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Journal articles on the topic 'Mahalanobis squared distance'

Author: Grafiati

Published: 28 May 2022

Last updated: 30 July 2025

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1

Etherington, Thomas R. "Mahalanobis distances and ecological niche modelling: correcting a chi-squared probability error." PeerJ 7 (April 2, 2019): e6678. http://dx.doi.org/10.7717/peerj.6678.

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The Mahalanobis distance is a statistical technique that can be used to measure how distant a point is from the centre of a multivariate normal distribution. By measuring Mahalanobis distances in environmental space ecologists have also used the technique to model: ecological niches, habitat suitability, species distributions, and resource selection functions. Unfortunately, the original description of the Mahalanobis distance technique for ecological modelling contained an error describing how Mahalanobis distances could be converted into probabilities using a chi-squared distribution. This e

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2

Nikita, Efthymia, and Panos Nikitas. "Simulation methods for squared Euclidean and Mahalanobis type distances for multivariate data and their application in assessing the uncertainty in hierarchical clustering." Journal of Statistical Computation and Simulation 92, no. 11 (2022): 2403–24. https://doi.org/10.1080/00949655.2022.2030338.

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This paper extends the Suzuki and Shimodora method [Suzuki R, Shimodora H. Pvclust: an R package for assessing the uncertainty in hierarchical clustering. Bioinformatics. 2006;22:1540–1542] for assessing uncertainty in hierarchical cluster analysis to multivariate datasets and examines the reliability of the simulated cluster probabilities in relation to the simulation method adopted. The extension is applied to squared Euclidean and Mahalanobis-type distances and employs three simulation methods, the Monte-Carlo and bootstrap methods, and a new proposed method, the distance distribution

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Mukhopadhaya, Sayan, Anil Kumar та Alfred Stein. "FCM Approach of Similarity and Dissimilarity Measures with α-Cut for Handling Mixed Pixels". Remote Sensing 10, № 11 (2018): 1707. http://dx.doi.org/10.3390/rs10111707.

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In this paper, the fuzzy c-means (FCM) classifier has been studied with 12 similarity and dissimilarity measures: Manhattan distance, chessboard distance, Bray–Curtis distance, Canberra, Cosine distance, correlation distance, mean absolute difference, median absolute difference, Euclidean, Mahalanobis, diagonal Mahalanobis and normalised squared Euclidean distance. Both single and composite modes were used with a varying weight constant (m*) and also at different α-cuts. The two best single measures obtained were combined to study the effect of composite measures on the datasets used. An image

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Nguyen, Theanh, Tommy HT Chan, and David P. Thambiratnam. "Controlled Monte Carlo data generation for statistical damage identification employing Mahalanobis squared distance." Structural Health Monitoring: An International Journal 13, no. 4 (2014): 461–72. http://dx.doi.org/10.1177/1475921714521270.

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Garrido-Varo, A., J. Garcia-Olmo, and T. Fearn. "A note on Mahalanobis and related distance measures in WinISI and The Unscrambler." Journal of Near Infrared Spectroscopy 27, no. 4 (2019): 253–58. http://dx.doi.org/10.1177/0967033519848296.

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In identifying spectral outliers in near infrared calibration it is common to use a distance measure that is related to Mahalanobis distance. However, different software packages tend to use different variants, which lead to a translation problem if more than one package is used. Here the relationships between squared Mahalanobis distance D2, the GH distance of WinISI, and the T2 and leverage (L) statistics of The Unscrambler are established as D2 = T2 ≈ L × n ≈ GH × k, where n and k are the numbers of samples and variables, respectively, in the set of spectral data used to establish the dista

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Sarmadi, Hassan, Alireza Entezami, and Mohammadhassan Daneshvar Khorram. "Energy-based damage localization under ambient vibration and non-stationary signals by ensemble empirical mode decomposition and Mahalanobis-squared distance." Journal of Vibration and Control 26, no. 11-12 (2019): 1012–27. http://dx.doi.org/10.1177/1077546319891306.

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Damage localization of damaged structures is an important issue in structural health monitoring. In data-based methods based on statistical pattern recognition, it is necessary to extract meaningful features from measured vibration signals and utilize a reliable statistical technique for locating damage. One of the challenging issues is to extract reliable features from non-stationary vibration signals caused by ambient excitation sources. This article proposes a new energy-based method by using ensemble empirical mode decomposition and Mahalanobis-squared distance to obtain energy-based multi

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7

Iida, Takahisa, Takahiro Fukushima, and Nobuo Shinozaki. "Detection of Abnormality Using Squared Mahalanobis Distance When Both Continuous and Dichotomous Variables Exist." Japanese Journal of Applied Statistics 37, no. 2 (2008): 55–76. http://dx.doi.org/10.5023/jappstat.37.55.

