Quantification of 397 pesticide residues in different types of commercial teas: Validation of high accuracy methods and quality assessment

2022 ◽  
Vol 370 ◽  
pp. 130986
Author(s):  
Tuan-Kiet Ly ◽  
Philippe Behra ◽  
Tran-Thi Nhu-Trang
Keyword(s):  
Quality Assessment ◽  
Pesticide Residues ◽  
High Accuracy ◽  
Different Types

Squeak and rattle noise classification using radial basis function neural networks

2020 ◽  
Vol 68 (4) ◽  
pp. 283-293
Author(s):  
Oleksandr Pogorilyi ◽  
Mohammad Fard ◽  
John Davy ◽  
Mechanical and Automotive Engineering, School ◽  
Mechanical and Automotive Engineering, School ◽  
...  
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
High Accuracy ◽  
Training Method ◽  
Vehicle Interior ◽  
Trained Classifier ◽  
Different Types ◽  
Noise Classification ◽  
Automatic Tool ◽  
Multi Class Classification

In this article, an artificial neural network is proposed to classify short audio sequences of squeak and rattle (S&R) noises. The aim of the classification is to see how accurately the trained classifier can recognize different types of S&R sounds. Having a high accuracy model that can recognize audible S&R noises could help to build an automatic tool able to identify unpleasant vehicle interior sounds in a matter of seconds from a short audio recording of the sounds. In this article, the training method of the classifier is proposed, and the results show that the trained model can identify various classes of S&R noises: simple (binary clas- sification) and complex ones (multi class classification).

Fuzzified time-frequency method for identification and localization of power system faults

2021 ◽  
pp. 1-13
Author(s):  
Pullabhatla Srikanth ◽  
Chiranjib Koley
Keyword(s):  
Power System ◽  
High Accuracy ◽  
Fuzzy Decision ◽  
Frequency Method ◽  
Time Frequency ◽  
Novel Approach ◽  
S Transform ◽  
Different Types ◽  
Power System Faults ◽  
Frequency Magnitude

In this work, different types of power system faults at various distances have been identified using a novel approach based on Discrete S-Transform clubbed with a Fuzzy decision box. The area under the maximum values of the dilated Gaussian windows in the time-frequency domain has been used as the critical input values to the fuzzy machine. In this work, IEEE-9 and IEEE-14 bus systems have been considered as the test systems for validating the proposed methodology for identification and localization of Power System Faults. The proposed algorithm can identify different power system faults like Asymmetrical Phase Faults, Asymmetrical Ground Faults, and Symmetrical Phase faults, occurring at 20% to 80% of the transmission line. The study reveals that the variation in distance and type of fault creates a change in time-frequency magnitude in a unique pattern. The method can identify and locate the faulted bus with high accuracy in comparison to SVM.

scholarly journals Data-bearing halftone image alignment and assessment on 3D surface

2020 ◽  
Vol 2020 (15) ◽  
pp. 196-1-196-7 ◽  
Author(s):  
Ziyi Zhao ◽  
Yujian Xu ◽  
Robert Ulichney ◽  
Matthew Gaubatz ◽  
Stephen Pollard ◽  
...  
Keyword(s):  
Data Retrieval ◽  
High Accuracy ◽  
Image Alignment ◽  
Original Image ◽  
Halftone Image ◽  
3D Surface ◽  
Different Types ◽  
Alignment Problem ◽  
Halftone Images

An alignment approach for data-bearing halftone images, which are a visually pleasant alternative to barcodes, is proposed in this paper. In this paper, we address the alignment problem of data-bearing halftone images on a 3D surface. Different types of surfaces have been tested , using our proposed approach, and high accuracy results have been achieved. Additionally, we also develop a data retrieval tool from an aligned image, in order to decode the data embedded in the original image. A system to assess the accuracy of alignment is introduced to quantify the effectiveness of the proposed alignment approach.

scholarly journals Image Compression Based on Deep Learning: A Review

2021 ◽  
pp. 62-76
Author(s):  
Hajar Maseeh Yasin ◽  
Adnan Mohsin Abdulazeez
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Image Compression ◽  
Recurrent Neural Networks ◽  
Deep Neural Networks ◽  
Review Paper ◽  
High Accuracy ◽  
Machine Learning Methods ◽  
Digital Era ◽  
Different Types

Image compression is an essential technology for encoding and improving various forms of images in the digital era. The inventors have extended the principle of deep learning to the different states of neural networks as one of the most exciting machine learning methods to show that it is the most versatile way to analyze, classify, and compress images. Many neural networks are required for image compressions, such as deep neural networks, artificial neural networks, recurrent neural networks, and convolution neural networks. Therefore, this review paper discussed how to apply the rule of deep learning to various neural networks to obtain better compression in the image with high accuracy and minimize loss and superior visibility of the image. Therefore, deep learning and its application to different types of images in a justified manner with distinct analysis to obtain these things need deep learning.

scholarly journals Wood Surface Roughness Prediction Modeling Depending on Influential Cutting Variables

2021 ◽  
Vol 1208 (1) ◽  
pp. 012005
Author(s):  
Atif Hodžić ◽  
Elmasa Aldžić ◽  
Damir Hodžić
Keyword(s):  
Design Of Experiment ◽  
Roughness Parameter ◽  
Solid Wood ◽  
High Accuracy ◽  
R Software ◽  
Design Expert ◽  
Different Types ◽  
Roughness Prediction ◽  
Central Composite ◽  
Cutting Speeds

Abstract Paper presents the design of experiment and determining mathematical model to calculate roughness parameter of wood planned surface. For design of experiment three different types of solid wood were taken and processed on the planner with three different displacements and three different cutting speeds. After measuring the roughness parameter Rz, experimental results were obtained on the basis of which the central composite plan of the experiment was made. Based on that, a model of roughness parameter Rz was made, which is adequate and with high accuracy. The significance of the model coefficients was determined using the R software and the results were presented using the Design Expert software.

