Curvature and wrinkling of premixed flame kernels-comparisons of OH PLIF and DNS data

The effects of curvature and wrinkling on the growth of turbulent premixed flame kernels were studied using both two-dimensional OH Planar Laser-Induced Fluorescence (PLIF) and three-dimensional Direct Numerical Simulation (DNS). Comparisons of results between the two approaches showed a high level of agreement, providing confidence in the simplified chemistry treatment employed in the DNS, and indicating that chemistry might have only a limited influence on the evolution of the freely propagating flame. The usefulness of PLIF in providing data over a wide parameter range was illustrated using statistics obtained from both CH4/air and H2/air mixtures, which show markedly different behavior due to their different thermo-diffusive properties. The results provided a demonstration of the combined power of PLIF and DNS for flame investigation. Each technique compensate for the weaknesses of the other, and to reinforce the strengths of both.

Design-phase-specific selection of user research methods

For increasing the usability of a medical device the usability engineering standards IEC 60601-1-6 and IEC 62366 suggest incorporating user information in the design and development process. However, practice shows that integrating user information and the related investigation of users, called user research, is difficult in the field of medical devices. In particular, identifying the most appropriate user research methods is a difficult process. This difficulty results from the complexity of the medical device industry, especially with respect to regulations and standards, the characteristics of this market and the broad range of potential user research methods available from various research disciplines. Against this background, this study aimed at guiding designers and engineers in selecting effective user research methods according to their stage in the design process. Two approaches are described which reduce the complexity of method selection by summarizing the high number of methods into homogenous method classes. These approaches are closely connected to the medical device industry characteristic design phases and therefore provide the possibility of selecting design-phase- specific user research methods. In the first approach potential user research methods are classified after their characteristics in the design process. The second approach suggests a method summarization according to their similarity in the data collection techniques and provides an additional linkage to design phase characteristics. Both approaches have been tested in practice and the results show that both approaches facilitate user research method selection. © 2009 Springer-Verlag.

Control theory and systems biology

Presenting a control-theoretic treatment of stoichiometric systems, ... local parametric sensitivity analysis, the two approaches yield identical results. ...

Efficient Implementation of Spatially-Varying 3-D Ultrasound Deconvolution

Abstract—There are sometimes occasions when ultrasound beamforming is performed with only a subset of the total data that will eventually be available. The most obvious example is a mechanically-swept (wobbler) probe in which the three-dimensional data block is formed from a set of individual B-scans. In these circumstances, non-blind deconvolution can be used to improve the resolution of the data. Unfortunately, most of these situations involve large blocks of three-dimensional data. Furthermore, the ultrasound blur function varies spatially with distance from the transducer. These two facts make the deconvolution process time-consuming to implement. This paper is about ways to address this problem and produce spatially-varying deconvolution of large blocks of three-dimensional data in a matter of seconds. We present two approaches, one based on hardware and the other based on software. We compare the time they each take to achieve similar results and discuss the computational resources and form of blur model that each requires.

Linear quadratic game and non-cooperative predictive methods for potential application to modelling driver-AFS interactive steering control

This paper is concerned with the modelling of strategic interactions between the human driver and the vehicle active front steering (AFS) controller in a path-following task where the two controllers hold different target paths. The work is aimed at extending the use of mathematical models in representing driver steering behaviour in complicated driving situations. Two game theoretic approaches, namely linear quadratic game and non-cooperative model predictive control (non-cooperative MPC), are used for developing the driver-AFS interactive steering control model. For each approach, the open-loop Nash steering control solution is derived; the influences of the path-following weights, preview and control horizons, driver time delay and arm neuromuscular system (NMS) dynamics are investigated, and the CPU time consumed is recorded. It is found that the two approaches give identical time histories as well as control gains, while the non-cooperative MPC method uses much less CPU time. Specifically, it is observed that the introduction of weight on the integral of vehicle lateral displacement error helps to eliminate the steady-state path-following error; the increase in preview horizon and NMS natural frequency and the decline in time delay and NMS damping ratio improve the path-following accuracy. © 2013 Copyright Taylor and Francis Group, LLC.

Reinforcement learning using a continuous time actor-critic framework with spiking neurons.

Animals repeat rewarded behaviors, but the physiological basis of reward-based learning has only been partially elucidated. On one hand, experimental evidence shows that the neuromodulator dopamine carries information about rewards and affects synaptic plasticity. On the other hand, the theory of reinforcement learning provides a framework for reward-based learning. Recent models of reward-modulated spike-timing-dependent plasticity have made first steps towards bridging the gap between the two approaches, but faced two problems. First, reinforcement learning is typically formulated in a discrete framework, ill-adapted to the description of natural situations. Second, biologically plausible models of reward-modulated spike-timing-dependent plasticity require precise calculation of the reward prediction error, yet it remains to be shown how this can be computed by neurons. Here we propose a solution to these problems by extending the continuous temporal difference (TD) learning of Doya (2000) to the case of spiking neurons in an actor-critic network operating in continuous time, and with continuous state and action representations. In our model, the critic learns to predict expected future rewards in real time. Its activity, together with actual rewards, conditions the delivery of a neuromodulatory TD signal to itself and to the actor, which is responsible for action choice. In simulations, we show that such an architecture can solve a Morris water-maze-like navigation task, in a number of trials consistent with reported animal performance. We also use our model to solve the acrobot and the cartpole problems, two complex motor control tasks. Our model provides a plausible way of computing reward prediction error in the brain. Moreover, the analytically derived learning rule is consistent with experimental evidence for dopamine-modulated spike-timing-dependent plasticity.

