454 resultados para common stochastic component


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The Business Process Management domain has evolved at a dramatic pace over the past two decades and the notion of the business process has become a ubiquitous part of the modern business enterprise. Most organizations now view their operations in terms of business processes and manage these business processes in the same way as other corporate assets. In recent years, an increasingly broad range of generic technology has become available for automating business processes. This is part of a growing trend in the software engineering field throughout the past 40 years, where aspects of functionality that are potentially reusable on a widespread basis have coalesced into generic software components. Figure 2.1 illustrates this trend and shows how software systems have evolved from the monolithic applications of the 1960s developed in their entirety often by a single development team to today’s offerings that are based on the integration of a range of generic technologies with only a small component of the application actually being developed from scratch. In the 1990s, generic functionality for the automation of business processes first became commercially available in the form of workflow technology and subsequently evolved in the broader field of business process management systems (BPMS). This technology alleviated the necessity to develop process support within applications from scratch and provided a variety of off-the-shelf options on which these requirements could be based. The demand for this technology was significant and it is estimated that by 2000 there were well over 200 distinct workflow offerings in the market, each with a distinct conceptual foundation. Anticipating the difficulties that would be experienced by organizations seeking to utilize and integrate distinct workflow offerings, the Workflow Management Coalition (WfMC), an industry group formed to advance technology in this area, proposed a standard reference model for workflow technology with an express desire to seek a common platform for achieving workflow interoperation.

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Recent findings from the clinic and the laboratory have transformed the way proteases and their inhibitors are perceived in the outermost layer of the skin, the epidermis. It now appears that an integrated proteolytic network operates within the epidermis, comprising more than 30 enzymes that carry out a growing list of essential functions. Equally, defective regulation or execution of protease-mediated processes is emerging as a key contributor to diverse human skin pathologies, and in recent years the number of diseases attributable to aberrant proteolytic activity has more than doubled. Here, we survey the different roles of proteases in epidermal homeostasis (from processing enzymes to signalling molecules) and explore the spectrum of rare and common human skin disorders where proteolytic pathways are dysregulated.

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We address the problem of finite horizon optimal control of discrete-time linear systems with input constraints and uncertainty. The uncertainty for the problem analysed is related to incomplete state information (output feedback) and stochastic disturbances. We analyse the complexities associated with finding optimal solutions. We also consider two suboptimal strategies that could be employed for larger optimization horizons.

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Most urban dwelling Australians take secure and safe water supplies for granted. That is, they have an adequate quantity of water at a quality that can be used by people without harm from human and animal wastes, salinity and hardness or pollutants from agriculture and manufacturing industries. Australia wide urban and peri-urban dwellers use safe water for all domestic as well as industrial purposes. However, this is not the situation remote regions in Australia where availability and poor quality water can be a development constraint. Nor is it the case in Sri Lanka where people in rural regions are struggling to obtain a secure supply of water, irrespective of it being safe because of the impact of faecal and other contaminants. The purposes of this paper are to overview: the population and environmental health challenges arising from the lack of safe water in rural and remote communities; response pathways to address water quality issues; and the status of and need for integrated catchment management (ICM) in selected remote regions of Australia and vulnerable and lagging rural regions in Sri Lanka. Conclusions are drawn that focus on the opportunity for inter-regional collaborations between Australia and Sri Lanka for the delivery of safe water through ICM.

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ORIGO Stepping Stones is written and developed by a team of experts to provide teachers with a world-class elementary math program. Our expert team of authors and consultants are utilizing all available educational research to create a unique program that has never before been available to teachers. The full color Student Practice Book provides practice pages that support previous and current lessons.

