An adaptation framework for head-pose classification in dynamic multi-view scenarios

Multi-view head-pose estimation in low-resolution, dynamic scenes is difficult due to blurred facial appearance and perspective changes as targets move around freely in the environment. Under these conditions, acquiring sufficient training examples to learn the dynamic relationship between position, face appearance and head-pose can be very expensive. Instead, a transfer learning approach is proposed in this work. Upon learning a weighted-distance function from many examples where the target position is fixed, we adapt these weights to the scenario where target positions are varying. The adaptation framework incorporates reliability of the different face regions for pose estimation under positional variation, by transforming the target appearance to a canonical appearance corresponding to a reference scene location. Experimental results confirm effectiveness of the proposed approach, which outperforms state-of-the-art by 9.5% under relevant conditions. To aid further research on this topic, we also make DPOSE- a dynamic, multi-view head-pose dataset with ground-truth publicly available with this paper.

Modeling the dynamic response of wrap-faced reinforced soil retaining walls

This paper describes the development of a numerical model for simulating the shaking table tests on wrap-faced reinforced soil retaining walls. Some of the physical model tests carried out on reinforced soil retaining walls subjected to dynamic excitation through uniaxial shaking tests are briefly discussed. Models of retaining walls are constructed in a perspex box with geotextile reinforcement using the wraparound technique with dry sand backfill and instrumented with displacement sensors, accelerometers, and soil pressure sensors. Results showed that the displacements decrease with the increase in number of reinforcement layers, whereas acceleration amplifications were not affected significantly. Numerical modeling of these shaking table tests is carried out using the Fast Lagrangian Analysis of Continua program. The numerical model is validated by comparing the results with experiments on physical models. Responses of wrap-faced walls with varying numbers of reinforcement layers are compared. Sensitivity analysis performed on the numerical models showed that the friction and dilation angle of backfill material and stiffness properties of the geotextile-soil interface are the most affecting parameters for the model response.

Stability analysis of aperiodic messages scheduled in the dynamic segment of flex ray protocol

In a cyber physical system like vehicles number of signals to be communicated in a network system has an increasing trend. More and more mechanical and hydraulic parts are replaced by electronic control units and infotainment and multimedia applications has increased in vehicles. Safety critical hard real time messages and aperiodic messages communicated between electronic control units have been increased in recent times. Flexray is a high bandwidth protocol consisting of static segment for supporting hard real time messages and a dynamic segment for transmitting soft and non real time messages. In this paper, a method to obtain the stability region for the random arrival of messages in each electronic control units which is scheduled in the dynamic segment of Flexray protocol is presented. Number of mini slots available in the dynamic segment of Flexray restricts the arrival rate of tasks to the micro controllers or the number of micro controllers connected to the Flexray bus. Stability region of mathematical model of the system is compared with the Flexray protocol simulation results.

Intensity profile of light scattered from a rough surface

We present in this paper, approximate analytical expressions for the intensity of light scattered by a rough surface, whose elevation. xi(x,y) in the z-direction is a zero mean stationary Gaussian random variable. With (x,y) and (x',y') being two points on the surface, we have h. = 0 with a correlation, = sigma(2)g(r), where r = (x - x')(2) + ( y - y')(2)](1/2) is the distance between these two points. We consider g(r) = exp-r/l)(beta)] with 1 <= beta <= 2, showing that g(0) = 1 and g(r) -> 0 for r >> l. The intensity expression is sought to be expressed as f(v(xy)) = {1 + (c/2y)v(x)(2) + v(y)(2)]}(-y), where v(x) and v(y) are the wave vectors of scattering, as defined by the Beckmann notation. In the paper, we present expressions for c and y, in terms of sigma, l, and beta. The closed form expressions are verified to be true, for the cases beta = 1 and beta = 2, for which exact expressions are known. For other cases, i.e., beta not equal 1, 2 we present approximate expressions for the scattered intensity, in the range, v(xy) = (v(x)(2) + v(y)(2))(1/2) <= 6.0 and show that the relation for f(v(xy)), given above, expresses the scattered intensity quite accurately, thus providing a simple computational methods in situations of practical importance.

