Better powder diffractometers. II—Optimal choice of U, V and W

NASA Astrophysics Data System (ADS)

Cussen, L. D.

2007-12-01

This article presents a technique for optimising constant wavelength (CW) neutron powder diffractometers (NPDs) using conventional nonlinear least squares methods. This is believed to be the first such design optimisation for a neutron spectrometer. The validity of this approach and discussion should extend beyond the Gaussian element approximation used and also to instruments using different radiation, such as X-rays. This approach could later be extended to include vertical and perhaps horizontal focusing monochromators and probably other types of instruments such as three axis spectrometers. It is hoped that this approach will help in comparisons of CW and time-of-flight (TOF) instruments. Recent work showed that many different beam element combinations can give identical resolution on CW NPDs and presented a procedure to find these combinations and also find an "optimum" choice of detector collimation. Those results enable the previous redundancy in the description of instrument performance to be removed and permit a least squares optimisation of design. New inputs are needed and are identified as the sample plane spacing ( dS) of interest in the measurement. The optimisation requires a "quality factor", QPD, chosen here to be minimising the worst Bragg peak separation ability over some measurement range ( dS) while maintaining intensity. Any other QPD desired could be substituted. It is argued that high resolution and high intensity powder diffractometers (HRPDs and HIPDs) should have similar designs adjusted by a single scaling factor. Simulated comparisons are described suggesting significant improvements in performance for CW HIPDs. Optimisation with unchanged wavelength suggests improvements by factors of about 2 for HRPDs and 25 for HIPDs. A recently quantified design trade-off between the maximum line intensity possible and the degree of variation of angular resolution over the scattering angle range leads to efficiency gains at short wavelengths. This in turn leads in practice to another trade-off between this efficiency gain and losses at short wavelength due to technical effects. The exact gains from varying wavelength depend on the details of the short wavelength technical losses. Simulations suggest that the total potential PD performance gains may be very significant-factors of about 3 for HRPDs and more than 90 for HIPDs.

A hybrid credibility-based fuzzy multiple objective optimisation to differential pricing and inventory policies with arbitrage consideration

NASA Astrophysics Data System (ADS)

Ghasemy Yaghin, R.; Fatemi Ghomi, S. M. T.; Torabi, S. A.

2015-10-01

In most markets, price differentiation mechanisms enable manufacturers to offer different prices for their products or services in different customer segments; however, the perfect price discrimination is usually impossible for manufacturers. The importance of accounting for uncertainty in such environments spurs an interest to develop appropriate decision-making tools to deal with uncertain and ill-defined parameters in joint pricing and lot-sizing problems. This paper proposes a hybrid bi-objective credibility-based fuzzy optimisation model including both quantitative and qualitative objectives to cope with these issues. Taking marketing and lot-sizing decisions into account simultaneously, the model aims to maximise the total profit of manufacturer and to improve service aspects of retailing simultaneously to set different prices with arbitrage consideration. After applying appropriate strategies to defuzzify the original model, the resulting non-linear multi-objective crisp model is then solved by a fuzzy goal programming method. An efficient stochastic search procedure using particle swarm optimisation is also proposed to solve the non-linear crisp model.

Trans-dimensional Bayesian inversion of airborne electromagnetic data for 2D conductivity profiles

NASA Astrophysics Data System (ADS)

Hawkins, Rhys; Brodie, Ross C.; Sambridge, Malcolm

2018-02-01

This paper presents the application of a novel trans-dimensional sampling approach to a time domain airborne electromagnetic (AEM) inverse problem to solve for plausible conductivities of the subsurface. Geophysical inverse field problems, such as time domain AEM, are well known to have a large degree of non-uniqueness. Common least-squares optimisation approaches fail to take this into account and provide a single solution with linearised estimates of uncertainty that can result in overly optimistic appraisal of the conductivity of the subsurface. In this new non-linear approach, the spatial complexity of a 2D profile is controlled directly by the data. By examining an ensemble of proposed conductivity profiles it accommodates non-uniqueness and provides more robust estimates of uncertainties.

On the estimation of the domain of attraction for discrete-time switched and hybrid nonlinear systems

NASA Astrophysics Data System (ADS)

Kit Luk, Chuen; Chesi, Graziano

2015-11-01

This paper addresses the estimation of the domain of attraction for discrete-time nonlinear systems where the vector field is subject to changes. First, the paper considers the case of switched systems, where the vector field is allowed to arbitrarily switch among the elements of a finite family. Second, the paper considers the case of hybrid systems, where the state space is partitioned into several regions described by polynomial inequalities, and the vector field is defined on each region independently from the other ones. In both cases, the problem consists of computing the largest sublevel set of a Lyapunov function included in the domain of attraction. An approach is proposed for solving this problem based on convex programming, which provides a guaranteed inner estimate of the sought sublevel set. The conservatism of the provided estimate can be decreased by increasing the size of the optimisation problem. Some numerical examples illustrate the proposed approach.

Adding flexibility to the search for robust portfolios in non-linear water resource planning

NASA Astrophysics Data System (ADS)

Tomlinson, James; Harou, Julien

2017-04-01

To date robust optimisation of water supply systems has sought to find portfolios or strategies that are robust to a range of uncertainties or scenarios. The search for a single portfolio that is robust in all scenarios is necessarily suboptimal compared to portfolios optimised for a single scenario deterministic future. By contrast establishing a separate portfolio for each future scenario is unhelpful to the planner who must make a single decision today under deep uncertainty. In this work we show that a middle ground is possible by allowing a small number of different portfolios to be found that are each robust to a different subset of the global scenarios. We use evolutionary algorithms and a simple water resource system model to demonstrate this approach. The primary contribution is to demonstrate that flexibility can be added to the search for portfolios, in complex non-linear systems, at the expense of complete robustness across all future scenarios. In this context we define flexibility as the ability to design a portfolio in which some decisions are delayed, but those decisions that are not delayed are themselves shown to be robust to the future. We recognise that some decisions in our portfolio are more important than others. An adaptive portfolio is found by allowing no flexibility for these near-term "important" decisions, but maintaining flexibility in the remaining longer term decisions. In this sense we create an effective 2-stage decision process for a non-linear water resource supply system. We show how this reduces a measure of regret versus the inflexible robust solution for the same system.

Grey-box state-space identification of nonlinear mechanical vibrations

NASA Astrophysics Data System (ADS)

Noël, J. P.; Schoukens, J.

2018-05-01

The present paper deals with the identification of nonlinear mechanical vibrations. A grey-box, or semi-physical, nonlinear state-space representation is introduced, expressing the nonlinear basis functions using a limited number of measured output variables. This representation assumes that the observed nonlinearities are localised in physical space, which is a generic case in mechanics. A two-step identification procedure is derived for the grey-box model parameters, integrating nonlinear subspace initialisation and weighted least-squares optimisation. The complete procedure is applied to an electrical circuit mimicking the behaviour of a single-input, single-output (SISO) nonlinear mechanical system and to a single-input, multiple-output (SIMO) geometrically nonlinear beam structure.

An effective pseudospectral method for constraint dynamic optimisation problems with characteristic times

NASA Astrophysics Data System (ADS)

Xiao, Long; Liu, Xinggao; Ma, Liang; Zhang, Zeyin

2018-03-01

Dynamic optimisation problem with characteristic times, widely existing in many areas, is one of the frontiers and hotspots of dynamic optimisation researches. This paper considers a class of dynamic optimisation problems with constraints that depend on the interior points either fixed or variable, where a novel direct pseudospectral method using Legendre-Gauss (LG) collocation points for solving these problems is presented. The formula for the state at the terminal time of each subdomain is derived, which results in a linear combination of the state at the LG points in the subdomains so as to avoid the complex nonlinear integral. The sensitivities of the state at the collocation points with respect to the variable characteristic times are derived to improve the efficiency of the method. Three well-known characteristic time dynamic optimisation problems are solved and compared in detail among the reported literature methods. The research results show the effectiveness of the proposed method.

Enhancement of temporal contrast of high-power laser pulses in an anisotropic medium with cubic nonlinearity

NASA Astrophysics Data System (ADS)

Kuz'mina, M. S.; Khazanov, E. A.

2015-05-01

We consider the methods for enhancing the temporal contrast of super-high-power laser pulses, based on the conversion of radiation polarisation in a medium with cubic nonlinearity. For a medium with weak birefringence and isotropic nonlinearity, we propose a new scheme to enhance the temporal contrast. For a medium with anisotropic nonlinearity, the efficiency of the temporal contrast optimisation is shown to depend not only on the spatial orientation of the crystal and B-integral, but also on the type of the crystal lattice symmetry.

The dynamics of a stabilised Wien bridge oscillator

NASA Astrophysics Data System (ADS)

Lerner, L.

2016-11-01

We present for the first time analytic solutions for the nonlinear dynamics of a Wien bridge oscillator stabilised by three common methods: an incandescent lamp, signal diodes, and the field effect transistor. The results can be used to optimise oscillator design, and agree well with measurements. The effect of operational amplifier marginal nonlinearity on oscillator performance at high frequencies is clarified. The oscillator circuits and their analysis can be used to demonstrate nonlinear dynamics in the undergraduate laboratory.

Is 3D true non linear traveltime tomography reasonable ?

NASA Astrophysics Data System (ADS)

Herrero, A.; Virieux, J.

2003-04-01

The data sets requiring 3D analysis tools in the context of seismic exploration (both onshore and offshore experiments) or natural seismicity (micro seismicity surveys or post event measurements) are more and more numerous. Classical linearized tomographies and also earthquake localisation codes need an accurate 3D background velocity model. However, if the medium is complex and a priori information not available, a 1D analysis is not able to provide an adequate background velocity image. Moreover, the design of the acquisition layouts is often intrinsically 3D and renders difficult even 2D approaches, especially in natural seismicity cases. Thus, the solution relies on the use of a 3D true non linear approach, which allows to explore the model space and to identify an optimal velocity image. The problem becomes then practical and its feasibility depends on the available computing resources (memory and time). In this presentation, we show that facing a 3D traveltime tomography problem with an extensive non-linear approach combining fast travel time estimators based on level set methods and optimisation techniques such as multiscale strategy is feasible. Moreover, because management of inhomogeneous inversion parameters is more friendly in a non linear approach, we describe how to perform a jointly non-linear inversion for the seismic velocities and the sources locations.

Strategic optimisation of microgrid by evolving a unitised regenerative fuel cell system operational criterion

NASA Astrophysics Data System (ADS)

Bhansali, Gaurav; Singh, Bhanu Pratap; Kumar, Rajesh

2016-09-01

In this paper, the problem of microgrid optimisation with storage has been addressed in an unaccounted way rather than confining it to loss minimisation. Unitised regenerative fuel cell (URFC) systems have been studied and employed in microgrids to store energy and feed it back into the system when required. A value function-dependent on line losses, URFC system operational cost and stored energy at the end of the day are defined here. The function is highly complex, nonlinear and multi dimensional in nature. Therefore, heuristic optimisation techniques in combination with load flow analysis are used here to resolve the network and time domain complexity related with the problem. Particle swarm optimisation with the forward/backward sweep algorithm ensures optimal operation of microgrid thereby minimising the operational cost of the microgrid. Results are shown and are found to be consistently improving with evolution of the solution strategy.

Optimal and robust control of a class of nonlinear systems using dynamically re-optimised single network adaptive critic design

NASA Astrophysics Data System (ADS)

Tiwari, Shivendra N.; Padhi, Radhakant

2018-01-01

Following the philosophy of adaptive optimal control, a neural network-based state feedback optimal control synthesis approach is presented in this paper. First, accounting for a nominal system model, a single network adaptive critic (SNAC) based multi-layered neural network (called as NN1) is synthesised offline. However, another linear-in-weight neural network (called as NN2) is trained online and augmented to NN1 in such a manner that their combined output represent the desired optimal costate for the actual plant. To do this, the nominal model needs to be updated online to adapt to the actual plant, which is done by synthesising yet another linear-in-weight neural network (called as NN3) online. Training of NN3 is done by utilising the error information between the nominal and actual states and carrying out the necessary Lyapunov stability analysis using a Sobolev norm based Lyapunov function. This helps in training NN2 successfully to capture the required optimal relationship. The overall architecture is named as 'Dynamically Re-optimised single network adaptive critic (DR-SNAC)'. Numerical results for two motivating illustrative problems are presented, including comparison studies with closed form solution for one problem, which clearly demonstrate the effectiveness and benefit of the proposed approach.

The role of predictive uncertainty in the operational management of reservoirs

NASA Astrophysics Data System (ADS)

Todini, E.

2014-09-01

The present work deals with the operational management of multi-purpose reservoirs, whose optimisation-based rules are derived, in the planning phase, via deterministic (linear and nonlinear programming, dynamic programming, etc.) or via stochastic (generally stochastic dynamic programming) approaches. In operation, the resulting deterministic or stochastic optimised operating rules are then triggered based on inflow predictions. In order to fully benefit from predictions, one must avoid using them as direct inputs to the reservoirs, but rather assess the "predictive knowledge" in terms of a predictive probability density to be operationally used in the decision making process for the estimation of expected benefits and/or expected losses. Using a theoretical and extremely simplified case, it will be shown why directly using model forecasts instead of the full predictive density leads to less robust reservoir management decisions. Moreover, the effectiveness and the tangible benefits for using the entire predictive probability density instead of the model predicted values will be demonstrated on the basis of the Lake Como management system, operational since 1997, as well as on the basis of a case study on the lake of Aswan.

Design and experimental validation of linear and nonlinear vehicle steering control strategies

NASA Astrophysics Data System (ADS)

Menhour, Lghani; Lechner, Daniel; Charara, Ali

2012-06-01

This paper proposes the design of three control laws dedicated to vehicle steering control, two based on robust linear control strategies and one based on nonlinear control strategies, and presents a comparison between them. The two robust linear control laws (indirect and direct methods) are built around M linear bicycle models, each of these control laws is composed of two M proportional integral derivative (PID) controllers: one M PID controller to control the lateral deviation and the other M PID controller to control the vehicle yaw angle. The indirect control law method is designed using an oscillation method and a nonlinear optimisation subject to H ∞ constraint. The direct control law method is designed using a linear matrix inequality optimisation in order to achieve H ∞ performances. The nonlinear control method used for the correction of the lateral deviation is based on a continuous first-order sliding-mode controller. The different methods are designed using a linear bicycle vehicle model with variant parameters, but the aim is to simulate the nonlinear vehicle behaviour under high dynamic demands with a four-wheel vehicle model. These steering vehicle controls are validated experimentally using the data acquired using a laboratory vehicle, Peugeot 307, developed by National Institute for Transport and Safety Research - Department of Accident Mechanism Analysis Laboratory's (INRETS-MA) and their performance results are compared. Moreover, an unknown input sliding-mode observer is introduced to estimate the road bank angle.

Warpage optimisation on the moulded part with straight-drilled and conformal cooling channels using response surface methodology (RSM) and glowworm swarm optimisation (GSO)

NASA Astrophysics Data System (ADS)

Hazwan, M. H. M.; Shayfull, Z.; Sharif, S.; Nasir, S. M.; Zainal, N.

2017-09-01

In injection moulding process, quality and productivity are notably important and must be controlled for each product type produced. Quality is measured as the extent of warpage of moulded parts while productivity is measured as a duration of moulding cycle time. To control the quality, many researchers have introduced various of optimisation approaches which have been proven enhanced the quality of the moulded part produced. In order to improve the productivity of injection moulding process, some of researches have proposed the application of conformal cooling channels which have been proven reduced the duration of moulding cycle time. Therefore, this paper presents an application of alternative optimisation approach which is Response Surface Methodology (RSM) with Glowworm Swarm Optimisation (GSO) on the moulded part with straight-drilled and conformal cooling channels mould. This study examined the warpage condition of the moulded parts before and after optimisation work applied for both cooling channels. A front panel housing have been selected as a specimen and the performance of proposed optimisation approach have been analysed on the conventional straight-drilled cooling channels compared to the Milled Groove Square Shape (MGSS) conformal cooling channels by simulation analysis using Autodesk Moldflow Insight (AMI) 2013. Based on the results, melt temperature is the most significant factor contribute to the warpage condition and warpage have optimised by 39.1% after optimisation for straight-drilled cooling channels and cooling time is the most significant factor contribute to the warpage condition and warpage have optimised by 38.7% after optimisation for MGSS conformal cooling channels. In addition, the finding shows that the application of optimisation work on the conformal cooling channels offers the better quality and productivity of the moulded part produced.

[New approaches in pharmacology: numerical modelling and simulation].

PubMed

Boissel, Jean-Pierre; Cucherat, Michel; Nony, Patrice; Dronne, Marie-Aimée; Kassaï, Behrouz; Chabaud, Sylvie

2005-01-01

The complexity of pathophysiological mechanisms is beyond the capabilities of traditional approaches. Many of the decision-making problems in public health, such as initiating mass screening, are complex. Progress in genomics and proteomics, and the resulting extraordinary increase in knowledge with regard to interactions between gene expression, the environment and behaviour, the customisation of risk factors and the need to combine therapies that individually have minimal though well documented efficacy, has led doctors to raise new questions: how to optimise choice and the application of therapeutic strategies at the individual rather than the group level, while taking into account all the available evidence? This is essentially a problem of complexity with dimensions similar to the previous ones: multiple parameters with nonlinear relationships between them, varying time scales that cannot be ignored etc. Numerical modelling and simulation (in silico investigations) have the potential to meet these challenges. Such approaches are considered in drug innovation and development. They require a multidisciplinary approach, and this will involve modification of the way research in pharmacology is conducted.

Computational studies on nonlinear optical property of novel Wittig-based Schiff-base ligands and copper(II) complex

NASA Astrophysics Data System (ADS)

Rajasekhar, Bathula; Patowary, Nidarshana; K. Z., Danish; Swu, Toka

2018-07-01

Hundred and forty-five novel molecules of Wittig-based Schiff-base (WSB), including copper(II) complex and precursors, were computationally screened for nonlinear optical (NLO) properties. WSB ligands were derived from various categories of amines and aldehydes. Wittig-based precursor aldehydes, (E)-2-hydroxy-5-(4-nitrostyryl)benzaldehyde (f) and 2-hydroxy-5-((1Z,3E)-4-phenylbuta-1,3-dien-1-yl) benzaldehyde (g) were synthesised and spectroscopically confirmed. Schiff-base ligands and copper(II) complex were designed, optimised and their NLO property was studied using GAUSSIAN09 computer program. For both optimisation and hyperpolarisability (finite-field approach) calculations, Density Functional Theory (DFT)-based B3LYP method was applied with LANL2DZ basis set for metal ion and 6-31G* basis set for C, H, N, O and Cl atoms. This is the first report to present the structure-activity relationship between hyperpolarisability (β) and WSB ligands containing mono imine group. The study reveals that Schiff-base ligands of the category N-2, which are the ones derived from the precursor aldehyde, 2-hydroxy-5-(4nitro-styryl)benzaldehyde and pre-polarised WSB coordinated with Cu(II), encoded as Complex-1 (β = 14.671 × 10-30 e.s.u) showed higher β values over other categories, N-1 and N-3, i.e. WSB derived from precursor aldehydes, 2-hydroxy-5-styrylbenzaldehyde and 2-hydroxy-5-((1Z,3E)-4-phenylbuta-1,3-dien-1-yl)benzaldehyde, respectively. For the first time here we report the geometrical isomeric effect on β value.

Topology optimisation for natural convection problems

NASA Astrophysics Data System (ADS)

Alexandersen, Joe; Aage, Niels; Andreasen, Casper Schousboe; Sigmund, Ole

2014-12-01

This paper demonstrates the application of the density-based topology optimisation approach for the design of heat sinks and micropumps based on natural convection effects. The problems are modelled under the assumptions of steady-state laminar flow using the incompressible Navier-Stokes equations coupled to the convection-diffusion equation through the Boussinesq approximation. In order to facilitate topology optimisation, the Brinkman approach is taken to penalise velocities inside the solid domain and the effective thermal conductivity is interpolated in order to accommodate differences in thermal conductivity of the solid and fluid phases. The governing equations are discretised using stabilised finite elements and topology optimisation is performed for two different problems using discrete adjoint sensitivity analysis. The study shows that topology optimisation is a viable approach for designing heat sink geometries cooled by natural convection and micropumps powered by natural convection.

Nonlinear ultrasonic stimulated thermography for damage assessment in isotropic fatigued structures

NASA Astrophysics Data System (ADS)

Fierro, Gian Piero Malfense; Calla', Danielle; Ginzburg, Dmitri; Ciampa, Francesco; Meo, Michele

2017-09-01

Traditional non-destructive evaluation (NDE) and structural health monitoring (SHM) systems are used to analyse that a structure is free of any harmful damage. However, these techniques still lack sensitivity to detect the presence of material micro-flaws in the form of fatigue damage and often require time-consuming procedures and expensive equipment. This research work presents a novel "nonlinear ultrasonic stimulated thermography" (NUST) method able to overcome some of the limitations of traditional linear ultrasonic/thermography NDE-SHM systems and to provide a reliable, rapid and cost effective estimation of fatigue damage in isotropic materials. Such a hybrid imaging approach combines the high sensitivity of nonlinear acoustic/ultrasonic techniques to detect micro-damage, with local defect frequency selection and infrared imaging. When exciting structures with an optimised frequency, nonlinear elastic waves are observed and higher frictional work at the fatigue damaged area is generated due to clapping and rubbing of the crack faces. This results in heat at cracked location that can be measured using an infrared camera. A Laser Vibrometer (LV) was used to evaluate the extent that individual frequency components contribute to the heating of the damage region by quantifying the out-of-plane velocity associated with the fundamental and second order harmonic responses. It was experimentally demonstrated the relationship between a nonlinear ultrasound parameter (βratio) of the material nonlinear response to the actual temperature rises near the crack. These results demonstrated that heat generation at damaged regions could be amplified by exciting at frequencies that provide nonlinear responses, thus improving the imaging of material damage and the reliability of NUST in a quick and reproducible manner.

Self-optimisation and model-based design of experiments for developing a C-H activation flow process.

PubMed

Echtermeyer, Alexander; Amar, Yehia; Zakrzewski, Jacek; Lapkin, Alexei

2017-01-01

A recently described C(sp 3 )-H activation reaction to synthesise aziridines was used as a model reaction to demonstrate the methodology of developing a process model using model-based design of experiments (MBDoE) and self-optimisation approaches in flow. The two approaches are compared in terms of experimental efficiency. The self-optimisation approach required the least number of experiments to reach the specified objectives of cost and product yield, whereas the MBDoE approach enabled a rapid generation of a process model.

Boundary element based multiresolution shape optimisation in electrostatics

NASA Astrophysics Data System (ADS)

Bandara, Kosala; Cirak, Fehmi; Of, Günther; Steinbach, Olaf; Zapletal, Jan

2015-09-01

We consider the shape optimisation of high-voltage devices subject to electrostatic field equations by combining fast boundary elements with multiresolution subdivision surfaces. The geometry of the domain is described with subdivision surfaces and different resolutions of the same geometry are used for optimisation and analysis. The primal and adjoint problems are discretised with the boundary element method using a sufficiently fine control mesh. For shape optimisation the geometry is updated starting from the coarsest control mesh with increasingly finer control meshes. The multiresolution approach effectively prevents the appearance of non-physical geometry oscillations in the optimised shapes. Moreover, there is no need for mesh regeneration or smoothing during the optimisation due to the absence of a volume mesh. We present several numerical experiments and one industrial application to demonstrate the robustness and versatility of the developed approach.

Synthesis of concentric circular antenna arrays using dragonfly algorithm

NASA Astrophysics Data System (ADS)

Babayigit, B.

2018-05-01

Due to the strong non-linear relationship between the array factor and the array elements, concentric circular antenna array (CCAA) synthesis problem is challenging. Nature-inspired optimisation techniques have been playing an important role in solving array synthesis problems. Dragonfly algorithm (DA) is a novel nature-inspired optimisation technique which is based on the static and dynamic swarming behaviours of dragonflies in nature. This paper presents the design of CCAAs to get low sidelobes using DA. The effectiveness of the proposed DA is investigated in two different (with and without centre element) cases of two three-ring (having 4-, 6-, 8-element or 8-, 10-, 12-element) CCAA design. The radiation pattern of each design cases is obtained by finding optimal excitation weights of the array elements using DA. Simulation results show that the proposed algorithm outperforms the other state-of-the-art techniques (symbiotic organisms search, biogeography-based optimisation, sequential quadratic programming, opposition-based gravitational search algorithm, cat swarm optimisation, firefly algorithm, evolutionary programming) for all design cases. DA can be a promising technique for electromagnetic problems.

Optimisation of micro-perforated cylindrical silencers in linear and nonlinear regimes

NASA Astrophysics Data System (ADS)

Bravo, Teresa; Maury, Cédric; Pinhède, Cédric

2016-02-01

This paper describes analytical and experimental studies conducted to understand the potential of lightweight non-fibrous alternatives to dissipative mufflers for in-duct noise control problems, especially under high sound pressure levels (SPLs) and in the low frequency domain. The cost-efficient multi-modal propagation method has been extended to predict nonlinear effects in the dissipation and the transmission loss (TL) of micro-perforated cylindrical liners with sub-millimetric holes diameter. A validation experiment was performed in a standing wave tube to measure the power dissipated and transmitted by a nonlocally reacting liner under moderate and high SPLs. Although nonlinear effects significantly reduce the dissipation and TL around the liner maximum damping frequency, these power quantities may be enhanced below the half-bandwidth resonance. An optimal value of the in-hole peak particle velocity has been found that maximizes the TL of locally reacting liners at low frequencies. Optimisation studies based on dissipation or TL maximization showed the sensitivity of the liner constituting parameters to variations in the design target range such as the center frequency, the levels of acoustic excitation and the nature of the surface impedance (locally or nonlocally reacting). An analysis is proposed of the deviation observed at low frequencies between the optimum impedance of the locally reacting liner under moderate SPLs and Cremer's optimum impedances.

SLA-based optimisation of virtualised resource for multi-tier web applications in cloud data centres

NASA Astrophysics Data System (ADS)

Bi, Jing; Yuan, Haitao; Tie, Ming; Tan, Wei

2015-10-01

Dynamic virtualised resource allocation is the key to quality of service assurance for multi-tier web application services in cloud data centre. In this paper, we develop a self-management architecture of cloud data centres with virtualisation mechanism for multi-tier web application services. Based on this architecture, we establish a flexible hybrid queueing model to determine the amount of virtual machines for each tier of virtualised application service environments. Besides, we propose a non-linear constrained optimisation problem with restrictions defined in service level agreement. Furthermore, we develop a heuristic mixed optimisation algorithm to maximise the profit of cloud infrastructure providers, and to meet performance requirements from different clients as well. Finally, we compare the effectiveness of our dynamic allocation strategy with two other allocation strategies. The simulation results show that the proposed resource allocation method is efficient in improving the overall performance and reducing the resource energy cost.

Identifying the nonlinear mechanical behaviour of micro-speakers from their quasi-linear electrical response

NASA Astrophysics Data System (ADS)

Zilletti, Michele; Marker, Arthur; Elliott, Stephen John; Holland, Keith

2017-05-01

In this study model identification of the nonlinear dynamics of a micro-speaker is carried out by purely electrical measurements, avoiding any explicit vibration measurements. It is shown that a dynamic model of the micro-speaker, which takes into account the nonlinear damping characteristic of the device, can be identified by measuring the response between the voltage input and the current flowing into the coil. An analytical formulation of the quasi-linear model of the micro-speaker is first derived and an optimisation method is then used to identify a polynomial function which describes the mechanical damping behaviour of the micro-speaker. The analytical results of the quasi-linear model are compared with numerical results. This study potentially opens up the possibility of efficiently implementing nonlinear echo cancellers.

Quantum chemical calculations of Cr2O3/SnO2 using density functional theory method

NASA Astrophysics Data System (ADS)

Jawaher, K. Rackesh; Indirajith, R.; Krishnan, S.; Robert, R.; Das, S. Jerome

2018-03-01

Quantum chemical calculations have been employed to study the molecular effects produced by Cr2O3/SnO2 optimised structure. The theoretical parameters of the transparent conducting metal oxides were calculated using DFT / B3LYP / LANL2DZ method. The optimised bond parameters such as bond lengths, bond angles and dihedral angles were calculated using the same theory. The non-linear optical property of the title compound was calculated using first-order hyperpolarisability calculation. The calculated HOMO-LUMO analysis explains the charge transfer interaction between the molecule. In addition, MEP and Mulliken atomic charges were also calculated and analysed.

Increasing the information rates of optical communications via coded modulation: a study of transceiver performance

NASA Astrophysics Data System (ADS)

Maher, Robert; Alvarado, Alex; Lavery, Domaniç; Bayvel, Polina

2016-02-01

Optical fibre underpins the global communications infrastructure and has experienced an astonishing evolution over the past four decades, with current commercial systems transmitting data rates in excess of 10 Tb/s over a single fibre core. The continuation of this dramatic growth in throughput has become constrained due to a power dependent nonlinear distortion arising from a phenomenon known as the Kerr effect. The mitigation of fibre nonlinearities is an area of intense research. However, even in the absence of nonlinear distortion, the practical limit on the transmission throughput of a single fibre core is dominated by the finite signal-to-noise ratio (SNR) afforded by current state-of-the-art coherent optical transceivers. Therefore, the key to maximising the number of information bits that can be reliably transmitted over a fibre channel hinges on the simultaneous optimisation of the modulation format and code rate, based on the SNR achieved at the receiver. In this work, we use an information theoretic approach based on the mutual information and the generalised mutual information to characterise a state-of-the-art dual polarisation m-ary quadrature amplitude modulation transceiver and subsequently apply this methodology to a 15-carrier super-channel to achieve the highest throughput (1.125 Tb/s) ever recorded using a single coherent receiver.

Increasing the information rates of optical communications via coded modulation: a study of transceiver performance

PubMed Central

Maher, Robert; Alvarado, Alex; Lavery, Domaniç; Bayvel, Polina

2016-01-01

Optical fibre underpins the global communications infrastructure and has experienced an astonishing evolution over the past four decades, with current commercial systems transmitting data rates in excess of 10 Tb/s over a single fibre core. The continuation of this dramatic growth in throughput has become constrained due to a power dependent nonlinear distortion arising from a phenomenon known as the Kerr effect. The mitigation of fibre nonlinearities is an area of intense research. However, even in the absence of nonlinear distortion, the practical limit on the transmission throughput of a single fibre core is dominated by the finite signal-to-noise ratio (SNR) afforded by current state-of-the-art coherent optical transceivers. Therefore, the key to maximising the number of information bits that can be reliably transmitted over a fibre channel hinges on the simultaneous optimisation of the modulation format and code rate, based on the SNR achieved at the receiver. In this work, we use an information theoretic approach based on the mutual information and the generalised mutual information to characterise a state-of-the-art dual polarisation m-ary quadrature amplitude modulation transceiver and subsequently apply this methodology to a 15-carrier super-channel to achieve the highest throughput (1.125 Tb/s) ever recorded using a single coherent receiver. PMID:26864633

Genetic programming based models in plant tissue culture: An addendum to traditional statistical approach.

PubMed

Mridula, Meenu R; Nair, Ashalatha S; Kumar, K Satheesh

2018-02-01

In this paper, we compared the efficacy of observation based modeling approach using a genetic algorithm with the regular statistical analysis as an alternative methodology in plant research. Preliminary experimental data on in vitro rooting was taken for this study with an aim to understand the effect of charcoal and naphthalene acetic acid (NAA) on successful rooting and also to optimize the two variables for maximum result. Observation-based modelling, as well as traditional approach, could identify NAA as a critical factor in rooting of the plantlets under the experimental conditions employed. Symbolic regression analysis using the software deployed here optimised the treatments studied and was successful in identifying the complex non-linear interaction among the variables, with minimalistic preliminary data. The presence of charcoal in the culture medium has a significant impact on root generation by reducing basal callus mass formation. Such an approach is advantageous for establishing in vitro culture protocols as these models will have significant potential for saving time and expenditure in plant tissue culture laboratories, and it further reduces the need for specialised background.

Advanced treatment planning using direct 4D optimisation for pencil-beam scanned particle therapy

NASA Astrophysics Data System (ADS)

Bernatowicz, Kinga; Zhang, Ye; Perrin, Rosalind; Weber, Damien C.; Lomax, Antony J.

2017-08-01

We report on development of a new four-dimensional (4D) optimisation approach for scanned proton beams, which incorporates both irregular motion patterns and the delivery dynamics of the treatment machine into the plan optimiser. Furthermore, we assess the effectiveness of this technique to reduce dose to critical structures in proximity to moving targets, while maintaining effective target dose homogeneity and coverage. The proposed approach has been tested using both a simulated phantom and a clinical liver cancer case, and allows for realistic 4D calculations and optimisation using irregular breathing patterns extracted from e.g. 4DCT-MRI (4D computed tomography-magnetic resonance imaging). 4D dose distributions resulting from our 4D optimisation can achieve almost the same quality as static plans, independent of the studied geometry/anatomy or selected motion (regular and irregular). Additionally, current implementation of the 4D optimisation approach requires less than 3 min to find the solution for a single field planned on 4DCT of a liver cancer patient. Although 4D optimisation allows for realistic calculations using irregular breathing patterns, it is very sensitive to variations from the planned motion. Based on a sensitivity analysis, target dose homogeneity comparable to static plans (D5-D95  <5%) has been found only for differences in amplitude of up to 1 mm, for changes in respiratory phase  <200 ms and for changes in the breathing period of  <20 ms in comparison to the motions used during optimisation. As such, methods to robustly deliver 4D optimised plans employing 4D intensity-modulated delivery are discussed.

A rapid, automated approach to optimisation of multiple reaction monitoring conditions for quantitative bioanalytical mass spectrometry.

PubMed

Higton, D M

2001-01-01

An improvement to the procedure for the rapid optimisation of mass spectrometry (PROMS), for the development of multiple reaction methods (MRM) for quantitative bioanalytical liquid chromatography/tandem mass spectrometry (LC/MS/MS), is presented. PROMS is an automated protocol that uses flow-injection analysis (FIA) and AppleScripts to create methods and acquire the data for optimisation. The protocol determines the optimum orifice potential, the MRM conditions for each compound, and finally creates the MRM methods needed for sample analysis. The sensitivities of the MRM methods created by PROMS approach those created manually. MRM method development using PROMS currently takes less than three minutes per compound compared to at least fifteen minutes manually. To further enhance throughput, approaches to MRM optimisation using one injection per compound, two injections per pool of five compounds and one injection per pool of five compounds have been investigated. No significant difference in the optimised instrumental parameters for MRM methods were found between the original PROMS approach and these new methods, which are up to ten times faster. The time taken for an AppleScript to determine the optimum conditions and build the MRM methods is the same with all approaches. Copyright 2001 John Wiley & Sons, Ltd.

Constrained non-linear multi-objective optimisation of preventive maintenance scheduling for offshore wind farms

NASA Astrophysics Data System (ADS)

Zhong, Shuya; Pantelous, Athanasios A.; Beer, Michael; Zhou, Jian

2018-05-01

Offshore wind farm is an emerging source of renewable energy, which has been shown to have tremendous potential in recent years. In this blooming area, a key challenge is that the preventive maintenance of offshore turbines should be scheduled reasonably to satisfy the power supply without failure. In this direction, two significant goals should be considered simultaneously as a trade-off. One is to maximise the system reliability and the other is to minimise the maintenance related cost. Thus, a non-linear multi-objective programming model is proposed including two newly defined objectives with thirteen families of constraints suitable for the preventive maintenance of offshore wind farms. In order to solve our model effectively, the nondominated sorting genetic algorithm II, especially for the multi-objective optimisation is utilised and Pareto-optimal solutions of schedules can be obtained to offer adequate support to decision-makers. Finally, an example is given to illustrate the performances of the devised model and algorithm, and explore the relationships of the two targets with the help of a contrast model.

Data-driven nonlinear optimisation of a simple air pollution dispersion model generating high resolution spatiotemporal exposure

NASA Astrophysics Data System (ADS)

Yuval; Bekhor, Shlomo; Broday, David M.

2013-11-01

Spatially detailed estimation of exposure to air pollutants in the urban environment is needed for many air pollution epidemiological studies. To benefit studies of acute effects of air pollution such exposure maps are required at high temporal resolution. This study introduces nonlinear optimisation framework that produces high resolution spatiotemporal exposure maps. An extensive traffic model output, serving as proxy for traffic emissions, is fitted via a nonlinear model embodying basic dispersion properties, to high temporal resolution routine observations of traffic-related air pollutant. An optimisation problem is formulated and solved at each time point to recover the unknown model parameters. These parameters are then used to produce a detailed concentration map of the pollutant for the whole area covered by the traffic model. Repeating the process for multiple time points results in the spatiotemporal concentration field. The exposure at any location and for any span of time can then be computed by temporal integration of the concentration time series at selected receptor locations for the durations of desired periods. The methodology is demonstrated for NO2 exposure using the output of a traffic model for the greater Tel Aviv area, Israel, and the half-hourly monitoring and meteorological data from the local air quality network. A leave-one-out cross-validation resulted in simulated half-hourly concentrations that are almost unbiased compared to the observations, with a mean error (ME) of 5.2 ppb, normalised mean error (NME) of 32%, 78% of the simulated values are within a factor of two (FAC2) of the observations, and the coefficient of determination (R2) is 0.6. The whole study period integrated exposure estimations are also unbiased compared with their corresponding observations, with ME of 2.5 ppb, NME of 18%, FAC2 of 100% and R2 that equals 0.62.

A New Computational Technique for the Generation of Optimised Aircraft Trajectories

NASA Astrophysics Data System (ADS)

Chircop, Kenneth; Gardi, Alessandro; Zammit-Mangion, David; Sabatini, Roberto

2017-12-01

A new computational technique based on Pseudospectral Discretisation (PSD) and adaptive bisection ɛ-constraint methods is proposed to solve multi-objective aircraft trajectory optimisation problems formulated as nonlinear optimal control problems. This technique is applicable to a variety of next-generation avionics and Air Traffic Management (ATM) Decision Support Systems (DSS) for strategic and tactical replanning operations. These include the future Flight Management Systems (FMS) and the 4-Dimensional Trajectory (4DT) planning and intent negotiation/validation tools envisaged by SESAR and NextGen for a global implementation. In particular, after describing the PSD method, the adaptive bisection ɛ-constraint method is presented to allow an efficient solution of problems in which two or multiple performance indices are to be minimized simultaneously. Initial simulation case studies were performed adopting suitable aircraft dynamics models and addressing a classical vertical trajectory optimisation problem with two objectives simultaneously. Subsequently, a more advanced 4DT simulation case study is presented with a focus on representative ATM optimisation objectives in the Terminal Manoeuvring Area (TMA). The simulation results are analysed in-depth and corroborated by flight performance analysis, supporting the validity of the proposed computational techniques.

Optimised robot-based system for the exploration of elastic joint properties.

PubMed

Frey, M; Burgkart, R; Regenfelder, F; Riener, R

2004-09-01

Numerous publications provide measured biomechanical data relating to synovial joints. However, in general, they do not reflect the non-linear elastic joint properties in detail or do not consider all degrees of freedom (DOF), or the quantity of data is sparse. To perform more comprehensive, extended measurements of elastic joint properties, an optimised robot-based approach was developed. The basis was an industrial, high-precision robot that was capable of applying loads to the joint and measuring the joint displacement in 6 DOF. The system was equipped with novel, custom-made control hardware. In contrast to the commonly used sampling rates that are below 100 Hz, a rate of 4 kHz was realised for each DOF. This made it possible to implement advanced, highly dynamic, quasi-continuous closed-loop controllers. Thus oscillations of the robot were avoided, and measurements were speeded up. The stiffness of the entire system was greater than 44 kNm(-1) and 22 Nm deg(-1), and the maximum difference between two successive measurements was less than 0.5 deg. A sophisticated CT-based referencing routine facilitated the matching of kinematic data with the individual anatomy of the tested joint. The detailed detection of the elastic varus-valgus properties of a human knee joint is described, and the need for high spatial resolution is demonstrated.

Thermal-economic optimisation of a CHP gas turbine system by applying a fit-problem genetic algorithm

NASA Astrophysics Data System (ADS)

Ferreira, Ana C. M.; Teixeira, Senhorinha F. C. F.; Silva, Rui G.; Silva, Ângela M.

2018-04-01

Cogeneration allows the optimal use of the primary energy sources and significant reductions in carbon emissions. Its use has great potential for applications in the residential sector. This study aims to develop a methodology for thermal-economic optimisation of small-scale micro-gas turbine for cogeneration purposes, able to fulfil domestic energy needs with a thermal power out of 125 kW. A constrained non-linear optimisation model was built. The objective function is the maximisation of the annual worth from the combined heat and power, representing the balance between the annual incomes and the expenditures subject to physical and economic constraints. A genetic algorithm coded in the java programming language was developed. An optimal micro-gas turbine able to produce 103.5 kW of electrical power with a positive annual profit (i.e. 11,925 €/year) was disclosed. The investment can be recovered in 4 years and 9 months, which is less than half of system lifetime expectancy.

Homogenisation of the strain distribution in stretch formed parts to improve part properties

NASA Astrophysics Data System (ADS)

Schmitz, Roman; Winkelmann, Mike; Bailly, David; Hirt, Gerhard

2018-05-01

Inhomogeneous strain and sheet thickness distributions can be observed in complex sheet metal parts manufactured by stretch forming. In literature, this problem is solved by flexible clampings adapted to the part geometry. In this paper, an approach, which does not rely on extensive tooling, is presented. The strain distribution in the sheet is influenced by means of hole patterns. Holes are introduced into the sheet area between clamping and part next to areas where high strains are expected. When deforming the sheet, high strains are shifted out of the part area. In a local area around the holes, high strains concentrate perpendicular to the drawing direction. Thus, high strains in the part area are reduced and the strain distribution is homogenised. To verify this approach, an FE-model of a stretch forming process of a conical part is implemented in LS-Dyna. The model is validated by corresponding experiments. In the first step, the positioning of the holes is applied manually based on the numerically determined strain distribution and experience. In order to automate the positioning of the holes, an optimisation method is applied in a second step. The presented approach implemented in LS-OPT uses the response surface method to identify the positioning and radius of the holes homogenising the strain in a defined area of the sheet. Due to nonlinear increase of computational complexity with increasing number of holes, the maximum number of holes is set to three. With both, the manual and the automated method, hole patterns were found which allow for a relative reduction of maximum strains and for a homogenisation of the strain distribution. Comparing the manual and automated positioning of holes, the pattern determined by automated optimisation shows better results in terms of homogenising the strain distribution.

A Galerkin discretisation-based identification for parameters in nonlinear mechanical systems

NASA Astrophysics Data System (ADS)

Liu, Zuolin; Xu, Jian

2018-04-01

In the paper, a new parameter identification method is proposed for mechanical systems. Based on the idea of Galerkin finite-element method, the displacement over time history is approximated by piecewise linear functions, and the second-order terms in model equation are eliminated by integrating by parts. In this way, the lost function of integration form is derived. Being different with the existing methods, the lost function actually is a quadratic sum of integration over the whole time history. Then for linear or nonlinear systems, the optimisation of the lost function can be applied with traditional least-squares algorithm or the iterative one, respectively. Such method could be used to effectively identify parameters in linear and arbitrary nonlinear mechanical systems. Simulation results show that even under the condition of sparse data or low sampling frequency, this method could still guarantee high accuracy in identifying linear and nonlinear parameters.

Integration of vehicle yaw stabilisation and rollover prevention through nonlinear hierarchical control allocation

NASA Astrophysics Data System (ADS)

Alberding, Matthäus B.; Tjønnås, Johannes; Johansen, Tor A.

2014-12-01

This work presents an approach to rollover prevention that takes advantage of the modular structure and optimisation properties of the control allocation paradigm. It eliminates the need for a stabilising roll controller by introducing rollover prevention as a constraint on the control allocation problem. The major advantage of this approach is the control authority margin that remains with a high-level controller even during interventions for rollover prevention. In this work, the high-level control is assigned to a yaw stabilising controller. It could be replaced by any other controller. The constraint for rollover prevention could be replaced by or extended to different control objectives. This work uses differential braking for actuation. The use of additional or different actuators is possible. The developed control algorithm is computationally efficient and suitable for low-cost automotive electronic control units. The predictive design of the rollover prevention constraint does not require any sensor equipment in addition to the yaw controller. The method is validated using an industrial multi-body vehicle simulation environment.

Simulation of non-linear acoustic field and thermal pattern of phased-array high-intensity focused ultrasound (HIFU).

PubMed

Wang, Mingjun; Zhou, Yufeng

2016-08-01

HIFU becomes an effective and non-invasive modality of solid tumour/cancer ablation. Simulation of the non-linear acoustic wave propagation using a phased-array transducer in multiple layered media using different focusing strategies and the consequent lesion formation are essential in HIFU planning in order to enhance the efficacy and efficiency of treatment. An angular spectrum approach with marching fractional steps was applied in the wave propagation from phased-array HIFU transducer, and diffraction, attenuation, and non-linearity effects were accounted for by a second-order operator splitting scheme. The simulated distributions of the first three harmonics along and transverse to the transducer axis were compared to the hydrophone measurements. The bioheat equation was used to simulate the subsequent temperature elevation using the deposited acoustic energy, and lesion formation was determined by the thermal dose. Better agreement was found between the measured harmonics distribution and simulation using the proposed algorithm than the Khokhlov-Zabozotskaya-Kuznetsov equation. Variable focusing of the phased-array transducer (geometric focusing, transverse shifting and the generation of multiple foci) can be simulated successfully. The shifting and splitting of focus was found to result in significantly less temperature elevation at the focus and the subsequently, the smaller lesion size, but the larger grating lobe grating lobe in the pre-focal region. The proposed algorithm could simulate the non-linear wave propagation from the source with arbitrary shape and distribution of excitation through multiple tissue layers in high computation accuracy. The performance of phased-array HIFU can be optimised in the treatment planning.

A study on the role of powertrain system dynamics on vehicle driveability

NASA Astrophysics Data System (ADS)

Castellazzi, Luca; Tonoli, Andrea; Amati, Nicola; Galliera, Enrico

2017-07-01

Vehicle driveability describes the complex interactions between the driver and the vehicle, mainly related to longitudinal vibrations. Today, a relevant part of the driveability process optimisation is realised by means of track tests, which require a considerable effort due to the number of parameters (such as stiffness and damping components) affecting this behaviour. The drawback of this approach is that it is carried on at a stage when a design iteration becomes very expensive in terms of time and cost. The objective of this work is to propose a light and accurate tool to represent the relevant quantities involved in the driveability analysis, and to understand which are the main vehicle parameters that influence the torsional vibrations transmitted to the driver. Particular attention is devoted to the role of the tyre, the engine mount, the dual mass flywheel and their possible interactions. The presented nonlinear dynamic model has been validated in time and frequency domain and, through linearisation of its nonlinear components, allows to exploit modal and energy analysis. Objective indexes regarding the driving comfort are additionally considered in order to evaluate possible driveability improvements related to the sensitivity of powertrain parameters.

H∞ filter design for nonlinear systems with quantised measurements in finite frequency domain

NASA Astrophysics Data System (ADS)

El Hellani, D.; El Hajjaji, A.; Ceschi, R.

2017-04-01

This paper deals with the problem of finite frequency (FF) H∞ full-order fuzzy filter design for nonlinear discrete-time systems with quantised measurements, described by Takagi-Sugeno models. The measured signals are assumed to be quantised with a logarithmic quantiser. Using a fuzzy-basis-dependent Lyapunov function, the finite frequency ℓ2 gain definition, the generalised S-procedure, and Finsler's lemma, a set of sufficient conditions are established in terms of matrix inequalities, ensuring that the filtering error system is stable and the H∞ attenuation level, from disturbance to the estimation error, is smaller than a given value over a prescribed finite frequency domain of the external disturbances. With the aid of Finsler's lemma, a large number of slack variables are introduced to the design conditions, which provides extra degrees of freedom in optimising the guaranteed H∞ performance. This directly leads to performance improvement and reduction of conservatism. Finally, we give a simulation example to demonstrate the efficiency of the proposed design method, and we show that a lower H∞ attenuation level can be obtained by our developed approach in comparison with another result in the literature.

A Bayesian Approach for Sensor Optimisation in Impact Identification

PubMed Central

Mallardo, Vincenzo; Sharif Khodaei, Zahra; Aliabadi, Ferri M. H.

2016-01-01

This paper presents a Bayesian approach for optimizing the position of sensors aimed at impact identification in composite structures under operational conditions. The uncertainty in the sensor data has been represented by statistical distributions of the recorded signals. An optimisation strategy based on the genetic algorithm is proposed to find the best sensor combination aimed at locating impacts on composite structures. A Bayesian-based objective function is adopted in the optimisation procedure as an indicator of the performance of meta-models developed for different sensor combinations to locate various impact events. To represent a real structure under operational load and to increase the reliability of the Structural Health Monitoring (SHM) system, the probability of malfunctioning sensors is included in the optimisation. The reliability and the robustness of the procedure is tested with experimental and numerical examples. Finally, the proposed optimisation algorithm is applied to a composite stiffened panel for both the uniform and non-uniform probability of impact occurrence. PMID:28774064

Suspension parameter estimation in the frequency domain using a matrix inversion approach

NASA Astrophysics Data System (ADS)

Thite, A. N.; Banvidi, S.; Ibicek, T.; Bennett, L.

2011-12-01

The dynamic lumped parameter models used to optimise the ride and handling of a vehicle require base values of the suspension parameters. These parameters are generally experimentally identified. The accuracy of identified parameters can depend on the measurement noise and the validity of the model used. The existing publications on suspension parameter identification are generally based on the time domain and use a limited degree of freedom. Further, the data used are either from a simulated 'experiment' or from a laboratory test on an idealised quarter or a half-car model. In this paper, a method is developed in the frequency domain which effectively accounts for the measurement noise. Additional dynamic constraining equations are incorporated and the proposed formulation results in a matrix inversion approach. The nonlinearities in damping are estimated, however, using a time-domain approach. Full-scale 4-post rig test data of a vehicle are used. The variations in the results are discussed using the modal resonant behaviour. Further, a method is implemented to show how the results can be improved when the matrix inverted is ill-conditioned. The case study shows a good agreement between the estimates based on the proposed frequency-domain approach and measurable physical parameters.

Using Optimisation Techniques to Granulise Rough Set Partitions

NASA Astrophysics Data System (ADS)

Crossingham, Bodie; Marwala, Tshilidzi

2007-11-01

This paper presents an approach to optimise rough set partition sizes using various optimisation techniques. Three optimisation techniques are implemented to perform the granularisation process, namely, genetic algorithm (GA), hill climbing (HC) and simulated annealing (SA). These optimisation methods maximise the classification accuracy of the rough sets. The proposed rough set partition method is tested on a set of demographic properties of individuals obtained from the South African antenatal survey. The three techniques are compared in terms of their computational time, accuracy and number of rules produced when applied to the Human Immunodeficiency Virus (HIV) data set. The optimised methods results are compared to a well known non-optimised discretisation method, equal-width-bin partitioning (EWB). The accuracies achieved after optimising the partitions using GA, HC and SA are 66.89%, 65.84% and 65.48% respectively, compared to the accuracy of EWB of 59.86%. In addition to rough sets providing the plausabilities of the estimated HIV status, they also provide the linguistic rules describing how the demographic parameters drive the risk of HIV.

Advantages of Task-Specific Multi-Objective Optimisation in Evolutionary Robotics.

PubMed

Trianni, Vito; López-Ibáñez, Manuel

2015-01-01

The application of multi-objective optimisation to evolutionary robotics is receiving increasing attention. A survey of the literature reveals the different possibilities it offers to improve the automatic design of efficient and adaptive robotic systems, and points to the successful demonstrations available for both task-specific and task-agnostic approaches (i.e., with or without reference to the specific design problem to be tackled). However, the advantages of multi-objective approaches over single-objective ones have not been clearly spelled out and experimentally demonstrated. This paper fills this gap for task-specific approaches: starting from well-known results in multi-objective optimisation, we discuss how to tackle commonly recognised problems in evolutionary robotics. In particular, we show that multi-objective optimisation (i) allows evolving a more varied set of behaviours by exploring multiple trade-offs of the objectives to optimise, (ii) supports the evolution of the desired behaviour through the introduction of objectives as proxies, (iii) avoids the premature convergence to local optima possibly introduced by multi-component fitness functions, and (iv) solves the bootstrap problem exploiting ancillary objectives to guide evolution in the early phases. We present an experimental demonstration of these benefits in three different case studies: maze navigation in a single robot domain, flocking in a swarm robotics context, and a strictly collaborative task in collective robotics.

Solving Fuzzy Fractional Differential Equations Using Zadeh's Extension Principle

PubMed Central

Ahmad, M. Z.; Hasan, M. K.; Abbasbandy, S.

2013-01-01

We study a fuzzy fractional differential equation (FFDE) and present its solution using Zadeh's extension principle. The proposed study extends the case of fuzzy differential equations of integer order. We also propose a numerical method to approximate the solution of FFDEs. To solve nonlinear problems, the proposed numerical method is then incorporated into an unconstrained optimisation technique. Several numerical examples are provided. PMID:24082853

CAMELOT: Computational-Analytical Multi-fidElity Low-thrust Optimisation Toolbox

NASA Astrophysics Data System (ADS)

Di Carlo, Marilena; Romero Martin, Juan Manuel; Vasile, Massimiliano

2018-03-01

Computational-Analytical Multi-fidElity Low-thrust Optimisation Toolbox (CAMELOT) is a toolbox for the fast preliminary design and optimisation of low-thrust trajectories. It solves highly complex combinatorial problems to plan multi-target missions characterised by long spirals including different perturbations. To do so, CAMELOT implements a novel multi-fidelity approach combining analytical surrogate modelling and accurate computational estimations of the mission cost. Decisions are then made using two optimisation engines included in the toolbox, a single-objective global optimiser, and a combinatorial optimisation algorithm. CAMELOT has been applied to a variety of case studies: from the design of interplanetary trajectories to the optimal de-orbiting of space debris and from the deployment of constellations to on-orbit servicing. In this paper, the main elements of CAMELOT are described and two examples, solved using the toolbox, are presented.

Tail mean and related robust solution concepts

NASA Astrophysics Data System (ADS)

Ogryczak, Włodzimierz

2014-01-01

Robust optimisation might be viewed as a multicriteria optimisation problem where objectives correspond to the scenarios although their probabilities are unknown or imprecise. The simplest robust solution concept represents a conservative approach focused on the worst-case scenario results optimisation. A softer concept allows one to optimise the tail mean thus combining performances under multiple worst scenarios. We show that while considering robust models allowing the probabilities to vary only within given intervals, the tail mean represents the robust solution for only upper bounded probabilities. For any arbitrary intervals of probabilities the corresponding robust solution may be expressed by the optimisation of appropriately combined mean and tail mean criteria thus remaining easily implementable with auxiliary linear inequalities. Moreover, we use the tail mean concept to develope linear programming implementable robust solution concepts related to risk averse optimisation criteria.

Modelling the influence of sensory dynamics on linear and nonlinear driver steering control

NASA Astrophysics Data System (ADS)

Nash, C. J.; Cole, D. J.

2018-05-01

A recent review of the literature has indicated that sensory dynamics play an important role in the driver-vehicle steering task, motivating the design of a new driver model incorporating human sensory systems. This paper presents a full derivation of the linear driver model developed in previous work, and extends the model to control a vehicle with nonlinear tyres. Various nonlinear controllers and state estimators are compared with different approximations of the true system dynamics. The model simulation time is found to increase significantly with the complexity of the controller and state estimator. In general the more complex controllers perform best, although with certain vehicle and tyre models linearised controllers perform as well as a full nonlinear optimisation. Various extended Kalman filters give similar results, although the driver's sensory dynamics reduce control performance compared with full state feedback. The new model could be used to design vehicle systems which interact more naturally and safely with a human driver.

Convex optimisation approach to constrained fuel optimal control of spacecraft in close relative motion

NASA Astrophysics Data System (ADS)

Massioni, Paolo; Massari, Mauro

2018-05-01

This paper describes an interesting and powerful approach to the constrained fuel-optimal control of spacecraft in close relative motion. The proposed approach is well suited for problems under linear dynamic equations, therefore perfectly fitting to the case of spacecraft flying in close relative motion. If the solution of the optimisation is approximated as a polynomial with respect to the time variable, then the problem can be approached with a technique developed in the control engineering community, known as "Sum Of Squares" (SOS), and the constraints can be reduced to bounds on the polynomials. Such a technique allows rewriting polynomial bounding problems in the form of convex optimisation problems, at the cost of a certain amount of conservatism. The principles of the techniques are explained and some application related to spacecraft flying in close relative motion are shown.

Multi-objective optimisation and decision-making of space station logistics strategies

NASA Astrophysics Data System (ADS)

Zhu, Yue-he; Luo, Ya-zhong

2016-10-01

Space station logistics strategy optimisation is a complex engineering problem with multiple objectives. Finding a decision-maker-preferred compromise solution becomes more significant when solving such a problem. However, the designer-preferred solution is not easy to determine using the traditional method. Thus, a hybrid approach that combines the multi-objective evolutionary algorithm, physical programming, and differential evolution (DE) algorithm is proposed to deal with the optimisation and decision-making of space station logistics strategies. A multi-objective evolutionary algorithm is used to acquire a Pareto frontier and help determine the range parameters of the physical programming. Physical programming is employed to convert the four-objective problem into a single-objective problem, and a DE algorithm is applied to solve the resulting physical programming-based optimisation problem. Five kinds of objective preference are simulated and compared. The simulation results indicate that the proposed approach can produce good compromise solutions corresponding to different decision-makers' preferences.

A shrinking hypersphere PSO for engineering optimisation problems

NASA Astrophysics Data System (ADS)

Yadav, Anupam; Deep, Kusum

2016-03-01

Many real-world and engineering design problems can be formulated as constrained optimisation problems (COPs). Swarm intelligence techniques are a good approach to solve COPs. In this paper an efficient shrinking hypersphere-based particle swarm optimisation (SHPSO) algorithm is proposed for constrained optimisation. The proposed SHPSO is designed in such a way that the movement of the particle is set to move under the influence of shrinking hyperspheres. A parameter-free approach is used to handle the constraints. The performance of the SHPSO is compared against the state-of-the-art algorithms for a set of 24 benchmark problems. An exhaustive comparison of the results is provided statistically as well as graphically. Moreover three engineering design problems namely welded beam design, compressed string design and pressure vessel design problems are solved using SHPSO and the results are compared with the state-of-the-art algorithms.

Topology Optimisation of Wideband Coaxial-to-Waveguide Transitions

NASA Astrophysics Data System (ADS)

Hassan, Emadeldeen; Noreland, Daniel; Wadbro, Eddie; Berggren, Martin

2017-03-01

To maximize the matching between a coaxial cable and rectangular waveguides, we present a computational topology optimisation approach that decides for each point in a given domain whether to hold a good conductor or a good dielectric. The conductivity is determined by a gradient-based optimisation method that relies on finite-difference time-domain solutions to the 3D Maxwell’s equations. Unlike previously reported results in the literature for this kind of problems, our design algorithm can efficiently handle tens of thousands of design variables that can allow novel conceptual waveguide designs. We demonstrate the effectiveness of the approach by presenting optimised transitions with reflection coefficients lower than -15 dB over more than a 60% bandwidth, both for right-angle and end-launcher configurations. The performance of the proposed transitions is cross-verified with a commercial software, and one design case is validated experimentally.

Topology Optimisation of Wideband Coaxial-to-Waveguide Transitions.

PubMed

Hassan, Emadeldeen; Noreland, Daniel; Wadbro, Eddie; Berggren, Martin

2017-03-23

To maximize the matching between a coaxial cable and rectangular waveguides, we present a computational topology optimisation approach that decides for each point in a given domain whether to hold a good conductor or a good dielectric. The conductivity is determined by a gradient-based optimisation method that relies on finite-difference time-domain solutions to the 3D Maxwell's equations. Unlike previously reported results in the literature for this kind of problems, our design algorithm can efficiently handle tens of thousands of design variables that can allow novel conceptual waveguide designs. We demonstrate the effectiveness of the approach by presenting optimised transitions with reflection coefficients lower than -15 dB over more than a 60% bandwidth, both for right-angle and end-launcher configurations. The performance of the proposed transitions is cross-verified with a commercial software, and one design case is validated experimentally.

Topology Optimisation of Wideband Coaxial-to-Waveguide Transitions

PubMed Central

Hassan, Emadeldeen; Noreland, Daniel; Wadbro, Eddie; Berggren, Martin

2017-01-01

To maximize the matching between a coaxial cable and rectangular waveguides, we present a computational topology optimisation approach that decides for each point in a given domain whether to hold a good conductor or a good dielectric. The conductivity is determined by a gradient-based optimisation method that relies on finite-difference time-domain solutions to the 3D Maxwell’s equations. Unlike previously reported results in the literature for this kind of problems, our design algorithm can efficiently handle tens of thousands of design variables that can allow novel conceptual waveguide designs. We demonstrate the effectiveness of the approach by presenting optimised transitions with reflection coefficients lower than −15 dB over more than a 60% bandwidth, both for right-angle and end-launcher configurations. The performance of the proposed transitions is cross-verified with a commercial software, and one design case is validated experimentally. PMID:28332585

A management and optimisation model for water supply planning in water deficit areas

NASA Astrophysics Data System (ADS)

Molinos-Senante, María; Hernández-Sancho, Francesc; Mocholí-Arce, Manuel; Sala-Garrido, Ramón

2014-07-01

The integrated water resources management approach has proven to be a suitable option for efficient, equitable and sustainable water management. In water-poor regions experiencing acute and/or chronic shortages, optimisation techniques are a useful tool for supporting the decision process of water allocation. In order to maximise the value of water use, an optimisation model was developed which involves multiple supply sources (conventional and non-conventional) and multiple users. Penalties, representing monetary losses in the event of an unfulfilled water demand, have been incorporated into the objective function. This model represents a novel approach which considers water distribution efficiency and the physical connections between water supply and demand points. Subsequent empirical testing using data from a Spanish Mediterranean river basin demonstrated the usefulness of the global optimisation model to solve existing water imbalances at the river basin level.

Crystal structure optimisation using an auxiliary equation of state

NASA Astrophysics Data System (ADS)

Jackson, Adam J.; Skelton, Jonathan M.; Hendon, Christopher H.; Butler, Keith T.; Walsh, Aron

2015-11-01

Standard procedures for local crystal-structure optimisation involve numerous energy and force calculations. It is common to calculate an energy-volume curve, fitting an equation of state around the equilibrium cell volume. This is a computationally intensive process, in particular, for low-symmetry crystal structures where each isochoric optimisation involves energy minimisation over many degrees of freedom. Such procedures can be prohibitive for non-local exchange-correlation functionals or other "beyond" density functional theory electronic structure techniques, particularly where analytical gradients are not available. We present a simple approach for efficient optimisation of crystal structures based on a known equation of state. The equilibrium volume can be predicted from one single-point calculation and refined with successive calculations if required. The approach is validated for PbS, PbTe, ZnS, and ZnTe using nine density functionals and applied to the quaternary semiconductor Cu2ZnSnS4 and the magnetic metal-organic framework HKUST-1.

Optimal control of LQG problem with an explicit trade-off between mean and variance

NASA Astrophysics Data System (ADS)

Qian, Fucai; Xie, Guo; Liu, Ding; Xie, Wenfang

2011-12-01

For discrete-time linear-quadratic Gaussian (LQG) control problems, a utility function on the expectation and the variance of the conventional performance index is considered. The utility function is viewed as an overall objective of the system and can perform the optimal trade-off between the mean and the variance of performance index. The nonlinear utility function is first converted into an auxiliary parameters optimisation problem about the expectation and the variance. Then an optimal closed-loop feedback controller for the nonseparable mean-variance minimisation problem is designed by nonlinear mathematical programming. Finally, simulation results are given to verify the algorithm's effectiveness obtained in this article.

Application of Three Existing Stope Boundary Optimisation Methods in an Operating Underground Mine

NASA Astrophysics Data System (ADS)

Erdogan, Gamze; Yavuz, Mahmut

2017-12-01

The underground mine planning and design optimisation process have received little attention because of complexity and variability of problems in underground mines. Although a number of optimisation studies and software tools are available and some of them, in special, have been implemented effectively to determine the ultimate-pit limits in an open pit mine, there is still a lack of studies for optimisation of ultimate stope boundaries in underground mines. The proposed approaches for this purpose aim at maximizing the economic profit by selecting the best possible layout under operational, technical and physical constraints. In this paper, the existing three heuristic techniques including Floating Stope Algorithm, Maximum Value Algorithm and Mineable Shape Optimiser (MSO) are examined for optimisation of stope layout in a case study. Each technique is assessed in terms of applicability, algorithm capabilities and limitations considering the underground mine planning challenges. Finally, the results are evaluated and compared.

