An efficient Newton-type method for the computation of ML estimators in a uniform linear array

In the problem of estimating the angles of arrival to a uniform linear array, we present an efficient method to compute Maximum Likelihood (ML) estimations, based on the Modified Variable Projection (MVP) algorithm. In contrast to methods like Iterative Quadratical Maximum Likelihood (IQML) or the Iterative Method of Direction Estimation (IMODE), it is not based on a polynomial parameterization but on directly exploiting the Vandermonde structure through analytical tools like the Fast Fourier Transform (FFT), the geometric series summation formula, and Horner's synthetic division. The computational burden of the proposed method is significantly smaller than the burden of IMODE and of the Relaxation (RELAX) algorithm. Besides, it is shown that the computation of the ML estimation can be divided in a preliminary step in which a few FFTs are computed and an iterative step with a complexity that is independent of the array size.     

Synthesis,microstructure and optical characterization of zirconium oxide nanostructures

Zirconium oxide (ZrO₂) nanostructures were synthesized by hydrothermal route. Surface morphology analysis depicts the formation of the nanobars and hexagonal-shaped nanodiscs at different synthesis conditions. The structural analysis confirms that the as-synthesized ZrO₂ product is of pure monoclinic phase (m-ZrO₂) with crystallite size of about 25 nm. The product consists of monodispersed nanoparticles of uniform composition, high purity, and crystallinity. The Raman spectra are quantitatively analyzed and the observed peaks are attributed to various vibration modes of the m-ZrO₂. The UV–vis absorption spectrum showed a strong absorption peak at about 292 nm and the estimated optical band gap was around 3.57 eV. Photoluminescence (PL) spectrum of ZrO₂ nanostructure showed a strong and broad emission peak at around 410 nm at room temperature, which can be attributed to the ionized oxygen vacancy in the material.     

SAR image despeckling using heavy-tailed Burr distribution

Multiplicative speckle noise diminishes the radiometric resolution of the synthetic aperture radar (SAR) images and all the coherent images. Speckle removal adds an extra value to an automated SAR image interpretation and analysis. In this paper, dual-tree complex wavelet-transform-based Bayesian method is proposed for despeckling the SAR images. In each subband, the reflectance and noise of the logarithmically transformed wavelet coefficients are modeled using heavy-tailed Burr and zero-mean Gaussian distributions. The closed-form expression for the shape parameter of Burr distribution is derived by employing the Mellin transform. The resultant complex-free quadratic maximum a posteriori solution with suitable shrinkage function yields despeckled SAR images. Extensive experiments are carried out using real SAR images as well as simulated images. The proposed method performs well in terms of equivalent number of looks with 3.5751 dB improvement in homogeneous region1 of Pipe river SAR image, edge preservation with 0.6158 improvement, peak signal to noise ratio of 51.3305 dB, and mean structural similarity index measure of 0.9397 at 0.05 noise variance for synthetically speckled image in comparison to the existing methods and takes averagely 2.3461 times less computing time. The proposed method provides a computationally efficient better speckle reduction in homogeneous regions while still preserving the edge.     

Distance metric-based time-efficient fuzzy algorithm for abnormal magnetic resonance brain image segmentation

Image segmentation is one of the significant computational applications of the biomedical field. Automated computational methodologies are highly preferred for medical image segmentation since these techniques are immune to human perception error. Artificial intelligence (AI)-based techniques are often used for this process since they are superior to other automated techniques in terms of accuracy and convergence time period. Fuzzy systems hold a significant position among the AI techniques because of their high accuracy. Even though these systems are exceptionally accurate, the time period required for convergence is exceedingly high. In this work, a novel distance metric-based fuzzy C-means (FCM) algorithm is proposed to tackle the low-convergence-rate problem of the conventional fuzzy systems. This modified approach involves the concept of distance-based dimensionality reduction of the input vector space that substantially reduces the iterative time period of the conventional FCM algorithm. The effectiveness of the modified FCM algorithm is explored in the context of magnetic resonance brain tumor image segmentation. Experimental results show promising results for the proposed approach in terms of convergence time period and segmentation efficiency. Thus, this algorithm proves to be highly feasible for time-oriented real-time applications.     

Intra and interindividual variations of pelvic mobility in normal adult walk

PURPOSE OF THE STUDY: Pelvis motion appears as a main human gait component, it is linked to the lower limb joints and to the spine. Current devices, especially the opto-electronical systems, allow quantitative and tri-dimensional gait studies. The purpose of this study was to quantify the pelvic motion individual variability in a sample of healthy subjects. MATERIALS AND METHODS: The study based on a 18 volunters sample. There were 14 men and 4 women, ranged in age from 25 to 37 years. A clinical examination and a AP radiograph of pelvis allowed to include healthy subjects. We used the three-dimensional analysis VICON system with five cameras. Nine records were performed for each subject during a free-speed walking. These nine records were distributed on three different days. RESULTS: The step length medianes varied from 1100 to 1600 mm with a significantly (p < 0.05) regression between the step length, the walking speed and the subjects height. Vertical pelvic oscillations varied in this sample from 25 to 60 mm and linked with step length and walking speed. Pelvic rotation around the vertical axis varied from 1.5 to 15 degrees. We did not found regression between this pelvic rotation and the length step. It seems there are three types of pelvic rotation around the vertical axis. At the beginning of the stance phase, in type I, the pelvis is in the transversal plane whereas in the type II, it appears with the maximal rotation. In type III, the value of pelvic rotation is very low. The successive lateral inclinations of pelvic described a complex motion which varied from 1.5 to 9 degrees. The rotation of shoulders around the vertical axis varied from 4 degrees to 13 degrees and the successive inclinations varied from 3.25 degrees to 12 degrees. We did not found any regression between the pelvic and shoulders motion values. DISCUSSION: This study showed that the pelvis motion varied considerably from one subject to another. These variations induce different ways of walking with various consequences on the hip joint and the spine. We suppose that these variations could take a part in etiology of some diseases as hip arthritis or in total hip arthroplasty failure, especially in cup wearing.     

