Relevant bibliographies by topics / Conditional discriminant analysis

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers
  5. Reports

Academic literature on the topic 'Conditional discriminant analysis'

Author: Grafiati
Published: 5 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "Conditional discriminant analysis"

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Barrat, Sabine, and Salvatore Tabbone. "A Progressive Learning Method for Symbol Recognition." JUCS - Journal of Universal Computer Science 14, no. (2) (2008): 224–36. https://doi.org/10.3217/jucs-014-02-0224.

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This paper deals with a progressive learning method for symbol recognition which improves its own recognition rate when new symbols are recognized in graphic documents. We propose a discriminant analysis method which provides allocation rules from a training set of labelled data. However a discriminant analysis method is efficient only if the training set and the test data are defined in the same conditions but it is rare in real life. In order to overcome this problem, a conditional vector is added to each instance to take into account the parasitic effects between the test data and the train
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Rohmana, Shella Faiz, Agus Rusgiyono, and Sugito Sugito. "PENENTUAN FAKTOR-FAKTOR YANG MEMPENGARUHI INTENSITAS CURAH HUJAN DENGAN ANALISIS DISKRIMINAN GANDA DAN REGRESI LOGISTIK MULTINOMIAL (Studi Kasus: Data Curah Hujan Kota Semarang dari Stasiun Meteorologi Maritim Tanjung Emas Periode Oktober 2018 – Maret 2019)." Jurnal Gaussian 8, no. 3 (2019): 398–406. http://dx.doi.org/10.14710/j.gauss.v8i3.26684.

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Meteorologist develop rainfall forecasting methods to obtain better and more accurate rainfall information. One of them is the research of grid data and the method of grouping rainfall. According to BMKG, rainfall is classified into light, medium, and heavy rain. This study aims to determine the factors that influencing rainfall grouping using multiple discriminant analysis with a stepwise selection method. This study uses the daily climate data of Semarang City for period of October 2018 to March 2019. Based on its partial F value, the wind speed variable is eliminated so the significant vari
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Misra, R. K. "Quadratic Discriminant Analysis with Covariance for Stock Delineation and Population Differentiation: A Study of Beaked Redfishes (Sebastes mentella and S. fasciatus)." Canadian Journal of Fisheries and Aquatic Sciences 42, no. 10 (1985): 1672–76. http://dx.doi.org/10.1139/f85-209.

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Stock delineation is of vital importance in fisheries management programs. Linear discriminant function (LDF) has been employed extensively in population differentiation studies but is of severely restricted usefulness when populations differ in their dispersion matrices. Quadratic discriminant function (QDF) is the appropriate analysis to employ in these situations. Here, I analyzed morphometric data of beaked redfishes (Sebastes mentella and S. fasciatus) by a recently developed conditional QDF.
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Stabingis, Giedrius, Kęstutis Dučinskas, and Lijana Stabingienė. "Comparison of spatial classification rules with different conditional distributions of class label." Nonlinear Analysis: Modelling and Control 19, no. 1 (2014): 109–17. http://dx.doi.org/10.15388/na.2014.1.7.

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In this paper spatial classification rules based on Bayes discriminant functions are considered. The novelty of this work is that the statistical supervised classification method is improved by extending the influence of spatial correlation between observation to be classified and training sample. Such methods are used for data containing spatially correlated noise. Method accuracy is tested experimentally on artificially corrupted images. This classification rule with distance based conditional distribution for class label shows advantage against other classification rule ignoring such influe
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Xiao, Yutang, Hongbo Shi, Boyu Wang, Yang Tao, Shuai Tan, and Bing Song. "Weighted Conditional Discriminant Analysis for Unseen Operating Modes Fault Diagnosis in Chemical Processes." IEEE Transactions on Instrumentation and Measurement 71 (2022): 1–14. http://dx.doi.org/10.1109/tim.2022.3152235.

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Siddiqi, Muhammad Hameed, Rahman Ali, Adil Mehmood Khan, Young-Tack Park, and Sungyoung Lee. "Human Facial Expression Recognition Using Stepwise Linear Discriminant Analysis and Hidden Conditional Random Fields." IEEE Transactions on Image Processing 24, no. 4 (2015): 1386–98. http://dx.doi.org/10.1109/tip.2015.2405346.

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Hino, Hideitsu, and Noboru Murata. "A Conditional Entropy Minimization Criterion for Dimensionality Reduction and Multiple Kernel Learning." Neural Computation 22, no. 11 (2010): 2887–923. http://dx.doi.org/10.1162/neco_a_00027.

