X-Ray Testing of Weld Defect of Automatic Recognit Ion and Alarm Technology Research

2014 ◽  
Vol 472 ◽  
pp. 495-502 ◽  
Author(s):  
Peng Lin Zhang ◽  
Zhi Qiang Zhao ◽  
Yan Ping Wang
Keyword(s):  
Extraction Procedure ◽  
Dynamic Test ◽  
Extraction Methods ◽  
Technology Research ◽  
Gray Scale ◽  
X Ray ◽  
Signal Characteristics ◽  
Starting Point ◽  
Weld Defect ◽  
Defect Signal

This essay based on X-ray digital automatic detection as a starting point, and then to deal the typical X-ray digital image with median filtering and histogram threshold processing, with the help of a column gray method to extract respective column of each weld image gray scale curve, this essay tries to analyze the defect signal characteristics and discuss the extraction methods. In this essay, the author compiles the image preprocessing procedure, columns, gray-scale extraction procedure and defect alarm procedures; and also tries the X-ray weld defect detection of digital rapid recognition and prompt functions. Thorough the analysis we can draw the conclusion that column gray method can be used as a dynamic test basis of automatic alarm decision.

Embracing Uncertainty: Modeling Uncertainty in EPMA—Part II

2021 ◽  
Vol 27 (1) ◽  
pp. 74-89
Author(s):  
Nicholas W.M. Ritchie
Keyword(s):  
Beam Energy ◽  
Uncertainty Modeling ◽  
Matrix Correction ◽  
Correction Model ◽  
X Ray ◽  
Starting Point ◽  
Uncertainty Calculation ◽  
The Matrix ◽  
Measurement Design ◽  
New Framework

AbstractThis, the second in a series of articles present a new framework for considering the computation of uncertainty in electron excited X-ray microanalysis measurements, will discuss matrix correction. The framework presented in the first article will be applied to the matrix correction model called “Pouchou and Pichoir's Simplified Model” or simply “XPP.” This uncertainty calculation will consider the influence of beam energy, take-off angle, mass absorption coefficient, surface roughness, and other parameters. Since uncertainty calculations and measurement optimization are so intimately related, it also provides a starting point for optimizing accuracy through choice of measurement design.

Acidic Aqueous Extraction of Hypothalamic Luteinizing Hormone Releasing Hormone to Study Biological Effects

1974 ◽  
Vol 52 (3) ◽  
pp. 754-758 ◽  
Author(s):  
S. H. Shin ◽  
C. J. Howitt
Keyword(s):  
Luteinizing Hormone ◽  
Biological Effects ◽  
Extraction Procedure ◽  
Extraction Methods ◽  
Water Soluble ◽  
Acid Extraction ◽  
Luteinizing Hormone Releasing Hormone ◽  
Releasing Hormone ◽  
Aqueous Solvent ◽  
Lh Rh

Several aqueous solvent systems were tested for their efficiency in extracting luteinizing hormone releasing hormone (LH-RH) from rat hypothalamus. Although LH-RH is a water-soluble decapeptide, neutral distilled water extracted only 10% of the LH-RH obtained using acid extraction methods. The efficiency of the acid extraction procedure suggests that in the hypothalamus the releasing hormone is bound to a relatively large molecular weight compound. Using the acidic extraction procedure, we found that hypothalamic LH-RH content is significantly lower in the castrated animal than in the normal rat.

scholarly journals Evolving Deep Learning Convolutional Neural Networks for Early COVID-19 Detection in Chest X-ray Images

Mathematics ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1002
Author(s):  
Mohammad Khishe ◽  
Fabio Caraffini ◽  
Stefan Kuhn
Keyword(s):  
Deep Learning ◽  
Early Detection ◽  
Iterative Process ◽  
High Accuracy ◽  
X Ray ◽  
Starting Point ◽  
Reliable Model ◽  
Minimum Number ◽  
Chest X Ray ◽  
Deep Learning Model

