A two-stage algorithm for identification of nonlinear dynamic systems

This paper investigates the two-stage stepwise identification for a class of nonlinear dynamic systems that can be described by linear-in-the-parameters models, and the model has to be built from a very large pool of basis functions or model terms. The main objective is to improve the compactness of the model that is obtained by the forward stepwise methods, while retaining the computational efficiency. The proposed algorithm first generates an initial model using a forward stepwise procedure. The significance of each selected term is then reviewed at the second stage and all insignificant ones are replaced, resulting in an optimised compact model with significantly improved performance. The main contribution of this paper is that these two stages are performed within a well-defined regression context, leading to significantly reduced computational complexity. The efficiency of the algorithm is confirmed by the computational complexity analysis, and its effectiveness is demonstrated by the simulation results.

Statistical Monitoring of Dynamic Multivariate Processes: Part II: Identifying Fault Magnitude and Signature

This paper builds on work presented in the first paper, Part 1 [1] and is of equal significance. The paper proposes a novel compensation method to preserve the integrity of step-fault signatures prevalent in various processes that can be masked during the removal of both auto- and cross correlation. Using industrial data, the paper demonstrates the benefit of the proposed method, which is applicable to chemical, electrical, and mechanical process monitoring. This paper, (and Part 1 [1]), has led to further work supported by EPSRC grant GR/S84354/01 involving kernel PCA methods.

Clinical implementation of dynamic multileaf collimation for compensated bladder treatments.

BACKGROUND AND PURPOSE: To describe the clinical implementation of dynamic multileaf collimation (DMLC). Custom compensated four-field treatments of carcinoma of the bladder have been used as a simple test site for the introduction of intensity modulated radiotherapy.MATERIALS AND METHODS: Compensating intensity modulations are calculated from computed tomography (CT) data, accounting for scattered, as well as primary radiation. Modulations are converted to multileaf collimator (MLC) leaf and jaw settings for dynamic delivery on a linear accelerator. A full dose calculation is carried out, accounting for dynamic leaf and jaw motion and transmission through these components. Before treatment, a test run of the delivery is performed and an absolute dose measurement made in a water or solid water phantom. Treatments are verified by in vivo diode measurements and real-time electronic portal imaging. RESULTS: Seven patients have been treated using DMLC. The technique improves dose homogeneity within the target volume, reducing high dose areas and compensating for loss of scatter at the beam edge. A typical total treatment time is 20 min. CONCLUSIONS: Compensated bladder treatments have proven an effective test site for DMLC in an extremely busy clinic.

Relationship between microstructure and deformation behaviour during dynamic compression in Ti-3Al-5Mo-5V alloy

The relationship between microstructure and deformation and damage behaviour during dynamic compression in Ti-3Al-5Mo-5V alloy has been studied using several experimental techniques, including optical microscopy, scanning electron microscopy and microhardness measurements. It was found that the deformation behaviour during dynamic compression was closely related to deformation parameters. After dynamic deformation, the deformation shear band that formed in the titanium alloy had microhardness similar to that of the matrix. However, the microhardness of the white shear band was much higher than the matrix microhardness. The effects of deformation parameters, including deformation rate and deformation degree, on deformation localisation were investigated. Based on the results from the present work, the microstructure and deformation processing parameters can be optimised. In addition, treatment methods after dynamic compression were explored to restore alloy properties. Using post-deformation heat treatment, the microstructure and property inhomogeneity caused by shear bands could be largely removed.

Evaluation of leukocyte dynamic in mouse retinal circulation with scanning laser ophthalmoloscopy (Video report)

http://bjo.bmj.com/content/suppl/2001/06/20/85.7.DC1 Leukocyte-endothelial cell interactions play an important role in the pathogenesis of various types of retinal vascular diseases, including diabetes, uveitis, and ischemic lesions. Over the last few years, several methods have been devised in which the scanning laser ophthalmoscope (SLO) is used to study leukocyte-endothelial interactions in vivo [1,2]. Previously we reported a noninvasive in vivo leukocyte tracking method using the SLO in rat. In this method, a nontoxic fluorescent agent (6-carboxyfluorescein diacetate, CFDA) was used to label leukocytes in vitro. Leukocyte velocities within the retinal and choroidal circulations were be quantified simultaneously [3]. None of the previous methods has been developed for imaging the murine fundus, mainly due to problems arising from the small size of the mouse eye. However, there are many advantages of using a murine model to study retinal vascular diseases such as enhanced genetic definition, increased range of reagents available for immunological studies and cost reduction. We have developed our SLO method such that we can track leukocytes in the mouse retinal and choroidal circulations.

