Giuseppe; Pirozzi, Enrica
2017-05-01
We consider a stochastic differential equation in a strip, with coefficients suitably chosen to describe the acto-myosin interaction subject to time-varying forces. By simulating trajectories of the stochastic dynamics via an Euler discretization-based algorithm, we fit experimental data and determine the values of involved parameters. The steps of the myosin are represented by the exit events from the strip. Motivated by these results, we propose a specific stochastic model based on the corresponding time-inhomogeneous Gauss-Markov and diffusion process evolving between two absorbing boundaries. We specify the mean and covariance functions of the stochastic modeling process taking into account time-dependent forces including the effect of an external load. We accurately determine the probability density function (pdf) of the first exit time (FET) from the strip by solving a system of two non singular second-type Volterra integral equations via a numerical quadrature. We provide numerical estimations of the mean of FET as approximations of the dwell-time of the proteins dynamics. The percentage of backward steps is given in agreement to experimental data. Numerical and simulation results are compared and discussed.
International Nuclear Information System (INIS)
Hemmati, Reza; Saboori, Hedayat; Saboori, Saeid
2016-01-01
In recent decades, wind power resources have been integrated in the power systems increasingly. Besides confirmed benefits, utilization of large share of this volatile source in power generation portfolio has been faced system operators with new challenges in terms of uncertainty management. It is proved that energy storage systems are capable to handle projected uncertainty concerns. Risk-neutral methods have been proposed in the previous literature to schedule storage units considering wind resources uncertainty. Ignoring risk of the cost distributions with non-desirable properties may result in experiencing high costs in some unfavorable scenarios with high probability. In order to control the risk of the operator decisions, this paper proposes a new risk-constrained two-stage stochastic programming model to make optimal decisions on energy storage and thermal units in a transmission constrained hybrid wind-thermal power system. Risk-aversion procedure is explicitly formulated using the conditional value-at-risk measure, because of possessing distinguished features compared to the other risk measures. The proposed model is a mixed integer linear programming considering transmission network, thermal unit dynamics, and storage devices constraints. The simulations results demonstrate that taking the risk of the problem into account will affect scheduling decisions considerably depend on the level of the risk-aversion. - Highlights: • Risk of the operation decisions is handled by using risk-averse programming. • Conditional value-at-risk is used as risk measure. • Optimal risk level is obtained based on the cost/benefit analysis. • The proposed model is a two-stage stochastic mixed integer linear programming. • The unit commitment is integrated with ESSs and wind power penetration.
Wang, Fen; Chen, Yuanlong; Liu, Meichun
2018-02-01
Stochastic memristor-based bidirectional associative memory (BAM) neural networks with time delays play an increasingly important role in the design and implementation of neural network systems. Under the framework of Filippov solutions, the issues of the pth moment exponential stability of stochastic memristor-based BAM neural networks are investigated. By using the stochastic stability theory, Itô's differential formula and Young inequality, the criteria are derived. Meanwhile, with Lyapunov approach and Cauchy-Schwarz inequality, we derive some sufficient conditions for the mean square exponential stability of the above systems. The obtained results improve and extend previous works on memristor-based or usual neural networks dynamical systems. Four numerical examples are provided to illustrate the effectiveness of the proposed results. Copyright © 2017 Elsevier Ltd. All rights reserved.
Online stochastic UAV mission planning with time windows and time-sensitive targets
Evers, L.; Barros, A.I.; Monsuur, H.; Wagelmans, A.
2014-01-01
In this paper we simultaneously consider three extensions to the standard Orienteering Problem (OP) to model characteristics that are of practical relevance in planning reconnaissance missions of Unmanned Aerial Vehicles (UAVs). First, travel and recording times are uncertain. Secondly, the
Chen, Po-Wei; Chen, Bor-Sen
2011-08-01
Naturally, a cellular network consisted of a large amount of interacting cells is complex. These cells have to be synchronized in order to emerge their phenomena for some biological purposes. However, the inherently stochastic intra and intercellular interactions are noisy and delayed from biochemical processes. In this study, a robust synchronization scheme is proposed for a nonlinear stochastic time-delay coupled cellular network (TdCCN) in spite of the time-varying process delay and intracellular parameter perturbations. Furthermore, a nonlinear stochastic noise filtering ability is also investigated for this synchronized TdCCN against stochastic intercellular and environmental disturbances. Since it is very difficult to solve a robust synchronization problem with the Hamilton-Jacobi inequality (HJI) matrix, a linear matrix inequality (LMI) is employed to solve this problem via the help of a global linearization method. Through this robust synchronization analysis, we can gain a more systemic insight into not only the robust synchronizability but also the noise filtering ability of TdCCN under time-varying process delays, intracellular perturbations and intercellular disturbances. The measures of robustness and noise filtering ability of a synchronized TdCCN have potential application to the designs of neuron transmitters, on-time mass production of biochemical molecules, and synthetic biology. Finally, a benchmark of robust synchronization design in Escherichia coli repressilators is given to confirm the effectiveness of the proposed methods. Copyright © 2011 Elsevier Inc. All rights reserved.
Stochastic Averaging and Stochastic Extremum Seeking
Liu, Shu-Jun
2012-01-01
Stochastic Averaging and Stochastic Extremum Seeking develops methods of mathematical analysis inspired by the interest in reverse engineering and analysis of bacterial convergence by chemotaxis and to apply similar stochastic optimization techniques in other environments. The first half of the text presents significant advances in stochastic averaging theory, necessitated by the fact that existing theorems are restricted to systems with linear growth, globally exponentially stable average models, vanishing stochastic perturbations, and prevent analysis over infinite time horizon. The second half of the text introduces stochastic extremum seeking algorithms for model-free optimization of systems in real time using stochastic perturbations for estimation of their gradients. Both gradient- and Newton-based algorithms are presented, offering the user the choice between the simplicity of implementation (gradient) and the ability to achieve a known, arbitrary convergence rate (Newton). The design of algorithms...
Directory of Open Access Journals (Sweden)
Jing Cai
2016-01-01
Full Text Available Considering the wide application of condition-based maintenance in aeroengine maintenance practice, it becomes possible for aeroengines to carry out their preventive maintenance in just-in-time (JIT manner by reasonably planning their shop visits (SVs. In this study, an approach is proposed to make aeroengine SV decisions following the concept of JIT. Firstly, a state space model (SSM for aeroengine based on exhaust gas temperature margin is developed to predict the remaining useful life (RUL of aeroengine. Secondly, the effect of SV decisions on risk and service level (SL is analyzed, and an optimization of the aeroengine SV decisions based on RUL and stochastic repair time is performed to carry out JIT manner with the requirement of safety and SL. Finally, a case study considering two CFM-56 aeroengines is presented to demonstrate the proposed approach. The results show that predictive accuracy of RUL with SSM is higher than with linear regression, and the process of SV decisions is simple and feasible for airlines to improve the inventory management level of their aeroengines.
A stochastic HMM-based forecasting model for fuzzy time series.
Li, Sheng-Tun; Cheng, Yi-Chung
2010-10-01
Recently, fuzzy time series have attracted more academic attention than traditional time series due to their capability of dealing with the uncertainty and vagueness inherent in the data collected. The formulation of fuzzy relations is one of the key issues affecting forecasting results. Most of the present works adopt IF-THEN rules for relationship representation, which leads to higher computational overhead and rule redundancy. Sullivan and Woodall proposed a Markov-based formulation and a forecasting model to reduce computational overhead; however, its applicability is limited to handling one-factor problems. In this paper, we propose a novel forecasting model based on the hidden Markov model by enhancing Sullivan and Woodall's work to allow handling of two-factor forecasting problems. Moreover, in order to make the nature of conjecture and randomness of forecasting more realistic, the Monte Carlo method is adopted to estimate the outcome. To test the effectiveness of the resulting stochastic model, we conduct two experiments and compare the results with those from other models. The first experiment consists of forecasting the daily average temperature and cloud density in Taipei, Taiwan, and the second experiment is based on the Taiwan Weighted Stock Index by forecasting the exchange rate of the New Taiwan dollar against the U.S. dollar. In addition to improving forecasting accuracy, the proposed model adheres to the central limit theorem, and thus, the result statistically approximates to the real mean of the target value being forecast.
Geometro-stochastic quantization of gauge fields in curved space-time
International Nuclear Information System (INIS)
Prugovecki, E.
1988-01-01
It is shown that the geometro-stochastic method of quantization of massive fields in curved space-time can be extended to the massless cases of electromagnetic fields and general Yang-Mills fields. The Fock fibres of the massive case are replaced in the present context by fibres with indefinite inner products, such as Gupta-Bleuler fibres in the electromagnetic case. The quantum space-time form factor used in the massive case gives rise in the present case to quantum gauge frames whose elements are generalized coherent states corresponding to pseudounitary spin-one representations of direct products of the Poincare group with the U(1), SU(N) or other internal gauge groups. Quantum connections are introduced on bundles of second-quantized frames, and the corresponding parallel transport is expressed in terms of path integrals for quantum frame propagators. In the Yang-Mills case, these path integral make use of Faddeev-Popov quantum frames. It is shown, however, that in the present framework the ghost fields that give rise to these frames possess a geometric interpretation related to the presence of a super-gauge group that, in addition to the external Poincare and Yang-Mills gauge degrees of freedom, involves also the internal ones related to choices of gauge bases within the quantum fibres
International Nuclear Information System (INIS)
Karthik Raja, U; Leelamani, A; Raja, R; Samidurai, R
2013-01-01
In this paper, the exponential stability for a class of stochastic neural networks with time-varying delays and impulsive effects is considered. By constructing suitable Lyapunov functionals and by using the linear matrix inequality optimization approach, we obtain sufficient delay-dependent criteria to ensure the exponential stability of stochastic neural networks with time-varying delays and impulses. Two numerical examples with simulation results are provided to illustrate the effectiveness of the obtained results over those already existing in the literature. (paper)
Phenomenological and ratio bifurcations of a class of discrete time stochastic processes
Diks, C.G.H.; Wagener, F.O.O.
2011-01-01
Zeeman proposed a classification of stochastic dynamical systems based on the Morse classification of their invariant probability densities; the associated bifurcations are the ‘phenomenological bifurcations’ of L. Arnold. The classification is however not invariant under diffeomorphisms of the
ARIMA-Based Time Series Model of Stochastic Wind Power Generation
DEFF Research Database (Denmark)
Chen, Peiyuan; Pedersen, Troels; Bak-Jensen, Birgitte
2010-01-01
This paper proposes a stochastic wind power model based on an autoregressive integrated moving average (ARIMA) process. The model takes into account the nonstationarity and physical limits of stochastic wind power generation. The model is constructed based on wind power measurement of one year from...... the Nysted offshore wind farm in Denmark. The proposed limited-ARIMA (LARIMA) model introduces a limiter and characterizes the stochastic wind power generation by mean level, temporal correlation and driving noise. The model is validated against the measurement in terms of temporal correlation...... and probability distribution. The LARIMA model outperforms a first-order transition matrix based discrete Markov model in terms of temporal correlation, probability distribution and model parameter number. The proposed LARIMA model is further extended to include the monthly variation of the stochastic wind power...
International Nuclear Information System (INIS)
Shu Chang-Zheng; Nie Lin-Ru; Zhou Zhong-Rao
2012-01-01
Stochastic resonance (SR)-like and resonance suppression (RS)-like phenomena in a time-delayed bistable system driven by additive white noise are investigated by means of stochastic simulations of the power spectrum, the quality factor of the power spectrum, and the mean first-passage time (MFPT) of the system. The calculative results indicate that: (i) as the system is driven by a small periodic signal, the quality factor as a function delay time exhibits a maximal value at smaller noise intensities, i.e., an SR-like phenomenon. With the increment in additive noise intensity, the extremum gradually disappears and the quality factor decreases monotonously with delay time. (ii) As the additive noise intensity is smaller, the curve of the MFPT with respect to delay time displays a peak, i.e., an RS-like phenomenon. At higher levels of noise, however, the non-monotonic behavior is lost. (general)
International Nuclear Information System (INIS)
Calabrese, Pasquale; Hagendorf, Christian; Doussal, Pierre Le
2008-01-01
We study the time evolution of quantum one-dimensional gapless systems evolving from initial states with a domain wall. We generalize the path integral imaginary time approach that together with boundary conformal field theory allows us to derive the time and space dependence of general correlation functions. The latter are explicitly obtained for the Ising universality class, and the typical behavior of one- and two-point functions is derived for the general case. Possible connections with the stochastic Loewner evolution are discussed and explicit results for one-point time dependent averages are obtained for generic κ for boundary conditions corresponding to stochastic Loewner evolution. We use this set of results to predict the time evolution of the entanglement entropy and obtain the universal constant shift due to the presence of a domain wall in the initial state
International Nuclear Information System (INIS)
Li Hongjie; Yue Dong
2010-01-01
The paper investigates the synchronization stability problem for a class of complex dynamical networks with Markovian jumping parameters and mixed time delays. The complex networks consist of m modes and the networks switch from one mode to another according to a Markovian chain with known transition probability. The mixed time delays are composed of discrete and distributed delays, the discrete time delay is assumed to be random and its probability distribution is known a priori. In terms of the probability distribution of the delays, the new type of system model with probability-distribution-dependent parameter matrices is proposed. Based on the stochastic analysis techniques and the properties of the Kronecker product, delay-dependent synchronization stability criteria in the mean square are derived in the form of linear matrix inequalities which can be readily solved by using the LMI toolbox in MATLAB, the solvability of derived conditions depends on not only the size of the delay, but also the probability of the delay-taking values in some intervals. Finally, a numerical example is given to illustrate the feasibility and effectiveness of the proposed method.
A note on continuous-time stochastic approximation in infinite dimensions
Czech Academy of Sciences Publication Activity Database
Seidler, Jan; Žák, F.
2017-01-01
Roč. 22, č. 1 (2017), č. článku 36. ISSN 1083-589X R&D Projects: GA ČR(CZ) GA15-08819S Institutional support: RVO:67985556 Keywords : stochastic approximation * stochastic parabolic problems * variational solutions Subject RIV: BA - General Mathematics OBOR OECD: Statistics and probability Impact factor: 0.416, year: 2016 http://library.utia.cas.cz/separaty/2017/SI/seidler-0475647.pdf
Multivariate stochastic analysis for Monthly hydrological time series at Cuyahoga River Basin
zhang, L.
2011-12-01
Copula has become a very powerful statistic and stochastic methodology in case of the multivariate analysis in Environmental and Water resources Engineering. In recent years, the popular one-parameter Archimedean copulas, e.g. Gumbel-Houggard copula, Cook-Johnson copula, Frank copula, the meta-elliptical copula, e.g. Gaussian Copula, Student-T copula, etc. have been applied in multivariate hydrological analyses, e.g. multivariate rainfall (rainfall intensity, duration and depth), flood (peak discharge, duration and volume), and drought analyses (drought length, mean and minimum SPI values, and drought mean areal extent). Copula has also been applied in the flood frequency analysis at the confluences of river systems by taking into account the dependence among upstream gauge stations rather than by using the hydrological routing technique. In most of the studies above, the annual time series have been considered as stationary signal which the time series have been assumed as independent identically distributed (i.i.d.) random variables. But in reality, hydrological time series, especially the daily and monthly hydrological time series, cannot be considered as i.i.d. random variables due to the periodicity existed in the data structure. Also, the stationary assumption is also under question due to the Climate Change and Land Use and Land Cover (LULC) change in the fast years. To this end, it is necessary to revaluate the classic approach for the study of hydrological time series by relaxing the stationary assumption by the use of nonstationary approach. Also as to the study of the dependence structure for the hydrological time series, the assumption of same type of univariate distribution also needs to be relaxed by adopting the copula theory. In this paper, the univariate monthly hydrological time series will be studied through the nonstationary time series analysis approach. The dependence structure of the multivariate monthly hydrological time series will be
Energy Technology Data Exchange (ETDEWEB)
Zhang Jinhui [Department of Automatic Control, Beijing Institute of Technology, Beijing 100081 (China)], E-mail: jinhuizhang82@gmail.com; Shi Peng [Faculty of Advanced Technology, University of Glamorgan, Pontypridd CF37 1DL (United Kingdom); ILSCM, School of Science and Engineering, Victoria University, Melbourne, Vic. 8001 (Australia); School of Mathematics and Statistics, University of South Australia, Mawson Lakes, SA 5095 (Australia)], E-mail: pshi@glam.ac.uk; Yang Hongjiu [Department of Automatic Control, Beijing Institute of Technology, Beijing 100081 (China)], E-mail: yanghongjiu@gmail.com
2009-12-15
This paper deals with the problem of non-fragile robust stabilization and H{sub {infinity}} control for a class of uncertain stochastic nonlinear time-delay systems. The parametric uncertainties are real time-varying as well as norm bounded. The time-delay factors are unknown and time-varying with known bounds. The aim is to design a memoryless non-fragile state feedback control law such that the closed-loop system is stochastically asymptotically stable in the mean square and the effect of the disturbance input on the controlled output is less than a prescribed level for all admissible parameter uncertainties. New sufficient conditions for the existence of such controllers are presented based on the linear matrix inequalities (LMIs) approach. Numerical example is given to illustrate the effectiveness of the developed techniques.
Moreno, Jackeline; Vogeley, Michael S.; Richards, Gordon; O'Brien, John T.; Kasliwal, Vishal
2018-01-01
We present rigorous testing of survey cadences (K2, SDSS, CRTS, & Pan-STARRS) for quasar variability science using a magnetohydrodynamics synthetic lightcurve and the canonical lightcurve from Kepler, Zw 229.15. We explain where the state of the art is in regards to physical interpretations of stochastic models (CARMA) applied to AGN variability. Quasar variability offers a time domain approach of probing accretion physics at the SMBH scale. Evidence shows that the strongest amplitude changes in the brightness of AGN occur on long timescales ranging from months to hundreds of days. These global behaviors can be constrained by survey data despite low sampling resolution. CARMA processes provide a flexible family of models used to interpolate between data points, predict future observations and describe behaviors in a lightcurve. This is accomplished by decomposing a signal into rise and decay timescales, frequencies for cyclic behavior and shock amplitudes. Characteristic timescales may point to length-scales over which a physical process operates such as turbulent eddies, warping or hotspots due to local thermal instabilities. We present the distribution of SDSS Stripe 82 quasars in CARMA parameters space that pass our cadence tests and also explain how the Damped Harmonic Oscillator model, CARMA(2,1), reduces to the Damped Random Walk, CARMA(1,0), given the data in a specific region of the parameter space.
Wang, Kang-Kang; Zong, De-Cai; Wang, Ya-Jun; Li, Sheng-Hong
2016-05-01
In this paper, the transition between the stable state of a big density and the extinction state and stochastic resonance (SR) for a time-delayed metapopulation system disturbed by colored cross-correlated noises are investigated. By applying the fast descent method, the small time-delay approximation and McNamara and Wiesenfeld's SR theory, we investigate the impacts of time-delay, the multiplicative, additive noises and colored cross-correlated noise on the SNR and the shift between the two states of the system. Numerical results show that the multiplicative, additive noises and time-delay can all speed up the transition from the stable state to the extinction state, while the correlation noise and its correlation time can slow down the extinction process of the population system. With respect to SNR, the multiplicative noise always weakens the SR effect, while noise correlation time plays a dual role in motivating the SR phenomenon. Meanwhile, time-delay mainly plays a negative role in stimulating the SR phenomenon. Conversely, it could motivate the SR effect to increase the strength of the cross-correlation noise in the SNR-β plot, while the increase of additive noise intensity will firstly excite SR, and then suppress the SR effect.
International Nuclear Information System (INIS)
Gutierrez, Rafael M.; Useche, Gina M.; Buitrago, Elias
2007-01-01
We present a procedure developed to detect stochastic and deterministic information contained in empirical time series, useful to characterize and make models of different aspects of complex phenomena represented by such data. This procedure is applied to a seismological time series to obtain new information to study and understand geological phenomena. We use concepts and methods from nonlinear dynamics and maximum entropy. The mentioned method allows an optimal analysis of the available information
International Nuclear Information System (INIS)
Zhou Yu-Rong
2011-01-01
This paper considers the stochastic resonance for a time-delayed mono-stable system, driven by correlated multiplicative and additive white noise. It finds that the output signal-to-noise ratio (SNR) varies non-monotonically with the delayed times. The SNR varies non-monotonically with the increase of the intensities of the multiplicative and additive noise, with the increase of the correlation strength between the two noises, as well as with the system parameter. (general)
Chang, Mou-Hsiung
2015-01-01
The classical probability theory initiated by Kolmogorov and its quantum counterpart, pioneered by von Neumann, were created at about the same time in the 1930s, but development of the quantum theory has trailed far behind. Although highly appealing, the quantum theory has a steep learning curve, requiring tools from both probability and analysis and a facility for combining the two viewpoints. This book is a systematic, self-contained account of the core of quantum probability and quantum stochastic processes for graduate students and researchers. The only assumed background is knowledge of the basic theory of Hilbert spaces, bounded linear operators, and classical Markov processes. From there, the book introduces additional tools from analysis, and then builds the quantum probability framework needed to support applications to quantum control and quantum information and communication. These include quantum noise, quantum stochastic calculus, stochastic quantum differential equations, quantum Markov semigrou...
Measurement of the time of storage of ultracold neutrons in a magnetic trap
International Nuclear Information System (INIS)
Abov, Y.G.; Borovlev, S.P.; Vasil'ev, V.V.; Vladimirskii, V.V.; Mospan, E.N.
1983-01-01
The storage time of ultracold neutrons in an axial magnetic trap with a simple singly connected confinement region is measured. It is shown that the storage of the neutrons is due just to the magnetic field. The storage time achieved is tau = 303 +- 37 sec. In a working cycle 3.6 neutrons are accumulated
An Innovative Real-time Environment for Unified Deterministic and Stochastic Groundwater Modeling
Li, S.; Liu, Q.
2003-12-01
Despite an exponential growth of computational capability over the last two decades-one that has allowed computational science and engineering to become a unique, powerful tool for scientific discovery-the extreme cost of groundwater modeling continues to limit its use. This occurs primarily because the modeling paradigm that has been employed for decades limits our ability to take full advantage of recent developments in computer, communication, graphic, and visualization technologies. In this presentation we introduce an innovative and sophisticated computational environment for groundwater modeling that promises to eliminate the current bottleneck and greatly expand the utility of computational tools for scientific discovery related to groundwater. Based on a set of efficient and robust computational algorithms, the new software system, called Interactive Groundwater (IGW), allows simulating complex flow and transport in aquifers subject to both systematic and "randomly" varying stresses and geological and chemical heterogeneity. Adopting a new paradigm, IGW eliminates a major bottleneck inherent in the traditional fragmented modeling technologies and enables real-time modeling, real-time visualization, real-time analysis, and real-time presentation. IGW functions as a "numerical laboratory" in which a researcher can freely explore in real-time: creating visually an aquifer of desired configurations, interactively imposing desired stresses, and then immediately investigating and visualizing the geology and the processes of flow and contaminant transport and transformation. A modeler can pause to edit at any time and interact on-line with any aspects (e.g., conceptual and numerical representation, boundary conditions, model solvers, and ways of visualization and analysis) of the integrated modeling process; he/she can initiate or stop, whenever needed, particle tracking, plume modeling, subscale modeling, cross-sectional modeling, stochastic modeling, monitoring
Optimal Time to Invest Energy Storage System under Uncertainty Conditions
Directory of Open Access Journals (Sweden)
Yongma Moon
2014-04-01
Full Text Available This paper proposes a model to determine the optimal investment time for energy storage systems (ESSs in a price arbitrage trade application under conditions of uncertainty over future profits. The adoption of ESSs can generate profits from price arbitrage trade, which are uncertain because the future marginal prices of electricity will change depending on supply and demand. In addition, since the investment is optional, an investor can delay adopting an ESS until it becomes profitable, and can decide the optimal time. Thus, when we evaluate this investment, we need to incorporate the investor’s option which is not captured by traditional evaluation methods. In order to incorporate these aspects, we applied real option theory to our proposed model, which provides an optimal investment threshold. Our results concerning the optimal time to invest show that if future profits that are expected to be obtained from arbitrage trade become more uncertain, an investor needs to wait longer to invest. Also, improvement in efficiency of ESSs can reduce the uncertainty of arbitrage profit and, consequently, the reduced uncertainty enables earlier ESS investment, even for the same power capacity. Besides, when a higher rate of profits is expected and ESS costs are higher, an investor needs to wait longer. Also, by comparing a widely used net present value model to our real option model, we show that the net present value method underestimates the value for ESS investment and misleads the investor to make an investment earlier.
International Nuclear Information System (INIS)
Nojavan, Sayyad; Aalami, Habib allah
2015-01-01
Highlights: • A stochastic energy procurement cost function in presence of DRP is proposed. • The load, price and output power of PV and wind uncertainties are modeled. • Four case studies are used to assess the effects of ESS and DRP on SEPP. • Case 4 is considered the effects of ESS and DRP simultaneously. • The expected energy procurement cost of case 4 is lower than cases 1, 2 and 3. - Abstract: This paper proposes a stochastic energy procurement problem (SEPP) for large electricity consumer (LEC) with multiple energy procurement sources (EPSs) considering the effects of demand response program (DRP) and energy storage system (ESS). The EPSs contain power market (PM), bilateral contracts (BCs), micro-turbines (MTs), and renewable energy sources (RESs). Moreover, the RESs include photovoltaic (PV) systems and wind-turbines (WT). The ESS and DRP are incorporated in the SEPP by the LEC’s decision-maker to reduce the expected energy procurement cost (EEPC). Meanwhile, the uncertainty models of market price, load and RES output power are considered in the SEPP formulation. The error of forecasting of market price, load, temperature and radiation of PV systems are modeled using the normal distribution for generating the related scenarios. Also, the weibull distribution is used to generate variable wind speed scenarios for WT output power uncertainty modeling. Furthermore, the fast forward selection based on Kantorovich distance approach is used for the scenarios reduction. Finally, the influences of ESS and DRP on EEPC are investigated, and four case studies are used to illustrate the capability of the proposed SEPP. The obtained results demonstrate the efficiency of the proposed stochastic program
Simple DNA extraction of urine samples: Effects of storage temperature and storage time.
Ng, Huey Hian; Ang, Hwee Chen; Hoe, See Ying; Lim, Mae-Lynn; Tai, Hua Eng; Soh, Richard Choon Hock; Syn, Christopher Kiu-Choong
2018-06-01
Urine samples are commonly analysed in cases with suspected illicit drug consumption. In events of alleged sample mishandling, urine sample source identification may be necessary. A simple DNA extraction procedure suitable for STR typing of urine samples was established on the Promega Maxwell ® 16 paramagnetic silica bead platform. A small sample volume of 1.7mL was used. Samples were stored at room temperature, 4°C and -20°C for 100days to investigate the influence of storage temperature and time on extracted DNA quantity and success rate of STR typing. Samples stored at room temperature exhibited a faster decline in DNA yield with time and lower typing success rates as compared to those at 4°C and -20°C. This trend can likely be attributed to DNA degradation. In conclusion, this study presents a quick and effective DNA extraction protocol from a small urine volume stored for up to 100days at 4°C and -20°C. Copyright © 2018 Elsevier B.V. All rights reserved.
Finite approximations in discrete-time stochastic control quantized models and asymptotic optimality
Saldi, Naci; Yüksel, Serdar
2018-01-01
In a unified form, this monograph presents fundamental results on the approximation of centralized and decentralized stochastic control problems, with uncountable state, measurement, and action spaces. It demonstrates how quantization provides a system-independent and constructive method for the reduction of a system with Borel spaces to one with finite state, measurement, and action spaces. In addition to this constructive view, the book considers both the information transmission approach for discretization of actions, and the computational approach for discretization of states and actions. Part I of the text discusses Markov decision processes and their finite-state or finite-action approximations, while Part II builds from there to finite approximations in decentralized stochastic control problems. This volume is perfect for researchers and graduate students interested in stochastic controls. With the tools presented, readers will be able to establish the convergence of approximation models to original mo...
Optimal control strategy for an impulsive stochastic competition system with time delays and jumps
Liu, Lidan; Meng, Xinzhu; Zhang, Tonghua
2017-07-01
Driven by both white and jump noises, a stochastic delayed model with two competitive species in a polluted environment is proposed and investigated. By using the comparison theorem of stochastic differential equations and limit superior theory, sufficient conditions for persistence in mean and extinction of two species are established. In addition, we obtain that the system is asymptotically stable in distribution by using ergodic method. Furthermore, the optimal harvesting effort and the maximum of expectation of sustainable yield (ESY) are derived from Hessian matrix method and optimal harvesting theory of differential equations. Finally, some numerical simulations are provided to illustrate the theoretical results.
Directory of Open Access Journals (Sweden)
YaJun Li
2015-01-01
Full Text Available The passivity problem for a class of stochastic neural networks systems (SNNs with varying delay and leakage delay has been further studied in this paper. By constructing a more effective Lyapunov functional, employing the free-weighting matrix approach, and combining with integral inequality technic and stochastic analysis theory, the delay-dependent conditions have been proposed such that SNNs are asymptotically stable with guaranteed performance. The time-varying delay is divided into several subintervals and two adjustable parameters are introduced; more information about time delay is utilised and less conservative results have been obtained. Examples are provided to illustrate the less conservatism of the proposed method and simulations are given to show the impact of leakage delay on stability of SNNs.
Huang, Haiying; Du, Qiaosheng; Kang, Xibing
2013-11-01
In this paper, a class of neutral high-order stochastic Hopfield neural networks with Markovian jump parameters and mixed time delays is investigated. The jumping parameters are modeled as a continuous-time finite-state Markov chain. At first, the existence of equilibrium point for the addressed neural networks is studied. By utilizing the Lyapunov stability theory, stochastic analysis theory and linear matrix inequality (LMI) technique, new delay-dependent stability criteria are presented in terms of linear matrix inequalities to guarantee the neural networks to be globally exponentially stable in the mean square. Numerical simulations are carried out to illustrate the main results. © 2013 ISA. Published by ISA. All rights reserved.
