A clustered locally linear approach on face manifolds for pose estimation

Data points with small variations between them are assumed to lie close to each other on a smooth varying manifold in the feature space. Such data are hard to classify into separate classes . A sequence of face pose images with closely varying pose angles can be considered as such data. The pose angles when large enough create images that are largely differing from each other, and thus, the sequence of face images can be assumed to be on or near a nonlinear manifold. In this paper, we propose an unsupervised pose estimation method for face images based on clustered locally linear manifolds using discriminant analysis. We divide the data into multiple disjointed, locally linear and separable clusters. The problem of identifying which cluster to use is solved by dividing the entire process into two steps. The first step or projection using the entire smooth manifold identifies a rough region of interest. We use clustering techniques on entire data to form the pose-dependent classes which are then used to find the first set of discriminant functions. The second step or second projection uses trained cluster(s) from this neighbourhood to obtain a second set of discriminant functions. The idea behind such an approach is that the local neighbourhood would be linear and provide better between-class separation, and hence, the classification problem would now be simpler.     

Synergistic effect of carbon black and nanoclay fillers in styrene butadiene rubber matrix: Development of dual structure

Styrene butadiene rubber (SBR) based hybrid nanocomposites containing carbon black (CB) and organo-modified nanoclay (NC) was prepared. X-ray diffraction (XRD) and transmission electron microscopy (TEM) revealed the presence of intercalated, aggregated, and partially exfoliated structures. Incorporating 10 phr NC to the control SBR containing 20 phr CB resulted 153% increase in tensile strength, 157% increase in elongation at break and 144% stress improvement at 100% strain, which showed synergistic effect between the fillers. The dynamic modulus reinforcement of nanocomposites was examined by the Guth, Modified Guth, and Halpin–Tsai equations. For predicting CB filled nanocomposite modulus, the contribution of modified intercalated structure of clay and the ‘nano-unit’ (dual structure) comprising CB–NC should be considered.     

Viscous effect at an orthotropic micropolar boundary surface

Steady state responses at viscous fluid/ orthotropic micropolar solid interfaces to moving point loads have been studied. An eigenvalue approach using the Fourier transform has been employed to solve the problem. The displacement, microrotation and stress components for the orthotropic micropolar solids so obtained in the physical domain are computed numerically by applying numerical inversion technique. Viscosity and anisotropy effects on normal displacement, normal force stress and tangential couple stress have been shown graphically for a particular model. Some special cases of interest have been presented.     

A simple and efficient XFEM approach for 3-D cracks simulations

In this work, a simple and efficient XFEM approach has been presented to solve 3-D crack problems in linear elastic materials. In XFEM, displacement approximation is enriched by additional functions using the concept of partition of unity. In the proposed approach, a crack front is divided into a number of piecewise curve segments to avoid an iterative solution. A nearest point on the crack front from an arbitrary (Gauss) point is obtained for each crack segment. In crack front elements, the level set functions are approximated by higher order shape functions which assure the accurate modeling of the crack front. The values of stress intensity factors are obtained from XFEM solution by domain based interaction integral approach. Many benchmark crack problems are solved by the proposed XFEM approach. A convergence study has been conducted for few test problems. The results obtained by proposed XFEM approach are compared with the analytical/reference solutions.     

A simple and versatile overcurrent protection circuit for power MOSFETs

This paper proposes an overcurrent protection (OCP) circuit for power MOSFETs employed in low voltage power converters. The proposed configuration requires only discrete components with a gate driver IC and uses the voltage drop across the device for overcurrent detection. It can operate independently in cycle-by-cycle shutdown and multiple cycle shutdown modes. In coordination with a micro-controller based driver IC input signal generator and controller, the proposed OCP circuit can also operate in a single cycle latch-up and hiccup OCP modes. The performance of the proposed scheme is evaluated experimentally at both, hard and soft fault conditions. By experimentation, it is shown that the proposed circuit can operate in various protection modes and capable of protecting a MOSFET in both, hard and soft fault conditions.     

Neural networks and fuzzy logic-based spark advance control of SI engines

In SI engines, spark advance (SA) needs to be controlled to get Maximum Brake Torque (MBT) timing. Spark advance can be controlled either by open loop or by closed loop controller. The open loop controller requires extensive testing and calibration of engine, to develop look up tables. In closed loop controller, empirical rules relating variables deduced from cylinder pressure are used. One of such empirical rules is to fix location of peak pressure (LPP) at a desired value of the crank angle. In the present work, a combined neural network and fuzzy logic-based control scheme is designed for SA control to get MBT timing. The fuzzy logic controller is designed to maintain LPP of SI engine close to 16° ATDC. The controller works in conjunction with Recurrent Neural Network model for cylinder pressure identification. LPP is estimated from cylinder pressure curve reconstructed using neural network model and is used as feedback signal to fuzzy logic controller. The simulations have been carried out to test the performance of the combined neural network and fuzzy logic-based control strategy. The simulation results show that the proposed strategy can quite satisfactorily control LPP to its desired value.     

Characterization of Oxide Dispersed AlCoCrFe High Entropy Alloy Synthesized by Mechanical Alloying and Spark Plasma Sintering

The present study deals with phase evolution of oxide dispersed AlCoCrFe high entropy alloy during mechanical alloying and spark plasma sintering. Mechanical alloying of AlCoCrFe resulted in a single BCC phase. However, ordering of BCC phase with evolution of chromium carbide and sigma phase were observed after spark plasma sintering. High hardness of 1,050 ± 20 HV₁ and 1,070 ± 20 HV₁ was observed for AlCoCrFe high entropy alloy without and with oxide dispersion, respectively. Significant contribution from solid solution strengthening effect in high entropy alloys appears to have overwhelmed the effect of oxide dispersion on hardness.     

The Rising Costs of Floods: Examining the Impact of Planning and Development Decisions on Property Damage in Florida

The rising economic cost of floods in the United States cannot be explained solely by monetary inflation or growth in coastal populations. Damaging flood events are also influenced by the way society plans for and physically develops its communities, influencing where structures and impervious surfaces are concentrated and how hydrological systems are altered. We analyze 383 nonhurricane flood events in Florida counties between 1997 and 2001 to isolate how planning decisions and their effects on the built environment affect property damage caused by floods. Our results suggest that alteration of naturally occurring wetlands significantly increases the property damage caused by floods, all else equal. Also, nonstructural methods such as the Federal Emergency Management Agency's Community Rating System, while providing inexpensive means of reducing property damage directly, may also indirectly encourage more development in hazardous areas.     

Assessment of Nutritional and Antioxidant Potential of Selected Vitality Strengthening Himalayan Medicinal Plants

Three Himalayan medicinal plants (Habenaria intermedia, H. edgeworthii, and Roscoea procera), widely used in vitality strengthening Ayurvedic formulations in India, were assessed for nutritional phytochemical constituents, and antioxidant activity. These target species emerged as a good source of minerals and possessed important micro elements. Individually, H. intermedia contained a high content of total phenols, thiamins, tannins, and calcium; R. procera was rich in potassium and iron content; and H. edgeworthii emerged as a good source of sodium. While various antioxidant assays provided evidences on the antioxidant potential of target species, greater antioxidant potential of H. intermedia as compared to the other two species was revealing. This study, therefore, highlighted the possibilities of harnessing nutritional and antioxidant potential of these species.