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8

EADY, MATTHEW, BOSOON PARK, and SUN CHOI. "Rapid and Early Detection of Salmonella Serotypes with Hyperspectral Microscopy and Multivariate Data Analysis†." Journal of Food Protection 78, no. 4 (2015): 668–74. http://dx.doi.org/10.4315/0362-028x.jfp-14-366.

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This study was designed to evaluate hyperspectral microscope images for early and rapid detection of Salmonella serotypes Enteritidis, Heidelberg, Infantis, Kentucky, and Typhimurium at incubation times of 6, 8, 10, 12, and 24 h. Images were collected by an acousto-optical tunable filter hyperspectral microscope imaging system with a metal halide light source measuring 89 contiguous wavelengths every 4 nm between 450 and 800 nm. Pearson correlation values were calculated for incubation times of 8, 10, and 12 h and compared with data for 24 h to evaluate the change in spectral signatures from b

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9

Dzeverin, Igor, and Maria Ghazali. "Evolutionary Mechanisms Affecting the Multivariate Divergence in Some Myotis Species (Chiroptera, Vespertilionidae)." Evolutionary Biology 37, no. 2-3 (2010): 100–112. https://doi.org/10.5281/zenodo.13470115.

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(Uploaded by Plazi for the Bat Literature Project) Phenotypic evolutionary rates were measured for 27 craniometric characters in 12 extant OTUs from the bat genus Myotis (Chiroptera, Vespertilionidae). Squared Mahalanobis distance was used as a multivariate measure for amount of divergence, and squared Mahalanobis distance weighted by time was used as a measure for the rate of divergence. Estimates for the rates of divergence were found to be consistent with random walk hypothesis. Thus, the divergence in Myotis could be guided by random drift and mutations. The high dispersion in rate estimat

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Dzeverin, Igor, and Maria Ghazali. "Evolutionary Mechanisms Affecting the Multivariate Divergence in Some Myotis Species (Chiroptera, Vespertilionidae)." Evolutionary Biology 37, no. 2-3 (2010): 100–112. https://doi.org/10.5281/zenodo.13470115.

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(Uploaded by Plazi for the Bat Literature Project) Phenotypic evolutionary rates were measured for 27 craniometric characters in 12 extant OTUs from the bat genus Myotis (Chiroptera, Vespertilionidae). Squared Mahalanobis distance was used as a multivariate measure for amount of divergence, and squared Mahalanobis distance weighted by time was used as a measure for the rate of divergence. Estimates for the rates of divergence were found to be consistent with random walk hypothesis. Thus, the divergence in Myotis could be guided by random drift and mutations. The high dispersion in rate estimat

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Dzeverin, Igor, and Maria Ghazali. "Evolutionary Mechanisms Affecting the Multivariate Divergence in Some Myotis Species (Chiroptera, Vespertilionidae)." Evolutionary Biology 37, no. 2-3 (2010): 100–112. https://doi.org/10.5281/zenodo.13470115.

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(Uploaded by Plazi for the Bat Literature Project) Phenotypic evolutionary rates were measured for 27 craniometric characters in 12 extant OTUs from the bat genus Myotis (Chiroptera, Vespertilionidae). Squared Mahalanobis distance was used as a multivariate measure for amount of divergence, and squared Mahalanobis distance weighted by time was used as a measure for the rate of divergence. Estimates for the rates of divergence were found to be consistent with random walk hypothesis. Thus, the divergence in Myotis could be guided by random drift and mutations. The high dispersion in rate estimat

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Dzeverin, Igor, and Maria Ghazali. "Evolutionary Mechanisms Affecting the Multivariate Divergence in Some Myotis Species (Chiroptera, Vespertilionidae)." Evolutionary Biology 37, no. 2-3 (2010): 100–112. https://doi.org/10.5281/zenodo.13470115.

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(Uploaded by Plazi for the Bat Literature Project) Phenotypic evolutionary rates were measured for 27 craniometric characters in 12 extant OTUs from the bat genus Myotis (Chiroptera, Vespertilionidae). Squared Mahalanobis distance was used as a multivariate measure for amount of divergence, and squared Mahalanobis distance weighted by time was used as a measure for the rate of divergence. Estimates for the rates of divergence were found to be consistent with random walk hypothesis. Thus, the divergence in Myotis could be guided by random drift and mutations. The high dispersion in rate estimat

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13

Dzeverin, Igor, and Maria Ghazali. "Evolutionary Mechanisms Affecting the Multivariate Divergence in Some Myotis Species (Chiroptera, Vespertilionidae)." Evolutionary Biology 37, no. 2-3 (2010): 100–112. https://doi.org/10.5281/zenodo.13470115.

