Some characteristics of thin shear layers in homogeneous turbulent flow.

Tomographic particle image velocimetry measurements of homogeneous isotropic turbulence that have been made in a large mixing tank facility at Cambridge are analysed in order to characterize thin highly sheared regions that have been observed. The results indicate that such regions coincide with regions of high enstrophy, dissipation and stretching. Large velocity jumps are observed across the width of these regions. The thickness of the shear layers seems to scale with the Taylor microscale, as has been suggested previously. The results discussed here concentrate on examining individual realizations rather than statistics of these regions.

Analogical reasoning in case-based design

A computer can assist the process of design by analogy by recording past designs. The experience these represent could be much wider than that of designers using the system, who therefore need to identify potential cases of interest. If the computer assists with this lookup, the designers can concentrate on the more interesting aspect of extracting and using the ideas which are found. However, as the knowledge base grows it becomes ever harder to find relevant cases using a keyword indexing scheme without knowing precisely what to look for. Therefore a more flexible searching system is needed.

If a similarity measure can be defined for the features of the designs, then it is possible to match and cluster them. Using a simple measure like co-occurrence of features within a particular case would allow this to happen without human intervention, which is tedious and time- consuming. Any knowledge that is acquired about how features are related to each other will be very shallow: it is not intended as a cognitive model for how humans understand, learn, or retrieve information, but more an attempt to make effective, efficient use of the information available. The question remains of whether such shallow knowledge is sufficient for the task.

A system to retrieve information from a large database is described. It uses co-occurrences to relate keywords to each other, and then extends search queries with similar words. This seems to make relevant material more accessible, providing hope that this retrieval technique can be applied to a broader knowledge base.

One style does not fit all

The different types of outsourcing and the management requirements for each of them are discussed. An outsourcing has a high strategic importance to the buying company when it is aligned with the organization's long term strategies and when its results are either positive or negative. Functional outsourcings are characterized by both low strategic importance and financial impact, and the products/services that fall in this category belong to support activities which are highly standardized. Leverage outsourcings are those that have a low strategic importance, but high financial impact to the outsourcer, and they concentrate on operational aspects, leaving strategic issues.

An ecodesign model based on industry experience

With the increase in environmental legislation facing many industrial sectors organisations are now looking for ways to improve their environmental performance. To a large extent organisations have tended to concentrate on their operations inside the "factory gates" with little regard to the environmental performance of the products they produce. However, this is now changing and some organisations are beginning to take a close look at their products and their effects on the environment during its use phase as well as during the manufacture and disposal phases. At Cranfield University we have carried out a 3 year survey of US, Central European and UK companies claiming to practice ecodesign has been undertaken. Thirty electrical and electronic manufacturers were studied, some through in-depth observation of design programmes, most through semi-structured interviews. The survey and action research sought to understand the way in which these companies practised ecodesign and how they .had implemented ecodesign. A common pattern emerged from the data which suggests that companies successfully implementing ecodesign have many similar experiences. The resulting ecodesign model is presented and discussed, and the factors critical to successful implementation at various stages are explored. The factors cover a range of topics including design management, motivation, design tools, design phases, communication and the designers perspective.

Characteristics of blood flow in microchannels and relevant impact on modelling blood behaviour in biochip separators

This paper reports a perspective investigation of computational modelling of blood fluid in microchannel devices as a preparation for future research on fluid-structure interaction (FSI) in biofluid mechanics. The investigation is carried out through two aspects, respectively on physical behaviours of blood flow in microchannels and appropriate methodology for modelling. The physics of blood flow is targeted to the challenges for describing blood flow in microchannels, including rheology of blood fluid, suspension features of red blood cells (RBCs), laminar hydrodynamic influence and effect of surface roughness. The analysis shows that due to the hyperelastic property of RBC and its comparable dimension with microchannels, blood fluid shows complex behaviours of two phase flow. The trajectory and migration of RBCs require accurate description of RBC deformation and interaction with plasma. Following on a discussion of modelling approaches, i.e. Eulerian method and Lagrangian method, the main stream modelling methods for multiphase flow are reviewed and their suitability to blood flow is analysed. It is concluded that the key issue for blood flow modelling is how to describe the suspended blood cells, modelled by Lagrangian method, and couple them with the based flow, modelled by Eulerian method. The multiphase flow methods are thereby classified based on the number of points required for describing a particle, as follows: (i) single-point particle methods, (ii) mutli-point particle methods, (iii) functional particle methods, and (iv) fluid particle methods. While single-point particle methods concentrate on particle dynamic movement, multipoint and functional particle methods can take into account particle mechanics and thus offer more detailed information for individual particles. Fluid particle methods provide good compromise between two phases, but require additional information for particle mechanics. For furthermore detailed description, we suggest to investigate the possibility using two domain coupling method, in which particles and base flow are modelled by two separated solvers. It is expected that this paper could clarify relevant issues in numerical modelling of blood flow in microchannels and induce some considerations for modelling blood flow using multiphase flow methods. © 2012 IEEE.

Modeling natural sounds with modulation cascade processes

Natural sounds are structured on many time-scales. A typical segment of speech, for example, contains features that span four orders of magnitude: Sentences ($\sim1$s); phonemes ($\sim10$−$1$ s); glottal pulses ($\sim 10$−$2$s); and formants ($\sim 10$−$3$s). The auditory system uses information from each of these time-scales to solve complicated tasks such as auditory scene analysis [1]. One route toward understanding how auditory processing accomplishes this analysis is to build neuroscience-inspired algorithms which solve similar tasks and to compare the properties of these algorithms with properties of auditory processing. There is however a discord: Current machine-audition algorithms largely concentrate on the shorter time-scale structures in sounds, and the longer structures are ignored. The reason for this is two-fold. Firstly, it is a difficult technical problem to construct an algorithm that utilises both sorts of information. Secondly, it is computationally demanding to simultaneously process data both at high resolution (to extract short temporal information) and for long duration (to extract long temporal information). The contribution of this work is to develop a new statistical model for natural sounds that captures structure across a wide range of time-scales, and to provide efficient learning and inference algorithms. We demonstrate the success of this approach on a missing data task.

Probabilistic Amplitude Demodulation

Auditory scene analysis is extremely challenging. One approach, perhaps that adopted by the brain, is to shape useful representations of sounds on prior knowledge about their statistical structure. For example, sounds with harmonic sections are common and so time-frequency representations are efficient. Most current representations concentrate on the shorter components. Here, we propose representations for structures on longer time-scales, like the phonemes and sentences of speech. We decompose a sound into a product of processes, each with its own characteristic time-scale. This demodulation cascade relates to classical amplitude demodulation, but traditional algorithms fail to realise the representation fully. A new approach, probabilistic amplitude demodulation, is shown to out-perform the established methods, and to easily extend to representation of a full demodulation cascade.