Asymptotically optimal Bayesian sequential change detection and identification rules

We study the joint problem of sequential change detection and multiple hypothesis testing. Suppose that the common distribution of a sequence of i.i.d. random variables changes suddenly at some unobservable time to one of finitely many distinct alternatives, and one needs to both detect and identify the change at the earliest possible time. We propose computationally efficient sequential decision rules that are asymptotically either Bayes-optimal or optimal in a Bayesian fixed-error-probability formulation, as the unit detection delay cost or the misdiagnosis and false alarm probabilities go to zero, respectively. Numerical examples are provided to verify the asymptotic optimality and the speed of convergence. © 2012 Springer Science+Business Media, LLC

Handwritten digit recognition by bio-inspired hierarchical networks

The human brain processes information showing learning and prediction abilities but the underlying neuronal mechanisms still remain unknown. Recently, many studies prove that neuronal networks are able of both generalizations and associations of sensory inputs. In this paper, following a set of neurophysiological evidences, we propose a learning framework with a strong biological plausibility that mimics prominent functions of cortical circuitries. We developed the Inductive Conceptual Network (ICN), that is a hierarchical bio-inspired network, able to learn invariant patterns by Variable-order Markov Models implemented in its nodes. The outputs of the top-most node of ICN hierarchy, representing the highest input generalization, allow for automatic classification of inputs. We found that the ICN clusterized MNIST images with an error of 5.73% and USPS images with an error of 12.56%

A polynomial-time algorithm for optimizing over N-fold 4-block decomposable integer programs

In this paper we generalize N-fold integer programs and two-stage integer programs with N scenarios to N-fold 4-block decomposable integer programs. We show that for fixed blocks but variable N, these integer programs are polynomial-time solvable for any linear objective. Moreover, we present a polynomial-time computable optimality certificate for the case of fixed blocks, variable N and any convex separable objective function. We conclude with two sample applications, stochastic integer programs with second-order dominance constraints and stochastic integer multi-commodity flows, which (for fixed blocks) can be solved in polynomial time in the number of scenarios and commodities and in the binary encoding length of the input data. In the proof of our main theorem we combine several non-trivial constructions from the theory of Graver bases. We are confident that our approach paves the way for further extensions

A batch-service queueing model with a discrete batch Markovian arrival process

Queueing systems with batch service have been investigated extensively during the past decades. However, nearly all the studied models share the common feature that an uncorrelated arrival process is considered, which is unrealistic in several real-life situations. In this paper, we study a discrete-time queueing model, with a server that only initiates service when the amount of customers in system (system content) reaches or exceeds a threshold. Correlation is taken into account by assuming a discrete batch Markovian arrival process (D-BMAP), i.e. the distribution of the number of customer arrivals per slot depends on a background state which is determined by a first-order Markov chain. We deduce the probability generating function of the system content at random slot marks and we examine the influence of correlation in the arrival process on the behavior of the system. We show that correlation merely has a small impact on the threshold that minimizes the mean system content. In addition, we demonstrate that correlation might have a significant influence on the system content and therefore has to be included in the model

A non-parametric structural hybrid modeling approach for electricity prices

We develop a stochastic model of zonal/regional electricity prices, designed to reflect information in fuel forward curves and aggregated capacity and load as well as zonal or regional price spreads. We use a nonparametric model of the supply stack that captures heat rates and fuel prices for all generators in the market operator territory, combined with an adjustment term to approximate congestion and other zone-specific behavior. The approach requires minimal calibration effort, is readily adaptable to changing market conditions and regulations, and retains sufficient tractability for the purpose of forward price calibration. The model is illustrated for the spot and forward electricity prices of the PS zone in the PJM market, and the set of time-dependent risk premiums are inferred and analyzed

Financial diversification before modern portfolio theory: UK financial advice documents in the late nineteenth and the beginning of the twentieth century

The paper offers textual evidence from a series of financial advice documents in the late nineteenth century and the early twentieth century of how UK investors perceived of and managed risk. In the world’s largest financial centre of the time, UK investors were familiar with the concept of correlation and financial advisers’ suggestions were consistent with the recommendations of modern portfolio theory in relation to portfolio selection strategies. From the 1870s, there was an increased awareness of the benefits of financial diversification - primarily putting equal amounts into a number of different securities - with much of the emphasis being on geographical rather than sectoral diversification and some discussion of avoiding highly correlated investments. Investors in the past were not so naïve as mainstream financial discussions suggest today

Palaeoenvironment of Eocene prodelta in Spitsbergen recorded by the trace fossil Phycosiphon incertum

Ichnological, sedimentological and geochemical analyses were conducted on the Eocene Frysjaodden Formation in order to interpret palaeoenvironment prodelta sediments in the Central Basin of Spitsbergen. Phycosiphon incertum is the exclusive ichnotaxon showing differences in size, distribution, abundance and density, and relation to laminated/bioturbated intervals. Large P. incertum mainly occur dispersed, isolated and randomly distributed throughout the weakly laminated/non-laminated intervals. Small P. incertum occur occasionally in patches of several burrows within laminated intervals or as densely packed burrows in thin horizons in laminated intervals or constituting fully bioturbated intervals that are several centimetres thick. Ichnological changes are mainly controlled by oxygenation, although the availability of benthic food cannot be discarded. Changes in oxygenation and rate of sedimentation can be correlated with the registered variations in the Bouma sequence of the distal turbiditic beds within prodeltal shelf sediments.Funding for this research was provided by Project CGL2012-33281 (Secretaría de Estado de Investigación, Desarrollo e Innovación, Spain), Project RYC-2009-04316 (Ramón y Cajal Programme) and Projects RNM-3715 and RNM-7408 and Research Group RNM-178 (Junta de Andalucía). The authors benefited from a bilateral agreement between the universities of Granada and Oslo, supported by the University of Granada

J/ψ Production At Low Pt In Au+au And Cu+cu Collisions At Snn =200 Gev With The Star Detector

The J/ψ pT spectrum and nuclear modification factor (RAA) are reported for pT<5GeV/c and |y|<1 from 0% to 60% central Au+Au and Cu+Cu collisions at sNN=200GeV at STAR. A significant suppression of pT-integrated J/ψ production is observed in central Au+Au events. The Cu+Cu data are consistent with no suppression, although the precision is limited by the available statistics. RAA in Au+Au collisions exhibits a strong suppression at low transverse momentum and gradually increases with pT. The data are compared to high-pT STAR results and previously published BNL Relativistic Heavy Ion Collider results. 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