Sampled-data filtering with error covariance assignment

Copyright [2001] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.We consider the sampled-data filtering problem by proposing a new performance criterion in terms of the estimation error covariance. An innovation approach to sampled-data filtering is presented. First, the definition of the estimation covariance e for a sampled-data system is given, then the sampled-data filtering problem is reduced to the Kalman filter design problem for a fictitious discrete-time system, and finally, an effective method is developed to design discrete-time Kalman filters in such a way that the resulting sampled-data estimation covariance achieves a prescribed value. We derive both the existence conditions and the explicit expression of the desired filters and provide an illustrative numerical example to demonstrate the directness and flexibility of the present design metho

Online adaptive learning of continuous-density hidden Markov models based on multiple-stream prior evolution and posterior pooling

We introduce a new adaptive Bayesian learning framework, called multiple-stream prior evolution and posterior pooling, for online adaptation of the continuous density hidden Markov model (CDHMM) parameters. Among three architectures we proposed for this framework, we study in detail a specific two stream system where linear transformations are applied to the mean vectors of the CDHMMs to control the evolution of their prior distribution. This new stream of prior distribution can be combined with another stream of prior distribution evolved without any constraints applied. In a series of speaker adaptation experiments on the task of continuous Mandarin speech recognition, we show that the new adaptation algorithm achieves a similar fast-adaptation performance as that of the incremental maximum likelihood linear regression (MLLR) in the case of small amount of adaptation data, while maintains the good asymptotic convergence property as that of our previously proposed quasi-Bayes adaptation algorithms.published_or_final_versio

High-Resolution Analysis of the Efficiency, Heritability, and Editing Outcomes of CRISPR/Cas9-Induced Modifications of NCED4 in Lettuce (Lactuca sativa).

CRISPR/Cas9 is a transformative tool for making targeted genetic alterations. In plants, high mutation efficiencies have been reported in primary transformants. However, many of the mutations analyzed were somatic and therefore not heritable. To provide more insights into the efficiency of creating stable homozygous mutants using CRISPR/Cas9, we targeted LsNCED4 (9-cis-EPOXYCAROTENOID DIOXYGENASE4), a gene conditioning thermoinhibition of seed germination in lettuce. Three constructs, each capable of expressing Cas9 and a single gRNA targeting different sites in LsNCED4, were stably transformed into lettuce (Lactuca sativa) cvs. Salinas and Cobham Green. Analysis of 47 primary transformants (T1) and 368 T2 plants by deep amplicon sequencing revealed that 57% of T1 plants contained events at the target site: 28% of plants had germline mutations in one allele indicative of an early editing event (mono-allelic), 8% of plants had germline mutations in both alleles indicative of two early editing events (bi-allelic), and the remaining 21% of plants had multiple low frequency mutations indicative of late events (chimeric plants). Editing efficiency was similar in both genotypes, while the different gRNAs varied in efficiency. Amplicon sequencing of 20 T1 and more than 100 T2 plants for each of the three gRNAs showed that repair outcomes were not random, but reproducible and characteristic for each gRNA. Knockouts of NCED4 resulted in large increases in the maximum temperature for seed germination, with seeds of both cultivars capable of germinating >70% at 37°. Knockouts of NCED4 provide a whole-plant selectable phenotype that has minimal pleiotropic consequences. Targeting NCED4 in a co-editing strategy could therefore be used to enrich for germline-edited events simply by germinating seeds at high temperature

The impact of supply chain integration on performance: A contingency and configuration approach

This study extends the developing body of literature on supply chain integration (SCI), which is the degree to which a manufacturer strategically collaborates with its supply chain partners and collaboratively manages intra- and inter-organizational processes, in order to achieve effective and efficient flows of products and services, information, money and decisions, to provide maximum value to the customer. The previous research is inconsistent in its findings about the relationship between SCI and performance. We attribute this inconsistency to incomplete definitions of SCI, in particular, the tendency to focus on customer and supplier integration only, excluding the important central link of internal integration. We study the relationship between three dimensions of SCI, operational and business performance, from both a contingency and a configuration perspective. In applying the contingency approach, hierarchical regression was used to determine the impact of individual SCI dimensions (customer, supplier and internal integration) and their interactions on performance. In the configuration approach, cluster analysis was used to develop patterns of SCI, which were analyzed in terms of SCI strength and balance. Analysis of variance was used to examine the relationship between SCI pattern and performance. The findings of both the contingency and configuration approach indicated that SCI was related to both operational and business performance. Furthermore, the results indicated that internal and customer integration were more strongly related to improving performance than supplier integration

Irrelevant variability normalization in learning HMM state tying from data based on phonetic decision-tree