This article proposes a framework that automatically designs classifiers for the early detection of COVID-19 from chest X-ray images. To do this, our approach repeatedly makes use of a heuristic for optimisation to efficiently find the best combination of the hyperparameters of a convolutional deep learning model. The framework starts with optimising a basic convolutional neural network which represents the starting point for the evolution process. Subsequently, at most two additional convolutional layers are added, at a time, to the previous convolutional structure as a result of a further optimisation phase. Each performed phase maximises the the accuracy of the system, thus requiring training and assessment of the new model, which gets gradually deeper, with relevant COVID-19 chest X-ray images. This iterative process ends when no improvement, in terms of accuracy, is recorded. Hence, the proposed method evolves the most performing network with the minimum number of convolutional layers. In this light, we simultaneously achieve high accuracy while minimising the presence of redundant layers to guarantee a fast but reliable model. Our results show that the proposed implementation of such a framework achieves accuracy up to 99.11%, thus being particularly suitable for the early detection of COVID-19.

scholarly journals PERBANDINGAN IDENTIFIKASI PEMBICARA MENGGUNAKAN MFCC DAN SBC DENGAN CIRI PENCOCOKAN LBG-VQ

2018 ◽  
Author(s):  
Purwono Prasetyawan
Keyword(s):  
Feature Extraction ◽  
Human Behavior ◽  
Vector Quantization ◽  
Speaker Identification ◽  
Extraction Methods ◽  
Behavioral Characteristics ◽  
Physical Analysis ◽  
Test Results ◽  
Voice Signal ◽  
Signal Characteristics

Biometrics is a technology for physical analysis and human behavior used in authentication. One of the behavioral characteristics associated with a person is sound. A person's voice can be identified based on the person's voice signal characteristics. There are several methods in recognizing speaker sound, such as with Mel Frequency Cepstrum Calculation (MFCC) and Subband Based Cepstral (SBC). This study looked for the effectiveness of the use of MFCC and SBC feature extraction with LBG Vector Quantization matching characteristics. Effective feature extraction methods will be tested for realtime speaker identification. The results obtained from this research is the value of MFCC 32 coefficient more effective than the SBC accurately and the speed of the process of identification of both text-dependent and text-independent speaker. The test results of speaker identification in realtime using MFCC is still not satisfactory because the accuracy of recognition is still below 70%.

scholarly journals Evaluation of effective protein extraction procedure to profile petiole of Moringa oleifera

2020 ◽  
Vol 7 (2) ◽  
pp. 214
Author(s):  
Zetty Amirah Zulkifli ◽  
Zaidah Rahmat
Keyword(s):  
Moringa Oleifera ◽  
Protein Extraction ◽  
Polyacrylamide Gel Electrophoresis ◽  
Sodium Dodecyl ◽  
Extraction Procedure ◽  
Electrophoretic Pattern ◽  
Antioxidant Property ◽  
Extraction Methods ◽  
Protein Profiling ◽  
Sds Page

Moringa oleifera is widely known as multipurpose tree since all of its parts confer multiple functions. The leaf is highly favourable among consumers while the petiole is mostly wasted. There are numerous studies on the flavonoid and antioxidant property of the stem and twig. However, study on the petiole has never been done. There-upon, this study was conducted to develop protein profiling of the petiole. In this study, 6 different protein extraction methods were tested on the fresh petiole before its protein quantity and quality were checked via Bradford assay and Sodium Dodecyl Sulfate Polyacrylamide Gel Electrophoresis (SDS-PAGE) respectively. The in-solution digestion was then done prior to LC-MS/MS analysis. The protein electrophoretic pattern from the SDS-PAGE proves that method 6 using Tris HCl buffer with incorporation of dithiothreitol (DTT) and phenylmethylsulfonyl fluoride (PMSF) confers the best quality of protein. It produced the highest number of visible individual bands compared to other methods. Meanwhile, 93 proteins were successfully identified via LCMS analysis where the protein, signal response and carbohydrate metabolism categories confer the highest percentage. High quality and content of the protein extracted from the petiole including the antioxidant, anticancer and antidiabetic protein identified suggested that consuming this part of the plant could enhance nutrients of human body.

