Extended Energy Vector Prediction of Ambisonically Reproduced Image Direction at Off-Centre Listening Positions

This paper presents an extension to the energy vector, well known in the Ambisonics literature, to improve its predictions of localisation at off-centre listening positions. In determining the source direction, a perceptual weight is assigned to each loudspeaker gain, taking into account the relative arrival times, levels, and directions of the loudspeaker signals. The proposed model is evaluated alongside the original energy vector and two binaural models through comparison with the results of recent perceptual studies. The extended version was found to provide results that were at least 50% more accurate than the second best predictor for two experiments involving off-centre listeners with first- and third-order Ambisonics systems.

Magnetic and plagioclase linear fabric discrepancy in dykes: a new way to define the flow vector using magnetic foliation

In basaltic dykes the magnetic lineation K1 (maximum magnetic susceptibility axis) is generally taken to indicate the flow direction during solidification of the magma. This assumption was tested in Tertiary basaltic dykes from Greenland displaying independent evidence of subhorizontal flow. The digital processing of microphotographs from thin sections cut in (K1, K2) planes yields the preferred linear orientation of plagioclase, which apparently marks the magma flow lineation. In up to 60% of cases, the angular separation between K1 and the assumed flow direction is greater than 45degrees. This suggests that the uncorroborated use of magnetic lineations in dykes is risky. A simple geometrical method is proposed to infer the flow vector from AMS in dykes based solely on magnetic foliations.

Wind-direction effects on urban-type flows

Practically all extant work on flows over obstacle arrays, whether laboratory experiments or numerical modelling, is for cases where the oncoming wind is normal to salient faces of the obstacles. In the field, however, this is rarely the case. Here, simulations of flows at various directions over arrays of cubes representing typical urban canopy regions are presented and discussed. The computations are of both direct numerical simulation and large-eddy simulation type. Attention is concentrated on the differences in the mean flow within the canopy region arising from the different wind directions and the consequent effects on global properties such as the total surface drag, which can change very significantly—by up to a factor of three in some circumstances. It is shown that for a given Reynolds number the typical viscous forces are generally a rather larger fraction of the pressure forces (principally the drag) for non-normal than for normal wind directions and that, dependent on the surface morphology, the average flow direction deep within the canopy can be largely independent of the oncoming wind direction. Even for regular arrays of regular obstacles, a wind direction not normal to the obstacle faces can in general generate a lateral lift force (in the direction normal to the oncoming flow). The results demonstrate this and it is shown how computations in a finite domain with the oncoming flow generated by an appropriate forcing term (e.g. a pressure gradient) then lead inevitably to an oncoming wind direction aloft that is not aligned with the forcing term vector.

The role of the harmonic vector average in motion integration

The local speeds of object contours vary systematically with the cosine of the angle between the normal component of the local velocity and the global object motion direction. An array of Gabor elements whose speed changes with local spatial orientation in accordance with this pattern can appear to move as a single surface. The apparent direction of motion of plaids and Gabor arrays has variously been proposed to result from feature tracking, vector addition and vector averaging in addition to the geometrically correct global velocity as indicated by the intersection of constraints (IOC) solution. Here a new combination rule, the harmonic vector average (HVA), is introduced, as well as a new algorithm for computing the IOC solution. The vector sum can be discounted as an integration strategy as it increases with the number of elements. The vector average over local vectors that vary in direction always provides an underestimate of the true global speed. The HVA, however, provides the correct global speed and direction for an unbiased sample of local velocities with respect to the global motion direction, as is the case for a simple closed contour. The HVA over biased samples provides an aggregate velocity estimate that can still be combined through an IOC computation to give an accurate estimate of the global velocity, which is not true of the vector average. Psychophysical results for type II Gabor arrays show perceived direction and speed falls close to the IOC direction for Gabor arrays having a wide range of orientations but the IOC prediction fails as the mean orientation shifts away from the global motion direction and the orientation range narrows. In this case perceived velocity generally defaults to the HVA.

Generalized duality between local vector theories in D=2+1

The existence of an interpolating master action does not guarantee the same spectrum for the interpolated dual theories. In the specific case of a generalized self-dual (GSD) model defined as the addition of the Maxwell term to the self-dual model in D = 2 + 1, previous master actions have furnished a dual gauge theory which is either nonlocal or contains a ghost mode. Here we show that by reducing the Maxwell term to first order by means of an auxiliary field we are able to define a master action which interpolates between the GSD model and a couple of non-interacting Maxwell-Chern-Simons theories of opposite helicities. The presence of an auxiliary field explains the doubling of fields in the dual gauge theory. A generalized duality transformation is defined and both models can be interpreted as self-dual models. Furthermore, it is shown how to obtain the gauge invariant correlators of the non-interacting MCS theories from the correlators of the self-dual field in the GSD model and vice-versa. The derivation of the non-interacting MCS theories from the GSD model, as presented here, works in the opposite direction of the soldering approach.

Weight vector estimation of circular arrays of antennas using Artificial Neural Networks

This paper presents a model for the control of the radiation pattern of a circular array of antennas, shaping it to address the radiation beam in the direction of the user, in order to reduce the transmitted power and to attenuate interference. The control of the array is based on Artificial Neural Networks (ANN) of the type RBF (Radial Basis Functions), trained from samples generated by the Wiener equation. The obtained results suggest that the objective was reached.

