Spectral properties of the tandem Jackson network, seen as a quasi-birth-and-death process

Quasi-birth-and-death (QBD) processes with infinite “phase spaces” can exhibit unusual and interesting behavior. One of the simplest examples of such a process is the two-node tandem Jackson network, with the “phase” giving the state of the first queue and the “level” giving the state of the second queue. In this paper, we undertake an extensive analysis of the properties of this QBD. In particular, we investigate the spectral properties of Neuts’s R-matrix and show that the decay rate of the stationary distribution of the “level” process is not always equal to the convergence norm of R. In fact, we show that we can obtain any decay rate from a certain range by controlling only the transition structure at level zero, which is independent of R. We also consider the sequence of tandem queues that is constructed by restricting the waiting room of the first queue to some finite capacity, and then allowing this capacity to increase to infinity. We show that the decay rates for the finite truncations converge to a value, which is not necessarily the decay rate in the infinite waiting room case. Finally, we show that the probability that the process hits level n before level 0 given that it starts in level 1 decays at a rate which is not necessarily the same as the decay rate for the stationary distribution.

Efficient simulation of a Tandem Jackson Network

The two-node tandem Jackson network serves as a convenient reference model for the analysis and testing of different methodologies and techniques in rare event simulation. In this paper we consider a new approach to efficiently estimate the probability that the content of the second buffer exceeds some high level L before it becomes empty, starting from a given state. The approach is based on a Markov additive process representation of the buffer processes, leading to an exponential change of measure to be used in an importance sampling procedure. Unlike changes of measures proposed and studied in recent literature, the one derived here is a function of the content of the first buffer. We prove that when the first buffer is finite, this method yields asymptotically efficient simulation for any set of arrival and service rates. In fact, the relative error is bounded independent of the level L; a new result which is not established for any other known method. When the first buffer is infinite, we propose a natural extension of the exponential change of measure for the finite buffer case. In this case, the relative error is shown to be bounded (independent of L) only when the second server is the bottleneck; a result which is known to hold for some other methods derived through large deviations analysis. When the first server is the bottleneck, experimental results using our method seem to suggest that the relative error is bounded linearly in L.

A neural network-based preset generation tool for a steel tandem cold mill

This paper traces the development of a software tool, based oil a combination of artificial neural networks (ANN) and a few process equations. aiming to serve as a backup operation instrument in the reference generation for real-time controllers of a steel tandem cold mill By emulating the mathematical model responsible for generating presets under normal operational conditions, the system works as ail option to maintain plant operation in the event of a failure in the processing unit that executes the mathematical model. The system, built from the production data collected over six years of plant operation, steered to the replacement of the former backup operation mode (based oil a lookup table). which degraded both product quality and plant productivity. The study showed that ANN are appropriated tools for the intended purpose and that by this instrument it is possible to achieve nearly the totality of the presets needed by this land of process. The text characterizes the problem, relates the investigated options to solve it. justifies the choice of the ANN approach, describes the methodology and system implementation and, finally, shows and discusses the attained results. (C) 2009 Elsevier Ltd. All rights reserved

Mathematically gifted male adolescents activate a unique brain network during mental rotation

Mental rotation involves the creation and manipulation of internal images, with the later being particularly useful cognitive capacities when applied to high-level mathematical thinking and reasoning. Many neuroimaging studies have demonstrated mental rotation to be mediated primarily by the parietal lobes, particularly on the right side. Here, we use fMRI to show for the first time that when performing 3-dimensional mental rotations, mathematically gifted male adolescents engage a qualitatively different brain network than those of average math ability, one that involves bilateral activation of the parietal lobes and frontal cortex, along with heightened activation of the anterior cingulate. Reliance on the processing characteristics of this uniquely bilateral system and the interplay of these anterior/posterior regions may be contributors to their mathematical precocity.

Optical nonlinearity in Tandem SI-C photodetectors

The behavior of tandem pin heterojunctions based on a-SiC: H alloys is investigated under different optical and electrical bias conditions. The devices are optimized to act as optically selective wavelength filters. Depending on the device configuration (optical gaps, thickness, sequence of cells in the stack structure) and on the applied voltage (positive or negative) and optical bias (wavelength, intensity, frequency) it is possible to combine the wavelength discrimination function with the self amplification of the signal. This wavelength nonlinearity allows the amplification or the rejection of a weak signal-impulse. The device works as an active tunable optical filter for wavelength selection and can be used as an add/drop multiplexer (ADM) which enables data to enter and leave an optical network bit stream without having to demultiplex the stream. Results show that, even under weak transient input signals, the background wavelength controls the output signal. This nonlinearity, due to the transient asymmetrical light penetration of the input channels across the device together with the modification on the electrical field profile due to the optical bias, allows tuning an input channel without demultiplexing the stream. This high optical nonlinearity makes the optimized devices attractive for the amplification of all optical signals. Transfer characteristics effects due to changes in steady state light, control d.c. voltage and applied light pulses are presented. Based on the experimental results and device configuration an optoelectronic model is developed. The transfer characteristics effects due to changes in steady state light, dc control voltage or applied light pulses are simulated and compared with the experimental data. A good agreement was achieved.

