ChESS - Quick and robust detection of chess-board features

Localization of chess-board vertices is a common task in computer vision, underpinning many applications, but relatively little work focusses on designing a specific feature detector that is fast, accurate and robust. In this paper the 'Chess-board Extraction by Subtraction and Summation' (ChESS) feature detector, designed to exclusively respond to chess-board vertices, is presented. The method proposed is robust against noise, poor lighting and poor contrast, requires no prior knowledge of the extent of the chess-board pattern, is computationally very efficient, and provides a strength measure of detected features. Such a detector has significant application both in the key field of camera calibration, as well as in structured light 3D reconstruction. Evidence is presented showing its superior robustness, accuracy, and efficiency in comparison to other commonly used detectors, including Harris & Stephens and SUSAN, both under simulation and in experimental 3D reconstruction of flat plate and cylindrical objects. © 2013 Elsevier Inc. All rights reserved.

Robust recognition of chess-boards under deformation

Current methods for formation of detected chess-board vertices into a grid structure tend to be weak in situations with a warped grid, and false and missing vertex-features. In this paper we present a highly robust, yet efficient, scheme suitable for inference of regular 2D square mesh structure from vertices recorded both during projection of a chess-board pattern onto 3D objects, and in the more simple case of camera calibration. Examples of the method's performance in a lung function measuring application, observing chess-boards projected on to patients' chests, are given. The method presented is resilient to significant surface deformation, and tolerates inexact vertex-feature detection. This robustness results from the scheme's novel exploitation of feature orientation information. © 2013 IEEE.

Reusable, robust, and accurate laser-generated photonic nanosensor.

Developing noninvasive and accurate diagnostics that are easily manufactured, robust, and reusable will provide monitoring of high-risk individuals in any clinical or point-of-care environment. We have developed a clinically relevant optical glucose nanosensor that can be reused at least 400 times without a compromise in accuracy. The use of a single 6 ns laser (λ = 532 nm, 200 mJ) pulse rapidly produced off-axis Bragg diffraction gratings consisting of ordered silver nanoparticles embedded within a phenylboronic acid-functionalized hydrogel. This sensor exhibited reversible large wavelength shifts and diffracted the spectrum of narrow-band light over the wavelength range λpeak ≈ 510-1100 nm. The experimental sensitivity of the sensor permits diagnosis of glucosuria in the urine samples of diabetic patients with an improved performance compared to commercial high-throughput urinalysis devices. The sensor response was achieved within 5 min, reset to baseline in ∼10 s. It is anticipated that this sensing platform will have implications for the development of reusable, equipment-free colorimetric point-of-care diagnostic devices for diabetes screening.

Simulation of single electronic device and robust circuit construction

The article mainly focuses on the simulation of the single electron device and circuit. The orthodox model of single electronic device is introduced and the simulation with Matlab and Pspice is illustrated in the article. Moreover, the built of robust circuit using single electronic according to neural network is done and the simulation is also included in the paper. The result shows that neural network added with proper redundancy is an available candidate for single electron device circuit. The proposed structure is also promising for the realization of low ultra-low power consumption and solution of transient device failure.

Composition Optimization of Tellurite Glass for Low-Loss and Robust Fiber Fabrication

低损耗高强度碲酸盐玻璃光纤用光学材料的优化方案

Double neutron/proton ratio of nucleon emissions in isotopic reaction systems as a robust probe of nuclear symmetry energy

The double neutron/proton ratio of nucleon emissions taken from two reaction systems using four isotopes of the same element, namely, the neutron/proton ratio in the neutron-rich system over that in the more symmetric system, has the advantage of reducing systematically the influence of the Coulomb force and the normally poor efficiencies of detecting low energy neutrons. The double ratio thus suffers less systematic errors. Within the IBUU04 transport model the double neutron/proton ratio is shown to have about the same sensitivity to the density dependence of nuclear symmetry energy as the single neutron/proton ratio in the neutron-rich system involved. The double neutron/proton ratio is therefore more useful for further constraining the symmetry energy of neutron-rich matter.

Robust Tensor Analysis With L1-Norm

Tensor analysis plays an important role in modern image and vision computing problems. Most of the existing tensor analysis approaches are based on the Frobenius norm, which makes them sensitive to outliers. In this paper, we propose L1-norm-based tensor analysis (TPCA-L1), which is robust to outliers. Experimental results upon face and other datasets demonstrate the advantages of the proposed approach.

Robust Tris-Cyclometalated Iridium(III) Phosphors with Ligands for Effective Charge Carrier Injection/Transport: Synthesis, Redox, Photophysical, and Electrophosphorescent Behavior

With the target to design and develop new functionalized green triplet light emitters that possess distinctive electronic properties for robust and highly efficient phosphorescent organic light-emitting diodes (PHOLEDs), a series of bluish-green to yellow-green phosphorescent tris-cyclometalated homoleptic iridium(III) complexes [Ir(ppy-X)(3)] (X=SiPh3, GePh3, NPh2, POPh2, OPh, SPh, SO2Ph, Hppy=2-phenylpyridine) have been synthesized and fully characterized by spectroscopic, redox, and photophysical methods