scholarly journals An Image Reconstruction Framework for Characterizing Early Vision

2021 ◽  
Author(s):  
Ling-Qi Zhang ◽  
Nicolas P. Cottaris ◽  
David H. Brainard
Keyword(s):  
Image Reconstruction ◽  
Ideal Observer ◽  
Early Vision ◽  
Practical Applications ◽  
Cone Mosaic ◽  
Wide Range ◽  
Statistical Regularities ◽  
Observer Model ◽  
Ideal Observer Analysis ◽  
Bayesian Image Reconstruction

We developed an image-computable observer model of the early visual system that operates on fully naturalistic input, based on a framework of Bayesian image reconstruction from retinal cone mosaic excitations. Our model extends previous work on ideal observer analysis and the evaluation of performance beyond psychophysical discrimination tasks, takes into account the statistical regularities of our visual environment, and provides a unifying framework for answering a wide range of questions regarding early vision. Using the error in the reconstruction as a metric, we analyzed the variations of the number of different photoreceptor types on human retina as an optimal design problem. In addition, the reconstructions allow both visualization and quantification of information loss due to physiological optics and cone mosaic sampling, and how these vary with eccentricity. Furthermore, in simulations of color deficiencies and interferometric experiments, we found that the reconstructed images provide a reasonable proxy for directly modeling subjects' percepts. Lastly, we used the reconstruction-based observer for the analysis of psychophysical threshold, and found notable interactions between spatial frequency and chromatic direction in the resulting spatial contrast sensitivity function. Our method should be widely applicable to many experiments and practical applications in which early vision plays an important role.

A New Detector System For The HB5 Stem Instrument

1985 ◽  
Vol 43 ◽  
pp. 134-135
Author(s):  
J.M. Cowley
Keyword(s):  
Dark Field ◽  
Detector System ◽  
Electron Holography ◽  
Small Specimen ◽  
Bright Field ◽  
Multiple Images ◽  
Practical Applications ◽  
Wide Range ◽  
Diffraction Patterns ◽  
Operational Modes

The HB5 STEM instrument at ASU has been modified previously to include an efficient two-dimensional detector incorporating an optical analyser device and also a digital system for the recording of multiple images. The detector system was built to explore a wide range of possibilities including in-line electron holography, the observation and recording of diffraction patterns from very small specimen regions (having diameters as small as 3Å) and the formation of both bright field and dark field images by detection of various portions of the diffraction pattern. Experience in the use of this system has shown that sane of its capabilities are unique and valuable. For other purposes it appears that, while the principles of the operational modes may be verified, the practical applications are limited by the details of the initial design.

Object Detection Using an Ideal Observer Model

2020 ◽  
Vol 2020 (16) ◽  
pp. 41-1-41-7
Author(s):  
Orit Skorka ◽  
Paul J. Kane
Keyword(s):  
Object Detection ◽  
Matched Filter ◽  
Image Sensors ◽  
Ideal Observer ◽  
Noise Power ◽  
Relative Evaluation ◽  
Detection And Identification ◽  
Cross Correlation Analysis ◽  
Observer Model ◽  
The Ideal

Many of the metrics developed for informational imaging are useful in automotive imaging, since many of the tasks – for example, object detection and identification – are similar. This work discusses sensor characterization parameters for the Ideal Observer SNR model, and elaborates on the noise power spectrum. It presents cross-correlation analysis results for matched-filter detection of a tribar pattern in sets of resolution target images that were captured with three image sensors over a range of illumination levels. Lastly, the work compares the crosscorrelation data to predictions made by the Ideal Observer Model and demonstrates good agreement between the two methods on relative evaluation of detection capabilities.

scholarly journals Ring-Forming Polymerization toward Perfluorocyclobutyl and Ortho-Diynylarene-Derived Materials: From Synthesis to Practical Applications

Materials ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1486
Author(s):  
Eugene B. Caldona ◽  
Ernesto I. Borrego ◽  
Ketki E. Shelar ◽  
Karl M. Mukeba ◽  
Dennis W. Smith
Keyword(s):  
Chemical Resistance ◽  
Structural Features ◽  
Review Article ◽  
Aryl Ether ◽  
Aromatic Rings ◽  
Practical Applications ◽  
Repeat Units ◽  
Wide Range ◽  
Synthetic Routes ◽  
The Cost