International Nuclear Information System (INIS)
Pham, Nhu Viet Ha
2011-02-01
To predict the space-time dependent behavior of a nuclear reactor, the conventional space-dependent kinetics equations are widely used for treating the spatial variables. However, the solutions of such deterministic space-dependent kinetics equations, which give only the mean values of the neutron population and the delayed neutron precursor concentrations, do not offer sufficient insight into the actual dynamic processes within a reactor, where the interacting populations vary randomly with space and time. It is also noted that at high power levels, the random behavior of a reactor is negligible but at low power levels, such as at start-up, random fluctuations in population dynamics can be significant. To mathematically describe the evolution of the state of a nuclear reactor using a set of stochastic kinetics equations, the forward stochastic model (FSM) in stochastic kinetics theory is devised through the concept of reactor transition probability and its probability generating function as the spatial domain of a reactor is partitioned into a number of space cells. Nevertheless, the FSM equations for the mean value of neutron and precursor distribution are deterministic-like. Furthermore, the numerical treatment of the FSM equations for the means, variances, and covariances is quite complicated and time-consuming. In the present study, a generalized stochastic model (called the stochastic space-dependent kinetics model or SSKM) based on the FSM and the Its stochastic differential equations was newly developed for the analysis of monoenergetic spacetime nuclear reactor kinetics in one dimension. First, the FSM equations for determining the mean values of neutron and delayed-neutron precursor populations were considered as the deterministic ones without taking into account their variances and covariances. Second, the system of interest was randomized again in the light of the Its stochastic differential equations in order to derive the SSKM. The proposed model
Bakhtavar, E.; Abdollahisharif, J.; Aminzadeh, A.
2017-01-01
This research introduces a stochastic mathematical model that uses open pit long-term production planning on an integrated open pit and underground block model to determine the optimal time for transition from open pit to underground mining. In the model, ore grade is considered a random parameter in objective function and ore grade blending constraints. The objective function is modelled as the maximization of net present value in the mode of non-simultaneous combined open pit and undergroun...
International Nuclear Information System (INIS)
Nemnes, G A; Anghel, D V
2010-01-01
We present a stochastic method for the simulation of the time evolution in systems which obey generalized statistics, namely fractional exclusion statistics and Gentile's statistics. The transition rates are derived in the framework of canonical ensembles. This approach introduces a tool for describing interacting fermionic and bosonic systems in non-equilibrium as ideal FES systems, in a computationally efficient manner. The two types of statistics are analyzed comparatively, indicating their intrinsic thermodynamic differences and revealing key aspects related to the species size
Kozlovskaya, Luba; Popilski, Hen; Gorenbein, Pavel; Stepensky, David
2015-07-15
Disposable medical devices release toxic leachables during their clinical use. Specifically, the individual parts of the infusion sets (the drip chamber, tube, flashball and injection site) are composed of numerous chemical compounds that can reach the patients' systemic circulation and induce local and systemic toxic effects. We aimed to reveal the relative in vitro toxicity of infusion sets from the leading vendors that are used in Israel, and to determine its dependence on their design and storage time/conditions. We found that leachates of the rubber parts were more toxic than those of the other parts of the infusion sets. The measured toxicity was affected by the experimental settings: the cells, medium composition, exposure duration, and the type of assay applied for toxicity assessment. We recommend to use the capillary endothelium cells for in vitro toxicity testing of the infusion sets, and refrain from the use of the MTT test which is insufficiently reliable, and can lead to artefacts and incorrect conclusions. Further investigation is needed to identify the toxic leachables from the individual parts of the infusion sets, and to reveal the risk of their toxicity during the clinical use of the infusion sets. Copyright © 2015 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
Rathinasamy Sakthivel
2018-01-01
Full Text Available The problem of robust nonfragile synchronization is investigated in this paper for a class of complex dynamical networks subject to semi-Markov jumping outer coupling, time-varying coupling delay, randomly occurring gain variation, and stochastic noise over a desired finite-time interval. In particular, the network topology is assumed to follow a semi-Markov process such that it may switch from one to another at different instants. In this paper, the random gain variation is represented by a stochastic variable that is assumed to satisfy the Bernoulli distribution with white sequences. Based on these hypotheses and the Lyapunov-Krasovskii stability theory, a new finite-time stochastic synchronization criterion is established for the considered network in terms of linear matrix inequalities. Moreover, the control design parameters that guarantee the required criterion are computed by solving a set of linear matrix inequality constraints. An illustrative example is finally given to show the effectiveness and advantages of the developed analytical results.
Effect of semen extender and storage temperature on ram sperm motility over time
Storage of ram semen for long period of time depends on a number of factors, including type of extender and storage temperature. A study compared the effect of semen extender and storage temperature on motility of ram semen stored for 72 h. Semen collected via electroejaculator from 5 mature Katahd...
Effect of storage time and temperature on the rheological and microstructural properties of gluten
Nicolas, Y.; Smit, R.J.M.; van Aalst, H.; Esselink, F.J.; Weegels, P.L.; Agterof, W.G.M.
2003-01-01
To investigate the effects of frozen storage on the rheological and microstructural properties of gluten, two model systems were investigated: System A, gluten and water; System B, gluten, water, and NaCl. The storage time was varied from 1 to 16 weeks and the storage temperature was varied from -5
CHANGE OF BIOCHEMICAL COMPOSITION OF PUMPKIN FRUITS DEPENDING ON STORAGE TIME
Directory of Open Access Journals (Sweden)
A. S. Karapetyan
2015-01-01
Full Text Available Pumpkin fruits are the source of carbohydrates, mineral salts and vitamins during wintertime. The change of the biochemical compositions of pumpkin fruits depending on storage time has been studied. The results of chemical analysis revealed that during four months of storage the content of quality indicators increased followed by its reduction after five and more month of storage.
Directory of Open Access Journals (Sweden)
Shnoll S. E.
2006-04-01
Full Text Available This is a survey of the fine structure stochastic distributions in measurements obtained by me over 50 years. It is shown: (1 The forms of the histograms obtained at each geographic point (at each given moment of time are similar with high probability, even if we register phenomena of completely different nature --- from biochemical reactions to the noise in a gravitational antenna, or alpha-decay. (2 The forms of the histograms change with time. The iterations of the same form have the periods of the stellar day (1.436 min, the solar day (1.440 min, the calendar year (365 solar days, and the sidereal year (365 solar days plus 6 hours and 9 min. (3 At the same instants of the local time, at different geographic points, the forms of the histograms are the same, with high probability. (4 The forms of the histograms depend on the locations of the Moon and the Sun with respect to the horizon. (5 All the facts are proof of the dependance of the form of the histograms on the location of the measured objects with respect to stars, the Sun, and the Moon. (6 At the instants of New Moon and the maxima of solar eclipses there are specific forms of the histograms. (7 It is probable that the observed correlations are not connected to flow power changes (the changes of the gravity force --- we did not find the appropriate periods in changes in histogram form. (8 A sharp anisotropy of space was discovered, registered by alpha-decay detectors armed with collimators. Observations at 54 North (the collimator was pointed at the Pole Star showed no day-long periods, as was also the case for observations at 82 North, near the Pole. Histograms obtained by observations with an Easterly-directed collimator were determined every 718 minutes (half stellar day and with observations using a Westerly-directed collimator. (9 Collimators rotating counter-clockwise, in parallel with the celestial equator, gave the probability of changes in histograms as the number of the
Directory of Open Access Journals (Sweden)
Shnoll S. E.
2006-04-01
Full Text Available This is a survey of the fine structure stochastic distributions in measurements obtained by me over 50 years. It is shown: (1 The forms of the histograms obtained at each geographic point (at each given moment of time are similar with high probability, even if we register phenomena of completely different nature — from biochemical reactions to the noise in a gravitational antenna, or α-decay. (2 The forms of the histograms change with time. The iterations of the same form have the periods of the stellar day (1.436 min, the solar day (1.440 min, the calendar year (365 solar days, and the sidereal year (365 solar days plus 6 hours and 9 min. (3 At the same instants of the local time, at different geographic points, the forms of the histograms are the same, with high probability. (4 The forms of the histograms depend on the locations of the Moon and the Sun with respect to the horizon. (5 All the facts are proof of the dependance of the form of the histograms on the location of the measured objects with respect to stars, the Sun, and the Moon. (6 At the instants of New Moon and the maxima of solar eclipses there are specific forms of the histograms. (7 It is probable that the observed correlations are not connected to flow power changes (the changes of the gravity force — we did not find the appropriate periods in changes in histogram form. (8 A sharp anisotropy of space was discovered, registered by α-decay detectors armed with collimators. Observations at 54◦ North (the collimator was pointed at the Pole Star showed no day-long periods, as was also the case for observations at 82◦ North, near the Pole. Histograms obtained by observations with an Easterly-directed collimator were determined every 718 minutes (half stellar day and with observations using a Westerly-directed collimator. (9 Collimators rotating counter-clockwise, in parallel with the celestial equator, gave the probability of changes in histograms as the number of the
Water Storage, Mixing and Transit Times During a Multiyear Drought.
Van der Velde, Y.; Visser, A.; Thaw, M.; Safeeq, M.
2017-12-01
From 2012 to 2016, a five year intensive drought occurred in the Californian Sierra Nevada. We use this drought period as an opportunity to investigate how catchment water storage, mixing and transit times changes from wet to dry conditions using long term datasets of river discharge, evapotranspiration, water quality, and multiple cosmogenic radioactive isotopes. Characteristic features of the test catchment (4.6 km2 , altitude 1660-2117 m) include a thick (>5m) unsaturated zone in deeply weathered granite mountain soils, snow melt and events of high intensity rainfall, dry summers and numerous wetland meadows along the stream. Our data and model analysis suggest that under drought conditions, river flow predominantly consist of deep groundwater tapped by deeply incised sections of the stream, while the wetlands hold on to their water just below the root system of its shallow rooting vegetation. In contrast, during wet periods, most runoff is generated on the flat riparian wetland meadows, while the regional groundwater system slowly refills itself as water makes its way through the thick unsaturated zones. Antecedent wet or dry years play an crucial role as antecedent wet years cause a substantial regional groundwater flow towards the riparian wetlands, filling up the riparian wetlands and yielding a much stronger discharge response of the wetlands to rainfall events than under antecedent dry years This interaction between the regional groundwater system and the local wetland systems weakens as the drought progresses and regional groundwater flow to the wetlands lessens. Although, due to the wet events in 2016-2017, the catchment fills up rapidly to pre-drought conditions, we show that water transit times and therefore likely the water quality will contain drought signs for several years to come. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS- XXXXXX
Sharma, Pankaj; Jain, Ajai
2014-12-01
Stochastic dynamic job shop scheduling problem with consideration of sequence-dependent setup times are among the most difficult classes of scheduling problems. This paper assesses the performance of nine dispatching rules in such shop from makespan, mean flow time, maximum flow time, mean tardiness, maximum tardiness, number of tardy jobs, total setups and mean setup time performance measures viewpoint. A discrete event simulation model of a stochastic dynamic job shop manufacturing system is developed for investigation purpose. Nine dispatching rules identified from literature are incorporated in the simulation model. The simulation experiments are conducted under due date tightness factor of 3, shop utilization percentage of 90% and setup times less than processing times. Results indicate that shortest setup time (SIMSET) rule provides the best performance for mean flow time and number of tardy jobs measures. The job with similar setup and modified earliest due date (JMEDD) rule provides the best performance for makespan, maximum flow time, mean tardiness, maximum tardiness, total setups and mean setup time measures.
Yan, S.; Lin, H. C.; Jiang, X. Y.
2012-04-01
In this study the authors employ network flow techniques to construct a systematic model that helps ready mixed concrete carriers effectively plan production and truck dispatching schedules under stochastic travel times. The model is formulated as a mixed integer network flow problem with side constraints. Problem decomposition and relaxation techniques, coupled with the CPLEX mathematical programming solver, are employed to develop an algorithm that is capable of efficiently solving the problems. A simulation-based evaluation method is also proposed to evaluate the model, coupled with a deterministic model, and the method currently used in actual operations. Finally, a case study is performed using real operating data from a Taiwan RMC firm. The test results show that the system operating cost obtained using the stochastic model is a significant improvement over that obtained using the deterministic model or the manual approach. Consequently, the model and the solution algorithm could be useful for actual operations.
International Nuclear Information System (INIS)
Ali, M. Syed
2011-01-01
In this paper, the global stability of Takagi—Sugeno (TS) uncertain stochastic fuzzy recurrent neural networks with discrete and distributed time-varying delays (TSUSFRNNs) is considered. A novel LMI-based stability criterion is obtained by using Lyapunov functional theory to guarantee the asymptotic stability of TSUSFRNNs. The proposed stability conditions are demonstrated through numerical examples. Furthermore, the supplementary requirement that the time derivative of time-varying delays must be smaller than one is removed. Comparison results are demonstrated to show that the proposed method is more able to guarantee the widest stability region than the other methods available in the existing literature. (general)
Borodin, Andrei N
2017-01-01
This book provides a rigorous yet accessible introduction to the theory of stochastic processes. A significant part of the book is devoted to the classic theory of stochastic processes. In turn, it also presents proofs of well-known results, sometimes together with new approaches. Moreover, the book explores topics not previously covered elsewhere, such as distributions of functionals of diffusions stopped at different random times, the Brownian local time, diffusions with jumps, and an invariance principle for random walks and local times. Supported by carefully selected material, the book showcases a wealth of examples that demonstrate how to solve concrete problems by applying theoretical results. It addresses a broad range of applications, focusing on concrete computational techniques rather than on abstract theory. The content presented here is largely self-contained, making it suitable for researchers and graduate students alike.
Directory of Open Access Journals (Sweden)
Nishiura Hiroshi
2011-02-01
Full Text Available Abstract Background Real-time forecasting of epidemics, especially those based on a likelihood-based approach, is understudied. This study aimed to develop a simple method that can be used for the real-time epidemic forecasting. Methods A discrete time stochastic model, accounting for demographic stochasticity and conditional measurement, was developed and applied as a case study to the weekly incidence of pandemic influenza (H1N1-2009 in Japan. By imposing a branching process approximation and by assuming the linear growth of cases within each reporting interval, the epidemic curve is predicted using only two parameters. The uncertainty bounds of the forecasts are computed using chains of conditional offspring distributions. Results The quality of the forecasts made before the epidemic peak appears largely to depend on obtaining valid parameter estimates. The forecasts of both weekly incidence and final epidemic size greatly improved at and after the epidemic peak with all the observed data points falling within the uncertainty bounds. Conclusions Real-time forecasting using the discrete time stochastic model with its simple computation of the uncertainty bounds was successful. Because of the simplistic model structure, the proposed model has the potential to additionally account for various types of heterogeneity, time-dependent transmission dynamics and epidemiological details. The impact of such complexities on forecasting should be explored when the data become available as part of the disease surveillance.
Tavakkoli-Moghaddam, Reza; Alinaghian, Mehdi; Salamat-Bakhsh, Alireza; Norouzi, Narges
2012-05-01
A vehicle routing problem is a significant problem that has attracted great attention from researchers in recent years. The main objectives of the vehicle routing problem are to minimize the traveled distance, total traveling time, number of vehicles and cost function of transportation. Reducing these variables leads to decreasing the total cost and increasing the driver's satisfaction level. On the other hand, this satisfaction, which will decrease by increasing the service time, is considered as an important logistic problem for a company. The stochastic time dominated by a probability variable leads to variation of the service time, while it is ignored in classical routing problems. This paper investigates the problem of the increasing service time by using the stochastic time for each tour such that the total traveling time of the vehicles is limited to a specific limit based on a defined probability. Since exact solutions of the vehicle routing problem that belong to the category of NP-hard problems are not practical in a large scale, a hybrid algorithm based on simulated annealing with genetic operators was proposed to obtain an efficient solution with reasonable computational cost and time. Finally, for some small cases, the related results of the proposed algorithm were compared with results obtained by the Lingo 8 software. The obtained results indicate the efficiency of the proposed hybrid simulated annealing algorithm.
Extreme-Strike and Small-time Asymptotics for Gaussian Stochastic Volatility Models
Zhang, Xin
2016-01-01
Asymptotic behavior of implied volatility is of our interest in this dissertation. For extreme strike, we consider a stochastic volatility asset price model in which the volatility is the absolute value of a continuous Gaussian process with arbitrary prescribed mean and covariance. By exhibiting a Karhunen-Loève expansion for the integrated variance, and using sharp estimates of the density of a general second-chaos variable, we derive asymptotics for the asset price density for large or smal...
Czech Academy of Sciences Publication Activity Database
Baruník, Jozef; Kukačka, Jiří
2015-01-01
Roč. 15, č. 6 (2015), s. 959-973 ISSN 1469-7688 R&D Projects: GA ČR GA402/09/0965; GA ČR GA13-32263S EU Projects: European Commission 612955 - FINMAP Institutional support: RVO:67985556 Keywords : Stochastic cusp catastrophe model * Realized volatility * Bifurcations * Stock market crash Subject RIV: AH - Economics Impact factor: 0.794, year: 2015 http://library.utia.cas.cz/separaty/2014/E/barunik-0434202.pdf
Pan, Indranil; Das, Saptarshi; Gupta, Amitava
2011-01-01
An optimal PID and an optimal fuzzy PID have been tuned by minimizing the Integral of Time multiplied Absolute Error (ITAE) and squared controller output for a networked control system (NCS). The tuning is attempted for a higher order and a time delay system using two stochastic algorithms viz. the Genetic Algorithm (GA) and two variants of Particle Swarm Optimization (PSO) and the closed loop performances are compared. The paper shows that random variation in network delay can be handled efficiently with fuzzy logic based PID controllers over conventional PID controllers. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Wang Shen-Quan; Feng Jian; Zhao Qing
2012-01-01
In this paper, the problem of delay-distribution-dependent stability is investigated for continuous-time recurrent neural networks (CRNNs) with stochastic delay. Different from the common assumptions on time delays, it is assumed that the probability distribution of the delay taking values in some intervals is known a priori. By making full use of the information concerning the probability distribution of the delay and by using a tighter bounding technique (the reciprocally convex combination method), less conservative asymptotic mean-square stable sufficient conditions are derived in terms of linear matrix inequalities (LMIs). Two numerical examples show that our results are better than the existing ones. (general)
International Nuclear Information System (INIS)
Sharma, P.; Khare, M.
2000-01-01
Historical data of the time-series of carbon monoxide (CO) concentration was analysed using Box-Jenkins modelling approach. Univariate Linear Stochastic Models (ULSMs) were developed to examine the degree of prediction possible for situations where only a limited data set, restricted only to the past record of pollutant data are available. The developed models can be used to provide short-term, real-time forecast of extreme CO concentrations for an Air Quality Control Region (AQCR), comprising a major traffic intersection in a Central Business District of Delhi City, India. (author)
Pulping Variables, Storage Time and Pitch Deposit | Ogunwusi ...
African Journals Online (AJOL)
Pulp resin is also influenced by effective alkali concentration of the pulping medium. With increase in effective alkali concentration from 13% to 15%, pulp pitch is reduced. The interaction effect of storage and effective alkali concentration was not significant indicating that reduction in pulp pitch caused by effective alkali ...
Klos, A.; Bogusz, J.; Moreaux, G.
2017-12-01
This research focuses on the investigation of the deterministic and stochastic parts of the DORIS (Doppler Orbitography and Radiopositioning Integrated by Satellite) weekly coordinate time series from the IDS contribution to the ITRF2014A set of 90 stations was divided into three groups depending on when the data was collected at an individual station. To reliably describe the DORIS time series, we employed a mathematical model that included the long-term nonlinear signal, linear trend, seasonal oscillations (these three sum up to produce the Polynomial Trend Model) and a stochastic part, all being resolved with Maximum Likelihood Estimation (MLE). We proved that the values of the parameters delivered for DORIS data are strictly correlated with the time span of the observations, meaning that the most recent data are the most reliable ones. Not only did the seasonal amplitudes decrease over the years, but also, and most importantly, the noise level and its type changed significantly. We examined five different noise models to be applied to the stochastic part of the DORIS time series: a pure white noise (WN), a pure power-law noise (PL), a combination of white and power-law noise (WNPL), an autoregressive process of first order (AR(1)) and a Generalized Gauss Markov model (GGM). From our study it arises that the PL process may be chosen as the preferred one for most of the DORIS data. Moreover, the preferred noise model has changed through the years from AR(1) to pure PL with few stations characterized by a positive spectral index.
Guimarães, Rita Cabral; Santos, Emidio Gil
2011-01-01
Simulation has been an important tool for planners in many fields of knowledge. In the field of water resources the uncertainties due to unknown data population and the short length of the records work together to make the simulation especially important. The major utilization of water resources at the level needed in modern society makes water storage essential for satisfying the demand. Therefore, the need to reduce the uncertainty in the design of water storage capacity is an important pro...
Effect of storage media and time on fin explants culture in the ...
African Journals Online (AJOL)
The effect of storage media and time was investigated on fin explants culture in the goldfish (Carassius auratus). Fin explants under sterile conditions were able to produce cells at different storage media and time. On the outgrowth of cells, fin explants stored for seven days before culturing showed significantly higher growth ...
Post-cold-storage conditioning time affects soil denitrifying enzyme activity
DEFF Research Database (Denmark)
Chirinda, Ngonidzashe; Olesen, Jørgen Eivind; Porter, John Roy
2011-01-01
Soil denitrifying enzyme activity (DEA) is often assessed after cold storage. Previous studies using the short-term acetylene inhibition method have not considered conditioning time (post-cold-storage warm-up time prior to soil analysis) as a factor influencing results. We observed fluctuations...
International Nuclear Information System (INIS)
Ali, M. Syed
2014-01-01
In this paper, the global asymptotic stability problem of Markovian jumping stochastic Cohen—Grossberg neural networks with discrete and distributed time-varying delays (MJSCGNNs) is considered. A novel LMI-based stability criterion is obtained by constructing a new Lyapunov functional to guarantee the asymptotic stability of MJSCGNNs. Our results can be easily verified and they are also less restrictive than previously known criteria and can be applied to Cohen—Grossberg neural networks, recurrent neural networks, and cellular neural networks. Finally, the proposed stability conditions are demonstrated with numerical examples
Optimization of time and location dependent spent nuclear fuel storage capacity
International Nuclear Information System (INIS)
Macek, V.
1977-01-01
A linear spent fuel storage model is developed to identify cost-effective spent nuclear fuel storage strategies. The purpose of this model is to provide guidelines for the implementation of the optimal time-dependent spent fuel storage capacity expansion in view of the current economic and regulatory environment which has resulted in phase-out of the closed nuclear fuel cycle. Management alternatives of the spent fuel storage backlog, which is created by mismatch between spent fuel generation rate and spent fuel disposition capability, are represented by aggregate decision variables which describe the time dependent on-reactor-site and off-site spent fuel storage capacity additions, and the amount of spent fuel transferred to off-site storage facilities. Principal constraints of the model assure determination of cost optimal spent fuel storage expansion strategies, while spent fuel storage requirements are met at all times. A detailed physical and economic analysis of the essential components of the spent fuel storage problem, which precedes the model development, assures its realism. The effects of technological limitations on the on-site spent fuel storage expansion and timing of reinitiation of the spent fuel reprocessing on optimal spent fuel storage capacity expansion are investigated. The principal results of the study indicate that (a) expansion of storage capacity beyond that of currently planned facilities is necessary, and (b) economics of the post-reactor fuel cycle is extremely sensitive to the timing of reinitiation of spent fuel reprocessing. Postponement of reprocessing beyond mid-1982 may result in net negative economic liability of the back end of the nuclear fuel cycle
Eichhorn, Ralf; Aurell, Erik
2014-04-01
theory for small deviations from equilibrium, in which a general framework is constructed from the analysis of non-equilibrium states close to equilibrium. In a next step, Prigogine and others developed linear irreversible thermodynamics, which establishes relations between transport coefficients and entropy production on a phenomenological level in terms of thermodynamic forces and fluxes. However, beyond the realm of linear response no general theoretical results were available for quite a long time. This situation has changed drastically over the last 20 years with the development of stochastic thermodynamics, revealing that the range of validity of thermodynamic statements can indeed be extended deep into the non-equilibrium regime. Early developments in that direction trace back to the observations of symmetry relations between the probabilities for entropy production and entropy annihilation in non-equilibrium steady states [5-8] (nowadays categorized in the class of so-called detailed fluctuation theorems), and the derivations of the Bochkov-Kuzovlev [9, 10] and Jarzynski relations [11] (which are now classified as so-called integral fluctuation theorems). Apart from its fundamental theoretical interest, the developments in stochastic thermodynamics have experienced an additional boost from the recent experimental progress in fabricating, manipulating, controlling and observing systems on the micro- and nano-scale. These advances are not only of formidable use for probing and monitoring biological processes on the cellular, sub-cellular and molecular level, but even include the realization of a microscopic thermodynamic heat engine [12] or the experimental verification of Landauer's principle in a colloidal system [13]. The scientific program Stochastic Thermodynamics held between 4 and 15 March 2013, and hosted by The Nordic Institute for Theoretical Physics (Nordita), was attended by more than 50 scientists from the Nordic countries and elsewhere, amongst them
Larrañeta, M.; Moreno-Tejera, S.; Lillo-Bravo, I.; Silva-Pérez, M. A.
2018-02-01
Many of the available solar radiation databases only provide global horizontal irradiance (GHI) while there is a growing need of extensive databases of direct normal radiation (DNI) mainly for the development of concentrated solar power and concentrated photovoltaic technologies. In the present work, we propose a methodology for the generation of synthetic DNI hourly data from the hourly average GHI values by dividing the irradiance into a deterministic and stochastic component intending to emulate the dynamics of the solar radiation. The deterministic component is modeled through a simple classical model. The stochastic component is fitted to measured data in order to maintain the consistency of the synthetic data with the state of the sky, generating statistically significant DNI data with a cumulative frequency distribution very similar to the measured data. The adaptation and application of the model to the location of Seville shows significant improvements in terms of frequency distribution over the classical models. The proposed methodology applied to other locations with different climatological characteristics better results than the classical models in terms of frequency distribution reaching a reduction of the 50% in the Finkelstein-Schafer (FS) and Kolmogorov-Smirnov test integral (KSI) statistics.
Blanchet, Adrien
2009-01-01
A periodic perturbation of a Gaussian measure modifies the sharp constants in Poincarae and logarithmic Sobolev inequalities in the homogeniz ation limit, that is, when the period of a periodic perturbation converges to zero. We use variational techniques to determine the homogenized constants and get optimal convergence rates toward s equilibrium of the solutions of the perturbed diffusion equations. The study of these sharp constants is motivated by the study of the stochastic Stokes\\' drift. It also applies to Brownian ratchets and molecular motors in biology. We first establish a transport phenomenon. Asymptotically, the center of mass of the solution moves with a constant velocity, which is determined by a doubly periodic problem. In the reference frame attached to the center of mass, the behavior of the solution is governed at large scale by a diffusion with a modified diffusion coefficient. Using the homogenized logarithmic Sobolev inequality, we prove that the solution converges in self-similar variables attached to t he center of mass to a stationary solution of a Fokker-Planck equation modulated by a periodic perturbation with fast oscillations, with an explicit rate. We also give an asymptotic expansion of the traveling diffusion front corresponding to the stochastic Stokes\\' drift with given potential flow. © 2009 Society for Industrial and Applied Mathematics.
Wang, Pengfei; Jin, Wei; Su, Huan
2018-04-01
This paper deals with the synchronization problem of a class of coupled stochastic complex-valued drive-response networks with time-varying delays via aperiodically intermittent adaptive control. Different from the previous works, the intermittent control is aperiodic and adaptive, and the restrictions on the control width and time delay are removed, which lead to a larger application scope for this control strategy. Then, based on the Lyapunov method and Kirchhoff's Matrix Tree Theorem as well as differential inequality techniques, several novel synchronization conditions are derived for the considered model. Specially, impulsive control is also considered, which can be seen as a special case of the aperiodically intermittent control when the control width tends to zero. And the corresponding synchronization criteria are given as well. As an application of the theoretical results, a class of stochastic complex-valued coupled oscillators with time-varying delays is studied, and the numerical simulations are also given to demonstrate the effectiveness of the control strategies.
Si, Wenjie; Dong, Xunde; Yang, Feifei
2018-03-01
This paper is concerned with the problem of decentralized adaptive backstepping state-feedback control for uncertain high-order large-scale stochastic nonlinear time-delay systems. For the control design of high-order large-scale nonlinear systems, only one adaptive parameter is constructed to overcome the over-parameterization, and neural networks are employed to cope with the difficulties raised by completely unknown system dynamics and stochastic disturbances. And then, the appropriate Lyapunov-Krasovskii functional and the property of hyperbolic tangent functions are used to deal with the unknown unmatched time-delay interactions of high-order large-scale systems for the first time. At last, on the basis of Lyapunov stability theory, the decentralized adaptive neural controller was developed, and it decreases the number of learning parameters. The actual controller can be designed so as to ensure that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB) and the tracking error converges in the small neighborhood of zero. The simulation example is used to further show the validity of the design method. Copyright © 2018 Elsevier Ltd. All rights reserved.
Stochastic volatility and stochastic leverage
DEFF Research Database (Denmark)
Veraart, Almut; Veraart, Luitgard A. M.
This paper proposes the new concept of stochastic leverage in stochastic volatility models. Stochastic leverage refers to a stochastic process which replaces the classical constant correlation parameter between the asset return and the stochastic volatility process. We provide a systematic...... treatment of stochastic leverage and propose to model the stochastic leverage effect explicitly, e.g. by means of a linear transformation of a Jacobi process. Such models are both analytically tractable and allow for a direct economic interpretation. In particular, we propose two new stochastic volatility...... models which allow for a stochastic leverage effect: the generalised Heston model and the generalised Barndorff-Nielsen & Shephard model. We investigate the impact of a stochastic leverage effect in the risk neutral world by focusing on implied volatilities generated by option prices derived from our new...
