15 resultados para dynamic methods

em Aston University Research Archive


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Objectives and Methods: Contact angle, as a representative measure of surface wettability, is often employed to interpret contact lens surface properties. The literature is often contradictory and can lead to confusion. This literature review is part of a series regarding the analysis of hydrogel contact lenses using contact angle techniques. Here we present an overview of contact angle terminology, methodology, and analysis. Having discussed this background material, subsequent parts of the series will discuss the analysis of contact lens contact angles and evaluate differences in published laboratory results. Results: The concepts of contact angle, wettability and wetting are presented as an introduction. Contact angle hysteresis is outlined and highlights the advantages in using dynamic analytical techniques over static methods. The surface free energy of a material illustrates how contact angle analysis is capable of providing supplementary surface characterization. Although single values are able to distinguish individual material differences, surface free energy and dynamic methods provide an improved understanding of material behavior. The frequently used sessile drop, captive bubble, and Wilhelmy plate techniques are discussed. Their use as both dynamic and static methods, along with the advantages and disadvantages of each technique, is explained. Conclusions: No single contact angle technique fully characterizes the wettability of a material surface, and the application of complimenting methods allows increased characterization. At present, there is not an ISO standard method designed for soft materials. It is important that each contact angle technique has a standard protocol, as small protocol differences between laboratories often contribute to a variety of published data that are not easily comparable. © 2013 Contact Lens Association of Ophthalmologists.

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In recent work we have developed a novel variational inference method for partially observed systems governed by stochastic differential equations. In this paper we provide a comparison of the Variational Gaussian Process Smoother with an exact solution computed using a Hybrid Monte Carlo approach to path sampling, applied to a stochastic double well potential model. It is demonstrated that the variational smoother provides us a very accurate estimate of mean path while conditional variance is slightly underestimated. We conclude with some remarks as to the advantages and disadvantages of the variational smoother. © 2008 Springer Science + Business Media LLC.

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Purpose: Meibomian-derived lipid secretions are well characterised but their subsequent fate in the ocular environment is less well understood. Phospholipids are thought to facilitate the interface between aqueous and lipid layers of the tear film and to be involved in ocular lubrication processes. We have extended our previous studies on phospholipid levels in the tear film to encompass the fate of polar and non-polar lipids in progressive accumulation and aging processes on both conventional and silicone-modified hydrogel lenses. This is an important aspect of the developing understanding of the role of lipids in the clinical performance of silicone hydrogels. Method: Several techniques were used to identify lipids in the tear film. Mass-spectrometric methods included Agilent 1100-based liquid chromatography coupled to mass spectrometry (LCMS) and Perkin Elmer gas chromatography mass spectrometry (GCMS). Thin layer chromatography (TLC) was used for separation of lipids on the basis of increasing solvent polarity. Routine assay of lipid extractions from patient-worn lenses was carried out using a Hewlett Packard 1090 liquid chromatograph coupled to both uv and Agilent 1100 fluorescence detection. A range of histological together with optical, and electron microscope techniques was used in deposit analysis. Results: Progressive lipid uptake was assessed in various ways, including: composition changes with wear time, differential lipid penetrate into the lens matrix and, particularly, the extent to which lipids become unextractable as a function of wear time. Solvent-based separation and HPLC gave consistent results indicating that the polarity of lipid classes decreased as follows: phospholipids/fatty acids > triglycerides > cholesterol/cholesteryl esters. Tear lipids were found to show autofluorescence—which underpinned the value of fluorescence microscopy and fluorescence detection coupled with HPLC separation. The most fluorescent lipids were found to be cholesteryl esters; histological techniques coupled with fluorescence microscopy indicated that white spots (’’jelly bumps’’) formed on silicone hydrogel lenses contain a high proportion of cholesteryl esters. Lipid profiles averaged for 30 symptomatic and 30 asymptomatic contact lens wearers were compiled. Peak classes were split into: cholesterol (C), cholesteryl esters (CE), glycerides (G), polar fatty acids/phospholipids (PL). The lipid ratio for ymptomatic/symptomatic was 0.6 ± 0.1 for all classes except one—the cholesterol ratio was 0.2 ± 0.05. Significantly the PL ratio was no different from that of any other class except cholesterol. Chromatography indicated that: lipid polarity decreased with depth of penetration and that lipid extractability decreased with wear time. Conclusions: Meibomian lipid composition differs from that in the tear film and on worn lenses. Although the same broad lipid classes were obtained by extraction from all lenses and all patients studied, quantities vary with wear and material. Lipid extractability diminishes with wear time regardless of the use of cleaning regimes. Dry eye symptoms in contact lens wear are frequently linked to lipid layer behaviour but seem to relate more to total lipid than to specific composition. Understanding the detail of lipid related processes is an important element of improving the clinical performance of materials and care solutions.

