64 resultados para design-based inference
Resumo:
Time-course experiments with microarrays are often used to study dynamic biological systems and genetic regulatory networks (GRNs) that model how genes influence each other in cell-level development of organisms. The inference for GRNs provides important insights into the fundamental biological processes such as growth and is useful in disease diagnosis and genomic drug design. Due to the experimental design, multilevel data hierarchies are often present in time-course gene expression data. Most existing methods, however, ignore the dependency of the expression measurements over time and the correlation among gene expression profiles. Such independence assumptions violate regulatory interactions and can result in overlooking certain important subject effects and lead to spurious inference for regulatory networks or mechanisms. In this paper, a multilevel mixed-effects model is adopted to incorporate data hierarchies in the analysis of time-course data, where temporal and subject effects are both assumed to be random. The method starts with the clustering of genes by fitting the mixture model within the multilevel random-effects model framework using the expectation-maximization (EM) algorithm. The network of regulatory interactions is then determined by searching for regulatory control elements (activators and inhibitors) shared by the clusters of co-expressed genes, based on a time-lagged correlation coefficients measurement. The method is applied to two real time-course datasets from the budding yeast (Saccharomyces cerevisiae) genome. It is shown that the proposed method provides clusters of cell-cycle regulated genes that are supported by existing gene function annotations, and hence enables inference on regulatory interactions for the genetic network.
Resumo:
A method and a corresponding tool is described which assist design recovery and program understanding by recognising instances of design patterns semi-automatically. The approach taken is specifically designed to overcome the existing scalability problems caused by many design and implementation variants of design pattern instances. Our approach is based on a new recognition algorithm which works incrementally rather than trying to analyse a possibly large software system in one pass without any human intervention. The new algorithm exploits domain and context knowledge given by a reverse engineer and by a special underlying data structure, namely a special form of an annotated abstract syntax graph. A comparative and quantitative evaluation of applying the approach to the Java AWT and JGL libraries is also given.
Resumo:
In recent years, the design flows of many dams were re-evaluated, often resulting in discharges larger than the original design. In many cases, the occurrence of the revised flows could result in dam overtopping because of insufficient storage and spillway capacity. An experimental study was conducted herein to gain a better understanding of the flow properties in stepped chutes with slopes typical of embankment dams. The work was based upon a Froude similitude in large-size experimental facilities. A total of 10 configurations were tested including smooth steps, steps equipped with devices to enhance energy dissipation and rough steps. The present results yield a new design procedure. The design method includes some key issues not foreseen in prior studies : e.g., gradually varied flow, type of flow regime, flow resistance. It is believed that the outcomes are valid for a wide range of chute geometry and flow conditions typical of embankment chutes.
Resumo:
Extracting human postural information from video sequences has proved a difficult research question. The most successful approaches to date have been based on particle filtering, whereby the underlying probability distribution is approximated by a set of particles. The shape of the underlying observational probability distribution plays a significant role in determining the success, both accuracy and efficiency, of any visual tracker. In this paper we compare approaches used by other authors and present a cost path approach which is commonly used in image segmentation problems, however is currently not widely used in tracking applications.
Resumo:
A simple design process for the design of elliptical cross-section, transverse gradient coils for use in magnetic resonance imaging (MRI) is presented. This process is based on a flexible stochastic optimization method and results in designs of high linearity and efficiency with low switching times. A design study of a shielded, transverse asymmetric elliptical coil set for use in neural imaging is presented and includes the minimization of the torques experienced by the gradient set.
Resumo:
This paper presents the unique collection of additional features of Qu-Prolog, a variant of the Al programming language Prolog, and illustrates how they can be used for implementing DAI applications. By this we mean applications comprising communicating information servers, expert systems, or agents, with sophisticated reasoning capabilities and internal concurrency. Such an application exploits the key features of Qu-Prolog: support for the programming of sound non-clausal inference systems, multi-threading, and high level inter-thread message communication between Qu-Prolog query threads anywhere on the internet. The inter-thread communication uses email style symbolic names for threads, allowing easy construction of distributed applications using public names for threads. How threads react to received messages is specified by a disjunction of reaction rules which the thread periodically executes. A communications API allows smooth integration of components written in C, which to Qu-Prolog, look like remote query threads.
Resumo:
In this paper, a new v-metric based approach is proposed to design decentralized controllers for multi-unit nonlinear plants that admit a set of plant decompositions in an operating space. Similar to the gap metric approach in literature, it is shown that the operating space can also be divided into several subregions based on a v-metric indicator, and each of the subregions admits the same controller structure. A comparative case study is presented to display the advantages of proposed approach over the gap metric approach. (C) 2000 Elsevier Science Ltd. All rights reserved.
Resumo:
Objectives: To test the acceptability of screening and to identify modifiable risk factors for abdominal aortic aneurysm (AAA) in men. Design: A trial of ultrasound screening for AAA in a population-based random sample of men aged 65-83 years, and a cross-sectional case-control comparison of men in the same sample. Participants: 12203 men who had an ultrasound examination of their abdominal aorta, and completed a questionnaire covering demographic, behavioural and medical factors. Main outcome measures: Prevalence of AAA, and independent associations of AAA with demographic, medical and lifestyle factors. Results: Invitations to screening produced a corrected response of 70.5%. The prevalence of AAAs (> 30 mm) rose from 4.8% in men aged 65-69 years to 10.8% in those aged 80-83 years. The overall prevalence of large (> 50 mm) aneurysms was 0.69%. In a multivariate logistic model Mediterranean-born men had a 40% lower risk of AAA (> 30 mm) compared with men born in Australia (odds ratio [OR], 0.6; 95% CI, 0.4-0.8), while ex-smokers had a significantly increased risk of AAA (OR, 2.3; 95% CI, 1.9-2.8), and current smokers had even higher risks. AAA was significantly associated with established coronary and peripheral arterial disease and a waist:hip ratio greater than 0.9; men who regularly undertook vigorous exercise had a lower risk (OR, 0.8; 95% CI, 0.7-1.0). Conclusion: Ultrasound screening for AAA is acceptable to men in the likely target population. AAA shares some but not all of the risk factors for occlusive vascular disease, but the scope for primary prevention of AAA in later life is limited.
Resumo:
The simultaneous design of the steady-state and dynamic performance of a process has the ability to satisfy much more demanding dynamic performance criteria than the design of dynamics only by the connection of a control system. A method for designing process dynamics based on the use of a linearised systems' eigenvalues has been developed. The eigenvalues are associated with system states using the unit perturbation spectral resolution (UPSR), characterising the dynamics of each state. The design method uses a homotopy approach to determine a final design which satisfies both steady-state and dynamic performance criteria. A highly interacting single stage forced circulation evaporator system, including control loops, was designed by this method with the goal of reducing the time taken for the liquid composition to reach steady-state. Initially the system was successfully redesigned to speed up the eigenvalue associated with the liquid composition state, but this did not result in an improved startup performance. Further analysis showed that the integral action of the composition controller was the source of the limiting eigenvalue. Design changes made to speed up this eigenvalue did result in an improved startup performance. The proposed approach provides a structured way to address the design-control interface, giving significant insight into the dynamic behaviour of the system such that a systematic design or redesign of an existing system can be undertaken with confidence.