Dynamic state estimation for identifying earthquake support motions in instrumented structures

The problem of identification of multi-component and (or) spatially varying earthquake support motions based on measured responses in instrumented structures is considered. The governing equations of motion are cast in the state space form and a time domain solution to the input identification problem is developed based on the Kalman and particle filtering methods. The method allows for noise in measured responses, imperfections in mathematical model for the structure, and possible nonlinear behavior of the structure. The unknown support motions are treated as hypothetical additional system states and a prior model for these motions are taken to be given in terms of white noise processes. For linear systems, the solution is developed within the Kalman filtering framework while, for nonlinear systems, the Monte Carlo simulation based particle filtering tools are employed. In the latter case, the question of controlling sampling variance based on the idea of Rao-Blackwellization is also explored. Illustrative examples include identification of multi-component and spatially varying support motions in linear/nonlinear structures.

Dynamic multi-relational Chinese restaurant process for analyzing influences on users in social media

We study the problem of analyzing influence of various factors affecting individual messages posted in social media. The problem is challenging because of various types of influences propagating through the social media network that act simultaneously on any user. Additionally, the topic composition of the influencing factors and the susceptibility of users to these influences evolve over time. This problem has not been studied before, and off-the-shelf models are unsuitable for this purpose. To capture the complex interplay of these various factors, we propose a new non-parametric model called the Dynamic Multi-Relational Chinese Restaurant Process. This accounts for the user network for data generation and also allows the parameters to evolve over time. Designing inference algorithms for this model suited for large scale social-media data is another challenge. To this end, we propose a scalable and multi-threaded inference algorithm based on online Gibbs Sampling. Extensive evaluations on large-scale Twitter and Face book data show that the extracted topics when applied to authorship and commenting prediction outperform state-of-the-art baselines. More importantly, our model produces valuable insights on topic trends and user personality trends beyond the capability of existing approaches.

A Multicast Authentication Protocol (MAP) for Dynamic Multicast Groups in Wireless Networks

In this paper, we have proposed a centralized multicast authentication protocol (MAP) for dynamic multicast groups in wireless networks. In our protocol, a multicast group is defined only at the time of the multicasting. The authentication server (AS) in the network generates a session key and authenticates it to each of the members of a multicast group using the computationally inexpensive least common multiple (LCM) method. In addition, a pseudo random function (PRF) is used to bind the secret keys of the network members with their identities. By doing this, the AS is relieved from storing per member secrets in its memory, making the scheme completely storage scalable. The protocol minimizes the load on the network members by shifting the computational tasks towards the AS node as far as possible. The protocol possesses a membership revocation mechanism and is protected against replay attack and brute force attack. Analytical and simulation results confirm the effectiveness of the proposed protocol.

Simultaneous attitude control and trajectory tracking of a micro quadrotor: a SNAC aided nonlinear dynamic inversion approach

This paper presents an advanced single network adaptive critic (SNAC) aided nonlinear dynamic inversion (NDI) approach for simultaneous attitude control and trajectory tracking of a micro-quadrotor. Control of micro-quadrotors is a challenging problem due to its small size, strong coupling in pitch-yaw-roll and aerodynamic effects that often need to be ignored in the control design process to avoid mathematical complexities. In the proposed SNAC aided NDI approach, the gains of the dynamic inversion design are selected in such a way that the resulting controller behaves closely to a pre-synthesized SNAC controller for the output regulation problem. However, since SNAC is based on optimal control theory, it makes the dynamic inversion controller to operate near optimal and enhances its robustness property as well. More important, it retains two major benefits of dynamic inversion: (i) closed form expression of the controller and (ii) easy scalability to command tracking application even without any apriori knowledge of the reference command. Effectiveness of the proposed controller is demonstrated from six degree-of-freedom simulation studies of a micro-quadrotor. It has also been observed that the proposed SNAC aided NDI approach is more robust to modeling inaccuracies, as compared to the NDI controller designed independently from time domain specifications.