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In this thesis various mathematical methods of studying the transient and dynamic stabiIity of practical power systems are presented. Certain long established methods are reviewed and refinements of some proposed. New methods are presented which remove some of the difficulties encountered in applying the powerful stability theories based on the concepts of Liapunov. Chapter 1 is concerned with numerical solution of the transient stability problem. Following a review and comparison of synchronous machine models the superiority of a particular model from the point of view of combined computing time and accuracy is demonstrated. A digital computer program incorporating all the synchronous machine models discussed, and an induction machine model, is described and results of a practical multi-machine transient stability study are presented. Chapter 2 reviews certain concepts and theorems due to Liapunov. In Chapter 3 transient stability regions of single, two and multi~machine systems are investigated through the use of energy type Liapunov functions. The treatment removes several mathematical difficulties encountered in earlier applications of the method. In Chapter 4 a simple criterion for the steady state stability of a multi-machine system is developed and compared with established criteria and a state space approach. In Chapters 5, 6 and 7 dynamic stability and small signal dynamic response are studied through a state space representation of the system. In Chapter 5 the state space equations are derived for single machine systems. An example is provided in which the dynamic stability limit curves are plotted for various synchronous machine representations. In Chapter 6 the state space approach is extended to multi~machine systems. To draw conclusions concerning dynamic stability or dynamic response the system eigenvalues must be properly interpreted, and a discussion concerning correct interpretation is included. Chapter 7 presents a discussion of the optimisation of power system small sjgnal performance through the use of Liapunov functions.

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This study demonstrates a novel approach to characterizing hydrated bone's viscoelastic behavior at lamellar length scales using dynamic indentation techniques. We studied the submicron-level viscoelastic response of bone tissue from two different inbred mouse strains, A/J and B6, with known differences in whole bone and tissue-level mechanical properties. Our results show that bone having a higher collagen content or a lower mineral-to-matrix ratio demonstrates a trend towards a larger viscoelastic response. When normalized for anatomical location relative to biological growth patterns in the antero-medial (AM) cortex, bone tissue from B6 femora, known to have a lower mineral-to-matrix ratio, is shown to exhibit a significantly higher viscoelastic response compared to A/J tissue. Newer bone regions with a higher collagen content (closer to the endosteal edge of the AM cortex) showed a trend towards a larger viscoelastic response. Our study demonstrates the feasibility of this technique for analyzing local composition-property relationships in bone. Further, this technique of viscoelastic nanoindentation mapping of the bone surface at these submicron length scales is shown to be highly advantageous in studying subsurface features, such as porosity, of wet hydrated biological specimens, which are difficult to identify using other methods. © 2010 Elsevier Ltd.

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The main theme of research of this project concerns the study of neutral networks to control uncertain and non-linear control systems. This involves the control of continuous time, discrete time, hybrid and stochastic systems with input, state or output constraints by ensuring good performances. A great part of this project is devoted to the opening of frontiers between several mathematical and engineering approaches in order to tackle complex but very common non-linear control problems. The objectives are: 1. Design and develop procedures for neutral network enhanced self-tuning adaptive non-linear control systems; 2. To design, as a general procedure, neural network generalised minimum variance self-tuning controller for non-linear dynamic plants (Integration of neural network mapping with generalised minimum variance self-tuning controller strategies); 3. To develop a software package to evaluate control system performances using Matlab, Simulink and Neural Network toolbox. An adaptive control algorithm utilising a recurrent network as a model of a partial unknown non-linear plant with unmeasurable state is proposed. Appropriately, it appears that structured recurrent neural networks can provide conveniently parameterised dynamic models for many non-linear systems for use in adaptive control. Properties of static neural networks, which enabled successful design of stable adaptive control in the state feedback case, are also identified. A survey of the existing results is presented which puts them in a systematic framework showing their relation to classical self-tuning adaptive control application of neural control to a SISO/MIMO control. Simulation results demonstrate that the self-tuning design methods may be practically applicable to a reasonably large class of unknown linear and non-linear dynamic control systems.

