Automated Computation of the Fundamental Matrix for Vision-Based Construction Site Applications

Estimating the fundamental matrix (F), to determine the epipolar geometry between a pair of images or video frames, is a basic step for a wide variety of vision-based functions used in construction operations, such as camera-pair calibration, automatic progress monitoring, and 3D reconstruction. Currently, robust methods (e.g., SIFT + normalized eight-point algorithm + RANSAC) are widely used in the construction community for this purpose. Although they can provide acceptable accuracy, the significant amount of required computational time impedes their adoption in real-time applications, especially video data analysis with many frames per second. Aiming to overcome this limitation, this paper presents and evaluates the accuracy of a solution to find F by combining the use of two speedy and consistent methods: SURF for the selection of a robust set of point correspondences and the normalized eight-point algorithm. This solution is tested extensively on construction site image pairs including changes in viewpoint, scale, illumination, rotation, and moving objects. The results demonstrate that this method can be used for real-time applications (5 image pairs per second with the resolution of 640 × 480) involving scenes of the built environment.

Influence of the matrix properties on the performances of Er-doped Si nanoclusters light emitting devices

We investigated the properties of light emitting devices whose active layer consists of Er-doped Si nanoclusters (nc) generated by thermal annealing of Er-doped SiOx layers prepared by magnetron cosputtering. Differently from a widely used technique such as plasma enhanced chemical vapor deposition, sputtering allows to synthesize Er-doped Si nc embedded in an almost stoichiometric oxide matrix, so as to deeply influence the electroluminescence properties of the devices. Relevant results include the need for an unexpected low Si excess for optimizing the device efficiency and, above all, the strong reduction of the influence of Auger de-excitation, which represents the main nonradiative path which limits the performances of such devices and their application in silicon nanophotonics. © 2010 American Institute of Physics.

Low-rank optimization for distance matrix completion

This paper addresses the problem of low-rank distance matrix completion. This problem amounts to recover the missing entries of a distance matrix when the dimension of the data embedding space is possibly unknown but small compared to the number of considered data points. The focus is on high-dimensional problems. We recast the considered problem into an optimization problem over the set of low-rank positive semidefinite matrices and propose two efficient algorithms for low-rank distance matrix completion. In addition, we propose a strategy to determine the dimension of the embedding space. The resulting algorithms scale to high-dimensional problems and monotonically converge to a global solution of the problem. Finally, numerical experiments illustrate the good performance of the proposed algorithms on benchmarks. © 2011 IEEE.

Determination of the rheological parameters of self-compacting concrete matrix using slump flow test

The classification of a concrete mixture as self-compacting (SCC) is performed by a series of empirical characterization tests that have been designed to assess not only the flowability of the mixture but also its segregation resistance and filling ability. The objective of the present work is to correlate the rheological parameters of SCC matrix, yield stress and plastic viscosity, to slump flow measurements. The focus of the slump flow test investigation was centered on the fully yielded flow regime and an empirical model relating the yield stress to material and flow parameters is proposed. Our experimental data revealed that the time for a spread of 500 mm which is used in engineering practice as reference for measurement parameters, is an arbitrary choice. Our findings indicate that the non-dimensional final spread is linearly related to the non-dimensional yield-stress. Finally, there are strong indications that the non-dimensional viscosity of the mixture is associated with the non-dimensional final spread as well as the stopping time of the slump flow; this experimental data set suggests an exponential decay of the final spread and stopping time with viscosity. © Appl. Rheol.

Determination of 266 pesticide residues in apple juice by matrix solid-phase dispersion and gas chromatography-mass selective detection

A macro matrix solid-phase dispersion (MSPD) method was developed to extract 266 pesticides from apple juice samples prior to gas chromatography-mass selective detection (GC-MSD) determination. A 10 g samples was mixed with 20 g diatomaceous earth. The mixture was transferred into a glass column. Pesticide residues were leached with a 160 mL hexane-dichloromethane (1:1) at 5 mL/min. Two hundred and sixty-six pesticides were divided into three groups and detected by GC-MSD under selective ion monitoring. The proposed method takes advantage of both liquid-liquid extraction and conventional MSPD methods. Application was illustrated by the analysis of 236 apple juice samples produced in Shaanxi province China mainland this year. (C) 2004 Elsevier B.V. All rights reserved.

Fixed-rank matrix factorizations and Riemannian low-rank optimization

Motivated by the problem of learning a linear regression model whose parameter is a large fixed-rank non-symmetric matrix, we consider the optimization of a smooth cost function defined on the set of fixed-rank matrices. We adopt the geometric framework of optimization on Riemannian quotient manifolds. We study the underlying geometries of several well-known fixed-rank matrix factorizations and then exploit the Riemannian quotient geometry of the search space in the design of a class of gradient descent and trust-region algorithms. The proposed algorithms generalize our previous results on fixed-rank symmetric positive semidefinite matrices, apply to a broad range of applications, scale to high-dimensional problems, and confer a geometric basis to recent contributions on the learning of fixed-rank non-symmetric matrices. We make connections with existing algorithms in the context of low-rank matrix completion and discuss the usefulness of the proposed framework. Numerical experiments suggest that the proposed algorithms compete with state-of-the-art algorithms and that manifold optimization offers an effective and versatile framework for the design of machine learning algorithms that learn a fixed-rank matrix. © 2013 Springer-Verlag Berlin Heidelberg.

