Probabilistic Basis Research Articles

Risk-Responsive Orbitofrontal Neurons Track Acquired Salience

Decision making is impacted by uncertainty and risk (i.e., variance). Activity in the orbitofrontal cortex, an area implicated in decision making, covaries with these quantities. However, this activity could reflect the heightened salience of situations in which multiple outcomes-reward and reward omission-are expected. To resolve these accounts, rats were trained to respond to cues predicting 100%, 67%, 33%, or 0% reward. Consistent with prior reports, some orbitofrontal neurons fired differently in anticipation of uncertain (33% and 67%) versus certain (100% and 0%) reward. However, over 90% of these neurons also fired differently prior to 100% versus 0% reward (or baseline) or prior to 33% versus 67% reward. These responses are inconsistent with risk but fit well with the representation of acquired salience linked to the sum of cue-outcome and cue-no-outcome associative strengths. These results expand our understanding of how the orbitofrontal cortex might regulate learning and behavior.

Overall Cost Comparison Between Cable and Overhead Lines Including the Costs for Repair After Random Failures

This paper deals with the comparison between the overall whole-of-life costs of overhead lines (OHL) and those of underground insulated cables (UGC). Almost all the investigations published so far, when analyzing maintainability issues, take into account only the costs of planned/periodical maintenance; here, a method for assessing also the expenses sustained for repair after random failures is proposed. The number of random failure events for each kind of component over the entire service life of a transmission line can only be predicted on a probabilistic basis: its expected value is estimated by making use of the relevant mean failure rates from recent statistical surveys. The entire procedure is shown by carrying out a particular case study as an example; the break-even point between the OHL-UGC overall costs, corresponding to a typical rural land Italian market value w <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sub> = 26.9 Euros/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , is identified. Nonetheless, the method may be widely applied to any type of OHL-UGC comparison.

A population-based approach to background discrimination in particle physics

Background properties in experimental particle physics are typically estimated from control samples corresponding to large numbers of events. This can provide precise knowledge of average background distributions, but typically does not take into account statistical fluctuations in a data set of interest. A novel approach based on mixture model decomposition is presented, as a way to extract additional information about statistical fluctuations from a given data set with a view to improving on knowledge of background distributions obtained from control samples. Events are treated as heterogeneous populations comprising particles originating from different processes, and individual particles are mapped to a process of interest on a probabilistic basis. The proposed approach makes it possible to estimate features of the background distributions from the data, and to extract information about statistical fluctuations that would otherwise be lost using traditional supervised classifiers trained on high-statistics control samples. A feasibility study on Monte Carlo is presented, together with a comparison with existing techniques. Finally, the prospects for the development of tools for intensive offline analysis of individual interesting events at the Large Hadron Collider are discussed.

Quality of classification explanations with PRBF

Recently two general methods for explaining classification models and their predictions have been introduced. Both methods are based on an idea that importance of a feature or a group of features in a specific model can be estimated by simulating lack of knowledge about the values of the feature(s). For the majority of models this requires an approximation by averaging over all possible feature values. A probabilistic radial basis function network (PRBF) is one of the models where such approximation is not necessary and therefore offers a chance to evaluate the quality of approximation by comparing it to the exact solution.We present both explanation methods and demonstrate their behavior with PRBF. The explanations make individual decisions of classifiers transparent and allow inspection and visualization of otherwise opaque models.We empirically compare the quality of explanations based on marginalization of the Gaussian distribution (the exact method) and explanation with averaging over all feature values (the approximation). The results show that the approximation method and the exact solution give very similar results, which increases the confidence in the explanation methodology also for other classification models.

Evaluating the effective spectral seismic amplification factor on a probabilistic basis

All contemporary seismic Codes have adopted smooth design acceleration response spectra, which have derived by statistical analysis of many elastic response spectra of natural accelerograms. The above smooth design spectra are characterized by two main branches, an horizontal branch that is 2.5 times higher than the peak ground acceleration, and a declining parabolic branch. According to Eurocode EN/1998, the period range of the horizontal, flat branch is extended from 0.1 s, for rock soils, up to 0.8 s for softer ones. However, from many natural recorded accelerograms of important earthquakes, the real spectral amplification factor appears to be much higher than 2.5 and this means that the spectrum leads to an unsafe seismic design of the structures. This point is an issue open to question and it is the object of the present study. In the present paper, the spectral amplification factor of the smooth design acceleration spectra is re-calculated on the grounds of a known "reliability index" for a desired probability of exceedance. As a pilot scheme, the seismic area of Greece is chosen, as it is the most seismically hazardous area in Europe. The accelerograms of the 82 most important earthquakes, which have occurred in Greece during the last 38 years, are used. The soil categories are taken into account according to EN/1998. The results that have been concluded from these data are compared with the results obtained from other strong earthquakes reported in the World literature.