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This thesis demonstrates that the use of finite elements need not be confined to space alone, but that they may also be used in the time domain, It is shown that finite element methods may be used successfully to obtain the response of systems to applied forces, including, for example, the accelerations in a tall structure subjected to an earthquake shock. It is further demonstrated that at least one of these methods may be considered to be a practical alternative to more usual methods of solution. A detailed investigation of the accuracy and stability of finite element solutions is included, and methods of applications to both single- and multi-degree of freedom systems are described. Solutions using two different temporal finite elements are compared with those obtained by conventional methods, and a comparison of computation times for the different methods is given. The application of finite element methods to distributed systems is described, using both separate discretizations in space and time, and a combined space-time discretization. The inclusion of both viscous and hysteretic damping is shown to add little to the difficulty of the solution. Temporal finite elements are also seen to be of considerable interest when applied to non-linear systems, both when the system parameters are time-dependent and also when they are functions of displacement. Solutions are given for many different examples, and the computer programs used for the finite element methods are included in an Appendix.

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This is an Inter-Disciplinary Higher Degree (IHD) thesis about Water Pollution Control in the Iron and Steel Industry. After examining the compositions, and various treatment methods, for the major effluent streams from a typical Integrated Iron and Steel works, it was decided to concentrate investigative work on the activated-sludge treatment of coke-oven effluents. A mathematical model of this process was developed in an attempt to provide a tool for plant management that would enable improved performance, and enhanced control of Works Units. The model differs from conventional models in that allowance is made for the presence of two genera of microorganisms, each of which utilises a particular type of substrate as its energy source. Allowance is also made for the inhibitive effect of phenol on thiocyanate biodegradation, and for the self-toxicity of the bacteria when present in a high substrate concentration environment. The enumeration of the kinetic characteristics of the two groups of micro-organisms was shown to be of major importance. Laboratory experiments were instigated in an attempt to determine accurate values of these coefficients. The use of the Suspended Solids concentration was found to be too insensitive a measure of viable active mass. Other measures were investigated, and Adenosine Triphosphate concentration was chosen as the most effective measure of bacterial populations. Using this measure, a model was developed for phenol biodegradation from experimental results which implicated the possibility of storage of substate prior to metabolism. A model for thiocyanate biodegradation was also developed, although the experimental results indicate that much work is still required in this area.

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To carry out stability and voltage regulation studies on more electric aircraft systems in which there is a preponderance of multi-pulse, rectifier-fed motor-drive equipment, average dynamic models of the rectifier converters are required. Existing methods are difficult to apply to anything other than single converters with a low pulse number. Therefore an efficient, compact method for deriving the approximate, linear, average model of 6- and 12-pulse rectifiers, based on the assumption of a small duration of the overlap angle is presented. The models are validated against detailed simulations and laboratory prototypes.

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In this paper, we discuss some practical implications for implementing adaptable network algorithms applied to non-stationary time series problems. Two real world data sets, containing electricity load demands and foreign exchange market prices, are used to test several different methods, ranging from linear models with fixed parameters, to non-linear models which adapt both parameters and model order on-line. Training with the extended Kalman filter, we demonstrate that the dynamic model-order increment procedure of the resource allocating RBF network (RAN) is highly sensitive to the parameters of the novelty criterion. We investigate the use of system noise for increasing the plasticity of the Kalman filter training algorithm, and discuss the consequences for on-line model order selection. The results of our experiments show that there are advantages to be gained in tracking real world non-stationary data through the use of more complex adaptive models.