Xie, Bin
2018-01-01
In this paper, the main topic is to investigate the intermittent property of the one-dimensional stochastic heat equation driven by an inhomogeneous Brownian sheet, which is a noise deduced from the study of the catalytic super-Brownian motion. Under some proper conditions on the catalytic measure of the inhomogeneous Brownian sheet, we show that the solution is weakly full intermittent based on the estimates of moments of the solution. In particular, it is proved that the second moment of the solution grows at the exponential rate. The novelty is that the catalytic measure relative to the inhomogeneous noise is not required to be absolutely continuous with respect to the Lebesgue measure on R.
Effect of temperature and time of pasteurization on the milk quality during storage
Directory of Open Access Journals (Sweden)
Abubakar
2001-03-01
Full Text Available A study on the effect of temperature and time of pasteurization on the milk quality during storage was carried out using fresh milk. The aim of the experiment was to asses the storage time of pasteurized milk for consumption without nutrient losses. A completely randomized factorial design, 2 x 8 was used, with pasteurization temperature (T, consisted of 2 levels, the low temperature long time (LTLT, i.e. fresh milk was warmed at 65oC for 30 minutes (T1 and the high temperature short time (HTST, i.e. fresh milk was warmed at 71oC for 15 seconds (T2; and storage time (S, consisted of 8 levels, i.e. 0, 3, 6, 9, 12, 15, 18, and 21 hours respectively, as the factors, with 3 replicates. Parameters measured were alcohol test, water, fat, and protein concentrations, and microbial population of pasteurized milk during storage. Data were analyzed using analysis of variance and simple linear regression. The result showed that water and fat concentrations and microbial population was not significantly different (P>0.05 in pasteurization temperature treatment, but was significantly different (P<0.05 due to storage time treatment. Meanwhile, the protein concentration was significantly different (P<0.05 either in pasteurization temperature or storage time. It was concluded that pasteurized milk was still suitable for consumption at 15-21 hours storage, while protein concentration tended to be better when was pasteurized at 65oC.
Energy Technology Data Exchange (ETDEWEB)
Werner, U.J. [Bauhaus-Universitaet Weimar (Germany). Fakultaet Bauingenieurwesen
1998-09-01
In an earlier contribution, a stochastic model was presented for a hot water storage tank supplied by a solar collector. The model was characterized in that the storage tank was assumed to be an ideal stratified storage tank, and its volume was subdivided into discrete identical storage compartments, so-called states, on the basis of the energy withdrawn from the tank. This simple model is now extended by assuming a stochastic variable for energy withdrawal and by taking account of energy loss at the surface of the hot water storage tank and inside it. [Deutsch] In einem frueheren Beitrag war fuer einen thermischen Speicher, der von einem Sonnenkollektor gespeist wird, ein stochastisches mathematisches Modell derart aufgestellt worden, dass ein als idealer Schichtenspeicher konzipierter Warmwasserspeicher bezueglich seines Volumens in diskrete, an der Energieentnahme orientierte, gleiche Speichereinheiten, sogenannte Zustaende, unterteilt wurde. Das einfache Modell wird nunmehr erweitert, indem die Entnahme als eine stochastische Groesse angenommen wird und die Energieverluste am und im Warmwasserspeicher Beruecksichtigung finden. (orig.)
Barnawi, Abdulwasa Bakr
Hybrid power generation system and distributed generation technology are attracting more investments due to the growing demand for energy nowadays and the increasing awareness regarding emissions and their environmental impacts such as global warming and pollution. The price fluctuation of crude oil is an additional reason for the leading oil producing countries to consider renewable resources as an alternative. Saudi Arabia as the top oil exporter country in the word announced the "Saudi Arabia Vision 2030" which is targeting to generate 9.5 GW of electricity from renewable resources. Two of the most promising renewable technologies are wind turbines (WT) and photovoltaic cells (PV). The integration or hybridization of photovoltaics and wind turbines with battery storage leads to higher adequacy and redundancy for both autonomous and grid connected systems. This study presents a method for optimal generation unit planning by installing a proper number of solar cells, wind turbines, and batteries in such a way that the net present value (NPV) is minimized while the overall system redundancy and adequacy is maximized. A new renewable fraction technique (RFT) is used to perform the generation unit planning. RFT was tested and validated with particle swarm optimization and HOMER Pro under the same conditions and environment. Renewable resources and load randomness and uncertainties are considered. Both autonomous and grid-connected system designs were adopted in the optimal generation units planning process. An uncertainty factor was designed and incorporated in both autonomous and grid connected system designs. In the autonomous hybrid system design model, the strategy including an additional amount of operation reserve as a percent of the hourly load was considered to deal with resource uncertainty since the battery storage system is the only backup. While in the grid-connected hybrid system design model, demand response was incorporated to overcome the impact of
Directory of Open Access Journals (Sweden)
Mindaugas Snipas
2015-01-01
Full Text Available The primary goal of this work was to study advantages of numerical methods used for the creation of continuous time Markov chain models (CTMC of voltage gating of gap junction (GJ channels composed of connexin protein. This task was accomplished by describing gating of GJs using the formalism of the stochastic automata networks (SANs, which allowed for very efficient building and storing of infinitesimal generator of the CTMC that allowed to produce matrices of the models containing a distinct block structure. All of that allowed us to develop efficient numerical methods for a steady-state solution of CTMC models. This allowed us to accelerate CPU time, which is necessary to solve CTMC models, ∼20 times.
Pranevicius, Henrikas; Pranevicius, Mindaugas; Pranevicius, Osvaldas; Bukauskas, Feliksas F.
2015-01-01
The primary goal of this work was to study advantages of numerical methods used for the creation of continuous time Markov chain models (CTMC) of voltage gating of gap junction (GJ) channels composed of connexin protein. This task was accomplished by describing gating of GJs using the formalism of the stochastic automata networks (SANs), which allowed for very efficient building and storing of infinitesimal generator of the CTMC that allowed to produce matrices of the models containing a distinct block structure. All of that allowed us to develop efficient numerical methods for a steady-state solution of CTMC models. This allowed us to accelerate CPU time, which is necessary to solve CTMC models, ∼20 times. PMID:25705700
Immunomodulating effect of blood transfusion: is storage time important?
DEFF Research Database (Denmark)
Mynster, T; Dybkjoer, E; Kronborg, Gitte
1998-01-01
in stimulating TNF-alpha and IL-2 release in an ex vivo assay. METHODS: Supernatants of 10 units of whole blood and 10 units of SAGM blood were collected after 1, 21 and 35 days of standard blood bank storage. Heparinized blood from 20 healthy volunteers (as 'recipients'), corresponding in ABO and Rh type......OBJECTIVES: TNF-alpha and IL-2 are important cytokines in macrophage and T-lymphocyte activity against infection and dissemination of malignant cells. We studied the influence of supernatants from stored whole blood and buffy-coat-depleted SAGM (saline, adenine, glucose and mannitol) blood...... to the stored blood, were used in a culture system with LPS and PHA as stimulators of TNF-alpha and IL-2 release. The effect of added supernatants, from either stored whole blood or SAGM blood, on cytokine release was evaluated compared to saline as control. TNF-alpha concentration was analyzed by ELISA after...
Directory of Open Access Journals (Sweden)
Stefan Enroth
2016-10-01
Full Text Available The quality of clinical biobank samples is crucial to their value for life sciences research. A number of factors related to the collection and storage of samples may affect the biomolecular composition. We have studied the effect of long-time freezer storage, chronological age at sampling, season and month of the year and on the abundance levels of 108 proteins in 380 plasma samples collected from 106 Swedish women. Storage time affected 18 proteins and explained 4.8–34.9% of the observed variance. Chronological age at sample collection after adjustment for storage-time affected 70 proteins and explained 1.1–33.5% of the variance. Seasonal variation had an effect on 15 proteins and month (number of sun hours affected 36 proteins and explained up to 4.5% of the variance after adjustment for storage-time and age. The results show that freezer storage time and collection date (month and season exerted similar effect sizes as age on the protein abundance levels. This implies that information on the sample handling history, in particular storage time, should be regarded as equally prominent covariates as age or gender and need to be included in epidemiological studies involving protein levels.
Directory of Open Access Journals (Sweden)
Hamidreza Mostafaei
2013-01-01
Full Text Available In this study, it has been attempted to select the best continuous- time stochastic model, in order to describe and forecast the oil price of Russia, by information and statistics about oil price that has been available for oil price in the past. For this purpose, method of The Maximum Likelihood Estimation is implemented for estimation of the parameters of continuous-time stochastic processes. The result of unit root test with a structural break, reveals that time series of the crude oil price is a stationary series. The simulation of continuous-time stochastic processes and the mean square error between the simulated prices and the market ones shows that the Geometric Brownian Motion is the best model for the Russian crude oil price.
International Nuclear Information System (INIS)
Colombino, A.; Mosiello, R.; Norelli, F.; Jorio, V.M.; Pacilio, N.
1975-01-01
A nuclear system kinetics is formulated according to a stochastic approach. The detailed probability balance equations are written for the probability of finding the mixed population of neutrons and detected neutrons, i.e. detectrons, at a given level for a given instant of time. Equations are integrated in search of a probability profile: a series of cases is analyzed through a progressive criterium. It tends to take into account an increasing number of physical processes within the chosen model. The most important contribution is that solutions interpret analytically experimental conditions of equilibrium (moise analysis) and non equilibrium (pulsed neutron measurements, source drop technique, start up procedures)
International Nuclear Information System (INIS)
Barber, D.P.; Heinemann, K.; Mais, H.; Ripken, G.
1991-12-01
In the following report we investigate stochastic particle motion in electron-positron storage ring in the framework of a Fokker-Planck treatment. The motion is described by using the canonical variables χ, p χ , z, p z , σ = s - cxt, p σ = ΔE/E 0 of the fully six-dimensional formalism. Thus synchrotron- and betatron-oscillations are treated simultaneously taking into account all kinds of coupling (synchro-betatron coupling and the coupling of the betatron oscillations by skew quadrupoles and solenoids). In order to set up the Fokker-Planck equation, action-angle variables of the linear coupled motion are introduced. The averaged dimensions of the bunch, resulting from radiation damping of the synchro-betatron oscillations and from an excitation of these oscillations by quantum fluctuations, are calculated by solving the Fokker-Planck equation. The surfaces of constant density in the six-dimensional phase space, given by six-dimensional ellipsoids, are determined. It is shown that the motion of such an ellipsoid under the influence of external fields can be described by six generating orbit vectors which may be combined into a six-dimenional matrix B(s). This 'bunch-shape matrix', B(s), contains complete information about the configuration of the bunch. Classical spin diffusion in linear approximation has also been included so that the dependence of the polarization vector on the orbital phase space coordinates can be studied and another derivation of the linearized depolarization time obtained. (orig.)
Milne, R K; Yeo, G F; Edeson, R O; Madsen, B W
1988-04-22
Stochastic models of ion channels have been based largely on Markov theory where individual states and transition rates must be specified, and sojourn-time densities for each state are constrained to be exponential. This study presents an approach based on random-sum methods and alternating-renewal theory, allowing individual states to be grouped into classes provided the successive sojourn times in a given class are independent and identically distributed. Under these conditions Markov models form a special case. The utility of the approach is illustrated by considering the effects of limited time resolution (modelled by using a discrete detection limit, xi) on the properties of observable events, with emphasis on the observed open-time (xi-open-time). The cumulants and Laplace transform for a xi-open-time are derived for a range of Markov and non-Markov models; several useful approximations to the xi-open-time density function are presented. Numerical studies show that the effects of limited time resolution can be extreme, and also highlight the relative importance of the various model parameters. The theory could form a basis for future inferential studies in which parameter estimation takes account of limited time resolution in single channel records. Appendixes include relevant results concerning random sums and a discussion of the role of exponential distributions in Markov models.
Effects of Holding Time, Storage, and the Preservation of ...
The purpose of this project was to answer questions related to storage of samples to be analyzed by the quantitative polymerase chain reaction (qPCR)-based assays for fecal indicator bacteria. The project was divided into two parts. The first part was to determine if filters that were used to collect fecal indicators could be stored frozen and analyzed at a later date and the second part was to determine if refrigerated water samples could be held for 24 to 48 hours prior to analysis by qPCR. Both of these studies answer questions that were important in the analysis of fresh and marine surface water samples for beach monitoring purposes. 1) Develop and evaluate qPCR assays and test methods for the detection and quantification of genetic markers from indicator bacteria that are associated with human fecal waste and from two new groups of general fecal indicator bacteria (E. coli and Clostridia) that historically have been widely used or are favored in specific regions 2) Determine the occurrence and densities of genetic markers detected by new qPCR assays developed under objective 1 and compare with occurrence and densities of genetic markers detected by previously developed qPCR assays for enterococci and total Bacterioidalesin waste waters and fecal material from different animal sources. 3) Determine stability of fecal indicator bacteria target DNA sequences in freezer archived filter retentates of ambient surface water samples 4) Determine the densitie
Stochastic quantisation: theme and variation
International Nuclear Information System (INIS)
Klauder, J.R.; Kyoto Univ.
1987-01-01
The paper on stochastic quantisation is a contribution to the book commemorating the sixtieth birthday of E.S. Fradkin. Stochastic quantisation reformulates Euclidean quantum field theory in the language of Langevin equations. The generalised free field is discussed from the viewpoint of stochastic quantisation. An artificial family of highly singular model theories wherein the space-time derivatives are dropped altogether is also examined. Finally a modified form of stochastic quantisation is considered. (U.K.)
Directory of Open Access Journals (Sweden)
Rider Mark A
2012-06-01
Full Text Available Abstract Background Reliable methods to preserve mosquito vectors for malaria studies are necessary for detecting Plasmodium parasites. In field settings, however, maintaining a cold chain of storage from the time of collection until laboratory processing, or accessing other reliable means of sample preservation is often logistically impractical or cost prohibitive. As the Plasmodium infection rate of Anopheles mosquitoes is a central component of the entomological inoculation rate and other indicators of transmission intensity, storage conditions that affect pathogen detection may bias malaria surveillance indicators. This study investigated the effect of storage time and temperature on the ability to detect Plasmodium parasites in desiccated Anopheles mosquitoes by real-time polymerase chain reaction (PCR. Methods Laboratory-infected Anopheles stephensi mosquitoes were chloroform-killed and stored over desiccant for 0, 1, 3, and 6 months while being held at four different temperatures: 28, 37, -20 and -80°C. The detection of Plasmodium DNA was evaluated by real-time PCR amplification of a 111 base pair region of block 4 of the merozoite surface protein. Results Varying the storage time and temperature of desiccated mosquitoes did not impact the sensitivity of parasite detection. A two-way factorial analysis of variance suggested that storage time and temperature were not associated with a loss in the ability to detect parasites. Storage of samples at 28°C resulted in a significant increase in the ability to detect parasite DNA, though no other positive associations were observed between the experimental storage treatments and PCR amplification. Conclusions Cold chain maintenance of desiccated mosquito samples is not necessary for real-time PCR detection of parasite DNA. Though field-collected mosquitoes may be subjected to variable conditions prior to molecular processing, the storage of samples over an inexpensive and logistically
Shi, Peng; Zhang, Yingqi; Chadli, Mohammed; Agarwal, Ramesh K
2016-04-01
In this brief, the problems of the mixed H-infinity and passivity performance analysis and design are investigated for discrete time-delay neural networks with Markovian jump parameters represented by Takagi-Sugeno fuzzy model. The main purpose of this brief is to design a filter to guarantee that the augmented Markovian jump fuzzy neural networks are stable in mean-square sense and satisfy a prescribed passivity performance index by employing the Lyapunov method and the stochastic analysis technique. Applying the matrix decomposition techniques, sufficient conditions are provided for the solvability of the problems, which can be formulated in terms of linear matrix inequalities. A numerical example is also presented to illustrate the effectiveness of the proposed techniques.
Directory of Open Access Journals (Sweden)
Dan Ye
2013-01-01
Full Text Available This paper is concerned with delay-dependent stochastic stability for time-delay Markovian jump systems (MJSs with sector-bounded nonlinearities and more general transition probabilities. Different from the previous results where the transition probability matrix is completely known, a more general transition probability matrix is considered which includes completely known elements, boundary known elements, and completely unknown ones. In order to get less conservative criterion, the state and transition probability information is used as much as possible to construct the Lyapunov-Krasovskii functional and deal with stability analysis. The delay-dependent sufficient conditions are derived in terms of linear matrix inequalities to guarantee the stability of systems. Finally, numerical examples are exploited to demonstrate the effectiveness of the proposed method.
International Nuclear Information System (INIS)
Miniati, Francesco
2015-01-01
We use the Matryoshka run to study the time-dependent statistics of structure-formation-driven turbulence in the intracluster medium of a 10 15 M ☉ galaxy cluster. We investigate the turbulent cascade in the inner megaparsec for both compressional and incompressible velocity components. The flow maintains approximate conditions of fully developed turbulence, with departures thereof settling in about an eddy-turnover time. Turbulent velocity dispersion remains above 700 km s –1 even at low mass accretion rate, with the fraction of compressional energy between 10% and 40%. The normalization and the slope of the compressional turbulence are susceptible to large variations on short timescales, unlike the incompressible counterpart. A major merger occurs around redshift z ≅ 0 and is accompanied by a long period of enhanced turbulence, ascribed to temporal clustering of mass accretion related to spatial clustering of matter. We test models of stochastic acceleration by compressional modes for the origin of diffuse radio emission in galaxy clusters. The turbulence simulation model constrains an important unknown of this complex problem and brings forth its dependence on the elusive microphysics of the intracluster plasma. In particular, the specifics of the plasma collisionality and the dissipation physics of weak shocks affect the cascade of compressional modes with strong impact on the acceleration rates. In this context radio halos emerge as complex phenomena in which a hierarchy of processes acting on progressively smaller scales are at work. Stochastic acceleration by compressional modes implies statistical correlation of radio power and spectral index with merging cores distance, both testable in principle with radio surveys
Storage Time and Urine Biomarker Levels in the ASSESS-AKI Study
Liu, Kathleen D.; Siew, Edward D.; Reeves, W. Brian; Himmelfarb, Jonathan; Go, Alan S.; Hsu, Chi-yuan; Bennett, Michael R.; Devarajan, Prasad; Ikizler, T. Alp; Kaufman, James S.; Kimmel, Paul L.; Chinchilli, Vernon M.; Parikh, Chirag R.
2016-01-01
Background Although stored urine samples are often used in biomarker studies focused on acute and chronic kidney disease, how storage time impacts biomarker levels is not well understood. Methods 866 subjects enrolled in the NIDDK-sponsored ASsessment, Serial Evaluation, and Subsequent Sequelae in Acute Kidney Injury (ASSESS-AKI) Study were included. Samples were processed under standard conditions and stored at -70°C until analyzed. Kidney injury molecule-1 (KIM-1), neutrophil gelatinase-associated lipocalin (NGAL), interleukin-18 (IL-18), and liver fatty acid binding protein (L-FABP) were measured in urine samples collected during the index hospitalization or an outpatient visit 3 months later. Mixed effects models were used to determine the effect of storage time on biomarker levels and stratified by visit. Results Median storage was 17.8 months (25–75% IQR 10.6–23.7) for samples from the index hospitalization and 14.6 months (IQR 7.3–20.4) for outpatient samples. In the mixed effects models, the only significant association between storage time and biomarker concentration was for KIM-1 in outpatient samples, where each month of storage was associated with a 1.7% decrease (95% CI -3% to -0.3%). There was no relationship between storage time and KIM-1 levels in samples from the index hospitalization. Conclusion There was no significant impact of storage time over a median of 18 months on urine KIM-1, NGAL, IL-18 or L-FABP in hospitalized samples; a statistically significant effect towards a decrease over time was noted for KIM-1 in outpatient samples. Additional studies are needed to determine whether longer periods of storage at -70°C systematically impact levels of these analytes. PMID:27788160
Storage Time and Urine Biomarker Levels in the ASSESS-AKI Study.
Directory of Open Access Journals (Sweden)
Kathleen D Liu
Full Text Available Although stored urine samples are often used in biomarker studies focused on acute and chronic kidney disease, how storage time impacts biomarker levels is not well understood.866 subjects enrolled in the NIDDK-sponsored ASsessment, Serial Evaluation, and Subsequent Sequelae in Acute Kidney Injury (ASSESS-AKI Study were included. Samples were processed under standard conditions and stored at -70°C until analyzed. Kidney injury molecule-1 (KIM-1, neutrophil gelatinase-associated lipocalin (NGAL, interleukin-18 (IL-18, and liver fatty acid binding protein (L-FABP were measured in urine samples collected during the index hospitalization or an outpatient visit 3 months later. Mixed effects models were used to determine the effect of storage time on biomarker levels and stratified by visit.Median storage was 17.8 months (25-75% IQR 10.6-23.7 for samples from the index hospitalization and 14.6 months (IQR 7.3-20.4 for outpatient samples. In the mixed effects models, the only significant association between storage time and biomarker concentration was for KIM-1 in outpatient samples, where each month of storage was associated with a 1.7% decrease (95% CI -3% to -0.3%. There was no relationship between storage time and KIM-1 levels in samples from the index hospitalization.There was no significant impact of storage time over a median of 18 months on urine KIM-1, NGAL, IL-18 or L-FABP in hospitalized samples; a statistically significant effect towards a decrease over time was noted for KIM-1 in outpatient samples. Additional studies are needed to determine whether longer periods of storage at -70°C systematically impact levels of these analytes.
Bradley, D. Nathan
2017-12-01
A consensus has formed that the step length distribution of fluvial bed load is thin tailed and that the observed anomalous superdiffusion of bed load tracer particles must arise from heavy-tailed resting times. However, heavy-tailed resting times have never been directly observed in the field over multiple floods. Using 9 years of data from a large bed load tracer experiment, I show that the spatial variance of the tracer plume scales faster than linearly with integrated excess stream power, indicating anomalous superdiffusion. The superdiffusion is caused by a heavy-tailed distribution of observed storage times that is fit with a truncated Pareto distribution with a tail parameter that is predicted by anomalous diffusion theory. The heavy-tailed distribution of storage times causes the tracer virtual velocity to slow over time, indicated by a sublinear increase in the mean displacement that is predicted by the storage time distribution tail parameter.
Energy Technology Data Exchange (ETDEWEB)
Kitanidis, Peter [Stanford Univ., CA (United States)
2016-04-30
As large-scale, commercial storage projects become operational, the problem of utilizing information from diverse sources becomes more critically important. In this project, we developed, tested, and applied an advanced joint data inversion system for CO_{2} storage modeling with large data sets for use in site characterization and real-time monitoring. Emphasis was on the development of advanced and efficient computational algorithms for joint inversion of hydro-geophysical data, coupled with state-of-the-art forward process simulations. The developed system consists of (1) inversion tools using characterization data, such as 3D seismic survey (amplitude images), borehole log and core data, as well as hydraulic, tracer and thermal tests before CO_{2} injection, (2) joint inversion tools for updating the geologic model with the distribution of rock properties, thus reducing uncertainty, using hydro-geophysical monitoring data, and (3) highly efficient algorithms for directly solving the dense or sparse linear algebra systems derived from the joint inversion. The system combines methods from stochastic analysis, fast linear algebra, and high performance computing. The developed joint inversion tools have been tested through synthetic CO_{2} storage examples.
International Nuclear Information System (INIS)
Lu Haibin; Zhou Lei; Wan Lei; Li Shaobing; Rong Mingdeng; Guo Zehong
2012-01-01
Titanium implants are sold in the market as storable medical devices. All the implants have a certain shelf life during which they maintain their sterility, but variations of the surface properties through this duration have not been subject to a comprehensive assessment. The aim of this study was to investigate the effects of storage methods on time-related changes of titanium surface properties. Acid-etched titanium discs (Sa = 0.82 µm) were placed in a sealed container (tradition method) or submerged in the ddH 2 O/NaCl solution (0.15 mol L −1 )/CaCl 2 solution (0.15 mol L −1 ), and new titanium discs were used as a control group. SEM and optical profiler showed that surface morphology and roughness did not change within different groups, but the XPS analysis confirmed that the surface chemistry altered by different storage protocols as the storage duration increased, and the contact angle also varied with storage methods. The storage method also affected the protein adsorption capacity and cellular response on the titanium surface. All titanium discs stored in the solution maintained their excellent bioactivity even after four weeks storage time, but titanium discs stored in a traditional manner decreased substantially in an age-dependent manner. Much effort is needed to improve the storage methods in order to maintain the bioactivity of a titanium dental implant. (paper)
Quantifying Time Dependent Moisture Storage and Transport Properties
DEFF Research Database (Denmark)
Peuhkuri, Ruut H
2003-01-01
This paper describes an experimental and numerical approach to quantify the time dependence of sorption mechanisms for some hygroscopic building - mostly insulation - materials. Some investigations of retarded sorption and non-Fickian phenomena, mostly on wood, have given inspiration to the present...
Stochastic quantization and gravity
International Nuclear Information System (INIS)
Rumpf, H.
1984-01-01
We give a preliminary account of the application of stochastic quantization to the gravitational field. We start in Section I from Nelson's formulation of quantum mechanics as Newtonian stochastic mechanics and only then introduce the Parisi-Wu stochastic quantization scheme on which all the later discussion will be based. In Section II we present a generalization of the scheme that is applicable to fields in physical (i.e. Lorentzian) space-time and treat the free linearized gravitational field in this manner. The most remarkable result of this is the noncausal propagation of conformal gravitons. Moreover the concept of stochastic gauge-fixing is introduced and a complete discussion of all the covariant gauges is given. A special symmetry relating two classes of covariant gauges is exhibited. Finally Section III contains some preliminary remarks on full nonlinear gravity. In particular we argue that in contrast to gauge fields the stochastic gravitational field cannot be transformed to a Gaussian process. (Author)
An elapsed time-temperature monitor for blood storage.
Harris, G E; Cloud, S; Myhre, B A
1977-01-01
Blood should not be allowed to exceed 10 C while being stored or transported. However, one cannot test the internal temperature of a unit of blood without contaminating it. Most blood banks have established an arbitrary time limit beyond which a blood unit cannot be kept out of the refrigerator. This method is ineffective if blood is stored in a satellite refrigerator, since the blood may be moved in and out of the refrigerator and the blood bank personnel will be unaware of it. An elapsed time indicator is described which employs a small condenser (E-Cell-Plessey Electronics) charged with a known amount of electricity. If the device is removed from the refrigerator, it begins to discharge at a known rate. The amount of time subsequently can be determined by the loss of charge. The prototype of this instrument has been found to be quite accurate and small (2 inches X 2 inches X 1 inch). It would be rather inexpensive if made in considerable numbers.
Lanchier, Nicolas
2017-01-01
Three coherent parts form the material covered in this text, portions of which have not been widely covered in traditional textbooks. In this coverage the reader is quickly introduced to several different topics enriched with 175 exercises which focus on real-world problems. Exercises range from the classics of probability theory to more exotic research-oriented problems based on numerical simulations. Intended for graduate students in mathematics and applied sciences, the text provides the tools and training needed to write and use programs for research purposes. The first part of the text begins with a brief review of measure theory and revisits the main concepts of probability theory, from random variables to the standard limit theorems. The second part covers traditional material on stochastic processes, including martingales, discrete-time Markov chains, Poisson processes, and continuous-time Markov chains. The theory developed is illustrated by a variety of examples surrounding applications such as the ...
The impact of COI-based storage on order-picking times
Directory of Open Access Journals (Sweden)
Grzegorz Tarczyński
2017-09-01
Full Text Available Background: The increasing competitiveness on the global markets enforces the need for a fast and reliable delivery. This task is possible to perform by improving the order-picking systems. The implementation of automated storage and retrieval systems (AS/RS is not always profitable. In the warehouses where the order-picking is performed in accordance with the principle of picker-to-part rule, the picking efficiency optimization includes among others: the warehouse layout, the storage policy, the routing heuristic, the way of zoning, the order-batching method, and the sequencing of pick-lists. In the paper the impact of the storage policy on the order-picking times is checked. Methods: The influence of storage based on Heskett’s cube-per-order index (COI on the average order-picking times is analyzed. The items based on increasing values of COI index are divided on classes. To determine the demand for items the analytical function proposed by Caron is used. Results: In the paper the benefits of storage based on COI index are compared with random storage and storage based only on picking frequency. It is assumed that the bin, to which the picker collects items has limited capacity – some orders has to be divided on smaller pick-lists. The analysis was performed using simulation tools. Additionally, the algorithm (taking into account different sizes of picker’s bin for order-batching is presented. Conclusions: The analysis shows that the COI-based storage is particularly effective when the size of items increases. The COI-based curve is less skewed than the curve based only on picking frequency. The choice of storage policy should be carried out together with routing heuristic. The use of batching algorithm significantly increases the effectiveness of the order-picking process, but the optimal size of picker’s bin (and batch should be optimized with consideration the sorting process.
Leander, Jacob; Lundh, Torbjörn; Jirstrand, Mats
2014-05-01
In this paper we consider the problem of estimating parameters in ordinary differential equations given discrete time experimental data. The impact of going from an ordinary to a stochastic differential equation setting is investigated as a tool to overcome the problem of local minima in the objective function. Using two different models, it is demonstrated that by allowing noise in the underlying model itself, the objective functions to be minimized in the parameter estimation procedures are regularized in the sense that the number of local minima is reduced and better convergence is achieved. The advantage of using stochastic differential equations is that the actual states in the model are predicted from data and this will allow the prediction to stay close to data even when the parameters in the model is incorrect. The extended Kalman filter is used as a state estimator and sensitivity equations are provided to give an accurate calculation of the gradient of the objective function. The method is illustrated using in silico data from the FitzHugh-Nagumo model for excitable media and the Lotka-Volterra predator-prey system. The proposed method performs well on the models considered, and is able to regularize the objective function in both models. This leads to parameter estimation problems with fewer local minima which can be solved by efficient gradient-based methods. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.