A scaled unscented transformation based directed Gaussian sum filter for nonlinear dynamic system identification

Impoverishment of particles, i.e. the discretely simulated sample paths of the process dynamics, poses a major obstacle in employing the particle filters for large dimensional nonlinear system identification. A known route of alleviating this impoverishment, i.e. of using an exponentially increasing ensemble size vis-a-vis the system dimension, remains computationally infeasible in most cases of practical importance. In this work, we explore the possibility of unscented transformation on Gaussian random variables, as incorporated within a scaled Gaussian sum stochastic filter, as a means of applying the nonlinear stochastic filtering theory to higher dimensional structural system identification problems. As an additional strategy to reconcile the evolving process dynamics with the observation history, the proposed filtering scheme also modifies the process model via the incorporation of gain-weighted innovation terms. The reported numerical work on the identification of structural dynamic models of dimension up to 100 is indicative of the potential of the proposed filter in realizing the stated aim of successfully treating relatively larger dimensional filtering problems. (C) 2013 Elsevier Ltd. All rights reserved.

Molecular dynamic simulations of elastomer structure and its influence on anisotropic stress under time-varying strain

We investigate the evolution of polymer structure and its influence on uniaxial anisotropic stress under time-varying uniaxial strain, and the role of external control variables such as temperature, strain rate, chain length, and density, using molecular dynamics simulation. At temperatures higher than glass transition, stress anisotropy in the system is reduced even though the bond stretch is greater at higher temperatures. There is a significant increase in the stress level with increasing density. At higher densities, the uncoiling of the chains is suppressed and the major contribution to the deformation is by internal deformation of the chains. At faster rates of loading stress anisotropy increases. The deformation mechanism is mostly due to bond stretch and bond bending rather than overall shape and size. Stress levels increase with longer chain length. There is a critical value of the functionality of the cross-linkers beyond which the uniaxial stress developed increases caused primarily by bond stretching due to increased constraint on the motion of the monomers. Stacking of the chains in the system also plays a dominant role in the behaviour in terms of excluded volume interactions. Low density, high temperature, low values of functionality of cross-linkers, and short chain length facilitate chain uncoiling and chain slipping in cross-linked polymers.

Concentration Fluctuations and Segmental Dynamics in Weakly Dynamic Asymmetric Blends in the Presence of Surface-Functionalized Multiwall Carbon Nanotubes

Surface-functionalized multiwall carbon nanotubes (MWCNTs) are incorporated in poly(methyl methacrylate)/styrene acrylonitrile (PMMA/SAN) blends and the pretransitional regime is monitored in situ by melt rheology and dielectric spectroscopy. As the blends exhibit weak dynamic asymmetry, the obvious transitions in the melt rheology due to thermal concentration fluctuations are weak. This is further supported by the weak temperature dependence of the correlation length ( approximate to 10-12 angstrom) in the vicinity of demixing. Hence, various rheological techniques in both the temperature and frequency domains are adopted to evaluate the demixing temperature. The spinodal decomposition temperature is manifested in an increase in the miscibility gap in the presence of MWCNTs. Furthermore, MWCNTs lead to a significant slowdown of the segmental dynamics in the blends. Thermally induced phase separation in the PMMA/SAN blends lead to selective localization of MWCNTs in the PMMA phase. This further manifests itself in a significant increase in the melt conductivity.

Study of dynamic behaviour of recession curves

Since Brutsaert and Neiber (1977), recession curves are widely used to analyse subsurface systems of river basins by expressing -dQ/dt as a function of Q, which typically take a power law form: -dQ/dt=kQ, where Q is the discharge at a basin outlet at time t. Traditionally recession flows are modelled by single reservoir models that assume a unique relationship between -dQ/dt and Q for a basin. However, recent observations indicate that -dQ/dt-Q relationship of a basin varies greatly across recession events, indicating the limitation of such models. In this study, the dynamic relationship between -dQ/dt and Q of a basin is investigated through the geomorphological recession flow model which models recession flows by considering the temporal evolution of its active drainage network (the part of the stream network of the basin draining water at time t). Two primary factors responsible for the dynamic relationship are identified: (i) degree of aquifer recharge (ii) spatial variation of rainfall. Degree of aquifer recharge, which is likely to be controlled by (effective) rainfall patterns, influences the power law coefficient, k. It is found that k has correlation with past average streamflow, which confirms the notion that dynamic -dQ/dt-Q relationship is caused by the degree of aquifer recharge. Spatial variation of rainfall is found to have control on both the exponent, , and the power law coefficient, k. It is noticed that that even with same and k, recession curves can be different, possibly due to their different (recession) peak values. This may also happen due to spatial variation of rainfall. Copyright (c) 2012 John Wiley & Sons, Ltd.

