scholarly journals Supervised Learning in image enhance from electron microscopy inversion results

2022 ◽  
Author(s):  
Georgios Stagakis
Keyword(s):  
Electron Microscope ◽  
Material Science ◽  
Bayesian Learning ◽  
Test Sample ◽  
Sem Images ◽  
Material Density ◽  
Learning Framework ◽  
Image Enhance ◽  
Gaussian Stochastic Processes ◽  
Density Results

Abstract In Nondestructive testing there is a variety of applications in Material Science, where the specimen is imaged by an Electron Microscope and then by image inversion, informationis extracted for the material interior. This type of information might contain noise either by the imaging procedure or by the numerical part of the inversion. We present a method that can improve the interior density results of an inversed material from a series of Scanning Electron Microscope (SEM) images. For this method, the material density can contain some discontinuity, such as regions where it is dense and regions where there are voids.The proposed method directly stands on the Bayesian learning framework, adopting Gaussian Stochastic Processes (GSPs). Two test sample cases that contain some discontinuities in the density are tested. We also provide a comparison between two different GSP modelling approaches; one is a typical GSP and the other accounts for discontinuity, by introducing hyperparameters. The GSP method gives reconstructed data in reasonable agreement with the known original density distribution, giving confidence that the method can be applied to experimentally obtained SEM images.

scholarly journals Fabrication of Mesostructured Silica and Titania Rods on Substrates by Using Polycarbonate Membranes

2010 ◽  
Vol 2010 ◽  
pp. 1-4 ◽  
Author(s):  
Norihiro Suzuki ◽  
Yusuke Yamauchi
Keyword(s):  
Electron Microscope ◽  
Longitudinal Axis ◽  
Sem Images ◽  
One Pot ◽  
Polycarbonate Membrane ◽  
Entire Area ◽  
Transmission Electron ◽  
Polycarbonate Membranes ◽  
Fibrous Morphology ◽  
Oriented Parallel

By using the polycarbonate membrane a template, mesoporous silica rods are fabricated on a silicon substrate in one pot. From scanning electron microscope (SEM) images, the creation of fibrous morphology is confirmed over the entire area. The diameter of the obtained rods is consistent with that of the template. Transmission electron microscope (TEM) images revealed that the tubular mesochannels are uniaxially oriented parallel to the longitudinal axis of the silica rods. The mesoporous titania rods with anatase crystalline frameworks are also fabricated.

The Photoluminescence Enhancement and Stability of Porous Silicon by Cathodic Reduction and Acid Treatment

2014 ◽  
Vol 887-888 ◽  
pp. 458-461
Author(s):  
Chang Qing Li ◽  
Kun Wang ◽  
Pei Jia Liu ◽  
Qi Ming
Keyword(s):  
Electron Microscope ◽  
Porous Silicon ◽  
Acid Treatment ◽  
Cathodic Reduction ◽  
Luminescence Properties ◽  
Sem Images ◽  
Photoluminescence Enhancement ◽  
The Stability ◽  
Scanning Electron ◽  
Cathode Reduction

Porous silicon (PSi) was fabricated by using electrochemical anodic etching method. Then acid treatment and cathode reduction treatment were employed to improve the luminescence properties and stability of PSi material. Photoluminescence (PL) measurements and scanning electron microscope (SEM) were used to observe the luminescence properties and microstructure of samples, respectively. The results of PL measurements showed that the PL intensity and the stability of luminescence of samples after cathodic reduction and acid treatment were significantly improved. The SEM images showed that the porosity of PSi may be increased through the cathodic reduction treated.

Minimizing Segregation in Bunkers

1973 ◽  
Vol 95 (1) ◽  
pp. 81-85 ◽  
Author(s):  
K. Clague ◽  
H. Wright
Keyword(s):  
Particle Size ◽  
Flow Regime ◽  
Mass Flow ◽  
Raw Materials ◽  
Model Tests ◽  
Material Density ◽  
Filling Method ◽  
Density Results

Bunkers used in steelworks sinter plants and other applications need to be designed and operated so that the feed emerging is unsegregated. A series of model tests has been carried out to discover which bunker shape, flow regime, and filling method give the least segregation for raw materials of different particle size and density. Results are compared with results from larger bunkers. The main conclusions are that an evenly-filled wedge-shaped mass-flow bunker is best at preventing segregation and that material density has little effect.

The DMT Power Line Channel Sparse Bayesian Regression Estimation Based on Communication System

2014 ◽  
Vol 960-961 ◽  
pp. 1308-1311
Author(s):  
Yi Pei Huang ◽  
Ya Jun Han ◽  
Bao Fan Chen
Keyword(s):  
Channel Estimation ◽  
Bayesian Learning ◽  
Estimation Method ◽  
Power Line ◽  
Previous Method ◽  
Bayesian Regression ◽  
Estimation Model ◽  
Power Line Communications ◽  
Learning Framework ◽  
Performance Curves

This paper introduces the power line communications channel estimation method based on sparse Bayesian regression, it is through the use of Bayesian learning framework that provides a sparse model in the presence of noise accurate channel estimation model. Improved channel estimation using the power line for the system to consider the frequency domain equalization (FREQ) transmitter and receiver, the bit error rate and comparing the two methods for generating various channel estimation techniques, and (BER) performance curves simulation the results show that the performance of the method is better than the previous method of least squares technique.

