Millimeter-wave Ground-based Synthetic Aperture Radar Imaging for Foreign Object Debris Detection: Experimental Studies at Short Ranges

In this paper, millimeter-wave imaging of foreign object debris (FOD)-type objects on the ground is studied with the help of ground-based synthetic aperture radar (GB-SAR) technique. To test the feasibility of detecting runway FODs with this technique, some preliminary experiments are conducted within short antenna-to-target ranges of small imaging patches. An automated stripmap GB-SAR system with stepped-frequency transmission is constructed together with a quasi-monostatic data collection operation. The imaging experiments for various braces and screws are then carried out by using 32–36?GHz and 90–95?GHz frequency bands of the millimeter-wave. Images reconstructed by a matched-filter based algorithm are analyzed to determine the proper system parameters for an efficient imaging and to comprehend the factors against a successful detection. Results demonstrate the capability of GB-SAR imaging in accurately locating these FOD-like targets under near-range operating conditions.     

All‐pass sections with rich cascadability and IC realization suitability

In this paper, two new circuit configurations for realizing voltage‐mode (VM) all‐pass sections (APSs) are presented. The proposed circuits employ only two differential voltage current conveyors (DVCCs) and are cascadable with other VM circuits due to their high‐input and low‐output impedances. The first configuration uses a grounded resistor and a grounded capacitor without requiring matching constraints, whereas the second employs two grounded resistors and a grounded capacitor with a single matching condition. While the first configuration can realize only one all‐pass response, the second can provide inverting and non‐inverting all‐pass responses with selection of appropriate input port. Adding two grounded resistors to the proposed filters, variable gain APSs can also be obtained. As applications, two quadrature oscillators, each of which using one of the proposed all‐pass circuits, one grounded resistor and one grounded capacitor are presented. SPICE simulation results are included to verify the theory. Copyright © 2010 John Wiley & Sons, Ltd.     

Psychotic symptoms in post-traumatic stress disorder

The mouse has become the leading animal model for studying biological processes in mammals. Creation of additional genomic and genetic resources will make the mouse an even more useful model for the research community. On the basis of recommendations from the scientific community, the National Institutes of Health (NIH) plans to support grants to generate a 'working draft' sequence of the mouse genome by 2003, systematic mutagenesis and phenotyping centres, repositories for mouse strain maintenance, distribution and cryopreservation and training fellowships in mouse pathobiology.     

Effects of spraying nano‐materials on the absorption of metal(loid)s in cucumber

This report investigates the spraying of nano‐silica and fullerene on cucumber leaves to expose their ability to reduce the toxicity and uptake of metal(loid)s. Cucumber seedlings were randomly divided into six treatment groups: 10 mg/L nano‐SiO₂, 20 mg/L nano‐SiO₂, 10 mg/L Fullerene, 20 mg/L Fullerene, 5 mg/L Fullerene + 5 mg/L nano‐SiO₂, and 10 mg/L Fullerene + 10 mg/L nano‐SiO₂. Nano‐silica‐treated plants exhibited evidence of the potential mitigation of metal(loid)s poisoning. Specifically, results showed that 20 mg/L of nano‐silica promoted Cd uptake by plants; comparatively, 10 mg/L of nano‐silica did not significantly increase the silicon content in plants. Both low‐concentration combined treatment and low‐concentration fullerene groups inhibited metal(loid)s uptake by plants. Scanning electron microscopy (SEM) was then used to observe the surface morphology of cucumber leaves. Significant differences were observed on disease resistance in plants across the different nano‐material conditions. Collectively, these findings suggest that both nano‐silica materials and fullerene have the potential to control metal(loid)s toxicity in plants.Inspec keywords: soil pollution, cadmium, silicon compounds, surface morphology, fullerenes, toxicology, fertilisers, scanning electron microscopy, crops, spraying, nanoparticles, sorption, plant diseases, agricultural safetyOther keywords: cucumber leaves, nanosilica materials, fullerene, spraying process, metalloids absorption, toxicity, scanning electron microscopy, surface morphology, disease resistance, soil pollution, SiO₂ , Cd     

Anomaly localization in regular textures based on deep convolutional generative adversarial networks

Applied Intelligence - Pixel-level anomaly localization is a challenging problem due to the lack of abnormal training samples. The existing adversarial network methods attempt to segment anomalies...     

On self-routing in Clos connection networks

A self-routing connection network is a switching device where the routing of each switch can be determined in terms of the destination addresses of its inputs alone, i.e. independent of the routing information regarding the other switches in the network. One family of connection networks that were considered in the literature for self-routing are Clos networks. Earlier studies indicate that some Clos networks can be self-routed for certain permutations. In this paper, it is proved that the only category of Clos networks that can be self-routed for all permutations are those with at most two switches in their outer stages     

Face Recognition Based on Gabor Feature Extraction Followed by FastICA and LDA

Over the past few decades, face recognition has become the most effective biometric technique in recognizing people’s identity, as it is widely used in many areas of our daily lives. However, it is a challenging technique since facial images vary in rotations, expressions, and illuminations. To minimize the impact of these challenges, exploiting information from various feature extraction methods is recommended since one of the most critical tasks in face recognition system is the extraction of facial features. Therefore, this paper presents a new approach to face recognition based on the fusion of Gabor-based feature extraction, Fast Independent Component Analysis (FastICA), and Linear Discriminant Analysis (LDA). In the presented method, first, face images are transformed to grayscale and resized to have a uniform size. After that, facial features are extracted from the aligned face image using Gabor, FastICA, and LDA methods. Finally, the nearest distance classifier is utilized to recognize the identity of the individuals. Here, the performance of six distance classifiers, namely Euclidean, Cosine, Bray-Curtis, Mahalanobis, Correlation, and Manhattan, are investigated. Experimental results revealed that the presented method attains a higher rank-one recognition rate compared to the recent approaches in the literature on four benchmarked face datasets: ORL, GT, FEI, and Yale. Moreover, it showed that the proposed method not only helps in better extracting the features but also in improving the overall efficiency of the facial recognition system.     

A fast parallel algorithm for routing unicast assignments in Benesnetworks

This paper presents a new parallel algorithm for routing unicast (one-to-one) assignments in Benes networks. Parallel routing algorithms for such networks were reported earlier, but these algorithms were designed primarily to route permutation assignments. The routing algorithm presented in this paper removes this restriction without an increase in the order of routing cost or routing time. We realize this new routing algorithm on two different topologies. The algorithm routes a unicast assignment involving O(k) pairs of inputs and outputs in O(lg ² k+lg n) time on a completely connected network of n processors and in O(lg⁴ k+lg² k lg n) time on an extended shuffle-exchange network of n processors. Using O(n lg n) professors, the same algorithm can be pipelined to route α unicast assignments each involving O(k) pairs of inputs and outputs, in O(lg² k+lg n+(α-1) lg k) time on a completely connected network and in O(lg⁴ k+lg² k lg n+(α-1)(lg ³ k+lg k lg n)) time on the extended shuffle-exchange network. These yield an average routing time of O(lg k) in the first case, and O(lg³ k+1g k lg n) in the second case, for all α⩾lg n. These complexities indicate that the algorithm given in this paper is as fast as Nassimi and Sahni's algorithm for unicast assignments, and with pipelining, it is faster than the same algorithm at least by a factor of O(lg n) on both topologies. Furthermore, for sparse assignments, i.e., when k=O(1), it is the first algorithm which has an average routing time of O(1g n) on a topology with O(n) links