Two decades of array signal processing research: the parametricapproach

The quintessential goal of sensor array signal processing is the estimation of parameters by fusing temporal and spatial information, captured via sampling a wavefield with a set of judiciously placed antenna sensors. The wavefield is assumed to be generated by a finite number of emitters, and contains information about signal parameters characterizing the emitters. A review of the area of array processing is given. The focus is on parameter estimation methods, and many relevant problems are only briefly mentioned. We emphasize the relatively more recent subspace-based methods in relation to beamforming. The article consists of background material and of the basic problem formulation. Then we introduce spectral-based algorithmic solutions to the signal parameter estimation problem. We contrast these suboptimal solutions to parametric methods. Techniques derived from maximum likelihood principles as well as geometric arguments are covered. Later, a number of more specialized research topics are briefly reviewed. Then, we look at a number of real-world problems for which sensor array processing methods have been applied. We also include an example with real experimental data involving closely spaced emitters and highly correlated signals, as well as a manufacturing application example     

Information-Theoretic Active Polygons for Unsupervised Texture Segmentation

Curve evolution models used in image segmentation and based on image region information usually utilize simple statistics such as means and variances, hence can not account for higher order nature of the textural characteristics of image regions. In addition, the object delineation by active contour methods, results in a contour representation which still requires a substantial amount of data to be stored for subsequent multimedia applications such as visual information retrieval from databases. Polygonal approximations of the extracted continuous curves are required to reduce the amount of data since polygons are powerful approximators of shapes for use in later recognition stages such as shape matching and coding. The key contribution of this paper is the development of a new active contour model which nicely ties the desirable polygonal representation of an object directly to the image segmentation process. This model can robustly capture texture boundaries by way of higher-order statistics of the data and using an information-theoretic measure and with its nature of the ordinary differential equations. This new variational texture segmentation model, is unsupervised since no prior knowledge on the textural properties of image regions is used. Another contribution in this sequel is a new polygon regularizer algorithm which uses electrostatics principles. This is a global regularizer and is more consistent than a local polygon regularization in preserving local features such as corners.Supported by NSF grant CCR-0133736.Partially supported by AFOSR grant F49620-98-1-0190 and NSF grant CCR-9984067.     

Psychologists and public information.

The 1st peace group, inspired by Otto Klineberg and organized by Stanley Zuckerman in 1961, now called the "Social Scientists for Peace," had as its purpose the application of psychological knowledge to such urgent issues as war hysteria, cessations of nuclear tests, disarmament, and fall-out shelters. Activities of various groups of psychologists concerning such social endeavors are cited. 2 questions, "Should psychologists participate in demonstrations and similar activities?" and "Should psychologists be doing research rather than engaging in social action and public education?" are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

3D face recognition in the Fourier domain using deformed circular curves

One of the most significant problems in image and vision applications is the efficient representation of a target image containing a large amount of data with high complexity. The ability to analyze high dimensional signals in a lower dimension without losing their information, has been crucial in the field of image processing. This paper proposes an approach to 3D face recognition using dimensionality reduction based on deformed circular curves, on the shortest geodesic distances, and on the properties of the Fourier Transform. Measured geodesic distances information generates a matrix whose entities are geodesic distances between the reference point and an arbitrary point on a 3D object, and an one-dimensional vector is generated by reshaping the matrix without losing the original properties of the target object. Following the property of the Fourier Transform, symmetry of the magnitude response, the original signal can be analyzed in the lower dimensional space without loss of inherent characteristics. This paper mainly deal with the efficient representation and recognition algorithm using deformed circular curves and the simulation shows promising result for recognition of geometric face information.     

Electronic contributions to sliding friction

Two experimental approaches for determining the relative contributions of electronic and phononic dissipative mechanisms in sliding friction are discussed. The first involves comparison of electrical resistivity data with that recorded via a quartz crystal microbalance (QCM) technique. The second involves QCM studies of friction levels on clean and precoated metal surfaces. The first technique has been employed to study friction levels in the system H₂O/Ag, and the second technique has been employed to study the systems Ar/Ag and Ar/Xe/Ag. We conclude that electronic contributions to friction, long thought to be negligible with respect to phonon contributions, remain very viable as a significant source of energy dissipation. While the resistivity approach may ultimately yield accurate measurements of the electronic contributions to friction, we expect its use to be limited. Surface precoating experiments are meanwhile expected to be of widespread applicability.     

Image denoising: a nonlinear robust statistical approach

Nonlinear filtering techniques based on the theory of robust estimation are introduced. Some deterministic and asymptotic properties are derived. The proposed denoising methods are optimal over the Huber ε-contaminated normal neighborhood and are highly resistant to outliers. Experimental results showing a much improved performance of the proposed filters in the presence of Gaussian and heavy-tailed noise are analyzed and illustrated     

Effect of surface treatment on the physicomechanical and thermal properties of high‐density polyethylene/olive husk flour composites

In this study, a particular interest was focused on the recovery of lignocellulosic waste of olive husk flour (OHF) by its incorporation as filler in manufacturing composite materials based on high‐density polyethylene (HDPE) matrix with various filler contents (10, 20, and 30 wt %). The problem of incompatibility between the hydrophilic filler and the hydrophobic matrix was treated with two methods: the first method consists of using maleic anhydride‐grafted polyethylene (MAPE) as compatibilizer in HDPE/OHF composites. The second method, was focused on the chemical modification of OHF by vinyl‐triacetoxy‐silane (VTAS). Fourier transform infrared spectroscopy is used to analyze both grafting and silanization reactions involved. Scanning electron microscopy was used to show the morphology of the flour surface. Furthermore, the physicomechanical and thermal characteristics of the various composite samples were investigated as a function of filler contents and treatment types. The results showed that the properties of the composite materials are positively affected by the silanization treatment of OHF and also by MAPE addition. However, better mechanical and thermal properties with less moisture absorption were obtained for the composite materials compatibilized with MAPE. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Impact of oxygen and argon plasma exposure on the roughness of gold film surfaces

The impact of oxygen and argon plasma exposure on the roughness of gold film Quartz Crystal Microbalance (QCM) electrodes is reported here, employing low levels of gas uptake and scanning tunneling microscope measurements to probe the post-exposure surface morphology. For equal exposure times, argon plasma bombardment is observed to produce both greater material removal and greater change in surface roughness. A possible explanation for this is that the oxygen plasma produces a protective gold oxide layer, which may remove the contaminants from the surface without creating defects in the gold surface. The result is also consistent with prior reports of chemical cleaning of the surface by reactive oxygen ions. Pentane gas adsorption on the argon bombarded QCM surfaces was, moreover, observed to occur at pressures that are several orders of magnitude lower than that for an unbombarded surface.