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Article | 30-July-2021

Comparison of the static frictional resistance and surface topography of ceramic orthodontic brackets: an in vitro study

Objectives: The aim of this study was to investigate the frictional resistance (FR) and surface topography of newly available polycrystalline alumina (PCA) ceramic brackets characterised by a yttria-stabilised zirconia (YSZ) coating of the slots, compared with monocrystalline alumina (MCA) ceramic brackets and stainless steel (SS) brackets. Methods: The FR was investigated using a universal testing machine. The test groups included PCA (Clarity Advanced, 3M Unitek, CA, USA) and MCA (Inspire Ice

Mai AlSubaie, Nabeel Talic

Australasian Orthodontic Journal, Volume 33 , ISSUE 1, 24–34

research-article | 30-November-2019

An integrative approach to the study of Helicotylenchus (Nematoda: Hoplolaimidae) Colombian and Brazilian populations associated with Musa crops

, Lymington UK, 1995) with principal components analysis (PCA) and conglomerate analysis to determine groupings and evaluate those characters that could discriminate species. Extraction, amplification, and DNA sequencing For molecular analysis, DNA was extracted by the Proteinase K method of Múnera et al. (2009) with modifications. A single nematode was crushed with a sterile scalpel and transferred to an Eppendorf tube with 15 µl of worm lysis buffer (50 mM KCl, 10 mM Tris pH 8.0, 15 mM MgCl2, 0.5

Donald Riascos-Ortiz, Ana Teresa Mosquera-Espinosa, Francia Varón De Agudelo, Claudio Marcelo Gonçalves de Oliveira, Jaime Eduardo Muñoz-Florez

Journal of Nematology, Volume 52 , 1–19

Article | 05-September-2013

AN INVESTIGATION OF DECISION ANALYTIC METHODOLOGIES FOR STRESS IDENTIFICATION

In modern society, more and more people are suffering from some type of stress. Monitoring and timely detecting of stress level will be very valuable for the person to take counter measures. In this paper, we investigate the use of decision analytics methodologies to detect stress. We present a new feature selection method based on the principal component analysis (PCA), compare three feature selection methods, and evaluate five information fusion methods for stress detection. A driving stress

Yong Deng, Chao-Hsien Chu, Huayou Si, Qixun Zhang, Zhonghai Wu

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 4, 1675–1699

Research Article | 01-June-2017

AN INVESTIGATION OF DIFFERENT VIDEO WATERMARKING TECHNIQUES

B. Sridhar

International Journal on Smart Sensing and Intelligent Systems, Volume 10 , ISSUE 2, 387–406

Article | 14-October-2020

A Comparative Study of Face Recognition Classification Algorithms

analysis PCA data dimensionality reduction The data set contains a total of 400 photos. We use the machine learning library Scikit-learn provided by python to process the data, and display part of the data set pictures as shown in Figure 1. Figure 1. ORL partial face image The experimental data has 4096 features per picture. Since the number of features is much greater than the number of samples, it is easy to regenerate overfitting during training. Therefore, a principal component analysis

Changyuan Wang, Guang Li, Pengxiang Xue, Qiyou Wu

International Journal of Advanced Network, Monitoring and Controls, Volume 5 , ISSUE 3, 23–29

Research Article | 01-September-2017

IDENTIFICATION OF TWO TYPES OF ROTTEN MEAT USING AN ELECTRONIC NOSE FOR FOOD QUALITY CONTROL

identified by human. Durations and gases emit of its rotten are determined by the pattern recognition methods PCA (Principal Components Analysis) for classification and DFA (Discriminate factorial analysis) for dating, and we will be identify between those rotten meat by DFA method.

Nihad Benabdellah, Khalid Hachami, Mohammed Bourhaleb, Naima Benazzi

International Journal on Smart Sensing and Intelligent Systems, Volume 10 , ISSUE 3, 673–695

Article | 01-June-2016

PREDICTION OF SEWAGE QUALITY BASED ON FUSION OF BPNETWORKS

kinds, and train the corresponding BP networks with the two kinds of data. Before using SVM to classify the input data, PCA (principle component analysis) is used to analyze the correlation between sewage quality parameters. Then we predict the value of sewage quality parameters with the fusion results of the two BP networks. Test results of the case study show that fusion of BP networks not only can improve the stability of BP networks but also can improve the prediction accuracy.

