Capacity Requirements of Traffic Handling Schemes in Multi-Service Networks

Cataloged from PDF version of article.This paper deals with the impact of traffic handling mechanisms on capacity for different network architectures. Three traffic handling models are considered: per-flow, class-based and best-effort (BE). These models can be used to meet service guarantees, the major differences being in their complexity of implementations and in the quantity of network resources that must be provided. In this study, the performance is fixed and the required capacity determined for various combinations of traffic handling architectures for edge-core networks. This study provides a comparison of different QoS architectures. One key result of this work is that on the basis of capacity requirements, there is no significant difference between semi-aggregate traffic handling and per-flow traffic handling. However, best-effort handling requires significantly more capacity as compared to the other methods. (C) 2004 Elsevier B.V. All rights reserve

Computing moments of first passage times to a subset of states in Markov chains

This paper presents a relatively efficient and accurate method to compute the moments of first passage times to a subset of states in finite ergodic Markov chains. With the proposed method, the moment computation problem is reduced to the solution of a linear system of equations with the right-hand side governed by a novel recurrence for computing the higher-order moments. We propose using a form of the Grassmann-Taksar-Heyman (GTH) algorithm to solve these linear equations. Due to the form of the linear systems involved, the proposed method does not suffer from the drawbacks associated with GTH in a row-wise sparse implementation. © 2005 Society for Industrial and Applied Mathematics

Patterns of genetic diversity and linkage disequilibrium in a highly structured Hordeum vulgare association-mapping population for the Mediterranean basin

Population structure and genome-wide linkage disequilibrium (LD) were investigated in 192 Hordeum vulgare accessions providing a comprehensive coverage of past and present barley breeding in the Mediterranean basin, using 50 nuclear microsatellite and 1,130 DArT® markers. Both clustering and principal coordinate analyses clearly sub-divided the sample into five distinct groups centred on key ancestors and regions of origin of the germplasm. For given genetic distances, large variation in LD values was observed, ranging from closely linked markers completely at equilibrium to marker pairs at 50 cM separation still showing significant LD. Mean LD values across the whole population sample decayed below r 2 of 0.15 after 3.2 cM. By assaying 1,130 genome-wide DArT® markers, we demonstrated that, after accounting for population substructure, current genome coverage of 1 marker per 1.5 cM except for chromosome 4H with 1 marker per 3.62 cM is sufficient for whole genome association scans. We show, by identifying associations with powdery mildew that map in genomic regions known to have resistance loci, that associations can be detected in strongly stratified samples provided population structure is effectively controlled in the analysis. The population we describe is, therefore, shown to be a valuable resource, which can be used in basic and applied research in barle

Mapping adaptation of barley to droughted environments

Identifying barley genomic regions influencing the response of yield and its components to water deficits will aid in our understanding of the genetics of drought tolerance and the development of more drought tolerant cultivars. We assembled a population of 192 genotypes that represented landraces, old, and contemporary cultivars sampling key regions around the Mediterranean basin and the rest of Europe. The population was genotyped with a stratified set of 50 genomic and EST derived molecular markers, 49 of which were Simple Sequence Repeats (SSRs), which revealed an underlying population sub-structure that corresponded closely to the geographic regions in which the genotypes were grown. A more dense whole genome scan was generated by using Diversity Array Technology (DArT®) to generate 1130 biallelic markers for the population. The population was grown at two contrasting sites in each of seven Mediterranean countries for harvest 2004 and 2005 and grain yield data collected. Mean yield levels ranged from 0.3 to 6.2 t/ha, with highly significant genetic variation in low-yielding environments. Associations of yield with barley genomic regions were then detected by combining the DArT marker data with the yield data in mixed model analyses for the individual trials, followed by multiple regression of yield on markers to identify a multi-locus subset of significant markers/QTLs. QTLs exhibiting a pre-defined consistency across environments were detected in bins 4, 6, 6 and 7 on barley chromosomes 3H, 4H, 5H and 7H respectivel

Marked overlap of four genetic syndromes with dyskeratosis congenita confounds clinical diagnosis

Financial support provided by The Medical Research Council-MR/K000292/1, Children with Cancer- 2013/144 and Blood Wise-14032 (AJW, LC, SC, AE, TV, HT and ID). KMG is supported by the National Institute for Health Research through the NIHR Southampton Biomedical Research Centre

A Novel Poisoned Water Detection Method Using Smartphone Embedded Wi-Fi Technology and Machine Learning Algorithms

Water is a necessary fluid to the human body and automatic checking of its quality and cleanness is an ongoing area of research. One such approach is to present the liquid to various types of signals and make the amount of signal attenuation an indication of the liquid category. In this article, we have utilized the Wi-Fi signal to distinguish clean water from poisoned water via training different machine learning algorithms. The Wi-Fi access points (WAPs) signal is acquired via equivalent smartphone-embedded Wi-Fi chipsets, and then Channel-State-Information CSI measures are extracted and converted into feature vectors to be used as input for machine learning classification algorithms. The measured amplitude and phase of the CSI data are selected as input features into four classifiers k-NN, SVM, LSTM, and Ensemble. The experimental results show that the model is adequate to differentiate poison water from clean water with a classification accuracy of 89% when LSTM is applied, while 92% classification accuracy is achieved when the AdaBoost-Ensemble classifier is applied

First Observation of CP Violation in B0->D(*)CP h0 Decays by a Combined Time-Dependent Analysis of BaBar and Belle Data

We report a measurement of the time-dependent CP asymmetry of B0->D(*)CP h0 decays, where the light neutral hadron h0 is a pi0, eta or omega meson, and the neutral D meson is reconstructed in the CP eigenstates K+ K-, K0S pi0 or K0S omega. The measurement is performed combining the final data samples collected at the Y(4S) resonance by the BaBar and Belle experiments at the asymmetric-energy B factories PEP-II at SLAC and KEKB at KEK, respectively. The data samples contain ( 471 +/- 3 ) x 10^6 BB pairs recorded by the BaBar detector and ( 772 +/- 11 ) x 10^6, BB pairs recorded by the Belle detector. We measure the CP asymmetry parameters -eta_f S = +0.66 +/- 0.10 (stat.) +/- 0.06 (syst.) and C = -0.02 +/- 0.07 (stat.) +/- 0.03 (syst.). These results correspond to the first observation of CP violation in B0->D(*)CP h0 decays. The hypothesis of no mixing-induced CP violation is excluded in these decays at the level of 5.4 standard deviations.Comment: 9 pages, 2 figures, submitted to Physical Review Letter