The Evolution of roommate networks: a comment on Jackson and Watts JET (2002)

We extend Jackson and Watts's (2002) result on the coincidence of S-stochastically stable and core stable networks from marriage problems to roommate problems. In particular, we show that the existence of a side-optimal core stable network, on which the proof of Jackson and Watts (2002) hinges, is not crucial for their result.

Prospective universal application of mycobacterial interspersed repetitive-unit-variable-number tandem-repeat genotyping to characterize Mycobacterium tuberculosis isolates for fast identification of clustered and orphan cases.

The use of molecular tools for genotyping Mycobacterium tuberculosis isolates in epidemiological surveys in order to identify clustered and orphan strains requires faster response times than those offered by the reference method, IS6110 restriction fragment length polymorphism (RFLP) genotyping. A method based on PCR, the mycobacterial interspersed repetitive-unit-variable-number tandem-repeat (MIRU-VNTR) genotyping technique, is an option for fast fingerprinting of M. tuberculosis, although precise evaluations of correlation between MIRU-VNTR and RFLP findings in population-based studies in different contexts are required before the methods are switched. In this study, we evaluated MIRU-VNTR genotyping (with a set of 15 loci [MIRU-15]) in parallel to RFLP genotyping in a 39-month universal population-based study in a challenging setting with a high proportion of immigrants. For 81.9% (281/343) of the M. tuberculosis isolates, both RFLP and MIRU-VNTR types were obtained. The percentages of clustered cases were 39.9% (112/281) and 43.1% (121/281) for RFLP and MIRU-15 analyses, and the numbers of clusters identified were 42 and 45, respectively. For 85.4% of the cases, the RFLP and MIRU-15 results were concordant, identifying the same cases as clustered and orphan (kappa, 0.7). However, for the remaining 14.6% of the cases, discrepancies were observed: 16 of the cases clustered by RFLP analysis were identified as orphan by MIRU-15 analysis, and 25 cases identified as orphan by RFLP analysis were clustered by MIRU-15 analysis. When discrepant cases showing subtle genotypic differences were tolerated, the discrepancies fell from 14.6% to 8.6%. Epidemiological links were found for 83.8% of the cases clustered by both RFLP and MIRU-15 analyses, whereas for the cases clustered by RFLP or MIRU-VNTR analysis alone, links were identified for only 30.8% or 38.9% of the cases, respectively. The latter group of cases mainly comprised isolates that could also have been clustered, if subtle genotypic differences had been tolerated. MIRU-15 genotyping seems to be a good alternative to RFLP genotyping for real-time interventional schemes. The correlation between MIRU-15 and IS6110 RFLP findings was reasonable, although some uncertainties as to the assignation of clusters by MIRU-15 analysis were identified.

Rapid, automated detection of stem canker symptoms in woody perennials using artificial neural network analysis

Background Pseudomonas syringae can cause stem necrosis and canker in a wide range of woody species including cherry, plum, peach, horse chestnut and ash. The detection and quantification of lesion progression over time in woody tissues is a key trait for breeders to select upon for resistance. Results In this study a general, rapid and reliable approach to lesion quantification using image recognition and an artificial neural network model was developed. This was applied to screen both the virulence of a range of P. syringae pathovars and the resistance of a set of cherry and plum accessions to bacterial canker. The method developed was more objective than scoring by eye and allowed the detection of putatively resistant plant material for further study. Conclusions Automated image analysis will facilitate rapid screening of material for resistance to bacterial and other phytopathogens, allowing more efficient selection and quantification of resistance responses.

Efficient method for AC transmission network expansion planning

A combinatorial mathematical model in tandem with a metaheuristic technique for solving transmission network expansion planning (TNEP) using an AC model associated with reactive power planning (RPP) is presented in this paper. AC-TNEP is handled through a prior DC model while additional lines as well as VAr-plants are used as reinforcements to cope with real network requirements. The solution of the reinforcement stage can be obtained by assuming all reactive demands are supplied locally to achieve a solution for AC-TNEP and by neglecting the local reactive sources, a reactive power planning (RPP) will be managed to find the minimum required reactive power sources. Binary GA as well as a real genetic algorithm (RCA) are employed as metaheuristic optimization techniques for solving this combinatorial TNEP as well as the RPP problem. High quality results related with lower investment costs through case studies on test systems show the usefulness of the proposal when working directly with the AC model in transmission network expansion planning, instead of relaxed models. (C) 2010 Elsevier B.V. All rights reserved.