Liu, Jian; Wang, Youguo
2018-03-01
The simultaneous influence of potential asymmetries and time-delayed feedback on stochastic resonance (SR) subject to both periodic force and additive Gaussian white noise is investigated by using two-state theory and small-delay approximation, where three types of asymmetries include well-depth, well-width, and both well-depth and well-width asymmetries, respectively. The asymmetric types and time-delayed feedback determine the behaviors of SR, especially output signal-to-noise ratio (SNR) peaks, optimal additive noise intensity and feedback intensity. Moreover, the largest SNR in asymmetric SR is found to be relatively larger than symmetric one in some cases, whereas in other cases the symmetric SR is superior to asymmetric one, which is of dependence on time delay and feedback intensity. In addition, the SR with well-width asymmetry can suppress stronger noise than that with well-depth asymmetry under the action of same time delay, which is beneficial to weak signal detection.
Rt-Space: A Real-Time Stochastically-Provisioned Adaptive Container Environment
2017-08-04
Real-Time Systems (ECRTS) Conference Location: Toulouse, France Paper Title: Multiprocessor Real-Time Locking Protocols for Replicated Resources...Conference Location: Lille, France Paper Title: A Contention-Sensitive Fine-Grained Locking Protocol for Multiprocessor Real-Time Systems Publication...On the Soft Real-Time Optimality of Global EDF on Multiprocessors: From Identical to Uniform Heterogeneous Publication Type: Conference Paper or
Directory of Open Access Journals (Sweden)
Minghui Yu
2017-01-01
Full Text Available The global exponential antisynchronization in mean square of memristive neural networks with stochastic perturbation and mixed time-varying delays is studied in this paper. Then, two kinds of novel delay-dependent and delay-independent adaptive controllers are designed. With the ability of adapting to environment changes, the proposed controllers can modify their behaviors to achieve the best performance. In particular, on the basis of the differential inclusions theory, inequality theory, and stochastic analysis techniques, several sufficient conditions are obtained to guarantee the exponential antisynchronization between the drive system and response system. Furthermore, two numerical simulation examples are provided to the validity of the derived criteria.
International Nuclear Information System (INIS)
Pisciella, P.; Vespucci, M.T.; Bertocchi, M.; Zigrino, S.
2016-01-01
We propose a multi-stage stochastic optimization model for the generation capacity expansion problem of a price-taker power producer. Uncertainties regarding the evolution of electricity prices and fuel costs play a major role in long term investment decisions, therefore the objective function represents a trade-off between expected profit and risk. The Conditional Value at Risk is the risk measure used and is defined by a nested formulation that guarantees time consistency in the multi-stage model. The proposed model allows one to determine a long term expansion plan which takes into account uncertainty, while the LCoE approach, currently used by decision makers, only allows one to determine which technology should be chosen for the next power plant to be built. A sensitivity analysis is performed with respect to the risk weighting factor and budget amount. - Highlights: • We propose a time consistent risk averse multi-stage model for capacity expansion. • We introduce a case study with uncertainty on electricity prices and fuel costs. • Increased budget moves the investment from gas towards renewables and then coal. • Increased risk aversion moves the investment from coal towards renewables. • Time inconsistency leads to a profit gap between planned and implemented policies.
International Nuclear Information System (INIS)
Capilla Roma, J. E.; Gomez-Hernandez, J. J.; Sahuquillo Herraiz, A.
1999-01-01
Multiple equally likely transmissivity fields that honor piezo metric head measurements are generated as input to a Monte-Carlo exercise, for the stochastic analysis of travel times in the Culebra dolomite overlaying the Waste Isolation Pilot Plant (WIPP) in New Mexico, USA. Results of the analysis show the importance of modeling variable-density flow as accurately as possible, and of including as much information as possible in the simulations of alternative scenarios. Results also unveil a channel of high transmissivity when transmissivity fields are conditioned to piezo metric data. This channel leads to important reductions of travel time from the WIPP area to the south boundary. The uncertainty of the boundary conditions is analyzed searching for alternative boundary conditions can be obtained that improve the reproduction of piezo metric data and yield a reduction of the minimum travel times to the south boundary. Results of the Monte-Carlo exercise are compared with those from a deterministic analysis showing the limitations of the latter method when trying to estimate extreme values or characterizing the uncertainty of their predictions. The report ends with a brief study on the impact of the small transmissivity measurements at location P-18, showing that its value is not consistent with the model of spatial variability inferred from the data and that it has an important effect on model predictions. (Author)
Energy Technology Data Exchange (ETDEWEB)
Capilla Roma, J E; Gomez-Hernandez, J J; Sahuquillo Herraiz, A [Universidad Politecnia de Valencia (Spain)
1999-12-15
Multiple equally likely transmissivity fields that honor piezo metric head measurements are generated as input to a Monte-Carlo exercise, for the stochastic analysis of travel times in the Culebra dolomite overlaying the Waste Isolation Pilot Plant (WIPP) in New Mexico, USA. Results of the analysis show the importance of modeling variable-density flow as accurately as possible, and of including as much information as possible in the simulations of alternative scenarios. Results also unveil a channel of high transmissivity when transmissivity fields are conditioned to piezo metric data. This channel leads to important reductions of travel time from the WIPP area to the south boundary. The uncertainty of the boundary conditions is analyzed searching for alternative boundary conditions can be obtained that improve the reproduction of piezo metric data and yield a reduction of the minimum travel times to the south boundary. Results of the Monte-Carlo exercise are compared with those from a deterministic analysis showing the limitations of the latter method when trying to estimate extreme values or characterizing the uncertainty of their predictions. The report ends with a brief study on the impact of the small transmissivity measurements at location P-18, showing that its value is not consistent with the model of spatial variability inferred from the data and that it has an important effect on model predictions. (Author)
The stochastic goodwill problem
Marinelli, Carlo
2003-01-01
Stochastic control problems related to optimal advertising under uncertainty are considered. In particular, we determine the optimal strategies for the problem of maximizing the utility of goodwill at launch time and minimizing the disutility of a stream of advertising costs that extends until the launch time for some classes of stochastic perturbations of the classical Nerlove-Arrow dynamics. We also consider some generalizations such as problems with constrained budget and with discretionar...
The influences of delay time on the stability of a market model with stochastic volatility
Li, Jiang-Cheng; Mei, Dong-Cheng
2013-02-01
The effects of the delay time on the stability of a market model are investigated, by using a modified Heston model with a cubic nonlinearity and cross-correlated noise sources. These results indicate that: (i) There is an optimal delay time τo which maximally enhances the stability of the stock price under strong demand elasticity of stock price, and maximally reduces the stability of the stock price under weak demand elasticity of stock price; (ii) The cross correlation coefficient of noises and the delay time play an opposite role on the stability for the case of the delay time τo. Moreover, the probability density function of the escape time of stock price returns, the probability density function of the returns and the correlation function of the returns are compared with other literatures.
T.R. Jackson; R. Haggerty; S.V. Apte; A. Coleman; K.J. Drost
2012-01-01
Surface transient storage (STS) has functional significance in stream ecosystems because it increases solute interaction with sediments. After volume, mean residence time is the most important metric of STS, but it is unclear how this can be measured accurately or related to other timescales and field-measureable parameters. We studied mean residence time of lateral...
Lu, M.; Lall, U.
2013-12-01
In order to mitigate the impacts of climate change, proactive management strategies to operate reservoirs and dams are needed. A multi-time scale climate informed stochastic model is developed to optimize the operations for a multi-purpose single reservoir by simulating decadal, interannual, seasonal and sub-seasonal variability. We apply the model to a setting motivated by the largest multi-purpose dam in N. India, the Bhakhra reservoir on the Sutlej River, a tributary of the Indus. This leads to a focus on timing and amplitude of the flows for the monsoon and snowmelt periods. The flow simulations are constrained by multiple sources of historical data and GCM future projections, that are being developed through a NSF funded project titled 'Decadal Prediction and Stochastic Simulation of Hydroclimate Over Monsoon Asia'. The model presented is a multilevel, nonlinear programming model that aims to optimize the reservoir operating policy on a decadal horizon and the operation strategy on an updated annual basis. The model is hierarchical, in terms of having a structure that two optimization models designated for different time scales are nested as a matryoshka doll. The two optimization models have similar mathematical formulations with some modifications to meet the constraints within that time frame. The first level of the model is designated to provide optimization solution for policy makers to determine contracted annual releases to different uses with a prescribed reliability; the second level is a within-the-period (e.g., year) operation optimization scheme that allocates the contracted annual releases on a subperiod (e.g. monthly) basis, with additional benefit for extra release and penalty for failure. The model maximizes the net benefit of irrigation, hydropower generation and flood control in each of the periods. The model design thus facilitates the consistent application of weather and climate forecasts to improve operations of reservoir systems. The
Modeling and analysis for determining optimal suppliers under stochastic lead times
DEFF Research Database (Denmark)
Abginehchi, Soheil; Farahani, Reza Zanjirani
2010-01-01
systems. The item acquisition lead times of suppliers are random variables. Backorder is allowed and shortage cost is charged based on not only per unit in shortage but also per time unit. Continuous review (s,Q) policy has been assumed. When the inventory level depletes to a reorder level, the total...... order is split among n suppliers. Since the suppliers have different characteristics, the quantity ordered to different suppliers may be different. The problem is to determine the reorder level and quantity ordered to each supplier so that the expected total cost per time unit, including ordering cost...
Effect of harvest time on storage loss and sprouting in onion
Directory of Open Access Journals (Sweden)
T. SUOJALA
2008-12-01
Full Text Available Storability of onion is affected by timing of harvest. However, the optimal time for maximum yield and maximum storability do not necessarily coincide. This study aimed to determine the most suitable harvest time for obtaining a high bulb yield with high quality and storability. Storage experiments were conducted on onions produced in field experiments at a research field and on farms in four years. Results indicate that harvesting could be delayed to 100% maturity, or even longer, without a marked increase in storage loss. In rainy years, late harvest is likely to impair the quality. The incidence of sprouting in shelf life tests varied considerably between years. An early harvest before 50% maturity and a delayed harvest increased the risk of sprouting. It may be concluded that the harvesting of onions for long-term storage can be timed to take place between 50% maturity and even some weeks after complete maturity without a loss in storage quality. Therefore, it is possible to combine high yield and good storage quality.
Model of observed stochastic balance between work and free time supporting the LQTAI definition
DEFF Research Database (Denmark)
Ditlevsen, Ove Dalager
2008-01-01
A balance differential equation between free time and money-producing work time on the national economy level is formulated in a previous paper in terms of two dimensionless quantities, the fraction of work time and the total productivity factor defined as the ratio of the Gross Domestic Product...... significant systematically balance influencing parameters on the macro economical level than those considered in the definition in the previous paper of the Life Quality Time Allocation Index....... to the total salary paid in return for work. Among the solutions there is one relation that compares surprisingly well with the relevant sequences of Danish data spanning from 1948 to 2003, and also with similar data from several other countries except for slightly different model parameter values. Statistical...
Smolen, Paul; Baxter, Douglas A.; Byrne, John H.
2012-01-01
Multiple interlinked positive feedback loops shape the stimulus responses of various biochemical systems, such as the cell cycle or intracellular Ca2+ release. Recent studies with simplified models have identified two advantages of coupling fast and slow feedback loops. This dual-time structure enables a fast response while enhancing resistances of responses and bistability to stimulus noise. We now find that: 1) the dual-time structure similarly confers resistance to internal noise due to mo...
A Study on Efficient Robust Speech Recognition with Stochastic Dynamic Time Warping
孫, 喜浩
2014-01-01
In recent years, great progress has been made in automatic speech recognition (ASR) system. The hidden Markov model (HMM) and dynamic time warping (DTW) are the two main algorithms which have been widely applied to ASR system. Although, HMM technique achieves higher recognition accuracy in clear speech environment and noisy environment. It needs large-set of words and realizes the algorithm more complexly.Thus, more and more researchers have focused on DTW-based ASR system.Dynamic time warpin...
A stochastic analysis approach on the cost-time profile for selecting the best future state MA
Directory of Open Access Journals (Sweden)
Seyedhosseini, Seyed Mohammad
2015-05-01
Full Text Available In the literature on value stream mapping (VSM, the only basis for choosing the best future state map (FSM among the proposed alternatives is the time factor. As a result, the FSM is selected as the best option because it has the least amount of total production lead time (TPLT. In this paper, the cost factor is considered in the FSM selection process, in addition to the time factor. Thus, for each of the proposed FSMs, the cost-time profile (CTP is used. Two factors that are of particular importance for the customer and the manufacturer – the TPLT and the direct cost of the product – are reviewed and analysed by calculating the sub-area of the CTP curve, called the cost-time investment (CTI. In addition, variability in the generated data has been studied in each of the CTPs in order to choose the best FSM more precisely and accurately. Based on a proposed step-by-step stochastic analysis method, and also by using non-parametric Kernel estimation methods for estimating the probability density function of CTIs, the process of choosing the best FSM has been carried out, based not only on the minimum expected CTI, but also on the minimum expected variability amount in CTIs among proposed alternatives. By implementing this method during the process of choosing the best FSM, the manufacturing organisations will consider both the cost factor and the variability in the generated data, in addition to the time factor. Accordingly, the decision-making process proceeds more easily and logically than do traditional methods. Finally, to describe the effectiveness and applicability of the proposed method in this paper, it is applied to a case study on an industrial parts manufacturing company in Iran.
Storage capacity and retrieval time of small-world neural networks
International Nuclear Information System (INIS)
Oshima, Hiraku; Odagaki, Takashi
2007-01-01
To understand the influence of structure on the function of neural networks, we study the storage capacity and the retrieval time of Hopfield-type neural networks for four network structures: regular, small world, random networks generated by the Watts-Strogatz (WS) model, and the same network as the neural network of the nematode Caenorhabditis elegans. Using computer simulations, we find that (1) as the randomness of network is increased, its storage capacity is enhanced; (2) the retrieval time of WS networks does not depend on the network structure, but the retrieval time of C. elegans's neural network is longer than that of WS networks; (3) the storage capacity of the C. elegans network is smaller than that of networks generated by the WS model, though the neural network of C. elegans is considered to be a small-world network
Directory of Open Access Journals (Sweden)
Masoud Rabbani
2018-09-01
Full Text Available This paper presents a new multi-objective model for a vehicle routing problem under a stochastic uncertainty. It considers traffic point as an inflection point to deal with the arrival time of vehicles. It aims to minimize the total transportation cost, traffic pollution, customer dissatisfaction and maximizes the reliability of vehicles. Moreover, resiliency factors are included in the model to increase the flexibility of the system and decrease the possible losses that may impose on the system. Due to the NP-hardness of the presented model, a meta-heuristic algorithm, namely Simulated Annealing (SA is developed. Furthermore, a number of sensitivity analyses are provided to validate the effectiveness of the proposed model. Lastly, the foregoing meta-heuristic is compared with GAMS, in which the computational results demonstrate an acceptable performance of the proposed SA.
Stochastic processes and quantum theory
International Nuclear Information System (INIS)
Klauder, J.R.
1975-01-01
The author analyses a variety of stochastic processes, namely real time diffusion phenomena, which are analogues of imaginary time quantum theory and convariant imaginary time quantum field theory. He elaborates some standard properties involving probability measures and stochastic variables and considers a simple class of examples. Finally he develops the fact that certain stochastic theories actually exhibit divergences that simulate those of covariant quantum field theory and presents examples of both renormaizable and unrenormalizable behavior. (V.J.C.)
Klinkusch, Stefan; Tremblay, Jean Christophe
2016-05-14
In this contribution, we introduce a method for simulating dissipative, ultrafast many-electron dynamics in intense laser fields. The method is based on the norm-conserving stochastic unraveling of the dissipative Liouville-von Neumann equation in its Lindblad form. The N-electron wave functions sampling the density matrix are represented in the basis of singly excited configuration state functions. The interaction with an external laser field is treated variationally and the response of the electronic density is included to all orders in this basis. The coupling to an external environment is included via relaxation operators inducing transition between the configuration state functions. Single electron ionization is represented by irreversible transition operators from the ionizing states to an auxiliary continuum state. The method finds its efficiency in the representation of the operators in the interaction picture, where the resolution-of-identity is used to reduce the size of the Hamiltonian eigenstate basis. The zeroth-order eigenstates can be obtained either at the configuration interaction singles level or from a time-dependent density functional theory reference calculation. The latter offers an alternative to explicitly time-dependent density functional theory which has the advantage of remaining strictly valid for strong field excitations while improving the description of the correlation as compared to configuration interaction singles. The method is tested on a well-characterized toy system, the excitation of the low-lying charge transfer state in LiCN.
Energy Technology Data Exchange (ETDEWEB)
Klinkusch, Stefan; Tremblay, Jean Christophe [Institute for Chemistry and Biochemistry, Freie Universität Berlin, Takustr. 3, D-14195 Berlin (Germany)
2016-05-14
In this contribution, we introduce a method for simulating dissipative, ultrafast many-electron dynamics in intense laser fields. The method is based on the norm-conserving stochastic unraveling of the dissipative Liouville-von Neumann equation in its Lindblad form. The N-electron wave functions sampling the density matrix are represented in the basis of singly excited configuration state functions. The interaction with an external laser field is treated variationally and the response of the electronic density is included to all orders in this basis. The coupling to an external environment is included via relaxation operators inducing transition between the configuration state functions. Single electron ionization is represented by irreversible transition operators from the ionizing states to an auxiliary continuum state. The method finds its efficiency in the representation of the operators in the interaction picture, where the resolution-of-identity is used to reduce the size of the Hamiltonian eigenstate basis. The zeroth-order eigenstates can be obtained either at the configuration interaction singles level or from a time-dependent density functional theory reference calculation. The latter offers an alternative to explicitly time-dependent density functional theory which has the advantage of remaining strictly valid for strong field excitations while improving the description of the correlation as compared to configuration interaction singles. The method is tested on a well-characterized toy system, the excitation of the low-lying charge transfer state in LiCN.
Optimizing Real-Time Vaccine Allocation in a Stochastic SIR Model.
Directory of Open Access Journals (Sweden)
Chantal Nguyen
Full Text Available Real-time vaccination following an outbreak can effectively mitigate the damage caused by an infectious disease. However, in many cases, available resources are insufficient to vaccinate the entire at-risk population, logistics result in delayed vaccine deployment, and the interaction between members of different cities facilitates a wide spatial spread of infection. Limited vaccine, time delays, and interaction (or coupling of cities lead to tradeoffs that impact the overall magnitude of the epidemic. These tradeoffs mandate investigation of optimal strategies that minimize the severity of the epidemic by prioritizing allocation of vaccine to specific subpopulations. We use an SIR model to describe the disease dynamics of an epidemic which breaks out in one city and spreads to another. We solve a master equation to determine the resulting probability distribution of the final epidemic size. We then identify tradeoffs between vaccine, time delay, and coupling, and we determine the optimal vaccination protocols resulting from these tradeoffs.
Li, Jimeng; Li, Ming; Zhang, Jinfeng
2017-08-01
Rolling bearings are the key components in the modern machinery, and tough operation environments often make them prone to failure. However, due to the influence of the transmission path and background noise, the useful feature information relevant to the bearing fault contained in the vibration signals is weak, which makes it difficult to identify the fault symptom of rolling bearings in time. Therefore, the paper proposes a novel weak signal detection method based on time-delayed feedback monostable stochastic resonance (TFMSR) system and adaptive minimum entropy deconvolution (MED) to realize the fault diagnosis of rolling bearings. The MED method is employed to preprocess the vibration signals, which can deconvolve the effect of transmission path and clarify the defect-induced impulses. And a modified power spectrum kurtosis (MPSK) index is constructed to realize the adaptive selection of filter length in the MED algorithm. By introducing the time-delayed feedback item in to an over-damped monostable system, the TFMSR method can effectively utilize the historical information of input signal to enhance the periodicity of SR output, which is beneficial to the detection of periodic signal. Furthermore, the influence of time delay and feedback intensity on the SR phenomenon is analyzed, and by selecting appropriate time delay, feedback intensity and re-scaling ratio with genetic algorithm, the SR can be produced to realize the resonance detection of weak signal. The combination of the adaptive MED (AMED) method and TFMSR method is conducive to extracting the feature information from strong background noise and realizing the fault diagnosis of rolling bearings. Finally, some experiments and engineering application are performed to evaluate the effectiveness of the proposed AMED-TFMSR method in comparison with a traditional bistable SR method.
Modelling, interpolation and stochastic simulation in space and time of global solar radiation
Bechini, L.; Ducco, G.; Donatelli, M.; Stein, A.
2000-01-01
Global solar radiation data used as daily inputs for most cropping systems and water budget models are frequently available from only a few weather stations and over short periods of time. To overcome this limitation, the Campbell–Donatelli model relates daily maximum and minimum air temperatures to
A Stochastic Model of Space-Time Variability of Tropical Rainfall: I. Statistics of Spatial Averages
Kundu, Prasun K.; Bell, Thomas L.; Lau, William K. M. (Technical Monitor)
2002-01-01
Global maps of rainfall are of great importance in connection with modeling of the earth s climate. Comparison between the maps of rainfall predicted by computer-generated climate models with observation provides a sensitive test for these models. To make such a comparison, one typically needs the total precipitation amount over a large area, which could be hundreds of kilometers in size over extended periods of time of order days or months. This presents a difficult problem since rain varies greatly from place to place as well as in time. Remote sensing methods using ground radar or satellites detect rain over a large area by essentially taking a series of snapshots at infrequent intervals and indirectly deriving the average rain intensity within a collection of pixels , usually several kilometers in size. They measure area average of rain at a particular instant. Rain gauges, on the other hand, record rain accumulation continuously in time but only over a very small area tens of centimeters across, say, the size of a dinner plate. They measure only a time average at a single location. In making use of either method one needs to fill in the gaps in the observation - either the gaps in the area covered or the gaps in time of observation. This involves using statistical models to obtain information about the rain that is missed from what is actually detected. This paper investigates such a statistical model and validates it with rain data collected over the tropical Western Pacific from ship borne radars during TOGA COARE (Tropical Oceans Global Atmosphere Coupled Ocean-Atmosphere Response Experiment). The model incorporates a number of commonly observed features of rain. While rain varies rapidly with location and time, the variability diminishes when averaged over larger areas or longer periods of time. Moreover, rain is patchy in nature - at any instant on the average only a certain fraction of the observed pixels contain rain. The fraction of area covered by
Using stochastic space-time models to map extreme precipitation in southern Portugal
Directory of Open Access Journals (Sweden)
A. C. Costa
2008-07-01
Full Text Available The topographic characteristics and spatial climatic diversity are significant in the South of continental Portugal where the rainfall regime is typically Mediterranean. Direct sequential cosimulation is proposed for mapping an extreme precipitation index in southern Portugal using elevation as auxiliary information. The analysed index (R5D can be considered a flood indicator because it provides a measure of medium-term precipitation total. The methodology accounts for local data variability and incorporates space-time models that allow capturing long-term trends of extreme precipitation, and local changes in the relationship between elevation and extreme precipitation through time. Annual gridded datasets of the flood indicator are produced from 1940 to 1999 on 800 m×800 m grids by using the space-time relationship between elevation and the index. Uncertainty evaluations of the proposed scenarios are also produced for each year. The results indicate that the relationship between elevation and extreme precipitation varies locally and has decreased through time over the study region. In wetter years the flood indicator exhibits the highest values in mountainous regions of the South, while in drier years the spatial pattern of extreme precipitation has much less variability over the study region. The uncertainty of extreme precipitation estimates also varies in time and space, and in earlier decades is strongly dependent on the density of the monitoring stations network. The produced maps will be useful in regional and local studies related to climate change, desertification, land and water resources management, hydrological modelling, and flood mitigation planning.
Big Data impacts on stochastic Forecast Models: Evidence from FX time series
Directory of Open Access Journals (Sweden)
Sebastian Dietz
2013-12-01
Full Text Available With the rise of the Big Data paradigm new tasks for prediction models appeared. In addition to the volume problem of such data sets nonlinearity becomes important, as the more detailed data sets contain also more comprehensive information, e.g. about non regular seasonal or cyclical movements as well as jumps in time series. This essay compares two nonlinear methods for predicting a high frequency time series, the USD/Euro exchange rate. The first method investigated is Autoregressive Neural Network Processes (ARNN, a neural network based nonlinear extension of classical autoregressive process models from time series analysis (see Dietz 2011. Its advantage is its simple but scalable time series process model architecture, which is able to include all kinds of nonlinearities based on the universal approximation theorem of Hornik, Stinchcombe and White 1989 and the extensions of Hornik 1993. However, restrictions related to the numeric estimation procedures limit the flexibility of the model. The alternative is a Support Vector Machine Model (SVM, Vapnik 1995. The two methods compared have different approaches of error minimization (Empirical error minimization at the ARNN vs. structural error minimization at the SVM. Our new finding is, that time series data classified as “Big Data” need new methods for prediction. Estimation and prediction was performed using the statistical programming language R. Besides prediction results we will also discuss the impact of Big Data on data preparation and model validation steps. Normal 0 21 false false false DE X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Normale Tabelle"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif";}
Fang, Wen; Wang, Jun
2013-09-01
We develop a financial market model using an Ising spin system on a Sierpinski carpet lattice that breaks the equal status of each spin. To study the fluctuation behavior of the financial model, we present numerical research based on Monte Carlo simulation in conjunction with the statistical analysis and multifractal analysis of the financial time series. We extract the multifractal spectra by selecting various lattice size values of the Sierpinski carpet, and the inverse temperature of the Ising dynamic system. We also investigate the statistical fluctuation behavior, the time-varying volatility clustering, and the multifractality of returns for the indices SSE, SZSE, DJIA, IXIC, S&P500, HSI, N225, and for the simulation data derived from the Ising model on the Sierpinski carpet lattice. A numerical study of the model’s dynamical properties reveals that this financial model reproduces important features of the empirical data.
Comparison of deterministic and stochastic methods for time-dependent Wigner simulations
Energy Technology Data Exchange (ETDEWEB)
Shao, Sihong, E-mail: sihong@math.pku.edu.cn [LMAM and School of Mathematical Sciences, Peking University, Beijing 100871 (China); Sellier, Jean Michel, E-mail: jeanmichel.sellier@parallel.bas.bg [IICT, Bulgarian Academy of Sciences, Acad. G. Bonchev str. 25A, 1113 Sofia (Bulgaria)
2015-11-01
Recently a Monte Carlo method based on signed particles for time-dependent simulations of the Wigner equation has been proposed. While it has been thoroughly validated against physical benchmarks, no technical study about its numerical accuracy has been performed. To this end, this paper presents the first step towards the construction of firm mathematical foundations for the signed particle Wigner Monte Carlo method. An initial investigation is performed by means of comparisons with a cell average spectral element method, which is a highly accurate deterministic method and utilized to provide reference solutions. Several different numerical tests involving the time-dependent evolution of a quantum wave-packet are performed and discussed in deep details. In particular, this allows us to depict a set of crucial criteria for the signed particle Wigner Monte Carlo method to achieve a satisfactory accuracy.
Stochastic processes in cell biology
Bressloff, Paul C
2014-01-01
This book develops the theory of continuous and discrete stochastic processes within the context of cell biology. A wide range of biological topics are covered including normal and anomalous diffusion in complex cellular environments, stochastic ion channels and excitable systems, stochastic calcium signaling, molecular motors, intracellular transport, signal transduction, bacterial chemotaxis, robustness in gene networks, genetic switches and oscillators, cell polarization, polymerization, cellular length control, and branching processes. The book also provides a pedagogical introduction to the theory of stochastic process – Fokker Planck equations, stochastic differential equations, master equations and jump Markov processes, diffusion approximations and the system size expansion, first passage time problems, stochastic hybrid systems, reaction-diffusion equations, exclusion processes, WKB methods, martingales and branching processes, stochastic calculus, and numerical methods. This text is primarily...
Storage time of transfused blood and disease recurrence after colorectal cancer surgery
DEFF Research Database (Denmark)
Mynster, T; Nielsen, Hans Jørgen
2001-01-01
of the transfused blood. Therefore, we studied the relationship between blood storage time and the development of disease recurrence and long-term survival after colorectal cancer surgery. METHODS: Preoperative and postoperative data were prospectively recorded in 740 patients undergoing elective resection...... for primary colorectal cancer. None of the patients received preoperative or postoperative chemotherapy or radiation therapy. Endpoints were overall survival and disease recurrence in the subgroup of patients operated on with curative intention who also survived the first 30 days after operation. Storage......BACKGROUND: Perioperative blood transfusion and subsequent development of postoperative infectious complications may lead to poor prognosis of patients with colorectal cancer. It has been suggested that the development of postoperative infectious complications may be related to the storage time...
Stochastic massless fields I: Integer spin
International Nuclear Information System (INIS)
Lim, S.C.