Dynamic evolution of the genetic search region through fuzzy coding

A technique for automatic exploration of the genetic search region through fuzzy coding (Sharma and Irwin, 2003) has been proposed. Fuzzy coding (FC) provides the value of a variable on the basis of the optimum number of selected fuzzy sets and their effectiveness in terms of degree-of-membership. It is an indirect encoding method and has been shown to perform better than other conventional binary, Gray and floating-point encoding methods. However, the static range of the membership functions is a major problem in fuzzy coding, resulting in longer times to arrive at an optimum solution in large or complicated search spaces. This paper proposes a new algorithm, called fuzzy coding with a dynamic range (FCDR), which dynamically allocates the range of the variables to evolve an effective search region, thereby achieving faster convergence. Results are presented for two benchmark optimisation problems, and also for a case study involving neural identification of a highly non-linear pH neutralisation process from experimental data. It is shown that dynamic exploration of the genetic search region is effective for parameter optimisation in problems where the search space is complicated.

Nuclear activation as a high dynamic range diagnostic of laser-plasma interactions

Proton imaging has become a common diagnostic technique for use in laser-plasma research experiments due to their ability to diagnose electric field effects and to resolve small density differences caused through shock effects. These interactions are highly dependent on the use of radiochromic film (RCF) as a detection system for the particle probe, and produces very high-resolution images. However, saturation effects, and in many cases, damage to the film limits the usefulness of this technique for high-flux particle probing. This paper outlines the use of a new technique using contact radiography of (p,n)-generated isotopes in activation samples to produce high dynamic range 2D images with high spatial resolution and extremely high dynamic range, whilst maintaining both energy resolution and absolute flux measurements. (C)007 Elsevier B.V. All rights reserved.

Harnessing the complexity of gene expression data from cancer: from single gene to structural pathway methods

High-dimensional gene expression data provide a rich source of information because they capture the expression level of genes in dynamic states that reflect the biological functioning of a cell. For this reason, such data are suitable to reveal systems related properties inside a cell, e.g., in order to elucidate molecular mechanisms of complex diseases like breast or prostate cancer. However, this is not only strongly dependent on the sample size and the correlation structure of a data set, but also on the statistical hypotheses tested. Many different approaches have been developed over the years to analyze gene expression data to (I) identify changes in single genes, (II) identify changes in gene sets or pathways, and (III) identify changes in the correlation structure in pathways. In this paper, we review statistical methods for all three types of approaches, including subtypes, in the context of cancer data and provide links to software implementations and tools and address also the general problem of multiple hypotheses testing. Further, we provide recommendations for the selection of such analysis methods.

Dynamic properties of bright points in an active region

Context. Bright points (BPs) are small-scale, magnetic features ubiquitous across the solar surface. Previously, we have observed and noted their properties for quiet Sun regions. Here, we determine the dynamic properties of BPs using simultaneous quiet Sun and active region data.

Aims. The aim of this paper is to compare the properties of BPs in both active and quiet Sun regions and to determine any difference in the dynamics and general properties of BPs as a result of the varying magnetic activity within these two regions.

Methods. High spatial and temporal resolution G-band observations of active region AR11372 were obtained with the Rapid Oscillations in the Solar Atmosphere instrument at the Dunn Solar Telescope. Three subfields of varying polarity and magnetic flux density were selected with the aid of magnetograms obtained from the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory. Bright points within these subfields were subsequently tracked and analysed.