Design Optimisation of a Magnetic Field Based Soft Tactile Sensor

PubMed Central

Raske, Nicholas; Kow, Junwai; Alazmani, Ali; Ghajari, Mazdak; Culmer, Peter; Hewson, Robert

2017-01-01

This paper investigates the design optimisation of a magnetic field based soft tactile sensor, comprised of a magnet and Hall effect module separated by an elastomer. The aim was to minimise sensitivity of the output force with respect to the input magnetic field; this was achieved by varying the geometry and material properties. Finite element simulations determined the magnetic field and structural behaviour under load. Genetic programming produced phenomenological expressions describing these responses. Optimisation studies constrained by a measurable force and stable loading conditions were conducted; these produced Pareto sets of designs from which the optimal sensor characteristics were selected. The optimisation demonstrated a compromise between sensitivity and the measurable force, a fabricated version of the optimised sensor validated the improvements made using this methodology. The approach presented can be applied in general for optimising soft tactile sensor designs over a range of applications and sensing modes. PMID:29099787

Advantages of Task-Specific Multi-Objective Optimisation in Evolutionary Robotics

PubMed Central

Trianni, Vito; López-Ibáñez, Manuel

2015-01-01

The application of multi-objective optimisation to evolutionary robotics is receiving increasing attention. A survey of the literature reveals the different possibilities it offers to improve the automatic design of efficient and adaptive robotic systems, and points to the successful demonstrations available for both task-specific and task-agnostic approaches (i.e., with or without reference to the specific design problem to be tackled). However, the advantages of multi-objective approaches over single-objective ones have not been clearly spelled out and experimentally demonstrated. This paper fills this gap for task-specific approaches: starting from well-known results in multi-objective optimisation, we discuss how to tackle commonly recognised problems in evolutionary robotics. In particular, we show that multi-objective optimisation (i) allows evolving a more varied set of behaviours by exploring multiple trade-offs of the objectives to optimise, (ii) supports the evolution of the desired behaviour through the introduction of objectives as proxies, (iii) avoids the premature convergence to local optima possibly introduced by multi-component fitness functions, and (iv) solves the bootstrap problem exploiting ancillary objectives to guide evolution in the early phases. We present an experimental demonstration of these benefits in three different case studies: maze navigation in a single robot domain, flocking in a swarm robotics context, and a strictly collaborative task in collective robotics. PMID:26295151

Optimisation by hierarchical search

NASA Astrophysics Data System (ADS)

Zintchenko, Ilia; Hastings, Matthew; Troyer, Matthias

2015-03-01

Finding optimal values for a set of variables relative to a cost function gives rise to some of the hardest problems in physics, computer science and applied mathematics. Although often very simple in their formulation, these problems have a complex cost function landscape which prevents currently known algorithms from efficiently finding the global optimum. Countless techniques have been proposed to partially circumvent this problem, but an efficient method is yet to be found. We present a heuristic, general purpose approach to potentially improve the performance of conventional algorithms or special purpose hardware devices by optimising groups of variables in a hierarchical way. We apply this approach to problems in combinatorial optimisation, machine learning and other fields.

Multi-photon absorption limits to heralded single photon sources

PubMed Central

Husko, Chad A.; Clark, Alex S.; Collins, Matthew J.; De Rossi, Alfredo; Combrié, Sylvain; Lehoucq, Gaëlle; Rey, Isabella H.; Krauss, Thomas F.; Xiong, Chunle; Eggleton, Benjamin J.

2013-01-01

Single photons are of paramount importance to future quantum technologies, including quantum communication and computation. Nonlinear photonic devices using parametric processes offer a straightforward route to generating photons, however additional nonlinear processes may come into play and interfere with these sources. Here we analyse spontaneous four-wave mixing (SFWM) sources in the presence of multi-photon processes. We conduct experiments in silicon and gallium indium phosphide photonic crystal waveguides which display inherently different nonlinear absorption processes, namely two-photon (TPA) and three-photon absorption (ThPA), respectively. We develop a novel model capturing these diverse effects which is in excellent quantitative agreement with measurements of brightness, coincidence-to-accidental ratio (CAR) and second-order correlation function g(2)(0), showing that TPA imposes an intrinsic limit on heralded single photon sources. We build on these observations to devise a new metric, the quantum utility (QMU), enabling further optimisation of single photon sources. PMID:24186400

Neuromorphic Hardware Architecture Using the Neural Engineering Framework for Pattern Recognition.

PubMed

Wang, Runchun; Thakur, Chetan Singh; Cohen, Gregory; Hamilton, Tara Julia; Tapson, Jonathan; van Schaik, Andre

2017-06-01

We present a hardware architecture that uses the neural engineering framework (NEF) to implement large-scale neural networks on field programmable gate arrays (FPGAs) for performing massively parallel real-time pattern recognition. NEF is a framework that is capable of synthesising large-scale cognitive systems from subnetworks and we have previously presented an FPGA implementation of the NEF that successfully performs nonlinear mathematical computations. That work was developed based on a compact digital neural core, which consists of 64 neurons that are instantiated by a single physical neuron using a time-multiplexing approach. We have now scaled this approach up to build a pattern recognition system by combining identical neural cores together. As a proof of concept, we have developed a handwritten digit recognition system using the MNIST database and achieved a recognition rate of 96.55%. The system is implemented on a state-of-the-art FPGA and can process 5.12 million digits per second. The architecture and hardware optimisations presented offer high-speed and resource-efficient means for performing high-speed, neuromorphic, and massively parallel pattern recognition and classification tasks.

Insight into the theoretical and experimental studies of 1-phenyl-3-methyl-4-benzoyl-5-pyrazolone N(4)-methyl-N(4)- phenylthiosemicarbazone - A potential NLO material

NASA Astrophysics Data System (ADS)

Sangeetha, K. G.; Aravindakshan, K. K.; Safna Hussan, K. P.

2017-12-01

The synthesis, geometrical parameters, spectroscopic studies, optimised molecular structure, vibrational analysis, Mullikan population analysis, MEP, NBO, frontier molecular orbitals and NLO effects of 1-phenyl-3-methyl-4-benzoyl-5-pyrazolone N-(4)-methyl-N-(4)-phenylthiosemicarbazone, C25H23N5OS (L1) have been communicated in this paper. A combined experimental and theoretical approach was used to explore the structure and properties of the compound. For computational studies, Gaussian 09 program was used. Starting geometry of molecule was taken from X-ray refinement data and has been optimized by using DFT (B3LYP) method with the 6-31+G (d, p) basis sets. NBO analysis gave insight into the strongly delocalized structure, responsible for the nonlinearity and hence the stability of the molecule. Frontier molecular orbitals have been defined to forecast the global reactivity descriptors of L1. The computed first-order hyperpolarizability (β) of the compound is 2 times higher than that of urea and this account for its nonlinear optical property. Simultaneously, a molecular docking study of the compound was performed using GLIDE Program. For this, three biological enzymes, histone deacetylase, ribonucleotide reductase and DNA methyl transferase, were selected as receptor molecules.

Optimised collision avoidance for an ultra-close rendezvous with a failed satellite based on the Gauss pseudospectral method

NASA Astrophysics Data System (ADS)

Chu, Xiaoyu; Zhang, Jingrui; Lu, Shan; Zhang, Yao; Sun, Yue

2016-11-01

This paper presents a trajectory planning algorithm to optimise the collision avoidance of a chasing spacecraft operating in an ultra-close proximity to a failed satellite. The complex configuration and the tumbling motion of the failed satellite are considered. The two-spacecraft rendezvous dynamics are formulated based on the target body frame, and the collision avoidance constraints are detailed, particularly concerning the uncertainties. An optimisation solution of the approaching problem is generated using the Gauss pseudospectral method. A closed-loop control is used to track the optimised trajectory. Numerical results are provided to demonstrate the effectiveness of the proposed algorithms.

Optimisation of active suspension control inputs for improved performance of active safety systems

NASA Astrophysics Data System (ADS)

Čorić, Mirko; Deur, Joško; Xu, Li; Tseng, H. Eric; Hrovat, Davor

2018-01-01

A collocation-type control variable optimisation method is used to investigate the extent to which the fully active suspension (FAS) can be applied to improve the vehicle electronic stability control (ESC) performance and reduce the braking distance. First, the optimisation approach is applied to the scenario of vehicle stabilisation during the sine-with-dwell manoeuvre. The results are used to provide insights into different FAS control mechanisms for vehicle performance improvements related to responsiveness and yaw rate error reduction indices. The FAS control performance is compared to performances of the standard ESC system, optimal active brake system and combined FAS and ESC configuration. Second, the optimisation approach is employed to the task of FAS-based braking distance reduction for straight-line vehicle motion. Here, the scenarios of uniform and longitudinally or laterally non-uniform tyre-road friction coefficient are considered. The influences of limited anti-lock braking system (ABS) actuator bandwidth and limit-cycle ABS behaviour are also analysed. The optimisation results indicate that the FAS can provide competitive stabilisation performance and improved agility when compared to the ESC system, and that it can reduce the braking distance by up to 5% for distinctively non-uniform friction conditions.

Development and optimisation of atorvastatin calcium loaded self-nanoemulsifying drug delivery system (SNEDDS) for enhancing oral bioavailability: in vitro and in vivo evaluation.

PubMed

Kassem, Abdulsalam M; Ibrahim, Hany M; Samy, Ahmed M

2017-05-01

The objective of this study was to develop and optimise self-nanoemulsifying drug delivery system (SNEDDS) of atorvastatin calcium (ATC) for improving dissolution rate and eventually oral bioavailability. Ternary phase diagrams were constructed on basis of solubility and emulsification studies. The composition of ATC-SNEDDS was optimised using the Box-Behnken optimisation design. Optimised ATC-SNEDDS was characterised for various physicochemical properties. Pharmacokinetic, pharmacodynamic and histological findings were performed in rats. Optimised ATC-SNEDDS resulted in droplets size of 5.66 nm, zeta potential of -19.52 mV, t 90 of 5.43 min and completely released ATC within 30 min irrespective of pH of the medium. Area under the curve of optimised ATC-SNEDDS in rats was 2.34-folds higher than ATC suspension. Pharmacodynamic studies revealed significant reduction in serum lipids of rats with fatty liver. Photomicrographs showed improvement in hepatocytes structure. In this study, we confirmed that ATC-SNEDDS would be a promising approach for improving oral bioavailability of ATC.

Evolving optimised decision rules for intrusion detection using particle swarm paradigm

NASA Astrophysics Data System (ADS)

Sivatha Sindhu, Siva S.; Geetha, S.; Kannan, A.

2012-12-01

The aim of this article is to construct a practical intrusion detection system (IDS) that properly analyses the statistics of network traffic pattern and classify them as normal or anomalous class. The objective of this article is to prove that the choice of effective network traffic features and a proficient machine-learning paradigm enhances the detection accuracy of IDS. In this article, a rule-based approach with a family of six decision tree classifiers, namely Decision Stump, C4.5, Naive Baye's Tree, Random Forest, Random Tree and Representative Tree model to perform the detection of anomalous network pattern is introduced. In particular, the proposed swarm optimisation-based approach selects instances that compose training set and optimised decision tree operate over this trained set producing classification rules with improved coverage, classification capability and generalisation ability. Experiment with the Knowledge Discovery and Data mining (KDD) data set which have information on traffic pattern, during normal and intrusive behaviour shows that the proposed algorithm produces optimised decision rules and outperforms other machine-learning algorithm.

Optimisation of active suspension control inputs for improved vehicle ride performance

NASA Astrophysics Data System (ADS)

Čorić, Mirko; Deur, Joško; Xu, Li; Tseng, H. Eric; Hrovat, Davor

2016-07-01

A collocation-type control variable optimisation method is used in the paper to analyse to which extent the fully active suspension (FAS) can improve the vehicle ride comfort while preserving the wheel holding ability. The method is first applied for a cosine-shaped bump road disturbance of different heights, and for both quarter-car and full 10 degree-of-freedom vehicle models. A nonlinear anti-wheel hop constraint is considered, and the influence of bump preview time period is analysed. The analysis is then extended to the case of square- or cosine-shaped pothole with different lengths, and the quarter-car model. In this case, the cost function is extended with FAS energy consumption and wheel damage resilience costs. The FAS action is found to be such to provide a wheel hop over the pothole, in order to avoid or minimise the damage at the pothole trailing edge. In the case of long pothole, when the FAS cannot provide the wheel hop, the wheel is travelling over the pothole bottom and then hops over the pothole trailing edge. The numerical optimisation results are accompanied by a simplified algebraic analysis.

Optimisation of insect cell growth in deep-well blocks: development of a high-throughput insect cell expression screen.

PubMed

Bahia, Daljit; Cheung, Robert; Buchs, Mirjam; Geisse, Sabine; Hunt, Ian

2005-01-01

This report describes a method to culture insects cells in 24 deep-well blocks for the routine small-scale optimisation of baculovirus-mediated protein expression experiments. Miniaturisation of this process provides the necessary reduction in terms of resource allocation, reagents, and labour to allow extensive and rapid optimisation of expression conditions, with the concomitant reduction in lead-time before commencement of large-scale bioreactor experiments. This therefore greatly simplifies the optimisation process and allows the use of liquid handling robotics in much of the initial optimisation stages of the process, thereby greatly increasing the throughput of the laboratory. We present several examples of the use of deep-well block expression studies in the optimisation of therapeutically relevant protein targets. We also discuss how the enhanced throughput offered by this approach can be adapted to robotic handling systems and the implications this has on the capacity to conduct multi-parallel protein expression studies.

Application of snakes and dynamic programming optimisation technique in modeling of buildings in informal settlement areas

NASA Astrophysics Data System (ADS)

Rüther, Heinz; Martine, Hagai M.; Mtalo, E. G.

This paper presents a novel approach to semiautomatic building extraction in informal settlement areas from aerial photographs. The proposed approach uses a strategy of delineating buildings by optimising their approximate building contour position. Approximate building contours are derived automatically by locating elevation blobs in digital surface models. Building extraction is then effected by means of the snakes algorithm and the dynamic programming optimisation technique. With dynamic programming, the building contour optimisation problem is realized through a discrete multistage process and solved by the "time-delayed" algorithm, as developed in this work. The proposed building extraction approach is a semiautomatic process, with user-controlled operations linking fully automated subprocesses. Inputs into the proposed building extraction system are ortho-images and digital surface models, the latter being generated through image matching techniques. Buildings are modeled as "lumps" or elevation blobs in digital surface models, which are derived by altimetric thresholding of digital surface models. Initial windows for building extraction are provided by projecting the elevation blobs centre points onto an ortho-image. In the next step, approximate building contours are extracted from the ortho-image by region growing constrained by edges. Approximate building contours thus derived are inputs into the dynamic programming optimisation process in which final building contours are established. The proposed system is tested on two study areas: Marconi Beam in Cape Town, South Africa, and Manzese in Dar es Salaam, Tanzania. Sixty percent of buildings in the study areas have been extracted and verified and it is concluded that the proposed approach contributes meaningfully to the extraction of buildings in moderately complex and crowded informal settlement areas.

Distributed convex optimisation with event-triggered communication in networked systems

NASA Astrophysics Data System (ADS)

Liu, Jiayun; Chen, Weisheng

2016-12-01

This paper studies the distributed convex optimisation problem over directed networks. Motivated by practical considerations, we propose a novel distributed zero-gradient-sum optimisation algorithm with event-triggered communication. Therefore, communication and control updates just occur at discrete instants when some predefined condition satisfies. Thus, compared with the time-driven distributed optimisation algorithms, the proposed algorithm has the advantages of less energy consumption and less communication cost. Based on Lyapunov approaches, we show that the proposed algorithm makes the system states asymptotically converge to the solution of the problem exponentially fast and the Zeno behaviour is excluded. Finally, simulation example is given to illustrate the effectiveness of the proposed algorithm.

Floating-to-Fixed-Point Conversion for Digital Signal Processors

NASA Astrophysics Data System (ADS)

Menard, Daniel; Chillet, Daniel; Sentieys, Olivier

2006-12-01

Digital signal processing applications are specified with floating-point data types but they are usually implemented in embedded systems with fixed-point arithmetic to minimise cost and power consumption. Thus, methodologies which establish automatically the fixed-point specification are required to reduce the application time-to-market. In this paper, a new methodology for the floating-to-fixed point conversion is proposed for software implementations. The aim of our approach is to determine the fixed-point specification which minimises the code execution time for a given accuracy constraint. Compared to previous methodologies, our approach takes into account the DSP architecture to optimise the fixed-point formats and the floating-to-fixed-point conversion process is coupled with the code generation process. The fixed-point data types and the position of the scaling operations are optimised to reduce the code execution time. To evaluate the fixed-point computation accuracy, an analytical approach is used to reduce the optimisation time compared to the existing methods based on simulation. The methodology stages are described and several experiment results are presented to underline the efficiency of this approach.

A CONCEPTUAL FRAMEWORK FOR MANAGING RADIATION DOSE TO PATIENTS IN DIAGNOSTIC RADIOLOGY USING REFERENCE DOSE LEVELS.

PubMed

Almén, Anja; Båth, Magnus

2016-06-01

The overall aim of the present work was to develop a conceptual framework for managing radiation dose in diagnostic radiology with the intention to support optimisation. An optimisation process was first derived. The framework for managing radiation dose, based on the derived optimisation process, was then outlined. The outset of the optimisation process is four stages: providing equipment, establishing methodology, performing examinations and ensuring quality. The optimisation process comprises a series of activities and actions at these stages. The current system of diagnostic reference levels is an activity in the last stage, ensuring quality. The system becomes a reactive activity only to a certain extent engaging the core activity in the radiology department, performing examinations. Three reference dose levels-possible, expected and established-were assigned to the three stages in the optimisation process, excluding ensuring quality. A reasonably achievable dose range is also derived, indicating an acceptable deviation from the established dose level. A reasonable radiation dose for a single patient is within this range. The suggested framework for managing radiation dose should be regarded as one part of the optimisation process. The optimisation process constitutes a variety of complementary activities, where managing radiation dose is only one part. This emphasises the need to take a holistic approach integrating the optimisation process in different clinical activities. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Chiral light intrinsically couples to extrinsic/pseudo-chiral metasurfaces made of tilted gold nanowires

PubMed Central

Belardini, Alessandro; Centini, Marco; Leahu, Grigore; Hooper, David C.; Li Voti, Roberto; Fazio, Eugenio; Haus, Joseph W.; Sarangan, Andrew; Valev, Ventsislav K.; Sibilia, Concita

2016-01-01

Extrinsic or pseudo-chiral (meta)surfaces have an achiral structure, yet they can give rise to circular dichroism when the experiment itself becomes chiral. Although these surfaces are known to yield differences in reflected and transmitted circularly polarized light, the exact mechanism of the interaction has never been directly demonstrated. Here we present a comprehensive linear and nonlinear optical investigation of a metasurface composed of tilted gold nanowires. In the linear regime, we directly demonstrate the selective absorption of circularly polarised light depending on the orientation of the metasurface. In the nonlinear regime, we demonstrate for the first time how second harmonic generation circular dichroism in such extrinsic/pseudo-chiral materials can be understood in terms of effective nonlinear susceptibility tensor elements that switch sign depending on the orientation of the metasurface. By providing fundamental understanding of the chiroptical interactions in achiral metasurfaces, our work opens up new perspectives for the optimisation of their properties. PMID:27553888

HyFIS: adaptive neuro-fuzzy inference systems and their application to nonlinear dynamical systems.

PubMed

Kim, J; Kasabov, N

1999-11-01

This paper proposes an adaptive neuro-fuzzy system, HyFIS (Hybrid neural Fuzzy Inference System), for building and optimising fuzzy models. The proposed model introduces the learning power of neural networks to fuzzy logic systems and provides linguistic meaning to the connectionist architectures. Heuristic fuzzy logic rules and input-output fuzzy membership functions can be optimally tuned from training examples by a hybrid learning scheme comprised of two phases: rule generation phase from data; and rule tuning phase using error backpropagation learning scheme for a neural fuzzy system. To illustrate the performance and applicability of the proposed neuro-fuzzy hybrid model, extensive simulation studies of nonlinear complex dynamic systems are carried out. The proposed method can be applied to an on-line incremental adaptive learning for the prediction and control of nonlinear dynamical systems. Two benchmark case studies are used to demonstrate that the proposed HyFIS system is a superior neuro-fuzzy modelling technique.

Consideration of plant behaviour in optimal servo-compensator design

NASA Astrophysics Data System (ADS)

Moase, W. H.; Manzie, C.

2016-07-01

Where the most prevalent optimal servo-compensator formulations penalise the behaviour of an error system, this paper considers the problem of additionally penalising the actual states and inputs of the plant. Doing so has the advantage of enabling the penalty function to better resemble an economic cost. This is especially true of problems where control effort needs to be sensibly allocated across weakly redundant inputs or where one wishes to use penalties to soft-constrain certain states or inputs. It is shown that, although the resulting cost function grows unbounded as its horizon approaches infinity, it is possible to formulate an equivalent optimisation problem with a bounded cost. The resulting optimisation problem is similar to those in earlier studies but has an additional 'correction term' in the cost function, and a set of equality constraints that arise when there are redundant inputs. A numerical approach to solve the resulting optimisation problem is presented, followed by simulations on a micro-macro positioner that illustrate the benefits of the proposed servo-compensator design approach.

Sustainable Mining Land Use for Lignite Based Energy Projects

NASA Astrophysics Data System (ADS)

Dudek, Michal; Krysa, Zbigniew

2017-12-01

This research aims to discuss complex lignite based energy projects economic viability and its impact on sustainable land use with respect to project risk and uncertainty, economics, optimisation (e.g. Lerchs and Grossmann) and importance of lignite as fuel that may be expressed in situ as deposit of energy. Sensitivity analysis and simulation consist of estimated variable land acquisition costs, geostatistics, 3D deposit block modelling, electricity price considered as project product price, power station efficiency and power station lignite processing unit cost, CO2 allowance costs, mining unit cost and also lignite availability treated as lignite reserves kriging estimation error. Investigated parameters have nonlinear influence on results so that economically viable amount of lignite in optimal pit varies having also nonlinear impact on land area required for mining operation.

An improved PSO-SVM model for online recognition defects in eddy current testing

NASA Astrophysics Data System (ADS)

Liu, Baoling; Hou, Dibo; Huang, Pingjie; Liu, Banteng; Tang, Huayi; Zhang, Wubo; Chen, Peihua; Zhang, Guangxin

2013-12-01

Accurate and rapid recognition of defects is essential for structural integrity and health monitoring of in-service device using eddy current (EC) non-destructive testing. This paper introduces a novel model-free method that includes three main modules: a signal pre-processing module, a classifier module and an optimisation module. In the signal pre-processing module, a kind of two-stage differential structure is proposed to suppress the lift-off fluctuation that could contaminate the EC signal. In the classifier module, multi-class support vector machine (SVM) based on one-against-one strategy is utilised for its good accuracy. In the optimisation module, the optimal parameters of classifier are obtained by an improved particle swarm optimisation (IPSO) algorithm. The proposed IPSO technique can improve convergence performance of the primary PSO through the following strategies: nonlinear processing of inertia weight, introductions of the black hole and simulated annealing model with extremum disturbance. The good generalisation ability of the IPSO-SVM model has been validated through adding additional specimen into the testing set. Experiments show that the proposed algorithm can achieve higher recognition accuracy and efficiency than other well-known classifiers and the superiorities are more obvious with less training set, which contributes to online application.

Rational decisions, random matrices and spin glasses

NASA Astrophysics Data System (ADS)

Galluccio, Stefano; Bouchaud, Jean-Philippe; Potters, Marc

We consider the problem of rational decision making in the presence of nonlinear constraints. By using tools borrowed from spin glass and random matrix theory, we focus on the portfolio optimisation problem. We show that the number of optimal solutions is generally exponentially large, and each of them is fragile: rationality is in this case of limited use. In addition, this problem is related to spin glasses with Lévy-like (long-ranged) couplings, for which we show that the ground state is not exponentially degenerate.

A probabilistic neural network based approach for predicting the output power of wind turbines

NASA Astrophysics Data System (ADS)

Tabatabaei, Sajad

2017-03-01

Finding the authentic predicting tools of eliminating the uncertainty of wind speed forecasts is highly required while wind power sources are strongly penetrating. Recently, traditional predicting models of generating point forecasts have no longer been trustee. Thus, the present paper aims at utilising the concept of prediction intervals (PIs) to assess the uncertainty of wind power generation in power systems. Besides, this paper uses a newly introduced non-parametric approach called lower upper bound estimation (LUBE) to build the PIs since the forecasting errors are unable to be modelled properly by applying distribution probability functions. In the present proposed LUBE method, a PI combination-based fuzzy framework is used to overcome the performance instability of neutral networks (NNs) used in LUBE. In comparison to other methods, this formulation more suitably has satisfied the PI coverage and PI normalised average width (PINAW). Since this non-linear problem has a high complexity, a new heuristic-based optimisation algorithm comprising a novel modification is introduced to solve the aforesaid problems. Based on data sets taken from a wind farm in Australia, the feasibility and satisfying performance of the suggested method have been investigated.

Computational aero-acoustics for fan duct propagation and radiation. Current status and application to turbofan liner optimisation

NASA Astrophysics Data System (ADS)

Astley, R. J.; Sugimoto, R.; Mustafi, P.

2011-08-01

Novel techniques are presented to reduce noise from turbofan aircraft engines by optimising the acoustic treatment in engine ducts. The application of Computational Aero-Acoustics (CAA) to predict acoustic propagation and absorption in turbofan ducts is reviewed and a critical assessment of performance indicates that validated and accurate techniques are now available for realistic engine predictions. A procedure for integrating CAA methods with state of the art optimisation techniques is proposed in the remainder of the article. This is achieved by embedding advanced computational methods for noise prediction within automated and semi-automated optimisation schemes. Two different strategies are described and applied to realistic nacelle geometries and fan sources to demonstrate the feasibility of this approach for industry scale problems.

A robust optimisation approach to the problem of supplier selection and allocation in outsourcing

NASA Astrophysics Data System (ADS)

Fu, Yelin; Keung Lai, Kin; Liang, Liang

2016-03-01

We formulate the supplier selection and allocation problem in outsourcing under an uncertain environment as a stochastic programming problem. Both the decision-maker's attitude towards risk and the penalty parameters for demand deviation are considered in the objective function. A service level agreement, upper bound for each selected supplier's allocation and the number of selected suppliers are considered as constraints. A novel robust optimisation approach is employed to solve this problem under different economic situations. Illustrative examples are presented with managerial implications highlighted to support decision-making.

Optimisation of active suspension control inputs for improved vehicle handling performance

NASA Astrophysics Data System (ADS)

Čorić, Mirko; Deur, Joško; Kasać, Josip; Tseng, H. Eric; Hrovat, Davor

2016-11-01

Active suspension is commonly considered under the framework of vertical vehicle dynamics control aimed at improvements in ride comfort. This paper uses a collocation-type control variable optimisation tool to investigate to which extent the fully active suspension (FAS) application can be broaden to the task of vehicle handling/cornering control. The optimisation approach is firstly applied to solely FAS actuator configurations and three types of double lane-change manoeuvres. The obtained optimisation results are used to gain insights into different control mechanisms that are used by FAS to improve the handling performance in terms of path following error reduction. For the same manoeuvres the FAS performance is compared with the performance of different active steering and active differential actuators. The optimisation study is finally extended to combined FAS and active front- and/or rear-steering configurations to investigate if they can use their complementary control authorities (over the vertical and lateral vehicle dynamics, respectively) to further improve the handling performance.

Optimisation of warpage on thin shell plastic part using response surface methodology (RSM) and glowworm swarm optimisation (GSO)

NASA Astrophysics Data System (ADS)

Asyirah, B. N.; Shayfull, Z.; Nasir, S. M.; Fathullah, M.; Hazwan, M. H. M.

2017-09-01

In manufacturing a variety of parts, plastic injection moulding is widely use. The injection moulding process parameters have played important role that affects the product's quality and productivity. There are many approaches in minimising the warpage ans shrinkage such as artificial neural network, genetic algorithm, glowworm swarm optimisation and hybrid approaches are addressed. In this paper, a systematic methodology for determining a warpage and shrinkage in injection moulding process especially in thin shell plastic parts are presented. To identify the effects of the machining parameters on the warpage and shrinkage value, response surface methodology is applied. In thos study, a part of electronic night lamp are chosen as the model. Firstly, experimental design were used to determine the injection parameters on warpage for different thickness value. The software used to analyse the warpage is Autodesk Moldflow Insight (AMI) 2012.

Optimising the Collaborative Practice of Nurses in Primary Care Settings Using a Knowledge Translation Approach

ERIC Educational Resources Information Center

Oelke, Nelly; Wilhelm, Amanda; Jackson, Karen

2016-01-01

The role of nurses in primary care is poorly understood and many are not working to their full scope of practice. Building on previous research, this knowledge translation (KT) project's aim was to facilitate nurses' capacity to optimise their practice in these settings. A Summit engaging Alberta stakeholders in a deliberative discussion was the…

A reliability-based maintenance technicians' workloads optimisation model with stochastic consideration

NASA Astrophysics Data System (ADS)

Ighravwe, D. E.; Oke, S. A.; Adebiyi, K. A.

2016-06-01

The growing interest in technicians' workloads research is probably associated with the recent surge in competition. This was prompted by unprecedented technological development that triggers changes in customer tastes and preferences for industrial goods. In a quest for business improvement, this worldwide intense competition in industries has stimulated theories and practical frameworks that seek to optimise performance in workplaces. In line with this drive, the present paper proposes an optimisation model which considers technicians' reliability that complements factory information obtained. The information used emerged from technicians' productivity and earned-values using the concept of multi-objective modelling approach. Since technicians are expected to carry out routine and stochastic maintenance work, we consider these workloads as constraints. The influence of training, fatigue and experiential knowledge of technicians on workload management was considered. These workloads were combined with maintenance policy in optimising reliability, productivity and earned-values using the goal programming approach. Practical datasets were utilised in studying the applicability of the proposed model in practice. It was observed that our model was able to generate information that practicing maintenance engineers can apply in making more informed decisions on technicians' management.

Optimisation of a Generic Ionic Model of Cardiac Myocyte Electrical Activity

PubMed Central

Guo, Tianruo; Al Abed, Amr; Lovell, Nigel H.; Dokos, Socrates

2013-01-01

A generic cardiomyocyte ionic model, whose complexity lies between a simple phenomenological formulation and a biophysically detailed ionic membrane current description, is presented. The model provides a user-defined number of ionic currents, employing two-gate Hodgkin-Huxley type kinetics. Its generic nature allows accurate reconstruction of action potential waveforms recorded experimentally from a range of cardiac myocytes. Using a multiobjective optimisation approach, the generic ionic model was optimised to accurately reproduce multiple action potential waveforms recorded from central and peripheral sinoatrial nodes and right atrial and left atrial myocytes from rabbit cardiac tissue preparations, under different electrical stimulus protocols and pharmacological conditions. When fitted simultaneously to multiple datasets, the time course of several physiologically realistic ionic currents could be reconstructed. Model behaviours tend to be well identified when extra experimental information is incorporated into the optimisation. PMID:23710254

An adaptive critic-based scheme for consensus control of nonlinear multi-agent systems

NASA Astrophysics Data System (ADS)

Heydari, Ali; Balakrishnan, S. N.

2014-12-01

The problem of decentralised consensus control of a network of heterogeneous nonlinear systems is formulated as an optimal tracking problem and a solution is proposed using an approximate dynamic programming based neurocontroller. The neurocontroller training comprises an initial offline training phase and an online re-optimisation phase to account for the fact that the reference signal subject to tracking is not fully known and available ahead of time, i.e., during the offline training phase. As long as the dynamics of the agents are controllable, and the communication graph has a directed spanning tree, this scheme guarantees the synchronisation/consensus even under switching communication topology and directed communication graph. Finally, an aerospace application is selected for the evaluation of the performance of the method. Simulation results demonstrate the potential of the scheme.

Application of particle swarm optimisation for solving deteriorating inventory model with fluctuating demand and controllable deterioration rate

NASA Astrophysics Data System (ADS)

Chen, Yu-Ren; Dye, Chung-Yuan

2013-06-01

In most of the inventory models in the literature, the deterioration rate of goods is viewed as an exogenous variable, which is not subject to control. In the real market, the retailer can reduce the deterioration rate of product by making effective capital investment in storehouse equipments. In this study, we formulate a deteriorating inventory model with time-varying demand by allowing preservation technology cost as a decision variable in conjunction with replacement policy. The objective is to find the optimal replenishment and preservation technology investment strategies while minimising the total cost over the planning horizon. For any given feasible replenishment scheme, we first prove that the optimal preservation technology investment strategy not only exists but is also unique. Then, a particle swarm optimisation is coded and used to solve the nonlinear programming problem by employing the properties derived from this article. Some numerical examples are used to illustrate the features of the proposed model.

Random patterns in fish schooling enhance alertness: A hydrodynamic perspective

NASA Astrophysics Data System (ADS)

Kadri, U.; Brümmer, F.; Kadri, A.

2016-11-01

One of the most highly debated questions in the field of animal swarming and social behaviour is the collective random patterns and chaotic behaviour formed by some animal species, in particular if there is a danger. Is such a behaviour beneficial or unfavourable for survival? Here we report on one of the most remarkable forms of animal swarming and social behaviour —fish schooling— from a hydrodynamic point of view. We found that some fish species do not have preferred orientation and they swarm in a random pattern mode, despite the excess of energy consumed. Our analyses, which include calculations of the hydrodynamic forces between slender bodies, show that such a behaviour may enhance the transfer of hydrodynamic information, and thus the survivability of the school could improve. These findings support the general hypothesis that a disordered and nontrivial collective behaviour of individuals within a nonlinear dynamical system is essential for optimising transfer of information —an optimisation that might be crucial for survival.

Multi-Objectivising Combinatorial Optimisation Problems by Means of Elementary Landscape Decompositions.

PubMed

Ceberio, Josu; Calvo, Borja; Mendiburu, Alexander; Lozano, Jose A

2018-02-15

In the last decade, many works in combinatorial optimisation have shown that, due to the advances in multi-objective optimisation, the algorithms from this field could be used for solving single-objective problems as well. In this sense, a number of papers have proposed multi-objectivising single-objective problems in order to use multi-objective algorithms in their optimisation. In this article, we follow up this idea by presenting a methodology for multi-objectivising combinatorial optimisation problems based on elementary landscape decompositions of their objective function. Under this framework, each of the elementary landscapes obtained from the decomposition is considered as an independent objective function to optimise. In order to illustrate this general methodology, we consider four problems from different domains: the quadratic assignment problem and the linear ordering problem (permutation domain), the 0-1 unconstrained quadratic optimisation problem (binary domain), and the frequency assignment problem (integer domain). We implemented two widely known multi-objective algorithms, NSGA-II and SPEA2, and compared their performance with that of a single-objective GA. The experiments conducted on a large benchmark of instances of the four problems show that the multi-objective algorithms clearly outperform the single-objective approaches. Furthermore, a discussion on the results suggests that the multi-objective space generated by this decomposition enhances the exploration ability, thus permitting NSGA-II and SPEA2 to obtain better results in the majority of the tested instances.

Multiobjective optimisation of bogie suspension to boost speed on curves

NASA Astrophysics Data System (ADS)

Milad Mousavi-Bideleh, Seyed; Berbyuk, Viktor

2016-01-01

To improve safety and maximum admissible speed on different operational scenarios, multiobjective optimisation of bogie suspension components of a one-car railway vehicle model is considered. The vehicle model has 50 degrees of freedom and is developed in multibody dynamics software SIMPACK. Track shift force, running stability, and risk of derailment are selected as safety objective functions. The improved maximum admissible speeds of the vehicle on curves are determined based on the track plane accelerations up to 1.5 m/s2. To attenuate the number of design parameters for optimisation and improve the computational efficiency, a global sensitivity analysis is accomplished using the multiplicative dimensional reduction method (M-DRM). A multistep optimisation routine based on genetic algorithm (GA) and MATLAB/SIMPACK co-simulation is executed at three levels. The bogie conventional secondary and primary suspension components are chosen as the design parameters in the first two steps, respectively. In the last step semi-active suspension is in focus. The input electrical current to magnetorheological yaw dampers is optimised to guarantee an appropriate safety level. Semi-active controllers are also applied and the respective effects on bogie dynamics are explored. The safety Pareto optimised results are compared with those associated with in-service values. The global sensitivity analysis and multistep approach significantly reduced the number of design parameters and improved the computational efficiency of the optimisation. Furthermore, using the optimised values of design parameters give the possibility to run the vehicle up to 13% faster on curves while a satisfactory safety level is guaranteed. The results obtained can be used in Pareto optimisation and active bogie suspension design problems.

Vertical transportation systems embedded on shuffled frog leaping algorithm for manufacturing optimisation problems in industries.

PubMed

Aungkulanon, Pasura; Luangpaiboon, Pongchanun

2016-01-01

Response surface methods via the first or second order models are important in manufacturing processes. This study, however, proposes different structured mechanisms of the vertical transportation systems or VTS embedded on a shuffled frog leaping-based approach. There are three VTS scenarios, a motion reaching a normal operating velocity, and both reaching and not reaching transitional motion. These variants were performed to simultaneously inspect multiple responses affected by machining parameters in multi-pass turning processes. The numerical results of two machining optimisation problems demonstrated the high performance measures of the proposed methods, when compared to other optimisation algorithms for an actual deep cut design.

Using the Person-Based Approach to optimise a digital intervention for the management of hypertension

PubMed Central

Morton, Katherine; Band, Rebecca; van Woezik, Anne; Grist, Rebecca; McManus, Richard J.; Little, Paul; Yardley, Lucy

2018-01-01

Background For behaviour-change interventions to be successful they must be acceptable to users and overcome barriers to behaviour change. The Person-Based Approach can help to optimise interventions to maximise acceptability and engagement. This article presents a novel, efficient and systematic method that can be used as part of the Person-Based Approach to rapidly analyse data from development studies to inform intervention modifications. We describe how we used this approach to optimise a digital intervention for patients with hypertension (HOME BP), which aims to implement medication and lifestyle changes to optimise blood pressure control. Methods In study 1, hypertensive patients (N = 12) each participated in three think-aloud interviews, providing feedback on a prototype of HOME BP. In study 2 patients (N = 11) used HOME BP for three weeks and were then interviewed about their experiences. Studies 1 and 2 were used to identify detailed changes to the intervention content and potential barriers to engagement with HOME BP. In study 3 (N = 7) we interviewed hypertensive patients who were not interested in using an intervention like HOME BP to identify potential barriers to uptake, which informed modifications to our recruitment materials. Analysis in all three studies involved detailed tabulation of patient data and comparison to our modification criteria. Results Studies 1 and 2 indicated that the HOME BP procedures were generally viewed as acceptable and feasible, but also highlighted concerns about monitoring blood pressure correctly at home and making medication changes remotely. Patients in study 3 had additional concerns about the safety and security of the intervention. Modifications improved the acceptability of the intervention and recruitment materials. Conclusions This paper provides a detailed illustration of how to use the Person-Based Approach to refine a digital intervention for hypertension. The novel, efficient approach to analysis and criteria for deciding when to implement intervention modifications described here may be useful to others developing interventions. PMID:29723262

An optimisation methodology of artificial neural network models for predicting solar radiation: a case study

NASA Astrophysics Data System (ADS)

Rezrazi, Ahmed; Hanini, Salah; Laidi, Maamar

2016-02-01

The right design and the high efficiency of solar energy systems require accurate information on the availability of solar radiation. Due to the cost of purchase and maintenance of the radiometers, these data are not readily available. Therefore, there is a need to develop alternative ways of generating such data. Artificial neural networks (ANNs) are excellent and effective tools for learning, pinpointing or generalising data regularities, as they have the ability to model nonlinear functions; they can also cope with complex `noisy' data. The main objective of this paper is to show how to reach an optimal model of ANNs for applying in prediction of solar radiation. The measured data of the year 2007 in Ghardaïa city (Algeria) are used to demonstrate the optimisation methodology. The performance evaluation and the comparison of results of ANN models with measured data are made on the basis of mean absolute percentage error (MAPE). It is found that MAPE in the ANN optimal model reaches 1.17 %. Also, this model yields a root mean square error (RMSE) of 14.06 % and an MBE of 0.12. The accuracy of the outputs exceeded 97 % and reached up 99.29 %. Results obtained indicate that the optimisation strategy satisfies practical requirements. It can successfully be generalised for any location in the world and be used in other fields than solar radiation estimation.

Spectrally Shaped DP-16QAM Super-Channel Transmission with Multi-Channel Digital Back-Propagation

PubMed Central

Maher, Robert; Xu, Tianhua; Galdino, Lidia; Sato, Masaki; Alvarado, Alex; Shi, Kai; Savory, Seb J.; Thomsen, Benn C.; Killey, Robert I.; Bayvel, Polina

2015-01-01

The achievable transmission capacity of conventional optical fibre communication systems is limited by nonlinear distortions due to the Kerr effect and the difficulty in modulating the optical field to effectively use the available fibre bandwidth. In order to achieve a high information spectral density (ISD), while simultaneously maintaining transmission reach, multi-channel fibre nonlinearity compensation and spectrally efficient data encoding must be utilised. In this work, we use a single coherent super-receiver to simultaneously receive a DP-16QAM super-channel, consisting of seven spectrally shaped 10GBd sub-carriers spaced at the Nyquist frequency. Effective nonlinearity mitigation is achieved using multi-channel digital back-propagation (MC-DBP) and this technique is combined with an optimised forward error correction implementation to demonstrate a record gain in transmission reach of 85%; increasing the maximum transmission distance from 3190 km to 5890 km, with an ISD of 6.60 b/s/Hz. In addition, this report outlines for the first time, the sensitivity of MC-DBP gain to linear transmission line impairments and defines a trade-off between performance and complexity. PMID:25645457

Integrated optical devices based on sol – gel waveguides using the temperature dependence of the effective refractive index

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pavlov, S V; Trofimov, N S; Chekhlova, T K

2014-07-31

A possibility of designing optical waveguide devices based on sol – gel SiO{sub 2} – TiO{sub 2} films using the temperature dependence of the effective refractive index is shown. The dependences of the device characteristics on the parameters of the film and opticalsystem elements are analysed. The operation of a temperature recorder and a temperature limiter with a resolution of 0.6 K mm{sup -1} is demonstrated. The film and output-prism parameters are optimised. (fibreoptic and nonlinear-optic devices)

Modelling the firing pattern of bullfrog vestibular neurons responding to naturalistic stimuli

NASA Technical Reports Server (NTRS)

Paulin, M. G.; Hoffman, L. F.

1999-01-01

We have developed a neural system identification method for fitting models to stimulus-response data, where the response is a spike train. The method involves using a general nonlinear optimisation procedure to fit models in the time domain. We have applied the method to model bullfrog semicircular canal afferent neuron responses during naturalistic, broad-band head rotations. These neurons respond in diverse ways, but a simple four parameter class of models elegantly accounts for the various types of responses observed. c1999 Elsevier Science B.V. All rights reserved.

Achieving optimal SERS through enhanced experimental design

PubMed Central

Fisk, Heidi; Westley, Chloe; Turner, Nicholas J.

2016-01-01

One of the current limitations surrounding surface‐enhanced Raman scattering (SERS) is the perceived lack of reproducibility. SERS is indeed challenging, and for analyte detection, it is vital that the analyte interacts with the metal surface. However, as this is analyte dependent, there is not a single set of SERS conditions that are universal. This means that experimental optimisation for optimum SERS response is vital. Most researchers optimise one factor at a time, where a single parameter is altered first before going onto optimise the next. This is a very inefficient way of searching the experimental landscape. In this review, we explore the use of more powerful multivariate approaches to SERS experimental optimisation based on design of experiments and evolutionary computational methods. We particularly focus on colloidal‐based SERS rather than thin film preparations as a result of their popularity. © 2015 The Authors. Journal of Raman Spectroscopy published by John Wiley & Sons, Ltd. PMID:27587905

Assessment of grid optimisation measures for the German transmission grid using open source grid data

NASA Astrophysics Data System (ADS)

Böing, F.; Murmann, A.; Pellinger, C.; Bruckmeier, A.; Kern, T.; Mongin, T.

2018-02-01

The expansion of capacities in the German transmission grid is a necessity for further integration of renewable energy sources into the electricity sector. In this paper, the grid optimisation measures ‘Overhead Line Monitoring’, ‘Power-to-Heat’ and ‘Demand Response in the Industry’ are evaluated and compared against conventional grid expansion for the year 2030. Initially, the methodical approach of the simulation model is presented and detailed descriptions of the grid model and the used grid data, which partly originates from open-source platforms, are provided. Further, this paper explains how ‘Curtailment’ and ‘Redispatch’ can be reduced by implementing grid optimisation measures and how the depreciation of economic costs can be determined considering construction costs. The developed simulations show that the conventional grid expansion is more efficient and implies more grid relieving effects than the evaluated grid optimisation measures.

VLSI Technology for Cognitive Radio

NASA Astrophysics Data System (ADS)

VIJAYALAKSHMI, B.; SIDDAIAH, P.

2017-08-01

One of the most challenging tasks of cognitive radio is the efficiency in the spectrum sensing scheme to overcome the spectrum scarcity problem. The popular and widely used spectrum sensing technique is the energy detection scheme as it is very simple and doesn’t require any previous information related to the signal. We propose one such approach which is an optimised spectrum sensing scheme with reduced filter structure. The optimisation is done in terms of area and power performance of the spectrum. The simulations of the VLSI structure of the optimised flexible spectrum is done using verilog coding by using the XILINX ISE software. Our method produces performance with 13% reduction in area and 66% reduction in power consumption in comparison to the flexible spectrum sensing scheme. All the results are tabulated and comparisons are made. A new scheme for optimised and effective spectrum sensing opens up with our model.

Achieving optimal SERS through enhanced experimental design.

PubMed

Fisk, Heidi; Westley, Chloe; Turner, Nicholas J; Goodacre, Royston

2016-01-01

One of the current limitations surrounding surface-enhanced Raman scattering (SERS) is the perceived lack of reproducibility. SERS is indeed challenging, and for analyte detection, it is vital that the analyte interacts with the metal surface. However, as this is analyte dependent, there is not a single set of SERS conditions that are universal. This means that experimental optimisation for optimum SERS response is vital. Most researchers optimise one factor at a time, where a single parameter is altered first before going onto optimise the next. This is a very inefficient way of searching the experimental landscape. In this review, we explore the use of more powerful multivariate approaches to SERS experimental optimisation based on design of experiments and evolutionary computational methods. We particularly focus on colloidal-based SERS rather than thin film preparations as a result of their popularity. © 2015 The Authors. Journal of Raman Spectroscopy published by John Wiley & Sons, Ltd.

Navigating catastrophes: Local but not global optimisation allows for macro-economic navigation of crises

NASA Astrophysics Data System (ADS)

Harré, Michael S.

2013-02-01

Two aspects of modern economic theory have dominated the recent discussion on the state of the global economy: Crashes in financial markets and whether or not traditional notions of economic equilibrium have any validity. We have all seen the consequences of market crashes: plummeting share prices, businesses collapsing and considerable uncertainty throughout the global economy. This seems contrary to what might be expected of a system in equilibrium where growth dominates the relatively minor fluctuations in prices. Recent work from within economics as well as by physicists, psychologists and computational scientists has significantly improved our understanding of the more complex aspects of these systems. With this interdisciplinary approach in mind, a behavioural economics model of local optimisation is introduced and three general properties are proven. The first is that under very specific conditions local optimisation leads to a conventional macro-economic notion of a global equilibrium. The second is that if both global optimisation and economic growth are required then under very mild assumptions market catastrophes are an unavoidable consequence. Third, if only local optimisation and economic growth are required then there is sufficient parametric freedom for macro-economic policy makers to steer an economy around catastrophes without overtly disrupting local optimisation.

Reservoir optimisation using El Niño information. Case study of Daule Peripa (Ecuador)

NASA Astrophysics Data System (ADS)

Gelati, Emiliano; Madsen, Henrik; Rosbjerg, Dan

2010-05-01

The optimisation of water resources systems requires the ability to produce runoff scenarios that are consistent with available climatic information. We approach stochastic runoff modelling with a Markov-modulated autoregressive model with exogenous input, which belongs to the class of Markov-switching models. The model assumes runoff parameterisation to be conditioned on a hidden climatic state following a Markov chain, whose state transition probabilities depend on climatic information. This approach allows stochastic modeling of non-stationary runoff, as runoff anomalies are described by a mixture of autoregressive models with exogenous input, each one corresponding to a climate state. We calibrate the model on the inflows of the Daule Peripa reservoir located in western Ecuador, where the occurrence of El Niño leads to anomalously heavy rainfall caused by positive sea surface temperature anomalies along the coast. El Niño - Southern Oscillation (ENSO) information is used to condition the runoff parameterisation. Inflow predictions are realistic, especially at the occurrence of El Niño events. The Daule Peripa reservoir serves a hydropower plant and a downstream water supply facility. Using historical ENSO records, synthetic monthly inflow scenarios are generated for the period 1950-2007. These scenarios are used as input to perform stochastic optimisation of the reservoir rule curves with a multi-objective Genetic Algorithm (MOGA). The optimised rule curves are assumed to be the reservoir base policy. ENSO standard indices are currently forecasted at monthly time scale with nine-month lead time. These forecasts are used to perform stochastic optimisation of reservoir releases at each monthly time step according to the following procedure: (i) nine-month inflow forecast scenarios are generated using ENSO forecasts; (ii) a MOGA is set up to optimise the upcoming nine monthly releases; (iii) the optimisation is carried out by simulating the releases on the inflow forecasts, and by applying the base policy on a subsequent synthetic inflow scenario in order to account for long-term costs; (iv) the optimised release for the first month is implemented; (v) the state of the system is updated and (i), (ii), (iii), and (iv) are iterated for the following time step. The results highlight the advantages of using a climate-driven stochastic model to produce inflow scenarios and forecasts for reservoir optimisation, showing potential improvements with respect to the current management. Dynamic programming was used to find the best possible release time series given the inflow observations, in order to benchmark any possible operational improvement.

Comparing approaches for using climate projections in assessing water resources investments for systems with multiple stakeholder groups

NASA Astrophysics Data System (ADS)

Hurford, Anthony; Harou, Julien

2015-04-01

Climate change has challenged conventional methods of planning water resources infrastructure investment, relying on stationarity of time-series data. It is not clear how to best use projections of future climatic conditions. Many-objective simulation-optimisation and trade-off analysis using evolutionary algorithms has been proposed as an approach to addressing complex planning problems with multiple conflicting objectives. The search for promising assets and policies can be carried out across a range of climate projections, to identify the configurations of infrastructure investment shown by model simulation to be robust under diverse future conditions. Climate projections can be used in different ways within a simulation model to represent the range of possible future conditions and understand how optimal investments vary according to the different hydrological conditions. We compare two approaches, optimising over an ensemble of different 20-year flow and PET timeseries projections, and separately for individual future scenarios built synthetically from the original ensemble. Comparing trade-off curves and surfaces generated by the two approaches helps understand the limits and benefits of optimising under different sets of conditions. The comparison is made for the Tana Basin in Kenya, where climate change combined with multiple conflicting objectives of water management and infrastructure investment mean decision-making is particularly challenging.

Cost optimisation and minimisation of the environmental impact through life cycle analysis of the waste water treatment plant of Bree (Belgium).

PubMed

De Gussem, K; Wambecq, T; Roels, J; Fenu, A; De Gueldre, G; Van De Steene, B

2011-01-01

An ASM2da model of the full-scale waste water plant of Bree (Belgium) has been made. It showed very good correlation with reference operational data. This basic model has been extended to include an accurate calculation of environmental footprint and operational costs (energy consumption, dosing of chemicals and sludge treatment). Two optimisation strategies were compared: lowest cost meeting the effluent consent versus lowest environmental footprint. Six optimisation scenarios have been studied, namely (i) implementation of an online control system based on ammonium and nitrate sensors, (ii) implementation of a control on MLSS concentration, (iii) evaluation of internal recirculation flow, (iv) oxygen set point, (v) installation of mixing in the aeration tank, and (vi) evaluation of nitrate setpoint for post denitrification. Both an environmental impact or Life Cycle Assessment (LCA) based approach for optimisation are able to significantly lower the cost and environmental footprint. However, the LCA approach has some advantages over cost minimisation of an existing full-scale plant. LCA tends to chose control settings that are more logic: it results in a safer operation of the plant with less risks regarding the consents. It results in a better effluent at a slightly increased cost.

Single tube genotyping of sickle cell anaemia using PCR-based SNP analysis

PubMed Central

Waterfall, Christy M.; Cobb, Benjamin D.

2001-01-01

Allele-specific amplification (ASA) is a generally applicable technique for the detection of known single nucleotide polymorphisms (SNPs), deletions, insertions and other sequence variations. Conventionally, two reactions are required to determine the zygosity of DNA in a two-allele system, along with significant upstream optimisation to define the specific test conditions. Here, we combine single tube bi-directional ASA with a ‘matrix-based’ optimisation strategy, speeding up the whole process in a reduced reaction set. We use sickle cell anaemia as our model SNP system, a genetic disease that is currently screened using ASA methods. Discriminatory conditions were rapidly optimised enabling the unambiguous identification of DNA from homozygous sickle cell patients (HbS/S), heterozygous carriers (HbA/S) or normal DNA in a single tube. Simple downstream mathematical analyses based on product yield across the optimisation set allow an insight into the important aspects of priming competition and component interactions in this competitive PCR. This strategy can be applied to any polymorphism, defining specific conditions using a multifactorial approach. The inherent simplicity and low cost of this PCR-based method validates bi-directional ASA as an effective tool in future clinical screening and pharmacogenomic research where more expensive fluorescence-based approaches may not be desirable. PMID:11726702

Single tube genotyping of sickle cell anaemia using PCR-based SNP analysis.

PubMed

Waterfall, C M; Cobb, B D

2001-12-01

Allele-specific amplification (ASA) is a generally applicable technique for the detection of known single nucleotide polymorphisms (SNPs), deletions, insertions and other sequence variations. Conventionally, two reactions are required to determine the zygosity of DNA in a two-allele system, along with significant upstream optimisation to define the specific test conditions. Here, we combine single tube bi-directional ASA with a 'matrix-based' optimisation strategy, speeding up the whole process in a reduced reaction set. We use sickle cell anaemia as our model SNP system, a genetic disease that is currently screened using ASA methods. Discriminatory conditions were rapidly optimised enabling the unambiguous identification of DNA from homozygous sickle cell patients (HbS/S), heterozygous carriers (HbA/S) or normal DNA in a single tube. Simple downstream mathematical analyses based on product yield across the optimisation set allow an insight into the important aspects of priming competition and component interactions in this competitive PCR. This strategy can be applied to any polymorphism, defining specific conditions using a multifactorial approach. The inherent simplicity and low cost of this PCR-based method validates bi-directional ASA as an effective tool in future clinical screening and pharmacogenomic research where more expensive fluorescence-based approaches may not be desirable.

A data driven nonlinear stochastic model for blood glucose dynamics.

PubMed

Zhang, Yan; Holt, Tim A; Khovanova, Natalia

2016-03-01

The development of adequate mathematical models for blood glucose dynamics may improve early diagnosis and control of diabetes mellitus (DM). We have developed a stochastic nonlinear second order differential equation to describe the response of blood glucose concentration to food intake using continuous glucose monitoring (CGM) data. A variational Bayesian learning scheme was applied to define the number and values of the system's parameters by iterative optimisation of free energy. The model has the minimal order and number of parameters to successfully describe blood glucose dynamics in people with and without DM. The model accounts for the nonlinearity and stochasticity of the underlying glucose-insulin dynamic process. Being data-driven, it takes full advantage of available CGM data and, at the same time, reflects the intrinsic characteristics of the glucose-insulin system without detailed knowledge of the physiological mechanisms. We have shown that the dynamics of some postprandial blood glucose excursions can be described by a reduced (linear) model, previously seen in the literature. A comprehensive analysis demonstrates that deterministic system parameters belong to different ranges for diabetes and controls. Implications for clinical practice are discussed. This is the first study introducing a continuous data-driven nonlinear stochastic model capable of describing both DM and non-DM profiles. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Discovery and optimisation studies of antimalarial phenotypic hits

PubMed Central

Mital, Alka; Murugesan, Dinakaran; Kaiser, Marcel; Yeates, Clive; Gilbert, Ian H.

2015-01-01

There is an urgent need for the development of new antimalarial compounds. As a result of a phenotypic screen, several compounds with potent activity against the parasite Plasmodium falciparum were identified. Characterization of these compounds is discussed, along with approaches to optimise the physicochemical properties. The in vitro antimalarial activity of these compounds against P. falciparum K1 had EC50 values in the range of 0.09–29 μM, and generally good selectivity (typically >100-fold) compared to a mammalian cell line (L6). One example showed no significant activity against a rodent model of malaria, and more work is needed to optimise these compounds. PMID:26408453

INDIVIDUAL-BASED MODELS: POWERFUL OR POWER STRUGGLE?

PubMed

Willem, L; Stijven, S; Hens, N; Vladislavleva, E; Broeckhove, J; Beutels, P

2015-01-01

Individual-based models (IBMs) offer endless possibilities to explore various research questions but come with high model complexity and computational burden. Large-scale IBMs have become feasible but the novel hardware architectures require adapted software. The increased model complexity also requires systematic exploration to gain thorough system understanding. We elaborate on the development of IBMs for vaccine-preventable infectious diseases and model exploration with active learning. Investment in IBM simulator code can lead to significant runtime reductions. We found large performance differences due to data locality. Sorting the population once, reduced simulation time by a factor two. Storing person attributes separately instead of using person objects also seemed more efficient. Next, we improved model performance up to 70% by structuring potential contacts based on health status before processing disease transmission. The active learning approach we present is based on iterative surrogate modelling and model-guided experimentation. Symbolic regression is used for nonlinear response surface modelling with automatic feature selection. We illustrate our approach using an IBM for influenza vaccination. After optimizing the parameter spade, we observed an inverse relationship between vaccination coverage and the clinical attack rate reinforced by herd immunity. These insights can be used to focus and optimise research activities, and to reduce both dimensionality and decision uncertainty.

Quantification of fructo-oligosaccharides based on the evaluation of oligomer ratios using an artificial neural network.

PubMed

Onofrejová, Lucia; Farková, Marta; Preisler, Jan

2009-04-13

The application of an internal standard in quantitative analysis is desirable in order to correct for variations in sample preparation and instrumental response. In mass spectrometry of organic compounds, the internal standard is preferably labelled with a stable isotope, such as (18)O, (15)N or (13)C. In this study, a method for the quantification of fructo-oligosaccharides using matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI TOF MS) was proposed and tested on raftilose, a partially hydrolysed inulin with a degree of polymeration 2-7. A tetraoligosaccharide nystose, which is chemically identical to the raftilose tetramer, was used as an internal standard rather than an isotope-labelled analyte. Two mathematical approaches used for data processing, conventional calculations and artificial neural networks (ANN), were compared. The conventional data processing relies on the assumption that a constant oligomer dispersion profile will change after the addition of the internal standard and some simple numerical calculations. On the other hand, ANN was found to compensate for a non-linear MALDI response and variations in the oligomer dispersion profile with raftilose concentration. As a result, the application of ANN led to lower quantification errors and excellent day-to-day repeatability compared to the conventional data analysis. The developed method is feasible for MS quantification of raftilose in the range of 10-750 pg with errors below 7%. The content of raftilose was determined in dietary cream; application can be extended to other similar polymers. It should be stressed that no special optimisation of the MALDI process was carried out. A common MALDI matrix and sample preparation were used and only the basic parameters, such as sampling and laser energy, were optimised prior to quantification.

Rotational degree-of-freedom synthesis: An optimised finite difference method for non-exact data

NASA Astrophysics Data System (ADS)

Gibbons, T. J.; Öztürk, E.; Sims, N. D.

2018-01-01

Measuring the rotational dynamic behaviour of a structure is important for many areas of dynamics such as passive vibration control, acoustics, and model updating. Specialist and dedicated equipment is often needed, unless the rotational degree-of-freedom is synthesised based upon translational data. However, this involves numerically differentiating the translational mode shapes to approximate the rotational modes, for example using a finite difference algorithm. A key challenge with this approach is choosing the measurement spacing between the data points, an issue which has often been overlooked in the published literature. The present contribution will for the first time prove that the use of a finite difference approach can be unstable when using non-exact measured data and a small measurement spacing, for beam-like structures. Then, a generalised analytical error analysis is used to propose an optimised measurement spacing, which balances the numerical error of the finite difference equation with the propagation error from the perturbed data. The approach is demonstrated using both numerical and experimental investigations. It is shown that by obtaining a small number of test measurements it is possible to optimise the measurement accuracy, without any further assumptions on the boundary conditions of the structure.

A radiobiology-based inverse treatment planning method for optimisation of permanent l-125 prostate implants in focal brachytherapy.

PubMed

Haworth, Annette; Mears, Christopher; Betts, John M; Reynolds, Hayley M; Tack, Guido; Leo, Kevin; Williams, Scott; Ebert, Martin A

2016-01-07

Treatment plans for ten patients, initially treated with a conventional approach to low dose-rate brachytherapy (LDR, 145 Gy to entire prostate), were compared with plans for the same patients created with an inverse-optimisation planning process utilising a biologically-based objective. The 'biological optimisation' considered a non-uniform distribution of tumour cell density through the prostate based on known and expected locations of the tumour. Using dose planning-objectives derived from our previous biological-model validation study, the volume of the urethra receiving 125% of the conventional prescription (145 Gy) was reduced from a median value of 64% to less than 8% whilst maintaining high values of TCP. On average, the number of planned seeds was reduced from 85 to less than 75. The robustness of plans to random seed displacements needs to be carefully considered when using contemporary seed placement techniques. We conclude that an inverse planning approach to LDR treatments, based on a biological objective, has the potential to maintain high rates of tumour control whilst minimising dose to healthy tissue. In future, the radiobiological model will be informed using multi-parametric MRI to provide a personalised medicine approach.

Optimising a modified free-space permittivity characterisation method for civil engineering applications

NASA Astrophysics Data System (ADS)

Muller, Wayne; Scheuermann, Alexander

2016-04-01

Measuring the electrical permittivity of civil engineering materials is important for a range of ground penetrating radar (GPR) and pavement moisture measurement applications. Compacted unbound granular (UBG) pavement materials present a number of preparation and measurement challenges using conventional characterisation techniques. As an alternative to these methods, a modified free-space (MFS) characterisation approach has previously been investigated. This paper describes recent work to optimise and validate the MFS technique. The research included finite difference time domain (FDTD) modelling to better understand the nature of wave propagation within material samples and the test apparatus. This research led to improvements in the test approach and optimisation of sample sizes. The influence of antenna spacing and sample thickness on the permittivity results was investigated by a series of experiments separating antennas and measuring samples of nylon and water. Permittivity measurements of samples of nylon and water approximately 100 mm and 170 mm thick were also compared, showing consistent results. These measurements also agreed well with surface probe measurements of the nylon sample and literature values for water. The results indicate permittivity estimates of acceptable accuracy can be obtained using the proposed approach, apparatus and sample sizes.

Optimisation of a propagation-based x-ray phase-contrast micro-CT system

NASA Astrophysics Data System (ADS)

Nesterets, Yakov I.; Gureyev, Timur E.; Dimmock, Matthew R.

2018-03-01

Micro-CT scanners find applications in many areas ranging from biomedical research to material sciences. In order to provide spatial resolution on a micron scale, these scanners are usually equipped with micro-focus, low-power x-ray sources and hence require long scanning times to produce high resolution 3D images of the object with acceptable contrast-to-noise. Propagation-based phase-contrast tomography (PB-PCT) has the potential to significantly improve the contrast-to-noise ratio (CNR) or, alternatively, reduce the image acquisition time while preserving the CNR and the spatial resolution. We propose a general approach for the optimisation of the PB-PCT imaging system. When applied to an imaging system with fixed parameters of the source and detector this approach requires optimisation of only two independent geometrical parameters of the imaging system, i.e. the source-to-object distance R 1 and geometrical magnification M, in order to produce the best spatial resolution and CNR. If, in addition to R 1 and M, the system parameter space also includes the source size and the anode potential this approach allows one to find a unique configuration of the imaging system that produces the required spatial resolution and the best CNR.

Optimisation of the vibrational response of ultrasonic cutting systems

NASA Astrophysics Data System (ADS)

Cartmell, M. P.; Lim, F. C. N.; Cardoni, A.; Lucas, M.