1981-04-01
Nelson's stochastic quantization scheme is applied to classical massless tensor potential in ''Coulomb'' gauge. The relationship between stochastic potential field in various gauges is discussed using the case of vector potential as an illustration. It is possible to identify the Euclidean tensor potential with the corresponding stochastic field in physical Minkowski space-time. Stochastic quantization of massless fields can also be carried out in terms of field strength tensors. An example of linearized stochastic gravitational field in vacuum is given. (author)
Salunkhe, Vishal; De Cuyper, Iris M; Papadopoulos, Petros; van der Meer, Pieter F; Daal, Brunette B; Villa-Fajardo, María; de Korte, Dirk; van den Berg, Timo K; Gutiérrez, Laura
2018-03-19
Platelet concentrates (PCs) represent a blood transfusion product with a major concern for safety as their storage temperature (20-24°C) allows bacterial growth, and their maximum storage time period (less than a week) precludes complete microbiological testing. Pathogen inactivation technologies (PITs) provide an additional layer of safety to the blood transfusion products from known and unknown pathogens such as bacteria, viruses, and parasites. In this context, PITs, such as Mirasol Pathogen Reduction Technology (PRT), have been developed and are implemented in many countries. However, several studies have shown in vitro that Mirasol PRT induces a certain level of platelet shape change, hyperactivation, basal degranulation, and increased oxidative damage during storage. It has been suggested that Mirasol PRT might accelerate what has been described as the platelet storage lesion (PSL), but supportive molecular signatures have not been obtained. We aimed at dissecting the influence of both variables, that is, Mirasol PRT and storage time, at the proteome level. We present comprehensive proteomics data analysis of Control PCs and PCs treated with Mirasol PRT at storage days 1, 2, 6, and 8. Our workflow was set to perform proteomics analysis using a gel-free and label-free quantification (LFQ) approach. Semi-quantification was based on LFQ signal intensities of identified proteins using MaxQuant/Perseus software platform. Data are available via ProteomeXchange with identifier PXD008119. We identified marginal differences between Mirasol PRT and Control PCs during storage. However, those significant changes at the proteome level were specifically related to the functional aspects previously described to affect platelets upon Mirasol PRT. In addition, the effect of Mirasol PRT on the platelet proteome appeared not to be exclusively due to an accelerated or enhanced PSL. In summary, semi-quantitative proteomics allows to discern between proteome changes due to
International Nuclear Information System (INIS)
Wickart, Marcel; Madlener, Reinhard
2007-01-01
In this paper we develop an economic model that explains the decision-making problem under uncertainty of an industrial firm that wants to invest in a process technology. More specifically, the decision is between making an irreversible investment in a combined heat-and-power production (cogeneration) system, or to invest in a conventional heat-only generation system (steam boiler) and to purchase all electricity from the grid. In our model we include the main economic and technical variables of the investment decision process. We also account for the risk and uncertainty inherent in volatile energy prices that can greatly affect the valuation of the investment project. The dynamic stochastic model presented allows us to simultaneously determine the optimal technology choice and investment timing. We apply the theoretical model and illustrate our main findings with a numerical example that is based on realistic cost values for industrial oil- or gas-fired cogeneration and heat-only generation in Switzerland. We also briefly discuss expected effects of a CO 2 tax on the investment decision
Kareiva, Peter; Morse, Douglass H; Eccleston, Jill
1989-03-01
We compared the patch-choice performances of an ambush predator, the crab spider Misumena vatia (Thomisidae) hunting on common milkweed Asclepias syriaca (Asclepiadaceae) umbles, with two stochastic rule-of-thumb simulation models: one that employed a threshold giving-up time and one that assumed a fixed probability of moving. Adult female Misumena were placed on milkweed plants with three umbels, each with markedly different numbers of flower-seeking prey. Using a variety of visitation regimes derived from observed visitation patterns of insect prey, we found that decreases in among-umbel variance in visitation rates or increases in overall mean visitation rates reduced the "clarity of the optimum" (the difference in the yield obtained as foraging behavior changes), both locally and globally. Yield profiles from both models were extremely flat or jagged over a wide range of prey visitation regimes; thus, differences between optimal and "next-best" strategies differed only modestly over large parts of the "foraging landscape". Although optimal yields from fixed probability simulations were one-third to one-half those obtained from threshold simulations, spiders appear to depart umbels in accordance with the fixed probability rule.
FPGA-Based Stochastic Echo State Networks for Time-Series Forecasting.
Alomar, Miquel L; Canals, Vincent; Perez-Mora, Nicolas; Martínez-Moll, Víctor; Rosselló, Josep L
2016-01-01
Hardware implementation of artificial neural networks (ANNs) allows exploiting the inherent parallelism of these systems. Nevertheless, they require a large amount of resources in terms of area and power dissipation. Recently, Reservoir Computing (RC) has arisen as a strategic technique to design recurrent neural networks (RNNs) with simple learning capabilities. In this work, we show a new approach to implement RC systems with digital gates. The proposed method is based on the use of probabilistic computing concepts to reduce the hardware required to implement different arithmetic operations. The result is the development of a highly functional system with low hardware resources. The presented methodology is applied to chaotic time-series forecasting.
Approximating Preemptive Stochastic Scheduling
Megow Nicole; Vredeveld Tjark
2009-01-01
We present constant approximative policies for preemptive stochastic scheduling. We derive policies with a guaranteed performance ratio of 2 for scheduling jobs with release dates on identical parallel machines subject to minimizing the sum of weighted completion times. Our policies as well as their analysis apply also to the recently introduced more general model of stochastic online scheduling. The performance guarantee we give matches the best result known for the corresponding determinist...
Smolen, Paul; Baxter, Douglas A; Byrne, John H
2009-03-01
Multiple interlinked positive feedback loops shape the stimulus responses of various biochemical systems, such as the cell cycle or intracellular Ca2+ release. Recent studies with simplified models have identified two advantages of coupling fast and slow feedback loops. This dual-time structure enables a fast response while enhancing resistances of responses and bistability to stimulus noise. We now find that (1) the dual-time structure similarly confers resistance to internal noise due to molecule number fluctuations, and (2) model variants with altered coupling, which better represent some specific biochemical systems, share all the above advantages. We also develop a similar bistable model with coupling of a fast autoactivation loop to a slow loop. This model's topology was suggested by positive feedback proposed to play a role in long-term synaptic potentiation (LTP). The advantages of fast response and noise resistance are also present in this autoactivation model. Empirically, LTP develops resistance to reversal over approximately 1h . The model suggests this resistance may result from increased amounts of synaptic kinases involved in positive feedback.
Air exposure and sample storage time influence on hydrogen release from tungsten
Energy Technology Data Exchange (ETDEWEB)
Moshkunov, K.A., E-mail: moshkunov@gmail.co [National Research Nuclear University ' MEPhI' , Kashirskoe sh. 31, 115409 Moscow (Russian Federation); Schmid, K.; Mayer, M. [Max-Planck-Institut fuer Plasmaphysik, EURATOM Association, Boltzmannstrasse 2, D-85748 Garching (Germany); Kurnaev, V.A.; Gasparyan, Yu.M. [National Research Nuclear University ' MEPhI' , Kashirskoe sh. 31, 115409 Moscow (Russian Federation)
2010-09-30
In investigations of hydrogen retention in first wall components the influence of the conditions of the implanted target storage prior to analysis and the storage time is often neglected. Therefore we have performed a dedicated set of experiments. The release of hydrogen from samples exposed to ambient air after irradiation was compared to samples kept in vacuum. For air exposed samples significant amounts of HDO and D{sub 2}O are detected during TDS. Additional experiments have shown that heavy water is formed by recombination of releasing D and H atoms with O on the W surface. This water formation can alter hydrogen retention results significantly, in particular - for low retention cases. In addition to the influence of ambient air exposure also the influence of storage time in vacuum was investigated. After implantation at 300 K the samples were stored in vacuum for up to 1 week during which the retained amount decreased significantly. The subsequently measured TDS spectra showed that D was lost from both the high and low energy peaks during storage at ambient temperature of {approx}300 K. An attempt to simulate this release from both peaks during room temperature storage by TMAP 7 calculations showed that this effect cannot be explained by conventional diffusion/trapping models.
Air exposure and sample storage time influence on hydrogen release from tungsten
International Nuclear Information System (INIS)
Moshkunov, K.A.; Schmid, K.; Mayer, M.; Kurnaev, V.A.; Gasparyan, Yu.M.
2010-01-01
In investigations of hydrogen retention in first wall components the influence of the conditions of the implanted target storage prior to analysis and the storage time is often neglected. Therefore we have performed a dedicated set of experiments. The release of hydrogen from samples exposed to ambient air after irradiation was compared to samples kept in vacuum. For air exposed samples significant amounts of HDO and D 2 O are detected during TDS. Additional experiments have shown that heavy water is formed by recombination of releasing D and H atoms with O on the W surface. This water formation can alter hydrogen retention results significantly, in particular - for low retention cases. In addition to the influence of ambient air exposure also the influence of storage time in vacuum was investigated. After implantation at 300 K the samples were stored in vacuum for up to 1 week during which the retained amount decreased significantly. The subsequently measured TDS spectra showed that D was lost from both the high and low energy peaks during storage at ambient temperature of ∼300 K. An attempt to simulate this release from both peaks during room temperature storage by TMAP 7 calculations showed that this effect cannot be explained by conventional diffusion/trapping models.
Air exposure and sample storage time influence on hydrogen release from tungsten
Moshkunov, K. A.; Schmid, K.; Mayer, M.; Kurnaev, V. A.; Gasparyan, Yu. M.
2010-09-01
In investigations of hydrogen retention in first wall components the influence of the conditions of the implanted target storage prior to analysis and the storage time is often neglected. Therefore we have performed a dedicated set of experiments. The release of hydrogen from samples exposed to ambient air after irradiation was compared to samples kept in vacuum. For air exposed samples significant amounts of HDO and D 2O are detected during TDS. Additional experiments have shown that heavy water is formed by recombination of releasing D and H atoms with O on the W surface. This water formation can alter hydrogen retention results significantly, in particular - for low retention cases. In addition to the influence of ambient air exposure also the influence of storage time in vacuum was investigated. After implantation at 300 K the samples were stored in vacuum for up to 1 week during which the retained amount decreased significantly. The subsequently measured TDS spectra showed that D was lost from both the high and low energy peaks during storage at ambient temperature of ˜300 K. An attempt to simulate this release from both peaks during room temperature storage by TMAP 7 calculations showed that this effect cannot be explained by conventional diffusion/trapping models.
Importance of storage time in mesophilic anaerobic digestion of food waste.
Lü, Fan; Xu, Xian; Shao, Liming; He, Pinjing
2016-07-01
Storage was used as a pretreatment to enhance the methanization performance of mesophilic anaerobic digestion of food waste. Food wastes were separately stored for 0, 1, 2, 3, 4, 5, 7, and 12days, and then fed into a methanogenic reactor for a biochemical methane potential (BMP) test lasting up to 60days. Relative to the methane production of food waste stored for 0-1day (285-308mL/g-added volatile solids (VSadded)), that after 2-4days and after 5-12days of storage increased to 418-530 and 618-696mL/g-VSadded, respectively. The efficiency of hydrolysis and acidification of pre-stored food waste in the methanization reactors increased with storage time. The characteristics of stored waste suggest that methane production was not correlated with the total hydrolysis efficiency of organics in pre-stored food waste but was positively correlated with the storage time and acidification level of the waste. From the results, we recommend 5-7days of storage of food waste in anaerobic digestion treatment plants. Copyright © 2016. Published by Elsevier B.V.
Stochastic Games for Continuous-Time Jump Processes Under Finite-Horizon Payoff Criterion
Energy Technology Data Exchange (ETDEWEB)
Wei, Qingda, E-mail: weiqd@hqu.edu.cn [Huaqiao University, School of Economics and Finance (China); Chen, Xian, E-mail: chenxian@amss.ac.cn [Peking University, School of Mathematical Sciences (China)
2016-10-15
In this paper we study two-person nonzero-sum games for continuous-time jump processes with the randomized history-dependent strategies under the finite-horizon payoff criterion. The state space is countable, and the transition rates and payoff functions are allowed to be unbounded from above and from below. Under the suitable conditions, we introduce a new topology for the set of all randomized Markov multi-strategies and establish its compactness and metrizability. Then by constructing the approximating sequences of the transition rates and payoff functions, we show that the optimal value function for each player is a unique solution to the corresponding optimality equation and obtain the existence of a randomized Markov Nash equilibrium. Furthermore, we illustrate the applications of our main results with a controlled birth and death system.
On discrete stochastic processes with long-lasting time dependence in the variance
Queirós, S. M. D.
2008-11-01
In this manuscript, we analytically and numerically study statistical properties of an heteroskedastic process based on the celebrated ARCH generator of random variables whose variance is defined by a memory of qm-exponencial, form (eqm=1 x=ex). Specifically, we inspect the self-correlation function of squared random variables as well as the kurtosis. In addition, by numerical procedures, we infer the stationary probability density function of both of the heteroskedastic random variables and the variance, the multiscaling properties, the first-passage times distribution, and the dependence degree. Finally, we introduce an asymmetric variance version of the model that enables us to reproduce the so-called leverage effect in financial markets.
FPGA-Based Stochastic Echo State Networks for Time-Series Forecasting
Directory of Open Access Journals (Sweden)
Miquel L. Alomar
2016-01-01
Full Text Available Hardware implementation of artificial neural networks (ANNs allows exploiting the inherent parallelism of these systems. Nevertheless, they require a large amount of resources in terms of area and power dissipation. Recently, Reservoir Computing (RC has arisen as a strategic technique to design recurrent neural networks (RNNs with simple learning capabilities. In this work, we show a new approach to implement RC systems with digital gates. The proposed method is based on the use of probabilistic computing concepts to reduce the hardware required to implement different arithmetic operations. The result is the development of a highly functional system with low hardware resources. The presented methodology is applied to chaotic time-series forecasting.
Stochastic Games for Continuous-Time Jump Processes Under Finite-Horizon Payoff Criterion
International Nuclear Information System (INIS)
Wei, Qingda; Chen, Xian
2016-01-01
In this paper we study two-person nonzero-sum games for continuous-time jump processes with the randomized history-dependent strategies under the finite-horizon payoff criterion. The state space is countable, and the transition rates and payoff functions are allowed to be unbounded from above and from below. Under the suitable conditions, we introduce a new topology for the set of all randomized Markov multi-strategies and establish its compactness and metrizability. Then by constructing the approximating sequences of the transition rates and payoff functions, we show that the optimal value function for each player is a unique solution to the corresponding optimality equation and obtain the existence of a randomized Markov Nash equilibrium. Furthermore, we illustrate the applications of our main results with a controlled birth and death system.
DEFF Research Database (Denmark)
Barletta, Andrea; Nicolato, Elisa; Pagliarani, Stefano
error bounds for VIX futures, options and implied volatilities. In particular, we derive exact asymptotic results for VIX implied volatilities, and their sensitivities, in the joint limit of short time-to-maturity and small log-moneyness. The obtained expansions are explicit, based on elementary...... approximations of equity (SPX) options. However, the generalizations needed to cover the case of VIX options are by no means straightforward as the dynamics of the underlying VIX futures are not explicitly known. To illustrate the accuracy of our technique, we provide numerical implementations for a selection...... functions and they neatly uncover how the VIX skew depends on the specific choice of the volatility and the vol-of-vol processes. Our results are based on perturbation techniques applied to the infinitesimal generator of the underlying process. This methodology has been previously adopted to derive...
Liao, F.; Rasouli, S.; Timmermans, H.J.P.
2014-01-01
Multistate supernetwork approach has been advanced recently to study multimodal, multi-activity travel behavior. The approach allows simultaneously modeling multiple choice facets pertaining to activity-travel scheduling behavior, subject to space-time constraints, in the context of full daily
A Fractionally Integrated Wishart Stochastic Volatility Model
M. Asai (Manabu); M.J. McAleer (Michael)
2013-01-01
textabstractThere has recently been growing interest in modeling and estimating alternative continuous time multivariate stochastic volatility models. We propose a continuous time fractionally integrated Wishart stochastic volatility (FIWSV) process. We derive the conditional Laplace transform of
Deperas-Standylo, Joanna; Gudowska-Nowak, Ewa; Ritter, Sylvia
2014-07-01
Cytogenetic data accumulated from the experiments with peripheral blood lymphocytes exposed to densely ionizing radiation clearly demonstrate that for particles with linear energy transfer (LET) >100 keV/ μm the derived relative biological effectiveness (RBE) will strongly depend on the time point chosen for the analysis. A reasonable prediction of radiation-induced chromosome damage and its distribution among cells can be achieved by exploiting Monte Carlo methodology along with the information about the radius of the penetrating ion-track and the LET of the ion beam. In order to examine the relationship between the track structure and the distribution of aberrations induced in human lymphocytes and to clarify the correlation between delays in the cell cycle progression and the aberration burden visible at the first post-irradiation mitosis, we have analyzed chromosome aberrations in lymphocytes exposed to Fe-ions with LET values of 335 keV/ μm and formulated a Monte Carlo model which reflects time-delay in mitosis of aberrant cells. Within the model the frequency distributions of aberrations among cells follow the pattern of local energy distribution and are well approximated by a time-dependent compound Poisson statistics. The cell-division cycle of undamaged and aberrant cells and chromosome aberrations are modelled as a renewal process represented by a random sum of (independent and identically distributed) random elements S N = ∑ N i=0 X i . Here N stands for the number of particle traversals of cell nucleus, each leading to a statistically independent formation of X i aberrations. The parameter N is itself a random variable and reflects the cell cycle delay of heavily damaged cells. The probability distribution of S N follows a general law for which the moment generating function satisfies the relation Φ S N = Φ N ( Φ X i ). Formulation of the Monte Carlo model which allows to predict expected fluxes of aberrant and non-aberrant cells has been based
The effect of substrate composition and storage time on urine specific gravity in dogs.
Steinberg, E; Drobatz, K; Aronson, L
2009-10-01
The purpose of this study is to evaluate the effects of substrate composition and storage time on urine specific gravity in dogs. A descriptive cohort study of 15 dogs. The urine specific gravity of free catch urine samples was analysed during a 5-hour time period using three separate storage methods; a closed syringe, a diaper pad and non-absorbable cat litter. The urine specific gravity increased over time in all three substrates. The syringe sample had the least change from baseline and the diaper sample had the greatest change from baseline. The urine specific gravity for the litter and diaper samples had a statistically significant increase from the 1-hour to the 5-hour time point. The urine specific gravity from canine urine stored either on a diaper or in a non-absorbable litter increased over time. Although the change was found to be statistically significant over the 5-hour study period it is unlikely to be clinically significant.
Effect of storage time on microbial quality of some spices and dried ...
African Journals Online (AJOL)
The effect of storage time on the microbial quality of some spices and dried seasonings (SDS) (dawadawa, pepper, ginger, shrimp and fish powders) was studied over a 12-month period. Microbial load and profile of irradiated and unirradiated SDS were assessed at 0, 6 and 12-month periods. The range of total variable ...
Comparison of hydroxy naphthoquinone from North Qinglongyi with different storage times
Xin, G. S.; Ji, Y. B.; Wei, C.
2017-12-01
Objective: To determine the appropriate solvent for the extraction of hydroxy naphthoquinone, and to establish a method for the determination of the content of hydroxy naphthoquinone in the North Qinglongyi, and compare the changes of the content of hydroxy naphthoquinone in North Qinglongyi with different storage times. Methods: According to the nature of hydroxy naphthoquinone in alkaline solution will be discolored, so this experiment for Juglone as the standard reagent, 5% KOH solution as a developer, and the absorbance was measured by UV-spectrophotometry at the wavelength of 515 nm. The content of hydroxy naphthoquinone in North Qinglongyi was determined by colorimetric method, and the contents of hydroxy naphthoquinone in North Qinglongyi of different storage times were compared. Results: The optimum extraction solvent was ethyl acetate. The recoveries were 97.73%±1.11% and the RSD was 1.14% (n = 6). The contents of hydroxy naphthoquinone in the North Qinglunyi were 0.0141%, 0.0104% and 0.0073%, respectively, for one year, two years and three years. The content of hydroxy naphthoquinone decreased with the storage time prolonged. Conclusion This experimental method was stability, high recovery rate, simple and reliable. According to the results of this experiment, we can see that the storage time of North Qinglunyi should not be too long. Should try to choose this year’s North Qinglunyi for experimental research.
Factors affecting red blood cell storage age at the time of transfusion.
Dzik, Walter H; Beckman, Neil; Murphy, Michael F; Delaney, Meghan; Flanagan, Peter; Fung, Mark; Germain, Marc; Haspel, Richard L; Lozano, Miguel; Sacher, Ronald; Szczepiorkowski, Zbigniew; Wendel, Silvano
2013-12-01
Clinical trials are investigating the potential benefit resulting from a reduced maximum storage interval for red blood cells (RBCs). The key drivers that determine RBC age at the time of issue vary among individual hospitals. Although progressive reduction in the maximum storage period of RBCs would be expected to result in smaller hospital inventories and reduced blood availability, the magnitude of the effect is unknown. Data on current hospital blood inventories were collected from 11 hospitals and three blood centers in five nations. A general predictive model for the age of RBCs at the time of issue was developed based on considerations of demand for RBCs in the hospital. Age of RBCs at issue is sensitive to the following factors: ABO group, storage age at the time of receipt by the hospital, the restock interval, inventory reserve, mean demand, and variation in demand. A simple model, based on hospital demand, may serve as the basis for examining factors affecting the storage age of RBCs in hospital inventories. The model suggests that the age of RBCs at the time of their issue to the patient depends on factors external to the hospital transfusion service. Any substantial change in the expiration date of stored RBCs will need to address the broad variation in demand for RBCs while attempting to balance considerations of availability and blood wastage. © 2013 American Association of Blood Banks.
Retrieval-travel-time model for free-fall-flow-rack automated storage and retrieval system
Metahri, Dhiyaeddine; Hachemi, Khalid
2018-03-01
Automated storage and retrieval systems (AS/RSs) are material handling systems that are frequently used in manufacturing and distribution centers. The modelling of the retrieval-travel time of an AS/RS (expected product delivery time) is practically important, because it allows us to evaluate and improve the system throughput. The free-fall-flow-rack AS/RS has emerged as a new technology for drug distribution. This system is a new variation of flow-rack AS/RS that uses an operator or a single machine for storage operations, and uses a combination between the free-fall movement and a transport conveyor for retrieval operations. The main contribution of this paper is to develop an analytical model of the expected retrieval-travel time for the free-fall flow-rack under a dedicated storage assignment policy. The proposed model, which is based on a continuous approach, is compared for accuracy, via simulation, with discrete model. The obtained results show that the maximum deviation between the continuous model and the simulation is less than 5%, which shows the accuracy of our model to estimate the retrieval time. The analytical model is useful to optimise the dimensions of the rack, assess the system throughput, and evaluate different storage policies.
Coherence time of over a second in a telecom-compatible quantum memory storage material
Rančić, Miloš; Hedges, Morgan P.; Ahlefeldt, Rose L.; Sellars, Matthew J.
2018-01-01
Quantum memories for light will be essential elements in future long-range quantum communication networks. These memories operate by reversibly mapping the quantum state of light onto the quantum transitions of a material system. For networks, the quantum coherence times of these transitions must be long compared to the network transmission times, approximately 100 ms for a global communication network. Due to a lack of a suitable storage material, a quantum memory that operates in the 1,550 nm optical fibre communication band with a storage time greater than 1 μs has not been demonstrated. Here we describe the spin dynamics of 167Er3+: Y2SiO5 in a high magnetic field and demonstrate that this material has the characteristics for a practical quantum memory in the 1,550 nm communication band. We observe a hyperfine coherence time of 1.3 s. We also demonstrate efficient spin pumping of the entire ensemble into a single hyperfine state, a requirement for broadband spin-wave storage. With an absorption of 70 dB cm-1 at 1,538 nm and Λ transitions enabling spin-wave storage, this material is the first candidate identified for an efficient, broadband quantum memory at telecommunication wavelengths.
Stochastic, real-space, imaginary-time evaluation of third-order Feynman–Goldstone diagrams
International Nuclear Information System (INIS)
Willow, Soohaeng Yoo; Hirata, So
2014-01-01
A new, alternative set of interpretation rules of Feynman–Goldstone diagrams for many-body perturbation theory is proposed, which translates diagrams into algebraic expressions suitable for direct Monte Carlo integrations. A vertex of a diagram is associated with a Coulomb interaction (rather than a two-electron integral) and an edge with the trace of a Green's function in real space and imaginary time. With these, 12 diagrams of third-order many-body perturbation (MP3) theory are converted into 20-dimensional integrals, which are then evaluated by a Monte Carlo method. It uses redundant walkers for convergence acceleration and a weight function for importance sampling in conjunction with the Metropolis algorithm. The resulting Monte Carlo MP3 method has low-rank polynomial size dependence of the operation cost, a negligible memory cost, and a naturally parallel computational kernel, while reproducing the correct correlation energies of small molecules within a few mE h after 10 6 Monte Carlo steps
Stochastic, real-space, imaginary-time evaluation of third-order Feynman–Goldstone diagrams
Energy Technology Data Exchange (ETDEWEB)
Willow, Soohaeng Yoo [Department of Chemistry, University of Illinois at Urbana-Champaign, 600 South Mathews Avenue, Urbana, Illinois 61801 (United States); Center for Superfunctional Materials, Department of Chemistry, Pohang University of Science and Technology, San 31, Hyojadong, Namgu, Pohang 790-784 (Korea, Republic of); Hirata, So, E-mail: sohirata@illinois.edu [Department of Chemistry, University of Illinois at Urbana-Champaign, 600 South Mathews Avenue, Urbana, Illinois 61801 (United States); CREST, Japan Science and Technology Agency, Saitama 332-0012 (Japan)
2014-01-14
A new, alternative set of interpretation rules of Feynman–Goldstone diagrams for many-body perturbation theory is proposed, which translates diagrams into algebraic expressions suitable for direct Monte Carlo integrations. A vertex of a diagram is associated with a Coulomb interaction (rather than a two-electron integral) and an edge with the trace of a Green's function in real space and imaginary time. With these, 12 diagrams of third-order many-body perturbation (MP3) theory are converted into 20-dimensional integrals, which are then evaluated by a Monte Carlo method. It uses redundant walkers for convergence acceleration and a weight function for importance sampling in conjunction with the Metropolis algorithm. The resulting Monte Carlo MP3 method has low-rank polynomial size dependence of the operation cost, a negligible memory cost, and a naturally parallel computational kernel, while reproducing the correct correlation energies of small molecules within a few mE{sub h} after 10{sup 6} Monte Carlo steps.
Directory of Open Access Journals (Sweden)
Manman Yuan
2018-01-01
Full Text Available The paper addresses the issue of synchronization of memristive bidirectional associative memory neural networks (MBAMNNs with mixed time-varying delays and stochastic perturbation via a sampled-data controller. First, we propose a new model of MBAMNNs with mixed time-varying delays. In the proposed approach, the mixed delays include time-varying distributed delays and discrete delays. Second, we design a new method of sampled-data control for the stochastic MBAMNNs. Traditional control methods lack the capability of reflecting variable synaptic weights. In this paper, the methods are carefully designed to confirm the synchronization processes are suitable for the feather of the memristor. Third, sufficient criteria guaranteeing the synchronization of the systems are derived based on the derive-response concept. Finally, the effectiveness of the proposed mechanism is validated with numerical experiments.
Directory of Open Access Journals (Sweden)
Oana Lelia POP
2016-11-01
Full Text Available An innovative method of L. casei ATCC 393 encapsulation has been reported in the present study using pectin combined with alginate. The aim of this study was to investigate the effect of encapsulation on the survival of L. casei ATCC 393 in yoghurt during long time storage, free or encapsulated in alginate and alginate pectin microspheres, and influence over yoghurt properties, particularly acidification. Over 35 days of storage in yoghurt, the encapsulated probiotic cells proved a higher viability compared with free probiotic cells. An even higher viability and stability was observed for the samples where pectin was used. Pectin acts as prebiotic during encapsulation of L. casei ATCC 393.
Effect of gamma irradiation on storage time of tomatoes in three different stages of ripending
International Nuclear Information System (INIS)
Ozbek, N.; Ozbilgin, S.; Aysan, P.; Celen, H.
1985-01-01
Effect of g-irradiation on storage time of tomatoes was studied and tomatoes of Diego variety in three different stages of ripening were used for the experiment. Green-mature tomatoes were treated with 100 and 200 krad, pink (half-mature) tomatoes were treated with 50, 100, 200, 300, 400 and 500 krad doses of gamma rays respectively. After irradiation the tomatoes were stored in a room where the temperature was kept at 22 C with a humidity of 65%. During storage period color changes, softening, spoilage and molding of the fruits were controlled daily, weight loss measurements and all necessary chemical analysis were made periodically. (author)
Directory of Open Access Journals (Sweden)
YouHua Chen
2014-06-01
Full Text Available In the present report, the coexistence of Prisoners' Dilemma game players (cooperators and defectors were explored in an individual-based framework with the consideration of the impacts of deterministic and stochastic waiting time (WT for triggering mortality and/or colonization events. For the type of deterministic waiting time, the time step for triggering a mortality and/or colonization event is fixed. For the type of stochastic waiting time, whether a mortality and/or colonization event should be triggered for each time step of a simulation is randomly determined by a given acceptance probability (the event takes place when a variate drawn from a uniform distribution [0,1] is smaller than the acceptance probability. The two strategies of modeling waiting time are considered simultaneously and applied to both quantities (mortality: WTm, colonization: WTc. As such, when WT (WTm and/or WTc is an integral >=1, it indicated a deterministically triggering strategy. In contrast, when 1>WT>0, it indicated a stochastically triggering strategy and the WT value itself is used as the acceptance probability. The parameter space between the waiting time for mortality (WTm-[0.1,40] and colonization (WTc-[0.1,40] was traversed to explore the coexistence and non-coexistence regions. The role of defense award was evaluated. My results showed that, one non-coexistence region is identified consistently, located at the area where 1>=WTm>=0.3 and 40>=WTc>=0.1. As a consequence, it was found that the coexistence of cooperators and defectors in the community is largely dependent on the waiting time of mortality events, regardless of the defense or cooperation rewards. When the mortality events happen in terms of stochastic waiting time (1>=WTm>=0.3, extinction of either cooperators or defectors or both could be very likely, leading to the emergence of non-coexistence scenarios. However, when the mortality events occur in forms of relatively long deterministic
Introduction to stochastic calculus
Karandikar, Rajeeva L
2018-01-01
This book sheds new light on stochastic calculus, the branch of mathematics that is most widely applied in financial engineering and mathematical finance. The first book to introduce pathwise formulae for the stochastic integral, it provides a simple but rigorous treatment of the subject, including a range of advanced topics. The book discusses in-depth topics such as quadratic variation, Ito formula, and Emery topology. The authors briefly address continuous semi-martingales to obtain growth estimates and study solution of a stochastic differential equation (SDE) by using the technique of random time change. Later, by using Metivier–Pellumail inequality, the solutions to SDEs driven by general semi-martingales are discussed. The connection of the theory with mathematical finance is briefly discussed and the book has extensive treatment on the representation of martingales as stochastic integrals and a second fundamental theorem of asset pricing. Intended for undergraduate- and beginning graduate-level stud...