Results. It is found that BPs within active regions display attenuated velocity distributions with an average horizontal velocity of ~0.6 km s-1, compared to the quiet region which had an average velocity of 0.9 km s-1. Active region BPs are also ~21% larger than quiet region BPs and have longer average lifetimes (~132 s) than their quiet region counterparts (88 s). No preferential flow directions are observed within the active region subfields. The diffusion index (γ) is estimated at ~1.2 for the three regions.

Conclusions. We confirm that the dynamic properties of BPs arise predominately from convective motions. The presence of stronger field strengths within active regions is the likely reason behind the varying properties observed. We believe that larger amounts of magnetic flux will attenuate BP velocities by a combination of restricting motion within the intergranular lanes and by increasing the number of stagnation points produced by inhibited convection. Larger BPs are found in regions of higher magnetic flux density and we believe that lifetimes increase in active regions as the magnetic flux stabilises the BPs.

Development of dynamic structural testing to current state-of-the-art hybrid testing

Even though computational power used for structural analysis is ever increasing, there is still a fundamental need for testing in structural engineering, either for validation of complex numerical models or to assess material behaviour. In addition to analysis of structures using scale models, many structural engineers are aware to some extent of cyclic and shake-table test methods, but less so of ‘hybrid testing’. The latter is a combination of physical testing (e.g. hydraulic
actuators) and computational modelling (e.g. finite element modelling). Over the past 40 years, hybrid testing of engineering structures has developed from concept through to maturity to become a reliable and accurate dynamic testing technique. The hybrid test method provides users with some additional benefits that standard dynamic testing methods do not, and the method is more cost-effective in comparison to shake-table testing. This article aims to provide the reader with a basic understanding of the hybrid test method, including its contextual development and potential as a dynamic testing technique.

Doing Focus Groups and Interviews with Recent Migrants to Northern Ireland: A Dynamic Interplay of Ethics, Language and Access

This case describes a qualitative social science research project that was conducted in 2009 and that examined the experiences of recent migrants to Northern Ireland. While background to the research and key findings are presented, the topic forms a backdrop to the case. The following aspects of the study are presented: the theoretical context; formulating the research question, design and methodology; key methodological issues; data collection and analysis; project dissemination; and research funding and reporting. The case pays particular attention to the needs and impact of different groups including the researcher, the funding body, the researcher’s employer and the researched. The significance of access, language and ethics to this study are examined. Finally, the way in which the research unfolded in an often-unpredictable way throughout the implementation process is highlighted in the narrative.

Computational scheduling methods for integrating plug-in electric vehicles with power systems: a review

Traditional internal combustion engine vehicles are a major contributor to global greenhouse gas emissions and other air pollutants, such as particulate matter and nitrogen oxides. If the tail pipe point emissions could be managed centrally without reducing the commercial and personal user functionalities, then one of the most attractive solutions for achieving a significant reduction of emissions in the transport sector would be the mass deployment of electric vehicles. Though electric vehicle sales are still hindered by battery performance, cost and a few other technological bottlenecks, focused commercialisation and support from government policies are encouraging large scale electric vehicle adoptions. The mass proliferation of plug-in electric vehicles is likely to bring a significant additional electric load onto the grid creating a highly complex operational problem for power system operators. Electric vehicle batteries also have the ability to act as energy storage points on the distribution system. This double charge and storage impact of many uncontrollable small kW loads, as consumers will want maximum flexibility, on a distribution system which was originally not designed for such operations has the potential to be detrimental to grid balancing. Intelligent scheduling methods if established correctly could smoothly integrate electric vehicles onto the grid. Intelligent scheduling methods will help to avoid cycling of large combustion plants, using expensive fossil fuel peaking plant, match renewable generation to electric vehicle charging and not overload the distribution system causing a reduction in power quality. In this paper, a state-of-the-art review of scheduling methods to integrate plug-in electric vehicles are reviewed, examined and categorised based on their computational techniques. Thus, in addition to various existing approaches covering analytical scheduling, conventional optimisation methods (e.g. linear, non-linear mixed integer programming and dynamic programming), and game theory, meta-heuristic algorithms including genetic algorithm and particle swarm optimisation, are all comprehensively surveyed, offering a systematic reference for grid scheduling considering intelligent electric vehicle integration.