2005-10-01

This paper provides an account of an investigation into possible dynamic interactions between two coupled non-linear sub-systems, each possessing opposing non-linear overhang characteristics in the frequency domain in terms of positive and negative cubic stiffnesses. This system is a two-degree-of-freedom Duffing oscillator in which certain non-linear effects can be advantageously neutralised under specific conditions. This theoretical vehicle has been used as a preliminary methodology for understanding the interactive behaviour within typical industrial ultrasonic cutting components. Ultrasonic energy is generated within a piezoelectric exciter, which is inherently non-linear, and which is coupled to a bar- or block-horn, and to one or more material cutting blades, for example. The horn/blade configurations are also non-linear, and within the whole system there are response features which are strongly reminiscent of positive and negative cubic stiffness effects. The two-degree-of-freedom model is analysed and it is shown that a practically useful mitigating effect on the overall non-linear response of the system can be created under certain conditions when one of the cubic stiffnesses is varied. It has also been shown experimentally that coupling of ultrasonic components with different non-linear characteristics can strongly influence the performance of the system and that the general behaviour of the hypothetical theoretical model is indeed borne out in practice. Further experiments have shown that a multiple horn/blade configuration can, under certain circumstances, display autoparametric responses based on the forced response of the desired longitudinal mode parametrically exciting an undesired lateral mode. Typical autoparametric response phenomena have been observed and are presented at the end of the paper.

A supportive architecture for CFD-based design optimisation

NASA Astrophysics Data System (ADS)

Li, Ni; Su, Zeya; Bi, Zhuming; Tian, Chao; Ren, Zhiming; Gong, Guanghong

2014-03-01

Multi-disciplinary design optimisation (MDO) is one of critical methodologies to the implementation of enterprise systems (ES). MDO requiring the analysis of fluid dynamics raises a special challenge due to its extremely intensive computation. The rapid development of computational fluid dynamic (CFD) technique has caused a rise of its applications in various fields. Especially for the exterior designs of vehicles, CFD has become one of the three main design tools comparable to analytical approaches and wind tunnel experiments. CFD-based design optimisation is an effective way to achieve the desired performance under the given constraints. However, due to the complexity of CFD, integrating with CFD analysis in an intelligent optimisation algorithm is not straightforward. It is a challenge to solve a CFD-based design problem, which is usually with high dimensions, and multiple objectives and constraints. It is desirable to have an integrated architecture for CFD-based design optimisation. However, our review on existing works has found that very few researchers have studied on the assistive tools to facilitate CFD-based design optimisation. In the paper, a multi-layer architecture and a general procedure are proposed to integrate different CFD toolsets with intelligent optimisation algorithms, parallel computing technique and other techniques for efficient computation. In the proposed architecture, the integration is performed either at the code level or data level to fully utilise the capabilities of different assistive tools. Two intelligent algorithms are developed and embedded with parallel computing. These algorithms, together with the supportive architecture, lay a solid foundation for various applications of CFD-based design optimisation. To illustrate the effectiveness of the proposed architecture and algorithms, the case studies on aerodynamic shape design of a hypersonic cruising vehicle are provided, and the result has shown that the proposed architecture and developed algorithms have performed successfully and efficiently in dealing with the design optimisation with over 200 design variables.

On the dynamic rounding-off in analogue and RF optimal circuit sizing

NASA Astrophysics Data System (ADS)

Kotti, Mouna; Fakhfakh, Mourad; Fino, Maria Helena

2014-04-01

Frequently used approaches to solve discrete multivariable optimisation problems consist of computing solutions using a continuous optimisation technique. Then, using heuristics, the variables are rounded-off to their nearest available discrete values to obtain a discrete solution. Indeed, in many engineering problems, and particularly in analogue circuit design, component values, such as the geometric dimensions of the transistors, the number of fingers in an integrated capacitor or the number of turns in an integrated inductor, cannot be chosen arbitrarily since they have to obey to some technology sizing constraints. However, rounding-off the variables values a posteriori and can lead to infeasible solutions (solutions that are located too close to the feasible solution frontier) or degradation of the obtained results (expulsion from the neighbourhood of a 'sharp' optimum) depending on how the added perturbation affects the solution. Discrete optimisation techniques, such as the dynamic rounding-off technique (DRO) are, therefore, needed to overcome the previously mentioned situation. In this paper, we deal with an improvement of the DRO technique. We propose a particle swarm optimisation (PSO)-based DRO technique, and we show, via some analog and RF-examples, the necessity to implement such a routine into continuous optimisation algorithms.

PGA/MOEAD: a preference-guided evolutionary algorithm for multi-objective decision-making problems with interval-valued fuzzy preferences

NASA Astrophysics Data System (ADS)

Luo, Bin; Lin, Lin; Zhong, ShiSheng

2018-02-01

In this research, we propose a preference-guided optimisation algorithm for multi-criteria decision-making (MCDM) problems with interval-valued fuzzy preferences. The interval-valued fuzzy preferences are decomposed into a series of precise and evenly distributed preference-vectors (reference directions) regarding the objectives to be optimised on the basis of uniform design strategy firstly. Then the preference information is further incorporated into the preference-vectors based on the boundary intersection approach, meanwhile, the MCDM problem with interval-valued fuzzy preferences is reformulated into a series of single-objective optimisation sub-problems (each sub-problem corresponds to a decomposed preference-vector). Finally, a preference-guided optimisation algorithm based on MOEA/D (multi-objective evolutionary algorithm based on decomposition) is proposed to solve the sub-problems in a single run. The proposed algorithm incorporates the preference-vectors within the optimisation process for guiding the search procedure towards a more promising subset of the efficient solutions matching the interval-valued fuzzy preferences. In particular, lots of test instances and an engineering application are employed to validate the performance of the proposed algorithm, and the results demonstrate the effectiveness and feasibility of the algorithm.

Design optimisation of powers-of-two FIR filter using self-organising random immigrants GA

NASA Astrophysics Data System (ADS)

Chandra, Abhijit; Chattopadhyay, Sudipta

2015-01-01

In this communication, we propose a novel design strategy of multiplier-less low-pass finite impulse response (FIR) filter with the aid of a recent evolutionary optimisation technique, known as the self-organising random immigrants genetic algorithm. Individual impulse response coefficients of the proposed filter have been encoded as sum of signed powers-of-two. During the formulation of the cost function for the optimisation algorithm, both the frequency response characteristic and the hardware cost of the discrete coefficient FIR filter have been considered. The role of crossover probability of the optimisation technique has been evaluated on the overall performance of the proposed strategy. For this purpose, the convergence characteristic of the optimisation technique has been included in the simulation results. In our analysis, two design examples of different specifications have been taken into account. In order to substantiate the efficiency of our proposed structure, a number of state-of-the-art design strategies of multiplier-less FIR filter have also been included in this article for the purpose of comparison. Critical analysis of the result unambiguously establishes the usefulness of our proposed approach for the hardware efficient design of digital filter.

CubiCal - Fast radio interferometric calibration suite exploiting complex optimisation

NASA Astrophysics Data System (ADS)

Kenyon, J. S.; Smirnov, O. M.; Grobler, T. L.; Perkins, S. J.

2018-05-01

It has recently been shown that radio interferometric gain calibration can be expressed succinctly in the language of complex optimisation. In addition to providing an elegant framework for further development, it exposes properties of the calibration problem which can be exploited to accelerate traditional non-linear least squares solvers such as Gauss-Newton and Levenberg-Marquardt. We extend existing derivations to chains of Jones terms: products of several gains which model different aberrant effects. In doing so, we find that the useful properties found in the single term case still hold. We also develop several specialised solvers which deal with complex gains parameterised by real values. The newly developed solvers have been implemented in a Python package called CubiCal, which uses a combination of Cython, multiprocessing and shared memory to leverage the power of modern hardware. We apply CubiCal to both simulated and real data, and perform both direction-independent and direction-dependent self-calibration. Finally, we present the results of some rudimentary profiling to show that CubiCal is competitive with respect to existing calibration tools such as MeqTrees.

Natural Erosion of Sandstone as Shape Optimisation.

PubMed

Ostanin, Igor; Safonov, Alexander; Oseledets, Ivan

2017-12-11

Natural arches, pillars and other exotic sandstone formations have always been attracting attention for their unusual shapes and amazing mechanical balance that leave a strong impression of intelligent design rather than the result of a stochastic process. It has been recently demonstrated that these shapes could have been the result of the negative feedback between stress and erosion that originates in fundamental laws of friction between the rock's constituent particles. Here we present a deeper analysis of this idea and bridge it with the approaches utilized in shape and topology optimisation. It appears that the processes of natural erosion, driven by stochastic surface forces and Mohr-Coulomb law of dry friction, can be viewed within the framework of local optimisation for minimum elastic strain energy. Our hypothesis is confirmed by numerical simulations of the erosion using the topological-shape optimisation model. Our work contributes to a better understanding of stochastic erosion and feasible landscape formations that could be found on Earth and beyond.

Optimisation of synergistic biomass-degrading enzyme systems for efficient rice straw hydrolysis using an experimental mixture design.

PubMed

Suwannarangsee, Surisa; Bunterngsook, Benjarat; Arnthong, Jantima; Paemanee, Atchara; Thamchaipenet, Arinthip; Eurwilaichitr, Lily; Laosiripojana, Navadol; Champreda, Verawat

2012-09-01

Synergistic enzyme system for the hydrolysis of alkali-pretreated rice straw was optimised based on the synergy of crude fungal enzyme extracts with a commercial cellulase (Celluclast™). Among 13 enzyme extracts, the enzyme preparation from Aspergillus aculeatus BCC 199 exhibited the highest level of synergy with Celluclast™. This synergy was based on the complementary cellulolytic and hemicellulolytic activities of the BCC 199 enzyme extract. A mixture design was used to optimise the ternary enzyme complex based on the synergistic enzyme mixture with Bacillus subtilis expansin. Using the full cubic model, the optimal formulation of the enzyme mixture was predicted to the percentage of Celluclast™: BCC 199: expansin=41.4:37.0:21.6, which produced 769 mg reducing sugar/g biomass using 2.82 FPU/g enzymes. This work demonstrated the use of a systematic approach for the design and optimisation of a synergistic enzyme mixture of fungal enzymes and expansin for lignocellulosic degradation. Copyright © 2012 Elsevier Ltd. All rights reserved.

The development and optimisation of a primary care-based whole system complex intervention (CARE Plus) for patients with multimorbidity living in areas of high socioeconomic deprivation

PubMed Central

O'Brien, Rosaleen; Fitzpatrick, Bridie; Higgins, Maria; Guthrie, Bruce; Watt, Graham; Wyke, Sally

2016-01-01

Objectives To develop and optimise a primary care-based complex intervention (CARE Plus) to enhance the quality of life of patients with multimorbidity in the deprived areas. Methods Six co-design discussion groups involving 32 participants were held separately with multimorbid patients from the deprived areas, voluntary organisations, general practitioners and practice nurses working in the deprived areas. This was followed by piloting in two practices and further optimisation based on interviews with 11 general practitioners, 2 practice nurses and 6 participating multimorbid patients. Results Participants endorsed the need for longer consultations, relational continuity and a holistic approach. All felt that training and support of the health care staff was important. Most participants welcomed the idea of additional self-management support, though some practitioners were dubious about whether patients would use it. The pilot study led to changes including a revised care plan, the inclusion of mindfulness-based stress reduction techniques in the support of practitioners and patients, and the stream-lining of the written self-management support material for patients. Discussion We have co-designed and optimised an augmented primary care intervention involving a whole-system approach to enhance quality of life in multimorbid patients living in the deprived areas. CARE Plus will next be tested in a phase 2 cluster randomised controlled trial. PMID:27068113

Scintillator-based transverse proton beam profiler for laser-plasma ion sources.

PubMed

Dover, N P; Nishiuchi, M; Sakaki, H; Alkhimova, M A; Faenov, A Ya; Fukuda, Y; Kiriyama, H; Kon, A; Kondo, K; Nishitani, K; Ogura, K; Pikuz, T A; Pirozhkov, A S; Sagisaka, A; Kando, M; Kondo, K

2017-07-01

A high repetition rate scintillator-based transverse beam profile diagnostic for laser-plasma accelerated proton beams has been designed and commissioned. The proton beam profiler uses differential filtering to provide coarse energy resolution and a flexible design to allow optimisation for expected beam energy range and trade-off between spatial and energy resolution depending on the application. A plastic scintillator detector, imaged with a standard 12-bit scientific camera, allows data to be taken at a high repetition rate. An algorithm encompassing the scintillator non-linearity is described to estimate the proton spectrum at different spatial locations.

Determination of optimal ultrasound planes for the initialisation of image registration during endoscopic ultrasound-guided procedures.

PubMed

Bonmati, Ester; Hu, Yipeng; Gibson, Eli; Uribarri, Laura; Keane, Geri; Gurusami, Kurinchi; Davidson, Brian; Pereira, Stephen P; Clarkson, Matthew J; Barratt, Dean C

2018-06-01

Navigation of endoscopic ultrasound (EUS)-guided procedures of the upper gastrointestinal (GI) system can be technically challenging due to the small fields-of-view of ultrasound and optical devices, as well as the anatomical variability and limited number of orienting landmarks during navigation. Co-registration of an EUS device and a pre-procedure 3D image can enhance the ability to navigate. However, the fidelity of this contextual information depends on the accuracy of registration. The purpose of this study was to develop and test the feasibility of a simulation-based planning method for pre-selecting patient-specific EUS-visible anatomical landmark locations to maximise the accuracy and robustness of a feature-based multimodality registration method. A registration approach was adopted in which landmarks are registered to anatomical structures segmented from the pre-procedure volume. The predicted target registration errors (TREs) of EUS-CT registration were estimated using simulated visible anatomical landmarks and a Monte Carlo simulation of landmark localisation error. The optimal planes were selected based on the 90th percentile of TREs, which provide a robust and more accurate EUS-CT registration initialisation. The method was evaluated by comparing the accuracy and robustness of registrations initialised using optimised planes versus non-optimised planes using manually segmented CT images and simulated ([Formula: see text]) or retrospective clinical ([Formula: see text]) EUS landmarks. The results show a lower 90th percentile TRE when registration is initialised using the optimised planes compared with a non-optimised initialisation approach (p value [Formula: see text]). The proposed simulation-based method to find optimised EUS planes and landmarks for EUS-guided procedures may have the potential to improve registration accuracy. Further work will investigate applying the technique in a clinical setting.

A centre-free approach for resource allocation with lower bounds

NASA Astrophysics Data System (ADS)

Obando, Germán; Quijano, Nicanor; Rakoto-Ravalontsalama, Naly

2017-09-01

Since complexity and scale of systems are continuously increasing, there is a growing interest in developing distributed algorithms that are capable to address information constraints, specially for solving optimisation and decision-making problems. In this paper, we propose a novel method to solve distributed resource allocation problems that include lower bound constraints. The optimisation process is carried out by a set of agents that use a communication network to coordinate their decisions. Convergence and optimality of the method are guaranteed under some mild assumptions related to the convexity of the problem and the connectivity of the underlying graph. Finally, we compare our approach with other techniques reported in the literature, and we present some engineering applications.

A review on simple assembly line balancing type-e problem

NASA Astrophysics Data System (ADS)

Jusop, M.; Rashid, M. F. F. Ab

2015-12-01

Simple assembly line balancing (SALB) is an attempt to assign the tasks to the various workstations along the line so that the precedence relations are satisfied and some performance measure are optimised. Advanced approach of algorithm is necessary to solve large-scale problems as SALB is a class of NP-hard. Only a few studies are focusing on simple assembly line balancing of Type-E problem (SALB-E) since it is a general and complex problem. SALB-E problem is one of SALB problem which consider the number of workstation and the cycle time simultaneously for the purpose of maximising the line efficiency. This paper review previous works that has been done in order to optimise SALB -E problem. Besides that, this paper also reviewed the Genetic Algorithm approach that has been used to optimise SALB-E. From the reviewed that has been done, it was found that none of the existing works are concern on the resource constraint in the SALB-E problem especially on machine and tool constraints. The research on SALB-E will contribute to the improvement of productivity in real industrial application.

Development and in vitro/in vivo evaluation of a novel benznidazole liquid dosage form using a quality-by-design approach.

PubMed

Santos Souza, Higo Fernando; Real, Daniel; Leonardi, Darío; Rocha, Sandra Carla; Alonso, Victoria; Serra, Esteban; Silber, Ariel Mariano; Salomon, Claudio Javier

2017-12-01

To develop an alcohol-free solution suitable for children of benznidazole, the drug of choice for treatment of Chagas disease. In a quality-by-design approach, a systematic optimisation procedure was carried out to estimate the values of the factors leading to the maximum drug concentration. The formulations were analysed in terms of chemical and physical stability and drug content. The final preparation was subjected to an in vivo palatability assay. Mice were infected and treated orally in a murine model. The results showed that benznidazole solubility increased up to 18.38 mg/ml in the optimised co-solvent system. The final formulation remained stable at all three temperatures tested, with suitable drug content and no significant variability. Palatability of the preparation was improved by taste masking of BZL. In vivo studies showed that both parasitaemia and mortality diminished, particularly at a dose of 40 mg/kg/day. Quality by design was a suitable approach to formulate a co-solvent system of benznidazole. The in vivo studies confirmed the suitability of the optimised such solutions to diminish both parasitaemia and mortality. Thus, this novel alternative should be taken into account for further clinical evaluation in all age ranges. © 2017 John Wiley & Sons Ltd.

Airfoil Shape Optimization based on Surrogate Model

NASA Astrophysics Data System (ADS)

Mukesh, R.; Lingadurai, K.; Selvakumar, U.

2018-02-01

Engineering design problems always require enormous amount of real-time experiments and computational simulations in order to assess and ensure the design objectives of the problems subject to various constraints. In most of the cases, the computational resources and time required per simulation are large. In certain cases like sensitivity analysis, design optimisation etc where thousands and millions of simulations have to be carried out, it leads to have a life time of difficulty for designers. Nowadays approximation models, otherwise called as surrogate models (SM), are more widely employed in order to reduce the requirement of computational resources and time in analysing various engineering systems. Various approaches such as Kriging, neural networks, polynomials, Gaussian processes etc are used to construct the approximation models. The primary intention of this work is to employ the k-fold cross validation approach to study and evaluate the influence of various theoretical variogram models on the accuracy of the surrogate model construction. Ordinary Kriging and design of experiments (DOE) approaches are used to construct the SMs by approximating panel and viscous solution algorithms which are primarily used to solve the flow around airfoils and aircraft wings. The method of coupling the SMs with a suitable optimisation scheme to carryout an aerodynamic design optimisation process for airfoil shapes is also discussed.

Performance assessment and optimisation of a large information system by combined customer relationship management and resilience engineering: a mathematical programming approach

NASA Astrophysics Data System (ADS)

Azadeh, A.; Foroozan, H.; Ashjari, B.; Motevali Haghighi, S.; Yazdanparast, R.; Saberi, M.; Torki Nejad, M.

2017-10-01

ISs and ITs play a critical role in large complex gas corporations. Many factors such as human, organisational and environmental factors affect IS in an organisation. Therefore, investigating ISs success is considered to be a complex problem. Also, because of the competitive business environment and the high amount of information flow in organisations, new issues like resilient ISs and successful customer relationship management (CRM) have emerged. A resilient IS will provide sustainable delivery of information to internal and external customers. This paper presents an integrated approach to enhance and optimise the performance of each component of a large IS based on CRM and resilience engineering (RE) in a gas company. The enhancement of the performance can help ISs to perform business tasks efficiently. The data are collected from standard questionnaires. It is then analysed by data envelopment analysis by selecting the optimal mathematical programming approach. The selected model is validated and verified by principle component analysis method. Finally, CRM and RE factors are identified as influential factors through sensitivity analysis for this particular case study. To the best of our knowledge, this is the first study for performance assessment and optimisation of large IS by combined RE and CRM.

Optimal bioprocess design through a gene regulatory network - growth kinetic hybrid model: Towards Replacing Monod kinetics.

PubMed

Tsipa, Argyro; Koutinas, Michalis; Usaku, Chonlatep; Mantalaris, Athanasios

2018-05-02

Currently, design and optimisation of biotechnological bioprocesses is performed either through exhaustive experimentation and/or with the use of empirical, unstructured growth kinetics models. Whereas, elaborate systems biology approaches have been recently explored, mixed-substrate utilisation is predominantly ignored despite its significance in enhancing bioprocess performance. Herein, bioprocess optimisation for an industrially-relevant bioremediation process involving a mixture of highly toxic substrates, m-xylene and toluene, was achieved through application of a novel experimental-modelling gene regulatory network - growth kinetic (GRN-GK) hybrid framework. The GRN model described the TOL and ortho-cleavage pathways in Pseudomonas putida mt-2 and captured the transcriptional kinetics expression patterns of the promoters. The GRN model informed the formulation of the growth kinetics model replacing the empirical and unstructured Monod kinetics. The GRN-GK framework's predictive capability and potential as a systematic optimal bioprocess design tool, was demonstrated by effectively predicting bioprocess performance, which was in agreement with experimental values, when compared to four commonly used models that deviated significantly from the experimental values. Significantly, a fed-batch biodegradation process was designed and optimised through the model-based control of TOL Pr promoter expression resulting in 61% and 60% enhanced pollutant removal and biomass formation, respectively, compared to the batch process. This provides strong evidence of model-based bioprocess optimisation at the gene level, rendering the GRN-GK framework as a novel and applicable approach to optimal bioprocess design. Finally, model analysis using global sensitivity analysis (GSA) suggests an alternative, systematic approach for model-driven strain modification for synthetic biology and metabolic engineering applications. Copyright © 2018. Published by Elsevier Inc.

From staff-mix to skill-mix and beyond: towards a systemic approach to health workforce management

PubMed Central

2009-01-01

Throughout the world, countries are experiencing shortages of health care workers. Policy-makers and system managers have developed a range of methods and initiatives to optimise the available workforce and achieve the right number and mix of personnel needed to provide high-quality care. Our literature review found that such initiatives often focus more on staff types than on staff members' skills and the effective use of those skills. Our review describes evidence about the benefits and pitfalls of current approaches to human resources optimisation in health care. We conclude that in order to use human resources most effectively, health care organisations must consider a more systemic approach - one that accounts for factors beyond narrowly defined human resources management practices and includes organisational and institutional conditions. PMID:20021682

On some properties of bone functional adaptation phenomenon useful in mechanical design.

PubMed

Nowak, Michał

2010-01-01

The paper discusses some unique properties of trabecular bone functional adaptation phenomenon, useful in mechanical design. On the basis of the biological process observations and the principle of constant strain energy density on the surface of the structure, the generic structural optimisation system has been developed. Such approach allows fulfilling mechanical theorem for the stiffest design, comprising the optimisations of size, shape and topology, using the concepts known from biomechanical studies. Also the biomimetic solution of multiple load problems is presented.

Optimal integrated management of groundwater resources and irrigated agriculture in arid coastal regions

NASA Astrophysics Data System (ADS)

Grundmann, J.; Schütze, N.; Heck, V.

2014-09-01

Groundwater systems in arid coastal regions are particularly at risk due to limited potential for groundwater replenishment and increasing water demand, caused by a continuously growing population. For ensuring a sustainable management of those regions, we developed a new simulation-based integrated water management system. The management system unites process modelling with artificial intelligence tools and evolutionary optimisation techniques for managing both water quality and water quantity of a strongly coupled groundwater-agriculture system. Due to the large number of decision variables, a decomposition approach is applied to separate the original large optimisation problem into smaller, independent optimisation problems which finally allow for faster and more reliable solutions. It consists of an analytical inner optimisation loop to achieve a most profitable agricultural production for a given amount of water and an outer simulation-based optimisation loop to find the optimal groundwater abstraction pattern. Thereby, the behaviour of farms is described by crop-water-production functions and the aquifer response, including the seawater interface, is simulated by an artificial neural network. The methodology is applied exemplarily for the south Batinah re-gion/Oman, which is affected by saltwater intrusion into a coastal aquifer system due to excessive groundwater withdrawal for irrigated agriculture. Due to contradicting objectives like profit-oriented agriculture vs aquifer sustainability, a multi-objective optimisation is performed which can provide sustainable solutions for water and agricultural management over long-term periods at farm and regional scales in respect of water resources, environment, and socio-economic development.

Efficient computational nonlinear dynamic analysis using modal modification response technique

NASA Astrophysics Data System (ADS)

Marinone, Timothy; Avitabile, Peter; Foley, Jason; Wolfson, Janet

2012-08-01

Generally, structural systems contain nonlinear characteristics in many cases. These nonlinear systems require significant computational resources for solution of the equations of motion. Much of the model, however, is linear where the nonlinearity results from discrete local elements connecting different components together. Using a component mode synthesis approach, a nonlinear model can be developed by interconnecting these linear components with highly nonlinear connection elements. The approach presented in this paper, the Modal Modification Response Technique (MMRT), is a very efficient technique that has been created to address this specific class of nonlinear problem. By utilizing a Structural Dynamics Modification (SDM) approach in conjunction with mode superposition, a significantly smaller set of matrices are required for use in the direct integration of the equations of motion. The approach will be compared to traditional analytical approaches to make evident the usefulness of the technique for a variety of test cases.

An alternative approach to characterize nonlinear site effects

USGS Publications Warehouse

Zhang, R.R.; Hartzell, S.; Liang, J.; Hu, Y.

2005-01-01

This paper examines the rationale of a method of nonstationary processing and analysis, referred to as the Hilbert-Huang transform (HHT), for its application to a recording-based approach in quantifying influences of soil nonlinearity in site response. In particular, this paper first summarizes symptoms of soil nonlinearity shown in earthquake recordings, reviews the Fourier-based approach to characterizing nonlinearity, and offers justifications for the HHT in addressing nonlinearity issues. This study then uses the HHT method to analyze synthetic data and recordings from the 1964 Niigata and 2001 Nisqually earthquakes. In doing so, the HHT-based site response is defined as the ratio of marginal Hilbert amplitude spectra, alternative to the Fourier-based response that is the ratio of Fourier amplitude spectra. With the Fourier-based approach in studies of site response as a reference, this study shows that the alternative HHT-based approach is effective in characterizing soil nonlinearity and nonlinear site response.

Evaluation and optimisation of current milrinone prescribing for the treatment and prevention of low cardiac output syndrome in paediatric patients after open heart surgery using a physiology-based pharmacokinetic drug-disease model.

PubMed

Vogt, Winnie

2014-01-01

Milrinone is the drug of choice for the treatment and prevention of low cardiac output syndrome (LCOS) in paediatric patients after open heart surgery across Europe. Discrepancies, however, among prescribing guidance, clinical studies and practice pattern require clarification to ensure safe and effective prescribing. However, the clearance prediction equations derived from classical pharmacokinetic modelling provide limited support as they have recently failed a clinical practice evaluation. Therefore, the objective of this study was to evaluate current milrinone dosing using physiology-based pharmacokinetic (PBPK) modelling and simulation to complement the existing pharmacokinetic knowledge and propose optimised dosing regimens as a basis for improving the standard of care for paediatric patients. A PBPK drug-disease model using a population approach was developed in three steps from healthy young adults to adult patients and paediatric patients with and without LCOS after open heart surgery. Pre- and postoperative organ function values from adult and paediatric patients were collected from literature and integrated into a disease model as factorial changes from the reference values in healthy adults aged 20-40 years. The disease model was combined with the PBPK drug model and evaluated against existing pharmacokinetic data. Model robustness was assessed by parametric sensitivity analysis. In the next step, virtual patient populations were created, each with 1,000 subjects reflecting the average adult and paediatric patient characteristics with regard to age, sex, bodyweight and height. They were integrated into the PBPK drug-disease model to evaluate the effectiveness of current milrinone dosing in achieving the therapeutic target range of 100-300 ng/mL milrinone in plasma. Optimised dosing regimens were subsequently developed. The pharmacokinetics of milrinone in healthy young adults as well as adult and paediatric patients were accurately described with an average fold error of 1.1 ± 0.1 (mean ± standard deviation) and mean relative deviation of 1.5 ± 0.3 as measures of bias and precision, respectively. Normalised maximum sensitivity coefficients for model input parameters ranged from -0.84 to 0.71, which indicated model robustness. The evaluation of milrinone dosing across different paediatric age groups showed a non-linear age dependence of total plasma clearance and exposure differences of a factor 1.4 between patients with and without LCOS for a fixed dosing regimen. None of the currently used dosing regimens for milrinone achieved the therapeutic target range across all paediatric age groups and adult patients, so optimised dosing regimens were developed that considered the age-dependent and pathophysiological differences. The PBPK drug-disease model for milrinone in paediatric patients with and without LCOS after open heart surgery highlights that age, disease and surgery differently impact the pharmacokinetics of milrinone, and that current milrinone dosing for LCOS is suboptimal to maintain the therapeutic target range across the entire paediatric age range. Thus, optimised dosing strategies are proposed to ensure safe and effective prescribing.

[The motivational interview in the educational approach].

PubMed

Soudan, Corinne

2014-12-01

The motivational interview helps nurses trained in this technique to optimise the motivational approach with the patient. This communication tool also gives them greater understanding of the resistance of people confronted with a chronic disease and to support them more effectively towards change.

The 5C Concept and 5S Principles in Inflammatory Bowel Disease Management

PubMed Central

Hibi, Toshifumi; Panaccione, Remo; Katafuchi, Miiko; Yokoyama, Kaoru; Watanabe, Kenji; Matsui, Toshiyuki; Matsumoto, Takayuki; Travis, Simon; Suzuki, Yasuo

2017-01-01

Abstract Background and Aims The international Inflammatory Bowel Disease [IBD] Expert Alliance initiative [2012–2015] served as a platform to define and support areas of best practice in IBD management to help improve outcomes for all patients with IBD. Methods During the programme, IBD specialists from around the world established by consensus two best practice charters: the 5S Principles and the 5C Concept. Results The 5S Principles were conceived to provide health care providers with key guidance for improving clinical practice based on best management approaches. They comprise the following categories: Stage the disease; Stratify patients; Set treatment goals; Select appropriate treatment; and Supervise therapy. Optimised management of patients with IBD based on the 5S Principles can be achieved most effectively within an optimised clinical care environment. Guidance on optimising the clinical care setting in IBD management is provided through the 5C Concept, which encompasses: Comprehensive IBD care; Collaboration; Communication; Clinical nurse specialists; and Care pathways. Together, the 5C Concept and 5S Principles provide structured recommendations on organising the clinical care setting and developing best-practice approaches in IBD management. Conclusions Consideration and application of these two dimensions could help health care providers optimise their IBD centres and collaborate more effectively with their multidisciplinary team colleagues and patients, to provide improved IBD care in daily clinical practice. Ultimately, this could lead to improved outcomes for patients with IBD. PMID:28981622

Exploiting Genomic Knowledge in Optimising Molecular Breeding Programmes: Algorithms from Evolutionary Computing

PubMed Central

O'Hagan, Steve; Knowles, Joshua; Kell, Douglas B.

2012-01-01

Comparatively few studies have addressed directly the question of quantifying the benefits to be had from using molecular genetic markers in experimental breeding programmes (e.g. for improved crops and livestock), nor the question of which organisms should be mated with each other to best effect. We argue that this requires in silico modelling, an approach for which there is a large literature in the field of evolutionary computation (EC), but which has not really been applied in this way to experimental breeding programmes. EC seeks to optimise measurable outcomes (phenotypic fitnesses) by optimising in silico the mutation, recombination and selection regimes that are used. We review some of the approaches from EC, and compare experimentally, using a biologically relevant in silico landscape, some algorithms that have knowledge of where they are in the (genotypic) search space (G-algorithms) with some (albeit well-tuned ones) that do not (F-algorithms). For the present kinds of landscapes, F- and G-algorithms were broadly comparable in quality and effectiveness, although we recognise that the G-algorithms were not equipped with any ‘prior knowledge’ of epistatic pathway interactions. This use of algorithms based on machine learning has important implications for the optimisation of experimental breeding programmes in the post-genomic era when we shall potentially have access to the full genome sequence of every organism in a breeding population. The non-proprietary code that we have used is made freely available (via Supplementary information). PMID:23185279

Retrieval of all effective susceptibilities in nonlinear metamaterials

NASA Astrophysics Data System (ADS)

Larouche, Stéphane; Radisic, Vesna

2018-04-01

Electromagnetic metamaterials offer a great avenue to engineer and amplify the nonlinear response of materials. Their electric, magnetic, and magnetoelectric linear and nonlinear response are related to their structure, providing unprecedented liberty to control those properties. Both the linear and the nonlinear properties of metamaterials are typically anisotropic. While the methods to retrieve the effective linear properties are well established, existing nonlinear retrieval methods have serious limitations. In this work, we generalize a nonlinear transfer matrix approach to account for all nonlinear susceptibility terms and show how to use this approach to retrieve all effective nonlinear susceptibilities of metamaterial elements. The approach is demonstrated using sum frequency generation, but can be applied to other second-order or higher-order processes.

Discontinuous permeable adsorptive barrier design and cost analysis: a methodological approach to optimisation.

PubMed

Santonastaso, Giovanni Francesco; Bortone, Immacolata; Chianese, Simeone; Di Nardo, Armando; Di Natale, Michele; Erto, Alessandro; Karatza, Despina; Musmarra, Dino

2017-09-19

The following paper presents a method to optimise a discontinuous permeable adsorptive barrier (PAB-D). This method is based on the comparison of different PAB-D configurations obtained by changing some of the main PAB-D design parameters. In particular, the well diameters, the distance between two consecutive passive wells and the distance between two consecutive well lines were varied, and a cost analysis for each configuration was carried out in order to define the best performing and most cost-effective PAB-D configuration. As a case study, a benzene-contaminated aquifer located in an urban area in the north of Naples (Italy) was considered. The PAB-D configuration with a well diameter of 0.8 m resulted the best optimised layout in terms of performance and cost-effectiveness. Moreover, in order to identify the best configuration for the remediation of the aquifer studied, a comparison with a continuous permeable adsorptive barrier (PAB-C) was added. In particular, this showed a 40% reduction of the total remediation costs by using the optimised PAB-D.

Optimization of physical conditions for the production of thermostable T1 lipase in Pichia guilliermondii strain SO using response surface methodology.

PubMed

Abu, Mary Ladidi; Nooh, Hisham Mohd; Oslan, Siti Nurbaya; Salleh, Abu Bakar

2017-11-10

Pichia guilliermondii was found capable of expressing the recombinant thermostable lipase without methanol under the control of methanol dependent alcohol oxidase 1 promoter (AOXp 1). In this study, statistical approaches were employed for the screening and optimisation of physical conditions for T1 lipase production in P. guilliermondii. The screening of six physical conditions by Plackett-Burman Design has identified pH, inoculum size and incubation time as exerting significant effects on lipase production. These three conditions were further optimised using, Box-Behnken Design of Response Surface Methodology, which predicted an optimum medium comprising pH 6, 24 h incubation time and 2% inoculum size. T1 lipase activity of 2.0 U/mL was produced with a biomass of OD 600 23.0. The process of using RSM for optimisation yielded a 3-fold increase of T1 lipase over medium before optimisation. Therefore, this result has proven that T1 lipase can be produced at a higher yield in P. guilliermondii.

Rapid assessment of nonlinear optical propagation effects in dielectrics

PubMed Central

Hoyo, J. del; de la Cruz, A. Ruiz; Grace, E.; Ferrer, A.; Siegel, J.; Pasquazi, A.; Assanto, G.; Solis, J.

2015-01-01

Ultrafast laser processing applications need fast approaches to assess the nonlinear propagation of the laser beam in order to predict the optimal range of processing parameters in a wide variety of cases. We develop here a method based on the simple monitoring of the nonlinear beam shaping against numerical prediction. The numerical code solves the nonlinear Schrödinger equation with nonlinear absorption under simplified conditions by employing a state-of-the art computationally efficient approach. By comparing with experimental results we can rapidly estimate the nonlinear refractive index and nonlinear absorption coefficients of the material. The validity of this approach has been tested in a variety of experiments where nonlinearities play a key role, like spatial soliton shaping or fs-laser waveguide writing. The approach provides excellent results for propagated power densities for which free carrier generation effects can be neglected. Above such a threshold, the peculiarities of the nonlinear propagation of elliptical beams enable acquiring an instantaneous picture of the deposition of energy inside the material realistic enough to estimate the effective nonlinear refractive index and nonlinear absorption coefficients that can be used for predicting the spatial distribution of energy deposition inside the material and controlling the beam in the writing process. PMID:25564243

Rapid assessment of nonlinear optical propagation effects in dielectrics.

PubMed

del Hoyo, J; de la Cruz, A Ruiz; Grace, E; Ferrer, A; Siegel, J; Pasquazi, A; Assanto, G; Solis, J

2015-01-07

Ultrafast laser processing applications need fast approaches to assess the nonlinear propagation of the laser beam in order to predict the optimal range of processing parameters in a wide variety of cases. We develop here a method based on the simple monitoring of the nonlinear beam shaping against numerical prediction. The numerical code solves the nonlinear Schrödinger equation with nonlinear absorption under simplified conditions by employing a state-of-the art computationally efficient approach. By comparing with experimental results we can rapidly estimate the nonlinear refractive index and nonlinear absorption coefficients of the material. The validity of this approach has been tested in a variety of experiments where nonlinearities play a key role, like spatial soliton shaping or fs-laser waveguide writing. The approach provides excellent results for propagated power densities for which free carrier generation effects can be neglected. Above such a threshold, the peculiarities of the nonlinear propagation of elliptical beams enable acquiring an instantaneous picture of the deposition of energy inside the material realistic enough to estimate the effective nonlinear refractive index and nonlinear absorption coefficients that can be used for predicting the spatial distribution of energy deposition inside the material and controlling the beam in the writing process.

Rapid assessment of nonlinear optical propagation effects in dielectrics

NASA Astrophysics Data System (ADS)

Hoyo, J. Del; de La Cruz, A. Ruiz; Grace, E.; Ferrer, A.; Siegel, J.; Pasquazi, A.; Assanto, G.; Solis, J.

2015-01-01

Ultrafast laser processing applications need fast approaches to assess the nonlinear propagation of the laser beam in order to predict the optimal range of processing parameters in a wide variety of cases. We develop here a method based on the simple monitoring of the nonlinear beam shaping against numerical prediction. The numerical code solves the nonlinear Schrödinger equation with nonlinear absorption under simplified conditions by employing a state-of-the art computationally efficient approach. By comparing with experimental results we can rapidly estimate the nonlinear refractive index and nonlinear absorption coefficients of the material. The validity of this approach has been tested in a variety of experiments where nonlinearities play a key role, like spatial soliton shaping or fs-laser waveguide writing. The approach provides excellent results for propagated power densities for which free carrier generation effects can be neglected. Above such a threshold, the peculiarities of the nonlinear propagation of elliptical beams enable acquiring an instantaneous picture of the deposition of energy inside the material realistic enough to estimate the effective nonlinear refractive index and nonlinear absorption coefficients that can be used for predicting the spatial distribution of energy deposition inside the material and controlling the beam in the writing process.

Optimisation of Combined Cycle Gas Turbine Power Plant in Intraday Market: Riga CHP-2 Example

NASA Astrophysics Data System (ADS)

Ivanova, P.; Grebesh, E.; Linkevics, O.

2018-02-01

In the research, the influence of optimised combined cycle gas turbine unit - according to the previously developed EM & OM approach with its use in the intraday market - is evaluated on the generation portfolio. It consists of the two combined cycle gas turbine units. The introduced evaluation algorithm saves the power and heat balance before and after the performance of EM & OM approach by making changes in the generation profile of units. The aim of this algorithm is profit maximisation of the generation portfolio. The evaluation algorithm is implemented in multi-paradigm numerical computing environment MATLab on the example of Riga CHP-2. The results show that the use of EM & OM approach in the intraday market can be profitable or unprofitable. It depends on the initial state of generation units in the intraday market and on the content of the generation portfolio.

Nonlinear model predictive control of a wave energy converter based on differential flatness parameterisation

NASA Astrophysics Data System (ADS)

Li, Guang

2017-01-01

This paper presents a fast constrained optimization approach, which is tailored for nonlinear model predictive control of wave energy converters (WEC). The advantage of this approach relies on its exploitation of the differential flatness of the WEC model. This can reduce the dimension of the resulting nonlinear programming problem (NLP) derived from the continuous constrained optimal control of WEC using pseudospectral method. The alleviation of computational burden using this approach helps to promote an economic implementation of nonlinear model predictive control strategy for WEC control problems. The method is applicable to nonlinear WEC models, nonconvex objective functions and nonlinear constraints, which are commonly encountered in WEC control problems. Numerical simulations demonstrate the efficacy of this approach.

Easy-Going On-Spectrometer Optimisation of Phase Modulated Homonuclear Decoupling Sequences in Solid-State NMR

NASA Astrophysics Data System (ADS)

Grimminck, Dennis L. A. G.; Vasa, Suresh K.; Meerts, W. Leo; Kentgens, P. M.

2011-06-01

A global optimisation scheme for phase modulated proton homonuclear decoupling sequences in solid-state NMR is presented. Phase modulations, parameterised by DUMBO Fourier coefficients, were optimized using a Covariance Matrix Adaptation Evolution Strategies algorithm. Our method, denoted EASY-GOING homonuclear decoupling, starts with featureless spectra and optimises proton-proton decoupling, during either proton or carbon signal detection. On the one hand, our solutions closely resemble (e)DUMBO for moderate sample spinning frequencies and medium radio-frequency (rf) field strengths. On the other hand, the EASY-GOING approach resulted in a superior solution, achieving significantly better resolved proton spectra at very high 680 kHz rf field strength. N. Hansen, and A. Ostermeier. Evol. Comput. 9 (2001) 159-195 B. Elena, G. de Paepe, L. Emsley. Chem. Phys. Lett. 398 (2004) 532-538

Relative Displacement Method for Track-Structure Interaction

PubMed Central

Ramos, Óscar Ramón; Pantaleón, Marcos J.

2014-01-01

The track-structure interaction effects are usually analysed with conventional FEM programs, where it is difficult to implement the complex track-structure connection behaviour, which is nonlinear, elastic-plastic and depends on the vertical load. The authors developed an alternative analysis method, which they call the relative displacement method. It is based on the calculation of deformation states in single DOF element models that satisfy the boundary conditions. For its solution, an iterative optimisation algorithm is used. This method can be implemented in any programming language or analysis software. A comparison with ABAQUS calculations shows a very good result correlation and compliance with the standard's specifications. PMID:24634610

A modeling approach to predict acoustic nonlinear field generated by a transmitter with an aluminum lens.

PubMed

Fan, Tingbo; Liu, Zhenbo; Chen, Tao; Li, Faqi; Zhang, Dong

2011-09-01

In this work, the authors propose a modeling approach to compute the nonlinear acoustic field generated by a flat piston transmitter with an attached aluminum lens. In this approach, the geometrical parameters (radius and focal length) of a virtual source are initially determined by Snell's refraction law and then adjusted based on the Rayleigh integral result in the linear case. Then, this virtual source is used with the nonlinear spheroidal beam equation (SBE) model to predict the nonlinear acoustic field in the focal region. To examine the validity of this approach, the calculated nonlinear result is compared with those from the Westervelt and (Khokhlov-Zabolotskaya-Kuznetsov) KZK equations for a focal intensity of 7 kW/cm(2). Results indicate that this approach could accurately describe the nonlinear acoustic field in the focal region with less computation time. The proposed modeling approach is shown to accurately describe the nonlinear acoustic field in the focal region. Compared with the Westervelt equation, the computation time of this approach is significantly reduced. It might also be applicable for the widely used concave focused transmitter with a large aperture angle.

Design of a prototype flow microreactor for synthetic biology in vitro.

PubMed

Boehm, Christian R; Freemont, Paul S; Ces, Oscar

2013-09-07

As a reference platform for in vitro synthetic biology, we have developed a prototype flow microreactor for enzymatic biosynthesis. We report the design, implementation, and computer-aided optimisation of a three-step model pathway within a microfluidic reactor. A packed bed format was shown to be optimal for enzyme compartmentalisation after experimental evaluation of several approaches. The specific substrate conversion efficiency could significantly be improved by an optimised parameter set obtained by computational modelling. Our microreactor design provides a platform to explore new in vitro synthetic biology solutions for industrial biosynthesis.

Targeted flock/herd and individual ruminant treatment approaches.

PubMed

Kenyon, F; Jackson, F

2012-05-04

In Europe, most nematodoses are subclinical involving morbid rather than mortal effects and control is largely achieved using anthelmintics. In cattle, the genera most associated with sub-optimal performance are Ostertagia and Cooperia whereas in sheep and goats, subclinical losses are most often caused by Teladorsagia and Trichostrongylus. In some regions, at certain times, other species such as Nematodirus and Haemonchus also cause disease in sheep and goats. Unfortunately, anthelmintic resistance has now become an issue for European small ruminant producers. One of the key aims of the EU-funded PARASOL project was to identify low input and sustainable approaches to control nematode parasites in ruminants using refugia-based strategies. Two approaches to optimise anthelmintic treatments in sheep and cattle were studied; targeted treatments (TT) - whole-group treatments optimised on the basis of a marker of infection e.g. faecal egg count (FEC), and targeted selected treatment (TST) - treatments given to identified individuals to provide epidemiological and/or production benefits. A number of indicators for TT and TST were assessed to define parasitological and production-system specific indicators for treatment that best suited the regions where the PARASOL studies were conducted. These included liveweight gain, production efficiency, FEC, body condition score and diarrhoea score in small ruminants, and pepsinogen levels and Ostertagia bulk milk tank ELISA in cattle. The PARASOL studies confirmed the value of monitoring FEC as a means of targeting whole-flock treatments in small ruminants. In cattle, bulk milk tank ELISA and serum pepsinogen assays could be used retrospectively to determine the levels of exposure and hence, in the next season to optimise anthelmintic usage. TST approaches in sheep and goats examined production efficiency and liveweight gain as indicators for treatment and confirmed the value of this approach in maintaining performance and anthelmintic susceptibility in the predominant gastrointestinal nematodes. There is good evidence that the TST approach selected less heavily for the development of resistance in comparison to routine monthly treatments. Further research is required to optimise markers for TT and TST but it is also crucial to encourage producers/advisors to adapt these refugia-based strategies to maintain drug susceptible parasites in order to provide sustainable control. Copyright © 2011 Elsevier B.V. All rights reserved.

Cost-aware request routing in multi-geography cloud data centres using software-defined networking

NASA Astrophysics Data System (ADS)

Yuan, Haitao; Bi, Jing; Li, Bo Hu; Tan, Wei

2017-03-01

Current geographically distributed cloud data centres (CDCs) require gigantic energy and bandwidth costs to provide multiple cloud applications to users around the world. Previous studies only focus on energy cost minimisation in distributed CDCs. However, a CDC provider needs to deliver gigantic data between users and distributed CDCs through internet service providers (ISPs). Geographical diversity of bandwidth and energy costs brings a highly challenging problem of how to minimise the total cost of a CDC provider. With the recently emerging software-defined networking, we study the total cost minimisation problem for a CDC provider by exploiting geographical diversity of energy and bandwidth costs. We formulate the total cost minimisation problem as a mixed integer non-linear programming (MINLP). Then, we develop heuristic algorithms to solve the problem and to provide a cost-aware request routing for joint optimisation of the selection of ISPs and the number of servers in distributed CDCs. Besides, to tackle the dynamic workload in distributed CDCs, this article proposes a regression-based workload prediction method to obtain future incoming workload. Finally, this work evaluates the cost-aware request routing by trace-driven simulation and compares it with the existing approaches to demonstrate its effectiveness.

A framework for directional and higher-order reconstruction in photoacoustic tomography

NASA Astrophysics Data System (ADS)

Boink, Yoeri E.; Lagerwerf, Marinus J.; Steenbergen, Wiendelt; van Gils, Stephan A.; Manohar, Srirang; Brune, Christoph

2018-02-01

Photoacoustic tomography is a hybrid imaging technique that combines high optical tissue contrast with high ultrasound resolution. Direct reconstruction methods such as filtered back-projection, time reversal and least squares suffer from curved line artefacts and blurring, especially in the case of limited angles or strong noise. In recent years, there has been great interest in regularised iterative methods. These methods employ prior knowledge of the image to provide higher quality reconstructions. However, easy comparisons between regularisers and their properties are limited, since many tomography implementations heavily rely on the specific regulariser chosen. To overcome this bottleneck, we present a modular reconstruction framework for photoacoustic tomography, which enables easy comparisons between regularisers with different properties, e.g. nonlinear, higher-order or directional. We solve the underlying minimisation problem with an efficient first-order primal-dual algorithm. Convergence rates are optimised by choosing an operator-dependent preconditioning strategy. A variety of reconstruction methods are tested on challenging 2D synthetic and experimental data sets. They outperform direct reconstruction approaches for strong noise levels and limited angle measurements, offering immediate benefits in terms of acquisition time and quality. This work provides a basic platform for the investigation of future advanced regularisation methods in photoacoustic tomography.

Markovian queue optimisation analysis with an unreliable server subject to working breakdowns and impatient customers

NASA Astrophysics Data System (ADS)

Liou, Cheng-Dar

2015-09-01

This study investigates an infinite capacity Markovian queue with a single unreliable service station, in which the customers may balk (do not enter) and renege (leave the queue after entering). The unreliable service station can be working breakdowns even if no customers are in the system. The matrix-analytic method is used to compute the steady-state probabilities for the number of customers, rate matrix and stability condition in the system. The single-objective model for cost and bi-objective model for cost and expected waiting time are derived in the system to fit in with practical applications. The particle swarm optimisation algorithm is implemented to find the optimal combinations of parameters in the pursuit of minimum cost. Two different approaches are used to identify the Pareto optimal set and compared: the epsilon-constraint method and non-dominate sorting genetic algorithm. Compared results allow using the traditional optimisation approach epsilon-constraint method, which is computationally faster and permits a direct sensitivity analysis of the solution under constraint or parameter perturbation. The Pareto front and non-dominated solutions set are obtained and illustrated. The decision makers can use these to improve their decision-making quality.

Using Machine-Learning and Visualisation to Facilitate Learner Interpretation of Source Material

ERIC Educational Resources Information Center

Wolff, Annika; Mulholland, Paul; Zdrahal, Zdenek

2014-01-01

This paper describes an approach for supporting inquiry learning from source materials, realised and tested through a tool-kit. The approach is optimised for tasks that require a student to make interpretations across sets of resources, where opinions and justifications may be hard to articulate. We adopt a dialogue-based approach to learning…

An integrated modelling and multicriteria analysis approach to managing nitrate diffuse pollution: 2. A case study for a chalk catchment in England.

PubMed

Koo, B K; O'Connell, P E

2006-04-01

The site-specific land use optimisation methodology, suggested by the authors in the first part of this two-part paper, has been applied to the River Kennet catchment at Marlborough, Wiltshire, UK, for a case study. The Marlborough catchment (143 km(2)) is an agriculture-dominated rural area over a deep chalk aquifer that is vulnerable to nitrate pollution from agricultural diffuse sources. For evaluation purposes, the catchment was discretised into a network of 1 kmx1 km grid cells. For each of the arable-land grid cells, seven land use alternatives (four arable-land alternatives and three grassland alternatives) were evaluated for their environmental and economic potential. For environmental evaluation, nitrate leaching rates of land use alternatives were estimated using SHETRAN simulations and groundwater pollution potential was evaluated using the DRASTIC index. For economic evaluation, economic gross margins were estimated using a simple agronomic model based on nitrogen response functions and agricultural land classification grades. In order to see whether the site-specific optimisation is efficient at the catchment scale, land use optimisation was carried out for four optimisation schemes (i.e. using four sets of criterion weights). Consequently, four land use scenarios were generated and the site-specifically optimised land use scenario was evaluated as the best compromise solution between long term nitrate pollution and agronomy at the catchment scale.

Dynamic least-cost optimisation of wastewater system remedial works requirements.

PubMed

Vojinovic, Z; Solomatine, D; Price, R K

2006-01-01

In recent years, there has been increasing concern for wastewater system failure and identification of optimal set of remedial works requirements. So far, several methodologies have been developed and applied in asset management activities by various water companies worldwide, but often with limited success. In order to fill the gap, there are several research projects that have been undertaken in exploring various algorithms to optimise remedial works requirements, but mostly for drinking water supply systems, and very limited work has been carried out for the wastewater assets. Some of the major deficiencies of commonly used methods can be found in either one or more of the following aspects: inadequate representation of systems complexity, incorporation of a dynamic model into the decision-making loop, the choice of an appropriate optimisation technique and experience in applying that technique. This paper is oriented towards resolving these issues and discusses a new approach for the optimisation of wastewater systems remedial works requirements. It is proposed that the optimal problem search is performed by a global optimisation tool (with various random search algorithms) and the system performance is simulated by the hydrodynamic pipe network model. The work on assembling all required elements and the development of an appropriate interface protocols between the two tools, aimed to decode the potential remedial solutions into the pipe network model and to calculate the corresponding scenario costs, is currently underway.

Improving linear transport infrastructure efficiency by automated learning and optimised predictive maintenance techniques (INFRALERT)

NASA Astrophysics Data System (ADS)

Jiménez-Redondo, Noemi; Calle-Cordón, Alvaro; Kandler, Ute; Simroth, Axel; Morales, Francisco J.; Reyes, Antonio; Odelius, Johan; Thaduri, Aditya; Morgado, Joao; Duarte, Emmanuele

2017-09-01

The on-going H2020 project INFRALERT aims to increase rail and road infrastructure capacity in the current framework of increased transportation demand by developing and deploying solutions to optimise maintenance interventions planning. It includes two real pilots for road and railways infrastructure. INFRALERT develops an ICT platform (the expert-based Infrastructure Management System, eIMS) which follows a modular approach including several expert-based toolkits. This paper presents the methodologies and preliminary results of the toolkits for i) nowcasting and forecasting of asset condition, ii) alert generation, iii) RAMS & LCC analysis and iv) decision support. The results of these toolkits in a meshed road network in Portugal under the jurisdiction of Infraestruturas de Portugal (IP) are presented showing the capabilities of the approaches.

Scientific Approach for Optimising Performance, Health and Safety in High-Altitude Observatories

NASA Astrophysics Data System (ADS)

Böcker, Michael; Vogy, Joachim; Nolle-Gösser, Tanja

2008-09-01

The ESO coordinated study “Optimising Performance, Health and Safety in High-Altitude Observatories” is based on a psychological approach using a questionnaire for data collection and assessment of high-altitude effects. During 2007 and 2008, data from 28 staff and visitors involved in APEX and ALMA were collected and analysed and the first results of the study are summarised. While there is a lot of information about biomedical changes at high altitude, relatively few studies have focussed on psychological changes, for example with respect to performance of mental tasks, safety consciousness and emotions. Both, biomedical and psychological changes are relevant factors in occupational safety and health. The results of the questionnaire on safety, health and performance issues demonstrate that the working conditions at high altitude are less detrimental than expected.

CMOS analogue amplifier circuits optimisation using hybrid backtracking search algorithm with differential evolution

NASA Astrophysics Data System (ADS)

Mallick, S.; Kar, R.; Mandal, D.; Ghoshal, S. P.

2016-07-01

This paper proposes a novel hybrid optimisation algorithm which combines the recently proposed evolutionary algorithm Backtracking Search Algorithm (BSA) with another widely accepted evolutionary algorithm, namely, Differential Evolution (DE). The proposed algorithm called BSA-DE is employed for the optimal designs of two commonly used analogue circuits, namely Complementary Metal Oxide Semiconductor (CMOS) differential amplifier circuit with current mirror load and CMOS two-stage operational amplifier (op-amp) circuit. BSA has a simple structure that is effective, fast and capable of solving multimodal problems. DE is a stochastic, population-based heuristic approach, having the capability to solve global optimisation problems. In this paper, the transistors' sizes are optimised using the proposed BSA-DE to minimise the areas occupied by the circuits and to improve the performances of the circuits. The simulation results justify the superiority of BSA-DE in global convergence properties and fine tuning ability, and prove it to be a promising candidate for the optimal design of the analogue CMOS amplifier circuits. The simulation results obtained for both the amplifier circuits prove the effectiveness of the proposed BSA-DE-based approach over DE, harmony search (HS), artificial bee colony (ABC) and PSO in terms of convergence speed, design specifications and design parameters of the optimal design of the analogue CMOS amplifier circuits. It is shown that BSA-DE-based design technique for each amplifier circuit yields the least MOS transistor area, and each designed circuit is shown to have the best performance parameters such as gain, power dissipation, etc., as compared with those of other recently reported literature.

The 5C Concept and 5S Principles in Inflammatory Bowel Disease Management.

PubMed

Hibi, Toshifumi; Panaccione, Remo; Katafuchi, Miiko; Yokoyama, Kaoru; Watanabe, Kenji; Matsui, Toshiyuki; Matsumoto, Takayuki; Travis, Simon; Suzuki, Yasuo

2017-10-27

The international Inflammatory Bowel Disease [IBD] Expert Alliance initiative [2012-2015] served as a platform to define and support areas of best practice in IBD management to help improve outcomes for all patients with IBD. During the programme, IBD specialists from around the world established by consensus two best practice charters: the 5S Principles and the 5C Concept. The 5S Principles were conceived to provide health care providers with key guidance for improving clinical practice based on best management approaches. They comprise the following categories: Stage the disease; Stratify patients; Set treatment goals; Select appropriate treatment; and Supervise therapy. Optimised management of patients with IBD based on the 5S Principles can be achieved most effectively within an optimised clinical care environment. Guidance on optimising the clinical care setting in IBD management is provided through the 5C Concept, which encompasses: Comprehensive IBD care; Collaboration; Communication; Clinical nurse specialists; and Care pathways. Together, the 5C Concept and 5S Principles provide structured recommendations on organising the clinical care setting and developing best-practice approaches in IBD management. Consideration and application of these two dimensions could help health care providers optimise their IBD centres and collaborate more effectively with their multidisciplinary team colleagues and patients, to provide improved IBD care in daily clinical practice. Ultimately, this could lead to improved outcomes for patients with IBD. Copyright © 2017 European Crohn’s and Colitis Organisation (ECCO). Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com

Energy and wear optimisation of train longitudinal dynamics and of traction and braking systems

NASA Astrophysics Data System (ADS)

Conti, R.; Galardi, E.; Meli, E.; Nocciolini, D.; Pugi, L.; Rindi, A.

2015-05-01

Traction and braking systems deeply affect longitudinal train dynamics, especially when an extensive blending phase among different pneumatic, electric and magnetic devices is required. The energy and wear optimisation of longitudinal vehicle dynamics has a crucial economic impact and involves several engineering problems such as wear of braking friction components, energy efficiency, thermal load on components, level of safety under degraded or adhesion conditions (often constrained by the current regulation in force on signalling or other safety-related subsystem). In fact, the application of energy storage systems can lead to an efficiency improvement of at least 10% while, as regards the wear reduction, the improvement due to distributed traction systems and to optimised traction devices can be quantified in about 50%. In this work, an innovative integrated procedure is proposed by the authors to optimise longitudinal train dynamics and traction and braking manoeuvres in terms of both energy and wear. The new approach has been applied to existing test cases and validated with experimental data provided by Breda and, for some components and their homologation process, the results of experimental activities derive from cooperation performed with relevant industrial partners such as Trenitalia and Italcertifer. In particular, simulation results are referred to the simulation tests performed on a high-speed train (Ansaldo Breda Emu V250) and on a tram (Ansaldo Breda Sirio Tram). The proposed approach is based on a modular simulation platform in which the sub-models corresponding to different subsystems can be easily customised, depending on the considered application, on the availability of technical data and on the homologation process of different components.

An experimental study of nonlinear dynamic system identification

NASA Technical Reports Server (NTRS)

Stry, Greselda I.; Mook, D. Joseph

1990-01-01

A technique for robust identification of nonlinear dynamic systems is developed and illustrated using both simulations and analog experiments. The technique is based on the Minimum Model Error optimal estimation approach. A detailed literature review is included in which fundamental differences between the current approach and previous work is described. The most significant feature of the current work is the ability to identify nonlinear dynamic systems without prior assumptions regarding the form of the nonlinearities, in constrast to existing nonlinear identification approaches which usually require detailed assumptions of the nonlinearities. The example illustrations indicate that the method is robust with respect to prior ignorance of the model, and with respect to measurement noise, measurement frequency, and measurement record length.

A fuzzy controller with nonlinear control rules is the sum of a global nonlinear controller and a local nonlinear PI-like controller

NASA Technical Reports Server (NTRS)

Ying, Hao

1993-01-01

The fuzzy controllers studied in this paper are the ones that employ N trapezoidal-shaped members for input fuzzy sets, Zadeh fuzzy logic and a centroid defuzzification algorithm for output fuzzy set. The author analytically proves that the structure of the fuzzy controllers is the sum of a global nonlinear controller and a local nonlinear proportional-integral-like controller. If N approaches infinity, the global controller becomes a nonlinear controller while the local controller disappears. If linear control rules are used, the global controller becomes a global two-dimensional multilevel relay which approaches a global linear proportional-integral (PI) controller as N approaches infinity.

Photonic simulation of entanglement growth and engineering after a spin chain quench.

PubMed

Pitsios, Ioannis; Banchi, Leonardo; Rab, Adil S; Bentivegna, Marco; Caprara, Debora; Crespi, Andrea; Spagnolo, Nicolò; Bose, Sougato; Mataloni, Paolo; Osellame, Roberto; Sciarrino, Fabio

2017-11-17

The time evolution of quantum many-body systems is one of the most important processes for benchmarking quantum simulators. The most curious feature of such dynamics is the growth of quantum entanglement to an amount proportional to the system size (volume law) even when interactions are local. This phenomenon has great ramifications for fundamental aspects, while its optimisation clearly has an impact on technology (e.g., for on-chip quantum networking). Here we use an integrated photonic chip with a circuit-based approach to simulate the dynamics of a spin chain and maximise the entanglement generation. The resulting entanglement is certified by constructing a second chip, which measures the entanglement between multiple distant pairs of simulated spins, as well as the block entanglement entropy. This is the first photonic simulation and optimisation of the extensive growth of entanglement in a spin chain, and opens up the use of photonic circuits for optimising quantum devices.

A support vector machine approach for classification of welding defects from ultrasonic signals

NASA Astrophysics Data System (ADS)

Chen, Yuan; Ma, Hong-Wei; Zhang, Guang-Ming

2014-07-01

Defect classification is an important issue in ultrasonic non-destructive evaluation. A layered multi-class support vector machine (LMSVM) classification system, which combines multiple SVM classifiers through a layered architecture, is proposed in this paper. The proposed LMSVM classification system is applied to the classification of welding defects from ultrasonic test signals. The measured ultrasonic defect echo signals are first decomposed into wavelet coefficients by the wavelet packet transform. The energy of the wavelet coefficients at different frequency channels are used to construct the feature vectors. The bees algorithm (BA) is then used for feature selection and SVM parameter optimisation for the LMSVM classification system. The BA-based feature selection optimises the energy feature vectors. The optimised feature vectors are input to the LMSVM classification system for training and testing. Experimental results of classifying welding defects demonstrate that the proposed technique is highly robust, precise and reliable for ultrasonic defect classification.

Pre-operative optimisation of lung function

PubMed Central

Azhar, Naheed

2015-01-01

The anaesthetic management of patients with pre-existing pulmonary disease is a challenging task. It is associated with increased morbidity in the form of post-operative pulmonary complications. Pre-operative optimisation of lung function helps in reducing these complications. Patients are advised to stop smoking for a period of 4–6 weeks. This reduces airway reactivity, improves mucociliary function and decreases carboxy-haemoglobin. The widely used incentive spirometry may be useful only when combined with other respiratory muscle exercises. Volume-based inspiratory devices have the best results. Pharmacotherapy of asthma and chronic obstructive pulmonary disease must be optimised before considering the patient for elective surgery. Beta 2 agonists, inhaled corticosteroids and systemic corticosteroids, are the main drugs used for this and several drugs play an adjunctive role in medical therapy. A graded approach has been suggested to manage these patients for elective surgery with an aim to achieve optimal pulmonary function. PMID:26556913

Nonlinear analysis for high-temperature multilayered fiber composite structures. M.S. Thesis; [turbine blades

NASA Technical Reports Server (NTRS)

Hopkins, D. A.

1984-01-01

A unique upward-integrated top-down-structured approach is presented for nonlinear analysis of high-temperature multilayered fiber composite structures. Based on this approach, a special purpose computer code was developed (nonlinear COBSTRAN) which is specifically tailored for the nonlinear analysis of tungsten-fiber-reinforced superalloy (TFRS) composite turbine blade/vane components of gas turbine engines. Special features of this computational capability include accounting of; micro- and macro-heterogeneity, nonlinear (stess-temperature-time dependent) and anisotropic material behavior, and fiber degradation. A demonstration problem is presented to mainfest the utility of the upward-integrated top-down-structured approach, in general, and to illustrate the present capability represented by the nonlinear COBSTRAN code. Preliminary results indicate that nonlinear COBSTRAN provides the means for relating the local nonlinear and anisotropic material behavior of the composite constituents to the global response of the turbine blade/vane structure.