Many desirable characteristics of polymers arise from the method of polymerization and structural features of their repeat units, which typically are responsible for the polymer’s performance at the cost of processability. While linear alternatives are popular, polymers composed of cyclic repeat units across their backbones have generally been shown to exhibit higher optical transparency, lower water absorption, and higher glass transition temperatures. These specifically include polymers built with either substituted alicyclic structures or aromatic rings, or both. In this review article, we highlight two useful ring-forming polymer groups, perfluorocyclobutyl (PFCB) aryl ether polymers and ortho-diynylarene- (ODA) based thermosets, both demonstrating outstanding thermal stability, chemical resistance, mechanical integrity, and improved processability. Different synthetic routes (with emphasis on ring-forming polymerization) and properties for these polymers are discussed, followed by their relevant applications in a wide range of aspects.

scholarly journals Sensing of Nickel(II) Ions by Immobilizing Ligands and Using Different SPEs

2021 ◽  
Vol 6 (1) ◽  
pp. 2
Author(s):  
Liliana Anchidin-Norocel ◽  
Sonia Amariei ◽  
Gheorghe Gutt
Keyword(s):  
Bismuth Oxide ◽  
Human Population ◽  
Raw Materials ◽  
Sensor Technology ◽  
Cyclic Voltammogram ◽  
Accurate Analysis ◽  
Nickel Allergy ◽  
Nickel Ions ◽  
Practical Applications ◽  
Wide Range

The aim of this paper is the development of a sensor for the quantification of nickel ions in food raw materials and foods. It is believed that about 15% of the human population suffers from nickel allergy. In addition to digestive manifestations, food intolerance to nickel may also have systemic manifestations, such as diffuse dermatitis, diffuse itching, fever, rhinitis, headache, altered general condition. Therefore, it is necessary to control this content of nickel ions for the health of the human population by developing a new method that offers the advantages of a fast, not expensive, in situ, and accurate analysis. For this purpose, bismuth oxide-screen-printed electrodes (SPEs) and graphene-modified SPEs were used with a very small amount of dimethylglyoxime and amino acid L-histidine that were deposited. A potentiostat that displays the response in the form of a cyclic voltammogram was used to study the electrochemical properties of nickel standard solution with different concentrations. The results were compared and the most sensitive sensor proved to be bismuth oxide-SPEs with dimethylglyoxime (Bi2O3/C-dmgH2) with a linear response over a wide range (0.1–10 ppm) of nickel concentrations. Furthermore, the sensor shows excellent selectivity in the presence of common interfering species. The Bi2O3/C-dmgH2 sensor showed good viability for nickel analysis in food samples (cocoa, spinach, cabbage, and red wine) and demonstrated significant advancement in sensor technology for practical applications.

scholarly journals Assessment of Linearization Approaches for Multibody Dynamics Formulations

2017 ◽  
Vol 12 (4) ◽  
Author(s):  
Francisco González ◽  
Pierangelo Masarati ◽  
Javier Cuadrado ◽  
Miguel A. Naya
Keyword(s):  
Mechanical System ◽  
Multibody Dynamics ◽  
Equations Of Motion ◽  
Differential Algebraic Equations ◽  
Algebraic Equations ◽  
Practical Applications ◽  
Linearization Methods ◽  
Highly Nonlinear ◽  
Wide Range ◽  
The Way

Formulating the dynamics equations of a mechanical system following a multibody dynamics approach often leads to a set of highly nonlinear differential-algebraic equations (DAEs). While this form of the equations of motion is suitable for a wide range of practical applications, in some cases it is necessary to have access to the linearized system dynamics. This is the case when stability and modal analyses are to be carried out; the definition of plant and system models for certain control algorithms and state estimators also requires a linear expression of the dynamics. A number of methods for the linearization of multibody dynamics can be found in the literature. They differ in both the approach that they follow to handle the equations of motion and the way in which they deliver their results, which in turn are determined by the selection of the generalized coordinates used to describe the mechanical system. This selection is closely related to the way in which the kinematic constraints of the system are treated. Three major approaches can be distinguished and used to categorize most of the linearization methods published so far. In this work, we demonstrate the properties of each approach in the linearization of systems in static equilibrium, illustrating them with the study of two representative examples.