scholarly journals Structural and functional characterization of proteins from the fire blight pathogen Erwinia amylovora. A review on the state of the art

2020 ◽  
Author(s):  
Stefano Benini
Keyword(s):  
Fire Blight ◽  
Erwinia Amylovora ◽  
Functional Characterization ◽  
Data Bank ◽  
Knock Out ◽  
X Ray ◽  
X Ray Crystallography ◽  
Starting Point ◽  
Good Starting Point

Abstract Together with genome analysis and knock-out mutants, structural and functional characterization of proteins provide valuable hints on the biology of the organism under investigation. Structural characterization can be achieved by techniques such as X-ray crystallography, NMR, Cryo-EM. The information derived from the structure are a good starting point to comprehend the details of the proteins molecular function for a better understanding of their biological role. This review aims at describing the progress in the structural and functional characterization of proteins from the plant pathogen Erwinia amylovora obtained by structural biology and currently deposited in the Protein Data Bank.

Molecular X-ray Spectra of Sulfur and Chlorine Bearing Substances

1970 ◽  
Vol 14 ◽  
pp. 453-486 ◽  
Author(s):  
G. Andermann ◽  
H. C. Whitehead
Keyword(s):  
Theoretical Models ◽  
Quantum Mechanical ◽  
Quantum Mechanical Calculations ◽  
Molecular Models ◽  
X Ray ◽  
Starting Point ◽  
State Models ◽  
Basic Features ◽  
Photon Spectra ◽  
Molecular Bonding

AbstractThe interpretation and use of x-ray photon spectra of substances containing second row elements has utilized a number of theoretical models. These models may be divided into three basic categories, namely, the isolated atom model, various molecular models, and a number of solid state models, it is the purpose of this paper to examine critically the validity and limitations of molecular models for interpreting published x-ray photon spectra and spectra obtained by this group on chlorine and sulfur bearing substances.Chlorine and sulfur bearing substances were chosen for at least three important reasons. First, a great deal of published experimental data already exists on the Kα, Kβ, and L2, 3 transitions of these substances. Second, motivated in part by the long standing controversy concerning possible 3d orbital participation in the bonding of second row elements, there are extensive quantum mechanical calculations for ions containing sulfur and chlorine via simple molecular orbital concepts. Thirdj the availability of accurate photoelectron spectroscopic data on these substances now permits a detailed quantitative comparison of x-ray photon transitions with quantum mechanical calculations.Detailed evaluation along these lines indicates that for many substances the theoretically calculated energy values are frequently within a few electron volts (or less) of the experimentally observed energies. This study, therefore, tends to substantiate a viewpoint suggested by some recently; namely, that for many substances the starting point in interpreting most of the basic features of soft x-ray spectra should be based upon molecular bonding approaches.

Quantitation and Confirmation of Chloramphenicol, Florfenicol, and Nitrofuran Metabolites in Honey Using LC-MS/MS

2018 ◽  
Vol 101 (3) ◽  
pp. 897-903 ◽  
Author(s):  
Brian T Veach ◽  
Renea Anglin ◽  
Thilak K Mudalige ◽  
Paula J Barnes
Keyword(s):  
Extraction Procedure ◽  
Extraction Methods ◽  
Liquid Extraction ◽  
Tandem Ms ◽  
Robust Method ◽  
Calibration Standards ◽  
Single Extraction ◽  
Liquid Liquid Extraction ◽  
Lc Tandem Ms ◽  
Nitrofuran Metabolites

Abstract This paper describes a rapid and robust method utilizing a single liquid–liquid extraction for the quantitation and confirmation of chloramphenicol, florfenicol, and nitrofuran metabolites in honey. This methodology combines two previous extraction methods into a single extraction procedure and utilizes matrix-matched calibration standards and stable isotopically labeled standards to improve quantitation. The combined extraction procedure reduces the average extraction time by >50% when compared with previously used procedures. The drug residues were determined using two separate LC-tandem MS conditions. Validation of all the analytes was performed, with average quantitation ranging from 92 to 105% for all analytes and the RSDs for all analytes being ≤12%.

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