Nonlinear optics quantum computing with circuit QED.

PubMed

Adhikari, Prabin; Hafezi, Mohammad; Taylor, J M

2013-02-08

One approach to quantum information processing is to use photons as quantum bits and rely on linear optical elements for most operations. However, some optical nonlinearity is necessary to enable universal quantum computing. Here, we suggest a circuit-QED approach to nonlinear optics quantum computing in the microwave regime, including a deterministic two-photon phase gate. Our specific example uses a hybrid quantum system comprising a LC resonator coupled to a superconducting flux qubit to implement a nonlinear coupling. Compared to the self-Kerr nonlinearity, we find that our approach has improved tolerance to noise in the qubit while maintaining fast operation.

Localization and identification of structural nonlinearities using cascaded optimization and neural networks

NASA Astrophysics Data System (ADS)

Koyuncu, A.; Cigeroglu, E.; Özgüven, H. N.

2017-10-01

In this study, a new approach is proposed for identification of structural nonlinearities by employing cascaded optimization and neural networks. Linear finite element model of the system and frequency response functions measured at arbitrary locations of the system are used in this approach. Using the finite element model, a training data set is created, which appropriately spans the possible nonlinear configurations space of the system. A classification neural network trained on these data sets then localizes and determines the types of all nonlinearities associated with the nonlinear degrees of freedom in the system. A new training data set spanning the parametric space associated with the determined nonlinearities is created to facilitate parametric identification. Utilizing this data set, initially, a feed forward regression neural network is trained, which parametrically identifies the classified nonlinearities. Then, the results obtained are further improved by carrying out an optimization which uses network identified values as starting points. Unlike identification methods available in literature, the proposed approach does not require data collection from the degrees of freedoms where nonlinear elements are attached, and furthermore, it is sufficiently accurate even in the presence of measurement noise. The application of the proposed approach is demonstrated on an example system with nonlinear elements and on a real life experimental setup with a local nonlinearity.

Development of an optimised key worker framework for people with dementia, their family and caring unit living in the community.

PubMed

Renehan, Emma; Goeman, Dianne; Koch, Susan

2017-07-20

In Australia, dementia is a national health priority. With the rising number of people living with dementia and shortage of formal and informal carers predicted in the near future, developing approaches to coordinating services in quality-focused ways is considered an urgent priority. Key worker support models are one approach that have been used to assist people living with dementia and their caring unit coordinate services and navigate service systems; however, there is limited literature outlining comprehensive frameworks for the implementation of community dementia key worker roles in practice. In this paper an optimised key worker framework for people with dementia, their family and caring unit living in the community is developed and presented. A number of processes were undertaken to inform the development of a co-designed optimised key worker framework: an expert working and reference group; a systematic review of the literature; and a qualitative evaluation of 14 dementia key worker models operating in Australia involving 14 interviews with organisation managers, 19 with key workers and 15 with people living with dementia and/or their caring unit. Data from the systematic review and evaluation of dementia key worker models were analysed by the researchers and the expert working and reference group using a constant comparative approach to define the essential components of the optimised framework. The developed framework consisted of four main components: overarching philosophies; organisational context; role definition; and key worker competencies. A number of more clearly defined sub-themes sat under each component. Reflected in the framework is the complexity of the dementia journey and the difficulty in trying to develop a 'one size fits all' approach. This co-designed study led to the development of an evidence based framework which outlines a comprehensive synthesis of components viewed as being essential to the implementation of a dementia key worker model of care in the community. The framework was informed and endorsed by people living with dementia and their caring unit, key workers, managers, Australian industry experts, policy makers and researchers. An evaluation of its effectiveness and relevance for practice within the dementia care space is required.

Algorithme intelligent d'optimisation d'un design structurel de grande envergure

NASA Astrophysics Data System (ADS)

Dominique, Stephane

The implementation of an automated decision support system in the field of design and structural optimisation can give a significant advantage to any industry working on mechanical designs. Indeed, by providing solution ideas to a designer or by upgrading existing design solutions while the designer is not at work, the system may reduce the project cycle time, or allow more time to produce a better design. This thesis presents a new approach to automate a design process based on Case-Based Reasoning (CBR), in combination with a new genetic algorithm named Genetic Algorithm with Territorial core Evolution (GATE). This approach was developed in order to reduce the operating cost of the process. However, as the system implementation cost is quite expensive, the approach is better suited for large scale design problem, and particularly for design problems that the designer plans to solve for many different specification sets. First, the CBR process uses a databank filled with every known solution to similar design problems. Then, the closest solutions to the current problem in term of specifications are selected. After this, during the adaptation phase, an artificial neural network (ANN) interpolates amongst known solutions to produce an additional solution to the current problem using the current specifications as inputs. Each solution produced and selected by the CBR is then used to initialize the population of an island of the genetic algorithm. The algorithm will optimise the solution further during the refinement phase. Using progressive refinement, the algorithm starts using only the most important variables for the problem. Then, as the optimisation progress, the remaining variables are gradually introduced, layer by layer. The genetic algorithm that is used is a new algorithm specifically created during this thesis to solve optimisation problems from the field of mechanical device structural design. The algorithm is named GATE, and is essentially a real number genetic algorithm that prevents new individuals to be born too close to previously evaluated solutions. The restricted area becomes smaller or larger during the optimisation to allow global or local search when necessary. Also, a new search operator named Substitution Operator is incorporated in GATE. This operator allows an ANN surrogate model to guide the algorithm toward the most promising areas of the design space. The suggested CBR approach and GATE were tested on several simple test problems, as well as on the industrial problem of designing a gas turbine engine rotor's disc. These results are compared to other results obtained for the same problems by many other popular optimisation algorithms, such as (depending of the problem) gradient algorithms, binary genetic algorithm, real number genetic algorithm, genetic algorithm using multiple parents crossovers, differential evolution genetic algorithm, Hookes & Jeeves generalized pattern search method and POINTER from the software I-SIGHT 3.5. Results show that GATE is quite competitive, giving the best results for 5 of the 6 constrained optimisation problem. GATE also provided the best results of all on problem produced by a Maximum Set Gaussian landscape generator. Finally, GATE provided a disc 4.3% lighter than the best other tested algorithm (POINTER) for the gas turbine engine rotor's disc problem. One drawback of GATE is a lesser efficiency for highly multimodal unconstrained problems, for which he gave quite poor results with respect to its implementation cost. To conclude, according to the preliminary results obtained during this thesis, the suggested CBR process, combined with GATE, seems to be a very good candidate to automate and accelerate the structural design of mechanical devices, potentially reducing significantly the cost of industrial preliminary design processes.

Optimisation of the formulation of a bubble bath by a chemometric approach market segmentation and optimisation.

PubMed

Marengo, Emilio; Robotti, Elisa; Gennaro, Maria Carla; Bertetto, Mariella

2003-03-01

The optimisation of the formulation of a commercial bubble bath was performed by chemometric analysis of Panel Tests results. A first Panel Test was performed to choose the best essence, among four proposed to the consumers; the best essence chosen was used in the revised commercial bubble bath. Afterwards, the effect of changing the amount of four components (the amount of primary surfactant, the essence, the hydratant and the colouring agent) of the bubble bath was studied by a fractional factorial design. The segmentation of the bubble bath market was performed by a second Panel Test, in which the consumers were requested to evaluate the samples coming from the experimental design. The results were then treated by Principal Component Analysis. The market had two segments: people preferring a product with a rich formulation and people preferring a poor product. The final target, i.e. the optimisation of the formulation for each segment, was obtained by the calculation of regression models relating the subjective evaluations given by the Panel and the compositions of the samples. The regression models allowed to identify the best formulations for the two segments ofthe market.

Model fitting for small skin permeability data sets: hyperparameter optimisation in Gaussian Process Regression.

PubMed

Ashrafi, Parivash; Sun, Yi; Davey, Neil; Adams, Roderick G; Wilkinson, Simon C; Moss, Gary Patrick

2018-03-01

The aim of this study was to investigate how to improve predictions from Gaussian Process models by optimising the model hyperparameters. Optimisation methods, including Grid Search, Conjugate Gradient, Random Search, Evolutionary Algorithm and Hyper-prior, were evaluated and applied to previously published data. Data sets were also altered in a structured manner to reduce their size, which retained the range, or 'chemical space' of the key descriptors to assess the effect of the data range on model quality. The Hyper-prior Smoothbox kernel results in the best models for the majority of data sets, and they exhibited significantly better performance than benchmark quantitative structure-permeability relationship (QSPR) models. When the data sets were systematically reduced in size, the different optimisation methods generally retained their statistical quality, whereas benchmark QSPR models performed poorly. The design of the data set, and possibly also the approach to validation of the model, is critical in the development of improved models. The size of the data set, if carefully controlled, was not generally a significant factor for these models and that models of excellent statistical quality could be produced from substantially smaller data sets. © 2018 Royal Pharmaceutical Society.

Optimisation of SIW bandpass filter with wide and sharp stopband using space mapping

NASA Astrophysics Data System (ADS)

Xu, Juan; Bi, Jun Jian; Li, Zhao Long; Chen, Ru shan

2016-12-01

This work presents a substrate integrated waveguide (SIW) bandpass filter with wide and precipitous stopband, which is different from filters with a direct input/output coupling structure. Higher modes in the SIW cavities are used to generate the finite transmission zeros for improved stopband performance. The design of SIW filters requires full wave electromagnetic simulation and extensive optimisation. If a full wave solver is used for optimisation, the design process is very time consuming. The space mapping (SM) approach has been called upon to alleviate this problem. In this case, the coarse model is optimised using an equivalent circuit model-based representation of the structure for fast computations. On the other hand, the verification of the design is completed with an accurate fine model full wave simulation. A fourth-order filter with a passband of 12.0-12.5 GHz is fabricated on a single layer Rogers RT/Duroid 5880 substrate. The return loss is better than 17.4 dB in the passband and the rejection is more than 40 dB in the stopband. The stopband is from 2 to 11 GHz and 13.5 to 17.3 GHz, demonstrating a wide bandwidth performance.

A general procedure to generate models for urban environmental-noise pollution using feature selection and machine learning methods.

PubMed

Torija, Antonio J; Ruiz, Diego P

2015-02-01

The prediction of environmental noise in urban environments requires the solution of a complex and non-linear problem, since there are complex relationships among the multitude of variables involved in the characterization and modelling of environmental noise and environmental-noise magnitudes. Moreover, the inclusion of the great spatial heterogeneity characteristic of urban environments seems to be essential in order to achieve an accurate environmental-noise prediction in cities. This problem is addressed in this paper, where a procedure based on feature-selection techniques and machine-learning regression methods is proposed and applied to this environmental problem. Three machine-learning regression methods, which are considered very robust in solving non-linear problems, are used to estimate the energy-equivalent sound-pressure level descriptor (LAeq). These three methods are: (i) multilayer perceptron (MLP), (ii) sequential minimal optimisation (SMO), and (iii) Gaussian processes for regression (GPR). In addition, because of the high number of input variables involved in environmental-noise modelling and estimation in urban environments, which make LAeq prediction models quite complex and costly in terms of time and resources for application to real situations, three different techniques are used to approach feature selection or data reduction. The feature-selection techniques used are: (i) correlation-based feature-subset selection (CFS), (ii) wrapper for feature-subset selection (WFS), and the data reduction technique is principal-component analysis (PCA). The subsequent analysis leads to a proposal of different schemes, depending on the needs regarding data collection and accuracy. The use of WFS as the feature-selection technique with the implementation of SMO or GPR as regression algorithm provides the best LAeq estimation (R(2)=0.94 and mean absolute error (MAE)=1.14-1.16 dB(A)). Copyright © 2014 Elsevier B.V. All rights reserved.

Nonlinear flap-lag axial equations of a rotating beam

NASA Technical Reports Server (NTRS)

Kaza, K. R. V.; Kvaternik, R. G.

1977-01-01

It is possible to identify essentially four approaches by which analysts have established either the linear or nonlinear governing equations of motion for a particular problem related to the dynamics of rotating elastic bodies. The approaches include the effective applied load artifice in combination with a variational principle and the use of Newton's second law, written as D'Alembert's principle, applied to the deformed configuration. A third approach is a variational method in which nonlinear strain-displacement relations and a first-degree displacement field are used. The method introduced by Vigneron (1975) for deriving the linear flap-lag equations of a rotating beam constitutes the fourth approach. The reported investigation shows that all four approaches make use of the geometric nonlinear theory of elasticity. An alternative method for deriving the nonlinear coupled flap-lag-axial equations of motion is also discussed.

Optimisation of resolution in micellar electrokinetic chromatography by multivariate evaluation of electrolytes.

PubMed

Mikaeli, S; Thorsén, G; Karlberg, B

2001-01-12

A novel approach to multivariate evaluation of separation electrolytes for micellar electrokinetic chromatography is presented. An initial screening of the experimental parameters is performed using a Plackett-Burman design. Significant parameters are further evaluated using full factorial designs. The total resolution of the separation is calculated and used as response. The proposed scheme has been applied to the optimisation of the separation of phenols and the chiral separation of (+)-1-(9-anthryl)-2-propyl chloroformate-derivatized amino acids. A total of eight experimental parameters were evaluated and optimal conditions found in less than 48 experiments.

Environmental aspects of the implementation of geogrids for pavement optimisation

NASA Astrophysics Data System (ADS)

Kawalec, Jacek; Gołos, Michał; Mazurowski, Piotr

2018-05-01

Technological developments in highway construction should not only result in durable, safe and cost-effective solutions for roads and pavements but also, and perhaps above all, lead to solutions that minimise the negative impact of construction on the environment. One of the ways to ensure these requirements are met is to apply technology using geosynthetics. This paper discusses the stabilisation of aggregate with hexagonal geogrids and the benefits - from the point of view of reducing the emission of harmful gases to the atmosphere - which can be realised from this approach, compared with traditional approaches. Solutions for the improvement of weak subgrades and optimisation of the entire pavement structure are discussed, along with the presentation of sample calculations of greenhouse gas emissions, carried out with the use of specialized software related to the construction of the structures in various technologies.

Probabilistic Sizing and Verification of Space Ceramic Structures

NASA Astrophysics Data System (ADS)

Denaux, David; Ballhause, Dirk; Logut, Daniel; Lucarelli, Stefano; Coe, Graham; Laine, Benoit

2012-07-01

Sizing of ceramic parts is best optimised using a probabilistic approach which takes into account the preexisting flaw distribution in the ceramic part to compute a probability of failure of the part depending on the applied load, instead of a maximum allowable load as for a metallic part. This requires extensive knowledge of the material itself but also an accurate control of the manufacturing process. In the end, risk reduction approaches such as proof testing may be used to lower the final probability of failure of the part. Sizing and verification of ceramic space structures have been performed by Astrium for more than 15 years, both with Zerodur and SiC: Silex telescope structure, Seviri primary mirror, Herschel telescope, Formosat-2 instrument, and other ceramic structures flying today. Throughout this period of time, Astrium has investigated and developed experimental ceramic analysis tools based on the Weibull probabilistic approach. In the scope of the ESA/ESTEC study: “Mechanical Design and Verification Methodologies for Ceramic Structures”, which is to be concluded in the beginning of 2012, existing theories, technical state-of-the-art from international experts, and Astrium experience with probabilistic analysis tools have been synthesized into a comprehensive sizing and verification method for ceramics. Both classical deterministic and more optimised probabilistic methods are available, depending on the criticality of the item and on optimisation needs. The methodology, based on proven theory, has been successfully applied to demonstration cases and has shown its practical feasibility.

Global Corporate Priorities and Demand-Led Learning Strategies

ERIC Educational Resources Information Center

Dealtry, Richard

2008-01-01

Purpose: The purpose of this article is to start the process of exploring how to optimise connections between the strategic needs of an organisation as directed by top management and its learning management structures and strategies. Design/methodology/approach: The article takes a broad brush approach to a complex and large subject area that is…

Freeze drying formulation using microscale and design of experiment approaches: a case study using granulocyte colony-stimulating factor.

PubMed

Grant, Yitzchak; Matejtschuk, Paul; Bird, Christopher; Wadhwa, Meenu; Dalby, Paul A

2012-04-01

The lyophilization of proteins in microplates, to assess and optimise formulations rapidly, has been applied for the first time to a therapeutic protein and, in particular, one that requires a cell-based biological assay, in order to demonstrate the broader usefulness of the approach. Factorial design of experiment methods were combined with lyophilization in microplates to identify optimum formulations that stabilised granulocyte colony-stimulating factor during freeze drying. An initial screen rapidly identified key excipients and potential interactions, which was then followed by a central composite face designed optimisation experiment. Human serum albumin and Tween 20 had significant effects on maintaining protein stability. As previously, the optimum formulation was then freeze-dried in stoppered vials to verify that the microscale data is relevant to pilot scales. However, to validate the approach further, the selected formulation was also assessed for solid-state shelf-life through the use of accelerated stability studies. This approach allows for a high-throughput assessment of excipient options early on in product development, while also reducing costs in terms of time and quantity of materials required.

A computer-aided approach to nonlinear control systhesis

NASA Technical Reports Server (NTRS)

Wie, Bong; Anthony, Tobin

1988-01-01

The major objective of this project is to develop a computer-aided approach to nonlinear stability analysis and nonlinear control system design. This goal is to be obtained by refining the describing function method as a synthesis tool for nonlinear control design. The interim report outlines the approach by this study to meet these goals including an introduction to the INteractive Controls Analysis (INCA) program which was instrumental in meeting these study objectives. A single-input describing function (SIDF) design methodology was developed in this study; coupled with the software constructed in this study, the results of this project provide a comprehensive tool for design and integration of nonlinear control systems.

Explicit reference governor for linear systems

NASA Astrophysics Data System (ADS)

Garone, Emanuele; Nicotra, Marco; Ntogramatzidis, Lorenzo

2018-06-01

The explicit reference governor is a constrained control scheme that was originally introduced for generic nonlinear systems. This paper presents two explicit reference governor strategies that are specifically tailored for the constrained control of linear time-invariant systems subject to linear constraints. Both strategies are based on the idea of maintaining the system states within an invariant set which is entirely contained in the constraints. This invariant set can be constructed by exploiting either the Lyapunov inequality or modal decomposition. To improve the performance, we show that the two strategies can be combined by choosing at each time instant the least restrictive set. Numerical simulations illustrate that the proposed scheme achieves performances that are comparable to optimisation-based reference governors.

Optimisation of solar synoptic observations

NASA Astrophysics Data System (ADS)

Klvaña, Miroslav; Sobotka, Michal; Švanda, Michal

2012-09-01

The development of instrumental and computer technologies is connected with steadily increasing needs for archiving of large data volumes. The current trend to meet this requirement includes the data compression and growth of storage capacities. This approach, however, has technical and practical limits. A further reduction of the archived data volume can be achieved by means of an optimisation of the archiving that consists in data selection without losing the useful information. We describe a method of optimised archiving of solar images, based on the selection of images that contain a new information. The new information content is evaluated by means of the analysis of changes detected in the images. We present characteristics of different kinds of image changes and divide them into fictitious changes with a disturbing effect and real changes that provide a new information. In block diagrams describing the selection and archiving, we demonstrate the influence of clouds, the recording of images during an active event on the Sun, including a period before the event onset, and the archiving of long-term history of solar activity. The described optimisation technique is not suitable for helioseismology, because it does not conserve the uniform time step in the archived sequence and removes the information about solar oscillations. In case of long-term synoptic observations, the optimised archiving can save a large amount of storage capacities. The actual capacity saving will depend on the setting of the change-detection sensitivity and on the capability to exclude the fictitious changes.

Optimisation of logistics processes of energy grass collection

NASA Astrophysics Data System (ADS)

Bányai, Tamás.

2010-05-01

The collection of energy grass is a logistics-intensive process [1]. The optimal design and control of transportation and collection subprocesses is a critical point of the supply chain. To avoid irresponsible decisions by right of experience and intuition, the optimisation and analysis of collection processes based on mathematical models and methods is the scientific suggestible way. Within the frame of this work, the author focuses on the optimisation possibilities of the collection processes, especially from the point of view transportation and related warehousing operations. However the developed optimisation methods in the literature [2] take into account the harvesting processes, county-specific yields, transportation distances, erosion constraints, machinery specifications, and other key variables, but the possibility of more collection points and the multi-level collection were not taken into consideration. The possible areas of using energy grass is very wide (energetically use, biogas and bio alcohol production, paper and textile industry, industrial fibre material, foddering purposes, biological soil protection [3], etc.), so not only a single level but also a multi-level collection system with more collection and production facilities has to be taken into consideration. The input parameters of the optimisation problem are the followings: total amount of energy grass to be harvested in each region; specific facility costs of collection, warehousing and production units; specific costs of transportation resources; pre-scheduling of harvesting process; specific transportation and warehousing costs; pre-scheduling of processing of energy grass at each facility (exclusive warehousing). The model take into consideration the following assumptions: (1) cooperative relation among processing and production facilties, (2) capacity constraints are not ignored, (3) the cost function of transportation is non-linear, (4) the drivers conditions are ignored. The objective function of the optimisation is the maximisation of the profit which means the maximization of the difference between revenue and cost. The objective function trades off the income of the assigned transportation demands against the logistic costs. The constraints are the followings: (1) the free capacity of the assigned transportation resource is more than the re-quested capacity of the transportation demand; the calculated arrival time of the transportation resource to the harvesting place is not later than the requested arrival time of them; (3) the calculated arrival time of the transportation demand to the processing and production facility is not later than the requested arrival time; (4) one transportation demand is assigned to one transportation resource and one resource is assigned to one transportation resource. The decision variable of the optimisation problem is the set of scheduling variables and the assignment of resources to transportation demands. The evaluation parameters of the optimised system are the followings: total costs of the collection process; utilisation of transportation resources and warehouses; efficiency of production and/or processing facilities. However the multidimensional heuristic optimisation method is based on genetic algorithm, but the routing sequence of the optimisation works on the base of an ant colony algorithm. The optimal routes are calculated by the aid of the ant colony algorithm as a subroutine of the global optimisation method and the optimal assignment is given by the genetic algorithm. One important part of the mathematical method is the sensibility analysis of the objective function, which shows the influence rate of the different input parameters. Acknowledgements This research was implemented within the frame of the project entitled "Development and operation of the Technology and Knowledge Transfer Centre of the University of Miskolc". with support by the European Union and co-funding of the European Social Fund. References [1] P. R. Daniel: The Economics of Harvesting and Transporting Corn Stover for Conversion to Fuel Ethanol: A Case Study for Minnesota. University of Minnesota, Department of Applied Economics. 2006. http://ideas.repec.org/p/ags/umaesp/14213.html [2] T. G. Douglas, J. Brendan, D. Erin & V.-D. Becca: Energy and Chemicals from Native Grasses: Production, Transportation and Processing Technologies Considered in the Northern Great Plains. University of Minnesota, Department of Applied Economics. 2006. http://ideas.repec.org/p/ags/umaesp/13838.html [3] Homepage of energygrass. www.energiafu.hu

A bi-population based scheme for an explicit exploration/exploitation trade-off in dynamic environments

NASA Astrophysics Data System (ADS)

Ben-Romdhane, Hajer; Krichen, Saoussen; Alba, Enrique

2017-05-01

Optimisation in changing environments is a challenging research topic since many real-world problems are inherently dynamic. Inspired by the natural evolution process, evolutionary algorithms (EAs) are among the most successful and promising approaches that have addressed dynamic optimisation problems. However, managing the exploration/exploitation trade-off in EAs is still a prevalent issue, and this is due to the difficulties associated with the control and measurement of such a behaviour. The proposal of this paper is to achieve a balance between exploration and exploitation in an explicit manner. The idea is to use two equally sized populations: the first one performs exploration while the second one is responsible for exploitation. These tasks are alternated from one generation to the next one in a regular pattern, so as to obtain a balanced search engine. Besides, we reinforce the ability of our algorithm to quickly adapt after cnhanges by means of a memory of past solutions. Such a combination aims to restrain the premature convergence, to broaden the search area, and to speed up the optimisation. We show through computational experiments, and based on a series of dynamic problems and many performance measures, that our approach improves the performance of EAs and outperforms competing algorithms.

Roll and pitch independently tuned interconnected suspension: modelling and dynamic analysis

NASA Astrophysics Data System (ADS)

Xu, Guangzhong; Zhang, Nong; Roser, Holger M.

2015-12-01

In this paper, a roll and pitch independently tuned hydraulically interconnected passive suspension is presented. Due to decoupling of vibration modes and the improved lateral and longitudinal stability, the stiffness of individual suspension spring can be reduced for improving ride comfort and road grip. A generalised 14 degree-of-freedom nonlinear vehicle model with anti-roll bars is established to investigate the vehicle ride and handling dynamic responses. The nonlinear fluidic model of the hydraulically interconnected suspension is developed and integrated with the full vehicle model to investigate the anti-roll and anti-pitch characteristics. Time domain analysis of the vehicle model with the proposed suspension is conducted under different road excitations and steering/braking manoeuvres. The dynamic responses are compared with conventional suspensions to demonstrate the potential of enhanced ride and handling performance. The results illustrate the model-decoupling property of the hydraulically interconnected system. The anti-roll and anti-pitch performance could be tuned independently by the interconnected systems. With the improved anti-roll and anti-pitch characteristics, the bounce stiffness and ride damping can be optimised for better ride comfort and tyre grip.

Principles of VCSEL designing

NASA Astrophysics Data System (ADS)

Nakwaski, W.

2008-03-01

Comprehensive computer simulations are currently the most efficient and cheap methods in designing and optimisation of semiconductor device structures. Seemingly they should be as exact as possible, but in practice it is well known that the most exact approaches are also the most involved and the most time-consuming ones and need powerful computers. In some cases, cheaper somewhat simplified modelling simulations are sufficiently accurate. Therefore, an appropriate modelling approach should be chosen taking into account a compromise between our needs and our possibilities. Modelling of operation and designing of structures of vertical-cavity surface-emitting diode lasers (VCSELs) requires appropriate mathematical description of physical processes crucial for devices operation, i.e., various optical, electrical, thermal, recombination and sometimes also mechanical phenomena taking place within their volumes. Equally important are mutual interactions between above individual processes, usually strongly non-linear and creating a real network of various inter-relations. Chain is as strong as its weakest link. Analogously, model is as exact as its less exact part. Therefore it is useless to improve exactness of its more accurate parts and not to care about less exact ones. All model parts should exhibit similar accuracy. In any individual case, a reasonable compromise should be reached between high modelling fidelity and its practical convenience depending on a main modelling goal, importance and urgency of expected results, available equipment and also financial possibilities. In the present paper, some simplifications used in VCSEL modelling are discussed and their impact on exactness of VCSEL designing is analysed.

A mathematical programming approach for sequential clustering of dynamic networks

NASA Astrophysics Data System (ADS)

Silva, Jonathan C.; Bennett, Laura; Papageorgiou, Lazaros G.; Tsoka, Sophia

2016-02-01

A common analysis performed on dynamic networks is community structure detection, a challenging problem that aims to track the temporal evolution of network modules. An emerging area in this field is evolutionary clustering, where the community structure of a network snapshot is identified by taking into account both its current state as well as previous time points. Based on this concept, we have developed a mixed integer non-linear programming (MINLP) model, SeqMod, that sequentially clusters each snapshot of a dynamic network. The modularity metric is used to determine the quality of community structure of the current snapshot and the historical cost is accounted for by optimising the number of node pairs co-clustered at the previous time point that remain so in the current snapshot partition. Our method is tested on social networks of interactions among high school students, college students and members of the Brazilian Congress. We show that, for an adequate parameter setting, our algorithm detects the classes that these students belong more accurately than partitioning each time step individually or by partitioning the aggregated snapshots. Our method also detects drastic discontinuities in interaction patterns across network snapshots. Finally, we present comparative results with similar community detection methods for time-dependent networks from the literature. Overall, we illustrate the applicability of mathematical programming as a flexible, adaptable and systematic approach for these community detection problems. Contribution to the Topical Issue "Temporal Network Theory and Applications", edited by Petter Holme.

Kernel learning at the first level of inference.

PubMed

Cawley, Gavin C; Talbot, Nicola L C

2014-05-01

Kernel learning methods, whether Bayesian or frequentist, typically involve multiple levels of inference, with the coefficients of the kernel expansion being determined at the first level and the kernel and regularisation parameters carefully tuned at the second level, a process known as model selection. Model selection for kernel machines is commonly performed via optimisation of a suitable model selection criterion, often based on cross-validation or theoretical performance bounds. However, if there are a large number of kernel parameters, as for instance in the case of automatic relevance determination (ARD), there is a substantial risk of over-fitting the model selection criterion, resulting in poor generalisation performance. In this paper we investigate the possibility of learning the kernel, for the Least-Squares Support Vector Machine (LS-SVM) classifier, at the first level of inference, i.e. parameter optimisation. The kernel parameters and the coefficients of the kernel expansion are jointly optimised at the first level of inference, minimising a training criterion with an additional regularisation term acting on the kernel parameters. The key advantage of this approach is that the values of only two regularisation parameters need be determined in model selection, substantially alleviating the problem of over-fitting the model selection criterion. The benefits of this approach are demonstrated using a suite of synthetic and real-world binary classification benchmark problems, where kernel learning at the first level of inference is shown to be statistically superior to the conventional approach, improves on our previous work (Cawley and Talbot, 2007) and is competitive with Multiple Kernel Learning approaches, but with reduced computational expense. Copyright © 2014 Elsevier Ltd. All rights reserved.

Equivalent Linearization Analysis of Geometrically Nonlinear Random Vibrations Using Commercial Finite Element Codes

NASA Technical Reports Server (NTRS)

Rizzi, Stephen A.; Muravyov, Alexander A.

2002-01-01

Two new equivalent linearization implementations for geometrically nonlinear random vibrations are presented. Both implementations are based upon a novel approach for evaluating the nonlinear stiffness within commercial finite element codes and are suitable for use with any finite element code having geometrically nonlinear static analysis capabilities. The formulation includes a traditional force-error minimization approach and a relatively new version of a potential energy-error minimization approach, which has been generalized for multiple degree-of-freedom systems. Results for a simply supported plate under random acoustic excitation are presented and comparisons of the displacement root-mean-square values and power spectral densities are made with results from a nonlinear time domain numerical simulation.

Student-Centred Teaching Methods: Can They Optimise Students' Approaches to Learning in Professional Higher Education?

ERIC Educational Resources Information Center

Baeten, Marlies; Struyven, Katrien; Dochy, Filip

2013-01-01

This paper investigates dynamics in approaches to learning within different learning environments. Two quasi-experimental studies were conducted with first-year student teachers (N[subscript Study 1] = 496, N[subscript Study 2] = 1098) studying a child development course. Data collection was carried out using a pre-test/post-test design by means…

Reduced-order modelling of parameter-dependent, linear and nonlinear dynamic partial differential equation models.

PubMed

Shah, A A; Xing, W W; Triantafyllidis, V

2017-04-01

In this paper, we develop reduced-order models for dynamic, parameter-dependent, linear and nonlinear partial differential equations using proper orthogonal decomposition (POD). The main challenges are to accurately and efficiently approximate the POD bases for new parameter values and, in the case of nonlinear problems, to efficiently handle the nonlinear terms. We use a Bayesian nonlinear regression approach to learn the snapshots of the solutions and the nonlinearities for new parameter values. Computational efficiency is ensured by using manifold learning to perform the emulation in a low-dimensional space. The accuracy of the method is demonstrated on a linear and a nonlinear example, with comparisons with a global basis approach.

Reduced-order modelling of parameter-dependent, linear and nonlinear dynamic partial differential equation models

PubMed Central

Xing, W. W.; Triantafyllidis, V.

2017-01-01

In this paper, we develop reduced-order models for dynamic, parameter-dependent, linear and nonlinear partial differential equations using proper orthogonal decomposition (POD). The main challenges are to accurately and efficiently approximate the POD bases for new parameter values and, in the case of nonlinear problems, to efficiently handle the nonlinear terms. We use a Bayesian nonlinear regression approach to learn the snapshots of the solutions and the nonlinearities for new parameter values. Computational efficiency is ensured by using manifold learning to perform the emulation in a low-dimensional space. The accuracy of the method is demonstrated on a linear and a nonlinear example, with comparisons with a global basis approach. PMID:28484327

Noise in NC-AFM measurements with significant tip–sample interaction

PubMed Central

Lübbe, Jannis; Temmen, Matthias

2016-01-01

The frequency shift noise in non-contact atomic force microscopy (NC-AFM) imaging and spectroscopy consists of thermal noise and detection system noise with an additional contribution from amplitude noise if there are significant tip–sample interactions. The total noise power spectral density D Δ f(f m) is, however, not just the sum of these noise contributions. Instead its magnitude and spectral characteristics are determined by the strongly non-linear tip–sample interaction, by the coupling between the amplitude and tip–sample distance control loops of the NC-AFM system as well as by the characteristics of the phase locked loop (PLL) detector used for frequency demodulation. Here, we measure D Δ f(f m) for various NC-AFM parameter settings representing realistic measurement conditions and compare experimental data to simulations based on a model of the NC-AFM system that includes the tip–sample interaction. The good agreement between predicted and measured noise spectra confirms that the model covers the relevant noise contributions and interactions. Results yield a general understanding of noise generation and propagation in the NC-AFM and provide a quantitative prediction of noise for given experimental parameters. We derive strategies for noise-optimised imaging and spectroscopy and outline a full optimisation procedure for the instrumentation and control loops. PMID:28144538

Noise in NC-AFM measurements with significant tip-sample interaction.

PubMed

Lübbe, Jannis; Temmen, Matthias; Rahe, Philipp; Reichling, Michael

2016-01-01

The frequency shift noise in non-contact atomic force microscopy (NC-AFM) imaging and spectroscopy consists of thermal noise and detection system noise with an additional contribution from amplitude noise if there are significant tip-sample interactions. The total noise power spectral density D Δ f ( f m ) is, however, not just the sum of these noise contributions. Instead its magnitude and spectral characteristics are determined by the strongly non-linear tip-sample interaction, by the coupling between the amplitude and tip-sample distance control loops of the NC-AFM system as well as by the characteristics of the phase locked loop (PLL) detector used for frequency demodulation. Here, we measure D Δ f ( f m ) for various NC-AFM parameter settings representing realistic measurement conditions and compare experimental data to simulations based on a model of the NC-AFM system that includes the tip-sample interaction. The good agreement between predicted and measured noise spectra confirms that the model covers the relevant noise contributions and interactions. Results yield a general understanding of noise generation and propagation in the NC-AFM and provide a quantitative prediction of noise for given experimental parameters. We derive strategies for noise-optimised imaging and spectroscopy and outline a full optimisation procedure for the instrumentation and control loops.

SIMS(DAIRY): a modelling framework to identify sustainable dairy farms in the UK. Framework description and test for organic systems and N fertiliser optimisation.

PubMed

Del Prado, A; Misselbrook, T; Chadwick, D; Hopkins, A; Dewhurst, R J; Davison, P; Butler, A; Schröder, J; Scholefield, D

2011-09-01

Multiple demands are placed on farming systems today. Society, national legislation and market forces seek what could be seen as conflicting outcomes from our agricultural systems, e.g. food quality, affordable prices, a healthy environmental, consideration of animal welfare, biodiversity etc., Many of these demands, or desirable outcomes, are interrelated, so reaching one goal may often compromise another and, importantly, pose a risk to the economic viability of the farm. SIMS(DAIRY), a farm-scale model, was used to explore this complexity for dairy farm systems. SIMS(DAIRY) integrates existing approaches to simulate the effect of interactions between farm management, climate and soil characteristics on losses of nitrogen, phosphorus and carbon. The effects on farm profitability and attributes of biodiversity, milk quality, soil quality and animal welfare are also included. SIMS(DAIRY) can also be used to optimise fertiliser N. In this paper we discuss some limitations and strengths of using SIMS(DAIRY) compared to other modelling approaches and propose some potential improvements. Using the model we evaluated the sustainability of organic dairy systems compared with conventional dairy farms under non-optimised and optimised fertiliser N use. Model outputs showed for example, that organic dairy systems based on grass-clover swards and maize silage resulted in much smaller total GHG emissions per l of milk and slightly smaller losses of NO(3) leaching and NO(x) emissions per l of milk compared with the grassland/maize-based conventional systems. These differences were essentially because the conventional systems rely on indirect energy use for 'fixing' N compared with biological N fixation for the organic systems. SIMS(DAIRY) runs also showed some other potential benefits from the organic systems compared with conventional systems in terms of financial performance and soil quality and biodiversity scores. Optimisation of fertiliser N timings and rates showed a considerable scope to reduce the (GHG emissions per l milk too). Copyright © 2011 Elsevier B.V. All rights reserved.

The robust model predictive control based on mixed H2/H∞ approach with separated performance formulations and its ISpS analysis

NASA Astrophysics Data System (ADS)

Li, Dewei; Li, Jiwei; Xi, Yugeng; Gao, Furong

2017-12-01

In practical applications, systems are always influenced by parameter uncertainties and external disturbance. Both the H2 performance and the H∞ performance are important for the real applications. For a constrained system, the previous designs of mixed H2/H∞ robust model predictive control (RMPC) optimise one performance with the other performance requirement as a constraint. But the two performances cannot be optimised at the same time. In this paper, an improved design of mixed H2/H∞ RMPC for polytopic uncertain systems with external disturbances is proposed to optimise them simultaneously. In the proposed design, the original uncertain system is decomposed into two subsystems by the additive character of linear systems. Two different Lyapunov functions are used to separately formulate the two performance indices for the two subsystems. Then, the proposed RMPC is designed to optimise both the two performances by the weighting method with the satisfaction of the H∞ performance requirement. Meanwhile, to make the design more practical, a simplified design is also developed. The recursive feasible conditions of the proposed RMPC are discussed and the closed-loop input state practical stable is proven. The numerical examples reflect the enlarged feasible region and the improved performance of the proposed design.

Optimisation of assembly scheduling in VCIM systems using genetic algorithm

NASA Astrophysics Data System (ADS)

Dao, Son Duy; Abhary, Kazem; Marian, Romeo

2017-09-01

Assembly plays an important role in any production system as it constitutes a significant portion of the lead time and cost of a product. Virtual computer-integrated manufacturing (VCIM) system is a modern production system being conceptually developed to extend the application of traditional computer-integrated manufacturing (CIM) system to global level. Assembly scheduling in VCIM systems is quite different from one in traditional production systems because of the difference in the working principles of the two systems. In this article, the assembly scheduling problem in VCIM systems is modeled and then an integrated approach based on genetic algorithm (GA) is proposed to search for a global optimised solution to the problem. Because of dynamic nature of the scheduling problem, a novel GA with unique chromosome representation and modified genetic operations is developed herein. Robustness of the proposed approach is verified by a numerical example.

Hypertrophic scarring: the greatest unmet challenge following burn injury

PubMed Central

Finnerty, Celeste C; Jeschke, Marc G; Branski, Ludwik K; Barret, Juan P.; Dziewulski, Peter; Herndon, David N

2017-01-01

Summary Improvements in acute burn care have enabled patients to survive massive burns which would have once been fatal. Now up to 70% of patients develop hypertrophic scars following burns. The functional and psychosocial sequelae remain a major rehabilitative challenge, decreasing quality of life and delaying reintegration into society. The current approach is to optimise the healing potential of the burn wound using targeted wound care and surgery in order to minimise the development of hypertrophic scarring. This approach often fails, and modulation of established scar is continued although the optimal indication, timing, and combination of therapies have yet to be established. The need for novel treatments is paramount, and future efforts to improve outcomes and quality of life should include optimisation of wound healing to attenuate or prevent hypertrophic scarring, well-designed trials to confirm treatment efficacy, and further elucidation of molecular mechanisms to allow development of new preventative and therapeutic strategies. PMID:27707499

Magnetic resonance imaging-guided surgical design: can we optimise the Fontan operation?

PubMed

Haggerty, Christopher M; Yoganathan, Ajit P; Fogel, Mark A

2013-12-01

The Fontan procedure, although an imperfect solution for children born with a single functional ventricle, is the only reconstruction at present short of transplantation. The haemodynamics associated with the total cavopulmonary connection, the modern approach to Fontan, are severely altered from the normal biventricular circulation and may contribute to the long-term complications that are frequently noted. Through recent technological advances, spear-headed by advances in medical imaging, it is now possible to virtually model these surgical procedures and evaluate the patient-specific haemodynamics as part of the pre-operative planning process. This is a novel paradigm with the potential to revolutionise the approach to Fontan surgery, help to optimise the haemodynamic results, and improve patient outcomes. This review provides a brief overview of these methods, presents preliminary results of their clinical usage, and offers insights into its potential future directions.

Petri-net-based 2D design of DNA walker circuits.

PubMed

Gilbert, David; Heiner, Monika; Rohr, Christian

2018-01-01

We consider localised DNA computation, where a DNA strand walks along a binary decision graph to compute a binary function. One of the challenges for the design of reliable walker circuits consists in leakage transitions, which occur when a walker jumps into another branch of the decision graph. We automatically identify leakage transitions, which allows for a detailed qualitative and quantitative assessment of circuit designs, design comparison, and design optimisation. The ability to identify leakage transitions is an important step in the process of optimising DNA circuit layouts where the aim is to minimise the computational error inherent in a circuit while minimising the area of the circuit. Our 2D modelling approach of DNA walker circuits relies on coloured stochastic Petri nets which enable functionality, topology and dimensionality all to be integrated in one two-dimensional model. Our modelling and analysis approach can be easily extended to 3-dimensional walker systems.

More of the same? Comment on "An integrated framework for the optimisation of sport and athlete development: a practitioner approach".

PubMed

MacNamara, Aine; Collins, Dave

2014-01-01

Gulbin and colleagues (Gulbin, J. P., Croser, M. J., Morley, E. J., & Weissensteiner, J. R. (2013). An integrated framework for the optimisation of sport and athlete development: A practitioner approach. Journal of Sports Sciences) present a new sport and athlete development framework that evolved from empirical observations from working with the Australian Institute of Sport. The FTEM (Foundations, Talent, Elite, Mastery) framework is proposed to integrate general and specialised phases of development for participants within the active lifestyle, sport participation and sport excellence pathways. A number of issues concerning the FTEM framework are presented. We also propose the need to move beyond prescriptive models of talent identification and development towards a consideration of features of best practice and process markers of development together with robust guidelines about the implementation of these in applied practice.

Optimisation of strain selection in evolutionary continuous culture

NASA Astrophysics Data System (ADS)

Bayen, T.; Mairet, F.

2017-12-01

In this work, we study a minimal time control problem for a perfectly mixed continuous culture with n ≥ 2 species and one limiting resource. The model that we consider includes a mutation factor for the microorganisms. Our aim is to provide optimal feedback control laws to optimise the selection of the species of interest. Thanks to Pontryagin's Principle, we derive optimality conditions on optimal controls and introduce a sub-optimal control law based on a most rapid approach to a singular arc that depends on the initial condition. Using adaptive dynamics theory, we also study a simplified version of this model which allows to introduce a near optimal strategy.

Spurious Solutions Of Nonlinear Differential Equations

NASA Technical Reports Server (NTRS)

Yee, H. C.; Sweby, P. K.; Griffiths, D. F.

1992-01-01

Report utilizes nonlinear-dynamics approach to investigate possible sources of errors and slow convergence and non-convergence of steady-state numerical solutions when using time-dependent approach for problems containing nonlinear source terms. Emphasizes implications for development of algorithms in CFD and computational sciences in general. Main fundamental conclusion of study is that qualitative features of nonlinear differential equations cannot be adequately represented by finite-difference method and vice versa.

Fault-tolerant optimised tracking control for unknown discrete-time linear systems using a combined reinforcement learning and residual compensation methodology

NASA Astrophysics Data System (ADS)

Han, Ke-Zhen; Feng, Jian; Cui, Xiaohong

2017-10-01

This paper considers the fault-tolerant optimised tracking control (FTOTC) problem for unknown discrete-time linear system. A research scheme is proposed on the basis of data-based parity space identification, reinforcement learning and residual compensation techniques. The main characteristic of this research scheme lies in the parity-space-identification-based simultaneous tracking control and residual compensation. The specific technical line consists of four main contents: apply subspace aided method to design observer-based residual generator; use reinforcement Q-learning approach to solve optimised tracking control policy; rely on robust H∞ theory to achieve noise attenuation; adopt fault estimation triggered by residual generator to perform fault compensation. To clarify the design and implementation procedures, an integrated algorithm is further constructed to link up these four functional units. The detailed analysis and proof are subsequently given to explain the guaranteed FTOTC performance of the proposed conclusions. Finally, a case simulation is provided to verify its effectiveness.

Path optimisation of a mobile robot using an artificial neural network controller

NASA Astrophysics Data System (ADS)

Singh, M. K.; Parhi, D. R.

2011-01-01

This article proposed a novel approach for design of an intelligent controller for an autonomous mobile robot using a multilayer feed forward neural network, which enables the robot to navigate in a real world dynamic environment. The inputs to the proposed neural controller consist of left, right and front obstacle distance with respect to its position and target angle. The output of the neural network is steering angle. A four layer neural network has been designed to solve the path and time optimisation problem of mobile robots, which deals with the cognitive tasks such as learning, adaptation, generalisation and optimisation. A back propagation algorithm is used to train the network. This article also analyses the kinematic design of mobile robots for dynamic movements. The simulation results are compared with experimental results, which are satisfactory and show very good agreement. The training of the neural nets and the control performance analysis has been done in a real experimental setup.

Population response to climate change: linear vs. non-linear modeling approaches.

PubMed

Ellis, Alicia M; Post, Eric

2004-03-31

Research on the ecological consequences of global climate change has elicited a growing interest in the use of time series analysis to investigate population dynamics in a changing climate. Here, we compare linear and non-linear models describing the contribution of climate to the density fluctuations of the population of wolves on Isle Royale, Michigan from 1959 to 1999. The non-linear self excitatory threshold autoregressive (SETAR) model revealed that, due to differences in the strength and nature of density dependence, relatively small and large populations may be differentially affected by future changes in climate. Both linear and non-linear models predict a decrease in the population of wolves with predicted changes in climate. Because specific predictions differed between linear and non-linear models, our study highlights the importance of using non-linear methods that allow the detection of non-linearity in the strength and nature of density dependence. Failure to adopt a non-linear approach to modelling population response to climate change, either exclusively or in addition to linear approaches, may compromise efforts to quantify ecological consequences of future warming.

The optimisation of low-acceleration interstellar relativistic rocket trajectories using genetic algorithms

NASA Astrophysics Data System (ADS)

Fung, Kenneth K. H.; Lewis, Geraint F.; Wu, Xiaofeng

2017-04-01

A vast wealth of literature exists on the topic of rocket trajectory optimisation, particularly in the area of interplanetary trajectories due to its relevance today. Studies on optimising interstellar and intergalactic trajectories are usually performed in flat spacetime using an analytical approach, with very little focus on optimising interstellar trajectories in a general relativistic framework. This paper examines the use of low-acceleration rockets to reach galactic destinations in the least possible time, with a genetic algorithm being employed for the optimisation process. The fuel required for each journey was calculated for various types of propulsion systems to determine the viability of low-acceleration rockets to colonise the Milky Way. The results showed that to limit the amount of fuel carried on board, an antimatter propulsion system would likely be the minimum technological requirement to reach star systems tens of thousands of light years away. However, using a low-acceleration rocket would require several hundreds of thousands of years to reach these star systems, with minimal time dilation effects since maximum velocities only reached about 0.2 c . Such transit times are clearly impractical, and thus, any kind of colonisation using low acceleration rockets would be difficult. High accelerations, on the order of 1 g, are likely required to complete interstellar journeys within a reasonable time frame, though they may require prohibitively large amounts of fuel. So for now, it appears that humanity's ultimate goal of a galactic empire may only be possible at significantly higher accelerations, though the propulsion technology requirement for a journey that uses realistic amounts of fuel remains to be determined.

Zero Forcing Conditions for Nonlinear channel Equalisation using a pre-coding scheme

DOE Office of Scientific and Technical Information (OSTI.GOV)

Arfa, Hichem; Belghith, Safya; El Asmi, Sadok

2009-03-05

This paper shows how we can present a zero forcing conditions for a nonlinear channel equalisation. These zero forcing conditions based on the rank of nonlinear system are issued from an algebraic approach based on the module theoretical approach, in which the rank of nonlinear channel is clearly defined. In order to improve the performance of equalisation and reduce the complexity of used nonlinear systems, we will apply a pre-coding scheme. Theoretical results are given and computer simulation is used to corroborate the theory.

Neural net forecasting for geomagnetic activity

NASA Technical Reports Server (NTRS)

Hernandez, J. V.; Tajima, T.; Horton, W.

1993-01-01

We use neural nets to construct nonlinear models to forecast the AL index given solar wind and interplanetary magnetic field (IMF) data. We follow two approaches: (1) the state space reconstruction approach, which is a nonlinear generalization of autoregressive-moving average models (ARMA) and (2) the nonlinear filter approach, which reduces to a moving average model (MA) in the linear limit. The database used here is that of Bargatze et al. (1985).

Fuzzy model-based servo and model following control for nonlinear systems.

PubMed

Ohtake, Hiroshi; Tanaka, Kazuo; Wang, Hua O

2009-12-01

This correspondence presents servo and nonlinear model following controls for a class of nonlinear systems using the Takagi-Sugeno fuzzy model-based control approach. First, the construction method of the augmented fuzzy system for continuous-time nonlinear systems is proposed by differentiating the original nonlinear system. Second, the dynamic fuzzy servo controller and the dynamic fuzzy model following controller, which can make outputs of the nonlinear system converge to target points and to outputs of the reference system, respectively, are introduced. Finally, the servo and model following controller design conditions are given in terms of linear matrix inequalities. Design examples illustrate the utility of this approach.

Multi-frequency Defect Selective Imaging via Nonlinear Ultrasound

NASA Astrophysics Data System (ADS)

Solodov, Igor; Busse, Gerd

The concept of defect-selective ultrasonic nonlinear imaging is based on visualization of strongly nonlinear inclusions in the form of localized cracked defects. For intense excitation, the ultrasonic response of defects is affected by mechanical constraint between their fragments that makes their vibrations extremely nonlinear. The cracked flaws, therefore, efficiently generate multiple new frequencies, which can be used as a nonlinear "tag" to detect and image them. In this paper, the methodologies of nonlinear scanning laser vibrometry (NSLV) and nonlinear air-coupled emission (NACE) are applied for nonlinear imaging of various defects in hi-tech and constructional materials. A broad database obtained demonstrates evident advantages of the nonlinear approach over its linear counterpart. The higher-order nonlinear frequencies provide increase in signal-to-noise ratio and enhance the contrast of imaging. Unlike conventional ultrasonic instruments, the nonlinear approach yields abundant multi-frequency information on defect location. The application of image recognition and processing algorithms is described and shown to improve reliability and quality of ultrasonic imaging.

Cluster-based adaptive power control protocol using Hidden Markov Model for Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Vinutha, C. B.; Nalini, N.; Nagaraja, M.

2017-06-01

This paper presents strategies for an efficient and dynamic transmission power control technique, in order to reduce packet drop and hence energy consumption of power-hungry sensor nodes operated in highly non-linear channel conditions of Wireless Sensor Networks. Besides, we also focus to prolong network lifetime and scalability by designing cluster-based network structure. Specifically we consider weight-based clustering approach wherein, minimum significant node is chosen as Cluster Head (CH) which is computed stemmed from the factors distance, remaining residual battery power and received signal strength (RSS). Further, transmission power control schemes to fit into dynamic channel conditions are meticulously implemented using Hidden Markov Model (HMM) where probability transition matrix is formulated based on the observed RSS measurements. Typically, CH estimates initial transmission power of its cluster members (CMs) from RSS using HMM and broadcast this value to its CMs for initialising their power value. Further, if CH finds that there are variations in link quality and RSS of the CMs, it again re-computes and optimises the transmission power level of the nodes using HMM to avoid packet loss due noise interference. We have demonstrated our simulation results to prove that our technique efficiently controls the power levels of sensing nodes to save significant quantity of energy for different sized network.

Magneto-acoustic imaging by continuous-wave excitation.

PubMed

Shunqi, Zhang; Zhou, Xiaoqing; Tao, Yin; Zhipeng, Liu

2017-04-01

The electrical characteristics of tissue yield valuable information for early diagnosis of pathological changes. Magneto-acoustic imaging is a functional approach for imaging of electrical conductivity. This study proposes a continuous-wave magneto-acoustic imaging method. A kHz-range continuous signal with an amplitude range of several volts is used to excite the magneto-acoustic signal and improve the signal-to-noise ratio. The magneto-acoustic signal amplitude and phase are measured to locate the acoustic source via lock-in technology. An optimisation algorithm incorporating nonlinear equations is used to reconstruct the magneto-acoustic source distribution based on the measured amplitude and phase at various frequencies. Validation simulations and experiments were performed in pork samples. The experimental and simulation results agreed well. While the excitation current was reduced to 10 mA, the acoustic signal magnitude increased up to 10 -7  Pa. Experimental reconstruction of the pork tissue showed that the image resolution reached mm levels when the excitation signal was in the kHz range. The signal-to-noise ratio of the detected magneto-acoustic signal was improved by more than 25 dB at 5 kHz when compared to classical 1 MHz pulse excitation. The results reported here will aid further research into magneto-acoustic generation mechanisms and internal tissue conductivity imaging.

Finite difference time domain calculation of transients in antennas with nonlinear loads

NASA Technical Reports Server (NTRS)

Luebbers, Raymond J.; Beggs, John H.; Kunz, Karl S.; Chamberlin, Kent

1991-01-01

In this paper transient fields for antennas with more general geometries are calculated directly using Finite Difference Time Domain methods. In each FDTD cell which contains a nonlinear load, a nonlinear equation is solved at each time step. As a test case the transient current in a long dipole antenna with a nonlinear load excited by a pulsed plane wave is computed using this approach. The results agree well with both calculated and measured results previously published. The approach given here extends the applicability of the FDTD method to problems involving scattering from targets including nonlinear loads and materials, and to coupling between antennas containing nonlinear loads. It may also be extended to propagation through nonlinear materials.

Correlation techniques to determine model form in robust nonlinear system realization/identification

NASA Technical Reports Server (NTRS)

Stry, Greselda I.; Mook, D. Joseph

1991-01-01

The fundamental challenge in identification of nonlinear dynamic systems is determining the appropriate form of the model. A robust technique is presented which essentially eliminates this problem for many applications. The technique is based on the Minimum Model Error (MME) optimal estimation approach. A detailed literature review is included in which fundamental differences between the current approach and previous work is described. The most significant feature is the ability to identify nonlinear dynamic systems without prior assumption regarding the form of the nonlinearities, in contrast to existing nonlinear identification approaches which usually require detailed assumptions of the nonlinearities. Model form is determined via statistical correlation of the MME optimal state estimates with the MME optimal model error estimates. The example illustrations indicate that the method is robust with respect to prior ignorance of the model, and with respect to measurement noise, measurement frequency, and measurement record length.

State-Of in Uav Remote Sensing Survey - First Insights Into Applications of Uav Sensing Systems

NASA Astrophysics Data System (ADS)

Aasen, H.

2017-08-01

UAVs are increasingly adapted as remote sensing platforms. Together with specialized sensors, they become powerful sensing systems for environmental monitoring and surveying. Spectral data has great capabilities to the gather information about biophysical and biochemical properties. Still, capturing meaningful spectral data in a reproducible way is not trivial. Since a couple of years small and lightweight spectral sensors, which can be carried on small flexible platforms, have become available. With their adaption in the community, the responsibility to ensure the quality of the data is increasingly shifted from specialized companies and agencies to individual researchers or research teams. Due to the complexity of the data acquisition of spectral data, this poses a challenge for the community and standardized protocols, metadata and best practice procedures are needed to make data intercomparable. In November 2016, the ESSEM COST action Innovative optical Tools for proximal sensing of ecophysiological processes (OPTIMISE; http://optimise.dcs.aber.ac.uk/) held a workshop on best practices for UAV spectral sampling. The objective of this meeting was to trace the way from particle to pixel and identify influences on the data quality / reliability, to figure out how well we are currently doing with spectral sampling from UAVs and how we can improve. Additionally, a survey was designed to be distributed within the community to get an overview over the current practices and raise awareness for the topic. This talk will introduce the approach of the OPTIMISE community towards best practises in UAV spectral sampling and present first results of the survey (http://optimise.dcs.aber.ac.uk/uav-survey/). This contribution briefly introduces the survey and gives some insights into the first results given by the interviewees.

Simplified and refined finite element approaches for determining stresses and internal forces in geometrically nonlinear structural analysis

NASA Technical Reports Server (NTRS)

Robinson, J. C.

1979-01-01

Two methods for determining stresses and internal forces in geometrically nonlinear structural analysis are presented. The simplified approach uses the mid-deformed structural position to evaluate strains when rigid body rotation is present. The important feature of this approach is that it can easily be used with a general-purpose finite-element computer program. The refined approach uses element intrinsic or corotational coordinates and a geometric transformation to determine element strains from joint displacements. Results are presented which demonstrate the capabilities of these potentially useful approaches for geometrically nonlinear structural analysis.

The seasonal behaviour of carbon fluxes in the Amazon: fusion of FLUXNET data and the ORCHIDEE model

NASA Astrophysics Data System (ADS)

Verbeeck, H.; Peylin, P.; Bacour, C.; Ciais, P.

2009-04-01

Eddy covariance measurements at the Santarém (km 67) site revealed an unexpected seasonal pattern in carbon fluxes which could not be simulated by existing state-of-the-art global ecosystem models (Saleska et al., Sciece 2003). An unexpected high carbon uptake was measured during dry season. In contrast, carbon release was observed in the wet season. There are several possible (combined) underlying mechanisms of this phenomenon: (1) an increased soil respiration due to soil moisture in the wet season, (2) increased photosynthesis during the dry season due to deep rooting, hydraulic lift, increased radiation and/or a leaf flush. The objective of this study is to optimise the ORCHIDEE model using eddy covariance data in order to be able to mimic the seasonal response of carbon fluxes to dry/wet conditions in tropical forest ecosystems. By doing this, we try to identify the underlying mechanisms of this seasonal response. The ORCHIDEE model is a state of the art mechanistic global vegetation model that can be run at local or global scale. It calculates the carbon and water cycle in the different soil and vegetation pools and resolves the diurnal cycle of fluxes. ORCHIDEE is built on the concept of plant functional types (PFT) to describe vegetation. To bring the different carbon pool sizes to realistic values, spin-up runs are used. ORCHIDEE uses climate variables as drivers together with a number of ecosystem parameters that have been assessed from laboratory and in situ experiments. These parameters are still associated with a large uncertainty and may vary between and within PFTs in a way that is currently not informed or captured by the model. Recently, the development of assimilation techniques allows the objective use of eddy covariance data to improve our knowledge of these parameters in a statistically coherent approach. We use a Bayesian optimisation approach. This approach is based on the minimization of a cost function containing the mismatch between simulated model output and observations as well as the mismatch between a priori and optimized parameters. The parameters can be optimized on different time scales (annually, monthly, daily). For this study the model is optimised at local scale for 5 eddy flux sites: 4 sites in Brazil and one in French Guyana. The seasonal behaviour of C fluxes in response to wet and dry conditions differs among these sites. Key processes that are optimised include: the effect of the soil water on heterotrophic soil respiration, the effect of soil water availability on stomatal conductance and photosynthesis, and phenology. By optimising several key parameters we could improve the simulation of the seasonal pattern of NEE significantly. Nevertheless, posterior parameters should be interpreted with care, because resulting parameter values might compensate for uncertainties on the model structure or other parameters. Moreover, several critical issues appeared during this study e.g. how to assimilate latent and sensible heat data, when the energy balance is not closed in the data? Optimisation of the Q10 parameter showed that on some sites respiration was not sensitive at all to temperature, which show only small variations in this region. Considering this, one could question the reliability of the partitioned fluxes (GPP/Reco) at these sites. This study also tests if there is coherence between optimised parameter values of different sites within the tropical forest PFT and if the forward model response to climate variations is similar between sites.

An evaluation of alternative selection indexes for a non-linear profit trait approaching its economic optimum.

PubMed

Martin-Collado, D; Byrne, T J; Visser, B; Amer, P R

2016-12-01

This study used simulation to evaluate the performance of alternative selection index configurations in the context of a breeding programme where a trait with a non-linear economic value is approaching an economic optimum. The simulation used a simple population structure that approximately mimics selection in dual purpose sheep flocks in New Zealand (NZ). In the NZ dual purpose sheep population, number of lambs born is a genetic trait that is approaching an economic optimum, while genetically correlated growth traits have linear economic values and are not approaching any optimum. The predominant view among theoretical livestock geneticists is that the optimal approach to select for nonlinear profit traits is to use a linear selection index and to update it regularly. However, there are some nonlinear index approaches that have not been evaluated. This study assessed the efficiency of the following four alternative selection index approaches in terms of genetic progress relative to each other: (i) a linear index, (ii) a linear index updated regularly, (iii) a nonlinear (quadratic) index, and (iv) a NLF index (nonlinear index below the optimum and then flat). The NLF approach does not reward or penalize animals for additional genetic merit beyond the trait optimum. It was found to be at least comparable in efficiency to the approach of regularly updating the linear index with short (15 year) and long (30 year) time frames. The relative efficiency of this approach was slightly reduced when the current average value of the nonlinear trait was close to the optimum. Finally, practical issues of industry application of indexes are considered and some potential practical benefits of efficient deployment of a NLF index in highly heterogeneous industries (breeds, flocks and production environments) such as in the NZ dual purpose sheep population are discussed. © 2016 Blackwell Verlag GmbH.

Aggregated GPS tracking of vehicles and its use as a proxy of traffic-related air pollution emissions

NASA Astrophysics Data System (ADS)

Chen, Shimon; Bekhor, Shlomo; Yuval; Broday, David M.

2016-10-01

Most air quality models use traffic-related variables as an input. Previous studies estimated nearby vehicular activity through sporadic traffic counts or via traffic assignment models. Both methods have previously produced poor or no data for nights, weekends and holidays. Emerging technologies allow the estimation of traffic through passive monitoring of location-aware devices. Examples of such devices are GPS transceivers installed in vehicles. In this work, we studied traffic volumes that were derived from such data. Additionally, we used these data for estimating ambient nitrogen dioxide concentrations, using a non-linear optimisation model that includes basic dispersion properties. The GPS-derived data show great potential for use as a proxy for pollutant emissions from motor-vehicles.

Silicon photonic filters with high rejection of both TE and TM modes for on-chip four wave mixing applications.

PubMed

Cantarella, Giuseppe; Klitis, Charalambos; Sorel, Marc; Strain, Michael J

2017-08-21

Wavelength selective filters represent one of the key elements for photonic integrated circuits (PIC) and many of their applications in linear and non-linear optics. In devices optimised for single polarisation operation, cross-polarisation scattering can significantly limit the achievable filter rejection. An on-chip filter consisting of elements to filter both TE and TM polarisations is demonstrated, based on a cascaded ring resonator geometry, which exhibits a high total optical rejection of over 60 dB. Monolithic integration of a cascaded ring filter with a four-wave mixing micro-ring device is also experimentally demonstrated with a FWM efficiency of -22dB and pump filter extinction of 62dB.

Nonlinear degradation of a visible-light communication link: A Volterra-series approach

NASA Astrophysics Data System (ADS)

Kamalakis, Thomas; Dede, Georgia

2018-06-01

Visible light communications can be used to provide illumination and data communication at the same time. In this paper, a reverse-engineering approach is presented for assessing the impact of nonlinear signal distortion in visible light communication links. The approach is based on the Volterra series expansion and has the advantage of accurately accounting for memory effects in contrast to the static nonlinear models that are popular in the literature. Volterra kernels describe the end-to-end system response and can be inferred from measurements. Consequently, this approach does not rely on any particular physical models and assumptions regarding the individual link components. We provide the necessary framework for estimating the nonlinear distortion on the symbol estimates of a discrete multitone modulated link. Various design aspects such as waveform clipping and predistortion are also incorporated in the analysis. Using this framework, the nonlinear signal-to-interference is calculated for the system at hand. It is shown that at high signal amplitudes, the nonlinear signal-to-interference can be less than 25 dB.

A phenomenological approach to modeling chemical dynamics in nonlinear and two-dimensional spectroscopy.

