The Supermarket Model with Bounded Queue Lengths in Equilibrium

NASA Astrophysics Data System (ADS)

Brightwell, Graham; Fairthorne, Marianne; Luczak, Malwina J.

2018-04-01

In the supermarket model, there are n queues, each with a single server. Customers arrive in a Poisson process with arrival rate λ n , where λ = λ (n) \\in (0,1) . Upon arrival, a customer selects d=d(n) servers uniformly at random, and joins the queue of a least-loaded server amongst those chosen. Service times are independent exponentially distributed random variables with mean 1. In this paper, we analyse the behaviour of the supermarket model in the regime where λ (n) = 1 - n^{-α } and d(n) = \\lfloor n^β \\rfloor , where α and β are fixed numbers in (0, 1]. For suitable pairs (α , β ) , our results imply that, in equilibrium, with probability tending to 1 as n → ∞, the proportion of queues with length equal to k = \\lceil α /β \\rceil is at least 1-2n^{-α + (k-1)β } , and there are no longer queues. We further show that the process is rapidly mixing when started in a good state, and give bounds on the speed of mixing for more general initial conditions.

A heuristic method for consumable resource allocation in multi-class dynamic PERT networks

NASA Astrophysics Data System (ADS)

Yaghoubi, Saeed; Noori, Siamak; Mazdeh, Mohammad Mahdavi

2013-06-01

This investigation presents a heuristic method for consumable resource allocation problem in multi-class dynamic Project Evaluation and Review Technique (PERT) networks, where new projects from different classes (types) arrive to system according to independent Poisson processes with different arrival rates. Each activity of any project is operated at a devoted service station located in a node of the network with exponential distribution according to its class. Indeed, each project arrives to the first service station and continues its routing according to precedence network of its class. Such system can be represented as a queuing network, while the discipline of queues is first come, first served. On the basis of presented method, a multi-class system is decomposed into several single-class dynamic PERT networks, whereas each class is considered separately as a minisystem. In modeling of single-class dynamic PERT network, we use Markov process and a multi-objective model investigated by Azaron and Tavakkoli-Moghaddam in 2007. Then, after obtaining the resources allocated to service stations in every minisystem, the final resources allocated to activities are calculated by the proposed method.

Application of a deconvolution method for identifying burst amplitudes and arrival times in Alcator C-Mod far SOL plasma fluctuations

NASA Astrophysics Data System (ADS)

Theodorsen, Audun; Garcia, Odd Erik; Kube, Ralph; Labombard, Brian; Terry, Jim

2017-10-01

In the far scrape-off layer (SOL), radial motion of filamentary structures leads to excess transport of particles and heat. Amplitudes and arrival times of these filaments have previously been studied by conditional averaging in single-point measurements from Langmuir Probes and Gas Puff Imaging (GPI). Conditional averaging can be problematic: the cutoff for large amplitudes is mostly chosen by convention; the conditional windows used may influence the arrival time distribution; and the amplitudes cannot be separated from a background. Previous work has shown that SOL fluctuations are well described by a stochastic model consisting of a super-position of pulses with fixed shape and randomly distributed amplitudes and arrival times. The model can be formulated as a pulse shape convolved with a train of delta pulses. By choosing a pulse shape consistent with the power spectrum of the fluctuation time series, Richardson-Lucy deconvolution can be used to recover the underlying amplitudes and arrival times of the delta pulses. We apply this technique to both L and H-mode GPI data from the Alcator C-Mod tokamak. The pulse arrival times are shown to be uncorrelated and uniformly distributed, consistent with a Poisson process, and the amplitude distribution has an exponential tail.

Probabilistic SSME blades structural response under random pulse loading

NASA Technical Reports Server (NTRS)

Shiao, Michael; Rubinstein, Robert; Nagpal, Vinod K.

1987-01-01

The purpose is to develop models of random impacts on a Space Shuttle Main Engine (SSME) turbopump blade and to predict the probabilistic structural response of the blade to these impacts. The random loading is caused by the impact of debris. The probabilistic structural response is characterized by distribution functions for stress and displacements as functions of the loading parameters which determine the random pulse model. These parameters include pulse arrival, amplitude, and location. The analysis can be extended to predict level crossing rates. This requires knowledge of the joint distribution of the response and its derivative. The model of random impacts chosen allows the pulse arrivals, pulse amplitudes, and pulse locations to be random. Specifically, the pulse arrivals are assumed to be governed by a Poisson process, which is characterized by a mean arrival rate. The pulse intensity is modelled as a normally distributed random variable with a zero mean chosen independently at each arrival. The standard deviation of the distribution is a measure of pulse intensity. Several different models were used for the pulse locations. For example, three points near the blade tip were chosen at which pulses were allowed to arrive with equal probability. Again, the locations were chosen independently at each arrival. The structural response was analyzed both by direct Monte Carlo simulation and by a semi-analytical method.

A comprehensive review of prehospital and in-hospital delay times in acute stroke care.

PubMed

Evenson, K R; Foraker, R E; Morris, D L; Rosamond, W D

2009-06-01

The purpose of this study was to systematically review and summarize prehospital and in-hospital stroke evaluation and treatment delay times. We identified 123 unique peer-reviewed studies published from 1981 to 2007 of prehospital and in-hospital delay time for evaluation and treatment of patients with stroke, transient ischemic attack, or stroke-like symptoms. Based on studies of 65 different population groups, the weighted Poisson regression indicated a 6.0% annual decline (P<0.001) in hours/year for prehospital delay, defined from symptom onset to emergency department arrival. For in-hospital delay, the weighted Poisson regression models indicated no meaningful changes in delay time from emergency department arrival to emergency department evaluation (3.1%, P=0.49 based on 12 population groups). There was a 10.2% annual decline in hours/year from emergency department arrival to neurology evaluation or notification (P=0.23 based on 16 population groups) and a 10.7% annual decline in hours/year for delay time from emergency department arrival to initiation of computed tomography (P=0.11 based on 23 population groups). Only one study reported on times from arrival to computed tomography scan interpretation, two studies on arrival to drug administration, and no studies on arrival to transfer to an in-patient setting, precluding generalizations. Prehospital delay continues to contribute the largest proportion of delay time. The next decade provides opportunities to establish more effective community-based interventions worldwide. It will be crucial to have effective stroke surveillance systems in place to better understand and improve both prehospital and in-hospital delays for acute stroke care.

Interplay between spatially explicit sediment sourcing, hierarchical river-network structure, and in-channel bed material sediment transport and storage dynamics

NASA Astrophysics Data System (ADS)

Czuba, Jonathan A.; Foufoula-Georgiou, Efi; Gran, Karen B.; Belmont, Patrick; Wilcock, Peter R.

2017-05-01

Understanding how sediment moves along source to sink pathways through watersheds—from hillslopes to channels and in and out of floodplains—is a fundamental problem in geomorphology. We contribute to advancing this understanding by modeling the transport and in-channel storage dynamics of bed material sediment on a river network over a 600 year time period. Specifically, we present spatiotemporal changes in bed sediment thickness along an entire river network to elucidate how river networks organize and process sediment supply. We apply our model to sand transport in the agricultural Greater Blue Earth River Basin in Minnesota. By casting the arrival of sediment to links of the network as a Poisson process, we derive analytically (under supply-limited conditions) the time-averaged probability distribution function of bed sediment thickness for each link of the river network for any spatial distribution of inputs. Under transport-limited conditions, the analytical assumptions of the Poisson arrival process are violated (due to in-channel storage dynamics) where we find large fluctuations and periodicity in the time series of bed sediment thickness. The time series of bed sediment thickness is the result of dynamics on a network in propagating, altering, and amalgamating sediment inputs in sometimes unexpected ways. One key insight gleaned from the model is that there can be a small fraction of reaches with relatively low-transport capacity within a nonequilibrium river network acting as "bottlenecks" that control sediment to downstream reaches, whereby fluctuations in bed elevation can dissociate from signals in sediment supply.

Five easy equations for patient flow through an emergency department.

PubMed

Madsen, Thomas Lill; Kofoed-Enevoldsen, Allan

2011-10-01

Queue models are effective tools for framing management decisions and Danish hospitals could benefit from awareness of such models. Currently, as emergency departments (ED) are under reorganization, we deem it timely to empirically investigate the applicability of the standard "M/M/1" queue model in order to document its relevance. We compared actual versus theoretical distributions of hourly patient flow from 27,000 patient cases seen at Frederiksberg Hospital's ED. Formulating equations for arrivals and capacity, we wrote and tested a five equation simulation model. The Poisson distribution fitted arrivals with an hour-of-the-day specific parameter. Treatment times exceeding 15 minutes were well-described by an exponential distribution. The ED can be modelled as a black box with an hourly capacity that can be estimated either as admissions per hour when the ED operates full hilt Poisson distribution or from the linear dependency of waiting times on queue number. The results show that our ED capacity is surprisingly constant despite variations in staffing. These findings led to the formulation of a model giving a compact framework for assessing the behaviour of the ED under different assumptions about opening hours, capacity and workload. The M/M/1 almost perfectly fits our. Thus modeling and simulations have contributed to the management process. not relevant. not relevant.

Analysis and modeling of optical crosstalk in InP-based Geiger-mode avalanche photodiode FPAs

NASA Astrophysics Data System (ADS)

Chau, Quan; Jiang, Xudong; Itzler, Mark A.; Entwistle, Mark; Piccione, Brian; Owens, Mark; Slomkowski, Krystyna

2015-05-01

Optical crosstalk is a major factor limiting the performance of Geiger-mode avalanche photodiode (GmAPD) focal plane arrays (FPAs). This is especially true for arrays with increased pixel density and broader spectral operation. We have performed extensive experimental and theoretical investigations on the crosstalk effects in InP-based GmAPD FPAs for both 1.06-μm and 1.55-μm applications. Mechanisms responsible for intrinsic dark counts are Poisson processes, and their inter-arrival time distribution is an exponential function. In FPAs, intrinsic dark counts and cross talk events coexist, and the inter-arrival time distribution deviates from purely exponential behavior. From both experimental data and computer simulations, we show the dependence of this deviation on the crosstalk probability. The spatial characteristics of crosstalk are also demonstrated. From the temporal and spatial distribution of crosstalk, an efficient algorithm to identify and quantify crosstalk is introduced.

Performance characteristics of a batch service queueing system with functioning server failure and multiple vacations

NASA Astrophysics Data System (ADS)

Niranjan, S. P.; Chandrasekaran, V. M.; Indhira, K.

2018-04-01

This paper examines bulk arrival and batch service queueing system with functioning server failure and multiple vacations. Customers are arriving into the system in bulk according to Poisson process with rate λ. Arriving customers are served in batches with minimum of ‘a’ and maximum of ‘b’ number of customers according to general bulk service rule. In the service completion epoch if the queue length is less than ‘a’ then the server leaves for vacation (secondary job) of random length. After a vacation completion, if the queue length is still less than ‘a’ then the server leaves for another vacation. The server keeps on going vacation until the queue length reaches the value ‘a’. The server is not stable at all the times. Sometimes it may fails during functioning of customers. Though the server fails service process will not be interrupted.It will be continued for the current batch of customers with lower service rate than the regular service rate. The server will be repaired after the service completion with lower service rate. The probability generating function of the queue size at an arbitrary time epoch will be obtained for the modelled queueing system by using supplementary variable technique. Moreover various performance characteristics will also be derived with suitable numerical illustrations.

Quantitative model of price diffusion and market friction based on trading as a mechanistic random process.

PubMed

Daniels, Marcus G; Farmer, J Doyne; Gillemot, László; Iori, Giulia; Smith, Eric

2003-03-14

We model trading and price formation in a market under the assumption that order arrival and cancellations are Poisson random processes. This model makes testable predictions for the most basic properties of markets, such as the diffusion rate of prices (which is the standard measure of financial risk) and the spread and price impact functions (which are the main determinants of transaction cost). Guided by dimensional analysis, simulation, and mean-field theory, we find scaling relations in terms of order flow rates. We show that even under completely random order flow the need to store supply and demand to facilitate trading induces anomalous diffusion and temporal structure in prices.

Quantitative Model of Price Diffusion and Market Friction Based on Trading as a Mechanistic Random Process

NASA Astrophysics Data System (ADS)

Daniels, Marcus G.; Farmer, J. Doyne; Gillemot, László; Iori, Giulia; Smith, Eric

2003-03-01

We model trading and price formation in a market under the assumption that order arrival and cancellations are Poisson random processes. This model makes testable predictions for the most basic properties of markets, such as the diffusion rate of prices (which is the standard measure of financial risk) and the spread and price impact functions (which are the main determinants of transaction cost). Guided by dimensional analysis, simulation, and mean-field theory, we find scaling relations in terms of order flow rates. We show that even under completely random order flow the need to store supply and demand to facilitate trading induces anomalous diffusion and temporal structure in prices.

On the delay analysis of a TDMA channel with finite buffer capacity

NASA Technical Reports Server (NTRS)

Yan, T.-Y.

1982-01-01

The throughput performance of a TDMA channel with finite buffer capacity for transmitting data messages is considered. Each station has limited message buffer capacity and has Poisson message arrivals. Message arrivals will be blocked if the buffers are congested. Using the embedded Markov chain model, the solution procedure for the limiting system-size probabilities is presented in a recursive fashion. Numerical examples are given to demonstrate the tradeoffs between the blocking probabilities and the buffer sizing strategy.

Improving Bed Management at Wright-Patterson Medical Center

DTIC Science & Technology

1989-09-01

arrival distributions are Poisson, as in Sim2, then interarrival times are distributed exponentially (Budnick, Mcleavey , and Mojena, 1988:770). While... McLeavey , D. and Mojena R., Principles of Operations Research for Management (second edition). Homewood IL: Irwin, 1988. Cannoodt, L. J. and

DISCRETE COMPOUND POISSON PROCESSES AND TABLES OF THE GEOMETRIC POISSON DISTRIBUTION.

DTIC Science & Technology

A concise summary of the salient properties of discrete Poisson processes , with emphasis on comparing the geometric and logarithmic Poisson processes . The...the geometric Poisson process are given for 176 sets of parameter values. New discrete compound Poisson processes are also introduced. These...processes have properties that are particularly relevant when the summation of several different Poisson processes is to be analyzed. This study provides the

Vesicle Motion during Sustained Exocytosis in Chromaffin Cells: Numerical Model Based on Amperometric Measurements.

PubMed

Jarukanont, Daungruthai; Bonifas Arredondo, Imelda; Femat, Ricardo; Garcia, Martin E

2015-01-01

Chromaffin cells release catecholamines by exocytosis, a process that includes vesicle docking, priming and fusion. Although all these steps have been intensively studied, some aspects of their mechanisms, particularly those regarding vesicle transport to the active sites situated at the membrane, are still unclear. In this work, we show that it is possible to extract information on vesicle motion in Chromaffin cells from the combination of Langevin simulations and amperometric measurements. We developed a numerical model based on Langevin simulations of vesicle motion towards the cell membrane and on the statistical analysis of vesicle arrival times. We also performed amperometric experiments in bovine-adrenal Chromaffin cells under Ba2+ stimulation to capture neurotransmitter releases during sustained exocytosis. In the sustained phase, each amperometric peak can be related to a single release from a new vesicle arriving at the active site. The amperometric signal can then be mapped into a spike-series of release events. We normalized the spike-series resulting from the current peaks using a time-rescaling transformation, thus making signals coming from different cells comparable. We discuss why the obtained spike-series may contain information about the motion of all vesicles leading to release of catecholamines. We show that the release statistics in our experiments considerably deviate from Poisson processes. Moreover, the interspike-time probability is reasonably well described by two-parameter gamma distributions. In order to interpret this result we computed the vesicles' arrival statistics from our Langevin simulations. As expected, assuming purely diffusive vesicle motion we obtain Poisson statistics. However, if we assume that all vesicles are guided toward the membrane by an attractive harmonic potential, simulations also lead to gamma distributions of the interspike-time probability, in remarkably good agreement with experiment. We also show that including the fusion-time statistics in our model does not produce any significant changes on the results. These findings indicate that the motion of the whole ensemble of vesicles towards the membrane is directed and reflected in the amperometric signals. Our results confirm the conclusions of previous imaging studies performed on single vesicles that vesicles' motion underneath plasma membranes is not purely random, but biased towards the membrane.

Vesicle Motion during Sustained Exocytosis in Chromaffin Cells: Numerical Model Based on Amperometric Measurements

PubMed Central

Jarukanont, Daungruthai; Bonifas Arredondo, Imelda; Femat, Ricardo; Garcia, Martin E.

2015-01-01

Chromaffin cells release catecholamines by exocytosis, a process that includes vesicle docking, priming and fusion. Although all these steps have been intensively studied, some aspects of their mechanisms, particularly those regarding vesicle transport to the active sites situated at the membrane, are still unclear. In this work, we show that it is possible to extract information on vesicle motion in Chromaffin cells from the combination of Langevin simulations and amperometric measurements. We developed a numerical model based on Langevin simulations of vesicle motion towards the cell membrane and on the statistical analysis of vesicle arrival times. We also performed amperometric experiments in bovine-adrenal Chromaffin cells under Ba2+ stimulation to capture neurotransmitter releases during sustained exocytosis. In the sustained phase, each amperometric peak can be related to a single release from a new vesicle arriving at the active site. The amperometric signal can then be mapped into a spike-series of release events. We normalized the spike-series resulting from the current peaks using a time-rescaling transformation, thus making signals coming from different cells comparable. We discuss why the obtained spike-series may contain information about the motion of all vesicles leading to release of catecholamines. We show that the release statistics in our experiments considerably deviate from Poisson processes. Moreover, the interspike-time probability is reasonably well described by two-parameter gamma distributions. In order to interpret this result we computed the vesicles’ arrival statistics from our Langevin simulations. As expected, assuming purely diffusive vesicle motion we obtain Poisson statistics. However, if we assume that all vesicles are guided toward the membrane by an attractive harmonic potential, simulations also lead to gamma distributions of the interspike-time probability, in remarkably good agreement with experiment. We also show that including the fusion-time statistics in our model does not produce any significant changes on the results. These findings indicate that the motion of the whole ensemble of vesicles towards the membrane is directed and reflected in the amperometric signals. Our results confirm the conclusions of previous imaging studies performed on single vesicles that vesicles’ motion underneath plasma membranes is not purely random, but biased towards the membrane. PMID:26675312

Counting Raindrops and the Distribution of Intervals Between Them.

NASA Astrophysics Data System (ADS)

Van De Giesen, N.; Ten Veldhuis, M. C.; Hut, R.; Pape, J. J.

2017-12-01

Drop size distributions are often assumed to follow a generalized gamma function, characterized by one parameter, Λ, [1]. In principle, this Λ can be estimated by measuring the arrival rate of raindrops. The arrival rate should follow a Poisson distribution. By measuring the distribution of the time intervals between drops arriving at a certain surface area, one should not only be able to estimate the arrival rate but also the robustness of the underlying assumption concerning steady state. It is important to note that many rainfall radar systems also assume fixeddrop size distributions, and associated arrival rates, to derive rainfall rates. By testing these relationships with a simple device, we will be able to improve both land-based and space-based radar rainfall estimates. Here, an open-hardware sensor design is presented, consisting of a 3D printed housing for a piezoelectric element, some simple electronics and an Arduino. The target audience for this device are citizen scientists who want to contribute to collecting rainfall information beyond the standard rain gauge. The core of the sensor is a simple piezo-buzzer, as found in many devices such as watches and fire alarms. When a raindrop falls on a piezo-buzzer, a small voltage is generated , which can be used to register the drop's arrival time. By registering the intervals between raindrops, the associated Poisson distribution can be estimated. In addition to the hardware, we will present the first results of a measuring campaign in Myanmar that will have ran from August to October 2017. All design files and descriptions are available through GitHub: https://github.com/nvandegiesen/Intervalometer. This research is partially supported through the TWIGA project, funded by the European Commission's H2020 program under call SC5-18-2017 `Novel in-situ observation systems'. Reference [1]: Uijlenhoet, R., and J. N. M. Stricker. "A consistent rainfall parameterization based on the exponential raindrop size distribution." Journal of Hydrology 218, no. 3 (1999): 101-127.

Analytical results for a stochastic model of gene expression with arbitrary partitioning of proteins

NASA Astrophysics Data System (ADS)

Tschirhart, Hugo; Platini, Thierry

2018-05-01

In biophysics, the search for analytical solutions of stochastic models of cellular processes is often a challenging task. In recent work on models of gene expression, it was shown that a mapping based on partitioning of Poisson arrivals (PPA-mapping) can lead to exact solutions for previously unsolved problems. While the approach can be used in general when the model involves Poisson processes corresponding to creation or degradation, current applications of the method and new results derived using it have been limited to date. In this paper, we present the exact solution of a variation of the two-stage model of gene expression (with time dependent transition rates) describing the arbitrary partitioning of proteins. The methodology proposed makes full use of the PPA-mapping by transforming the original problem into a new process describing the evolution of three biological switches. Based on a succession of transformations, the method leads to a hierarchy of reduced models. We give an integral expression of the time dependent generating function as well as explicit results for the mean, variance, and correlation function. Finally, we discuss how results for time dependent parameters can be extended to the three-stage model and used to make inferences about models with parameter fluctuations induced by hidden stochastic variables.

Properties of the Bivariate Delayed Poisson Process

DTIC Science & Technology

1974-07-01

and Lewis (1972) in their Berkeley Symposium paper and here their analysis of the bivariate Poisson processes (without Poisson noise) is carried... Poisson processes . They cannot, however, be independent Poisson processes because their events are associated in pairs by the displace- ment centres...process because its marginal processes for events of each type are themselves (univariate) Poisson processes . Cox and Lewis (1972) assumed a

Maximum likelihood-based analysis of single-molecule photon arrival trajectories

NASA Astrophysics Data System (ADS)

Hajdziona, Marta; Molski, Andrzej

2011-02-01

In this work we explore the statistical properties of the maximum likelihood-based analysis of one-color photon arrival trajectories. This approach does not involve binning and, therefore, all of the information contained in an observed photon strajectory is used. We study the accuracy and precision of parameter estimates and the efficiency of the Akaike information criterion and the Bayesian information criterion (BIC) in selecting the true kinetic model. We focus on the low excitation regime where photon trajectories can be modeled as realizations of Markov modulated Poisson processes. The number of observed photons is the key parameter in determining model selection and parameter estimation. For example, the BIC can select the true three-state model from competing two-, three-, and four-state kinetic models even for relatively short trajectories made up of 2 × 103 photons. When the intensity levels are well-separated and 104 photons are observed, the two-state model parameters can be estimated with about 10% precision and those for a three-state model with about 20% precision.

Estimating random errors due to shot noise in backscatter lidar observations.

PubMed

Liu, Zhaoyan; Hunt, William; Vaughan, Mark; Hostetler, Chris; McGill, Matthew; Powell, Kathleen; Winker, David; Hu, Yongxiang

2006-06-20

We discuss the estimation of random errors due to shot noise in backscatter lidar observations that use either photomultiplier tube (PMT) or avalanche photodiode (APD) detectors. The statistical characteristics of photodetection are reviewed, and photon count distributions of solar background signals and laser backscatter signals are examined using airborne lidar observations at 532 nm using a photon-counting mode APD. Both distributions appear to be Poisson, indicating that the arrival at the photodetector of photons for these signals is a Poisson stochastic process. For Poisson- distributed signals, a proportional, one-to-one relationship is known to exist between the mean of a distribution and its variance. Although the multiplied photocurrent no longer follows a strict Poisson distribution in analog-mode APD and PMT detectors, the proportionality still exists between the mean and the variance of the multiplied photocurrent. We make use of this relationship by introducing the noise scale factor (NSF), which quantifies the constant of proportionality that exists between the root mean square of the random noise in a measurement and the square root of the mean signal. Using the NSF to estimate random errors in lidar measurements due to shot noise provides a significant advantage over the conventional error estimation techniques, in that with the NSF, uncertainties can be reliably calculated from or for a single data sample. Methods for evaluating the NSF are presented. Algorithms to compute the NSF are developed for the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations lidar and tested using data from the Lidar In-space Technology Experiment.

Estimating Random Errors Due to Shot Noise in Backscatter Lidar Observations

NASA Technical Reports Server (NTRS)

Liu, Zhaoyan; Hunt, William; Vaughan, Mark A.; Hostetler, Chris A.; McGill, Matthew J.; Powell, Kathy; Winker, David M.; Hu, Yongxiang

2006-01-01

In this paper, we discuss the estimation of random errors due to shot noise in backscatter lidar observations that use either photomultiplier tube (PMT) or avalanche photodiode (APD) detectors. The statistical characteristics of photodetection are reviewed, and photon count distributions of solar background signals and laser backscatter signals are examined using airborne lidar observations at 532 nm using a photon-counting mode APD. Both distributions appear to be Poisson, indicating that the arrival at the photodetector of photons for these signals is a Poisson stochastic process. For Poisson-distributed signals, a proportional, one-to-one relationship is known to exist between the mean of a distribution and its variance. Although the multiplied photocurrent no longer follows a strict Poisson distribution in analog-mode APD and PMT detectors, the proportionality still exists between the mean and the variance of the multiplied photocurrent. We make use of this relationship by introducing the noise scale factor (NSF), which quantifies the constant of proportionality that exists between the root-mean-square of the random noise in a measurement and the square root of the mean signal. Using the NSF to estimate random errors in lidar measurements due to shot noise provides a significant advantage over the conventional error estimation techniques, in that with the NSF uncertainties can be reliably calculated from/for a single data sample. Methods for evaluating the NSF are presented. Algorithms to compute the NSF are developed for the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar and tested using data from the Lidar In-space Technology Experiment (LITE). OCIS Codes:

On the fractal characterization of Paretian Poisson processes

NASA Astrophysics Data System (ADS)

Eliazar, Iddo I.; Sokolov, Igor M.

2012-06-01

Paretian Poisson processes are Poisson processes which are defined on the positive half-line, have maximal points, and are quantified by power-law intensities. Paretian Poisson processes are elemental in statistical physics, and are the bedrock of a host of power-law statistics ranging from Pareto's law to anomalous diffusion. In this paper we establish evenness-based fractal characterizations of Paretian Poisson processes. Considering an array of socioeconomic evenness-based measures of statistical heterogeneity, we show that: amongst the realm of Poisson processes which are defined on the positive half-line, and have maximal points, Paretian Poisson processes are the unique class of 'fractal processes' exhibiting scale-invariance. The results established in this paper are diametric to previous results asserting that the scale-invariance of Poisson processes-with respect to physical randomness-based measures of statistical heterogeneity-is characterized by exponential Poissonian intensities.

The effect of model uncertainty on some optimal routing problems

NASA Technical Reports Server (NTRS)

Mohanty, Bibhu; Cassandras, Christos G.

1991-01-01

The effect of model uncertainties on optimal routing in a system of parallel queues is examined. The uncertainty arises in modeling the service time distribution for the customers (jobs, packets) to be served. For a Poisson arrival process and Bernoulli routing, the optimal mean system delay generally depends on the variance of this distribution. However, as the input traffic load approaches the system capacity the optimal routing assignment and corresponding mean system delay are shown to converge to a variance-invariant point. The implications of these results are examined in the context of gradient-based routing algorithms. An example of a model-independent algorithm using online gradient estimation is also included.

Characterization of Nonhomogeneous Poisson Processes Via Moment Conditions.

DTIC Science & Technology

1986-08-01

Poisson processes play an important role in many fields. The Poisson process is one of the simplest counting processes and is a building block for...place of independent increments. This provides a somewhat different viewpoint for examining Poisson processes . In addition, new characterizations for

NEWTPOIS- NEWTON POISSON DISTRIBUTION PROGRAM

NASA Technical Reports Server (NTRS)

Bowerman, P. N.

1994-01-01

The cumulative poisson distribution program, NEWTPOIS, is one of two programs which make calculations involving cumulative poisson distributions. Both programs, NEWTPOIS (NPO-17715) and CUMPOIS (NPO-17714), can be used independently of one another. NEWTPOIS determines percentiles for gamma distributions with integer shape parameters and calculates percentiles for chi-square distributions with even degrees of freedom. It can be used by statisticians and others concerned with probabilities of independent events occurring over specific units of time, area, or volume. NEWTPOIS determines the Poisson parameter (lambda), that is; the mean (or expected) number of events occurring in a given unit of time, area, or space. Given that the user already knows the cumulative probability for a specific number of occurrences (n) it is usually a simple matter of substitution into the Poisson distribution summation to arrive at lambda. However, direct calculation of the Poisson parameter becomes difficult for small positive values of n and unmanageable for large values. NEWTPOIS uses Newton's iteration method to extract lambda from the initial value condition of the Poisson distribution where n=0, taking successive estimations until some user specified error term (epsilon) is reached. The NEWTPOIS program is written in C. It was developed on an IBM AT with a numeric co-processor using Microsoft C 5.0. Because the source code is written using standard C structures and functions, it should compile correctly on most C compilers. The program format is interactive, accepting epsilon, n, and the cumulative probability of the occurrence of n as inputs. It has been implemented under DOS 3.2 and has a memory requirement of 30K. NEWTPOIS was developed in 1988.

Maximum likelihood-based analysis of single-molecule photon arrival trajectories.

PubMed

Hajdziona, Marta; Molski, Andrzej

2011-02-07

In this work we explore the statistical properties of the maximum likelihood-based analysis of one-color photon arrival trajectories. This approach does not involve binning and, therefore, all of the information contained in an observed photon strajectory is used. We study the accuracy and precision of parameter estimates and the efficiency of the Akaike information criterion and the Bayesian information criterion (BIC) in selecting the true kinetic model. We focus on the low excitation regime where photon trajectories can be modeled as realizations of Markov modulated Poisson processes. The number of observed photons is the key parameter in determining model selection and parameter estimation. For example, the BIC can select the true three-state model from competing two-, three-, and four-state kinetic models even for relatively short trajectories made up of 2 × 10(3) photons. When the intensity levels are well-separated and 10(4) photons are observed, the two-state model parameters can be estimated with about 10% precision and those for a three-state model with about 20% precision.

Analysis of two production inventory systems with buffer, retrials and different production rates

NASA Astrophysics Data System (ADS)

Jose, K. P.; Nair, Salini S.

2017-09-01

This paper considers the comparison of two ( {s,S} ) production inventory systems with retrials of unsatisfied customers. The time for producing and adding each item to the inventory is exponentially distributed with rate β. However, a production rate α β higher than β is used at the beginning of the production. The higher production rate will reduce customers' loss when inventory level approaches zero. The demand from customers is according to a Poisson process. Service times are exponentially distributed. Upon arrival, the customers enter into a buffer of finite capacity. An arriving customer, who finds the buffer full, moves to an orbit. They can retry from there and inter-retrial times are exponentially distributed. The two models differ in the capacity of the buffer. The aim is to find the minimum value of total cost by varying different parameters and compare the efficiency of the models. The optimum value of α corresponding to minimum total cost is an important evaluation. Matrix analytic method is used to find an algorithmic solution to the problem. We also provide several numerical or graphical illustrations.

Fractional Poisson Fields and Martingales

NASA Astrophysics Data System (ADS)

Aletti, Giacomo; Leonenko, Nikolai; Merzbach, Ely

2018-02-01

We present new properties for the Fractional Poisson process (FPP) and the Fractional Poisson field on the plane. A martingale characterization for FPPs is given. We extend this result to Fractional Poisson fields, obtaining some other characterizations. The fractional differential equations are studied. We consider a more general Mixed-Fractional Poisson process and show that this process is the stochastic solution of a system of fractional differential-difference equations. Finally, we give some simulations of the Fractional Poisson field on the plane.

Random matrices and the New York City subway system

NASA Astrophysics Data System (ADS)

Jagannath, Aukosh; Trogdon, Thomas

2017-09-01

We analyze subway arrival times in the New York City subway system. We find regimes where the gaps between trains are well modeled by (unitarily invariant) random matrix statistics and Poisson statistics. The departure from random matrix statistics is captured by the value of the Coulomb potential along the subway route. This departure becomes more pronounced as trains make more stops.

A Martingale Characterization of Mixed Poisson Processes.

DTIC Science & Technology

1985-10-01

03LA A 11. TITLE (Inciuae Security Clanafication, ",A martingale characterization of mixed Poisson processes " ________________ 12. PERSONAL AUTHOR... POISSON PROCESSES Jostification .......... . ... . . Di.;t ib,,jtion by Availability Codes Dietmar Pfeifer* Technical University Aachen Dist Special and...Mixed Poisson processes play an important role in many branches of applied probability, for instance in insurance mathematics and physics (see Albrecht

Stationary and non-stationary occurrences of miniature end plate potentials are well described as stationary and non-stationary Poisson processes in the mollusc Navanax inermis.

PubMed

Cappell, M S; Spray, D C; Bennett, M V

1988-06-28

Protractor muscles in the gastropod mollusc Navanax inermis exhibit typical spontaneous miniature end plate potentials with mean amplitude 1.71 +/- 1.19 (standard deviation) mV. The evoked end plate potential is quantized, with a quantum equal to the miniature end plate potential amplitude. When their rate is stationary, occurrence of miniature end plate potentials is a random, Poisson process. When non-stationary, spontaneous miniature end plate potential occurrence is a non-stationary Poisson process, a Poisson process with the mean frequency changing with time. This extends the random Poisson model for miniature end plate potentials to the frequently observed non-stationary occurrence. Reported deviations from a Poisson process can sometimes be accounted for by the non-stationary Poisson process and more complex models, such as clustered release, are not always needed.

Rate of occurrence of failures based on a nonhomogeneous Poisson process: an ozone analyzer case study.

PubMed

de Moura Xavier, José Carlos; de Andrade Azevedo, Irany; de Sousa Junior, Wilson Cabral; Nishikawa, Augusto

2013-02-01

Atmospheric pollutant monitoring constitutes a primordial activity in public policies concerning air quality. In São Paulo State, Brazil, the São Paulo State Environment Company (CETESB) maintains an automatic network which continuously monitors CO, SO(2), NO(x), O(3), and particulate matter concentrations in the air. The monitoring process accuracy is a fundamental condition for the actions to be taken by CETESB. As one of the support systems, a preventive maintenance program for the different analyzers used is part of the data quality strategy. Knowledge of the behavior of analyzer failure times could help optimize the program. To achieve this goal, the failure times of an ozone analyzer-considered a repairable system-were modeled by means of the nonhomogeneous Poisson process. The rate of occurrence of failures (ROCOF) was estimated for the intervals 0-70,800 h and 0-88,320 h, in which six and seven failures were observed, respectively. The results showed that the ROCOF estimate is influenced by the choice of the observation period, t(0) = 70,800 h and t(7) = 88,320 h in the cases analyzed. Identification of preventive maintenance actions, mainly when parts replacement occurs in the last interval of observation, is highlighted, justifying the alteration in the behavior of the inter-arrival times. The performance of a follow-up on each analyzer is recommended in order to record the impact of the performed preventive maintenance program on the enhancement of its useful life.

Generation of Non-Homogeneous Poisson Processes by Thinning: Programming Considerations and Comparision with Competing Algorithms.

DTIC Science & Technology

1978-12-01

Poisson processes . The method is valid for Poisson processes with any given intensity function. The basic thinning algorithm is modified to exploit several refinements which reduce computer execution time by approximately one-third. The basic and modified thinning programs are compared with the Poisson decomposition and gap-statistics algorithm, which is easily implemented for Poisson processes with intensity functions of the form exp(a sub 0 + a sub 1t + a sub 2 t-squared. The thinning programs are competitive in both execution

Non-Poisson Processes: Regression to Equilibrium Versus Equilibrium Correlation Functions

DTIC Science & Technology

2004-07-07

ARTICLE IN PRESSPhysica A 347 (2005) 268–2880378-4371/$ - doi:10.1016/j Correspo E-mail adwww.elsevier.com/locate/physaNon- Poisson processes : regression...05.40.a; 89.75.k; 02.50.Ey Keywords: Stochastic processes; Non- Poisson processes ; Liouville and Liouville-like equations; Correlation function...which is not legitimate with renewal non- Poisson processes , is a correct property if the deviation from the exponential relaxation is obtained by time

Compositions, Random Sums and Continued Random Fractions of Poisson and Fractional Poisson Processes

NASA Astrophysics Data System (ADS)

Orsingher, Enzo; Polito, Federico

2012-08-01

In this paper we consider the relation between random sums and compositions of different processes. In particular, for independent Poisson processes N α ( t), N β ( t), t>0, we have that N_{α}(N_{β}(t)) stackrel{d}{=} sum_{j=1}^{N_{β}(t)} Xj, where the X j s are Poisson random variables. We present a series of similar cases, where the outer process is Poisson with different inner processes. We highlight generalisations of these results where the external process is infinitely divisible. A section of the paper concerns compositions of the form N_{α}(tauk^{ν}), ν∈(0,1], where tauk^{ν} is the inverse of the fractional Poisson process, and we show how these compositions can be represented as random sums. Furthermore we study compositions of the form Θ( N( t)), t>0, which can be represented as random products. The last section is devoted to studying continued fractions of Cauchy random variables with a Poisson number of levels. We evaluate the exact distribution and derive the scale parameter in terms of ratios of Fibonacci numbers.

Interarrival times of message propagation on directed networks.

PubMed

Mihaljev, Tamara; de Arcangelis, Lucilla; Herrmann, Hans J

2011-08-01

One of the challenges in fighting cybercrime is to understand the dynamics of message propagation on botnets, networks of infected computers used to send viruses, unsolicited commercial emails (SPAM) or denial of service attacks. We map this problem to the propagation of multiple random walkers on directed networks and we evaluate the interarrival time distribution between successive walkers arriving at a target. We show that the temporal organization of this process, which models information propagation on unstructured peer to peer networks, has the same features as SPAM reaching a single user. We study the behavior of the message interarrival time distribution on three different network topologies using two different rules for sending messages. In all networks the propagation is not a pure Poisson process. It shows universal features on Poissonian networks and a more complex behavior on scale free networks. Results open the possibility to indirectly learn about the process of sending messages on networks with unknown topologies, by studying interarrival times at any node of the network.

Interarrival times of message propagation on directed networks

NASA Astrophysics Data System (ADS)

Mihaljev, Tamara; de Arcangelis, Lucilla; Herrmann, Hans J.

2011-08-01

One of the challenges in fighting cybercrime is to understand the dynamics of message propagation on botnets, networks of infected computers used to send viruses, unsolicited commercial emails (SPAM) or denial of service attacks. We map this problem to the propagation of multiple random walkers on directed networks and we evaluate the interarrival time distribution between successive walkers arriving at a target. We show that the temporal organization of this process, which models information propagation on unstructured peer to peer networks, has the same features as SPAM reaching a single user. We study the behavior of the message interarrival time distribution on three different network topologies using two different rules for sending messages. In all networks the propagation is not a pure Poisson process. It shows universal features on Poissonian networks and a more complex behavior on scale free networks. Results open the possibility to indirectly learn about the process of sending messages on networks with unknown topologies, by studying interarrival times at any node of the network.

Graphic Simulations of the Poisson Process.

DTIC Science & Technology

1982-10-01

RANDOM NUMBERS AND TRANSFORMATIONS..o......... 11 Go THE RANDOM NUMBERGENERATOR....... .oo..... 15 III. POISSON PROCESSES USER GUIDE....oo.ooo ......... o...again. In the superimposed mode, two Poisson processes are active, each with a different rate parameter, (call them Type I and Type II with respective...occur. The value ’p’ is generated by the following equation where ’Li’ and ’L2’ are the rates of the two Poisson processes ; p = Li / (Li + L2) The value

Simulation Methods for Poisson Processes in Nonstationary Systems.

DTIC Science & Technology

1978-08-01

for simulation of nonhomogeneous Poisson processes is stated with log-linear rate function. The method is based on an identity relating the...and relatively efficient new method for simulation of one-dimensional and two-dimensional nonhomogeneous Poisson processes is described. The method is

Identification of a Class of Filtered Poisson Processes.

DTIC Science & Technology

1981-01-01

LD-A135 371 IDENTIFICATION OF A CLASS OF FILERED POISSON PROCESSES I AU) NORTH CAROLINA UNIV AT CHAPEL HIL DEPT 0F STATISTICS D DE RRUC ET AL 1981...STNO&IO$ !tt ~ 4.s " . , ".7" -L N ~ TITLE :IDENTIFICATION OF A CLASS OF FILTERED POISSON PROCESSES Authors : DE BRUCQ Denis - GUALTIEROTTI Antonio...filtered Poisson processes is intro- duced : the amplitude has a law which is spherically invariant and the filter is real, linear and causal. It is shown

Mitigating Photon Jitter in Optical PPM Communication

NASA Technical Reports Server (NTRS)

Moision, Bruce

2008-01-01

A theoretical analysis of photon-arrival jitter in an optical pulse-position-modulation (PPM) communication channel has been performed, and now constitutes the basis of a methodology for designing receivers to compensate so that errors attributable to photon-arrival jitter would be minimized or nearly minimized. Photon-arrival jitter is an uncertainty in the estimated time of arrival of a photon relative to the boundaries of a PPM time slot. Photon-arrival jitter is attributable to two main causes: (1) receiver synchronization error [error in the receiver operation of partitioning time into PPM slots] and (2) random delay between the time of arrival of a photon at a detector and the generation, by the detector circuitry, of a pulse in response to the photon. For channels with sufficiently long time slots, photon-arrival jitter is negligible. However, as durations of PPM time slots are reduced in efforts to increase throughputs of optical PPM communication channels, photon-arrival jitter becomes a significant source of error, leading to significant degradation of performance if not taken into account in design. For the purpose of the analysis, a receiver was assumed to operate in a photon- starved regime, in which photon counts follow a Poisson distribution. The analysis included derivation of exact equations for symbol likelihoods in the presence of photon-arrival jitter. These equations describe what is well known in the art as a matched filter for a channel containing Gaussian noise. These equations would yield an optimum receiver if they could be implemented in practice. Because the exact equations may be too complex to implement in practice, approximations that would yield suboptimal receivers were also derived.

State Estimation for Linear Systems Driven Simultaneously by Wiener and Poisson Processes.

DTIC Science & Technology

1978-12-01

The state estimation problem of linear stochastic systems driven simultaneously by Wiener and Poisson processes is considered, especially the case...where the incident intensities of the Poisson processes are low and the system is observed in an additive white Gaussian noise. The minimum mean squared

Poisson pre-processing of nonstationary photonic signals: Signals with equality between mean and variance.

PubMed

Poplová, Michaela; Sovka, Pavel; Cifra, Michal

2017-01-01

Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal.

Poisson pre-processing of nonstationary photonic signals: Signals with equality between mean and variance

PubMed Central

Poplová, Michaela; Sovka, Pavel

2017-01-01

Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal. PMID:29216207

Modeling laser velocimeter signals as triply stochastic Poisson processes

NASA Technical Reports Server (NTRS)

Mayo, W. T., Jr.

1976-01-01

Previous models of laser Doppler velocimeter (LDV) systems have not adequately described dual-scatter signals in a manner useful for analysis and simulation of low-level photon-limited signals. At low photon rates, an LDV signal at the output of a photomultiplier tube is a compound nonhomogeneous filtered Poisson process, whose intensity function is another (slower) Poisson process with the nonstationary rate and frequency parameters controlled by a random flow (slowest) process. In the present paper, generalized Poisson shot noise models are developed for low-level LDV signals. Theoretical results useful in detection error analysis and simulation are presented, along with measurements of burst amplitude statistics. Computer generated simulations illustrate the difference between Gaussian and Poisson models of low-level signals.

Anomaly Detection in Dynamic Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Turcotte, Melissa

2014-10-14

Anomaly detection in dynamic communication networks has many important security applications. These networks can be extremely large and so detecting any changes in their structure can be computationally challenging; hence, computationally fast, parallelisable methods for monitoring the network are paramount. For this reason the methods presented here use independent node and edge based models to detect locally anomalous substructures within communication networks. As a first stage, the aim is to detect changes in the data streams arising from node or edge communications. Throughout the thesis simple, conjugate Bayesian models for counting processes are used to model these data streams. Amore » second stage of analysis can then be performed on a much reduced subset of the network comprising nodes and edges which have been identified as potentially anomalous in the first stage. The first method assumes communications in a network arise from an inhomogeneous Poisson process with piecewise constant intensity. Anomaly detection is then treated as a changepoint problem on the intensities. The changepoint model is extended to incorporate seasonal behavior inherent in communication networks. This seasonal behavior is also viewed as a changepoint problem acting on a piecewise constant Poisson process. In a static time frame, inference is made on this extended model via a Gibbs sampling strategy. In a sequential time frame, where the data arrive as a stream, a novel, fast Sequential Monte Carlo (SMC) algorithm is introduced to sample from the sequence of posterior distributions of the change points over time. A second method is considered for monitoring communications in a large scale computer network. The usage patterns in these types of networks are very bursty in nature and don’t fit a Poisson process model. For tractable inference, discrete time models are considered, where the data are aggregated into discrete time periods and probability models are fitted to the communication counts. In a sequential analysis, anomalous behavior is then identified from outlying behavior with respect to the fitted predictive probability models. Seasonality is again incorporated into the model and is treated as a changepoint model on the transition probabilities of a discrete time Markov process. Second stage analytics are then developed which combine anomalous edges to identify anomalous substructures in the network.« less

Information transmission using non-poisson regular firing.

PubMed

Koyama, Shinsuke; Omi, Takahiro; Kass, Robert E; Shinomoto, Shigeru

2013-04-01

In many cortical areas, neural spike trains do not follow a Poisson process. In this study, we investigate a possible benefit of non-Poisson spiking for information transmission by studying the minimal rate fluctuation that can be detected by a Bayesian estimator. The idea is that an inhomogeneous Poisson process may make it difficult for downstream decoders to resolve subtle changes in rate fluctuation, but by using a more regular non-Poisson process, the nervous system can make rate fluctuations easier to detect. We evaluate the degree to which regular firing reduces the rate fluctuation detection threshold. We find that the threshold for detection is reduced in proportion to the coefficient of variation of interspike intervals.

Identification d’une Classe de Processus de Poisson Filtres (Identification of a Class of Filtered Poisson Processes).

DTIC Science & Technology

1983-05-20

Poisson processes is introduced: the amplitude has a law which is spherically invariant and the filter is real, linear and causal. It is shown how such a model can be identified from experimental data. (Author)

From Loss of Memory to Poisson.

ERIC Educational Resources Information Center

Johnson, Bruce R.

1983-01-01

A way of presenting the Poisson process and deriving the Poisson distribution for upper-division courses in probability or mathematical statistics is presented. The main feature of the approach lies in the formulation of Poisson postulates with immediate intuitive appeal. (MNS)

Flood return level analysis of Peaks over Threshold series under changing climate

NASA Astrophysics Data System (ADS)

Li, L.; Xiong, L.; Hu, T.; Xu, C. Y.; Guo, S.

2016-12-01

Obtaining insights into future flood estimation is of great significance for water planning and management. Traditional flood return level analysis with the stationarity assumption has been challenged by changing environments. A method that takes into consideration the nonstationarity context has been extended to derive flood return levels for Peaks over Threshold (POT) series. With application to POT series, a Poisson distribution is normally assumed to describe the arrival rate of exceedance events, but this distribution assumption has at times been reported as invalid. The Negative Binomial (NB) distribution is therefore proposed as an alternative to the Poisson distribution assumption. Flood return levels were extrapolated in nonstationarity context for the POT series of the Weihe basin, China under future climate scenarios. The results show that the flood return levels estimated under nonstationarity can be different with an assumption of Poisson and NB distribution, respectively. The difference is found to be related to the threshold value of POT series. The study indicates the importance of distribution selection in flood return level analysis under nonstationarity and provides a reference on the impact of climate change on flood estimation in the Weihe basin for the future.

Effects of unstratified and centre-stratified randomization in multi-centre clinical trials.

PubMed

Anisimov, Vladimir V

2011-01-01

This paper deals with the analysis of randomization effects in multi-centre clinical trials. The two randomization schemes most often used in clinical trials are considered: unstratified and centre-stratified block-permuted randomization. The prediction of the number of patients randomized to different treatment arms in different regions during the recruitment period accounting for the stochastic nature of the recruitment and effects of multiple centres is investigated. A new analytic approach using a Poisson-gamma patient recruitment model (patients arrive at different centres according to Poisson processes with rates sampled from a gamma distributed population) and its further extensions is proposed. Closed-form expressions for corresponding distributions of the predicted number of the patients randomized in different regions are derived. In the case of two treatments, the properties of the total imbalance in the number of patients on treatment arms caused by using centre-stratified randomization are investigated and for a large number of centres a normal approximation of imbalance is proved. The impact of imbalance on the power of the study is considered. It is shown that the loss of statistical power is practically negligible and can be compensated by a minor increase in sample size. The influence of patient dropout is also investigated. The impact of randomization on predicted drug supply overage is discussed. Copyright © 2010 John Wiley & Sons, Ltd.

Spatiotemporal reconstruction of list-mode PET data.

PubMed

Nichols, Thomas E; Qi, Jinyi; Asma, Evren; Leahy, Richard M

2002-04-01

We describe a method for computing a continuous time estimate of tracer density using list-mode positron emission tomography data. The rate function in each voxel is modeled as an inhomogeneous Poisson process whose rate function can be represented using a cubic B-spline basis. The rate functions are estimated by maximizing the likelihood of the arrival times of detected photon pairs over the control vertices of the spline, modified by quadratic spatial and temporal smoothness penalties and a penalty term to enforce nonnegativity. Randoms rate functions are estimated by assuming independence between the spatial and temporal randoms distributions. Similarly, scatter rate functions are estimated by assuming spatiotemporal independence and that the temporal distribution of the scatter is proportional to the temporal distribution of the trues. A quantitative evaluation was performed using simulated data and the method is also demonstrated in a human study using 11C-raclopride.

On the optimal use of a slow server in two-stage queueing systems

NASA Astrophysics Data System (ADS)

Papachristos, Ioannis; Pandelis, Dimitrios G.

2017-07-01

We consider two-stage tandem queueing systems with a dedicated server in each queue and a slower flexible server that can attend both queues. We assume Poisson arrivals and exponential service times, and linear holding costs for jobs present in the system. We study the optimal dynamic assignment of servers to jobs assuming that two servers cannot collaborate to work on the same job and preemptions are not allowed. We formulate the problem as a Markov decision process and derive properties of the optimal allocation for the dedicated (fast) servers. Specifically, we show that the one downstream should not idle, and the same is true for the one upstream when holding costs are larger there. The optimal allocation of the slow server is investigated through extensive numerical experiments that lead to conjectures on the structure of the optimal policy.

On buffer overflow duration in a finite-capacity queueing system with multiple vacation policy

NASA Astrophysics Data System (ADS)

Kempa, Wojciech M.

2017-12-01

A finite-buffer queueing system with Poisson arrivals and generally distributed processing times, operating under multiple vacation policy, is considered. Each time when the system becomes empty, the service station takes successive independent and identically distributed vacation periods, until, at the completion epoch of one of them, at least one job waiting for service is detected in the buffer. Applying analytical approach based on the idea of embedded Markov chain, integral equations and linear algebra, the compact-form representation for the cumulative distribution function (CDF for short) of the first buffer overflow duration is found. Hence, the formula for the CDF of next such periods is obtained. Moreover, probability distributions of the number of job losses in successive buffer overflow periods are found. The considered queueing system can be efficienly applied in modelling energy saving mechanisms in wireless network communication.

Super-stable Poissonian structures

NASA Astrophysics Data System (ADS)

Eliazar, Iddo

2012-10-01

In this paper we characterize classes of Poisson processes whose statistical structures are super-stable. We consider a flow generated by a one-dimensional ordinary differential equation, and an ensemble of particles ‘surfing’ the flow. The particles start from random initial positions, and are propagated along the flow by stochastic ‘wave processes’ with general statistics and general cross correlations. Setting the initial positions to be Poisson processes, we characterize the classes of Poisson processes that render the particles’ positions—at all times, and invariantly with respect to the wave processes—statistically identical to their initial positions. These Poisson processes are termed ‘super-stable’ and facilitate the generalization of the notion of stationary distributions far beyond the realm of Markov dynamics.

The Use of Crow-AMSAA Plots to Assess Mishap Trends

NASA Technical Reports Server (NTRS)

Dawson, Jeffrey W.

2011-01-01

Crow-AMSAA (CA) plots are used to model reliability growth. Use of CA plots has expanded into other areas, such as tracking events of interest to management, maintenance problems, and safety mishaps. Safety mishaps can often be successfully modeled using a Poisson probability distribution. CA plots show a Poisson process in log-log space. If the safety mishaps are a stable homogenous Poisson process, a linear fit to the points in a CA plot will have a slope of one. Slopes of greater than one indicate a nonhomogenous Poisson process, with increasing occurrence. Slopes of less than one indicate a nonhomogenous Poisson process, with decreasing occurrence. Changes in slope, known as "cusps," indicate a change in process, which could be an improvement or a degradation. After presenting the CA conceptual framework, examples are given of trending slips, trips and falls, and ergonomic incidents at NASA (from Agency-level data). Crow-AMSAA plotting is a robust tool for trending safety mishaps that can provide insight into safety performance over time.

Effect of non-Poisson samples on turbulence spectra from laser velocimetry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sree, D.; Kjelgaard, S.O.; Sellers, W.L. III

1994-12-01

Spectral estimations from LV data are typically based on the assumption of a Poisson sampling process. It is demonstrated here that the sampling distribution must be considered before spectral estimates are used to infer turbulence scales. A non-Poisson sampling process can occur if there is nonhomogeneous distribution of particles in the flow. Based on the study of a simulated first-order spectrum, it has been shown that a non-Poisson sampling process causes the estimated spectrum to deviate from the true spectrum. Also, in this case the prefiltering techniques do not improve the spectral estimates at higher frequencies. 4 refs.

Evolutionary inference via the Poisson Indel Process.

PubMed

Bouchard-Côté, Alexandre; Jordan, Michael I

2013-01-22

We address the problem of the joint statistical inference of phylogenetic trees and multiple sequence alignments from unaligned molecular sequences. This problem is generally formulated in terms of string-valued evolutionary processes along the branches of a phylogenetic tree. The classic evolutionary process, the TKF91 model [Thorne JL, Kishino H, Felsenstein J (1991) J Mol Evol 33(2):114-124] is a continuous-time Markov chain model composed of insertion, deletion, and substitution events. Unfortunately, this model gives rise to an intractable computational problem: The computation of the marginal likelihood under the TKF91 model is exponential in the number of taxa. In this work, we present a stochastic process, the Poisson Indel Process (PIP), in which the complexity of this computation is reduced to linear. The Poisson Indel Process is closely related to the TKF91 model, differing only in its treatment of insertions, but it has a global characterization as a Poisson process on the phylogeny. Standard results for Poisson processes allow key computations to be decoupled, which yields the favorable computational profile of inference under the PIP model. We present illustrative experiments in which Bayesian inference under the PIP model is compared with separate inference of phylogenies and alignments.

Evolutionary inference via the Poisson Indel Process

PubMed Central

Bouchard-Côté, Alexandre; Jordan, Michael I.

2013-01-01

We address the problem of the joint statistical inference of phylogenetic trees and multiple sequence alignments from unaligned molecular sequences. This problem is generally formulated in terms of string-valued evolutionary processes along the branches of a phylogenetic tree. The classic evolutionary process, the TKF91 model [Thorne JL, Kishino H, Felsenstein J (1991) J Mol Evol 33(2):114–124] is a continuous-time Markov chain model composed of insertion, deletion, and substitution events. Unfortunately, this model gives rise to an intractable computational problem: The computation of the marginal likelihood under the TKF91 model is exponential in the number of taxa. In this work, we present a stochastic process, the Poisson Indel Process (PIP), in which the complexity of this computation is reduced to linear. The Poisson Indel Process is closely related to the TKF91 model, differing only in its treatment of insertions, but it has a global characterization as a Poisson process on the phylogeny. Standard results for Poisson processes allow key computations to be decoupled, which yields the favorable computational profile of inference under the PIP model. We present illustrative experiments in which Bayesian inference under the PIP model is compared with separate inference of phylogenies and alignments. PMID:23275296

Monitoring Poisson observations using combined applications of Shewhart and EWMA charts

NASA Astrophysics Data System (ADS)

Abujiya, Mu'azu Ramat

2017-11-01

The Shewhart and exponentially weighted moving average (EWMA) charts for nonconformities are the most widely used procedures of choice for monitoring Poisson observations in modern industries. Individually, the Shewhart EWMA charts are only sensitive to large and small shifts, respectively. To enhance the detection abilities of the two schemes in monitoring all kinds of shifts in Poisson count data, this study examines the performance of combined applications of the Shewhart, and EWMA Poisson control charts. Furthermore, the study proposes modifications based on well-structured statistical data collection technique, ranked set sampling (RSS), to detect shifts in the mean of a Poisson process more quickly. The relative performance of the proposed Shewhart-EWMA Poisson location charts is evaluated in terms of the average run length (ARL), standard deviation of the run length (SDRL), median run length (MRL), average ratio ARL (ARARL), average extra quadratic loss (AEQL) and performance comparison index (PCI). Consequently, all the new Poisson control charts based on RSS method are generally more superior than most of the existing schemes for monitoring Poisson processes. The use of these combined Shewhart-EWMA Poisson charts is illustrated with an example to demonstrate the practical implementation of the design procedure.

Calculation of the Poisson cumulative distribution function

NASA Technical Reports Server (NTRS)

Bowerman, Paul N.; Nolty, Robert G.; Scheuer, Ernest M.

1990-01-01

A method for calculating the Poisson cdf (cumulative distribution function) is presented. The method avoids computer underflow and overflow during the process. The computer program uses this technique to calculate the Poisson cdf for arbitrary inputs. An algorithm that determines the Poisson parameter required to yield a specified value of the cdf is presented.

Poisson process stimulation of an excitable membrane cable model.

PubMed Central

Goldfinger, M D

1986-01-01

The convergence of multiple inputs within a single-neuronal substrate is a common design feature of both peripheral and central nervous systems. Typically, the result of such convergence impinges upon an intracellularly contiguous axon, where it is encoded into a train of action potentials. The simplest representation of the result of convergence of multiple inputs is a Poisson process; a general representation of axonal excitability is the Hodgkin-Huxley/cable theory formalism. The present work addressed multiple input convergence upon an axon by applying Poisson process stimulation to the Hodgkin-Huxley axonal cable. The results showed that both absolute and relative refractory periods yielded in the axonal output a random but non-Poisson process. While smaller amplitude stimuli elicited a type of short-interval conditioning, larger amplitude stimuli elicited impulse trains approaching Poisson criteria except for the effects of refractoriness. These results were obtained for stimulus trains consisting of pulses of constant amplitude and constant or variable durations. By contrast, with or without stimulus pulse shape variability, the post-impulse conditional probability for impulse initiation in the steady-state was a Poisson-like process. For stimulus variability consisting of randomly smaller amplitudes or randomly longer durations, mean impulse frequency was attenuated or potentiated, respectively. Limitations and implications of these computations are discussed. PMID:3730505

Analysis of overdispersed count data by mixtures of Poisson variables and Poisson processes.

PubMed

Hougaard, P; Lee, M L; Whitmore, G A

1997-12-01

Count data often show overdispersion compared to the Poisson distribution. Overdispersion is typically modeled by a random effect for the mean, based on the gamma distribution, leading to the negative binomial distribution for the count. This paper considers a larger family of mixture distributions, including the inverse Gaussian mixture distribution. It is demonstrated that it gives a significantly better fit for a data set on the frequency of epileptic seizures. The same approach can be used to generate counting processes from Poisson processes, where the rate or the time is random. A random rate corresponds to variation between patients, whereas a random time corresponds to variation within patients.

Universal Poisson Statistics of mRNAs with Complex Decay Pathways.