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(Uploaded by Plazi for the Bat Literature Project) Phenotypic evolutionary rates were measured for 27 craniometric characters in 12 extant OTUs from the bat genus Myotis (Chiroptera, Vespertilionidae). Squared Mahalanobis distance was used as a multivariate measure for amount of divergence, and squared Mahalanobis distance weighted by time was used as a measure for the rate of divergence. Estimates for the rates of divergence were found to be consistent with random walk hypothesis. Thus, the divergence in Myotis could be guided by random drift and mutations. The high dispersion in rate estimat

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14

Liu, Lijun, Xin Zhang, Ying Lei, and Zhupeng Zheng. "Structural Damage Localization under Unknown Seismic Excitation Based on Mahalanobis Squared Distance of Strain Transmissibility Function." Applied Sciences 12, no. 6 (2022): 3115. http://dx.doi.org/10.3390/app12063115.

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Due to the unpredictability of seismic excitation, the data-driven damage identification method, which only depends on the monitoring response data, has a good development prospect in structural health monitoring. In recent years, damage identification methods based on transmissibility function (TF) and Mahalanobis squared distance (MSD) have been widely studied. However, the existing methods are only applicable to damage warning. To overcome this limitation, an improved method for structural damage localization is proposed. Strain TF is used to eliminate the influence of unknown ambient excit

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15

Nguyen, Theanh, Tommy HT Chan, and David P. Thambiratnam. "Field validation of controlled Monte Carlo data generation for statistical damage identification employing Mahalanobis squared distance." Structural Health Monitoring: An International Journal 13, no. 4 (2014): 473–88. http://dx.doi.org/10.1177/1475921714542892.

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16

Kim, Ill Soo, Qian Qian Wu, Ji Hye Lee, Jong Pyo Lee, Min Ho Park, and Young Su Kim. "The Optimal Levenberg-Marquardt Algorithm to Predict Welding Quality Using Mahalanobis Distance Theory." Advanced Materials Research 936 (June 2014): 1873–77. http://dx.doi.org/10.4028/www.scientific.net/amr.936.1873.

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With the development of computational technology, neural network has attracted the more and more attentions to reveal the relationships between the process parameters and welding geometry. However, the Gas Metal Arc (GMA) welding is complex and of multiple interactions so that mathematical model for welding parameters has not been achieved. Neural networks have been noted as being particularly advantageous for modeling systems which contain noisy, fuzzy and uncertain elements, while a sufficient algorithm is employed. In this study, Levenberg-Marquardt algorithm was employed into GMA welding p

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17

Deraemaeker, A., and K. Worden. "On the use of the Mahalanobis squared-distance to filter out environmental effects in structural health monitoring." MATEC Web of Conferences 16 (2014): 02004. http://dx.doi.org/10.1051/matecconf/20141602004.

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18

Abubacker, K. A. Shaheer, J. Sutha, and K. A. Shahul Hameed. "A simple multi-feature based stereoscopic medical image retrieval system." Polish Journal of Medical Physics and Engineering 25, no. 2 (2019): 127–30. http://dx.doi.org/10.2478/pjmpe-2019-0017.

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Abstract This paper describes a method of retrieving stereoscopic medical images from the database that consists of feature extraction, similarity measure, and re-ranking of retrieved images. This method retrieves similar images of the query image from the database and re-ranks them according to the disparity map. The performance is evaluated using the metrics namely average retrieval precision (APR) and average retrieval rate (ARR). According to the performance outcomes, the multi-feature based image retrieval using Mahalanobis distance measure has produced better result compared to other dis

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19

Reggente, Matteo, Ann M. Dillner, and Satoshi Takahama. "Predicting ambient aerosol thermal–optical reflectance (TOR) measurements from infrared spectra: extending the predictions to different years and different sites." Atmospheric Measurement Techniques 9, no. 2 (2016): 441–54. http://dx.doi.org/10.5194/amt-9-441-2016.

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Abstract. Organic carbon (OC) and elemental carbon (EC) are major components of atmospheric particulate matter (PM), which has been associated with increased morbidity and mortality, climate change, and reduced visibility. Typically OC and EC concentrations are measured using thermal–optical methods such as thermal–optical reflectance (TOR) from samples collected on quartz filters. In this work, we estimate TOR OC and EC using Fourier transform infrared (FT-IR) absorbance spectra from polytetrafluoroethylene (PTFE Teflon) filters using partial least square regression (PLSR) calibrated to TOR O

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Reggente, M., A. M. Dillner, and S. Takahama. "Predicting ambient aerosol thermal-optical reflectance (TOR) measurements from infrared spectra: extending the predictions to different years and different sites." Atmospheric Measurement Techniques Discussions 8, no. 11 (2015): 12433–74. http://dx.doi.org/10.5194/amtd-8-12433-2015.

