Optimal decision fusion and its application on 3D face recognition

Fusion is a popular practice to combine multiple classifiers or multiple modalities in biometrics. In this paper, optimal decision fusion (ODF) by AND rule and OR rule is presented. We show that the decision fusion can be done in an optimal way such that it always gives an improvement in terms of error rates over the classifiers that are fused. Both the optimal decision fusion theory and the experimental results on the FRGC 2D and 3D face data are given. Experiments show that the optimal decision fusion effectively combines the 2D texture and 3D shape information, and boosts the performance of the system

A Linux Real-Time Packet Scheduler for Reliable Static SDN Routing

In a distributed computing environment, guaranteeing the hard deadline for real-time messages is essential to ensure schedulability of real-time tasks. Since capabilities of the shared resources for transmission are limited, e.g., the buffer size is limited on network devices, it becomes a challenge to design an effective and feasible resource sharing policy based on both the demand of real-time packet transmissions and the limitation of resource capabilities. We address this challenge in two cooperative mechanisms. First, we design a static routing algorithm to find forwarding paths for packets to guarantee their hard deadlines. The routing algorithm employs a validation-based backtracking procedure capable of deriving the demand of a set of real-time packets on each shared network device, and it checks whether this demand can be met on the device. Second, we design a packet scheduler that runs on network devices to transmit messages according to our routing requirements. We implement these mechanisms on virtual software-defined network (SDN) switches and evaluate them on real hardware in a local cluster to demonstrate the feasibility and effectiveness of our routing algorithm and packet scheduler

A role for jasmonates in the release of dormancy by cold stratification in wheat

Hydration at low temperatures, commonly referred to as cold stratification, is widely used for releasing dormancy and triggering germination in a wide range of species including wheat. However, the molecular mechanism that underlies its effect on germination has largely remained unknown. Our previous studies showed that methyl-jasmonate, a derivative of jasmonic acid (JA), promotes dormancy release in wheat. In this study, we found that cold-stimulated germination of dormant grains correlated with a transient increase in JA content and expression of JA biosynthesis genes in the dormant embryos after transfer to 20 (o)C. The induction of JA production was dependent on the extent of cold imbibition and precedes germination. Blocking JA biosynthesis with acetylsalicylic acid (ASA) inhibited the cold-stimulated germination in a dose-dependent manner. In addition, we have explored the relationship between JA and abscisic acid (ABA), a well-known dormancy promoter, in cold regulation of dormancy. We found an inverse relationship between JA and ABA content in dormant wheat embryos following stratification. ABA content decreased rapidly in response to stratification, and the decrease was reversed by addition of ASA. Our results indicate that the action of JA on cold-stratified grains is mediated by suppression of two key ABA biosynthesis genes, TaNCED1 and TaNCED2.This project was funded by a CSIRO Office of the Chief Executive PDF scheme

Grand canonical diffusion-influenced reactions: a stochastic theory with applications to multiscale reaction-diffusion simulations

Smoluchowski-type models for diffusion-influenced reactions (A+B -> C) can be formulated within two frameworks: the probabilistic-based approach for a pair A, B of reacting particles and the concentration-based approach for systems in contact with a bath that generates a concentration gradient of B particles that interact with A. Although these two approaches are mathematically similar, it is not straightforward to establish a precise mathematical relationship between them. Determining this relationship is essential to derive particle-based numerical methods that are quantitatively consistent with bulk concentration dynamics. In this work, we determine the relationship between the two approaches by introducing the grand canonical Smoluchowski master equation (GC-SME), which consists of a continuous-time Markov chain that models an arbitrary number of B particles, each one of them following Smoluchowski's probabilistic dynamics. We show that the GC-SME recovers the concentration-based approach by taking either the hydrodynamic or the large copy number limit. In addition, we show that the GC-SME provides a clear statistical mechanical interpretation of the concentration-based approach and yields an emergent chemical potential for nonequilibrium spatially inhomogeneous reaction processes. We further exploit the GC-SME robust framework to accurately derive multiscale/hybrid numerical methods that couple particle-based reaction-diffusion simulations with bulk concentration descriptions, as described in detail through two computational implementations

A Geovisual Analytic Approach to Understanding Geo-Social Relationships in the International Trade Network