PubMed

Thattai, Mukund

2016-01-19

Messenger RNA (mRNA) dynamics in single cells are often modeled as a memoryless birth-death process with a constant probability per unit time that an mRNA molecule is synthesized or degraded. This predicts a Poisson steady-state distribution of mRNA number, in close agreement with experiments. This is surprising, since mRNA decay is known to be a complex process. The paradox is resolved by realizing that the Poisson steady state generalizes to arbitrary mRNA lifetime distributions. A mapping between mRNA dynamics and queueing theory highlights an identifiability problem: a measured Poisson steady state is consistent with a large variety of microscopic models. Here, I provide a rigorous and intuitive explanation for the universality of the Poisson steady state. I show that the mRNA birth-death process and its complex decay variants all take the form of the familiar Poisson law of rare events, under a nonlinear rescaling of time. As a corollary, not only steady-states but also transients are Poisson distributed. Deviations from the Poisson form occur only under two conditions, promoter fluctuations leading to transcriptional bursts or nonindependent degradation of mRNA molecules. These results place severe limits on the power of single-cell experiments to probe microscopic mechanisms, and they highlight the need for single-molecule measurements. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Modeling spiking behavior of neurons with time-dependent Poisson processes.

PubMed

Shinomoto, S; Tsubo, Y

2001-10-01

Three kinds of interval statistics, as represented by the coefficient of variation, the skewness coefficient, and the correlation coefficient of consecutive intervals, are evaluated for three kinds of time-dependent Poisson processes: pulse regulated, sinusoidally regulated, and doubly stochastic. Among these three processes, the sinusoidally regulated and doubly stochastic Poisson processes, in the case when the spike rate varies slowly compared with the mean interval between spikes, are found to be consistent with the three statistical coefficients exhibited by data recorded from neurons in the prefrontal cortex of monkeys.

Poisson point process modeling for polyphonic music transcription.

PubMed

Peeling, Paul; Li, Chung-fai; Godsill, Simon

2007-04-01

Peaks detected in the frequency domain spectrum of a musical chord are modeled as realizations of a nonhomogeneous Poisson point process. When several notes are superimposed to make a chord, the processes for individual notes combine to give another Poisson process, whose likelihood is easily computable. This avoids a data association step linking individual harmonics explicitly with detected peaks in the spectrum. The likelihood function is ideal for Bayesian inference about the unknown note frequencies in a chord. Here, maximum likelihood estimation of fundamental frequencies shows very promising performance on real polyphonic piano music recordings.

Limiting Distributions of Functionals of Markov Chains.

DTIC Science & Technology

1984-08-01

limiting distributions; periodic * nonhomoger.,!ous Poisson processes . 19 ANS? MACY IConuui oe nonoe’ee if necorglooy and edern thty by block numbers...homogeneous Poisson processes is of interest in itself. The problem considered in this paper is of interest in the theory of partially observable...where we obtain the limiting distribution of the interevent times. Key Words: Markov Chains, Limiting Distributions, Periodic Nonhomogeneous Poisson

Wigner surmises and the two-dimensional homogeneous Poisson point process.

PubMed

Sakhr, Jamal; Nieminen, John M

2006-04-01

We derive a set of identities that relate the higher-order interpoint spacing statistics of the two-dimensional homogeneous Poisson point process to the Wigner surmises for the higher-order spacing distributions of eigenvalues from the three classical random matrix ensembles. We also report a remarkable identity that equates the second-nearest-neighbor spacing statistics of the points of the Poisson process and the nearest-neighbor spacing statistics of complex eigenvalues from Ginibre's ensemble of 2 x 2 complex non-Hermitian random matrices.

A digital simulation of message traffic for natural disaster warning communications satellite

NASA Technical Reports Server (NTRS)

Hein, G. F.; Stevenson, S. M.

1972-01-01

Various types of weather communications are required to alert industries and the general public about the impending occurrence of tornados, hurricanes, snowstorms, floods, etc. A natural disaster warning satellite system has been proposed for meeting the communications requirements of the National Oceanic and Atmospheric Administration. Message traffic for a communications satellite was simulated with a digital computer in order to determine the number of communications channels to meet system requirements. Poisson inputs are used for arrivals and an exponential distribution is used for service.

Nonparametric Bayesian Segmentation of a Multivariate Inhomogeneous Space-Time Poisson Process.

PubMed

Ding, Mingtao; He, Lihan; Dunson, David; Carin, Lawrence

2012-12-01

A nonparametric Bayesian model is proposed for segmenting time-evolving multivariate spatial point process data. An inhomogeneous Poisson process is assumed, with a logistic stick-breaking process (LSBP) used to encourage piecewise-constant spatial Poisson intensities. The LSBP explicitly favors spatially contiguous segments, and infers the number of segments based on the observed data. The temporal dynamics of the segmentation and of the Poisson intensities are modeled with exponential correlation in time, implemented in the form of a first-order autoregressive model for uniformly sampled discrete data, and via a Gaussian process with an exponential kernel for general temporal sampling. We consider and compare two different inference techniques: a Markov chain Monte Carlo sampler, which has relatively high computational complexity; and an approximate and efficient variational Bayesian analysis. The model is demonstrated with a simulated example and a real example of space-time crime events in Cincinnati, Ohio, USA.

Determination of elastic constants of a generally orthotropic plate by modal analysis

NASA Astrophysics Data System (ADS)

Lai, T. C.; Lau, T. C.

1993-01-01

This paper describes a method of finding the elastic constants of a generally orthotropic composite thin plate through modal analysis based on a Rayleigh-Ritz formulation. The natural frequencies and mode shapes for a plate with free-free boundary conditions are obtained with chirp excitation. Based on the eigenvalue equation and the constitutive equations of the plate, an iteration scheme is derived using the experimentally determined natural frequencies to arrive at a set of converged values for the elastic constants. Four sets of experimental data are required for the four independent constants: namely the two Young's moduli E1 and E2, the in-plane shear modulus G12, and one Poisson's ratio nu12. The other Poisson's ratio nu21 can then be determined from the relationship among the constants. Comparison with static test results indicate good agreement. Choosing the right combinations of natural modes together with a set of reasonable initial estimates for the constants to start the iteration has been found to be crucial in achieving convergence.

Doubly stochastic Poisson processes in artificial neural learning.

PubMed

Card, H C

1998-01-01

This paper investigates neuron activation statistics in artificial neural networks employing stochastic arithmetic. It is shown that a doubly stochastic Poisson process is an appropriate model for the signals in these circuits.

Noisy cooperative intermittent processes: From blinking quantum dots to human consciousness

NASA Astrophysics Data System (ADS)

Allegrini, Paolo; Paradisi, Paolo; Menicucci, Danilo; Bedini, Remo; Gemignani, Angelo; Fronzoni, Leone

2011-07-01

We study the superposition of a non-Poisson renewal process with the presence of a superimposed Poisson noise. The non-Poisson renewals mark the passage between meta-stable states in system with self-organization. We propose methods to measure the amount of information due to the two independent processes independently, and we see that a superficial study based on the survival probabilities yield stretched-exponential relaxations. Our method is in fact able to unravel the inverse-power law relaxation of the isolated non-Poisson processes, even when noise is present. We provide examples of this behavior in system of diverse nature, from blinking nano-crystals to weak turbulence. Finally we focus our discussion on events extracted from human electroencephalograms, and we discuss their connection with emerging properties of integrated neural dynamics, i.e. consciousness.

Applying the compound Poisson process model to the reporting of injury-related mortality rates.

PubMed

Kegler, Scott R

2007-02-16

Injury-related mortality rate estimates are often analyzed under the assumption that case counts follow a Poisson distribution. Certain types of injury incidents occasionally involve multiple fatalities, however, resulting in dependencies between cases that are not reflected in the simple Poisson model and which can affect even basic statistical analyses. This paper explores the compound Poisson process model as an alternative, emphasizing adjustments to some commonly used interval estimators for population-based rates and rate ratios. The adjusted estimators involve relatively simple closed-form computations, which in the absence of multiple-case incidents reduce to familiar estimators based on the simpler Poisson model. Summary data from the National Violent Death Reporting System are referenced in several examples demonstrating application of the proposed methodology.

Complete synchronization of the global coupled dynamical network induced by Poisson noises.

PubMed

Guo, Qing; Wan, Fangyi

2017-01-01

The different Poisson noise-induced complete synchronization of the global coupled dynamical network is investigated. Based on the stability theory of stochastic differential equations driven by Poisson process, we can prove that Poisson noises can induce synchronization and sufficient conditions are established to achieve complete synchronization with probability 1. Furthermore, numerical examples are provided to show the agreement between theoretical and numerical analysis.

? filtering for stochastic systems driven by Poisson processes

NASA Astrophysics Data System (ADS)

Song, Bo; Wu, Zheng-Guang; Park, Ju H.; Shi, Guodong; Zhang, Ya

2015-01-01

This paper investigates the ? filtering problem for stochastic systems driven by Poisson processes. By utilising the martingale theory such as the predictable projection operator and the dual predictable projection operator, this paper transforms the expectation of stochastic integral with respect to the Poisson process into the expectation of Lebesgue integral. Then, based on this, this paper designs an ? filter such that the filtering error system is mean-square asymptotically stable and satisfies a prescribed ? performance level. Finally, a simulation example is given to illustrate the effectiveness of the proposed filtering scheme.

Intertime jump statistics of state-dependent Poisson processes.

PubMed

Daly, Edoardo; Porporato, Amilcare

2007-01-01

A method to obtain the probability distribution of the interarrival times of jump occurrences in systems driven by state-dependent Poisson noise is proposed. Such a method uses the survivor function obtained by a modified version of the master equation associated to the stochastic process under analysis. A model for the timing of human activities shows the capability of state-dependent Poisson noise to generate power-law distributions. The application of the method to a model for neuron dynamics and to a hydrological model accounting for land-atmosphere interaction elucidates the origin of characteristic recurrence intervals and possible persistence in state-dependent Poisson models.

Segmentation algorithm for non-stationary compound Poisson processes. With an application to inventory time series of market members in a financial market

NASA Astrophysics Data System (ADS)

Tóth, B.; Lillo, F.; Farmer, J. D.

2010-11-01

We introduce an algorithm for the segmentation of a class of regime switching processes. The segmentation algorithm is a non parametric statistical method able to identify the regimes (patches) of a time series. The process is composed of consecutive patches of variable length. In each patch the process is described by a stationary compound Poisson process, i.e. a Poisson process where each count is associated with a fluctuating signal. The parameters of the process are different in each patch and therefore the time series is non-stationary. Our method is a generalization of the algorithm introduced by Bernaola-Galván, et al. [Phys. Rev. Lett. 87, 168105 (2001)]. We show that the new algorithm outperforms the original one for regime switching models of compound Poisson processes. As an application we use the algorithm to segment the time series of the inventory of market members of the London Stock Exchange and we observe that our method finds almost three times more patches than the original one.

Protein electrostatics: a review of the equations and methods used to model electrostatic equations in biomolecules--applications in biotechnology.

PubMed

Neves-Petersen, Maria Teresa; Petersen, Steffen B

2003-01-01

The molecular understanding of the initial interaction between a protein and, e.g., its substrate, a surface or an inhibitor is essentially an understanding of the role of electrostatics in intermolecular interactions. When studying biomolecules it is becoming increasingly evident that electrostatic interactions play a role in folding, conformational stability, enzyme activity and binding energies as well as in protein-protein interactions. In this chapter we present the key basic equations of electrostatics necessary to derive the equations used to model electrostatic interactions in biomolecules. We will also address how to solve such equations. This chapter is divided into two major sections. In the first part we will review the basic Maxwell equations of electrostatics equations called the Laws of Electrostatics that combined will result in the Poisson equation. This equation is the starting point of the Poisson-Boltzmann (PB) equation used to model electrostatic interactions in biomolecules. Concepts as electric field lines, equipotential surfaces, electrostatic energy and when can electrostatics be applied to study interactions between charges will be addressed. In the second part we will arrive at the electrostatic equations for dielectric media such as a protein. We will address the theory of dielectrics and arrive at the Poisson equation for dielectric media and at the PB equation, the main equation used to model electrostatic interactions in biomolecules (e.g., proteins, DNA). It will be shown how to compute forces and potentials in a dielectric medium. In order to solve the PB equation we will present the continuum electrostatic models, namely the Tanford-Kirkwood and the modified Tandord-Kirkwood methods. Priority will be given to finding the protonation state of proteins prior to solving the PB equation. We also present some methods that can be used to map and study the electrostatic potential distribution on the molecular surface of proteins. The combination of graphical visualisation of the electrostatic fields combined with knowledge about the location of key residues on the protein surface allows us to envision atomic models for enzyme function. Finally, we exemplify the use of some of these methods on the enzymes of the lipase family.

Dependent Neyman type A processes based on common shock Poisson approach

NASA Astrophysics Data System (ADS)

Kadilar, Gamze Özel; Kadilar, Cem

2016-04-01

The Neyman type A process is used for describing clustered data since the Poisson process is insufficient for clustering of events. In a multivariate setting, there may be dependencies between multivarite Neyman type A processes. In this study, dependent form of the Neyman type A process is considered under common shock approach. Then, the joint probability function are derived for the dependent Neyman type A Poisson processes. Then, an application based on forest fires in Turkey are given. The results show that the joint probability function of the dependent Neyman type A processes, which is obtained in this study, can be a good tool for the probabilistic fitness for the total number of burned trees in Turkey.

Modeling Stochastic Variability in the Numbers of Surviving Salmonella enterica, Enterohemorrhagic Escherichia coli, and Listeria monocytogenes Cells at the Single-Cell Level in a Desiccated Environment

PubMed Central

Koyama, Kento; Hokunan, Hidekazu; Hasegawa, Mayumi; Kawamura, Shuso

2016-01-01

ABSTRACT Despite effective inactivation procedures, small numbers of bacterial cells may still remain in food samples. The risk that bacteria will survive these procedures has not been estimated precisely because deterministic models cannot be used to describe the uncertain behavior of bacterial populations. We used the Poisson distribution as a representative probability distribution to estimate the variability in bacterial numbers during the inactivation process. Strains of four serotypes of Salmonella enterica, three serotypes of enterohemorrhagic Escherichia coli, and one serotype of Listeria monocytogenes were evaluated for survival. We prepared bacterial cell numbers following a Poisson distribution (indicated by the parameter λ, which was equal to 2) and plated the cells in 96-well microplates, which were stored in a desiccated environment at 10% to 20% relative humidity and at 5, 15, and 25°C. The survival or death of the bacterial cells in each well was confirmed by adding tryptic soy broth as an enrichment culture. Changes in the Poisson distribution parameter during the inactivation process, which represent the variability in the numbers of surviving bacteria, were described by nonlinear regression with an exponential function based on a Weibull distribution. We also examined random changes in the number of surviving bacteria using a random number generator and computer simulations to determine whether the number of surviving bacteria followed a Poisson distribution during the bacterial death process by use of the Poisson process. For small initial cell numbers, more than 80% of the simulated distributions (λ = 2 or 10) followed a Poisson distribution. The results demonstrate that variability in the number of surviving bacteria can be described as a Poisson distribution by use of the model developed by use of the Poisson process. IMPORTANCE We developed a model to enable the quantitative assessment of bacterial survivors of inactivation procedures because the presence of even one bacterium can cause foodborne disease. The results demonstrate that the variability in the numbers of surviving bacteria was described as a Poisson distribution by use of the model developed by use of the Poisson process. Description of the number of surviving bacteria as a probability distribution rather than as the point estimates used in a deterministic approach can provide a more realistic estimation of risk. The probability model should be useful for estimating the quantitative risk of bacterial survival during inactivation. PMID:27940547

Modeling Stochastic Variability in the Numbers of Surviving Salmonella enterica, Enterohemorrhagic Escherichia coli, and Listeria monocytogenes Cells at the Single-Cell Level in a Desiccated Environment.

PubMed

Koyama, Kento; Hokunan, Hidekazu; Hasegawa, Mayumi; Kawamura, Shuso; Koseki, Shigenobu

2017-02-15

Despite effective inactivation procedures, small numbers of bacterial cells may still remain in food samples. The risk that bacteria will survive these procedures has not been estimated precisely because deterministic models cannot be used to describe the uncertain behavior of bacterial populations. We used the Poisson distribution as a representative probability distribution to estimate the variability in bacterial numbers during the inactivation process. Strains of four serotypes of Salmonella enterica, three serotypes of enterohemorrhagic Escherichia coli, and one serotype of Listeria monocytogenes were evaluated for survival. We prepared bacterial cell numbers following a Poisson distribution (indicated by the parameter λ, which was equal to 2) and plated the cells in 96-well microplates, which were stored in a desiccated environment at 10% to 20% relative humidity and at 5, 15, and 25°C. The survival or death of the bacterial cells in each well was confirmed by adding tryptic soy broth as an enrichment culture. Changes in the Poisson distribution parameter during the inactivation process, which represent the variability in the numbers of surviving bacteria, were described by nonlinear regression with an exponential function based on a Weibull distribution. We also examined random changes in the number of surviving bacteria using a random number generator and computer simulations to determine whether the number of surviving bacteria followed a Poisson distribution during the bacterial death process by use of the Poisson process. For small initial cell numbers, more than 80% of the simulated distributions (λ = 2 or 10) followed a Poisson distribution. The results demonstrate that variability in the number of surviving bacteria can be described as a Poisson distribution by use of the model developed by use of the Poisson process. We developed a model to enable the quantitative assessment of bacterial survivors of inactivation procedures because the presence of even one bacterium can cause foodborne disease. The results demonstrate that the variability in the numbers of surviving bacteria was described as a Poisson distribution by use of the model developed by use of the Poisson process. Description of the number of surviving bacteria as a probability distribution rather than as the point estimates used in a deterministic approach can provide a more realistic estimation of risk. The probability model should be useful for estimating the quantitative risk of bacterial survival during inactivation. Copyright © 2017 Koyama et al.

Algorithm Calculates Cumulative Poisson Distribution

NASA Technical Reports Server (NTRS)

Bowerman, Paul N.; Nolty, Robert C.; Scheuer, Ernest M.

1992-01-01

Algorithm calculates accurate values of cumulative Poisson distribution under conditions where other algorithms fail because numbers are so small (underflow) or so large (overflow) that computer cannot process them. Factors inserted temporarily to prevent underflow and overflow. Implemented in CUMPOIS computer program described in "Cumulative Poisson Distribution Program" (NPO-17714).

On the validity of the Poisson assumption in sampling nanometer-sized aerosols

DOE Office of Scientific and Technical Information (OSTI.GOV)

Damit, Brian E; Wu, Dr. Chang-Yu; Cheng, Mengdawn

2014-01-01

A Poisson process is traditionally believed to apply to the sampling of aerosols. For a constant aerosol concentration, it is assumed that a Poisson process describes the fluctuation in the measured concentration because aerosols are stochastically distributed in space. Recent studies, however, have shown that sampling of micrometer-sized aerosols has non-Poissonian behavior with positive correlations. The validity of the Poisson assumption for nanometer-sized aerosols has not been examined and thus was tested in this study. Its validity was tested for four particle sizes - 10 nm, 25 nm, 50 nm and 100 nm - by sampling from indoor air withmore » a DMA- CPC setup to obtain a time series of particle counts. Five metrics were calculated from the data: pair-correlation function (PCF), time-averaged PCF, coefficient of variation, probability of measuring a concentration at least 25% greater than average, and posterior distributions from Bayesian inference. To identify departures from Poissonian behavior, these metrics were also calculated for 1,000 computer-generated Poisson time series with the same mean as the experimental data. For nearly all comparisons, the experimental data fell within the range of 80% of the Poisson-simulation values. Essentially, the metrics for the experimental data were indistinguishable from a simulated Poisson process. The greater influence of Brownian motion for nanometer-sized aerosols may explain the Poissonian behavior observed for smaller aerosols. Although the Poisson assumption was found to be valid in this study, it must be carefully applied as the results here do not definitively prove applicability in all sampling situations.« less

Statistical properties of superimposed stationary spike trains.

PubMed

Deger, Moritz; Helias, Moritz; Boucsein, Clemens; Rotter, Stefan

2012-06-01

The Poisson process is an often employed model for the activity of neuronal populations. It is known, though, that superpositions of realistic, non- Poisson spike trains are not in general Poisson processes, not even for large numbers of superimposed processes. Here we construct superimposed spike trains from intracellular in vivo recordings from rat neocortex neurons and compare their statistics to specific point process models. The constructed superimposed spike trains reveal strong deviations from the Poisson model. We find that superpositions of model spike trains that take the effective refractoriness of the neurons into account yield a much better description. A minimal model of this kind is the Poisson process with dead-time (PPD). For this process, and for superpositions thereof, we obtain analytical expressions for some second-order statistical quantities-like the count variability, inter-spike interval (ISI) variability and ISI correlations-and demonstrate the match with the in vivo data. We conclude that effective refractoriness is the key property that shapes the statistical properties of the superposition spike trains. We present new, efficient algorithms to generate superpositions of PPDs and of gamma processes that can be used to provide more realistic background input in simulations of networks of spiking neurons. Using these generators, we show in simulations that neurons which receive superimposed spike trains as input are highly sensitive for the statistical effects induced by neuronal refractoriness.

A Novel Method for Preparing Auxetic Foam from Closed-cell Polymer Foam Based on Steam Penetration and Condensation (SPC) Process.

PubMed

Fan, Donglei; Li, Minggang; Qiu, Jian; Xing, Haiping; Jiang, Zhiwei; Tang, Tao

2018-05-31

Auxetic materials are a class of materials possessing negative Poisson's ratio. Here we establish a novel method for preparing auxetic foam from closed-cell polymer foam based on steam penetration and condensation (SPC) process. Using polyethylene (PE) closed-cell foam as an example, the resultant foams treated by SPC process present negative Poisson's ratio during stretching and compression testing. The effect of steam-treated temperature and time on the conversion efficiency of negative Poisson's ratio foam is investigated, and the mechanism of SPC method for forming re-entrant structure is discussed. The results indicate that the presence of enough steam within the cells is a critical factor for the negative Poisson's ratio conversion in the SPC process. The pressure difference caused by steam condensation is the driving force for the conversion from conventional closed-cell foam to the negative Poisson's ratio foam. Furthermore, the applicability of SPC process for fabricating auxetic foam is studied by replacing PE foam by polyvinyl chloride (PVC) foam with closed-cell structure or replacing water steam by ethanol steam. The results verify the universality of SPC process for fabricating auxetic foams from conventional foams with closed-cell structure. In addition, we explored potential application of the obtained auxetic foams by SPC process in the fabrication of shape memory polymer materials.

Bayesian inference on multiscale models for poisson intensity estimation: applications to photon-limited image denoising.

PubMed

Lefkimmiatis, Stamatios; Maragos, Petros; Papandreou, George

2009-08-01

We present an improved statistical model for analyzing Poisson processes, with applications to photon-limited imaging. We build on previous work, adopting a multiscale representation of the Poisson process in which the ratios of the underlying Poisson intensities (rates) in adjacent scales are modeled as mixtures of conjugate parametric distributions. Our main contributions include: 1) a rigorous and robust regularized expectation-maximization (EM) algorithm for maximum-likelihood estimation of the rate-ratio density parameters directly from the noisy observed Poisson data (counts); 2) extension of the method to work under a multiscale hidden Markov tree model (HMT) which couples the mixture label assignments in consecutive scales, thus modeling interscale coefficient dependencies in the vicinity of image edges; 3) exploration of a 2-D recursive quad-tree image representation, involving Dirichlet-mixture rate-ratio densities, instead of the conventional separable binary-tree image representation involving beta-mixture rate-ratio densities; and 4) a novel multiscale image representation, which we term Poisson-Haar decomposition, that better models the image edge structure, thus yielding improved performance. Experimental results on standard images with artificially simulated Poisson noise and on real photon-limited images demonstrate the effectiveness of the proposed techniques.

The Validity of Poisson Assumptions in a Combined Loglinear/MDS Mapping Model.

ERIC Educational Resources Information Center

Everett, James E.

1993-01-01

Addresses objections to the validity of assuming a Poisson loglinear model as the generating process for citations from one journal into another. Fluctuations in citation rate, serial dependence on citations, impossibility of distinguishing between rate changes and serial dependence, evidence for changes in Poisson rate, and transitivity…

A Family of Poisson Processes for Use in Stochastic Models of Precipitation

NASA Astrophysics Data System (ADS)

Penland, C.

2013-12-01

Both modified Poisson processes and compound Poisson processes can be relevant to stochastic parameterization of precipitation. This presentation compares the dynamical properties of these systems and discusses the physical situations in which each might be appropriate. If the parameters describing either class of systems originate in hydrodynamics, then proper consideration of stochastic calculus is required during numerical implementation of the parameterization. It is shown here that an improper numerical treatment can have severe implications for estimating rainfall distributions, particularly in the tails of the distributions and, thus, on the frequency of extreme events.

Doubly stochastic Poisson process models for precipitation at fine time-scales

NASA Astrophysics Data System (ADS)

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.

Harmonic statistics

NASA Astrophysics Data System (ADS)

Eliazar, Iddo

2017-05-01

The exponential, the normal, and the Poisson statistical laws are of major importance due to their universality. Harmonic statistics are as universal as the three aforementioned laws, but yet they fall short in their 'public relations' for the following reason: the full scope of harmonic statistics cannot be described in terms of a statistical law. In this paper we describe harmonic statistics, in their full scope, via an object termed harmonic Poisson process: a Poisson process, over the positive half-line, with a harmonic intensity. The paper reviews the harmonic Poisson process, investigates its properties, and presents the connections of this object to an assortment of topics: uniform statistics, scale invariance, random multiplicative perturbations, Pareto and inverse-Pareto statistics, exponential growth and exponential decay, power-law renormalization, convergence and domains of attraction, the Langevin equation, diffusions, Benford's law, and 1/f noise.

Negative Binomial Process Count and Mixture Modeling.

PubMed

Zhou, Mingyuan; Carin, Lawrence

2015-02-01

The seemingly disjoint problems of count and mixture modeling are united under the negative binomial (NB) process. A gamma process is employed to model the rate measure of a Poisson process, whose normalization provides a random probability measure for mixture modeling and whose marginalization leads to an NB process for count modeling. A draw from the NB process consists of a Poisson distributed finite number of distinct atoms, each of which is associated with a logarithmic distributed number of data samples. We reveal relationships between various count- and mixture-modeling distributions and construct a Poisson-logarithmic bivariate distribution that connects the NB and Chinese restaurant table distributions. Fundamental properties of the models are developed, and we derive efficient Bayesian inference. It is shown that with augmentation and normalization, the NB process and gamma-NB process can be reduced to the Dirichlet process and hierarchical Dirichlet process, respectively. These relationships highlight theoretical, structural, and computational advantages of the NB process. A variety of NB processes, including the beta-geometric, beta-NB, marked-beta-NB, marked-gamma-NB and zero-inflated-NB processes, with distinct sharing mechanisms, are also constructed. These models are applied to topic modeling, with connections made to existing algorithms under Poisson factor analysis. Example results show the importance of inferring both the NB dispersion and probability parameters.

Discrimination of shot-noise-driven Poisson processes by external dead time - Application of radioluminescence from glass

NASA Technical Reports Server (NTRS)

Saleh, B. E. A.; Tavolacci, J. T.; Teich, M. C.

1981-01-01

Ways in which dead time can be used to constructively enhance or diminish the effects of point processes that display bunching in the shot-noise-driven doubly stochastic Poisson point process (SNDP) are discussed. Interrelations between photocount bunching arising in the SNDP and the antibunching character arising from dead-time effects are investigated. It is demonstrated that the dead-time-modified count mean and variance for an arbitrary doubly stochastic Poisson point process can be obtained from the Laplace transform of the single-fold and joint-moment-generating functions for the driving rate process. The theory is in good agreement with experimental values for radioluminescence radiation in fused silica, quartz, and glass, and the process has many applications in pulse, particle, and photon detection.

Matrix decomposition graphics processing unit solver for Poisson image editing

NASA Astrophysics Data System (ADS)

Lei, Zhao; Wei, Li

2012-10-01

In recent years, gradient-domain methods have been widely discussed in the image processing field, including seamless cloning and image stitching. These algorithms are commonly carried out by solving a large sparse linear system: the Poisson equation. However, solving the Poisson equation is a computational and memory intensive task which makes it not suitable for real-time image editing. A new matrix decomposition graphics processing unit (GPU) solver (MDGS) is proposed to settle the problem. A matrix decomposition method is used to distribute the work among GPU threads, so that MDGS will take full advantage of the computing power of current GPUs. Additionally, MDGS is a hybrid solver (combines both the direct and iterative techniques) and has two-level architecture. These enable MDGS to generate identical solutions with those of the common Poisson methods and achieve high convergence rate in most cases. This approach is advantageous in terms of parallelizability, enabling real-time image processing, low memory-taken and extensive applications.

Exact solution for the Poisson field in a semi-infinite strip.

PubMed

Cohen, Yossi; Rothman, Daniel H

2017-04-01

The Poisson equation is associated with many physical processes. Yet exact analytic solutions for the two-dimensional Poisson field are scarce. Here we derive an analytic solution for the Poisson equation with constant forcing in a semi-infinite strip. We provide a method that can be used to solve the field in other intricate geometries. We show that the Poisson flux reveals an inverse square-root singularity at a tip of a slit, and identify a characteristic length scale in which a small perturbation, in a form of a new slit, is screened by the field. We suggest that this length scale expresses itself as a characteristic spacing between tips in real Poisson networks that grow in response to fluxes at tips.

Minimum risk wavelet shrinkage operator for Poisson image denoising.

PubMed

Cheng, Wu; Hirakawa, Keigo

2015-05-01

The pixel values of images taken by an image sensor are said to be corrupted by Poisson noise. To date, multiscale Poisson image denoising techniques have processed Haar frame and wavelet coefficients--the modeling of coefficients is enabled by the Skellam distribution analysis. We extend these results by solving for shrinkage operators for Skellam that minimizes the risk functional in the multiscale Poisson image denoising setting. The minimum risk shrinkage operator of this kind effectively produces denoised wavelet coefficients with minimum attainable L2 error.

Estimating the intensity of a cyclic Poisson process in the presence of additive and multiplicative linear trend

NASA Astrophysics Data System (ADS)

Wayan Mangku, I.

2017-10-01

In this paper we survey some results on estimation of the intensity function of a cyclic Poisson process in the presence of additive and multiplicative linear trend. We do not assume any parametric form for the cyclic component of the intensity function, except that it is periodic. Moreover, we consider the case when there is only a single realization of the Poisson process is observed in a bounded interval. The considered estimators are weakly and strongly consistent when the size of the observation interval indefinitely expands. Asymptotic approximations to the bias and variance of those estimators are presented.

Gene regulation and noise reduction by coupling of stochastic processes

NASA Astrophysics Data System (ADS)

Ramos, Alexandre F.; Hornos, José Eduardo M.; Reinitz, John

2015-02-01

Here we characterize the low-noise regime of a stochastic model for a negative self-regulating binary gene. The model has two stochastic variables, the protein number and the state of the gene. Each state of the gene behaves as a protein source governed by a Poisson process. The coupling between the two gene states depends on protein number. This fact has a very important implication: There exist protein production regimes characterized by sub-Poissonian noise because of negative covariance between the two stochastic variables of the model. Hence the protein numbers obey a probability distribution that has a peak that is sharper than those of the two coupled Poisson processes that are combined to produce it. Biochemically, the noise reduction in protein number occurs when the switching of the genetic state is more rapid than protein synthesis or degradation. We consider the chemical reaction rates necessary for Poisson and sub-Poisson processes in prokaryotes and eucaryotes. Our results suggest that the coupling of multiple stochastic processes in a negative covariance regime might be a widespread mechanism for noise reduction.

Gene regulation and noise reduction by coupling of stochastic processes

PubMed Central

Hornos, José Eduardo M.; Reinitz, John

2015-01-01

Here we characterize the low noise regime of a stochastic model for a negative self-regulating binary gene. The model has two stochastic variables, the protein number and the state of the gene. Each state of the gene behaves as a protein source governed by a Poisson process. The coupling between the the two gene states depends on protein number. This fact has a very important implication: there exist protein production regimes characterized by sub-Poissonian noise because of negative covariance between the two stochastic variables of the model. Hence the protein numbers obey a probability distribution that has a peak that is sharper than those of the two coupled Poisson processes that are combined to produce it. Biochemically, the noise reduction in protein number occurs when the switching of genetic state is more rapid than protein synthesis or degradation. We consider the chemical reaction rates necessary for Poisson and sub-Poisson processes in prokaryotes and eucaryotes. Our results suggest that the coupling of multiple stochastic processes in a negative covariance regime might be a widespread mechanism for noise reduction. PMID:25768447

Gene regulation and noise reduction by coupling of stochastic processes.

PubMed

Ramos, Alexandre F; Hornos, José Eduardo M; Reinitz, John

2015-02-01

Here we characterize the low-noise regime of a stochastic model for a negative self-regulating binary gene. The model has two stochastic variables, the protein number and the state of the gene. Each state of the gene behaves as a protein source governed by a Poisson process. The coupling between the two gene states depends on protein number. This fact has a very important implication: There exist protein production regimes characterized by sub-Poissonian noise because of negative covariance between the two stochastic variables of the model. Hence the protein numbers obey a probability distribution that has a peak that is sharper than those of the two coupled Poisson processes that are combined to produce it. Biochemically, the noise reduction in protein number occurs when the switching of the genetic state is more rapid than protein synthesis or degradation. We consider the chemical reaction rates necessary for Poisson and sub-Poisson processes in prokaryotes and eucaryotes. Our results suggest that the coupling of multiple stochastic processes in a negative covariance regime might be a widespread mechanism for noise reduction.

Dead time corrections for inbeam γ-spectroscopy measurements

NASA Astrophysics Data System (ADS)

Boromiza, M.; Borcea, C.; Negret, A.; Olacel, A.; Suliman, G.

2017-08-01

Relatively high counting rates were registered in a proton inelastic scattering experiment on 16O and 28Si using HPGe detectors which was performed at the Tandem facility of IFIN-HH, Bucharest. In consequence, dead time corrections were needed in order to determine the absolute γ-production cross sections. Considering that the real counting rate follows a Poisson distribution, the dead time correction procedure is reformulated in statistical terms. The arriving time interval between the incoming events (Δt) obeys an exponential distribution with a single parameter - the average of the associated Poisson distribution. We use this mathematical connection to calculate and implement the dead time corrections for the counting rates of the mentioned experiment. Also, exploiting an idea introduced by Pommé et al., we describe a consistent method for calculating the dead time correction which completely eludes the complicated problem of measuring the dead time of a given detection system. Several comparisons are made between the corrections implemented through this method and by using standard (phenomenological) dead time models and we show how these results were used for correcting our experimental cross sections.

Cumulative sum control charts for monitoring geometrically inflated Poisson processes: An application to infectious disease counts data.

PubMed

Rakitzis, Athanasios C; Castagliola, Philippe; Maravelakis, Petros E

2018-02-01

In this work, we study upper-sided cumulative sum control charts that are suitable for monitoring geometrically inflated Poisson processes. We assume that a process is properly described by a two-parameter extension of the zero-inflated Poisson distribution, which can be used for modeling count data with an excessive number of zero and non-zero values. Two different upper-sided cumulative sum-type schemes are considered, both suitable for the detection of increasing shifts in the average of the process. Aspects of their statistical design are discussed and their performance is compared under various out-of-control situations. Changes in both parameters of the process are considered. Finally, the monitoring of the monthly cases of poliomyelitis in the USA is given as an illustrative example.

Vertically Integrated Seismological Analysis I : Modeling

NASA Astrophysics Data System (ADS)

Russell, S.; Arora, N. S.; Jordan, M. I.; Sudderth, E.

2009-12-01

As part of its CTBT verification efforts, the International Data Centre (IDC) analyzes seismic and other signals collected from hundreds of stations around the world. Current processing at the IDC proceeds in a series of pipelined stages. From station processing to network processing, each decision is made on the basis of local information. This has the advantage of efficiency, and simplifies the structure of software implementations. However, this approach may reduce accuracy in the detection and phase classification of arrivals, association of detections to hypothesized events, and localization of small-magnitude events.In our work, we approach such detection and association problems as ones of probabilistic inference. In simple terms, let X be a random variable ranging over all possible collections of events, with each event defined by time, location, magnitude, and type (natural or man-made). Let Y range over all possible waveform signal recordings at all detection stations. Then Pθ(X) describes a parameterized generative prior over events, and P[|#30#|]φ(Y | X) describes how the signal is propagated and measured (including travel time, selective absorption and scattering, noise, artifacts, sensor bias, sensor failures, etc.). Given observed recordings Y = y, we are interested in the posterior P(X | Y = y), and perhaps in the value of X that maximizes it—i.e., the most likely explanation for all the sensor readings. As detailed below, an additional focus of our work is to robustly learn appropriate model parameters θ and φ from historical data. The primary advantage we expect is that decisions about arrivals, phase classifications, and associations are made with the benefit of all available evidence, not just the local signal or predefined recipes. Important phenomena—such as the successful detection of sub-threshold signals, correction of phase classifications using arrival information at other stations, and removal of false events based on the absence of signals—should all fall out of our probabilistic framework without the need for special processing rules. In our baseline model, natural events occur according to a spatially inhomogeneous Poisson process. Complex events (swarms and aftershocks) may then be captured via temporally inhomogeneous extensions. Man-made events have a uniform probability of occurring anywhere on the earth, with a tendency to occur closer to the surface. Phases are modelled via their amplitude, frequency distribution, and origin. In the simplest case, transmission times are characterized via the one-dimensional IASPEI-91 model, accounting for model errors with Gaussian uncertainty. Such homogeneous, approximate physical models can be further refined via historical data and previously developed corrections. Signal measurements are captured by station-specific models, based on sensor types and geometries, local frequency absorption characteristics, and time-varying noise models. At the conference, we expect to be able to quantitatively demonstrate the advantages of our approach, at least for simulated data. When reporting their findings, such systems can easily flag low-confidence events, unexplained arrivals, and ambiguous classifications to focus the efforts of expert analysts.

LDPC-PPM Coding Scheme for Optical Communication

NASA Technical Reports Server (NTRS)

Barsoum, Maged; Moision, Bruce; Divsalar, Dariush; Fitz, Michael

2009-01-01

In a proposed coding-and-modulation/demodulation-and-decoding scheme for a free-space optical communication system, an error-correcting code of the low-density parity-check (LDPC) type would be concatenated with a modulation code that consists of a mapping of bits to pulse-position-modulation (PPM) symbols. Hence, the scheme is denoted LDPC-PPM. This scheme could be considered a competitor of a related prior scheme in which an outer convolutional error-correcting code is concatenated with an interleaving operation, a bit-accumulation operation, and a PPM inner code. Both the prior and present schemes can be characterized as serially concatenated pulse-position modulation (SCPPM) coding schemes. Figure 1 represents a free-space optical communication system based on either the present LDPC-PPM scheme or the prior SCPPM scheme. At the transmitting terminal, the original data (u) are processed by an encoder into blocks of bits (a), and the encoded data are mapped to PPM of an optical signal (c). For the purpose of design and analysis, the optical channel in which the PPM signal propagates is modeled as a Poisson point process. At the receiving terminal, the arriving optical signal (y) is demodulated to obtain an estimate (a^) of the coded data, which is then processed by a decoder to obtain an estimate (u^) of the original data.

Renewal processes based on generalized Mittag-Leffler waiting times

NASA Astrophysics Data System (ADS)

Cahoy, Dexter O.; Polito, Federico

2013-03-01

The fractional Poisson process has recently attracted experts from several fields of study. Its natural generalization of the ordinary Poisson process made the model more appealing for real-world applications. In this paper, we generalized the standard and fractional Poisson processes through the waiting time distribution, and showed their relations to an integral operator with a generalized Mittag-Leffler function in the kernel. The waiting times of the proposed renewal processes have the generalized Mittag-Leffler and stretched-squashed Mittag-Leffler distributions. Note that the generalizations naturally provide greater flexibility in modeling real-life renewal processes. Algorithms to simulate sample paths and to estimate the model parameters are derived. Note also that these procedures are necessary to make these models more usable in practice. State probabilities and other qualitative or quantitative features of the models are also discussed.

A poisson process model for hip fracture risk.

PubMed

Schechner, Zvi; Luo, Gangming; Kaufman, Jonathan J; Siffert, Robert S

2010-08-01

The primary method for assessing fracture risk in osteoporosis relies primarily on measurement of bone mass. Estimation of fracture risk is most often evaluated using logistic or proportional hazards models. Notwithstanding the success of these models, there is still much uncertainty as to who will or will not suffer a fracture. This has led to a search for other components besides mass that affect bone strength. The purpose of this paper is to introduce a new mechanistic stochastic model that characterizes the risk of hip fracture in an individual. A Poisson process is used to model the occurrence of falls, which are assumed to occur at a rate, lambda. The load induced by a fall is assumed to be a random variable that has a Weibull probability distribution. The combination of falls together with loads leads to a compound Poisson process. By retaining only those occurrences of the compound Poisson process that result in a hip fracture, a thinned Poisson process is defined that itself is a Poisson process. The fall rate is modeled as an affine function of age, and hip strength is modeled as a power law function of bone mineral density (BMD). The risk of hip fracture can then be computed as a function of age and BMD. By extending the analysis to a Bayesian framework, the conditional densities of BMD given a prior fracture and no prior fracture can be computed and shown to be consistent with clinical observations. In addition, the conditional probabilities of fracture given a prior fracture and no prior fracture can also be computed, and also demonstrate results similar to clinical data. The model elucidates the fact that the hip fracture process is inherently random and improvements in hip strength estimation over and above that provided by BMD operate in a highly "noisy" environment and may therefore have little ability to impact clinical practice.

Birth and Death Process Modeling Leads to the Poisson Distribution: A Journey Worth Taking

ERIC Educational Resources Information Center

Rash, Agnes M.; Winkel, Brian J.

2009-01-01

This paper describes details of development of the general birth and death process from which we can extract the Poisson process as a special case. This general process is appropriate for a number of courses and units in courses and can enrich the study of mathematics for students as it touches and uses a diverse set of mathematical topics, e.g.,…

Fast and Accurate Poisson Denoising With Trainable Nonlinear Diffusion.

PubMed

Feng, Wensen; Qiao, Peng; Chen, Yunjin; Wensen Feng; Peng Qiao; Yunjin Chen; Feng, Wensen; Chen, Yunjin; Qiao, Peng

2018-06-01

The degradation of the acquired signal by Poisson noise is a common problem for various imaging applications, such as medical imaging, night vision, and microscopy. Up to now, many state-of-the-art Poisson denoising techniques mainly concentrate on achieving utmost performance, with little consideration for the computation efficiency. Therefore, in this paper we aim to propose an efficient Poisson denoising model with both high computational efficiency and recovery quality. To this end, we exploit the newly developed trainable nonlinear reaction diffusion (TNRD) model which has proven an extremely fast image restoration approach with performance surpassing recent state-of-the-arts. However, the straightforward direct gradient descent employed in the original TNRD-based denoising task is not applicable in this paper. To solve this problem, we resort to the proximal gradient descent method. We retrain the model parameters, including the linear filters and influence functions by taking into account the Poisson noise statistics, and end up with a well-trained nonlinear diffusion model specialized for Poisson denoising. The trained model provides strongly competitive results against state-of-the-art approaches, meanwhile bearing the properties of simple structure and high efficiency. Furthermore, our proposed model comes along with an additional advantage, that the diffusion process is well-suited for parallel computation on graphics processing units (GPUs). For images of size , our GPU implementation takes less than 0.1 s to produce state-of-the-art Poisson denoising performance.

Poisson, Poisson-gamma and zero-inflated regression models of motor vehicle crashes: balancing statistical fit and theory.

PubMed

Lord, Dominique; Washington, Simon P; Ivan, John N

2005-01-01

There has been considerable research conducted over the last 20 years focused on predicting motor vehicle crashes on transportation facilities. The range of statistical models commonly applied includes binomial, Poisson, Poisson-gamma (or negative binomial), zero-inflated Poisson and negative binomial models (ZIP and ZINB), and multinomial probability models. Given the range of possible modeling approaches and the host of assumptions with each modeling approach, making an intelligent choice for modeling motor vehicle crash data is difficult. There is little discussion in the literature comparing different statistical modeling approaches, identifying which statistical models are most appropriate for modeling crash data, and providing a strong justification from basic crash principles. In the recent literature, it has been suggested that the motor vehicle crash process can successfully be modeled by assuming a dual-state data-generating process, which implies that entities (e.g., intersections, road segments, pedestrian crossings, etc.) exist in one of two states-perfectly safe and unsafe. As a result, the ZIP and ZINB are two models that have been applied to account for the preponderance of "excess" zeros frequently observed in crash count data. The objective of this study is to provide defensible guidance on how to appropriate model crash data. We first examine the motor vehicle crash process using theoretical principles and a basic understanding of the crash process. It is shown that the fundamental crash process follows a Bernoulli trial with unequal probability of independent events, also known as Poisson trials. We examine the evolution of statistical models as they apply to the motor vehicle crash process, and indicate how well they statistically approximate the crash process. We also present the theory behind dual-state process count models, and note why they have become popular for modeling crash data. A simulation experiment is then conducted to demonstrate how crash data give rise to "excess" zeros frequently observed in crash data. It is shown that the Poisson and other mixed probabilistic structures are approximations assumed for modeling the motor vehicle crash process. Furthermore, it is demonstrated that under certain (fairly common) circumstances excess zeros are observed-and that these circumstances arise from low exposure and/or inappropriate selection of time/space scales and not an underlying dual state process. In conclusion, carefully selecting the time/space scales for analysis, including an improved set of explanatory variables and/or unobserved heterogeneity effects in count regression models, or applying small-area statistical methods (observations with low exposure) represent the most defensible modeling approaches for datasets with a preponderance of zeros.

Sample size calculations for comparative clinical trials with over-dispersed Poisson process data.

PubMed

Matsui, Shigeyuki

2005-05-15

This paper develops a new formula for sample size calculations for comparative clinical trials with Poisson or over-dispersed Poisson process data. The criteria for sample size calculations is developed on the basis of asymptotic approximations for a two-sample non-parametric test to compare the empirical event rate function between treatment groups. This formula can accommodate time heterogeneity, inter-patient heterogeneity in event rate, and also, time-varying treatment effects. An application of the formula to a trial for chronic granulomatous disease is provided. Copyright 2004 John Wiley & Sons, Ltd.

A new approach for handling longitudinal count data with zero-inflation and overdispersion: poisson geometric process model.

PubMed

Wan, Wai-Yin; Chan, Jennifer S K

2009-08-01

For time series of count data, correlated measurements, clustering as well as excessive zeros occur simultaneously in biomedical applications. Ignoring such effects might contribute to misleading treatment outcomes. A generalized mixture Poisson geometric process (GMPGP) model and a zero-altered mixture Poisson geometric process (ZMPGP) model are developed from the geometric process model, which was originally developed for modelling positive continuous data and was extended to handle count data. These models are motivated by evaluating the trend development of new tumour counts for bladder cancer patients as well as by identifying useful covariates which affect the count level. The models are implemented using Bayesian method with Markov chain Monte Carlo (MCMC) algorithms and are assessed using deviance information criterion (DIC).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eliazar, Iddo, E-mail: eliazar@post.tau.ac.il

The exponential, the normal, and the Poisson statistical laws are of major importance due to their universality. Harmonic statistics are as universal as the three aforementioned laws, but yet they fall short in their ‘public relations’ for the following reason: the full scope of harmonic statistics cannot be described in terms of a statistical law. In this paper we describe harmonic statistics, in their full scope, via an object termed harmonic Poisson process: a Poisson process, over the positive half-line, with a harmonic intensity. The paper reviews the harmonic Poisson process, investigates its properties, and presents the connections of thismore » object to an assortment of topics: uniform statistics, scale invariance, random multiplicative perturbations, Pareto and inverse-Pareto statistics, exponential growth and exponential decay, power-law renormalization, convergence and domains of attraction, the Langevin equation, diffusions, Benford’s law, and 1/f noise. - Highlights: • Harmonic statistics are described and reviewed in detail. • Connections to various statistical laws are established. • Connections to perturbation, renormalization and dynamics are established.« less

Integrate-and-fire vs Poisson models of LGN input to V1 cortex: noisier inputs reduce orientation selectivity

PubMed Central

Lin, I-Chun; Xing, Dajun; Shapley, Robert

2014-01-01

One of the reasons the visual cortex has attracted the interest of computational neuroscience is that it has well-defined inputs. The lateral geniculate nucleus (LGN) of the thalamus is the source of visual signals to the primary visual cortex (V1). Most large-scale cortical network models approximate the spike trains of LGN neurons as simple Poisson point processes. However, many studies have shown that neurons in the early visual pathway are capable of spiking with high temporal precision and their discharges are not Poisson-like. To gain an understanding of how response variability in the LGN influences the behavior of V1, we study response properties of model V1 neurons that receive purely feedforward inputs from LGN cells modeled either as noisy leaky integrate-and-fire (NLIF) neurons or as inhomogeneous Poisson processes. We first demonstrate that the NLIF model is capable of reproducing many experimentally observed statistical properties of LGN neurons. Then we show that a V1 model in which the LGN input to a V1 neuron is modeled as a group of NLIF neurons produces higher orientation selectivity than the one with Poisson LGN input. The second result implies that statistical characteristics of LGN spike trains are important for V1's function. We conclude that physiologically motivated models of V1 need to include more realistic LGN spike trains that are less noisy than inhomogeneous Poisson processes. PMID:22684587

Integrate-and-fire vs Poisson models of LGN input to V1 cortex: noisier inputs reduce orientation selectivity.

PubMed

Lin, I-Chun; Xing, Dajun; Shapley, Robert

2012-12-01

One of the reasons the visual cortex has attracted the interest of computational neuroscience is that it has well-defined inputs. The lateral geniculate nucleus (LGN) of the thalamus is the source of visual signals to the primary visual cortex (V1). Most large-scale cortical network models approximate the spike trains of LGN neurons as simple Poisson point processes. However, many studies have shown that neurons in the early visual pathway are capable of spiking with high temporal precision and their discharges are not Poisson-like. To gain an understanding of how response variability in the LGN influences the behavior of V1, we study response properties of model V1 neurons that receive purely feedforward inputs from LGN cells modeled either as noisy leaky integrate-and-fire (NLIF) neurons or as inhomogeneous Poisson processes. We first demonstrate that the NLIF model is capable of reproducing many experimentally observed statistical properties of LGN neurons. Then we show that a V1 model in which the LGN input to a V1 neuron is modeled as a group of NLIF neurons produces higher orientation selectivity than the one with Poisson LGN input. The second result implies that statistical characteristics of LGN spike trains are important for V1's function. We conclude that physiologically motivated models of V1 need to include more realistic LGN spike trains that are less noisy than inhomogeneous Poisson processes.

Poisson Coordinates.

PubMed

Li, Xian-Ying; Hu, Shi-Min

2013-02-01

Harmonic functions are the critical points of a Dirichlet energy functional, the linear projections of conformal maps. They play an important role in computer graphics, particularly for gradient-domain image processing and shape-preserving geometric computation. We propose Poisson coordinates, a novel transfinite interpolation scheme based on the Poisson integral formula, as a rapid way to estimate a harmonic function on a certain domain with desired boundary values. Poisson coordinates are an extension of the Mean Value coordinates (MVCs) which inherit their linear precision, smoothness, and kernel positivity. We give explicit formulas for Poisson coordinates in both continuous and 2D discrete forms. Superior to MVCs, Poisson coordinates are proved to be pseudoharmonic (i.e., they reproduce harmonic functions on n-dimensional balls). Our experimental results show that Poisson coordinates have lower Dirichlet energies than MVCs on a number of typical 2D domains (particularly convex domains). As well as presenting a formula, our approach provides useful insights for further studies on coordinates-based interpolation and fast estimation of harmonic functions.

Poissonian renormalizations, exponentials, and power laws.

PubMed

Eliazar, Iddo

2013-05-01

This paper presents a comprehensive "renormalization study" of Poisson processes governed by exponential and power-law intensities. These Poisson processes are of fundamental importance, as they constitute the very bedrock of the universal extreme-value laws of Gumbel, Fréchet, and Weibull. Applying the method of Poissonian renormalization we analyze the emergence of these Poisson processes, unveil their intrinsic dynamical structures, determine their domains of attraction, and characterize their structural phase transitions. These structural phase transitions are shown to be governed by uniform and harmonic intensities, to have universal domains of attraction, to uniquely display intrinsic invariance, and to be intimately connected to "white noise" and to "1/f noise." Thus, we establish a Poissonian explanation to the omnipresence of white and 1/f noises.

Poisson mixture model for measurements using counting.

PubMed

Miller, Guthrie; Justus, Alan; Vostrotin, Vadim; Dry, Donald; Bertelli, Luiz

2010-03-01

Starting with the basic Poisson statistical model of a counting measurement process, 'extraPoisson' variance or 'overdispersion' are included by assuming that the Poisson parameter representing the mean number of counts itself comes from another distribution. The Poisson parameter is assumed to be given by the quantity of interest in the inference process multiplied by a lognormally distributed normalising coefficient plus an additional lognormal background that might be correlated with the normalising coefficient (shared uncertainty). The example of lognormal environmental background in uranium urine data is discussed. An additional uncorrelated background is also included. The uncorrelated background is estimated from a background count measurement using Bayesian arguments. The rather complex formulas are validated using Monte Carlo. An analytical expression is obtained for the probability distribution of gross counts coming from the uncorrelated background, which allows straightforward calculation of a classical decision level in the form of a gross-count alarm point with a desired false-positive rate. The main purpose of this paper is to derive formulas for exact likelihood calculations in the case of various kinds of backgrounds.

Weblog patterns and human dynamics with decreasing interest

NASA Astrophysics Data System (ADS)

Guo, J.-L.; Fan, C.; Guo, Z.-H.

2011-06-01

In order to describe the phenomenon that people's interest in doing something always keep high in the beginning while gradually decreases until reaching the balance, a model which describes the attenuation of interest is proposed to reflect the fact that people's interest becomes more stable after a long time. We give a rigorous analysis on this model by non-homogeneous Poisson processes. Our analysis indicates that the interval distribution of arrival-time is a mixed distribution with exponential and power-law feature, which is a power law with an exponential cutoff. After that, we collect blogs in ScienceNet.cn and carry on empirical study on the interarrival time distribution. The empirical results agree well with the theoretical analysis, obeying a special power law with the exponential cutoff, that is, a special kind of Gamma distribution. These empirical results verify the model by providing an evidence for a new class of phenomena in human dynamics. It can be concluded that besides power-law distributions, there are other distributions in human dynamics. These findings demonstrate the variety of human behavior dynamics.

Scheduling admissions and reducing variability in bed demand.

PubMed

Bekker, René; Koeleman, Paulien M

2011-09-01

Variability in admissions and lengths of stay inherently leads to variability in bed occupancy. The aim of this paper is to analyse the impact of these sources of variability on the required amount of capacity and to determine admission quota for scheduled admissions to regulate the occupancy pattern. For the impact of variability on the required number of beds, we use a heavy-traffic limit theorem for the G/G/∞ queue yielding an intuitively appealing approximation in case the arrival process is not Poisson. Also, given a structural weekly admission pattern, we apply a time-dependent analysis to determine the mean offered load per day. This time-dependent analysis is combined with a Quadratic Programming model to determine the optimal number of elective admissions per day, such that an average desired daily occupancy is achieved. From the mathematical results, practical scenarios and guidelines are derived that can be used by hospital managers and support the method of quota scheduling. In practice, the results can be implemented by providing admission quota prescribing the target number of admissions for each patient group.

Paretian Poisson Processes

NASA Astrophysics Data System (ADS)

Eliazar, Iddo; Klafter, Joseph

2008-05-01

Many random populations can be modeled as a countable set of points scattered randomly on the positive half-line. The points may represent magnitudes of earthquakes and tornados, masses of stars, market values of public companies, etc. In this article we explore a specific class of random such populations we coin ` Paretian Poisson processes'. This class is elemental in statistical physics—connecting together, in a deep and fundamental way, diverse issues including: the Poisson distribution of the Law of Small Numbers; Paretian tail statistics; the Fréchet distribution of Extreme Value Theory; the one-sided Lévy distribution of the Central Limit Theorem; scale-invariance, renormalization and fractality; resilience to random perturbations.

Architecture and robustness tradeoffs in speed-scaled queues with application to energy management

NASA Astrophysics Data System (ADS)

Dinh, Tuan V.; Andrew, Lachlan L. H.; Nazarathy, Yoni

2014-08-01

We consider single-pass, lossless, queueing systems at steady-state subject to Poisson job arrivals at an unknown rate. Service rates are allowed to depend on the number of jobs in the system, up to a fixed maximum, and power consumption is an increasing function of speed. The goal is to control the state dependent service rates such that both energy consumption and delay are kept low. We consider a linear combination of the mean job delay and energy consumption as the performance measure. We examine both the 'architecture' of the system, which we define as a specification of the number of speeds that the system can choose from, and the 'design' of the system, which we define as the actual speeds available. Previous work has illustrated that when the arrival rate is precisely known, there is little benefit in introducing complex (multi-speed) architectures, yet in view of parameter uncertainty, allowing a variable number of speeds improves robustness. We quantify the tradeoffs of architecture specification with respect to robustness, analysing both global robustness and a newly defined measure which we call local robustness.

Optimal control of M/M/1 two-phase queueing system with state-dependent arrival rate, server breakdowns, delayed repair, and N-policy

NASA Astrophysics Data System (ADS)

Rao, Hanumantha; Kumar, Vasanta; Srinivasa Rao, T.; Srinivasa Kumar, B.

2018-04-01

In this paper, we examine a two-stage queueing system where the arrivals are Poisson with rate depends on the condition of the server to be specific: vacation, pre-service, operational or breakdown state. The service station is liable to breakdowns and deferral in repair because of non-accessibility of the repair facility. The service is in two basic stages, the first being bulk service to every one of the customers holding up on the line and the second stage is individual to each of them. The server works under N-policy. The server needs preliminary time (startup time) to begin batch service after a vacation period. Startup times, uninterrupted service times, the length of each vacation period, delay times and service times follows an exponential distribution. The closed form of expressions for the mean system size at different conditions of the server is determined. Numerical investigations are directed to concentrate the impact of the system parameters on the ideal limit N and the minimum base expected unit cost.

Time distributions of solar energetic particle events: Are SEPEs really random?

NASA Astrophysics Data System (ADS)

Jiggens, P. T. A.; Gabriel, S. B.

2009-10-01

Solar energetic particle events (SEPEs) can exhibit flux increases of several orders of magnitude over background levels and have always been considered to be random in nature in statistical models with no dependence of any one event on the occurrence of previous events. We examine whether this assumption of randomness in time is correct. Engineering modeling of SEPEs is important to enable reliable and efficient design of both Earth-orbiting and interplanetary spacecraft and future manned missions to Mars and the Moon. All existing engineering models assume that the frequency of SEPEs follows a Poisson process. We present analysis of the event waiting times using alternative distributions described by Lévy and time-dependent Poisson processes and compared these with the usual Poisson distribution. The results show significant deviation from a Poisson process and indicate that the underlying physical processes might be more closely related to a Lévy-type process, suggesting that there is some inherent “memory” in the system. Inherent Poisson assumptions of stationarity and event independence are investigated, and it appears that they do not hold and can be dependent upon the event definition used. SEPEs appear to have some memory indicating that events are not completely random with activity levels varying even during solar active periods and are characterized by clusters of events. This could have significant ramifications for engineering models of the SEP environment, and it is recommended that current statistical engineering models of the SEP environment should be modified to incorporate long-term event dependency and short-term system memory.

The contribution of simple random sampling to observed variations in faecal egg counts.