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Recently, the tissue origin of MDA-MB-435 cell line has been the subject of considerable debate. In this study, we set out to determine whether MDA-MB-435-DTP cells shown to express melanoma-specific genes were identical to various other MDA-MB-435 cell stocks worldwide. CGH-microarray, genetic polymorphism genotyping, microsatellite fingerprint analysis and/or chromosomal number confirmed that the MDA-MB-435 cells maintained at the Lombardi Comprehensive Cancer Center (MDA-MB-435-LCC) are almost identical to the MDA-MB-435-DTP cells, and showed a very similar profile to those obtained from the same original source (MD Anderson Cancer Center) but maintained independently (MDA-MB-435-PMCC). Gene expression profile analy-sis confirmed common expression of genes among different MDA-MB-435-LCC cell stocks, and identified some unique gene products in MDA-MB-435-PMCC cells. RT-PCR analysis confirmed the expression of the melanoma marker tyrosinase across multiple MDA-MB-435 cell stocks. Collectively, our results show that the MDA-MB-435 cells used widely have identical origins to those that exhibit a melanoma-like gene expression signature, but exhibit a small degree of genotypic and phenotypic drift.

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Background Heatwaves could cause the population excess death numbers to be ranged from tens to thousands within a couple of weeks in a local area. An excess mortality due to a special event (e.g., a heatwave or an epidemic outbreak) is estimated by subtracting the mortality figure under ‘normal’ conditions from the historical daily mortality records. The calculation of the excess mortality is a scientific challenge because of the stochastic temporal pattern of the daily mortality data which is characterised by (a) the long-term changing mean levels (i.e., non-stationarity); (b) the non-linear temperature-mortality association. The Hilbert-Huang Transform (HHT) algorithm is a novel method originally developed for analysing the non-linear and non-stationary time series data in the field of signal processing, however, it has not been applied in public health research. This paper aimed to demonstrate the applicability and strength of the HHT algorithm in analysing health data. Methods Special R functions were developed to implement the HHT algorithm to decompose the daily mortality time series into trend and non-trend components in terms of the underlying physical mechanism. The excess mortality is calculated directly from the resulting non-trend component series. Results The Brisbane (Queensland, Australia) and the Chicago (United States) daily mortality time series data were utilized for calculating the excess mortality associated with heatwaves. The HHT algorithm estimated 62 excess deaths related to the February 2004 Brisbane heatwave. To calculate the excess mortality associated with the July 1995 Chicago heatwave, the HHT algorithm needed to handle the mode mixing issue. The HHT algorithm estimated 510 excess deaths for the 1995 Chicago heatwave event. To exemplify potential applications, the HHT decomposition results were used as the input data for a subsequent regression analysis, using the Brisbane data, to investigate the association between excess mortality and different risk factors. Conclusions The HHT algorithm is a novel and powerful analytical tool in time series data analysis. It has a real potential to have a wide range of applications in public health research because of its ability to decompose a nonlinear and non-stationary time series into trend and non-trend components consistently and efficiently.

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For users of germplasm collections, the purpose of measuring characterization and evaluation descriptors, and subsequently using statistical methodology to summarize the data, is not only to interpret the relationships between the descriptors, but also to characterize the differences and similarities between accessions in relation to their phenotypic variability for each of the measured descriptors. The set of descriptors for the accessions of most germplasm collections consists of both numerical and categorical descriptors. This poses problems for a combined analysis of all descriptors because few statistical techniques deal with mixtures of measurement types. In this article, nonlinear principal component analysis was used to analyze the descriptors of the accessions in the Australian groundnut collection. It was demonstrated that the nonlinear variant of ordinary principal component analysis is an appropriate analytical tool because subspecies and botanical varieties could be identified on the basis of the analysis and characterized in terms of all descriptors. Moreover, outlying accessions could be easily spotted and their characteristics established. The statistical results and their interpretations provide users with a more efficient way to identify accessions of potential relevance for their plant improvement programs and encourage and improve the usefulness and utilization of germplasm collections.

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This article explains the new pre-court procedures and additional procedures designed to foster settlement of claims introduced by the Workcover Queensland Act 1996, and the implication of the new provisions for practitioners.