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Abstract. Organic carbon (OC) and elemental carbon (EC) are major components of atmospheric particulate matter (PM), which has been associated with increased morbidity and mortality, climate change and reduced visibility. Typically OC and EC concentrations are measured using thermal optical methods such as thermal optical reflectance (TOR) from samples collected on quartz filters. In this work, we estimate TOR OC and EC using Fourier transform infrared (FT-IR) absorbance spectra from polytetrafluoroethylene (PTFE or Teflon) filters using partial least square regression (PLSR) calibrated to TOR

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21

Nikitas, Panos, and Efthymia Nikita. "Assessing Algorithms Used for Constructing Confidence Ellipses in Multidimensional Scaling Solutions." Algorithms 16, no. 12 (2023): 535. http://dx.doi.org/10.3390/a16120535.

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This paper assesses algorithms proposed for constructing confidence ellipses in multidimensional scaling (MDS) solutions and proposes a new approach to interpreting these confidence ellipses via hierarchical cluster analysis (HCA). It is shown that the most effective algorithm for constructing confidence ellipses involves the generation of simulated distances based on the original multivariate dataset and then the creation of MDS maps that are scaled, reflected, rotated, translated, and finally superimposed. For this algorithm, the stability measure of the average areas tends to zero with incr

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22

Silva, Anderson Rodrigo da, and Carlos Tadeu dos Santos Dias. "A cophenetic correlation coefficient for Tocher's method." Pesquisa Agropecuária Brasileira 48, no. 6 (2013): 589–96. http://dx.doi.org/10.1590/s0100-204x2013000600003.

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The objective of this work was to propose a way of using the Tocher's method of clustering to obtain a matrix similar to the cophenetic one obtained for hierarchical methods, which would allow the calculation of a cophenetic correlation. To illustrate the obtention of the proposed cophenetic matrix, we used two dissimilarity matrices - one obtained with the generalized squared Mahalanobis distance and the other with the Euclidean distance - between 17 garlic cultivars, based on six morphological characters. Basically, the proposal for obtaining the cophenetic matrix was to use the average dist

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23

MANGKU, I. W. "MONTE CARLO EVALUATION OF ERROR RATE ESTIMATORS IN DISCRIMINANT ANALYSIS UNDER MULTIVARIATE NORMAL DATA." Journal of Mathematics and Its Applications 9, no. 1 (2010): 1. http://dx.doi.org/10.29244/jmap.9.1.1-14.

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This paper is concerned with the problem of estimating the error rate in two-group discriminant analysis. Here, behaviour of 19 existing error rate estimators are compared and contrasted by mean of Monte Carlo simulations under the ideal condition that both parent populations are multivariate normal with common covariance matrix. The criterion used for comparing those error rate estimators is sum squared error (SSE). Five experimental factors are considered for the simulation, they are the number of variables, the sample size relative to the number of variables, the Mahalanobis squared distanc

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Khan, Kabiruddin, and Probir Kumar Ojha. "Ecotoxicological Modeling of Organic Chemicals for Their Acute Toxicity in Algae Using Classification and Toxicophore-Based Approaches." International Journal of Quantitative Structure-Property Relationships 5, no. 2 (2020): 17–72. http://dx.doi.org/10.4018/ijqspr.2020040102.

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To study the relationship between toxicity of organic chemicals (OCs) with their structural and physicochemical features, the authors have developed a linear discriminant analysis (LDA) model for the classification of organic chemicals based on their acute observed toxicity in algae. This is done by employing a sufficiently large dataset of 352 chemicals following the strict Organization for Economic Cooperation and Development (OECD) guidelines for the quantitative structure-activity relationship (QSAR) validation. Additionally, 3D toxicophore models were generated to explore for the presence

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Deli, Temim, Khaled Said, and Noureddine Chatti. "Morphological differentiation among geographically close populations of the green crab Carcinus aestuarii Nardo, 1847 (Brachyura, Carcinidae) from the Tunisian coast." Crustaceana 87, no. 3 (2014): 257–83. http://dx.doi.org/10.1163/15685403-00003291.

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In the present study, we assessed patterns of morphological variation among populations of the Mediterranean green crabCarcinus aestuariiNardo, 1847 from the Tunisian coast. Eleven morphometric traits were measured on 464 specimens from nine sites, and the pattern of morphological variation among sites was assessed using multivariate approach. Non-parametric MANOVA (NPMANOVA) and non-metric Multidimensional Scaling (MDS) analyses revealed statistically significant differences among the studied locations for both sexes proving that natural variability of the measured traits differs clearly betw

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Chen, Chuang, Yinhui Wang, Tao Wang, and Xiaoyan Yang. "A Mahalanobis Distance Cumulant-Based Structural Damage Identification Method with IMFs and Fitting Residual of SHM Measurements." Mathematical Problems in Engineering 2020 (September 30, 2020): 1–17. http://dx.doi.org/10.1155/2020/6932463.