PubMed

Torgerson, Paul R; Paul, Michaela; Lewis, Fraser I

2012-09-10

It has been over 100 years since the classical paper published by Gosset in 1907, under the pseudonym "Student", demonstrated that yeast cells suspended in a fluid and measured by a haemocytometer conformed to a Poisson process. Similarly parasite eggs in a faecal suspension also conform to a Poisson process. Despite this there are common misconceptions how to analyse or interpret observations from the McMaster or similar quantitative parasitic diagnostic techniques, widely used for evaluating parasite eggs in faeces. The McMaster technique can easily be shown from a theoretical perspective to give variable results that inevitably arise from the random distribution of parasite eggs in a well mixed faecal sample. The Poisson processes that lead to this variability are described and illustrative examples of the potentially large confidence intervals that can arise from observed faecal eggs counts that are calculated from the observations on a McMaster slide. Attempts to modify the McMaster technique, or indeed other quantitative techniques, to ensure uniform egg counts are doomed to failure and belie ignorance of Poisson processes. A simple method to immediately identify excess variation/poor sampling from replicate counts is provided. Copyright © 2012 Elsevier B.V. All rights reserved.

Pattern analysis of community health center location in Surabaya using spatial Poisson point process

NASA Astrophysics Data System (ADS)

Kusumaningrum, Choriah Margareta; Iriawan, Nur; Winahju, Wiwiek Setya

2017-11-01

Community health center (puskesmas) is one of the closest health service facilities for the community, which provide healthcare for population on sub-district level as one of the government-mandated community health clinics located across Indonesia. The increasing number of this puskesmas does not directly comply the fulfillment of basic health services needed in such region. Ideally, a puskesmas has to cover up to maximum 30,000 people. The number of puskesmas in Surabaya indicates an unbalance spread in all of the area. This research aims to analyze the spread of puskesmas in Surabaya using spatial Poisson point process model in order to get the effective location of Surabaya's puskesmas which based on their location. The results of the analysis showed that the distribution pattern of puskesmas in Surabaya is non-homogeneous Poisson process and is approched by mixture Poisson model. Based on the estimated model obtained by using Bayesian mixture model couple with MCMC process, some characteristics of each puskesmas have no significant influence as factors to decide the addition of health center in such location. Some factors related to the areas of sub-districts have to be considered as covariate to make a decision adding the puskesmas in Surabaya.

Itô and Stratonovich integrals on compound renewal processes: the normal/Poisson case

NASA Astrophysics Data System (ADS)

Germano, Guido; Politi, Mauro; Scalas, Enrico; Schilling, René L.

2010-06-01

Continuous-time random walks, or compound renewal processes, are pure-jump stochastic processes with several applications in insurance, finance, economics and physics. Based on heuristic considerations, a definition is given for stochastic integrals driven by continuous-time random walks, which includes the Itô and Stratonovich cases. It is then shown how the definition can be used to compute these two stochastic integrals by means of Monte Carlo simulations. Our example is based on the normal compound Poisson process, which in the diffusive limit converges to the Wiener process.

Poissonian renormalizations, exponentials, and power laws

NASA Astrophysics Data System (ADS)

Eliazar, Iddo

2013-05-01

This paper presents a comprehensive “renormalization study” of Poisson processes governed by exponential and power-law intensities. These Poisson processes are of fundamental importance, as they constitute the very bedrock of the universal extreme-value laws of Gumbel, Fréchet, and Weibull. Applying the method of Poissonian renormalization we analyze the emergence of these Poisson processes, unveil their intrinsic dynamical structures, determine their domains of attraction, and characterize their structural phase transitions. These structural phase transitions are shown to be governed by uniform and harmonic intensities, to have universal domains of attraction, to uniquely display intrinsic invariance, and to be intimately connected to “white noise” and to “1/f noise.” Thus, we establish a Poissonian explanation to the omnipresence of white and 1/f noises.

Stochastic modeling for neural spiking events based on fractional superstatistical Poisson process

NASA Astrophysics Data System (ADS)

Konno, Hidetoshi; Tamura, Yoshiyasu

2018-01-01

In neural spike counting experiments, it is known that there are two main features: (i) the counting number has a fractional power-law growth with time and (ii) the waiting time (i.e., the inter-spike-interval) distribution has a heavy tail. The method of superstatistical Poisson processes (SSPPs) is examined whether these main features are properly modeled. Although various mixed/compound Poisson processes are generated with selecting a suitable distribution of the birth-rate of spiking neurons, only the second feature (ii) can be modeled by the method of SSPPs. Namely, the first one (i) associated with the effect of long-memory cannot be modeled properly. Then, it is shown that the two main features can be modeled successfully by a class of fractional SSPP (FSSPP).

Probability distribution functions for intermittent scrape-off layer plasma fluctuations

NASA Astrophysics Data System (ADS)

Theodorsen, A.; Garcia, O. E.

2018-03-01

A stochastic model for intermittent fluctuations in the scrape-off layer of magnetically confined plasmas has been constructed based on a super-position of uncorrelated pulses arriving according to a Poisson process. In the most common applications of the model, the pulse amplitudes are assumed exponentially distributed, supported by conditional averaging of large-amplitude fluctuations in experimental measurement data. This basic assumption has two potential limitations. First, statistical analysis of measurement data using conditional averaging only reveals the tail of the amplitude distribution to be exponentially distributed. Second, exponentially distributed amplitudes leads to a positive definite signal which cannot capture fluctuations in for example electric potential and radial velocity. Assuming pulse amplitudes which are not positive definite often make finding a closed form for the probability density function (PDF) difficult, even if the characteristic function remains relatively simple. Thus estimating model parameters requires an approach based on the characteristic function, not the PDF. In this contribution, the effect of changing the amplitude distribution on the moments, PDF and characteristic function of the process is investigated and a parameter estimation method using the empirical characteristic function is presented and tested on synthetically generated data. This proves valuable for describing intermittent fluctuations of all plasma parameters in the boundary region of magnetized plasmas.

Developing an economical and reliable test for measuring the resilient modulus and Poisson's ratio of subgrade.

DOT National Transportation Integrated Search

2010-11-01

The resilient modulus and Poissons ratio of base and sublayers in highway use are : important parameters in design and quality control process. The currently used techniques : include CBR (California Bearing Ratio) test, resilient modulus test,...

Explanation of the Reaction of Monoclonal Antibodies with Candida Albicans Cell Surface in Terms of Compound Poisson Process

NASA Astrophysics Data System (ADS)

Dudek, Mirosław R.; Mleczko, Józef

Surprisingly, still very little is known about the mathematical modeling of peaks in the binding affinities distribution function. In general, it is believed that the peaks represent antibodies directed towards single epitopes. In this paper, we refer to fluorescence flow cytometry experiments and show that even monoclonal antibodies can display multi-modal histograms of affinity distribution. This result take place when some obstacles appear in the paratope-epitope reaction such that the process of reaching the specific epitope ceases to be a point Poisson process. A typical example is the large area of cell surface, which could be unreachable by antibodies leading to the heterogeneity of the cell surface repletion. In this case the affinity of cells to bind the antibodies should be described by a more complex process than the pure-Poisson point process. We suggested to use a doubly stochastic Poisson process, where the points are replaced by a binomial point process resulting in the Neyman distribution. The distribution can have a strongly multinomial character, and with the number of modes depending on the concentration of antibodies and epitopes. All this means that there is a possibility to go beyond the simplified theory, one response towards one epitope. As a consequence, our description provides perspectives for describing antigen-antibody reactions, both qualitatively and quantitavely, even in the case when some peaks result from more than one binding mechanism.

Theory of earthquakes interevent times applied to financial markets

NASA Astrophysics Data System (ADS)

Jagielski, Maciej; Kutner, Ryszard; Sornette, Didier

2017-10-01

We analyze the probability density function (PDF) of waiting times between financial loss exceedances. The empirical PDFs are fitted with the self-excited Hawkes conditional Poisson process with a long power law memory kernel. The Hawkes process is the simplest extension of the Poisson process that takes into account how past events influence the occurrence of future events. By analyzing the empirical data for 15 different financial assets, we show that the formalism of the Hawkes process used for earthquakes can successfully model the PDF of interevent times between successive market losses.

Equivalence of MAXENT and Poisson point process models for species distribution modeling in ecology.

PubMed

Renner, Ian W; Warton, David I

2013-03-01

Modeling the spatial distribution of a species is a fundamental problem in ecology. A number of modeling methods have been developed, an extremely popular one being MAXENT, a maximum entropy modeling approach. In this article, we show that MAXENT is equivalent to a Poisson regression model and hence is related to a Poisson point process model, differing only in the intercept term, which is scale-dependent in MAXENT. We illustrate a number of improvements to MAXENT that follow from these relations. In particular, a point process model approach facilitates methods for choosing the appropriate spatial resolution, assessing model adequacy, and choosing the LASSO penalty parameter, all currently unavailable to MAXENT. The equivalence result represents a significant step in the unification of the species distribution modeling literature. Copyright © 2013, The International Biometric Society.

Does the U.S. exercise contagion on Italy? A theoretical model and empirical evidence

NASA Astrophysics Data System (ADS)

Cerqueti, Roy; Fenga, Livio; Ventura, Marco

2018-06-01

This paper deals with the theme of contagion in financial markets. At this aim, we develop a model based on Mixed Poisson Processes to describe the abnormal returns of financial markets of two considered countries. In so doing, the article defines the theoretical conditions to be satisfied in order to state that one of them - the so-called leader - exercises contagion on the others - the followers. Specifically, we employ an invariant probabilistic result stating that a suitable transformation of a Mixed Poisson Process is still a Mixed Poisson Process. The theoretical claim is validated by implementing an extensive simulation analysis grounded on empirical data. The countries considered are the U.S. (as the leader) and Italy (as the follower) and the period under scrutiny is very large, ranging from 1970 to 2014.

Seasonally adjusted birth frequencies follow the Poisson distribution.

PubMed

Barra, Mathias; Lindstrøm, Jonas C; Adams, Samantha S; Augestad, Liv A

2015-12-15

Variations in birth frequencies have an impact on activity planning in maternity wards. Previous studies of this phenomenon have commonly included elective births. A Danish study of spontaneous births found that birth frequencies were well modelled by a Poisson process. Somewhat unexpectedly, there were also weekly variations in the frequency of spontaneous births. Another study claimed that birth frequencies follow the Benford distribution. Our objective was to test these results. We analysed 50,017 spontaneous births at Akershus University Hospital in the period 1999-2014. To investigate the Poisson distribution of these births, we plotted their variance over a sliding average. We specified various Poisson regression models, with the number of births on a given day as the outcome variable. The explanatory variables included various combinations of years, months, days of the week and the digit sum of the date. The relationship between the variance and the average fits well with an underlying Poisson process. A Benford distribution was disproved by a goodness-of-fit test (p < 0.01). The fundamental model with year and month as explanatory variables is significantly improved (p < 0.001) by adding day of the week as an explanatory variable. Altogether 7.5% more children are born on Tuesdays than on Sundays. The digit sum of the date is non-significant as an explanatory variable (p = 0.23), nor does it increase the explained variance. INERPRETATION: Spontaneous births are well modelled by a time-dependent Poisson process when monthly and day-of-the-week variation is included. The frequency is highest in summer towards June and July, Friday and Tuesday stand out as particularly busy days, and the activity level is at its lowest during weekends.

NON-HOMOGENEOUS POISSON PROCESS MODEL FOR GENETIC CROSSOVER INTERFERENCE.

PubMed

Leu, Szu-Yun; Sen, Pranab K

2014-01-01

The genetic crossover interference is usually modeled with a stationary renewal process to construct the genetic map. We propose two non-homogeneous, also dependent, Poisson process models applied to the known physical map. The crossover process is assumed to start from an origin and to occur sequentially along the chromosome. The increment rate depends on the position of the markers and the number of crossover events occurring between the origin and the markers. We show how to obtain parameter estimates for the process and use simulation studies and real Drosophila data to examine the performance of the proposed models.

Irreversible thermodynamics of Poisson processes with reaction.

PubMed

Méndez, V; Fort, J

1999-11-01

A kinetic model is derived to study the successive movements of particles, described by a Poisson process, as well as their generation. The irreversible thermodynamics of this system is also studied from the kinetic model. This makes it possible to evaluate the differences between thermodynamical quantities computed exactly and up to second-order. Such differences determine the range of validity of the second-order approximation to extended irreversible thermodynamics.

A Hands-on Activity for Teaching the Poisson Distribution Using the Stock Market

ERIC Educational Resources Information Center

Dunlap, Mickey; Studstill, Sharyn

2014-01-01

The number of increases a particular stock makes over a fixed period follows a Poisson distribution. This article discusses using this easily-found data as an opportunity to let students become involved in the data collection and analysis process.

Superlinear scaling of offspring at criticality in branching processes

NASA Astrophysics Data System (ADS)

Saichev, A.; Sornette, D.

2014-01-01

For any branching process, we demonstrate that the typical total number rmp(ντ) of events triggered over all generations within any sufficiently large time window τ exhibits, at criticality, a superlinear dependence rmp(ντ)˜(ντ)γ (with γ >1) on the total number ντ of the immigrants arriving at the Poisson rate ν. In branching processes in which immigrants (or sources) are characterized by fertilities distributed according to an asymptotic power-law tail with tail exponent 1<γ ⩽2, the exponent of the superlinear law for rmp(ντ) is identical to the exponent γ of the distribution of fertilities. For γ >2 and for standard branching processes without power-law distribution of fertilities, rmp(ντ)˜(ντ)2. This scaling law replaces and tames the divergence ντ /(1-n) of the mean total number R¯t(τ) of events, as the branching ratio (defined as the average number of triggered events of first generation per source) tends to 1. The derivation uses the formalism of generating probability functions. The corresponding prediction is confirmed by numerical calculations, and an heuristic derivation enlightens its underlying mechanism. We also show that R¯t(τ) is always linear in ντ even at criticality (n =1). Our results thus illustrate the fundamental difference between the mean total number, which is controlled by a few extremely rare realizations, and the typical behavior represented by rmp(ντ).

Modeling environmental noise exceedances using non-homogeneous Poisson processes.

PubMed

Guarnaccia, Claudio; Quartieri, Joseph; Barrios, Juan M; Rodrigues, Eliane R

2014-10-01

In this work a non-homogeneous Poisson model is considered to study noise exposure. The Poisson process, counting the number of times that a sound level surpasses a threshold, is used to estimate the probability that a population is exposed to high levels of noise a certain number of times in a given time interval. The rate function of the Poisson process is assumed to be of a Weibull type. The presented model is applied to community noise data from Messina, Sicily (Italy). Four sets of data are used to estimate the parameters involved in the model. After the estimation and tuning are made, a way of estimating the probability that an environmental noise threshold is exceeded a certain number of times in a given time interval is presented. This estimation can be very useful in the study of noise exposure of a population and also to predict, given the current behavior of the data, the probability of occurrence of high levels of noise in the near future. One of the most important features of the model is that it implicitly takes into account different noise sources, which need to be treated separately when using usual models.

Simple and Hierarchical Models for Stochastic Test Misgrading.

ERIC Educational Resources Information Center

Wang, Jianjun

1993-01-01

Test misgrading is treated as a stochastic process. The expected number of misgradings, inter-occurrence time of misgradings, and waiting time for the "n"th misgrading are discussed based on a simple Poisson model and a hierarchical Beta-Poisson model. Examples of model construction are given. (SLD)

Tidal analysis and Arrival Process Mining Using Automatic Identification System (AIS) Data

DTIC Science & Technology

2017-01-01

files, organized by location. The data were processed using the Python programming language (van Rossum and Drake 2001), the Pandas data analysis...ER D C/ CH L TR -1 7- 2 Coastal Inlets Research Program Tidal Analysis and Arrival Process Mining Using Automatic Identification System...17-2 January 2017 Tidal Analysis and Arrival Process Mining Using Automatic Identification System (AIS) Data Brandan M. Scully Coastal and

Nonparametric estimation of the heterogeneity of a random medium using compound Poisson process modeling of wave multiple scattering.

PubMed

Le Bihan, Nicolas; Margerin, Ludovic

2009-07-01

In this paper, we present a nonparametric method to estimate the heterogeneity of a random medium from the angular distribution of intensity of waves transmitted through a slab of random material. Our approach is based on the modeling of forward multiple scattering using compound Poisson processes on compact Lie groups. The estimation technique is validated through numerical simulations based on radiative transfer theory.

Filtering with Marked Point Process Observations via Poisson Chaos Expansion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun Wei, E-mail: wsun@mathstat.concordia.ca; Zeng Yong, E-mail: zengy@umkc.edu; Zhang Shu, E-mail: zhangshuisme@hotmail.com

2013-06-15

We study a general filtering problem with marked point process observations. The motivation comes from modeling financial ultra-high frequency data. First, we rigorously derive the unnormalized filtering equation with marked point process observations under mild assumptions, especially relaxing the bounded condition of stochastic intensity. Then, we derive the Poisson chaos expansion for the unnormalized filter. Based on the chaos expansion, we establish the uniqueness of solutions of the unnormalized filtering equation. Moreover, we derive the Poisson chaos expansion for the unnormalized filter density under additional conditions. To explore the computational advantage, we further construct a new consistent recursive numerical schememore » based on the truncation of the chaos density expansion for a simple case. The new algorithm divides the computations into those containing solely system coefficients and those including the observations, and assign the former off-line.« less

Study on reservoir time-varying design flood of inflow based on Poisson process with time-dependent parameters

NASA Astrophysics Data System (ADS)

Li, Jiqing; Huang, Jing; Li, Jianchang

2018-06-01

The time-varying design flood can make full use of the measured data, which can provide the reservoir with the basis of both flood control and operation scheduling. This paper adopts peak over threshold method for flood sampling in unit periods and Poisson process with time-dependent parameters model for simulation of reservoirs time-varying design flood. Considering the relationship between the model parameters and hypothesis, this paper presents the over-threshold intensity, the fitting degree of Poisson distribution and the design flood parameters are the time-varying design flood unit period and threshold discriminant basis, deduced Longyangxia reservoir time-varying design flood process at 9 kinds of design frequencies. The time-varying design flood of inflow is closer to the reservoir actual inflow conditions, which can be used to adjust the operating water level in flood season and make plans for resource utilization of flood in the basin.

Population processes during establishment and spread of invading species: implications for survey and detection programs

Treesearch

Andrew Liebhold

2000-01-01

Three important population processes occur during any biological invasion: arrival, establishment, and spread. Arrival is the process by which individual(s) of the invading organism are transported to their new habitat. Establishment can be considered the opposite of extinction and represents the growth of a newly arrived population sufficient such that extinction is...

Using the Gamma-Poisson Model to Predict Library Circulations.

ERIC Educational Resources Information Center

Burrell, Quentin L.

1990-01-01

Argues that the gamma mixture of Poisson processes, for all its perceived defects, can be used to make predictions regarding future library book circulations of a quality adequate for general management requirements. The use of the model is extensively illustrated with data from two academic libraries. (Nine references) (CLB)

Questionable Validity of Poisson Assumptions in a Combined Loglinear/MDS Mapping Model.

ERIC Educational Resources Information Center

Gleason, John M.

1993-01-01

This response to an earlier article on a combined log-linear/MDS model for mapping journals by citation analysis discusses the underlying assumptions of the Poisson model with respect to characteristics of the citation process. The importance of empirical data analysis is also addressed. (nine references) (LRW)

Extensions of Rasch's Multiplicative Poisson Model.

ERIC Educational Resources Information Center

Jansen, Margo G. H.; van Duijn, Marijtje A. J.

1992-01-01

A model developed by G. Rasch that assumes scores on some attainment tests can be realizations of a Poisson process is explained and expanded by assuming a prior distribution, with fixed but unknown parameters, for the subject parameters. How additional between-subject and within-subject factors can be incorporated is discussed. (SLD)

Transport of Multivalent Electrolyte Mixtures in Micro- and Nanochannels

DTIC Science & Technology

2013-11-08

equations for this process are the unsteady Navier-Stokes equations along with continuity and the Poisson- Nernst -Planck system for the electro- static part...about five times the Debye screening length D (the 1/e lengthscale for the potential from the solution of the linearized Poisson- Boltzmann equation

Do bacterial cell numbers follow a theoretical Poisson distribution? Comparison of experimentally obtained numbers of single cells with random number generation via computer simulation.

PubMed

Koyama, Kento; Hokunan, Hidekazu; Hasegawa, Mayumi; Kawamura, Shuso; Koseki, Shigenobu

2016-12-01

We investigated a bacterial sample preparation procedure for single-cell studies. In the present study, we examined whether single bacterial cells obtained via 10-fold dilution followed a theoretical Poisson distribution. Four serotypes of Salmonella enterica, three serotypes of enterohaemorrhagic Escherichia coli and one serotype of Listeria monocytogenes were used as sample bacteria. An inoculum of each serotype was prepared via a 10-fold dilution series to obtain bacterial cell counts with mean values of one or two. To determine whether the experimentally obtained bacterial cell counts follow a theoretical Poisson distribution, a likelihood ratio test between the experimentally obtained cell counts and Poisson distribution which parameter estimated by maximum likelihood estimation (MLE) was conducted. The bacterial cell counts of each serotype sufficiently followed a Poisson distribution. Furthermore, to examine the validity of the parameters of Poisson distribution from experimentally obtained bacterial cell counts, we compared these with the parameters of a Poisson distribution that were estimated using random number generation via computer simulation. The Poisson distribution parameters experimentally obtained from bacterial cell counts were within the range of the parameters estimated using a computer simulation. These results demonstrate that the bacterial cell counts of each serotype obtained via 10-fold dilution followed a Poisson distribution. The fact that the frequency of bacterial cell counts follows a Poisson distribution at low number would be applied to some single-cell studies with a few bacterial cells. In particular, the procedure presented in this study enables us to develop an inactivation model at the single-cell level that can estimate the variability of survival bacterial numbers during the bacterial death process. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multiserver Queueing Model subject to Single Exponential Vacation

NASA Astrophysics Data System (ADS)

Vijayashree, K. V.; Janani, B.

2018-04-01

A multi-server queueing model subject to single exponential vacation is considered. The arrivals are allowed to join the queue according to a Poisson distribution and services takes place according to an exponential distribution. Whenever the system becomes empty, all the servers goes for a vacation and returns back after a fixed interval of time. The servers then starts providing service if there are waiting customers otherwise they will wait to complete the busy period. The vacation times are also assumed to be exponentially distributed. In this paper, the stationary and transient probabilities for the number of customers during ideal and functional state of the server are obtained explicitly. Also, numerical illustrations are added to visualize the effect of various parameters.

Generalized Poisson-Kac Processes: Basic Properties and Implications in Extended Thermodynamics and Transport

NASA Astrophysics Data System (ADS)

Giona, Massimiliano; Brasiello, Antonio; Crescitelli, Silvestro

2016-04-01

We introduce a new class of stochastic processes in Rn,{{{mathbb R}}^n}, referred to as generalized Poisson-Kac (GPK) processes, that generalizes the Poisson-Kac telegrapher's random motion in higher dimensions. These stochastic processes possess finite propagation velocity, almost everywhere smooth trajectories, and converge in the Kac limit to Brownian motion. GPK processes are defined by coupling the selection of a bounded velocity vector from a family of N distinct ones with a Markovian dynamics controlling probabilistically this selection. This model can be used as a probabilistic tool for a stochastically consistent formulation of extended thermodynamic theories far from equilibrium.

Applying the Anderson-Darling test to suicide clusters: evidence of contagion at U. S. universities?

PubMed

MacKenzie, Donald W

2013-01-01

Suicide clusters at Cornell University and the Massachusetts Institute of Technology (MIT) prompted popular and expert speculation of suicide contagion. However, some clustering is to be expected in any random process. This work tested whether suicide clusters at these two universities differed significantly from those expected under a homogeneous Poisson process, in which suicides occur randomly and independently of one another. Suicide dates were collected for MIT and Cornell for 1990-2012. The Anderson-Darling statistic was used to test the goodness-of-fit of the intervals between suicides to distribution expected under the Poisson process. Suicides at MIT were consistent with the homogeneous Poisson process, while those at Cornell showed clustering inconsistent with such a process (p = .05). The Anderson-Darling test provides a statistically powerful means to identify suicide clustering in small samples. Practitioners can use this method to test for clustering in relevant communities. The difference in clustering behavior between the two institutions suggests that more institutions should be studied to determine the prevalence of suicide clustering in universities and its causes.

A comparison between Poisson and zero-inflated Poisson regression models with an application to number of black spots in Corriedale sheep

PubMed Central

Naya, Hugo; Urioste, Jorge I; Chang, Yu-Mei; Rodrigues-Motta, Mariana; Kremer, Roberto; Gianola, Daniel

2008-01-01

Dark spots in the fleece area are often associated with dark fibres in wool, which limits its competitiveness with other textile fibres. Field data from a sheep experiment in Uruguay revealed an excess number of zeros for dark spots. We compared the performance of four Poisson and zero-inflated Poisson (ZIP) models under four simulation scenarios. All models performed reasonably well under the same scenario for which the data were simulated. The deviance information criterion favoured a Poisson model with residual, while the ZIP model with a residual gave estimates closer to their true values under all simulation scenarios. Both Poisson and ZIP models with an error term at the regression level performed better than their counterparts without such an error. Field data from Corriedale sheep were analysed with Poisson and ZIP models with residuals. Parameter estimates were similar for both models. Although the posterior distribution of the sire variance was skewed due to a small number of rams in the dataset, the median of this variance suggested a scope for genetic selection. The main environmental factor was the age of the sheep at shearing. In summary, age related processes seem to drive the number of dark spots in this breed of sheep. PMID:18558072

An intrinsic algorithm for parallel Poisson disk sampling on arbitrary surfaces.

PubMed

Ying, Xiang; Xin, Shi-Qing; Sun, Qian; He, Ying

2013-09-01

Poisson disk sampling has excellent spatial and spectral properties, and plays an important role in a variety of visual computing. Although many promising algorithms have been proposed for multidimensional sampling in euclidean space, very few studies have been reported with regard to the problem of generating Poisson disks on surfaces due to the complicated nature of the surface. This paper presents an intrinsic algorithm for parallel Poisson disk sampling on arbitrary surfaces. In sharp contrast to the conventional parallel approaches, our method neither partitions the given surface into small patches nor uses any spatial data structure to maintain the voids in the sampling domain. Instead, our approach assigns each sample candidate a random and unique priority that is unbiased with regard to the distribution. Hence, multiple threads can process the candidates simultaneously and resolve conflicts by checking the given priority values. Our algorithm guarantees that the generated Poisson disks are uniformly and randomly distributed without bias. It is worth noting that our method is intrinsic and independent of the embedding space. This intrinsic feature allows us to generate Poisson disk patterns on arbitrary surfaces in IR(n). To our knowledge, this is the first intrinsic, parallel, and accurate algorithm for surface Poisson disk sampling. Furthermore, by manipulating the spatially varying density function, we can obtain adaptive sampling easily.

General methodology for nonlinear modeling of neural systems with Poisson point-process inputs.

PubMed

Marmarelis, V Z; Berger, T W

2005-07-01

This paper presents a general methodological framework for the practical modeling of neural systems with point-process inputs (sequences of action potentials or, more broadly, identical events) based on the Volterra and Wiener theories of functional expansions and system identification. The paper clarifies the distinctions between Volterra and Wiener kernels obtained from Poisson point-process inputs. It shows that only the Wiener kernels can be estimated via cross-correlation, but must be defined as zero along the diagonals. The Volterra kernels can be estimated far more accurately (and from shorter data-records) by use of the Laguerre expansion technique adapted to point-process inputs, and they are independent of the mean rate of stimulation (unlike their P-W counterparts that depend on it). The Volterra kernels can also be estimated for broadband point-process inputs that are not Poisson. Useful applications of this modeling approach include cases where we seek to determine (model) the transfer characteristics between one neuronal axon (a point-process 'input') and another axon (a point-process 'output') or some other measure of neuronal activity (a continuous 'output', such as population activity) with which a causal link exists.

KENNEDY SPACE CENTER, FLA. - In the Space Station Processing Facility, Executive Director of NASDA Koji Yamamoto (right) looks at the newly arrived Japanese Experiment Module (JEM)/pressurized module. Mr. Yamamoto is at KSC for a welcome ceremony involving the arrival of JEM.

NASA Image and Video Library

2003-06-12

KENNEDY SPACE CENTER, FLA. - In the Space Station Processing Facility, Executive Director of NASDA Koji Yamamoto (right) looks at the newly arrived Japanese Experiment Module (JEM)/pressurized module. Mr. Yamamoto is at KSC for a welcome ceremony involving the arrival of JEM.

KENNEDY SPACE CENTER, FLA. - In the Space Station Processing Facility, Executive Director of NASDA Koji Yamamoto (left) looks at the newly arrived Japanese Experiment Module (JEM)/pressurized module. Mr. Yamamoto is at KSC for a welcome ceremony involving the arrival of JEM.

NASA Image and Video Library

2003-06-12

KENNEDY SPACE CENTER, FLA. - In the Space Station Processing Facility, Executive Director of NASDA Koji Yamamoto (left) looks at the newly arrived Japanese Experiment Module (JEM)/pressurized module. Mr. Yamamoto is at KSC for a welcome ceremony involving the arrival of JEM.

Inferring the background traffic arrival process in the Internet.

PubMed

Hága, Péter; Csabai, István; Vattay, Gábor

2009-12-01

Phase transition has been found in many complex interactivity systems. Complex networks are not exception either but there are quite few real systems where we can directly understand the emergence of this nontrivial behavior from the microscopic view. In this paper, we present the emergence of the phase transition between the congested and uncongested phases of a network link. We demonstrate a method to infer the background traffic arrival process, which is one of the key state parameters of the Internet traffic. The traffic arrival process in the Internet has been investigated in several studies, since the recognition of its self-similar nature. The statistical properties of the traffic arrival process are very important since they are fundamental in modeling the dynamical behavior. Here, we demonstrate how the widely used packet train technique can be used to determine the main properties of the traffic arrival process. We show that the packet train dispersion is sensitive to the congestion on the network path. We introduce the packet train stretch as an order parameter to describe the phase transition between the congested and uncongested phases of the bottleneck link in the path. We find that the distribution of the background traffic arrival process can be determined from the average packet train dispersion at the critical point of the system.

Mean-square state and parameter estimation for stochastic linear systems with Gaussian and Poisson noises

NASA Astrophysics Data System (ADS)

Basin, M.; Maldonado, J. J.; Zendejo, O.

2016-07-01

This paper proposes new mean-square filter and parameter estimator design for linear stochastic systems with unknown parameters over linear observations, where unknown parameters are considered as combinations of Gaussian and Poisson white noises. The problem is treated by reducing the original problem to a filtering problem for an extended state vector that includes parameters as additional states, modelled as combinations of independent Gaussian and Poisson processes. The solution to this filtering problem is based on the mean-square filtering equations for incompletely polynomial states confused with Gaussian and Poisson noises over linear observations. The resulting mean-square filter serves as an identifier for the unknown parameters. Finally, a simulation example shows effectiveness of the proposed mean-square filter and parameter estimator.

An unbiased risk estimator for image denoising in the presence of mixed poisson-gaussian noise.

PubMed

Le Montagner, Yoann; Angelini, Elsa D; Olivo-Marin, Jean-Christophe

2014-03-01

The behavior and performance of denoising algorithms are governed by one or several parameters, whose optimal settings depend on the content of the processed image and the characteristics of the noise, and are generally designed to minimize the mean squared error (MSE) between the denoised image returned by the algorithm and a virtual ground truth. In this paper, we introduce a new Poisson-Gaussian unbiased risk estimator (PG-URE) of the MSE applicable to a mixed Poisson-Gaussian noise model that unifies the widely used Gaussian and Poisson noise models in fluorescence bioimaging applications. We propose a stochastic methodology to evaluate this estimator in the case when little is known about the internal machinery of the considered denoising algorithm, and we analyze both theoretically and empirically the characteristics of the PG-URE estimator. Finally, we evaluate the PG-URE-driven parametrization for three standard denoising algorithms, with and without variance stabilizing transforms, and different characteristics of the Poisson-Gaussian noise mixture.

Statistical error in simulations of Poisson processes: Example of diffusion in solids

NASA Astrophysics Data System (ADS)

Nilsson, Johan O.; Leetmaa, Mikael; Vekilova, Olga Yu.; Simak, Sergei I.; Skorodumova, Natalia V.

2016-08-01

Simulations of diffusion in solids often produce poor statistics of diffusion events. We present an analytical expression for the statistical error in ion conductivity obtained in such simulations. The error expression is not restricted to any computational method in particular, but valid in the context of simulation of Poisson processes in general. This analytical error expression is verified numerically for the case of Gd-doped ceria by running a large number of kinetic Monte Carlo calculations.

Fractional Brownian motion and long term clinical trial recruitment

PubMed Central

Zhang, Qiang; Lai, Dejian

2015-01-01

Prediction of recruitment in clinical trials has been a challenging task. Many methods have been studied, including models based on Poisson process and its large sample approximation by Brownian motion (BM), however, when the independent incremental structure is violated for BM model, we could use fractional Brownian motion to model and approximate the underlying Poisson processes with random rates. In this paper, fractional Brownian motion (FBM) is considered for such conditions and compared to BM model with illustrated examples from different trials and simulations. PMID:26347306

Fractional Brownian motion and long term clinical trial recruitment.

PubMed

Zhang, Qiang; Lai, Dejian

2011-05-01

Prediction of recruitment in clinical trials has been a challenging task. Many methods have been studied, including models based on Poisson process and its large sample approximation by Brownian motion (BM), however, when the independent incremental structure is violated for BM model, we could use fractional Brownian motion to model and approximate the underlying Poisson processes with random rates. In this paper, fractional Brownian motion (FBM) is considered for such conditions and compared to BM model with illustrated examples from different trials and simulations.

An Intrinsic Algorithm for Parallel Poisson Disk Sampling on Arbitrary Surfaces.

PubMed

Ying, Xiang; Xin, Shi-Qing; Sun, Qian; He, Ying

2013-03-08

Poisson disk sampling plays an important role in a variety of visual computing, due to its useful statistical property in distribution and the absence of aliasing artifacts. While many effective techniques have been proposed to generate Poisson disk distribution in Euclidean space, relatively few work has been reported to the surface counterpart. This paper presents an intrinsic algorithm for parallel Poisson disk sampling on arbitrary surfaces. We propose a new technique for parallelizing the dart throwing. Rather than the conventional approaches that explicitly partition the spatial domain to generate the samples in parallel, our approach assigns each sample candidate a random and unique priority that is unbiased with regard to the distribution. Hence, multiple threads can process the candidates simultaneously and resolve conflicts by checking the given priority values. It is worth noting that our algorithm is accurate as the generated Poisson disks are uniformly and randomly distributed without bias. Our method is intrinsic in that all the computations are based on the intrinsic metric and are independent of the embedding space. This intrinsic feature allows us to generate Poisson disk distributions on arbitrary surfaces. Furthermore, by manipulating the spatially varying density function, we can obtain adaptive sampling easily.

Bayesian analysis of volcanic eruptions

NASA Astrophysics Data System (ADS)

Ho, Chih-Hsiang

1990-10-01

The simple Poisson model generally gives a good fit to many volcanoes for volcanic eruption forecasting. Nonetheless, empirical evidence suggests that volcanic activity in successive equal time-periods tends to be more variable than a simple Poisson with constant eruptive rate. An alternative model is therefore examined in which eruptive rate(λ) for a given volcano or cluster(s) of volcanoes is described by a gamma distribution (prior) rather than treated as a constant value as in the assumptions of a simple Poisson model. Bayesian analysis is performed to link two distributions together to give the aggregate behavior of the volcanic activity. When the Poisson process is expanded to accomodate a gamma mixing distribution on λ, a consequence of this mixed (or compound) Poisson model is that the frequency distribution of eruptions in any given time-period of equal length follows the negative binomial distribution (NBD). Applications of the proposed model and comparisons between the generalized model and simple Poisson model are discussed based on the historical eruptive count data of volcanoes Mauna Loa (Hawaii) and Etna (Italy). Several relevant facts lead to the conclusion that the generalized model is preferable for practical use both in space and time.

Modeling animal-vehicle collisions using diagonal inflated bivariate Poisson regression.

PubMed

Lao, Yunteng; Wu, Yao-Jan; Corey, Jonathan; Wang, Yinhai

2011-01-01

Two types of animal-vehicle collision (AVC) data are commonly adopted for AVC-related risk analysis research: reported AVC data and carcass removal data. One issue with these two data sets is that they were found to have significant discrepancies by previous studies. In order to model these two types of data together and provide a better understanding of highway AVCs, this study adopts a diagonal inflated bivariate Poisson regression method, an inflated version of bivariate Poisson regression model, to fit the reported AVC and carcass removal data sets collected in Washington State during 2002-2006. The diagonal inflated bivariate Poisson model not only can model paired data with correlation, but also handle under- or over-dispersed data sets as well. Compared with three other types of models, double Poisson, bivariate Poisson, and zero-inflated double Poisson, the diagonal inflated bivariate Poisson model demonstrates its capability of fitting two data sets with remarkable overlapping portions resulting from the same stochastic process. Therefore, the diagonal inflated bivariate Poisson model provides researchers a new approach to investigating AVCs from a different perspective involving the three distribution parameters (λ(1), λ(2) and λ(3)). The modeling results show the impacts of traffic elements, geometric design and geographic characteristics on the occurrences of both reported AVC and carcass removal data. It is found that the increase of some associated factors, such as speed limit, annual average daily traffic, and shoulder width, will increase the numbers of reported AVCs and carcass removals. Conversely, the presence of some geometric factors, such as rolling and mountainous terrain, will decrease the number of reported AVCs. Published by Elsevier Ltd.

An empirical Bayesian and Buhlmann approach with non-homogenous Poisson process

NASA Astrophysics Data System (ADS)

Noviyanti, Lienda

2015-12-01

All general insurance companies in Indonesia have to adjust their current premium rates according to maximum and minimum limit rates in the new regulation established by the Financial Services Authority (Otoritas Jasa Keuangan / OJK). In this research, we estimated premium rate by means of the Bayesian and the Buhlmann approach using historical claim frequency and claim severity in a five-group risk. We assumed a Poisson distributed claim frequency and a Normal distributed claim severity. Particularly, we used a non-homogenous Poisson process for estimating the parameters of claim frequency. We found that estimated premium rates are higher than the actual current rate. Regarding to the OJK upper and lower limit rates, the estimates among the five-group risk are varied; some are in the interval and some are out of the interval.

The Dependent Poisson Race Model and Modeling Dependence in Conjoint Choice Experiments

ERIC Educational Resources Information Center

Ruan, Shiling; MacEachern, Steven N.; Otter, Thomas; Dean, Angela M.

2008-01-01

Conjoint choice experiments are used widely in marketing to study consumer preferences amongst alternative products. We develop a class of choice models, belonging to the class of Poisson race models, that describe a "random utility" which lends itself to a process-based description of choice. The models incorporate a dependence structure which…

Generalized master equations for non-Poisson dynamics on networks.

PubMed

Hoffmann, Till; Porter, Mason A; Lambiotte, Renaud

2012-10-01

The traditional way of studying temporal networks is to aggregate the dynamics of the edges to create a static weighted network. This implicitly assumes that the edges are governed by Poisson processes, which is not typically the case in empirical temporal networks. Accordingly, we examine the effects of non-Poisson inter-event statistics on the dynamics of edges, and we apply the concept of a generalized master equation to the study of continuous-time random walks on networks. We show that this equation reduces to the standard rate equations when the underlying process is Poissonian and that its stationary solution is determined by an effective transition matrix whose leading eigenvector is easy to calculate. We conduct numerical simulations and also derive analytical results for the stationary solution under the assumption that all edges have the same waiting-time distribution. We discuss the implications of our work for dynamical processes on temporal networks and for the construction of network diagnostics that take into account their nontrivial stochastic nature.

Generalized master equations for non-Poisson dynamics on networks

NASA Astrophysics Data System (ADS)

Hoffmann, Till; Porter, Mason A.; Lambiotte, Renaud

2012-10-01

The traditional way of studying temporal networks is to aggregate the dynamics of the edges to create a static weighted network. This implicitly assumes that the edges are governed by Poisson processes, which is not typically the case in empirical temporal networks. Accordingly, we examine the effects of non-Poisson inter-event statistics on the dynamics of edges, and we apply the concept of a generalized master equation to the study of continuous-time random walks on networks. We show that this equation reduces to the standard rate equations when the underlying process is Poissonian and that its stationary solution is determined by an effective transition matrix whose leading eigenvector is easy to calculate. We conduct numerical simulations and also derive analytical results for the stationary solution under the assumption that all edges have the same waiting-time distribution. We discuss the implications of our work for dynamical processes on temporal networks and for the construction of network diagnostics that take into account their nontrivial stochastic nature.

Weber's law implies neural discharge more regular than a Poisson process.

PubMed

Kang, Jing; Wu, Jianhua; Smerieri, Anteo; Feng, Jianfeng

2010-03-01

Weber's law is one of the basic laws in psychophysics, but the link between this psychophysical behavior and the neuronal response has not yet been established. In this paper, we carried out an analysis on the spike train statistics when Weber's law holds, and found that the efferent spike train of a single neuron is less variable than a Poisson process. For population neurons, Weber's law is satisfied only when the population size is small (< 10 neurons). However, if the population neurons share a weak correlation in their discharges and individual neuronal spike train is more regular than a Poisson process, Weber's law is true without any restriction on the population size. Biased competition attractor network also demonstrates that the coefficient of variation of interspike interval in the winning pool should be less than one for the validity of Weber's law. Our work links Weber's law with neural firing property quantitatively, shedding light on the relation between psychophysical behavior and neuronal responses.

Pareto genealogies arising from a Poisson branching evolution model with selection.

PubMed

Huillet, Thierry E

2014-02-01

We study a class of coalescents derived from a sampling procedure out of N i.i.d. Pareto(α) random variables, normalized by their sum, including β-size-biasing on total length effects (β < α). Depending on the range of α we derive the large N limit coalescents structure, leading either to a discrete-time Poisson-Dirichlet (α, -β) Ξ-coalescent (α ε[0, 1)), or to a family of continuous-time Beta (2 - α, α - β)Λ-coalescents (α ε[1, 2)), or to the Kingman coalescent (α ≥ 2). We indicate that this class of coalescent processes (and their scaling limits) may be viewed as the genealogical processes of some forward in time evolving branching population models including selection effects. In such constant-size population models, the reproduction step, which is based on a fitness-dependent Poisson Point Process with scaling power-law(α) intensity, is coupled to a selection step consisting of sorting out the N fittest individuals issued from the reproduction step.

Stochastic and Deterministic Models for the Metastatic Emission Process: Formalisms and Crosslinks.

PubMed

Gomez, Christophe; Hartung, Niklas

2018-01-01

Although the detection of metastases radically changes prognosis of and treatment decisions for a cancer patient, clinically undetectable micrometastases hamper a consistent classification into localized or metastatic disease. This chapter discusses mathematical modeling efforts that could help to estimate the metastatic risk in such a situation. We focus on two approaches: (1) a stochastic framework describing metastatic emission events at random times, formalized via Poisson processes, and (2) a deterministic framework describing the micrometastatic state through a size-structured density function in a partial differential equation model. Three aspects are addressed in this chapter. First, a motivation for the Poisson process framework is presented and modeling hypotheses and mechanisms are introduced. Second, we extend the Poisson model to account for secondary metastatic emission. Third, we highlight an inherent crosslink between the stochastic and deterministic frameworks and discuss its implications. For increased accessibility the chapter is split into an informal presentation of the results using a minimum of mathematical formalism and a rigorous mathematical treatment for more theoretically interested readers.

Clustered mixed nonhomogeneous Poisson process spline models for the analysis of recurrent event panel data.

PubMed

Nielsen, J D; Dean, C B

2008-09-01

A flexible semiparametric model for analyzing longitudinal panel count data arising from mixtures is presented. Panel count data refers here to count data on recurrent events collected as the number of events that have occurred within specific follow-up periods. The model assumes that the counts for each subject are generated by mixtures of nonhomogeneous Poisson processes with smooth intensity functions modeled with penalized splines. Time-dependent covariate effects are also incorporated into the process intensity using splines. Discrete mixtures of these nonhomogeneous Poisson process spline models extract functional information from underlying clusters representing hidden subpopulations. The motivating application is an experiment to test the effectiveness of pheromones in disrupting the mating pattern of the cherry bark tortrix moth. Mature moths arise from hidden, but distinct, subpopulations and monitoring the subpopulation responses was of interest. Within-cluster random effects are used to account for correlation structures and heterogeneity common to this type of data. An estimating equation approach to inference requiring only low moment assumptions is developed and the finite sample properties of the proposed estimating functions are investigated empirically by simulation.

Stationary moments, diffusion limits, and extinction times for logistic growth with random catastrophes.

PubMed

Schlomann, Brandon H

2018-06-06

A central problem in population ecology is understanding the consequences of stochastic fluctuations. Analytically tractable models with Gaussian driving noise have led to important, general insights, but they fail to capture rare, catastrophic events, which are increasingly observed at scales ranging from global fisheries to intestinal microbiota. Due to mathematical challenges, growth processes with random catastrophes are less well characterized and it remains unclear how their consequences differ from those of Gaussian processes. In the face of a changing climate and predicted increases in ecological catastrophes, as well as increased interest in harnessing microbes for therapeutics, these processes have never been more relevant. To better understand them, I revisit here a differential equation model of logistic growth coupled to density-independent catastrophes that arrive as a Poisson process, and derive new analytic results that reveal its statistical structure. First, I derive exact expressions for the model's stationary moments, revealing a single effective catastrophe parameter that largely controls low order statistics. Then, I use weak convergence theorems to construct its Gaussian analog in a limit of frequent, small catastrophes, keeping the stationary population mean constant for normalization. Numerically computing statistics along this limit shows how they transform as the dynamics shifts from catastrophes to diffusions, enabling quantitative comparisons. For example, the mean time to extinction increases monotonically by orders of magnitude, demonstrating significantly higher extinction risk under catastrophes than under diffusions. Together, these results provide insight into a wide range of stochastic dynamical systems important for ecology and conservation. Copyright © 2018 Elsevier Ltd. All rights reserved.

Ensemble-based methods for forecasting census in hospital units

PubMed Central

2013-01-01

Background The ability to accurately forecast census counts in hospital departments has considerable implications for hospital resource allocation. In recent years several different methods have been proposed forecasting census counts, however many of these approaches do not use available patient-specific information. Methods In this paper we present an ensemble-based methodology for forecasting the census under a framework that simultaneously incorporates both (i) arrival trends over time and (ii) patient-specific baseline and time-varying information. The proposed model for predicting census has three components, namely: current census count, number of daily arrivals and number of daily departures. To model the number of daily arrivals, we use a seasonality adjusted Poisson Autoregressive (PAR) model where the parameter estimates are obtained via conditional maximum likelihood. The number of daily departures is predicted by modeling the probability of departure from the census using logistic regression models that are adjusted for the amount of time spent in the census and incorporate both patient-specific baseline and time varying patient-specific covariate information. We illustrate our approach using neonatal intensive care unit (NICU) data collected at Women & Infants Hospital, Providence RI, which consists of 1001 consecutive NICU admissions between April 1st 2008 and March 31st 2009. Results Our results demonstrate statistically significant improved prediction accuracy for 3, 5, and 7 day census forecasts and increased precision of our forecasting model compared to a forecasting approach that ignores patient-specific information. Conclusions Forecasting models that utilize patient-specific baseline and time-varying information make the most of data typically available and have the capacity to substantially improve census forecasts. PMID:23721123

Ensemble-based methods for forecasting census in hospital units.

PubMed

Koestler, Devin C; Ombao, Hernando; Bender, Jesse

2013-05-30

The ability to accurately forecast census counts in hospital departments has considerable implications for hospital resource allocation. In recent years several different methods have been proposed forecasting census counts, however many of these approaches do not use available patient-specific information. In this paper we present an ensemble-based methodology for forecasting the census under a framework that simultaneously incorporates both (i) arrival trends over time and (ii) patient-specific baseline and time-varying information. The proposed model for predicting census has three components, namely: current census count, number of daily arrivals and number of daily departures. To model the number of daily arrivals, we use a seasonality adjusted Poisson Autoregressive (PAR) model where the parameter estimates are obtained via conditional maximum likelihood. The number of daily departures is predicted by modeling the probability of departure from the census using logistic regression models that are adjusted for the amount of time spent in the census and incorporate both patient-specific baseline and time varying patient-specific covariate information. We illustrate our approach using neonatal intensive care unit (NICU) data collected at Women & Infants Hospital, Providence RI, which consists of 1001 consecutive NICU admissions between April 1st 2008 and March 31st 2009. Our results demonstrate statistically significant improved prediction accuracy for 3, 5, and 7 day census forecasts and increased precision of our forecasting model compared to a forecasting approach that ignores patient-specific information. Forecasting models that utilize patient-specific baseline and time-varying information make the most of data typically available and have the capacity to substantially improve census forecasts.

Orientational analysis of planar fibre systems observed as a Poisson shot-noise process.

PubMed

Kärkkäinen, Salme; Lantuéjoul, Christian

2007-10-01

We consider two-dimensional fibrous materials observed as a digital greyscale image. The problem addressed is to estimate the orientation distribution of unobservable thin fibres from a greyscale image modelled by a planar Poisson shot-noise process. The classical stereological approach is not straightforward, because the point intensities of thin fibres along sampling lines may not be observable. For such cases, Kärkkäinen et al. (2001) suggested the use of scaled variograms determined from grey values along sampling lines in several directions. Their method is based on the assumption that the proportion between the scaled variograms and point intensities in all directions of sampling lines is constant. This assumption is proved to be valid asymptotically for Boolean models and dead leaves models, under some regularity conditions. In this work, we derive the scaled variogram and its approximations for a planar Poisson shot-noise process using the modified Bessel function. In the case of reasonable high resolution of the observed image, the scaled variogram has an approximate functional relation to the point intensity, and in the case of high resolution the relation is proportional. As the obtained relations are approximative, they are tested on simulations. The existing orientation analysis method based on the proportional relation is further experimented on images with different resolutions. The new result, the asymptotic proportionality between the scaled variograms and the point intensities for a Poisson shot-noise process, completes the earlier results for the Boolean models and for the dead leaves models.

Brain, music, and non-Poisson renewal processes

NASA Astrophysics Data System (ADS)

Bianco, Simone; Ignaccolo, Massimiliano; Rider, Mark S.; Ross, Mary J.; Winsor, Phil; Grigolini, Paolo

2007-06-01

In this paper we show that both music composition and brain function, as revealed by the electroencephalogram (EEG) analysis, are renewal non-Poisson processes living in the nonergodic dominion. To reach this important conclusion we process the data with the minimum spanning tree method, so as to detect significant events, thereby building a sequence of times, which is the time series to analyze. Then we show that in both cases, EEG and music composition, these significant events are the signature of a non-Poisson renewal process. This conclusion is reached using a technique of statistical analysis recently developed by our group, the aging experiment (AE). First, we find that in both cases the distances between two consecutive events are described by nonexponential histograms, thereby proving the non-Poisson nature of these processes. The corresponding survival probabilities Ψ(t) are well fitted by stretched exponentials [ Ψ(t)∝exp (-(γt)α) , with 0.5<α<1 .] The second step rests on the adoption of AE, which shows that these are renewal processes. We show that the stretched exponential, due to its renewal character, is the emerging tip of an iceberg, whose underwater part has slow tails with an inverse power law structure with power index μ=1+α . Adopting the AE procedure we find that both EEG and music composition yield μ<2 . On the basis of the recently discovered complexity matching effect, according to which a complex system S with μS<2 responds only to a complex driving signal P with μP⩽μS , we conclude that the results of our analysis may explain the influence of music on the human brain.

Tidal Analysis and Arrival Process Mining Using Automatic Identification System (AIS) Data

DTIC Science & Technology

2017-01-01

elevation at the time of vessel movement and calculating the tidal dependence (TD) parameter to 23 U.S. port areas for the years 2012– 2014. Tidal prediction...predictions, obtained from the National Oceanographic and Atmospheric Administration, are used to rank relative tidal dependence for arriving cargo and...sector traffic percentages and tidal dependence metric ............................. 11 Arrival process mining

Analysis of single-molecule fluorescence spectroscopic data with a Markov-modulated Poisson process.

PubMed

Jäger, Mark; Kiel, Alexander; Herten, Dirk-Peter; Hamprecht, Fred A

2009-10-05

We present a photon-by-photon analysis framework for the evaluation of data from single-molecule fluorescence spectroscopy (SMFS) experiments using a Markov-modulated Poisson process (MMPP). A MMPP combines a discrete (and hidden) Markov process with an additional Poisson process reflecting the observation of individual photons. The algorithmic framework is used to automatically analyze the dynamics of the complex formation and dissociation of Cu2+ ions with the bidentate ligand 2,2'-bipyridine-4,4'dicarboxylic acid in aqueous media. The process of association and dissociation of Cu2+ ions is monitored with SMFS. The dcbpy-DNA conjugate can exist in two or more distinct states which influence the photon emission rates. The advantage of a photon-by-photon analysis is that no information is lost in preprocessing steps. Different model complexities are investigated in order to best describe the recorded data and to determine transition rates on a photon-by-photon basis. The main strength of the method is that it allows to detect intermittent phenomena which are masked by binning and that are difficult to find using correlation techniques when they are short-lived.

Bringing consistency to simulation of population models--Poisson simulation as a bridge between micro and macro simulation.

PubMed

Gustafsson, Leif; Sternad, Mikael

2007-10-01

Population models concern collections of discrete entities such as atoms, cells, humans, animals, etc., where the focus is on the number of entities in a population. Because of the complexity of such models, simulation is usually needed to reproduce their complete dynamic and stochastic behaviour. Two main types of simulation models are used for different purposes, namely micro-simulation models, where each individual is described with its particular attributes and behaviour, and macro-simulation models based on stochastic differential equations, where the population is described in aggregated terms by the number of individuals in different states. Consistency between micro- and macro-models is a crucial but often neglected aspect. This paper demonstrates how the Poisson Simulation technique can be used to produce a population macro-model consistent with the corresponding micro-model. This is accomplished by defining Poisson Simulation in strictly mathematical terms as a series of Poisson processes that generate sequences of Poisson distributions with dynamically varying parameters. The method can be applied to any population model. It provides the unique stochastic and dynamic macro-model consistent with a correct micro-model. The paper also presents a general macro form for stochastic and dynamic population models. In an appendix Poisson Simulation is compared with Markov Simulation showing a number of advantages. Especially aggregation into state variables and aggregation of many events per time-step makes Poisson Simulation orders of magnitude faster than Markov Simulation. Furthermore, you can build and execute much larger and more complicated models with Poisson Simulation than is possible with the Markov approach.

Morphology and linear-elastic moduli of random network solids.

PubMed

Nachtrab, Susan; Kapfer, Sebastian C; Arns, Christoph H; Madadi, Mahyar; Mecke, Klaus; Schröder-Turk, Gerd E

2011-06-17

The effective linear-elastic moduli of disordered network solids are analyzed by voxel-based finite element calculations. We analyze network solids given by Poisson-Voronoi processes and by the structure of collagen fiber networks imaged by confocal microscopy. The solid volume fraction ϕ is varied by adjusting the fiber radius, while keeping the structural mesh or pore size of the underlying network fixed. For intermediate ϕ, the bulk and shear modulus are approximated by empirical power-laws K(phi)proptophin and G(phi)proptophim with n≈1.4 and m≈1.7. The exponents for the collagen and the Poisson-Voronoi network solids are similar, and are close to the values n=1.22 and m=2.11 found in a previous voxel-based finite element study of Poisson-Voronoi systems with different boundary conditions. However, the exponents of these empirical power-laws are at odds with the analytic values of n=1 and m=2, valid for low-density cellular structures in the limit of thin beams. We propose a functional form for K(ϕ) that models the cross-over from a power-law at low densities to a porous solid at high densities; a fit of the data to this functional form yields the asymptotic exponent n≈1.00, as expected. Further, both the intensity of the Poisson-Voronoi process and the collagen concentration in the samples, both of which alter the typical pore or mesh size, affect the effective moduli only by the resulting change of the solid volume fraction. These findings suggest that a network solid with the structure of the collagen networks can be modeled in quantitative agreement by a Poisson-Voronoi process. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Tracking climate impacts on the migratory monarch butterfly

USGS Publications Warehouse

Zipkin, Elise F.; Ries, Leslie; Reeves, Rick; Regetz, James; Oberhauser, Karen S.

2012-01-01

Understanding the impacts of climate on migratory species is complicated by the fact that these species travel through several climates that may be changing in diverse ways throughout their complete migratory cycle. Most studies are not designed to tease out the direct and indirect effects of climate at various stages along the migration route. We assess the impacts of spring and summer climate conditions on breeding monarch butterflies, a species that completes its annual migration cycle over several generations. No single, broad-scale climate metric can explain summer breeding phenology or the substantial year-to-year fluctuations observed in population abundances. As such, we built a Poisson regression model to help explain annual arrival times and abundances in the Midwestern United States. We incorporated the climate conditions experienced both during a spring migration/breeding phase in Texas as well as during subsequent arrival and breeding during the main recruitment period in Ohio. Using data from a state-wide butterfly monitoring network in Ohio, our results suggest that climate acts in conflicting ways during the spring and summer seasons. High spring precipitation in Texas is associated with the largest annual population growth in Ohio and the earliest arrival to the summer breeding ground, as are intermediate spring temperatures in Texas. On the other hand, the timing of monarch arrivals to the summer breeding grounds is not affected by climate conditions within Ohio. Once in Ohio for summer breeding, precipitation has minimal impacts on overall abundances, whereas warmer summer temperatures are generally associated with the highest expected abundances, yet this effect is mitigated by the average seasonal temperature of each location in that the warmest sites receive no benefit of above average summer temperatures. Our results highlight the complex relationship between climate and performance for a migrating species and suggest that attempts to understand how monarchs will be affected by future climate conditions will be challenging.

A random-censoring Poisson model for underreported data.

PubMed

de Oliveira, Guilherme Lopes; Loschi, Rosangela Helena; Assunção, Renato Martins

2017-12-30

A major challenge when monitoring risks in socially deprived areas of under developed countries is that economic, epidemiological, and social data are typically underreported. Thus, statistical models that do not take the data quality into account will produce biased estimates. To deal with this problem, counts in suspected regions are usually approached as censored information. The censored Poisson model can be considered, but all censored regions must be precisely known a priori, which is not a reasonable assumption in most practical situations. We introduce the random-censoring Poisson model (RCPM) which accounts for the uncertainty about both the count and the data reporting processes. Consequently, for each region, we will be able to estimate the relative risk for the event of interest as well as the censoring probability. To facilitate the posterior sampling process, we propose a Markov chain Monte Carlo scheme based on the data augmentation technique. We run a simulation study comparing the proposed RCPM with 2 competitive models. Different scenarios are considered. RCPM and censored Poisson model are applied to account for potential underreporting of early neonatal mortality counts in regions of Minas Gerais State, Brazil, where data quality is known to be poor. Copyright © 2017 John Wiley & Sons, Ltd.

On Subset Selection Procedures for Poisson Processes and Some Applications to the Binomial and Multinomial Problems

DTIC Science & Technology

1976-07-01

PURDUE UNIVERSITY DEPARTMENT OF STATISTICS DIVISION OF MATHEMATICAL SCIENCES ON SUBSET SELECTION PROCEDURES FOR POISSON PROCESSES AND SOME...Mathematical Sciences Mimeograph Series #457, July 1976 This research was supported by the Office of Naval Research under Contract NOOO14-75-C-0455 at Purdue...11 CON PC-111 riFIC-F ,A.F ANO ADDPFS Office of INaval ResearchJu#07 Washington, DC07 36AE 14~~~ rjCr; NF A ’ , A FAA D F 6 - I S it 9 i 1, - ,1 I

Crystalline nucleation in undercooled liquids: a Bayesian data-analysis approach for a nonhomogeneous Poisson process.

PubMed

Filipponi, A; Di Cicco, A; Principi, E

2012-12-01

A Bayesian data-analysis approach to data sets of maximum undercooling temperatures recorded in repeated melting-cooling cycles of high-purity samples is proposed. The crystallization phenomenon is described in terms of a nonhomogeneous Poisson process driven by a temperature-dependent sample nucleation rate J(T). The method was extensively tested by computer simulations and applied to real data for undercooled liquid Ge. It proved to be particularly useful in the case of scarce data sets where the usage of binned data would degrade the available experimental information.