Determination of Rate of Medical Waste Generation Using RVM, MARS and MPMR

2016 ◽  
pp. 1-18
Author(s):  
Jagan J. ◽  
Pijush Samui ◽  
Barnali Dixon
Keyword(s):  
Bayesian Learning ◽  
Piecewise Linear ◽  
Regression Function ◽  
Relevance Vector Machine ◽  
Medical Waste ◽  
Waste Generation ◽  
Learning Framework ◽  
Adaptive Regression ◽  
Regression Techniques

The prediction of medical waste generation is an important task in hospital waste management. This article uses Relevance Vector Machine (RVM), Multivariate Adaptive Regression Spline (MARS) and Minimax Probability Machine Regression (MPMR) for prediction of rate of medical waste generation. Type of hospital, Capacity and Bed Occupancy has been used as inputs of RVM, MARS and MPMR. RVM is a probabilistic bayesian learning framework. MARS builds flexible model by using piecewise linear regressions. MPMR maximizes the minimum probability that future predicted outputs of the regression model will be within some bound of the true regression function. MARS, RVM and MPMR have been used as regression techniques. The results show that the developed RVM, MPMR and MARS give excellent models for determination of rate of medical waste generation.

The Energy Spectra of Secondary Electrons

2000 ◽  
Vol 6 (S2) ◽  
pp. 750-751
Author(s):  
David C Joy ◽  
David Braski
Keyword(s):  
Surface Layer ◽  
Electron Microscope ◽  
Secondary Electron ◽  
High Vacuum ◽  
Ultra High Vacuum ◽  
Energy Spectra ◽  
Yield Coefficient ◽  
Sem Images ◽  
Secondary Electrons ◽  
Scanning Electron

It has been estimated that more than 90% of all scanning electron microscope (SEM) images ever published have been obtained using secondary electrons (SE) which are defined as being those electrons emitted with energies between 0 and 50eV. The properties of these secondary electron are therefore of considerable interest and importance. However, although secondary electrons have been intensively studied since their discovery by Starke in 1901 the majority of the work has been aimed at determining the SE yield coefficient and its variation with energy for elements and compounds. The energy spectrum of secondary electrons has received far less attention although it is evident that the form of the spectrum must have an effect on the image contrast observed in the SEM because SE detectors are energy selective devices. The few studies that have been made have mostly concentrated on spectra obtained from clean samples observed under ultra-high vacuum conditions. This is understandable, because it is certain that the presence of a surface layer of contamination will change the SE spectrum to some degree or other, but it is unfortunate because all specimens in real SEMs are dirty and it is information about this situation that is required.

Effect of Deposition Potential and Bath Temperature on One-Step Electrochemical Synthesis of One and Two Dimensional Nanostructured ZnO Thin Films on Fluorine Doped Tin Oxide Substrates

2019 ◽  
Vol 19 (11) ◽  
pp. 7014-7025 ◽  
Author(s):  
T. Marimuthu ◽  
N. Anandhan ◽  
R. Thangamuthu ◽  
S. Surya ◽  
R. Panneerselvam ◽  
...  
Keyword(s):  
Electron Microscope ◽  
Film Thickness ◽  
Tin Oxide ◽  
Electrochemical Impedance ◽  
Dye Sensitized Solar Cells ◽  
Deposition Potential ◽  
Zno Films ◽  
Zinc Hydroxide ◽  
Sem Images ◽  
Zinc Deposition

Different zinc oxide (ZnO) morphologies such as platelets, nanowalls and nanorods were electrochemically synthesized on fluorine doped tin oxide (FTO) substrates by varying the deposition potentials and bath temperatures, respectively. Cyclic voltammetry (CV) curves reveal that ZnO deposition potentials are decreased as the bath temperatures are increased. X-ray diffraction (XRD) patterns and transmission electron microscope (TEM) images confirm that the synthesized ZnO nanostructures are hexagonal wurtzite structure. The XRD results reveal that the crystallinity of the films is increased when ZnO deposition potentials and temperatures are increased. Field emission scanning electron microscope (FE-SEM) images display platelets, nanowalls and nanorods structures for films synthesized -1.1 V, -1.2 V and -1.3 V respectively. The increase in deposition potential not only increases the growth rate of ZnO with metallic zinc deposition, but also decreases zinc hydroxide chloride hydrate. Fourier transform infrared microscope (FTIR) spectra confirm that the formation of zinc hydroxide (Zn(OH)2) is decreased as the bath temperatures are increased from 30 to 70 °C. Photoluminescence (PL) spectra depict that the crystal quality of the ZnO films are notably improved as the bath temperatures are increased. The film thickness is increased as the deposition potentials and bath temperatures are increased. The dye absorbance is increased with respect to the film thickness. The efficiencies of dye sensitized solar cells (DSSCs) fabricated with diverse morphologies such as platelets, nanowalls and nanorods are found to be 0.10, 0.49 and 0.47%, respectively. Electrochemical impedance spectroscopy (EIS) spectra reveal that the charge transfer recombination resistance (Rrec) is continuously decreased as metal zinc deposition is increased in ZnO films with increase in deposition potentials.

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