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Data-driven damage identification based on measurements of the structural health monitoring (SHM) system is a hot issue. In this study, based on the intrinsic mode functions (IMFs) decomposed by the empirical mode decomposition (EMD) method and the trend term fitting residual of measured data, a structural damage identification method based on Mahalanobis distance cumulant (MDC) was proposed. The damage feature vector is composed of the squared MDC values and is calculated by the segmentation data set. It makes the changes of monitoring points caused by damage accumulate as “amplification effe

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MANGKU, I. W. "COMPARING OPTIMISM OF ERROR RATE ESTIMATORS IN DISCRIMINANT ANALYSIS BY MONTE CARLO SIMULATION ON MULTIVARIATE NORMAL DATA." Journal of Mathematics and Its Applications 9, no. 2 (2010): 1. http://dx.doi.org/10.29244/jmap.9.2.1-12.

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The problem considered in this paper is estimation of the error rate in two-group discriminant analysis. Here, performance of 19 existing error rate estimators are compared and contrasted by mean of Monte Carlo simulations under the ideal condition that both parent populations are multivariate normal with common covariance matrix. The criterion used for comparing those error rate estimators is optimism. Five experimental factors are considered for the simulation, they are the number of variables, the sample size relative to the number of variables, the Mahalanobis squared distance between the

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Nguyen, Thi, Anne Ruiz-Gazen, Christine Thomas-Agnan, and Thibault Laurent. "Multivariate Student versus Multivariate Gaussian Regression Models with Application to Finance." Journal of Risk and Financial Management 12, no. 1 (2019): 28. http://dx.doi.org/10.3390/jrfm12010028.

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To model multivariate, possibly heavy-tailed data, we compare the multivariate normal model (N) with two versions of the multivariate Student model: the independent multivariate Student (IT) and the uncorrelated multivariate Student (UT). After recalling some facts about these distributions and models, known but scattered in the literature, we prove that the maximum likelihood estimator of the covariance matrix in the UT model is asymptotically biased and propose an unbiased version. We provide implementation details for an iterative reweighted algorithm to compute the maximum likelihood estim

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Yan, Gang, Xiang Lu, and Jianfei Tang. "Guided Wave-Based Monitoring of Evolution of Fatigue Damage in Glass Fiber/Epoxy Composites." Applied Sciences 9, no. 7 (2019): 1394. http://dx.doi.org/10.3390/app9071394.

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This paper presents an experimental study on detecting and monitoring of evolution of fatigue damage in composites under cyclic loads by using guided waves. Composite specimens fabricated by glass fiber/epoxy laminates and surface mounted with piezoelectric wafers are fatigued under tension–tension loads. A laser extensometer is used to obtain the degradation of longitudinal stiffness of the specimens under fatigue states to reflect the accumulation of internal fatigue damage. Meanwhile, at different fatigue cycles, one wafer acts as actuator to excite diagnostic guided waves, and the other ac

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Sarmadi, Hassan, and Abbas Karamodin. "A novel anomaly detection method based on adaptive Mahalanobis-squared distance and one-class kNN rule for structural health monitoring under environmental effects." Mechanical Systems and Signal Processing 140 (June 2020): 106495. http://dx.doi.org/10.1016/j.ymssp.2019.106495.

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Xu, Shaohua, Songnan Liu, and Yongdao Zhou. "MODE: Minimax Optimal Deterministic Experiments for Causal Inference in the Presence of Covariates." Entropy 26, no. 12 (2024): 1023. http://dx.doi.org/10.3390/e26121023.

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Data-driven decision-making has become crucial across various domains. Randomization and re-randomization are standard techniques employed in controlled experiments to estimate causal effects in the presence of numerous pre-treatment covariates. This paper quantifies the worst-case mean squared error of the difference-in-means estimator as a generalized discrepancy of covariates between treatment and control groups. We demonstrate that existing randomized or re-randomized experiments utilizing Monte Carlo methods are sub-optimal in minimizing this generalized discrepancy. To address this limit

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Lucà, Francescantonio, Stefano Manzoni, Francesco Cerutti, and Alfredo Cigada. "A Damage Detection Approach for Axially Loaded Beam-Like Structures Based on Gaussian Mixture Model." Sensors 22, no. 21 (2022): 8336. http://dx.doi.org/10.3390/s22218336.

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Axially loaded beam-like structures represent a challenging case study for unsupervised learning vibration-based damage detection. Under real environmental and operational conditions, changes in axial load cause changes in the characteristics of the dynamic response that are significantly greater than those due to damage at an early stage. In previous works, the authors proposed the adoption of a multivariate damage feature composed of eigenfrequencies of multiple vibration modes. Successful results were obtained by framing the problem of damage detection as that of unsupervised outlier detect

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Huang, Jingyi, Terence Nhan, Vanessa N. L. Wong, Scott G. Johnston, R. Murray Lark, and John Triantafilis. "Digital soil mapping of a coastal acid sulfate soil landscape." Soil Research 52, no. 4 (2014): 327. http://dx.doi.org/10.1071/sr13314.