Extended Poisson process modelling and analysis of grouped binary data.

PubMed

Faddy, Malcolm J; Smith, David M

2012-05-01

A simple extension of the Poisson process results in binomially distributed counts of events in a time interval. A further extension generalises this to probability distributions under- or over-dispersed relative to the binomial distribution. Substantial levels of under-dispersion are possible with this modelling, but only modest levels of over-dispersion - up to Poisson-like variation. Although simple analytical expressions for the moments of these probability distributions are not available, approximate expressions for the mean and variance are derived, and used to re-parameterise the models. The modelling is applied in the analysis of two published data sets, one showing under-dispersion and the other over-dispersion. More appropriate assessment of the precision of estimated parameters and reliable model checking diagnostics follow from this more general modelling of these data sets. © 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Adiabatic elimination for systems with inertia driven by compound Poisson colored noise.

PubMed

Li, Tiejun; Min, Bin; Wang, Zhiming

2014-02-01

We consider the dynamics of systems driven by compound Poisson colored noise in the presence of inertia. We study the limit when the frictional relaxation time and the noise autocorrelation time both tend to zero. We show that the Itô and Marcus stochastic calculuses naturally arise depending on these two time scales, and an extra intermediate type occurs when the two time scales are comparable. This leads to three different limiting regimes which are supported by numerical simulations. Furthermore, we establish that when the resulting compound Poisson process tends to the Wiener process in the frequent jump limit the Itô and Marcus calculuses, respectively, tend to the classical Itô and Stratonovich calculuses for Gaussian white noise, and the crossover type calculus tends to a crossover between the Itô and Stratonovich calculuses. Our results would be very helpful for understanding relevant experiments when jump type noise is involved.

Measurement of Poisson's ratio of nonmetallic materials by laser holographic interferometry

NASA Astrophysics Data System (ADS)

Zhu, Jian T.

1991-12-01

By means of the off-axis collimated plane wave coherent light arrangement and a loading device by pure bending, Poisson's ratio values of CFRP (carbon fiber-reinforced plactics plates, lay-up 0 degree(s), 90 degree(s)), GFRP (glass fiber-reinforced plactics plates, radial direction) and PMMA (polymethyl methacrylate, x, y direction) have been measured. In virtue of this study, the ministry standard for the Ministry of Aeronautical Industry (Testing method for the measurement of Poisson's ratio of non-metallic by laser holographic interferometry) has been published. The measurement process is fast and simple. The measuring results are reliable and accurate.

Reduction of Poisson noise in measured time-resolved data for time-domain diffuse optical tomography.

PubMed

Okawa, S; Endo, Y; Hoshi, Y; Yamada, Y

2012-01-01

A method to reduce noise for time-domain diffuse optical tomography (DOT) is proposed. Poisson noise which contaminates time-resolved photon counting data is reduced by use of maximum a posteriori estimation. The noise-free data are modeled as a Markov random process, and the measured time-resolved data are assumed as Poisson distributed random variables. The posterior probability of the occurrence of the noise-free data is formulated. By maximizing the probability, the noise-free data are estimated, and the Poisson noise is reduced as a result. The performances of the Poisson noise reduction are demonstrated in some experiments of the image reconstruction of time-domain DOT. In simulations, the proposed method reduces the relative error between the noise-free and noisy data to about one thirtieth, and the reconstructed DOT image was smoothed by the proposed noise reduction. The variance of the reconstructed absorption coefficients decreased by 22% in a phantom experiment. The quality of DOT, which can be applied to breast cancer screening etc., is improved by the proposed noise reduction.

Image denoising in mixed Poisson-Gaussian noise.

PubMed

Luisier, Florian; Blu, Thierry; Unser, Michael

2011-03-01

We propose a general methodology (PURE-LET) to design and optimize a wide class of transform-domain thresholding algorithms for denoising images corrupted by mixed Poisson-Gaussian noise. We express the denoising process as a linear expansion of thresholds (LET) that we optimize by relying on a purely data-adaptive unbiased estimate of the mean-squared error (MSE), derived in a non-Bayesian framework (PURE: Poisson-Gaussian unbiased risk estimate). We provide a practical approximation of this theoretical MSE estimate for the tractable optimization of arbitrary transform-domain thresholding. We then propose a pointwise estimator for undecimated filterbank transforms, which consists of subband-adaptive thresholding functions with signal-dependent thresholds that are globally optimized in the image domain. We finally demonstrate the potential of the proposed approach through extensive comparisons with state-of-the-art techniques that are specifically tailored to the estimation of Poisson intensities. We also present denoising results obtained on real images of low-count fluorescence microscopy.

Chernobyl cleanup workers from Estonia: follow-up for cancer incidence and mortality

PubMed Central

Rahu, Kaja; Auvinen, Anssi; Hakulinen, Timo; Tekkel, Mare; Inskip, Peter D; Bromet, Evelyn J; Boice, John D; Rahu, Mati

2013-01-01

This study examined cancer incidence (1986–2008) and mortality (1986–2011) among the Estonian Chernobyl cleanup workers in comparison with the Estonian male population. The cohort of 4,810 men was followed through nationwide population, mortality and cancer registries. Cancer and death risks were measured by standardized incidence ratio (SIR) and standardized mortality ratio (SMR), respectively. Poisson regression was used to analyze the effects of year of arrival, duration of stay, and time since return on cancer and death risks. The SIR for all cancers was 1.06 with 95% confidence interval 0.93–1.20 (232 cases). Elevated risks were found for cancers of pharynx, oesophagus, and the joint category of alcohol-related sites. No clear evidence of an increased risk of thyroid cancer, leukaemia, or radiation-related cancer sites combined was apparent. The SMR for all causes of death was 1.02 with 95% confidence interval 0.96–1.08 (1,018 deaths). Excess mortality was observed for mouth and pharynx cancer, alcohol-related cancer sites together, and suicide. Duration of stay rather than year of arrival was associated with increased mortality. Twenty-six years of follow-up of this cohort indicates no definite health effects attributable to radiation, but the elevated suicide risk has persisted. PMID:23532116

Limitations of the ideal phase-Doppler system: Extension to spatially and temporally inhomogeneous particle flows with an application to diesel sprays

NASA Astrophysics Data System (ADS)

Marx, K. D.; Edwards, C. F.

1992-12-01

The effect of the single-particle constraint on the response of phase-Doppler instruments is determined for particle flows which are spatially nonuniform and time-dependent. Poisson statistics are applied to particle positions and arrival times within the phase-Doppler probe volume to determine the probability that a particle is measured successfully. It is shown that the single-particle constraint can be viewed as applying spatial and temporal filters to the particle flow. These filters have the same meaning as those that were defined previously for uniform, steady-state sprays, but in space- and time-dependent form. Criteria are developed for determining when a fully inhomogeneous analysis of a flow is required and when a quasi-steady analysis will suffice. A new bias due to particle arrival time displacement is identified and the conditions under which it must be considered are established. The present work provides the means to rigorously investigate the response of phase-Doppler measurement systems to transient sprays such as those which occur in diesel engines. To this end, the results are applied to a numerical simulation of a diesel spray. The calculated hypothetical response of the ideal instrument provides a quantitative demonstration of the regimes within which measurements can accurately be made in such sprays.

Analyzing hospitalization data: potential limitations of Poisson regression.

PubMed

Weaver, Colin G; Ravani, Pietro; Oliver, Matthew J; Austin, Peter C; Quinn, Robert R

2015-08-01

Poisson regression is commonly used to analyze hospitalization data when outcomes are expressed as counts (e.g. number of days in hospital). However, data often violate the assumptions on which Poisson regression is based. More appropriate extensions of this model, while available, are rarely used. We compared hospitalization data between 206 patients treated with hemodialysis (HD) and 107 treated with peritoneal dialysis (PD) using Poisson regression and compared results from standard Poisson regression with those obtained using three other approaches for modeling count data: negative binomial (NB) regression, zero-inflated Poisson (ZIP) regression and zero-inflated negative binomial (ZINB) regression. We examined the appropriateness of each model and compared the results obtained with each approach. During a mean 1.9 years of follow-up, 183 of 313 patients (58%) were never hospitalized (indicating an excess of 'zeros'). The data also displayed overdispersion (variance greater than mean), violating another assumption of the Poisson model. Using four criteria, we determined that the NB and ZINB models performed best. According to these two models, patients treated with HD experienced similar hospitalization rates as those receiving PD {NB rate ratio (RR): 1.04 [bootstrapped 95% confidence interval (CI): 0.49-2.20]; ZINB summary RR: 1.21 (bootstrapped 95% CI 0.60-2.46)}. Poisson and ZIP models fit the data poorly and had much larger point estimates than the NB and ZINB models [Poisson RR: 1.93 (bootstrapped 95% CI 0.88-4.23); ZIP summary RR: 1.84 (bootstrapped 95% CI 0.88-3.84)]. We found substantially different results when modeling hospitalization data, depending on the approach used. Our results argue strongly for a sound model selection process and improved reporting around statistical methods used for modeling count data. © The Author 2015. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Evolving Scale-Free Networks by Poisson Process: Modeling and Degree Distribution.

PubMed

Feng, Minyu; Qu, Hong; Yi, Zhang; Xie, Xiurui; Kurths, Jurgen

2016-05-01

Since the great mathematician Leonhard Euler initiated the study of graph theory, the network has been one of the most significant research subject in multidisciplinary. In recent years, the proposition of the small-world and scale-free properties of complex networks in statistical physics made the network science intriguing again for many researchers. One of the challenges of the network science is to propose rational models for complex networks. In this paper, in order to reveal the influence of the vertex generating mechanism of complex networks, we propose three novel models based on the homogeneous Poisson, nonhomogeneous Poisson and birth death process, respectively, which can be regarded as typical scale-free networks and utilized to simulate practical networks. The degree distribution and exponent are analyzed and explained in mathematics by different approaches. In the simulation, we display the modeling process, the degree distribution of empirical data by statistical methods, and reliability of proposed networks, results show our models follow the features of typical complex networks. Finally, some future challenges for complex systems are discussed.

Investigating on the Differences between Triggered and Background Seismicity in Italy and Southern California.

NASA Astrophysics Data System (ADS)

Stallone, A.; Marzocchi, W.

2017-12-01

Earthquake occurrence may be approximated by a multidimensional Poisson clustering process, where each point of the Poisson process is replaced by a cluster of points, the latter corresponding to the well-known aftershock sequence (triggered events). Earthquake clusters and their parents are assumed to occur according to a Poisson process at a constant temporal rate proportional to the tectonic strain rate, while events within a cluster are modeled as generations of dependent events reproduced by a branching process. Although the occurrence of such space-time clusters is a general feature in different tectonic settings, seismic sequences seem to have marked differences from region to region: one example, among many others, is that seismic sequences of moderate magnitude in Italian Apennines seem to last longer than similar seismic sequences in California. In this work we investigate on the existence of possible differences in the earthquake clustering process in these two areas. At first, we separate the triggered and background components of seismicity in the Italian and Southern California seismic catalog. Then we study the space-time domain of the triggered earthquakes with the aim to identify possible variations in the triggering properties across the two regions. In the second part of the work we focus our attention on the characteristics of the background seismicity in both seismic catalogs. The assumption of time stationarity of the background seismicity (which includes both cluster parents and isolated events) is still under debate. Some authors suggest that the independent component of seismicity could undergo transient perturbations at various time scales due to different physical mechanisms, such as, for example, viscoelastic relaxation, presence of fluids, non-stationary plate motion, etc, whose impact may depend on the tectonic setting. Here we test if the background seismicity in the two regions can be satisfactorily described by the time-homogeneous Poisson process, and, in case, we characterize quantitatively possible discrepancies with this reference process, and the differences between the two regions.

Information-based models for finance and insurance

NASA Astrophysics Data System (ADS)

Hoyle, Edward

2010-10-01

In financial markets, the information that traders have about an asset is reflected in its price. The arrival of new information then leads to price changes. The `information-based framework' of Brody, Hughston and Macrina (BHM) isolates the emergence of information, and examines its role as a driver of price dynamics. This approach has led to the development of new models that capture a broad range of price behaviour. This thesis extends the work of BHM by introducing a wider class of processes for the generation of the market filtration. In the BHM framework, each asset is associated with a collection of random cash flows. The asset price is the sum of the discounted expectations of the cash flows. Expectations are taken with respect (i) an appropriate measure, and (ii) the filtration generated by a set of so-called information processes that carry noisy or imperfect market information about the cash flows. To model the flow of information, we introduce a class of processes termed Lévy random bridges (LRBs), generalising the Brownian and gamma information processes of BHM. Conditioned on its terminal value, an LRB is identical in law to a Lévy bridge. We consider in detail the case where the asset generates a single cash flow X_T at a fixed date T. The flow of information about X_T is modelled by an LRB with random terminal value X_T. An explicit expression for the price process is found by working out the discounted conditional expectation of X_T with respect to the natural filtration of the LRB. New models are constructed using information processes related to the Poisson process, the Cauchy process, the stable-1/2 subordinator, the variance-gamma process, and the normal inverse-Gaussian process. These are applied to the valuation of credit-risky bonds, vanilla and exotic options, and non-life insurance liabilities.

Fast immersed interface Poisson solver for 3D unbounded problems around arbitrary geometries

NASA Astrophysics Data System (ADS)

Gillis, T.; Winckelmans, G.; Chatelain, P.

2018-02-01

We present a fast and efficient Fourier-based solver for the Poisson problem around an arbitrary geometry in an unbounded 3D domain. This solver merges two rewarding approaches, the lattice Green's function method and the immersed interface method, using the Sherman-Morrison-Woodbury decomposition formula. The method is intended to be second order up to the boundary. This is verified on two potential flow benchmarks. We also further analyse the iterative process and the convergence behavior of the proposed algorithm. The method is applicable to a wide range of problems involving a Poisson equation around inner bodies, which goes well beyond the present validation on potential flows.

Prevalence of multi drug antimicrobial resistance in isolated from high-risk stocker cattle at arrival and two weeks after processing.

PubMed

Snyder, E; Credille, B; Berghaus, R; Giguère, S

2017-03-01

Bovine respiratory disease (BRD) is the leading cause of morbidity and mortality in North American beef cattle. () is the bacterial pathogen most frequently isolated from cattle with BRD and the prevalence of antimicrobial resistance in this pathogen has been increasing. Administration of antimicrobials to prevent BRD is commonplace in stocker cattle, but the impact of this practice on emergence of resistance in is unknown. High risk, sale barn origin bull and steer calves ( = 169) were transported to a stocker facility in central Georgia and sampled via deep nasopharyngeal swab (NPS) at arrival processing. All calves received the macrolide antimicrobial tulathromycin (2.5 mg/kg subcutaneously) at arrival processing. A second NPS was collected from each calf 10 to 14 d after arrival. The occasional calves diagnosed and treated for BRD prior to 10 to 14 d were swabbed and cultured prior to treatment. Swabs were submitted for culture and antimicrobial susceptibility testing using the Kirby-Bauer disk diffusion method. Of the 169 cattle enrolled, 27 (16.0%) were culture positive for at arrival processing and of these, a multi-drug resistant (MDR) strain of was detected in 1 (3.7%). In contrast, 123 (72.8%) cattle were culture positive for at second sampling and of these, a MDR strain of was detected in 122 (99.2%). The proportions of cattle culture positive for and positive for MDR at arrival processing and at second sampling were significantly different ( < 0.001). At the level of the individual bacterial isolate, 366 individual isolates were collected from the calves at the time of the second sampling. Of these isolates, 361 (98.6%) were intermediate or resistant to all macrolides tested (tilmicosin, gamithromycin, tulathromycin) and the fluoroquinolone enrofloxacin. In addition, 254 isolates (69.4%) were intermediate or resistant to florfenicol and 4 (1.1%) were intermediate or resistant to ceftiofur. There was a significant difference in the proportion of isolates resistant to all of the drug classes except cephalosporins at arrival processing versus second sampling ( < 0.001). Our results show that there was an increase in the proportion of calves positive for from arrival processing to second sampling, and that there was an increase in the proportion of calves that had MDR strains of detected from arrival processing to second sampling. More research is needed to understand the role of metaphylaxis on MDR in and the impact of MDR on morbidity and mortality in stocker cattle.

Increasing Dengue Incidence in Singapore over the Past 40 Years: Population Growth, Climate and Mobility

PubMed Central

Struchiner, Claudio Jose; Rocklöv, Joacim; Wilder-Smith, Annelies; Massad, Eduardo

2015-01-01

In Singapore, the frequency and magnitude of dengue epidemics have increased significantly over the past 40 years. It is important to understand the main drivers for the rapid increase in dengue incidence. We studied the relative contributions of putative drivers for the rise of dengue in Singapore: population growth, climate parameters and international air passenger arrivals from dengue endemic countries, for the time period of 1974 until 2011. We used multivariable Poisson regression models with the following predictors: Annual Population Size; Aedes Premises Index; Mean Annual Temperature; Minimum and Maximum Temperature Recorded in each year; Annual Precipitation and Annual Number of Air Passengers arriving from dengue-endemic South-East Asia to Singapore. The relative risk (RR) of the increase in dengue incidence due to population growth over the study period was 42.7, while the climate variables (mean and minimum temperature) together explained an RR of 7.1 (RR defined as risk at the end of the time period relative to the beginning and goodness of fit associated with the model leading to these estimates assessed by pseudo-R2 equal to 0.83). Estimating the extent of the contribution of these individual factors on the increasing dengue incidence, we found that population growth contributed to 86% while the residual 14% was explained by increase in temperature. We found no correlation with incoming air passenger arrivals into Singapore from dengue endemic countries. Our findings have significant implications for predicting future trends of the dengue epidemics given the rapid urbanization with population growth in many dengue endemic countries. It is time for policy-makers and the scientific community alike to pay more attention to the negative impact of urbanization and urban climate on diseases such as dengue. PMID:26322517

Increasing Dengue Incidence in Singapore over the Past 40 Years: Population Growth, Climate and Mobility.

PubMed

Struchiner, Claudio Jose; Rocklöv, Joacim; Wilder-Smith, Annelies; Massad, Eduardo

2015-01-01

In Singapore, the frequency and magnitude of dengue epidemics have increased significantly over the past 40 years. It is important to understand the main drivers for the rapid increase in dengue incidence. We studied the relative contributions of putative drivers for the rise of dengue in Singapore: population growth, climate parameters and international air passenger arrivals from dengue endemic countries, for the time period of 1974 until 2011. We used multivariable Poisson regression models with the following predictors: Annual Population Size; Aedes Premises Index; Mean Annual Temperature; Minimum and Maximum Temperature Recorded in each year; Annual Precipitation and Annual Number of Air Passengers arriving from dengue-endemic South-East Asia to Singapore. The relative risk (RR) of the increase in dengue incidence due to population growth over the study period was 42.7, while the climate variables (mean and minimum temperature) together explained an RR of 7.1 (RR defined as risk at the end of the time period relative to the beginning and goodness of fit associated with the model leading to these estimates assessed by pseudo-R2 equal to 0.83). Estimating the extent of the contribution of these individual factors on the increasing dengue incidence, we found that population growth contributed to 86% while the residual 14% was explained by increase in temperature. We found no correlation with incoming air passenger arrivals into Singapore from dengue endemic countries. Our findings have significant implications for predicting future trends of the dengue epidemics given the rapid urbanization with population growth in many dengue endemic countries. It is time for policy-makers and the scientific community alike to pay more attention to the negative impact of urbanization and urban climate on diseases such as dengue.

Waiting-time distributions of magnetic discontinuities: clustering or Poisson process?

PubMed

Greco, A; Matthaeus, W H; Servidio, S; Dmitruk, P

2009-10-01

Using solar wind data from the Advanced Composition Explorer spacecraft, with the support of Hall magnetohydrodynamic simulations, the waiting-time distributions of magnetic discontinuities have been analyzed. A possible phenomenon of clusterization of these discontinuities is studied in detail. We perform a local Poisson's analysis in order to establish if these intermittent events are randomly distributed or not. Possible implications about the nature of solar wind discontinuities are discussed.

The Poisson Random Process. Applications of Probability Theory to Operations Research. Modules and Monographs in Undergraduate Mathematics and Its Applications Project. UMAP Unit 340.

ERIC Educational Resources Information Center

Wilde, Carroll O.

The Poisson probability distribution is seen to provide a mathematical model from which useful information can be obtained in practical applications. The distribution and some situations to which it applies are studied, and ways to find answers to practical questions are noted. The unit includes exercises and a model exam, and provides answers to…

Waiting-time distributions of magnetic discontinuities: Clustering or Poisson process?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Greco, A.; Matthaeus, W. H.; Servidio, S.

2009-10-15

Using solar wind data from the Advanced Composition Explorer spacecraft, with the support of Hall magnetohydrodynamic simulations, the waiting-time distributions of magnetic discontinuities have been analyzed. A possible phenomenon of clusterization of these discontinuities is studied in detail. We perform a local Poisson's analysis in order to establish if these intermittent events are randomly distributed or not. Possible implications about the nature of solar wind discontinuities are discussed.

Electrodeposition of Isolated Platinum Atoms and Clusters on Bismuth-Characterization and Electrocatalysis.

PubMed

Zhou, Min; Dick, Jeffrey E; Bard, Allen J

2017-12-06

We describe a method for the electrodeposition of an isolated single Pt atom or small cluster, up to 9 atoms, on a bismuth ultramicroelectrode (UME). This deposition was immediately followed by electrochemical characterization via the hydrogen evolution reaction (HER) that occurs readily on the electrodeposited Pt but not on Bi. The observed voltammetric current plateau, even for a single atom, which behaves as an electrode, allows the estimation of deposit size. Pt was plated from solutions of femtomolar PtCl 6 2- , which allowed precise control of the arrival of ions and thus the plating rate on the Bi UME, to one ion every few seconds. This allowed the atom-by-atom fabrication of isolated platinum deposits, ranging from single atoms to 9-atom clusters. The limiting currents in voltammetry gave the size and number of atoms of the clusters. Given the stochasticity of the plating process, we show that the number of atoms plated over a given time (10 and 20 s) follows a Poisson distribution. Taking the potential at a certain current density as a measure of the relative rate of the HER, we found that the potential shifted positively as the size increased, with single atoms showing the largest overpotentials compared to bulk Pt.

Queueing system analysis of multi server model at XYZ insurance company in Tasikmalaya city

NASA Astrophysics Data System (ADS)

Muhajir, Ahmad; Binatari, Nikenasih

2017-08-01

Queueing theory or waiting line theory is a theory that deals with the queue process from the customer comes, queue to be served, served and left on service facilities. Queue occurs because of a mismatch between the numbers of customers that will be served with the available number of services, as an example at XYZ insurance company in Tasikmalaya. This research aims to determine the characteristics of the queue system which then to optimize the number of server in term of total cost. The result shows that the queue model can be represented by (M/M/4):(GD/∞/∞), where the arrivals are Poisson distributed while the service time is following exponential distribution. The probability of idle customer service is 2,39% of the working time, the average number of customer in the queue is 3 customers, the average number of customer in a system is 6 customers, the average time of a customer spent in the queue is 15,9979 minutes, the average time a customer spends in the system is 34,4141 minutes, and the average number of busy customer servicer is 3 server. The optimized number of customer service is 5 servers, and the operational cost has minimum cost at Rp 4.323.

Two-sample discrimination of Poisson means

NASA Technical Reports Server (NTRS)

Lampton, M.

1994-01-01

This paper presents a statistical test for detecting significant differences between two random count accumulations. The null hypothesis is that the two samples share a common random arrival process with a mean count proportional to each sample's exposure. The model represents the partition of N total events into two counts, A and B, as a sequence of N independent Bernoulli trials whose partition fraction, f, is determined by the ratio of the exposures of A and B. The detection of a significant difference is claimed when the background (null) hypothesis is rejected, which occurs when the observed sample falls in a critical region of (A, B) space. The critical region depends on f and the desired significance level, alpha. The model correctly takes into account the fluctuations in both the signals and the background data, including the important case of small numbers of counts in the signal, the background, or both. The significance can be exactly determined from the cumulative binomial distribution, which in turn can be inverted to determine the critical A(B) or B(A) contour. This paper gives efficient implementations of these tests, based on lookup tables. Applications include the detection of clustering of astronomical objects, the detection of faint emission or absorption lines in photon-limited spectroscopy, the detection of faint emitters or absorbers in photon-limited imaging, and dosimetry.

Holonomy, quantum mechanics and the signal-tuned Gabor approach to the striate cortex

NASA Astrophysics Data System (ADS)

Torreão, José R. A.

2016-02-01

It has been suggested that an appeal to holographic and quantum properties will be ultimately required for the understanding of higher brain functions. On the other hand, successful quantum-like approaches to cognitive and behavioral processes bear witness to the usefulness of quantum prescriptions as applied to the analysis of complex non-quantum systems. Here, we show that the signal-tuned Gabor approach for modeling cortical neurons, although not based on quantum assumptions, also admits a quantum-like interpretation. Recently, the equation of motion for the signal-tuned complex cell response has been derived and proven equivalent to the Schrödinger equation for a dissipative quantum system whose solutions come under two guises: as plane-wave and Airy-packet responses. By interpreting the squared magnitude of the plane-wave solution as a probability density, in accordance with the quantum mechanics prescription, we arrive at a Poisson spiking probability — a common model of neuronal response — while spike propagation can be described by the Airy-packet solution. The signal-tuned approach is also proven consistent with holonomic brain theories, as it is based on Gabor functions which provide a holographic representation of the cell’s input, in the sense that any restricted subset of these functions still allows stimulus reconstruction.

Introducing the "Decider" Design Process

ERIC Educational Resources Information Center

Prasa, Anthony R., Jr.; Del Guercio, Ryan

2016-01-01

Engineers are faced with solving important problems every day and must follow a step-by-step design process to arrive at solutions. Students who are taught an effective design process to apply to engineering projects begin to see problems as an engineer would, consider all ideas, and arrive at the best solution. Using an effective design process…

Wavelets, ridgelets, and curvelets for Poisson noise removal.

PubMed

Zhang, Bo; Fadili, Jalal M; Starck, Jean-Luc

2008-07-01

In order to denoise Poisson count data, we introduce a variance stabilizing transform (VST) applied on a filtered discrete Poisson process, yielding a near Gaussian process with asymptotic constant variance. This new transform, which can be deemed as an extension of the Anscombe transform to filtered data, is simple, fast, and efficient in (very) low-count situations. We combine this VST with the filter banks of wavelets, ridgelets and curvelets, leading to multiscale VSTs (MS-VSTs) and nonlinear decomposition schemes. By doing so, the noise-contaminated coefficients of these MS-VST-modified transforms are asymptotically normally distributed with known variances. A classical hypothesis-testing framework is adopted to detect the significant coefficients, and a sparsity-driven iterative scheme reconstructs properly the final estimate. A range of examples show the power of this MS-VST approach for recovering important structures of various morphologies in (very) low-count images. These results also demonstrate that the MS-VST approach is competitive relative to many existing denoising methods.

Clinical characterization of 2D pressure field in human left ventricles

NASA Astrophysics Data System (ADS)

Borja, Maria; Rossini, Lorenzo; Martinez-Legazpi, Pablo; Benito, Yolanda; Alhama, Marta; Yotti, Raquel; Perez Del Villar, Candelas; Gonzalez-Mansilla, Ana; Barrio, Alicia; Fernandez-Aviles, Francisco; Bermejo, Javier; Khan, Andrew; Del Alamo, Juan Carlos

2014-11-01

The evaluation of left ventricle (LV) function in the clinical setting remains a challenge. Pressure gradient is a reliable and reproducible indicator of the LV function. We obtain 2D relative pressure field in the LV using in-vivo measurements obtained by processing Doppler-echocardiography images of healthy and dilated hearts. Exploiting mass conservation, we solve the Poisson pressure equation (PPE) dropping the time derivatives and viscous terms. The flow acceleration appears only in the boundary conditions, making our method weakly sensible to the time resolution of in-vivo acquisitions. To ensure continuity with respect to the discrete operator and grid used, a potential flow correction is applied beforehand, which gives another Poisson equation. The new incompressible velocity field ensures that the compatibility equation for the PPE is satisfied. Both Poisson equations are efficiently solved on a Cartesian grid using a multi-grid method and immersed boundary for the LV wall. The whole process is computationally inexpensive and could play a diagnostic role in the clinical assessment of LV function.

Eruption patterns of the chilean volcanoes Villarrica, Llaima, and Tupungatito

NASA Astrophysics Data System (ADS)

Muñoz, Miguel

1983-09-01

The historical eruption records of three Chilean volcanoes have been subjected to many statistical tests, and none have been found to differ significantly from random, or Poissonian, behaviour. The statistical analysis shows rough conformity with the descriptions determined from the eruption rate functions. It is possible that a constant eruption rate describes the activity of Villarrica; Llaima and Tupungatito present complex eruption rate patterns that appear, however, to have no statistical significance. Questions related to loading and extinction processes and to the existence of shallow secondary magma chambers to which magma is supplied from a deeper system are also addressed. The analysis and the computation of the serial correlation coefficients indicate that the three series may be regarded as stationary renewal processes. None of the test statistics indicates rejection of the Poisson hypothesis at a level less than 5%, but the coefficient of variation for the eruption series at Llaima is significantly different from the value expected for a Poisson process. Also, the estimates of the normalized spectrum of the counting process for the three series suggest a departure from the random model, but the deviations are not found to be significant at the 5% level. Kolmogorov-Smirnov and chi-squared test statistics, applied directly to ascertaining to which probability P the random Poisson model fits the data, indicate that there is significant agreement in the case of Villarrica ( P=0.59) and Tupungatito ( P=0.3). Even though the P-value for Llaima is a marginally significant 0.1 (which is equivalent to rejecting the Poisson model at the 90% confidence level), the series suggests that nonrandom features are possibly present in the eruptive activity of this volcano.

Filling of a Poisson trap by a population of random intermittent searchers.

PubMed

Bressloff, Paul C; Newby, Jay M

2012-03-01

We extend the continuum theory of random intermittent search processes to the case of N independent searchers looking to deliver cargo to a single hidden target located somewhere on a semi-infinite track. Each searcher randomly switches between a stationary state and either a leftward or rightward constant velocity state. We assume that all of the particles start at one end of the track and realize sample trajectories independently generated from the same underlying stochastic process. The hidden target is treated as a partially absorbing trap in which a particle can only detect the target and deliver its cargo if it is stationary and within range of the target; the particle is removed from the system after delivering its cargo. As a further generalization of previous models, we assume that up to n successive particles can find the target and deliver its cargo. Assuming that the rate of target detection scales as 1/N, we show that there exists a well-defined mean-field limit N→∞, in which the stochastic model reduces to a deterministic system of linear reaction-hyperbolic equations for the concentrations of particles in each of the internal states. These equations decouple from the stochastic process associated with filling the target with cargo. The latter can be modeled as a Poisson process in which the time-dependent rate of filling λ(t) depends on the concentration of stationary particles within the target domain. Hence, we refer to the target as a Poisson trap. We analyze the efficiency of filling the Poisson trap with n particles in terms of the waiting time density f(n)(t). The latter is determined by the integrated Poisson rate μ(t)=∫(0)(t)λ(s)ds, which in turn depends on the solution to the reaction-hyperbolic equations. We obtain an approximate solution for the particle concentrations by reducing the system of reaction-hyperbolic equations to a scalar advection-diffusion equation using a quasisteady-state analysis. We compare our analytical results for the mean-field model with Monte Carlo simulations for finite N. We thus determine how the mean first passage time (MFPT) for filling the target depends on N and n.

Joseph eleve des poissons au Gabon. Guide pour l'elevage des poissons (Joseph Raises Fish in Gabon. Guide for Raising Fish).

ERIC Educational Resources Information Center

Needham, Scott

A guide, in French, to raising fish for food and profit is designed to instruct and encourage Gabonese natives to establish family fisheries. It describes and illustrates in story form the process used to plan the fishery, clear the land, seek help from an agricultural agent, create a dam, make compost, plan and build the pond, feed the fish,…

A stochastic model for stationary dynamics of prices in real estate markets. A case of random intensity for Poisson moments of prices changes

NASA Astrophysics Data System (ADS)

Rusakov, Oleg; Laskin, Michael

2017-06-01

We consider a stochastic model of changes of prices in real estate markets. We suppose that in a book of prices the changes happen in points of jumps of a Poisson process with a random intensity, i.e. moments of changes sequently follow to a random process of the Cox process type. We calculate cumulative mathematical expectations and variances for the random intensity of this point process. In the case that the process of random intensity is a martingale the cumulative variance has a linear grows. We statistically process a number of observations of real estate prices and accept hypotheses of a linear grows for estimations as well for cumulative average, as for cumulative variance both for input and output prises that are writing in the book of prises.

A Conway-Maxwell-Poisson (CMP) model to address data dispersion on positron emission tomography.

PubMed

Santarelli, Maria Filomena; Della Latta, Daniele; Scipioni, Michele; Positano, Vincenzo; Landini, Luigi

2016-10-01

Positron emission tomography (PET) in medicine exploits the properties of positron-emitting unstable nuclei. The pairs of γ- rays emitted after annihilation are revealed by coincidence detectors and stored as projections in a sinogram. It is well known that radioactive decay follows a Poisson distribution; however, deviation from Poisson statistics occurs on PET projection data prior to reconstruction due to physical effects, measurement errors, correction of deadtime, scatter, and random coincidences. A model that describes the statistical behavior of measured and corrected PET data can aid in understanding the statistical nature of the data: it is a prerequisite to develop efficient reconstruction and processing methods and to reduce noise. The deviation from Poisson statistics in PET data could be described by the Conway-Maxwell-Poisson (CMP) distribution model, which is characterized by the centring parameter λ and the dispersion parameter ν, the latter quantifying the deviation from a Poisson distribution model. In particular, the parameter ν allows quantifying over-dispersion (ν<1) or under-dispersion (ν>1) of data. A simple and efficient method for λ and ν parameters estimation is introduced and assessed using Monte Carlo simulation for a wide range of activity values. The application of the method to simulated and experimental PET phantom data demonstrated that the CMP distribution parameters could detect deviation from the Poisson distribution both in raw and corrected PET data. It may be usefully implemented in image reconstruction algorithms and quantitative PET data analysis, especially in low counting emission data, as in dynamic PET data, where the method demonstrated the best accuracy. Copyright © 2016 Elsevier Ltd. All rights reserved.

Information transfer with rate-modulated Poisson processes: a simple model for nonstationary stochastic resonance.

PubMed

Goychuk, I

2001-08-01

Stochastic resonance in a simple model of information transfer is studied for sensory neurons and ensembles of ion channels. An exact expression for the information gain is obtained for the Poisson process with the signal-modulated spiking rate. This result allows one to generalize the conventional stochastic resonance (SR) problem (with periodic input signal) to the arbitrary signals of finite duration (nonstationary SR). Moreover, in the case of a periodic signal, the rate of information gain is compared with the conventional signal-to-noise ratio. The paper establishes the general nonequivalence between both measures notwithstanding their apparent similarity in the limit of weak signals.

A Poisson process approximation for generalized K-5 confidence regions

NASA Technical Reports Server (NTRS)

Arsham, H.; Miller, D. R.

1982-01-01

One-sided confidence regions for continuous cumulative distribution functions are constructed using empirical cumulative distribution functions and the generalized Kolmogorov-Smirnov distance. The band width of such regions becomes narrower in the right or left tail of the distribution. To avoid tedious computation of confidence levels and critical values, an approximation based on the Poisson process is introduced. This aproximation provides a conservative confidence region; moreover, the approximation error decreases monotonically to 0 as sample size increases. Critical values necessary for implementation are given. Applications are made to the areas of risk analysis, investment modeling, reliability assessment, and analysis of fault tolerant systems.

Mixed-Poisson Point Process with Partially-Observed Covariates: Ecological Momentary Assessment of Smoking.

PubMed

Neustifter, Benjamin; Rathbun, Stephen L; Shiffman, Saul

2012-01-01

Ecological Momentary Assessment is an emerging method of data collection in behavioral research that may be used to capture the times of repeated behavioral events on electronic devices, and information on subjects' psychological states through the electronic administration of questionnaires at times selected from a probability-based design as well as the event times. A method for fitting a mixed Poisson point process model is proposed for the impact of partially-observed, time-varying covariates on the timing of repeated behavioral events. A random frailty is included in the point-process intensity to describe variation among subjects in baseline rates of event occurrence. Covariate coefficients are estimated using estimating equations constructed by replacing the integrated intensity in the Poisson score equations with a design-unbiased estimator. An estimator is also proposed for the variance of the random frailties. Our estimators are robust in the sense that no model assumptions are made regarding the distribution of the time-varying covariates or the distribution of the random effects. However, subject effects are estimated under gamma frailties using an approximate hierarchical likelihood. The proposed approach is illustrated using smoking data.

Toward negative Poisson's ratio composites: Investigation of the auxetic behavior of fibrous networks

NASA Astrophysics Data System (ADS)

Tatlier, Mehmet Seha

Random fibrous can be found among natural and synthetic materials. Some of these random fibrous networks possess negative Poisson's ratio and they are extensively called auxetic materials. The governing mechanisms behind this counter intuitive property in random networks are yet to be understood and this kind of auxetic material remains widely under-explored. However, most of synthetic auxetic materials suffer from their low strength. This shortcoming can be rectified by developing high strength auxetic composites. The process of embedding auxetic random fibrous networks in a polymer matrix is an attractive alternate route to the manufacture of auxetic composites, however before such an approach can be developed, a methodology for designing fibrous networks with the desired negative Poisson's ratios must first be established. This requires an understanding of the factors which bring about negative Poisson's ratios in these materials. In this study, a numerical model is presented in order to investigate the auxetic behavior in compressed random fiber networks. Finite element analyses of three-dimensional stochastic fiber networks were performed to gain insight into the effects of parameters such as network anisotropy, network density, and degree of network compression on the out-of-plane Poisson's ratio and Young's modulus. The simulation results suggest that the compression is the critical parameter that gives rise to negative Poisson's ratio while anisotropy significantly promotes the auxetic behavior. This model can be utilized to design fibrous auxetic materials and to evaluate feasibility of developing auxetic composites by using auxetic fibrous networks as the reinforcing layer.

Seismic Wave Velocity in the Subducted Oceanic Crust from Autocorrelation of Tectonic Tremor Signals

NASA Astrophysics Data System (ADS)

Ducellier, A.; Creager, K.

2017-12-01

Hydration and dehydration of minerals in subduction zones play a key role in the geodynamic processes that generate seismicity and that allow tectonic plates to subduct. Detecting the presence of water in the subducted plate is thus crucial to better understand the seismogenesis and the consequent seismic hazard. A landward dipping, low velocity layer has been detected in most subduction zones. In Cascadia, this low velocity zone is characterized by a low S-wave velocity and a very high Poisson's ratio, which has been interpreted as high pore-fluid pressure in the upper half part of the subducted oceanic crust. Most previous studies were based on seismic reflection imaging, receiver function analysis, or body wave tomography, with seismic sources located far from the low velocity zone. In contrast, the sources of the tectonic tremors generated during Episodic Tremor and Slip (ETS) events are located on the plate boundary. As the sources of the tremors are much closer to the low velocity zone, seismic waves recorded during ETS events should illuminate the area with greater precision. Most methods to detect and locate tectonic tremors and low-frequency earthquakes are based on the cross correlation of seismic signals; either signals at the same station for different events, or the same event at different stations. We use the autocorrelation of the seismic signal recorded by eight arrays of stations, located in the Olympic Peninsula, Washington. Each tremor, assumed to be on the plate boundary, generates a direct wave and reflected and converted waves from both the strong shear-wave velocity contrast in the mid-oceanic crust, and from the Moho of the subducted oceanic crust. The time lag between the arrivals of these different waves at a seismic station corresponds to a peak of amplitude on the autocorrelation signals. Using the time lags observed for different locations of the tremor source, we intend to invert for the seismic wave velocity of the subducted oceanic crust under the arrays. Identifying zones with lower S-wave velocity and a high Poisson's ratio will then help detecting the presence of water in the subducted oceanic crust. Our ultimate goal is contributing to a better understanding of the mechanism of ETS and subduction zone processes.

De Rham-Hodge decomposition and vanishing of harmonic forms by derivation operators on the Poisson space

NASA Astrophysics Data System (ADS)

Privault, Nicolas

2016-05-01

We construct differential forms of all orders and a covariant derivative together with its adjoint on the probability space of a standard Poisson process, using derivation operators. In this framewok we derive a de Rham-Hodge-Kodaira decomposition as well as Weitzenböck and Clark-Ocone formulas for random differential forms. As in the Wiener space setting, this construction provides two distinct approaches to the vanishing of harmonic differential forms.

Tooth loss patterns in older adults with special needs: a Minnesota cohort

PubMed Central

Chen, Xi; Clark, Jennifer J

2011-01-01

This study was conducted to detail tooth loss patterns in older adults with special needs. A total of 491 elderly subjects with special needs were retrospectively selected and followed during 10/1999-12/2006. Medical, dental, cognitive, and functional assessments were abstracted from dental records and used to predict risk of tooth loss. Tooth loss events were recorded for subjects during follow-up. Chi-squared tests were used to study the association between tooth loss and the selected risk factors. Logistic, poisson, and negative binomial regressions were developed to study tooth loss patterns. Overall, 27% of the subjects lost at least one tooth during follow-up. Fourteen subjects had tooth loss events per 100 person-years. Tooth loss pattern did not differ significantly among different special-needs subgroups (i.e. community-dwelling vs. long-term care, physically disabled vs. functionally independent). Special-needs subjects with three or more active dental conditions at arrival had more than twice the risk of losing teeth than those without any existing conditions. After adjusting other factors, the number of carious teeth or retained roots at arrival was a significant predictor of tooth loss for older adults with special needs (P=0.001). These findings indicate that appropriately managing active caries and associated conditions is important to prevent tooth loss for older adults with special needs. PMID:21449213

The Effect of Ongoing Exposure Dynamics in Dose Response Relationships

PubMed Central

Pujol, Josep M.; Eisenberg, Joseph E.; Haas, Charles N.; Koopman, James S.

2009-01-01

Characterizing infectivity as a function of pathogen dose is integral to microbial risk assessment. Dose-response experiments usually administer doses to subjects at one time. Phenomenological models of the resulting data, such as the exponential and the Beta-Poisson models, ignore dose timing and assume independent risks from each pathogen. Real world exposure to pathogens, however, is a sequence of discrete events where concurrent or prior pathogen arrival affects the capacity of immune effectors to engage and kill newly arriving pathogens. We model immune effector and pathogen interactions during the period before infection becomes established in order to capture the dynamics generating dose timing effects. Model analysis reveals an inverse relationship between the time over which exposures accumulate and the risk of infection. Data from one time dose experiments will thus overestimate per pathogen infection risks of real world exposures. For instance, fitting our model to one time dosing data reveals a risk of 0.66 from 313 Cryptosporidium parvum pathogens. When the temporal exposure window is increased 100-fold using the same parameters fitted by our model to the one time dose data, the risk of infection is reduced to 0.09. Confirmation of this risk prediction requires data from experiments administering doses with different timings. Our model demonstrates that dose timing could markedly alter the risks generated by airborne versus fomite transmitted pathogens. PMID:19503605

Optical Signal Processing: Poisson Image Restoration and Shearing Interferometry

NASA Technical Reports Server (NTRS)

Hong, Yie-Ming

1973-01-01

Optical signal processing can be performed in either digital or analog systems. Digital computers and coherent optical systems are discussed as they are used in optical signal processing. Topics include: image restoration; phase-object visualization; image contrast reversal; optical computation; image multiplexing; and fabrication of spatial filters. Digital optical data processing deals with restoration of images degraded by signal-dependent noise. When the input data of an image restoration system are the numbers of photoelectrons received from various areas of a photosensitive surface, the data are Poisson distributed with mean values proportional to the illuminance of the incoherently radiating object and background light. Optical signal processing using coherent optical systems is also discussed. Following a brief review of the pertinent details of Ronchi's diffraction grating interferometer, moire effect, carrier-frequency photography, and achromatic holography, two new shearing interferometers based on them are presented. Both interferometers can produce variable shear.

Generic Schemes for Single-Molecule Kinetics. 2: Information Content of the Poisson Indicator.

PubMed

Avila, Thomas R; Piephoff, D Evan; Cao, Jianshu

2017-08-24

Recently, we described a pathway analysis technique (paper 1) for analyzing generic schemes for single-molecule kinetics based upon the first-passage time distribution. Here, we employ this method to derive expressions for the Poisson indicator, a normalized measure of stochastic variation (essentially equivalent to the Fano factor and Mandel's Q parameter), for various renewal (i.e., memoryless) enzymatic reactions. We examine its dependence on substrate concentration, without assuming all steps follow Poissonian kinetics. Based upon fitting to the functional forms of the first two waiting time moments, we show that, to second order, the non-Poissonian kinetics are generally underdetermined but can be specified in certain scenarios. For an enzymatic reaction with an arbitrary intermediate topology, we identify a generic minimum of the Poisson indicator as a function of substrate concentration, which can be used to tune substrate concentration to the stochastic fluctuations and to estimate the largest number of underlying consecutive links in a turnover cycle. We identify a local maximum of the Poisson indicator (with respect to substrate concentration) for a renewal process as a signature of competitive binding, either between a substrate and an inhibitor or between multiple substrates. Our analysis explores the rich connections between Poisson indicator measurements and microscopic kinetic mechanisms.

The Poisson model limits in NBA basketball: Complexity in team sports

NASA Astrophysics Data System (ADS)

Martín-González, Juan Manuel; de Saá Guerra, Yves; García-Manso, Juan Manuel; Arriaza, Enrique; Valverde-Estévez, Teresa

2016-12-01

Team sports are frequently studied by researchers. There is presumption that scoring in basketball is a random process and that can be described using the Poisson Model. Basketball is a collaboration-opposition sport, where the non-linear local interactions among players are reflected in the evolution of the score that ultimately determines the winner. In the NBA, the outcomes of close games are often decided in the last minute, where fouls play a main role. We examined 6130 NBA games in order to analyze the time intervals between baskets and scoring dynamics. Most numbers of baskets (n) over a time interval (ΔT) follow a Poisson distribution, but some (e.g., ΔT = 10 s, n > 3) behave as a Power Law. The Poisson distribution includes most baskets in any game, in most game situations, but in close games in the last minute, the numbers of events are distributed following a Power Law. The number of events can be adjusted by a mixture of two distributions. In close games, both teams try to maintain their advantage solely in order to reach the last minute: a completely different game. For this reason, we propose to use the Poisson model as a reference. The complex dynamics will emerge from the limits of this model.

A model of seismic coda arrivals to suppress spurious events.

NASA Astrophysics Data System (ADS)

Arora, N.; Russell, S.

2012-04-01

We describe a model of coda arrivals which has been added to NET-VISA (Network processing Vertically Integrated Seismic Analysis) our probabilistic generative model of seismic events, their transmission, and detection on a global seismic network. The scattered energy that follows a seismic phase arrival tends to deceive typical STA/LTA based arrival picking software into believing that a real seismic phase has been detected. These coda arrivals which tend to follow all seismic phases cause most network processing software including NET-VISA to believe that multiple events have taken place. It is not a simple matter of ignoring closely spaced arrivals since arrivals from multiple events can indeed overlap. The current practice in NET-VISA of pruning events within a small space-time neighborhood of a larger event works reasonably well, but it may mask real events produced in an after-shock sequence. Our new model allows any seismic arrival, even coda arrivals, to trigger a subsequent coda arrival. The probability of such a triggered arrival depends on the amplitude of the triggering arrival. Although real seismic phases are more likely to generate such coda arrivals. Real seismic phases also tend to generate coda arrivals with more strongly correlated parameters, for example azimuth and slowness. However, the SNR (Signal to Noise Ratio) of a coda arrival immediately following a phase arrival tends to be lower because of the nature of the SNR calculation. We have calibrated our model on historical statistics of such triggered arrivals and our inference accounts for them while searching for the best explanation of seismic events their association to the arrivals and the coda arrivals. We have tested our new model on one week of global seismic data spanning March 22, 2009 to March 29, 2009. Our model was trained on two and half months of data from April 5, 2009 to June 20, 2009. We use the LEB bulletin produced by the IDC (International Data Center) as the ground truth and computed the precision (percentage of reported events which are true) and recall (percentage of true events which are reported). The existing model has a precision of 32.2 and recall of 88.6 which changes to a precision of 50.7 and recall of 88.5 after pruning. The new model has a precision of 56.8 and recall of 86.9 without any pruning and the corresponding precision recall curve is dramatically improved. In contrast, the performance of the current automated bulletin at the IDC, SEL3, has a precision of 46.2 and recall of 69.7.

Normal forms for Poisson maps and symplectic groupoids around Poisson transversals

NASA Astrophysics Data System (ADS)

Frejlich, Pedro; Mărcuț, Ioan

2018-03-01

Poisson transversals are submanifolds in a Poisson manifold which intersect all symplectic leaves transversally and symplectically. In this communication, we prove a normal form theorem for Poisson maps around Poisson transversals. A Poisson map pulls a Poisson transversal back to a Poisson transversal, and our first main result states that simultaneous normal forms exist around such transversals, for which the Poisson map becomes transversally linear, and intertwines the normal form data of the transversals. Our second result concerns symplectic integrations. We prove that a neighborhood of a Poisson transversal is integrable exactly when the Poisson transversal itself is integrable, and in that case we prove a normal form theorem for the symplectic groupoid around its restriction to the Poisson transversal, which puts all structure maps in normal form. We conclude by illustrating our results with examples arising from Lie algebras.

Normal forms for Poisson maps and symplectic groupoids around Poisson transversals.

PubMed

Frejlich, Pedro; Mărcuț, Ioan

2018-01-01

Poisson transversals are submanifolds in a Poisson manifold which intersect all symplectic leaves transversally and symplectically. In this communication, we prove a normal form theorem for Poisson maps around Poisson transversals. A Poisson map pulls a Poisson transversal back to a Poisson transversal, and our first main result states that simultaneous normal forms exist around such transversals, for which the Poisson map becomes transversally linear, and intertwines the normal form data of the transversals. Our second result concerns symplectic integrations. We prove that a neighborhood of a Poisson transversal is integrable exactly when the Poisson transversal itself is integrable, and in that case we prove a normal form theorem for the symplectic groupoid around its restriction to the Poisson transversal, which puts all structure maps in normal form. We conclude by illustrating our results with examples arising from Lie algebras.

A Gibbs point field model for the spatial pattern of coronary capillaries

NASA Astrophysics Data System (ADS)

Karch, R.; Neumann, M.; Neumann, F.; Ullrich, R.; Neumüller, J.; Schreiner, W.

2006-09-01

We propose a Gibbs point field model for the pattern of coronary capillaries in transverse histologic sections from human hearts, based on the physiology of oxygen supply from capillaries to tissue. To specify the potential energy function of the Gibbs point field, we draw on an analogy between the equation of steady-state oxygen diffusion from an array of parallel capillaries to the surrounding tissue and Poisson's equation for the electrostatic potential of a two-dimensional distribution of identical point charges. The influence of factors other than diffusion is treated as a thermal disturbance. On this basis, we arrive at the well-known two-dimensional one-component plasma, a system of identical point charges exhibiting a weak (logarithmic) repulsive interaction that is completely characterized by a single dimensionless parameter. By variation of this parameter, the model is able to reproduce many characteristics of real capillary patterns.

A Search for Short Timescale Microvariability in Active Galactic Nuclei in the Ultraviolet

NASA Technical Reports Server (NTRS)

Dolan, Joseph F.; Clark, L. Lee

2003-01-01

We observed four AGNs (the type-1 Seyfert systems 3C249.1, NGC 6814 and Mrk 205, and the BL Lac object 3C371) using the High Speed Photometer on the Hubble Space Telescope to search for short timescale microvariability in the W. Continuous observations of 3 0 0 0 s duration were obtained for each system on several consecutive HST orbits using a 1 s sample time in a 1400 - 3000 2 bandpass. variability > 0.3 % (0 . 003 mag) was detected in any AGN on timescales shorter than 1500 s. The distribution of photon arrival times observed from each source was consistent with Poisson statistics. Because of HST optical problems, the limit on photometric variability at longer timescales is less precise. These results restrict models of supermassive black holes as the central engine of an AGN and the diskoseismology oscillations of any accretion disk around such a black hole.

The fully actuated traffic control problem solved by global optimization and complementarity

NASA Astrophysics Data System (ADS)

Ribeiro, Isabel M.; de Lurdes de Oliveira Simões, Maria

2016-02-01

Global optimization and complementarity are used to determine the signal timing for fully actuated traffic control, regarding effective green and red times on each cycle. The average values of these parameters can be used to estimate the control delay of vehicles. In this article, a two-phase queuing system for a signalized intersection is outlined, based on the principle of minimization of the total waiting time for the vehicles. The underlying model results in a linear program with linear complementarity constraints, solved by a sequential complementarity algorithm. Departure rates of vehicles during green and yellow periods were treated as deterministic, while arrival rates of vehicles were assumed to follow a Poisson distribution. Several traffic scenarios were created and solved. The numerical results reveal that it is possible to use global optimization and complementarity over a reasonable number of cycles and determine with efficiency effective green and red times for a signalized intersection.

An implicit solution of the three-dimensional Navier-Stokes equations for an airfoil spanning a wind tunnel. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Moitra, A.

1982-01-01

An implicit finite-difference algorithm is developed for the numerical solution of the incompressible three dimensional Navier-Stokes equations in the non-conservative primitive-variable formulation. The flow field about an airfoil spanning a wind-tunnel is computed. The coordinate system is generated by an extension of the two dimensional body-fitted coordinate generation techniques of Thompson, as well as that of Sorenson, into three dimensions. Two dimensional grids are stacked along a spanwise coordinate defined by a simple analytical function. A Poisson pressure equation for advancing the pressure in time is arrived at by performing a divergence operation on the momentum equations. The pressure at each time-step is calculated on the assumption that continuity be unconditionally satisfied. An eddy viscosity coefficient, computed according to the algebraic turbulence formulation of Baldwin and Lomax, simulates the effects of turbulence.

Optimal pricing policies for services with consideration of facility maintenance costs

NASA Astrophysics Data System (ADS)

Yeh, Ruey Huei; Lin, Yi-Fang

2012-06-01

For survival and success, pricing is an essential issue for service firms. This article deals with the pricing strategies for services with substantial facility maintenance costs. For this purpose, a mathematical framework that incorporates service demand and facility deterioration is proposed to address the problem. The facility and customers constitute a service system driven by Poisson arrivals and exponential service times. A service demand with increasing price elasticity and a facility lifetime with strictly increasing failure rate are also adopted in modelling. By examining the bidirectional relationship between customer demand and facility deterioration in the profit model, the pricing policies of the service are investigated. Then analytical conditions of customer demand and facility lifetime are derived to achieve a unique optimal pricing policy. The comparative statics properties of the optimal policy are also explored. Finally, numerical examples are presented to illustrate the effects of parameter variations on the optimal pricing policy.

The queueing perspective of asynchronous network coding in two-way relay network

NASA Astrophysics Data System (ADS)

Liang, Yaping; Chang, Qing; Li, Xianxu

2018-04-01

Asynchronous network coding (NC) has potential to improve the wireless network performance compared with a routing or the synchronous network coding. Recent researches concentrate on the optimization between throughput/energy consuming and delay with a couple of independent input flow. However, the implementation of NC requires a thorough investigation of its impact on relevant queueing systems where few work focuses on. Moreover, few works study the probability density function (pdf) in network coding scenario. In this paper, the scenario with two independent Poisson input flows and one output flow is considered. The asynchronous NC-based strategy is that a new arrival evicts a head packet holding in its queue when waiting for another packet from the other flow to encode. The pdf for the output flow which contains both coded and uncoded packets is derived. Besides, the statistic characteristics of this strategy are analyzed. These results are verified by numerical simulations.

Optimal execution in high-frequency trading with Bayesian learning

NASA Astrophysics Data System (ADS)

Du, Bian; Zhu, Hongliang; Zhao, Jingdong

2016-11-01

We consider optimal trading strategies in which traders submit bid and ask quotes to maximize the expected quadratic utility of total terminal wealth in a limit order book. The trader's bid and ask quotes will be changed by the Poisson arrival of market orders. Meanwhile, the trader may update his estimate of other traders' target sizes and directions by Bayesian learning. The solution of optimal execution in the limit order book is a two-step procedure. First, we model an inactive trading with no limit order in the market. The dealer simply holds dollars and shares of stocks until terminal time. Second, he calibrates his bid and ask quotes to the limit order book. The optimal solutions are given by dynamic programming and in fact they are globally optimal. We also give numerical simulation to the value function and optimal quotes at the last part of the article.

Origin of translocation barriers for polyelectrolyte chains.

PubMed

Kumar, Rajeev; Muthukumar, M

2009-11-21

For single-file translocations of a charged macromolecule through a narrow pore, the crucial step of arrival of an end at the pore suffers from free energy barriers, arising from changes in intrachain electrostatic interaction, distribution of ionic clouds and solvent molecules, and conformational entropy of the chain. All contributing factors to the barrier in the initial stage of translocation are evaluated by using the self-consistent field theory for the polyelectrolyte and the coupled Poisson-Boltzmann description for ions without radial symmetry. The barrier is found to be essentially entropic due to conformational changes. For moderate and high salt concentrations, the barriers for the polyelectrolyte chain are quantitatively equivalent to that of uncharged self-avoiding walks. Electrostatic effects are shown to increase the free energy barriers, but only slightly. The degree of ionization, electrostatic interaction strength, decreasing salt concentration, and the solvent quality all result in increases in the barrier.

Zeroth Poisson Homology, Foliated Cohomology and Perfect Poisson Manifolds

NASA Astrophysics Data System (ADS)

Martínez-Torres, David; Miranda, Eva

2018-01-01

We prove that, for compact regular Poisson manifolds, the zeroth homology group is isomorphic to the top foliated cohomology group, and we give some applications. In particular, we show that, for regular unimodular Poisson manifolds, top Poisson and foliated cohomology groups are isomorphic. Inspired by the symplectic setting, we define what a perfect Poisson manifold is. We use these Poisson homology computations to provide families of perfect Poisson manifolds.

Compound Poisson Law for Hitting Times to Periodic Orbits in Two-Dimensional Hyperbolic Systems

NASA Astrophysics Data System (ADS)

Carney, Meagan; Nicol, Matthew; Zhang, Hong-Kun

2017-11-01

We show that a compound Poisson distribution holds for scaled exceedances of observables φ uniquely maximized at a periodic point ζ in a variety of two-dimensional hyperbolic dynamical systems with singularities (M,T,μ ), including the billiard maps of Sinai dispersing billiards in both the finite and infinite horizon case. The observable we consider is of form φ (z)=-ln d(z,ζ ) where d is a metric defined in terms of the stable and unstable foliation. The compound Poisson process we obtain is a Pólya-Aeppli distibution of index θ . We calculate θ in terms of the derivative of the map T. Furthermore if we define M_n=\\max {φ ,\\ldots ,φ circ T^n} and u_n (τ ) by \\lim _{n→ ∞} nμ (φ >u_n (τ ) )=τ the maximal process satisfies an extreme value law of form μ (M_n ≤ u_n)=e^{-θ τ }. These results generalize to a broader class of functions maximized at ζ , though the formulas regarding the parameters in the distribution need to be modified.

Overdispersion of the Molecular Clock: Temporal Variation of Gene-Specific Substitution Rates in Drosophila

PubMed Central

Hartl, Daniel L.

