Co-occurrence flow for pedestrian detection

The last few years have seen considerable progress in pedestrian detection. Recent work has established a combination of oriented gradients and optic flow as effective features although the detection rates are still unsatisfactory for practical use. This paper introduces a new type of motion feature, the co-occurrence flow (CoF). The advance is to capture relative movements of different parts of the entire body, unlike existing motion features which extract internal motion in a local fashion. Through evaluations on the TUD-Brussels pedestrian dataset, we show that our motion feature based on co-occurrence flow contributes to boost the performance of existing methods. © 2011 IEEE.

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.

The direct field boundary impedance of two-dimensional periodic structures with application to high frequency vibration prediction.

Large sections of many types of engineering construction can be considered to constitute a two-dimensional periodic structure, with examples ranging from an orthogonally stiffened shell to a honeycomb sandwich panel. In this paper, a method is presented for computing the boundary (or edge) impedance of a semi-infinite two-dimensional periodic structure, a quantity which is referred to as the direct field boundary impedance matrix. This terminology arises from the fact that none of the waves generated at the boundary (the direct field) are reflected back to the boundary in a semi-infinite system. The direct field impedance matrix can be used to calculate elastic wave transmission coefficients, and also to calculate the coupling loss factors (CLFs), which are required by the statistical energy analysis (SEA) approach to predicting high frequency vibration levels in built-up systems. The calculation of the relevant CLFs enables a two-dimensional periodic region of a structure to be modeled very efficiently as a single subsystem within SEA, and also within related methods, such as a recently developed hybrid approach, which couples the finite element method with SEA. The analysis is illustrated by various numerical examples involving stiffened plate structures.

Global linear and nonlinear stability of viscous confined plane wakes with co-flow

The global stability of confined uniform density wakes is studied numerically, using two-dimensional linear global modes and nonlinear direct numerical simulations. The wake inflow velocity is varied between different amounts of co-flow (base bleed). In accordance with previous studies, we find that the frequencies of both the most unstable linear and the saturated nonlinear global mode increase with confinement. For wake Reynolds number Re = 100 we find the confinement to be stabilising, decreasing the growth rate of the linear and the saturation amplitude of the nonlinear modes. The dampening effect is connected to the streamwise development of the base flow, and decreases for more parallel flows at higher Re. The linear analysis reveals that the critical wake velocities are almost identical for unconfined and confined wakes at Re ≈ 400. Further, the results are compared with literature data for an inviscid parallel wake. The confined wake is found to be more stable than its inviscid counterpart, whereas the unconfined wake is more unstable than the inviscid wake. The main reason for both is the base flow development. A detailed comparison of the linear and nonlinear results reveals that the most unstable linear global mode gives in all cases an excellent prediction of the initial nonlinear behaviour and therefore the stability boundary. However, the nonlinear saturated state is different, mainly for higher Re. For Re = 100, the saturated frequency differs less than 5% from the linear frequency, and trends regarding confinement observed in the linear analysis are confirmed.

The structure of turbulent stratified and premixed methane/air flames I: Non-swirling flows

A series of flames in a turbulent methane/air stratified swirl burner is presented. The degree of stratification and swirl are systematically varied to generate a matrix of experimental conditions, allowing their separate and combined effects to be investigated. Non-swirling flows are considered in the present paper, and the effects of swirl are considered in a companion paper (Part II). A mean equivalence ratio of φ=0.75 is used, with φ for the highest level of stratification spanning 0.375-1.125. The burner features a central bluff-body to aid flame stabilization, and the influence of the induced recirculation zone is also considered. The current work focuses on non-swirling flows where two-component particle image velocimetry (PIV) measurements are sufficient to characterize the main features of the flow field. Scalar data obtained from Rayleigh/Raman/CO laser induced fluorescence (CO-LIF) line measurements at 103μm resolution allow the behavior of key combustion species-CH 4, CO 2, CO, H 2, H 2O and O 2-to be probed within the instantaneous flame front. Simultaneous cross-planar OH-PLIF is used to determine the orientation of the instantaneous flame normal in the scalar measurement window, allowing gradients in temperature and progress variable to be angle corrected to their three dimensional values. The relationship between curvature and flame thickness is investigated using the OH-PLIF images, as well as the effect of stratification on curvature.The main findings are that the behavior of the key combustion species in temperature space is well captured on the mean by laminar flame calculations regardless of the level of stratification. H 2 and CO are significant exceptions, both appearing at elevated levels in the stratified flames. Values for surface density function and by extension thermal scalar dissipation rate are found to be substantially lower than laminar values, as the thickening of the flame due to turbulence dominates the effect of increased strain. These findings hold for both premixed and stratified flames. The current series of flames is proposed as an interesting if challenging set of test cases for existing and emerging turbulent flame models, and data are available on request. © 2012 The Combustion Institute.