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As a sequel to a paper that dealt with the analysis of two-way quantitative data in large germplasm collections, this paper presents analytical methods appropriate for two-way data matrices consisting of mixed data types, namely, ordered multicategory and quantitative data types. While various pattern analysis techniques have been identified as suitable for analysis of the mixed data types which occur in germplasm collections, the clustering and ordination methods used often can not deal explicitly with the computational consequences of large data sets (i.e. greater than 5000 accessions) with incomplete information. However, it is shown that the ordination technique of principal component analysis and the mixture maximum likelihood method of clustering can be employed to achieve such analyses. Germplasm evaluation data for 11436 accessions of groundnut (Arachis hypogaea L.) from the International Research Institute of the Semi-Arid Tropics, Andhra Pradesh, India were examined. Data for nine quantitative descriptors measured in the post-rainy season and five ordered multicategory descriptors were used. Pattern analysis results generally indicated that the accessions could be distinguished into four regions along the continuum of growth habit (or plant erectness). Interpretation of accession membership in these regions was found to be consistent with taxonomic information, such as subspecies. Each growth habit region contained accessions from three of the most common groundnut botanical varieties. This implies that within each of the habit types there is the full range of expression for the other descriptors used in the analysis. Using these types of insights, the patterns of variability in germplasm collections can provide scientists with valuable information for their plant improvement programs.

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This paper examines the properties of various approximation methods for solving stochastic dynamic programs in structural estimation problems. The problem addressed is evaluating the expected value of the maximum of available choices. The paper shows that approximating this by the maximum of expected values frequently has poor properties. It also shows that choosing a convenient distributional assumptions for the errors and then solving exactly conditional on the distributional assumption leads to small approximation errors even if the distribution is misspecified. © 1997 Cambridge University Press.

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We consider the following problem: users in a dynamic group store their encrypted documents on an untrusted server, and wish to retrieve documents containing some keywords without any loss of data confidentiality. In this paper, we investigate common secure indices which can make multi-users in a dynamic group to obtain securely the encrypted documents shared among the group members without re-encrypting them. We give a formal definition of common secure index for conjunctive keyword-based retrieval over encrypted data (CSI-CKR), define the security requirement for CSI-CKR, and construct a CSI-CKR based on dynamic accumulators, Paillier’s cryptosystem and blind signatures. The security of proposed scheme is proved under strong RSA and co-DDH assumptions.

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The quick detection of an abrupt unknown change in the conditional distribution of a dependent stochastic process has numerous applications. In this paper, we pose a minimax robust quickest change detection problem for cases where there is uncertainty about the post-change conditional distribution. Our minimax robust formulation is based on the popular Lorden criteria of optimal quickest change detection. Under a condition on the set of possible post-change distributions, we show that the widely known cumulative sum (CUSUM) rule is asymptotically minimax robust under our Lorden minimax robust formulation as a false alarm constraint becomes more strict. We also establish general asymptotic bounds on the detection delay of misspecified CUSUM rules (i.e. CUSUM rules that are designed with post- change distributions that differ from those of the observed sequence). We exploit these bounds to compare the delay performance of asymptotically minimax robust, asymptotically optimal, and other misspecified CUSUM rules. In simulation examples, we illustrate that asymptotically minimax robust CUSUM rules can provide better detection delay performance at greatly reduced computation effort compared to competing generalised likelihood ratio procedures.

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This paper presents the design of a dual Z-source inverter that can be used with either a single dc source or two isolated dc sources. Unlike traditional inverters, the integration of a properly designed Z-source network and semiconductor switches to the proposed dual inverter allows buck-boost power conversion to be performed over a wide modulation range with three-level output waveforms generated. The connection of an additional transformer to the inverter ac output also allows all generic wye- or delta-connected loads with three-wire or four-wire configuration to be supplied by the inverter. Modulation-wise, the dual inverter can be controlled using a carefully designed carrier-based pulse-width modulation (PWM) scheme that always will ensure balanced voltage boosting of the Z-source network, while simultaneously achieving reduced common-mode switching. Because of the omission of dead-time delays in the dual inverter PWM scheme, its switched common-mode voltage can be completely eliminated, unlike in traditional inverters where narrow common-mode spikes are still generated. Under semiconductor failure conditions, the presented PWM schemes can easily be modified to allow the inverter to operate without interruption and for cases where two isolated sources are used, zero common-mode voltage can still be ensured. These theoretical findings together with the inverter practicality have been confirmed both in simulations using PSIM with Matlab/Simulink coupler and experimentally using a laboratory implemented inverter prototype.