2008-01-01

Simple models of molecular evolution assume that sequences evolve by a Poisson process in which nucleotide or amino acid substitutions occur as rare independent events. In these models, the expected ratio of the variance to the mean of substitution counts equals 1, and substitution processes with a ratio greater than 1 are called overdispersed. Comparing the genomes of 10 closely related species of Drosophila, we extend earlier evidence for overdispersion in amino acid replacements as well as in four-fold synonymous substitutions. The observed deviation from the Poisson expectation can be described as a linear function of the rate at which substitutions occur on a phylogeny, which implies that deviations from the Poisson expectation arise from gene-specific temporal variation in substitution rates. Amino acid sequences show greater temporal variation in substitution rates than do four-fold synonymous sequences. Our findings provide a general phenomenological framework for understanding overdispersion in the molecular clock. Also, the presence of substantial variation in gene-specific substitution rates has broad implications for work in phylogeny reconstruction and evolutionary rate estimation. PMID:18480070

Computation of solar perturbations with Poisson series

NASA Technical Reports Server (NTRS)

Broucke, R.

1974-01-01

Description of a project for computing first-order perturbations of natural or artificial satellites by integrating the equations of motion on a computer with automatic Poisson series expansions. A basic feature of the method of solution is that the classical variation-of-parameters formulation is used rather than rectangular coordinates. However, the variation-of-parameters formulation uses the three rectangular components of the disturbing force rather than the classical disturbing function, so that there is no problem in expanding the disturbing function in series. Another characteristic of the variation-of-parameters formulation employed is that six rather unusual variables are used in order to avoid singularities at the zero eccentricity and zero (or 90 deg) inclination. The integration process starts by assuming that all the orbit elements present on the right-hand sides of the equations of motion are constants. These right-hand sides are then simple Poisson series which can be obtained with the use of the Bessel expansions of the two-body problem in conjunction with certain interation methods. These Poisson series can then be integrated term by term, and a first-order solution is obtained.

Lindley frailty model for a class of compound Poisson processes

NASA Astrophysics Data System (ADS)

Kadilar, Gamze Özel; Ata, Nihal

2013-10-01

The Lindley distribution gain importance in survival analysis for the similarity of exponential distribution and allowance for the different shapes of hazard function. Frailty models provide an alternative to proportional hazards model where misspecified or omitted covariates are described by an unobservable random variable. Despite of the distribution of the frailty is generally assumed to be continuous, it is appropriate to consider discrete frailty distributions In some circumstances. In this paper, frailty models with discrete compound Poisson process for the Lindley distributed failure time are introduced. Survival functions are derived and maximum likelihood estimation procedures for the parameters are studied. Then, the fit of the models to the earthquake data set of Turkey are examined.

Application of spatial Poisson process models to air mass thunderstorm rainfall

NASA Technical Reports Server (NTRS)

Eagleson, P. S.; Fennessy, N. M.; Wang, Qinliang; Rodriguez-Iturbe, I.

1987-01-01

Eight years of summer storm rainfall observations from 93 stations in and around the 154 sq km Walnut Gulch catchment of the Agricultural Research Service, U.S. Department of Agriculture, in Arizona are processed to yield the total station depths of 428 storms. Statistical analysis of these random fields yields the first two moments, the spatial correlation and variance functions, and the spatial distribution of total rainfall for each storm. The absolute and relative worth of three Poisson models are evaluated by comparing their prediction of the spatial distribution of storm rainfall with observations from the second half of the sample. The effect of interstorm parameter variation is examined.

Coupling Poisson rectangular pulse and multiplicative microcanonical random cascade models to generate sub-daily precipitation timeseries

NASA Astrophysics Data System (ADS)

Pohle, Ina; Niebisch, Michael; Müller, Hannes; Schümberg, Sabine; Zha, Tingting; Maurer, Thomas; Hinz, Christoph

2018-07-01

To simulate the impacts of within-storm rainfall variabilities on fast hydrological processes, long precipitation time series with high temporal resolution are required. Due to limited availability of observed data such time series are typically obtained from stochastic models. However, most existing rainfall models are limited in their ability to conserve rainfall event statistics which are relevant for hydrological processes. Poisson rectangular pulse models are widely applied to generate long time series of alternating precipitation events durations and mean intensities as well as interstorm period durations. Multiplicative microcanonical random cascade (MRC) models are used to disaggregate precipitation time series from coarse to fine temporal resolution. To overcome the inconsistencies between the temporal structure of the Poisson rectangular pulse model and the MRC model, we developed a new coupling approach by introducing two modifications to the MRC model. These modifications comprise (a) a modified cascade model ("constrained cascade") which preserves the event durations generated by the Poisson rectangular model by constraining the first and last interval of a precipitation event to contain precipitation and (b) continuous sigmoid functions of the multiplicative weights to consider the scale-dependency in the disaggregation of precipitation events of different durations. The constrained cascade model was evaluated in its ability to disaggregate observed precipitation events in comparison to existing MRC models. For that, we used a 20-year record of hourly precipitation at six stations across Germany. The constrained cascade model showed a pronounced better agreement with the observed data in terms of both the temporal pattern of the precipitation time series (e.g. the dry and wet spell durations and autocorrelations) and event characteristics (e.g. intra-event intermittency and intensity fluctuation within events). The constrained cascade model also slightly outperformed the other MRC models with respect to the intensity-frequency relationship. To assess the performance of the coupled Poisson rectangular pulse and constrained cascade model, precipitation events were stochastically generated by the Poisson rectangular pulse model and then disaggregated by the constrained cascade model. We found that the coupled model performs satisfactorily in terms of the temporal pattern of the precipitation time series, event characteristics and the intensity-frequency relationship.

Robotic Refueling Mission-3 Arrival and Processing

NASA Image and Video Library

2018-05-08

NASA’s Robotic Refueling Mission 3 (RRM3) arrived at Kennedy Space Center’s Space Station Processing Facility on May 8. The fluid transfer module will demonstrate innovative methods to store, transfer and freeze standard cryogenic fluid in space. RRM3 is scheduled to launch to the International Space Station later this year.

Weak convergence to isotropic complex [Formula: see text] random measure.

PubMed

Wang, Jun; Li, Yunmeng; Sang, Liheng

2017-01-01

In this paper, we prove that an isotropic complex symmetric α -stable random measure ([Formula: see text]) can be approximated by a complex process constructed by integrals based on the Poisson process with random intensity.

Estimation of parameters in Shot-Noise-Driven Doubly Stochastic Poisson processes using the EM algorithm--modeling of pre- and postsynaptic spike trains.

PubMed

Mino, H

2007-01-01

To estimate the parameters, the impulse response (IR) functions of some linear time-invariant systems generating intensity processes, in Shot-Noise-Driven Doubly Stochastic Poisson Process (SND-DSPP) in which multivariate presynaptic spike trains and postsynaptic spike trains can be assumed to be modeled by the SND-DSPPs. An explicit formula for estimating the IR functions from observations of multivariate input processes of the linear systems and the corresponding counting process (output process) is derived utilizing the expectation maximization (EM) algorithm. The validity of the estimation formula was verified through Monte Carlo simulations in which two presynaptic spike trains and one postsynaptic spike train were assumed to be observable. The IR functions estimated on the basis of the proposed identification method were close to the true IR functions. The proposed method will play an important role in identifying the input-output relationship of pre- and postsynaptic neural spike trains in practical situations.

Theoretical and Experimental Investigations of Coincidences in Poisson Distributed Pulse Trains and Spectral Distortion Caused by Pulse Pileup.

NASA Astrophysics Data System (ADS)

Bristow, Quentin

1990-01-01

Part one of this two-part study is concerned with the multiple coincidences in pulse trains from X-ray and gamma radiation detectors which are the cause of pulse pileup. A sequence of pulses with inter-arrival times less than tau, the resolving time of the pulse-height analysis system used to acquire spectra, is called a multiple pulse string. Such strings can be classified on the basis of the number of pulses they contain, or the number of resolving times they cover. The occurrence rates of such strings are derived from theoretical considerations. Logic circuits were devised to make experimental measurements of multiple pulse string occurrence rates in the output from a NaI(Tl) scintillation detector over a wide range of count rates. Markov process theory was used to predict state transition rates in the logic circuits, enabling the experimental data to be checked rigorously for conformity with those predicted for a Poisson distribution. No fundamental discrepancies were observed. Part two of the study is concerned with a theoretical analysis of pulse pileup and the development of a discrete correction algorithm, based on the use of a function to simulate the coincidence spectrum produced by partial sums of pulses. Monte Carlo simulations, incorporating criteria for pulse pileup inherent in the operation of modern ADC's, were used to generate pileup spectra due to coincidences between two pulses, (1st order pileup) and three pulses (2nd order pileup), for different semi-Gaussian pulse shapes. Coincidences between pulses in a single channel produced a basic probability density function spectrum which can be regarded as an impulse response for a particular pulse shape. The use of a flat spectrum (identical count rates in all channels) in the simulations, and in a parallel theoretical analysis, showed the 1st order pileup distorted the spectrum to a linear ramp with a pileup tail. The correction algorithm was successfully applied to correct entire spectra for 1st and 2nd order pileup; both those generated by Monte Carlo simulations and in addition some real spectra acquired with a laboratory multichannel analysis system.

Determining the Uncertainty of X-Ray Absorption Measurements

PubMed Central

Wojcik, Gary S.

2004-01-01

X-ray absorption (or more properly, x-ray attenuation) techniques have been applied to study the moisture movement in and moisture content of materials like cement paste, mortar, and wood. An increase in the number of x-ray counts with time at a location in a specimen may indicate a decrease in moisture content. The uncertainty of measurements from an x-ray absorption system, which must be known to properly interpret the data, is often assumed to be the square root of the number of counts, as in a Poisson process. No detailed studies have heretofore been conducted to determine the uncertainty of x-ray absorption measurements or the effect of averaging data on the uncertainty. In this study, the Poisson estimate was found to adequately approximate normalized root mean square errors (a measure of uncertainty) of counts for point measurements and profile measurements of water specimens. The Poisson estimate, however, was not reliable in approximating the magnitude of the uncertainty when averaging data from paste and mortar specimens. Changes in uncertainty from differing averaging procedures were well-approximated by a Poisson process. The normalized root mean square errors decreased when the x-ray source intensity, integration time, collimator size, and number of scanning repetitions increased. Uncertainties in mean paste and mortar count profiles were kept below 2 % by averaging vertical profiles at horizontal spacings of 1 mm or larger with counts per point above 4000. Maximum normalized root mean square errors did not exceed 10 % in any of the tests conducted. PMID:27366627

A dictionary learning approach for Poisson image deblurring.

PubMed

Ma, Liyan; Moisan, Lionel; Yu, Jian; Zeng, Tieyong

2013-07-01

The restoration of images corrupted by blur and Poisson noise is a key issue in medical and biological image processing. While most existing methods are based on variational models, generally derived from a maximum a posteriori (MAP) formulation, recently sparse representations of images have shown to be efficient approaches for image recovery. Following this idea, we propose in this paper a model containing three terms: a patch-based sparse representation prior over a learned dictionary, the pixel-based total variation regularization term and a data-fidelity term capturing the statistics of Poisson noise. The resulting optimization problem can be solved by an alternating minimization technique combined with variable splitting. Extensive experimental results suggest that in terms of visual quality, peak signal-to-noise ratio value and the method noise, the proposed algorithm outperforms state-of-the-art methods.

Space-time-modulated stochastic processes

NASA Astrophysics Data System (ADS)

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.

Yes, the GIGP Really Does Work--And Is Workable!

ERIC Educational Resources Information Center

Burrell, Quentin L.; Fenton, Michael R.

1993-01-01

Discusses the generalized inverse Gaussian-Poisson (GIGP) process for informetric modeling. Negative binomial distribution is discussed, construction of the GIGP process is explained, zero-truncated GIGP is considered, and applications of the process with journals, library circulation statistics, and database index terms are described. (50…

Study of photon correlation techniques for processing of laser velocimeter signals

NASA Technical Reports Server (NTRS)

Mayo, W. T., Jr.

1977-01-01

The objective was to provide the theory and a system design for a new type of photon counting processor for low level dual scatter laser velocimeter (LV) signals which would be capable of both the first order measurements of mean flow and turbulence intensity and also the second order time statistics: cross correlation auto correlation, and related spectra. A general Poisson process model for low level LV signals and noise which is valid from the photon-resolved regime all the way to the limiting case of nonstationary Gaussian noise was used. Computer simulation algorithms and higher order statistical moment analysis of Poisson processes were derived and applied to the analysis of photon correlation techniques. A system design using a unique dual correlate and subtract frequency discriminator technique is postulated and analyzed. Expectation analysis indicates that the objective measurements are feasible.

Joint Cross Well and Single Well Seismic Studies at Lost Hills, California

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gritto, Roland; Daley, Thomas M.; Myer, Larry R.

2002-06-25

A series of time-lapse seismic cross well and single well experiments were conducted in a diatomite reservoir to monitor the injection of CO{sub 2} into a hydrofracture zone, based on P- and S-wave data. A high-frequency piezo-electric P-wave source and an orbital-vibrator S-wave source were used to generate waves that were recorded by hydrophones as well as three-component geophones. The injection well was located about 12 m from the source well. During the pre-injection phase water was injected into the hydrofrac-zone. The set of seismic experiments was repeated after a time interval of 7 months during which CO{sub 2} wasmore » injected into the hydrofractured zone. The questions to be answered ranged from the detectability of the geologic structure in the diatomic reservoir to the detectability of CO{sub 2} within the hydrofracture. Furthermore it was intended to determine which experiment (cross well or single well) is best suited to resolve these features. During the pre-injection experiment, the P-wave velocities exhibited relatively low values between 1700-1900 m/s, which decreased to 1600-1800 m/s during the post-injection phase (-5%). The analysis of the pre-injection S-wave data revealed slow S-wave velocities between 600-800 m/s, while the post-injection data revealed velocities between 500-700 m/s (-6%). These velocity estimates produced high Poisson ratios between 0.36 and 0.46 for this highly porous ({approx} 50%) material. Differencing post- and pre-injection data revealed an increase in Poisson ratio of up to 5%. Both, velocity and Poisson estimates indicate the dissolution of CO{sub 2} in the liquid phase of the reservoir accompanied by a pore-pressure increase. The single well data supported the findings of the cross well experiments. P- and S-wave velocities as well as Poisson ratios were comparable to the estimates of the cross well data. The cross well experiment did not detect the presence of the hydrofracture but appeared to be sensitive to overall changes in the reservoir and possibly the presence of a fault. In contrast, the single well reflection data revealed an arrival that could indicate the presence of the hydrofracture between the source and receiver wells, while it did not detect the presence of the fault, possibly due to out of plane reflections.« less

Inhomogeneous Poisson process rate function inference from dead-time limited observations.

PubMed

Verma, Gunjan; Drost, Robert J

2017-05-01

The estimation of an inhomogeneous Poisson process (IHPP) rate function from a set of process observations is an important problem arising in optical communications and a variety of other applications. However, because of practical limitations of detector technology, one is often only able to observe a corrupted version of the original process. In this paper, we consider how inference of the rate function is affected by dead time, a period of time after the detection of an event during which a sensor is insensitive to subsequent IHPP events. We propose a flexible nonparametric Bayesian approach to infer an IHPP rate function given dead-time limited process realizations. Simulation results illustrate the effectiveness of our inference approach and suggest its ability to extend the utility of existing sensor technology by permitting more accurate inference on signals whose observations are dead-time limited. We apply our inference algorithm to experimentally collected optical communications data, demonstrating the practical utility of our approach in the context of channel modeling and validation.

Serial Spike Time Correlations Affect Probability Distribution of Joint Spike Events.

PubMed

Shahi, Mina; van Vreeswijk, Carl; Pipa, Gordon

2016-01-01

Detecting the existence of temporally coordinated spiking activity, and its role in information processing in the cortex, has remained a major challenge for neuroscience research. Different methods and approaches have been suggested to test whether the observed synchronized events are significantly different from those expected by chance. To analyze the simultaneous spike trains for precise spike correlation, these methods typically model the spike trains as a Poisson process implying that the generation of each spike is independent of all the other spikes. However, studies have shown that neural spike trains exhibit dependence among spike sequences, such as the absolute and relative refractory periods which govern the spike probability of the oncoming action potential based on the time of the last spike, or the bursting behavior, which is characterized by short epochs of rapid action potentials, followed by longer episodes of silence. Here we investigate non-renewal processes with the inter-spike interval distribution model that incorporates spike-history dependence of individual neurons. For that, we use the Monte Carlo method to estimate the full shape of the coincidence count distribution and to generate false positives for coincidence detection. The results show that compared to the distributions based on homogeneous Poisson processes, and also non-Poisson processes, the width of the distribution of joint spike events changes. Non-renewal processes can lead to both heavy tailed or narrow coincidence distribution. We conclude that small differences in the exact autostructure of the point process can cause large differences in the width of a coincidence distribution. Therefore, manipulations of the autostructure for the estimation of significance of joint spike events seem to be inadequate.

Serial Spike Time Correlations Affect Probability Distribution of Joint Spike Events

PubMed Central

Shahi, Mina; van Vreeswijk, Carl; Pipa, Gordon

2016-01-01

Detecting the existence of temporally coordinated spiking activity, and its role in information processing in the cortex, has remained a major challenge for neuroscience research. Different methods and approaches have been suggested to test whether the observed synchronized events are significantly different from those expected by chance. To analyze the simultaneous spike trains for precise spike correlation, these methods typically model the spike trains as a Poisson process implying that the generation of each spike is independent of all the other spikes. However, studies have shown that neural spike trains exhibit dependence among spike sequences, such as the absolute and relative refractory periods which govern the spike probability of the oncoming action potential based on the time of the last spike, or the bursting behavior, which is characterized by short epochs of rapid action potentials, followed by longer episodes of silence. Here we investigate non-renewal processes with the inter-spike interval distribution model that incorporates spike-history dependence of individual neurons. For that, we use the Monte Carlo method to estimate the full shape of the coincidence count distribution and to generate false positives for coincidence detection. The results show that compared to the distributions based on homogeneous Poisson processes, and also non-Poisson processes, the width of the distribution of joint spike events changes. Non-renewal processes can lead to both heavy tailed or narrow coincidence distribution. We conclude that small differences in the exact autostructure of the point process can cause large differences in the width of a coincidence distribution. Therefore, manipulations of the autostructure for the estimation of significance of joint spike events seem to be inadequate. PMID:28066225

FIND: difFerential chromatin INteractions Detection using a spatial Poisson process

PubMed Central

Chen, Yang; Zhang, Michael Q.

2018-01-01

Polymer-based simulations and experimental studies indicate the existence of a spatial dependency between the adjacent DNA fibers involved in the formation of chromatin loops. However, the existing strategies for detecting differential chromatin interactions assume that the interacting segments are spatially independent from the other segments nearby. To resolve this issue, we developed a new computational method, FIND, which considers the local spatial dependency between interacting loci. FIND uses a spatial Poisson process to detect differential chromatin interactions that show a significant difference in their interaction frequency and the interaction frequency of their neighbors. Simulation and biological data analysis show that FIND outperforms the widely used count-based methods and has a better signal-to-noise ratio. PMID:29440282

Oscillatory Reduction in Option Pricing Formula Using Shifted Poisson and Linear Approximation

NASA Astrophysics Data System (ADS)

Nur Rachmawati, Ro'fah; Irene; Budiharto, Widodo

2014-03-01

Option is one of derivative instruments that can help investors improve their expected return and minimize the risks. However, the Black-Scholes formula is generally used in determining the price of the option does not involve skewness factor and it is difficult to apply in computing process because it produces oscillation for the skewness values close to zero. In this paper, we construct option pricing formula that involve skewness by modified Black-Scholes formula using Shifted Poisson model and transformed it into the form of a Linear Approximation in the complete market to reduce the oscillation. The results are Linear Approximation formula can predict the price of an option with very accurate and successfully reduce the oscillations in the calculation processes.

Replication of Cancellation Orders Using First-Passage Time Theory in Foreign Currency Market

NASA Astrophysics Data System (ADS)

Boilard, Jean-François; Kanazawa, Kiyoshi; Takayasu, Hideki; Takayasu, Misako

Our research focuses on the annihilation dynamics of limit orders in a spot foreign currency market for various currency pairs. We analyze the cancellation order distribution conditioned on the normalized distance from the mid-price; where the normalized distance is defined as the final distance divided by the initial distance. To reproduce real data, we introduce two simple models that assume the market price moves randomly and cancellation occurs either after fixed time t or following the Poisson process. Results of our model qualitatively reproduce basic statistical properties of cancellation orders of the data when limit orders are cancelled according to the Poisson process. We briefly discuss implication of our findings in the construction of more detailed microscopic models.

Advanced Models and Algorithms for Self-Similar IP Network Traffic Simulation and Performance Analysis

NASA Astrophysics Data System (ADS)

Radev, Dimitar; Lokshina, Izabella

2010-11-01

The paper examines self-similar (or fractal) properties of real communication network traffic data over a wide range of time scales. These self-similar properties are very different from the properties of traditional models based on Poisson and Markov-modulated Poisson processes. Advanced fractal models of sequentional generators and fixed-length sequence generators, and efficient algorithms that are used to simulate self-similar behavior of IP network traffic data are developed and applied. Numerical examples are provided; and simulation results are obtained and analyzed.

Quasi-neutral limit of Euler–Poisson system of compressible fluids coupled to a magnetic field

NASA Astrophysics Data System (ADS)

Yang, Jianwei

2018-06-01

In this paper, we consider the quasi-neutral limit of a three-dimensional Euler-Poisson system of compressible fluids coupled to a magnetic field. We prove that, as Debye length tends to zero, periodic initial-value problems of the model have unique smooth solutions existing in the time interval where the ideal incompressible magnetohydrodynamic equations has smooth solution. Meanwhile, it is proved that smooth solutions converge to solutions of incompressible magnetohydrodynamic equations with a sharp convergence rate in the process of quasi-neutral limit.

Effect of non-Poisson samples on turbulence spectra from laser velocimetry

NASA Technical Reports Server (NTRS)

Sree, Dave; Kjelgaard, Scott O.; Sellers, William L., III

1994-01-01

Spectral analysis of laser velocimetry (LV) data plays an important role in characterizing a turbulent flow and in estimating the associated turbulence scales, which can be helpful in validating theoretical and numerical turbulence models. The determination of turbulence scales is critically dependent on the accuracy of the spectral estimates. Spectral estimations from 'individual realization' laser velocimetry data are typically based on the assumption of a Poisson sampling process. What this Note has demonstrated is that the sampling distribution must be considered before spectral estimates are used to infer turbulence scales.

Fission meter and neutron detection using poisson distribution comparison

DOEpatents

Rowland, Mark S; Snyderman, Neal J

2014-11-18

A neutron detector system and method for discriminating fissile material from non-fissile material wherein a digital data acquisition unit collects data at high rate, and in real-time processes large volumes of data directly into information that a first responder can use to discriminate materials. The system comprises counting neutrons from the unknown source and detecting excess grouped neutrons to identify fission in the unknown source. Comparison of the observed neutron count distribution with a Poisson distribution is performed to distinguish fissile material from non-fissile material.

First seismic shear wave velocity profile of the lunar crust as extracted from the Apollo 17 active seismic data by wavefield gradient analysis

NASA Astrophysics Data System (ADS)

Sollberger, David; Schmelzbach, Cedric; Robertsson, Johan O. A.; Greenhalgh, Stewart A.; Nakamura, Yosio; Khan, Amir

2016-04-01

We present a new seismic velocity model of the shallow lunar crust, including, for the first time, shear wave velocity information. So far, the shear wave velocity structure of the lunar near-surface was effectively unconstrained due to the complexity of lunar seismograms. Intense scattering and low attenuation in the lunar crust lead to characteristic long-duration reverberations on the seismograms. The reverberations obscure later arriving shear waves and mode conversions, rendering them impossible to identify and analyze. Additionally, only vertical component data were recorded during the Apollo active seismic experiments, which further compromises the identification of shear waves. We applied a novel processing and analysis technique to the data of the Apollo 17 lunar seismic profiling experiment (LSPE), which involved recording seismic energy generated by several explosive packages on a small areal array of four vertical component geophones. Our approach is based on the analysis of the spatial gradients of the seismic wavefield and yields key parameters such as apparent phase velocity and rotational ground motion as a function of time (depth), which cannot be obtained through conventional seismic data analysis. These new observables significantly enhance the data for interpretation of the recorded seismic wavefield and allow, for example, for the identification of S wave arrivals based on their lower apparent phase velocities and distinct higher amount of generated rotational motion relative to compressional (P-) waves. Using our methodology, we successfully identified pure-mode and mode-converted refracted shear wave arrivals in the complex LSPE data and derived a P- and S-wave velocity model of the shallow lunar crust at the Apollo 17 landing site. The extracted elastic-parameter model supports the current understanding of the lunar near-surface structure, suggesting a thin layer of low-velocity lunar regolith overlying a heavily fractured crust of basaltic material showing high (>0.4 down to 60 m) Poisson's ratios. Our new model can be used in future studies to better constrain the deep interior of the Moon. Given the rich information derived from the minimalistic recording configuration, our results demonstrate that wavefield gradient analysis should be critically considered for future space missions that aim to explore the interior structure of extraterrestrial objects by seismic methods. Additionally, we anticipate that the proposed shear wave identification methodology can also be applied to the routinely recorded vertical component data from land seismic exploration on Earth.

Parker Solar Probe Arrival, Offload, and Transport to Astrotech

NASA Image and Video Library

2018-04-03

NASA's Parker Solar Probe arrives for launch processing at the agency's Kennedy Space Center. The mission will revolutionize our understanding of the sun, where changing conditions can propegate out into the solar system.

Method for resonant measurement

DOEpatents

Rhodes, G.W.; Migliori, A.; Dixon, R.D.

1996-03-05

A method of measurement of objects to determine object flaws, Poisson`s ratio ({sigma}) and shear modulus ({mu}) is shown and described. First, the frequency for expected degenerate responses is determined for one or more input frequencies and then splitting of degenerate resonant modes are observed to identify the presence of flaws in the object. Poisson`s ratio and the shear modulus can be determined by identification of resonances dependent only on the shear modulus, and then using that shear modulus to find Poisson`s ratio using other modes dependent on both the shear modulus and Poisson`s ratio. 1 fig.

Process improvement to enhance existing stroke team activity toward more timely thrombolytic treatment.

PubMed

Cho, Han-Jin; Lee, Kyung Yul; Nam, Hyo Suk; Kim, Young Dae; Song, Tae-Jin; Jung, Yo Han; Choi, Hye-Yeon; Heo, Ji Hoe

2014-10-01

Process improvement (PI) is an approach for enhancing the existing quality improvement process by making changes while keeping the existing process. We have shown that implementation of a stroke code program using a computerized physician order entry system is effective in reducing the in-hospital time delay to thrombolysis in acute stroke patients. We investigated whether implementation of this PI could further reduce the time delays by continuous improvement of the existing process. After determining a key indicator [time interval from emergency department (ED) arrival to intravenous (IV) thrombolysis] and conducting data analysis, the target time from ED arrival to IV thrombolysis in acute stroke patients was set at 40 min. The key indicator was monitored continuously at a weekly stroke conference. The possible reasons for the delay were determined in cases for which IV thrombolysis was not administered within the target time and, where possible, the problems were corrected. The time intervals from ED arrival to the various evaluation steps and treatment before and after implementation of the PI were compared. The median time interval from ED arrival to IV thrombolysis in acute stroke patients was significantly reduced after implementation of the PI (from 63.5 to 45 min, p=0.001). The variation in the time interval was also reduced. A reduction in the evaluation time intervals was achieved after the PI [from 23 to 17 min for computed tomography scanning (p=0.003) and from 35 to 29 min for complete blood counts (p=0.006)]. PI is effective for continuous improvement of the existing process by reducing the time delays between ED arrival and IV thrombolysis in acute stroke patients.

Formulation of the Multi-Hit Model With a Non-Poisson Distribution of Hits

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vassiliev, Oleg N., E-mail: Oleg.Vassiliev@albertahealthservices.ca

2012-07-15

Purpose: We proposed a formulation of the multi-hit single-target model in which the Poisson distribution of hits was replaced by a combination of two distributions: one for the number of particles entering the target and one for the number of hits a particle entering the target produces. Such an approach reflects the fact that radiation damage is a result of two different random processes: particle emission by a radiation source and interaction of particles with matter inside the target. Methods and Materials: Poisson distribution is well justified for the first of the two processes. The second distribution depends on howmore » a hit is defined. To test our approach, we assumed that the second distribution was also a Poisson distribution. The two distributions combined resulted in a non-Poisson distribution. We tested the proposed model by comparing it with previously reported data for DNA single- and double-strand breaks induced by protons and electrons, for survival of a range of cell lines, and variation of the initial slopes of survival curves with radiation quality for heavy-ion beams. Results: Analysis of cell survival equations for this new model showed that they had realistic properties overall, such as the initial and high-dose slopes of survival curves, the shoulder, and relative biological effectiveness (RBE) In most cases tested, a better fit of survival curves was achieved with the new model than with the linear-quadratic model. The results also suggested that the proposed approach may extend the multi-hit model beyond its traditional role in analysis of survival curves to predicting effects of radiation quality and analysis of DNA strand breaks. Conclusions: Our model, although conceptually simple, performed well in all tests. The model was able to consistently fit data for both cell survival and DNA single- and double-strand breaks. It correctly predicted the dependence of radiation effects on parameters of radiation quality.« less

Including long-range dependence in integrate-and-fire models of the high interspike-interval variability of cortical neurons.

PubMed

Jackson, B Scott

2004-10-01

Many different types of integrate-and-fire models have been designed in order to explain how it is possible for a cortical neuron to integrate over many independent inputs while still producing highly variable spike trains. Within this context, the variability of spike trains has been almost exclusively measured using the coefficient of variation of interspike intervals. However, another important statistical property that has been found in cortical spike trains and is closely associated with their high firing variability is long-range dependence. We investigate the conditions, if any, under which such models produce output spike trains with both interspike-interval variability and long-range dependence similar to those that have previously been measured from actual cortical neurons. We first show analytically that a large class of high-variability integrate-and-fire models is incapable of producing such outputs based on the fact that their output spike trains are always mathematically equivalent to renewal processes. This class of models subsumes a majority of previously published models, including those that use excitation-inhibition balance, correlated inputs, partial reset, or nonlinear leakage to produce outputs with high variability. Next, we study integrate-and-fire models that have (nonPoissonian) renewal point process inputs instead of the Poisson point process inputs used in the preceding class of models. The confluence of our analytical and simulation results implies that the renewal-input model is capable of producing high variability and long-range dependence comparable to that seen in spike trains recorded from cortical neurons, but only if the interspike intervals of the inputs have infinite variance, a physiologically unrealistic condition. Finally, we suggest a new integrate-and-fire model that does not suffer any of the previously mentioned shortcomings. By analyzing simulation results for this model, we show that it is capable of producing output spike trains with interspike-interval variability and long-range dependence that match empirical data from cortical spike trains. This model is similar to the other models in this study, except that its inputs are fractional-gaussian-noise-driven Poisson processes rather than renewal point processes. In addition to this model's success in producing realistic output spike trains, its inputs have long-range dependence similar to that found in most subcortical neurons in sensory pathways, including the inputs to cortex. Analysis of output spike trains from simulations of this model also shows that a tight balance between the amounts of excitation and inhibition at the inputs to cortical neurons is not necessary for high interspike-interval variability at their outputs. Furthermore, in our analysis of this model, we show that the superposition of many fractional-gaussian-noise-driven Poisson processes does not approximate a Poisson process, which challenges the common assumption that the total effect of a large number of inputs on a neuron is well represented by a Poisson process.

A Random Variable Transformation Process.

ERIC Educational Resources Information Center

Scheuermann, Larry

1989-01-01

Provides a short BASIC program, RANVAR, which generates random variates for various theoretical probability distributions. The seven variates include: uniform, exponential, normal, binomial, Poisson, Pascal, and triangular. (MVL)

Calculating shock arrival in expansion tubes and shock tunnels using Bayesian changepoint analysis

NASA Astrophysics Data System (ADS)

James, Christopher M.; Bourke, Emily J.; Gildfind, David E.

2018-06-01

To understand the flow conditions generated in expansion tubes and shock tunnels, shock speeds are generally calculated based on shock arrival times at high-frequency wall-mounted pressure transducers. These calculations require that the shock arrival times are obtained accurately. This can be non-trivial for expansion tubes especially because pressure rises may be small and shock speeds high. Inaccurate shock arrival times can be a significant source of uncertainty. To help address this problem, this paper investigates two separate but complimentary techniques. Principally, it proposes using a Bayesian changepoint detection method to automatically calculate shock arrival, potentially reducing error and simplifying the shock arrival finding process. To compliment this, a technique for filtering the raw data without losing the shock arrival time is also presented and investigated. To test the validity of the proposed techniques, tests are performed using both a theoretical step change with different levels of noise and real experimental data. It was found that with conditions added to ensure that a real shock arrival time was found, the Bayesian changepoint analysis method was able to automatically find the shock arrival time, even for noisy signals.

Seismicity, faulting, and structure of the Koyna-Warna seismic region, Western India from local earthquake tomography and hypocenter locations

NASA Astrophysics Data System (ADS)

Dixit, Madan M.; Kumar, Sanjay; Catchings, R. D.; Suman, K.; Sarkar, Dipankar; Sen, M. K.

2014-08-01

Although seismicity near Koyna Reservoir (India) has persisted for ~50 years and includes the largest induced earthquake (M 6.3) reported worldwide, the seismotectonic framework of the area is not well understood. We recorded ~1800 earthquakes from 6 January 2010 to 28 May 2010 and located a subset of 343 of the highest-quality earthquakes using the tomoDD code of Zhang and Thurber (2003) to better understand the framework. We also inverted first arrivals for 3-D Vp, Vs, and Vp/Vs and Poisson's ratio tomography models of the upper 12 km of the crust. Epicenters for the recorded earthquakes are located south of the Koyna River, including a high-density cluster that coincides with a shallow depth (<1.5 km) zone of relatively high Vp and low Vs (also high Vp/Vs and Poisson's ratios) near Warna Reservoir. This anomalous zone, which extends near vertically to at least 8 km depth and laterally northward at least 15 km, is likely a water-saturated zone of faults under high pore pressures. Because many of the earthquakes occur on the periphery of the fault zone, rather than near its center, the observed seismicity-velocity correlations are consistent with the concept that many of the earthquakes nucleate in fractures adjacent to the main fault zone due to high pore pressure. We interpret our velocity images as showing a series of northwest trending faults locally near the central part of Warna Reservoir and a major northward trending fault zone north of Warna Reservoir.

Lognormal Distribution of Cellular Uptake of Radioactivity: Statistical Analysis of α-Particle Track Autoradiography

PubMed Central

Neti, Prasad V.S.V.; Howell, Roger W.

2010-01-01

Recently, the distribution of radioactivity among a population of cells labeled with 210Po was shown to be well described by a log-normal (LN) distribution function (J Nucl Med. 2006;47:1049–1058) with the aid of autoradiography. To ascertain the influence of Poisson statistics on the interpretation of the autoradiographic data, the present work reports on a detailed statistical analysis of these earlier data. Methods The measured distributions of α-particle tracks per cell were subjected to statistical tests with Poisson, LN, and Poisson-lognormal (P-LN) models. Results The LN distribution function best describes the distribution of radioactivity among cell populations exposed to 0.52 and 3.8 kBq/mL of 210Po-citrate. When cells were exposed to 67 kBq/mL, the P-LN distribution function gave a better fit; however, the underlying activity distribution remained log-normal. Conclusion The present analysis generally provides further support for the use of LN distributions to describe the cellular uptake of radioactivity. Care should be exercised when analyzing autoradiographic data on activity distributions to ensure that Poisson processes do not distort the underlying LN distribution. PMID:18483086

Log Normal Distribution of Cellular Uptake of Radioactivity: Statistical Analysis of Alpha Particle Track Autoradiography

PubMed Central

Neti, Prasad V.S.V.; Howell, Roger W.

2008-01-01

Recently, the distribution of radioactivity among a population of cells labeled with 210Po was shown to be well described by a log normal distribution function (J Nucl Med 47, 6 (2006) 1049-1058) with the aid of an autoradiographic approach. To ascertain the influence of Poisson statistics on the interpretation of the autoradiographic data, the present work reports on a detailed statistical analyses of these data. Methods The measured distributions of alpha particle tracks per cell were subjected to statistical tests with Poisson (P), log normal (LN), and Poisson – log normal (P – LN) models. Results The LN distribution function best describes the distribution of radioactivity among cell populations exposed to 0.52 and 3.8 kBq/mL 210Po-citrate. When cells were exposed to 67 kBq/mL, the P – LN distribution function gave a better fit, however, the underlying activity distribution remained log normal. Conclusions The present analysis generally provides further support for the use of LN distributions to describe the cellular uptake of radioactivity. Care should be exercised when analyzing autoradiographic data on activity distributions to ensure that Poisson processes do not distort the underlying LN distribution. PMID:16741316

Poisson-Gaussian Noise Reduction Using the Hidden Markov Model in Contourlet Domain for Fluorescence Microscopy Images

PubMed Central

Yang, Sejung; Lee, Byung-Uk

2015-01-01

In certain image acquisitions processes, like in fluorescence microscopy or astronomy, only a limited number of photons can be collected due to various physical constraints. The resulting images suffer from signal dependent noise, which can be modeled as a Poisson distribution, and a low signal-to-noise ratio. However, the majority of research on noise reduction algorithms focuses on signal independent Gaussian noise. In this paper, we model noise as a combination of Poisson and Gaussian probability distributions to construct a more accurate model and adopt the contourlet transform which provides a sparse representation of the directional components in images. We also apply hidden Markov models with a framework that neatly describes the spatial and interscale dependencies which are the properties of transformation coefficients of natural images. In this paper, an effective denoising algorithm for Poisson-Gaussian noise is proposed using the contourlet transform, hidden Markov models and noise estimation in the transform domain. We supplement the algorithm by cycle spinning and Wiener filtering for further improvements. We finally show experimental results with simulations and fluorescence microscopy images which demonstrate the improved performance of the proposed approach. PMID:26352138

Mapping species abundance by a spatial zero-inflated Poisson model: a case study in the Wadden Sea, the Netherlands.

PubMed

Lyashevska, Olga; Brus, Dick J; van der Meer, Jaap

2016-01-01

The objective of the study was to provide a general procedure for mapping species abundance when data are zero-inflated and spatially correlated counts. The bivalve species Macoma balthica was observed on a 500×500 m grid in the Dutch part of the Wadden Sea. In total, 66% of the 3451 counts were zeros. A zero-inflated Poisson mixture model was used to relate counts to environmental covariates. Two models were considered, one with relatively fewer covariates (model "small") than the other (model "large"). The models contained two processes: a Bernoulli (species prevalence) and a Poisson (species intensity, when the Bernoulli process predicts presence). The model was used to make predictions for sites where only environmental data are available. Predicted prevalences and intensities show that the model "small" predicts lower mean prevalence and higher mean intensity, than the model "large". Yet, the product of prevalence and intensity, which might be called the unconditional intensity, is very similar. Cross-validation showed that the model "small" performed slightly better, but the difference was small. The proposed methodology might be generally applicable, but is computer intensive.

Derivation of kinetic equations from non-Wiener stochastic differential equations

NASA Astrophysics Data System (ADS)

Basharov, A. M.

2013-12-01

Kinetic differential-difference equations containing terms with fractional derivatives and describing α -stable Levy processes with 0 < α < 1 have been derived in a unified manner in terms of one-dimensional stochastic differential equations controlled merely by the Poisson processes.

Sojourning with the Homogeneous Poisson Process.

PubMed

Liu, Piaomu; Peña, Edsel A

2016-01-01

In this pedagogical article, distributional properties, some surprising, pertaining to the homogeneous Poisson process (HPP), when observed over a possibly random window, are presented. Properties of the gap-time that covered the termination time and the correlations among gap-times of the observed events are obtained. Inference procedures, such as estimation and model validation, based on event occurrence data over the observation window, are also presented. We envision that through the results in this paper, a better appreciation of the subtleties involved in the modeling and analysis of recurrent events data will ensue, since the HPP is arguably one of the simplest among recurrent event models. In addition, the use of the theorem of total probability, Bayes theorem, the iterated rules of expectation, variance and covariance, and the renewal equation could be illustrative when teaching distribution theory, mathematical statistics, and stochastic processes at both the undergraduate and graduate levels. This article is targeted towards both instructors and students.

Poisson-Nernst-Planck Equations for Simulating Biomolecular Diffusion-Reaction Processes II: Size Effects on Ionic Distributions and Diffusion-Reaction Rates

PubMed Central

Lu, Benzhuo; Zhou, Y.C.

2011-01-01

The effects of finite particle size on electrostatics, density profiles, and diffusion have been a long existing topic in the study of ionic solution. The previous size-modified Poisson-Boltzmann and Poisson-Nernst-Planck models are revisited in this article. In contrast to many previous works that can only treat particle species with a single uniform size or two sizes, we generalize the Borukhov model to obtain a size-modified Poisson-Nernst-Planck (SMPNP) model that is able to treat nonuniform particle sizes. The numerical tractability of the model is demonstrated as well. The main contributions of this study are as follows. 1), We show that an (arbitrarily) size-modified PB model is indeed implied by the SMPNP equations under certain boundary/interface conditions, and can be reproduced through numerical solutions of the SMPNP. 2), The size effects in the SMPNP effectively reduce the densities of highly concentrated counterions around the biomolecule. 3), The SMPNP is applied to the diffusion-reaction process for the first time, to our knowledge. In the case of low substrate density near the enzyme reactive site, it is observed that the rate coefficients predicted by SMPNP model are considerably larger than those by the PNP model, suggesting both ions and substrates are subject to finite size effects. 4), An accurate finite element method and a convergent Gummel iteration are developed for the numerical solution of the completely coupled nonlinear system of SMPNP equations. PMID:21575582

Environmental heterogeneity blurs the signature of dispersal syndromes on spatial patterns of woody species in a moist tropical forest

PubMed Central

Velázquez, Eduardo; Escudero, Adrián; de la Cruz, Marcelino

2018-01-01

We assessed the relative importance of dispersal limitation, environmental heterogeneity and their joint effects as determinants of the spatial patterns of 229 species in the moist tropical forest of Barro Colorado Island (Panama). We differentiated five types of species according to their dispersal syndrome; autochorous, anemochorous, and zoochorous species with small, medium-size and large fruits. We characterized the spatial patterns of each species and we checked whether they were best fitted by Inhomogeneous Poisson (IPP), Homogeneous Poisson cluster (HPCP) and Inhomogeneous Poisson cluster processes (IPCP) by means of the Akaike Information Criterion. We also assessed the influence of species’ dispersal mode in the average cluster size. We found that 63% of the species were best fitted by IPCP regardless of their dispersal syndrome, although anemochorous species were best described by HPCP. Our results indicate that spatial patterns of tree species in this forest cannot be explained only by dispersal limitation, but by the joint effects of dispersal limitation and environmental heterogeneity. The absence of relationships between dispersal mode and degree of clustering suggests that several processes modify the original spatial pattern generated by seed dispersal. These findings emphasize the importance of fitting point process models with a different biological meaning when studying the main determinants of spatial structure in plant communities. PMID:29451871

Applying Flammability Limit Probabilities and the Normoxic Upward Limiting Pressure Concept to NASA STD-6001 Test 1

NASA Technical Reports Server (NTRS)

Olson, Sandra L.; Beeson, Harold; Fernandez-Pello, A. Carlos

2014-01-01

Repeated Test 1 extinction tests near the upward flammability limit are expected to follow a Poisson process trend. This Poisson process trend suggests that rather than define a ULOI and MOC (which requires two limits to be determined), it might be better to define a single upward limit as being where 1/e (where e (approx. equal to 2.7183) is the characteristic time of the normalized Poisson process) of the materials burn, or, rounding, where approximately 1/3 of the samples fail the test (and burn). Recognizing that spacecraft atmospheres will not bound the entire oxygen-pressure parameter space, but actually lie along the normoxic atmosphere control band, we can focus the materials flammability testing along this normoxic band. A Normoxic Upward Limiting Pressure (NULP) is defined that determines the minimum safe total pressure for a material within the constant partial pressure control band. Then, increasing this pressure limit by a factor of safety, we can define the material as being safe to use at the NULP + SF (where SF is on the order of 10 kilopascal, based on existing flammability data). It is recommended that the thickest material to be tested with the current Test 1 igniter should be 3 mm thick (1/8 inches) to avoid the problem of differentiating between an ignition limit and a true flammability limit.

Automatic pickup of arrival time of channel wave based on multi-channel constraints

NASA Astrophysics Data System (ADS)

Wang, Bao-Li

2018-03-01

Accurately detecting the arrival time of a channel wave in a coal seam is very important for in-seam seismic data processing. The arrival time greatly affects the accuracy of the channel wave inversion and the computed tomography (CT) result. However, because the signal-to-noise ratio of in-seam seismic data is reduced by the long wavelength and strong frequency dispersion, accurately timing the arrival of channel waves is extremely difficult. For this purpose, we propose a method that automatically picks up the arrival time of channel waves based on multi-channel constraints. We first estimate the Jaccard similarity coefficient of two ray paths, then apply it as a weight coefficient for stacking the multichannel dispersion spectra. The reasonableness and effectiveness of the proposed method is verified in an actual data application. Most importantly, the method increases the degree of automation and the pickup precision of the channel-wave arrival time.

KSC-03PD-1953

NASA Technical Reports Server (NTRS)

2003-01-01

KENNEDY SPACE CENTER, FLA. In the Space Station Processing Facility, Executive Director of NASDA Koji Yamamoto (left) looks at the newly arrived Japanese Experiment Module (JEM)/pressurized module. Mr. Yamamoto is at KSC for a welcome ceremony involving the arrival of JEM.

KSC-03PD-1952

NASA Technical Reports Server (NTRS)

2003-01-01

KENNEDY SPACE CENTER, FLA. In the Space Station Processing Facility, Executive Director of NASDA Koji Yamamoto (right) looks at the newly arrived Japanese Experiment Module (JEM)/pressurized module. Mr. Yamamoto is at KSC for a welcome ceremony involving the arrival of JEM.

77 FR 13691 - Qualification of Drivers; Exemption Applications; Vision

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-07

..., ocular hypertension, retinal detachment, cataracts and corneal scaring. In most cases, their eye... Application of Multiple Regression Analysis of a Poisson Process,'' Journal of American Statistical...

Internal Stress Distribution Measurement of TIG Welded SUS304 Samples Using Neutron Diffraction Technique

NASA Astrophysics Data System (ADS)

Muslih, M. Refai; Sumirat, I.; Sairun; Purwanta

2008-03-01

The distribution of residual stress of SUS304 samples that were undergone TIG welding process with four different electric currents has been measured. The welding has been done in the middle part of the samples that was previously grooved by milling machine. Before they were welded the samples were annealed at 650 degree Celsius for one hour. The annealing process was done to eliminate residual stress generated by grooving process so that the residual stress within the samples was merely produced from welding process. The calculation of distribution of residual stress was carried out by measuring the strains within crystal planes of Fe(220) SUS304. Strain, Young modulus, and Poisson ratio of Fe(220) SUS304 were measured using DN1-M neutron diffractometer. Young modulus and Poisson ratio of Fe(220) SUS304 sample were measured in-situ. The result of calculations showed that distribution of residual stress of SUS304 in the vicinity of welded area is influenced both by treatments given at the samples-making process and by the electric current used during welding process.

Analytically Solvable Model of Spreading Dynamics with Non-Poissonian Processes

NASA Astrophysics Data System (ADS)

Jo, Hang-Hyun; Perotti, Juan I.; Kaski, Kimmo; Kertész, János

2014-01-01

Non-Poissonian bursty processes are ubiquitous in natural and social phenomena, yet little is known about their effects on the large-scale spreading dynamics. In order to characterize these effects, we devise an analytically solvable model of susceptible-infected spreading dynamics in infinite systems for arbitrary inter-event time distributions and for the whole time range. Our model is stationary from the beginning, and the role of the lower bound of inter-event times is explicitly considered. The exact solution shows that for early and intermediate times, the burstiness accelerates the spreading as compared to a Poisson-like process with the same mean and same lower bound of inter-event times. Such behavior is opposite for late-time dynamics in finite systems, where the power-law distribution of inter-event times results in a slower and algebraic convergence to a fully infected state in contrast to the exponential decay of the Poisson-like process. We also provide an intuitive argument for the exponent characterizing algebraic convergence.

Video Coding and the Application Level Framing Protocol Architecture

DTIC Science & Technology

1992-06-01

missing ADU can be sent to the decoder when and if it arrives. The need for out-of- order processing arises for two reasons. First, ADUs may be reordered...by the network. Second, an ADU which is lost and then successfully retransmitted will arrive out of order. In either case, out-of- order processing makes...the code do not allow at least some out-of- order processing , one of the strong points of the ALF architecture is eliminated. 2.3.4 Header Data

FIND: difFerential chromatin INteractions Detection using a spatial Poisson process.

PubMed

Djekidel, Mohamed Nadhir; Chen, Yang; Zhang, Michael Q

2018-02-12

Polymer-based simulations and experimental studies indicate the existence of a spatial dependency between the adjacent DNA fibers involved in the formation of chromatin loops. However, the existing strategies for detecting differential chromatin interactions assume that the interacting segments are spatially independent from the other segments nearby. To resolve this issue, we developed a new computational method, FIND, which considers the local spatial dependency between interacting loci. FIND uses a spatial Poisson process to detect differential chromatin interactions that show a significant difference in their interaction frequency and the interaction frequency of their neighbors. Simulation and biological data analysis show that FIND outperforms the widely used count-based methods and has a better signal-to-noise ratio. © 2018 Djekidel et al.; Published by Cold Spring Harbor Laboratory Press.

Simulation of diffuse-charge capacitance in electric double layer capacitors

NASA Astrophysics Data System (ADS)

Sun, Ning; Gersappe, Dilip

2017-01-01

We use a Lattice Boltzmann Model (LBM) in order to simulate diffuse-charge dynamics in Electric Double Layer Capacitors (EDLCs). Simulations are carried out for both the charge and the discharge processes on 2D systems of complex random electrode geometries (pure random, random spheres and random fibers). The steric effect of concentrated solutions is considered by using a Modified Poisson-Nernst-Planck (MPNP) equations and compared with regular Poisson-Nernst-Planck (PNP) systems. The effects of electrode microstructures (electrode density, electrode filler morphology, filler size, etc.) on the net charge distribution and charge/discharge time are studied in detail. The influence of applied potential during discharging process is also discussed. Our studies show how electrode morphology can be used to tailor the properties of supercapacitors.

A stochastical event-based continuous time step rainfall generator based on Poisson rectangular pulse and microcanonical random cascade models

NASA Astrophysics Data System (ADS)

Pohle, Ina; Niebisch, Michael; Zha, Tingting; Schümberg, Sabine; Müller, Hannes; Maurer, Thomas; Hinz, Christoph

2017-04-01

Rainfall variability within a storm is of major importance for fast hydrological processes, e.g. surface runoff, erosion and solute dissipation from surface soils. To investigate and simulate the impacts of within-storm variabilities on these processes, long time series of rainfall with high resolution are required. Yet, observed precipitation records of hourly or higher resolution are in most cases available only for a small number of stations and only for a few years. To obtain long time series of alternating rainfall events and interstorm periods while conserving the statistics of observed rainfall events, the Poisson model can be used. Multiplicative microcanonical random cascades have been widely applied to disaggregate rainfall time series from coarse to fine temporal resolution. We present a new coupling approach of the Poisson rectangular pulse model and the multiplicative microcanonical random cascade model that preserves the characteristics of rainfall events as well as inter-storm periods. In the first step, a Poisson rectangular pulse model is applied to generate discrete rainfall events (duration and mean intensity) and inter-storm periods (duration). The rainfall events are subsequently disaggregated to high-resolution time series (user-specified, e.g. 10 min resolution) by a multiplicative microcanonical random cascade model. One of the challenges of coupling these models is to parameterize the cascade model for the event durations generated by the Poisson model. In fact, the cascade model is best suited to downscale rainfall data with constant time step such as daily precipitation data. Without starting from a fixed time step duration (e.g. daily), the disaggregation of events requires some modifications of the multiplicative microcanonical random cascade model proposed by Olsson (1998): Firstly, the parameterization of the cascade model for events of different durations requires continuous functions for the probabilities of the multiplicative weights, which we implemented through sigmoid functions. Secondly, the branching of the first and last box is constrained to preserve the rainfall event durations generated by the Poisson rectangular pulse model. The event-based continuous time step rainfall generator has been developed and tested using 10 min and hourly rainfall data of four stations in North-Eastern Germany. The model performs well in comparison to observed rainfall in terms of event durations and mean event intensities as well as wet spell and dry spell durations. It is currently being tested using data from other stations across Germany and in different climate zones. Furthermore, the rainfall event generator is being applied in modelling approaches aimed at understanding the impact of rainfall variability on hydrological processes. Reference Olsson, J.: Evaluation of a scaling cascade model for temporal rainfall disaggregation, Hydrology and Earth System Sciences, 2, 19.30

On a Poisson homogeneous space of bilinear forms with a Poisson-Lie action

NASA Astrophysics Data System (ADS)

Chekhov, L. O.; Mazzocco, M.

2017-12-01

Let \\mathscr A be the space of bilinear forms on C^N with defining matrices A endowed with a quadratic Poisson structure of reflection equation type. The paper begins with a short description of previous studies of the structure, and then this structure is extended to systems of bilinear forms whose dynamics is governed by the natural action A\\mapsto B ABT} of the {GL}_N Poisson-Lie group on \\mathscr A. A classification is given of all possible quadratic brackets on (B, A)\\in {GL}_N× \\mathscr A preserving the Poisson property of the action, thus endowing \\mathscr A with the structure of a Poisson homogeneous space. Besides the product Poisson structure on {GL}_N× \\mathscr A, there are two other (mutually dual) structures, which (unlike the product Poisson structure) admit reductions by the Dirac procedure to a space of bilinear forms with block upper triangular defining matrices. Further generalisations of this construction are considered, to triples (B,C, A)\\in {GL}_N× {GL}_N× \\mathscr A with the Poisson action A\\mapsto B ACT}, and it is shown that \\mathscr A then acquires the structure of a Poisson symmetric space. Generalisations to chains of transformations and to the quantum and quantum affine algebras are investigated, as well as the relations between constructions of Poisson symmetric spaces and the Poisson groupoid. Bibliography: 30 titles.

A multiscale filter for noise reduction of low-dose cone beam projections.

PubMed

Yao, Weiguang; Farr, Jonathan B

2015-08-21

The Poisson or compound Poisson process governs the randomness of photon fluence in cone beam computed tomography (CBCT) imaging systems. The probability density function depends on the mean (noiseless) of the fluence at a certain detector. This dependence indicates the natural requirement of multiscale filters to smooth noise while preserving structures of the imaged object on the low-dose cone beam projection. In this work, we used a Gaussian filter, exp(-x2/2σ(2)(f)) as the multiscale filter to de-noise the low-dose cone beam projections. We analytically obtained the expression of σ(f), which represents the scale of the filter, by minimizing local noise-to-signal ratio. We analytically derived the variance of residual noise from the Poisson or compound Poisson processes after Gaussian filtering. From the derived analytical form of the variance of residual noise, optimal σ(2)(f)) is proved to be proportional to the noiseless fluence and modulated by local structure strength expressed as the linear fitting error of the structure. A strategy was used to obtain the reliable linear fitting error: smoothing the projection along the longitudinal direction to calculate the linear fitting error along the lateral direction and vice versa. The performance of our multiscale filter was examined on low-dose cone beam projections of a Catphan phantom and a head-and-neck patient. After performing the filter on the Catphan phantom projections scanned with pulse time 4 ms, the number of visible line pairs was similar to that scanned with 16 ms, and the contrast-to-noise ratio of the inserts was higher than that scanned with 16 ms about 64% in average. For the simulated head-and-neck patient projections with pulse time 4 ms, the visibility of soft tissue structures in the patient was comparable to that scanned with 20 ms. The image processing took less than 0.5 s per projection with 1024   ×   768 pixels.

Poisson-event-based analysis of cell proliferation.

PubMed

Summers, Huw D; Wills, John W; Brown, M Rowan; Rees, Paul

2015-05-01

A protocol for the assessment of cell proliferation dynamics is presented. This is based on the measurement of cell division events and their subsequent analysis using Poisson probability statistics. Detailed analysis of proliferation dynamics in heterogeneous populations requires single cell resolution within a time series analysis and so is technically demanding to implement. Here, we show that by focusing on the events during which cells undergo division rather than directly on the cells themselves a simplified image acquisition and analysis protocol can be followed, which maintains single cell resolution and reports on the key metrics of cell proliferation. The technique is demonstrated using a microscope with 1.3 μm spatial resolution to track mitotic events within A549 and BEAS-2B cell lines, over a period of up to 48 h. Automated image processing of the bright field images using standard algorithms within the ImageJ software toolkit yielded 87% accurate recording of the manually identified, temporal, and spatial positions of the mitotic event series. Analysis of the statistics of the interevent times (i.e., times between observed mitoses in a field of view) showed that cell division conformed to a nonhomogeneous Poisson process in which the rate of occurrence of mitotic events, λ exponentially increased over time and provided values of the mean inter mitotic time of 21.1 ± 1.2 hours for the A549 cells and 25.0 ± 1.1 h for the BEAS-2B cells. Comparison of the mitotic event series for the BEAS-2B cell line to that predicted by random Poisson statistics indicated that temporal synchronisation of the cell division process was occurring within 70% of the population and that this could be increased to 85% through serum starvation of the cell culture. © 2015 International Society for Advancement of Cytometry.

Computing angle of arrival of radio signals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Borchardt, John J.; Steele, David K.

Various technologies pertaining to computing angle of arrival of radio signals are described. A system that is configured for computing the angle of arrival of a radio signal includes a cylindrical sheath wrapped around a cylindrical object, where the cylindrical sheath acts as a ground plane. The system further includes a plurality of antennas that are positioned about an exterior surface of the cylindrical sheath, and receivers respectively coupled to the antennas. The receivers output measurements pertaining to the radio signal. A processing circuit receives the measurements and computes the angle of arrival of the radio signal based upon themore » measurements.« less

Statistical properties of several models of fractional random point processes

NASA Astrophysics Data System (ADS)

Bendjaballah, C.

2011-08-01

Statistical properties of several models of fractional random point processes have been analyzed from the counting and time interval statistics points of view. Based on the criterion of the reduced variance, it is seen that such processes exhibit nonclassical properties. The conditions for these processes to be treated as conditional Poisson processes are examined. Numerical simulations illustrate part of the theoretical calculations.

Automatic microseismic event picking via unsupervised machine learning

NASA Astrophysics Data System (ADS)

Chen, Yangkang

2018-01-01

Effective and efficient arrival picking plays an important role in microseismic and earthquake data processing and imaging. Widely used short-term-average long-term-average ratio (STA/LTA) based arrival picking algorithms suffer from the sensitivity to moderate-to-strong random ambient noise. To make the state-of-the-art arrival picking approaches effective, microseismic data need to be first pre-processed, for example, removing sufficient amount of noise, and second analysed by arrival pickers. To conquer the noise issue in arrival picking for weak microseismic or earthquake event, I leverage the machine learning techniques to help recognizing seismic waveforms in microseismic or earthquake data. Because of the dependency of supervised machine learning algorithm on large volume of well-designed training data, I utilize an unsupervised machine learning algorithm to help cluster the time samples into two groups, that is, waveform points and non-waveform points. The fuzzy clustering algorithm has been demonstrated to be effective for such purpose. A group of synthetic, real microseismic and earthquake data sets with different levels of complexity show that the proposed method is much more robust than the state-of-the-art STA/LTA method in picking microseismic events, even in the case of moderately strong background noise.

Improving queuing service at McDonald's

NASA Astrophysics Data System (ADS)

Koh, Hock Lye; Teh, Su Yean; Wong, Chin Keat; Lim, Hooi Kie; Migin, Melissa W.