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Reducing the dimensionality of high-dimensional data without losing its essential information is an important task in information processing. When class labels of training data are available, Fisher discriminant analysis (FDA) has been widely used. However, the optimality of FDA is guaranteed only in a very restricted ideal circumstance, and it is often observed that FDA does not provide a good classification surface for many real problems. This letter treats the problem of supervised dimensionality reduction from the viewpoint of information theory and proposes a framework of dimensionality r
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Bi, Yingtao, and Daniel R. Jeske. "The efficiency of logistic regression compared to normal discriminant analysis under class-conditional classification noise." Journal of Multivariate Analysis 101, no. 7 (2010): 1622–37. http://dx.doi.org/10.1016/j.jmva.2010.03.001.

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Liu, Xingye, Jingye Li, Xiaohong Chen, Lin Zhou, and Kangkang Guo. "Bayesian discriminant analysis of lithofacies integrate the Fisher transformation and the kernel function estimation." Interpretation 5, no. 2 (2017): SE1—SE10. http://dx.doi.org/10.1190/int-2016-0025.1.

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The accurate identification of lithofacies is indispensable for reservoir parameter prediction. In recent years, the application of multivariate statistical methods has gained more and more attention in petroleum geology. In terms of the identification for lithofacies, the commonly used multivariate statistical methods include discriminant analysis and cluster analysis. Fisher and Bayesian discriminant analyses are two different discriminant analysis methods, which include intrinsic advantages and disadvantages. Given the discriminant efficiency of different methods, calculation cost, difficul
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Baliyan, Mohit, and Evgeny M. Mirkes. "Linear Dimensionality Reduction: What Is Better?" Data 10, no. 5 (2025): 70. https://doi.org/10.3390/data10050070.

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This research paper focuses on dimensionality reduction, which is a major subproblem in any data processing operation. Dimensionality reduction based on principal components is the most used methodology. Our paper examines three heuristics, namely Kaiser’s rule, the broken stick, and the conditional number rule, for selecting informative principal components when using principal component analysis to reduce high-dimensional data to lower dimensions. This study uses 22 classification datasets and three classifiers, namely Fisher’s discriminant classifier, logistic regression, and K nearest neig
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Dissertations / Theses on the topic "Conditional discriminant analysis"

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Elnady, Maged Elsaid. "On-shaft vibration measurement using a MEMS accelerometer for faults diagnosis in rotating machines." Thesis, University of Manchester, 2013. https://www.research.manchester.ac.uk/portal/en/theses/onshaft-vibration-measurement-using-a-mems-accelerometer-for-faults-diagnosis-in-rotating-machines(cf9b9848-972d-49ff-a6b0-97bef1ad0e93).html.

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The healthy condition of a rotating machine leads to safe and cheap operation of almost all industrial facilities and mechanical systems. To achieve such a goal, vibration-based condition monitoring has proved to be a well-accepted technique that detects incipient fault symptoms. The conventional way of On-Bearing Vibration Measurement (OBVM) captures symptoms of different faults, however, it requires a relatively expensive setup, an additional space for the auxiliary devices and cabling in addition to an experienced analyst. On-Shaft Vibration Measurement (OSVM) is an emerging method proposed
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Васильченко, А. Д. "Аналіз підходів щодо визначення фінансового механізму підприємства". Thesis, Київський національний університет технологій та дизайну, 2018. https://er.knutd.edu.ua/handle/123456789/9578.

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У статті висвітлено теоретичні підходи до визначення фінансового стану та механізму підприємства шляхом розрахунку інтегрального показника.<br>В статье освещены теоретические подходы к определению финансового состояния и механизма предприятия путем расчета интегрального показателя.<br>In the article the theoretical approaches to the definition of the financial state and the mechanism of the enterprise by means of calculation of the integral indicator are highlighted.
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Головко, Віталій Олексійович. "Моделі, методи та інформаційні технології розробки нечіткої експертної системи діагностики фінансового стану підприємства". Thesis, НТУ "ХПІ", 2016. http://repository.kpi.kharkov.ua/handle/KhPI-Press/21976.