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Coastal floodplains are commonly underlain by sulfidic sediments and coastal acid sulfate soils (CASS). Oxidation of sulfidic sediments leads to increases in acidity and mobilisation of trace metals, resulting in an increase in the concentrations of conducting ions in sediment and pore water. The distribution of these sediments on floodplains is highly heterogeneous. Accurately identifying the distribution of CASS is essential for developing targeted management strategies. One approach is the use of digital soil mapping (DSM) using ancillary information. Proximal sensing instruments such as an

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Nikula, Riku-Pekka, Mika Ruusunen, Joni Keski-Rahkonen, Lars Saarinen, and Fredrik Fagerholm. "Probabilistic Condition Monitoring of Azimuth Thrusters Based on Acceleration Measurements." Machines 9, no. 2 (2021): 39. http://dx.doi.org/10.3390/machines9020039.

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Drill ships and offshore rigs use azimuth thrusters for propulsion, maneuvering and steering, attitude control and dynamic positioning activities. The versatile operating modes and the challenging marine environment create demand for flexible and practical condition monitoring solutions onboard. This study introduces a condition monitoring algorithm using acceleration and shaft speed data to detect anomalies that give information on the defects in the driveline components of the thrusters. Statistical features of vibration are predicted with linear regression models and the residuals are then

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Lucà, Francescantonio, Stefano Manzoni, Alfredo Cigada, Silvia Barella, Andrea Gruttadauria, and Francesco Cerutti. "Automatic Detection of Real Damage in Operating Tie-Rods." Sensors 22, no. 4 (2022): 1370. http://dx.doi.org/10.3390/s22041370.

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Many researchers have proposed vibration-based damage-detection approaches for continuous structural health monitoring. Translation to real applications is not always straightforward because the proposed methods have mostly been developed and validated in controlled environments, and they have not proven to be effective in detecting real damage when considering real scenarios in which environmental and operational variations are not controlled. This work was aimed to develop a fully-automated strategy to detect damage in operating tie-rods that only requires one sensor and that can be carried

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Kabi, F., C. Masembe, R. Negrini, and V. Muwanika. "Patterns of indigenous female cattle morphometric traits variations in Uganda: Evidence for farmers’ selection to enhance agro-ecological fitness." Animal Genetic Resources/Ressources génétiques animales/Recursos genéticos animales 56 (February 2, 2015): 79–90. http://dx.doi.org/10.1017/s2078633614000551.

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SummaryGlobally, rural cattle keeping communities actively select and breed indigenous cattle to satisfy their interests and enhance adaptation to local landscapes. This study investigated how traditional systems in Uganda have shaped the morphometric population structure of indigenous cattle breeds. Ten linear morphometric traits were interrogated amongst 801 female cattle, comprising 46 Nganda (Bos indicus), 368 Ankole (B. taurus indicus) and 387 East African shorthorn zebu (EASZ,B. indicus). The study cattle were obtained evenly at random from 209 herds in their agro-ecological zones (AEZs)

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Entezami, Alireza, Carlo De Michele, Ali Nadir Arslan, and Bahareh Behkamal. "Detection of Partially Structural Collapse Using Long-Term Small Displacement Data from Satellite Images." Sensors 22, no. 13 (2022): 4964. http://dx.doi.org/10.3390/s22134964.

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The development of satellite sensors and interferometry synthetic aperture radar (InSAR) technology has enabled the exploitation of their benefits for long-term structural health monitoring (SHM). However, some restrictions cause this process to provide a small number of images leading to the problem of small data for SAR-based SHM. Conversely, the major challenge of the long-term monitoring of civil structures pertains to variations in their inherent properties by environmental and/or operational variability. This article aims to propose new hybrid unsupervised learning methods for addressing

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GONÇALVES, Viviane Pereira, Francisco Laurimar do Nascimento ANDRADE, Rafaelle Fazzi GOMES, and Lucas da Silva SANTOS. "Genetic diversity in creole genotypes of Amazon chicory." Acta Amazonica 52, no. 2 (2022): 89–95. http://dx.doi.org/10.1590/1809-4392202102852.