PubMed

Ramasesha, Krupa; De Marco, Luigi; Horning, Andrew D; Mandal, Aritra; Tokmakoff, Andrei

2012-04-07

We present an approach for calculating nonlinear spectroscopic observables, which overcomes the approximations inherent to current phenomenological models without requiring the computational cost of performing molecular dynamics simulations. The trajectory mapping method uses the semi-classical approximation to linear and nonlinear response functions, and calculates spectra from trajectories of the system's transition frequencies and transition dipole moments. It rests on identifying dynamical variables important to the problem, treating the dynamics of these variables stochastically, and then generating correlated trajectories of spectroscopic quantities by mapping from the dynamical variables. This approach allows one to describe non-Gaussian dynamics, correlated dynamics between variables of the system, and nonlinear relationships between spectroscopic variables of the system and the bath such as non-Condon effects. We illustrate the approach by applying it to three examples that are often not adequately treated by existing analytical models--the non-Condon effect in the nonlinear infrared spectra of water, non-Gaussian dynamics inherent to strongly hydrogen bonded systems, and chemical exchange processes in barrier crossing reactions. The methods described are generally applicable to nonlinear spectroscopy throughout the optical, infrared and terahertz regions.

Dipeptidyl Peptidase-4 Inhibitor Development and Post-authorisation Programme for Vildagliptin - Clinical Evidence for Optimised Management of Chronic Diseases Beyond Type 2 Diabetes.

PubMed

Strain, William David; Paldánius, Päivi M

2017-08-01

The last decade has witnessed the role of dipeptidyl peptidase-4 (DPP-4) inhibitors in producing a conceptual change in early management of type 2 diabetes mellitus (T2DM) by shifting emphasis from a gluco-centric approach to holistically treating underlying pathophysiological processes. DPP-4 inhibitors highlighted the importance of acknowledging hypoglycaemia and weight gain as barriers to optimised care in T2DM. These complications were an integral part of diabetes management before the introduction of DPP-4 inhibitors. During the development of DPP-4 inhibitors, regulatory requirements for introducing new agents underwent substantial changes, with increased emphasis on safety. This led to the systematic collection of adjudicated cardiovascular (CV) safety data, and, where 95% confidence of a lack of harm could not be demonstrated, the standardised CV safety studies. Furthermore, the growing awareness of the worldwide extent of T2DM demanded a more diverse approach to recruitment and participation in clinical trials. Finally, the global financial crisis placed a new awareness on the health economics of diabetes, which rapidly became the most expensive disease in the world. This review encompasses unique developments in the global landscape, and the role DPP-4 inhibitors, specifically vildagliptin, have played in research advancement and optimisation of diabetes care in a diverse population with T2DM worldwide.

Dipeptidyl Peptidase-4 Inhibitor Development and Post-authorisation Programme for Vildagliptin — Clinical Evidence for Optimised Management of Chronic Diseases Beyond Type 2 Diabetes

PubMed Central

Paldánius, Päivi M

2017-01-01

Abstract The last decade has witnessed the role of dipeptidyl peptidase-4 (DPP-4) inhibitors in producing a conceptual change in early management of type 2 diabetes mellitus (T2DM) by shifting emphasis from a gluco-centric approach to holistically treating underlying pathophysiological processes. DPP-4 inhibitors highlighted the importance of acknowledging hypoglycaemia and weight gain as barriers to optimised care in T2DM. These complications were an integral part of diabetes management before the introduction of DPP-4 inhibitors. During the development of DPP-4 inhibitors, regulatory requirements for introducing new agents underwent substantial changes, with increased emphasis on safety. This led to the systematic collection of adjudicated cardiovascular (CV) safety data, and, where 95% confidence of a lack of harm could not be demonstrated, the standardised CV safety studies. Furthermore, the growing awareness of the worldwide extent of T2DM demanded a more diverse approach to recruitment and participation in clinical trials. Finally, the global financial crisis placed a new awareness on the health economics of diabetes, which rapidly became the most expensive disease in the world. This review encompasses unique developments in the global landscape, and the role DPP-4 inhibitors, specifically vildagliptin, have played in research advancement and optimisation of diabetes care in a diverse population with T2DM worldwide. PMID:29632609

A novel probabilistic approach to generating PTV with partial voxel contributions

NASA Astrophysics Data System (ADS)

Tsang, H. S.; Kamerling, C. P.; Ziegenhein, P.; Nill, S.; Oelfke, U.

2017-06-01

Radiotherapy treatment planning for use with high-energy photon beams currently employs a binary approach in defining the planning target volume (PTV). We propose a margin concept that takes the beam directions into account, generating beam-dependent PTVs (bdPTVs) on a beam-by-beam basis. The resulting degree of overlaps between the bdPTVs are used within the optimisation process; the optimiser effectively considers the same voxel to be both target and organ at risk (OAR) with fractional contributions. We investigate the impact of this novel approach when applied to prostate radiotherapy treatments, and compare treatment plans generated using beam dependent margins to conventional margins. Five prostate patients were used in this planning study, and plans using beam dependent margins improved the sparing of high doses to target-surrounding OARs, though a trade-off in delivering additional low dose to the OARs can be observed. Plans using beam dependent margins are observed to have a slightly reduced target coverage. Nevertheless, all plans are able to satisfy 90% population coverage with the target receiving at least 95% of the prescribed dose to D98% .

Control allocation-based adaptive control for greenhouse climate

NASA Astrophysics Data System (ADS)

Su, Yuanping; Xu, Lihong; Goodman, Erik D.

2018-04-01

This paper presents an adaptive approach to greenhouse climate control, as part of an integrated control and management system for greenhouse production. In this approach, an adaptive control algorithm is first derived to guarantee the asymptotic convergence of the closed system with uncertainty, then using that control algorithm, a controller is designed to satisfy the demands for heat and mass fluxes to maintain inside temperature, humidity and CO2 concentration at their desired values. Instead of applying the original adaptive control inputs directly, second, a control allocation technique is applied to distribute the demands of the heat and mass fluxes to the actuators by minimising tracking errors and energy consumption. To find an energy-saving solution, both single-objective optimisation (SOO) and multiobjective optimisation (MOO) in the control allocation structure are considered. The advantage of the proposed approach is that it does not require any a priori knowledge of the uncertainty bounds, and the simulation results illustrate the effectiveness of the proposed control scheme. It also indicates that MOO saves more energy in the control process.

Workplace mental health: developing an integrated intervention approach.

PubMed

LaMontagne, Anthony D; Martin, Angela; Page, Kathryn M; Reavley, Nicola J; Noblet, Andrew J; Milner, Allison J; Keegel, Tessa; Smith, Peter M

2014-05-09

Mental health problems are prevalent and costly in working populations. Workplace interventions to address common mental health problems have evolved relatively independently along three main threads or disciplinary traditions: medicine, public health, and psychology. In this Debate piece, we argue that these three threads need to be integrated to optimise the prevention of mental health problems in working populations. To realise the greatest population mental health benefits, workplace mental health intervention needs to comprehensively 1) protect mental health by reducing work-related risk factors for mental health problems; 2) promote mental health by developing the positive aspects of work as well as worker strengths and positive capacities; and 3) address mental health problems among working people regardless of cause. We outline the evidence supporting such an integrated intervention approach and consider the research agenda and policy developments needed to move towards this goal, and propose the notion of integrated workplace mental health literacy. An integrated approach to workplace mental health combines the strengths of medicine, public health, and psychology, and has the potential to optimise both the prevention and management of mental health problems in the workplace.

Kurtosis Approach for Nonlinear Blind Source Separation

NASA Technical Reports Server (NTRS)

Duong, Vu A.; Stubbemd, Allen R.

2005-01-01

In this paper, we introduce a new algorithm for blind source signal separation for post-nonlinear mixtures. The mixtures are assumed to be linearly mixed from unknown sources first and then distorted by memoryless nonlinear functions. The nonlinear functions are assumed to be smooth and can be approximated by polynomials. Both the coefficients of the unknown mixing matrix and the coefficients of the approximated polynomials are estimated by the gradient descent method conditional on the higher order statistical requirements. The results of simulation experiments presented in this paper demonstrate the validity and usefulness of our approach for nonlinear blind source signal separation.

Study of cumulative fatigue damage detection for used parts with nonlinear output frequency response functions based on NARMAX modelling

NASA Astrophysics Data System (ADS)

Huang, Honglan; Mao, Hanying; Mao, Hanling; Zheng, Weixue; Huang, Zhenfeng; Li, Xinxin; Wang, Xianghong

2017-12-01

Cumulative fatigue damage detection for used parts plays a key role in the process of remanufacturing engineering and is related to the service safety of the remanufactured parts. In light of the nonlinear properties of used parts caused by cumulative fatigue damage, the based nonlinear output frequency response functions detection approach offers a breakthrough to solve this key problem. First, a modified PSO-adaptive lasso algorithm is introduced to improve the accuracy of the NARMAX model under impulse hammer excitation, and then, an effective new algorithm is derived to estimate the nonlinear output frequency response functions under rectangular pulse excitation, and a based nonlinear output frequency response functions index is introduced to detect the cumulative fatigue damage in used parts. Then, a novel damage detection approach that integrates the NARMAX model and the rectangular pulse is proposed for nonlinear output frequency response functions identification and cumulative fatigue damage detection of used parts. Finally, experimental studies of fatigued plate specimens and used connecting rod parts are conducted to verify the validity of the novel approach. The obtained results reveal that the new approach can detect cumulative fatigue damages of used parts effectively and efficiently and that the various values of the based nonlinear output frequency response functions index can be used to detect the different fatigue damages or working time. Since the proposed new approach can extract nonlinear properties of systems by only a single excitation of the inspected system, it shows great promise for use in remanufacturing engineering applications.

Multiscale Approach For Simulating Nonlinear Wave Propagation In Materials with Localized Microdamage

NASA Astrophysics Data System (ADS)

Vanaverbeke, Sigfried; Van Den Abeele, Koen

2006-05-01

A multiscale model for the simulation of two-dimensional nonlinear wave propagation in microcracked materials exhibiting hysteretic nonlinearity is presented. We use trigger-like elements with a two state nonlinear stress-strain relation to simulate microcracks at the microlevel. A generalized Preisach space approach, based on the eigenstress-eigenstrain formulation, upscales the microscopic state relation to the mesoscopic level. The macroscopic response of the sample to an arbitrary excitation signal is then predicted using a staggered grid Elastodynamic Finite Integration Technique (EFIT) formalism. We apply the model to investigate spectral changes of a pulsed signal traversing a localized microdamaged region with hysteretic nonlinearity in a plate, and to study the influence of a superficial region with hysteretic nonlinearity on the nonlinear Rayleigh wave propagation.

Time domain nonlinear SMA damper force identification approach and its numerical validation

NASA Astrophysics Data System (ADS)

Xin, Lulu; Xu, Bin; He, Jia

2012-04-01

Most of the currently available vibration-based identification approaches for structural damage detection are based on eigenvalues and/or eigenvectors extracted from vibration measurements and, strictly speaking, are only suitable for linear system. However, the initiation and development of damage in engineering structures under severe dynamic loadings are typical nonlinear procedure. Studies on the identification of restoring force which is a direct indicator of the extent of the nonlinearity have received increasing attention in recent years. In this study, a date-based time domain identification approach for general nonlinear system was developed. The applied excitation and the corresponding response time series of the structure were used for identification by means of standard least-square techniques and a power series polynomial model (PSPM) which was utilized to model the nonlinear restoring force (NRF). The feasibility and robustness of the proposed approach was verified by a 2 degree-of-freedoms (DOFs) lumped mass numerical model equipped with a shape memory ally (SMA) damper mimicking nonlinear behavior. The results show that the proposed data-based time domain method is capable of identifying the NRF in engineering structures without any assumptions on the mass distribution and the topology of the structure, and provides a promising way for damage detection in the presence of structural nonlinearities.

An Unscented Kalman Filter Approach to the Estimation of Nonlinear Dynamical Systems Models

ERIC Educational Resources Information Center

Chow, Sy-Miin; Ferrer, Emilio; Nesselroade, John R.

2007-01-01

In the past several decades, methodologies used to estimate nonlinear relationships among latent variables have been developed almost exclusively to fit cross-sectional models. We present a relatively new estimation approach, the unscented Kalman filter (UKF), and illustrate its potential as a tool for fitting nonlinear dynamic models in two ways:…

Optimal control of LQR for discrete time-varying systems with input delays

NASA Astrophysics Data System (ADS)

Yin, Yue-Zhu; Yang, Zhong-Lian; Yin, Zhi-Xiang; Xu, Feng

2018-04-01

In this work, we consider the optimal control problem of linear quadratic regulation for discrete time-variant systems with single input and multiple input delays. An innovative and simple method to derive the optimal controller is given. The studied problem is first equivalently converted into a problem subject to a constraint condition. Last, with the established duality, the problem is transformed into a static mathematical optimisation problem without input delays. The optimal control input solution to minimise performance index function is derived by solving this optimisation problem with two methods. A numerical simulation example is carried out and its results show that our two approaches are both feasible and very effective.

Using Neural Networks for Sensor Validation

NASA Technical Reports Server (NTRS)

Mattern, Duane L.; Jaw, Link C.; Guo, Ten-Huei; Graham, Ronald; McCoy, William

1998-01-01

This paper presents the results of applying two different types of neural networks in two different approaches to the sensor validation problem. The first approach uses a functional approximation neural network as part of a nonlinear observer in a model-based approach to analytical redundancy. The second approach uses an auto-associative neural network to perform nonlinear principal component analysis on a set of redundant sensors to provide an estimate for a single failed sensor. The approaches are demonstrated using a nonlinear simulation of a turbofan engine. The fault detection and sensor estimation results are presented and the training of the auto-associative neural network to provide sensor estimates is discussed.

New recursive-least-squares algorithms for nonlinear active control of sound and vibration using neural networks.

PubMed

Bouchard, M

2001-01-01

In recent years, a few articles describing the use of neural networks for nonlinear active control of sound and vibration were published. Using a control structure with two multilayer feedforward neural networks (one as a nonlinear controller and one as a nonlinear plant model), steepest descent algorithms based on two distinct gradient approaches were introduced for the training of the controller network. The two gradient approaches were sometimes called the filtered-x approach and the adjoint approach. Some recursive-least-squares algorithms were also introduced, using the adjoint approach. In this paper, an heuristic procedure is introduced for the development of recursive-least-squares algorithms based on the filtered-x and the adjoint gradient approaches. This leads to the development of new recursive-least-squares algorithms for the training of the controller neural network in the two networks structure. These new algorithms produce a better convergence performance than previously published algorithms. Differences in the performance of algorithms using the filtered-x and the adjoint gradient approaches are discussed in the paper. The computational load of the algorithms discussed in the paper is evaluated for multichannel systems of nonlinear active control. Simulation results are presented to compare the convergence performance of the algorithms, showing the convergence gain provided by the new algorithms.

Multi-objective optimisation of wastewater treatment plant control to reduce greenhouse gas emissions.

PubMed

Sweetapple, Christine; Fu, Guangtao; Butler, David

2014-05-15

This study investigates the potential of control strategy optimisation for the reduction of operational greenhouse gas emissions from wastewater treatment in a cost-effective manner, and demonstrates that significant improvements can be realised. A multi-objective evolutionary algorithm, NSGA-II, is used to derive sets of Pareto optimal operational and control parameter values for an activated sludge wastewater treatment plant, with objectives including minimisation of greenhouse gas emissions, operational costs and effluent pollutant concentrations, subject to legislative compliance. Different problem formulations are explored, to identify the most effective approach to emissions reduction, and the sets of optimal solutions enable identification of trade-offs between conflicting objectives. It is found that multi-objective optimisation can facilitate a significant reduction in greenhouse gas emissions without the need for plant redesign or modification of the control strategy layout, but there are trade-offs to consider: most importantly, if operational costs are not to be increased, reduction of greenhouse gas emissions is likely to incur an increase in effluent ammonia and total nitrogen concentrations. Design of control strategies for a high effluent quality and low costs alone is likely to result in an inadvertent increase in greenhouse gas emissions, so it is of key importance that effects on emissions are considered in control strategy development and optimisation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Optimisation of phase ratio in the triple jump using computer simulation.

PubMed

Allen, Sam J; King, Mark A; Yeadon, M R Fred

2016-04-01

The triple jump is an athletic event comprising three phases in which the optimal proportion of each phase to the total distance jumped, termed the phase ratio, is unknown. This study used a whole-body torque-driven computer simulation model of all three phases of the triple jump to investigate optimal technique. The technique of the simulation model was optimised by varying torque generator activation parameters using a Genetic Algorithm in order to maximise total jump distance, resulting in a hop-dominated technique (35.7%:30.8%:33.6%) and a distance of 14.05m. Optimisations were then run with penalties forcing the model to adopt hop and jump phases of 33%, 34%, 35%, 36%, and 37% of the optimised distance, resulting in total distances of: 13.79m, 13.87m, 13.95m, 14.05m, and 14.02m; and 14.01m, 14.02m, 13.97m, 13.84m, and 13.67m respectively. These results indicate that in this subject-specific case there is a plateau in optimum technique encompassing balanced and hop-dominated techniques, but that a jump-dominated technique is associated with a decrease in performance. Hop-dominated techniques are associated with higher forces than jump-dominated techniques; therefore optimal phase ratio may be related to a combination of strength and approach velocity. Copyright © 2016 Elsevier B.V. All rights reserved.

Predicting emergency coronary artery bypass graft following PCI: application of a computational model to refer patients to hospitals with and without onsite surgical backup

PubMed Central

Syed, Zeeshan; Moscucci, Mauro; Share, David; Gurm, Hitinder S

2015-01-01

Background Clinical tools to stratify patients for emergency coronary artery bypass graft (ECABG) after percutaneous coronary intervention (PCI) create the opportunity to selectively assign patients undergoing procedures to hospitals with and without onsite surgical facilities for dealing with potential complications while balancing load across providers. The goal of our study was to investigate the feasibility of a computational model directly optimised for cohort-level performance to predict ECABG in PCI patients for this application. Methods Blue Cross Blue Shield of Michigan Cardiovascular Consortium registry data with 69 pre-procedural and angiographic risk variables from 68 022 PCI procedures in 2004–2007 were used to develop a support vector machine (SVM) model for ECABG. The SVM model was optimised for the area under the receiver operating characteristic curve (AUROC) at the level of the training cohort and validated on 42 310 PCI procedures performed in 2008–2009. Results There were 87 cases of ECABG (0.21%) in the validation cohort. The SVM model achieved an AUROC of 0.81 (95% CI 0.76 to 0.86). Patients in the predicted top decile were at a significantly increased risk relative to the remaining patients (OR 9.74, 95% CI 6.39 to 14.85, p<0.001) for ECABG. The SVM model optimised for the AUROC on the training cohort significantly improved discrimination, net reclassification and calibration over logistic regression and traditional SVM classification optimised for univariate performance. Conclusions Computational risk stratification directly optimising cohort-level performance holds the potential of high levels of discrimination for ECABG following PCI. This approach has value in selectively referring PCI patients to hospitals with and without onsite surgery. PMID:26688738

Sequential projection pursuit for optimised vibration-based damage detection in an experimental wind turbine blade

NASA Astrophysics Data System (ADS)

Hoell, Simon; Omenzetter, Piotr

2018-02-01

To advance the concept of smart structures in large systems, such as wind turbines (WTs), it is desirable to be able to detect structural damage early while using minimal instrumentation. Data-driven vibration-based damage detection methods can be competitive in that respect because global vibrational responses encompass the entire structure. Multivariate damage sensitive features (DSFs) extracted from acceleration responses enable to detect changes in a structure via statistical methods. However, even though such DSFs contain information about the structural state, they may not be optimised for the damage detection task. This paper addresses the shortcoming by exploring a DSF projection technique specialised for statistical structural damage detection. High dimensional initial DSFs are projected onto a low-dimensional space for improved damage detection performance and simultaneous computational burden reduction. The technique is based on sequential projection pursuit where the projection vectors are optimised one by one using an advanced evolutionary strategy. The approach is applied to laboratory experiments with a small-scale WT blade under wind-like excitations. Autocorrelation function coefficients calculated from acceleration signals are employed as DSFs. The optimal numbers of projection vectors are identified with the help of a fast forward selection procedure. To benchmark the proposed method, selections of original DSFs as well as principal component analysis scores from these features are additionally investigated. The optimised DSFs are tested for damage detection on previously unseen data from the healthy state and a wide range of damage scenarios. It is demonstrated that using selected subsets of the initial and transformed DSFs improves damage detectability compared to the full set of features. Furthermore, superior results can be achieved by projecting autocorrelation coefficients onto just a single optimised projection vector.

Improving Vector Evaluated Particle Swarm Optimisation by Incorporating Nondominated Solutions

PubMed Central

Lim, Kian Sheng; Ibrahim, Zuwairie; Buyamin, Salinda; Ahmad, Anita; Naim, Faradila; Ghazali, Kamarul Hawari; Mokhtar, Norrima

2013-01-01

The Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective optimisation problems. This algorithm optimises one objective using a swarm of particles where their movements are guided by the best solution found by another swarm. However, the best solution of a swarm is only updated when a newly generated solution has better fitness than the best solution at the objective function optimised by that swarm, yielding poor solutions for the multiobjective optimisation problems. Thus, an improved Vector Evaluated Particle Swarm Optimisation algorithm is introduced by incorporating the nondominated solutions as the guidance for a swarm rather than using the best solution from another swarm. In this paper, the performance of improved Vector Evaluated Particle Swarm Optimisation algorithm is investigated using performance measures such as the number of nondominated solutions found, the generational distance, the spread, and the hypervolume. The results suggest that the improved Vector Evaluated Particle Swarm Optimisation algorithm has impressive performance compared with the conventional Vector Evaluated Particle Swarm Optimisation algorithm. PMID:23737718

Improving Vector Evaluated Particle Swarm Optimisation by incorporating nondominated solutions.

PubMed

Lim, Kian Sheng; Ibrahim, Zuwairie; Buyamin, Salinda; Ahmad, Anita; Naim, Faradila; Ghazali, Kamarul Hawari; Mokhtar, Norrima

2013-01-01

The Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective optimisation problems. This algorithm optimises one objective using a swarm of particles where their movements are guided by the best solution found by another swarm. However, the best solution of a swarm is only updated when a newly generated solution has better fitness than the best solution at the objective function optimised by that swarm, yielding poor solutions for the multiobjective optimisation problems. Thus, an improved Vector Evaluated Particle Swarm Optimisation algorithm is introduced by incorporating the nondominated solutions as the guidance for a swarm rather than using the best solution from another swarm. In this paper, the performance of improved Vector Evaluated Particle Swarm Optimisation algorithm is investigated using performance measures such as the number of nondominated solutions found, the generational distance, the spread, and the hypervolume. The results suggest that the improved Vector Evaluated Particle Swarm Optimisation algorithm has impressive performance compared with the conventional Vector Evaluated Particle Swarm Optimisation algorithm.

Nonlinear normal modes in electrodynamic systems: A nonperturbative approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kudrin, A. V., E-mail: kud@rf.unn.ru; Kudrina, O. A.; Petrov, E. Yu.

2016-06-15

We consider electromagnetic nonlinear normal modes in cylindrical cavity resonators filled with a nonlinear nondispersive medium. The key feature of the analysis is that exact analytic solutions of the nonlinear field equations are employed to study the mode properties in detail. Based on such a nonperturbative approach, we rigorously prove that the total energy of free nonlinear oscillations in a distributed conservative system, such as that considered in our work, can exactly coincide with the sum of energies of the normal modes of the system. This fact implies that the energy orthogonality property, which has so far been known tomore » hold only for linear oscillations and fields, can also be observed in a nonlinear oscillatory system.« less

Nonlinear Analysis for High-temperature Composites: Turbine Blades/vanes

NASA Technical Reports Server (NTRS)

Hopkins, D. A.; Chamis, C. C.

1984-01-01

An integrated approach to nonlinear analysis of high-temperature composites in turbine blade/vane applications is presented. The overall strategy of this approach and the key elements comprising this approach are summarized. Preliminary results for a tungsten-fiber-reinforced superalloy (TFRS) composite are discussed.

Volterra Series Approach for Nonlinear Aeroelastic Response of 2-D Lifting Surfaces

NASA Technical Reports Server (NTRS)

Silva, Walter A.; Marzocca, Piergiovanni; Librescu, Liviu

2001-01-01

The problem of the determination of the subcritical aeroelastic response and flutter instability of nonlinear two-dimensional lifting surfaces in an incompressible flow-field via Volterra series approach is addressed. The related aeroelastic governing equations are based upon the inclusion of structural nonlinearities, of the linear unsteady aerodynamics and consideration of an arbitrary time-dependent external pressure pulse. Unsteady aeroelastic nonlinear kernels are determined, and based on these, frequency and time histories of the subcritical aeroelastic response are obtained, and in this context the influence of geometric nonlinearities is emphasized. Conclusions and results displaying the implications of the considered effects are supplied.

Kurtosis Approach Nonlinear Blind Source Separation

NASA Technical Reports Server (NTRS)

Duong, Vu A.; Stubbemd, Allen R.

2005-01-01

In this paper, we introduce a new algorithm for blind source signal separation for post-nonlinear mixtures. The mixtures are assumed to be linearly mixed from unknown sources first and then distorted by memoryless nonlinear functions. The nonlinear functions are assumed to be smooth and can be approximated by polynomials. Both the coefficients of the unknown mixing matrix and the coefficients of the approximated polynomials are estimated by the gradient descent method conditional on the higher order statistical requirements. The results of simulation experiments presented in this paper demonstrate the validity and usefulness of our approach for nonlinear blind source signal separation Keywords: Independent Component Analysis, Kurtosis, Higher order statistics.

A Locally Modal B-Spline Based Full-Vector Finite-Element Method with PML for Nonlinear and Lossy Plasmonic Waveguide

NASA Astrophysics Data System (ADS)

Karimi, Hossein; Nikmehr, Saeid; Khodapanah, Ehsan

2016-09-01

In this paper, we develop a B-spline finite-element method (FEM) based on a locally modal wave propagation with anisotropic perfectly matched layers (PMLs), for the first time, to simulate nonlinear and lossy plasmonic waveguides. Conventional approaches like beam propagation method, inherently omit the wave spectrum and do not provide physical insight into nonlinear modes especially in the plasmonic applications, where nonlinear modes are constructed by linear modes with very close propagation constant quantities. Our locally modal B-spline finite element method (LMBS-FEM) does not suffer from the weakness of the conventional approaches. To validate our method, first, propagation of wave for various kinds of linear, nonlinear, lossless and lossy materials of metal-insulator plasmonic structures are simulated using LMBS-FEM in MATLAB and the comparisons are made with FEM-BPM module of COMSOL Multiphysics simulator and B-spline finite-element finite-difference wide angle beam propagation method (BSFEFD-WABPM). The comparisons show that not only our developed numerical approach is computationally more accurate and efficient than conventional approaches but also it provides physical insight into the nonlinear nature of the propagation modes.

Predictive models reduce talent development costs in female gymnastics.

PubMed

Pion, Johan; Hohmann, Andreas; Liu, Tianbiao; Lenoir, Matthieu; Segers, Veerle

2017-04-01

This retrospective study focuses on the comparison of different predictive models based on the results of a talent identification test battery for female gymnasts. We studied to what extent these models have the potential to optimise selection procedures, and at the same time reduce talent development costs in female artistic gymnastics. The dropout rate of 243 female elite gymnasts was investigated, 5 years past talent selection, using linear (discriminant analysis) and non-linear predictive models (Kohonen feature maps and multilayer perceptron). The coaches classified 51.9% of the participants correct. Discriminant analysis improved the correct classification to 71.6% while the non-linear technique of Kohonen feature maps reached 73.7% correctness. Application of the multilayer perceptron even classified 79.8% of the gymnasts correctly. The combination of different predictive models for talent selection can avoid deselection of high-potential female gymnasts. The selection procedure based upon the different statistical analyses results in decrease of 33.3% of cost because the pool of selected athletes can be reduced to 92 instead of 138 gymnasts (as selected by the coaches). Reduction of the costs allows the limited resources to be fully invested in the high-potential athletes.

Joint location, inventory, and preservation decisions for non-instantaneous deterioration items under delay in payments

NASA Astrophysics Data System (ADS)

Tsao, Yu-Chung

2016-02-01

This study models a joint location, inventory and preservation decision-making problem for non-instantaneous deteriorating items under delay in payments. An outside supplier provides a credit period to the wholesaler which has a distribution system with distribution centres (DCs). The non-instantaneous deteriorating means no deterioration occurs in the earlier stage, which is very useful for items such as fresh food and fruits. This paper also considers that the deteriorating rate will decrease and the reservation cost will increase as the preservation effort increases. Therefore, how much preservation effort should be made is a crucial decision. The objective of this paper is to determine the optimal locations and number of DCs, the optimal replenishment cycle time at DCs, and the optimal preservation effort simultaneously such that the total network profit is maximised. The problem is formulated as piecewise nonlinear functions and has three different cases. Algorithms based on piecewise nonlinear optimisation are provided to solve the joint location and inventory problem for all cases. Computational analysis illustrates the solution procedures and the impacts of the related parameters on decisions and profits. The results of this study can serve as references for business managers or administrators.

Multi-objective ACO algorithms to minimise the makespan and the total rejection cost on BPMs with arbitrary job weights

NASA Astrophysics Data System (ADS)

Jia, Zhao-hong; Pei, Ming-li; Leung, Joseph Y.-T.

2017-12-01

In this paper, we investigate the batch-scheduling problem with rejection on parallel machines with non-identical job sizes and arbitrary job-rejected weights. If a job is rejected, the corresponding penalty has to be paid. Our objective is to minimise the makespan of the processed jobs and the total rejection cost of the rejected jobs. Based on the selected multi-objective optimisation approaches, two problems, P1 and P2, are considered. In P1, the two objectives are linearly combined into one single objective. In P2, the two objectives are simultaneously minimised and the Pareto non-dominated solution set is to be found. Based on the ant colony optimisation (ACO), two algorithms, called LACO and PACO, are proposed to address the two problems, respectively. Two different objective-oriented pheromone matrices and heuristic information are designed. Additionally, a local optimisation algorithm is adopted to improve the solution quality. Finally, simulated experiments are conducted, and the comparative results verify the effectiveness and efficiency of the proposed algorithms, especially on large-scale instances.

Optimisation of flavour ester biosynthesis in an aqueous system of coconut cream and fusel oil catalysed by lipase.

PubMed

Sun, Jingcan; Yu, Bin; Curran, Philip; Liu, Shao-Quan

2012-12-15

Coconut cream and fusel oil, two low-cost natural substances, were used as starting materials for the biosynthesis of flavour-active octanoic acid esters (ethyl-, butyl-, isobutyl- and (iso)amyl octanoate) using lipase Palatase as the biocatalyst. The Taguchi design method was used for the first time to optimize the biosynthesis of esters by a lipase in an aqueous system of coconut cream and fusel oil. Temperature, time and enzyme amount were found to be statistically significant factors and the optimal conditions were determined to be as follows: temperature 30°C, fusel oil concentration 9% (v/w), reaction time 24h, pH 6.2 and enzyme amount 0.26 g. Under the optimised conditions, a yield of 14.25mg/g (based on cream weight) and signal-to-noise (S/N) ratio of 23.07 dB were obtained. The results indicate that the Taguchi design method was an efficient and systematic approach to the optimisation of lipase-catalysed biological processes. Copyright © 2012 Elsevier Ltd. All rights reserved.

A catalyst layer optimisation approach using electrochemical impedance spectroscopy for PEM fuel cells operated with pyrolysed transition metal-N-C catalysts

NASA Astrophysics Data System (ADS)

Malko, Daniel; Lopes, Thiago; Ticianelli, Edson A.; Kucernak, Anthony

2016-08-01

The effect of the ionomer to carbon (I/C) ratio on the performance of single cell polymer electrolyte fuel cells is investigated for three different types of non-precious metal cathodic catalysts. Polarisation curves as well as impedance spectra are recorded at different potentials in the presence of argon or oxygen at the cathode and hydrogen at the anode. It is found that a optimised ionomer content is a key factor for improving the performance of the catalyst. Non-optimal ionomer loading can be assessed by two different factors from the impedance spectra. Hence this observation could be used as a diagnostic element to determine the ideal ionomer content and distribution in newly developed catalyst-electrodes. An electrode morphology based on the presence of inhomogeneous resistance distribution within the porous structure is suggested to explain the observed phenomena. The back-pressure and relative humidity effect on this feature is also investigated and supports the above hypothesis. We give a simple flowchart to aid optimisation of electrodes with the minimum number of trials.

Optimisation of ultrasound-assisted reverse micelles dispersive liquid-liquid micro-extraction by Box-Behnken design for determination of acetoin in butter followed by high performance liquid chromatography.

PubMed

Roosta, Mostafa; Ghaedi, Mehrorang; Daneshfar, Ali

2014-10-15

A novel approach, ultrasound-assisted reverse micelles dispersive liquid-liquid microextraction (USA-RM-DLLME) followed by high performance liquid chromatography (HPLC) was developed for selective determination of acetoin in butter. The melted butter sample was diluted and homogenised by n-hexane and Triton X-100, respectively. Subsequently, 400μL of distilled water was added and the microextraction was accelerated by 4min sonication. After 8.5min of centrifugation, sedimented phase (surfactant-rich phase) was withdrawn by microsyringe and injected into the HPLC system for analysis. The influence of effective variables was optimised using Box-Behnken design (BBD) combined with desirability function (DF). Under optimised experimental conditions, the calibration graph was linear over the range of 0.6-200mgL(-1). The detection limit of method was 0.2mgL(-1) and coefficient of determination was 0.9992. The relative standard deviations (RSDs) were less than 5% (n=5) while the recoveries were in the range of 93.9-107.8%. Copyright © 2014. Published by Elsevier Ltd.

Spoken language identification based on the enhanced self-adjusting extreme learning machine approach.

PubMed

Albadr, Musatafa Abbas Abbood; Tiun, Sabrina; Al-Dhief, Fahad Taha; Sammour, Mahmoud A M

2018-01-01

Spoken Language Identification (LID) is the process of determining and classifying natural language from a given content and dataset. Typically, data must be processed to extract useful features to perform LID. The extracting features for LID, based on literature, is a mature process where the standard features for LID have already been developed using Mel-Frequency Cepstral Coefficients (MFCC), Shifted Delta Cepstral (SDC), the Gaussian Mixture Model (GMM) and ending with the i-vector based framework. However, the process of learning based on extract features remains to be improved (i.e. optimised) to capture all embedded knowledge on the extracted features. The Extreme Learning Machine (ELM) is an effective learning model used to perform classification and regression analysis and is extremely useful to train a single hidden layer neural network. Nevertheless, the learning process of this model is not entirely effective (i.e. optimised) due to the random selection of weights within the input hidden layer. In this study, the ELM is selected as a learning model for LID based on standard feature extraction. One of the optimisation approaches of ELM, the Self-Adjusting Extreme Learning Machine (SA-ELM) is selected as the benchmark and improved by altering the selection phase of the optimisation process. The selection process is performed incorporating both the Split-Ratio and K-Tournament methods, the improved SA-ELM is named Enhanced Self-Adjusting Extreme Learning Machine (ESA-ELM). The results are generated based on LID with the datasets created from eight different languages. The results of the study showed excellent superiority relating to the performance of the Enhanced Self-Adjusting Extreme Learning Machine LID (ESA-ELM LID) compared with the SA-ELM LID, with ESA-ELM LID achieving an accuracy of 96.25%, as compared to the accuracy of SA-ELM LID of only 95.00%.

Spoken language identification based on the enhanced self-adjusting extreme learning machine approach

PubMed Central

Tiun, Sabrina; AL-Dhief, Fahad Taha; Sammour, Mahmoud A. M.

2018-01-01

Spoken Language Identification (LID) is the process of determining and classifying natural language from a given content and dataset. Typically, data must be processed to extract useful features to perform LID. The extracting features for LID, based on literature, is a mature process where the standard features for LID have already been developed using Mel-Frequency Cepstral Coefficients (MFCC), Shifted Delta Cepstral (SDC), the Gaussian Mixture Model (GMM) and ending with the i-vector based framework. However, the process of learning based on extract features remains to be improved (i.e. optimised) to capture all embedded knowledge on the extracted features. The Extreme Learning Machine (ELM) is an effective learning model used to perform classification and regression analysis and is extremely useful to train a single hidden layer neural network. Nevertheless, the learning process of this model is not entirely effective (i.e. optimised) due to the random selection of weights within the input hidden layer. In this study, the ELM is selected as a learning model for LID based on standard feature extraction. One of the optimisation approaches of ELM, the Self-Adjusting Extreme Learning Machine (SA-ELM) is selected as the benchmark and improved by altering the selection phase of the optimisation process. The selection process is performed incorporating both the Split-Ratio and K-Tournament methods, the improved SA-ELM is named Enhanced Self-Adjusting Extreme Learning Machine (ESA-ELM). The results are generated based on LID with the datasets created from eight different languages. The results of the study showed excellent superiority relating to the performance of the Enhanced Self-Adjusting Extreme Learning Machine LID (ESA-ELM LID) compared with the SA-ELM LID, with ESA-ELM LID achieving an accuracy of 96.25%, as compared to the accuracy of SA-ELM LID of only 95.00%. PMID:29672546

The AOLI Non-Linear Curvature Wavefront Sensor: High sensitivity reconstruction for low-order AO

NASA Astrophysics Data System (ADS)

Crass, Jonathan; King, David; Mackay, Craig

2013-12-01

Many adaptive optics (AO) systems in use today require bright reference objects to determine the effects of atmospheric distortions on incoming wavefronts. This requirement is because Shack Hartmann wavefront sensors (SHWFS) distribute incoming light from reference objects into a large number of sub-apertures. Bright natural reference objects occur infrequently across the sky leading to the use of laser guide stars which add complexity to wavefront measurement systems. The non-linear curvature wavefront sensor as described by Guyon et al. has been shown to offer a significant increase in sensitivity when compared to a SHWFS. This facilitates much greater sky coverage using natural guide stars alone. This paper describes the current status of the non-linear curvature wavefront sensor being developed as part of an adaptive optics system for the Adaptive Optics Lucky Imager (AOLI) project. The sensor comprises two photon-counting EMCCD detectors from E2V Technologies, recording intensity at four near-pupil planes. These images are used with a reconstruction algorithm to determine the phase correction to be applied by an ALPAO 241-element deformable mirror. The overall system is intended to provide low-order correction for a Lucky Imaging based multi CCD imaging camera. We present the current optical design of the instrument including methods to minimise inherent optical effects, principally chromaticity. Wavefront reconstruction methods are discussed and strategies for their optimisation to run at the required real-time speeds are introduced. Finally, we discuss laboratory work with a demonstrator setup of the system.

Modal Substructuring of Geometrically Nonlinear Finite-Element Models

DOE PAGES

Kuether, Robert J.; Allen, Matthew S.; Hollkamp, Joseph J.

2015-12-21

The efficiency of a modal substructuring method depends on the component modes used to reduce each subcomponent model. Methods such as Craig–Bampton have been used extensively to reduce linear finite-element models with thousands or even millions of degrees of freedom down orders of magnitude while maintaining acceptable accuracy. A novel reduction method is proposed here for geometrically nonlinear finite-element models using the fixed-interface and constraint modes of the linearized system to reduce each subcomponent model. The geometric nonlinearity requires an additional cubic and quadratic polynomial function in the modal equations, and the nonlinear stiffness coefficients are determined by applying amore » series of static loads and using the finite-element code to compute the response. The geometrically nonlinear, reduced modal equations for each subcomponent are then coupled by satisfying compatibility and force equilibrium. This modal substructuring approach is an extension of the Craig–Bampton method and is readily applied to geometrically nonlinear models built directly within commercial finite-element packages. The efficiency of this new approach is demonstrated on two example problems: one that couples two geometrically nonlinear beams at a shared rotational degree of freedom, and another that couples an axial spring element to the axial degree of freedom of a geometrically nonlinear beam. The nonlinear normal modes of the assembled models are compared with those of a truth model to assess the accuracy of the novel modal substructuring approach.« less

Modal Substructuring of Geometrically Nonlinear Finite-Element Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuether, Robert J.; Allen, Matthew S.; Hollkamp, Joseph J.

The efficiency of a modal substructuring method depends on the component modes used to reduce each subcomponent model. Methods such as Craig–Bampton have been used extensively to reduce linear finite-element models with thousands or even millions of degrees of freedom down orders of magnitude while maintaining acceptable accuracy. A novel reduction method is proposed here for geometrically nonlinear finite-element models using the fixed-interface and constraint modes of the linearized system to reduce each subcomponent model. The geometric nonlinearity requires an additional cubic and quadratic polynomial function in the modal equations, and the nonlinear stiffness coefficients are determined by applying amore » series of static loads and using the finite-element code to compute the response. The geometrically nonlinear, reduced modal equations for each subcomponent are then coupled by satisfying compatibility and force equilibrium. This modal substructuring approach is an extension of the Craig–Bampton method and is readily applied to geometrically nonlinear models built directly within commercial finite-element packages. The efficiency of this new approach is demonstrated on two example problems: one that couples two geometrically nonlinear beams at a shared rotational degree of freedom, and another that couples an axial spring element to the axial degree of freedom of a geometrically nonlinear beam. The nonlinear normal modes of the assembled models are compared with those of a truth model to assess the accuracy of the novel modal substructuring approach.« less

Analysis of dynamic cerebral autoregulation using an ARX model based on arterial blood pressure and middle cerebral artery velocity simulation.

PubMed

Liu, Y; Allen, R

2002-09-01

The study aimed to model the cerebrovascular system, using a linear ARX model based on data simulated by a comprehensive physiological model, and to assess the range of applicability of linear parametric models. Arterial blood pressure (ABP) and middle cerebral arterial blood flow velocity (MCAV) were measured from 11 subjects non-invasively, following step changes in ABP, using the thigh cuff technique. By optimising parameters associated with autoregulation, using a non-linear optimisation technique, the physiological model showed a good performance (r=0.83+/-0.14) in fitting MCAV. An additional five sets of measured ABP of length 236+/-154 s were acquired from a subject at rest. These were normalised and rescaled to coefficients of variation (CV=SD/mean) of 2% and 10% for model comparisons. Randomly generated Gaussian noise with standard deviation (SD) from 1% to 5% was added to both ABP and physiologically simulated MCAV (SMCAV), with 'normal' and 'impaired' cerebral autoregulation, to simulate the real measurement conditions. ABP and SMCAV were fitted by ARX modelling, and cerebral autoregulation was quantified by a 5 s recovery percentage R5% of the step responses of the ARX models. The study suggests that cerebral autoregulation can be assessed by computing the R5% of the step response of an ARX model of appropriate order, even when measurement noise is considerable.

Influence of the Size of Cohorts in Adaptive Design for Nonlinear Mixed Effects Models: An Evaluation by Simulation for a Pharmacokinetic and Pharmacodynamic Model for a Biomarker in Oncology

PubMed Central

Lestini, Giulia; Dumont, Cyrielle; Mentré, France

2015-01-01

Purpose In this study we aimed to evaluate adaptive designs (ADs) by clinical trial simulation for a pharmacokinetic-pharmacodynamic model in oncology and to compare them with one-stage designs, i.e. when no adaptation is performed, using wrong prior parameters. Methods We evaluated two one-stage designs, ξ0 and ξ*, optimised for prior and true population parameters, Ψ0 and Ψ*, and several ADs (two-, three- and five-stage). All designs had 50 patients. For ADs, the first cohort design was ξ0. The next cohort design was optimised using prior information updated from the previous cohort. Optimal design was based on the determinant of the Fisher information matrix using PFIM. Design evaluation was performed by clinical trial simulations using data simulated from Ψ*. Results Estimation results of two-stage ADs and ξ* were close and much better than those obtained with ξ0. The balanced two-stage AD performed better than two-stage ADs with different cohort sizes. Three-and five-stage ADs were better than two-stage with small first cohort, but not better than the balanced two-stage design. Conclusions Two-stage ADs are useful when prior parameters are unreliable. In case of small first cohort, more adaptations are needed but these designs are complex to implement. PMID:26123680

Influence of the Size of Cohorts in Adaptive Design for Nonlinear Mixed Effects Models: An Evaluation by Simulation for a Pharmacokinetic and Pharmacodynamic Model for a Biomarker in Oncology.

PubMed

Lestini, Giulia; Dumont, Cyrielle; Mentré, France

2015-10-01

In this study we aimed to evaluate adaptive designs (ADs) by clinical trial simulation for a pharmacokinetic-pharmacodynamic model in oncology and to compare them with one-stage designs, i.e., when no adaptation is performed, using wrong prior parameters. We evaluated two one-stage designs, ξ0 and ξ*, optimised for prior and true population parameters, Ψ0 and Ψ*, and several ADs (two-, three- and five-stage). All designs had 50 patients. For ADs, the first cohort design was ξ0. The next cohort design was optimised using prior information updated from the previous cohort. Optimal design was based on the determinant of the Fisher information matrix using PFIM. Design evaluation was performed by clinical trial simulations using data simulated from Ψ*. Estimation results of two-stage ADs and ξ * were close and much better than those obtained with ξ 0. The balanced two-stage AD performed better than two-stage ADs with different cohort sizes. Three- and five-stage ADs were better than two-stage with small first cohort, but not better than the balanced two-stage design. Two-stage ADs are useful when prior parameters are unreliable. In case of small first cohort, more adaptations are needed but these designs are complex to implement.

An approach to optimised control of HVAC systems in indoor swimming pools

NASA Astrophysics Data System (ADS)

Ribeiro, Eliseu M. A.; Jorge, Humberto M. M.; Quintela, Divo A. A.

2016-04-01

Indoor swimming pools are recognised as having a high level of energy consumption and present a great potential for energy saving. The energy is spent in several ways such as evaporation heat loss from the pool, high rates of ventilation required to guarantee the indoor air quality, and ambient temperatures with expressive values (typically 28-30°C) required to maintain conditions of comfort. This paper presents an approach to optimising control of heat ventilation and air conditioning systems that could be implemented in a building energy management system. It is easily adapted to any kind of pool and results in significant energy consumption reduction. The development and validation of the control model were carried out with a building thermal simulation software. The use of this control model in the case study building could reduce the energy efficiency index by 7.14 points (7.4% of total) which adds up to an energy cost saving of 15,609€ (7.5% of total).

Novel Approach on the Optimisation of Mid-Course Corrections Along Interplanetary Trajectories

NASA Astrophysics Data System (ADS)

Iorfida, Elisabetta; Palmer, Phil; Roberts, Mark

The primer vector theory, firstly proposed by Lawden, defines a set of necessary conditions to characterise whether an impulsive thrust trajectory is optimal with respect to propellant usage, within a two-body problem context. If the conditions are not satisfied, one or more potential intermediate impulses are performed along the transfer arc, in order to lower the overall cost. The method is based on the propagation of the state transition matrix and on the solution of a boundary value problem, which leads to a mathematical and computational complexity.In this paper, a different approach is introduced. It is based on a polar coordinates transformation of the primer vector which allows the decoupling between its in-plane and out-of-plane components. The out-of-plane component is solved analytically while for the in-plane ones a Hamiltonian approximation is made.The novel procedure reduces the mathematical complexity and the computational cost of Lawden's problem and gives also a different perspective about the optimisation of a transfer trajectory.

Geo-information processing service composition for concurrent tasks: A QoS-aware game theory approach

NASA Astrophysics Data System (ADS)

Li, Haifeng; Zhu, Qing; Yang, Xiaoxia; Xu, Linrong

2012-10-01

Typical characteristics of remote sensing applications are concurrent tasks, such as those found in disaster rapid response. The existing composition approach to geographical information processing service chain, searches for an optimisation solution and is what can be deemed a "selfish" way. This way leads to problems of conflict amongst concurrent tasks and decreases the performance of all service chains. In this study, a non-cooperative game-based mathematical model to analyse the competitive relationships between tasks, is proposed. A best response function is used, to assure each task maintains utility optimisation by considering composition strategies of other tasks and quantifying conflicts between tasks. Based on this, an iterative algorithm that converges to Nash equilibrium is presented, the aim being to provide good convergence and maximise the utilisation of all tasks under concurrent task conditions. Theoretical analyses and experiments showed that the newly proposed method, when compared to existing service composition methods, has better practical utility in all tasks.

Nonlinear viscoelastic characterization of human vocal fold tissues under large-amplitude oscillatory shear (LAOS)

PubMed Central

Chan, Roger W.

2018-01-01

Viscoelastic shear properties of human vocal fold tissues were previously quantified by the shear moduli (G′ and G″). Yet these small-strain linear measures were unable to describe any nonlinear tissue behavior. This study attempted to characterize the nonlinear viscoelastic response of the vocal fold lamina propria under large-amplitude oscillatory shear (LAOS) with a stress decomposition approach. Human vocal fold cover and vocal ligament specimens from eight subjects were subjected to LAOS rheometric testing with a simple-shear rheometer. The empirical total stress response was decomposed into elastic and viscous stress components, based on odd-integer harmonic decomposition approach with Fourier transform. Nonlinear viscoelastic measures derived from the decomposition were plotted in Pipkin space and as rheological fingerprints to observe the onset of nonlinearity and the type of nonlinear behavior. Results showed that both the vocal fold cover and the vocal ligament experienced intercycle strain softening, intracycle strain stiffening, as well as shear thinning both intercycle and intracycle. The vocal ligament appeared to demonstrate an earlier onset of nonlinearity at phonatory frequencies, and higher sensitivity to changes in frequency and strain. In summary, the stress decomposition approach provided much better insights into the nonlinear viscoelastic behavior of the vocal fold lamina propria than the traditional linear measures. PMID:29780189

Nonlinear viscoelastic characterization of human vocal fold tissues under large-amplitude oscillatory shear (LAOS).

PubMed

Chan, Roger W

2018-05-01

Viscoelastic shear properties of human vocal fold tissues were previously quantified by the shear moduli ( G' and G″ ). Yet these small-strain linear measures were unable to describe any nonlinear tissue behavior. This study attempted to characterize the nonlinear viscoelastic response of the vocal fold lamina propria under large-amplitude oscillatory shear (LAOS) with a stress decomposition approach. Human vocal fold cover and vocal ligament specimens from eight subjects were subjected to LAOS rheometric testing with a simple-shear rheometer. The empirical total stress response was decomposed into elastic and viscous stress components, based on odd-integer harmonic decomposition approach with Fourier transform. Nonlinear viscoelastic measures derived from the decomposition were plotted in Pipkin space and as rheological fingerprints to observe the onset of nonlinearity and the type of nonlinear behavior. Results showed that both the vocal fold cover and the vocal ligament experienced intercycle strain softening, intracycle strain stiffening, as well as shear thinning both intercycle and intracycle. The vocal ligament appeared to demonstrate an earlier onset of nonlinearity at phonatory frequencies, and higher sensitivity to changes in frequency and strain. In summary, the stress decomposition approach provided much better insights into the nonlinear viscoelastic behavior of the vocal fold lamina propria than the traditional linear measures.

Developing a local least-squares support vector machines-based neuro-fuzzy model for nonlinear and chaotic time series prediction.

PubMed

Miranian, A; Abdollahzade, M

2013-02-01

Local modeling approaches, owing to their ability to model different operating regimes of nonlinear systems and processes by independent local models, seem appealing for modeling, identification, and prediction applications. In this paper, we propose a local neuro-fuzzy (LNF) approach based on the least-squares support vector machines (LSSVMs). The proposed LNF approach employs LSSVMs, which are powerful in modeling and predicting time series, as local models and uses hierarchical binary tree (HBT) learning algorithm for fast and efficient estimation of its parameters. The HBT algorithm heuristically partitions the input space into smaller subdomains by axis-orthogonal splits. In each partitioning, the validity functions automatically form a unity partition and therefore normalization side effects, e.g., reactivation, are prevented. Integration of LSSVMs into the LNF network as local models, along with the HBT learning algorithm, yield a high-performance approach for modeling and prediction of complex nonlinear time series. The proposed approach is applied to modeling and predictions of different nonlinear and chaotic real-world and hand-designed systems and time series. Analysis of the prediction results and comparisons with recent and old studies demonstrate the promising performance of the proposed LNF approach with the HBT learning algorithm for modeling and prediction of nonlinear and chaotic systems and time series.

Structural stability of nonlinear population dynamics.

PubMed

Cenci, Simone; Saavedra, Serguei

2018-01-01

In population dynamics, the concept of structural stability has been used to quantify the tolerance of a system to environmental perturbations. Yet, measuring the structural stability of nonlinear dynamical systems remains a challenging task. Focusing on the classic Lotka-Volterra dynamics, because of the linearity of the functional response, it has been possible to measure the conditions compatible with a structurally stable system. However, the functional response of biological communities is not always well approximated by deterministic linear functions. Thus, it is unclear the extent to which this linear approach can be generalized to other population dynamics models. Here, we show that the same approach used to investigate the classic Lotka-Volterra dynamics, which is called the structural approach, can be applied to a much larger class of nonlinear models. This class covers a large number of nonlinear functional responses that have been intensively investigated both theoretically and experimentally. We also investigate the applicability of the structural approach to stochastic dynamical systems and we provide a measure of structural stability for finite populations. Overall, we show that the structural approach can provide reliable and tractable information about the qualitative behavior of many nonlinear dynamical systems.

Structural stability of nonlinear population dynamics

NASA Astrophysics Data System (ADS)

Cenci, Simone; Saavedra, Serguei

2018-01-01

In population dynamics, the concept of structural stability has been used to quantify the tolerance of a system to environmental perturbations. Yet, measuring the structural stability of nonlinear dynamical systems remains a challenging task. Focusing on the classic Lotka-Volterra dynamics, because of the linearity of the functional response, it has been possible to measure the conditions compatible with a structurally stable system. However, the functional response of biological communities is not always well approximated by deterministic linear functions. Thus, it is unclear the extent to which this linear approach can be generalized to other population dynamics models. Here, we show that the same approach used to investigate the classic Lotka-Volterra dynamics, which is called the structural approach, can be applied to a much larger class of nonlinear models. This class covers a large number of nonlinear functional responses that have been intensively investigated both theoretically and experimentally. We also investigate the applicability of the structural approach to stochastic dynamical systems and we provide a measure of structural stability for finite populations. Overall, we show that the structural approach can provide reliable and tractable information about the qualitative behavior of many nonlinear dynamical systems.

Design of optimised backstepping controller for the synchronisation of chaotic Colpitts oscillator using shark smell algorithm

NASA Astrophysics Data System (ADS)

Fouladi, Ehsan; Mojallali, Hamed

2018-01-01

In this paper, an adaptive backstepping controller has been tuned to synchronise two chaotic Colpitts oscillators in a master-slave configuration. The parameters of the controller are determined using shark smell optimisation (SSO) algorithm. Numerical results are presented and compared with those of particle swarm optimisation (PSO) algorithm. Simulation results show better performance in terms of accuracy and convergence for the proposed optimised method compared to PSO optimised controller or any non-optimised backstepping controller.

Subsampling for dataset optimisation

NASA Astrophysics Data System (ADS)

Ließ, Mareike

2017-04-01

Soil-landscapes have formed by the interaction of soil-forming factors and pedogenic processes. In modelling these landscapes in their pedodiversity and the underlying processes, a representative unbiased dataset is required. This concerns model input as well as output data. However, very often big datasets are available which are highly heterogeneous and were gathered for various purposes, but not to model a particular process or data space. As a first step, the overall data space and/or landscape section to be modelled needs to be identified including considerations regarding scale and resolution. Then the available dataset needs to be optimised via subsampling to well represent this n-dimensional data space. A couple of well-known sampling designs may be adapted to suit this purpose. The overall approach follows three main strategies: (1) the data space may be condensed and de-correlated by a factor analysis to facilitate the subsampling process. (2) Different methods of pattern recognition serve to structure the n-dimensional data space to be modelled into units which then form the basis for the optimisation of an existing dataset through a sensible selection of samples. Along the way, data units for which there is currently insufficient soil data available may be identified. And (3) random samples from the n-dimensional data space may be replaced by similar samples from the available dataset. While being a presupposition to develop data-driven statistical models, this approach may also help to develop universal process models and identify limitations in existing models.

DIY soundcard based temperature logging system. Part I: design

NASA Astrophysics Data System (ADS)

Nunn, John

2016-11-01

This paper aims to enable schools to make their own low-cost temperature logging instrument and to learn a something about its calibration in the process. This paper describes how a thermistor can be integrated into a simple potential divider circuit which is powered with the sound output of a computer and monitored by the microphone input. The voltage across a fixed resistor is recorded and scaled to convert it into a temperature reading in the range 0-100 °C. The calibration process is described with reference to fixed points and the effects of non-linearity are highlighted. An optimised calibration procedure is described which enables sub degree resolution and a software program was written which makes it possible to log, display and save temperature changes over a user determined period of time.

Inverse constraints for emission fluxes of atmospheric tracers estimated from concentration measurements and Lagrangian transport

NASA Astrophysics Data System (ADS)

Pisso, Ignacio; Patra, Prabir; Breivik, Knut

2015-04-01

Lagrangian transport models based on times series of Eulerian fields provide a computationally affordable way of achieving very high resolution for limited areas and time periods. This makes them especially suitable for the analysis of point-wise measurements of atmospheric tracers. We present an application illustrated with examples of greenhouse gases from anthropogenic emissions in urban areas and biogenic emissions in Japan and of pollutants in the Arctic. We asses the algorithmic complexity of the numerical implementation as well as the use of non-procedural techniques such as Object-Oriented programming. We discuss aspects related to the quantification of uncertainty from prior information in the presence of model error and limited number of observations. The case of non-linear constraints is explored using direct numerical optimisation methods.

Sugeno-Fuzzy Expert System Modeling for Quality Prediction of Non-Contact Machining Process

NASA Astrophysics Data System (ADS)

Sivaraos; Khalim, A. Z.; Salleh, M. S.; Sivakumar, D.; Kadirgama, K.

2018-03-01

Modeling can be categorised into four main domains: prediction, optimisation, estimation and calibration. In this paper, the Takagi-Sugeno-Kang (TSK) fuzzy logic method is examined as a prediction modelling method to investigate the taper quality of laser lathing, which seeks to replace traditional lathe machines with 3D laser lathing in order to achieve the desired cylindrical shape of stock materials. Three design parameters were selected: feed rate, cutting speed and depth of cut. A total of twenty-four experiments were conducted with eight sequential runs and replicated three times. The results were found to be 99% of accuracy rate of the TSK fuzzy predictive model, which suggests that the model is a suitable and practical method for non-linear laser lathing process.

Parameters estimation for reactive transport: A way to test the validity of a reactive model

NASA Astrophysics Data System (ADS)

Aggarwal, Mohit; Cheikh Anta Ndiaye, Mame; Carrayrou, Jérôme

The chemical parameters used in reactive transport models are not known accurately due to the complexity and the heterogeneous conditions of a real domain. We will present an efficient algorithm in order to estimate the chemical parameters using Monte-Carlo method. Monte-Carlo methods are very robust for the optimisation of the highly non-linear mathematical model describing reactive transport. Reactive transport of tributyltin (TBT) through natural quartz sand at seven different pHs is taken as the test case. Our algorithm will be used to estimate the chemical parameters of the sorption of TBT onto the natural quartz sand. By testing and comparing three models of surface complexation, we show that the proposed adsorption model cannot explain the experimental data.

Reconfigurable Flight Control Using Nonlinear Dynamic Inversion with a Special Accelerometer Implementation

NASA Technical Reports Server (NTRS)

Bacon, Barton J.; Ostroff, Aaron J.

2000-01-01

This paper presents an approach to on-line control design for aircraft that have suffered either actuator failure, missing effector surfaces, surface damage, or any combination. The approach is based on a modified version of nonlinear dynamic inversion. The approach does not require a model of the baseline vehicle (effectors at zero deflection), but does require feedback of accelerations and effector positions. Implementation issues are addressed and the method is demonstrated on an advanced tailless aircraft. An experimental simulation analysis tool is used to directly evaluate the nonlinear system's stability robustness.

Silicone rod extraction followed by liquid desorption-large volume injection-programmable temperature vaporiser-gas chromatography-mass spectrometry for trace analysis of priority organic pollutants in environmental water samples.

PubMed

Delgado, Alejandra; Posada-Ureta, Oscar; Olivares, Maitane; Vallejo, Asier; Etxebarria, Nestor

2013-12-15

In this study a priority organic pollutants usually found in environmental water samples were considered to accomplish two extraction and analysis approaches. Among those compounds organochlorine compounds, pesticides, phthalates, phenols and residues of pharmaceutical and personal care products were included. The extraction and analysis steps were based on silicone rod extraction (SR) followed by liquid desorption in combination with large volume injection-programmable temperature vaporiser (LVI-PTV) and gas chromatography-mass spectrometry (GC-MS). Variables affecting the analytical response as a function of the programmable temperature vaporiser (PTV) parameters were firstly optimised following an experimental design approach. The SR extraction and desorption conditions were assessed afterwards, including matrix modification, time extraction, and stripping solvent composition. Subsequently, the possibility of performing membrane enclosed sorptive coating extraction (MESCO) as a modified extraction approach was also evaluated. The optimised method showed low method detection limits (3-35 ng L(-1)), acceptable accuracy (78-114%) and precision values (<13%) for most of the studied analytes regardless of the aqueous matrix. Finally, the developed approach was successfully applied to the determination of target analytes in aqueous environmental matrices including estuarine and wastewater samples. © 2013 Elsevier B.V. All rights reserved.

Wiener-Hammerstein system identification - an evolutionary approach

NASA Astrophysics Data System (ADS)

Naitali, Abdessamad; Giri, Fouad

2016-01-01

The problem of identifying parametric Wiener-Hammerstein (WH) systems is addressed within the evolutionary optimisation context. Specifically, a hybrid culture identification method is developed that involves model structure adaptation using genetic recombination and model parameter learning using particle swarm optimisation. The method enjoys three interesting features: (1) the risk of premature convergence of model parameter estimates to local optima is significantly reduced, due to the constantly maintained diversity of model candidates; (2) no prior knowledge is needed except for upper bounds on the system structure indices; (3) the method is fully autonomous as no interaction is needed with the user during the optimum search process. The performances of the proposed method will be illustrated and compared to alternative methods using a well-established WH benchmark.

Optimisation of Critical Infrastructure Protection: The SiVe Project on Airport Security

NASA Astrophysics Data System (ADS)

Breiing, Marcus; Cole, Mara; D'Avanzo, John; Geiger, Gebhard; Goldner, Sascha; Kuhlmann, Andreas; Lorenz, Claudia; Papproth, Alf; Petzel, Erhard; Schwetje, Oliver

This paper outlines the scientific goals, ongoing work and first results of the SiVe research project on critical infrastructure security. The methodology is generic while pilot studies are chosen from airport security. The outline proceeds in three major steps, (1) building a threat scenario, (2) development of simulation models as scenario refinements, and (3) assessment of alternatives. Advanced techniques of systems analysis and simulation are employed to model relevant airport structures and processes as well as offences. Computer experiments are carried out to compare and optimise alternative solutions. The optimality analyses draw on approaches to quantitative risk assessment recently developed in the operational sciences. To exploit the advantages of the various techniques, an integrated simulation workbench is build up in the project.

High-accuracy power series solutions with arbitrarily large radius of convergence for the fractional nonlinear Schrödinger-type equations

NASA Astrophysics Data System (ADS)

Khawaja, U. Al; Al-Refai, M.; Shchedrin, Gavriil; Carr, Lincoln D.

2018-06-01

Fractional nonlinear differential equations present an interplay between two common and important effective descriptions used to simplify high dimensional or more complicated theories: nonlinearity and fractional derivatives. These effective descriptions thus appear commonly in physical and mathematical modeling. We present a new series method providing systematic controlled accuracy for solutions of fractional nonlinear differential equations, including the fractional nonlinear Schrödinger equation and the fractional nonlinear diffusion equation. The method relies on spatially iterative use of power series expansions. Our approach permits an arbitrarily large radius of convergence and thus solves the typical divergence problem endemic to power series approaches. In the specific case of the fractional nonlinear Schrödinger equation we find fractional generalizations of cnoidal waves of Jacobi elliptic functions as well as a fractional bright soliton. For the fractional nonlinear diffusion equation we find the combination of fractional and nonlinear effects results in a more strongly localized solution which nevertheless still exhibits power law tails, albeit at a much lower density.

Zero-sum two-player game theoretic formulation of affine nonlinear discrete-time systems using neural networks.

PubMed

Mehraeen, Shahab; Dierks, Travis; Jagannathan, S; Crow, Mariesa L

2013-12-01

In this paper, the nearly optimal solution for discrete-time (DT) affine nonlinear control systems in the presence of partially unknown internal system dynamics and disturbances is considered. The approach is based on successive approximate solution of the Hamilton-Jacobi-Isaacs (HJI) equation, which appears in optimal control. Successive approximation approach for updating control and disturbance inputs for DT nonlinear affine systems are proposed. Moreover, sufficient conditions for the convergence of the approximate HJI solution to the saddle point are derived, and an iterative approach to approximate the HJI equation using a neural network (NN) is presented. Then, the requirement of full knowledge of the internal dynamics of the nonlinear DT system is relaxed by using a second NN online approximator. The result is a closed-loop optimal NN controller via offline learning. A numerical example is provided illustrating the effectiveness of the approach.