Comparison of Microbial Communities in Swine Manure at Various Temperatures and storage times.
Lim, Joung-Soo; Yang, Seung Hak; Kim, Bong-Soo; Lee, Eun Young
2018-01-26
This study was designed to investigate the effects of temperature and storage time on the evolution of bacterial communities in swine manure. Manure was stored at -20°C, 4°C, 20°C, or 37°C and sampled at 7-day intervals over 28 days of storage, for a total of 5 time points. To assess the bacterial species present, 16S ribosomal RNA gene sequences were analyzed using pyrosequencing. After normalization, 113,934 sequence reads were obtained, with an average length of 466.6 ± 4.4 bp. The diversity indices of the communities reduced as temperature and storage time increased, and the slopes of rarefaction curves decreased from the second week in samples stored at -20 °C and 4 °C. These results indicate that the richness of the bacterial community in the manure reduced as temperature and storage time increased. Firmicutes were the dominant phylum in all samples examined, ranging from 89.3% to 98.8% of total reads, followed by Actinobacteria, which accounted for 0.6% to 7.9%. A change in community composition was observed in samples stored at 37 °C during the first 7 days, indicating that temperature plays an important role in determining the microbiota of swine manure. Clostridium, Turicibacter, Streptococcus, and Lactobacillus within Firmicutes, and Corynebacterium within Actinobacteria were the most dominant genera in fresh manure and all stored samples. Based on our findings, we propose Clostridium as an indicator genus of swine manure decomposition in an anaerobic environment. The proportions of dominant genera changed in samples stored at 20 °C and 37 °C during the fourth week. Based on these results, it was concluded that the microbial communities of swine manure change rapidly as storage time and temperature increase.
Parzen, Emanuel
1962-01-01
Well-written and accessible, this classic introduction to stochastic processes and related mathematics is appropriate for advanced undergraduate students of mathematics with a knowledge of calculus and continuous probability theory. The treatment offers examples of the wide variety of empirical phenomena for which stochastic processes provide mathematical models, and it develops the methods of probability model-building.Chapter 1 presents precise definitions of the notions of a random variable and a stochastic process and introduces the Wiener and Poisson processes. Subsequent chapters examine
Manzione, Rodrigo L.; Wendland, Edson; Tanikawa, Diego H.
2012-11-01
Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.
Irradiation control of pathogenic bacteria and their growth during storage time in cooled chicken
International Nuclear Information System (INIS)
Ha Yiming; Wang Feng; Fan Bei; Liu Shuliang; Ju Hua
2009-01-01
The growth of pathogenic bacteria during storage time and their D 10 values by irradiation in cooled chicken were evaluated. The total numbers of colony, E.coli 10003, Campylobacter jejuni33560 and CY04 of the D 10 values were 1.434 kGy, 0.408 kGy, 0.175 kGy, 0.2 kGy respectively in cooled chicken. The results show that total bacteria count in vacuum packaged cooled chicken sample is 5.66 lg(CFU/g) and 4.90 lg (CFU/g) after 3 kGy and 5 kGy irradiation. And in storage at 0∼4 degree C the storage shelf-life of irradiated vacuum packaged cooled chicken could extend to 21 d and 28 d. It can be deduced that pathogenic bacteria can be controlled effectively by irradiation. (authors)
The impact of baking time and bread storage temperature on bread crumb properties.
Bosmans, Geertrui M; Lagrain, Bert; Fierens, Ellen; Delcour, Jan A
2013-12-15
Two baking times (9 and 24 min) and storage temperatures (4 and 25 °C) were used to explore the impact of heat exposure during bread baking and subsequent storage on amylopectin retrogradation, water mobility, and bread crumb firming. Shorter baking resulted in less retrogradation, a less extended starch network and smaller changes in crumb firmness and elasticity. A lower storage temperature resulted in faster retrogradation, a more rigid starch network with more water inclusion and larger changes in crumb firmness and elasticity. Crumb to crust moisture migration was lower for breads baked shorter and stored at lower temperature, resulting in better plasticized biopolymer networks in crumb. Network stiffening, therefore, contributed less to crumb firmness. A negative relation was found between proton mobilities of water and biopolymers in the crumb gel network and crumb firmness. The slope of this linear function was indicative for the strength of the starch network. Copyright © 2013 Elsevier Ltd. All rights reserved.
The influence of storage duration on the setting time of type 1 alginate impression material
Rahmadina, A.; Triaminingsih, S.; Irawan, B.
2017-08-01
Alginate is one of the most commonly used dental impression materials; however, its setting time is subject to change depending on storage conditions and duration. This creates problems because consumer carelessness can affect alginate shelf life and quality. In the present study, the setting times of two groups of type I alginate with different expiry dates was tested. The first group consisted of 11 alginate specimens that had not yet passed the expiry date, and the second group consisted of alginates that had passed the expiry date. The alginate powder was mixed with distilled water, poured into a metal ring, and tested with a polished rod of poly-methyl methacrylate. Statistical analysis showed a significant difference (p<0.05) between the setting times of the alginate that had not passed the expiry date (157 ± 3 seconds) and alginate that had passed the expiry date (144 ± 2 seconds). These findings indicate that storage duration can affect alginate setting time.
International Nuclear Information System (INIS)
Klauder, J.R.
1983-01-01
The author provides an introductory survey to stochastic quantization in which he outlines this new approach for scalar fields, gauge fields, fermion fields, and condensed matter problems such as electrons in solids and the statistical mechanics of quantum spins. (Auth.)
Tsujimura, Maki; Ogawa, Mahiro; Yamamoto, Chisato; Sakakibara, Koichi; Sugiyama, Ayumi; Kato, Kenji; Nagaosa, Kazuyo; Yano, Shinjiro
2017-04-01
Headwater catchments in mountainous region are the most important recharge area for surface and subsurface waters, and time and stock information of the water is principal to understand hydrological processes in the catchments. Also, a variety of microbes are included in the groundwater and spring water, and those varies in time and space, suggesting that information of microbe could be used as tracer for groundwater flow system. However, there have been few researches to evaluate the relationship among the residence time, microbe and storage volume of the groundwater in headwater catchments. We performed an investigation on age dating using SF6 and CFCs, microbe counting in the spring water, and evaluation of groundwater storage volume based on water budget analysis in 8 regions underlain by different lithology, those are granite, dacite, sedimentary rocks, serpentinite, basalt and volcanic lava all over Japan. We conducted hydrometric measurements and sampling of spring water in base flow conditions during the rainless periods 2015 and 2016 in those regions, and SF6, CFCs, stable isotopic ratios of oxygen-18 and deuterium, inorganic solute concentrations and total number of prokaryotes were determined on all water samples. Residence time of spring water ranged from 0 to 16 years in all regions, and storage volume of the groundwater within topographical watershed was estimated to be 0.1 m to 222 m in water height. The spring with the longer residence time tends to have larger storage volume in the watershed, and the spring underlain by dacite tends to have larger storage volume as compared with that underlain by sand stone and chert. Also, total number of prokaryotes in the spring water ranged from 103 to 105 cells/mL, and the spring tends to show clear increasing of total number of prokaryotes with decreasing of residence time. Thus, we observed a certain relationship among residence time, storage volume and total number of prokaryotes in the spring water, and
Deville, S.; Champollion, C.; chery, J.; Doerflinger, E.; Le Moigne, N.; Bayer, R.; Vernant, P.
2011-12-01
The assessment of water storage in the unsaturated zone in karstic areas is particularly challenging. Indeed, water flow path and water storage occur in quite heterogeneous ways through small scale porosity, fractures, joints and large voids. Due to this large heterogeneity, it is therefore difficult to estimate the amount of water circulating in the vadose zone by hydrological means. One indirect method consists to measure the gravity variation associated to water storage and withdrawal. Here, we apply a gravimetric method in which the gravity is measured at the surface and at depth on different sites. Then the time variations of the surface to depth (STD) gravity differences are compared for each site. In this study we attempt to evaluate the magnitude of epikarstic water storage variation in various karst settings using a CG5 portable gravimeter. Surface to depth gravity measurements are performed two times a year since 2009 at the surface an inside caves at different depths on three karst aquifers in southern France : 1. A limestone site on the Larzac plateau with a vadose zone thickness of 300m On this site measurements are done on five locations at different depths going from 0 to 50 m; 2. A dolomitic site on the Larzac plateau (Durzon karst aquifer) with a vadose zone thickness of 200m; Measurements are taken at the surface and at 60m depth 3. A limestone site on the Hortus karst aquifer and "Larzac Septentrional karst aquifer") with a vadose zone thickness of only 35m. Measurements are taken at the surface and at 30m depth Therefore, our measurements are used in two ways : First, the STD differences between dry and wet seasons are used to estimate the capacity of differential storage of each aquifer. Surprisingly, the differential storage capacity of all the sites is relatively invariant despite their variable geological of hydrological contexts. Moreover, the STD gravity variations on site 1 show that no water storage variation occurs beneath 10m depth
Wang, Qian; Lu, Guangqi; Li, Xiaoyu; Zhang, Yichi; Yun, Zejian; Bian, Di
2018-01-01
To take advantage of the energy storage system (ESS) sufficiently, the factors that the service life of the distributed energy storage system (DESS) and the load should be considered when establishing optimization model. To reduce the complexity of the load shifting of DESS in the solution procedure, the loss coefficient and the equal capacity ratio distribution principle were adopted in this paper. Firstly, the model was established considering the constraint conditions of the cycles, depth, power of the charge-discharge of the ESS, the typical daily load curves, as well. Then, dynamic programming method was used to real-time solve the model in which the difference of power Δs, the real-time revised energy storage capacity Sk and the permission error of depth of charge-discharge were introduced to optimize the solution process. The simulation results show that the optimized results was achieved when the load shifting in the load variance was not considered which means the charge-discharge of the energy storage system was not executed. In the meantime, the service life of the ESS would increase.
do Nascimento, Cássio; Muller, Katia; Sato, Sandra; Albuquerque Junior, Rubens Ferreira
2012-04-01
Long-term sample storage can affect the intensity of the hybridization signals provided by molecular diagnostic methods that use chemiluminescent detection. The aim of this study was to evaluate the effect of different storage times on the hybridization signals of 13 bacterial species detected by the Checkerboard DNA-DNA hybridization method using whole-genomic DNA probes. Ninety-six subgingival biofilm samples were collected from 36 healthy subjects, and the intensity of hybridization signals was evaluated at 4 different time periods: (1) immediately after collecting (n = 24) and (2) after storage at -20 °C for 6 months (n = 24), (3) for 12 months (n = 24), and (4) for 24 months (n = 24). The intensity of hybridization signals obtained from groups 1 and 2 were significantly higher than in the other groups (p 0.05). The Checkerboard DNA-DNA hybridization method was suitable to detect hybridization signals from all groups evaluated, and the intensity of signals decreased significantly after long periods of sample storage.
Monitoring storage time and quality attribute of egg based on electronic nose
International Nuclear Information System (INIS)
Wang Yongwei; Jun Wang; Bo Zhou; Qiujun Lu
2009-01-01
The objective of this study was to investigate the potential of an electronic nose (E-nose) technique for monitoring egg storage time and quality attributes. An electronic nose was used to distinguish eggs under cool and room-temperature storage by means of principal component analysis (PCA), linear discriminant analysis (LDA), BP neural network (BPNN) and the combination of a genetic algorithm and BP neural network (GANN). Results showed that the E-nose could distinguish eggs of different storage time under cool and room-temperature storage by LDA, PCA, BPNN and GANN; better prediction values were obtained by GANN than by BPNN. Relationships were established between the E-nose signal and egg quality indices (Haugh unit and yolk factor) by quadratic polynomial step regression (QPSR). The prediction models for Haugh unit and yolk factor indicated a good prediction performance. The Haugh unit model had a standard error of prediction of 3.74 and correlation coefficient 0.91; the yolk factor model had a 0.02 SEP and 0.93 correlation coefficient between predicted and measured values respectively.
International Nuclear Information System (INIS)
Lee, Youn Myoung
1995-02-01
As a newly approaching model, a stochastic model using continuous time Markov process for nuclide decay chain transport of arbitrary length in the fractured porous rock medium has been proposed, by which the need for solving a set of partial differential equations corresponding to various sets of side conditions can be avoided. Once the single planar fracture in the rock matrix is represented by a series of finite number of compartments having region wise constant parameter values in them, the medium is continuous in view of various processes associated with nuclide transport but discrete in medium space and such geologic system is assumed to have Markov property, since the Markov process requires that only the present value of the time dependent random variable be known to determine the future value of random variable, nuclide transport in the medium can then be modeled as a continuous time Markov process. Processes that are involved in nuclide transport are advective transport due to groundwater flow, diffusion into the rock matrix, adsorption onto the wall of the fracture and within the pores in the rock matrix, and radioactive decay chain. The transition probabilities for nuclide from the transition intensities between and out of the compartments are represented utilizing Chapman-Kolmogorov equation, through which the expectation and the variance of nuclide distribution for each compartment or the fractured rock medium can be obtained. Some comparisons between Markov process model developed in this work and available analytical solutions for one-dimensional layered porous medium, fractured medium with rock matrix diffusion, and porous medium considering three member nuclide decay chain without rock matrix diffusion have been made showing comparatively good agreement for all cases. To verify the model developed in this work another comparative study was also made by fitting the experimental data obtained with NaLS and uranine running in the artificial fractured
STOCHASTIC ASSESSMENT OF NIGERIAN STOCHASTIC ...
African Journals Online (AJOL)
eobe
STOCHASTIC ASSESSMENT OF NIGERIAN WOOD FOR BRIDGE DECKS ... abandoned bridges with defects only in their decks in both rural and urban locations can be effectively .... which can be seen as the detection of rare physical.
Microparticles variability in fresh frozen plasma: preparation protocol and storage time effects.
Kriebardis, Anastasios G; Antonelou, Marianna H; Georgatzakou, Hara T; Tzounakas, Vassilis L; Stamoulis, Konstantinos E; Papassideri, Issidora S
2016-05-01
Extracellular vesicles or microparticles exhibiting procoagulant and thrombogenic activity may contribute to the haemostatic potential of fresh frozen plasma. Fresh frozen plasma was prepared from platelet-rich plasma at 20 °C (Group-1 donors) or directly from whole blood at 4 °C (Group-2 donors). Each unit was aseptically divided into three parts, stored frozen for specific periods of time, and analysed by flow cytometry for procoagulant activity immediately after thaw or following post-thaw storage for 24 h at 4 °C. Donors' haematologic, biochemical and life-style profiles as well as circulating microparticles were analysed in parallel. Circulating microparticles exhibited a considerable interdonor but not intergroup variation. Fresh frozen plasma units were enriched in microparticles compared to plasma in vivo. Duration of storage significantly affected platelet- and red cell-derived microparticles. Fresh frozen plasma prepared directly from whole blood contained more residual platelets and more platelet-derived microparticles compared to fresh frozen plasma prepared from platelet-rich plasma. Consequently, there was a statistically significant difference in total, platelet- and red cell-derived microparticles between the two preparation protocols over storage time in the freezer. Preservation of the thawed units for 24 h at 4 °C did not significantly alter microparticle accumulation. Microparticle accumulation and anti-oxidant capacity of fresh frozen plasma was positively or negatively correlated, respectively, with the level of circulating microparticles in individual donors. The preparation protocol and the duration of storage in the freezer, independently and in combination, influenced the accumulation of microparticles in fresh frozen plasma units. In contrast, storage of thawed units for 24 h at 4 °C had no significant effect on the concentration of microparticles.
Transport properties of stochastic Lorentz models
Beijeren, H. van
Diffusion processes are considered for one-dimensional stochastic Lorentz models, consisting of randomly distributed fixed scatterers and one moving light particle. In waiting time Lorentz models the light particle makes instantaneous jumps between scatterers after a stochastically distributed
Six-month storage-time evaluation of one-bottle adhesive systems to dentin.
Giannini, Marcelo; Seixas, Carla Alessandra Marcelino; Reis, Andre Figueiredo; Pimenta, Luiz André Freire
2003-01-01
The goal of this study was to evaluate the 1-week, 3-month, and 6-month performance of eight commercially available one-bottle adhesive systems to dentin. Lingual and buccal surfaces from human third molars were ground wet on 600-grit SiC paper to obtain a flat dentinal surface. The specimens were randomly divided into 24 groups (n = 10), which were established to measure the shear bond strengths of Bond-1 (B1), ONE-STEP (OS), OptiBond SOLO (OP), Prime & Bond 2.1 (PB), Single Bond (SB), STAE (ST), Syntac Sprint (SS), and Tenure Quick (TQ) after 1-week, 3-month, and 6-month water storage at 37 degrees C. One-bottle adhesives were applied according to manufacturers' instructions and Z100 composite cylinders were applied on the bonded dentinal surfaces. The 3-month water-storage groups were thermocycled for 1500 cycles at 5 degrees C and 55 degrees C and 6-month groups for 3000 cycles. After storage periods, specimens were tested in shear in a universal testing machine (0.5 mm/min). were statistically analyzed by analysis of variance and Tukey test. Results: The changes in shear bond strengths were not uniform over time. Over the test period, OS, PB, SB, and SS exhibited bond strength stability, however, SS presented low bond strengths on all tested periods. A significant decrease in bond strength was observed for B1, OP, ST, and TQ after the 6-month storage period.
Storage time of transfused blood and disease recurrence after colorectal cancer surgery
DEFF Research Database (Denmark)
Mynster, T; Nielsen, Hans Jørgen
2001-01-01
of the transfused blood. Therefore, we studied the relationship between blood storage time and the development of disease recurrence and long-term survival after colorectal cancer surgery. METHODS: Preoperative and postoperative data were prospectively recorded in 740 patients undergoing elective resection......BACKGROUND: Perioperative blood transfusion and subsequent development of postoperative infectious complications may lead to poor prognosis of patients with colorectal cancer. It has been suggested that the development of postoperative infectious complications may be related to the storage time...... transfused patients (P = 0.004). The survival of patients receiving blood exclusively stored blood stored > or = 21 days, survival was 3.7 years (P = 0.12). Among patients with curative resection (n = 532), the hazard ratio of disease recurrence was 1.5 (95...
Stochastic Analysis with Financial Applications
Kohatsu-Higa, Arturo; Sheu, Shuenn-Jyi
2011-01-01
Stochastic analysis has a variety of applications to biological systems as well as physical and engineering problems, and its applications to finance and insurance have bloomed exponentially in recent times. The goal of this book is to present a broad overview of the range of applications of stochastic analysis and some of its recent theoretical developments. This includes numerical simulation, error analysis, parameter estimation, as well as control and robustness properties for stochastic equations. This book also covers the areas of backward stochastic differential equations via the (non-li
Brownian motion and stochastic calculus
Karatzas, Ioannis
1998-01-01
This book is designed as a text for graduate courses in stochastic processes. It is written for readers familiar with measure-theoretic probability and discrete-time processes who wish to explore stochastic processes in continuous time. The vehicle chosen for this exposition is Brownian motion, which is presented as the canonical example of both a martingale and a Markov process with continuous paths. In this context, the theory of stochastic integration and stochastic calculus is developed. The power of this calculus is illustrated by results concerning representations of martingales and change of measure on Wiener space, and these in turn permit a presentation of recent advances in financial economics (option pricing and consumption/investment optimization). This book contains a detailed discussion of weak and strong solutions of stochastic differential equations and a study of local time for semimartingales, with special emphasis on the theory of Brownian local time. The text is complemented by a large num...
Marquez, Ana; Serratosa, Maria P; Merida, Julieta
2014-03-01
Changes in colour and phenolic composition in sweet red wines made from Merlot, Syrah and Tempranillo grapes were studied in order to assess the influence of bottle storage over a period of 12months. For this purpose, wine colour parameters, sensory analysis and concentrations of monomeric anthocyanins, pyranoanthocyanins, methylmethine-mediated condensation adducts, flavan3-ol derivatives and flavonols were measured. Hue increased and red colours decreased with the storage time, particularly over the first 3months. The concentrations of low molecular weight flavan-3-ol derivatives decreased with time due to the effect of their conversion into tannins of high molecular weight. In addition, the glycosylated flavonols decreased through hydrolysis to give the corresponding aglycones. Overall, the concentration of phenolic compounds decreased markedly with storage time, whereas the antioxidant activity in the wines remained constant throughout. A panel of expert tasters judged the colour, aroma and flavour of all initial and final wines to be acceptable. Copyright © 2013 Elsevier Ltd. All rights reserved.
Some illustrations of stochasticity
International Nuclear Information System (INIS)
Laslett, L.J.
1977-01-01
A complex, and apparently stochastic, character frequently can be seen to occur in the solutions to simple Hamiltonian problems. Such behavior is of interest, and potentially of importance, to designers of particle accelerators--as well as to workers in other fields of physics and related disciplines. Even a slow development of disorder in the motion of particles in a circular accelerator or storage ring could be troublesome, because a practical design requires the beam particles to remain confined in an orderly manner within a narrow beam tube for literally tens of billions of revolutions. The material presented is primarily the result of computer calculations made to investigate the occurrence of ''stochasticity,'' and is organized in a manner similar to that adopted for presentation at a 1974 accelerator conference
International Nuclear Information System (INIS)
Wei, Zhenbo; Wang, Jun; Zhang, Xi
2013-01-01
A voltammetric electronic tongue (VE-tongue) was self-developed and applied to monitor the quality and storage time of unsealed pasteurized milk. The VE-tongue comprised four working electrodes: gold, silver, platinum, and palladium electrode. Two potential waveforms: Multi-frequency rectangle pulse voltammetry (MRPV) and multi-frequency staircase pulse voltammetry (MSPV) were applied to working electrodes in the study, and both of MRPV and MSPV consisted of three frequency segments: 1 Hz, 10 Hz, and 100 Hz. The total areas under the corresponding curves obtained by VE-tongue in the three frequencies were applied as characteristic data, which were evaluated by the principal component analysis (PCA) and cluster analysis (CA). The results of PCA and CA indicate that the milk samples of different storage time could be successfully classified by the VE-tongue based on MRPV and MSPV, respectively. Combining the areas obtained by the VE-tongue based on MRPV and MSPV, the classification results of PCA and CA were improved evidently. The total bacterial count, acidity and viscosity of the milk samples were also measured during the storage, and those physicochemical characteristics showed regular configuration in PCA and CA plots. Furthermore, the total bacterial count and viscosity properties were predicted by partial least squares regression (PLSR) and least squares-support vector machines (LS-SVM), and the combination of the areas obtained by the VE-tongue based on the MRPV and MSPV were applied as the input data of PLSR and LS-SVM. Both the prediction techniques performed well in predicting viscosity and total bacterial count, and the prediction results of LS-SVM were better than that of PLSR. Those results demonstrate that the VE-tongue could be applied to monitor the quality storage time of unsealed pasteurized milk
Exploring the economic consequences of letting a supplier hold reserve storage
DEFF Research Database (Denmark)
Abginehchi, Soheil; Larsen, Christian; Thorstenson, Anders
2015-01-01
We consider a single-item, periodic review inventory control problem with discrete non-stationary stochastic demand. The time horizon is finite and all shortages at the downstream level are backordered. There are two modes of supply: a normal supplier and a reserve storage supply. The reserve...... storage is capacitated and the downstream buyer can only order the entire inventory in the reserve storage or nothing. If the reserve storage is empty, it takes a fixed time interval before it is replenished again. Provided that the reserve storage is fully replenished it can be used at any time period...
Directory of Open Access Journals (Sweden)
M. Farzin
2010-12-01
Full Text Available Objective: The aim of this study was to evaluate the dimensional stability of casts made from an alginate impression material poured immediately and stored after specific periods.Materials and Methods: The common alginate used in Iran (Super; Iralgin, Golchai Co.,Tehran, Iran was tested. A master model was mounted on a special device and used to obtain the impressions. These impressions were stored at 23°C (SD=1 and 4°C (SD=1 in100% relative humidity, then poured with gypsum immediately and again after 12, 25, 45 and 60 minutes. The casts were measured with a traveling microscope with the precision of 0.5 micrometer.Results: The dimensional stability of the alginate and impressions were both significantly time and temperature dependent. The impressions were dimensionally stable significantly until 12 minutes of storage at room temperature and until 45 minutes of storage at 4°C(SD=1.Conclusion: The dimensional stability of the alginate impressions was influenced by the storage time and environment temperature, but a humid environment and 4°C (SD=1temperature may delay the pouring.
Directory of Open Access Journals (Sweden)
Putri Dian Wulansari
2016-05-01
Full Text Available This research was aimed to evaluate the composition (total solids, water content, fat and protein, qualitative properties (color, aroma, and texture and quantitative properties (free fatty acid and lactic acid of cow milk yogurt with different fruits addition and storage time. Experimental method applied Completely Randomized Design with five treatments namely control, dragon fruit, mango, apple and banana (20% v/v, each with 5 replicates. Qualitative characteristic assessment was conducted on 0, 5, 10 and 15 days of storage. Result showed that fruit addition significantly affected the composition and characteristics, while storage time significantly affected quantitative characteristics of yogurt. Apple and banana increased 13% total solids of plain yogurt, while the highest fat content (4,516% was observed in control yogurt which had the lowest protein content (2,564. The highest free fatty acid was in control yogurt ripen for 15 days (22,885% while the lowest free fatty acid was in mango yogurt ripen for 10 days (13,915%. Fruit addition in yogurt ripen for 15 days at 5C resulted in a safe consumed product.
Tarazona-Díaz, Martha Patricia; Aguayo, Encarna
2013-12-01
Watermelon juice has gained increasing popularity among consumers as a rich natural source of functional compounds such as lycopene and citrulline. However, the final quality of the juice depends significantly on its acidification, pasteurization, centrifugation and storage time and temperature. In this study, these characteristics were assessed in watermelon juice pasteurized at 87.7 °C for 20 s and stored for up to 30 days at 4 or 8 °C. The acidifier citric acid provided an adequate sensory quality, similar to natural watermelon juice. Centrifugation and pasteurization significantly reduced the red color, bioactive compounds (lycopene, antioxidant capacity and total polyphenols) and sensory quality of the juice, particularly when the storage time was extended and a temperature of 8 °C was used (P ≤ 0.05). All treated juices were microbiologically safe for up to 30 days when stored at 4 or 8 °C. In terms of sensory acceptability, only non-centrifuged juices stored for up to 20 days at 4 °C remained above the commercial limit. The present results suggest that using a non-centrifugation process and a storage temperature of 4 °C yields a watermelon juice that better retains its sensory and functional qualities. © 2013 Society of Chemical Industry.
International Nuclear Information System (INIS)
Wellens, Thomas; Shatokhin, Vyacheslav; Buchleitner, Andreas
2004-01-01
We are taught by conventional wisdom that the transmission and detection of signals is hindered by noise. However, during the last two decades, the paradigm of stochastic resonance (SR) proved this assertion wrong: indeed, addition of the appropriate amount of noise can boost a signal and hence facilitate its detection in a noisy environment. Due to its simplicity and robustness, SR has been implemented by mother nature on almost every scale, thus attracting interdisciplinary interest from physicists, geologists, engineers, biologists and medical doctors, who nowadays use it as an instrument for their specific purposes. At the present time, there exist a lot of diversified models of SR. Taking into account the progress achieved in both theoretical understanding and practical application of this phenomenon, we put the focus of the present review not on discussing in depth technical details of different models and approaches but rather on presenting a general and clear physical picture of SR on a pedagogical level. Particular emphasis will be given to the implementation of SR in generic quantum systems-an issue that has received limited attention in earlier review papers on the topic. The major part of our presentation relies on the two-state model of SR (or on simple variants thereof), which is general enough to exhibit the main features of SR and, in fact, covers many (if not most) of the examples of SR published so far. In order to highlight the diversity of the two-state model, we shall discuss several examples from such different fields as condensed matter, nonlinear and quantum optics and biophysics. Finally, we also discuss some situations that go beyond the generic SR scenario but are still characterized by a constructive role of noise
Nath, Caroline Daiane; Neres, Marcela Abbado; Scheidt, Kácia Carine; Bersot, Luciano Dos Santos; Sunahara, Samantha Mariana Monteiro; Sarto, Jaqueline Rocha Wobeto; Stangarlin, José Renato; Gomes, Simone Damasceno; Sereno, Mallu Jagnow; Perin, Ana Paula
2018-03-02
The objective was to characterize the fermentative and microbiological profile of Tifton 85 bermudagrass haylage with different layers of polyethylene film and storage time. The experimental design consisted of a randomized block design with four and six wrapping layers (100 and 150 microns in total. respectively) allocated in the main plots, through repeated measures analysis (30, 60, and 90 days of storage) with four replicates. The storage time and number of wrapping layers did not show changes in the population of Clostridium and lactic acid bacteria. A decrease was observed in the enterobacteria population with an increase in the storage period in the two wrapping layers studied. Upon opening of the haylage at 30 days, the population of Bacillus was lower in haylages made with six layers of wrapping (3.63 log colony forming units (CFU) g-1). No growth of Listeria sp. or Salmonella sp. was observed during the experimental period. The fungal genera with greater occurrence were Penicillium sp. and Fusarium sp. The following mycotoxins were not detected: ochratoxin A, fumonisins, and zearalenone. Relative to the organic butyric, propionic, and acetic acids, the haylages presented a low concentration of lactic acid; this may have prevented a drop in the pH, which was high when the silos were opened (5.4). The levels of ammoniacal nitrogen and soluble carbohydrates presented no variation among the number of wrapping layers, with an overall average of 35.55 and 38.04 g kg-1. Tifton 85 bermudagrass haylage wrapped with four and six layers presented adequate fermentation and microbiological characteristics in the evaluated periods.