Development of a support vector machine-based navigation system for driving a mobile robot through paths in plantations

The use of mobile robots turns out to be interesting in activities where the action of human specialist is difficult or dangerous. Mobile robots are often used for the exploration in areas of difficult access, such as rescue operations and space missions, to avoid human experts exposition to risky situations. Mobile robots are also used in agriculture for planting tasks as well as for keeping the application of pesticides within minimal amounts to mitigate environmental pollution. In this paper we present the development of a system to control the navigation of an autonomous mobile robot through tracks in plantations. Track images are used to control robot direction by preprocessing them to extract image features. Such features are then submitted to a support vector machine in order to find out the most appropriate route. The overall goal of the project to which this work is connected is to develop a real time robot control system to be embedded into a hardware platform. In this paper we report the software implementation of a support vector machine, which so far presented around 93% accuracy in predicting the appropriate route. © 2012 IEEE.

Comparing support vector machines and artificial neural networks in the recognition of steering angle for driving of mobile robots through paths in plantations

The use of mobile robots turns out to be interesting in activities where the action of human specialist is difficult or dangerous. Mobile robots are often used for the exploration in areas of difficult access, such as rescue operations and space missions, to avoid human experts exposition to risky situations. Mobile robots are also used in agriculture for planting tasks as well as for keeping the application of pesticides within minimal amounts to mitigate environmental pollution. In this paper we present the development of a system to control the navigation of an autonomous mobile robot through tracks in plantations. Track images are used to control robot direction by pre-processing them to extract image features. Such features are then submitted to a support vector machine and an artificial neural network in order to find out the most appropriate route. A comparison of the two approaches was performed to ascertain the one presenting the best outcome. The overall goal of the project to which this work is connected is to develop a real time robot control system to be embedded into a hardware platform. In this paper we report the software implementation of a support vector machine and of an artificial neural network, which so far presented respectively around 93% and 90% accuracy in predicting the appropriate route. (C) 2013 The Authors. Published by Elsevier B.V. Selection and peer review under responsibility of the organizers of the 2013 International Conference on Computational Science

Exclusive vector meson production in pp collisions at the COMPASS experiment

Produktionsmechanismen für Teilchenproduktion im mittleren Energiebereich wurden in Proton-Proton Kollisionen innerhalb der COMPASS-Kollaboration mit Hilfe des COMPASS-Spektrometers am SPS Beschleuniger am CERN untersucht. Die verschiedenen Produktionsmechanismen werden mittels Produktion der Vektormesonen omega und phi studiert und können die diffraktive Anregung des Strahlteilchens mit anschliessendem Zerfall der Resonanz, zentrale Produktion und den damit verwandten “Shake-off” Mechanismus enthalten. Die für diese Arbeit verwendeten Daten wurden in den Jahren 2008 und 2009 mit 190 GeV/c-Protonen aufgenommen, die auf ein Flüssigwasserstofftarget trafen. Das Target war von einem Rückstoßprotonendetektor umgeben, der ein integraler Bestandteil des neuentwickelten Hadrontriggersystems ist. Für dieses System wurden außerdem einige neue Detektoren gebaut. Die Leistungsfähigkeit des Rückstoßprotonendetektors und des Triggersystems wird untersucht und Effizienzen extrahiert. Außerdem wird sowohl eine Methode zur Rekonstruktion von Rückstoßprotonen als auch eine Methode zur Kalibration des Rückstoßprotonendetektors entwickelt und beschrieben. Die Produktion von omega-Mesonen wurde in der Reaktion pp -> p omega p, omega -> pi+pi-pi0 und die Produktion von phi-Mesonen in der Reaktion pp -> p phi p, phi -> K+K- bei einem Impulsübertrag zwischen 0.1 (GeV/c)^2 und 1 (GeV/c)^2 gemessen. Das Produktionsverhältnis s(pp -> p phi p)/s(pp -> p omega p) wird als Funktion des longitudinalen Impulsanteils xF bestimmt und mit der Vorhersage durch die Zweigregel verglichen. Es ergibt sich eine signifikante Verletzung der Zweigregel, die abhängig von xF ist. Die Verletzung wird in Verbindung zu resonanten Strukturen im pomega-Massenspektrum diskutiert. Die xF-Abhängigkeit verschwindet, wenn man die Region niedriger pomega- und pphi-Masse entfernt, die solche resonanten Strukturen aufweist. Zusätzlich wird die Spinausrichtung bzw. das Spindichtematrixelement rho00 für omega- und phi-Mesonen untersucht. Die Spinausrichtung wird im Helizitätssystemrnanalysiert, welches für eine Abgrenzung von resonanten, diffraktiven Anregungen geeignet ist. Außerdem wird die Spinausrichtung in einem Referenzsystem mit Bezug auf die Richtung des Impulsübertrags untersucht, mit dessen Hilfe zentrale Prozesse wie zentrale Produktion oder “shake-off” abgegrenzt werden. Auch hier wird eine Abhängigkeit von xF und der invarianten Masse des pomega-Systems beobachtet. Diese Abhängigkeit kann wieder auf die resonanten Strukturen in der Produktion von omega-Mesonen zurückgeführt werden. Die Ergebnisse werden abschließend im Hinblick auf die verschiedenen Produktionsmechanismen diskutiert.

Modelling wind direction from satellite scatterometer data

Most of the common techniques for estimating conditional probability densities are inappropriate for applications involving periodic variables. In this paper we apply two novel techniques to the problem of extracting the distribution of wind vector directions from radar scatterometer data gathered by a remote-sensing satellite.