Video coding mode decision as a classification problem

In this paper, we show that it is possible to reduce the complexity of Intra MB coding in H.264/AVC based on a novel chance constrained classifier. Using the pairs of simple mean-variances values, our technique is able to reduce the complexity of Intra MB coding process with a negligible loss in PSNR. We present an alternate approach to address the classification problem which is equivalent to machine learning. Implementation results show that the proposed method reduces encoding time to about 20% of the reference implementation with average loss of 0.05 dB in PSNR.

Design and Optimization of Broadband Micromachined Antenna

Performance improvement of a micromachined patch antenna operating at 30 GHz with a capacitively coupled feed arrangement is presented here. Such antennas are useful for monolithic integration with active components. Specifically, micromachining can be employed to achieve a low dielectric constant region under the patch which causes (i) the suppression of surface waves and hence the increase in radiation efficiency and (ii) increase in the bandwidth. The performance of such a patch antenna can be significantly improved by selecting a coupled feed arrangement. We have optimized the dimensions and location of the capacitive feeding strip to get the maximum improvement in bandwidth. Since this is a totally planar arrangement, and does not involve any stacked structures, this antenna is easy to fabricate using standard microfabrication techniques. The antenna element thus designed has a -10 dB bandwidth of 1600 MHz

Ag@Pd core-shell nanoparticles

Colloids of silver and palladium nanoparticles have been prepared by the Solvated Metal Atom Dispersion method. The as-prepared Ag colloid consisting of polydisperse nanoparticles is transformed into a monodisperse colloid by the digestive ripening process which involves refluxing the as-prepared colloid in the presence of a surfactant. In addition to the monodisperse nanoparticles, a small amount of an Ag-thiolate complex is also formed. Refluxing a mixture of the as-prepared Ag and Pd colloids results in Ag@Pd core-shell nanoparticles. The core-shell structure has been established using a combination of techniques such as UV-visible spectroscopy, high resolution electron microscopy, energy filtered electron microscopy, energy dispersive X-ray analysis, high angle annular dark field imaging and powder X-ray diffraction.

Analysis of the consolidation of preloaded clays

Precompression, wherein the probable settlements are achieved at an accelerated pace through preloading, well before the construction is take up, has been widely used in areas of ground improvement with respect to soft clays. By applying a temporary surcharge load in excess or less than the permanent load, the soil achieves higher initial effective stress and when the final load is applied, the soil experiences, lower load increment ratio or negative load increment ratio. In this paper, based on the laboratory experiments conducted on cochin marine clays and Mangalore marine clays, attempts have been made to analyse the volume change behaviour of preloaded clays. It has been brought out that for a preloaded clay, the final load increment ratio has an important role in its behaviour. Effective preloading not only reduces the final settlement due to primary, the secondary consolidation settlement also gets reduced.

A Five-Level Inverter Topology with Single-DC Supply by Cascading a Flying Capacitor Inverter and an H-Bridge

In this paper, a new three-phase, five-level inverter topology with a single-dc source is presented. The proposed topology is obtained by cascading a three-level flying capacitor inverter with a flying H-bridge power cell in each phase. This topology has redundant switching states for generating different pole voltages. By selecting appropriate switching states, the capacitor voltages can be balanced instantaneously (as compared to the fundamental) in any direction of the current, irrespective of the load power factor. Another important feature of this topology is that if any H-bridge fails, it can be bypassed and the configuration can still operate as a three-level inverter at its full power rating. This feature improves the reliability of the circuit. A 3-kW induction motor is run with the proposed topology for the full modulation range. The effectiveness of the capacitor balancing algorithm is tested for the full range of speed and during the sudden acceleration of the motor.

Relaxor Ferroelectric Behavior and Structural Aspects of SrNaBi2Nb3O12 Ceramics

The SrNaBi2Nb3O12 (SNBN) powder was prepared via the conventional solid-state reaction method. X-ray structural studies confirmed the phase to be a three-layered member of the Aurivillius family of oxides. The SNBN ceramics exhibited the typical characteristics of relaxor ferroelectrics, associated with broad and dispersive dielectric maxima. The variation of temperature of dielectric maxima (T-m) with frequency obeyed the Vogel-Fulcher relationship. Relaxor behavior was believed to be arising from the cationic disorder at A-site. Pinched ferroelectric hysteresis loops were observed well above T-m.