Iterated gain-based stochastic filters for dynamic system identification

We propose a novel form of nonlinear stochastic filtering based on an iterative evaluation of a Kalman-like gain matrix computed within a Monte Carlo scheme as suggested by the form of the parent equation of nonlinear filtering (Kushner-Stratonovich equation) and retains the simplicity of implementation of an ensemble Kalman filter (EnKF). The numerical results, presently obtained via EnKF-like simulations with or without a reduced-rank unscented transformation, clearly indicate remarkably superior filter convergence and accuracy vis-a-vis most available filtering schemes and eminent applicability of the methods to higher dimensional dynamic system identification problems of engineering interest. (C) 2013 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

Kinematic and Mechanical Profile of the Self-Actuation of Thermosalient Crystal Twins of 1,2,4,5-Tetrabromobenzene: A Molecular Crystalline Analogue of a Bimetallic Strip

A paradigm shift from hard to flexible, organic-based optoelectronics requires fast and reversible mechanical response from actuating materials that are used for conversion of heat or light into mechanical motion. As the limits in the response times of polymer-based actuating materials are reached, which are inherent to the less-than-optimal coupling between the light/heat and mechanical energy in them, 1 a conceptually new approach to mechanical actuation is required to leapfrog the performance of organic actuators. Herein, we explore single crystals of 1,2,4,5-tetrabromobenzene (TBB) as actuating elements and establish relations between their kinematic profile and mechanical properties. Centimeter-size acicular crystals of TBB are the only naturally twinned crystals out of about a dozen known materials that exhibit the thermosalient effect-an extremely rare and visually impressive crystal locomotion. When taken over a phase transition, crystals of this material store mechanical strain and are rapidly self-actuated to sudden jumps to release the internal strain, leaping up to several centimeters. To establish the structural basis for this colossal crystal motility, we investigated the mechanical profile of the crystals from macroscale, in response to externally induced deformation under microscope, to nanoscale, by using nanoindentation. Kinematic analysis based on high-speed recordings of over 200 twinned TBB crystals exposed to directional or nondirectional heating unraveled that the crystal locomotion is a kinematically complex phenomenon that includes at least six kinematic effects. The nanoscale tests confirm the highly elastic nature, with an elastic deformation recovery (60%) that is far superior to those of molecular crystals reported earlier. This property appears to be critical for accumulation of stress required for crystal jumping. Twinned crystals of TBB exposed to moderate directional heating behave as all-organic analogue of a bimetallic `strip, where the lattice misfit between the two crystal components drives reveriible deformation of the crystal.

Temperature dependent magnetic ordering and electrical transport behavior of nano zinc ferrite from 20 to 800 K

The nano ZnFe2O4 compound was prepared by eco-friendly hydrothermal method. The characterization of the sample for its structure, morphology and composition were done by powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), dynamic light scattering, Fourier transform infrared spectroscopy, zeta surface profiler and UV-Visible spectroscopy studies. The PXRD measurement reveals that the compound shows spinel cubic phase belong Fd (3) over barm (227) space group. Morphology of the compound from SEM and surface profile shows nearly spherical agglomerated particles with well defined grains and grain boundaries. The material shows the semiconducting behavior with E-g of 2.3 eV at room temperature (RT). The variation in the magnetic ordering was observed for wide range of temperature. The compound behaves like a soft magnetic material with ferrimagnetic at various temperatures except at RT. Both magnetic and EPR studies supports the superparamagnetic behavior of the the sample. The DC conductivity, dielectric and AC conductivity behavior of the 1000 degrees C pellets sintered for 2 h shows good frequency dependent transport properties. The present study facilitate in selecting the suitable materials for the nanoelectronics and spintronic applications. (C) 2013 Elsevier B.V. All rights reserved.