POLMICRO 2015 – Polish National External Quality Assessment Scheme in Microbiological Diagnostics

2016 ◽  
Vol 52 (1) ◽  
pp. 29-38
Author(s):  
Elżbieta Stefaniuk ◽  
Karolina Bosacka ◽  
Ewa Młodzińska ◽  
Anna Mikołajczyk ◽  
Waleria Chryniewicz ◽  
...  
Keyword(s):  
Quality Control ◽  
Quality Assessment ◽  
External Quality Assessment ◽  
Resistance Mechanisms ◽  
External Quality ◽  
External Quality Assessment Scheme ◽  
Microbiological Diagnostics ◽  
Different Types ◽  
Enteric Infections ◽  
Antibiotics Detection

In 2015 Centre for Quality Control in Microbiology (CQCM) conducted Polish National External Quality Assessment Scheme in Microbiological Diagnostics according to the requirements of PN-EN ISO/IEC 17043:2011. The CQCM organized two different types of proficiency programmes: one was designed for laboratories providing a broad spectrum of microbiological diagnostics and the second one was prepared for laboratories dealing with enteric infections only. The aim of the POLMICRO 2015 programme was to evaluate proficiency of laboratories in the identification of microorganisms, determination and clinical interpretation of bacterial susceptibility to antibiotics, detection of different resistance mechanisms and interpretation of Gram slides. The paper presents the results of the XXII edition of the Programme POLMICRO 2015.

Automatic Test System for the Basic Properties of Solar Cells

2012 ◽  
Vol 251 ◽  
pp. 26-30
Author(s):  
Jia Jia Tu ◽  
Guo Wei Liang
Keyword(s):  
Solar Cells ◽  
Real Time ◽  
Natural Environment ◽  
Environmental Conditions ◽  
High Accuracy ◽  
Test System ◽  
Automatic Test System ◽  
Basic Properties ◽  
Different Types ◽  
Accuracy And Repeatability

A solar cells test system that can be used in the natural environment is designed, which can complete a variety of test experiments on different types of solar cells under different environmental conditions. In the testing process, the basic properties of solar cells are given and recorded in real time. Since installed and operated, the system works stable. Experimental results show that the test system has high accuracy and repeatability, and in line with the requirements of solar cells testing.

scholarly journals A New Algorithm for Lane Level Irregular Driving Identification

2015 ◽  
Vol 68 (6) ◽  
pp. 1173-1194 ◽  
Author(s):  
Rui Sun ◽  
Washington Ochieng ◽  
Cheng Fang ◽  
Shaojun Feng
Keyword(s):  
Intelligent Transportation System ◽  
Fuzzy Inference ◽  
High Accuracy ◽  
Global Navigation Satellite Systems ◽  
Inference System ◽  
Satellite Systems ◽  
Motion Models ◽  
Driving Behaviour ◽  
Different Types ◽  
Global Navigation Satellite

Global Navigation Satellite Systems (GNSS) are used widely in the provision of Intelligent Transportation System (ITS) services. Today, there is an increasing demand on GNSS to support applications at lane level. These applications required at lane level include lane control, collision avoidance and intelligent speed assistance. In lane control, detecting irregular driving behaviour within the lane is a basic requirement for safety related lane level applications. There are two major issues involved in lane level irregular driving identification: access to high accuracy positioning and vehicle dynamic parameters, and extraction of erratic driving behaviour from this and other related information. This paper proposes an integrated algorithm for lane level irregular driving identification. Access to high accuracy positioning is enabled by GNSS and its integration with an Inertial Navigation System (INS) using filtering with precise vehicle motion models and lane information. The identification of irregular driving behaviour is achieved by algorithms developed for different types of events based on the application of a Fuzzy Inference System (FIS). The results show that decimetre level accuracy can be achieved and that different types of lane level irregular driving behaviour can be identified.

A New Tightening Technique for Threaded Fasteners

1994 ◽  
Vol 116 (2) ◽  
pp. 64-69 ◽  
Author(s):  
M. Hagiwara ◽  
N. Ohashi
Keyword(s):  
Rotation Angle ◽  
High Accuracy ◽  
Experimental Results ◽  
New Technique ◽  
Relative Rotation ◽  
Threaded Fasteners ◽  
Accuracy And Precision ◽  
Different Types ◽  
A New Technique

A new technique for tightening threaded fasteners was proposed aiming to assure the quality and the reliability in the tightening operations. The technique is based on the torque difference and the relative rotation angle in tightening and loosening process, and no preliminary experiment is required. Repeated tightening (and loosening) experiments were performed for different types of lubricant to verify the applicability of this technique. Experimental results show that the preload provided to the joint can be estimated with high accuracy and precision by this technique, and the possibility to boost the reliability of tightening control is confirmed.

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