Additivity of nonlinear biomass equations

Treesearch

Bernard R. Parresol

2001-01-01

Two procedures that guarantee the property of additivity among the components of tree biomass and total tree biomass utilizing nonlinear functions are developed. Procedure 1 is a simple combination approach, and procedure 2 is based on nonlinear joint-generalized regression (nonlinear seemingly unrelated regressions) with parameter restrictions. Statistical theory is...

Nonlinear viscoelastic characterization of polymer materials using a dynamic-mechanical methodology

NASA Technical Reports Server (NTRS)

Strganac, Thomas W.; Payne, Debbie Flowers; Biskup, Bruce A.; Letton, Alan

1995-01-01

Polymer materials retrieved from LDEF exhibit nonlinear constitutive behavior; thus the authors present a method to characterize nonlinear viscoelastic behavior using measurements from dynamic (oscillatory) mechanical tests. Frequency-derived measurements are transformed into time-domain properties providing the capability to predict long term material performance without a lengthy experimentation program. Results are presented for thin-film high-performance polymer materials used in the fabrication of high-altitude scientific balloons. Predictions based upon a linear test and analysis approach are shown to deteriorate for moderate to high stress levels expected for extended applications. Tests verify that nonlinear viscoelastic response is induced by large stresses. Hence, an approach is developed in which the stress-dependent behavior is examined in a manner analogous to modeling temperature-dependent behavior with time-temperature correspondence and superposition principles. The development leads to time-stress correspondence and superposition of measurements obtained through dynamic mechanical tests. Predictions of material behavior using measurements based upon linear and nonlinear approaches are compared with experimental results obtained from traditional creep tests. Excellent agreement is shown for the nonlinear model.

Treatment options for moderate-to-very severe chronic obstructive pulmonary disease.

PubMed

Cazzola, Mario; Rogliani, Paola; Ora, Josuel; Matera, Maria Gabriella

2016-01-01

The appropriate drug management of COPD is still based on the use of bronchodilators, possibly associated with an anti-inflammatory agent. However, there are still fundamental questions that require clarification to optimise their use and major unmet clinical needs that must be addressed. The advances obtained with the pharmacological options currently consolidated and the different approaches that are often used in an attempt to respond to unmet therapeutic needs are reviewed Expert opinion: In view of the unsatisfactory status of current treatments for COPD, there is an urgent need for alternative and more effective therapeutic approaches that will help to relieve patient symptoms and affect the natural course of COPD, inhibiting chronic inflammation and reversing the disease process or preventing its progression. However, new pharmacologic options have proved difficult to develop. Therefore, it is mandatory to optimize the use of the treatment options at our disposal. However, there are still fundamental questions regarding their use, including the step-up and step-down pharmacological approach, that require clarification to optimise the use of these drugs. It is likely that phenotyping COPD patients would help in identifying the right treatment for each COPD patient and improve the effectiveness of therapies.

COPD patient education and support - Achieving patient-centredness.

PubMed

Stoilkova-Hartmann, Ana; Franssen, Frits M E; Augustin, Ingrid M L; Wouters, Emiel F M; Barnard, Katharine D

2018-06-01

The art of medicine is undergoing a dramatic shift in focus, evolving to focus on patient involvement as partners in care, transforming the traditional, prescriptive, reactive practice of healthcare into a proactive discipline. The personal and societal burden of chronic diseases is burgeoning and unsustainable in current systems, novel approaches are required to address this. Although considerable progress has been made in the development of diagnostics, therapeutics and care guidelines for patients with chronic obstructive pulmonary disease (COPD), questions remain surrounding the implementation of best practice education and support. Current educational programmes, personal limitations and preferences and patient-clinician communication in modification of coping styles and behaviour are discussed. A novel holistic model, the Kaleidoscope Model of Care is proposed to address the barriers to optimal self-care behaviours. Holistic approaches are essential for optimal self-management and improved outcomes. Guidance on personalised goals for patients to help meeting their therapy priorities is needed to aid healthcare professionals (HCPs) and funders to minimise healthcare burden and costs. The novel KALMOD approach may optimise patient empowerment, exploring whole-life factors that impact COPD care and improve interactions between patients and HCPs for optimised outcomes. Copyright © 2018. Published by Elsevier B.V.

A radiobiology-based inverse treatment planning method for optimisation of permanent l-125 prostate implants in focal brachytherapy

NASA Astrophysics Data System (ADS)

Haworth, Annette; Mears, Christopher; Betts, John M.; Reynolds, Hayley M.; Tack, Guido; Leo, Kevin; Williams, Scott; Ebert, Martin A.

2016-01-01

Treatment plans for ten patients, initially treated with a conventional approach to low dose-rate brachytherapy (LDR, 145 Gy to entire prostate), were compared with plans for the same patients created with an inverse-optimisation planning process utilising a biologically-based objective. The ‘biological optimisation’ considered a non-uniform distribution of tumour cell density through the prostate based on known and expected locations of the tumour. Using dose planning-objectives derived from our previous biological-model validation study, the volume of the urethra receiving 125% of the conventional prescription (145 Gy) was reduced from a median value of 64% to less than 8% whilst maintaining high values of TCP. On average, the number of planned seeds was reduced from 85 to less than 75. The robustness of plans to random seed displacements needs to be carefully considered when using contemporary seed placement techniques. We conclude that an inverse planning approach to LDR treatments, based on a biological objective, has the potential to maintain high rates of tumour control whilst minimising dose to healthy tissue. In future, the radiobiological model will be informed using multi-parametric MRI to provide a personalised medicine approach.

Workplace mental health: developing an integrated intervention approach

PubMed Central

2014-01-01

Background Mental health problems are prevalent and costly in working populations. Workplace interventions to address common mental health problems have evolved relatively independently along three main threads or disciplinary traditions: medicine, public health, and psychology. In this Debate piece, we argue that these three threads need to be integrated to optimise the prevention of mental health problems in working populations. Discussion To realise the greatest population mental health benefits, workplace mental health intervention needs to comprehensively 1) protect mental health by reducing work–related risk factors for mental health problems; 2) promote mental health by developing the positive aspects of work as well as worker strengths and positive capacities; and 3) address mental health problems among working people regardless of cause. We outline the evidence supporting such an integrated intervention approach and consider the research agenda and policy developments needed to move towards this goal, and propose the notion of integrated workplace mental health literacy. Summary An integrated approach to workplace mental health combines the strengths of medicine, public health, and psychology, and has the potential to optimise both the prevention and management of mental health problems in the workplace. PMID:24884425

A closer look at the FTEM framework. Response to "More of the same? Comment on 'An integrated framework for the optimisation of sport and athlete development: a practitioner approach'".

PubMed

Gulbin, Jason P; Croser, Morag J; Morley, Elissa J; Weissensteiner, Juanita R

2014-01-01

The Foundations, Talent, Elite and Mastery (FTEM) framework was designed through the lens of a world leading high-performance sport agency to assist sporting stakeholders operationalise and research their whole of sport development pathways (Gulbin, J. P., Croser, M. J., Morley, E. J., & Weissensteiner, J. R. (2013). An integrated framework for the optimisation of sport and athlete development: A practitioner approach. Journal of Sport Sciences, 31, 1319-1331). In response to the commentary by MacNamara and Collins (2013) (Journal of Sports Sciences, doi:10.1080/02640414.2013. 855805), it was possible to document many inaccurate, false and misleading statements based on inattentive reading of the original article. We reinforce that: FTEM is a holistic framework of sport and athlete development and not a surrogate for a talent identification ( TID) model; bio-psycho-social components of development are liberally embedded throughout the FTEM framework; and the combined research and applied insights of development practitioners provide strong ecological validity for the consideration of stakeholders looking to explore applied approaches to athlete pathway management.

Finite difference time domain calculation of transients in antennas with nonlinear loads

NASA Technical Reports Server (NTRS)

Luebbers, Raymond J.; Beggs, John H.; Kunz, Karl S.; Chamberlin, Kent

1991-01-01

Determining transient electromagnetic fields in antennas with nonlinear loads is a challenging problem. Typical methods used involve calculating frequency domain parameters at a large number of different frequencies, then applying Fourier transform methods plus nonlinear equation solution techniques. If the antenna is simple enough so that the open circuit time domain voltage can be determined independently of the effects of the nonlinear load on the antennas current, time stepping methods can be applied in a straightforward way. Here, transient fields for antennas with more general geometries are calculated directly using Finite Difference Time Domain (FDTD) methods. In each FDTD cell which contains a nonlinear load, a nonlinear equation is solved at each time step. As a test case, the transient current in a long dipole antenna with a nonlinear load excited by a pulsed plane wave is computed using this approach. The results agree well with both calculated and measured results previously published. The approach given here extends the applicability of the FDTD method to problems involving scattering from targets, including nonlinear loads and materials, and to coupling between antennas containing nonlinear loads. It may also be extended to propagation through nonlinear materials.

A general U-block model-based design procedure for nonlinear polynomial control systems

NASA Astrophysics Data System (ADS)

Zhu, Q. M.; Zhao, D. Y.; Zhang, Jianhua

2016-10-01

The proposition of U-model concept (in terms of 'providing concise and applicable solutions for complex problems') and a corresponding basic U-control design algorithm was originated in the first author's PhD thesis. The term of U-model appeared (not rigorously defined) for the first time in the first author's other journal paper, which established a framework for using linear polynomial control system design approaches to design nonlinear polynomial control systems (in brief, linear polynomial approaches → nonlinear polynomial plants). This paper represents the next milestone work - using linear state-space approaches to design nonlinear polynomial control systems (in brief, linear state-space approaches → nonlinear polynomial plants). The overall aim of the study is to establish a framework, defined as the U-block model, which provides a generic prototype for using linear state-space-based approaches to design the control systems with smooth nonlinear plants/processes described by polynomial models. For analysing the feasibility and effectiveness, sliding mode control design approach is selected as an exemplary case study. Numerical simulation studies provide a user-friendly step-by-step procedure for the readers/users with interest in their ad hoc applications. In formality, this is the first paper to present the U-model-oriented control system design in a formal way and to study the associated properties and theorems. The previous publications, in the main, have been algorithm-based studies and simulation demonstrations. In some sense, this paper can be treated as a landmark for the U-model-based research from intuitive/heuristic stage to rigour/formal/comprehensive studies.

Population pharmacokinetic modelling of rupatadine solution in 6-11 year olds and optimisation of the experimental design in younger children.

PubMed

Santamaría, Eva; Estévez, Javier Alejandro; Riba, Jordi; Izquierdo, Iñaki; Valle, Marta

2017-01-01

To optimise a pharmacokinetic (PK) study design of rupatadine for 2-5 year olds by using a population PK model developed with data from a study in 6-11 year olds. The design optimisation was driven by the need to avoid children's discomfort in the study. PK data from 6-11 year olds with allergic rhinitis available from a previous study were used to construct a population PK model which we used in simulations to assess the dose to administer in a study in 2-5 year olds. In addition, an optimal design approach was used to determine the most appropriate number of sampling groups, sampling days, total samples and sampling times. A two-compartmental model with first-order absorption and elimination, with clearance dependent on weight adequately described the PK of rupatadine for 6-11 year olds. The dose selected for a trial in 2-5 year olds was 2.5 mg, as it provided a Cmax below the 3 ng/ml threshold. The optimal study design consisted of four groups of children (10 children each), a maximum sampling window of 2 hours in two clinic visits for drawing three samples on day 14 and one on day 28 coinciding with the final examination of the study. A PK study design was optimised in order to prioritise avoidance of discomfort for enrolled 2-5 year olds by taking only four blood samples from each child and minimising the length of hospital stays.

Optimisation of a machine learning algorithm in human locomotion using principal component and discriminant function analyses.

PubMed

Bisele, Maria; Bencsik, Martin; Lewis, Martin G C; Barnett, Cleveland T

2017-01-01

Assessment methods in human locomotion often involve the description of normalised graphical profiles and/or the extraction of discrete variables. Whilst useful, these approaches may not represent the full complexity of gait data. Multivariate statistical methods, such as Principal Component Analysis (PCA) and Discriminant Function Analysis (DFA), have been adopted since they have the potential to overcome these data handling issues. The aim of the current study was to develop and optimise a specific machine learning algorithm for processing human locomotion data. Twenty participants ran at a self-selected speed across a 15m runway in barefoot and shod conditions. Ground reaction forces (BW) and kinematics were measured at 1000 Hz and 100 Hz, respectively from which joint angles (°), joint moments (N.m.kg-1) and joint powers (W.kg-1) for the hip, knee and ankle joints were calculated in all three anatomical planes. Using PCA and DFA, power spectra of the kinematic and kinetic variables were used as a training database for the development of a machine learning algorithm. All possible combinations of 10 out of 20 participants were explored to find the iteration of individuals that would optimise the machine learning algorithm. The results showed that the algorithm was able to successfully predict whether a participant ran shod or barefoot in 93.5% of cases. To the authors' knowledge, this is the first study to optimise the development of a machine learning algorithm.

Statistical optimisation techniques in fatigue signal editing problem

NASA Astrophysics Data System (ADS)

Nopiah, Z. M.; Osman, M. H.; Baharin, N.; Abdullah, S.

2015-02-01

Success in fatigue signal editing is determined by the level of length reduction without compromising statistical constraints. A great reduction rate can be achieved by removing small amplitude cycles from the recorded signal. The long recorded signal sometimes renders the cycle-to-cycle editing process daunting. This has encouraged researchers to focus on the segment-based approach. This paper discusses joint application of the Running Damage Extraction (RDE) technique and single constrained Genetic Algorithm (GA) in fatigue signal editing optimisation.. In the first section, the RDE technique is used to restructure and summarise the fatigue strain. This technique combines the overlapping window and fatigue strain-life models. It is designed to identify and isolate the fatigue events that exist in the variable amplitude strain data into different segments whereby the retention of statistical parameters and the vibration energy are considered. In the second section, the fatigue data editing problem is formulated as a constrained single optimisation problem that can be solved using GA method. The GA produces the shortest edited fatigue signal by selecting appropriate segments from a pool of labelling segments. Challenges arise due to constraints on the segment selection by deviation level over three signal properties, namely cumulative fatigue damage, root mean square and kurtosis values. Experimental results over several case studies show that the idea of solving fatigue signal editing within a framework of optimisation is effective and automatic, and that the GA is robust for constrained segment selection.

Optimisation of a machine learning algorithm in human locomotion using principal component and discriminant function analyses

PubMed Central

Bisele, Maria; Bencsik, Martin; Lewis, Martin G. C.

2017-01-01

Assessment methods in human locomotion often involve the description of normalised graphical profiles and/or the extraction of discrete variables. Whilst useful, these approaches may not represent the full complexity of gait data. Multivariate statistical methods, such as Principal Component Analysis (PCA) and Discriminant Function Analysis (DFA), have been adopted since they have the potential to overcome these data handling issues. The aim of the current study was to develop and optimise a specific machine learning algorithm for processing human locomotion data. Twenty participants ran at a self-selected speed across a 15m runway in barefoot and shod conditions. Ground reaction forces (BW) and kinematics were measured at 1000 Hz and 100 Hz, respectively from which joint angles (°), joint moments (N.m.kg-1) and joint powers (W.kg-1) for the hip, knee and ankle joints were calculated in all three anatomical planes. Using PCA and DFA, power spectra of the kinematic and kinetic variables were used as a training database for the development of a machine learning algorithm. All possible combinations of 10 out of 20 participants were explored to find the iteration of individuals that would optimise the machine learning algorithm. The results showed that the algorithm was able to successfully predict whether a participant ran shod or barefoot in 93.5% of cases. To the authors’ knowledge, this is the first study to optimise the development of a machine learning algorithm. PMID:28886059

Statistical optimisation techniques in fatigue signal editing problem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nopiah, Z. M.; Osman, M. H.; Baharin, N.

Success in fatigue signal editing is determined by the level of length reduction without compromising statistical constraints. A great reduction rate can be achieved by removing small amplitude cycles from the recorded signal. The long recorded signal sometimes renders the cycle-to-cycle editing process daunting. This has encouraged researchers to focus on the segment-based approach. This paper discusses joint application of the Running Damage Extraction (RDE) technique and single constrained Genetic Algorithm (GA) in fatigue signal editing optimisation.. In the first section, the RDE technique is used to restructure and summarise the fatigue strain. This technique combines the overlapping window andmore » fatigue strain-life models. It is designed to identify and isolate the fatigue events that exist in the variable amplitude strain data into different segments whereby the retention of statistical parameters and the vibration energy are considered. In the second section, the fatigue data editing problem is formulated as a constrained single optimisation problem that can be solved using GA method. The GA produces the shortest edited fatigue signal by selecting appropriate segments from a pool of labelling segments. Challenges arise due to constraints on the segment selection by deviation level over three signal properties, namely cumulative fatigue damage, root mean square and kurtosis values. Experimental results over several case studies show that the idea of solving fatigue signal editing within a framework of optimisation is effective and automatic, and that the GA is robust for constrained segment selection.« less

Optimisation of MSW collection routes for minimum fuel consumption using 3D GIS modelling.

PubMed

Tavares, G; Zsigraiova, Z; Semiao, V; Carvalho, M G

2009-03-01

Collection of municipal solid waste (MSW) may account for more than 70% of the total waste management budget, most of which is for fuel costs. It is therefore crucial to optimise the routing network used for waste collection and transportation. This paper proposes the use of geographical information systems (GIS) 3D route modelling software for waste collection and transportation, which adds one more degree of freedom to the system and allows driving routes to be optimised for minimum fuel consumption. The model takes into account the effects of road inclination and vehicle weight. It is applied to two different cases: routing waste collection vehicles in the city of Praia, the capital of Cape Verde, and routing the transport of waste from different municipalities of Santiago Island to an incineration plant. For the Praia city region, the 3D model that minimised fuel consumption yielded cost savings of 8% as compared with an approach that simply calculated the shortest 3D route. Remarkably, this was true despite the fact that the GIS-recommended fuel reduction route was actually 1.8% longer than the shortest possible travel distance. For the Santiago Island case, the difference was even more significant: a 12% fuel reduction for a similar total travel distance. These figures indicate the importance of considering both the relief of the terrain and fuel consumption in selecting a suitable cost function to optimise vehicle routing.

Chemical study, antioxidant, anti-hypertensive, and cytotoxic/cytoprotective activities of Centaurea cyanus L. petals aqueous extract.

PubMed

Escher, Graziela Bragueto; Santos, Jânio Sousa; Rosso, Neiva Deliberali; Marques, Mariza Boscacci; Azevedo, Luciana; do Carmo, Mariana Araújo Vieira; Daguer, Heitor; Molognoni, Luciano; Prado-Silva, Leonardo do; Sant'Ana, Anderson S; da Silva, Marcia Cristina; Granato, Daniel

2018-05-19

This study aimed to optimise the experimental conditions of extraction of the phytochemical compounds and functional properties of Centaurea cyanus petals. The following parameters were determined: the chemical composition (LC-ESI-MS/MS), the effects of pH on the stability and antioxidant activity of anthocyanins, the inhibition of lipid peroxidation, antioxidant activity, anti-hemolytic activity, antimicrobial, anti-hypertensive, and cytotoxic/cytoprotective effect, and the measurements of intracellular reactive oxygen species. Results showed that the temperature and time influenced (p ≤ 0.05) the content of flavonoids, anthocyanins, and FRAP. Only the temperature influenced the total phenolic content, non-anthocyanin flavonoids, and antioxidant activity (DPPH). The statistical approach made it possible to obtain the optimised experimental extraction conditions to increase the level of bioactive compounds. Chlorogenic, caffeic, ferulic, and p-coumaric acids, isoquercitrin, and coumarin were identified as the major compounds in the optimised extract. The optimised extract presented anti-hemolytic and anti-hypertensive activity in vitro, in addition to showing stability and reversibility of anthocyanins and antioxidant activity with pH variation. The C. cyanus petals aqueous extract exhibited high IC 50 and GI 50 (>900 μg/mL) values for all cell lines, meaning low cytotoxicity. Based on the stress oxidative assay, the extract exhibited pro-oxidant action (10-100 μg/mL) but did not cause damage or cell death. Copyright © 2018 Elsevier Ltd. All rights reserved.

Nonlinear ultrasonic measurements with EMATs for detecting pre-cracking fatigue damage

NASA Astrophysics Data System (ADS)

Cobb, A.; Capps, M.; Duffer, C.; Feiger, J.; Robinson, K.; Hollingshaus, B.

2012-05-01

This paper describes an approach for measuring material degradation using nonlinear acoustics. The importance of this measurement is that prior efforts have shown that the degree of acoustic nonlinearity increases as a function of fatigue damage accumulation. By exploiting this physical mechanism, there is the potential to develop methods for measuring the remaining life of critical components. The challenge with existing approaches for measuring acoustic nonlinearity is that primarily they have only been shown to be successful in a laboratory setting. This paper presents a potential approach for field measurement of acoustic nonlinearity that utilizes Rayleigh waves generated from electromagnetic acoustic transducers (EMATs). Rayleigh waves have unique advantages because the sound propagates along the surface, allowing for application on complex engineering structures. EMATs were used in place of traditional piezoelectric transducers because the sound is generated directly in the metallic structure, eliminating the need for sound coupling fluids that are a source of variability. Custom EMATs were developed and nonlinearity measurements were performed on 410 stainless steel specimens that were subjected to a fatigue process. Some experiments showed an increase in the acoustic nonlinearity of up to 500% compared to the unfatigued value. Other experiments had too much scatter and did not show this relationship consistently due to unanticipated challenges in producing repeatable measurements. Lessons learned from the project effort will be presented to potentially improve the repeatability of the measurement approach. If the scatter can be reduced, this EMAT-based technique could result in a field deployable prognosis tool.

Guaranteed cost control with poles assignment for a flexible air-breathing hypersonic vehicle

NASA Astrophysics Data System (ADS)

Li, Hongyi; Si, Yulin; Wu, Ligang; Hu, Xiaoxiang; Gao, Huijun

2011-05-01

This article investigates the problem of guaranteed cost control for a flexible air-breathing hypersonic vehicle (FAHV). The FAHV includes intricate coupling between the engine and flight dynamics as well as complex interplay between flexible and rigid modes, which results in an intractable system for the control design. A longitudinal model is adopted for control design due to the complexity of the vehicle. First, for a highly nonlinear and coupled FAHV, a linearised model is established around the trim condition, which includes the state of altitude, velocity, angle of attack, pitch angle and pitch rate, etc. Secondly, by using the Lyapunov approach, performance analysis is carried out for the resulting closed-loop FAHV system, whose criterion with respect to guaranteed performance cost and poles assignment is expressed in the framework of linear matrix inequalities (LMIs). The established criterion exhibits a kind of decoupling between the Lyapunov positive-definite matrices to be determined and the FAHV system matrices, which is enabled by the introduction of additional slack matrix variables. Thirdly, a convex optimisation problem with LMI constraints is formulated for designing an admissible controller, which guarantees a prescribed performance cost with the simultaneous consideration of poles assignment for the resulting closed-loop system. Finally, some simulation results are provided to show that the guaranteed cost controller could assign the poles into the desired regional and achieve excellent reference altitude and velocity tracking performance.

Learning Content and Software Evaluation and Personalisation Problems

ERIC Educational Resources Information Center

Kurilovas, Eugenijus; Serikoviene, Silvija

2010-01-01

The paper aims to analyse several scientific approaches how to evaluate, implement or choose learning content and software suitable for personalised users/learners needs. Learning objects metadata customisation method as well as the Method of multiple criteria evaluation and optimisation of learning software represented by the experts' additive…

Flexible Work Options within the Organisational System

ERIC Educational Resources Information Center

Albion, Majella J.; Chee, Munli

2006-01-01

The availability of flexible work options provides an opportunity for individuals to shape their careers in order to optimise their work and life goals. This study takes a systems theory approach to examine how the use of flexible work options influences relationships and interactions in the workplace. The "Flexible Work Options…

Semiclassical limit of the focusing NLS: Whitham equations and the Riemann-Hilbert Problem approach

NASA Astrophysics Data System (ADS)

Tovbis, Alexander; El, Gennady A.

2016-10-01

The main goal of this paper is to put together: a) the Whitham theory applicable to slowly modulated N-phase nonlinear wave solutions to the focusing nonlinear Schrödinger (fNLS) equation, and b) the Riemann-Hilbert Problem approach to particular solutions of the fNLS in the semiclassical (small dispersion) limit that develop slowly modulated N-phase nonlinear wave in the process of evolution. Both approaches have their own merits and limitations. Understanding of the interrelations between them could prove beneficial for a broad range of problems involving the semiclassical fNLS.

A nonlinear circuit architecture for magnetoencephalographic signal analysis.

PubMed

Bucolo, M; Fortuna, L; Frasca, M; La Rosa, M; Virzì, M C; Shannahoff-Khalsa, D

2004-01-01

The objective of this paper was to face the complex spatio-temporal dynamics shown by Magnetoencephalography (MEG) data by applying a nonlinear distributed approach for the Blind Sources Separation. The effort was to characterize and differ-entiate the phases of a yogic respiratory exercise used in the treatment of obsessive compulsive disorders. The patient performed a precise respiratory protocol, at one breath per minute for 31 minutes, with 10 minutes resting phase before and after. The two steps of classical Independent Component Approach have been performed by using a Cellular Neural Network with two sets of templates. The choice of the couple of suitable templates has been carried out using genetic algorithm optimization techniques. Performing BSS with a nonlinear distributed approach, the outputs of the CNN have been compared to the ICA ones. In all the protocol phases, the main components founded with CNN have similar trends compared with that ones obtained with ICA. Moreover, using this distributed approach, a spatial location has been associated to each component. To underline the spatio-temporal and the nonlinearly of the neural process a distributed nonlinear architecture has been proposed. This strategy has been designed in order to overcome the hypothesis of linear combination among the sources signals, that is characteristic of the ICA approach, taking advantage of the spatial information.

Trainable Nonlinear Reaction Diffusion: A Flexible Framework for Fast and Effective Image Restoration.

PubMed

Chen, Yunjin; Pock, Thomas

2017-06-01

Image restoration is a long-standing problem in low-level computer vision with many interesting applications. We describe a flexible learning framework based on the concept of nonlinear reaction diffusion models for various image restoration problems. By embodying recent improvements in nonlinear diffusion models, we propose a dynamic nonlinear reaction diffusion model with time-dependent parameters (i.e., linear filters and influence functions). In contrast to previous nonlinear diffusion models, all the parameters, including the filters and the influence functions, are simultaneously learned from training data through a loss based approach. We call this approach TNRD-Trainable Nonlinear Reaction Diffusion. The TNRD approach is applicable for a variety of image restoration tasks by incorporating appropriate reaction force. We demonstrate its capabilities with three representative applications, Gaussian image denoising, single image super resolution and JPEG deblocking. Experiments show that our trained nonlinear diffusion models largely benefit from the training of the parameters and finally lead to the best reported performance on common test datasets for the tested applications. Our trained models preserve the structural simplicity of diffusion models and take only a small number of diffusion steps, thus are highly efficient. Moreover, they are also well-suited for parallel computation on GPUs, which makes the inference procedure extremely fast.

Robust model predictive control of nonlinear systems with unmodeled dynamics and bounded uncertainties based on neural networks.

PubMed

Yan, Zheng; Wang, Jun

2014-03-01

This paper presents a neural network approach to robust model predictive control (MPC) for constrained discrete-time nonlinear systems with unmodeled dynamics affected by bounded uncertainties. The exact nonlinear model of underlying process is not precisely known, but a partially known nominal model is available. This partially known nonlinear model is first decomposed to an affine term plus an unknown high-order term via Jacobian linearization. The linearization residue combined with unmodeled dynamics is then modeled using an extreme learning machine via supervised learning. The minimax methodology is exploited to deal with bounded uncertainties. The minimax optimization problem is reformulated as a convex minimization problem and is iteratively solved by a two-layer recurrent neural network. The proposed neurodynamic approach to nonlinear MPC improves the computational efficiency and sheds a light for real-time implementability of MPC technology. Simulation results are provided to substantiate the effectiveness and characteristics of the proposed approach.

An Efficient Numerical Approach for Nonlinear Fokker-Planck equations

NASA Astrophysics Data System (ADS)

Otten, Dustin; Vedula, Prakash

2009-03-01

Fokker-Planck equations which are nonlinear with respect to their probability densities that occur in many nonequilibrium systems relevant to mean field interaction models, plasmas, classical fermions and bosons can be challenging to solve numerically. To address some underlying challenges in obtaining numerical solutions, we propose a quadrature based moment method for efficient and accurate determination of transient (and stationary) solutions of nonlinear Fokker-Planck equations. In this approach the distribution function is represented as a collection of Dirac delta functions with corresponding quadrature weights and locations, that are in turn determined from constraints based on evolution of generalized moments. Properties of the distribution function can be obtained by solution of transport equations for quadrature weights and locations. We will apply this computational approach to study a wide range of problems, including the Desai-Zwanzig Model (for nonlinear muscular contraction) and multivariate nonlinear Fokker-Planck equations describing classical fermions and bosons, and will also demonstrate good agreement with results obtained from Monte Carlo and other standard numerical methods.

Exact and Approximate Statistical Inference for Nonlinear Regression and the Estimating Equation Approach.

PubMed

Demidenko, Eugene

2017-09-01

The exact density distribution of the nonlinear least squares estimator in the one-parameter regression model is derived in closed form and expressed through the cumulative distribution function of the standard normal variable. Several proposals to generalize this result are discussed. The exact density is extended to the estimating equation (EE) approach and the nonlinear regression with an arbitrary number of linear parameters and one intrinsically nonlinear parameter. For a very special nonlinear regression model, the derived density coincides with the distribution of the ratio of two normally distributed random variables previously obtained by Fieller (1932), unlike other approximations previously suggested by other authors. Approximations to the density of the EE estimators are discussed in the multivariate case. Numerical complications associated with the nonlinear least squares are illustrated, such as nonexistence and/or multiple solutions, as major factors contributing to poor density approximation. The nonlinear Markov-Gauss theorem is formulated based on the near exact EE density approximation.

A Genetic Algorithm Approach to Nonlinear Least Squares Estimation

ERIC Educational Resources Information Center

Olinsky, Alan D.; Quinn, John T.; Mangiameli, Paul M.; Chen, Shaw K.

2004-01-01

A common type of problem encountered in mathematics is optimizing nonlinear functions. Many popular algorithms that are currently available for finding nonlinear least squares estimators, a special class of nonlinear problems, are sometimes inadequate. They might not converge to an optimal value, or if they do, it could be to a local rather than…

A comparative analysis of alternative approaches for quantifying nonlinear dynamics in cardiovascular system.

PubMed

Chen, Yun; Yang, Hui

2013-01-01

Heart rate variability (HRV) analysis has emerged as an important research topic to evaluate autonomic cardiac function. However, traditional time and frequency-domain analysis characterizes and quantify only linear and stationary phenomena. In the present investigation, we made a comparative analysis of three alternative approaches (i.e., wavelet multifractal analysis, Lyapunov exponents and multiscale entropy analysis) for quantifying nonlinear dynamics in heart rate time series. Note that these extracted nonlinear features provide information about nonlinear scaling behaviors and the complexity of cardiac systems. To evaluate the performance, we used 24-hour HRV recordings from 54 healthy subjects and 29 heart failure patients, available in PhysioNet. Three nonlinear methods are evaluated not only individually but also in combination using three classification algorithms, i.e., linear discriminate analysis, quadratic discriminate analysis and k-nearest neighbors. Experimental results show that three nonlinear methods capture nonlinear dynamics from different perspectives and the combined feature set achieves the best performance, i.e., sensitivity 97.7% and specificity 91.5%. Collectively, nonlinear HRV features are shown to have the promise to identify the disorders in autonomic cardiovascular function.

Fast prediction of pulsed nonlinear acoustic fields from clinically relevant sources using Time-Averaged Wave Envelope approach: comparison of numerical simulations and experimental results

PubMed Central

Wójcik, J.; Kujawska, T.; Nowicki, A.; Lewin, P.A.

2008-01-01

The primary goal of this work was to verify experimentally the applicability of the recently introduced Time-Averaged Wave Envelope (TAWE) method [1] as a tool for fast prediction of four dimensional (4D) pulsed nonlinear pressure fields from arbitrarily shaped acoustic sources in attenuating media. The experiments were performed in water at the fundamental frequency of 2.8 MHz for spherically focused (focal length F = 80 mm) square (20 × 20 mm) and rectangular (10 × 25 mm) sources similar to those used in the design of 1D linear arrays operating with ultrasonic imaging systems. The experimental results obtained with 10-cycle tone bursts at three different excitation levels corresponding to linear, moderately nonlinear and highly nonlinear propagation conditions (0.045, 0.225 and 0.45 MPa on-source pressure amplitude, respectively) were compared with those yielded using the TAWE approach [1]. The comparison of the experimental results and numerical simulations has shown that the TAWE approach is well suited to predict (to within ± 1 dB) both the spatial-temporal and spatial-spectral pressure variations in the pulsed nonlinear acoustic beams. The obtained results indicated that implementation of the TAWE approach enabled shortening of computation time in comparison with the time needed for prediction of the full 4D pulsed nonlinear acoustic fields using a conventional (Fourier-series) approach [2]. The reduction in computation time depends on several parameters, including the source geometry, dimensions, fundamental resonance frequency, excitation level as well as the strength of the medium nonlinearity. For the non-axisymmetric focused transducers mentioned above and excited by a tone burst corresponding to moderately nonlinear and highly nonlinear conditions the execution time of computations was 3 and 12 hours, respectively, when using a 1.5 GHz clock frequency, 32-bit processor PC laptop with 2 GB RAM memory, only. Such prediction of the full 4D pulsed field is not possible when using conventional, Fourier-series scheme as it would require increasing the RAM memory by at least 2 orders of magnitude. PMID:18474387

Microscopic cascading of second-order molecular nonlinearity: New design principles for enhancing third-order nonlinearity.

PubMed

Baev, Alexander; Autschbach, Jochen; Boyd, Robert W; Prasad, Paras N

2010-04-12

Herein, we develop a phenomenological model for microscopic cascading and substantiate it with ab initio calculations. It is shown that the concept of local microscopic cascading of a second-order nonlinearity can lead to a third-order nonlinearity, without introducing any new loss mechanisms that could limit the usefulness of our approach. This approach provides a new molecular design protocol, in which the current great successes achieved in producing molecules with extremely large second-order nonlinearity can be used in a supra molecular organization in a preferred orientation to generate very large third-order response magnitudes. The results of density functional calculations for a well-known second-order molecule, (para)nitroaniline, show that a head-to-tail dimer configuration exhibits enhanced third-order nonlinearity, in agreement with the phenomenological model which suggests that such an arrangement will produce cascading due to local field effects.

Nonlinear terahertz devices utilizing semiconducting plasmonic metamaterials

DOE PAGES

Seren, Huseyin R.; Zhang, Jingdi; Keiser, George R.; ...

2016-01-26

The development of responsive metamaterials has enabled the realization of compact tunable photonic devices capable of manipulating the amplitude, polarization, wave vector and frequency of light. Integration of semiconductors into the active regions of metallic resonators is a proven approach for creating nonlinear metamaterials through optoelectronic control of the semiconductor carrier density. Metal-free subwavelength resonant semiconductor structures offer an alternative approach to create dynamic metamaterials. We present InAs plasmonic disk arrays as a viable resonant metamaterial at terahertz frequencies. Importantly, InAs plasmonic disks exhibit a strong nonlinear response arising from electric field-induced intervalley scattering, resulting in a reduced carrier mobilitymore » thereby damping the plasmonic response. here, we demonstrate nonlinear perfect absorbers configured as either optical limiters or saturable absorbers, including flexible nonlinear absorbers achieved by transferring the disks to polyimide films. Nonlinear plasmonic metamaterials show potential for use in ultrafast terahertz (THz) optics and for passive protection of sensitive electromagnetic devices.« less

Nonlinear terahertz devices utilizing semiconducting plasmonic metamaterials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seren, Huseyin R.; Zhang, Jingdi; Keiser, George R.

The development of responsive metamaterials has enabled the realization of compact tunable photonic devices capable of manipulating the amplitude, polarization, wave vector and frequency of light. Integration of semiconductors into the active regions of metallic resonators is a proven approach for creating nonlinear metamaterials through optoelectronic control of the semiconductor carrier density. Metal-free subwavelength resonant semiconductor structures offer an alternative approach to create dynamic metamaterials. We present InAs plasmonic disk arrays as a viable resonant metamaterial at terahertz frequencies. Importantly, InAs plasmonic disks exhibit a strong nonlinear response arising from electric field-induced intervalley scattering, resulting in a reduced carrier mobilitymore » thereby damping the plasmonic response. here, we demonstrate nonlinear perfect absorbers configured as either optical limiters or saturable absorbers, including flexible nonlinear absorbers achieved by transferring the disks to polyimide films. Nonlinear plasmonic metamaterials show potential for use in ultrafast terahertz (THz) optics and for passive protection of sensitive electromagnetic devices.« less

Real-Time Nonlinear Optical Information Processing.

DTIC Science & Technology

1979-06-01

operations aree presented. One approach realizes the halftone method of nonlinear optical processing in real time by replacing the conventional...photographic recording medium with a real-time image transducer. In the second approach halftoning is eliminated and the real-time device is used directly

Simulations of nonlinear continuous wave pressure fields in FOCUS

NASA Astrophysics Data System (ADS)

Zhao, Xiaofeng; Hamilton, Mark F.; McGough, Robert J.

2017-03-01

The Khokhlov - Zabolotskaya - Kuznetsov (KZK) equation is a parabolic approximation to the Westervelt equation that models the effects of diffraction, attenuation, and nonlinearity. Although the KZK equation is only valid in the far field of the paraxial region for mildly focused or unfocused transducers, the KZK equation is widely applied in medical ultrasound simulations. For a continuous wave input, the KZK equation is effectively modeled by the Bergen Code [J. Berntsen, Numerical Calculations of Finite Amplitude Sound Beams, in M. F. Hamilton and D. T. Blackstock, editors, Frontiers of Nonlinear Acoustics: Proceedings of 12th ISNA, Elsevier, 1990], which is a finite difference model that utilizes operator splitting. Similar C++ routines have been developed for FOCUS, the `Fast Object-Oriented C++ Ultrasound Simulator' (http://www.egr.msu.edu/˜fultras-web) to calculate nonlinear pressure fields generated by axisymmetric flat circular and spherically focused ultrasound transducers. This new routine complements an existing FOCUS program that models nonlinear ultrasound propagation with the angular spectrum approach [P. T. Christopher and K. J. Parker, J. Acoust. Soc. Am. 90, 488-499 (1991)]. Results obtained from these two nonlinear ultrasound simulation approaches are evaluated and compared for continuous wave linear simulations. The simulation results match closely in the farfield of the paraxial region, but the results differ in the nearfield. The nonlinear pressure field generated by a spherically focused transducer with a peak surface pressure of 0.2MPa radiating in a lossy medium with β = 3.5 is simulated, and the computation times are also evaluated. The nonlinear simulation results demonstrate acceptable agreement in the focal zone. These two related nonlinear simulation approaches are now included with FOCUS to enable convenient simulations of nonlinear pressure fields on desktop and laptop computers.

Nonlinear pedagogy: an effective approach to cater for individual differences in learning a sports skill.

PubMed

Lee, Miriam Chang Yi; Chow, Jia Yi; Komar, John; Tan, Clara Wee Keat; Button, Chris

2014-01-01

Learning a sports skill is a complex process in which practitioners are challenged to cater for individual differences. The main purpose of this study was to explore the effectiveness of a Nonlinear Pedagogy approach for learning a sports skill. Twenty-four 10-year-old females participated in a 4-week intervention involving either a Nonlinear Pedagogy (i.e.,manipulation of task constraints including equipment and rules) or a Linear Pedagogy (i.e., prescriptive, repetitive drills) approach to learn a tennis forehand stroke. Performance accuracy scores, movement criterion scores and kinematic data were measured during pre-intervention, post-intervention and retention tests. While both groups showed improvements in performance accuracy scores over time, the Nonlinear Pedagogy group displayed a greater number of movement clusters at post-test indicating the presence of degeneracy (i.e., many ways to achieve the same outcome). The results suggest that degeneracy is effective for learning a sports skill facilitated by a Nonlinear Pedagogy approach. These findings challenge the common misconception that there must be only one ideal movement solution for a task and thus have implications for coaches and educators when designing instructions for skill acquisition.

Nonlinear Pedagogy: An Effective Approach to Cater for Individual Differences in Learning a Sports Skill

PubMed Central

Lee, Miriam Chang Yi; Chow, Jia Yi; Komar, John; Tan, Clara Wee Keat; Button, Chris

2014-01-01

Learning a sports skill is a complex process in which practitioners are challenged to cater for individual differences. The main purpose of this study was to explore the effectiveness of a Nonlinear Pedagogy approach for learning a sports skill. Twenty-four 10-year-old females participated in a 4-week intervention involving either a Nonlinear Pedagogy (i.e.,manipulation of task constraints including equipment and rules) or a Linear Pedagogy (i.e., prescriptive, repetitive drills) approach to learn a tennis forehand stroke. Performance accuracy scores, movement criterion scores and kinematic data were measured during pre-intervention, post-intervention and retention tests. While both groups showed improvements in performance accuracy scores over time, the Nonlinear Pedagogy group displayed a greater number of movement clusters at post-test indicating the presence of degeneracy (i.e., many ways to achieve the same outcome). The results suggest that degeneracy is effective for learning a sports skill facilitated by a Nonlinear Pedagogy approach. These findings challenge the common misconception that there must be only one ideal movement solution for a task and thus have implications for coaches and educators when designing instructions for skill acquisition. PMID:25140822

A nonlinear dynamics approach for incorporating wind-speed patterns into wind-power project evaluation.

PubMed

Huffaker, Ray; Bittelli, Marco

2015-01-01

Wind-energy production may be expanded beyond regions with high-average wind speeds (such as the Midwest U.S.A.) to sites with lower-average speeds (such as the Southeast U.S.A.) by locating favorable regional matches between natural wind-speed and energy-demand patterns. A critical component of wind-power evaluation is to incorporate wind-speed dynamics reflecting documented diurnal and seasonal behavioral patterns. Conventional probabilistic approaches remove patterns from wind-speed data. These patterns must be restored synthetically before they can be matched with energy-demand patterns. How to accurately restore wind-speed patterns is a vexing problem spurring an expanding line of papers. We propose a paradigm shift in wind power evaluation that employs signal-detection and nonlinear-dynamics techniques to empirically diagnose whether synthetic pattern restoration can be avoided altogether. If the complex behavior of observed wind-speed records is due to nonlinear, low-dimensional, and deterministic system dynamics, then nonlinear dynamics techniques can reconstruct wind-speed dynamics from observed wind-speed data without recourse to conventional probabilistic approaches. In the first study of its kind, we test a nonlinear dynamics approach in an application to Sugarland Wind-the first utility-scale wind project proposed in Florida, USA. We find empirical evidence of a low-dimensional and nonlinear wind-speed attractor characterized by strong temporal patterns that match up well with regular daily and seasonal electricity demand patterns.

Optimisation of Ferrochrome Addition Using Multi-Objective Evolutionary and Genetic Algorithms for Stainless Steel Making via AOD Converter

NASA Astrophysics Data System (ADS)

Behera, Kishore Kumar; Pal, Snehanshu

2018-03-01

This paper describes a new approach towards optimum utilisation of ferrochrome added during stainless steel making in AOD converter. The objective of optimisation is to enhance end blow chromium content of steel and reduce the ferrochrome addition during refining. By developing a thermodynamic based mathematical model, a study has been conducted to compute the optimum trade-off between ferrochrome addition and end blow chromium content of stainless steel using a predator prey genetic algorithm through training of 100 dataset considering different input and output variables such as oxygen, argon, nitrogen blowing rate, duration of blowing, initial bath temperature, chromium and carbon content, weight of ferrochrome added during refining. Optimisation is performed within constrained imposed on the input parameters whose values fall within certain ranges. The analysis of pareto fronts is observed to generate a set of feasible optimal solution between the two conflicting objectives that provides an effective guideline for better ferrochrome utilisation. It is found out that after a certain critical range, further addition of ferrochrome does not affect the chromium percentage of steel. Single variable response analysis is performed to study the variation and interaction of all individual input parameters on output variables.

A novel swarm intelligence algorithm for finding DNA motifs.

PubMed

Lei, Chengwei; Ruan, Jianhua

2009-01-01

Discovering DNA motifs from co-expressed or co-regulated genes is an important step towards deciphering complex gene regulatory networks and understanding gene functions. Despite significant improvement in the last decade, it still remains one of the most challenging problems in computational molecular biology. In this work, we propose a novel motif finding algorithm that finds consensus patterns using a population-based stochastic optimisation technique called Particle Swarm Optimisation (PSO), which has been shown to be effective in optimising difficult multidimensional problems in continuous domains. We propose to use a word dissimilarity graph to remap the neighborhood structure of the solution space of DNA motifs, and propose a modification of the naive PSO algorithm to accommodate discrete variables. In order to improve efficiency, we also propose several strategies for escaping from local optima and for automatically determining the termination criteria. Experimental results on simulated challenge problems show that our method is both more efficient and more accurate than several existing algorithms. Applications to several sets of real promoter sequences also show that our approach is able to detect known transcription factor binding sites, and outperforms two of the most popular existing algorithms.

Lévy flight artificial bee colony algorithm

NASA Astrophysics Data System (ADS)

Sharma, Harish; Bansal, Jagdish Chand; Arya, K. V.; Yang, Xin-She

2016-08-01

Artificial bee colony (ABC) optimisation algorithm is a relatively simple and recent population-based probabilistic approach for global optimisation. The solution search equation of ABC is significantly influenced by a random quantity which helps in exploration at the cost of exploitation of the search space. In the ABC, there is a high chance to skip the true solution due to its large step sizes. In order to balance between diversity and convergence in the ABC, a Lévy flight inspired search strategy is proposed and integrated with ABC. The proposed strategy is named as Lévy Flight ABC (LFABC) has both the local and global search capability simultaneously and can be achieved by tuning the Lévy flight parameters and thus automatically tuning the step sizes. In the LFABC, new solutions are generated around the best solution and it helps to enhance the exploitation capability of ABC. Furthermore, to improve the exploration capability, the numbers of scout bees are increased. The experiments on 20 test problems of different complexities and five real-world engineering optimisation problems show that the proposed strategy outperforms the basic ABC and recent variants of ABC, namely, Gbest-guided ABC, best-so-far ABC and modified ABC in most of the experiments.

Development and validation of a rapid capillary zone electrophoresis method for the determination of aconite alkaloids in aconite roots.

PubMed

Song, Jing-Zheng; Han, Quan-Bin; Qiao, Chun-Feng; But, Paul Pui-Hay; Xu, Hong-Xi

2010-01-01

Aconites, with aconite alkaloids as the major therapeutic and toxic components, are used for the treatment of analgesic, antirheumatic and neurological symptoms. Quantification of the aconite alkaloids is important for the quality control of aconite-containing drugs. To establish a validated capillary zone electrophoresis (CZE) method for the simultaneous determination of six major alkaloids, namely aconitine, mesaconitine, hypaconitine, benzoylaconine, benzoylmesaconine and benzoylhypaconine, in crude and processed aconite roots. The CZE method was optimised and validated using a stability-indicating method. The optimised running buffer was a mixture of 200 mm Tris, 150 mm perchloric acid and 40% 1,4-dioxane (pH 7.8) with the capillary thermostated at 25 degrees C. Using the optimised method, six aconite alkaloids were well separated. The established method showed good precision, accuracy and recovery. Contents of these alkaloids in crude and processed aconites were determined and it was observed that the levels of individual alkaloids varied between samples. The developed CZE method was reliable for the quality control of aconites contained in herbal medicines. The method could also be used as an approach for toxicological studies.

Acquisition of business intelligence from human experience in route planning

NASA Astrophysics Data System (ADS)

Bello Orgaz, Gema; Barrero, David F.; R-Moreno, María D.; Camacho, David

2015-04-01

The logistic sector raises a number of highly challenging problems. Probably one of the most important ones is the shipping planning, i.e. plan the routes that the shippers have to follow to deliver the goods. In this article, we present an artificial intelligence-based solution that has been designed to help a logistic company to improve its routes planning process. In order to achieve this goal, the solution uses the knowledge acquired by the company drivers to propose optimised routes. Hence, the proposed solution gathers the experience of the drivers, processes it and optimises the delivery process. The solution uses data mining to extract knowledge from the company information systems and prepares it for analysis with a case-based reasoning (CBR) algorithm. The CBR obtains critical business intelligence knowledge from the drivers experience that is needed by the planner. The design of the routes is done by a genetic algorithm that, given the processed information, optimises the routes following several objectives, such as minimise the distance or time. Experimentation shows that the proposed approach is able to find routes that improve, on average, the routes made by the human experts.

Integration of PGD-virtual charts into an engineering design process

NASA Astrophysics Data System (ADS)

Courard, Amaury; Néron, David; Ladevèze, Pierre; Ballere, Ludovic

2016-04-01

This article deals with the efficient construction of approximations of fields and quantities of interest used in geometric optimisation of complex shapes that can be encountered in engineering structures. The strategy, which is developed herein, is based on the construction of virtual charts that allow, once computed offline, to optimise the structure for a negligible online CPU cost. These virtual charts can be used as a powerful numerical decision support tool during the design of industrial structures. They are built using the proper generalized decomposition (PGD) that offers a very convenient framework to solve parametrised problems. In this paper, particular attention has been paid to the integration of the procedure into a genuine engineering design process. In particular, a dedicated methodology is proposed to interface the PGD approach with commercial software.

Virtual test rig to improve the design and optimisation process of the vehicle steering and suspension systems

NASA Astrophysics Data System (ADS)

Mántaras, Daniel A.; Luque, Pablo

2012-10-01

A virtual test rig is presented using a three-dimensional model of the elasto-kinematic behaviour of a vehicle. A general approach is put forward to determine the three-dimensional position of the body and the main parameters which influence the handling of the vehicle. For the design process, the variable input data are the longitudinal and lateral acceleration and the curve radius, which are defined by the user as a design goal. For the optimisation process, once the vehicle has been built, the variable input data are the travel of the four struts and the steering wheel angle, which is obtained through monitoring the vehicle. The virtual test rig has been applied to a standard vehicle and the validity of the results has been proven.

Optimised cross-layer synchronisation schemes for wireless sensor networks

NASA Astrophysics Data System (ADS)

Nasri, Nejah; Ben Fradj, Awatef; Kachouri, Abdennaceur

2017-07-01

This paper aims at synchronisation between the sensor nodes. Indeed, in the context of wireless sensor networks, it is necessary to take into consideration the energy cost induced by the synchronisation, which can represent the majority of the energy consumed. On communication, an already identified hard point consists in imagining a fine synchronisation protocol which must be sufficiently robust to the intermittent energy in the sensors. Hence, this paper worked on aspects of performance and energy saving, in particular on the optimisation of the synchronisation protocol using cross-layer design method such as synchronisation between layers. Our approach consists in balancing the energy consumption between the sensors and choosing the cluster head with the highest residual energy in order to guarantee the reliability, integrity and continuity of communication (i.e. maximising the network lifetime).

An intelligent factory-wide optimal operation system for continuous production process

NASA Astrophysics Data System (ADS)

Ding, Jinliang; Chai, Tianyou; Wang, Hongfeng; Wang, Junwei; Zheng, Xiuping

2016-03-01

In this study, a novel intelligent factory-wide operation system for a continuous production process is designed to optimise the entire production process, which consists of multiple units; furthermore, this system is developed using process operational data to avoid the complexity of mathematical modelling of the continuous production process. The data-driven approach aims to specify the structure of the optimal operation system; in particular, the operational data of the process are used to formulate each part of the system. In this context, the domain knowledge of process engineers is utilised, and a closed-loop dynamic optimisation strategy, which combines feedback, performance prediction, feed-forward, and dynamic tuning schemes into a framework, is employed. The effectiveness of the proposed system has been verified using industrial experimental results.

A hybrid approach for nonlinear computational aeroacoustics predictions

NASA Astrophysics Data System (ADS)

Sassanis, Vasileios; Sescu, Adrian; Collins, Eric M.; Harris, Robert E.; Luke, Edward A.

2017-01-01

In many aeroacoustics applications involving nonlinear waves and obstructions in the far-field, approaches based on the classical acoustic analogy theory or the linearised Euler equations are unable to fully characterise the acoustic field. Therefore, computational aeroacoustics hybrid methods that incorporate nonlinear wave propagation have to be constructed. In this study, a hybrid approach coupling Navier-Stokes equations in the acoustic source region with nonlinear Euler equations in the acoustic propagation region is introduced and tested. The full Navier-Stokes equations are solved in the source region to identify the acoustic sources. The flow variables of interest are then transferred from the source region to the acoustic propagation region, where the full nonlinear Euler equations with source terms are solved. The transition between the two regions is made through a buffer zone where the flow variables are penalised via a source term added to the Euler equations. Tests were conducted on simple acoustic and vorticity disturbances, two-dimensional jets (Mach 0.9 and 2), and a three-dimensional jet (Mach 1.5), impinging on a wall. The method is proven to be effective and accurate in predicting sound pressure levels associated with the propagation of linear and nonlinear waves in the near- and far-field regions.

Opportunistic data locality for end user data analysis

NASA Astrophysics Data System (ADS)

Fischer, M.; Heidecker, C.; Kuehn, E.; Quast, G.; Giffels, M.; Schnepf, M.; Heiss, A.; Petzold, A.

2017-10-01

With the increasing data volume of LHC Run2, user analyses are evolving towards increasing data throughput. This evolution translates to higher requirements for efficiency and scalability of the underlying analysis infrastructure. We approach this issue with a new middleware to optimise data access: a layer of coordinated caches transparently provides data locality for high-throughput analyses. We demonstrated the feasibility of this approach with a prototype used for analyses of the CMS working groups at KIT. In this paper, we present our experience both with the approach in general, and our prototype in specific.

Nonlinear adaptive control system design with asymptotically stable parameter estimation error

NASA Astrophysics Data System (ADS)

Mishkov, Rumen; Darmonski, Stanislav

2018-01-01

The paper presents a new general method for nonlinear adaptive system design with asymptotic stability of the parameter estimation error. The advantages of the approach include asymptotic unknown parameter estimation without persistent excitation and capability to directly control the estimates transient response time. The method proposed modifies the basic parameter estimation dynamics designed via a known nonlinear adaptive control approach. The modification is based on the generalised prediction error, a priori constraints with a hierarchical parameter projection algorithm, and the stable data accumulation concepts. The data accumulation principle is the main tool for achieving asymptotic unknown parameter estimation. It relies on the parametric identifiability system property introduced. Necessary and sufficient conditions for exponential stability of the data accumulation dynamics are derived. The approach is applied in a nonlinear adaptive speed tracking vector control of a three-phase induction motor.

ATLAS software configuration and build tool optimisation

NASA Astrophysics Data System (ADS)

Rybkin, Grigory; Atlas Collaboration

2014-06-01

ATLAS software code base is over 6 million lines organised in about 2000 packages. It makes use of some 100 external software packages, is developed by more than 400 developers and used by more than 2500 physicists from over 200 universities and laboratories in 6 continents. To meet the challenge of configuration and building of this software, the Configuration Management Tool (CMT) is used. CMT expects each package to describe its build targets, build and environment setup parameters, dependencies on other packages in a text file called requirements, and each project (group of packages) to describe its policies and dependencies on other projects in a text project file. Based on the effective set of configuration parameters read from the requirements files of dependent packages and project files, CMT commands build the packages, generate the environment for their use, or query the packages. The main focus was on build time performance that was optimised within several approaches: reduction of the number of reads of requirements files that are now read once per package by a CMT build command that generates cached requirements files for subsequent CMT build commands; introduction of more fine-grained build parallelism at package task level, i.e., dependent applications and libraries are compiled in parallel; code optimisation of CMT commands used for build; introduction of package level build parallelism, i. e., parallelise the build of independent packages. By default, CMT launches NUMBER-OF-PROCESSORS build commands in parallel. The other focus was on CMT commands optimisation in general that made them approximately 2 times faster. CMT can generate a cached requirements file for the environment setup command, which is especially useful for deployment on distributed file systems like AFS or CERN VMFS. The use of parallelism, caching and code optimisation significantly-by several times-reduced software build time, environment setup time, increased the efficiency of multi-core computing resources utilisation, and considerably improved software developer and user experience.

Integration of environmental aspects in modelling and optimisation of water supply chains.

PubMed

Koleva, Mariya N; Calderón, Andrés J; Zhang, Di; Styan, Craig A; Papageorgiou, Lazaros G

2018-04-26

Climate change becomes increasingly more relevant in the context of water systems planning. Tools are necessary to provide the most economic investment option considering the reliability of the infrastructure from technical and environmental perspectives. Accordingly, in this work, an optimisation approach, formulated as a spatially-explicit multi-period Mixed Integer Linear Programming (MILP) model, is proposed for the design of water supply chains at regional and national scales. The optimisation framework encompasses decisions such as installation of new purification plants, capacity expansion, and raw water trading schemes. The objective is to minimise the total cost incurring from capital and operating expenditures. Assessment of available resources for withdrawal is performed based on hydrological balances, governmental rules and sustainable limits. In the light of the increasing importance of reliability of water supply, a second objective, seeking to maximise the reliability of the supply chains, is introduced. The epsilon-constraint method is used as a solution procedure for the multi-objective formulation. Nash bargaining approach is applied to investigate the fair trade-offs between the two objectives and find the Pareto optimality. The models' capability is addressed through a case study based on Australia. The impact of variability in key input parameters is tackled through the implementation of a rigorous global sensitivity analysis (GSA). The findings suggest that variations in water demand can be more disruptive for the water supply chain than scenarios in which rainfalls are reduced. The frameworks can facilitate governmental multi-aspect decision making processes for the adequate and strategic investments of regional water supply infrastructure. Copyright © 2018. Published by Elsevier B.V.

A novel artificial immune clonal selection classification and rule mining with swarm learning model

NASA Astrophysics Data System (ADS)

Al-Sheshtawi, Khaled A.; Abdul-Kader, Hatem M.; Elsisi, Ashraf B.

2013-06-01

Metaheuristic optimisation algorithms have become popular choice for solving complex problems. By integrating Artificial Immune clonal selection algorithm (CSA) and particle swarm optimisation (PSO) algorithm, a novel hybrid Clonal Selection Classification and Rule Mining with Swarm Learning Algorithm (CS2) is proposed. The main goal of the approach is to exploit and explore the parallel computation merit of Clonal Selection and the speed and self-organisation merits of Particle Swarm by sharing information between clonal selection population and particle swarm. Hence, we employed the advantages of PSO to improve the mutation mechanism of the artificial immune CSA and to mine classification rules within datasets. Consequently, our proposed algorithm required less training time and memory cells in comparison to other AIS algorithms. In this paper, classification rule mining has been modelled as a miltiobjective optimisation problem with predictive accuracy. The multiobjective approach is intended to allow the PSO algorithm to return an approximation to the accuracy and comprehensibility border, containing solutions that are spread across the border. We compared our proposed algorithm classification accuracy CS2 with five commonly used CSAs, namely: AIRS1, AIRS2, AIRS-Parallel, CLONALG, and CSCA using eight benchmark datasets. We also compared our proposed algorithm classification accuracy CS2 with other five methods, namely: Naïve Bayes, SVM, MLP, CART, and RFB. The results show that the proposed algorithm is comparable to the 10 studied algorithms. As a result, the hybridisation, built of CSA and PSO, can develop respective merit, compensate opponent defect, and make search-optimal effect and speed better.

Nonlinear effective theory of dark energy

NASA Astrophysics Data System (ADS)

Cusin, Giulia; Lewandowski, Matthew; Vernizzi, Filippo

2018-04-01

We develop an approach to parametrize cosmological perturbations beyond linear order for general dark energy and modified gravity models characterized by a single scalar degree of freedom. We derive the full nonlinear action, focusing on Horndeski theories. In the quasi-static, non-relativistic limit, there are a total of six independent relevant operators, three of which start at nonlinear order. The new nonlinear couplings modify, beyond linear order, the generalized Poisson equation relating the Newtonian potential to the matter density contrast. We derive this equation up to cubic order in perturbations and, in a companion article [1], we apply it to compute the one-loop matter power spectrum. Within this approach, we also discuss the Vainshtein regime around spherical sources and the relation between the Vainshtein scale and the nonlinear scale for structure formation.

Analysis of optimisation method for a two-stroke piston ring using the Finite Element Method and the Simulated Annealing Method

NASA Astrophysics Data System (ADS)

Kaliszewski, M.; Mazuro, P.

2016-09-01

Simulated Annealing Method of optimisation for the sealing piston ring geometry is tested. The aim of optimisation is to develop ring geometry which would exert demanded pressure on a cylinder just while being bended to fit the cylinder. Method of FEM analysis of an arbitrary piston ring geometry is applied in an ANSYS software. The demanded pressure function (basing on formulae presented by A. Iskra) as well as objective function are introduced. Geometry definition constructed by polynomials in radial coordinate system is delivered and discussed. Possible application of Simulated Annealing Method in a piston ring optimisation task is proposed and visualised. Difficulties leading to possible lack of convergence of optimisation are presented. An example of an unsuccessful optimisation performed in APDL is discussed. Possible line of further optimisation improvement is proposed.

Detection of Differential Item Functioning with Nonlinear Regression: A Non-IRT Approach Accounting for Guessing

ERIC Educational Resources Information Center

Drabinová, Adéla; Martinková, Patrícia

2017-01-01

In this article we present a general approach not relying on item response theory models (non-IRT) to detect differential item functioning (DIF) in dichotomous items with presence of guessing. The proposed nonlinear regression (NLR) procedure for DIF detection is an extension of method based on logistic regression. As a non-IRT approach, NLR can…

Sliding mode control: an approach to regulate nonlinear chemical processes

PubMed

Camacho; Smith

2000-01-01

A new approach for the design of sliding mode controllers based on a first-order-plus-deadtime model of the process, is developed. This approach results in a fixed structure controller with a set of tuning equations as a function of the characteristic parameters of the model. The controller performance is judged by simulations on two nonlinear chemical processes.

A seesaw-type approach for enhancing nonlinear energy harvesting

NASA Astrophysics Data System (ADS)

Deng, Huaxia; Wang, Zhemin; Du, Yu; Zhang, Jin; Ma, Mengchao; Zhong, Xiang

2018-05-01

Harvesting sustainable mechanical energy is the ultimate objective of nonlinear energy harvesters. However, overcoming potential barriers, especially without the use of extra excitations, poses a great challenge for the development of nonlinear generators. In contrast to the existing methods, which typically modify the barrier height or utilize additional excitations, this letter proposes a seesaw-type approach to facilitate escape from potential wells by transfer of internal energy, even under low-intensity excitation. This approach is adopted in the design of a seesaw-type nonlinear piezoelectric energy harvester and the energy transfer process is analyzed by deriving expressions for the energy to reveal the working mechanism. Comparison experiments demonstrate that this approach improves energy harvesting in terms of an increase in the working frequency bandwidth by a factor of 60.14 and an increase in the maximum output voltage by a factor of 5.1. Moreover, the output power is increased by a factor of 51.3, which indicates that this approach significantly improves energy collection efficiency. This seesaw-type approach provides a welcome boost to the development of renewable energy collection methods by improving the efficiency of harvesting of low-intensity ambient mechanical energy.

Chaos, patterns, coherent structures, and turbulence: Reflections on nonlinear science.

PubMed

Ecke, Robert E

2015-09-01

The paradigms of nonlinear science were succinctly articulated over 25 years ago as deterministic chaos, pattern formation, coherent structures, and adaptation/evolution/learning. For chaos, the main unifying concept was universal routes to chaos in general nonlinear dynamical systems, built upon a framework of bifurcation theory. Pattern formation focused on spatially extended nonlinear systems, taking advantage of symmetry properties to develop highly quantitative amplitude equations of the Ginzburg-Landau type to describe early nonlinear phenomena in the vicinity of critical points. Solitons, mathematically precise localized nonlinear wave states, were generalized to a larger and less precise class of coherent structures such as, for example, concentrated regions of vorticity from laboratory wake flows to the Jovian Great Red Spot. The combination of these three ideas was hoped to provide the tools and concepts for the understanding and characterization of the strongly nonlinear problem of fluid turbulence. Although this early promise has been largely unfulfilled, steady progress has been made using the approaches of nonlinear science. I provide a series of examples of bifurcations and chaos, of one-dimensional and two-dimensional pattern formation, and of turbulence to illustrate both the progress and limitations of the nonlinear science approach. As experimental and computational methods continue to improve, the promise of nonlinear science to elucidate fluid turbulence continues to advance in a steady manner, indicative of the grand challenge nature of strongly nonlinear multi-scale dynamical systems.