N and p doped poly(3,4-ethylenedioxythiophene) electrode materials for symmetric redox supercapacitors

A symmetric redox supercapacitor has been fabricated based on n and p doped Poly(3,4-ethylenedioxythiophene)(PEDOT) coated on stainless steel (SS) electrodes. The characterization and performance of the supercapacitor has been studied by FTIR, Cyclic Voltammetry and AC Impedance spectroscopy. The supercapacitor showed a maximum specific capacitance of 121 F g⁻¹ at a scan rate of 10 mV s⁻¹. The time constant calculated for the supercapacitor through the active–reactive power behavior measurement was 12 milliseconds indicating the suitability of the system for efficient use at low frequency range.     

SMOS REFLEX 2003: L-band emissivity characterization of vineyards

The goal of the Soil Moisture and Ocean Salinity mission over land is to infer surface soil moisture from multiangular L-band radiometric measurements. As the canopy affects the microwave emission of land, it is necessary to characterize different vegetation layers. This paper presents the Reference Pixel L-Band Experiment (REFLEX), carried out in June-July 2003 at the Vale/spl grave/ncia Anchor Station, Spain, to study the effects of grapevines on the soil emission and on the soil moisture retrieval. A wide range of soil moisture (SM), from saturated to completely dry soil, was measured with the Universitat Polite/spl grave/cnica de Catalunya's L-band Automatic Radiometer (LAURA). Concurrently with the radiometric measurements, the gravimetric soil moisture, temperature, and roughness were measured, and the vines were fully characterized. The opacity and albedo of the vineyard have been estimated and found to be independent on the polarization. The /spl tau/--/spl omega/ model has been used to retrieve the SM and the vegetation parameters, obtaining a good accuracy for incidence angles up to 55/spl deg/. Algorithms with a three-parameter optimization (SM, albedo albedo, and opacity) exhibit a better performance than those with one-parameter optimization (SM).     

Digital processing of mechanical transient response signals—Digital filter approach

The primary aim of this paper is to bring to the attention of shock and vibration engineers the advantages of using digital filters for processing transient response signals. Specifically, the development of reliable high pass digital filters to remove the low frequency components in the acquired acceleration signals so as to obtain valid velocity and displacement-time records, is presented. It is concluded that the non-recursive filters are well suited for mechanical engineering transient response applications. The viability of the non-recursive digital filters for the intended application is established with the use of acceleration signals obtained from a laboratory shock test. Also as a part of this investigation, a set of user-friendly, computer programs for filter design and filtering are developed and implemented.     

Escherichia coli cytotoxic necrotizing factor 1 effaces microvilli and decreases transmigration of polymorphonuclear leukocytes in intestinal T84 epithelial cell monolayers

Cytotoxic necrotizing factor type 1 (CNF1), a 110-kDa toxin-like protein from pathogenic Escherichia coli strains, induces an actin cytoskeleton reorganization consisting of the formation of prominent stress fibers by permanent activation of the small GTP-binding protein Rho. Since p21Rho regulates tight-junction permeability and perijunctional actin reorganization in epithelial intestinal cells (A. Nusrat, M. Giry, J. R. Turner, S. P. Colgan, C. A. Parkos, E. Lemichez, P. Boquet, and J. L. Madara, Proc. Natl. Acad. Sci. USA 92:10629-10633, 1995), we used polarized T84 epithelial intestinal cell monolayers to examine whether CNF1 could affect microvillus structure, transepithelial resistance, and polymorphonuclear leukocyte (PMN) transmigration. Incubation of T84 cells with CNF1 did not influence transepithelial resistance, suggesting that barrier function and surface polarity were not affected by the toxin. However, CNF1 effaced intestinal cell microvilli and induced a strong decrease of PMN transepithelial migration in either the luminal-to-basolateral or the basolateral-to-luminal direction. CNF1 could thus be a virulence factor exhibiting a new type of combined activity consisting of effacing of microvilli and occlusion of the epithelial barrier to PMNs. Attenuated transepithelial migration of PMNs could result in the enhanced growth and protection of luminal bacteria.     

Double Stage Gaussian Filter for Better Underwater Image Enhancement

Wireless Personal Communications - Major issue in marine environment imaging is the expulsion of hazy scenes caused by natural phenomena such as absorption and scattering in underwater images. The...