The world has become a complex set of geo-social systems interconnected by networks, including transportation networks, telecommunications, and the internet. Understanding the interactions between spatial and social relationships within such geo-social systems is a challenge. This research aims to address this challenge through the framework of geovisual analytics. We present the GeoSocialApp which implements traditional network analysis methods in the context of explicitly spatial and social representations. We then apply it to an exploration of international trade networks in terms of the complex interactions between spatial and social relationships. This exploration using the GeoSocialApp helps us develop a two-part hypothesis: international trade network clusters with structural equivalence are strongly ‘balkanized’ (fragmented) according to the geography of trading partners, and the geographical distance weighted by population within each network cluster has a positive relationship with the development level of countries. In addition to demonstrating the potential of visual analytics to provide insight concerning complex geo-social relationships at a global scale, the research also addresses the challenge of validating insights derived through interactive geovisual analytics. We develop two indicators to quantify the observed patterns, and then use a Monte-Carlo approach to support the hypothesis developed above

Over-expression of miR172 causes loss of spikelet determinacy and floral organ abnormalities in rice (Oryza sativa)

<p>Abstract</p> <p>Background</p> <p>Regulation of gene expression by microRNAs (miRNAs) plays a crucial role in many developmental and physiological processes in plants. miRNAs act to repress expression of their target genes via mRNA cleavage or translational repression. Dozens of miRNA families have been identified in rice, 21 of which are conserved between rice and Arabidopsis. miR172 is a conserved miRNA family which has been shown to regulate expression of <it>APETALA2 </it>(<it>AP2</it>)-like transcription factors in Arabidopsis and maize. The rice genome encodes five <it>AP2</it>-like genes predicted to be targets of miR172. To determine whether these rice <it>AP2</it>-like genes are regulated by miR172 and investigate the function of the target genes, we studied the effect of over-expressing two members of the miR172 family on rice plant development.</p> <p>Results</p> <p>Analysis of miR172 expression showed that it is most highly expressed in late vegetative stages and developing panicles. Analyses of expression of three miR172 targets showed that <it>SUPERNUMERARY BRACT </it>(<it>SNB</it>) and <it>Os03g60430 </it>have high expression in developing panicles. Expression of miR172 was not inversely correlated with expression of its targets although miR172-mediated cleavage of <it>SNB </it>was detected by 5' rapid amplification of cDNA ends (RACE). Over-expression of miR172b in rice delayed the transition from spikelet meristem to floral meristem, and resulted in floral and seed developmental defects, including changes to the number and identity of floral organs, lower fertility and reduced seed weight. Plants over-expressing miR172b not only phenocopied the T-DNA insertion mutant of <it>SNB </it>but showed additional defects in floret development not seen in the <it>snb </it>mutant. However <it>SNB </it>expression was not reduced in the miR172b over-expression plants.</p> <p>Conclusions</p> <p>The phenotypes resulting from over-expression of miR172b suggests it represses <it>SNB </it>and at least one of the other miR172 targets, most likely <it>Os03g60430</it>, indicating roles for other <it>AP2</it>-like genes in rice floret development. miR172 and the <it>AP2</it>-like genes had overlapping expression patterns in rice and their expression did not show an obvious negative correlation. There was not a uniform decrease in the expression of the <it>AP2</it>-like miR172 target mRNAs in the miR172b over-expression plants. These observations are consistent with miR172 functioning via translational repression or with expression of the <it>AP2</it>-like genes being regulated by a negative feedback loop.</p

Optimal consumption and portfolio choice with ambiguity

Lin Q, Riedel F. Optimal consumption and portfolio choice with ambiguity. Center for Mathematical Economics Working Papers. Vol 497. Bielefeld: Center for Mathematical Economics; 2014.We consider optimal consumption and portfolio choice in the presence of Knightian uncertainty in continuous-time. We embed the problem into the new framework of stochastic calculus for such settings, dealing in particular with the issue of non-equivalent multiple priors. We solve the problem completely by identifying the worst-case measure. Our setup also allows to consider interest rate uncertainty; we show that under some robust parameter constellations, the investor optimally puts all his wealth into the asset market, and does not save or borrow at all