Periodic wavelet descriptor of plant leaf and its application in botany

2015 ◽  
Vol 13 (06) ◽  
pp. 1550043 ◽  
Author(s):  
Qing-Mao Zeng ◽  
Tong-Lin Zhu ◽  
Xue-Ying Zhuang ◽  
Ming-Xuan Zheng
Keyword(s):  
Species Identification ◽  
Plant Species ◽  
Shape Descriptor ◽  
Plant Leaf ◽  
Practical Applications ◽  
Wide Range ◽  
Periodic Wavelet ◽  
Plant Species Identification ◽  
Botanical Research ◽  
Wavelet Descriptor

Leaf is one of the most important organs of plant. Leaf contour or outline, usually a closed curve, is a fundamental morphological feature of leaf in botanical research. In this paper, a novel shape descriptor based on periodic wavelet series and leaf contour is presented, which we name as Periodic Wavelet Descriptor (PWD). The PWD of a leaf actually expresses the leaf contour in a vector form. Consequently, the PWD of a leaf has a wide range in practical applications, such as leaf modeling, plant species identification and classification, etc. In this work, the plant species identification and the leaf contour reconstruction, as two practical applications, are discussed to elaborate how to employ the PWD of a plant leaf in botanical research.

Long-offset moveout for VTI using Padé approximation

Geophysics ◽  
2016 ◽  
Vol 81 (5) ◽  
pp. C219-C227 ◽  
Author(s):  
Hanjie Song ◽  
Yingjie Gao ◽  
Jinhai Zhang ◽  
Zhenxing Yao
Keyword(s):  
Padé Approximation ◽  
Pade Approximation ◽  
Practical Applications ◽  
Long Offset ◽  
Wide Range ◽  
Isotropic Media ◽  
Transversally Isotropic ◽  
Error Accumulation ◽  
Anisotropy Parameters ◽  
Vti Media

The approximation of normal moveout is essential for estimating the anisotropy parameters of the transversally isotropic media with vertical symmetry axis (VTI). We have approximated the long-offset moveout using the Padé approximation based on the higher order Taylor series coefficients for VTI media. For a given anellipticity parameter, we have the best accuracy when the numerator is one order higher than the denominator (i.e., [[Formula: see text]]); thus, we suggest using [4/3] and [7/6] orders for practical applications. A [7/6] Padé approximation can handle a much larger offset and stronger anellipticity parameter. We have further compared the relative traveltime errors between the Padé approximation and several approximations. Our method shows great superiority to most existing methods over a wide range of offset (normalized offset up to 2 or offset-to-depth ratio up to 4) and anellipticity parameter (0–0.5). The Padé approximation provides us with an attractive high-accuracy scheme with an error that is negligible within its convergence domain. This is important for reducing the error accumulation especially for deeper substructures.

Application of neural networks in membrane separation

2020 ◽  
Vol 36 (2) ◽  
pp. 265-310 ◽  
Author(s):  
Morteza Asghari ◽  
Amir Dashti ◽  
Mashallah Rezakazemi ◽  
Ebrahim Jokar ◽  
Hadi Halakoei
Keyword(s):  
Neural Networks ◽  
Chemical Engineering ◽  
Membrane Separation ◽  
Mechanistic Model ◽  
Computing Time ◽  
Permeate Flux ◽  
Practical Applications ◽  
Advantages And Disadvantages ◽  
Wide Range ◽  
Physical And Chemical

AbstractArtificial neural networks (ANNs) as a powerful technique for solving complicated problems in membrane separation processes have been employed in a wide range of chemical engineering applications. ANNs can be used in the modeling of different processes more easily than other modeling methods. Besides that, the computing time in the design of a membrane separation plant is shorter compared to many mass transfer models. The membrane separation field requires an alternative model that can work alone or in parallel with theoretical or numerical types, which can be quicker and, many a time, much more reliable. They are helpful in cases when scientists do not thoroughly know the physical and chemical rules that govern systems. In ANN modeling, there is no requirement for a deep knowledge of the processes and mathematical equations that govern them. Neural networks are commonly used for the estimation of membrane performance characteristics such as the permeate flux and rejection over the entire range of the process variables, such as pressure, solute concentration, temperature, superficial flow velocity, etc. This review investigates the important aspects of ANNs such as methods of development and training, and modeling strategies in correlation with different types of applications [microfiltration (MF), ultrafiltration (UF), nanofiltration (NF), reverse osmosis (RO), electrodialysis (ED), etc.]. It also deals with particular types of ANNs that have been confirmed to be effective in practical applications and points out the advantages and disadvantages of using them. The combination of ANN with accurate model predictions and a mechanistic model with less accurate predictions that render physical and chemical laws can provide a thorough understanding of a process.

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