Extraction of fibre network architecture by X-ray tomography and prediction of elastic properties using an affine analytical model

This paper proposes a method for extracting reliable architectural characteristics from complex porous structures using micro-computed tomography (μCT) images. The work focuses on a highly porous material composed of a network of fibres bonded together. The segmentation process, allowing separation of the fibres from the remainder of the image, is the most critical step in constructing an accurate representation of the network architecture. Segmentation methods, based on local and global thresholding, were investigated and evaluated by a quantitative comparison of the architectural parameters they yielded, such as the fibre orientation and segment length (sections between joints) distributions and the number of inter-fibre crossings. To improve segmentation accuracy, a deconvolution algorithm was proposed to restore the original images. The efficacy of the proposed method was verified by comparing μCT network architectural characteristics with those obtained using high resolution CT scans (nanoCT). The results indicate that this approach resolves the architecture of these complex networks and produces results approaching the quality of nanoCT scans. The extracted architectural parameters were used in conjunction with an affine analytical model to predict the axial and transverse stiffnesses of the fibre network. Transverse stiffness predictions were compared with experimentally measured values obtained by vibration testing. © 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Characterization of the sleep architecture in two species of fruit bat

Bats (Chiroptera) are the second-most abundant mammalian order in the world, occupying a diverse range of habitats and exhibiting many different life history traits. In order to contribute to this highly underrepresented group we describe the sleep architecture of two species of frugivorous bat, the greater short-nosed fruit bat (Cynopterus sphinx) and the lesser dawn fruit bat (Eonycteris spelaea). Electroencephalogram (EEG) and electromyogram (EMG) data were recorded from multiple individuals (>= 5) by telemetry over a 72-h period in a laboratory setting with light/dark cycles equivalent to those found in the wild. Our results show that over a 24-h period both species spent more time asleep than awake (mean 15 h), less than previous reported for Chiroptera (20 h). C sphinx spent significantly more of its non-rapid eye movement sleep (NREM) and rapid eye movement sleep (REM) quotas during the light phase, while E. spelaea divided its sleep-wake architecture equally between both light and dark phases. Comparing the sleep patterns of the two species found that C. sphinx had significantly fewer NREM and REM episodes than E. spelaea but each episode lasted for a significantly longer period of time. Potential hypotheses to explain the differences in the sleep architecture of C. sphinx with E. spelaea, including risk of predation and social interaction are discussed. (C) 2010 Published by Elsevier B.V.

Regenerative polymeric bus architecture for board-level optical interconnects

A scalable multi-channel optical regenerative bus architecture based on the use of polymer waveguides is presented for the first time. The architecture offers high-speed interconnection between electrical cards allowing regenerative bus extension with multiple segments and therefore connection of an arbitrary number of cards onto the bus. In a proof-ofprinciple demonstration, a 4-channel 3-card polymeric bus module is designed and fabricated on standard FR4 substrates. Low insertion losses (≤ -15 dB) and low crosstalk values (< -30 dB) are achieved for the fabricated samples while better than ± 6 μm -1 dB alignment tolerances are obtained. 10 Gb/s data communication with a bit-error-rate (BER) lower than 10-12 is demonstrated for the first time between card interfaces on two different bus modules using a prototype 3R regenerator. © 2012 Optical Society of America.

Gated three-terminal device architecture to eliminate persistent photoconductivity in oxide semiconductor photosensor arrays

The composition of amorphous oxide semiconductors, which are well known for their optical transparency, can be tailored to enhance their absorption and induce photoconductivity for irradiation with green, and shorter wavelength light. In principle, amorphous oxide semiconductor-based thin-film photoconductors could hence be applied as photosensors. However, their photoconductivity persists for hours after illumination has been removed, which severely degrades the response time and the frame rate of oxide-based sensor arrays. We have solved the problem of persistent photoconductivity (PPC) by developing a gated amorphous oxide semiconductor photo thin-film transistor (photo-TFT) that can provide direct control over the position of the Fermi level in the active layer. Applying a short-duration (10 ns) voltage pulse to these devices induces electron accumulation and accelerates their recombination with ionized oxygen vacancy sites, which are thought to cause PPC. We have integrated these photo-TFTs in a transparent active-matrix photosensor array that can be operated at high frame rates and that has potential applications in contact-free interactive displays. © 2012 Macmillan Publishers Limited. All rights reserved.

Content Based Integration of Construction Site Images in Architecture, Engineering, Construction, and Facilities Management (AEC/FM) Model based Systems

This book explores the processes for retrieval, classification, and integration of construction images in AEC/FM model based systems. The author describes a combination of techniques from the areas of image and video processing, computer vision, information retrieval, statistics and content-based image and video retrieval that have been integrated into a novel method for the retrieval of related construction site image data from components of a project model. This method has been tested on available construction site images from a variety of sources like past and current building construction and transportation projects and is able to automatically classify, store, integrate and retrieve image data files in inter-organizational systems so as to allow their usage in project management related tasks. objects. Therefore, automated methods for the integration of construction images are important for construction information management. During this research, processes for retrieval, classification, and integration of construction images in AEC/FM model based systems have been explored. Specifically, a combination of techniques from the areas of image and video processing, computer vision, information retrieval, statistics and content-based image and video retrieval have been deployed in order to develop a methodology for the retrieval of related construction site image data from components of a project model. This method has been tested on available construction site images from a variety of sources like past and current building construction and transportation projects and is able to automatically classify, store, integrate and retrieve image data files in inter-organizational systems so as to allow their usage in project management related tasks.