Characterisation of power system events on South African transmission power lines

Records of faults occurring on the South African power transmission system over a 16-year period have been collected. Over 12,000 faults were analysed to find statistical relationships between local climate, key design parameters of the overhead lines, and the main causes of power system faults identified as bird streamers, lightning, fire and pollution. The results characterise the performance of the South African transmission system on a probabilistic basis and illustrate differences in fault cause statistics for the summer and winter rainfall areas of South Africa and for different times of the year and day. The analysis illustrates the effectiveness of bird guards on towers.

Copula-based modeling of stochastic wind power in Europe and implications for the Swiss power grid

Large scale integration of wind energy poses new challenges to the European power system due to its stochastic nature and often remote location. In this paper a multivariate uncertainty analysis problem is formulated for the integration of stochastic wind energy in the European grid. By applying copula theory a synthetic set of data is generated from scarce wind speed reanalysis data in order to achieve the increased sample size for the subsequent Monte Carlo simulation.In the presented case study, European wind power samples are generated from the modeled stochastic process. Under the precondition of a modeled perfect market environment, wind power impacts dispatch decisions and therefore leads to alterations in power balances. Stochastic power balances are implemented in a detailed model of the European electricity network, based on the generated samples. Finally, a Monte Carlo method is used to determine power flows and contingencies in the system. An indicator is elaborated in order to analyze risk of overloading and to prioritize necessary grid reinforcements. Implications for the Swiss power grid are investigated in detail, revealing that the current system is significantly put at risk in certain areas by the further integration of wind power in Europe.It is the first time that the results of a probabilistic model for wind energy are further deployed within a power system analysis of the interconnected European grid. The method presented in this paper allows to account for stochastic wind energy in a load flow analysis and to evaluate deterministic indicators, such as the N−1 criterion, on a probabilistic basis. Thus, it constitutes an important extension of deterministic models.

Modeling Undeposited CNTs for CNTFET Operation

The carbon nanotube field-effect transistor (CNTFET) is a promising device to supersede the MOSFET at the end of the technology roadmap of the CMOS. When designing and manufacturing a CNTFET, additional features such as pitch, number, and position of the CNTs must be considered to assess its performance. One of the defect types that can occur when fabricating a CNTFET is the absence of some CNTs following the deposition/growth step. As a result of this type of defect, a CNTFET will show a change in operational characteristics because the drain current, gate capacitance, and delay will be affected due to the lower number of CNTs with uneven spacing between them present in the channel of the transistor. This paper presents a new model by which the drain current, the gate capacitance, and the delay can be found when not all CNTs are deposited on the substrate. This results in an uneven CNT spacing in the channel; new equations are derived and shown to be applicable to both defective and defect-free CNTFETs. The proposed model has been implemented in MATLAB and has been extensively simulated to show that defects due to undeposited CNTs have a significant impact on the operation of a CNTFET. Delay as degradation in performance is shown to be related to both the number and position of the defects; an extensive delay analysis on both deterministic and probabilistic basis is presented.

Maximum-likelihood estimation of damage location in guided-wave structural health monitoring

This paper describes the formulation of a maximum-likelihood estimate of damage location for guided-wave structural health monitoring (GWSHM) using a minimally informed, Rayleigh-based statistical model of scattered wave measurements. Also introduced are two statistics-based methods for evaluating localization performance: the localization probability density function estimate and the localizer operating characteristic curve. Using an ensemble of measurements from an instrumented plate with stiffening stringers, the statistical performance of the so-called Rayleigh maximum-likelihood estimate (RMLE) is compared with that of seven previously reported localization methods. The RMLE proves superior in all test cases, and is particularly effective in localizing damage using very sparse arrays consisting of as few as three transducers. The probabilistic basis used for modelling the complicated wave scattering behaviour makes the algorithm especially suited for localizing damage in complicated structures, with the potential for improved performance with increasing structure complexity.