[Inter-disciplinary approach of a mobile team specialised in geriatric oncology].

PubMed

Benyahia, Stéphanie; Cudennec, Tristan

2015-01-01

Ageing is an individual process. Chronological age does not reflect life expectancy or functional capacity. That is why, in geriatric oncology, the estimation of this capacity is a determining factor. An inter-disciplinary approach is necessary in order to coordinate the different players in the care and optimise the hospitalisation of elderly patients with multiple pathologies, all the more so when they are suffering from cancer. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Observability of nonlinear dynamics: normalized results and a time-series approach.

PubMed

Aguirre, Luis A; Bastos, Saulo B; Alves, Marcela A; Letellier, Christophe

2008-03-01

This paper investigates the observability of nonlinear dynamical systems. Two difficulties associated with previous studies are dealt with. First, a normalized degree observability is defined. This permits the comparison of different systems, which was not generally possible before. Second, a time-series approach is proposed based on omnidirectional nonlinear correlation functions to rank a set of time series of a system in terms of their potential use to reconstruct the original dynamics without requiring the knowledge of the system equations. The two approaches proposed in this paper and a former method were applied to five benchmark systems and an overall agreement of over 92% was found.

Traduction et langues de specialite: Approches theoriques et considerations pedagogiques (Translation and Specialty Languages: Theoretical Approaches and Pedagogic Considerations).

ERIC Educational Resources Information Center

Guevel, Zelie, Ed.; Valentine, Egan, Ed.

Essays on the teaching of translation and on specialized translation, all in French, include: "Perspectives d'optimisation de la formation du traducteur: quelques reflexions" ("Perspectives on Optimization of Training of Translation Teachers: Some Reflections") (Egan Valentine); "L'enseignement de la revision…

A Strategy-Based Approach towards Optimising Research Output

ERIC Educational Resources Information Center

Lues, L.

2013-01-01

The South African higher education fraternity has experienced an outflow of senior research capacity during the past decade, resulting in a large influx of younger and less-published academics. More emphasis is therefore placed on the role of the central institution in ensuring research output. The Faculty of Economic and Management Sciences at a…

[The representation of scientific research through a poster].

PubMed

Dupin, Cécile-Marie

2013-12-01

The poster is a medium of scientific communication. When presented in public, it optimises the value of an original research approach. The poster sessions are devoted to one-to-one exchanges with peers on the subject of the research. The poster can help to integrate scientific knowledge into the nursing decision-making process.

Utilisation and Satisfaction with Rehabilitation Services in Children with Primary Language Impairment Transitioning to School: Parents' Perspective

ERIC Educational Resources Information Center

Mazer, Barbara; Dion, Karyne; Moryoussef, Aguy

2017-01-01

Children with disabilities require coordinated services to optimise transition into school. This study compared type, frequency and approach to service utilisation for children with primary language impairment transitioning from rehabilitation to the educational system, and examined parent satisfaction. Parents responded to a telephone…

Expressing the human proteome for affinity proteomics: optimising expression of soluble protein domains and in vivo biotinylation.

PubMed

Keates, Tracy; Cooper, Christopher D O; Savitsky, Pavel; Allerston, Charles K; Phillips, Claire; Hammarström, Martin; Daga, Neha; Berridge, Georgina; Mahajan, Pravin; Burgess-Brown, Nicola A; Müller, Susanne; Gräslund, Susanne; Gileadi, Opher

2012-06-15

The generation of affinity reagents to large numbers of human proteins depends on the ability to express the target proteins as high-quality antigens. The Structural Genomics Consortium (SGC) focuses on the production and structure determination of human proteins. In a 7-year period, the SGC has deposited crystal structures of >800 human protein domains, and has additionally expressed and purified a similar number of protein domains that have not yet been crystallised. The targets include a diversity of protein domains, with an attempt to provide high coverage of protein families. The family approach provides an excellent basis for characterising the selectivity of affinity reagents. We present a summary of the approaches used to generate purified human proteins or protein domains, a test case demonstrating the ability to rapidly generate new proteins, and an optimisation study on the modification of >70 proteins by biotinylation in vivo. These results provide a unique synergy between large-scale structural projects and the recent efforts to produce a wide coverage of affinity reagents to the human proteome. Copyright © 2011 Elsevier B.V. All rights reserved.

Statistical methods for convergence detection of multi-objective evolutionary algorithms.

PubMed

Trautmann, H; Wagner, T; Naujoks, B; Preuss, M; Mehnen, J

2009-01-01

In this paper, two approaches for estimating the generation in which a multi-objective evolutionary algorithm (MOEA) shows statistically significant signs of convergence are introduced. A set-based perspective is taken where convergence is measured by performance indicators. The proposed techniques fulfill the requirements of proper statistical assessment on the one hand and efficient optimisation for real-world problems on the other hand. The first approach accounts for the stochastic nature of the MOEA by repeating the optimisation runs for increasing generation numbers and analysing the performance indicators using statistical tools. This technique results in a very robust offline procedure. Moreover, an online convergence detection method is introduced as well. This method automatically stops the MOEA when either the variance of the performance indicators falls below a specified threshold or a stagnation of their overall trend is detected. Both methods are analysed and compared for two MOEA and on different classes of benchmark functions. It is shown that the methods successfully operate on all stated problems needing less function evaluations while preserving good approximation quality at the same time.

An illustration of new methods in machine condition monitoring, Part I: stochastic resonance

NASA Astrophysics Data System (ADS)

Worden, K.; Antoniadou, I.; Marchesiello, S.; Mba, C.; Garibaldi, L.

2017-05-01

There have been many recent developments in the application of data-based methods to machine condition monitoring. A powerful methodology based on machine learning has emerged, where diagnostics are based on a two-step procedure: extraction of damage-sensitive features, followed by unsupervised learning (novelty detection) or supervised learning (classification). The objective of the current pair of papers is simply to illustrate one state-of-the-art procedure for each step, using synthetic data representative of reality in terms of size and complexity. The first paper in the pair will deal with feature extraction. Although some papers have appeared in the recent past considering stochastic resonance as a means of amplifying damage information in signals, they have largely relied on ad hoc specifications of the resonator used. In contrast, the current paper will adopt a principled optimisation-based approach to the resonator design. The paper will also show that a discrete dynamical system can provide all the benefits of a continuous system, but also provide a considerable speed-up in terms of simulation time in order to facilitate the optimisation approach.

Expressing the human proteome for affinity proteomics: optimising expression of soluble protein domains and in vivo biotinylation

PubMed Central

Keates, Tracy; Cooper, Christopher D.O.; Savitsky, Pavel; Allerston, Charles K.; Phillips, Claire; Hammarström, Martin; Daga, Neha; Berridge, Georgina; Mahajan, Pravin; Burgess-Brown, Nicola A.; Müller, Susanne; Gräslund, Susanne; Gileadi, Opher

2012-01-01

The generation of affinity reagents to large numbers of human proteins depends on the ability to express the target proteins as high-quality antigens. The Structural Genomics Consortium (SGC) focuses on the production and structure determination of human proteins. In a 7-year period, the SGC has deposited crystal structures of >800 human protein domains, and has additionally expressed and purified a similar number of protein domains that have not yet been crystallised. The targets include a diversity of protein domains, with an attempt to provide high coverage of protein families. The family approach provides an excellent basis for characterising the selectivity of affinity reagents. We present a summary of the approaches used to generate purified human proteins or protein domains, a test case demonstrating the ability to rapidly generate new proteins, and an optimisation study on the modification of >70 proteins by biotinylation in vivo. These results provide a unique synergy between large-scale structural projects and the recent efforts to produce a wide coverage of affinity reagents to the human proteome. PMID:22027370

Statistical modelling of thermal annealing of fission tracks in apatite

NASA Astrophysics Data System (ADS)

Laslett, G. M.; Galbraith, R. F.

1996-12-01

We develop an improved methodology for modelling the relationship between mean track length, temperature, and time in fission track annealing experiments. We consider "fanning Arrhenius" models, in which contours of constant mean length on an Arrhenius plot are straight lines meeting at a common point. Features of our approach are explicit use of subject matter knowledge, treating mean length as the response variable, modelling of the mean-variance relationship with two components of variance, improved modelling of the control sample, and using information from experiments in which no tracks are seen. This approach overcomes several weaknesses in previous models and provides a robust six parameter model that is widely applicable. Estimation is via direct maximum likelihood which can be implemented using a standard numerical optimisation package. Because the model is highly nonlinear, some reparameterisations are needed to achieve stable estimation and calculation of precisions. Experience suggests that precisions are more convincingly estimated from profile log-likelihood functions than from the information matrix. We apply our method to the B-5 and Sr fluorapatite data of Crowley et al. (1991) and obtain well-fitting models in both cases. For the B-5 fluorapatite, our model exhibits less fanning than that of Crowley et al. (1991), although fitted mean values above 12 μm are fairly similar. However, predictions can be different, particularly for heavy annealing at geological time scales, where our model is less retentive. In addition, the refined error structure of our model results in tighter prediction errors, and has components of error that are easier to verify or modify. For the Sr fluorapatite, our fitted model for mean lengths does not differ greatly from that of Crowley et al. (1991), but our error structure is quite different.

Modelling the nonlinear behaviour of an underplatform damper test rig for turbine applications

NASA Astrophysics Data System (ADS)

Pesaresi, L.; Salles, L.; Jones, A.; Green, J. S.; Schwingshackl, C. W.

2017-02-01

Underplatform dampers (UPD) are commonly used in aircraft engines to mitigate the risk of high-cycle fatigue failure of turbine blades. The energy dissipated at the friction contact interface of the damper reduces the vibration amplitude significantly, and the couplings of the blades can also lead to significant shifts of the resonance frequencies of the bladed disk. The highly nonlinear behaviour of bladed discs constrained by UPDs requires an advanced modelling approach to ensure that the correct damper geometry is selected during the design of the turbine, and that no unexpected resonance frequencies and amplitudes will occur in operation. Approaches based on an explicit model of the damper in combination with multi-harmonic balance solvers have emerged as a promising way to predict the nonlinear behaviour of UPDs correctly, however rigorous experimental validations are required before approaches of this type can be used with confidence. In this study, a nonlinear analysis based on an updated explicit damper model having different levels of detail is performed, and the results are evaluated against a newly-developed UPD test rig. Detailed linear finite element models are used as input for the nonlinear analysis, allowing the inclusion of damper flexibility and inertia effects. The nonlinear friction interface between the blades and the damper is described with a dense grid of 3D friction contact elements which allow accurate capturing of the underlying nonlinear mechanism that drives the global nonlinear behaviour. The introduced explicit damper model showed a great dependence on the correct contact pressure distribution. The use of an accurate, measurement based, distribution, better matched the nonlinear dynamic behaviour of the test rig. Good agreement with the measured frequency response data could only be reached when the zero harmonic term (constant term) was included in the multi-harmonic expansion of the nonlinear problem, highlighting its importance when the contact interface experiences large normal load variation. The resulting numerical damper kinematics with strong translational and rotational motion, and the global blades frequency response were fully validated experimentally, showing the accuracy of the suggested high detailed explicit UPD modelling approach.

Multidisciplinary design optimisation of a recurve bow based on applications of the autogenetic design theory and distributed computing

NASA Astrophysics Data System (ADS)

Fritzsche, Matthias; Kittel, Konstantin; Blankenburg, Alexander; Vajna, Sándor

2012-08-01

The focus of this paper is to present a method of multidisciplinary design optimisation based on the autogenetic design theory (ADT) that provides methods, which are partially implemented in the optimisation software described here. The main thesis of the ADT is that biological evolution and the process of developing products are mainly similar, i.e. procedures from biological evolution can be transferred into product development. In order to fulfil requirements and boundary conditions of any kind (that may change at any time), both biological evolution and product development look for appropriate solution possibilities in a certain area, and try to optimise those that are actually promising by varying parameters and combinations of these solutions. As the time necessary for multidisciplinary design optimisations is a critical aspect in product development, ways to distribute the optimisation process with the effective use of unused calculating capacity, can reduce the optimisation time drastically. Finally, a practical example shows how ADT methods and distributed optimising are applied to improve a product.

Improved packing of protein side chains with parallel ant colonies.

PubMed

Quan, Lijun; Lü, Qiang; Li, Haiou; Xia, Xiaoyan; Wu, Hongjie

2014-01-01

The accurate packing of protein side chains is important for many computational biology problems, such as ab initio protein structure prediction, homology modelling, and protein design and ligand docking applications. Many of existing solutions are modelled as a computational optimisation problem. As well as the design of search algorithms, most solutions suffer from an inaccurate energy function for judging whether a prediction is good or bad. Even if the search has found the lowest energy, there is no certainty of obtaining the protein structures with correct side chains. We present a side-chain modelling method, pacoPacker, which uses a parallel ant colony optimisation strategy based on sharing a single pheromone matrix. This parallel approach combines different sources of energy functions and generates protein side-chain conformations with the lowest energies jointly determined by the various energy functions. We further optimised the selected rotamers to construct subrotamer by rotamer minimisation, which reasonably improved the discreteness of the rotamer library. We focused on improving the accuracy of side-chain conformation prediction. For a testing set of 442 proteins, 87.19% of X1 and 77.11% of X12 angles were predicted correctly within 40° of the X-ray positions. We compared the accuracy of pacoPacker with state-of-the-art methods, such as CIS-RR and SCWRL4. We analysed the results from different perspectives, in terms of protein chain and individual residues. In this comprehensive benchmark testing, 51.5% of proteins within a length of 400 amino acids predicted by pacoPacker were superior to the results of CIS-RR and SCWRL4 simultaneously. Finally, we also showed the advantage of using the subrotamers strategy. All results confirmed that our parallel approach is competitive to state-of-the-art solutions for packing side chains. This parallel approach combines various sources of searching intelligence and energy functions to pack protein side chains. It provides a frame-work for combining different inaccuracy/usefulness objective functions by designing parallel heuristic search algorithms.

Trajectory tracking in quadrotor platform by using PD controller and LQR control approach

NASA Astrophysics Data System (ADS)

Islam, Maidul; Okasha, Mohamed; Idres, Moumen Mohammad

2017-11-01

The purpose of the paper is to discuss a comparative evaluation of performance of two different controllers i.e. Proportional-Derivative Controller (PD) and Linear Quadratic Regulation (LQR) in Quadrotor dynamic system that is under-actuated with high nonlinearity. As only four states can be controlled at the same time in the Quadrotor, the trajectories are designed on the basis of the four states whereas three dimensional position and rotation along an axis, known as yaw movement are considered. In this work, both the PD controller and LQR control approach are used for Quadrotor nonlinear model to track the trajectories. LQR control approach for nonlinear model is designed on the basis of a linear model of the Quadrotor because the performance of linear model and nonlinear model around certain nominal point is almost similar. Simulink and MATLAB software is used to design the controllers and to evaluate the performance of both the controllers.

Observed-Based Adaptive Fuzzy Tracking Control for Switched Nonlinear Systems With Dead-Zone.

PubMed

Tong, Shaocheng; Sui, Shuai; Li, Yongming

2015-12-01

In this paper, the problem of adaptive fuzzy output-feedback control is investigated for a class of uncertain switched nonlinear systems in strict-feedback form. The considered switched systems contain unknown nonlinearities, dead-zone, and immeasurable states. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions, a switched fuzzy state observer is designed and thus the immeasurable states are obtained by it. By applying the adaptive backstepping design principle and the average dwell time method, an adaptive fuzzy output-feedback tracking control approach is developed. It is proved that the proposed control approach can guarantee that all the variables in the closed-loop system are bounded under a class of switching signals with average dwell time, and also that the system output can track a given reference signal as closely as possible. The simulation results are given to check the effectiveness of the proposed approach.

A novel method to produce nonlinear empirical physical formulas for experimental nonlinear electro-optical responses of doped nematic liquid crystals: Feedforward neural network approach

NASA Astrophysics Data System (ADS)

Yildiz, Nihat; San, Sait Eren; Okutan, Mustafa; Kaya, Hüseyin

2010-04-01

Among other significant obstacles, inherent nonlinearity in experimental physical response data poses severe difficulty in empirical physical formula (EPF) construction. In this paper, we applied a novel method (namely layered feedforward neural network (LFNN) approach) to produce explicit nonlinear EPFs for experimental nonlinear electro-optical responses of doped nematic liquid crystals (NLCs). Our motivation was that, as we showed in a previous theoretical work, an appropriate LFNN, due to its exceptional nonlinear function approximation capabilities, is highly relevant to EPF construction. Therefore, in this paper, we obtained excellently produced LFNN approximation functions as our desired EPFs for above-mentioned highly nonlinear response data of NLCs. In other words, by using suitable LFNNs, we successfully fitted the experimentally measured response and predicted the new (yet-to-be measured) response data. The experimental data (response versus input) were diffraction and dielectric properties versus bias voltage; and they were all taken from our previous experimental work. We conclude that in general, LFNN can be applied to construct various types of EPFs for the corresponding various nonlinear physical perturbation (thermal, electronic, molecular, electric, optical, etc.) data of doped NLCs.

Estimating and Visualizing Nonlinear Relations among Latent Variables: A Semiparametric Approach

ERIC Educational Resources Information Center

Pek, Jolynn; Sterba, Sonya K.; Kok, Bethany E.; Bauer, Daniel J.

2009-01-01

The graphical presentation of any scientific finding enhances its description, interpretation, and evaluation. Research involving latent variables is no exception, especially when potential nonlinear effects are suspect. This article has multiple aims. First, it provides a nontechnical overview of a semiparametric approach to modeling nonlinear…

Confidence Intervals for a Semiparametric Approach to Modeling Nonlinear Relations among Latent Variables

ERIC Educational Resources Information Center

Pek, Jolynn; Losardo, Diane; Bauer, Daniel J.

2011-01-01

Compared to parametric models, nonparametric and semiparametric approaches to modeling nonlinearity between latent variables have the advantage of recovering global relationships of unknown functional form. Bauer (2005) proposed an indirect application of finite mixtures of structural equation models where latent components are estimated in the…

A Bohmian approach to the non-Markovian non-linear Schrödinger–Langevin equation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vargas, Andrés F.; Morales-Durán, Nicolás; Bargueño, Pedro, E-mail: p.bargueno@uniandes.edu.co

2015-05-15

In this work, a non-Markovian non-linear Schrödinger–Langevin equation is derived from the system-plus-bath approach. After analyzing in detail previous Markovian cases, Bohmian mechanics is shown to be a powerful tool for obtaining the desired generalized equation.

An efficient nonlinear finite-difference approach in the computational modeling of the dynamics of a nonlinear diffusion-reaction equation in microbial ecology.

PubMed

Macías-Díaz, J E; Macías, Siegfried; Medina-Ramírez, I E

2013-12-01

In this manuscript, we present a computational model to approximate the solutions of a partial differential equation which describes the growth dynamics of microbial films. The numerical technique reported in this work is an explicit, nonlinear finite-difference methodology which is computationally implemented using Newton's method. Our scheme is compared numerically against an implicit, linear finite-difference discretization of the same partial differential equation, whose computer coding requires an implementation of the stabilized bi-conjugate gradient method. Our numerical results evince that the nonlinear approach results in a more efficient approximation to the solutions of the biofilm model considered, and demands less computer memory. Moreover, the positivity of initial profiles is preserved in the practice by the nonlinear scheme proposed. Copyright © 2013 Elsevier Ltd. All rights reserved.

Time-Reversal Generation of Rogue Waves

NASA Astrophysics Data System (ADS)

Chabchoub, Amin; Fink, Mathias

2014-03-01

The formation of extreme localizations in nonlinear dispersive media can be explained and described within the framework of nonlinear evolution equations, such as the nonlinear Schrödinger equation (NLS). Within the class of exact NLS breather solutions on a finite background, which describe the modulational instability of monochromatic wave trains, the hierarchy of rational solutions localized in both time and space is considered to provide appropriate prototypes to model rogue wave dynamics. Here, we use the time-reversal invariance of the NLS to propose and experimentally demonstrate a new approach to constructing strongly nonlinear localized waves focused in both time and space. The potential applications of this time-reversal approach include remote sensing and motivated analogous experimental analysis in other nonlinear dispersive media, such as optics, Bose-Einstein condensates, and plasma, where the wave motion dynamics is governed by the NLS.

Technique for Very High Order Nonlinear Simulation and Validation

NASA Technical Reports Server (NTRS)

Dyson, Rodger W.

2001-01-01

Finding the sources of sound in large nonlinear fields via direct simulation currently requires excessive computational cost. This paper describes a simple technique for efficiently solving the multidimensional nonlinear Euler equations that significantly reduces this cost and demonstrates a useful approach for validating high order nonlinear methods. Up to 15th order accuracy in space and time methods were compared and it is shown that an algorithm with a fixed design accuracy approaches its maximal utility and then its usefulness exponentially decays unless higher accuracy is used. It is concluded that at least a 7th order method is required to efficiently propagate a harmonic wave using the nonlinear Euler equations to a distance of 5 wavelengths while maintaining an overall error tolerance that is low enough to capture both the mean flow and the acoustics.

Nonlinear mechanics of non-rigid origami: an efficient computational approach

NASA Astrophysics Data System (ADS)

Liu, K.; Paulino, G. H.

2017-10-01

Origami-inspired designs possess attractive applications to science and engineering (e.g. deployable, self-assembling, adaptable systems). The special geometric arrangement of panels and creases gives rise to unique mechanical properties of origami, such as reconfigurability, making origami designs well suited for tunable structures. Although often being ignored, origami structures exhibit additional soft modes beyond rigid folding due to the flexibility of thin sheets that further influence their behaviour. Actual behaviour of origami structures usually involves significant geometric nonlinearity, which amplifies the influence of additional soft modes. To investigate the nonlinear mechanics of origami structures with deformable panels, we present a structural engineering approach for simulating the nonlinear response of non-rigid origami structures. In this paper, we propose a fully nonlinear, displacement-based implicit formulation for performing static/quasi-static analyses of non-rigid origami structures based on `bar-and-hinge' models. The formulation itself leads to an efficient and robust numerical implementation. Agreement between real models and numerical simulations demonstrates the ability of the proposed approach to capture key features of origami behaviour.

Nonlinear mechanics of non-rigid origami: an efficient computational approach.

PubMed

Liu, K; Paulino, G H

2017-10-01

Origami-inspired designs possess attractive applications to science and engineering (e.g. deployable, self-assembling, adaptable systems). The special geometric arrangement of panels and creases gives rise to unique mechanical properties of origami, such as reconfigurability, making origami designs well suited for tunable structures. Although often being ignored, origami structures exhibit additional soft modes beyond rigid folding due to the flexibility of thin sheets that further influence their behaviour. Actual behaviour of origami structures usually involves significant geometric nonlinearity, which amplifies the influence of additional soft modes. To investigate the nonlinear mechanics of origami structures with deformable panels, we present a structural engineering approach for simulating the nonlinear response of non-rigid origami structures. In this paper, we propose a fully nonlinear, displacement-based implicit formulation for performing static/quasi-static analyses of non-rigid origami structures based on 'bar-and-hinge' models. The formulation itself leads to an efficient and robust numerical implementation. Agreement between real models and numerical simulations demonstrates the ability of the proposed approach to capture key features of origami behaviour.

Scalar-vector soliton fiber laser mode-locked by nonlinear polarization rotation.

PubMed

Wu, Zhichao; Liu, Deming; Fu, Songnian; Li, Lei; Tang, Ming; Zhao, Luming

2016-08-08

We report a passively mode-locked fiber laser by nonlinear polarization rotation (NPR), where both vector and scalar soliton can co-exist within the laser cavity. The mode-locked pulse evolves as a vector soliton in the strong birefringent segment and is transformed into a regular scalar soliton after the polarizer within the laser cavity. The existence of solutions in a polarization-dependent cavity comprising a periodic combination of two distinct nonlinear waves is first demonstrated and likely to be applicable to various other nonlinear systems. For very large local birefringence, our laser approaches the operation regime of vector soliton lasers, while it approaches scalar soliton fiber lasers under the condition of very small birefringence.

A Nonlinear Dynamics Approach for Incorporating Wind-Speed Patterns into Wind-Power Project Evaluation

PubMed Central

Huffaker, Ray; Bittelli, Marco

2015-01-01

Wind-energy production may be expanded beyond regions with high-average wind speeds (such as the Midwest U.S.A.) to sites with lower-average speeds (such as the Southeast U.S.A.) by locating favorable regional matches between natural wind-speed and energy-demand patterns. A critical component of wind-power evaluation is to incorporate wind-speed dynamics reflecting documented diurnal and seasonal behavioral patterns. Conventional probabilistic approaches remove patterns from wind-speed data. These patterns must be restored synthetically before they can be matched with energy-demand patterns. How to accurately restore wind-speed patterns is a vexing problem spurring an expanding line of papers. We propose a paradigm shift in wind power evaluation that employs signal-detection and nonlinear-dynamics techniques to empirically diagnose whether synthetic pattern restoration can be avoided altogether. If the complex behavior of observed wind-speed records is due to nonlinear, low-dimensional, and deterministic system dynamics, then nonlinear dynamics techniques can reconstruct wind-speed dynamics from observed wind-speed data without recourse to conventional probabilistic approaches. In the first study of its kind, we test a nonlinear dynamics approach in an application to Sugarland Wind—the first utility-scale wind project proposed in Florida, USA. We find empirical evidence of a low-dimensional and nonlinear wind-speed attractor characterized by strong temporal patterns that match up well with regular daily and seasonal electricity demand patterns. PMID:25617767

An Analytical Dynamics Approach to the Control of Mechanical Systems

NASA Astrophysics Data System (ADS)

Mylapilli, Harshavardhan

A new and novel approach to the control of nonlinear mechanical systems is presented in this study. The approach is inspired by recent results in analytical dynamics that deal with the theory of constrained motion. The control requirements on the dynamical system are viewed from an analytical dynamics perspective and the theory of constrained motion is used to recast these control requirements as constraints on the dynamical system. Explicit closed form expressions for the generalized nonlinear control forces are obtained by using the fundamental equation of mechanics. The control so obtained is optimal at each instant of time and causes the constraints to be exactly satisfied. No linearizations and/or approximations of the nonlinear dynamical system are made, and no a priori structure is imposed on the nature of nonlinear controller. Three examples dealing with highly nonlinear complex dynamical systems that are chosen from diverse areas of discrete and continuum mechanics are presented to demonstrate the control approach. The first example deals with the energy control of underactuated inhomogeneous nonlinear lattices (or chains), the second example deals with the synchronization of the motion of multiple coupled slave gyros with that of a master gyro, and the final example deals with the control of incompressible hyperelastic rubber-like thin cantilever beams. Numerical simulations accompanying these examples show the ease, simplicity and the efficacy with which the control methodology can be applied and the accuracy with which the desired control objectives can be met.

Time domain contact model for tyre/road interaction including nonlinear contact stiffness due to small-scale roughness

NASA Astrophysics Data System (ADS)

Andersson, P. B. U.; Kropp, W.

2008-11-01

Rolling resistance, traction, wear, excitation of vibrations, and noise generation are all attributes to consider in optimisation of the interaction between automotive tyres and wearing courses of roads. The key to understand and describe the interaction is to include a wide range of length scales in the description of the contact geometry. This means including scales on the order of micrometres that have been neglected in previous tyre/road interaction models. A time domain contact model for the tyre/road interaction that includes interfacial details is presented. The contact geometry is discretised into multiple elements forming pairs of matching points. The dynamic response of the tyre is calculated by convolving the contact forces with pre-calculated Green's functions. The smaller-length scales are included by using constitutive interfacial relations, i.e. by using nonlinear contact springs, for each pair of contact elements. The method is presented for normal (out-of-plane) contact and a method for assessing the stiffness of the nonlinear springs based on detailed geometry and elastic data of the tread is suggested. The governing equations of the nonlinear contact problem are solved with the Newton-Raphson iterative scheme. Relations between force, indentation, and contact stiffness are calculated for a single tread block in contact with a road surface. The calculated results have the same character as results from measurements found in literature. Comparison to traditional contact formulations shows that the effect of the small-scale roughness is large; the contact stiffness is only up to half of the stiffness that would result if contact is made over the whole element directly to the bulk of the tread. It is concluded that the suggested contact formulation is a suitable model to include more details of the contact interface. Further, the presented result for the tread block in contact with the road is a suitable input for a global tyre/road interaction model that is also based on the presented contact formulation.

Optimisation in radiotherapy. III: Stochastic optimisation algorithms and conclusions.

PubMed

Ebert, M

1997-12-01

This is the final article in a three part examination of optimisation in radiotherapy. Previous articles have established the bases and form of the radiotherapy optimisation problem, and examined certain types of optimisation algorithm, namely, those which perform some form of ordered search of the solution space (mathematical programming), and those which attempt to find the closest feasible solution to the inverse planning problem (deterministic inversion). The current paper examines algorithms which search the space of possible irradiation strategies by stochastic methods. The resulting iterative search methods move about the solution space by sampling random variates, which gradually become more constricted as the algorithm converges upon the optimal solution. This paper also discusses the implementation of optimisation in radiotherapy practice.

Investigating the Trade-Off Between Power Generation and Environmental Impact of Tidal-Turbine Arrays Using Array Layout Optimisation and Habitat Sustainability Modelling.

NASA Astrophysics Data System (ADS)

du Feu, R. J.; Funke, S. W.; Kramer, S. C.; Hill, J.; Piggott, M. D.

2016-12-01

The installation of tidal turbines into the ocean will inevitably affect the environment around them. However, due to the relative infancy of this sector the extent and severity of such effects is unknown. The layout of an array of turbines is an important factor in determining not only the array's final yield but also how it will influence regional hydrodynamics. This in turn could affect, for example, sediment transportation or habitat suitability. The two potentially competing objectives of extracting energy from the tidal current, and of limiting any environmental impact consequent to influencing that current, are investigated here. This relationship is posed as a multi-objective optimisation problem. OpenTidalFarm, an array layout optimisation tool, and MaxEnt, habitat sustainability modelling software, are used to evaluate scenarios off the coast of the UK. MaxEnt is used to estimate the likelihood of finding a species in a given location based upon environmental input data and presence data of the species. Environmental features which are known to impact habitat, specifically those affected by the presence of an array, such as bed shear stress, are chosen as inputs. MaxEnt then uses a maximum-entropy modelling approach to estimate population distribution across the modelled area. OpenTidalFarm is used to maximise the power generated by an array, or multiple arrays, through adjusting the position and number of turbines within them. It uses a 2D shallow water model with turbine arrays represented as adjustable friction fields. It has the capability to also optimise for user created functionals that can be expressed mathematically. This work uses two functionals; power extracted by the array, and the suitability of habitat as predicted by MaxEnt. A gradient-based local optimisation is used to adjust the array layout at each iteration. This work presents arrays that are optimised for both yield and the viability of habitat for chosen species. In each scenario studied, a range of array formations is found expressing varying preferences for either functional. Further analyses then allow for the identification of trade-offs between the two key societal objectives of energy production and conservation. This in turn produces information valuable to stakeholders and policymakers when making decisions on array design.

Local numerical modelling of ultrasonic guided waves in linear and nonlinear media

NASA Astrophysics Data System (ADS)

Packo, Pawel; Radecki, Rafal; Kijanka, Piotr; Staszewski, Wieslaw J.; Uhl, Tadeusz; Leamy, Michael J.

2017-04-01

Nonlinear ultrasonic techniques provide improved damage sensitivity compared to linear approaches. The combination of attractive properties of guided waves, such as Lamb waves, with unique features of higher harmonic generation provides great potential for characterization of incipient damage, particularly in plate-like structures. Nonlinear ultrasonic structural health monitoring techniques use interrogation signals at frequencies other than the excitation frequency to detect changes in structural integrity. Signal processing techniques used in non-destructive evaluation are frequently supported by modeling and numerical simulations in order to facilitate problem solution. This paper discusses known and newly-developed local computational strategies for simulating elastic waves, and attempts characterization of their numerical properties in the context of linear and nonlinear media. A hybrid numerical approach combining advantages of the Local Interaction Simulation Approach (LISA) and Cellular Automata for Elastodynamics (CAFE) is proposed for unique treatment of arbitrary strain-stress relations. The iteration equations of the method are derived directly from physical principles employing stress and displacement continuity, leading to an accurate description of the propagation in arbitrarily complex media. Numerical analysis of guided wave propagation, based on the newly developed hybrid approach, is presented and discussed in the paper for linear and nonlinear media. Comparisons to Finite Elements (FE) are also discussed.

Neurobiologically Inspired Approaches to Nonlinear Process Control and Modeling

DTIC Science & Technology

1999-12-31

incorporates second messenger reaction kinetics and calcium dynamics to represent the nonlinear dynamics and the crucial role of neuromodulation in local...reflex). The dynamic neuromodulation as a mechanism for the nonlinear attenuation is the novel result of this study. Ear- lier simulations have shown

A data-driven approach for modeling post-fire debris-flow volumes and their uncertainty

USGS Publications Warehouse

Friedel, Michael J.

2011-01-01

This study demonstrates the novel application of genetic programming to evolve nonlinear post-fire debris-flow volume equations from variables associated with a data-driven conceptual model of the western United States. The search space is constrained using a multi-component objective function that simultaneously minimizes root-mean squared and unit errors for the evolution of fittest equations. An optimization technique is then used to estimate the limits of nonlinear prediction uncertainty associated with the debris-flow equations. In contrast to a published multiple linear regression three-variable equation, linking basin area with slopes greater or equal to 30 percent, burn severity characterized as area burned moderate plus high, and total storm rainfall, the data-driven approach discovers many nonlinear and several dimensionally consistent equations that are unbiased and have less prediction uncertainty. Of the nonlinear equations, the best performance (lowest prediction uncertainty) is achieved when using three variables: average basin slope, total burned area, and total storm rainfall. Further reduction in uncertainty is possible for the nonlinear equations when dimensional consistency is not a priority and by subsequently applying a gradient solver to the fittest solutions. The data-driven modeling approach can be applied to nonlinear multivariate problems in all fields of study.

A scattering approach to sea wave diffraction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Corradini, M. L., E-mail: letizia.corradini@unicam.it; Garbuglia, M., E-mail: milena.garbuglia@unicam.it; Maponi, P., E-mail: pierluigi.maponi@unicam.it

This paper intends to show a model for the diffraction of sea waves approaching an OWC device, which converts the sea waves motion into mechanical energy and then electrical energy. This is a preliminary study to the optimisation of the device, in fact the computation of sea waves diffraction around the device allows the estimation of the sea waves energy which enters into the device. The computation of the diffraction phenomenon is the result of a sea waves scattering problem, solved with an integral equation method.

A novel textile characterisation approach using an embedded sensor system and segmented textile manipulation

NASA Astrophysics Data System (ADS)

Fial, Julian; Carosella, Stefan; Langheinz, Mario; Wiest, Patrick; Middendorf, Peter

2018-05-01

This paper investigates the application of sensors on carbon fibre textiles for the purpose of textile characterisation and draping process optimisation. The objective is to analyse a textile's condition during the draping operation and actively manipulate boundary conditions in order to create better preform qualities. Various realisations of textile integrated sensors are presented, focusing on the measurement of textile strain. Furthermore, a complex textile characterisation approach is presented where these sensors shall be implemented in.

Non-linear modeling of RF in fusion grade plasmas

NASA Astrophysics Data System (ADS)

Austin, Travis; Smithe, David; Hakim, Ammar; Jenkins, Thomas

2011-10-01

We are seeking to model nonlinear effects, particularly parametric decay instability in the vicinity of the edge plasma and RF launchers, which is thought to be a potential parasitic loss mechanism. We will use time-domain approaches which treat the full spectrum of modes. Two approaches are being tested for feasibility, a non-linear delta-f particle approach, and a higher order many-fluid closure approach. Our particle approach builds on extensive previous work demonstrating the ability to model IBW waves (one of the PDI daughter waves) with a linear delta-f particle model. Here we report on the performance of such simulations when the linear constraint is relaxed, and in particular on the ability of the low-noise loading scheme, specially developed for RF and ion-time scale physics, to operate and maintain low noise in the non-linear regime. Similarly, a novel high-order closure of the fluid equations is necessary to model the IBW and higher harmonics. We will report on the benchmarking of the fluid closure, and its ability to model the anticipated pump and daughter waves in a PDI scenario. This research supported by US DOE Grant # DE-SC0006242.

A Bayesian approach to identifying structural nonlinearity using free-decay response: Application to damage detection in composites

USGS Publications Warehouse

Nichols, J.M.; Link, W.A.; Murphy, K.D.; Olson, C.C.

2010-01-01

This work discusses a Bayesian approach to approximating the distribution of parameters governing nonlinear structural systems. Specifically, we use a Markov Chain Monte Carlo method for sampling the posterior parameter distributions thus producing both point and interval estimates for parameters. The method is first used to identify both linear and nonlinear parameters in a multiple degree-of-freedom structural systems using free-decay vibrations. The approach is then applied to the problem of identifying the location, size, and depth of delamination in a model composite beam. The influence of additive Gaussian noise on the response data is explored with respect to the quality of the resulting parameter estimates.

Flat nonlinear optics: metasurfaces for efficient frequency mixing

NASA Astrophysics Data System (ADS)

Nookala, Nishant; Lee, Jongwon; Liu, Yingnan; Bishop, Wells; Tymchenko, Mykhailo; Gomez-Diaz, J. Sebastian; Demmerle, Frederic; Boehm, Gerhard; Amann, Markus-Christian; Wolf, Omri; Brener, Igal; Alu, Andrea; Belkin, Mikhail A.

2017-02-01

Gradient metasurfaces, or ultrathin optical components with engineered transverse impedance gradients along the surface, are able to locally control the phase and amplitude of the scattered fields over subwavelength scales, enabling a broad range of linear components in a flat, integrable platform1-4. On the contrary, due to the weakness of their nonlinear optical responses, conventional nonlinear optical components are inherently bulky, with stringent requirements associated with phase matching and poor control over the phase and amplitude of the generated beam. Nonlinear metasurfaces have been recently proposed to enable frequency conversion in thin films without phase-matching constraints and subwavelength control of the local nonlinear phase5-8. However, the associated optical nonlinearities are far too small to produce significant nonlinear conversion efficiency and compete with conventional nonlinear components for pump intensities below the materials damage threshold. Here, we report multi-quantum-well based gradient nonlinear metasurfaces with second-order nonlinear susceptibility over 106 pm/V for second harmonic generation at a fundamental pump wavelength of 10 μm, 5-6 orders of magnitude larger than traditional crystals. Further, we demonstrate the efficacy of this approach to designing metasurfaces optimized for frequency conversion over a large range of wavelengths, by reporting multi-quantum-well and metasurface structures optimized for a pump wavelength of 6.7 μm. Finally, we demonstrate how the phase of this nonlinearly generated light can be locally controlled well below the diffraction limit using the Pancharatnam-Berry phase approach5,7,9, opening a new paradigm for ultrathin, flat nonlinear optical components.

Performance comparisons between PCA-EA-LBG and PCA-LBG-EA approaches in VQ codebook generation for image compression

NASA Astrophysics Data System (ADS)

Tsai, Jinn-Tsong; Chou, Ping-Yi; Chou, Jyh-Horng

2015-11-01

The aim of this study is to generate vector quantisation (VQ) codebooks by integrating principle component analysis (PCA) algorithm, Linde-Buzo-Gray (LBG) algorithm, and evolutionary algorithms (EAs). The EAs include genetic algorithm (GA), particle swarm optimisation (PSO), honey bee mating optimisation (HBMO), and firefly algorithm (FF). The study is to provide performance comparisons between PCA-EA-LBG and PCA-LBG-EA approaches. The PCA-EA-LBG approaches contain PCA-GA-LBG, PCA-PSO-LBG, PCA-HBMO-LBG, and PCA-FF-LBG, while the PCA-LBG-EA approaches contain PCA-LBG, PCA-LBG-GA, PCA-LBG-PSO, PCA-LBG-HBMO, and PCA-LBG-FF. All training vectors of test images are grouped according to PCA. The PCA-EA-LBG used the vectors grouped by PCA as initial individuals, and the best solution gained by the EAs was given for LBG to discover a codebook. The PCA-LBG approach is to use the PCA to select vectors as initial individuals for LBG to find a codebook. The PCA-LBG-EA used the final result of PCA-LBG as an initial individual for EAs to find a codebook. The search schemes in PCA-EA-LBG first used global search and then applied local search skill, while in PCA-LBG-EA first used local search and then employed global search skill. The results verify that the PCA-EA-LBG indeed gain superior results compared to the PCA-LBG-EA, because the PCA-EA-LBG explores a global area to find a solution, and then exploits a better one from the local area of the solution. Furthermore the proposed PCA-EA-LBG approaches in designing VQ codebooks outperform existing approaches shown in the literature.

Optimisation on processing parameters for minimising warpage on side arm using response surface methodology (RSM) and particle swarm optimisation (PSO)

NASA Astrophysics Data System (ADS)

Rayhana, N.; Fathullah, M.; Shayfull, Z.; Nasir, S. M.; Hazwan, M. H. M.; Sazli, M.; Yahya, Z. R.

2017-09-01

This study presents the application of optimisation method to reduce the warpage of side arm part. Autodesk Moldflow Insight software was integrated into this study to analyse the warpage. The design of Experiment (DOE) for Response Surface Methodology (RSM) was constructed and by using the equation from RSM, Particle Swarm Optimisation (PSO) was applied. The optimisation method will result in optimised processing parameters with minimum warpage. Mould temperature, melt temperature, packing pressure, packing time and cooling time was selected as the variable parameters. Parameters selection was based on most significant factor affecting warpage stated by previous researchers. The results show that warpage was improved by 28.16% for RSM and 28.17% for PSO. The warpage improvement in PSO from RSM is only by 0.01 %. Thus, the optimisation using RSM is already efficient to give the best combination parameters and optimum warpage value for side arm part. The most significant parameters affecting warpage are packing pressure.

Optimisation study of a vehicle bumper subsystem with fuzzy parameters

NASA Astrophysics Data System (ADS)

Farkas, L.; Moens, D.; Donders, S.; Vandepitte, D.

2012-10-01

This paper deals with the design and optimisation for crashworthiness of a vehicle bumper subsystem, which is a key scenario for vehicle component design. The automotive manufacturers and suppliers have to find optimal design solutions for such subsystems that comply with the conflicting requirements of the regulatory bodies regarding functional performance (safety and repairability) and regarding the environmental impact (mass). For the bumper design challenge, an integrated methodology for multi-attribute design engineering of mechanical structures is set up. The integrated process captures the various tasks that are usually performed manually, this way facilitating the automated design iterations for optimisation. Subsequently, an optimisation process is applied that takes the effect of parametric uncertainties into account, such that the system level of failure possibility is acceptable. This optimisation process is referred to as possibility-based design optimisation and integrates the fuzzy FE analysis applied for the uncertainty treatment in crash simulations. This process is the counterpart of the reliability-based design optimisation used in a probabilistic context with statistically defined parameters (variabilities).

Towards homoscedastic nonlinear cointegration for structural health monitoring

NASA Astrophysics Data System (ADS)

Zolna, Konrad; Dao, Phong B.; Staszewski, Wieslaw J.; Barszcz, Tomasz

2016-06-01

The paper presents the homoscedastic nonlinear cointegration. The method leads to stable variances in nonlinear cointegration residuals. The adapted Breusch-Pagan test procedure is developed to test for the presence of heteroscedasticity (or homoscedasticity) in the cointegration residuals obtained from the nonlinear cointegration analysis. Three different time series - i.e. one with a nonlinear quadratic deterministic trend, simulated vibration data and experimental wind turbine data - are used to illustrate the application of the proposed method. The proposed approach can be used for effective removal of nonlinear trends from various types of data and for reliable structural damage detection based on data that are corrupted by environmental and/or operational nonlinear trends.

Nonlinear graphene plasmonics

PubMed Central

2017-01-01

The rapid development of graphene has opened up exciting new fields in graphene plasmonics and nonlinear optics. Graphene's unique two-dimensional band structure provides extraordinary linear and nonlinear optical properties, which have led to extreme optical confinement in graphene plasmonics and ultrahigh nonlinear optical coefficients, respectively. The synergy between graphene's linear and nonlinear optical properties gave rise to nonlinear graphene plasmonics, which greatly augments graphene-based nonlinear device performance beyond a billion-fold. This nascent field of research will eventually find far-reaching revolutionary technological applications that require device miniaturization, low power consumption and a broad range of operating wavelengths approaching the far-infrared, such as optical computing, medical instrumentation and security applications. PMID:29118665

Nonlinear graphene plasmonics

NASA Astrophysics Data System (ADS)

Ooi, Kelvin J. A.; Tan, Dawn T. H.

2017-10-01

The rapid development of graphene has opened up exciting new fields in graphene plasmonics and nonlinear optics. Graphene's unique two-dimensional band structure provides extraordinary linear and nonlinear optical properties, which have led to extreme optical confinement in graphene plasmonics and ultrahigh nonlinear optical coefficients, respectively. The synergy between graphene's linear and nonlinear optical properties gave rise to nonlinear graphene plasmonics, which greatly augments graphene-based nonlinear device performance beyond a billion-fold. This nascent field of research will eventually find far-reaching revolutionary technological applications that require device miniaturization, low power consumption and a broad range of operating wavelengths approaching the far-infrared, such as optical computing, medical instrumentation and security applications.

Nonlinear Instability of Hypersonic Flow past a Wedge

NASA Technical Reports Server (NTRS)

Seddougui, Sharon O.; Bassom, Andrew P.

1991-01-01

The nonlinear stability of a compressible flow past a wedge is investigated in the hypersonic limit. The analysis follows the ideas of a weakly nonlinear approach. Interest is focussed on Tollmien-Schlichting waves governed by a triple deck structure and it is found that the attached shock can profoundly affect the stability characteristics of the flow. In particular, it is shown that nonlinearity tends to have a stabilizing influence. The nonlinear evolution of the Tollmien-Schlichting mode is described in a number of asymptotic limits.

Tuning group-velocity dispersion by optical force.

PubMed

Jiang, Wei C; Lin, Qiang

2013-07-15

We propose an optomechanical approach for dispersion dynamic tuning and microengineering by taking advantage of the optical force in nano-optomechanical structures. Simulations of a suspended coupled silicon waveguide show that the zero-dispersion wavelength can be tuned by 40 nm by an optical pump power of 3 mW. Our approach exhibits great potential for broad applications in dispersion-sensitive processes, which not only offers a new root toward versatile tunable nonlinear photonics but may also open up a great avenue toward a new regime of nonlinear dynamics coupling between nonlinear optical and optomechanical effects.

Simulation of nonlinear convective thixotropic liquid with Cattaneo-Christov heat flux

NASA Astrophysics Data System (ADS)

Zubair, M.; Waqas, M.; Hayat, T.; Ayub, M.; Alsaedi, A.

2018-03-01

In this communication we utilized a modified Fourier approach featuring thermal relaxation effect in nonlinear convective flow by a vertical exponentially stretchable surface. Temperature-dependent thermal conductivity describes the heat transfer process. Thixotropic liquid is modeled. Convergent local similar solutions by homotopic approach are obtained. Graphical results for emerging parameters of interest are analyzed. Skin friction is calculated and interpreted. Consideration of larger local buoyancy and nonlinear convection parameters yields an enhancement in velocity distribution. Temperature and thermal layer thickness are reduced for larger thermal relaxation factor.

Teaching and Learning in the Digital Era: A Case Study of Video-Conference Lectures from Japan to Australia

ERIC Educational Resources Information Center

Yasumoto, Seiko

2014-01-01

"Blended learning" has been attracting academic interest catalysed by the advance of mixed-media technology and has significance for the global educational community and evolutionary development of pedagogical approaches to optimise student learning. This paper examines one aspect of blended teaching of Japanese language and culture in…

Moving towards Optimising Demand-Led Learning: The 2005-2007 ECUANET Leonardo Da Vinci Project

ERIC Educational Resources Information Center

Dealtry, Richard; Howard, Keith

2008-01-01

Purpose: The purpose of this paper is to present the key project learning points and outcomes as a guideline for the future quality management of demand-led learning and development. Design/methodology/approach: The research methodology was based upon a corporate university blueprint architecture and browser toolkit developed by a member of the…

Education for Peace and a Pedagogy of Hope

ERIC Educational Resources Information Center

Carl, A. E.

2011-01-01

There are many approaches and arguments on how hope could be given to children in a society characterised by violence and conflict, hope that may contribute towards optimising their potential. This article focuses on the notion and meaning of Peace Education, what the possible link between Peace Education and a Pedagogy of Hope might be and…

[The medicine use pathway in paediatrics].

PubMed

Didelot, Nicolas

2016-01-01

The medicine use pathway is a process which is constantly evolving in order to comply with intangible rules. As in other therapeutic fields, the drug regimen in paediatrics must tolerate no error and must be able to detect all warning signs, however minor, in order to optimise this approach. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Optimising Inter-Disciplinary Problem-Based Learning in Postgraduate Environmental and Science Education: Recommendations from a Case Study

ERIC Educational Resources Information Center

Redshaw, Clare H; Frampton, Ian

2014-01-01

As the value of multi-disciplinary working in the business and research worlds is becoming more recognised, the number of inter-disciplinary postgraduate environmental and health sciences courses is also increasing. Equally, the popularity of problem-based learning (PBL) is expected to grow and influence instructional approaches in many…

CLASS Challenging Tasks: Using Cognitive Load Theory to Inform the Design of Challenging Mathematical Tasks

ERIC Educational Resources Information Center

Russo, James; Hopkins, Sarah

2017-01-01

This paper outlines a seven-step process for developing problem-solving tasks informed by cognitive load theory. Through an example of a task developed for Year 2 students, we show how this approach can be used to produce challenging mathematical tasks that aim to optimise cognitive load for each student.

An Alternative Approach for Nonlinear Latent Variable Models

ERIC Educational Resources Information Center

Mooijaart, Ab; Bentler, Peter M.

2010-01-01

In the last decades there has been an increasing interest in nonlinear latent variable models. Since the seminal paper of Kenny and Judd, several methods have been proposed for dealing with these kinds of models. This article introduces an alternative approach. The methodology involves fitting some third-order moments in addition to the means and…

A Bayesian Approach for Nonlinear Structural Equation Models with Dichotomous Variables Using Logit and Probit Links

ERIC Educational Resources Information Center

Lee, Sik-Yum; Song, Xin-Yuan; Cai, Jing-Heng

2010-01-01

Analysis of ordered binary and unordered binary data has received considerable attention in social and psychological research. This article introduces a Bayesian approach, which has several nice features in practical applications, for analyzing nonlinear structural equation models with dichotomous data. We demonstrate how to use the software…

A Bayesian approach for estimating under-reported dengue incidence with a focus on non-linear associations between climate and dengue in Dhaka, Bangladesh.

PubMed

Sharmin, Sifat; Glass, Kathryn; Viennet, Elvina; Harley, David

2018-04-01

Determining the relation between climate and dengue incidence is challenging due to under-reporting of disease and consequent biased incidence estimates. Non-linear associations between climate and incidence compound this. Here, we introduce a modelling framework to estimate dengue incidence from passive surveillance data while incorporating non-linear climate effects. We estimated the true number of cases per month using a Bayesian generalised linear model, developed in stages to adjust for under-reporting. A semi-parametric thin-plate spline approach was used to quantify non-linear climate effects. The approach was applied to data collected from the national dengue surveillance system of Bangladesh. The model estimated that only 2.8% (95% credible interval 2.7-2.8) of all cases in the capital Dhaka were reported through passive case reporting. The optimal mean monthly temperature for dengue transmission is 29℃ and average monthly rainfall above 15 mm decreases transmission. Our approach provides an estimate of true incidence and an understanding of the effects of temperature and rainfall on dengue transmission in Dhaka, Bangladesh.

An interactive approach based on a discrete differential evolution algorithm for a class of integer bilevel programming problems

NASA Astrophysics Data System (ADS)

Li, Hong; Zhang, Li; Jiao, Yong-Chang

2016-07-01

This paper presents an interactive approach based on a discrete differential evolution algorithm to solve a class of integer bilevel programming problems, in which integer decision variables are controlled by an upper-level decision maker and real-value or continuous decision variables are controlled by a lower-level decision maker. Using the Karush--Kuhn-Tucker optimality conditions in the lower-level programming, the original discrete bilevel formulation can be converted into a discrete single-level nonlinear programming problem with the complementarity constraints, and then the smoothing technique is applied to deal with the complementarity constraints. Finally, a discrete single-level nonlinear programming problem is obtained, and solved by an interactive approach. In each iteration, for each given upper-level discrete variable, a system of nonlinear equations including the lower-level variables and Lagrange multipliers is solved first, and then a discrete nonlinear programming problem only with inequality constraints is handled by using a discrete differential evolution algorithm. Simulation results show the effectiveness of the proposed approach.

Model-free inference of direct network interactions from nonlinear collective dynamics.

PubMed

Casadiego, Jose; Nitzan, Mor; Hallerberg, Sarah; Timme, Marc

2017-12-19

The topology of interactions in network dynamical systems fundamentally underlies their function. Accelerating technological progress creates massively available data about collective nonlinear dynamics in physical, biological, and technological systems. Detecting direct interaction patterns from those dynamics still constitutes a major open problem. In particular, current nonlinear dynamics approaches mostly require to know a priori a model of the (often high dimensional) system dynamics. Here we develop a model-independent framework for inferring direct interactions solely from recording the nonlinear collective dynamics generated. Introducing an explicit dependency matrix in combination with a block-orthogonal regression algorithm, the approach works reliably across many dynamical regimes, including transient dynamics toward steady states, periodic and non-periodic dynamics, and chaos. Together with its capabilities to reveal network (two point) as well as hypernetwork (e.g., three point) interactions, this framework may thus open up nonlinear dynamics options of inferring direct interaction patterns across systems where no model is known.

Optimization of Stability Constrained Geometrically Nonlinear Shallow Trusses Using an Arc Length Sparse Method with a Strain Energy Density Approach

NASA Technical Reports Server (NTRS)

Hrinda, Glenn A.; Nguyen, Duc T.

2008-01-01

A technique for the optimization of stability constrained geometrically nonlinear shallow trusses with snap through behavior is demonstrated using the arc length method and a strain energy density approach within a discrete finite element formulation. The optimization method uses an iterative scheme that evaluates the design variables' performance and then updates them according to a recursive formula controlled by the arc length method. A minimum weight design is achieved when a uniform nonlinear strain energy density is found in all members. This minimal condition places the design load just below the critical limit load causing snap through of the structure. The optimization scheme is programmed into a nonlinear finite element algorithm to find the large strain energy at critical limit loads. Examples of highly nonlinear trusses found in literature are presented to verify the method.

{open_quotes}Quadrupoled{close_quotes} materials for second-order nonlinear optics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hubbard, S.F.; Petschek, R.G.; Singer, K.D.

1997-10-01

We describe a new approach to second-order nonlinear optical materials, namely quadrupoling. This approach is valid in the regime of Kleinman (full permutation) symmetry breaking, and thus requires a two- or three dimensional microscopic nonlinearity at wavelengths away from material resonances. This {open_quotes}quadrupolar{close_quotes} nonlinearity arises from the second rank pseudotensor of the rotationally invariant representation of the second-order nonlinear optical tensor. We have experimentally investigated candidate molecules comprised of chiral camphorquinone derivatives by measuring the scalar invariant associated with the rank two pseudotensor using hyper-Rayleigh scattering. We have found sizable scalar figures of merit for several compounds using light formore » which the second harmonic wavelengths are greater than 100 nm longer than the absorption peak location. At these wavelengths, the quadrupolar scalar is as large as the polar (EFISH) scalar of p-nitroaniline. Prospects for applications are discussed.« less

Multivariable control of the Space Shuttle Remote Manipulator System using linearization by state feedback

NASA Technical Reports Server (NTRS)

Gettman, Chang-Ching L.; Adams, Neil; Bedrossian, Nazareth; Valavani, Lena

1993-01-01

This paper demonstrates an approach to nonlinear control system design that uses linearization by state feedback to allow faster maneuvering of payloads by the Shuttle Remote Manipulator System (SRMS). A nonlinear feedback law is defined to cancel the nonlinear plant dynamics so that a linear controller can be designed for the SRMS. First a nonlinear design model was generated via SIMULINK. This design model included nonlinear arm dynamics derived from the Lagrangian approach, linearized servo model, and linearized gearbox model. The current SRMS position hold controller was implemented on this system. Next, a trajectory was defined using a rigid body kinematics SRMS tool, KRMS. The maneuver was simulated. Finally, higher bandwidth controllers were developed. Results of the new controllers were compared with the existing SRMS automatic control modes for the Space Station Freedom Mission Build 4 Payload extended on the SRMS.

Bluegenics: Bioactive Natural Products of Medicinal Relevance and Approaches to Their Diversification.

PubMed

Zarins-Tutt, Joseph S; Abraham, Emily R; Bailey, Christopher S; Goss, Rebecca J M

Nature provides a valuable resource of medicinally relevant compounds, with many antimicrobial and antitumor agents entering clinical trials being derived from natural products. The generation of analogues of these bioactive natural products is important in order to gain a greater understanding of structure activity relationships; probing the mechanism of action, as well as to optimise the natural product's bioactivity and bioavailability. This chapter critically examines different approaches to generating natural products and their analogues, exploring the way in which synthetic and biosynthetic approaches may be blended together to enable expeditious access to new designer natural products.

Nonlinear absorption dynamics using field-induced surface hopping: zinc porphyrin in water.

PubMed

Röhr, Merle I S; Petersen, Jens; Wohlgemuth, Matthias; Bonačić-Koutecký, Vlasta; Mitrić, Roland

2013-05-10

We wish to present the application of our field-induced surface-hopping (FISH) method to simulate nonlinear absorption dynamics induced by strong nonresonant laser fields. We provide a systematic comparison of the FISH approach with exact quantum dynamics simulations on a multistate model system and demonstrate that FISH allows for accurate simulations of nonlinear excitation processes including multiphoton electronic transitions. In particular, two different approaches for simulating two-photon transitions are compared. The first approach is essentially exact and involves the solution of the time-dependent Schrödinger equation in an extended manifold of excited states, while in the second one only transiently populated nonessential states are replaced by an effective quadratic coupling term, and dynamics is performed in a considerably smaller manifold of states. We illustrate the applicability of our method to complex molecular systems by simulating the linear and nonlinear laser-driven dynamics in zinc (Zn) porphyrin in the gas phase and in water. For this purpose, the FISH approach is connected with the quantum mechanical-molecular mechanical approach (QM/MM) which is generally applicable to large classes of complex systems. Our findings that multiphoton absorption and dynamics increase the population of higher excited states of Zn porphyrin in the nonlinear regime, in particular in solution, provides a means for manipulating excited-state properties, such as transient absorption dynamics and electronic relaxation. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Geomorphologic Synthesis of Nonlinearity in Surface Runoff

NASA Astrophysics Data System (ADS)

Wang, C. T.; Gupta, Vijay K.; Waymire, Ed

1981-06-01

The geomorphic approach leading to a representation of an instantaneous unit hydrograph (iuh) which we developed earlier is generalized to incorporate nonlinear effects in the rainfall-runoff transformation. It is demonstrated that the nonlinearity in the transformation enters in part through the dependence of the mean holding time on the rainfall intensity. Under an assumed first approximation that this dependence is the sole source of nonlinearity an explicit quasi-linear representation results for the rainfall- runoff transformation. The kernel function of this transformation can be termed as the instantaneous response function (irf) in contradistinction to the notion of an iuh for the case of a linear rainfall-runoff transformation. The predictions from the quasi-linear theory agree very well with predictions from the kinematic wave approach for the one small basin that is analyzed. Also, for two large basins in Illinois having areas of about 1100 mi2 the predictions from the quasi-linear approach compare very well with the observed flows. A measure of nonlinearity, α naturally arises through the dependence of the mean holding time KB(i0) on the rainfall intensity i0via KB (i0) ˜ i0 -α. Computations of α for four basins show that α approaches ⅔ as basin size decreases and approaches zero as the basin size increases. A semilog plot of α versus the square root of the basin area gives a straight line. Confirmation of this relationship for other basins would be of basic importance in predicting flows from ungaged basins.

Designing synthetic networks in silico: a generalised evolutionary algorithm approach.

PubMed

Smith, Robert W; van Sluijs, Bob; Fleck, Christian

2017-12-02

Evolution has led to the development of biological networks that are shaped by environmental signals. Elucidating, understanding and then reconstructing important network motifs is one of the principal aims of Systems & Synthetic Biology. Consequently, previous research has focused on finding optimal network structures and reaction rates that respond to pulses or produce stable oscillations. In this work we present a generalised in silico evolutionary algorithm that simultaneously finds network structures and reaction rates (genotypes) that can satisfy multiple defined objectives (phenotypes). The key step to our approach is to translate a schema/binary-based description of biological networks into systems of ordinary differential equations (ODEs). The ODEs can then be solved numerically to provide dynamic information about an evolved networks functionality. Initially we benchmark algorithm performance by finding optimal networks that can recapitulate concentration time-series data and perform parameter optimisation on oscillatory dynamics of the Repressilator. We go on to show the utility of our algorithm by finding new designs for robust synthetic oscillators, and by performing multi-objective optimisation to find a set of oscillators and feed-forward loops that are optimal at balancing different system properties. In sum, our results not only confirm and build on previous observations but we also provide new designs of synthetic oscillators for experimental construction. In this work we have presented and tested an evolutionary algorithm that can design a biological network to produce desired output. Given that previous designs of synthetic networks have been limited to subregions of network- and parameter-space, the use of our evolutionary optimisation algorithm will enable Synthetic Biologists to construct new systems with the potential to display a wider range of complex responses.

A more fundamental approach to the derivation of nonlinear acoustic wave equations with fractional loss operators (L).

PubMed

Prieur, Fabrice; Vilenskiy, Gregory; Holm, Sverre

2012-10-01

A corrected derivation of nonlinear wave propagation equations with fractional loss operators is presented. The fundamental approach is based on fractional formulations of the stress-strain and heat flux definitions but uses the energy equation and thermodynamic identities to link density and pressure instead of an erroneous fractional form of the entropy equation as done in Prieur and Holm ["Nonlinear acoustic wave equations with fractional loss operators," J. Acoust. Soc. Am. 130(3), 1125-1132 (2011)]. The loss operator of the obtained nonlinear wave equations differs from the previous derivations as well as the dispersion equation, but when approximating for low frequencies the expressions for the frequency dependent attenuation and velocity dispersion remain unchanged.

The nonlinear modified equation approach to analyzing finite difference schemes

NASA Technical Reports Server (NTRS)

Klopfer, G. H.; Mcrae, D. S.

1981-01-01

The nonlinear modified equation approach is taken in this paper to analyze the generalized Lax-Wendroff explicit scheme approximation to the unsteady one- and two-dimensional equations of gas dynamics. Three important applications of the method are demonstrated. The nonlinear modified equation analysis is used to (1) generate higher order accurate schemes, (2) obtain more accurate estimates of the discretization error for nonlinear systems of partial differential equations, and (3) generate an adaptive mesh procedure for the unsteady gas dynamic equations. Results are obtained for all three areas. For the adaptive mesh procedure, mesh point requirements for equal resolution of discontinuities were reduced by a factor of five for a 1-D shock tube problem solved by the explicit MacCormack scheme.

Modified nonlinear amplifying loop mirror for mode-locked fibre oscillators with record-high energy and high-average-power pulsed output

NASA Astrophysics Data System (ADS)

Kobtsev, Sergey; Ivanenko, Alexey; Smirnov, Sergey; Kokhanovsky, Alexey

2018-02-01

The present work proposes and studies approaches for development of new modified non-linear amplifying loop mirror (NALM) allowing flexible and dynamic control of their non-linear properties within a relatively broad range of radiation powers. Using two independently pumped active media in the loop reflector constitutes one of the most promising approaches to development of better NALM with nonlinear properties controllable independently of the intra-cavity radiation power. This work reports on experimental and theoretical studies of the proposed redesigned NALM allowing both a higher level of energy parameters of output generated by mode-locked fibre oscillators and new possibilities of switching among different mode-locked regimes.

A Unified Approach for Solving Nonlinear Regular Perturbation Problems

ERIC Educational Resources Information Center

Khuri, S. A.