Search for supersymmetry in events with opposite-sign dileptons and missing transverse energy using an artificial neural network

In this paper, a search for supersymmetry (SUSY) is presented in events with two opposite-sign isolated leptons in the final state, accompanied by hadronic jets and missing transverse energy. An artificial neural network is employed to discriminate possible SUSY signals from a standard model background. The analysis uses a data sample collected with the CMS detector during the 2011 LHC run, corresponding to an integrated luminosity of 4.98 fb-1 of proton-proton collisions at the center-of-mass energy of 7 TeV. Compared to other CMS analyses, this one uses relaxed criteria on missing transverse energy (EÌ̧T>40 GeV) and total hadronic transverse energy (HT>120 GeV), thus probing different regions of parameter space. Agreement is found between standard model expectation and observations, yielding limits in the context of the constrained minimal supersymmetric standard model and on a set of simplified models. © 2013 CERN.

NOR (NAND) network design : error-compensation procedures for fan-in and fan-out restricted networks (NETTRA-E1-FIFO and NETTRA-E2-FIFO /

Thesis (M. S.)--University of Illinois at Urbana-Champaign.

Wavelength-division and spatial multiplexing using tandem interferometers for Bragg grating sensor networks

We present a new method for the interrogation of large arrays of Bragg grating sensors. Eight gratings operating between the wavelengths of 1533 and 1555 nm have been demultiplexed. An unbalanced Mach—Zehnder interferometer illuminated by a single low-coherence source provides a high-phase-resolution output for each sensor, the outputs of which are sequentially selected in wavelength by a tunable Fabry-Perot interferometer. The minimum detectable strain measured was 90 ne-vHz at 7 Hz for a wavelength of 1535 nm.

The upstream Variable Number Tandem Repeat polymorphism of the monoamine oxidase type A gene influences trigeminal pain-related evoked responses

Monoamines have an important role in neural plasticity, a key factor in cortical pain processing that promotes changes in neuronal network connectivity. Monoamine oxidase type A (MAOA) is an enzyme that, due to its modulating role in monoaminergic activity, could play a role in cortical pain processing. The X-linked MAOA gene is characterized by an allelic variant of length, the MAOA upstream Variable Number Tandem Repeat (MAOA-uVNTR) region polymorphism. Two allelic variants of this gene are known, the high-activity MAOA (HAM) and low-activity MAOA (LAM). We investigated the role of MAOA-uVNTR in cortical pain processing in a group of healthy individuals measured by the trigeminal electric pain-related evoked potential (tPREP) elicited by repeated painful stimulation. A group of healthy volunteers was genotyped to detect MAOA-uVNTR polymorphism. Electrical tPREPs were recorded by stimulating the right supraorbital nerve with a concentric electrode. The N2 and P2 component amplitude and latency as well as the N2-P2 inter-peak amplitude were measured. The recording was divided into three blocks, each containing 10 consecutive stimuli and the N2-P2 amplitude was compared between blocks. Of the 67 volunteers, 37 were HAM and 30 were LAM. HAM subjects differed from LAM subjects in terms of amplitude of the grand-averaged and first-block N2-P2 responses (HAM>LAM). The N2-P2 amplitude decreased between the first and third block in HAM subjects but not LAM subjects. The MAOA-uVNTR polymorphism seemed to influence the brain response in a repeated tPREP paradigm and suggested a role of the MAOA as a modulator of neural plasticity related to cortical pain processing. Monoamines have an important role in neural plasticity, a key factor in cortical pain processing that promotes changes in neuronal network connectivity. Monoamine oxidase type A (MAOA) is an enzyme that, due to its modulating role in monoaminergic activity, could play a role in cortical pain processing. © 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Wavelength-division and spatial multiplexing using tandem interferometers for Bragg grating sensor networks

We present a new method for the interrogation of large arrays of Bragg grating sensors. Eight gratings operating between the wavelengths of 1533 and 1555 nm have been demultiplexed. An unbalanced Mach—Zehnder interferometer illuminated by a single low-coherence source provides a high-phase-resolution output for each sensor, the outputs of which are sequentially selected in wavelength by a tunable Fabry-Perot interferometer. The minimum detectable strain measured was 90 ne-vHz at 7 Hz for a wavelength of 1535 nm.

Measuring the Diversity and the Integration of Film Production in Mercosur: A Social Network Analysis

Based on an original and comprehensive database of all feature fiction films produced in Mercosur between 2004 and 2012, the paper analyses whether the Mercosur film industry has evolved towards an integrated and culturally more diverse market. It provides a summary of policy opportunities in terms of integration and diversity, emphasizing the limiter role played by regional policies. It then shows that although the Mercosur film industry remains rather disintegrated, it tends to become more integrated and culturally more diverse. From a methodological point of view, the combination of Social Network Analysis and the Stirling Model opens up interesting research tracks to analyse creative industries in terms of their market integration and their cultural diversity.