A Comparative Study of Signal Processing and Pattern Recognition Approach for Power Quality Disturbance Classification

This paper presents an extensive study of the advanced signal processing techniques for the classification of different Power Quality (PQ) disturbances. A detailed study of application of the signal processing techniques like Wavelet Transform (WT) and Wavelet Packet Transform (WPT) is carried out for the said purpose. These techniques are used to extract useful information from the raw signal in different frequency bands and give the time–frequency information. Hence, the statistical features are derived from this information and are used for the classification purpose. The features extracted are given to the Neural Network (NN) for training and subsequently it is tested for an effective classification. Three types of NN classifiers, namely, Multi Layer Feed Forward (MLFF), Probabilistic Neural Network (PNN) and Radial Basis Function (RBF) NN are analyzed for effective classification of PQ disturbances. For real-time implementation, one has to see the structural complexity of NN along with its capability of accurate classification. Hence, these NNs are compared with respect to classification performance and structural complexity. The simulation results show that the PNN offers acceptable classification accuracies.

Aplicação do conceito do índice padronizado de precipitação à série decendial da diferença entre precipitação pluvial e evapotranspiração potencial

O monitoramento probabilístico e padronizado da variabilidade temporal dos totais de chuva, proposto pelo modelo do Índice Padronizado de Precipitação (SPI), tem sido utilizado por programas estaduais e federais na detecção de regiões com severos déficits de precipitação pluvial. Contudo, algumas questões conceituais, inerentes a um índice que utiliza apenas a precipitação pluvial como variável independente, tendem a distanciar esse índice dos interesses agrícolas. O objetivo do trabalho foi verificar a possibilidade de aplicação desse conceito de monitoramento probabilístico/padronizado, adotado/proposto pelo SPI, às séries decendiais da diferença entre precipitação pluvial e evapotranspiração potencial (P-ETP). Utilizando dados meteorológicos da localidade de Campinas (SP), entre 1948 e 2008, verificou-se bom ajuste das séries de P-ETP à distribuição geral dos valores extremos. Essa última característica permitiu o desenvolvimento de um algoritmo cujo resultado foi denominado de índice padronizado da diferença entre a precipitação pluvial e a evapotranspiração potencial (IPP-ETP) que, por sua vez, possibilitou a incorporação do conceito do SPI às séries decendiais da diferença entre precipitação pluvial e evapotranspiração potencial.

Optimising the balance between security and economy on a probabilistic basis

Decision-making methods based on a deterministic criterion, such as optimal power flow (OPF) and security-constrained optimal power flow (SCOPF), have been widely applied to practical power system operation. With these methods, the operating conditions of the power system are classified as secure or insecure based on predefined deterministic criteria. However, such a binary secure/insecure index based on a deterministic analysis does not take into account the relative risks associated with random outages of generation and transmission facilities. Therefore using deterministic decision-making methods such as OPF and SCOPF to balance the security and economy can be unnecessarily expensive. This study proposes an optimal probabilistic security (OPS) approach, which balances security and economy on a probabilistic basis. The objective of the OPS is to minimise the expected social cost, which is the sum of the expected operating cost and the expected interruption cost. An improved particle swarm optimisation technique is used to solve this probabilistic optimisation problem. Unlike other risk-based decision-making algorithms, the OPS is a self-contained decision-making tool, which does not require the definition of an arbitrary risk threshold. The OPS determines operator actions that optimally balance security and economy for given weather and operating conditions. The OPS is compared with the OPF and SCOPF using a six-bus system and the IEEE-RTS.

Markov Decision Processes for Optimizing Human Workflows

Workflows are used by domain analysts as a tool to describe the synchronization of activities in a business domain. The Business Process Management Notation (BPMN) has become a standard to characterize Workflows. Nevertheless, BPMN alone does not provide tools for aligning business models and IT architectures. Currently, there is not a method which promotes making decisions based on a technique with a probabilistic basis for providing financial value to a [human] workflow. If such method could exist, it would help the domain analyst to understand what sections of the business and IT architecture could be re-engineered for adding value. Markov Decision Processes (MDP's) can be the centerpiece of such a method. MDP's are introduced as a means to pinpoint assets to be designed, managed, and continuously improved, while enhancing business agility and operational performance. [Service Science, ISSN 2164-3962 (print), ISSN 2164-3970 (online), was published by Services Science Global (SSG) from 2009 to 2011 as issues under ISBN 978-1-4276-2090-3.]