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ABSTRACT Amazon chicory is still a little-known vegetable despite its great agronomic potential. The characterization of chicory genotypes concerning genetic divergence is a key step for breeding programs, as it allows the selection of superior individuals and to explore the variability and complementarity of characteristics via interbreeding between newly generated genotypes. In this context, this study aimed to evaluate the genetic divergence among Amazon chicory creole genotypes from the northern Brazilian states of Pará and Rondônia based on morpho-agronomic traits. We conducted an experim

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Zheng, Bowen, Piervincenzo Rizzo, and Amir Nasrollahi. "Outlier analysis of nonlinear solitary waves for health monitoring applications." Structural Health Monitoring 19, no. 4 (2019): 1160–74. http://dx.doi.org/10.1177/1475921719876089.

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The structural health monitoring/nondestructive evaluation method based on the generation and detection of highly nonlinear solitary waves is emerging as a cost-effective technique to monitor or inspect a variety of structures and materials. These waves possess unique characteristics not seen in conventional ultrasounds. Outlier analysis is a statistic tool able to identify anomalies in data that diverge from a set of baseline data. Although outlier analysis has received considerable attention for defect detection using modal data, guided ultrasonic waves, or other nondestructive approaches, i

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Muluneh, Bekalu, Mengistie Taye, Tadelle Dessie, Dessie Salilew Wondim, Damitie Kebede, and Andualem Tenagne. "Morpho-biometric characterization of indigenous chicken ecotypes in north-western Ethiopia." PLOS ONE 18, no. 6 (2023): e0286299. http://dx.doi.org/10.1371/journal.pone.0286299.

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Morphological characterization of Animal Genetic Resources is the first step to documenting diversity and designing breed specific breeding programs. The current study characterized the morpho-biometric variation of indigenous chicken ecotypes prevailing in northwestern Ethiopia. A multi-stage purposive, stratified, and random sampling method was employed to select the study areas and chickens. A total of 1200 adult chickens were sampled and characterized for 12 qualitative and 11 quantitative traits. Univariate and multivariate data analysis methods were employed to analyze the data using SAS

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Drangsfeldt, Casper Aaskov, and Luis David Avendaño-Valencia. "A combined implicit-explicit vibration-based SHM method for damage detection of wind turbine blades." Journal of Physics: Conference Series 2647, no. 18 (2024): 182030. http://dx.doi.org/10.1088/1742-6596/2647/18/182030.

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Abstract Today, the green transition is being pursued more than ever, leading to a significant increase in the installation of wind turbines and wind farms. Maintaining and servicing the wind turbines is accompanied by extensive expenses. Therefore, predictive maintenance techniques are in increasing demand, including the implementation of a well-functioning Structural Health Monitoring (SHM) system. In this work, physical and non-physical vibration features along with various techniques to mitigate the effect of Environmental and Operational Variability (EOV) are investigated. Vibration featu

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Boujenane, I., and D. Petit. "Between- and within-breed morphological variability in Moroccan sheep breeds." Animal Genetic Resources/Ressources génétiques animales/Recursos genéticos animales 58 (May 31, 2016): 91–100. http://dx.doi.org/10.1017/s2078633616000059.

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SummaryThe objective of this study was a morphological characterization of five Moroccan sheep breeds (Béni Guil, Boujaâd, D'man, Sardi and Timahdite) to assess between- and within-breed variability using multivariate analyses. Fourteen morphological measurements were collected on 876 adult animals of both sexes in 98 different flocks located in 22 geographic localities of five breeds. The multiple analysis of variance revealed that significant morphological differences existed between breeds. The overall proportion of total variance due to between-breed component was 28.3 percent. The factor

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Li, Bangjie, Dongdong Guan, Yuzhen Xie, et al. "Global Optical and SAR Image Registration Method Based on Local Distortion Division." Remote Sensing 17, no. 9 (2025): 1642. https://doi.org/10.3390/rs17091642.

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Variations in terrain elevation cause images acquired under different imaging modalities to deviate from a linear mapping relationship. This effect is particularly pronounced between optical and SAR images, where the range-based imaging mechanism of SAR sensors leads to significant local geometric distortions, such as perspective shrinkage and occlusion. As a result, it becomes difficult to represent the spatial correspondence between optical and SAR images using a single geometric model. To address this challenge, we propose a global optical-SAR image registration method that leverages local

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Chen, Lifang, Dai Cao, and Yuan Liu. "A New Intelligent Jigsaw Puzzle Algorithm Base on Mixed Similarity and Symbol Matrix." International Journal of Pattern Recognition and Artificial Intelligence 32, no. 02 (2017): 1859001. http://dx.doi.org/10.1142/s0218001418590012.

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Jigsaw puzzle algorithm is important as it can be applied to many areas such as biology, image editing, archaeology and incomplete crime-scene reconstruction. But, still, some problems exist in the process of practical application, for example, when there are a large number of similar objects in the puzzle fragments, the error rate will reach 30%–50%. When some fragments are missing, most algorithms fail to restore the images accurately. When the number of fragments of the jigsaw puzzle is large, efficiency is reduced. During the intelligent puzzle, mainly the Sum of Squared Distance Scoring (

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Kociuba, Wanda, Wieslaw Mądry, Aneta Kramek, Krzysztof Ukalski, and Marcin Studnicki. "Multtvariate diversity of Polish winter triticale cultivars for spike and other traits." Plant Breeding and Seed Science 62, no. 1 (2010): 31–42. http://dx.doi.org/10.2478/v10129-011-0003-4.