2014-07-01

Fast food restaurants are popular among price-sensitive youths and working adults who value the conducive environment and convenient services. McDonald's chains of restaurants promote their sales during lunch hours by offering package meals which are perceived to be inexpensive. These promotional lunch meals attract good response, resulting in occasional long queues and inconvenient waiting times. A study is conducted to monitor the distribution of waiting time, queue length, customer arrival and departure patterns at a McDonald's restaurant located in Kuala Lumpur. A customer survey is conducted to gauge customers' satisfaction regarding waiting time and queue length. An android app named Que is developed to perform onsite queuing analysis and report key performance indices. The queuing theory in Que is based upon the concept of Poisson distribution. In this paper, Que is utilized to perform queuing analysis at this McDonald's restaurant with the aim of improving customer service, with particular reference to reducing queuing time and shortening queue length. Some results will be presented.

Impact of lean six sigma process improvement methodology on cardiac catheterization laboratory efficiency.

PubMed

Agarwal, Shikhar; Gallo, Justin J; Parashar, Akhil; Agarwal, Kanika K; Ellis, Stephen G; Khot, Umesh N; Spooner, Robin; Murat Tuzcu, Emin; Kapadia, Samir R

2016-03-01

Operational inefficiencies are ubiquitous in several healthcare processes. To improve the operational efficiency of our catheterization laboratory (Cath Lab), we implemented a lean six sigma process improvement initiative, starting in June 2010. We aimed to study the impact of lean six sigma implementation on improving the efficiency and the patient throughput in our Cath Lab. All elective and urgent cardiac catheterization procedures including diagnostic coronary angiography, percutaneous coronary interventions, structural interventions and peripheral interventions performed between June 2009 and December 2012 were included in the study. Performance metrics utilized for analysis included turn-time, physician downtime, on-time patient arrival, on-time physician arrival, on-time start and manual sheath-pulls inside the Cath Lab. After implementation of lean six sigma in the Cath Lab, we observed a significant improvement in turn-time, physician downtime, on-time patient arrival, on-time physician arrival, on-time start as well as sheath-pulls inside the Cath Lab. The percentage of cases with optimal turn-time increased from 43.6% in 2009 to 56.6% in 2012 (p-trend<0.001). Similarly, the percentage of cases with an aggregate on-time start increased from 41.7% in 2009 to 62.8% in 2012 (p-trend<0.001). In addition, the percentage of manual sheath-pulls performed in the Cath Lab decreased from 60.7% in 2009 to 22.7% in 2012 (p-trend<0.001). The current longitudinal study illustrates the impact of successful implementation of a well-known process improvement initiative, lean six sigma, on improving and sustaining efficiency of our Cath Lab operation. After the successful implementation of this continuous quality improvement initiative, there was a significant improvement in the selected performance metrics namely turn-time, physician downtime, on-time patient arrival, on-time physician arrival, on-time start as well as sheath-pulls inside the Cath Lab. Copyright © 2016 Elsevier Inc. All rights reserved.

On the Singularity of the Vlasov-Poisson System

DOE Office of Scientific and Technical Information (OSTI.GOV)

and Hong Qin, Jian Zheng

2013-04-26

The Vlasov-Poisson system can be viewed as the collisionless limit of the corresponding Fokker- Planck-Poisson system. It is reasonable to expect that the result of Landau damping can also be obtained from the Fokker-Planck-Poisson system when the collision frequency v approaches zero. However, we show that the colllisionless Vlasov-Poisson system is a singular limit of the collisional Fokker-Planck-Poisson system, and Landau's result can be recovered only as the approaching zero from the positive side.

On the singularity of the Vlasov-Poisson system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zheng, Jian; Qin, Hong; Plasma Physics Laboratory, Princeton University, Princeton, New Jersey 08550

2013-09-15

The Vlasov-Poisson system can be viewed as the collisionless limit of the corresponding Fokker-Planck-Poisson system. It is reasonable to expect that the result of Landau damping can also be obtained from the Fokker-Planck-Poisson system when the collision frequency ν approaches zero. However, we show that the collisionless Vlasov-Poisson system is a singular limit of the collisional Fokker-Planck-Poisson system, and Landau's result can be recovered only as the ν approaches zero from the positive side.

Some functional limit theorems for compound Cox processes

NASA Astrophysics Data System (ADS)

Korolev, Victor Yu.; Chertok, A. V.; Korchagin, A. Yu.; Kossova, E. V.; Zeifman, Alexander I.

2016-06-01

An improved version of the functional limit theorem is proved establishing weak convergence of random walks generated by compound doubly stochastic Poisson processes (compound Cox processes) to Lévy processes in the Skorokhod space under more realistic moment conditions. As corollaries, theorems are proved on convergence of random walks with jumps having finite variances to Lévy processes with variance-mean mixed normal distributions, in particular, to stable Lévy processes.

Some functional limit theorems for compound Cox processes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Korolev, Victor Yu.; Institute of Informatics Problems FRC CSC RAS; Chertok, A. V.

2016-06-08

An improved version of the functional limit theorem is proved establishing weak convergence of random walks generated by compound doubly stochastic Poisson processes (compound Cox processes) to Lévy processes in the Skorokhod space under more realistic moment conditions. As corollaries, theorems are proved on convergence of random walks with jumps having finite variances to Lévy processes with variance-mean mixed normal distributions, in particular, to stable Lévy processes.

Stochastic Processes as True-Score Models for Highly Speeded Mental Tests.

ERIC Educational Resources Information Center

Moore, William E.

The previous theoretical development of the Poisson process as a strong model for the true-score theory of mental tests is discussed, and additional theoretical properties of the model from the standpoint of individual examinees are developed. The paper introduces the Erlang process as a family of test theory models and shows in the context of…

The impact of fog on soil moisture dynamics in the Namib Desert

NASA Astrophysics Data System (ADS)

Li, Bonan; Wang, Lixin; Kaseke, Kudzai F.; Vogt, Roland; Li, Lin; Seely, Mary K.

2018-03-01

Soil moisture is a crucial component supporting vegetation dynamics in drylands. Despite increasing attention on fog in dryland ecosystems, the statistical characterization of fog distribution and how fog affects soil moisture dynamics have not been seen in literature. To this end, daily fog records over two years (Dec 1, 2014-Nov 1, 2016) from three sites within the Namib Desert were used to characterize fog distribution. Two sites were located within the Gobabeb Research and Training Center vicinity, the gravel plains and the sand dunes. The third site was located at the gravel plains, Kleinberg. A subset of the fog data during rainless period was used to investigate the effect of fog on soil moisture. A stochastic modeling framework was used to simulate the effect of fog on soil moisture dynamics. Our results showed that fog distribution can be characterized by a Poisson process with two parameters (arrival rate λ and average depth α (mm)). Fog and soil moisture observations from eighty (Aug 19, 2015-Nov 6, 2015) rainless days indicated a moderate positive relationship between soil moisture and fog in the Gobabeb gravel plains, a weaker relationship in the Gobabeb sand dunes while no relationship was observed at the Kleinberg site. The modeling results suggested that mean and major peaks of soil moisture dynamics can be captured by the fog modeling. Our field observations demonstrated the effects of fog on soil moisture dynamics during rainless periods at some locations, which has important implications on soil biogeochemical processes. The statistical characterization and modeling of fog distribution are of great value to predict fog distribution and investigate the effects of potential changes in fog distribution on soil moisture dynamics.

Effects of rainfall seasonality and soil moisture capacity on mean annual water balance for Australian catchments

USGS Publications Warehouse

Potter, N.J.; Zhang, L.; Milly, P.C.D.; McMahon, T.A.; Jakeman, A.J.

2005-01-01

An important factor controlling catchment‐scale water balance is the seasonal variation of climate. The aim of this study is to investigate the effect of the seasonal distributions of water and energy, and their interactions with the soil moisture store, on mean annual water balance in Australia at catchment scales using a stochastic model of soil moisture balance with seasonally varying forcing. The rainfall regime at 262 catchments around Australia was modeled as a Poisson process with the mean storm arrival rate and the mean storm depth varying throughout the year as cosine curves with annual periods. The soil moisture dynamics were represented by use of a single, finite water store having infinite infiltration capacity, and the potential evapotranspiration rate was modeled as an annual cosine curve. The mean annual water budget was calculated numerically using a Monte Carlo simulation. The model predicted that for a given level of climatic aridity the ratio of mean annual evapotranspiration to rainfall was larger where the potential evapotranspiration and rainfall were in phase, that is, in summer‐dominant rainfall catchments, than where they were out of phase. The observed mean annual evapotranspiration ratios have opposite results. As a result, estimates of mean annual evapotranspiration from the model compared poorly with observational data. Because the inclusion of seasonally varying forcing alone was not sufficient to explain variability in the mean annual water balance, other catchment properties may play a role. Further analysis showed that the water balance was highly sensitive to the catchment‐scale soil moisture capacity. Calibrations of this parameter indicated that infiltration‐excess runoff might be an important process, especially for the summer‐dominant rainfall catchments; most similar studies have shown that modeling of infiltration‐excess runoff is not required at the mean annual timescale.

[Statistical (Poisson) motor unit number estimation. Methodological aspects and normal results in the extensor digitorum brevis muscle of healthy subjects].

PubMed

Murga Oporto, L; Menéndez-de León, C; Bauzano Poley, E; Núñez-Castaín, M J

Among the differents techniques for motor unit number estimation (MUNE) there is the statistical one (Poisson), in which the activation of motor units is carried out by electrical stimulation and the estimation performed by means of a statistical analysis based on the Poisson s distribution. The study was undertaken in order to realize an approximation to the MUNE Poisson technique showing a coprehensible view of its methodology and also to obtain normal results in the extensor digitorum brevis muscle (EDB) from a healthy population. One hundred fourteen normal volunteers with age ranging from 10 to 88 years were studied using the MUNE software contained in a Viking IV system. The normal subjects were divided into two age groups (10 59 and 60 88 years). The EDB MUNE from all them was 184 49. Both, the MUNE and the amplitude of the compound muscle action potential (CMAP) were significantly lower in the older age group (p< 0.0001), showing the MUNE a better correlation with age than CMAP amplitude ( 0.5002 and 0.4142, respectively p< 0.0001). Statistical MUNE method is an important way for the assessment to the phisiology of the motor unit. The value of MUNE correlates better with the neuromuscular aging process than CMAP amplitude does.

Bayesian semi-parametric analysis of Poisson change-point regression models: application to policy making in Cali, Colombia.

PubMed

Park, Taeyoung; Krafty, Robert T; Sánchez, Alvaro I

2012-07-27

A Poisson regression model with an offset assumes a constant baseline rate after accounting for measured covariates, which may lead to biased estimates of coefficients in an inhomogeneous Poisson process. To correctly estimate the effect of time-dependent covariates, we propose a Poisson change-point regression model with an offset that allows a time-varying baseline rate. When the nonconstant pattern of a log baseline rate is modeled with a nonparametric step function, the resulting semi-parametric model involves a model component of varying dimension and thus requires a sophisticated varying-dimensional inference to obtain correct estimates of model parameters of fixed dimension. To fit the proposed varying-dimensional model, we devise a state-of-the-art MCMC-type algorithm based on partial collapse. The proposed model and methods are used to investigate an association between daily homicide rates in Cali, Colombia and policies that restrict the hours during which the legal sale of alcoholic beverages is permitted. While simultaneously identifying the latent changes in the baseline homicide rate which correspond to the incidence of sociopolitical events, we explore the effect of policies governing the sale of alcohol on homicide rates and seek a policy that balances the economic and cultural dependencies on alcohol sales to the health of the public.

A Stabilized Finite Element Method for Modified Poisson-Nernst-Planck Equations to Determine Ion Flow Through a Nanopore

PubMed Central

Chaudhry, Jehanzeb Hameed; Comer, Jeffrey; Aksimentiev, Aleksei; Olson, Luke N.

2013-01-01

The conventional Poisson-Nernst-Planck equations do not account for the finite size of ions explicitly. This leads to solutions featuring unrealistically high ionic concentrations in the regions subject to external potentials, in particular, near highly charged surfaces. A modified form of the Poisson-Nernst-Planck equations accounts for steric effects and results in solutions with finite ion concentrations. Here, we evaluate numerical methods for solving the modified Poisson-Nernst-Planck equations by modeling electric field-driven transport of ions through a nanopore. We describe a novel, robust finite element solver that combines the applications of the Newton's method to the nonlinear Galerkin form of the equations, augmented with stabilization terms to appropriately handle the drift-diffusion processes. To make direct comparison with particle-based simulations possible, our method is specifically designed to produce solutions under periodic boundary conditions and to conserve the number of ions in the solution domain. We test our finite element solver on a set of challenging numerical experiments that include calculations of the ion distribution in a volume confined between two charged plates, calculations of the ionic current though a nanopore subject to an external electric field, and modeling the effect of a DNA molecule on the ion concentration and nanopore current. PMID:24363784

Fractional models of seismoacoustic and electromagnetic activity

NASA Astrophysics Data System (ADS)

Shevtsov, Boris; Sheremetyeva, Olga

2017-10-01

Statistical models of the seismoacoustic and electromagnetic activity caused by deformation disturbances are considered on the basis of compound Poisson process and its fractional generalizations. Wave representations of these processes are used too. It is discussed five regimes of deformation activity and their role in understanding of the earthquakes precursors nature.

Library Book Circulation and the Beta-Binomial Distribution.

ERIC Educational Resources Information Center

Gelman, E.; Sichel, H. S.

1987-01-01

Argues that library book circulation is a binomial rather than a Poisson process, and that individual book popularities are continuous beta distributions. Three examples demonstrate the superiority of beta over negative binomial distribution, and it is suggested that a bivariate-binomial process would be helpful in predicting future book…

Adiabatic reduction of a model of stochastic gene expression with jump Markov process.

PubMed

Yvinec, Romain; Zhuge, Changjing; Lei, Jinzhi; Mackey, Michael C

2014-04-01

This paper considers adiabatic reduction in a model of stochastic gene expression with bursting transcription considered as a jump Markov process. In this model, the process of gene expression with auto-regulation is described by fast/slow dynamics. The production of mRNA is assumed to follow a compound Poisson process occurring at a rate depending on protein levels (the phenomena called bursting in molecular biology) and the production of protein is a linear function of mRNA numbers. When the dynamics of mRNA is assumed to be a fast process (due to faster mRNA degradation than that of protein) we prove that, with appropriate scalings in the burst rate, jump size or translational rate, the bursting phenomena can be transmitted to the slow variable. We show that, depending on the scaling, the reduced equation is either a stochastic differential equation with a jump Poisson process or a deterministic ordinary differential equation. These results are significant because adiabatic reduction techniques seem to have not been rigorously justified for a stochastic differential system containing a jump Markov process. We expect that the results can be generalized to adiabatic methods in more general stochastic hybrid systems.

Atomic clocks and the continuous-time random-walk

NASA Astrophysics Data System (ADS)

Formichella, Valerio; Camparo, James; Tavella, Patrizia

2017-11-01

Atomic clocks play a fundamental role in many fields, most notably they generate Universal Coordinated Time and are at the heart of all global navigation satellite systems. Notwithstanding their excellent timekeeping performance, their output frequency does vary: it can display deterministic frequency drift; diverse continuous noise processes result in nonstationary clock noise (e.g., random-walk frequency noise, modelled as a Wiener process), and the clock frequency may display sudden changes (i.e., "jumps"). Typically, the clock's frequency instability is evaluated by the Allan or Hadamard variances, whose functional forms can identify the different operative noise processes. Here, we show that the Allan and Hadamard variances of a particular continuous-time random-walk, the compound Poisson process, have the same functional form as for a Wiener process with drift. The compound Poisson process, introduced as a model for observed frequency jumps, is an alternative to the Wiener process for modelling random walk frequency noise. This alternate model fits well the behavior of the rubidium clocks flying on GPS Block-IIR satellites. Further, starting from jump statistics, the model can be improved by considering a more general form of continuous-time random-walk, and this could bring new insights into the physics of atomic clocks.

A Generalized QMRA Beta-Poisson Dose-Response Model.

PubMed

Xie, Gang; Roiko, Anne; Stratton, Helen; Lemckert, Charles; Dunn, Peter K; Mengersen, Kerrie

2016-10-01

Quantitative microbial risk assessment (QMRA) is widely accepted for characterizing the microbial risks associated with food, water, and wastewater. Single-hit dose-response models are the most commonly used dose-response models in QMRA. Denoting PI(d) as the probability of infection at a given mean dose d, a three-parameter generalized QMRA beta-Poisson dose-response model, PI(d|α,β,r*), is proposed in which the minimum number of organisms required for causing infection, K min , is not fixed, but a random variable following a geometric distribution with parameter 0

Nambu-Poisson gauge theory

NASA Astrophysics Data System (ADS)

Jurčo, Branislav; Schupp, Peter; Vysoký, Jan

2014-06-01

We generalize noncommutative gauge theory using Nambu-Poisson structures to obtain a new type of gauge theory with higher brackets and gauge fields. The approach is based on covariant coordinates and higher versions of the Seiberg-Witten map. We construct a covariant Nambu-Poisson gauge theory action, give its first order expansion in the Nambu-Poisson tensor and relate it to a Nambu-Poisson matrix model.

Localization of Gunfire from Multiple Shooters (ARO Research Topic 5.2, Information Processing and Fusion; STIR Program)

DTIC Science & Technology

2016-03-03

for each shot, as well as "raw" data that includes time-of-arrival (TOA) and direction-of-arrival (DOA) of the muzzle blast (MB) produced by the weapon...angle of arrival, muzzle blast, shock wave, bullet deceleration, fusion REPORT DOCUMENTATION PAGE 11. SPONSOR/MONITOR’S REPORT NUMBER(S) 10. SPONSOR...of the muzzle blast (MB) produced by the weapon and the shock wave (SW) produced by the supersonic bullet. The localization accuracy is improved

Hardware-software complex of informing passengers of forecasted route transport arrival at stop

NASA Astrophysics Data System (ADS)

Pogrebnoy, V. Yu; Pushkarev, M. I.; Fadeev, A. S.

2017-02-01

The paper presents the hardware-software complex of informing the passengers of the forecasted route transport arrival. A client-server architecture of the forecasting information system is represented and an electronic information board prototype is described. The scheme of information transfer and processing, starting with receiving navigating telemetric data from a transport vehicle and up to the time of passenger public transport arrival at the stop, as well as representation of the information on the electronic board is illustrated and described. Methods and algorithms of determination of the transport vehicle current location in the city route network are considered in detail. The description of the proposed forecasting model of transport vehicle arrival time at the stop is given. The obtained result is applied in Tomsk for forecasting and displaying the arrival time information at the stops.

STDP allows fast rate-modulated coding with Poisson-like spike trains.

PubMed

Gilson, Matthieu; Masquelier, Timothée; Hugues, Etienne

2011-10-01

Spike timing-dependent plasticity (STDP) has been shown to enable single neurons to detect repeatedly presented spatiotemporal spike patterns. This holds even when such patterns are embedded in equally dense random spiking activity, that is, in the absence of external reference times such as a stimulus onset. Here we demonstrate, both analytically and numerically, that STDP can also learn repeating rate-modulated patterns, which have received more experimental evidence, for example, through post-stimulus time histograms (PSTHs). Each input spike train is generated from a rate function using a stochastic sampling mechanism, chosen to be an inhomogeneous Poisson process here. Learning is feasible provided significant covarying rate modulations occur within the typical timescale of STDP (~10-20 ms) for sufficiently many inputs (~100 among 1000 in our simulations), a condition that is met by many experimental PSTHs. Repeated pattern presentations induce spike-time correlations that are captured by STDP. Despite imprecise input spike times and even variable spike counts, a single trained neuron robustly detects the pattern just a few milliseconds after its presentation. Therefore, temporal imprecision and Poisson-like firing variability are not an obstacle to fast temporal coding. STDP provides an appealing mechanism to learn such rate patterns, which, beyond sensory processing, may also be involved in many cognitive tasks.

A modified Poisson-Boltzmann equation applied to protein adsorption.

PubMed

Gama, Marlon de Souza; Santos, Mirella Simões; Lima, Eduardo Rocha de Almeida; Tavares, Frederico Wanderley; Barreto, Amaro Gomes Barreto

2018-01-05

Ion-exchange chromatography has been widely used as a standard process in purification and analysis of protein, based on the electrostatic interaction between the protein and the stationary phase. Through the years, several approaches are used to improve the thermodynamic description of colloidal particle-surface interaction systems, however there are still a lot of gaps specifically when describing the behavior of protein adsorption. Here, we present an improved methodology for predicting the adsorption equilibrium constant by solving the modified Poisson-Boltzmann (PB) equation in bispherical coordinates. By including dispersion interactions between ions and protein, and between ions and surface, the modified PB equation used can describe the Hofmeister effects. We solve the modified Poisson-Boltzmann equation to calculate the protein-surface potential of mean force, treated as spherical colloid-plate system, as a function of process variables. From the potential of mean force, the Henry constants of adsorption, for different proteins and surfaces, are calculated as a function of pH, salt concentration, salt type, and temperature. The obtained Henry constants are compared with experimental data for several isotherms showing excellent agreement. We have also performed a sensitivity analysis to verify the behavior of different kind of salts and the Hofmeister effects. Copyright © 2017 Elsevier B.V. All rights reserved.

STDP Allows Fast Rate-Modulated Coding with Poisson-Like Spike Trains

PubMed Central

Hugues, Etienne

2011-01-01

Spike timing-dependent plasticity (STDP) has been shown to enable single neurons to detect repeatedly presented spatiotemporal spike patterns. This holds even when such patterns are embedded in equally dense random spiking activity, that is, in the absence of external reference times such as a stimulus onset. Here we demonstrate, both analytically and numerically, that STDP can also learn repeating rate-modulated patterns, which have received more experimental evidence, for example, through post-stimulus time histograms (PSTHs). Each input spike train is generated from a rate function using a stochastic sampling mechanism, chosen to be an inhomogeneous Poisson process here. Learning is feasible provided significant covarying rate modulations occur within the typical timescale of STDP (∼10–20 ms) for sufficiently many inputs (∼100 among 1000 in our simulations), a condition that is met by many experimental PSTHs. Repeated pattern presentations induce spike-time correlations that are captured by STDP. Despite imprecise input spike times and even variable spike counts, a single trained neuron robustly detects the pattern just a few milliseconds after its presentation. Therefore, temporal imprecision and Poisson-like firing variability are not an obstacle to fast temporal coding. STDP provides an appealing mechanism to learn such rate patterns, which, beyond sensory processing, may also be involved in many cognitive tasks. PMID:22046113

ECOSTRESS Arrival and Processing

NASA Image and Video Library

2018-04-09

In the Space Station Processing Facility at NASA's Kennedy Space Center in Florida, the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) has arrived in its shipping container. The container is being inspected and thoroughly cleaned prior to opening. ECOSTRESS is designed to monitor one of the most basic processes in living plants: the loss of water through the tiny pores in leaves. ECOSTRESS will launch to the International Space Station aboard a Dragon spacecraft launched by a Falcon 9 rocket on the SpaceX CRS-15 mission in June 2018.

Error Recovery in the Time-Triggered Paradigm with FTT-CAN.

PubMed

Marques, Luis; Vasconcelos, Verónica; Pedreiras, Paulo; Almeida, Luís

2018-01-11

Data networks are naturally prone to interferences that can corrupt messages, leading to performance degradation or even to critical failure of the corresponding distributed system. To improve resilience of critical systems, time-triggered networks are frequently used, based on communication schedules defined at design-time. These networks offer prompt error detection, but slow error recovery that can only be compensated with bandwidth overprovisioning. On the contrary, the Flexible Time-Triggered (FTT) paradigm uses online traffic scheduling, which enables a compromise between error detection and recovery that can achieve timely recovery with a fraction of the needed bandwidth. This article presents a new method to recover transmission errors in a time-triggered Controller Area Network (CAN) network, based on the Flexible Time-Triggered paradigm, namely FTT-CAN. The method is based on using a server (traffic shaper) to regulate the retransmission of corrupted or omitted messages. We show how to design the server to simultaneously: (1) meet a predefined reliability goal, when considering worst case error recovery scenarios bounded probabilistically by a Poisson process that models the fault arrival rate; and, (2) limit the direct and indirect interference in the message set, preserving overall system schedulability. Extensive simulations with multiple scenarios, based on practical and randomly generated systems, show a reduction of two orders of magnitude in the average bandwidth taken by the proposed error recovery mechanism, when compared with traditional approaches available in the literature based on adding extra pre-defined transmission slots.

Error Recovery in the Time-Triggered Paradigm with FTT-CAN

PubMed Central

Pedreiras, Paulo; Almeida, Luís

2018-01-01

Data networks are naturally prone to interferences that can corrupt messages, leading to performance degradation or even to critical failure of the corresponding distributed system. To improve resilience of critical systems, time-triggered networks are frequently used, based on communication schedules defined at design-time. These networks offer prompt error detection, but slow error recovery that can only be compensated with bandwidth overprovisioning. On the contrary, the Flexible Time-Triggered (FTT) paradigm uses online traffic scheduling, which enables a compromise between error detection and recovery that can achieve timely recovery with a fraction of the needed bandwidth. This article presents a new method to recover transmission errors in a time-triggered Controller Area Network (CAN) network, based on the Flexible Time-Triggered paradigm, namely FTT-CAN. The method is based on using a server (traffic shaper) to regulate the retransmission of corrupted or omitted messages. We show how to design the server to simultaneously: (1) meet a predefined reliability goal, when considering worst case error recovery scenarios bounded probabilistically by a Poisson process that models the fault arrival rate; and, (2) limit the direct and indirect interference in the message set, preserving overall system schedulability. Extensive simulations with multiple scenarios, based on practical and randomly generated systems, show a reduction of two orders of magnitude in the average bandwidth taken by the proposed error recovery mechanism, when compared with traditional approaches available in the literature based on adding extra pre-defined transmission slots. PMID:29324723

Hazard function theory for nonstationary natural hazards

NASA Astrophysics Data System (ADS)

Read, L.; Vogel, R. M.

2015-12-01

Studies from the natural hazards literature indicate that many natural processes, including wind speeds, landslides, wildfires, precipitation, streamflow and earthquakes, show evidence of nonstationary behavior such as trends in magnitudes through time. Traditional probabilistic analysis of natural hazards based on partial duration series (PDS) generally assumes stationarity in the magnitudes and arrivals of events, i.e. that the probability of exceedance is constant through time. Given evidence of trends and the consequent expected growth in devastating impacts from natural hazards across the world, new methods are needed to characterize their probabilistic behavior. The field of hazard function analysis (HFA) is ideally suited to this problem because its primary goal is to describe changes in the exceedance probability of an event over time. HFA is widely used in medicine, manufacturing, actuarial statistics, reliability engineering, economics, and elsewhere. HFA provides a rich theory to relate the natural hazard event series (x) with its failure time series (t), enabling computation of corresponding average return periods and reliabilities associated with nonstationary event series. This work investigates the suitability of HFA to characterize nonstationary natural hazards whose PDS magnitudes are assumed to follow the widely applied Poisson-GP model. We derive a 2-parameter Generalized Pareto hazard model and demonstrate how metrics such as reliability and average return period are impacted by nonstationarity and discuss the implications for planning and design. Our theoretical analysis linking hazard event series x, with corresponding failure time series t, should have application to a wide class of natural hazards.

How to deal with the Poisson-gamma model to forecast patients' recruitment in clinical trials when there are pauses in recruitment dynamic?

PubMed

Minois, Nathan; Savy, Stéphanie; Lauwers-Cances, Valérie; Andrieu, Sandrine; Savy, Nicolas

2017-03-01

Recruiting patients is a crucial step of a clinical trial. Estimation of the trial duration is a question of paramount interest. Most techniques are based on deterministic models and various ad hoc methods neglecting the variability in the recruitment process. To overpass this difficulty the so-called Poisson-gamma model has been introduced involving, for each centre, a recruitment process modelled by a Poisson process whose rate is assumed constant in time and gamma-distributed. The relevancy of this model has been widely investigated. In practice, rates are rarely constant in time, there are breaks in recruitment (for instance week-ends or holidays). Such information can be collected and included in a model considering piecewise constant rate functions yielding to an inhomogeneous Cox model. The estimation of the trial duration is much more difficult. Three strategies of computation of the expected trial duration are proposed considering all the breaks, considering only large breaks and without considering breaks. The bias of these estimations procedure are assessed by means of simulation studies considering three scenarios of breaks simulation. These strategies yield to estimations with a very small bias. Moreover, the strategy with the best performances in terms of prediction and with the smallest bias is the one which does not take into account of breaks. This result is important as, in practice, collecting breaks data is pretty hard to manage.

Framework based on stochastic L-Systems for modeling IP traffic with multifractal behavior

NASA Astrophysics Data System (ADS)

Salvador, Paulo S.; Nogueira, Antonio; Valadas, Rui

2003-08-01

In a previous work we have introduced a multifractal traffic model based on so-called stochastic L-Systems, which were introduced by biologist A. Lindenmayer as a method to model plant growth. L-Systems are string rewriting techniques, characterized by an alphabet, an axiom (initial string) and a set of production rules. In this paper, we propose a novel traffic model, and an associated parameter fitting procedure, which describes jointly the packet arrival and the packet size processes. The packet arrival process is modeled through a L-System, where the alphabet elements are packet arrival rates. The packet size process is modeled through a set of discrete distributions (of packet sizes), one for each arrival rate. In this way the model is able to capture correlations between arrivals and sizes. We applied the model to measured traffic data: the well-known pOct Bellcore, a trace of aggregate WAN traffic and two traces of specific applications (Kazaa and Operation Flashing Point). We assess the multifractality of these traces using Linear Multiscale Diagrams. The suitability of the traffic model is evaluated by comparing the empirical and fitted probability mass and autocovariance functions; we also compare the packet loss ratio and average packet delay obtained with the measured traces and with traces generated from the fitted model. Our results show that our L-System based traffic model can achieve very good fitting performance in terms of first and second order statistics and queuing behavior.

Sparsity-based Poisson denoising with dictionary learning.

PubMed

Giryes, Raja; Elad, Michael

2014-12-01

The problem of Poisson denoising appears in various imaging applications, such as low-light photography, medical imaging, and microscopy. In cases of high SNR, several transformations exist so as to convert the Poisson noise into an additive-independent identically distributed. Gaussian noise, for which many effective algorithms are available. However, in a low-SNR regime, these transformations are significantly less accurate, and a strategy that relies directly on the true noise statistics is required. Salmon et al took this route, proposing a patch-based exponential image representation model based on Gaussian mixture model, leading to state-of-the-art results. In this paper, we propose to harness sparse-representation modeling to the image patches, adopting the same exponential idea. Our scheme uses a greedy pursuit with boot-strapping-based stopping condition and dictionary learning within the denoising process. The reconstruction performance of the proposed scheme is competitive with leading methods in high SNR and achieving state-of-the-art results in cases of low SNR.

Fourier ptychographic reconstruction using Poisson maximum likelihood and truncated Wirtinger gradient.

PubMed

Bian, Liheng; Suo, Jinli; Chung, Jaebum; Ou, Xiaoze; Yang, Changhuei; Chen, Feng; Dai, Qionghai

2016-06-10

Fourier ptychographic microscopy (FPM) is a novel computational coherent imaging technique for high space-bandwidth product imaging. Mathematically, Fourier ptychographic (FP) reconstruction can be implemented as a phase retrieval optimization process, in which we only obtain low resolution intensity images corresponding to the sub-bands of the sample's high resolution (HR) spatial spectrum, and aim to retrieve the complex HR spectrum. In real setups, the measurements always suffer from various degenerations such as Gaussian noise, Poisson noise, speckle noise and pupil location error, which would largely degrade the reconstruction. To efficiently address these degenerations, we propose a novel FP reconstruction method under a gradient descent optimization framework in this paper. The technique utilizes Poisson maximum likelihood for better signal modeling, and truncated Wirtinger gradient for effective error removal. Results on both simulated data and real data captured using our laser-illuminated FPM setup show that the proposed method outperforms other state-of-the-art algorithms. Also, we have released our source code for non-commercial use.

Poisson property of the occurrence of flip-flops in a model membrane.

PubMed

Arai, Noriyoshi; Akimoto, Takuma; Yamamoto, Eiji; Yasui, Masato; Yasuoka, Kenji

2014-02-14

How do lipid molecules in membranes perform a flip-flop? The flip-flops of lipid molecules play a crucial role in the formation and flexibility of membranes. However, little has been determined about the behavior of flip-flops, either experimentally, or in molecular dynamics simulations. Here, we provide numerical results of the flip-flops of model lipid molecules in a model membrane and investigate the statistical properties, using millisecond-order coarse-grained molecular simulations (dissipative particle dynamics). We find that there are three different ways of flip-flops, which can be clearly characterized by their paths on the free energy surface. Furthermore, we found that the probability of the number of the flip-flops is well fitted by the Poisson distribution, and the probability density function for the inter-occurrence times of flip-flops coincides with that of the forward recurrence times. These results indicate that the occurrence of flip-flops is a Poisson process, which will play an important role in the flexibilities of membranes.

Modeling motor vehicle crashes using Poisson-gamma models: examining the effects of low sample mean values and small sample size on the estimation of the fixed dispersion parameter.

PubMed

Lord, Dominique

2006-07-01

There has been considerable research conducted on the development of statistical models for predicting crashes on highway facilities. Despite numerous advancements made for improving the estimation tools of statistical models, the most common probabilistic structure used for modeling motor vehicle crashes remains the traditional Poisson and Poisson-gamma (or Negative Binomial) distribution; when crash data exhibit over-dispersion, the Poisson-gamma model is usually the model of choice most favored by transportation safety modelers. Crash data collected for safety studies often have the unusual attributes of being characterized by low sample mean values. Studies have shown that the goodness-of-fit of statistical models produced from such datasets can be significantly affected. This issue has been defined as the "low mean problem" (LMP). Despite recent developments on methods to circumvent the LMP and test the goodness-of-fit of models developed using such datasets, no work has so far examined how the LMP affects the fixed dispersion parameter of Poisson-gamma models used for modeling motor vehicle crashes. The dispersion parameter plays an important role in many types of safety studies and should, therefore, be reliably estimated. The primary objective of this research project was to verify whether the LMP affects the estimation of the dispersion parameter and, if it is, to determine the magnitude of the problem. The secondary objective consisted of determining the effects of an unreliably estimated dispersion parameter on common analyses performed in highway safety studies. To accomplish the objectives of the study, a series of Poisson-gamma distributions were simulated using different values describing the mean, the dispersion parameter, and the sample size. Three estimators commonly used by transportation safety modelers for estimating the dispersion parameter of Poisson-gamma models were evaluated: the method of moments, the weighted regression, and the maximum likelihood method. In an attempt to complement the outcome of the simulation study, Poisson-gamma models were fitted to crash data collected in Toronto, Ont. characterized by a low sample mean and small sample size. The study shows that a low sample mean combined with a small sample size can seriously affect the estimation of the dispersion parameter, no matter which estimator is used within the estimation process. The probability the dispersion parameter becomes unreliably estimated increases significantly as the sample mean and sample size decrease. Consequently, the results show that an unreliably estimated dispersion parameter can significantly undermine empirical Bayes (EB) estimates as well as the estimation of confidence intervals for the gamma mean and predicted response. The paper ends with recommendations about minimizing the likelihood of producing Poisson-gamma models with an unreliable dispersion parameter for modeling motor vehicle crashes.

A Three-dimensional Polymer Scaffolding Material Exhibiting a Zero Poisson's Ratio.

PubMed

Soman, Pranav; Fozdar, David Y; Lee, Jin Woo; Phadke, Ameya; Varghese, Shyni; Chen, Shaochen

2012-05-14

Poisson's ratio describes the degree to which a material contracts (expands) transversally when axially strained. A material with a zero Poisson's ratio does not transversally deform in response to an axial strain (stretching). In tissue engineering applications, scaffolding having a zero Poisson's ratio (ZPR) may be more suitable for emulating the behavior of native tissues and accommodating and transmitting forces to the host tissue site during wound healing (or tissue regrowth). For example, scaffolding with a zero Poisson's ratio may be beneficial in the engineering of cartilage, ligament, corneal, and brain tissues, which are known to possess Poisson's ratios of nearly zero. Here, we report a 3D biomaterial constructed from polyethylene glycol (PEG) exhibiting in-plane Poisson's ratios of zero for large values of axial strain. We use digital micro-mirror device projection printing (DMD-PP) to create single- and double-layer scaffolds composed of semi re-entrant pores whose arrangement and deformation mechanisms contribute the zero Poisson's ratio. Strain experiments prove the zero Poisson's behavior of the scaffolds and that the addition of layers does not change the Poisson's ratio. Human mesenchymal stem cells (hMSCs) cultured on biomaterials with zero Poisson's ratio demonstrate the feasibility of utilizing these novel materials for biological applications which require little to no transverse deformations resulting from axial strains. Techniques used in this work allow Poisson's ratio to be both scale-independent and independent of the choice of strut material for strains in the elastic regime, and therefore ZPR behavior can be imparted to a variety of photocurable biomaterial.

It is more efficient to type: innovative self-registration and appointment self-arrival system improves the patient reception process.

PubMed

Knight, Vickie; Guy, Rebecca J; Handan, Wand; Lu, Heng; McNulty, Anna

2014-06-01

In 2010, we introduced an express sexually transmitted infection/HIV testing service at a large metropolitan sexual health clinic, which significantly increased clinical service capacity. However, it also increased reception staff workload and caused backlogs of patients waiting to register or check in for appointments. We therefore implemented a new electronic self-registration and appointment self-arrival system in March 2012 to increase administrative efficiency and reduce waiting time for patients. We compared the median processing time overall and for each step of the registration and arrival process as well as the completeness of patient contact information recorded, in a 1-week period before and after the redesign of the registration system. χ2 Test and rank sum tests were used. Before the redesign, the median processing time was 8.33 minutes (interquartile range [IQR], 6.82-15.43), decreasing by 30% to 5.83 minutes (IQR, 4.75-7.42) when the new electronic self-registration and appointment self-arrival system was introduced (P < 0.001). The largest gain in efficiency was in the time taken to prepare the medical record for the clinician, reducing from a median of 5.31 minutes (IQR, 4.02-8.29) to 0.57 minutes (IQR, 0.38-1) in the 2 periods. Before implementation, 20% of patients provided a postal address and 31% an e-mail address, increasing to 60% and 70% post redesign, respectively (P < 0.001). Our evaluation shows that an electronic patient self-registration and appointment self-arrival system can improve clinic efficiency and save patient time. Systems like this one could be used by any outpatient service with large patient volumes as an integrated part of the electronic patient management system or as a standalone feature.

Sustained reductions in time to antibiotic delivery in febrile immunocompromised children: results of a quality improvement collaborative.

PubMed

Dandoy, Christopher E; Hariharan, Selena; Weiss, Brian; Demmel, Kathy; Timm, Nathan; Chiarenzelli, Janis; Dewald, Mary Katherine; Kennebeck, Stephanie; Langworthy, Shawna; Pomales, Jennifer; Rineair, Sylvia; Sandfoss, Erin; Volz-Noe, Pamela; Nagarajan, Rajaram; Alessandrini, Evaline

2016-02-01

Timely delivery of antibiotics to febrile immunocompromised (F&I) paediatric patients in the emergency department (ED) and outpatient clinic reduces morbidity and mortality. The aim of this quality improvement initiative was to increase the percentage of F&I patients who received antibiotics within goal in the clinic and ED from 25% to 90%. Using the Model of Improvement, we performed Plan-Do-Study-Act cycles to design, test and implement high-reliability interventions to decrease time to antibiotics. Pre-arrival interventions were tested and implemented, followed by post-arrival interventions in the ED. Many processes were spread successfully to the outpatient clinic. The Chronic Care Model was used, in addition to active family engagement, to inform and improve processes. The study period was from January 2010 to January 2015. Pre-arrival planning improved our F&I time to antibiotics in the ED from 137 to 88 min. This was sustained until October 2012, when further interventions including a pre-arrival huddle decreased the median time to <50 min. Implementation of the various processes to the clinic delivery system increased the mean percentage of patients receiving antibiotics within 60 min to >90%. In September 2014, we implemented a rapid response team to improve reliable venous access in the ED, which increased our mean percentage of patients receiving timely antibiotics to its highest rate (95%). This stepwise approach with pre-arrival planning using the Chronic Care Model, followed by standardisation of processes, created a sustainable improvement of timely antibiotic delivery in F&I patients. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Seismicity, faulting, and structure of the Koyna-Warna seismic region, Western India from local earthquake tomography and hypocenter locations

USGS Publications Warehouse

Dixit, Madan M.; Kumar, Sanjay; Catchings, Rufus D.; Suman, K.; Sarkar, Dipankar; Sen, M.K.

2014-01-01

Although seismicity near Koyna Reservoir (India) has persisted for ~50 years and includes the largest induced earthquake (M 6.3) reported worldwide, the seismotectonic framework of the area is not well understood. We recorded ~1800 earthquakes from 6 January 2010 to 28 May 2010 and located a subset of 343 of the highest-quality earthquakes using the tomoDD code of Zhang and Thurber (2003) to better understand the framework. We also inverted first arrivals for 3-D Vp, Vs, and Vp/Vs and Poisson's ratio tomography models of the upper 12 km of the crust. Epicenters for the recorded earthquakes are located south of the Koyna River, including a high-density cluster that coincides with a shallow depth (<1.5 km) zone of relatively high Vp and low Vs (also high Vp/Vs and Poisson's ratios) near Warna Reservoir. This anomalous zone, which extends near vertically to at least 8 km depth and laterally northward at least 15 km, is likely a water-saturated zone of faults under high pore pressures. Because many of the earthquakes occur on the periphery of the fault zone, rather than near its center, the observed seismicity-velocity correlations are consistent with the concept that many of the earthquakes nucleate in fractures adjacent to the main fault zone due to high pore pressure. We interpret our velocity images as showing a series of northwest trending faults locally near the central part of Warna Reservoir and a major northward trending fault zone north of Warna Reservoir.

Research in Stochastic Processes.

DTIC Science & Technology

1983-10-01

increases. A more detailed investigation for the exceedances themselves (rather than Just the cluster centers) was undertaken, together with J. HUsler and...J. HUsler and M.R. Leadbetter, Compoung Poisson limit theorems for high level exceedances by stationary sequences, Center for Stochastic Processes...stability by a random linear operator. C.D. Hardin, General (asymmetric) stable variables and processes. T. Hsing, J. HUsler and M.R. Leadbetter, Compound

Nonlocal Poisson-Fermi model for ionic solvent.

PubMed

Xie, Dexuan; Liu, Jinn-Liang; Eisenberg, Bob

2016-07-01

We propose a nonlocal Poisson-Fermi model for ionic solvent that includes ion size effects and polarization correlations among water molecules in the calculation of electrostatic potential. It includes the previous Poisson-Fermi models as special cases, and its solution is the convolution of a solution of the corresponding nonlocal Poisson dielectric model with a Yukawa-like kernel function. The Fermi distribution is shown to be a set of optimal ionic concentration functions in the sense of minimizing an electrostatic potential free energy. Numerical results are reported to show the difference between a Poisson-Fermi solution and a corresponding Poisson solution.

Nonlinear Poisson Equation for Heterogeneous Media

PubMed Central

Hu, Langhua; Wei, Guo-Wei

2012-01-01

The Poisson equation is a widely accepted model for electrostatic analysis. However, the Poisson equation is derived based on electric polarizations in a linear, isotropic, and homogeneous dielectric medium. This article introduces a nonlinear Poisson equation to take into consideration of hyperpolarization effects due to intensive charges and possible nonlinear, anisotropic, and heterogeneous media. Variational principle is utilized to derive the nonlinear Poisson model from an electrostatic energy functional. To apply the proposed nonlinear Poisson equation for the solvation analysis, we also construct a nonpolar solvation energy functional based on the nonlinear Poisson equation by using the geometric measure theory. At a fixed temperature, the proposed nonlinear Poisson theory is extensively validated by the electrostatic analysis of the Kirkwood model and a set of 20 proteins, and the solvation analysis of a set of 17 small molecules whose experimental measurements are also available for a comparison. Moreover, the nonlinear Poisson equation is further applied to the solvation analysis of 21 compounds at different temperatures. Numerical results are compared to theoretical prediction, experimental measurements, and those obtained from other theoretical methods in the literature. A good agreement between our results and experimental data as well as theoretical results suggests that the proposed nonlinear Poisson model is a potentially useful model for electrostatic analysis involving hyperpolarization effects. PMID:22947937

Transparency in the reporting of in vivo pre-clinical pain research: The relevance and implications of the ARRIVE (Animal Research: Reporting In Vivo Experiments) guidelines.

PubMed

Rice, Andrew S C; Morland, Rosemary; Huang, Wenlong; Currie, Gillian L; Sena, Emily S; Macleod, Malcolm R

2017-12-29

Clear reporting of research is crucial to the scientific process. Poorly designed and reported studies are damaging not only to the efforts of individual researchers, but also to science as a whole. Standardised reporting methods, such as those already established for reporting randomised clinical trials, have led to improved study design and facilitated the processes of clinical systematic review and meta-analysis. Such standards were lacking in the pre-clinical field until the development of the ARRIVE (Animal Research: Reporting In Vivo Experiments) guidelines. These were prompted following a survey which highlighted a widespread lack of robust and consistent reporting of pre-clinical in vivo research, with reports frequently omitting basic information required for study replication and quality assessment. The resulting twenty item checklist in ARRIVE covers all aspects of experimental design with particular emphasis on bias reduction and methodological transparency. Influential publishers and research funders have already adopted ARRIVE. Further dissemination and acknowledgement of the importance of these guidelines is vital to their widespread implementation. Conclusions and implications Wide implementation of the ARRIVE guidelines for reporting of in vivo preclinical research, especially pain research, are essential for a much needed increased transparency and quality in publishing such research. ARRIVE will also positively influence improvements in experimental design and quality, assist the conduct of accurate replication studies of important new findings and facilitate meta-analyses of preclinical research.

Physical properties of biophotons and their biological functions.

PubMed

Chang, Jiin-Ju

2008-05-01

Biophotons (BPHs) are weak photons within or emitted from living organisms. The intensities of BPHs range from a few to several hundred photons s(-1) x cm(-2). BPH emission originates from a de-localized coherent electromagnetic field within the living organisms and is regulated by the field. In this paper based on the experimental results of Poisson and sub-Poisson distributions of photocount statistics, the coherent properties of BPHs and their functions in cell communication are described. Discussions are made on functions which BPHs may play in DNA and proteins functioning including the process of DNA replication, protein synthesis and cell signalling and in oxidative phosporylation and photosynthesis.

7 CFR 361.4 - Inspection at the port of first arrival.

Code of Federal Regulations, 2012 CFR

2012-01-01

...) indicates that the screenings are being imported for processing or manufacturing purposes; (4) Seed that is... INSPECTION SERVICE, DEPARTMENT OF AGRICULTURE IMPORTATION OF SEED AND SCREENINGS UNDER THE FEDERAL SEED ACT § 361.4 Inspection at the port of first arrival. (a) All agricultural seed, vegetable seed, and...

7 CFR 361.4 - Inspection at the port of first arrival.

Code of Federal Regulations, 2014 CFR

2014-01-01

...) indicates that the screenings are being imported for processing or manufacturing purposes; (4) Seed that is... INSPECTION SERVICE, DEPARTMENT OF AGRICULTURE IMPORTATION OF SEED AND SCREENINGS UNDER THE FEDERAL SEED ACT § 361.4 Inspection at the port of first arrival. (a) All agricultural seed, vegetable seed, and...

7 CFR 361.4 - Inspection at the port of first arrival.

Code of Federal Regulations, 2011 CFR

2011-01-01

...) indicates that the screenings are being imported for processing or manufacturing purposes; (4) Seed that is... INSPECTION SERVICE, DEPARTMENT OF AGRICULTURE IMPORTATION OF SEED AND SCREENINGS UNDER THE FEDERAL SEED ACT § 361.4 Inspection at the port of first arrival. (a) All agricultural seed, vegetable seed, and...

7 CFR 361.4 - Inspection at the port of first arrival.

Code of Federal Regulations, 2013 CFR

2013-01-01

...) indicates that the screenings are being imported for processing or manufacturing purposes; (4) Seed that is... INSPECTION SERVICE, DEPARTMENT OF AGRICULTURE IMPORTATION OF SEED AND SCREENINGS UNDER THE FEDERAL SEED ACT § 361.4 Inspection at the port of first arrival. (a) All agricultural seed, vegetable seed, and...

7 CFR 361.4 - Inspection at the port of first arrival.

Code of Federal Regulations, 2010 CFR

2010-01-01

...) indicates that the screenings are being imported for processing or manufacturing purposes; (4) Seed that is... INSPECTION SERVICE, DEPARTMENT OF AGRICULTURE IMPORTATION OF SEED AND SCREENINGS UNDER THE FEDERAL SEED ACT § 361.4 Inspection at the port of first arrival. (a) All agricultural seed, vegetable seed, and...

Focusing on Mathematical Arguments

ERIC Educational Resources Information Center

Singletary, Laura M.; Conner, AnnaMarie

2015-01-01

"Collective argumentation" occurs when a group works together to arrive at a conclusion (supporting it with evidence). Simplistically, this occurs when students give answers to questions and tell how they arrived at the answer, perhaps prompted by a teacher. But collective argumentation can be much richer, with a focus on the process of…

InSight Spacecraft Arrival

NASA Image and Video Library

2018-02-28

At Vandenberg Air Force Base in California, NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport, or InSight, spacecraft arrives at the Astrotech processing facility. InSight was developed and built by Lockheed-Martin Space Systems in Denver, Colorado, and is scheduled for liftoff is May 5, 2018. InSight is the first mission to land on Mars and explore the Red Planet's deep interior. It will investigate processes that shaped the rocky planets of the inner solar system including Earth.

Queues with Dropping Functions and General Arrival Processes

PubMed Central

Chydzinski, Andrzej; Mrozowski, Pawel

2016-01-01

In a queueing system with the dropping function the arriving customer can be denied service (dropped) with the probability that is a function of the queue length at the time of arrival of this customer. The potential applicability of such mechanism is very wide due to the fact that by choosing the shape of this function one can easily manipulate several performance characteristics of the queueing system. In this paper we carry out analysis of the queueing system with the dropping function and a very general model of arrival process—the model which includes batch arrivals and the interarrival time autocorrelation, and allows for fitting the actual shape of the interarrival time distribution and its moments. For such a system we obtain formulas for the distribution of the queue length and the overall customer loss ratio. The analytical results are accompanied with numerical examples computed for several dropping functions. PMID:26943171

Saint-Venant end effects for materials with negative Poisson's ratios

NASA Technical Reports Server (NTRS)

Lakes, R. S.

1992-01-01

Results are presented from an analysis of Saint-Venant end effects for materials with negative Poisson's ratio. Examples are presented showing that slow decay of end stress occurs in circular cylinders of negative Poisson's ratio, whereas a sandwich panel containing rigid face sheets and a compliant core exhibits no anomalous effects for negative Poisson's ratio (but exhibits slow stress decay for core Poisson's ratios approaching 0.5). In sand panels with stiff but not perfectly rigid face sheets, a negative Poisson's ratio results in end stress decay, which is faster than it would be otherwise. It is suggested that the slow decay previously predicted for sandwich strips in plane deformation as a result of the geometry can be mitigated by the use of a negative Poisson's ratio material for the core.

Poisson's ratio of fiber-reinforced composites

NASA Astrophysics Data System (ADS)

Christiansson, Henrik; Helsing, Johan

1996-05-01

Poisson's ratio flow diagrams, that is, the Poisson's ratio versus the fiber fraction, are obtained numerically for hexagonal arrays of elastic circular fibers in an elastic matrix. High numerical accuracy is achieved through the use of an interface integral equation method. Questions concerning fixed point theorems and the validity of existing asymptotic relations are investigated and partially resolved. Our findings for the transverse effective Poisson's ratio, together with earlier results for random systems by other authors, make it possible to formulate a general statement for Poisson's ratio flow diagrams: For composites with circular fibers and where the phase Poisson's ratios are equal to 1/3, the system with the lowest stiffness ratio has the highest Poisson's ratio. For other choices of the elastic moduli for the phases, no simple statement can be made.

Statistical properties of a filtered Poisson process with additive random noise: distributions, correlations and moment estimation

NASA Astrophysics Data System (ADS)

Theodorsen, A.; E Garcia, O.; Rypdal, M.

2017-05-01

Filtered Poisson processes are often used as reference models for intermittent fluctuations in physical systems. Such a process is here extended by adding a noise term, either as a purely additive term to the process or as a dynamical term in a stochastic differential equation. The lowest order moments, probability density function, auto-correlation function and power spectral density are derived and used to identify and compare the effects of the two different noise terms. Monte-Carlo studies of synthetic time series are used to investigate the accuracy of model parameter estimation and to identify methods for distinguishing the noise types. It is shown that the probability density function and the three lowest order moments provide accurate estimations of the model parameters, but are unable to separate the noise types. The auto-correlation function and the power spectral density also provide methods for estimating the model parameters, as well as being capable of identifying the noise type. The number of times the signal crosses a prescribed threshold level in the positive direction also promises to be able to differentiate the noise type.

KSC-2014-4488

NASA Image and Video Library

2014-11-13

CAPE CANAVERAL, Fla. – All four of the Magnetospheric Multiscale, or MMS, spacecraft have arrived in the Building 1 high bay of the Astrotech payload processing facility in Titusville, Florida, near Kennedy Space Center. The two MMS spacecraft comprising the upper deck arrived Nov. 12; the two MMS spacecraft comprising the lower stack arrived Oct. 29. The Magnetospheric Multiscale mission is a Solar Terrestrial Probes mission comprising four identically instrumented spacecraft that will use Earth’s magnetosphere as a laboratory to study the microphysics of three fundamental plasma processes: magnetic reconnection, energetic particle acceleration and turbulence. Launch aboard a United Launch Alliance Atlas V rocket from Space Launch Complex 41 on Cape Canaveral Air Force Station is targeted for March 12, 2015. To learn more about MMS, visit http://mms.gsfc.nasa.gov. Photo credit: NASA/Kim Shiflett

Poisson Mixture Regression Models for Heart Disease Prediction.

PubMed

Mufudza, Chipo; Erol, Hamza

2016-01-01

Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model.

Constructions and classifications of projective Poisson varieties.

PubMed

Pym, Brent

2018-01-01

This paper is intended both as an introduction to the algebraic geometry of holomorphic Poisson brackets, and as a survey of results on the classification of projective Poisson manifolds that have been obtained in the past 20 years. It is based on the lecture series delivered by the author at the Poisson 2016 Summer School in Geneva. The paper begins with a detailed treatment of Poisson surfaces, including adjunction, ruled surfaces and blowups, and leading to a statement of the full birational classification. We then describe several constructions of Poisson threefolds, outlining the classification in the regular case, and the case of rank-one Fano threefolds (such as projective space). Following a brief introduction to the notion of Poisson subspaces, we discuss Bondal's conjecture on the dimensions of degeneracy loci on Poisson Fano manifolds. We close with a discussion of log symplectic manifolds with simple normal crossings degeneracy divisor, including a new proof of the classification in the case of rank-one Fano manifolds.

Poisson Mixture Regression Models for Heart Disease Prediction

PubMed Central

Erol, Hamza

2016-01-01

Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model. PMID:27999611

Constructions and classifications of projective Poisson varieties

NASA Astrophysics Data System (ADS)

Pym, Brent

2018-03-01

This paper is intended both as an introduction to the algebraic geometry of holomorphic Poisson brackets, and as a survey of results on the classification of projective Poisson manifolds that have been obtained in the past 20 years. It is based on the lecture series delivered by the author at the Poisson 2016 Summer School in Geneva. The paper begins with a detailed treatment of Poisson surfaces, including adjunction, ruled surfaces and blowups, and leading to a statement of the full birational classification. We then describe several constructions of Poisson threefolds, outlining the classification in the regular case, and the case of rank-one Fano threefolds (such as projective space). Following a brief introduction to the notion of Poisson subspaces, we discuss Bondal's conjecture on the dimensions of degeneracy loci on Poisson Fano manifolds. We close with a discussion of log symplectic manifolds with simple normal crossings degeneracy divisor, including a new proof of the classification in the case of rank-one Fano manifolds.

Statistical distributions of earthquake numbers: consequence of branching process

NASA Astrophysics Data System (ADS)

Kagan, Yan Y.

2010-03-01

We discuss various statistical distributions of earthquake numbers. Previously, we derived several discrete distributions to describe earthquake numbers for the branching model of earthquake occurrence: these distributions are the Poisson, geometric, logarithmic and the negative binomial (NBD). The theoretical model is the `birth and immigration' population process. The first three distributions above can be considered special cases of the NBD. In particular, a point branching process along the magnitude (or log seismic moment) axis with independent events (immigrants) explains the magnitude/moment-frequency relation and the NBD of earthquake counts in large time/space windows, as well as the dependence of the NBD parameters on the magnitude threshold (magnitude of an earthquake catalogue completeness). We discuss applying these distributions, especially the NBD, to approximate event numbers in earthquake catalogues. There are many different representations of the NBD. Most can be traced either to the Pascal distribution or to the mixture of the Poisson distribution with the gamma law. We discuss advantages and drawbacks of both representations for statistical analysis of earthquake catalogues. We also consider applying the NBD to earthquake forecasts and describe the limits of the application for the given equations. In contrast to the one-parameter Poisson distribution so widely used to describe earthquake occurrence, the NBD has two parameters. The second parameter can be used to characterize clustering or overdispersion of a process. We determine the parameter values and their uncertainties for several local and global catalogues, and their subdivisions in various time intervals, magnitude thresholds, spatial windows, and tectonic categories. The theoretical model of how the clustering parameter depends on the corner (maximum) magnitude can be used to predict future earthquake number distribution in regions where very large earthquakes have not yet occurred.

Comment on: 'A Poisson resampling method for simulating reduced counts in nuclear medicine images'.

PubMed

de Nijs, Robin

2015-07-21

In order to be able to calculate half-count images from already acquired data, White and Lawson published their method based on Poisson resampling. They verified their method experimentally by measurements with a Co-57 flood source. In this comment their results are reproduced and confirmed by a direct numerical simulation in Matlab. Not only Poisson resampling, but also two direct redrawing methods were investigated. Redrawing methods were based on a Poisson and a Gaussian distribution. Mean, standard deviation, skewness and excess kurtosis half-count/full-count ratios were determined for all methods, and compared to the theoretical values for a Poisson distribution. Statistical parameters showed the same behavior as in the original note and showed the superiority of the Poisson resampling method. Rounding off before saving of the half count image had a severe impact on counting statistics for counts below 100. Only Poisson resampling was not affected by this, while Gaussian redrawing was less affected by it than Poisson redrawing. Poisson resampling is the method of choice, when simulating half-count (or less) images from full-count images. It simulates correctly the statistical properties, also in the case of rounding off of the images.

Influence of loading and unloading velocity of confining pressure on strength and permeability characteristics of crystalline sandstone

NASA Astrophysics Data System (ADS)

Zhang, Dong-ming; Yang, Yu-shun; Chu, Ya-pei; Zhang, Xiang; Xue, Yan-guang

2018-06-01

The triaxial compression test of crystalline sandstone under different loading and unloading velocity of confining pressure is carried out by using the self-made "THM coupled with servo-controlled seepage apparatus for containing-gas coal", analyzed the strength, deformation and permeability characteristics of the sample, the results show that: with the increase of confining pressures loading-unloading velocity, Mohr's stress circle center of the specimen shift to the right, and the ultimate intensity, peak strain and residual stress of the specimens increase gradually. With the decrease of unloading velocity of confining pressure, the axial strain, the radial strain and the volumetric strain of the sample decrease first and then increases, but the radial strain decreases more greatly. The loading and unloading of confining pressure has greater influence on axial strain of specimens. The deformation modulus decreases rapidly with the increase of axial strain and the Poisson's ratio decreases gradually at the initial stage of loading. When the confining pressure is loaded, the deformation modulus decrease gradually, and the Poisson's ratio increases gradually. When the confining pressure is unloaded, the deformation modulus increase gradually, and the Poisson's ratio decreases gradually. When the specimen reaches the ultimate intensity, the deformation modulus decreases rapidly, while the Poisson's ratio increases rapidly. The fitting curve of the confining pressure and the deformation modulus and the Poisson's ratio in accordance with the distribution of quadratic polynomial function in the loading-unloading confining pressure. There is a corresponding relationship between the evolution of rock permeability and damage deformation during the process of loading and unloading. In the late stage of yielding, the permeability increases slowly, and the permeability increases sharply after the rock sample is destroyed. Fitting the permeability and confining pressure conform to the variation law of the exponential function.