Averting biodiversity collapse in tropical forest protected areas

The rapid disruption of tropical forests probably imperils global biodiversity more than any other contemporary phenomenon(1-3). With deforestation advancing quickly, protected areas are increasingly becoming final refuges for threatened species and natural ecosystem processes. However, many protected areas in the tropics are themselves vulnerable to human encroachment and other environmental stresses(4-9). As pressures mount, it is vital to know whether existing reserves can sustain their biodiversity. A critical constraint in addressing this question has been that data describing a broad array of biodiversity groups have been unavailable for a sufficiently large and representative sample of reserves. Here we present a uniquely comprehensive data set on changes over the past 20 to 30 years in 31 functional groups of species and 21 potential drivers of environmental change, for 60 protected areas stratified across the world's major tropical regions. Our analysis reveals great variation in reserve `health': about half of all reserves have been effective or performed passably, but the rest are experiencing an erosion of biodiversity that is often alarmingly widespread taxonomically and functionally. Habitat disruption, hunting and forest-product exploitation were the strongest predictors of declining reserve health. Crucially, environmental changes immediately outside reserves seemed nearly as important as those inside in determining their ecological fate, with changes inside reserves strongly mirroring those occurring around them. These findings suggest that tropical protected areas are often intimately linked ecologically to their surrounding habitats, and that a failure to stem broad-scale loss and degradation of such habitats could sharply increase the likelihood of serious biodiversity declines.

Nanomechanical and optical properties of highly a-axis oriented AlN films

This paper reports optical and nanomechanical properties of predominantly a-axis oriented AlN thin films. These films were deposited by reactive DC magnetron sputtering technique at an optimal target to substrate distance of 180 mm. X-ray rocking curve (FWHM = 52 arcsec) studies confirmed the preferred orientation. Spectroscopic ellipsometry revealed a refractive index of 1.93 at a wavelength of 546 nm. The hardness and elastic modulus of these films were 17 and 190 GPa, respectively, which are much higher than those reported earlier can be useful for piezoelectric films in bulk acoustic wave resonators. (C) 2012 American Institute of Physics. http://dx.doi.org/10.1063/1.4772204]

Automatic compilation of MATLAB programs for synergistic execution on heterogeneous processors

MATLAB is an array language, initially popular for rapid prototyping, but is now being increasingly used to develop production code for numerical and scientific applications. Typical MATLAB programs have abundant data parallelism. These programs also have control flow dominated scalar regions that have an impact on the program's execution time. Today's computer systems have tremendous computing power in the form of traditional CPU cores and throughput oriented accelerators such as graphics processing units(GPUs). Thus, an approach that maps the control flow dominated regions to the CPU and the data parallel regions to the GPU can significantly improve program performance. In this paper, we present the design and implementation of MEGHA, a compiler that automatically compiles MATLAB programs to enable synergistic execution on heterogeneous processors. Our solution is fully automated and does not require programmer input for identifying data parallel regions. We propose a set of compiler optimizations tailored for MATLAB. Our compiler identifies data parallel regions of the program and composes them into kernels. The problem of combining statements into kernels is formulated as a constrained graph clustering problem. Heuristics are presented to map identified kernels to either the CPU or GPU so that kernel execution on the CPU and the GPU happens synergistically and the amount of data transfer needed is minimized. In order to ensure required data movement for dependencies across basic blocks, we propose a data flow analysis and edge splitting strategy. Thus our compiler automatically handles composition of kernels, mapping of kernels to CPU and GPU, scheduling and insertion of required data transfer. The proposed compiler was implemented and experimental evaluation using a set of MATLAB benchmarks shows that our approach achieves a geometric mean speedup of 19.8X for data parallel benchmarks over native execution of MATLAB.

Fully complex-valued ELM classifiers for human action recognition

In this paper, we present a fast learning neural network classifier for human action recognition. The proposed classifier is a fully complex-valued neural network with a single hidden layer. The neurons in the hidden layer employ the fully complex-valued hyperbolic secant as an activation function. The parameters of the hidden layer are chosen randomly and the output weights are estimated analytically as a minimum norm least square solution to a set of linear equations. The fast leaning fully complex-valued neural classifier is used for recognizing human actions accurately. Optical flow-based features extracted from the video sequences are utilized to recognize 10 different human actions. The feature vectors are computationally simple first order statistics of the optical flow vectors, obtained from coarse to fine rectangular patches centered around the object. The results indicate the superior performance of the complex-valued neural classifier for action recognition. The superior performance of the complex neural network for action recognition stems from the fact that motion, by nature, consists of two components, one along each of the axes.