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.

Common-mode voltage eliminated three-level inverter using a three-level flying-capacitor inverter and cascaded H-bridge

This paper proposes a new 3 level common mode voltage eliminated inverter using an inverter structure formed by cascading a H-Bridge with a three-level flying capacitor inverter. The three phase space vector polygon formed by this configuration and the polygon formed by the common-mode eliminated states have been discussed. The entire system is simulated in Simulink and the results are experimentally verified. This system has an advantage that if one of devices in the H-Bridge fails, the system can still be operated as a normal 3 level inverter mode at full power. This inverter has many advantages like use of single DC-supply, making it possible for a back to back grid-tied converter application, improved reliability etc.

Maximum likelihood algorithms for joint estimation of synchronisation impairments and channel in multiple input multiple output-orthogonal frequency division multiplexing system

Maximum likelihood (ML) algorithms, for the joint estimation of synchronisation impairments and channel in multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) system, are investigated in this work. A system model that takes into account the effects of carrier frequency offset, sampling frequency offset, symbol timing error and channel impulse response is formulated. Cramer-Rao lower bounds for the estimation of continuous parameters are derived, which show the coupling effect among different impairments and the significance of the joint estimation. The authors propose an ML algorithm for the estimation of synchronisation impairments and channel together, using the grid search method. To reduce the complexity of the joint grid search in the ML algorithm, a modified ML (MML) algorithm with multiple one-dimensional searches is also proposed. Further, a stage-wise ML (SML) algorithm using existing algorithms, which estimate less number of parameters, is also proposed. Performance of the estimation algorithms is studied through numerical simulations and it is found that the proposed ML and MML algorithms exhibit better performance than SML algorithm.

Joint estimation of synchronization impairments in MIMO-OFDM system

A joint Maximum Likelihood (ML) estimation algorithm for the synchronization impairments such as Carrier Frequency Offset (CFO), Sampling Frequency Offset (SFO) and Symbol Timing Error (STE) in single user MIMO-OFDM system is investigated in this work. A received signal model that takes into account the nonlinear effects of CFO, SFO, STE and Channel Impulse Response (CIR) is formulated. Based on the signal model, a joint ML estimation algorithm is proposed. Cramer-Rao Lower Bound (CRLB) for the continuous parameters CFO and SFO is derived for the cases of with and without channel response effects and is used to compare the effect of coupling between different estimated parameters. The performance of the estimation method is studied through numerical simulations.

Data acquisition and processing at ocean bottom for a Tsunami warning system

The design and development of a Bottom Pressure Recorder for a Tsunami Early Warning System is described here. The special requirements that it should satisfy for the specific application of deployment at ocean bed and pressure monitoring of the water column above are dealt with. A high-resolution data digitization and low circuit power consumption are typical ones. The implementation details of the data sensing and acquisition part to meet these are also brought out. The data processing part typically encompasses a Tsunami detection algorithm that should detect an event of significance in the background of a variety of periodic and aperiodic noise signals. Such an algorithm and its simulation are presented. Further, the results of sea trials carried out on the system off the Chennai coast are presented. The high quality and fidelity of the data prove that the system design is robust despite its low cost and with suitable augmentations, is ready for a full-fledged deployment at ocean bed. (C) 2013 Elsevier Ltd. All rights reserved.

A Three-Level Common-Mode Voltage Eliminated Inverter With Single DC Supply Using Flying Capacitor Inverter and Cascaded H-Bridge

A three-level common-mode voltage eliminated inverter with single dc supply using flying capacitor inverter and cascaded H-bridge has been proposed in this paper. The three phase space vector polygon formed by this configuration and the polygon formed by the common-mode eliminated states have been discussed. The entire system is simulated in Simulink and the results are experimentally verified. This system has an advantage that if one of devices in the H-bridge fails, the system can still be operated as a normal three-level inverter at full power. This inverter has many other advantages like use of single dc supply, making it possible for a back-to-back grid-tied converter application, improved reliability, etc.

BILATERAL EDGE DETECTORS

We propose to employ bilateral filters to solve the problem of edge detection. The proposed methodology presents an efficient and noise robust method for detecting edges. Classical bilateral filters smooth images without distorting edges. In this paper, we modify the bilateral filter to perform edge detection, which is the opposite of bilateral smoothing. The Gaussian domain kernel of the bilateral filter is replaced with an edge detection mask, and Gaussian range kernel is replaced with an inverted Gaussian kernel. The modified range kernel serves to emphasize dissimilar regions. The resulting approach effectively adapts the detection mask according as the pixel intensity differences. The results of the proposed algorithm are compared with those of standard edge detection masks. Comparisons of the bilateral edge detector with Canny edge detection algorithm, both after non-maximal suppression, are also provided. The results of our technique are observed to be better and noise-robust than those offered by methods employing masks alone, and are also comparable to the results from Canny edge detector, outperforming it in certain cases.

Low complexity joint estimation of synchronization impairments in sparse channel for MIMO-OFDM system

Low complexity joint estimation of synchronization impairments and channel in a single-user MIMO-OFDM system is presented in this paper. Based on a system model that takes into account the effects of synchronization impairments such as carrier frequency offset, sampling frequency offset, and symbol timing error, and channel, a Maximum Likelihood (ML) algorithm for the joint estimation is proposed. To reduce the complexity of ML grid search, the number of received signal samples used for estimation need to be reduced. The conventional channel estimation techniques using Least-Squares (LS) or Maximum a posteriori (MAP) methods fail for the reduced sample under-determined system, which results in poor performance of the joint estimator. The proposed ML algorithm uses Compressed Sensing (CS) based channel estimation method in a sparse fading scenario, where the received samples used for estimation are less than that required for an LS or MAP based estimation. The performance of the estimation method is studied through numerical simulations, and it is observed that CS based joint estimator performs better than LS and MAP based joint estimator. (C) 2013 Elsevier GmbH. All rights reserved.