Bayesian two-sample tests

In this paper, we present two classes of Bayesian approaches to the two-sample problem. Our first class of methods extends the Bayesian t-test to include all parametric models in the exponential family and their conjugate priors. Our second class of methods uses Dirichlet process mixtures (DPM) of such conjugate-exponential distributions as flexible nonparametric priors over the unknown distributions.

Model-based approaches to handling additive noise in reverberant environments

Model-based approaches to handle additive and convolutional noise have been extensively investigated and used. However, the application of these schemes to handling reverberant noise has received less attention. This paper examines the extension of two standard additive/convolutional noise approaches to handling reverberant noise. The first is an extension of vector Taylor series (VTS) compensation, reverberant VTS, where a mismatch function including reverberant noise is used. The second scheme modifies constrained MLLR to allow a wide-span of frames to be taken into account and projected into the required dimensionality. To allow additive noise to be handled, both these schemes are combined with standard VTS. The approaches are evaluated and compared on two tasks, MC-WSJ-AV, and a reverberant simulated version of AURORA-4. © 2011 IEEE.

Alternative approaches to slum upgrading in Kibera, Nairobi

This paper discusses the sustainability of two different approaches to upgrade water and sanitation infrastructure in Kenya’s largest informal settlement, Kibera. A background to the urbanization of poverty is outlined along with approaches to urban slums. Two case-studies of completed interventions of infrastructure upgrading have been investigated. In one case-study, the upgrading method driven by an NGO uses an integrated livelihoods and partnership technique at community level to create an individual project. in the other case-study, the method is a collaboration between the government and a multi-lateral agency to deliver upgraded services as a part of a country-wide programme. The ‘bottom-up’ (project) and ‘top-down’ (programme) approaches each seek sustainability and aim to achieve this in the same context using different techniques. This paper investigates the sustainability of each approach. The merits and challenges of the approaches are discussed with the projected future of Kibera. The paper highlights the valuable opportunity for the role of appropriate engineering infrastructure for sustainable urban development, as well as the alleviation of poverty in a developing context.

System-of-system Approaches and Challenges for Multi-Site Manufacturing

In the multi-site manufacturing domain, systems-of-systems (SoS) are rarely called so. However, there exist a number of collaborative manufacturing paradigms which closely relate to system-of-system principles. These include distributed manufacturing, dispersed network manufacturing, virtual enterprises and cloud manufacturing/manufacturing-as-a-service. This paper provides an overview of these terms and paradigms, exploring their characteristics, overlaps and differences. These manufacturing paradigms are then considered in relation to five key system-of-systems characteristics: autonomy, belonging, connectivity, diversity and emergence. Data collected from two surveys of academic and industry experts is presented and discussed, with key challenges and barriers to multi-site manufacturing SoS identified.

Alternative approaches to slum upgrading in Kibera, Nairobi

This paper discusses the sustainability of two different approaches to upgrade water and sanitation infrastructure in Kenya's largest informal settlement, Kibera. A background to the urbanisation of poverty is outlined along with approaches to urban slums. Two case studies of completed interventions of infrastructure upgrading have been investigated. In one case study, the upgrading method driven by a non-government organisation uses an integrated livelihoods and partnership technique at community level to create an individual project. In the other case study, the method is a collaboration between the government and a multi-lateral agency to deliver upgraded services as part of a country-wide programme. The 'bottom-up' (project) and 'top-down' (programme) approaches both seek sustainability and aim to achieve this in the same context using different techniques. This paper investigates the sustainability of each approach. The merits and challenges of the approaches are discussed with the projected future of Kibera. The paper highlights the valuable opportunity for the role of appropriate engineering infrastructure for sustainable urban development, as well as the alleviation of poverty in a developing context.

New approaches for enhancing light emission from Er-based materials and devices

In this work, we present some approaches recently developed for enhancing light emission from Er-based materials and devices. We have investigated the luminescence quenching processes limiting quantum efficiency in light-emitting devices based on Si nanoclusters (Si nc) or Er-doped Si nc. It is found that carrier injection, while needed to excite Si nc or Er ions through electron-hole recombination, at the same time produces an efficient non-radiative Auger de-excitation with trapped carriers. A strong light confinement and enhancement of Er emission at 1.54 μm in planar silicon-on-insulator waveguides containing a thin layer (slot) of SiO2 with Er-doped Si nc at the center of the Si core has been obtained. By measuring the guided photoluminescence from the cleaved edge of the sample, we have observed a more than fivefold enhancement of emission for the transverse magnetic mode over the transverse electric one at room temperature. Slot waveguides have also been integrated with a photonic crystal (PhC), consisting of a triangular lattice of holes. An enhancement by more than two orders of magnitude of the Er near-normal emission is observed when the transition is in resonance with an appropriate mode of the PhC slab. Finally, in order to increase the concentration of excitable Er ions, a completely different approach, based on Er disilicate thin films, has been explored. Under proper annealing conditions crystalline and chemically stable Er2Si2O7 films are obtained; these films exhibit a strong luminescence at 1.54 μm owing to the efficient reduction of the defect density. © 2008 Elsevier B.V. All rights reserved.