2008-01-01

This article describes a simple alternative unified method of solving nonlinear regular perturbation problems. The procedure is based upon the manipulation of Taylor's approximation for the expansion of the nonlinear term in the perturbed equation. An essential feature of this technique is the relative simplicity used and the associated unified…

The multiple roles of computational chemistry in fragment-based drug design

NASA Astrophysics Data System (ADS)

Law, Richard; Barker, Oliver; Barker, John J.; Hesterkamp, Thomas; Godemann, Robert; Andersen, Ole; Fryatt, Tara; Courtney, Steve; Hallett, Dave; Whittaker, Mark

2009-08-01

Fragment-based drug discovery (FBDD) represents a change in strategy from the screening of molecules with higher molecular weights and physical properties more akin to fully drug-like compounds, to the screening of smaller, less complex molecules. This is because it has been recognised that fragment hit molecules can be efficiently grown and optimised into leads, particularly after the binding mode to the target protein has been first determined by 3D structural elucidation, e.g. by NMR or X-ray crystallography. Several studies have shown that medicinal chemistry optimisation of an already drug-like hit or lead compound can result in a final compound with too high molecular weight and lipophilicity. The evolution of a lower molecular weight fragment hit therefore represents an attractive alternative approach to optimisation as it allows better control of compound properties. Computational chemistry can play an important role both prior to a fragment screen, in producing a target focussed fragment library, and post-screening in the evolution of a drug-like molecule from a fragment hit, both with and without the available fragment-target co-complex structure. We will review many of the current developments in the area and illustrate with some recent examples from successful FBDD discovery projects that we have conducted.

Determination of acrylamide in coffee and chocolate by pressurised fluid extraction and liquid chromatography-tandem mass spectrometry.

PubMed

Pardo, O; Yusà, V; Coscollà, C; León, N; Pastor, A

2007-07-01

A selective and sensitive procedure has been developed and validated for the determination of acrylamide in difficult matrices, such as coffee and chocolate. The proposed method includes pressurised fluid extraction (PFE) with acetonitrile, florisil clean-up purification inside the PFE extraction cell and detection by liquid chromatography (LC) coupled to atmospheric pressure ionisation in positive mode tandem mass spectrometry (APCI-MS-MS). Comparison of ionisation sources (atmospheric pressure chemical ionisation (APCI), atmospheric pressure photoionization (APPI) and the combined APCI/APPI) and clean-up procedures were carried out to improve the analytical signal. The main parameters affecting the performance of the different ionisation sources were previously optimised using statistical design of experiments (DOE). PFE parameters were also optimised by DOE. For quantitation, an isotope dilution approach was used. The limit of quantification (LOQ) of the method was 1 microg kg(-1) for coffee and 0.6 microg kg(-1) for chocolate. Recoveries ranged between 81-105% in coffee and 87-102% in chocolate. The accuracy was evaluated using a coffee reference test material FAPAS T3008. Using the optimised method, 20 coffee and 15 chocolate samples collected from Valencian (Spain) supermarkets, were investigated for acrylamide, yielding median levels of 146 microg kg(-1) in coffee and 102 microg kg(-1) in chocolate.

A new paradigm in personal dosimetry using LiF:Mg,Cu,P.

PubMed

Cassata, J R; Moscovitch, M; Rotunda, J E; Velbeck, K J

2002-01-01

The United States Navy has been monitoring personnel for occupational exposure to ionising radiation since 1947. Film was exclusively used until 1973 when thermoluminescence dosemeters were introduced and used to the present time. In 1994, a joint research project between the Naval Dosimetry Center, Georgetown University, and Saint Gobain Crystals and Detectors (formerly Bicron RMP formerly Harshaw TLD) began to develop a state of the art thermoluminescent dosimetry system. The study was conducted from a large-scale dosimetry processor point of view with emphasis on a systems approach. Significant improvements were achieved by replacing the LiF:Mg,Ti with LiF:Mg,Cu,P TL elements due to the significant sensitivity increase, linearity, and negligible hiding. Dosemeter filters were optimised for gamma and X ray energy discrimination using Monte Carlo modelling (MCNP) resulting in significant improvement in accuracy and precision. Further improvements were achieved through the use of neural-network based dose calculation algorithms. Both back propagation and functional link methods were implemented and the data compared with essentially the same results. Several operational aspects of the system are discussed, including (1) background subtraction using control dosemeters, (2) selection criteria for control dosemeters, (3) optimisation of the TLD readers, (4) calibration methodology, and (5) the optimisation of the heating profile.

A novel approach for the elimination of artefacts from EEG signals employing an improved Artificial Immune System algorithm

NASA Astrophysics Data System (ADS)

Suja Priyadharsini, S.; Edward Rajan, S.; Femilin Sheniha, S.

2016-03-01

Electroencephalogram (EEG) is the recording of electrical activities of the brain. It is contaminated by other biological signals, such as cardiac signal (electrocardiogram), signals generated by eye movement/eye blinks (electrooculogram) and muscular artefact signal (electromyogram), called artefacts. Optimisation is an important tool for solving many real-world problems. In the proposed work, artefact removal, based on the adaptive neuro-fuzzy inference system (ANFIS) is employed, by optimising the parameters of ANFIS. Artificial Immune System (AIS) algorithm is used to optimise the parameters of ANFIS (ANFIS-AIS). Implementation results depict that ANFIS-AIS is effective in removing artefacts from EEG signal than ANFIS. Furthermore, in the proposed work, improved AIS (IAIS) is developed by including suitable selection processes in the AIS algorithm. The performance of the proposed method IAIS is compared with AIS and with genetic algorithm (GA). Measures such as signal-to-noise ratio, mean square error (MSE) value, correlation coefficient, power spectrum density plot and convergence time are used for analysing the performance of the proposed method. From the results, it is found that the IAIS algorithm converges faster than the AIS and performs better than the AIS and GA. Hence, IAIS tuned ANFIS (ANFIS-IAIS) is effective in removing artefacts from EEG signals.

Optimising the use of marine tephrochronology in the North Atlantic: a detailed investigation of the Faroe Marine Ash Zones II, III and IV

NASA Astrophysics Data System (ADS)

Griggs, Adam J.; Davies, Siwan M.; Abbott, Peter M.; Rasmussen, Tine L.; Palmer, Adrian P.

2014-12-01

Tephrochronology is central to the INTIMATE goals for testing the degree of climatic synchroneity during abrupt climatic events that punctuated the last glacial period. Since their identification in North Atlantic marine sequences, the Faroe Marine Ash Zone II (FMAZ II), FMAZ III and FMAZ IV have received considerable attention due to their potential for high-precision synchronisation with the Greenland ice-cores. In order to optimise the use of these horizons as isochronous markers, a detailed re-investigation of their geochemical composition, sedimentology and the processes that deposited each ash zone is presented. Shard concentration profiles, geochemical homogeneity and micro-sedimentological structures are investigated for each ash zone preserved within core JM11-19PC, retrieved from the southeastern Norwegian Sea on the central North Faroe Slope. This approach allows a thorough assessment of primary ash-fall preservation and secondary depositional features and demonstrates its value for assessing depositional integrity in the marine environment. Results indicate that the FMAZ II and IV are well-resolved primary deposits that can be used as isochrons for high-precision correlation studies. We outline key recommendations for future marine tephra studies and provide a protocol for optimising the application of tephrochronology to meet the INTIMATE synchronisation goals.

Microencapsulation Approach for Orally Extended Delivery of Glipizide: In vitro and in vivo Evaluation

PubMed Central

Abdelbary, A.; El-gendy, N. A.; Hosny, A.

2012-01-01

Glipizide is an effective antidiabetic agent, however, it suffers from relatively short biological half-life. To solve this encumbrance, it is a prospective candidate for fabricating glipizide extended release microcapsules. Microencapsulation of glipizde with a coat of alginate alone or in combination with chitosan or carbomer 934P was prepared employing ionotropic gelation process. The prepared microcapsules were evaluated in vitro by microscopical examination, determination of the particle size, yield and microencapsulation efficiency. The filled capsules were assessed for content uniformity and drug release characteristics. Stability study of the optimised formulas was carried out at three different temperatures over 12 weeks. In vivo bioavailability study and hypoglycemic activity of C9 microcapsules were done on albino rabbits. All formulas achieved high yield, microencapsulation efficiency and extended t1/2. C9 and C19 microcapsules attained the most optimised results in all tests and complied with the dissolution requirements for extended release dosage forms. These two formulas were selected for stability studies. C9 exhibited longer shelf-life and hence was chosen for in vivo studies. C9 microcapsules showed an improvement in the drug bioavailability and significant hypoglycemic activity compared to immediate release tablets (Minidiab® 5 mg). The optimised microcapsule formulation developed was found to produce extended antidiabetic activity. PMID:23626387

Demonstrating the suitability of genetic algorithms for driving microbial ecosystems in desirable directions.

PubMed

Vandecasteele, Frederik P J; Hess, Thomas F; Crawford, Ronald L

2007-07-01

The functioning of natural microbial ecosystems is determined by biotic interactions, which are in turn influenced by abiotic environmental conditions. Direct experimental manipulation of such conditions can be used to purposefully drive ecosystems toward exhibiting desirable functions. When a set of environmental conditions can be manipulated to be present at a discrete number of levels, finding the right combination of conditions to obtain the optimal desired effect becomes a typical combinatorial optimisation problem. Genetic algorithms are a class of robust and flexible search and optimisation techniques from the field of computer science that may be very suitable for such a task. To verify this idea, datasets containing growth levels of the total microbial community of four different natural microbial ecosystems in response to all possible combinations of a set of five chemical supplements were obtained. Subsequently, the ability of a genetic algorithm to search this parameter space for combinations of supplements driving the microbial communities to high levels of growth was compared to that of a random search, a local search, and a hill-climbing algorithm, three intuitive alternative optimisation approaches. The results indicate that a genetic algorithm is very suitable for driving microbial ecosystems in desirable directions, which opens opportunities for both fundamental ecological research and industrial applications.

Optimizing Polymer Infusion Process for Thin Ply Textile Composites with Novel Matrix System

PubMed Central

Bhudolia, Somen K.; Perrotey, Pavel; Joshi, Sunil C.

2017-01-01

For mass production of structural composites, use of different textile patterns, custom preforming, room temperature cure high performance polymers and simplistic manufacturing approaches are desired. Woven fabrics are widely used for infusion processes owing to their high permeability but their localised mechanical performance is affected due to inherent associated crimps. The current investigation deals with manufacturing low-weight textile carbon non-crimp fabrics (NCFs) composites with a room temperature cure epoxy and a novel liquid Methyl methacrylate (MMA) thermoplastic matrix, Elium®. Vacuum assisted resin infusion (VARI) process is chosen as a cost effective manufacturing technique. Process parameters optimisation is required for thin NCFs due to intrinsic resistance it offers to the polymer flow. Cycles of repetitive manufacturing studies were carried out to optimise the NCF-thermoset (TS) and NCF with novel reactive thermoplastic (TP) resin. It was noticed that the controlled and optimised usage of flow mesh, vacuum level and flow speed during the resin infusion plays a significant part in deciding the final quality of the fabricated composites. The material selections, the challenges met during the manufacturing and the methods to overcome these are deliberated in this paper. An optimal three stage vacuum technique developed to manufacture the TP and TS composites with high fibre volume and lower void content is established and presented. PMID:28772654

Optimizing Polymer Infusion Process for Thin Ply Textile Composites with Novel Matrix System.

PubMed

Bhudolia, Somen K; Perrotey, Pavel; Joshi, Sunil C

2017-03-15

For mass production of structural composites, use of different textile patterns, custom preforming, room temperature cure high performance polymers and simplistic manufacturing approaches are desired. Woven fabrics are widely used for infusion processes owing to their high permeability but their localised mechanical performance is affected due to inherent associated crimps. The current investigation deals with manufacturing low-weight textile carbon non-crimp fabrics (NCFs) composites with a room temperature cure epoxy and a novel liquid Methyl methacrylate (MMA) thermoplastic matrix, Elium ® . Vacuum assisted resin infusion (VARI) process is chosen as a cost effective manufacturing technique. Process parameters optimisation is required for thin NCFs due to intrinsic resistance it offers to the polymer flow. Cycles of repetitive manufacturing studies were carried out to optimise the NCF-thermoset (TS) and NCF with novel reactive thermoplastic (TP) resin. It was noticed that the controlled and optimised usage of flow mesh, vacuum level and flow speed during the resin infusion plays a significant part in deciding the final quality of the fabricated composites. The material selections, the challenges met during the manufacturing and the methods to overcome these are deliberated in this paper. An optimal three stage vacuum technique developed to manufacture the TP and TS composites with high fibre volume and lower void content is established and presented.

Interactions of nonlocal dark solitons under competing cubic-quintic nonlinearities.

PubMed

Chen, Wei; Shen, Ming; Kong, Qian; Shi, Jielong; Wang, Qi; Krolikowski, Wieslaw

2014-04-01

We investigate analytically and numerically the interactions of dark solitons under competing nonlocal cubic and local quintic nonlinearities. It is shown that the self-defocusing quintic nonlinearity will strengthen the attractive interaction and decrease the relative distance between solitons, whereas the self-focusing quintic nonlinearity will enhance the repulsive interaction and increase soliton separation. We demonstrate these results by approximate variational approach and direct numerical simulation.

Green functions and Langevin equations for nonlinear diffusion equations: A comment on ‘Markov processes, Hurst exponents, and nonlinear diffusion equations’ by Bassler et al.

NASA Astrophysics Data System (ADS)

Frank, T. D.

2008-02-01

We discuss two central claims made in the study by Bassler et al. [K.E. Bassler, G.H. Gunaratne, J.L. McCauley, Physica A 369 (2006) 343]. Bassler et al. claimed that Green functions and Langevin equations cannot be defined for nonlinear diffusion equations. In addition, they claimed that nonlinear diffusion equations are linear partial differential equations disguised as nonlinear ones. We review bottom-up and top-down approaches that have been used in the literature to derive Green functions for nonlinear diffusion equations and, in doing so, show that the first claim needs to be revised. We show that the second claim as well needs to be revised. To this end, we point out similarities and differences between non-autonomous linear Fokker-Planck equations and autonomous nonlinear Fokker-Planck equations. In this context, we raise the question whether Bassler et al.’s approach to financial markets is physically plausible because it necessitates the introduction of external traders and causes. Such external entities can easily be eliminated when taking self-organization principles and concepts of nonextensive thermostatistics into account and modeling financial processes by means of nonlinear Fokker-Planck equations.

Ice-sheet modelling accelerated by graphics cards

NASA Astrophysics Data System (ADS)

Brædstrup, Christian Fredborg; Damsgaard, Anders; Egholm, David Lundbek

2014-11-01

Studies of glaciers and ice sheets have increased the demand for high performance numerical ice flow models over the past decades. When exploring the highly non-linear dynamics of fast flowing glaciers and ice streams, or when coupling multiple flow processes for ice, water, and sediment, researchers are often forced to use super-computing clusters. As an alternative to conventional high-performance computing hardware, the Graphical Processing Unit (GPU) is capable of massively parallel computing while retaining a compact design and low cost. In this study, we present a strategy for accelerating a higher-order ice flow model using a GPU. By applying the newest GPU hardware, we achieve up to 180× speedup compared to a similar but serial CPU implementation. Our results suggest that GPU acceleration is a competitive option for ice-flow modelling when compared to CPU-optimised algorithms parallelised by the OpenMP or Message Passing Interface (MPI) protocols.

Synthesis, tautomeric stability, spectroscopy and computational study of a potential molecular switch of (Z)-4-(phenylamino)pent-3-en-2-one

NASA Astrophysics Data System (ADS)

Fahid, Farzaneh; Kanaani, Ayoub; Pourmousavi, Seied Ali; Ajloo, Davood

2017-04-01

The (Z)-4-(phenylamino) pent-3-en-2-one (PAPO) was synthesised applying carbon-based solid acid and described by experimental techniques. Calculated results reveal that its keto-amine form is more stable than its enol-imine form. A relaxed potential energy surface scan has been accomplished based on the optimised geometry of NH tautomeric form to depict the potential energy barrier related to intramolecular proton transfer. The spectroscopic results and theoretical calculations demonstrate that the intramolecular hydrogen bonding strength of PAPO is stronger than that in 4-amino-3-penten-2-one)APO(. In addition, molecular electrostatic potential, total and partial density of stats (TDOS, PDOS) and non-linear optical properties of the compound were studied using same theoretical calculations. Our calculations show that the title molecule has the potential to be used as molecular switch.

A support vector machine for predicting defibrillation outcomes from waveform metrics.

PubMed

Howe, Andrew; Escalona, Omar J; Di Maio, Rebecca; Massot, Bertrand; Cromie, Nick A; Darragh, Karen M; Adgey, Jennifer; McEneaney, David J

2014-03-01

Algorithms to predict shock success based on VF waveform metrics could significantly enhance resuscitation by optimising the timing of defibrillation. To investigate robust methods of predicting defibrillation success in VF cardiac arrest patients, by using a support vector machine (SVM) optimisation approach. Frequency-domain (AMSA, dominant frequency and median frequency) and time-domain (slope and RMS amplitude) VF waveform metrics were calculated in a 4.1Y window prior to defibrillation. Conventional prediction test validity of each waveform parameter was conducted and used AUC>0.6 as the criterion for inclusion as a corroborative attribute processed by the SVM classification model. The latter used a Gaussian radial-basis-function (RBF) kernel and the error penalty factor C was fixed to 1. A two-fold cross-validation resampling technique was employed. A total of 41 patients had 115 defibrillation instances. AMSA, slope and RMS waveform metrics performed test validation with AUC>0.6 for predicting termination of VF and return-to-organised rhythm. Predictive accuracy of the optimised SVM design for termination of VF was 81.9% (± 1.24 SD); positive and negative predictivity were respectively 84.3% (± 1.98 SD) and 77.4% (± 1.24 SD); sensitivity and specificity were 87.6% (± 2.69 SD) and 71.6% (± 9.38 SD) respectively. AMSA, slope and RMS were the best VF waveform frequency-time parameters predictors of termination of VF according to test validity assessment. This a priori can be used for a simplified SVM optimised design that combines the predictive attributes of these VF waveform metrics for improved prediction accuracy and generalisation performance without requiring the definition of any threshold value on waveform metrics. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

A study of lateral fall-off (penumbra) optimisation for pencil beam scanning (PBS) proton therapy

NASA Astrophysics Data System (ADS)

Winterhalter, C.; Lomax, A.; Oxley, D.; Weber, D. C.; Safai, S.

2018-01-01

The lateral fall-off is crucial for sparing organs at risk in proton therapy. It is therefore of high importance to minimize the penumbra for pencil beam scanning (PBS). Three optimisation approaches are investigated: edge-collimated uniformly weighted spots (collimation), pencil beam optimisation of uncollimated pencil beams (edge-enhancement) and the optimisation of edge collimated pencil beams (collimated edge-enhancement). To deliver energies below 70 MeV, these strategies are evaluated in combination with the following pre-absorber methods: field specific fixed thickness pre-absorption (fixed), range specific, fixed thickness pre-absorption (automatic) and range specific, variable thickness pre-absorption (variable). All techniques are evaluated by Monte Carlo simulated square fields in a water tank. For a typical air gap of 10 cm, without pre-absorber collimation reduces the penumbra only for water equivalent ranges between 4-11 cm by up to 2.2 mm. The sharpest lateral fall-off is achieved through collimated edge-enhancement, which lowers the penumbra down to 2.8 mm. When using a pre-absorber, the sharpest fall-offs are obtained when combining collimated edge-enhancement with a variable pre-absorber. For edge-enhancement and large air gaps, it is crucial to minimize the amount of material in the beam. For small air gaps however, the superior phase space of higher energetic beams can be employed when more material is used. In conclusion, collimated edge-enhancement combined with the variable pre-absorber is the recommended setting to minimize the lateral penumbra for PBS. Without collimator, it would be favourable to use a variable pre-absorber for large air gaps and an automatic pre-absorber for small air gaps.

Nurse strategies for optimising patient participation in nursing care.

PubMed

Sahlsten, Monika J M; Larsson, Inga E; Sjöström, Björn; Plos, Kaety A E

2009-09-01

THE STUDY'S RATIONALE: Patient participation is an essential factor in nursing care and medical treatment and a legal right in many countries. Despite this, patients have experienced insufficient participation, inattention and neglect regarding their problems and may respond with dependence, passivity or taciturnity. Accordingly, nurses strategies for optimising patient participation in nursing care is an important question for the nursing profession. The aim was to explore Registered Nurses' strategies to stimulate and optimise patient participation in nursing care. The objective was to identify ward nurses' supporting practices. A qualitative research approach was applied. Three focus groups with experienced Registered Nurses providing inpatient somatic care (n = 16) were carried out. These nurses were recruited from three hospitals in West Sweden. The data were analysed using content analysis technique. The ethics of scientific work was adhered to. According to national Swedish legislation, no formal permit from an ethics committee was required. The participants gave informed consent after verbal and written information. Nurse strategies for optimising patient participation in nursing care were identified as three categories: 'Building close co-operation', 'Getting to know the person' and 'Reinforcing self-care capacity' and their 10 subcategories. The strategies point to a process of emancipation of the patient's potential by finding his/her own inherent knowledge, values, motivation and goals and linking these to actions. Nurses need to strive for guiding the patient towards attaining meaningful experiences, discoveries, learning and development. The strategies are important and useful to balance the asymmetry in the nurse-patient relationship in daily nursing practice and also in quality assurance to evaluate and improve patient participation and in education. However, further verification of the findings is recommended by means of replication or other studies in different clinical settings. © 2009 The Authors. Journal compilation © 2009 Nordic College of Caring Science.

Basis for the development of sustainable optimisation indicators for activated sludge wastewater treatment plants in the Republic of Ireland.

PubMed

Gordon, G T; McCann, B P

2015-01-01

This paper describes the basis of a stakeholder-based sustainable optimisation indicator (SOI) system to be developed for small-to-medium sized activated sludge (AS) wastewater treatment plants (WwTPs) in the Republic of Ireland (ROI). Key technical publications relating to best practice plant operation, performance audits and optimisation, and indicator and benchmarking systems for wastewater services are identified. Optimisation studies were developed at a number of Irish AS WwTPs and key findings are presented. A national AS WwTP manager/operator survey was carried out to verify the applied operational findings and identify the key operator stakeholder requirements for this proposed SOI system. It was found that most plants require more consistent operational data-based decision-making, monitoring and communication structures to facilitate optimised, sustainable and continuous performance improvement. The applied optimisation and stakeholder consultation phases form the basis of the proposed stakeholder-based SOI system. This system will allow for continuous monitoring and rating of plant performance, facilitate optimised operation and encourage the prioritisation of performance improvement through tracking key operational metrics. Plant optimisation has become a major focus due to the transfer of all ROI water services to a national water utility from individual local authorities and the implementation of the EU Water Framework Directive.

Nonlinear response and avalanche behavior in metallic glasses

NASA Astrophysics Data System (ADS)

Riechers, B.; Samwer, K.

2017-08-01

The response to different stress amplitudes at temperatures below the glass transition temperature is analyzed by mechanical oscillatory excitation of Pd40Ni40P20 metallic glass samples in single cantilever bending geometry. While low amplitude oscillatory excitations are commonly used in mechanical spectroscopy to probe the relaxation spectrum, in this work the response to comparably high amplitudes is investigated. The strain response of the material is well below the critical yield stress even for highest stress amplitudes, implying the expectation of a linear relation between stress and strain according to Hooke's Law. However, a deviation from the linear behavior is evident, which is analyzed in terms of temperature dependence and influence of the applied stress amplitude by two different approaches of evaluation. The nonlinear approach is based on a nonlinear expansion of the stress-strain-relation, assuming an intrinsic nonlinear character of the shear or elastic modulus. The degree of nonlinearity is extracted by a period-by-period Fourier-analysis and connected to nonlinear coefficients, describing the intensity of nonlinearity at the fundamental and higher harmonic frequencies. The characteristic timescale to adapt to a significant change in stress amplitude in terms of a recovery timescale to a steady state value is connected to the structural relaxation time of the material, suggesting a connection between the observed nonlinearity and primary relaxation processes. The second approach of evaluation is termed the incremental analysis and relates the observed response behavior to avalanches, which occur due to the activation and correlation of local microstructural rearrangements. These rearrangements are connected with shear transformation zones and correspond to localized plastic events, which are superimposed on the linear response behavior of the material.

Cost-effectiveness analysis of risk-reduction measures to reach water safety targets.

PubMed

Lindhe, Andreas; Rosén, Lars; Norberg, Tommy; Bergstedt, Olof; Pettersson, Thomas J R

2011-01-01

Identifying the most suitable risk-reduction measures in drinking water systems requires a thorough analysis of possible alternatives. In addition to the effects on the risk level, also the economic aspects of the risk-reduction alternatives are commonly considered important. Drinking water supplies are complex systems and to avoid sub-optimisation of risk-reduction measures, the entire system from source to tap needs to be considered. There is a lack of methods for quantification of water supply risk reduction in an economic context for entire drinking water systems. The aim of this paper is to present a novel approach for risk assessment in combination with economic analysis to evaluate risk-reduction measures based on a source-to-tap approach. The approach combines a probabilistic and dynamic fault tree method with cost-effectiveness analysis (CEA). The developed approach comprises the following main parts: (1) quantification of risk reduction of alternatives using a probabilistic fault tree model of the entire system; (2) combination of the modelling results with CEA; and (3) evaluation of the alternatives with respect to the risk reduction, the probability of not reaching water safety targets and the cost-effectiveness. The fault tree method and CEA enable comparison of risk-reduction measures in the same quantitative unit and consider costs and uncertainties. The approach provides a structured and thorough analysis of risk-reduction measures that facilitates transparency and long-term planning of drinking water systems in order to avoid sub-optimisation of available resources for risk reduction. Copyright © 2010 Elsevier Ltd. All rights reserved.

Evaluation of simulation alternatives for the brute-force ray-tracing approach used in backlight design

NASA Astrophysics Data System (ADS)

Desnijder, Karel; Hanselaer, Peter; Meuret, Youri

2016-04-01

A key requirement to obtain a uniform luminance for a side-lit LED backlight is the optimised spatial pattern of structures on the light guide that extract the light. The generation of such a scatter pattern is usually performed by applying an iterative approach. In each iteration, the luminance distribution of the backlight with a particular scatter pattern is analysed. This is typically performed with a brute-force ray-tracing algorithm, although this approach results in a time-consuming optimisation process. In this study, the Adding-Doubling method is explored as an alternative way for evaluating the luminance of a backlight. Due to the similarities between light propagating in a backlight with extraction structures and light scattering in a cloud of light scatterers, the Adding-Doubling method which is used to model the latter could also be used to model the light distribution in a backlight. The backlight problem is translated to a form upon which the Adding-Doubling method is directly applicable. The calculated luminance for a simple uniform extraction pattern with the Adding-Doubling method matches the luminance generated by a commercial raytracer very well. Although successful, no clear computational advantage over ray tracers is realised. However, the dynamics of light propagation in a light guide as used the Adding-Doubling method, also allow to enhance the efficiency of brute-force ray-tracing algorithms. The performance of this enhanced ray-tracing approach for the simulation of backlights is also evaluated against a typical brute-force ray-tracing approach.

Ecosystem Health Disorders - changing perspectives in clinical medicine and nutrition.

PubMed

Wahlqvist, Mark L

2014-01-01

The inseparability of people from their ecosystem without biological change is increasingly clear. The discrete species concept is becoming more an approximation as the interconnectedness of all things, animate and inanimate, becomes more apparent. Yet this was evident even to our earliest Homo Sapiens sapiens ancestors as they hunted and gathered from one locality to another and migrated across the globe. During a rather short 150-200,000 years of ancestral history, we have changed the aeons-old planet and our ecology with dubious sustainability. As we have changed the ecosystems of which we are a part, with their opportunities for shelter, rest, ambulation, discourse, food, recreation and their sensory inputs, we have changed our shared biology and our health prospects. The rate of ecosystem change has increased quantitatively and qualitatively and so will that of our health patterns, depending on our resilience and how linear, non-linear or fractal-like the linkage. Our health-associated ecosystem trajectories are uncertain. The interfaces between us and our environment are blurred, but comprise time, biorhythms, prokaryotic organisms, sensory (auditory, visual, tactile, taste and smell), conjoint movement, endocrine with various external hormonal through food and contaminants, the reflection of soil and rock composition in the microbes, plants, insects and animals that we eat (our biogeology) and much more. We have sought ways to optimise our health through highly anthropocentric means, which have proven inadequate. Accumulated ecosystem change may now overwhelm our health. On these accounts, more integrative approaches and partnerships for health care practice are required.

Adjoint-Based Sensitivity Kernels for Glacial Isostatic Adjustment in a Laterally Varying Earth

NASA Astrophysics Data System (ADS)

Crawford, O.; Al-Attar, D.; Tromp, J.; Mitrovica, J. X.; Austermann, J.; Lau, H. C. P.

2017-12-01

We consider a new approach to both the forward and inverse problems in glacial isostatic adjustment. We present a method for forward modelling GIA in compressible and laterally heterogeneous earth models with a variety of linear and non-linear rheologies. Instead of using the so-called sea level equation, which must be solved iteratively, the forward theory we present consists of a number of coupled evolution equations that can be straightforwardly numerically integrated. We also apply the adjoint method to the inverse problem in order to calculate the derivatives of measurements of GIA with respect to the viscosity structure of the Earth. Such derivatives quantify the sensitivity of the measurements to the model. The adjoint method enables efficient calculation of continuous and laterally varying derivatives, allowing us to calculate the sensitivity of measurements of glacial isostatic adjustment to the Earth's three-dimensional viscosity structure. The derivatives have a number of applications within the inverse method. Firstly, they can be used within a gradient-based optimisation method to find a model which minimises some data misfit function. The derivatives can also be used to quantify the uncertainty in such a model and hence to provide understanding of which parts of the model are well constrained. Finally, they enable construction of measurements which provide sensitivity to a particular part of the model space. We illustrate both the forward and inverse aspects with numerical examples in a spherically symmetric earth model.

Wiener sliding-mode control for artificial pancreas: a new nonlinear approach to glucose regulation.

PubMed

Abu-Rmileh, Amjad; Garcia-Gabin, Winston

2012-08-01

Type 1 diabetic patients need insulin therapy to keep their blood glucose close to normal. In this paper an attempt is made to show how nonlinear control-oriented model may be used to improve the performance of closed-loop control of blood glucose in diabetic patients. The nonlinear Wiener model is used as a novel modeling approach to be applied to the glucose control problem. The identified Wiener model is used in the design of a robust nonlinear sliding mode control strategy. Two configurations of the nonlinear controller are tested and compared to a controller designed with a linear model. The controllers are designed in a Smith predictor structure to reduce the effect of system time delay. To improve the meal compensation features, the controllers are provided with a simple feedforward controller to inject an insulin bolus at meal time. Different simulation scenarios have been used to evaluate the proposed controllers. The obtained results show that the new approach outperforms the linear control scheme, and regulates the glucose level within safe limits in the presence of measurement and modeling errors, meal uncertainty and patient variations. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

A novel approach to solve nonlinear Fredholm integral equations of the second kind.

PubMed

Li, Hu; Huang, Jin

2016-01-01

In this paper, we present a novel approach to solve nonlinear Fredholm integral equations of the second kind. This algorithm is constructed by the integral mean value theorem and Newton iteration. Convergence and error analysis of the numerical solutions are given. Moreover, Numerical examples show the algorithm is very effective and simple.

Nonlinear Image Denoising Methodologies

DTIC Science & Technology

2002-05-01

53 5.3 A Multiscale Approach to Scale-Space Analysis . . . . . . . . . . . . . . . . 53 5.4...etc. In this thesis, Our approach to denoising is first based on a controlled nonlinear stochastic random walk to achieve a scale space analysis ( as in... stochastic treatment or interpretation of the diffusion. In addition, unless a specific stopping time is known to be adequate, the resulting evolution

The Search for an Effective Clinical Behavior Analysis: The Nonlinear Thinking of Israel Goldiamond

ERIC Educational Resources Information Center

Layng, T. V. Joe

2009-01-01

This paper has two purposes; the first is to reintroduce Goldiamond's constructional approach to clinical behavior analysis and to the field of behavior analysis as a whole, which, unfortunately, remains largely unaware of his nonlinear functional analysis and its implications. The approach is not simply a set of clinical techniques; instead it…

Approaches to the Optimal Nonlinear Analysis of Microcalorimeter Pulses

NASA Astrophysics Data System (ADS)

Fowler, J. W.; Pappas, C. G.; Alpert, B. K.; Doriese, W. B.; O'Neil, G. C.; Ullom, J. N.; Swetz, D. S.

2018-03-01

We consider how to analyze microcalorimeter pulses for quantities that are nonlinear in the data, while preserving the signal-to-noise advantages of linear optimal filtering. We successfully apply our chosen approach to compute the electrothermal feedback energy deficit (the "Joule energy") of a pulse, which has been proposed as a linear estimator of the deposited photon energy.

Force-controlled absorption in a fully-nonlinear numerical wave tank

NASA Astrophysics Data System (ADS)

Spinneken, Johannes; Christou, Marios; Swan, Chris

2014-09-01

An active control methodology for the absorption of water waves in a numerical wave tank is introduced. This methodology is based upon a force-feedback technique which has previously been shown to be very effective in physical wave tanks. Unlike other methods, an a-priori knowledge of the wave conditions in the tank is not required; the absorption controller being designed to automatically respond to a wide range of wave conditions. In comparison to numerical sponge layers, effective wave absorption is achieved on the boundary, thereby minimising the spatial extent of the numerical wave tank. In contrast to the imposition of radiation conditions, the scheme is inherently capable of absorbing irregular waves. Most importantly, simultaneous generation and absorption can be achieved. This is an important advance when considering inclusion of reflective bodies within the numerical wave tank. In designing the absorption controller, an infinite impulse response filter is adopted, thereby eliminating the problem of non-causality in the controller optimisation. Two alternative controllers are considered, both implemented in a fully-nonlinear wave tank based on a multiple-flux boundary element scheme. To simplify the problem under consideration, the present analysis is limited to water waves propagating in a two-dimensional domain. The paper presents an extensive numerical validation which demonstrates the success of the method for a wide range of wave conditions including regular, focused and random waves. The numerical investigation also highlights some of the limitations of the method, particularly in simultaneously generating and absorbing large amplitude or highly-nonlinear waves. The findings of the present numerical study are directly applicable to related fields where optimum absorption is sought; these include physical wavemaking, wave power absorption and a wide range of numerical wave tank schemes.

A feedback linearization approach to spacecraft control using momentum exchange devices. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Dzielski, John Edward

1988-01-01

Recent developments in the area of nonlinear control theory have shown how coordiante changes in the state and input spaces can be used with nonlinear feedback to transform certain nonlinear ordinary differential equations into equivalent linear equations. These feedback linearization techniques are applied to resolve two problems arising in the control of spacecraft equipped with control moment gyroscopes (CMGs). The first application involves the computation of rate commands for the gimbals that rotate the individual gyroscopes to produce commanded torques on the spacecraft. The second application is to the long-term management of stored momentum in the system of control moment gyroscopes using environmental torques acting on the vehicle. An approach to distributing control effort among a group of redundant actuators is described that uses feedback linearization techniques to parameterize sets of controls which influence a specified subsystem in a desired way. The approach is adapted for use in spacecraft control with double-gimballed gyroscopes to produce an algorithm that avoids problematic gimbal configurations by approximating sets of gimbal rates that drive CMG rotors into desirable configurations. The momentum management problem is stated as a trajectory optimization problem with a nonlinear dynamical constraint. Feedback linearization and collocation are used to transform this problem into an unconstrainted nonlinear program. The approach to trajectory optimization is fast and robust. A number of examples are presented showing applications to the proposed NASA space station.

Combined genetic algorithm and multiple linear regression (GA-MLR) optimizer: Application to multi-exponential fluorescence decay surface.

PubMed

Fisz, Jacek J

2006-12-07

The optimization approach based on the genetic algorithm (GA) combined with multiple linear regression (MLR) method, is discussed. The GA-MLR optimizer is designed for the nonlinear least-squares problems in which the model functions are linear combinations of nonlinear functions. GA optimizes the nonlinear parameters, and the linear parameters are calculated from MLR. GA-MLR is an intuitive optimization approach and it exploits all advantages of the genetic algorithm technique. This optimization method results from an appropriate combination of two well-known optimization methods. The MLR method is embedded in the GA optimizer and linear and nonlinear model parameters are optimized in parallel. The MLR method is the only one strictly mathematical "tool" involved in GA-MLR. The GA-MLR approach simplifies and accelerates considerably the optimization process because the linear parameters are not the fitted ones. Its properties are exemplified by the analysis of the kinetic biexponential fluorescence decay surface corresponding to a two-excited-state interconversion process. A short discussion of the variable projection (VP) algorithm, designed for the same class of the optimization problems, is presented. VP is a very advanced mathematical formalism that involves the methods of nonlinear functionals, algebra of linear projectors, and the formalism of Fréchet derivatives and pseudo-inverses. Additional explanatory comments are added on the application of recently introduced the GA-NR optimizer to simultaneous recovery of linear and weakly nonlinear parameters occurring in the same optimization problem together with nonlinear parameters. The GA-NR optimizer combines the GA method with the NR method, in which the minimum-value condition for the quadratic approximation to chi(2), obtained from the Taylor series expansion of chi(2), is recovered by means of the Newton-Raphson algorithm. The application of the GA-NR optimizer to model functions which are multi-linear combinations of nonlinear functions, is indicated. The VP algorithm does not distinguish the weakly nonlinear parameters from the nonlinear ones and it does not apply to the model functions which are multi-linear combinations of nonlinear functions.

Stabilization Approaches for Linear and Nonlinear Reduced Order Models

NASA Astrophysics Data System (ADS)

Rezaian, Elnaz; Wei, Mingjun

2017-11-01

It has been a major concern to establish reduced order models (ROMs) as reliable representatives of the dynamics inherent in high fidelity simulations, while fast computation is achieved. In practice it comes to stability and accuracy of ROMs. Given the inviscid nature of Euler equations it becomes more challenging to achieve stability, especially where moving discontinuities exist. Originally unstable linear and nonlinear ROMs are stabilized here by two approaches. First, a hybrid method is developed by integrating two different stabilization algorithms. At the same time, symmetry inner product is introduced in the generation of ROMs for its known robust behavior for compressible flows. Results have shown a notable improvement in computational efficiency and robustness compared to similar approaches. Second, a new stabilization algorithm is developed specifically for nonlinear ROMs. This method adopts Particle Swarm Optimization to enforce a bounded ROM response for minimum discrepancy between the high fidelity simulation and the ROM outputs. Promising results are obtained in its application on the nonlinear ROM of an inviscid fluid flow with discontinuities. Supported by ARL.

A genuine nonlinear approach for controller design of a boiler-turbine system.

PubMed

Yang, Shizhong; Qian, Chunjiang; Du, Haibo

2012-05-01

This paper proposes a genuine nonlinear approach for controller design of a drum-type boiler-turbine system. Based on a second order nonlinear model, a finite-time convergent controller is first designed to drive the states to their setpoints in a finite time. In the case when the state variables are unmeasurable, the system will be regulated using a constant controller or an output feedback controller. An adaptive controller is also designed to stabilize the system since the model parameters may vary under different operating points. The novelty of the proposed controller design approach lies in fully utilizing the system nonlinearities instead of linearizing or canceling them. In addition, the newly developed techniques for finite-time convergent controller are used to guarantee fast convergence of the system. Simulations are conducted under different cases and the results are presented to illustrate the performance of the proposed controllers. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Nonlinear dispersion effects in elastic plates: numerical modelling and validation

NASA Astrophysics Data System (ADS)

Kijanka, Piotr; Radecki, Rafal; Packo, Pawel; Staszewski, Wieslaw J.; Uhl, Tadeusz; Leamy, Michael J.

2017-04-01

Nonlinear features of elastic wave propagation have attracted significant attention recently. The particular interest herein relates to complex wave-structure interactions, which provide potential new opportunities for feature discovery and identification in a variety of applications. Due to significant complexity associated with wave propagation in nonlinear media, numerical modeling and simulations are employed to facilitate design and development of new measurement, monitoring and characterization systems. However, since very high spatio- temporal accuracy of numerical models is required, it is critical to evaluate their spectral properties and tune discretization parameters for compromise between accuracy and calculation time. Moreover, nonlinearities in structures give rise to various effects that are not present in linear systems, e.g. wave-wave interactions, higher harmonics generation, synchronism and | recently reported | shifts to dispersion characteristics. This paper discusses local computational model based on a new HYBRID approach for wave propagation in nonlinear media. The proposed approach combines advantages of the Local Interaction Simulation Approach (LISA) and Cellular Automata for Elastodynamics (CAFE). The methods are investigated in the context of their accuracy for predicting nonlinear wavefields, in particular shifts to dispersion characteristics for finite amplitude waves and secondary wavefields. The results are validated against Finite Element (FE) calculations for guided waves in copper plate. Critical modes i.e., modes determining accuracy of a model at given excitation frequency - are identified and guidelines for numerical model parameters are proposed.

Maximum Likelihood Analysis of Nonlinear Structural Equation Models with Dichotomous Variables

ERIC Educational Resources Information Center

Song, Xin-Yuan; Lee, Sik-Yum

2005-01-01

In this article, a maximum likelihood approach is developed to analyze structural equation models with dichotomous variables that are common in behavioral, psychological and social research. To assess nonlinear causal effects among the latent variables, the structural equation in the model is defined by a nonlinear function. The basic idea of the…

Bayesian Analysis of Structural Equation Models with Nonlinear Covariates and Latent Variables

ERIC Educational Resources Information Center

Song, Xin-Yuan; Lee, Sik-Yum

2006-01-01

In this article, we formulate a nonlinear structural equation model (SEM) that can accommodate covariates in the measurement equation and nonlinear terms of covariates and exogenous latent variables in the structural equation. The covariates can come from continuous or discrete distributions. A Bayesian approach is developed to analyze the…

Nonlocal dark solitons under competing cubic-quintic nonlinearities.

PubMed

Chen, L; Wang, Q; Shen, M; Zhao, H; Lin, Y-Y; Jeng, C-C; Lee, R-K; Krolikowski, W

2013-01-01

We investigate properties of dark solitons under competing nonlocal cubic-local quintic nonlinearities. Analytical results, based on a variational approach and confirmed by direct numerical simulations, reveal the existence of a unique dark soliton solutions with their width being independent of the degree of nonlocality, due to the competing cubic-quintic nonlinearities.

Exact multisoliton solutions of general nonlinear Schrödinger equation with derivative.

PubMed

Li, Qi; Duan, Qiu-yuan; Zhang, Jian-bing

2014-01-01

Multisoliton solutions are derived for a general nonlinear Schrödinger equation with derivative by using Hirota's approach. The dynamics of one-soliton solution and two-soliton interactions are also illustrated. The considered equation can reduce to nonlinear Schrödinger equation with derivative as well as the solutions.

Joint nonlinearity effects in the design of a flexible truss structure control system

NASA Technical Reports Server (NTRS)

Mercadal, Mathieu

1986-01-01

Nonlinear effects are introduced in the dynamics of large space truss structures by the connecting joints which are designed with rather important tolerances to facilitate the assembly of the structures in space. The purpose was to develop means to investigate the nonlinear dynamics of the structures, particularly the limit cycles that might occur when active control is applied to the structures. An analytical method was sought and derived to predict the occurrence of limit cycles and to determine their stability. This method is mainly based on the quasi-linearization of every joint using describing functions. This approach was proven successful when simple dynamical systems were tested. Its applicability to larger systems depends on the amount of computations it requires, and estimates of the computational task tend to indicate that the number of individual sources of nonlinearity should be limited. Alternate analytical approaches, which do not account for every single nonlinearity, or the simulation of a simplified model of the dynamical system should, therefore, be investigated to determine a more effective way to predict limit cycles in large dynamical systems with an important number of distributed nonlinearities.

Spectral analysis for nonstationary and nonlinear systems: a discrete-time-model-based approach.

PubMed

He, Fei; Billings, Stephen A; Wei, Hua-Liang; Sarrigiannis, Ptolemaios G; Zhao, Yifan

2013-08-01

A new frequency-domain analysis framework for nonlinear time-varying systems is introduced based on parametric time-varying nonlinear autoregressive with exogenous input models. It is shown how the time-varying effects can be mapped to the generalized frequency response functions (FRFs) to track nonlinear features in frequency, such as intermodulation and energy transfer effects. A new mapping to the nonlinear output FRF is also introduced. A simulated example and the application to intracranial electroencephalogram data are used to illustrate the theoretical results.

Nonlinear optical interactions in silicon waveguides

NASA Astrophysics Data System (ADS)

Kuyken, B.; Leo, F.; Clemmen, S.; Dave, U.; Van Laer, R.; Ideguchi, T.; Zhao, H.; Liu, X.; Safioui, J.; Coen, S.; Gorza, S. P.; Selvaraja, S. K.; Massar, S.; Osgood, R. M.; Verheyen, P.; Van Campenhout, J.; Baets, R.; Green, W. M. J.; Roelkens, G.

2017-03-01

The strong nonlinear response of silicon photonic nanowire waveguides allows for the integration of nonlinear optical functions on a chip. However, the detrimental nonlinear optical absorption in silicon at telecom wavelengths limits the efficiency of many such experiments. In this review, several approaches are proposed and demonstrated to overcome this fundamental issue. By using the proposed methods, we demonstrate amongst others supercontinuum generation, frequency comb generation, a parametric optical amplifier, and a parametric optical oscillator.

In vivo multimodal nonlinear optical imaging of mucosal tissue

NASA Astrophysics Data System (ADS)

Sun, Ju; Shilagard, Tuya; Bell, Brent; Motamedi, Massoud; Vargas, Gracie

2004-05-01

We present a multimodal nonlinear imaging approach to elucidate microstructures and spectroscopic features of oral mucosa and submucosa in vivo. The hamster buccal pouch was imaged using 3-D high resolution multiphoton and second harmonic generation microscopy. The multimodal imaging approach enables colocalization and differentiation of prominent known spectroscopic and structural features such as keratin, epithelial cells, and submucosal collagen at various depths in tissue. Visualization of cellular morphology and epithelial thickness are in excellent agreement with histological observations. These results suggest that multimodal nonlinear optical microscopy can be an effective tool for studying the physiology and pathology of mucosal tissue.

gpICA: A Novel Nonlinear ICA Algorithm Using Geometric Linearization

NASA Astrophysics Data System (ADS)

Nguyen, Thang Viet; Patra, Jagdish Chandra; Emmanuel, Sabu

2006-12-01

A new geometric approach for nonlinear independent component analysis (ICA) is presented in this paper. Nonlinear environment is modeled by the popular post nonlinear (PNL) scheme. To eliminate the nonlinearity in the observed signals, a novel linearizing method named as geometric post nonlinear ICA (gpICA) is introduced. Thereafter, a basic linear ICA is applied on these linearized signals to estimate the unknown sources. The proposed method is motivated by the fact that in a multidimensional space, a nonlinear mixture is represented by a nonlinear surface while a linear mixture is represented by a plane, a special form of the surface. Therefore, by geometrically transforming the surface representing a nonlinear mixture into a plane, the mixture can be linearized. Through simulations on different data sets, superior performance of gpICA algorithm has been shown with respect to other algorithms.

Determining the Number of Participants Needed for the Usability Evaluation of E-Learning Resources: A Monte Carlo Simulation

ERIC Educational Resources Information Center

Davids, Mogamat Razeen; Harvey, Justin; Halperin, Mitchell L.; Chikte, Usuf M. E.

2015-01-01

The usability of computer interfaces has a major influence on learning. Optimising the usability of e-learning resources is therefore essential. However, this may be neglected because of time and monetary constraints. User testing is a common approach to usability evaluation and involves studying typical end-users interacting with the application…

Spaced Learning: The Design, Feasibility and Optimisation of SMART Spaces. Evaluation Report and Executive Summary

ERIC Educational Resources Information Center

O'Hare, Liam; Stark, Patrick; McGuinness, Carol; Biggart, Andy; Thurston, Allen

2017-01-01

This report describes the development and pilot evaluation of SMART Spaces. This programme aims to boost GCSE science outcomes by applying the principle that information is more easily learnt when it is repeated multiple times, with time passing between the repetitions. This approach is known as "spaced learning" and is contrasted with a…

Approaches to S&T Cost Modeling at the U.S. Air Force Research Laboratory/Vehicle Aeronautics Directorate

DTIC Science & Technology

2000-09-01

fassent, si rien ne change par ailleurs. plus proche de l’ing~ni~rie du vivant . Une vdritable optimisation des 6ldinents de soutien logistique A bord...s souvent dans les arbres l’utilisation en service. fonctionnels, peuvent 8tre recueillies plus facilement dans un tableau crois6 avec les divers syst

Need a University Adopt a Formal Environmental Management System?: Progress without an EMS at a Small University

ERIC Educational Resources Information Center

Spellerberg, Ian F.; Buchan, Graeme D.; Englefield, Russell

2004-01-01

What system does a university need to optimise its progress to sustainability? Discusses the gradation of approaches possible for a university as it strives to improve its environmental performance. Argues that an environmental policy plus mechanisms for its implementation can be adequate, and endorsement of a single formal EMS need not be…

Economic evaluation of pharmacist-led medication reviews in residential aged care facilities.

PubMed

Hasan, Syed Shahzad; Thiruchelvam, Kaeshaelya; Kow, Chia Siang; Ghori, Muhammad Usman; Babar, Zaheer-Ud-Din

2017-10-01

Medication reviews is a widely accepted approach known to have a substantial impact on patients' pharmacotherapy and safety. Numerous options to optimise pharmacotherapy in older people have been reported in literature and they include medication reviews, computerised decision support systems, management teams, and educational approaches. Pharmacist-led medication reviews are increasingly being conducted, aimed at attaining patient safety and medication optimisation. Cost effectiveness is an essential aspect of a medication review evaluation. Areas covered: A systematic searching of articles that examined the cost-effectiveness of medication reviews conducted in aged care facilities was performed using the relevant databases. Pharmacist-led medication reviews confer many benefits such as attainment of biomarker targets for improved clinical outcomes, and other clinical parameters, as well as depict concrete financial advantages in terms of decrement in total medication costs and associated cost savings. Expert commentary: The cost-effectiveness of medication reviews are more consequential than ever before. A critical evaluation of pharmacist-led medication reviews in residential aged care facilities from an economical aspect is crucial in determining if the time, effort, and direct and indirect costs involved in the review rationalise the significance of conducting medication reviews for older people in aged care facilities.

An Integrated Qualitative and Quantitative Biochemical Model Learning Framework Using Evolutionary Strategy and Simulated Annealing.

PubMed

Wu, Zujian; Pang, Wei; Coghill, George M

2015-01-01

Both qualitative and quantitative model learning frameworks for biochemical systems have been studied in computational systems biology. In this research, after introducing two forms of pre-defined component patterns to represent biochemical models, we propose an integrative qualitative and quantitative modelling framework for inferring biochemical systems. In the proposed framework, interactions between reactants in the candidate models for a target biochemical system are evolved and eventually identified by the application of a qualitative model learning approach with an evolution strategy. Kinetic rates of the models generated from qualitative model learning are then further optimised by employing a quantitative approach with simulated annealing. Experimental results indicate that our proposed integrative framework is feasible to learn the relationships between biochemical reactants qualitatively and to make the model replicate the behaviours of the target system by optimising the kinetic rates quantitatively. Moreover, potential reactants of a target biochemical system can be discovered by hypothesising complex reactants in the synthetic models. Based on the biochemical models learned from the proposed framework, biologists can further perform experimental study in wet laboratory. In this way, natural biochemical systems can be better understood.

Efficient Genotyping of KRAS Mutant Non-Small Cell Lung Cancer Using a Multiplexed Droplet Digital PCR Approach.

PubMed

Pender, Alexandra; Garcia-Murillas, Isaac; Rana, Sareena; Cutts, Rosalind J; Kelly, Gavin; Fenwick, Kerry; Kozarewa, Iwanka; Gonzalez de Castro, David; Bhosle, Jaishree; O'Brien, Mary; Turner, Nicholas C; Popat, Sanjay; Downward, Julian

2015-01-01

Droplet digital PCR (ddPCR) can be used to detect low frequency mutations in oncogene-driven lung cancer. The range of KRAS point mutations observed in NSCLC necessitates a multiplex approach to efficient mutation detection in circulating DNA. Here we report the design and optimisation of three discriminatory ddPCR multiplex assays investigating nine different KRAS mutations using PrimePCR™ ddPCR™ Mutation Assays and the Bio-Rad QX100 system. Together these mutations account for 95% of the nucleotide changes found in KRAS in human cancer. Multiplex reactions were optimised on genomic DNA extracted from KRAS mutant cell lines and tested on DNA extracted from fixed tumour tissue from a cohort of lung cancer patients without prior knowledge of the specific KRAS genotype. The multiplex ddPCR assays had a limit of detection of better than 1 mutant KRAS molecule in 2,000 wild-type KRAS molecules, which compared favourably with a limit of detection of 1 in 50 for next generation sequencing and 1 in 10 for Sanger sequencing. Multiplex ddPCR assays thus provide a highly efficient methodology to identify KRAS mutations in lung adenocarcinoma.

Efficient Genotyping of KRAS Mutant Non-Small Cell Lung Cancer Using a Multiplexed Droplet Digital PCR Approach

PubMed Central

Pender, Alexandra; Garcia-Murillas, Isaac; Rana, Sareena; Cutts, Rosalind J.; Kelly, Gavin; Fenwick, Kerry; Kozarewa, Iwanka; Gonzalez de Castro, David; Bhosle, Jaishree; O’Brien, Mary; Turner, Nicholas C.; Popat, Sanjay; Downward, Julian

2015-01-01

Droplet digital PCR (ddPCR) can be used to detect low frequency mutations in oncogene-driven lung cancer. The range of KRAS point mutations observed in NSCLC necessitates a multiplex approach to efficient mutation detection in circulating DNA. Here we report the design and optimisation of three discriminatory ddPCR multiplex assays investigating nine different KRAS mutations using PrimePCR™ ddPCR™ Mutation Assays and the Bio-Rad QX100 system. Together these mutations account for 95% of the nucleotide changes found in KRAS in human cancer. Multiplex reactions were optimised on genomic DNA extracted from KRAS mutant cell lines and tested on DNA extracted from fixed tumour tissue from a cohort of lung cancer patients without prior knowledge of the specific KRAS genotype. The multiplex ddPCR assays had a limit of detection of better than 1 mutant KRAS molecule in 2,000 wild-type KRAS molecules, which compared favourably with a limit of detection of 1 in 50 for next generation sequencing and 1 in 10 for Sanger sequencing. Multiplex ddPCR assays thus provide a highly efficient methodology to identify KRAS mutations in lung adenocarcinoma. PMID:26413866

[Quality management in implementing specialist pediatric palliative home care in Lower Saxony, Germany].

PubMed

Kremeike, Kerstin; Eulitz, Nina; Sens, Brigitte; Geraedts, Max; Reinhardt, Dirk

2012-01-01

To provide comprehensive high-quality health care is a great challenge in the context of high specialisation and intensive costs. This problem becomes further aggravated in service areas with low patient numbers and low numbers of specialists. Therefore, a multidimensional approach to quality development was chosen in order to optimise the care of children and adolescents with life-limiting conditions in Lower Saxony, a German federal state with a predominantly rural infrastructure. Different service structures were implemented and a classification of service provider's specialisation was defined on the basis of existing references of professional associations. Measures to optimise care were implemented in a process-oriented manner. High-quality health care can be facilitated by carefully worded requirements concerning the quality of structures combined with optimally designed processes. Parts of the newly implemented paediatric palliative care structures are funded by the statutory health insurance. Copyright © 2012. Published by Elsevier GmbH.

Comparisons of the utility of researcher-defined and participant-defined successful ageing.

PubMed

Brown, Lynsey J; Bond, Malcolm J

2016-03-01

To investigate the impact of different approaches for measuring 'successful ageing', four alternative researcher and participant definitions were compared, including a novel measure informed by cluster analysis. Rates of successful ageing were explored, as were their relative associations with age and measures of successful adaptation, to assess construct validity. Participants, aged over 65, were recruited from community-based organisations. Questionnaires (assessing successful ageing, lifestyle activities and selective optimisation with compensation) were completed by 317 individuals. Successful ageing ranged from 11.4% to 87.4%, with higher rates evident from participant definitions. Though dependent upon the definition, successful agers were typically younger, reported greater engagement with lifestyle activities and more frequent optimisation. While the current study suggested an improved classification algorithm using a common research definition, future research should explore how subjective and objective aspects of successful ageing may be combined to derive a measure relevant to policy and practice. © 2016 AJA Inc.

Achieving an optimal allocation of resources for animal health surveillance, intervention and disease mitigation.

PubMed

Hasler, B; Delabouglise, A; Babo Martins, S

2017-04-01

The primary role of animal health economics is to inform decision-making by determining optimal investments for animal health. Animal health surveillance produces information to guide interventions. Consequently, investments in surveillance and intervention must be evaluated together. This article explores the different theoretical frameworks and methods developed to assess and optimise the spending of resources in surveillance and intervention and their technical interdependence. The authors present frameworks that define the relationship between health investment and losses due to disease, and the relationship between surveillance and intervention resources. Surveillance and intervention are usually considered as technical substitutes, since increased investments in surveillance reduce the level of intervention resources required to reach the same benefit. The authors also discuss approaches used to quantify externalities and non-monetary impacts. Finally, they describe common economic evaluation types, including optimisation, acceptability and least-cost studies.

Towards optimal experimental tests on the reality of the quantum state

NASA Astrophysics Data System (ADS)

Knee, George C.

2017-02-01

The Barrett-Cavalcanti-Lal-Maroney (BCLM) argument stands as the most effective means of demonstrating the reality of the quantum state. Its advantages include being derived from very few assumptions, and a robustness to experimental error. Finding the best way to implement the argument experimentally is an open problem, however, and involves cleverly choosing sets of states and measurements. I show that techniques from convex optimisation theory can be leveraged to numerically search for these sets, which then form a recipe for experiments that allow for the strongest statements about the ontology of the wavefunction to be made. The optimisation approach presented is versatile, efficient and can take account of the finite errors present in any real experiment. I find significantly improved low-cardinality sets which are guaranteed partially optimal for a BCLM test in low Hilbert space dimension. I further show that mixed states can be more optimal than pure states.

Important considerations about nursing intelligence and information systems.

PubMed

Ballard, E C

1997-01-01

This discussion focuses on the importance of nursing intelligence to the organisation, and the nurses' role in gathering and utilising such intelligence. Deliberations with professional colleagues suggest that intelligence can only be utilised fully when the information systems are developed in such a way as to meet the needs of the people who manage and provide nursing care at the consumer level; that is, the activity of nursing itself. If accommodation is made for the recycling of nursing intelligence, there would be a support and furtherance of 'professional' intelligence. Two main issues emerge: how can nurses support the needs of management to optimise intelligence input? how can organisations optimise the contribution of nurses to its information processes and interpretation of intelligence? The expansion of this 'professional' intelligence would promote a generation of constantly reviewed data, offering a quality approach to nursing activities and an organisation's intelligence system.

Fluid Mechanics Optimising Organic Synthesis

NASA Astrophysics Data System (ADS)

Leivadarou, Evgenia; Dalziel, Stuart

2015-11-01

The Vortex Fluidic Device (VFD) is a new ``green'' approach in the synthesis of organic chemicals with many industrial applications in biodiesel generation, cosmetics, protein folding and pharmaceutical production. The VFD is a rapidly rotating tube that can operate with a jet feeding drops of liquid reactants to the base of the tube. The aim of this project is to explain the fluid mechanics of the VFD that influence the rate of reactions. The reaction rate is intimately related to the intense shearing that promotes collision between reactant molecules. In the VFD, the highest shears are found at the bottom of the tube in the Rayleigh and the Ekman layer and at the walls in the Stewardson layers. As a step towards optimising the performance of the VFD we present experiments conducted in order to establish the minimum drop volume and maximum rotation rate for maximum axisymmetric spreading without fingering instability. PhD candidate, Department of Applied Mathematics and Theoretical Physics.

Optimisation algorithms for ECG data compression.

PubMed

Haugland, D; Heber, J G; Husøy, J H

1997-07-01

The use of exact optimisation algorithms for compressing digital electrocardiograms (ECGs) is demonstrated. As opposed to traditional time-domain methods, which use heuristics to select a small subset of representative signal samples, the problem of selecting the subset is formulated in rigorous mathematical terms. This approach makes it possible to derive algorithms guaranteeing the smallest possible reconstruction error when a bounded selection of signal samples is interpolated. The proposed model resembles well-known network models and is solved by a cubic dynamic programming algorithm. When applied to standard test problems, the algorithm produces a compressed representation for which the distortion is about one-half of that obtained by traditional time-domain compression techniques at reasonable compression ratios. This illustrates that, in terms of the accuracy of decoded signals, existing time-domain heuristics for ECG compression may be far from what is theoretically achievable. The paper is an attempt to bridge this gap.

H∞ output tracking control of discrete-time nonlinear systems via standard neural network models.

PubMed

Liu, Meiqin; Zhang, Senlin; Chen, Haiyang; Sheng, Weihua

2014-10-01

This brief proposes an output tracking control for a class of discrete-time nonlinear systems with disturbances. A standard neural network model is used to represent discrete-time nonlinear systems whose nonlinearity satisfies the sector conditions. H∞ control performance for the closed-loop system including the standard neural network model, the reference model, and state feedback controller is analyzed using Lyapunov-Krasovskii stability theorem and linear matrix inequality (LMI) approach. The H∞ controller, of which the parameters are obtained by solving LMIs, guarantees that the output of the closed-loop system closely tracks the output of a given reference model well, and reduces the influence of disturbances on the tracking error. Three numerical examples are provided to show the effectiveness of the proposed H∞ output tracking design approach.

Frequency-domain full-waveform inversion with non-linear descent directions

NASA Astrophysics Data System (ADS)

Geng, Yu; Pan, Wenyong; Innanen, Kristopher A.

2018-05-01

Full-waveform inversion (FWI) is a highly non-linear inverse problem, normally solved iteratively, with each iteration involving an update constructed through linear operations on the residuals. Incorporating a flexible degree of non-linearity within each update may have important consequences for convergence rates, determination of low model wavenumbers and discrimination of parameters. We examine one approach for doing so, wherein higher order scattering terms are included within the sensitivity kernel during the construction of the descent direction, adjusting it away from that of the standard Gauss-Newton approach. These scattering terms are naturally admitted when we construct the sensitivity kernel by varying not the current but the to-be-updated model at each iteration. Linear and/or non-linear inverse scattering methodologies allow these additional sensitivity contributions to be computed from the current data residuals within any given update. We show that in the presence of pre-critical reflection data, the error in a second-order non-linear update to a background of s0 is, in our scheme, proportional to at most (Δs/s0)3 in the actual parameter jump Δs causing the reflection. In contrast, the error in a standard Gauss-Newton FWI update is proportional to (Δs/s0)2. For numerical implementation of more complex cases, we introduce a non-linear frequency-domain scheme, with an inner and an outer loop. A perturbation is determined from the data residuals within the inner loop, and a descent direction based on the resulting non-linear sensitivity kernel is computed in the outer loop. We examine the response of this non-linear FWI using acoustic single-parameter synthetics derived from the Marmousi model. The inverted results vary depending on data frequency ranges and initial models, but we conclude that the non-linear FWI has the capability to generate high-resolution model estimates in both shallow and deep regions, and to converge rapidly, relative to a benchmark FWI approach involving the standard gradient.

Engineering high-order nonlinear dissipation for quantum superconducting circuits

NASA Astrophysics Data System (ADS)

Mundhada, S. O.; Grimm, A.; Touzard, S.; Shankar, S.; Minev, Z. K.; Vool, U.; Mirrahimi, M.; Devoret, M. H.

Engineering nonlinear driven-dissipative processes is essential for quantum control. In the case of a harmonic oscillator, nonlinear dissipation can stabilize a decoherence-free manifold, leading to protected quantum information encoding. One possible approach to implement such nonlinear interactions is to combine the nonlinearities provided by Josephson circuits with parametric pump drives. However, it is usually hard to achieve strong nonlinearities while avoiding undesired couplings. Here we propose a scheme to engineer a four-photon drive and dissipation in a harmonic oscillator by cascading experimentally demonstrated two-photon processes. We also report experimental progress towards realization of such a scheme. Work supported by: ARO, ONR, AFOSR and YINQE.

Non-linear heterogeneous FE approach for FRP strengthened masonry arches

NASA Astrophysics Data System (ADS)

Bertolesi, Elisa; Milani, Gabriele; Fedele, Roberto

2015-12-01

A fast and reliable non-linear heterogeneous FE approach specifically conceived for the analysis of FRP-reinforced masonry arches is presented. The approach proposed relies into the reduction of mortar joints to interfaces exhibiting a non-linear holonomic behavior, with a discretization of bricks by means of four-noded elastic elements. The FRP reinforcement is modeled by means of truss elements with elastic-brittle behavior, where the peak tensile strength is estimated by means of a consolidated approach provided by the Italian guidelines CNR-DT200 on masonry strengthening with fiber materials, where the delamination of the strip from the support is taken into account. The model is validated against some recent experimental results relying into circular masonry arches reinforced at both the intrados and the extrados. Some sensitivity analyses are conducted varying the peak tensile strength of the trusses representing the FRP reinforcement.