Probabilistic tools for planning and operating power systems with distributed energy storage
DEFF Research Database (Denmark)
Klöckl, Bernd; Papaefthymiou, George; Pinson, Pierre
2008-01-01
Stochastic energy flows are an increasingly important phenomenon in today's power system planning and operation. They are – among other reasons – caused by large amounts of stochastic generation such as wind. The inclusion of energy storage devices, distributed in future systems (distributed energy...... owners are either the grid operators, the generation owners, or the energy traders. For the grid operators being the DES owners, storage operation will have to be integrated into the planning of the system, therefore multivariate nonparametric time series analysis and synthesis methods have to be applied...... to recorded data of stochastic energy resources. Together with suited storage models, the implications of DES on the planning of the system can then be assessed. For the producers or traders being the owners of the DES, the topic to be addressed is the real-time operation of each storage device in the power...
International Nuclear Information System (INIS)
Du Luchun; Mei Dongcheng
2011-01-01
The non-adiabatic regime of stochastic resonance (SR) in a bistable system with time delay, an additive white noise and a periodic signal was investigated. The signal power amplification η was employed to characterize the SR of the system. The simulation results indicate that (i) in the case of intermediate frequency Ω of the periodic signal, the typical behavior of SR is lowered monotonically by increasing the delay time τ; in the case of large Ω, τ weakens the SR behavior and then enhances it, with a non-monotonic behavior as a function of time delay; (ii) time delay induces SR when A is above the threshold, whereas no such resonance exists in the absence of time delay; (iii) time delay induces a transition from bimodal to unimodal configuration of η; (iv) varying the particular form of time delay results in different phenomena.
Cost-effective design of ringwall storage hybrid power plants: A real options analysis
International Nuclear Information System (INIS)
Weibel, Sebastian; Madlener, Reinhard
2015-01-01
Highlights: • Economic viability, optimal size, and siting of a hybrid ringwall hydro power plant. • Real options analysis for optimal investment timing and stochastic storage volumes. • Stochastic PV and solar power production affects optimal size of the storage device. • Monte Carlo simulation is used for wind/solar power, el. price, and investment cost. • Numerical computations for two different hybrid ringwall storage plant scenarios. - Abstract: We study the economic viability and optimal sizing and siting of a hybrid plant that combines a ringwall hydro storage system with wind and solar power plants (ringwall storage hybrid power plant, RSHPP). A real options model is introduced to analyze the economics of an onshore RSHPP, and in particular of the varying storage volume in light of the stochastic character of wind and solar power, as well as the optimal investment timing under uncertainty. In fact, many uncertainties arise in such a project. Energy production is determined by the stochastic character of wind and solar power, and affects the optimal size of the storage device. Monte Carlo simulation is performed to analyze the following sources of uncertainty: (i) wind intensity and solar irradiation; (ii) future electricity price; and (iii) investment costs. The results yield the optimal size of the storage device; the energy market on which the operator should sell the electricity generated; numerical examples for two different RSHPP scenarios; and a real options model for analyzing the opportunity to defer the project investment and thus to exploit the value of waiting
Directory of Open Access Journals (Sweden)
Bożena Cwalina-Ambroziak
2012-12-01
Full Text Available The object of the experiment were seeds of two traditional cultivars of yellow lupin (Juno and Amulet cultivated in 1999 in two crop-rotation with 20% and 33% yellow lupine contribution. The quantitative and qualitative composition of the fungal community colonizing the seeds were determined in the laboratory conditions after 0.5-, 1.5- and 2.5-year of storage time. In total 1077 fungal colonies were isolated from the lupin seeds. Fungi representing the species of Penicillium - 29.3%, Alternaria alternata - 26.7% and Rhizopus nigricans - 12.7% were isolated most widely. Among the fungi pathogenic to lupin, the species of Colletotrichum gloeosporioides (16.3% isolates was dominant. The crop rotation with 20% lupin reduced the number of fungal colonies colonizing the seeds including the pathogens from the species of C. gloeosporioides. Seed disinfection decreased the total number of fungal colonies isolated from both cultivars. Higher number of C. gloeosporioides isolates was found in the combination with disinfected seeds. More fungal colonies were obtained from seeds of cv. Amulet than from those of cv. Juno. The storage duration had an effect on the population and the composition of species of fungi isolated from seeds of yellow lupine. With longer storage population of Penicillium spp. and Rhizopus spp. increased, whereas the population of C. gloeosporioides decreased.
Effect of storage time on microbial quality of some spices and dried seasonings
International Nuclear Information System (INIS)
Adu-Gyamfi, A.
2006-01-01
The effect of storage time on the microbial quality of some spices and dried seasonings (SOS) (dawadawa, pepper, ginger, shrimp and fish powders) was studied over a 12-month period. Microbial load and profile of irradiated and unirradiated SOS were assessed at 0, 6 and 12-month periods. The range of total variable counts (TVCs) were initially determined at 0.81-4.53 and 4.658.51 log 10 cfu g -1 for irradiated and un irradiated SDS, respectively; those for mould and yeast counts (MYCs) were determined at 0-1.74 and 1.55-3.35 log 10 cfu g -1 , respectively. Generally, TVCs were not significantly affected (P<0.05) by the 6 and 12-month periods, but MYCs were significantly reduced (P<0.05) after the storage periods in some SDS. Microbial profile, mainly dominated by Bacillus spp., Laclobacillus spp., Clostridium spp., Aspergillus spp. and Penicillium spp., was stable after the 6 and 12-month periods for all the SDS. However, the profile was consistently more diverse on dawadawa. pepper and ginger powders. No adverse change in microbial quality of irradiated and unirradiated SDS was observed at the end of the storage periods
Beato, Victor Manuel; Sánchez, Antonio Higinio; de Castro, Antonio; Montaño, Alfredo
2012-04-04
The influence of processing, with and without fermentation, on the contents of organosulfur compounds, namely, γ-glutamyl peptides, S-alk(en)yl-L-cysteine sulfoxides (ACSOs), and S-allyl-L-cysteine (SAC), in pickled blanched garlic was evaluated. For each processing type, the effect of the preservation method and storage time was also analyzed. Blanching in hot water (90 °C for 5 min) hardly affected the individual organosulfur compound content. The fermentation and packing steps negatively affected the levels of all compounds except for SAC. The content of this compound increased during storage at room temperature whereas γ-glutamyl peptides and ACSOs were degraded to various extents. The pasteurization treatment itself had no significant effect on the concentrations of organosulfur compounds. Use of the corresponding fermentation brine in the case of the fermented product in conjunction with refrigerated storage was found to be the best method to preserve the levels of organosulfur compounds in pickled garlic stored for up to one year.
Effect of storage of shelled Moringa oleifera seeds from reaping time on turbidity removal.
Golestanbagh, M; Ahamad, I S; Idris, A; Yunus, R
2011-09-01
Moringa oleifera is an indigenous plant to Malaysia whose seeds are used for water purification. Many studies on Moringa oleifera have shown that it is highly effective as a natural coagulant for turbidity removal. In this study, two different methods for extraction of Moringa's active ingredient were investigated. Results of sodium chloride (NaCl) and distilled water extraction of Moringa oleifera seeds showed that salt solution extraction was more efficient than distilled water in extracting Moringa's active coagulant ingredient. The optimum dosage of shelled Moringa oleifera seeds extracted by the NaCl solution was comparable with that of the conventional chemical coagulant alum. Moreover, the turbidity removal efficiency was investigated for shelled Moringa oleifera seeds before drying in the oven under different storage conditions (i.e. open and closed containers at room temperature, 27 °C) and durations (fresh, and storage for 2, 4, 6 and 8 weeks from the time the seeds were picked from the trees). Our results indicate that there are no significant differences in coagulation efficiencies and, accordingly, turbidity removals between the examined storage conditions and periods.
Directory of Open Access Journals (Sweden)
Bo Sun
2018-03-01
Full Text Available In the degradation process, the randomness and multiplicity of variables are difficult to describe by mathematical models. However, they are common in engineering and cannot be neglected, so it is necessary to study this issue in depth. In this paper, the copper bending pipe in seawater piping systems is taken as the analysis object, and the time-variant reliability is calculated by solving the interference of limit strength and maximum stress. We did degradation experiments and tensile experiments on copper material, and obtained the limit strength at each time. In addition, degradation experiments on copper bending pipe were done and the thickness at each time has been obtained, then the response of maximum stress was calculated by simulation. Further, with the help of one kind of Monte Carlo method we propose, the time-variant reliability of copper bending pipe was calculated based on the stochastic degradation process and interference theory. Compared with traditional methods and verified by maintenance records, the results show that the time-variant reliability model based on the stochastic degradation process proposed in this paper has better applicability in the reliability analysis, and it can be more convenient and accurate to predict the replacement cycle of copper bending pipe under seawater-active corrosion.
Stochastic modeling and analysis of telecoms networks
Decreusefond, Laurent
2012-01-01
This book addresses the stochastic modeling of telecommunication networks, introducing the main mathematical tools for that purpose, such as Markov processes, real and spatial point processes and stochastic recursions, and presenting a wide list of results on stability, performances and comparison of systems.The authors propose a comprehensive mathematical construction of the foundations of stochastic network theory: Markov chains, continuous time Markov chains are extensively studied using an original martingale-based approach. A complete presentation of stochastic recursions from an
Markov stochasticity coordinates
International Nuclear Information System (INIS)
Eliazar, Iddo
2017-01-01
Markov dynamics constitute one of the most fundamental models of random motion between the states of a system of interest. Markov dynamics have diverse applications in many fields of science and engineering, and are particularly applicable in the context of random motion in networks. In this paper we present a two-dimensional gauging method of the randomness of Markov dynamics. The method–termed Markov Stochasticity Coordinates–is established, discussed, and exemplified. Also, the method is tweaked to quantify the stochasticity of the first-passage-times of Markov dynamics, and the socioeconomic equality and mobility in human societies.
Markov stochasticity coordinates
Energy Technology Data Exchange (ETDEWEB)
Eliazar, Iddo, E-mail: iddo.eliazar@intel.com
2017-01-15
Markov dynamics constitute one of the most fundamental models of random motion between the states of a system of interest. Markov dynamics have diverse applications in many fields of science and engineering, and are particularly applicable in the context of random motion in networks. In this paper we present a two-dimensional gauging method of the randomness of Markov dynamics. The method–termed Markov Stochasticity Coordinates–is established, discussed, and exemplified. Also, the method is tweaked to quantify the stochasticity of the first-passage-times of Markov dynamics, and the socioeconomic equality and mobility in human societies.
Flow and Residence Times of Dynamic River Bank Storage and Sinuosity-Driven Hyporheic Exchange
Gomez-Velez, J. D.; Wilson, J. L.; Cardenas, M. B.; Harvey, J. W.
2017-10-01
Hydrologic exchange fluxes (HEFs) vary significantly along river corridors due to spatiotemporal changes in discharge and geomorphology. This variability results in the emergence of biogeochemical hot-spots and hot-moments that ultimately control solute and energy transport and ecosystem services from the local to the watershed scales. In this work, we use a reduced-order model to gain mechanistic understanding of river bank storage and sinuosity-driven hyporheic exchange induced by transient river discharge. This is the first time that a systematic analysis of both processes is presented and serves as an initial step to propose parsimonious, physics-based models for better predictions of water quality at the large watershed scale. The effects of channel sinuosity, alluvial valley slope, hydraulic conductivity, and river stage forcing intensity and duration are encapsulated in dimensionless variables that can be easily estimated or constrained. We find that the importance of perturbations in the hyporheic zone's flux, residence times, and geometry is mainly explained by two-dimensionless variables representing the ratio of the hydraulic time constant of the aquifer and the duration of the event (Γd) and the importance of the ambient groundwater flow (Δh∗). Our model additionally shows that even systems with small sensitivity, resulting in small changes in the hyporheic zone extent, are characterized by highly variable exchange fluxes and residence times. These findings highlight the importance of including dynamic changes in hyporheic zones for typical HEF models such as the transient storage model.
Energy Technology Data Exchange (ETDEWEB)
Tollestrup, A.V.; Dugan, G
1983-12-01
Major headings in this review include: proton sources; antiproton production; antiproton sources and Liouville, the role of the Debuncher; transverse stochastic cooling, time domain; the accumulator; frequency domain; pickups and kickers; Fokker-Planck equation; calculation of constants in the Fokker-Planck equation; and beam feedback. (GHT)
Composite stochastic processes
Kampen, N.G. van
Certain problems in physics and chemistry lead to the definition of a class of stochastic processes. Although they are not Markovian they can be treated explicitly to some extent. In particular, the probability distribution for large times can be found. It is shown to obey a master equation. This
Stochastic Control - External Models
DEFF Research Database (Denmark)
Poulsen, Niels Kjølstad
2005-01-01
This note is devoted to control of stochastic systems described in discrete time. We are concerned with external descriptions or transfer function model, where we have a dynamic model for the input output relation only (i.e.. no direct internal information). The methods are based on LTI systems...
DEFF Research Database (Denmark)
Sørensen, P.
1998-01-01
Animal slurries are stored for a variable period of time before application in the field. The effect of cattle slurry storage time and temperature on the subsequent mineralization of C and N in soil was studied under laboratory conditions. Urine and faeces from a dairy cow were sampled separately...... and mixed to a slurry. After 4 weeks of storage under anaerobic conditions at 15 degrees C, the NH4+ N content exceeded the original urinary N content of the slurry; the NH4+ content increased only slightly during the following 16 weeks of storage. After 4 weeks of storage, the proportion of slurry C...... in volatile fatty acids (VFA) amounted to 10% and increased to 15% after 20 weeks. Straw addition to the slurry caused an increase of VFA-C in stored slurry, but had a negligible influence on the proportion of slurry N in the form of NH4+. Slurries subjected to different storage conditions were added...
Entropy Production in Stochastics
Directory of Open Access Journals (Sweden)
Demetris Koutsoyiannis
2017-10-01
Full Text Available While the modern definition of entropy is genuinely probabilistic, in entropy production the classical thermodynamic definition, as in heat transfer, is typically used. Here we explore the concept of entropy production within stochastics and, particularly, two forms of entropy production in logarithmic time, unconditionally (EPLT or conditionally on the past and present having been observed (CEPLT. We study the theoretical properties of both forms, in general and in application to a broad set of stochastic processes. A main question investigated, related to model identification and fitting from data, is how to estimate the entropy production from a time series. It turns out that there is a link of the EPLT with the climacogram, and of the CEPLT with two additional tools introduced here, namely the differenced climacogram and the climacospectrum. In particular, EPLT and CEPLT are related to slopes of log-log plots of these tools, with the asymptotic slopes at the tails being most important as they justify the emergence of scaling laws of second-order characteristics of stochastic processes. As a real-world application, we use an extraordinary long time series of turbulent velocity and show how a parsimonious stochastic model can be identified and fitted using the tools developed.
Crisan, Dan
2011-01-01
"Stochastic Analysis" aims to provide mathematical tools to describe and model high dimensional random systems. Such tools arise in the study of Stochastic Differential Equations and Stochastic Partial Differential Equations, Infinite Dimensional Stochastic Geometry, Random Media and Interacting Particle Systems, Super-processes, Stochastic Filtering, Mathematical Finance, etc. Stochastic Analysis has emerged as a core area of late 20th century Mathematics and is currently undergoing a rapid scientific development. The special volume "Stochastic Analysis 2010" provides a sa
Variation in content of macronutrients of guava tree leaves, in function of type and time of storage
Directory of Open Access Journals (Sweden)
Henrique Antunes de Souza
2010-10-01
Full Text Available Leaf analysis for perennial crops such as the guava tree is an important tool. It was used to evaluate the influence of the type of packaging (with or without refrigerator and storage time after collection on the macronutrient composition of guava tree leaves. The leaf sampling was carried out on a commercial guava tree (cv. Paluma, collecting the third pair of recently matured leaves in full bloom. The experimental design was in randomized blocks, subdivided according to the type of packaging (with or without refrigerator and further subdivided into eight storage times before washing (zero, 6, 12, 24, 48, 72, 96 and 168h after sampling, with four replications. The storage time significantly affected the concentration of leaf nitrogen, calcium and sulfur. Moreover, the type and time of conditioning (with or without refrigerator affected only the magnesium. In general, storage fot up to 12h before washing produced no significant changes in the levels of macronutrients.
Variation in content of macronutrients of guava tree leaves, in function of type and time of storage
Directory of Open Access Journals (Sweden)
Henrique Antunes de Souza
2010-09-01
Full Text Available Leaf analysis for perennial crops such as the guava tree is an important tool. It was used to evaluate the influence of the type of packaging (with or without refrigerator and storage time after collection on the macronutrient composition of guava tree leaves. The leaf sampling was carried out on a commercial guava tree (cv. Paluma, collecting the third pair of recently matured leaves in full bloom. The experimental design was in randomized blocks, subdivided according to the type of packaging (with or without refrigerator and further subdivided into eight storage times before washing (zero, 6, 12, 24, 48, 72, 96 and 168h after sampling, with four replications. The storage time significantly affected the concentration of leaf nitrogen, calcium and sulfur. Moreover, the type and time of conditioning (with or without refrigerator affected only the magnesium. In general, storage fot up to 12h before washing produced no significant changes in the levels of macronutrients.
Raat, N. J.; Verhoeven, A. J.; Mik, E. G.; Gouwerok, C. W.; Verhaar, R.; Goedhart, P. T.; de Korte, D.; Ince, C.
2005-01-01
Objective: To determine whether the storage time of human leukodepleted red blood cell concentrates compromises intestinal microvascular oxygen concentration oxygen (muPo(2)) during isovolemic exchange transfusion at low hematocrit. Design: Prospective, randomized, controlled study. Setting:
Mahanaxar: quality of service guarantees in high-bandwidth, real-time streaming data storage
Energy Technology Data Exchange (ETDEWEB)
Bigelow, David [Los Alamos National Laboratory; Bent, John [Los Alamos National Laboratory; Chen, Hsing-Bung [Los Alamos National Laboratory; Brandt, Scott [UCSC
2010-04-05
Large radio telescopes, cyber-security systems monitoring real-time network traffic, and others have specialized data storage needs: guaranteed capture of an ultra-high-bandwidth data stream, retention of the data long enough to determine what is 'interesting,' retention of interesting data indefinitely, and concurrent read/write access to determine what data is interesting, without interrupting the ongoing capture of incoming data. Mahanaxar addresses this problem. Mahanaxar guarantees streaming real-time data capture at (nearly) the full rate of the raw device, allows concurrent read and write access to the device on a best-effort basis without interrupting the data capture, and retains data as long as possible given the available storage. It has built in mechanisms for reliability and indexing, can scale to meet arbitrary bandwidth requirements, and handles both small and large data elements equally well. Results from our prototype implementation shows that Mahanaxar provides both better guarantees and better performance than traditional file systems.
Sheng, Li; Wang, Zidong; Zou, Lei; Alsaadi, Fuad E
2017-10-01
In this paper, the event-based finite-horizon H ∞ state estimation problem is investigated for a class of discrete time-varying stochastic dynamical networks with state- and disturbance-dependent noises [also called (x,v) -dependent noises]. An event-triggered scheme is proposed to decrease the frequency of the data transmission between the sensors and the estimator, where the signal is transmitted only when certain conditions are satisfied. The purpose of the problem addressed is to design a time-varying state estimator in order to estimate the network states through available output measurements. By employing the completing-the-square technique and the stochastic analysis approach, sufficient conditions are established to ensure that the error dynamics of the state estimation satisfies a prescribed H ∞ performance constraint over a finite horizon. The desired estimator parameters can be designed via solving coupled backward recursive Riccati difference equations. Finally, a numerical example is exploited to demonstrate the effectiveness of the developed state estimation scheme.
DEFF Research Database (Denmark)
Akkerman, Renzo; van Donk, Dirk Pieter; Gaalman, Gerard
2007-01-01
In food processing, two-stage production systems with a batch processor in the first stage and packaging lines in the second stage are common and mostly separated by capacity- and time-constrained intermediate storage. This combination of constraints is common in practice, but the literature hardly...... of systems like this. Contrary to the common sense in operations management, the LPT rule is able to maximize the total production volume per day. Furthermore, we show that adding one tank has considerable effects. Finally, we conclude that the optimal setup frequency for batches in the first stage...... pays any attention to this. In this paper, we show how various capacity and time constraints influence the performance of a specific two-stage system. We study the effects of several basic scheduling and sequencing rules in the presence of these constraints in order to learn the characteristics...
Storage time of platelet concentrates and risk of a positive blood culture
DEFF Research Database (Denmark)
Kreuger, Aukje L; Rostgaard, Klaus; Middelburg, Rutger A
2018-01-01
BACKGROUND: Concern of transfusion-transmitted bacterial infections has been the major hurdle to extend shelf life of platelet (PLT) concentrates. We aimed to investigate the association between storage time and risk of positive blood cultures at different times after transfusion. STUDY DESIGN...... AND METHODS: We performed a nationwide cohort study among PLT transfusion recipients in Denmark between 2010 and 2012, as recorded in the Scandinavian Donations and Transfusions (SCANDAT2) database. Linking with a nationwide database on blood cultures (MiBa), we compared the incidence of a positive blood......) of a positive blood culture the day after transfusion of at least one old PLT concentrate was 0.77 (95% confidence interval [CI], 0.54-1.09) compared to transfusion of fresh PLT concentrates. The incidence rate of a positive blood culture was lower the day after receiving one old compared to one fresh PLT...
Sugiyama, Ikumi; Takahashi, Namiki; Sadzuka, Yasuyuki
2016-01-01
In dermatologic therapy, several external preparations formulated as ointments or creams are prescribed. And they are often admixture to improve patient compliance. In this study, we prepared admixtures of moisturizer with steroids and examined their usability and the amount of principal agent in formulations, particularly focusing on the moisturizer content. Four heparinoid semisolid formulations were selected: Hirudoid ® soft ointment 0.3% (Formulation A) and 3 generic agents [(Besoften ® oil-based cream 0.3% (Formulation B), Kuradoido ® ointment 0.3% (Formulation C), and Hepadaerm ointment 0.3% (Formulation D)], and Antebate ® ointment 0.05% (Formulation E) were used as steroids. Formulation A and B are water-in-oil emulsions, and Formulation C and D are oil-in-water emulsions. Admixtures looked like to be mixed uniformly by visual observation. In the examination of heparinoid amount, admixture A+E and B+E were mixed uniformly. On the other hand, admixture C+E was remarkable un-uniformly. It was speculated that the emulsification of formulation C was broken. The phenomenon was supported by the result of malleability. After 8 weeks storage, the heparinoid ratio in each formulation could be expressed as follows: Admixture B≥Admixture A>Admixture C=Admixture D. A suitable storage temperature was 4°C. The results of physicochemical data analysis reveal the formulations composed of water-in-oil cream, i.e., Formulation A and Formulation B, to be the optimal choices for mixing with steroid ointments. Mixing time and storage conditions may be optimized to solve pharmaceutical problems. Moreover, understanding the emulsion type and character of semisolid formulations can expand the range of formulation options.
Stochastic TDHF and the Boltzman-Langevin equation
International Nuclear Information System (INIS)
Suraud, E.; Reinhard, P.G.
1991-01-01
Outgoing from a time-dependent theory of correlations, we present a stochastic differential equation for the propagation of ensembles of Slater determinants, called Stochastic Time-Dependent Hartree-Fock (Stochastic TDHF). These ensembles are allowed to develop large fluctuations in the Hartree-Fock mean fields. An alternative stochastic differential equation, the Boltzmann-Langevin equation, can be derived from Stochastic TDHF by averaging over subensembles with small fluctuations
Memory effects on stochastic resonance
Neiman, Alexander; Sung, Wokyung
1996-02-01
We study the phenomenon of stochastic resonance (SR) in a bistable system with internal colored noise. In this situation the system possesses time-dependent memory friction connected with noise via the fluctuation-dissipation theorem, so that in the absence of periodic driving the system approaches the thermodynamic equilibrium state. For this non-Markovian case we find that memory usually suppresses stochastic resonance. However, for a large memory time SR can be enhanced by the memory.
Sensory stability of whole mango juice: influence of temperature and storage time
Directory of Open Access Journals (Sweden)
Anderson do Nascimento Oliveira
2012-12-01
Full Text Available This study investigated the degradation kinetics of the sensory attributes of commercial whole mango (cv. Ubá juice and evaluated its sensory acceptability during storage. Samples of the product were stored in a BOD incubator at 25, 35, and 45 ºC under 24 hours light (650 lux for 120 days. Sensory analyses (Quantitative Descriptive Analysis - QDA were conducted with trained panel and consumers. The correlations between sensory and physicochemical characteristics (instrumental color and vitamin C content were also assessed. Flavor, aroma, and color vary with temperature and time of storage. Aroma and flavor were most affected by temperature with values of Q10 and Ea equal to 4.16 and 25.31 kcal.mol-1; and 3.61 and 22.80 kcal.mol-1, respectively. The sensory changes observed by the trained panel are related to the degradation of vitamin C and changes in the color coordinates (L* and ΔE* of mango juice. However, consumers were unable to detect changes in the overall quality of the juices. It was observed that the QDA can be a useful tool to assess shelf-life.
A cryogenic electrostatic trap for long-time storage of keV ion beams
Lange, M.; Froese, M.; Menk, S.; Varju, J.; Bastert, R.; Blaum, K.; López-Urrutia, J. R. Crespo; Fellenberger, F.; Grieser, M.; von Hahn, R.; Heber, O.; Kühnel, K.-U.; Laux, F.; Orlov, D. A.; Rappaport, M. L.; Repnow, R.; Schröter, C. D.; Schwalm, D.; Shornikov, A.; Sieber, T.; Toker, Y.; Ullrich, J.; Wolf, A.; Zajfman, D.
2010-05-01
We report on the realization and operation of a fast ion beam trap of the linear electrostatic type employing liquid helium cooling to reach extremely low blackbody radiation temperature and residual gas density and, hence, long storage times of more than 5 min which are unprecedented for keV ion beams. Inside a beam pipe that can be cooled to temperatures <15 K, with 1.8 K reached in some locations, an ion beam pulse can be stored at kinetic energies of 2-20 keV between two electrostatic mirrors. Along with an overview of the cryogenic trap design, we present a measurement of the residual gas density inside the trap resulting in only 2×103 cm-3, which for a room temperature environment corresponds to a pressure in the 10-14 mbar range. The device, called the cryogenic trap for fast ion beams, is now being used to investigate molecules and clusters at low temperatures, but has also served as a design prototype for the cryogenic heavy-ion storage ring currently under construction at the Max-Planck Institute for Nuclear Physics.
A cryogenic electrostatic trap for long-time storage of keV ion beams.
Lange, M; Froese, M; Menk, S; Varju, J; Bastert, R; Blaum, K; López-Urrutia, J R Crespo; Fellenberger, F; Grieser, M; von Hahn, R; Heber, O; Kühnel, K-U; Laux, F; Orlov, D A; Rappaport, M L; Repnow, R; Schröter, C D; Schwalm, D; Shornikov, A; Sieber, T; Toker, Y; Ullrich, J; Wolf, A; Zajfman, D
2010-05-01
We report on the realization and operation of a fast ion beam trap of the linear electrostatic type employing liquid helium cooling to reach extremely low blackbody radiation temperature and residual gas density and, hence, long storage times of more than 5 min which are unprecedented for keV ion beams. Inside a beam pipe that can be cooled to temperatures <15 K, with 1.8 K reached in some locations, an ion beam pulse can be stored at kinetic energies of 2-20 keV between two electrostatic mirrors. Along with an overview of the cryogenic trap design, we present a measurement of the residual gas density inside the trap resulting in only 2 x 10(3) cm(-3), which for a room temperature environment corresponds to a pressure in the 10(-14) mbar range. The device, called the cryogenic trap for fast ion beams, is now being used to investigate molecules and clusters at low temperatures, but has also served as a design prototype for the cryogenic heavy-ion storage ring currently under construction at the Max-Planck Institute for Nuclear Physics.
Directory of Open Access Journals (Sweden)
Dafei Yin
2017-09-01
Full Text Available Corn is one of the staple food and feed ingredients in China, therefore its storage is of particular importance. Corn is typically stored for 2 or more years in national barns before it is sold as a food or feed ingredient. However, the effects of stored corn in national barns on the animal performance and nutrient utilization have not been investigated thus far. This study attempted to determine the effects of storage time on the chemical and physical characteristics of corn and its nutritional value, broiler growth performance, and meat quality. Corn grains used in the present study were stored for 4 different periods, from 2 to 5 yr, under the same conditions in a building at the Beijing National Grain Storage Facility. A total of 240 birds in Exp. 1 and 90 birds in Exp. 2 were used to compare the effects of storage time on the utilization of nutrients of corn, the performance, and meat quality of broilers. The content of starch, crude protein, amino acids, fatty acids, and test weight generally decreased with increasing storage time. Corn stored for over 4 yr showed decreased catalase (CAT and peroxidase (POD activities and increased fat acidity. Body weight gain (BWG and European production index (EPI of broilers from 0 to 3 wk tended to decrease linearly with storage time (0.05 0.05. The digestibility of histidine and arginine, and C18:2 and C18:3 changed quadratically with storage time (P < 0.05. Collectively, the results suggest that the use of corn stored for 4 yr in animal feed decreased the performance and meat quality of broilers. Fat acidity, CAT, and POD activities can be used as indexes for evaluating the storage quality of corn.
DEFF Research Database (Denmark)
Rygård, S L; Jonsson, A B; Madsen, M B
2017-01-01
BACKGROUND: Patients in the intensive care unit (ICU) are often anaemic due to blood loss, impaired red blood cell (RBC) production and increased RBC destruction. In some studies, more than half of the patients were treated with RBC transfusion. During storage, the RBC and the storage medium...... evidence to assess the effects of shorter vs. longer storage time of transfused RBCs for ICU patients. METHODS: We will conduct a systematic review with meta-analyses and trial sequential analyses of randomised clinical trials, and also include results of severe adverse events from large observational...