Convergent recombination shapes the clonotypic landscape of the naive T-cell repertoire.

Adaptive T-cell immunity relies on the recruitment of antigen-specific clonotypes, each defined by the expression of a distinct T-cell receptor (TCR), from an array of naïve T-cell precursors. Despite the enormous clonotypic diversity that resides within the naïve T-cell pool, interindividual sharing of TCR sequences has been observed within mobilized T-cell responses specific for certain peptide-major histocompatibility complex (pMHC) antigens. The mechanisms that underlie this phenomenon have not been fully elucidated, however. A mechanism of convergent recombination has been proposed to account for the occurrence of shared, or "public," TCRs in specific memory T-cell populations. According to this model, TCR sharing between individuals is directly related to TCR production frequency; this, in turn, is determined on a probabilistic basis by the relative generation efficiency of particular nucleotide and amino acid sequences during the recombination process. Here, we tested the key predictions of convergent recombination in a comprehensive evaluation of the naïve CD8(+) TCRβ repertoire in mice. Within defined segments of the naïve CD8(+) T-cell repertoire, TCRβ sequences with convergent features were (i) present at higher copy numbers within individual mice and (ii) shared between individual mice. Thus, the naïve CD8(+) T-cell repertoire is not flat, but comprises a hierarchy of recurrence rates for individual clonotypes that is determined by relative production frequencies. These findings provide a framework for understanding the early mobilization of public CD8(+) T-cell clonotypes, which can exert profound biological effects during acute infectious processes.

Classification using distance nearest neighbours

This paper proposes a new probabilistic classification algorithm using a Markov random field approach. The joint distribution of class labels is explicitly modelled using the distances between feature vectors. Intuitively, a class label should depend more on class labels which are closer in the feature space, than those which are further away. Our approach builds on previous work by Holmes and Adams (2002, 2003) and Cucala et al. (2008). Our work shares many of the advantages of these approaches in providing a probabilistic basis for the statistical inference. In comparison to previous work, we present a more efficient computational algorithm to overcome the intractability of the Markov random field model. The results of our algorithm are encouraging in comparison to the k-nearest neighbour algorithm.

Characterization of Parathyroid Hormone using HMM Framework

Sequence comparison is a key tool in bioinformatics. The objective of a HMM profile is to statistically model patterns in biological sequences by identifying combinations of matches, in-dels, and gaps in the alignment of a query sequence to a profile model. HMM profile analysis can be used for multiple sequence alignment, for a database search, to analyze sequence composition and pattern segmentation, and to predict protein structure and locate genes by predicting open reading frames. Profile analysis has long been a useful tool in finding and aligning distantly related sequences and in identifying known sequence domains in new sequences. Hidden Markov modeling, a technique that has been used for years in speech recognition, is now being applied to many types of problems in molecular sequence analysis. In particular, this technique can produce profiles that are an improvement over traditionally constructed profiles. Profile hidden Markov models (HMMs) have several advantages over standard profiles. Profile HMMs have a formal probabilistic basis and have a consistant theory behind gap and insertion scores, in contrast to standard profile methods which use heuristic methods. This paper describes how HMM profiles are used to characterize protein families. The full text of the article is not available in the cache. Kindly refer the IJCA digital library at www.ijcaonline.org for the complete article. In case, you face problems while downloading the full-text, please send a mail to editor at editor@ijcaonline.org

Probabilistic Design of Wind Turbines

Probabilistic design of wind turbines requires definition of the structural elements to be included in the probabilistic basis: e.g., blades, tower, foundation; identification of important failure modes; careful stochastic modeling of the uncertain parameters; recommendations for target reliability levels and recommendation for consideration of system aspects. The uncertainties are characterized as aleatoric (physical uncertainty) or epistemic (statistical, measurement and model uncertainties). Methods for uncertainty modeling consistent with methods for estimating the reliability are described. It is described how uncertainties in wind turbine design related to computational models, statistical data from test specimens, results from a few full-scale tests and from prototype wind turbines can be accounted for using the Maximum Likelihood Method and a Bayesian approach. Assessment of the optimal reliability level by cost-benefit optimization is illustrated by an offshore wind turbine example. Uncertainty modeling is illustrated by an example where physical, statistical and model uncertainties are estimated.