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PURPOSE. The purpose of this study was to evaluate the potential of the portable Grand Seiko FR-5000 autorefractor to allow objective, continuous, open-field measurement of accommodation and pupil size for the investigation of the visual response to real-world environments and changes in the optical components of the eye. METHODS. The FR-5000 projects a pair of infrared horizontal and vertical lines on either side of fixation, analyzing the separation of the bars in the reflected image. The measurement bars were turned on permanently and the video output of the FR-5000 fed into a PC for real-time analysis. The calibration between infrared bar separation and the refractive error was assessed over a range of 10.0 D with a model eye. Tolerance to longitudinal instrument head shift was investigated over a ±15 mm range and to eye alignment away from the visual axis over eccentricities up to 25.0°. The minimum pupil size for measurement was determined with a model eye. RESULTS. The separation of the measurement bars changed linearly (r = 0.99), allowing continuous online analysis of the refractive state at 60 Hz temporal and approximately 0.01 D system resolution with pupils >2 mm. The pupil edge could be analyzed on the diagonal axes at the same rate with a system resolution of approximately 0.05 mm. The measurement of accommodation and pupil size were affected by eccentricity of viewing and instrument focusing inaccuracies. CONCLUSIONS. The small size of the instrument together with its resolution and temporal properties and ability to measure through a 2 mm pupil make it useful for the measurement of dynamic accommodation and pupil responses in confined environments, although good eye alignment is important. Copyright © 2006 American Academy of Optometry.

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Dynamic Optimization Problems (DOPs) have been widely studied using Evolutionary Algorithms (EAs). Yet, a clear and rigorous definition of DOPs is lacking in the Evolutionary Dynamic Optimization (EDO) community. In this paper, we propose a unified definition of DOPs based on the idea of multiple-decision-making discussed in the Reinforcement Learning (RL) community. We draw a connection between EDO and RL by arguing that both of them are studying DOPs according to our definition of DOPs. We point out that existing EDO or RL research has been mainly focused on some types of DOPs. A conceptualized benchmark problem, which is aimed at the systematic study of various DOPs, is then developed. Some interesting experimental studies on the benchmark reveal that EDO and RL methods are specialized in certain types of DOPs and more importantly new algorithms for DOPs can be developed by combining the strength of both EDO and RL methods.

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Dynamic asset rating is one of a number of techniques that could be used to facilitate low carbon electricity network operation. This paper focusses on distribution level transformer dynamic rating under this context. The models available for use with dynamic asset rating are discussed and compared using measured load and weather conditions from a trial Network area within Milton Keynes. The paper then uses the most appropriate model to investigate, through simulation, the potential gains in dynamic rating compared to static rating under two transformer cooling methods to understand the potential gain to the Network Operator.

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Adaptive critic methods have common roots as generalizations of dynamic programming for neural reinforcement learning approaches. Since they approximate the dynamic programming solutions, they are potentially suitable for learning in noisy, nonlinear and nonstationary environments. In this study, a novel probabilistic dual heuristic programming (DHP) based adaptive critic controller is proposed. Distinct to current approaches, the proposed probabilistic (DHP) adaptive critic method takes uncertainties of forward model and inverse controller into consideration. Therefore, it is suitable for deterministic and stochastic control problems characterized by functional uncertainty. Theoretical development of the proposed method is validated by analytically evaluating the correct value of the cost function which satisfies the Bellman equation in a linear quadratic control problem. The target value of the critic network is then calculated and shown to be equal to the analytically derived correct value.

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Random Walk with Restart (RWR) is an appealing measure of proximity between nodes based on graph structures. Since real graphs are often large and subject to minor changes, it is prohibitively expensive to recompute proximities from scratch. Previous methods use LU decomposition and degree reordering heuristics, entailing O(|V|^3) time and O(|V|^2) memory to compute all (|V|^2) pairs of node proximities in a static graph. In this paper, a dynamic scheme to assess RWR proximities is proposed: (1) For unit update, we characterize the changes to all-pairs proximities as the outer product of two vectors. We notice that the multiplication of an RWR matrix and its transition matrix, unlike traditional matrix multiplications, is commutative. This can greatly reduce the computation of all-pairs proximities from O(|V|^3) to O(|delta|) time for each update without loss of accuracy, where |delta| (<<|V|^2) is the number of affected proximities. (2) To avoid O(|V|^2) memory for all pairs of outputs, we also devise efficient partitioning techniques for our dynamic model, which can compute all pairs of proximities segment-wisely within O(l|V|) memory and O(|V|/l) I/O costs, where 1<=l<=|V| is a user-controlled trade-off between memory and I/O costs. (3) For bulk updates, we also devise aggregation and hashing methods, which can discard many unnecessary updates further and handle chunks of unit updates simultaneously. Our experimental results on various datasets demonstrate that our methods can be 1–2 orders of magnitude faster than other competitors while securing scalability and exactness.