Low-rank optimization for distance matrix completion

This paper addresses the problem of low-rank distance matrix completion. This problem amounts to recover the missing entries of a distance matrix when the dimension of the data embedding space is possibly unknown but small compared to the number of considered data points. The focus is on high-dimensional problems. We recast the considered problem into an optimization problem over the set of low-rank positive semidefinite matrices and propose two efficient algorithms for low-rank distance matrix completion. In addition, we propose a strategy to determine the dimension of the embedding space. The resulting algorithms scale to high-dimensional problems and monotonically converge to a global solution of the problem. Finally, numerical experiments illustrate the good performance of the proposed algorithms on benchmarks. © 2011 IEEE.

Differentiated adipose-derived stem cells act synergistically with RGD-modified surfaces to improve neurite outgrowth in a co-culture model.

Peripheral nerve damage is a problem encountered after trauma and during surgery and the development of synthetic polymer conduits may offer a promising alternative to autografts. In order to improve the performance of the polymer to be used for nerve conduits, poly-ε-caprolactone (PCL) films were chemically functionalized with RGD moieties, using a chemical reaction previously developed. In vitro cultures of dissociated dorsal root ganglion (DRG) neurons provide a valid model to study different factors affecting axonal growth. In this work, DRG neurons were cultured on RGD-functionalized PCL films. Adult adipose-derived stem cells differentiated to Schwann cells (dASCs) were initially cultured on the functionalized PCL films, resulting in improved attachment and proliferation. dASCs were also co-cultured with DRG neurons on treated and untreated PCL to assess stimulation by dASCs on neurite outgrowth. Neuron response was generally poor on untreated PCL films, but long neurites were observed in the presence of dASCs or RGD moieties. A combination of the two factors enhanced even further neurite outgrowth, acting synergistically. Finally, in order to better understand the extracellular matrix (ECM)-cell interaction, a β1 integrin blocking experiment was carried out. Neurite outgrowth was not affected by the specific antibody blocking, showing that β1 integrin function can be compensated by other molecules present on the cell membrane. Copyright © 2013 John Wiley & Sons, Ltd.

Determination of the rheological parameters of self-compacting concrete matrix using slump flow test

The classification of a concrete mixture as self-compacting (SCC) is performed by a series of empirical characterization tests that have been designed to assess not only the flowability of the mixture but also its segregation resistance and filling ability. The objective of the present work is to correlate the rheological parameters of SCC matrix, yield stress and plastic viscosity, to slump flow measurements. The focus of the slump flow test investigation was centered on the fully yielded flow regime and an empirical model relating the yield stress to material and flow parameters is proposed. Our experimental data revealed that the time for a spread of 500 mm which is used in engineering practice as reference for measurement parameters, is an arbitrary choice. Our findings indicate that the non-dimensional final spread is linearly related to the non-dimensional yield-stress. Finally, there are strong indications that the non-dimensional viscosity of the mixture is associated with the non-dimensional final spread as well as the stopping time of the slump flow; this experimental data set suggests an exponential decay of the final spread and stopping time with viscosity. © Appl. Rheol.

Dynamics of filopodium-like protrusion and endothelial cellular motility on onedimensional extracellular matrix fibrils

Endothelial filopodia play key roles in guiding the tubular sprouting during angiogenesis. However, their dynamic morphological characteristics, with the associated implications in cell motility, have been subjected to limited investigations. In this work, the interaction between endothelial cells and extracellular matrix fibrils was recapitulated in vitro, where a specific focus was paid to derive the key morphological parameters to define the dynamics of filopodium-like protrusion during cell motility. Based on one-dimensional gelatin fibrils patterned by near-field electrospinning (NFES), we study the response of endothelial cells (EA.hy926) under normal culture or ROCK inhibition. It is shown that the behaviour of temporal protrusion length versus cell motility can be divided into distinct modes. Persistent migration was found to be one of the modes which permitted cell displacement for over 300 μm at a speed of approximately 1 μm min-1. ROCK inhibition resulted in abnormally long protrusions and diminished the persistent migration, but dramatically increased the speeds of protrusion extension and retraction. Finally, we also report the breakage of protrusion during cell motility, and examine its phenotypic behaviours. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Fixed-rank matrix factorizations and Riemannian low-rank optimization

Motivated by the problem of learning a linear regression model whose parameter is a large fixed-rank non-symmetric matrix, we consider the optimization of a smooth cost function defined on the set of fixed-rank matrices. We adopt the geometric framework of optimization on Riemannian quotient manifolds. We study the underlying geometries of several well-known fixed-rank matrix factorizations and then exploit the Riemannian quotient geometry of the search space in the design of a class of gradient descent and trust-region algorithms. The proposed algorithms generalize our previous results on fixed-rank symmetric positive semidefinite matrices, apply to a broad range of applications, scale to high-dimensional problems, and confer a geometric basis to recent contributions on the learning of fixed-rank non-symmetric matrices. We make connections with existing algorithms in the context of low-rank matrix completion and discuss the usefulness of the proposed framework. Numerical experiments suggest that the proposed algorithms compete with state-of-the-art algorithms and that manifold optimization offers an effective and versatile framework for the design of machine learning algorithms that learn a fixed-rank matrix. © 2013 Springer-Verlag Berlin Heidelberg.