Laser warning receiver to identify the wavelength and angle of arrival of incident laser light

DOEpatents

Sinclair; Michael B.; Sweatt, William C.

2010-03-23

A laser warning receiver is disclosed which has up to hundreds of individual optical channels each optically oriented to receive laser light from a different angle of arrival. Each optical channel has an optical wedge to define the angle of arrival, and a lens to focus the laser light onto a multi-wavelength photodetector for that channel. Each multi-wavelength photodetector has a number of semiconductor layers which are located in a multi-dielectric stack that concentrates the laser light into one of the semiconductor layers according to wavelength. An electrical signal from the multi-wavelength photodetector can be processed to determine both the angle of arrival and the wavelength of the laser light.

Systematic design of 3D auxetic lattice materials with programmable Poisson's ratio for finite strains

NASA Astrophysics Data System (ADS)

Wang, Fengwen

2018-05-01

This paper presents a systematic approach for designing 3D auxetic lattice materials, which exhibit constant negative Poisson's ratios over large strain intervals. A unit cell model mimicking tensile tests is established and based on the proposed model, the secant Poisson's ratio is defined as the negative ratio between the lateral and the longitudinal engineering strains. The optimization problem for designing a material unit cell with a target Poisson's ratio is formulated to minimize the average lateral engineering stresses under the prescribed deformations. Numerical results demonstrate that 3D auxetic lattice materials with constant Poisson's ratios can be achieved by the proposed optimization formulation and that two sets of material architectures are obtained by imposing different symmetry on the unit cell. Moreover, inspired by the topology-optimized material architecture, a subsequent shape optimization is proposed by parametrizing material architectures using super-ellipsoids. By designing two geometrical parameters, simple optimized material microstructures with different target Poisson's ratios are obtained. By interpolating these two parameters as polynomial functions of Poisson's ratios, material architectures for any Poisson's ratio in the interval of ν ∈ [ - 0.78 , 0.00 ] are explicitly presented. Numerical evaluations show that interpolated auxetic lattice materials exhibit constant Poisson's ratios in the target strain interval of [0.00, 0.20] and that 3D auxetic lattice material architectures with programmable Poisson's ratio are achievable.

Nonlinear Poisson equation for heterogeneous media.

PubMed

Hu, Langhua; Wei, Guo-Wei

2012-08-22

The Poisson equation is a widely accepted model for electrostatic analysis. However, the Poisson equation is derived based on electric polarizations in a linear, isotropic, and homogeneous dielectric medium. This article introduces a nonlinear Poisson equation to take into consideration of hyperpolarization effects due to intensive charges and possible nonlinear, anisotropic, and heterogeneous media. Variational principle is utilized to derive the nonlinear Poisson model from an electrostatic energy functional. To apply the proposed nonlinear Poisson equation for the solvation analysis, we also construct a nonpolar solvation energy functional based on the nonlinear Poisson equation by using the geometric measure theory. At a fixed temperature, the proposed nonlinear Poisson theory is extensively validated by the electrostatic analysis of the Kirkwood model and a set of 20 proteins, and the solvation analysis of a set of 17 small molecules whose experimental measurements are also available for a comparison. Moreover, the nonlinear Poisson equation is further applied to the solvation analysis of 21 compounds at different temperatures. Numerical results are compared to theoretical prediction, experimental measurements, and those obtained from other theoretical methods in the literature. A good agreement between our results and experimental data as well as theoretical results suggests that the proposed nonlinear Poisson model is a potentially useful model for electrostatic analysis involving hyperpolarization effects. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Photon statistics in scintillation crystals

NASA Astrophysics Data System (ADS)

Bora, Vaibhav Joga Singh

Scintillation based gamma-ray detectors are widely used in medical imaging, high-energy physics, astronomy and national security. Scintillation gamma-ray detectors are eld-tested, relatively inexpensive, and have good detection eciency. Semi-conductor detectors are gaining popularity because of their superior capability to resolve gamma-ray energies. However, they are relatively hard to manufacture and therefore, at this time, not available in as large formats and much more expensive than scintillation gamma-ray detectors. Scintillation gamma-ray detectors consist of: a scintillator, a material that emits optical (scintillation) photons when it interacts with ionization radiation, and an optical detector that detects the emitted scintillation photons and converts them into an electrical signal. Compared to semiconductor gamma-ray detectors, scintillation gamma-ray detectors have relatively poor capability to resolve gamma-ray energies. This is in large part attributed to the "statistical limit" on the number of scintillation photons. The origin of this statistical limit is the assumption that scintillation photons are either Poisson distributed or super-Poisson distributed. This statistical limit is often dened by the Fano factor. The Fano factor of an integer-valued random process is dened as the ratio of its variance to its mean. Therefore, a Poisson process has a Fano factor of one. The classical theory of light limits the Fano factor of the number of photons to a value greater than or equal to one (Poisson case). However, the quantum theory of light allows for Fano factors to be less than one. We used two methods to look at the correlations between two detectors looking at same scintillation pulse to estimate the Fano factor of the scintillation photons. The relationship between the Fano factor and the correlation between the integral of the two signals detected was analytically derived, and the Fano factor was estimated using the measurements for SrI2:Eu, YAP:Ce and CsI:Na. We also found an empirical relationship between the Fano factor and the covariance as a function of time between two detectors looking at the same scintillation pulse. This empirical model was used to estimate the Fano factor of LaBr3:Ce and YAP:Ce using the experimentally measured timing-covariance. The estimates of the Fano factor from the time-covariance results were consistent with the estimates of the correlation between the integral signals. We found scintillation light from some scintillators to be sub-Poisson. For the same mean number of total scintillation photons, sub-Poisson light has lower noise. We then conducted a simulation study to investigate whether this low-noise sub-Poisson light can be used to improve spatial resolution. We calculated the Cramer-Rao bound for dierent detector geometries, position of interactions and Fano factors. The Cramer-Rao calculations were veried by generating simulated data and estimating the variance of the maximum likelihood estimator. We found that the Fano factor has no impact on the spatial resolution in gamma-ray imaging systems.

KENNEDY SPACE CENTER, FLA. - In the Space Station Processing Facility, Executive Director of NASDA Koji Yamamoto (center) joins others for a tour. Mr. Yamamoto is at KSC for a welcome ceremony involving the arrival of the newest Space Station module, the Japanese Experiment Module/pressurized module.

NASA Image and Video Library

2003-06-12

KENNEDY SPACE CENTER, FLA. - In the Space Station Processing Facility, Executive Director of NASDA Koji Yamamoto (center) joins others for a tour. Mr. Yamamoto is at KSC for a welcome ceremony involving the arrival of the newest Space Station module, the Japanese Experiment Module/pressurized module.

KENNEDY SPACE CENTER, FLA. - In the Space Station Processing Facility, Executive Director of NASDA Koji Yamamoto points to other Space Station elements. Behind him is the Japanese Experiment Module (JEM)/pressurized module. Mr. Yamamoto is at KSC for a welcome ceremony involving the arrival of JEM.

NASA Image and Video Library

2003-06-12

KENNEDY SPACE CENTER, FLA. - In the Space Station Processing Facility, Executive Director of NASDA Koji Yamamoto points to other Space Station elements. Behind him is the Japanese Experiment Module (JEM)/pressurized module. Mr. Yamamoto is at KSC for a welcome ceremony involving the arrival of JEM.

InSight Spacecraft Arrival

NASA Image and Video Library

2018-02-28

After arrival at Vandenberg Air Force Base in California, ground crews prepare NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport, or InSight, spacecraft for transportation to the Astrotech processing facility. InSight was developed and built by Lockheed-Martin Space Systems in Denver, Colorado, and is scheduled for liftoff is May 5, 2018. InSight is the first mission to explore the deep interior of Mars. It will investigate processes that shaped the rocky planets of the inner solar system including Earth.

Earthquake number forecasts testing

NASA Astrophysics Data System (ADS)

Kagan, Yan Y.

2017-10-01

We study the distributions of earthquake numbers in two global earthquake catalogues: Global Centroid-Moment Tensor and Preliminary Determinations of Epicenters. The properties of these distributions are especially required to develop the number test for our forecasts of future seismic activity rate, tested by the Collaboratory for Study of Earthquake Predictability (CSEP). A common assumption, as used in the CSEP tests, is that the numbers are described by the Poisson distribution. It is clear, however, that the Poisson assumption for the earthquake number distribution is incorrect, especially for the catalogues with a lower magnitude threshold. In contrast to the one-parameter Poisson distribution so widely used to describe earthquake occurrences, the negative-binomial distribution (NBD) has two parameters. The second parameter can be used to characterize the clustering or overdispersion of a process. We also introduce and study a more complex three-parameter beta negative-binomial distribution. We investigate the dependence of parameters for both Poisson and NBD distributions on the catalogue magnitude threshold and on temporal subdivision of catalogue duration. First, we study whether the Poisson law can be statistically rejected for various catalogue subdivisions. We find that for most cases of interest, the Poisson distribution can be shown to be rejected statistically at a high significance level in favour of the NBD. Thereafter, we investigate whether these distributions fit the observed distributions of seismicity. For this purpose, we study upper statistical moments of earthquake numbers (skewness and kurtosis) and compare them to the theoretical values for both distributions. Empirical values for the skewness and the kurtosis increase for the smaller magnitude threshold and increase with even greater intensity for small temporal subdivision of catalogues. The Poisson distribution for large rate values approaches the Gaussian law, therefore its skewness and kurtosis both tend to zero for large earthquake rates: for the Gaussian law, these values are identically zero. A calculation of the NBD skewness and kurtosis levels based on the values of the first two statistical moments of the distribution, shows rapid increase of these upper moments levels. However, the observed catalogue values of skewness and kurtosis are rising even faster. This means that for small time intervals, the earthquake number distribution is even more heavy-tailed than the NBD predicts. Therefore for small time intervals, we propose using empirical number distributions appropriately smoothed for testing forecasted earthquake numbers.

Stochastic foundations of undulatory transport phenomena: generalized Poisson-Kac processes—part III extensions and applications to kinetic theory and transport

NASA Astrophysics Data System (ADS)

Giona, Massimiliano; Brasiello, Antonio; Crescitelli, Silvestro

2017-08-01

This third part extends the theory of Generalized Poisson-Kac (GPK) processes to nonlinear stochastic models and to a continuum of states. Nonlinearity is treated in two ways: (i) as a dependence of the parameters (intensity of the stochastic velocity, transition rates) of the stochastic perturbation on the state variable, similarly to the case of nonlinear Langevin equations, and (ii) as the dependence of the stochastic microdynamic equations of motion on the statistical description of the process itself (nonlinear Fokker-Planck-Kac models). Several numerical and physical examples illustrate the theory. Gathering nonlinearity and a continuum of states, GPK theory provides a stochastic derivation of the nonlinear Boltzmann equation, furnishing a positive answer to the Kac’s program in kinetic theory. The transition from stochastic microdynamics to transport theory within the framework of the GPK paradigm is also addressed.

On the statistical properties of viral misinformation in online social media

NASA Astrophysics Data System (ADS)

Bessi, Alessandro

2017-03-01

The massive diffusion of online social media allows for the rapid and uncontrolled spreading of conspiracy theories, hoaxes, unsubstantiated claims, and false news. Such an impressive amount of misinformation can influence policy preferences and encourage behaviors strongly divergent from recommended practices. In this paper, we study the statistical properties of viral misinformation in online social media. By means of methods belonging to Extreme Value Theory, we show that the number of extremely viral posts over time follows a homogeneous Poisson process, and that the interarrival times between such posts are independent and identically distributed, following an exponential distribution. Moreover, we characterize the uncertainty around the rate parameter of the Poisson process through Bayesian methods. Finally, we are able to derive the predictive posterior probability distribution of the number of posts exceeding a certain threshold of shares over a finite interval of time.

A preliminary analysis of quantifying computer security vulnerability data in "the wild"

NASA Astrophysics Data System (ADS)

Farris, Katheryn A.; McNamara, Sean R.; Goldstein, Adam; Cybenko, George

2016-05-01

A system of computers, networks and software has some level of vulnerability exposure that puts it at risk to criminal hackers. Presently, most vulnerability research uses data from software vendors, and the National Vulnerability Database (NVD). We propose an alternative path forward through grounding our analysis in data from the operational information security community, i.e. vulnerability data from "the wild". In this paper, we propose a vulnerability data parsing algorithm and an in-depth univariate and multivariate analysis of the vulnerability arrival and deletion process (also referred to as the vulnerability birth-death process). We find that vulnerability arrivals are best characterized by the log-normal distribution and vulnerability deletions are best characterized by the exponential distribution. These distributions can serve as prior probabilities for future Bayesian analysis. We also find that over 22% of the deleted vulnerability data have a rate of zero, and that the arrival vulnerability data is always greater than zero. Finally, we quantify and visualize the dependencies between vulnerability arrivals and deletions through a bivariate scatterplot and statistical observations.

Poisson Noise Removal in Spherical Multichannel Images: Application to Fermi data

NASA Astrophysics Data System (ADS)

Schmitt, Jérémy; Starck, Jean-Luc; Fadili, Jalal; Digel, Seth

2012-03-01

The Fermi Gamma-ray Space Telescope, which was launched by NASA in June 2008, is a powerful space observatory which studies the high-energy gamma-ray sky [5]. Fermi's main instrument, the Large Area Telescope (LAT), detects photons in an energy range between 20MeV and >300 GeV. The LAT is much more sensitive than its predecessor, the energetic gamma ray experiment telescope (EGRET) telescope on the Compton Gamma-ray Observatory, and is expected to find several thousand gamma-ray point sources, which is an order of magnitude more than its predecessor EGRET [13]. Even with its relatively large acceptance (∼2m2 sr), the number of photons detected by the LAT outside the Galactic plane and away from intense sources is relatively low and the sky overall has a diffuse glow from cosmic-ray interactions with interstellar gas and low energy photons that makes a background against which point sources need to be detected. In addition, the per-photon angular resolution of the LAT is relatively poor and strongly energy dependent, ranging from>10° at 20MeV to ∼0.1° above 100 GeV. Consequently, the spherical photon count images obtained by Fermi are degraded by the fluctuations on the number of detected photons. This kind of noise is strongly signal dependent : on the brightest parts of the image like the galactic plane or the brightest sources, we have a lot of photons per pixel, and so the photon noise is low. Outside the galactic plane, the number of photons per pixel is low, which means that the photon noise is high. Such a signal-dependent noise cannot be accurately modeled by a Gaussian distribution. The basic photon-imaging model assumes that the number of detected photons at each pixel location is Poisson distributed. More specifically, the image is considered as a realization of an inhomogeneous Poisson process. This statistical noise makes the source detection more difficult, consequently it is highly desirable to have an efficient denoising method for spherical Poisson data. Several techniques have been proposed in the literature to estimate Poisson intensity in 2-dimensional (2D). A major class of methods adopt a multiscale Bayesian framework specifically tailored for Poisson data [18], independently initiated by Timmerman and Nowak [23] and Kolaczyk [14]. Lefkimmiaits et al. [15] proposed an improved Bayesian framework for analyzing Poisson processes, based on a multiscale representation of the Poisson process in which the ratios of the underlying Poisson intensities in adjacent scales are modeled as mixtures of conjugate parametric distributions. Another approach includes preprocessing the count data by a variance stabilizing transform(VST) such as theAnscombe [4] and the Fisz [10] transforms, applied respectively in the spatial [8] or in the wavelet domain [11]. The transform reforms the data so that the noise approximately becomes Gaussian with a constant variance. Standard techniques for independent identically distributed Gaussian noise are then used for denoising. Zhang et al. [25] proposed a powerful method called multiscale (MS-VST). It consists in combining a VST with a multiscale transform (wavelets, ridgelets, or curvelets), yielding asymptotically normally distributed coefficients with known variances. The interest of using a multiscale method is to exploit the sparsity properties of the data : the data are transformed into a domain in which it is sparse, and, as the noise is not sparse in any transform domain, it is easy to separate it from the signal. When the noise is Gaussian of known variance, it is easy to remove it with a high thresholding in the wavelet domain. The choice of the multiscale transform depends on the morphology of the data. Wavelets represent more efficiently regular structures and isotropic singularities, whereas ridgelets are designed to represent global lines in an image, and curvelets represent efficiently curvilinear contours. Significant coefficients are then detected with binary hypothesis testing, and the final estimate is reconstructed with an iterative scheme. In Ref

Unimodularity criteria for Poisson structures on foliated manifolds

NASA Astrophysics Data System (ADS)

Pedroza, Andrés; Velasco-Barreras, Eduardo; Vorobiev, Yury

2018-03-01

We study the behavior of the modular class of an orientable Poisson manifold and formulate some unimodularity criteria in the semilocal context, around a (singular) symplectic leaf. Our results generalize some known unimodularity criteria for regular Poisson manifolds related to the notion of the Reeb class. In particular, we show that the unimodularity of the transverse Poisson structure of the leaf is a necessary condition for the semilocal unimodular property. Our main tool is an explicit formula for a bigraded decomposition of modular vector fields of a coupling Poisson structure on a foliated manifold. Moreover, we also exploit the notion of the modular class of a Poisson foliation and its relationship with the Reeb class.

A test of inflated zeros for Poisson regression models.

PubMed

He, Hua; Zhang, Hui; Ye, Peng; Tang, Wan

2017-01-01

Excessive zeros are common in practice and may cause overdispersion and invalidate inference when fitting Poisson regression models. There is a large body of literature on zero-inflated Poisson models. However, methods for testing whether there are excessive zeros are less well developed. The Vuong test comparing a Poisson and a zero-inflated Poisson model is commonly applied in practice. However, the type I error of the test often deviates seriously from the nominal level, rendering serious doubts on the validity of the test in such applications. In this paper, we develop a new approach for testing inflated zeros under the Poisson model. Unlike the Vuong test for inflated zeros, our method does not require a zero-inflated Poisson model to perform the test. Simulation studies show that when compared with the Vuong test our approach not only better at controlling type I error rate, but also yield more power.

Variance to mean ratio, R(t), for poisson processes on phylogenetic trees.

PubMed

Goldman, N

1994-09-01

The ratio of expected variance to mean, R(t), of numbers of DNA base substitutions for contemporary sequences related by a "star" phylogeny is widely seen as a measure of the adherence of the sequences' evolution to a Poisson process with a molecular clock, as predicted by the "neutral theory" of molecular evolution under certain conditions. A number of estimators of R(t) have been proposed, all predicted to have mean 1 and distributions based on the chi 2. Various genes have previously been analyzed and found to have values of R(t) far in excess of 1, calling into question important aspects of the neutral theory. In this paper, I use Monte Carlo simulation to show that the previously suggested means and distributions of estimators of R(t) are highly inaccurate. The analysis is applied to star phylogenies and to general phylogenetic trees, and well-known gene sequences are reanalyzed. For star phylogenies the results show that Kimura's estimators ("The Neutral Theory of Molecular Evolution," Cambridge Univ. Press, Cambridge, 1983) are unsatisfactory for statistical testing of R(t), but confirm the accuracy of Bulmer's correction factor (Genetics 123: 615-619, 1989). For all three nonstar phylogenies studied, attained values of all three estimators of R(t), although larger than 1, are within their true confidence limits under simple Poisson process models. This shows that lineage effects can be responsible for high estimates of R(t), restoring some limited confidence in the molecular clock and showing that the distinction between lineage and molecular clock effects is vital.(ABSTRACT TRUNCATED AT 250 WORDS)

Double-observer line transect surveys with Markov-modulated Poisson process models for animal availability.

PubMed

Borchers, D L; Langrock, R

2015-12-01

We develop maximum likelihood methods for line transect surveys in which animals go undetected at distance zero, either because they are stochastically unavailable while within view or because they are missed when they are available. These incorporate a Markov-modulated Poisson process model for animal availability, allowing more clustered availability events than is possible with Poisson availability models. They include a mark-recapture component arising from the independent-observer survey, leading to more accurate estimation of detection probability given availability. We develop models for situations in which (a) multiple detections of the same individual are possible and (b) some or all of the availability process parameters are estimated from the line transect survey itself, rather than from independent data. We investigate estimator performance by simulation, and compare the multiple-detection estimators with estimators that use only initial detections of individuals, and with a single-observer estimator. Simultaneous estimation of detection function parameters and availability model parameters is shown to be feasible from the line transect survey alone with multiple detections and double-observer data but not with single-observer data. Recording multiple detections of individuals improves estimator precision substantially when estimating the availability model parameters from survey data, and we recommend that these data be gathered. We apply the methods to estimate detection probability from a double-observer survey of North Atlantic minke whales, and find that double-observer data greatly improve estimator precision here too. © 2015 The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.

Health inequality between immigrants and natives in Spain: the loss of the healthy immigrant effect in times of economic crisis.

PubMed

Gotsens, Mercè; Malmusi, Davide; Villarroel, Nazmy; Vives-Cases, Carmen; Garcia-Subirats, Irene; Hernando, Cristina; Borrell, Carme

2015-12-01

The immigrant population living in Spain grew exponentially in the early 2000s but has been particularly affected by the economic crisis. This study aims to analyse health inequalities between immigrants born in middle- or low-income countries and natives in Spain, in 2006 and 2012, taking into account gender, year of arrival and socioeconomic exposures. Study of trends using two cross-sections, the 2006 and 2012 editions of the Spanish National Health Survey, including residents in Spain aged 15-64 years (20 810 natives and 2950 immigrants in 2006, 14 291 natives and 2448 immigrants in 2012). Fair/poor self-rated health, poor mental health (GHQ-12 > 2), chronic activity limitation and use of psychotropic drugs were compared between natives and immigrants who arrived in Spain before 2006, adjusting robust Poisson regression models for age and socioeconomic variables to obtain prevalence ratios (PR) and 95% confidence interval (CI). Inequalities in poor self-rated health between immigrants and natives tend to increase among women (age-adjusted PR2006 = 1.39; 95% CI: 1.24-1.56, PR2012 = 1.56; 95% CI: 1.33-1.82). Among men, there is a new onset of inequalities in poor mental health (PR2006 = 1.10; 95% CI: 0.86-1.40, PR2012 = 1.34; 95% CI: 1.06-1.69) and an equalization of the previously lower use of psychotropic drugs (PR2006 = 0.22; 95% CI: 0.11-0.43, PR2012 = 1.20; 95% CI: 0.73-2.01). Between 2006 and 2012, immigrants who arrived in Spain before 2006 appeared to worsen their health status when compared with natives. The loss of the healthy immigrant effect in the context of a worse impact of the economic crisis on immigrants appears as potential explanation. Employment, social protection and re-universalization of healthcare would prevent further deterioration of immigrants' health status. © The Author 2015. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

Protein-ion binding process on finite macromolecular concentration. A Poisson-Boltzmann and Monte Carlo study.

PubMed

de Carvalho, Sidney Jurado; Fenley, Márcia O; da Silva, Fernando Luís Barroso

2008-12-25

Electrostatic interactions are one of the key driving forces for protein-ligands complexation. Different levels for the theoretical modeling of such processes are available on the literature. Most of the studies on the Molecular Biology field are performed within numerical solutions of the Poisson-Boltzmann Equation and the dielectric continuum models framework. In such dielectric continuum models, there are two pivotal questions: (a) how the protein dielectric medium should be modeled, and (b) what protocol should be used when solving this effective Hamiltonian. By means of Monte Carlo (MC) and Poisson-Boltzmann (PB) calculations, we define the applicability of the PB approach with linear and nonlinear responses for macromolecular electrostatic interactions in electrolyte solution, revealing some physical mechanisms and limitations behind it especially due the raise of both macromolecular charge and concentration out of the strong coupling regime. A discrepancy between PB and MC for binding constant shifts is shown and explained in terms of the manner PB approximates the excess chemical potentials of the ligand, and not as a consequence of the nonlinear thermal treatment and/or explicit ion-ion interactions as it could be argued. Our findings also show that the nonlinear PB predictions with a low dielectric response well reproduce the pK shifts calculations carried out with an uniform dielectric model. This confirms and completes previous results obtained by both MC and linear PB calculations.

Poisson's Ratio of a Hyperelastic Foam Under Quasi-static and Dynamic Loading

DOE PAGES

Sanborn, Brett; Song, Bo

2018-06-03

Poisson's ratio is a material constant representing compressibility of material volume. However, when soft, hyperelastic materials such as silicone foam are subjected to large deformation into densification, the Poisson's ratio may rather significantly change, which warrants careful consideration in modeling and simulation of impact/shock mitigation scenarios where foams are used as isolators. The evolution of Poisson's ratio of silicone foam materials has not yet been characterized, particularly under dynamic loading. In this study, radial and axial measurements of specimen strain are conducted simultaneously during quasi-static and dynamic compression tests to determine the Poisson's ratio of silicone foam. The Poisson's ratiomore » of silicone foam exhibited a transition from compressible to nearly incompressible at a threshold strain that coincided with the onset of densification in the material. Poisson's ratio as a function of engineering strain was different at quasi-static and dynamic rates. Here, the Poisson's ratio behavior is presented and can be used to improve constitutive modeling of silicone foams subjected to a broad range of mechanical loading.« less

Poisson's Ratio of a Hyperelastic Foam Under Quasi-static and Dynamic Loading

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanborn, Brett; Song, Bo

Poisson's ratio is a material constant representing compressibility of material volume. However, when soft, hyperelastic materials such as silicone foam are subjected to large deformation into densification, the Poisson's ratio may rather significantly change, which warrants careful consideration in modeling and simulation of impact/shock mitigation scenarios where foams are used as isolators. The evolution of Poisson's ratio of silicone foam materials has not yet been characterized, particularly under dynamic loading. In this study, radial and axial measurements of specimen strain are conducted simultaneously during quasi-static and dynamic compression tests to determine the Poisson's ratio of silicone foam. The Poisson's ratiomore » of silicone foam exhibited a transition from compressible to nearly incompressible at a threshold strain that coincided with the onset of densification in the material. Poisson's ratio as a function of engineering strain was different at quasi-static and dynamic rates. Here, the Poisson's ratio behavior is presented and can be used to improve constitutive modeling of silicone foams subjected to a broad range of mechanical loading.« less

Reducing time-to-unit among patients referred to an outpatient stroke assessment unit with a novel triage process: a prospective cohort study.

PubMed

Bibok, Maximilian B; Votova, Kristine; Balshaw, Robert F; Lesperance, Mary L; Croteau, Nicole S; Trivedi, Anurag; Morrison, Jaclyn; Sedgwick, Colin; Penn, Andrew M

2018-02-27

To evaluate the performance of a novel triage system for Transient Ischemic Attack (TIA) units built upon an existent clinical prediction rule (CPR) to reduce time to unit arrival, relative to the time of symptom onset, for true TIA and minor stroke patients. Differentiating between true and false TIA/minor stroke cases (mimics) is necessary for effective triage as medical intervention for true TIA/minor stroke is time-sensitive and TIA unit spots are a finite resource. Prospective cohort study design utilizing patient referral data and TIA unit arrival times from a regional fast-track TIA unit on Vancouver Island, Canada, accepting referrals from emergency departments (ED) and general practice (GP). Historical referral cohort (N = 2942) from May 2013-Oct 2014 was triaged using the ABCD2 score; prospective referral cohort (N = 2929) from Nov 2014-Apr 2016 was triaged using the novel system. A retrospective survival curve analysis, censored at 28 days to unit arrival, was used to compare days to unit arrival from event date between cohort patients matched by low (0-3), moderate (4-5) and high (6-7) ABCD2 scores. Survival curve analysis indicated that using the novel triage system, prospectively referred TIA/minor stroke patients with low and moderate ABCD2 scores arrived at the unit 2 and 1 day earlier than matched historical patients, respectively. The novel triage process is associated with a reduction in time to unit arrival from symptom onset for referred true TIA/minor stroke patients with low and moderate ABCD2 scores.

Modelling on optimal portfolio with exchange rate based on discontinuous stochastic process

NASA Astrophysics Data System (ADS)

Yan, Wei; Chang, Yuwen

2016-12-01

Considering the stochastic exchange rate, this paper is concerned with the dynamic portfolio selection in financial market. The optimal investment problem is formulated as a continuous-time mathematical model under mean-variance criterion. These processes follow jump-diffusion processes (Weiner process and Poisson process). Then the corresponding Hamilton-Jacobi-Bellman(HJB) equation of the problem is presented and its efferent frontier is obtained. Moreover, the optimal strategy is also derived under safety-first criterion.

A multiscale filter for noise reduction of low-dose cone beam projections

NASA Astrophysics Data System (ADS)

Yao, Weiguang; Farr, Jonathan B.

2015-08-01

The Poisson or compound Poisson process governs the randomness of photon fluence in cone beam computed tomography (CBCT) imaging systems. The probability density function depends on the mean (noiseless) of the fluence at a certain detector. This dependence indicates the natural requirement of multiscale filters to smooth noise while preserving structures of the imaged object on the low-dose cone beam projection. In this work, we used a Gaussian filter, \\text{exp}≤ft(-{{x}2}/2σ f2\\right) as the multiscale filter to de-noise the low-dose cone beam projections. We analytically obtained the expression of {σf} , which represents the scale of the filter, by minimizing local noise-to-signal ratio. We analytically derived the variance of residual noise from the Poisson or compound Poisson processes after Gaussian filtering. From the derived analytical form of the variance of residual noise, optimal σ f2 is proved to be proportional to the noiseless fluence and modulated by local structure strength expressed as the linear fitting error of the structure. A strategy was used to obtain the reliable linear fitting error: smoothing the projection along the longitudinal direction to calculate the linear fitting error along the lateral direction and vice versa. The performance of our multiscale filter was examined on low-dose cone beam projections of a Catphan phantom and a head-and-neck patient. After performing the filter on the Catphan phantom projections scanned with pulse time 4 ms, the number of visible line pairs was similar to that scanned with 16 ms, and the contrast-to-noise ratio of the inserts was higher than that scanned with 16 ms about 64% in average. For the simulated head-and-neck patient projections with pulse time 4 ms, the visibility of soft tissue structures in the patient was comparable to that scanned with 20 ms. The image processing took less than 0.5 s per projection with 1024   ×   768 pixels.

Application of the Hyper-Poisson Generalized Linear Model for Analyzing Motor Vehicle Crashes.

PubMed

Khazraee, S Hadi; Sáez-Castillo, Antonio Jose; Geedipally, Srinivas Reddy; Lord, Dominique

2015-05-01

The hyper-Poisson distribution can handle both over- and underdispersion, and its generalized linear model formulation allows the dispersion of the distribution to be observation-specific and dependent on model covariates. This study's objective is to examine the potential applicability of a newly proposed generalized linear model framework for the hyper-Poisson distribution in analyzing motor vehicle crash count data. The hyper-Poisson generalized linear model was first fitted to intersection crash data from Toronto, characterized by overdispersion, and then to crash data from railway-highway crossings in Korea, characterized by underdispersion. The results of this study are promising. When fitted to the Toronto data set, the goodness-of-fit measures indicated that the hyper-Poisson model with a variable dispersion parameter provided a statistical fit as good as the traditional negative binomial model. The hyper-Poisson model was also successful in handling the underdispersed data from Korea; the model performed as well as the gamma probability model and the Conway-Maxwell-Poisson model previously developed for the same data set. The advantages of the hyper-Poisson model studied in this article are noteworthy. Unlike the negative binomial model, which has difficulties in handling underdispersed data, the hyper-Poisson model can handle both over- and underdispersed crash data. Although not a major issue for the Conway-Maxwell-Poisson model, the effect of each variable on the expected mean of crashes is easily interpretable in the case of this new model. © 2014 Society for Risk Analysis.

Tailpulse signal generator

DOEpatents

Baker, John [Walnut Creek, CA; Archer, Daniel E [Knoxville, TN; Luke, Stanley John [Pleasanton, CA; Decman, Daniel J [Livermore, CA; White, Gregory K [Livermore, CA

2009-06-23

A tailpulse signal generating/simulating apparatus, system, and method designed to produce electronic pulses which simulate tailpulses produced by a gamma radiation detector, including the pileup effect caused by the characteristic exponential decay of the detector pulses, and the random Poisson distribution pulse timing for radioactive materials. A digital signal process (DSP) is programmed and configured to produce digital values corresponding to pseudo-randomly selected pulse amplitudes and pseudo-randomly selected Poisson timing intervals of the tailpulses. Pulse amplitude values are exponentially decayed while outputting the digital value to a digital to analog converter (DAC). And pulse amplitudes of new pulses are added to decaying pulses to simulate the pileup effect for enhanced realism in the simulation.

Deformation mechanisms in negative Poisson's ratio materials - Structural aspects

NASA Technical Reports Server (NTRS)

Lakes, R.

1991-01-01

Poisson's ratio in materials is governed by the following aspects of the microstructure: the presence of rotational degrees of freedom, non-affine deformation kinematics, or anisotropic structure. Several structural models are examined. The non-affine kinematics are seen to be essential for the production of negative Poisson's ratios for isotropic materials containing central force linkages of positive stiffness. Non-central forces combined with pre-load can also give rise to a negative Poisson's ratio in isotropic materials. A chiral microstructure with non-central force interaction or non-affine deformation can also exhibit a negative Poisson's ratio. Toughness and damage resistance in these materials may be affected by the Poisson's ratio itself, as well as by generalized continuum aspects associated with the microstructure.

Officials welcome the arrival of the Japanese Experiment Module

NASA Image and Video Library

2007-04-17

In the Space Station Processing Facility, astronaut Takao Doi (left) and Commander Dominic Gorie pose in front of the Experiment Logistics Module Pressurized Section for the Japanese Experiment Module, or JEM, that recently arrived at Kennedy. Doi and Gorie are crew members for mission STS-123 that will deliver the logistics module to the International Space Station. Earlier, NASA and Japanese Aerospace and Exploration Agency (JAXA) officials welcomed the arrival of the module. The new International Space Station component arrived at Kennedy March 12 to begin preparations for its future launch on mission STS-123. It will serve as an on-orbit storage area for materials, tools and supplies. It can hold up to eight experiment racks and will attach to the top of another larger pressurized module.

Applications of MMPBSA to Membrane Proteins I: Efficient Numerical Solutions of Periodic Poisson-Boltzmann Equation

PubMed Central

Botello-Smith, Wesley M.; Luo, Ray

2016-01-01

Continuum solvent models have been widely used in biomolecular modeling applications. Recently much attention has been given to inclusion of implicit membrane into existing continuum Poisson-Boltzmann solvent models to extend their applications to membrane systems. Inclusion of an implicit membrane complicates numerical solutions of the underlining Poisson-Boltzmann equation due to the dielectric inhomogeneity on the boundary surfaces of a computation grid. This can be alleviated by the use of the periodic boundary condition, a common practice in electrostatic computations in particle simulations. The conjugate gradient and successive over-relaxation methods are relatively straightforward to be adapted to periodic calculations, but their convergence rates are quite low, limiting their applications to free energy simulations that require a large number of conformations to be processed. To accelerate convergence, the Incomplete Cholesky preconditioning and the geometric multi-grid methods have been extended to incorporate periodicity for biomolecular applications. Impressive convergence behaviors were found as in the previous applications of these numerical methods to tested biomolecules and MMPBSA calculations. PMID:26389966

Guia para su incorporacion a los Estados Unidos de America (A Guide to Resettlement in the United States. Spanish).

ERIC Educational Resources Information Center

Center for Applied Linguistics, Washington, DC. Refugee Service Center.

This resettlement guide, entirely in Spanish, describes the initial stage of resettlement and the processes that refugees undergo as new arrivals. Subjects covered in this guide include pre-arrival procedures, admissions criteria, immigrant's statement of understanding, travel costs and U.S. Customs; resettlement procedures, immigrants'…

Block and Thread Intercultural Narratives and Positioning: Conversations with Newly Arrived Postgraduate Students

ERIC Educational Resources Information Center

Amadasi, Sara; Holliday, Adrian

2017-01-01

This paper considers how, in the process of positioning that is implicit in every interaction, all of us employ multiple and often competing narratives when we talk about cultural identity and our relationships with new cultural environments. In interviews with newly arrived postgraduate students about their experience of travelling to study…

Kennedy Marks 20th Anniversary of Cassini Arrival

NASA Image and Video Library

2017-04-20

NASA's Cassini spacecraft arrived at Kennedy Space Center 20 years ago to begin processing for launch on a mission that would see it deliver spectacular images and data from the ringed planet Saturn. As the massive spacecraft begins its final chapter, engineers at Kennedy took a look back to how their contributions to the mission began.

A Model of Batch Scheduling for a Single Batch Processor with Additional Setups to Minimize Total Inventory Holding Cost of Parts of a Single Item Requested at Multi-due-date

NASA Astrophysics Data System (ADS)

Hakim Halim, Abdul; Ernawati; Hidayat, Nita P. A.

2018-03-01

This paper deals with a model of batch scheduling for a single batch processor on which a number of parts of a single items are to be processed. The process needs two kinds of setups, i. e., main setups required before processing any batches, and additional setups required repeatedly after the batch processor completes a certain number of batches. The parts to be processed arrive at the shop floor at the times coinciding with their respective starting times of processing, and the completed parts are to be delivered at multiple due dates. The objective adopted for the model is that of minimizing total inventory holding cost consisting of holding cost per unit time for a part in completed batches, and that in in-process batches. The formulation of total inventory holding cost is derived from the so-called actual flow time defined as the interval between arrival times of parts at the production line and delivery times of the completed parts. The actual flow time satisfies not only minimum inventory but also arrival and delivery just in times. An algorithm to solve the model is proposed and a numerical example is shown.

Slow diffusion by Markov random flights

NASA Astrophysics Data System (ADS)

Kolesnik, Alexander D.

2018-06-01

We present a conception of the slow diffusion processes in the Euclidean spaces Rm , m ≥ 1, based on the theory of random flights with small constant speed that are driven by a homogeneous Poisson process of small rate. The slow diffusion condition that, on long time intervals, leads to the stationary distributions, is given. The stationary distributions of slow diffusion processes in some Euclidean spaces of low dimensions, are presented.

Fuzzy classifier based support vector regression framework for Poisson ratio determination

NASA Astrophysics Data System (ADS)

Asoodeh, Mojtaba; Bagheripour, Parisa

2013-09-01

Poisson ratio is considered as one of the most important rock mechanical properties of hydrocarbon reservoirs. Determination of this parameter through laboratory measurement is time, cost, and labor intensive. Furthermore, laboratory measurements do not provide continuous data along the reservoir intervals. Hence, a fast, accurate, and inexpensive way of determining Poisson ratio which produces continuous data over the whole reservoir interval is desirable. For this purpose, support vector regression (SVR) method based on statistical learning theory (SLT) was employed as a supervised learning algorithm to estimate Poisson ratio from conventional well log data. SVR is capable of accurately extracting the implicit knowledge contained in conventional well logs and converting the gained knowledge into Poisson ratio data. Structural risk minimization (SRM) principle which is embedded in the SVR structure in addition to empirical risk minimization (EMR) principle provides a robust model for finding quantitative formulation between conventional well log data and Poisson ratio. Although satisfying results were obtained from an individual SVR model, it had flaws of overestimation in low Poisson ratios and underestimation in high Poisson ratios. These errors were eliminated through implementation of fuzzy classifier based SVR (FCBSVR). The FCBSVR significantly improved accuracy of the final prediction. This strategy was successfully applied to data from carbonate reservoir rocks of an Iranian Oil Field. Results indicated that SVR predicted Poisson ratio values are in good agreement with measured values.

Performance of the modified Poisson regression approach for estimating relative risks from clustered prospective data.

PubMed

Yelland, Lisa N; Salter, Amy B; Ryan, Philip

2011-10-15

Modified Poisson regression, which combines a log Poisson regression model with robust variance estimation, is a useful alternative to log binomial regression for estimating relative risks. Previous studies have shown both analytically and by simulation that modified Poisson regression is appropriate for independent prospective data. This method is often applied to clustered prospective data, despite a lack of evidence to support its use in this setting. The purpose of this article is to evaluate the performance of the modified Poisson regression approach for estimating relative risks from clustered prospective data, by using generalized estimating equations to account for clustering. A simulation study is conducted to compare log binomial regression and modified Poisson regression for analyzing clustered data from intervention and observational studies. Both methods generally perform well in terms of bias, type I error, and coverage. Unlike log binomial regression, modified Poisson regression is not prone to convergence problems. The methods are contrasted by using example data sets from 2 large studies. The results presented in this article support the use of modified Poisson regression as an alternative to log binomial regression for analyzing clustered prospective data when clustering is taken into account by using generalized estimating equations.

A generalized Poisson and Poisson-Boltzmann solver for electrostatic environments.

PubMed

Fisicaro, G; Genovese, L; Andreussi, O; Marzari, N; Goedecker, S

2016-01-07

The computational study of chemical reactions in complex, wet environments is critical for applications in many fields. It is often essential to study chemical reactions in the presence of applied electrochemical potentials, taking into account the non-trivial electrostatic screening coming from the solvent and the electrolytes. As a consequence, the electrostatic potential has to be found by solving the generalized Poisson and the Poisson-Boltzmann equations for neutral and ionic solutions, respectively. In the present work, solvers for both problems have been developed. A preconditioned conjugate gradient method has been implemented for the solution of the generalized Poisson equation and the linear regime of the Poisson-Boltzmann, allowing to solve iteratively the minimization problem with some ten iterations of the ordinary Poisson equation solver. In addition, a self-consistent procedure enables us to solve the non-linear Poisson-Boltzmann problem. Both solvers exhibit very high accuracy and parallel efficiency and allow for the treatment of periodic, free, and slab boundary conditions. The solver has been integrated into the BigDFT and Quantum-ESPRESSO electronic-structure packages and will be released as an independent program, suitable for integration in other codes.

A Review of Multivariate Distributions for Count Data Derived from the Poisson Distribution.

PubMed

Inouye, David; Yang, Eunho; Allen, Genevera; Ravikumar, Pradeep

2017-01-01

The Poisson distribution has been widely studied and used for modeling univariate count-valued data. Multivariate generalizations of the Poisson distribution that permit dependencies, however, have been far less popular. Yet, real-world high-dimensional count-valued data found in word counts, genomics, and crime statistics, for example, exhibit rich dependencies, and motivate the need for multivariate distributions that can appropriately model this data. We review multivariate distributions derived from the univariate Poisson, categorizing these models into three main classes: 1) where the marginal distributions are Poisson, 2) where the joint distribution is a mixture of independent multivariate Poisson distributions, and 3) where the node-conditional distributions are derived from the Poisson. We discuss the development of multiple instances of these classes and compare the models in terms of interpretability and theory. Then, we empirically compare multiple models from each class on three real-world datasets that have varying data characteristics from different domains, namely traffic accident data, biological next generation sequencing data, and text data. These empirical experiments develop intuition about the comparative advantages and disadvantages of each class of multivariate distribution that was derived from the Poisson. Finally, we suggest new research directions as explored in the subsequent discussion section.

Application of zero-inflated poisson mixed models in prognostic factors of hepatitis C.

PubMed

Akbarzadeh Baghban, Alireza; Pourhoseingholi, Asma; Zayeri, Farid; Jafari, Ali Akbar; Alavian, Seyed Moayed

2013-01-01

In recent years, hepatitis C virus (HCV) infection represents a major public health problem. Evaluation of risk factors is one of the solutions which help protect people from the infection. This study aims to employ zero-inflated Poisson mixed models to evaluate prognostic factors of hepatitis C. The data was collected from a longitudinal study during 2005-2010. First, mixed Poisson regression (PR) model was fitted to the data. Then, a mixed zero-inflated Poisson model was fitted with compound Poisson random effects. For evaluating the performance of the proposed mixed model, standard errors of estimators were compared. The results obtained from mixed PR showed that genotype 3 and treatment protocol were statistically significant. Results of zero-inflated Poisson mixed model showed that age, sex, genotypes 2 and 3, the treatment protocol, and having risk factors had significant effects on viral load of HCV patients. Of these two models, the estimators of zero-inflated Poisson mixed model had the minimum standard errors. The results showed that a mixed zero-inflated Poisson model was the almost best fit. The proposed model can capture serial dependence, additional overdispersion, and excess zeros in the longitudinal count data.

A generalized Poisson and Poisson-Boltzmann solver for electrostatic environments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fisicaro, G., E-mail: giuseppe.fisicaro@unibas.ch; Goedecker, S.; Genovese, L.

2016-01-07

The computational study of chemical reactions in complex, wet environments is critical for applications in many fields. It is often essential to study chemical reactions in the presence of applied electrochemical potentials, taking into account the non-trivial electrostatic screening coming from the solvent and the electrolytes. As a consequence, the electrostatic potential has to be found by solving the generalized Poisson and the Poisson-Boltzmann equations for neutral and ionic solutions, respectively. In the present work, solvers for both problems have been developed. A preconditioned conjugate gradient method has been implemented for the solution of the generalized Poisson equation and themore » linear regime of the Poisson-Boltzmann, allowing to solve iteratively the minimization problem with some ten iterations of the ordinary Poisson equation solver. In addition, a self-consistent procedure enables us to solve the non-linear Poisson-Boltzmann problem. Both solvers exhibit very high accuracy and parallel efficiency and allow for the treatment of periodic, free, and slab boundary conditions. The solver has been integrated into the BigDFT and Quantum-ESPRESSO electronic-structure packages and will be released as an independent program, suitable for integration in other codes.« less

Statistical analysis of CCSN/SS7 traffic data from working CCS subnetworks

NASA Astrophysics Data System (ADS)

Duffy, Diane E.; McIntosh, Allen A.; Rosenstein, Mark; Willinger, Walter

1994-04-01

In this paper, we report on an ongoing statistical analysis of actual CCSN traffic data. The data consist of approximately 170 million signaling messages collected from a variety of different working CCS subnetworks. The key findings from our analysis concern: (1) the characteristics of both the telephone call arrival process and the signaling message arrival process; (2) the tail behavior of the call holding time distribution; and (3) the observed performance of the CCSN with respect to a variety of performance and reliability measurements.

Inhomogeneity of the density of Parascaris spp. eggs in faeces of individual foals and the use of hypothesis testing for treatment decision making.

PubMed

Wilkes, E J A; Cowling, A; Woodgate, R G; Hughes, K J

2016-10-15

Faecal egg counts (FEC) are used widely for monitoring of parasite infection in animals, treatment decision-making and estimation of anthelmintic efficacy. When a single count or sample mean is used as a point estimate of the expectation of the egg distribution over some time interval, the variability in the egg density is not accounted for. Although variability, including quantifying sources, of egg count data has been described, the spatiotemporal distribution of nematode eggs in faeces is not well understood. We believe that statistical inference about the mean egg count for treatment decision-making has not been used previously. The aim of this study was to examine the density of Parascaris eggs in solution and faeces and to describe the use of hypothesis testing for decision-making. Faeces from two foals with Parascaris burdens were mixed with magnesium sulphate solution and 30 McMaster chambers were examined to determine the egg distribution in a well-mixed solution. To examine the distribution of eggs in faeces from an individual animal, three faecal piles from a foal with a known Parascaris burden were obtained, from which 81 counts were performed. A single faecal sample was also collected daily from 20 foals on three consecutive days and a FEC was performed on three separate portions of each sample. As appropriate, Poisson or negative binomial confidence intervals for the distribution mean were calculated. Parascaris eggs in a well-mixed solution conformed to a homogeneous Poisson process, while the egg density in faeces was not homogeneous, but aggregated. This study provides an extension from homogeneous to inhomogeneous Poisson processes, leading to an understanding of why Poisson and negative binomial distributions correspondingly provide a good fit for egg count data. The application of one-sided hypothesis tests for decision-making is presented. Copyright © 2016 Elsevier B.V. All rights reserved.

Electrodiffusion: a continuum modeling framework for biomolecular systems with realistic spatiotemporal resolution.

PubMed

Lu, Benzhuo; Zhou, Y C; Huber, Gary A; Bond, Stephen D; Holst, Michael J; McCammon, J Andrew

2007-10-07

A computational framework is presented for the continuum modeling of cellular biomolecular diffusion influenced by electrostatic driving forces. This framework is developed from a combination of state-of-the-art numerical methods, geometric meshing, and computer visualization tools. In particular, a hybrid of (adaptive) finite element and boundary element methods is adopted to solve the Smoluchowski equation (SE), the Poisson equation (PE), and the Poisson-Nernst-Planck equation (PNPE) in order to describe electrodiffusion processes. The finite element method is used because of its flexibility in modeling irregular geometries and complex boundary conditions. The boundary element method is used due to the convenience of treating the singularities in the source charge distribution and its accurate solution to electrostatic problems on molecular boundaries. Nonsteady-state diffusion can be studied using this framework, with the electric field computed using the densities of charged small molecules and mobile ions in the solvent. A solution for mesh generation for biomolecular systems is supplied, which is an essential component for the finite element and boundary element computations. The uncoupled Smoluchowski equation and Poisson-Boltzmann equation are considered as special cases of the PNPE in the numerical algorithm, and therefore can be solved in this framework as well. Two types of computations are reported in the results: stationary PNPE and time-dependent SE or Nernst-Planck equations solutions. A biological application of the first type is the ionic density distribution around a fragment of DNA determined by the equilibrium PNPE. The stationary PNPE with nonzero flux is also studied for a simple model system, and leads to an observation that the interference on electrostatic field of the substrate charges strongly affects the reaction rate coefficient. The second is a time-dependent diffusion process: the consumption of the neurotransmitter acetylcholine by acetylcholinesterase, determined by the SE and a single uncoupled solution of the Poisson-Boltzmann equation. The electrostatic effects, counterion compensation, spatiotemporal distribution, and diffusion-controlled reaction kinetics are analyzed and different methods are compared.

A fourth order PDE based fuzzy c- means approach for segmentation of microscopic biopsy images in presence of Poisson noise for cancer detection.

PubMed

Kumar, Rajesh; Srivastava, Subodh; Srivastava, Rajeev

2017-07-01

For cancer detection from microscopic biopsy images, image segmentation step used for segmentation of cells and nuclei play an important role. Accuracy of segmentation approach dominate the final results. Also the microscopic biopsy images have intrinsic Poisson noise and if it is present in the image the segmentation results may not be accurate. The objective is to propose an efficient fuzzy c-means based segmentation approach which can also handle the noise present in the image during the segmentation process itself i.e. noise removal and segmentation is combined in one step. To address the above issues, in this paper a fourth order partial differential equation (FPDE) based nonlinear filter adapted to Poisson noise with fuzzy c-means segmentation method is proposed. This approach is capable of effectively handling the segmentation problem of blocky artifacts while achieving good tradeoff between Poisson noise removals and edge preservation of the microscopic biopsy images during segmentation process for cancer detection from cells. The proposed approach is tested on breast cancer microscopic biopsy data set with region of interest (ROI) segmented ground truth images. The microscopic biopsy data set contains 31 benign and 27 malignant images of size 896 × 768. The region of interest selected ground truth of all 58 images are also available for this data set. Finally, the result obtained from proposed approach is compared with the results of popular segmentation algorithms; fuzzy c-means, color k-means, texture based segmentation, and total variation fuzzy c-means approaches. The experimental results shows that proposed approach is providing better results in terms of various performance measures such as Jaccard coefficient, dice index, Tanimoto coefficient, area under curve, accuracy, true positive rate, true negative rate, false positive rate, false negative rate, random index, global consistency error, and variance of information as compared to other segmentation approaches used for cancer detection. Copyright © 2017 Elsevier B.V. All rights reserved.

On the Overdispersed Molecular Clock

PubMed Central

Takahata, Naoyuki

1987-01-01

Rates of molecular evolution at some loci are more irregular than described by simple Poisson processes. Three situations under which molecular evolution would not follow simple Poisson processes are reevaluated from the viewpoint of the neutrality hypothesis: (i) concomitant or multiple substitutions in a gene, (ii) fluctuating substitution rates in time caused by coupled effects of deleterious mutations and bottlenecks, and (iii) changes in the degree of selective constraints against a gene (neutral space) caused by successive substitutions. The common underlying assumption that these causes are lineage nonspecific excludes the case where mutation rates themselves change systematically among lineages or taxonomic groups, and severely limits the extent of variation in the number of substitutions among lineages. Even under this stringent condition, however, the third hypothesis, the fluctuating neutral space model, can generate fairly large variation. This is described by a time-dependent renewal process, which does not exhibit any episodic nature of molecular evolution. It is argued that the observed elevated variances in the number of nucleotide or amino acid substitutions do not immediately call for positive Darwinian selection in molecular evolution. PMID:3596230

A two-phase Poisson process model and its application to analysis of cancer mortality among A-bomb survivors.

PubMed

Ohtaki, Megu; Tonda, Tetsuji; Aihara, Kazuyuki

2015-10-01

We consider a two-phase Poisson process model where only early successive transitions are assumed to be sensitive to exposure. In the case where intensity transitions are low, we derive analytically an approximate formula for the distribution of time to event for the excess hazard ratio (EHR) due to a single point exposure. The formula for EHR is a polynomial in exposure dose. Since the formula for EHR contains no unknown parameters except for the number of total stages, number of exposure-sensitive stages, and a coefficient of exposure effect, it is applicable easily under a variety of situations where there exists a possible latency time from a single point exposure to occurrence of event. Based on the multistage hypothesis of cancer, we formulate a radiation carcinogenesis model in which only some early consecutive stages of the process are sensitive to exposure, whereas later stages are not affected. An illustrative analysis using the proposed model is given for cancer mortality among A-bomb survivors. Copyright © 2015 Elsevier Inc. All rights reserved.

A least squares approach to estimating the probability distribution of unobserved data in multiphoton microscopy

NASA Astrophysics Data System (ADS)

Salama, Paul

2008-02-01

Multi-photon microscopy has provided biologists with unprecedented opportunities for high resolution imaging deep into tissues. Unfortunately deep tissue multi-photon microscopy images are in general noisy since they are acquired at low photon counts. To aid in the analysis and segmentation of such images it is sometimes necessary to initially enhance the acquired images. One way to enhance an image is to find the maximum a posteriori (MAP) estimate of each pixel comprising an image, which is achieved by finding a constrained least squares estimate of the unknown distribution. In arriving at the distribution it is assumed that the noise is Poisson distributed, the true but unknown pixel values assume a probability mass function over a finite set of non-negative values, and since the observed data also assumes finite values because of low photon counts, the sum of the probabilities of the observed pixel values (obtained from the histogram of the acquired pixel values) is less than one. Experimental results demonstrate that it is possible to closely estimate the unknown probability mass function with these assumptions.

Elasticity, slowness, thermal conductivity and the anisotropies in the Mn3Cu1-xGexN compounds

NASA Astrophysics Data System (ADS)

Li, Guan-Nan; Chen, Zhi-Qian; Lu, Yu-Ming; Hu, Meng; Jiao, Li-Na; Zhao, Hao-Ting

2018-03-01

We perform the first-principles to systematically investigate the elastic properties, minimum thermal conductivity and anisotropy of the negative thermal expansion compounds Mn3Cu1-xGexN. The elastic constant, bulk modulus, shear modulus, Young’s modulus and Poisson ratio are calculated for all the compounds. The results of the elastic constant indicate that all the compounds are mechanically stable and the doped Ge can adjust the ductile character of the compounds. According to the values of the percent ratio of the elastic anisotropy AB, AE and AG, shear anisotropic factors A1, A2 and A3, all the Mn3Cu1-xGexN compounds are elastic anisotropy. The three-dimensional diagrams of elastic moduli in space also show that all the compounds are elastic anisotropy. In addition, the acoustic wave speed, slowness, minimum thermal conductivity and Debye temperature are also calculated. When the ratio of content for Cu and Ge arrived to 1:1, the compound has the lowest thermal conductivity and the highest Debye temperature.

Detection and Localization of Subsurface Two-Dimensional Metallic Objects

NASA Astrophysics Data System (ADS)

Meschino, S.; Pajewski, L.; Schettini, G.

2009-04-01

"Roma Tre" University, Applied Electronics Dept.v. Vasca Navale 84, 00146 Rome, Italy Non-invasive identification of buried objects in the near-field of a receiver array is a subject of great interest, due to its application to the remote sensing of the earth's subsurface, to the detection of landmines, pipes, conduits, to the archaeological site characterization, and more. In this work, we present a Sub-Array Processing (SAP) approach for the detection and localization of subsurface perfectly-conducting circular cylinders. We consider a plane wave illuminating the region of interest, which is assumed to be a homogeneous, unlossy medium of unknown permittivity containing one or more targets. In a first step, we partition the receiver array so that the field scattered from the targets result to be locally plane at each sub-array. Then, we apply a Direction of Arrival (DOA) technique to obtain a set of angles for each locally plane wave, and triangulate these directions obtaining a collection of crossing crowding in the expected object locations [1]. We compare several DOA algorithms such as the traditional Bartlett and Capon Beamforming, the Pisarenko Harmonic Decomposition (PHD), the Minimum-Norm method, the Multiple Signal Classification (MUSIC) and the Estimation of Signal Parameters via Rotational Techinque (ESPRIT) [2]. In a second stage, we develop a statistical Poisson based model to manage the crossing pattern in order to extract the probable target's centre position. In particular, if the crossings are Poisson distributed, it is possible to feature two different distribution parameters [3]. These two parameters perform two density rate for the crossings, so that we can previously divide the crossing pattern in a certain number of equal-size windows and we can collect the windows of the crossing pattern with low rate parameters (that probably are background windows) and remove them. In this way we can consider only the high rate parameter windows (that most probably locate the target) and extract the center position of the object. We also consider some other localization-connected aspects. For example how to obtain a likely estimation of the soil permittivity and of the cylinders radius. Finally, when multiple objects are present, we refine our localization procedure by performing a Clustering Analysis of the crossing pattern. In particular, we apply the K-means algorithm to extract the coordinates of the objects centroids and the clusters extension. References [1] Şahin A., Miller L., "Object Detection Using High Resolution Near-Field Array Processing", IEEE Trans. on Geoscience and Remote Sensing, vol.39, no.1, Jan. 2001, pp. 136-141. [2] Gross F.B., "Smart Antennas for Wireless Communications", Mc.Graw-Hill 2005. [3] Hoaglin D.C., "A Poisonnes Plot", The American Statistician, vol.34, no.3 August 1980, pp.146-149.

Multichannel analysis of surface-waves and integration of downhole acoustic televiewer imaging, ultrasonic Vs and Vp, and vertical seismic profiling in an NEHRP-standard classification, South of Concordia, Kansas, USA

NASA Astrophysics Data System (ADS)

Raef, Abdelmoneam; Gad, Sabreen; Tucker-Kulesza, Stacey

2015-10-01

Seismic site characteristics, as pertaining to earthquake hazard reduction, are a function of the subsurface elastic moduli and the geologic structures. This study explores how multiscale (surface, downhole, and laboratory) datasets can be utilized to improve "constrained" average Vs30 (shear-wave velocity to a 30-meter depth). We integrate borehole, surface and laboratory measurements for a seismic site classification based on the standards of the National Earthquake Hazard Reduction Program (NEHRP). The seismic shear-wave velocity (Vs30) was derived from a geophysical inversion workflow that utilized multichannel analysis of surface-waves (MASW) and downhole acoustic televiewer imaging (DATI). P-wave and S-wave velocities, based on laboratory measurements of arrival times of ultrasonic-frequency signals, supported the workflow by enabling us to calculate Poisson's ratio, which was incorporated in building an initial model for the geophysical inversion of MASW. Extraction of core samples from two boreholes provided lithology and thickness calibration of the amplitudes of the acoustic televiewer imaging for each layer. The MASW inversion, for calculating Vs sections, was constrained with both ultrasonic laboratory measurements (from first arrivals of Vs and Vp waveforms at simulated in situ overburden stress conditions) and the downhole acoustic televiewer (DATV) amplitude logs. The Vs30 calculations enabled categorizing the studied site as NEHRP-class "C" - very dense soil and soft rock. Unlike shallow fractured carbonates in the studied area, S-wave and P-wave velocities at ultrasonic frequency for the deeper intact shale core-samples from two boreholes were in better agreement with the corresponding velocities from both a zero-offset vertical seismic profiling (VSP) and inversion of Rayleigh-wave velocity dispersion curves.