Spin relaxation in submonolayer and monolayer InAs structures grown in a GaAs matrix

Electron-spin dynamics in InAs/GaAs heterostructures consisting of a single layer of InAs (1/3-1 monolayer) embedded in (001) and (311)A GaAs matrix was studied by means of time-resolved Kerr rotation spectroscopy. The spin-relaxation time of the submonolayer InAs samples is significantly enhanced, compared with that of the monolayer InAs sample. The electron-spin-relaxation time and the effective g factor in submonolayer samples were found to be strongly dependent on the photogenerated carrier density. The contribution from both the D'yakonov-Perel' mechanism and Bir-Aronov-Pikus mechanism are discussed to interpret the temperature dependence of spin decoherence at various carrier densities.

Formation of ferromagnetic clusters in GaAs matrix and GaAs/AlGaAs superlattice through Mn ion implantation at two different temperatures

Different submicron ferromagnets are fabricated into GaAs and GaAs/AlGaAs superlattice through ion implantation at two different temperatures followed by thermal annealing. The structural and magnetic properties of the granular film are studied by an atomic force microscope, X-ray diffraction and alternating gradient magnetometer. By analyzing the saturation magnetization M-s, remanence M-r, coercivity H-c and remanence ratio S-q, it is confirmed that both MnGa and MnAs clusters are formed in the 350degreesC-implanted samples whereas only MnAs clusters are formed in the room-temperature implanted samples. (C) 2004 Elsevier B.V. All rights reserved.

Effect of substrate misorientation on the InAs/InAlAs/InP nanostructure morphology and lateral composition modulation in the InAlAs matrix

The authors report the self-organized growth of InAs/InAlAs quantum wires on nominal (001) InP substrate and (001) InP substrates misoriented by 2 degrees, 4 degrees, and 8 degrees towards both [-110] and [110]. The influence of substrate misorientation on the structural and optical properties of these InAs/InAlAs quantum wires is studied by transmission electron microscopy and photoluminescence measurements. Compared with that grown on nominal (001) InP substrate, the density of InAs/InAlAs quantum wires grown on misoriented InP(001) substrates is enhanced. A strong lateral composition modulation effect take place in the InAlAs buffer layers grown on misoriented InP substrates with large off-cut angles (4 degrees and 8 degrees), which induces a nucleation template for the first-period InAs quantum wires and greatly improve the size distribution of InAs quantum wires. InAs/InAlAs quantum wires grown on InP (001) substrate 8 degrees off cut towards [-110] show the best size homogeneity and photoluminescence intensity. (c) 2007 American Institute of Physics.

Absorption spectra of nanocrystalline silicon embedded in SiO2 matrix

Nanocrystalline silicon (nc-Si) embedded SiO2 matrix has been formed by annealing the SiOx films fabricated by plasma-enhanced chemical vapor deposition (PECVD) technique. Absorption coefficient and photoluminescence of the films have been measured at room temperature. The experimental results show that there is an "aUrbach-like" b exponential absorption in the spectral range of 2.0-3.0 eV. The relationship of (alpha hv)(1/2) proportional to(hv - E-g) demonstrates that the luminescent nc-Si have an indirect band structure. The existence of Stokes shift between photoluminescence and absorption edge indicates that radiative combination can take place not only between electron states and hole states but also between shallow trap states of electrons and holes. (C) 2000 Elsevier Science B.V. All rights reserved.

Zinc phthalocyanine (ZnPc) incorporated into silicon matrix grown by plasma enhanced chemical vapor deposition (PECVD)

Hybrid composites composed of zinc phthalocyanine embedded in silicon matrixes have attracted attention because of the potential for solar energy conversion. We produce hybrid composites by thermal evaporation for the plithalocyanine and PECVD (Plasma Enhanced Chemical Vapor Deposition) for the silicon matrix. Deposition of ZnPc/a-Si(amorphous silicon) composites was achieved in a sequential manner. The compound films were characterized by optical transmittance spectra and photoconductivity measurement. The optical transmittance measurements were carried out in the visible region (500 - 800 nm). Compared to pure silicon film, the photosensitivity of compound functional films was enhanced by one order of magnitude. This demonstrates the Si sensitized by adding ZnPc.

Performance of an embedded optical vector matrix multiplication processor architecture

An embedded architecture of optical vector matrix multiplier (OVMM) is presented. The embedded architecture is aimed at optimising the data flow of vector matrix multiplier (VMM) to promote its performance. Data dependence is discussed when the OVMM is connected to a cluster system. A simulator is built to analyse the performance according to the architecture. According to the simulation, Amdahl's law is used to analyse the hybrid opto-electronic system. It is found that the electronic part and its interaction with optical part form the bottleneck of system.