Lijuan Wang

International Journal on Smart Sensing and Intelligent Systems, Volume 9 , ISSUE 2, 909–926

Article | 01-September-2015

FRAGRANCE MEASUREMENT OF SCENTED RICE USING ELECTRONIC NOSE

into a sensor chamber; a water bath module for preparing rice sample, said water bath module including a heater attachment to facilitate cooking; a computing module to quantify the aroma data acquired by sensors; data acquisition module etc. Principal Component Analysis (PCA) implemented for clustering the data sets acquired from sensor array. Also data generated from sensor array was fed to Probabilistic Neural Network (PNN), Back-propagation Multilayer Perceptron (BPMLP) and Linear Discriminant

Arun Jana, Nabarun Bhattacharyya, Rajib Bandyopadhyay, Bipan Tudu, Subhankar Mukherjee, Devdulal Ghosh, Jayanta Kumar Roy

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 3, 1730–1747

Article | 02-November-2017

Normalization techniques for gas sensor array as applied to classification for black tea

tea-taster like scores. It has been observed that pre-processing of gas sensor data improves the classification accuracy and in this paper, a comparative study of different normalization techniques is presented for black tea application using electronic nose. For this study black tea samples were collected from different tea gardens in India. At first Principal Component Analysis (PCA) is used to investigate the presence of clusters in the sensors responses in multidimensional space. Then

Bipan Tudu, Bikram Kow, Nabarun Bhattacharyya, Rajib Bandyopadhyay

International Journal on Smart Sensing and Intelligent Systems, Volume 2 , ISSUE 1, 176–189

Research Article | 17-October-2018

NMR Analysis Reveals a Wealth of Metabolites in Root-Knot Nematode Resistant Roots of Citrullus amarus Watermelon Plants

) technology and principal component analysis (PCA) were used to analyze and compare metabolic profiles of seven CA accessions resistant to RKN along with two RKN-susceptible watermelon cultivars (Charleston Gray and Crimson Sweet). Calculation of the Mahalanobis distance revealed that the CA United States Plant Introduction (PI) 189225 (Line number 1832) and PI 482324 (1849) have the most distinct metabolic profiles compared with the watermelon cultivars Charleston Gray and Crimson Sweet, respectively

Mihail Kantor, Amnon Levi, Judith Thies, Nihat Guner, Camelia Kantor, Stuart Parnham, Arezue Boroujerdi

Journal of Nematology, Volume 50 , ISSUE 3, 303–316

Original Paper | 28-June-2017

Molecular Study of Indigenous Bacterial Community Composition on Exposure to Soil Arsenic Concentration Gradient

Actinobacteria and Proteobacteria but a shift towards Proteobacteria was observed with increasing arsenic concentration, and number of Actinobacteria eventually decreases. PCA (Principle Component Analysis) plot of bacterial community composition indicated a distinct resemblance among high arsenic content samples, while low arsenic content samples remained separated from others. Cluster analysis of soil parameters identifies three clusters, each of them was related to the arsenic content. Further, cluster

Semanti Basu, Tanima Paul, Priya Yadav, Abhijit Debnath, Keka Sarkar

Polish Journal of Microbiology, Volume 66 , ISSUE 2, 209–221

Research Article | 15-February-2020

Thin Film Coated QCM-Sensors and Pattern Recognition Methods for Discrimination of VOCs

gas sensors with different chemical affinity towards VOC molecules. The sensitivity of the elaborated QCMbased sensors was evaluated by monitoring the frequency shifts of the quartz exposed to different concentrations of volatile organic compounds, such as; ethanol, benzene and chloroform. The sensors responses data have been used for the identification and quantification of VOCs. The principal component analysis (PCA) and the neural-network (NNs) pattern recognition analysis were used for the

Omar C. Lezzar, A. Bellel, M. Boutamine, S. Sahli, Y. Segui, P. Raynaud

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 5, 1–6

original-paper | 11-March-2020

Oligotrophic Nitrification and Denitrification Bacterial Communities in a Constructed Sewage Treatment Ecosystem and Nitrogen Removal of Delftia tsuruhatensis NF4

compare the means of water quality parameters, and the nitrate and TN removal efficiency, the statistical analysis was performed using one-way ANOVA followed by a Tukey HSD post-hoc test using Rstudio (version 3.5, Rstudio Inc, San Francisco, USA). The significance level was set at α = 0.05. Alpha diversity of Illumina HiSeq sequencing analysis, including Chao1, ACE, rarefaction plots, and PCA plots were performed using QIIME and displayed with Rstudio. Results and Discussion Water quality

RUILAN YANG, JING LI, LUYAO WEI-XIE, LIN SHAO

Polish Journal of Microbiology, Volume 69 , ISSUE 1, 99–108

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