Bayesian analysis of Jolly-Seber type models

USGS Publications Warehouse

Matechou, Eleni; Nicholls, Geoff K.; Morgan, Byron J. T.; Collazo, Jaime A.; Lyons, James E.

2016-01-01

We propose the use of finite mixtures of continuous distributions in modelling the process by which new individuals, that arrive in groups, become part of a wildlife population. We demonstrate this approach using a data set of migrating semipalmated sandpipers (Calidris pussila) for which we extend existing stopover models to allow for individuals to have different behaviour in terms of their stopover duration at the site. We demonstrate the use of reversible jump MCMC methods to derive posterior distributions for the model parameters and the models, simultaneously. The algorithm moves between models with different numbers of arrival groups as well as between models with different numbers of behavioural groups. The approach is shown to provide new ecological insights about the stopover behaviour of semipalmated sandpipers but is generally applicable to any population in which animals arrive in groups and potentially exhibit heterogeneity in terms of one or more other processes.

Fedosov’s formal symplectic groupoids and contravariant connections

NASA Astrophysics Data System (ADS)

Karabegov, Alexander V.

2006-10-01

Using Fedosov's approach we give a geometric construction of a formal symplectic groupoid over any Poisson manifold endowed with a torsion-free Poisson contravariant connection. In the case of Kähler-Poisson manifolds this construction provides, in particular, the formal symplectic groupoids with separation of variables. We show that the dual of a semisimple Lie algebra does not admit torsion-free Poisson contravariant connections.

Improving outpatient phlebotomy service efficiency and patient experience using discrete-event simulation.

PubMed

Yip, Kenneth; Pang, Suk-King; Chan, Kui-Tim; Chan, Chi-Kuen; Lee, Tsz-Leung

2016-08-08

Purpose - The purpose of this paper is to present a simulation modeling application to reconfigure the outpatient phlebotomy service of an acute regional and teaching hospital in Hong Kong, with an aim to improve service efficiency, shorten patient queuing time and enhance workforce utilization. Design/methodology/approach - The system was modeled as an inhomogeneous Poisson process and a discrete-event simulation model was developed to simulate the current setting, and to evaluate how various performance metrics would change if switched from a decentralized to a centralized model. Variations were then made to the model to test different workforce arrangements for the centralized service, so that managers could decide on the service's final configuration via an evidence-based and data-driven approach. Findings - This paper provides empirical insights about the relationship between staffing arrangement and system performance via a detailed scenario analysis. One particular staffing scenario was chosen by manages as it was considered to strike the best balance between performance and workforce scheduled. The resulting centralized phlebotomy service was successfully commissioned. Practical implications - This paper demonstrates how analytics could be used for operational planning at the hospital level. The authors show that a transparent and evidence-based scenario analysis, made available through analytics and simulation, greatly facilitates management and clinical stakeholders to arrive at the ideal service configuration. Originality/value - The authors provide a robust method in evaluating the relationship between workforce investment, queuing reduction and workforce utilization, which is crucial for managers when deciding the delivery model for any outpatient-related service.

Delta II JPSS-1 Spacecraft Arrival

NASA Image and Video Library

2017-09-01

The Joint Polar Satellite System-1, or JPSS-1, arrives at the Astrotech Processing Facility at Vandenberg Air Force Base in California. JPSS is the first in a series four next-generation environmental satellites in a collaborative program between the National Oceanic and Atmospheric Administration (NOAA) and NASA. The satellite is scheduled to liftoff Nov. 10, 2017 atop a United Launch Alliance Delta II rocket.

Young Children in Day and Night Care: Negotiating and Constructing Belonging during Daily Arrivals

ERIC Educational Resources Information Center

Salonen, Eija; Laakso, Marja-Leena; Sevón, Eija

2016-01-01

The paper aims at understanding the processes related to young children's belonging during daily arrivals at day and night care. Two aspects of a child's belonging are considered: membership and sense of belonging. Data were gathered by ethnographic observation of 8 children aged from 20 to 36 months in two Finnish day care centres offering day…

Cultivating Asian Students' Willingness to Communicate in American Classrooms Using an Online Video-Based Pre-Arrival Course

ERIC Educational Resources Information Center

Hsu, Hui-Ching Kayla

2017-01-01

The purpose of this mixed-methods study was: (1) to document the design and implementation process of an online video-based pre-arrival course that was intended to cultivate Asian students' willingness to communicate in American Classrooms; (2) to assess the effectiveness of the course by measuring students' oral proficiency and willingness to…

Application of the Conway-Maxwell-Poisson generalized linear model for analyzing motor vehicle crashes.

PubMed

Lord, Dominique; Guikema, Seth D; Geedipally, Srinivas Reddy

2008-05-01

This paper documents the application of the Conway-Maxwell-Poisson (COM-Poisson) generalized linear model (GLM) for modeling motor vehicle crashes. The COM-Poisson distribution, originally developed in 1962, has recently been re-introduced by statisticians for analyzing count data subjected to over- and under-dispersion. This innovative distribution is an extension of the Poisson distribution. The objectives of this study were to evaluate the application of the COM-Poisson GLM for analyzing motor vehicle crashes and compare the results with the traditional negative binomial (NB) model. The comparison analysis was carried out using the most common functional forms employed by transportation safety analysts, which link crashes to the entering flows at intersections or on segments. To accomplish the objectives of the study, several NB and COM-Poisson GLMs were developed and compared using two datasets. The first dataset contained crash data collected at signalized four-legged intersections in Toronto, Ont. The second dataset included data collected for rural four-lane divided and undivided highways in Texas. Several methods were used to assess the statistical fit and predictive performance of the models. The results of this study show that COM-Poisson GLMs perform as well as NB models in terms of GOF statistics and predictive performance. Given the fact the COM-Poisson distribution can also handle under-dispersed data (while the NB distribution cannot or has difficulties converging), which have sometimes been observed in crash databases, the COM-Poisson GLM offers a better alternative over the NB model for modeling motor vehicle crashes, especially given the important limitations recently documented in the safety literature about the latter type of model.

Conditional Poisson models: a flexible alternative to conditional logistic case cross-over analysis.

PubMed

Armstrong, Ben G; Gasparrini, Antonio; Tobias, Aurelio

2014-11-24

The time stratified case cross-over approach is a popular alternative to conventional time series regression for analysing associations between time series of environmental exposures (air pollution, weather) and counts of health outcomes. These are almost always analyzed using conditional logistic regression on data expanded to case-control (case crossover) format, but this has some limitations. In particular adjusting for overdispersion and auto-correlation in the counts is not possible. It has been established that a Poisson model for counts with stratum indicators gives identical estimates to those from conditional logistic regression and does not have these limitations, but it is little used, probably because of the overheads in estimating many stratum parameters. The conditional Poisson model avoids estimating stratum parameters by conditioning on the total event count in each stratum, thus simplifying the computing and increasing the number of strata for which fitting is feasible compared with the standard unconditional Poisson model. Unlike the conditional logistic model, the conditional Poisson model does not require expanding the data, and can adjust for overdispersion and auto-correlation. It is available in Stata, R, and other packages. By applying to some real data and using simulations, we demonstrate that conditional Poisson models were simpler to code and shorter to run than are conditional logistic analyses and can be fitted to larger data sets than possible with standard Poisson models. Allowing for overdispersion or autocorrelation was possible with the conditional Poisson model but when not required this model gave identical estimates to those from conditional logistic regression. Conditional Poisson regression models provide an alternative to case crossover analysis of stratified time series data with some advantages. The conditional Poisson model can also be used in other contexts in which primary control for confounding is by fine stratification.

Frequency-Rank Distributions

ERIC Educational Resources Information Center

Brookes, Bertram C.; Griffiths, Jose M.

1978-01-01

Frequency, rank, and frequency rank distributions are defined. Extensive discussion on several aspects of frequency rank distributions includes the Poisson process as a means of exploring the stability of ranks; the correlation of frequency rank distributions; and the transfer coefficient, a new measure in frequency rank distribution. (MBR)

A New Model that Generates Lotka's Law.

ERIC Educational Resources Information Center

Huber, John C.

2002-01-01

Develops a new model for a process that generates Lotka's Law. Topics include measuring scientific productivity through the number of publications; rate of production; career duration; randomness; Poisson distribution; computer simulations; goodness-of-fit; theoretical support for the model; and future research. (Author/LRW)

A Behavioral Theory of Timing.

ERIC Educational Resources Information Center

Killeen, Peter R.; Fetterman, J. Gregor

1988-01-01

A theory of timing is proposed, based on the observation that signals of reinforcement elicit adjunctive behaviors. Transitions between these behaviors are described as a Poisson process. These behaviors may come to serve as the basis for conditional discriminations of the passage of time. (SLD)

Characterizing the performance of the Conway-Maxwell Poisson generalized linear model.

PubMed

Francis, Royce A; Geedipally, Srinivas Reddy; Guikema, Seth D; Dhavala, Soma Sekhar; Lord, Dominique; LaRocca, Sarah

2012-01-01

Count data are pervasive in many areas of risk analysis; deaths, adverse health outcomes, infrastructure system failures, and traffic accidents are all recorded as count events, for example. Risk analysts often wish to estimate the probability distribution for the number of discrete events as part of doing a risk assessment. Traditional count data regression models of the type often used in risk assessment for this problem suffer from limitations due to the assumed variance structure. A more flexible model based on the Conway-Maxwell Poisson (COM-Poisson) distribution was recently proposed, a model that has the potential to overcome the limitations of the traditional model. However, the statistical performance of this new model has not yet been fully characterized. This article assesses the performance of a maximum likelihood estimation method for fitting the COM-Poisson generalized linear model (GLM). The objectives of this article are to (1) characterize the parameter estimation accuracy of the MLE implementation of the COM-Poisson GLM, and (2) estimate the prediction accuracy of the COM-Poisson GLM using simulated data sets. The results of the study indicate that the COM-Poisson GLM is flexible enough to model under-, equi-, and overdispersed data sets with different sample mean values. The results also show that the COM-Poisson GLM yields accurate parameter estimates. The COM-Poisson GLM provides a promising and flexible approach for performing count data regression. © 2011 Society for Risk Analysis.

A Method of Poisson's Ration Imaging Within a Material Part

NASA Technical Reports Server (NTRS)

Roth, Don J. (Inventor)

1994-01-01

The present invention is directed to a method of displaying the Poisson's ratio image of a material part. In the present invention, longitudinal data is produced using a longitudinal wave transducer and shear wave data is produced using a shear wave transducer. The respective data is then used to calculate the Poisson's ratio for the entire material part. The Poisson's ratio approximations are then used to display the data.

Method of Poisson's ratio imaging within a material part

NASA Technical Reports Server (NTRS)

Roth, Don J. (Inventor)

1996-01-01

The present invention is directed to a method of displaying the Poisson's ratio image of a material part. In the present invention longitudinal data is produced using a longitudinal wave transducer and shear wave data is produced using a shear wave transducer. The respective data is then used to calculate the Poisson's ratio for the entire material part. The Poisson's ratio approximations are then used to displayed the image.

Effect of Poisson's loss factor of rubbery material on underwater sound absorption of anechoic coatings

NASA Astrophysics Data System (ADS)

Zhong, Jie; Zhao, Honggang; Yang, Haibin; Yin, Jianfei; Wen, Jihong

2018-06-01

Rubbery coatings embedded with air cavities are commonly used on underwater structures to reduce reflection of incoming sound waves. In this paper, the relationships between Poisson's and modulus loss factors of rubbery materials are theoretically derived, the different effects of the tiny Poisson's loss factor on characterizing the loss factors of shear and longitudinal moduli are revealed. Given complex Young's modulus and dynamic Poisson's ratio, it is found that the shear loss factor has almost invisible variation with the Poisson's loss factor and is very close to the loss factor of Young's modulus, while the longitudinal loss factor almost linearly decreases with the increase of Poisson's loss factor. Then, a finite element (FE) model is used to investigate the effect of the tiny Poisson's loss factor, which is generally neglected in some FE models, on the underwater sound absorption of rubbery coatings. Results show that the tiny Poisson's loss factor has a significant effect on the sound absorption of homogeneous coatings within the concerned frequency range, while it has both frequency- and structure-dependent influence on the sound absorption of inhomogeneous coatings with embedded air cavities. Given the material parameters and cavity dimensions, more obvious effect can be observed for the rubbery coating with a larger lattice constant and/or a thicker cover layer.

A Review of Multivariate Distributions for Count Data Derived from the Poisson Distribution

PubMed Central

Inouye, David; Yang, Eunho; Allen, Genevera; Ravikumar, Pradeep

2017-01-01

The Poisson distribution has been widely studied and used for modeling univariate count-valued data. Multivariate generalizations of the Poisson distribution that permit dependencies, however, have been far less popular. Yet, real-world high-dimensional count-valued data found in word counts, genomics, and crime statistics, for example, exhibit rich dependencies, and motivate the need for multivariate distributions that can appropriately model this data. We review multivariate distributions derived from the univariate Poisson, categorizing these models into three main classes: 1) where the marginal distributions are Poisson, 2) where the joint distribution is a mixture of independent multivariate Poisson distributions, and 3) where the node-conditional distributions are derived from the Poisson. We discuss the development of multiple instances of these classes and compare the models in terms of interpretability and theory. Then, we empirically compare multiple models from each class on three real-world datasets that have varying data characteristics from different domains, namely traffic accident data, biological next generation sequencing data, and text data. These empirical experiments develop intuition about the comparative advantages and disadvantages of each class of multivariate distribution that was derived from the Poisson. Finally, we suggest new research directions as explored in the subsequent discussion section. PMID:28983398

Hierarchical random additive process and logarithmic scaling of generalized high order, two-point correlations in turbulent boundary layer flow

NASA Astrophysics Data System (ADS)

Yang, X. I. A.; Marusic, I.; Meneveau, C.

2016-06-01

Townsend [Townsend, The Structure of Turbulent Shear Flow (Cambridge University Press, Cambridge, UK, 1976)] hypothesized that the logarithmic region in high-Reynolds-number wall-bounded flows consists of space-filling, self-similar attached eddies. Invoking this hypothesis, we express streamwise velocity fluctuations in the inertial layer in high-Reynolds-number wall-bounded flows as a hierarchical random additive process (HRAP): uz+=∑i=1Nzai . Here u is the streamwise velocity fluctuation, + indicates normalization in wall units, z is the wall normal distance, and ai's are independently, identically distributed random additives, each of which is associated with an attached eddy in the wall-attached hierarchy. The number of random additives is Nz˜ln(δ /z ) where δ is the boundary layer thickness and ln is natural log. Due to its simplified structure, such a process leads to predictions of the scaling behaviors for various turbulence statistics in the logarithmic layer. Besides reproducing known logarithmic scaling of moments, structure functions, and correlation function [" close="]3/2 uz(x ) uz(x +r ) >, new logarithmic laws in two-point statistics such as uz4(x ) > 1 /2, 1/3, etc. can be derived using the HRAP formalism. Supporting empirical evidence for the logarithmic scaling in such statistics is found from the Melbourne High Reynolds Number Boundary Layer Wind Tunnel measurements. We also show that, at high Reynolds numbers, the above mentioned new logarithmic laws can be derived by assuming the arrival of an attached eddy at a generic point in the flow field to be a Poisson process [Woodcock and Marusic, Phys. Fluids 27, 015104 (2015), 10.1063/1.4905301]. Taken together, the results provide new evidence supporting the essential ingredients of the attached eddy hypothesis to describe streamwise velocity fluctuations of large, momentum transporting eddies in wall-bounded turbulence, while observed deviations suggest the need for further extensions of the model.

Non-linear properties of metallic cellular materials with a negative Poisson's ratio

NASA Technical Reports Server (NTRS)

Choi, J. B.; Lakes, R. S.

1992-01-01

Negative Poisson's ratio copper foam was prepared and characterized experimentally. The transformation into re-entrant foam was accomplished by applying sequential permanent compressions above the yield point to achieve a triaxial compression. The Poisson's ratio of the re-entrant foam depended on strain and attained a relative minimum at strains near zero. Poisson's ratio as small as -0.8 was achieved. The strain dependence of properties occurred over a narrower range of strain than in the polymer foams studied earlier. Annealing of the foam resulted in a slightly greater magnitude of negative Poisson's ratio and greater toughness at the expense of a decrease in the Young's modulus.

Relation Between Firing Statistics of Spiking Neuron with Delayed Fast Inhibitory Feedback and Without Feedback

NASA Astrophysics Data System (ADS)

Vidybida, Alexander; Shchur, Olha

We consider a class of spiking neuronal models, defined by a set of conditions typical for basic threshold-type models, such as the leaky integrate-and-fire or the binding neuron model and also for some artificial neurons. A neuron is fed with a Poisson process. Each output impulse is applied to the neuron itself after a finite delay Δ. This impulse acts as being delivered through a fast Cl-type inhibitory synapse. We derive a general relation which allows calculating exactly the probability density function (pdf) p(t) of output interspike intervals of a neuron with feedback based on known pdf p0(t) for the same neuron without feedback and on the properties of the feedback line (the Δ value). Similar relations between corresponding moments are derived. Furthermore, we prove that the initial segment of pdf p0(t) for a neuron with a fixed threshold level is the same for any neuron satisfying the imposed conditions and is completely determined by the input stream. For the Poisson input stream, we calculate that initial segment exactly and, based on it, obtain exactly the initial segment of pdf p(t) for a neuron with feedback. That is the initial segment of p(t) is model-independent as well. The obtained expressions are checked by means of Monte Carlo simulation. The course of p(t) has a pronounced peculiarity, which makes it impossible to approximate p(t) by Poisson or another simple stochastic process.

WAITING TIME DISTRIBUTION OF SOLAR ENERGETIC PARTICLE EVENTS MODELED WITH A NON-STATIONARY POISSON PROCESS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, C.; Su, W.; Fang, C.

2014-09-10

We present a study of the waiting time distributions (WTDs) of solar energetic particle (SEP) events observed with the spacecraft WIND and GOES. The WTDs of both solar electron events (SEEs) and solar proton events (SPEs) display a power-law tail of ∼Δt {sup –γ}. The SEEs display a broken power-law WTD. The power-law index is γ{sub 1} = 0.99 for the short waiting times (<70 hr) and γ{sub 2} = 1.92 for large waiting times (>100 hr). The break of the WTD of SEEs is probably due to the modulation of the corotating interaction regions. The power-law index, γ ∼more » 1.82, is derived for the WTD of the SPEs which is consistent with the WTD of type II radio bursts, indicating a close relationship between the shock wave and the production of energetic protons. The WTDs of SEP events can be modeled with a non-stationary Poisson process, which was proposed to understand the waiting time statistics of solar flares. We generalize the method and find that, if the SEP event rate λ = 1/Δt varies as the time distribution of event rate f(λ) = Aλ{sup –α}exp (– βλ), the time-dependent Poisson distribution can produce a power-law tail WTD of ∼Δt {sup α} {sup –3}, where 0 ≤ α < 2.« less

Markov and semi-Markov processes as a failure rate

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grabski, Franciszek

2016-06-08

In this paper the reliability function is defined by the stochastic failure rate process with a non negative and right continuous trajectories. Equations for the conditional reliability functions of an object, under assumption that the failure rate is a semi-Markov process with an at most countable state space are derived. A proper theorem is presented. The linear systems of equations for the appropriate Laplace transforms allow to find the reliability functions for the alternating, the Poisson and the Furry-Yule failure rate processes.

A POISSON PROCESS APPROACH FOR RECURRENT EVENT DATA WITH ENVIRONMENTAL COVARIATES. (R825266)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

Modeling Creep Processes in Aging Polymers

NASA Astrophysics Data System (ADS)

Olali, N. V.; Voitovich, L. V.; Zazimko, N. N.; Malezhik, M. P.

2016-03-01

The photoelastic method is generalized to creep in hereditary aging materials. Optical-creep curves and mechanical-creep or optical-relaxation curves are used to interpret fringe patterns. For materials with constant Poisson's ratio, it is sufficient to use mechanical- or optical-creep curves for this purpose

Functional Integration

NASA Astrophysics Data System (ADS)

Cartier, Pierre; DeWitt-Morette, Cecile

2006-11-01

Acknowledgements; List symbols, conventions, and formulary; Part I. The Physical and Mathematical Environment: 1. The physical and mathematical environment; Part II. Quantum Mechanics: 2. First lesson: gaussian integrals; 3. Selected examples; 4. Semiclassical expansion: WKB; 5. Semiclassical expansion: beyond WKB; 6. Quantum dynamics: path integrals and operator formalism; Part III. Methods from Differential Geometry: 7. Symmetries; 8. Homotopy; 9. Grassmann analysis: basics; 10. Grassmann analysis: applications; 11. Volume elements, divergences, gradients; Part IV. Non-Gaussian Applications: 12. Poisson processes in physics; 13. A mathematical theory of Poisson processes; 14. First exit time: energy problems; Part V. Problems in Quantum Field Theory: 15. Renormalization 1: an introduction; 16. Renormalization 2: scaling; 17. Renormalization 3: combinatorics; 18. Volume elements in quantum field theory Bryce DeWitt; Part VI. Projects: 19. Projects; Appendix A. Forward and backward integrals: spaces of pointed paths; Appendix B. Product integrals; Appendix C. A compendium of gaussian integrals; Appendix D. Wick calculus Alexander Wurm; Appendix E. The Jacobi operator; Appendix F. Change of variables of integration; Appendix G. Analytic properties of covariances; Appendix H. Feynman's checkerboard; Bibliography; Index.

Functional Integration

NASA Astrophysics Data System (ADS)

Cartier, Pierre; DeWitt-Morette, Cecile

2010-06-01

Acknowledgements; List symbols, conventions, and formulary; Part I. The Physical and Mathematical Environment: 1. The physical and mathematical environment; Part II. Quantum Mechanics: 2. First lesson: gaussian integrals; 3. Selected examples; 4. Semiclassical expansion: WKB; 5. Semiclassical expansion: beyond WKB; 6. Quantum dynamics: path integrals and operator formalism; Part III. Methods from Differential Geometry: 7. Symmetries; 8. Homotopy; 9. Grassmann analysis: basics; 10. Grassmann analysis: applications; 11. Volume elements, divergences, gradients; Part IV. Non-Gaussian Applications: 12. Poisson processes in physics; 13. A mathematical theory of Poisson processes; 14. First exit time: energy problems; Part V. Problems in Quantum Field Theory: 15. Renormalization 1: an introduction; 16. Renormalization 2: scaling; 17. Renormalization 3: combinatorics; 18. Volume elements in quantum field theory Bryce DeWitt; Part VI. Projects: 19. Projects; Appendix A. Forward and backward integrals: spaces of pointed paths; Appendix B. Product integrals; Appendix C. A compendium of gaussian integrals; Appendix D. Wick calculus Alexander Wurm; Appendix E. The Jacobi operator; Appendix F. Change of variables of integration; Appendix G. Analytic properties of covariances; Appendix H. Feynman's checkerboard; Bibliography; Index.

Improvements in continuum modeling for biomolecular systems

NASA Astrophysics Data System (ADS)

Yu, Qiao; Ben-Zhuo, Lu

2016-01-01

Modeling of biomolecular systems plays an essential role in understanding biological processes, such as ionic flow across channels, protein modification or interaction, and cell signaling. The continuum model described by the Poisson- Boltzmann (PB)/Poisson-Nernst-Planck (PNP) equations has made great contributions towards simulation of these processes. However, the model has shortcomings in its commonly used form and cannot capture (or cannot accurately capture) some important physical properties of the biological systems. Considerable efforts have been made to improve the continuum model to account for discrete particle interactions and to make progress in numerical methods to provide accurate and efficient simulations. This review will summarize recent main improvements in continuum modeling for biomolecular systems, with focus on the size-modified models, the coupling of the classical density functional theory and the PNP equations, the coupling of polar and nonpolar interactions, and numerical progress. Project supported by the National Natural Science Foundation of China (Grant No. 91230106) and the Chinese Academy of Sciences Program for Cross & Cooperative Team of the Science & Technology Innovation.

The Nonhomogeneous Poisson Process for Fast Radio Burst Rates

DOE PAGES

Lawrence, Earl; Wiel, Scott Vander; Law, Casey; ...

2017-08-30

This paper presents the non-homogeneous Poisson process (NHPP) for modeling the rate of fast radio bursts (FRBs) and other infrequently observed astronomical events. The NHPP, well-known in statistics, can model dependence of the rate on both astronomical features and the details of an observing campaign. This is particularly helpful for rare events like FRBs because the NHPP can combine information across surveys, making the most of all available information. The goal of the paper is two-fold. First, it is intended to be a tutorial on the use of the NHPP. Second, we build an NHPP model that incorporates beam patternsmore » and a power law flux distribution for the rate of FRBs. Using information from 12 surveys including 15 detections, we find an all-sky FRB rate of 587 events per sky per day above a flux of 1 Jy (95% CI: 272, 924) and a flux power-law index of 0:91 (95% CI: 0.57, 1.25).« less

Single- and multiple-pulse noncoherent detection statistics associated with partially developed speckle.

PubMed

Osche, G R

2000-08-20

Single- and multiple-pulse detection statistics are presented for aperture-averaged direct detection optical receivers operating against partially developed speckle fields. A partially developed speckle field arises when the probability density function of the received intensity does not follow negative exponential statistics. The case of interest here is the target surface that exhibits diffuse as well as specular components in the scattered radiation. An approximate expression is derived for the integrated intensity at the aperture, which leads to single- and multiple-pulse discrete probability density functions for the case of a Poisson signal in Poisson noise with an additive coherent component. In the absence of noise, the single-pulse discrete density function is shown to reduce to a generalized negative binomial distribution. The radar concept of integration loss is discussed in the context of direct detection optical systems where it is shown that, given an appropriate set of system parameters, multiple-pulse processing can be more efficient than single-pulse processing over a finite range of the integration parameter n.

The Science of Climate Change

DOE Office of Scientific and Technical Information (OSTI.GOV)

Makundi, Willy R.

2002-09-20

What constitutes 'dangerous anthropogenic interference' is a value judgment arrived at through a socio-political process, taking issues like equity and sustainability into account. Science provides key information needed to arrive at an informed judgment. However, that judgment is primarily a political one, and not a purely scientific decision. Such judgments are based on risk assessment, and lead to risk management choices by decision makers, about actions and policies.

Spindled and hollow spars

NASA Technical Reports Server (NTRS)

Blyth, J D

1926-01-01

The most usual method of arriving at the maximum amount of spindling or hollowing out permissible in the case of any particular spar section is by trial and error, a process which is apt to become laborious in the absence of good guessing - or luck. The following tables have been got out with the object of making it possible to arrive with certainty at a suitable section at the first attempt.

Education without a Shared Language: Dynamics of Inclusion and Exclusion in Norwegian Introductory Classes for Newly Arrived Minority Language Students

ERIC Educational Resources Information Center

Hilt, Line Torbjørnsen

2017-01-01

Based upon fieldwork in two upper secondary schools in Norway, this article offers an analysis of inclusion and exclusion processes for newly arrived minority language students. Minority language students are defined by policy as students who have a different mother tongue than the Norwegian and Sami languages, and students who are newly arrived…

Collaborative Arrival Planning: Data Sharing and User Preference Tools

NASA Technical Reports Server (NTRS)

Zelenka, Richard E.; Edwards, Thomas A. (Technical Monitor)

1998-01-01

Air traffic growth and air carrier economic pressures have motivated efforts to increase the flexibility of the air traffic management process and change the relationship between the air traffic control service provider and the system user. One of the most visible of these efforts is the U.S. government/industry "free flight" initiative, in which the service provider concentrates on safety and cross-airline fairness, and the user on their business objectives and operating preferences, including selecting their own path and speed in real-time. In the terminal arrival phase of flight, severe restrictions and rigid control are currently placed on system users, typically without regard for individual user operational preferences. Airborne delays applied to arriving aircraft into capacity constrained airports are imposed on a first-come, first-serve basis, and thus do not allow the system user to plan for or prioritize late arrivals, or to economically optimize their arrival sequence. A central tenant of the free-flight operating paradigm is collaboration between service providers and users in reaching air traffic management decisions. Such collaboration would be particularly beneficial to an airline's "hub" operation, where off-schedule arrival aircraft are a consistent problem, as they cause serious air-port ramp difficulties, rippling airline scheduling effects, and result in large economic inefficiencies. Greater collaboration can also lead to increased airport capacity and decrease the severity of over-capacity rush periods. In the NASA Collaborative Arrival Planning (CAP) project, both independent exchange of real-time data between the service provider and system user and collaborative decision support tools are addressed. Data exchange of real-time arrival scheduling, airspace management, and air carrier fleet data between the FAA service provider and an air carrier is being conducted and evaluated. Collaborative arrival decision support tools to allow intra-airline arrival preferences are being developed and simulated. The CAP project is part of and leveraged from the NASA/FAA Center TRACON Automation System (CTAS), a fielded set of decision support tools that provide computer generated advisories for both enroute and terminal area controllers to manage and control arrival traffic more efficiently. In this paper, the NASA Collaborative Arrival Planning project is outlined and recent results detailed, including the real-time use of CTAS arrival scheduling data by a major air carrier and simulations of tactical and strategic user preference decision support tools.

Pumped shot noise in adiabatically modulated graphene-based double-barrier structures.

PubMed

Zhu, Rui; Lai, Maoli

2011-11-16

Quantum pumping processes are accompanied by considerable quantum noise. Based on the scattering approach, we investigated the pumped shot noise properties in adiabatically modulated graphene-based double-barrier structures. It is found that compared with the Poisson processes, the pumped shot noise is dramatically enhanced where the dc pumped current changes flow direction, which demonstrates the effect of the Klein paradox.

Pumped shot noise in adiabatically modulated graphene-based double-barrier structures

NASA Astrophysics Data System (ADS)

Zhu, Rui; Lai, Maoli

2011-11-01

Quantum pumping processes are accompanied by considerable quantum noise. Based on the scattering approach, we investigated the pumped shot noise properties in adiabatically modulated graphene-based double-barrier structures. It is found that compared with the Poisson processes, the pumped shot noise is dramatically enhanced where the dc pumped current changes flow direction, which demonstrates the effect of the Klein paradox.

KSC-2010-4497

NASA Image and Video Library

2010-08-26

CAPE CANAVERAL, Fla. -- At NASA's Kennedy Space Center in Florida, a tractor-trailer carrying the Alpha Magnetic Spectrometer, or AMS, arrives at the Space Station Processing Facility, where it will be processed for launch. The state-of-the-art particle physics detector arrived on Kennedy's Shuttle Landing Facility aboard an Air Force C-5M aircraft from Europe. It will operate as an external module on the International Space Station to study the universe and its origin by searching for dark matter. AMS will fly to the station aboard space shuttle Endeavour's STS-134 mission targeted to launch Feb. 26, 2011. Photo credit: NASA/Frankie Martin

KENNEDY SPACE CENTER, FLA. - In the Space Station Processing Facility, Executive Director of NASDA Koji Yamamoto (center) gets information about the facility while on a tour of KSC. Behind the group is the Japanese Experiment Module (JEM)/pressurized module. Mr. Yamamoto is at KSC for a welcome ceremony involving the arrival of JEM.

NASA Image and Video Library

2003-06-12

KENNEDY SPACE CENTER, FLA. - In the Space Station Processing Facility, Executive Director of NASDA Koji Yamamoto (center) gets information about the facility while on a tour of KSC. Behind the group is the Japanese Experiment Module (JEM)/pressurized module. Mr. Yamamoto is at KSC for a welcome ceremony involving the arrival of JEM.

Orion Stage Adapter Arrival

NASA Image and Video Library

2018-04-03

NASA's Super Guppy aircraft touches down at the Shuttle Landing Facility at the agency's Kennedy Space Center in Florida. The Super Guppy is carrying the Orion Stage Adapter (OSA), the second flight-hardware section of NASA's Space Launch System (SLS) rocket that has arrived at Kennedy. The OSA will connect the Orion spacecraft to the upper part of the SLS rocket, the interim cryogenic propulsion stage (ICPS). Both the OSA and ICPS are being stored for processing in the center's Space Station Processing Facility in preparation for Exploration Mission-1, the first uncrewed, integrated launch of the SLS rocket and Orion spacecraft.

Orion Stage Adapter Arrival

NASA Image and Video Library

2018-04-03

NASA's Super Guppy aircraft taxies onto the tarmac after touching down at the Shuttle Landing Facility at the agency's Kennedy Space Center in Florida. The Super Guppy is carrying the Orion Stage Adapter (OSA), the second flight-hardware section of NASA's Space Launch System (SLS) rocket that has arrived at Kennedy. The OSA will connect the Orion spacecraft to the upper part of the SLS rocket, the interim cryogenic propulsion stage (ICPS). Both the OSA and ICPS are being stored for processing in the center's Space Station Processing Facility in preparation for Exploration Mission-1, the first uncrewed, integrated launch of the SLS rocket and Orion spacecraft.

Orion Stage Adapter Arrival

NASA Image and Video Library

2018-04-03

NASA's Super Guppy aircraft glides to a stop at the Shuttle Landing Facility at the agency's Kennedy Space Center in Florida. The Super Guppy is carrying the Orion Stage Adapter (OSA), the second flight-hardware section of NASA's Space Launch System (SLS) rocket that has arrived at Kennedy. The OSA will connect the Orion spacecraft to the upper part of the SLS rocket, the interim cryogenic propulsion stage (ICPS). Both the OSA and ICPS are being stored for processing in the center's Space Station Processing Facility in preparation for Exploration Mission-1, the first uncrewed, integrated launch of the SLS rocket and Orion spacecraft.

Orion Stage Adapter Arrival

NASA Image and Video Library

2018-04-03

NASA's Super Guppy aircraft prepares to touch down at the Shuttle Landing Facility at the agency's Kennedy Space Center in Florida. The Super Guppy is carrying the Orion Stage Adapter (OSA), the second flight-hardware section of NASA's Space Launch System (SLS) rocket that has arrived at Kennedy. The OSA will connect the Orion spacecraft to the upper part of the SLS rocket, the interim cryogenic propulsion stage (ICPS). Both the OSA and ICPS are being stored for processing in the center's Space Station Processing Facility in preparation for Exploration Mission-1, the first uncrewed, integrated launch of the SLS rocket and Orion spacecraft.

Poisson-type inequalities for growth properties of positive superharmonic functions.

PubMed

Luan, Kuan; Vieira, John

2017-01-01

In this paper, we present new Poisson-type inequalities for Poisson integrals with continuous data on the boundary. The obtained inequalities are used to obtain growth properties at infinity of positive superharmonic functions in a smooth cone.

Soft network materials with isotropic negative Poisson's ratios over large strains.

PubMed

Liu, Jianxing; Zhang, Yihui

2018-01-31

Auxetic materials with negative Poisson's ratios have important applications across a broad range of engineering areas, such as biomedical devices, aerospace engineering and automotive engineering. A variety of design strategies have been developed to achieve artificial auxetic materials with controllable responses in the Poisson's ratio. The development of designs that can offer isotropic negative Poisson's ratios over large strains can open up new opportunities in emerging biomedical applications, which, however, remains a challenge. Here, we introduce deterministic routes to soft architected materials that can be tailored precisely to yield the values of Poisson's ratio in the range from -1 to 1, in an isotropic manner, with a tunable strain range from 0% to ∼90%. The designs rely on a network construction in a periodic lattice topology, which incorporates zigzag microstructures as building blocks to connect lattice nodes. Combined experimental and theoretical studies on broad classes of network topologies illustrate the wide-ranging utility of these concepts. Quantitative mechanics modeling under both infinitesimal and finite deformations allows the development of a rigorous design algorithm that determines the necessary network geometries to yield target Poisson ratios over desired strain ranges. Demonstrative examples in artificial skin with both the negative Poisson's ratio and the nonlinear stress-strain curve precisely matching those of the cat's skin and in unusual cylindrical structures with engineered Poisson effect and shape memory effect suggest potential applications of these network materials.

The hopes of West African refugees during resettlement in northern Sweden: a 6-year prospective qualitative study of pathways and agency thoughts.

PubMed

Anjum, Tanvir M; Nordqvist, Cecilia; Timpka, Toomas

2012-01-24

Little is known about how positive phenomena can support resettlement of refugees in a new country. The aim of this study was to examine the hopeful thinking in a group of West African quota refugees at arrival and after 6 years in Sweden and compare these thoughts to the views of resettlement support professionals. The primary study population comprised 56 adult refugees and 13 resettlement professionals. Qualitative data were collected from the refugees by questionnaires on arrival and 6 years later. Data were collected from the resettlement professionals by interview about 3 years after arrival of the refugees. Snyder's cognitive model of hope was used to inform the comparative data analyses. Hopes regarding education were in focus for the refugees shortly after arrival, but thoughts on family reunion were central later in the resettlement process. During the later stages of the resettlement process, the unresponsiveness of the support organization to the family reunion problem became as issue for the refugees. The professionals reported a complex mix of "silent agency thoughts" underlying the local resettlement process as a contributing reason for this unresponsiveness. Hopes regarding education and family reunion were central in the resettlement of West African refugees in Sweden. These thoughts were not systematically followed up by the support organization; possibly the resources for refugees were not fully released. More studies are needed to further investigate the motivational factors underpinning host community support of refugees' hopes and plans.

Fast first arrival picking algorithm for noisy microseismic data

NASA Astrophysics Data System (ADS)

Kim, Dowan; Byun, Joongmoo; Lee, Minho; Choi, Jihoon; Kim, Myungsun

2017-01-01

Most microseismic events occur during hydraulic fracturing. Thus microseismic monitoring, by recording seismic waves from microseismic events, is one of the best methods for locating the positions of hydraulic fractures. However, since microseismic events have very low energy, the data often have a low signal-to-noise ratio (S/N ratio) and it is not easy to pick the first arrival time. In this study, we suggest a new fast picking method optimised for noisy data using cross-correlation and stacking. In this method, a reference trace is selected and the time differences between the first arrivals of the reference trace and those of the other traces are computed by cross-correlation. Then, all traces are aligned with the reference trace by time shifting, and the aligned traces are summed together to produce a stacked reference trace that has a considerably improved S/N ratio. After the first arrival time of the stacked reference trace is picked, the first arrival time of each trace is calculated automatically using the time differences obtained in the cross-correlation process. In experiments with noisy synthetic data and field data, this method produces more reliable results than the traditional method, which picks the first arrival time of each noisy trace separately. In addition, the computation time is dramatically reduced.

Prescription-induced jump distributions in multiplicative Poisson processes.

PubMed

Suweis, Samir; Porporato, Amilcare; Rinaldo, Andrea; Maritan, Amos

2011-06-01

Generalized Langevin equations (GLE) with multiplicative white Poisson noise pose the usual prescription dilemma leading to different evolution equations (master equations) for the probability distribution. Contrary to the case of multiplicative Gaussian white noise, the Stratonovich prescription does not correspond to the well-known midpoint (or any other intermediate) prescription. By introducing an inertial term in the GLE, we show that the Itô and Stratonovich prescriptions naturally arise depending on two time scales, one induced by the inertial term and the other determined by the jump event. We also show that, when the multiplicative noise is linear in the random variable, one prescription can be made equivalent to the other by a suitable transformation in the jump probability distribution. We apply these results to a recently proposed stochastic model describing the dynamics of primary soil salinization, in which the salt mass balance within the soil root zone requires the analysis of different prescriptions arising from the resulting stochastic differential equation forced by multiplicative white Poisson noise, the features of which are tailored to the characters of the daily precipitation. A method is finally suggested to infer the most appropriate prescription from the data.

Prescription-induced jump distributions in multiplicative Poisson processes

NASA Astrophysics Data System (ADS)

Suweis, Samir; Porporato, Amilcare; Rinaldo, Andrea; Maritan, Amos

2011-06-01

Generalized Langevin equations (GLE) with multiplicative white Poisson noise pose the usual prescription dilemma leading to different evolution equations (master equations) for the probability distribution. Contrary to the case of multiplicative Gaussian white noise, the Stratonovich prescription does not correspond to the well-known midpoint (or any other intermediate) prescription. By introducing an inertial term in the GLE, we show that the Itô and Stratonovich prescriptions naturally arise depending on two time scales, one induced by the inertial term and the other determined by the jump event. We also show that, when the multiplicative noise is linear in the random variable, one prescription can be made equivalent to the other by a suitable transformation in the jump probability distribution. We apply these results to a recently proposed stochastic model describing the dynamics of primary soil salinization, in which the salt mass balance within the soil root zone requires the analysis of different prescriptions arising from the resulting stochastic differential equation forced by multiplicative white Poisson noise, the features of which are tailored to the characters of the daily precipitation. A method is finally suggested to infer the most appropriate prescription from the data.

Effect of Fiber Poisson Contraction on Matrix Multicracking Evolution of Fiber-Reinforced Ceramic-Matrix Composites

NASA Astrophysics Data System (ADS)

Longbiao, Li

2015-12-01

An analytical methodology has been developed to investigate the effect of fiber Poisson contraction on matrix multicracking evolution of fiber-reinforced ceramic-matrix composites (CMCs). The modified shear-lag model incorporated with the Coulomb friction law is adopted to solve the stress distribution in the interface slip region and intact region of the damaged composite. The critical matrix strain energy criterion which presupposes the existence of an ultimate or critical strain energy limit beyond which the matrix fails has been adopted to describe matrix multicracking of CMCs. As more energy is placed into the composite, matrix fractures and the interface debonding occurs to dissipate the extra energy. The interface debonded length under the process of matrix multicracking is obtained by treating the interface debonding as a particular crack propagation problem along the fiber/matrix interface. The effects of the interfacial frictional coefficient, fiber Poisson ratio, fiber volume fraction, interface debonded energy and cycle number on the interface debonding and matrix multicracking evolution have been analyzed. The theoretical results are compared with experimental data of unidirectional SiC/CAS, SiC/CAS-II and SiC/Borosilicate composites.

The solution of large multi-dimensional Poisson problems

NASA Technical Reports Server (NTRS)

Stone, H. S.

1974-01-01

The Buneman algorithm for solving Poisson problems can be adapted to solve large Poisson problems on computers with a rotating drum memory so that the computation is done with very little time lost due to rotational latency of the drum.

Accelerated iteration schemes for transonic flow calculations using fast poisson solvers. [aerodynamics

NASA Technical Reports Server (NTRS)

Jameson, A.

1975-01-01

The use of a fast elliptic solver in combination with relaxation is presented as an effective way to accelerate the convergence of transonic flow calculations, particularly when a marching scheme can be used to treat the supersonic zone in the relaxation process.

On the Determination of Poisson Statistics for Haystack Radar Observations of Orbital Debris

NASA Technical Reports Server (NTRS)

Stokely, Christopher L.; Benbrook, James R.; Horstman, Matt

2007-01-01

A convenient and powerful method is used to determine if radar detections of orbital debris are observed according to Poisson statistics. This is done by analyzing the time interval between detection events. For Poisson statistics, the probability distribution of the time interval between events is shown to be an exponential distribution. This distribution is a special case of the Erlang distribution that is used in estimating traffic loads on telecommunication networks. Poisson statistics form the basis of many orbital debris models but the statistical basis of these models has not been clearly demonstrated empirically until now. Interestingly, during the fiscal year 2003 observations with the Haystack radar in a fixed staring mode, there are no statistically significant deviations observed from that expected with Poisson statistics, either independent or dependent of altitude or inclination. One would potentially expect some significant clustering of events in time as a result of satellite breakups, but the presence of Poisson statistics indicates that such debris disperse rapidly with respect to Haystack's very narrow radar beam. An exception to Poisson statistics is observed in the months following the intentional breakup of the Fengyun satellite in January 2007.

ED Triage Process Improvement: Timely Vital Signs for Less Acute Patients.

PubMed

Falconer, Stella S; Karuppan, Corinne M; Kiehne, Emily; Rama, Shravan

2018-06-13

Vital signs can result in an upgrade of patients' Emergency Severity Index (ESI) levels. It is therefore preferable to obtain vital signs early in the triage process, particularly for ESI level 3 patients. Emergency departments have an opportunity to redesign triage processes to meet required protocols while enhancing the quality and experience of care. We performed process analyses to redesign the door-to-vital signs process. We also developed spaghetti diagrams to reconfigure the patient arrival area. The door-to-vital signs time was reduced from 43.1 minutes to 6.44 minutes. Both patients and triage staff seemed more satisfied with the new process. The patient arrival area was less congested and more welcoming. Performing activities in parallel reduces flow time with no additional resources. Staff involvement in process planning, redesign, and control ensures engagement and early buy-in. One should anticipate how changes to one process might affect other processes. Copyright © 2018. Published by Elsevier Inc.

Poisson geometry from a Dirac perspective

NASA Astrophysics Data System (ADS)

Meinrenken, Eckhard

2018-03-01

We present proofs of classical results in Poisson geometry using techniques from Dirac geometry. This article is based on mini-courses at the Poisson summer school in Geneva, June 2016, and at the workshop Quantum Groups and Gravity at the University of Waterloo, April 2016.

Interactive Graphic Simulation of Rolling Element Bearings. Phase I. Low Frequency Phenomenon and RAPIDREB Development.

DTIC Science & Technology

1981-11-01

RDRER413 C EH 11-22 HOUSING ELASTIC MODUJLUS (F/L**2). RDRE8415 C PO4 ?3-34 HOUSING POISSON-S PATTO . PDPR416 C DENH 35-46 HOUSING MATERIAL DFNSITY (MA/L...23-34 CAGE POISSON-S PATTO . RDPRE427 C DENC 35-46 CAC7E MATFRIAL DENSITY (MA/L-03), PDPEP4?8 C RDRER4?9 C CARD 11 RDRE9430 C ---- ROPER431 C JF 11-16

Cumulative Poisson Distribution Program

NASA Technical Reports Server (NTRS)

Bowerman, Paul N.; Scheuer, Ernest M.; Nolty, Robert

1990-01-01

Overflow and underflow in sums prevented. Cumulative Poisson Distribution Program, CUMPOIS, one of two computer programs that make calculations involving cumulative Poisson distributions. Both programs, CUMPOIS (NPO-17714) and NEWTPOIS (NPO-17715), used independently of one another. CUMPOIS determines cumulative Poisson distribution, used to evaluate cumulative distribution function (cdf) for gamma distributions with integer shape parameters and cdf for X (sup2) distributions with even degrees of freedom. Used by statisticians and others concerned with probabilities of independent events occurring over specific units of time, area, or volume. Written in C.

Poly-symplectic Groupoids and Poly-Poisson Structures

NASA Astrophysics Data System (ADS)

Martinez, Nicolas

2015-05-01

We introduce poly-symplectic groupoids, which are natural extensions of symplectic groupoids to the context of poly-symplectic geometry, and define poly-Poisson structures as their infinitesimal counterparts. We present equivalent descriptions of poly-Poisson structures, including one related with AV-Dirac structures. We also discuss symmetries and reduction in the setting of poly-symplectic groupoids and poly-Poisson structures, and use our viewpoint to revisit results and develop new aspects of the theory initiated in Iglesias et al. (Lett Math Phys 103:1103-1133, 2013).

Combined analysis of magnetic and gravity anomalies using normalized source strength (NSS)

NASA Astrophysics Data System (ADS)

Li, L.; Wu, Y.

2017-12-01

Gravity field and magnetic field belong to potential fields which lead inherent multi-solution. Combined analysis of magnetic and gravity anomalies based on Poisson's relation is used to determinate homology gravity and magnetic anomalies and decrease the ambiguity. The traditional combined analysis uses the linear regression of the reduction to pole (RTP) magnetic anomaly to the first order vertical derivative of the gravity anomaly, and provides the quantitative or semi-quantitative interpretation by calculating the correlation coefficient, slope and intercept. In the calculation process, due to the effect of remanent magnetization, the RTP anomaly still contains the effect of oblique magnetization. In this case the homology gravity and magnetic anomalies display irrelevant results in the linear regression calculation. The normalized source strength (NSS) can be transformed from the magnetic tensor matrix, which is insensitive to the remanence. Here we present a new combined analysis using NSS. Based on the Poisson's relation, the gravity tensor matrix can be transformed into the pseudomagnetic tensor matrix of the direction of geomagnetic field magnetization under the homologous condition. The NSS of pseudomagnetic tensor matrix and original magnetic tensor matrix are calculated and linear regression analysis is carried out. The calculated correlation coefficient, slope and intercept indicate the homology level, Poisson's ratio and the distribution of remanent respectively. We test the approach using synthetic model under complex magnetization, the results show that it can still distinguish the same source under the condition of strong remanence, and establish the Poisson's ratio. Finally, this approach is applied in China. The results demonstrated that our approach is feasible.

Examining the spatially non-stationary associations between the second demographic transition and infant mortality: A Poisson GWR approach.

PubMed

Yang, Tse-Chuan; Shoff, Carla; Matthews, Stephen A

2013-01-01

Based on ecological studies, second demographic transition (SDT) theorists concluded that some areas in the US were in vanguard of the SDT compared to others, implying spatial nonstationarity may be inherent in the SDT process. Linking the SDT to the infant mortality literature, we sought out to answer two related questions: Are the main components of the SDT, specifically marriage postponement, cohabitation, and divorce, associated with infant mortality? If yes, do these associations vary across the US? We applied global Poisson and geographically weighted Poisson regression (GWPR) models, a place-specific analytic approach, to county-level data in the contiguous US. After accounting for the racial/ethnic and socioeconomic compositions of counties and prenatal care utilization, we found (1) marriage postponement was negatively related to infant mortality in the southwestern states, but positively associated with infant mortality in parts of Indiana, Kentucky, and Tennessee, (2) cohabitation rates were positively related to infant mortality, and this relationship was stronger in California, coastal Virginia, and the Carolinas than other areas, and (3) a positive association between divorce rates and infant mortality in southwestern and northeastern areas of the US. These spatial patterns suggested that the associations between the SDT and infant mortality were stronger in the areas in vanguard of the SDT than in others. The comparison between global Poisson and GWPR results indicated that a place-specific spatial analysis not only fit the data better, but also provided insights into understanding the non-stationarity of the associations between the SDT and infant mortality.

Dual Roles for Spike Signaling in Cortical Neural Populations

PubMed Central

Ballard, Dana H.; Jehee, Janneke F. M.

2011-01-01

A prominent feature of signaling in cortical neurons is that of randomness in the action potential. The output of a typical pyramidal cell can be well fit with a Poisson model, and variations in the Poisson rate repeatedly have been shown to be correlated with stimuli. However while the rate provides a very useful characterization of neural spike data, it may not be the most fundamental description of the signaling code. Recent data showing γ frequency range multi-cell action potential correlations, together with spike timing dependent plasticity, are spurring a re-examination of the classical model, since precise timing codes imply that the generation of spikes is essentially deterministic. Could the observed Poisson randomness and timing determinism reflect two separate modes of communication, or do they somehow derive from a single process? We investigate in a timing-based model whether the apparent incompatibility between these probabilistic and deterministic observations may be resolved by examining how spikes could be used in the underlying neural circuits. The crucial component of this model draws on dual roles for spike signaling. In learning receptive fields from ensembles of inputs, spikes need to behave probabilistically, whereas for fast signaling of individual stimuli, the spikes need to behave deterministically. Our simulations show that this combination is possible if deterministic signals using γ latency coding are probabilistically routed through different members of a cortical cell population at different times. This model exhibits standard features characteristic of Poisson models such as orientation tuning and exponential interval histograms. In addition, it makes testable predictions that follow from the γ latency coding. PMID:21687798

Delta II JPSS-1 Spacecraft Arrival

NASA Image and Video Library

2017-09-01

Technicians at Vandenberg Air Force Base in California inspect the shipping container for the Joint Polar Satellite System-1, or JPSS-1, as it arrives at the Astrotech Processing Facility. JPSS is the first in a series four next-generation environmental satellites in a collaborative program between the National Oceanic and Atmospheric Administration (NOAA) and NASA. The satellite is scheduled to liftoff Nov. 10, 2017 atop a United Launch Alliance Delta II rocket.

2010 Defense Logistics Agency Enterprise Supplier Conference and Exhibition

DTIC Science & Technology

2010-08-25

into safety stock and if unfilled will cause safety stock depletion and UFOs . NOT CUSTOMER FOCUSED Processing/Reporting against Required Delivery...Date allows for full ALT and PLT, resulting in UFOs . WARFIGHTER FOCUSED, GLOBALLY RESPONSIVE SUPPLY CHAIN LEADERSHIP 5 ATP Overview • Definition of...Need Arrival Date – Limits impact to UFOs and SS depletion ATP Goal = Materiel receipt by the “Need Arrival Date” … period ADMINISTRATIVE LEAD TIME

8 CFR 286.9 - Fee for processing applications and issuing documentation at land border Ports-of-Entry.

Code of Federal Regulations, 2014 CFR

2014-01-01

...), Arrival/Departure Record, for admission at a land border Port-of-Entry must remit the required fee for... Card, issued by the DOS, or a passport and combined B-1/B-2 visa and non-biometric BCC (or similar stamp in a passport) issued by the DOS, who is required to be issued Form I-94, Arrival/Departure Record...

Fractional poisson--a simple dose-response model for human norovirus.

PubMed

Messner, Michael J; Berger, Philip; Nappier, Sharon P

2014-10-01

This study utilizes old and new Norovirus (NoV) human challenge data to model the dose-response relationship for human NoV infection. The combined data set is used to update estimates from a previously published beta-Poisson dose-response model that includes parameters for virus aggregation and for a beta-distribution that describes variable susceptibility among hosts. The quality of the beta-Poisson model is examined and a simpler model is proposed. The new model (fractional Poisson) characterizes hosts as either perfectly susceptible or perfectly immune, requiring a single parameter (the fraction of perfectly susceptible hosts) in place of the two-parameter beta-distribution. A second parameter is included to account for virus aggregation in the same fashion as it is added to the beta-Poisson model. Infection probability is simply the product of the probability of nonzero exposure (at least one virus or aggregate is ingested) and the fraction of susceptible hosts. The model is computationally simple and appears to be well suited to the data from the NoV human challenge studies. The model's deviance is similar to that of the beta-Poisson, but with one parameter, rather than two. As a result, the Akaike information criterion favors the fractional Poisson over the beta-Poisson model. At low, environmentally relevant exposure levels (<100), estimation error is small for the fractional Poisson model; however, caution is advised because no subjects were challenged at such a low dose. New low-dose data would be of great value to further clarify the NoV dose-response relationship and to support improved risk assessment for environmentally relevant exposures. © 2014 Society for Risk Analysis Published 2014. This article is a U.S. Government work and is in the public domain for the U.S.A.

Air Medical Evacuations From the German North Sea Wind Farm Bard Offshore 1: Traumatic Injuries, Acute Diseases, and Rescue Process Times (2011-2013).

PubMed

Dethleff, Dirk; Weinrich, Nils; Kowald, Birgitt; Hory, Dorothea; Franz, Rüdiger; Nielsen, Maja Verena; Seide, Klaus; Jürgens, Christian; Stuhr, Markus

2016-01-01

Our purpose was 2-fold: 1) to show emergency-related traumatic injury and acute disease patterns and 2) to evaluate air rescue process times in a remotely located German offshore wind farm. Optimally, this will support methodologies to reduce offshore help time (time from the incoming emergency call until offshore arrival of the helicopter). The type and severity of traumatic injuries and acute diseases were retrospectively analyzed for 39 air medevacs from August 2011 to December 2013, and the process times of air rescue missions were evaluated in detail. Forty-nine percent of the medevacs were related to traumatic injuries, whereas 41% were associated with acute diseases and 10% remained unclear. Cardiovascular and gastrointestinal disorders accounted for 90% of internal medical cases. About 69% of the trauma was related to contusions, lacerations, and cuts. The main body regions injured were limbs (∼59%) and head (∼32%). The total rescue time until arrival at the destination facility averaged 175.3 minutes (standard deviation = 54.4 minutes). The mean helicopter offshore arrival time was 106.9 minutes (standard deviation = 57.4 minutes) after the incoming emergency call. In 64% of the medevacs, the helicopter arrived on scene within a help time of 90 minutes. A reduction of help time (≤ 60 minutes) for time-critical severe trauma and acute diseases may be anticipated through rapid and focused medical and logistic decision-making processes by the onshore dispatch center combined with professional, qualified, and well-trained flight and rescue personnel. Copyright © 2016 Air Medical Journal Associates. Published by Elsevier Inc. All rights reserved.

Officials welcome the arrival of the Japanese Experiment Module

NASA Image and Video Library

2007-04-17

In the Space Station Processing Facility, Scott Higginbotham, payload manager for the International Space Station, discusses the Experiment Logistics Module Pressurized Section for the Japanese Experiment Module (JEM), with Dr. Hidetaka Tanaka, the JEM Project Team resident manager at KSC for the Japanese Aerospace and Exploration Agency (JAXA). Earlier, NASA and JAXA officials welcomed the arrival of the module. The new International Space Station component arrived at Kennedy March 12 to begin preparations for its future launch on mission STS-123. It will serve as an on-orbit storage area for materials, tools and supplies. It can hold up to eight experiment racks and will attach to the top of another larger pressurized module.

Parker Solar Probe Spacecraft Arrival, Offload and Transport

NASA Image and Video Library

2018-04-03

NASA's Parker Solar Probe, secured in its shipping container, arrives at the Astrotech processing facility near the agency's Kennedy Space Center in Florida. The spacecraft arrived aboard a U.S. Air Force C-5 transport aircraft at Space Coast Regional Airport in Titusville, Florida. The Parker Solar Probe will launch on a United Launch Alliance Delta IV Heavy rocket from Space Launch Complex 37 at Cape Canaveral Air Force Station in Florida in July 2018. The mission will perform the closest-ever observations of a star when it travels through the Sun's atmosphere, called the corona. The probe will rely on measurements and imaging to revolutionize our understanding of the corona and the Sun-Earth connection.

Concurrent topological design of composite structures and materials containing multiple phases of distinct Poisson's ratios

NASA Astrophysics Data System (ADS)

Long, Kai; Yuan, Philip F.; Xu, Shanqing; Xie, Yi Min

2018-04-01

Most studies on composites assume that the constituent phases have different values of stiffness. Little attention has been paid to the effect of constituent phases having distinct Poisson's ratios. This research focuses on a concurrent optimization method for simultaneously designing composite structures and materials with distinct Poisson's ratios. The proposed method aims to minimize the mean compliance of the macrostructure with a given mass of base materials. In contrast to the traditional interpolation of the stiffness matrix through numerical results, an interpolation scheme of the Young's modulus and Poisson's ratio using different parameters is adopted. The numerical results demonstrate that the Poisson effect plays a key role in reducing the mean compliance of the final design. An important contribution of the present study is that the proposed concurrent optimization method can automatically distribute base materials with distinct Poisson's ratios between the macrostructural and microstructural levels under a single constraint of the total mass.

Football goal distributions and extremal statistics

NASA Astrophysics Data System (ADS)

Greenhough, J.; Birch, P. C.; Chapman, S. C.; Rowlands, G.

2002-12-01

We analyse the distributions of the number of goals scored by home teams, away teams, and the total scored in the match, in domestic football games from 169 countries between 1999 and 2001. The probability density functions (PDFs) of goals scored are too heavy-tailed to be fitted over their entire ranges by Poisson or negative binomial distributions which would be expected for uncorrelated processes. Log-normal distributions cannot include zero scores and here we find that the PDFs are consistent with those arising from extremal statistics. In addition, we show that it is sufficient to model English top division and FA Cup matches in the seasons of 1970/71-2000/01 on Poisson or negative binomial distributions, as reported in analyses of earlier seasons, and that these are not consistent with extremal statistics.