We propose to apply the concept of irrelevant variability normalization to the general problem of learning structure from data. Because of the problems of a diversified training data set and/or possible acoustic mismatches between training and testing conditions, the structure learned from the training data by using a maximum likelihood training method will not necessarily generalize well on mismatched tasks. We apply the above concept to the structural learning problem of phonetic decision-tree based hidden Markov model (HMM) state tying. We present a new method that integrates a linear-transformation based normalization mechanism into the decision-tree construction process to make the learned structure have a better modeling capability and generalizability. The viability and efficacy of the proposed method are confirmed in a series of experiments for continuous speech recognition of Mandarin Chinese.published_or_final_versio

Assessment of China's virtual air pollution transport embodied in trade by using a consumption-based emission inventory

Substantial anthropogenic emissions from China have resulted in serious air pollution, and this has generated considerable academic and public concern. The physical transport of air pollutants in the atmosphere has been extensively investigated; however, understanding the mechanisms how the pollutant was transferred through economic and trade activities remains a challenge. For the first time, we quantified and tracked China's air pollutant emission flows embodied in interprovincial trade, using a multiregional input - output model framework. Trade relative emissions for four key air pollutants (primary fine particle matter, sulfur dioxide, nitrogen oxides and non-methane volatile organic compounds) were assessed for 2007 in each Chinese province. We found that emissions were significantly redistributed among provinces owing to interprovincial trade. Large amounts of emissions were embodied in the imports of eastern regions from northern and central regions, and these were determined by differences in regional economic status and environmental policy. It is suggested that measures should be introduced to reduce air pollution by integrating cross-regional consumers and producers within national agreements to encourage efficiency improvement in the supply chain and optimize consumption structure internationally. The consumption-based air pollutant emission inventory developed in this work can be further used to attribute pollution to various economic activities and final demand types with the aid of air quality models

Experimental study and analytical study of push-out shear tests in Ultra Shallow Floor Beams

The Ultra Shallow Floor Beam is a new type of composite floor beam fabricated by welding two highly asymmetric cellular tees together along the web and incorporating a concrete slab between the top and bottom flanges. The unique features of this system are circular and elongated web openings that allow tie-bars, building services and ducts passing through the structural depth of the beam. For the composite beam in bending, the longitudinal shear force is transferred by a unique shear mechanism which results from the special configuration of the beam, and shear connectors, if they are present. The work reported in this paper includes a total of 16 full-scale push-out tests aimed at investigating the longitudinal shear behaviour of these beams and the effects of additional shear connectors. A theoretical analysis was also performed to investigate the failure mechanism of the system

Shear Capacity of Perforated Concrete-Steel Ultra Shallow Floor Beams (USFB)

ABSTRACT : In modern building construction floor spans are becoming longer and one way of achieving this is to use composite beams. In order to minimize the structural depth of the composite sections, and to produce lighter members for economy reasons, steel perforated beams are designed to act compositely with the floor slab in an Ultra Shallow Floor Beam (USFB). In the USFB the concrete slab lies within the steel flanges and is connected through the web opening, providing enhanced longitudinal and vertical shear resistance. There is an additional benefit in increased fire resistance. The aim of this project is to investigate, through finite element simulations and suitable tests, the contribution of concrete in composite cellular beams in resisting vertical shear when the concrete slab lies between the flanges of the steel section. The concrete between the flanges provides the load path to transfer the shear force. For the computational approach to the problem, a three-dimensional Finite Element (FE) model was created, in which contact elements were implemented at the interface of the concrete and steel. In an earlier experimental study, four specimens of composite beams of similar concrete strength were tested under monotonic loading in order to produce reliable results. One specimen was from a lower grade of concrete and was tested in order to calibrate the shear resistance and the failure mode. One bare steel perforated section with web openings was also tested as a comparison. The comparison between the experimental and the computational results leads to useful conclusions. The results for the composite beams show a significant increase in shear resistance. The shear enhancement demonstrated in this study can now be used in design practice

Liouvillian Approach to the Integer Quantum Hall Effect Transition

We present a novel approach to the localization-delocalization transition in the integer quantum Hall effect. The Hamiltonian projected onto the lowest Landau level can be written in terms of the projected density operators alone. This and the closed set of commutation relations between the projected densities leads to simple equations for the time evolution of the density operators. These equations can be used to map the problem of calculating the disorder averaged and energetically unconstrained density-density correlation function to the problem of calculating the one-particle density of states of a dynamical system with a novel action. At the self-consistent mean-field level, this approach yields normal diffusion and a finite longitudinal conductivity. While we have not been able to go beyond the saddle point approximation analytically, we show numerically that the critical localization exponent can be extracted from the energetically integrated correlation function yielding $\nu=2.33 \pm 0.05$ in excellent agreement with previous finite-size scaling studies.Comment: 9 pages, submitted to PR

Corrigendum to "Assessment of China's virtual air pollution transport embodied in trade by using a consumption-based emission inventory" published in Atmos. Chem. Phys., 15, 5443-5456, 2015

No abstract available