Probabilistic modelling of the role of the human factor in the Helicopter-Landing-Ship (HLS) situation

This analysis contains a novel attempt to quantify, on the probabilistic basis, the role that the human factor plays, in terms of the total operation time, in the Helicopter-Landing-Ship (HLS) situation. The considered operation time includes the time required for the officer-on-ship-board and the helicopter pilot to make their go-ahead decisions, and the time needed for the actual landing. It is assumed, for the sake of simplicity, that these times could be approximated by the Rayleigh law, while the duration of the lull follows the normal (Gaussian) law. Safe landing can be expected if the probability that it takes place during the lull time in the sea condition is sufficiently high. We develop a simple, easy-to-use and physically meaningful model to evaluate this probability. Our model can be used in the risk analysis of the landing situation, as well as in the probabilistic assessment of the strength of the helicopter undercarriage, if necessary. The model can be employed also when developing guidelines for personnel training and particularly when there is a need (intent) to establish (specify) the acceptable (allowable) decision making time.

Maksymilian Rose, neurolog, psychiatra i wybitny znawca cytoarchitektoniki kory mózgu

<dm:abstracts xmlns:dm="http://www.elsevier.com/xml/dm/dtd"><ce:abstract xmlns:ce="http://www.elsevier.com/xml/common/dtd" view="all" class="author" id="aep-abstract-id1"><ce:section-title>Publisher Summary</ce:section-title><ce:abstract-sec view="all" id="aep-abstract-sec-id1"><ce:simple-para id="SP0005" view="all">This chapter discusses the principles of classical architectonic mapping in the context of recent imaging techniques. It presents an observer-independent approach for a quantitative analysis of cortical areas and their borders, which is based on a multivariate statistical analysis of the cytoarchitecture and illustrates the application of this approach for the cytoarchitectonic mapping of the human visual cortex. Important criteria for cytoarchitectonic mapping are the absolute thickness of cortical layers, the proportionate thickness of a layer relative to the other cortical layers and to the total cortical depth, the presence of clearly recognizable laminar borders and vertical columns, the packing density and size of neuronal cell bodies, the homogeneous or clustered distribution of cell bodies throughout the layers, and the presence of special cell types such as Betz cells. Understanding the regional distributions of neurotransmitter receptors is likely to provide a crucial intermediary level of description between function and structure, since different cytoarchitectonic and functional areas have different mean receptor densities as well as distinct laminar distribution patterns. Another way for a better understanding of brain function and the underlying anatomy is to compare architectonic maps obtained in postmortem brains with activation maps obtained in functional imaging studies in a common spatial reference system. Since these two kinds of maps stem from different subsets of brains, such a comparison must be performed on a probabilistic basis.</ce:simple-para></ce:abstract-sec></ce:abstract></dm:abstracts>

Helicopter Landing Ship: Undercarriage Strength and the Role of the Human Factor

We address, using probabilistic modeling and the extreme-value-distribution technique, the helicopter undercarriage strength in a helicopter-landing-ship situation. Our analysis contains an attempt to quantify, on the probabilistic basis, the role of the human factor in the situation in question. This factor is important from the standpoint of the operation time that affects the likelihood of safe landing during the lull period in the sea condition. The operation time includes (1) the time required for the officer-on-ship-board and the helicopter pilot to make their go-ahead decisions and (2) the time of actual landing. It is assumed, for the sake of simplicity, that both these times could be approximated by Rayleigh’s law, while the lull duration follows the normal law with a high enough ratio of the mean value to the standard deviation. Safe landing could be expected if the probability that it occurs during the lull time is sufficiently high. The probability that the helicopter undercarriage strength is not compromised can be evaluated as a product of the probability that landing indeed occurs during the lull time and the probability that the relative velocity of the helicopter undercarriage with respect to the ship’s deck at the moment of encounter does not exceed the allowable level. This level is supposed to be determined for the helicopter-landing-ground situation. The developed model can be used when developing specifications for the undercarriage strength, as well as guidelines for personnel training. Particularly, the model can be of help when establishing the times to be met by the two humans involved to make their go-ahead decisions for landing and to actually land the helicopter. Plenty of additional risk analyses (associated with the need to quantify various underlying uncertainties) and human psychology related efforts will be needed, of course, to make such guidelines practical.