Energy Technology Data Exchange (ETDEWEB)
Bahari, I; Ishak, S; Ayub, M K [National Univ. of Malaysia, Bangi, Selangor
1983-12-01
The use of gamma radiation in prolonging the storage life of black and white peppers is promising. Doses up to 9 kGy and storage period up to 6 months did not significantly change (P<0.05) the volatile constituents of the peppers. Besides the increase in piperine content of unirradiated pepper there was no change in piperettine and piperine contents of both pepper with respect to increase in dose and storage time. No sensory change was detected for the treatments used (author).
International Nuclear Information System (INIS)
Bahari, I.; Ishak, S.; Ayub, M.K.
1983-01-01
The use of gamma radiation in prolonging the storage life of black and white peppers is promising. Doses up to 9 kGy and storage period up to 6 months did not significantly change (P<0.05) the volatile constituents of the peppers. Besides the increase in piperine content of unirradiated pepper there was no change in piperettine and piperine contents of both pepper with respect to increase in dose and storage time. No sensory change was detected for the treatments used (author)
Directory of Open Access Journals (Sweden)
Romanu Ekaterini
2006-01-01
Full Text Available This article shows the similarities between Claude Debussy’s and Iannis Xenakis’ philosophy of music and work, in particular the formers Jeux and the latter’s Metastasis and the stochastic works succeeding it, which seem to proceed parallel (with no personal contact to what is perceived as the evolution of 20th century Western music. Those two composers observed the dominant (German tradition as outsiders, and negated some of its elements considered as constant or natural by "traditional" innovators (i.e. serialists: the linearity of musical texture, its form and rhythm.
Stochastic estimation of electricity consumption
International Nuclear Information System (INIS)
Kapetanovic, I.; Konjic, T.; Zahirovic, Z.
1999-01-01
Electricity consumption forecasting represents a part of the stable functioning of the power system. It is very important because of rationality and increase of control process efficiency and development planning of all aspects of society. On a scientific basis, forecasting is a possible way to solve problems. Among different models that have been used in the area of forecasting, the stochastic aspect of forecasting as a part of quantitative models takes a very important place in applications. ARIMA models and Kalman filter as stochastic estimators have been treated together for electricity consumption forecasting. Therefore, the main aim of this paper is to present the stochastic forecasting aspect using short time series. (author)
Battery Energy Storage Sizing When Time of Use Pricing Is Applied
Khormali, Shahab
2014-01-01
Battery energy storage systems (BESSs) are considered a key device to be introduced to actuate the smart grid paradigm. However, the most critical aspect related to the use of such device is its economic feasibility as it is a still developing technology characterized by high costs and limited life duration. Particularly, the sizing of BESSs must be performed in an optimized way in order to maximize the benefits related to their use. This paper presents a simple and quick closed form procedure for the sizing of BESSs in residential and industrial applications when time-of-use tariff schemes are applied. A sensitivity analysis is also performed to consider different perspectives in terms of life span and future costs. PMID:25295309
Long time storage containers for spent fuels and vitrified wastes: synthesis of the studies
International Nuclear Information System (INIS)
Beziat, A.
2004-01-01
This report presents a synthesis of the studies relatives to the containers devoted to the long time spent fuels storage and vitrified wastes packages. These studies were realized in the framework of the axis 3 of the law of 1991 on the radioactive wastes management. The first part is devoted to the presentation of the studies. The container sizing studies which constitute the first containment barrier are then presented. The material choice and the closed system are also detailed. The studies were validate by the realization of containers models and an associated demonstration program is proposed. A synthesis of the technical and economical studies allowed to determine the components and operation costs. (A.L.B.)
Battery Energy Storage Sizing When Time of Use Pricing Is Applied
Directory of Open Access Journals (Sweden)
Guido Carpinelli
2014-01-01
Full Text Available Battery energy storage systems (BESSs are considered a key device to be introduced to actuate the smart grid paradigm. However, the most critical aspect related to the use of such device is its economic feasibility as it is a still developing technology characterized by high costs and limited life duration. Particularly, the sizing of BESSs must be performed in an optimized way in order to maximize the benefits related to their use. This paper presents a simple and quick closed form procedure for the sizing of BESSs in residential and industrial applications when time-of-use tariff schemes are applied. A sensitivity analysis is also performed to consider different perspectives in terms of life span and future costs.
A multiple-orbit time-of-flight mass spectrometer based on a low energy electrostatic storage ring
Sullivan, M. R.; Spanjers, T. L.; Thorn, P. A.; Reddish, T. J.; Hammond, P.
2012-11-01
The results are presented for an electrostatic storage ring, consisting of two hemispherical deflector analyzers (HDA) connected by two separate sets of cylindrical lenses, used as a time-of-flight mass spectrometer. Based on the results of charged particle simulations and formal matrix model, the Ion Storage Ring is capable of operating with multiple stable orbits, for both single and multiply charged ions simultaneously.
Rohanian, Ahmad; Ommati Shabestari, Ghasem; Zeighami, Somayeh; Samadi, Mohammad Javad; Shamshiri, Ahmad Reza
2014-01-01
Objectives: Some manufacturers claim to have produced new irreversible hydro-colloids that are able to maintain their dimensional stability during storage. The present study evaluated the effect of storage time on dimensional stability of three alginates: Hydrogum 5, Tropicalgin and Alginoplast. Materials and Methods: In this experimental in-vitro trial, a total of 90 alginate impressions were made from a Dentoform model using Hydrogum 5, Tropicalgin and Alginoplast alginates. The impressions...
Optimum community energy storage system for PV energy time-shift
International Nuclear Information System (INIS)
Parra, David; Gillott, Mark; Norman, Stuart A.; Walker, Gavin S.
2015-01-01
Highlights: • The performance and economic benefits of Pb-acid and Li-ion batteries are compared. • The business case during the decarbonisation pathway is assessed. • The aggregation from a community approach reduced the levelised cost by 37% by 2020. • For a forecast price of 16.3 p/kW h Li-ion battery cost must be less than 275 £/kW h. • A 10% subsidy will be needed for Li-ion batteries to achieve the 2020 forecast. - Abstract: A novel method has been designed to obtain the optimum community energy storage (CES) systems for end user applications. The method evaluates the optimum performance (including the round trip efficiency and annual discharge), levelised cost (LCOES), the internal rate of return and the levelised value of suitable energy storage technologies. A complimentary methodology was developed including three reference years (2012, 2020 and zero carbon year) to show the evolution of the business case during the low carbon transition. The method follows a community approach and the optimum CES system was calculated as a function of the size of the community. In this work, this method was put in practice with lead-acid (PbA) and lithium-ion battery (Li-ion) technologies when performing PV energy time-shift using real demand data from a single home to a 100-home community. The community approach reduced the LCOES down to 0.30 £/kW h and 0.11 £/kW h in 2020 and the zero carbon year respectively. These values meant a cost reduction by 37% and 66% regarding a single home. Results demonstrated that PbA batteries needs from 1.5 to 2.5 times more capacity than Li-ion chemistry to reduce the LCOES, the worst case scenario being for the smallest communities, because the more spiky demand profile required proportionately larger PbA battery capacities
Mgaya-Kilima, Beatrice; Remberg, Siv Fagertun; Chove, Bernard Elias; Wicklund, Trude
2015-01-01
A study was conducted to determine the effects of packaging materials, seasonality, storage temperature and time on physiochemical and antioxidant properties of roselle-mango juice blends. Roselle extract (20%, 40%, 60%, and 80%) was mixed with mango juice and stored in glass and plastic bottles at 4°C and 28°C. Total soluble solids, pH, titratable acidity, reducing sugar, color, vitamin C, total monomeric anthocyanins, total phenols, and antioxidant activity (FRAP) were evaluated in freshly prepared juice, and after, 2, 4, and 6 months of storage. The results showed that total soluble solids, reducing sugars, and pH increased with storage times under different storage time, irrespective of packaging materials. The acidity, color, total monomeric anthocyanin, vitamin C, total phenols, and antioxidant activity decreased during storage irrespective of storage temperature and packaging material. Loss of anthocyanins, total phenols, and vitamin C content were higher in blends stored at 28°C than 4°C. PMID:25838888
RES: Regularized Stochastic BFGS Algorithm
Mokhtari, Aryan; Ribeiro, Alejandro
2014-12-01
RES, a regularized stochastic version of the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton method is proposed to solve convex optimization problems with stochastic objectives. The use of stochastic gradient descent algorithms is widespread, but the number of iterations required to approximate optimal arguments can be prohibitive in high dimensional problems. Application of second order methods, on the other hand, is impracticable because computation of objective function Hessian inverses incurs excessive computational cost. BFGS modifies gradient descent by introducing a Hessian approximation matrix computed from finite gradient differences. RES utilizes stochastic gradients in lieu of deterministic gradients for both, the determination of descent directions and the approximation of the objective function's curvature. Since stochastic gradients can be computed at manageable computational cost RES is realizable and retains the convergence rate advantages of its deterministic counterparts. Convergence results show that lower and upper bounds on the Hessian egeinvalues of the sample functions are sufficient to guarantee convergence to optimal arguments. Numerical experiments showcase reductions in convergence time relative to stochastic gradient descent algorithms and non-regularized stochastic versions of BFGS. An application of RES to the implementation of support vector machines is developed.
Set-Valued Stochastic Lebesque Integral and Representation Theorems
Directory of Open Access Journals (Sweden)
Jungang Li
2008-06-01
Full Text Available In this paper, we shall firstly illustrate why we should introduce set-valued stochastic integrals, and then we shall discuss some properties of set-valued stochastic processes and the relation between a set-valued stochastic process and its selection set. After recalling the Aumann type definition of stochastic integral, we shall introduce a new definition of Lebesgue integral of a set-valued stochastic process with respect to the time t . Finally we shall prove the presentation theorem of set-valued stochastic integral and dis- cuss further properties that will be useful to study set-valued stochastic differential equations with their applications.
Long-time dynamics of laser-cooled ions in the TSR storage ring
International Nuclear Information System (INIS)
Mudrich, M.
2000-01-01
This diploma thesis studies experimentally the long-time dynamics of laser-cooled 9 Be + -beams at the TSR under different cooling conditions. The goal is to enlarge the understanding of ultra-cold, non-neutral plasma at high center-of-mass energies. By means of improved measurement capabilities one can now for the first time monitor the entire phase-space over a long time. This makes it possible to quantitatively analyse the possibilities and limitations of laser cooling at a storage ring. Under optimum cooling conditions a regime of high phase-space density is reached, close to the region where influences of Coulomb coupling are expected. Furthermore, a Monte-Carlo model is worked out that qualitatively describes the beam dynamics. The model includes the influence of transverse-longitudinal coupling due to intra beam scattering on the longitudinal phase-space distribution. At high phase-space density a sudden disappearance of intra beam collisions is observed experimentally and possible interpretations are given. (orig.)
Stochastic efficiency: five case studies
International Nuclear Information System (INIS)
Proesmans, Karel; Broeck, Christian Van den
2015-01-01
Stochastic efficiency is evaluated in five case studies: driven Brownian motion, effusion with a thermo-chemical and thermo-velocity gradient, a quantum dot and a model for information to work conversion. The salient features of stochastic efficiency, including the maximum of the large deviation function at the reversible efficiency, are reproduced. The approach to and extrapolation into the asymptotic time regime are documented. (paper)
Optimal Liquidation under Stochastic Liquidity
Becherer, Dirk; Bilarev, Todor; Frentrup, Peter
2016-01-01
We solve explicitly a two-dimensional singular control problem of finite fuel type for infinite time horizon. The problem stems from the optimal liquidation of an asset position in a financial market with multiplicative and transient price impact. Liquidity is stochastic in that the volume effect process, which determines the inter-temporal resilience of the market in spirit of Predoiu, Shaikhet and Shreve (2011), is taken to be stochastic, being driven by own random noise. The optimal contro...
Bezuidenhout, Karla; Rensburg, Megan A; Hudson, Careen L; Essack, Younus; Davids, M Razeen
2016-07-01
Many clinical laboratories require that specimens for serum and urine osmolality determination be processed within 3 h of sampling or need to arrive at the laboratory on ice. This protocol is based on the World Health Organization report on sample storage and stability, but the recommendation lacks good supporting data. We studied the effect of storage temperature and time on osmolality measurements. Blood and urine samples were obtained from 16 patients and 25 healthy volunteers. Baseline serum, plasma and urine osmolality measurements were performed within 30 min. Measurements were then made at 3, 6, 12, 24 and 36 h on samples stored at 4-8℃ and room temperature. We compared baseline values with subsequent measurements and used difference plots to illustrate changes in osmolality. At 4-8℃, serum and plasma osmolality were stable for up to 36 h. At room temperature, serum and plasma osmolality were very stable for up to 12 h. At 24 and 36 h, changes from baseline osmolality were statistically significant and exceeded the total allowable error of 1.5% but not the reference change value of 4.1%. Urine osmolality was extremely stable at room temperature with a mean change of less than 1 mosmol/kg at 36 h. Serum and plasma samples can be stored at room temperature for up to 36 h before measuring osmolality. Cooling samples to 4-8℃ may be useful when delays in measurement beyond 12 h are anticipated. Urine osmolality is extremely stable for up to 36 h at room temperature. © The Author(s) 2015.
Gamma irradiation effect and time of storage on the beta-carotene rate of dehydrated parsley
International Nuclear Information System (INIS)
Sebastiao, K.I.; Romanelli, M.F.; Leite, Q.R.; Koseki, P.M.; Hamasaki, K.; Villavicencio, A.L.C.H.; Almeida-Muradian, L.B.
2000-01-01
The A vitamin is an essential nutrient for men. Therefore, this vitamin or one of its precursors must be ingested for a healthful diet. The carotenoids are also called pro-vitamin A. As any another carotenoid, the β-carotene has a structure with many unsaturations, conferring certain instability. It can be modified and even destroyed for acid, light, heat, oxygen; the formation of cis-trans isomers, reduction of its color and its pro-vitacimin A activity reduction can happen. Those alterations can occur during the processing or storage of the food. The use of the ionizing radiation is a kind of food processing that consists of the use of the high energy of the gamma ray or accelerates electrons, capable to ionize molecules. The carotenoids are considered by literature little sensible to the irradiation. It is suggested doses of 1 to 10 kGy in the irradiation of spices, dehydrated condiments and vegetables. These doses are enough to eliminate or to reduce pathogenic microorganisms and insects, to magnify the time of useful life and still substitute the use of chemical fumigants. They also reveal adequate to the organoleptic aspect, not affecting its flavor and smell. This study had as objective to search the different β-carotene levels in samples of dehydrated parsley submitted to the radiation of 60 Co and stored by 6 months. The results gotten in first analysis had not indicated difference significant statistics in β-carotene rate between the controlled sample and the radiated one. After 6 months of storage, were verified that the β-carotene rate had fallen for the half in both samples
Influence of storage times on bond strength of resin cements to root canal
Directory of Open Access Journals (Sweden)
Matheus Coêlho Bandéca
2010-03-01
Full Text Available The resin cements are responsible to retention of the indirect materials decreasing marginal leakage, increasing failure resistance compared with conventional cementation. The cementation within root canal is very hard due unfavorable conditions regarding the application of adhesive techniques caused by inadequate access. Therefore, considering the possibility to decrease steps of cementation, this study was performed to evaluate the bond strength of self-adhesive resin cement (RelyX TM U100, 3M ESPE and resin cement combined with self-ecthing adhesive system (Panavia® F 2.0, Kuraray light-cured with Quartz Tungsten Halogen (QTH following storage at 37 °C immediately after light-curing, 24 and 48 hours and 7 days. The root canals were prepared to receive the glass fiber post in the depth of 10 mm, irrigated with 17% EDTA and NaOCl, rinsed with distilled water and dried using paper points. The roots were perpendicularly sectioned into approximately 1 mm thick sections, obtaining ninety-six slices (n = 12. The slices were trimmed using a cylindrical diamond bur in the proximal surfaces until it touched the post and attached into a device, which were mounted on a strength tester (Bisco and loaded in tension at a speed of 0.5 mm/min until failure occurred at specimens. The analysis of variance (ANOVA and Tukey's post-hoc tests showed significant statistical differences (P .05. The resin cements 24 and 48 hours after light-curing were statistically similar among themselves (P > .05. The both resin cement showed similar bond strength into root canal on different storage times. The highest bond strength values of the resin cements were showed 7 days after curing.
Stochastic temperature and the Nicolai map
International Nuclear Information System (INIS)
Hueffel, H.
1989-01-01
Just as standard temperature can be related to the time coordinate of Euclidean space, a new concept of 'stochastic temperature' may be introduced by associating it to the Parisi-Wu time of stochastic quantization. The perturbative equilibrium limit for a self-interacting scalar field is studied, and a 'thermal' mass shift to one loop is shown. In addition one may interpret the underlying stochastic process as a Nicolai map at nonzero 'temperature'. 22 refs. (Author)
Directory of Open Access Journals (Sweden)
Yanhui Li
2014-01-01
Full Text Available This paper investigates the Hankel norm filter design problem for stochastic time-delay systems, which are represented by Takagi-Sugeno (T-S fuzzy model. Motivated by the parallel distributed compensation (PDC technique, a novel filtering error system is established. The objective is to design a suitable filter that guarantees the corresponding filtering error system to be mean-square asymptotically stable and to have a specified Hankel norm performance level γ. Based on the Lyapunov stability theory and the Itô differential rule, the Hankel norm criterion is first established by adopting the integral inequality method, which can make some useful efforts in reducing conservativeness. The Hankel norm filtering problem is casted into a convex optimization problem with a convex linearization approach, which expresses all the conditions for the existence of admissible Hankel norm filter as standard linear matrix inequalities (LMIs. The effectiveness of the proposed method is demonstrated via a numerical example.
Wang, Jun-Sheng; Yang, Guang-Hong
2017-07-25
This paper studies the optimal output-feedback control problem for unknown linear discrete-time systems with stochastic measurement and process noise. A dithered Bellman equation with the innovation covariance matrix is constructed via the expectation operator given in the form of a finite summation. On this basis, an output-feedback-based approximate dynamic programming method is developed, where the terms depending on the innovation covariance matrix are available with the aid of the innovation covariance matrix identified beforehand. Therefore, by iterating the Bellman equation, the resulting value function can converge to the optimal one in the presence of the aforementioned noise, and the nearly optimal control laws are delivered. To show the effectiveness and the advantages of the proposed approach, a simulation example and a velocity control experiment on a dc machine are employed.
STORAGE TIME EFFECT ON MINI-CUTTINGS ROOTING IN Tectona grandis LINN F. CLONES
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Yorleny Badilla
2017-08-01
Full Text Available ABSTRACT The study aimed to evaluate the influence of storage length on Tectona grandis mini-cuttings survival and rooting. A factorial arrangement (4 x 7 was utilized, based on four clones (Carapá, Ipê, GU5 and TB7 and seven time intervals from mini-cuttings harvesting until final sowing (0, 1, 2, 4, 8, 12 and 16 hours. A randomized block design with three replicates and 16 mini-cuttings per experimental unit was utilized. Survival and rooting rates were evaluated after greenhouse culture (30 days after sowing and after shadow house culture (40 days after sowing; as well as height, collar diameter, aerial and root biomass 55 days after sowing. No significant differences were observed in survival and rooting rates among time intervals in teak mini-cuttings preparation from these four clones. However differences among clones were registered for rooting rate, suggesting a genotypic effect. Survival and rooting rates were very high after greenhouse culture (93% and 90% respectively, as well as survival after culture in a shadow-house (88%.
Indirect Load Control for Energy Storage Systems Using Incentive Pricing under Time-of-Use Tariff
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Mu-Gu Jeong
2016-07-01
Full Text Available Indirect load control (ILC is a method by which the customer determines load reduction of electricity by using a price signal. One of the ILCs is a time-of-use (TOU tariff, which is the most commonly used time-varying retail pricing. Under the TOU tariff, the customer can reduce the energy cost through an energy storage system (ESS. However, because this tariff is fixed for several months, the ESS operation does not truly reflect the wholesale market price, which could widely fluctuate. To overcome this limitation, this paper proposes an incentive pricing method in which the load-serving entity (LSE gives the incentive pricing signal to the customers with ESSs. Because the ESS charging schedule is determined by the customer through ILC, a bilevel optimization problem that includes the customer optimization problem is utilized to determine the incentive pricing signal. Further, the bilevel optimization problem is reformulated into a one-level problem to be solved by an interior point method. In the proposed incentive scheme: (1 the social welfare increases and (2 the increased social welfare can be equitably divided between the LSE and the customer; and (3 the proposed incentive scheme leads the customer to voluntarily follow the pricing signal.
Essentials of stochastic processes
Durrett, Richard
2016-01-01
Building upon the previous editions, this textbook is a first course in stochastic processes taken by undergraduate and graduate students (MS and PhD students from math, statistics, economics, computer science, engineering, and finance departments) who have had a course in probability theory. It covers Markov chains in discrete and continuous time, Poisson processes, renewal processes, martingales, and option pricing. One can only learn a subject by seeing it in action, so there are a large number of examples and more than 300 carefully chosen exercises to deepen the reader’s understanding. Drawing from teaching experience and student feedback, there are many new examples and problems with solutions that use TI-83 to eliminate the tedious details of solving linear equations by hand, and the collection of exercises is much improved, with many more biological examples. Originally included in previous editions, material too advanced for this first course in stochastic processes has been eliminated while treatm...
Multistage stochastic optimization
Pflug, Georg Ch
2014-01-01
Multistage stochastic optimization problems appear in many ways in finance, insurance, energy production and trading, logistics and transportation, among other areas. They describe decision situations under uncertainty and with a longer planning horizon. This book contains a comprehensive treatment of today’s state of the art in multistage stochastic optimization. It covers the mathematical backgrounds of approximation theory as well as numerous practical algorithms and examples for the generation and handling of scenario trees. A special emphasis is put on estimation and bounding of the modeling error using novel distance concepts, on time consistency and the role of model ambiguity in the decision process. An extensive treatment of examples from electricity production, asset liability management and inventory control concludes the book
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
In this paper, the stochastic flow of mappings generated by a Feller convolution semigroup on a compact metric space is studied. This kind of flow is the generalization of superprocesses of stochastic flows and stochastic diffeomorphism induced by the strong solutions of stochastic differential equations.
The zeatin content of tomatoes as a function of the degree of ripeness, irradiation and storage time
International Nuclear Information System (INIS)
Kovacs, E.; Voeroes, Zs.
1975-01-01
The zeatin content of the San Marzano variety tomatoes was studied as a function of their degree of ripeness (fruitlet, green fruit, pink fruit, red fruit), storage time (at 20-23 deg C and 40-50% RH) and radiation treatment (4 krad). The zeatin content of tomatoes determined by thin-layer chromatography decreased with the advancement of ripening. The zeatin content of freshly picked pink tomatoes increased immediately upon radiation treatment with 4 krad. After 9 day storage the zeatin content of both irradiated and untreated tomato samples decreased during the 9-day storage time. On the 9th day the zeatin content of the irradiated tomatoes was 20% higher than that of the untreated ones. (F.J.)
Stochastic Model of TCP SYN Attacks
Directory of Open Access Journals (Sweden)
Simona Ramanauskaitė
2011-08-01
Full Text Available A great proportion of essential services are moving into internet space making the threat of DoS attacks even more actual. To estimate the real risk of some kind of denial of service (DoS attack in real world is difficult, but mathematical and software models make this task easier. In this paper we overview the ways of implementing DoS attack models and offer a stochastic model of SYN flooding attack. It allows evaluating the potential threat of SYN flooding attacks, taking into account both the legitimate system flow as well as the possible attack power. At the same time we can assess the effect of such parameters as buffer capacity, open connection storage in the buffer or filtering efficiency on the success of different SYN flooding attacks. This model can be used for other type of memory depletion denial of service attacks.Article in Lithuanian
Long-time storage of song types in birds: evidence from interactive playbacks.
Geberzahn, Nicole; Hultsch, Henrike
2003-05-22
In studies of birdsong learning, imitation-based assays of stimulus memorization do not take into account that tutored song types may have been stored, but were not retrieved from memory. Such a 'silent' reservoir of song material could be used later in the bird's life, e.g. during vocal interactions. We examined this possibility in hand-reared nightingales during their second year. The males had been exposed to songs, both as fledglings and later, during their first full song period in an interactive playback design. Our design allowed us to compare the performance of imitations from the following categories: (i) songs only experienced during the early tutoring; (ii) songs experienced both during early tutoring and interactive playbacks; and (iii) novel songs experienced only during the simulated interactions. In their second year, birds imitated song types from each category, including those from categories (i) and (ii) which they had failed to imitate before. In addition, the performance of these song types was different (category (ii) > category (i)) and more pronounced than for category (iii) songs. Our results demonstrate 'silent' song storage in nightingales and point to a graded influence of the time and the social context of experience on subsequent vocal imitation.
Effects of shorter versus longer storage time of transfused red blood cells in adult ICU patients
DEFF Research Database (Denmark)
Rygård, Sofie L; Jonsson, Andreas B; Madsen, Martin B
2018-01-01
on the effects of shorter versus longer storage time of transfused RBCs on outcomes in ICU patients. METHODS: We conducted a systematic review with meta-analyses and trial sequential analyses (TSA) of randomised clinical trials including adult ICU patients transfused with fresher versus older or standard issue...... blood. RESULTS: We included seven trials with a total of 18,283 randomised ICU patients; two trials of 7504 patients were judged to have low risk of bias. We observed no effects of fresher versus older blood on death (relative risk 1.04, 95% confidence interval (CI) 0.97-1.11; 7349 patients; TSA......-adjusted CI 0.93-1.15), adverse events (1.26, 0.76-2.09; 7332 patients; TSA-adjusted CI 0.16-9.87) or post-transfusion infections (1.07, 0.96-1.20; 7332 patients; TSA-adjusted CI 0.90-1.27). The results were unchanged by including trials with high risk of bias. TSA confirmed the results and the required...
Seminario, Diana M; Balaban, Murat O; Rodrick, Gary
2011-03-01
Vibrio vulnificus (Vv) is a pathogen that can be found in raw oysters. Freezing can reduce Vv and increase the shelf life of oysters. The objective of this study was to develop predictive inactivation kinetic models for pure cultures of Vv at different frozen storage temperatures and times. Vv was diluted in phosphate-buffered saline (PBS) to obtain about 10(7) CFU/mL. Samples were frozen at -10, -35, and -80 °C (different freezing rates), and stored at different temperatures. Survival of Vv was followed after freezing and storage at -10 °C (0, 3, 6, and 9 d) and at -35 and -80 °C (every week for 6 wk). For every treatment, time-temperature data was obtained using thermocouples in blank vials. Predictive models were developed using first-order, Weibull and Peleg inactivation kinetics. Different freezing temperatures did not significantly (α = 0.05) affect survival of Vv immediately after freezing. The combined effect of freezing and 1 wk frozen storage resulted in 1.5, 2.6, and 4.9 log10 reductions for samples stored at -80, -35, and -10 °C, respectively. Storage temperature was the critical parameter in survival of Vv. A modified Weibull model successfully predicted Vv survival during frozen storage: log10 Nt = log 10No - 1.22 - ([t/10{-1.163-0.0466T}][0.00025T(2) + 0.049325]). N(o) and N(t) are initial and time t (d) survival counts, T is frozen storage temperature, Celsius degree. Vibrio vulnificus can be inactivated by freezing. Models to predict survival of V. vulnificus at different freezing temperatures and times were developed. This is the first step towards the prediction of V. vulnificus related safety of frozen oysters.
Directory of Open Access Journals (Sweden)
Sareh Habibzadeh
2016-10-01
Full Text Available Objectives: This study aimed to assess the effect of storage time and temperature on dimensional stability of impressions made with Cavex Outline zinc oxide impression paste.Materials and Methods: A round stainless steel mold with five grooves (three horizontal and two vertical was used in this in-vitro experimental study. Cavex Outline impression paste was prepared according to the manufacturer’s instructions and applied to the mold. The mold was placed on a block and stored at 35°C and 100% humidity for setting. The impressions were poured with stone immediately and also after 30, 120, 240 and 420 minutes and 24 hours. The distance between the vertical lines on the casts was measured and compared with that in the immediately poured cast.Results: Storage in a refrigerator and at room temperature for zero to seven hours had no significant effect on dimensional stability of the impressions; however, 24 hours of storage in a refrigerator or at room temperature decreased the dimensional stability of Cavex Outline (P=0.001. Also, a significant association was found between dimensional changes following 24 hours of storage in a refrigerator (4°C and at room temperature (23°C; P<0.01.Conclusions: The optimal pouring time of Cavex Outline impressions with stone is between zero to seven hours, and 24 hours of storage significantly decreases the dimensional stability.Keywords: Dental Impression Materials; Zinc Oxide; Cavex
do Nascimento, Cássio; dos Santos, Janine Navarro; Pedrazzi, Vinícius; Pita, Murillo Sucena; Monesi, Nadia; Ribeiro, Ricardo Faria; de Albuquerque, Rubens Ferreira
2014-01-01
Molecular diagnosis methods have been largely used in epidemiological or clinical studies to detect and quantify microbial species that may colonize the oral cavity in healthy or disease. The preservation of genetic material from samples remains the major challenge to ensure the feasibility of these methodologies. Long-term storage may compromise the final result. The aim of this study was to evaluate the effect of temperature and time storage on the microbial detection of oral samples by Checkerboard DNA-DNA hybridization. Saliva and supragingival biofilm were taken from 10 healthy subjects, aliquoted (n=364) and processed according to proposed protocols: immediate processing and processed after 2 or 4 weeks, and 6 or 12 months of storage at 4°C, -20°C and -80°C. Either total or individual microbial counts were recorded in lower values for samples processed after 12 months of storage, irrespective of temperatures tested. Samples stored up to 6 months at cold temperatures showed similar counts to those immediately processed. The microbial incidence was also significantly reduced in samples stored during 12 months in all temperatures. Temperature and time of oral samples storage have relevant impact in the detection and quantification of bacterial and fungal species by Checkerboard DNA-DNA hybridization method. Samples should be processed immediately after collection or up to 6 months if conserved at cold temperatures to avoid false-negative results. Copyright © 2013 Elsevier Ltd. All rights reserved.