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Multtvariate diversity of Polish winter triticale cultivars for spike and other traits The objective of the present study was to determine the extent and pattern of genotypic diversity for six spike quantitative characters and two other traits in 36 winter triticale cultivars released in Poland, to classify the cultivars into similarity groups (clusters) and to identify those traits, among the studied ones, which mostly discriminated distinguished groups of cultivars. The 36 cultivars, released in the period from 1982 to 1999, were evaluated across three years 2002-2004 at the Experimental Fie

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Islam, Md Nazrul, Murat Tahtali, and Mark Pickering. "Specular Reflection Detection and Inpainting in Transparent Object through MSPLFI." Remote Sensing 13, no. 3 (2021): 455. http://dx.doi.org/10.3390/rs13030455.

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Multispectral polarimetric light field imagery (MSPLFI) contains significant information about a transparent object’s distribution over spectra, the inherent properties of its surface and its directional movement, as well as intensity, which all together can distinguish its specular reflection. Due to multispectral polarimetric signatures being limited to an object’s properties, specular pixel detection of a transparent object is a difficult task because the object lacks its own texture. In this work, we propose a two-fold approach for determining the specular reflection detection (SRD) and th

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Kim, Il Soo, Ji Hye Lee, Javad Malekani, and Prasad K. D. V. Yarlagadda. "Prediction of GMA Welding Characteristic Parameter by Artificial Neural Network System." Advanced Materials Research 1061-1062 (December 2014): 481–91. http://dx.doi.org/10.4028/www.scientific.net/amr.1061-1062.481.

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Nowadays, demand for automated Gas metal arc welding (GMAW) is growing and consequently need for intelligent systems is increased to ensure the accuracy of the procedure. To date, welding pool geometry has been the most used factor in quality assessment of intelligent welding systems. But, it has recently been found that Mahalanobis Distance (MD) not only can be used for this purpose but also is more efficient. In the present paper, Artificial Neural Networks (ANN) has been used for prediction of MD parameter. However, advantages and disadvantages of other methods have been discussed. The Leve

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Mediouni, Rida Mohammed, Sarra Said, Faiza Ilias, and Suheil Semir Bechir Gaouar. "Leaf Geometric morphometrics among a natural population of Norway maple (Acer platanoidesL.) in Northern Algeria." GABJ 5, no. 2 (2021): 123–34. http://dx.doi.org/10.46325/gabj.v5i2.81.

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Maple (Acer L.) is a diverse tree genera that includes more than a hundred of deciduous and evergreen species in Northern hemisphere,Acer platanoidesis a species from the maple’s genuswith an invasive aptitudes in Europe and North America,this specieshad never been recordedin North Africa andthe main aim of this work is to investigate the shape and size variability withina natural population in Northern Algeria. The study was carried out using a collection of multivariate, bivariate and univariate statistics, 303 A. platanoides leaves were includedin the analysis counting 2 taxa from8 countrie

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Prykhodko, S. B., and A. S. Trukhov. "KEYSTROKE DYNAMICS RECOGNITION USING NINE-VARIATE PREDICTION ELLIPSOID FOR NORMALIZED DATA." Radio Electronics, Computer Science, Control, no. 1 (April 10, 2025): 96–105. https://doi.org/10.15588/1607-3274-2025-1-9.

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Context. Keystroke dynamics recognition is a crucial element in enhancing security, enabling personalized user authentication, and supporting various identity verification systems. This study investigates the influence of data distribution on the performance of one-class classification models in keystroke dynamics, focusing on the application of a nine-variate prediction ellipsoid. The object of research is the keystroke dynamics recognition process. The subject of the research is a mathematical model for keystroke dynamics recognition. Unlike typical approaches assuming a multivariate normal

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Nowak, Edward. "Geodesic survey and modernization of a route as the task of optimization." Geodesy and Cartography 63, no. 1 (2014): 75–87. http://dx.doi.org/10.2478/geocart-2014-0006.

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Abstract A geodesic survey of an existing route requires one to determine the approximation curve by means of optimization using the total least squares method (TLSM). The objective function of the LSM was found to be a square of the Mahalanobis distance in the adjustment field ν. In approximation tasks, the Mahalanobis distance is the distance from a survey point to the desired curve. In the case of linear regression, this distance is codirectional with a coordinate axis; in orthogonal regression, it is codirectional with the normal line to the curve. Accepting the Mahalanobis distance from t

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