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Дисертація на здобуття вченого ступеня кандидату технічних наук за спеціальністю 05.13.06 – інформаційні технології. – Національний технічний університет "Харківський політехнічний інститут", м. Харків, 2016. У дисертації розглядається науково-практична задача ідентифікації фінансового стану підприємства в умовах нечітких даних про значення контрольованих фінансових показників. На основі аналізу традиційних методів рішення цієї задачі виявлено основний недолік традиційних методів ідентифікації: недостатній облік невизначеності вихідних даних. У зв'язку з цим удосконалені методи багатовимірног
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Головко, Виталий Алексеевич. "Модели, методы и информационные технологии разработки нечеткой экспертной системы диагностики финансового состояния предприятия". Thesis, НТУ "ХПИ", 2016. http://repository.kpi.kharkov.ua/handle/KhPI-Press/21977.

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Диссертация на соискание ученой степени кандидата технических наук по специальности 05.13.06 – информационные технологии. – Национальный технический университет "Харьковский политехнический институт", г. Харьков, 2016. В диссертации рассматривается важная научно-практическая задача идентификации финансового состояния предприятия в условиях нечетких данных о значениях контролируемых финансовых показателей. На основе анализа традиционных методов оценки финансового состояния предприятия выявлены их недостатки, из которых самый существенный – недостаточный учет неопределенности исходных данных. В
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Yueh-Hsuan, Chiang. "Lighting Condition Class-Based Locally Linear Discriminant Analysis for Face Recognition." 2005. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0001-1707200522292600.

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Chiang, Yueh-Hsuan, and 江岳軒. "Lighting Condition Class-Based Locally Linear Discriminant Analysis for Face Recognition." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/17645384797295834053.

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碩士<br>國立臺灣大學<br>資訊工程學研究所<br>93<br>We proposed a novel method of face recognition under varying lighting conditions. Face images under different lighting conditions are non-linear separable, image variation due to different lighting conditions is much more significant than that due to different personal identities. The basic idea of our approach is to find a set of lighting condition specific transformations which best separates the face images under varying lighting conditions. The proposed method has several steps, the first one is to find the optimal set of lighting condition classes which b
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Gamble, Andrew Stephan. "Combining Multivariate Statistical Methods and Spatial Analysis to Characterize Water Quality Conditions in the White River Basin, Indiana, U.S.A." Thesis, 2011. http://hdl.handle.net/1805/2460.

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Indiana University-Purdue University Indianapolis (IUPUI)<br>This research performs a comparative study of techniques for combining spatial data and multivariate statistical methods for characterizing water quality conditions in a river basin. The study has been performed on the White River basin in central Indiana, and uses sixteen physical and chemical water quality parameters collected from 44 different monitoring sites, along with various spatial data related to land use – land cover, soil characteristics, terrain characteristics, eco-regions, etc. Various parameters related to the spati
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Book chapters on the topic "Conditional discriminant analysis"

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Kedadouche, Mourad, Zhaoheng Liu, and Marc Thomas. "Bearing Fault Feature Extraction Using Autoregressive Coefficients, Linear Discriminant Analysis and Support Vector Machine Under Variable Operating Conditions." In Applied Condition Monitoring. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61927-9_32.

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Thaler, Tilen, Primož Potočnik, Peter Mužič, Ivan Bric, Rudi Bric, and Edvard Govekar. "Chatter Recognition in Band Sawing Based on Feature Extraction and Discriminant Analysis." In Condition Monitoring of Machinery in Non-Stationary Operations. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28768-8_63.

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Serafino, Francesco, and Andrea Bianco. "Analysis of the limits for the detection of small garbage island immersed in clutter radar." In Ninth International Symposium “Monitoring of Mediterranean Coastal Areas: Problems and Measurement Techniques”. Firenze University Press, 2022. http://dx.doi.org/10.36253/979-12-215-0030-1.51.

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This work show the limits of the detection capacity of X-band radars, as the sea state changes, in order to identify, discriminate, characterize and track small floating aggregations of plastic marine litter (Small Garbage Island - SGIs). Two distinct radar measurement campaigns were conducted at sea of SGI modules assembled in the laboratory. The measurement were carried out respectively in conditions of calm sea, to test the system in ideal conditions, and in rough sea conditions. The data analysis confirmed the ability of the X-band radars to detect the aggregations of floating waste on the
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Higano, Yoshiro. "Introduction: Real Estate Tax System and Real Estate Market in Japan." In New Frontiers in Regional Science: Asian Perspectives. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8848-8_8.

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AbstractThis introduction summarizes chapters of Part II. In Chap. 10.1007/978-981-15-8848-8_9, Yamamoto (Jpn J Real Estate Sci 31:88–96, 2018) has compared between the street method, the asset valuation adopted for the imposition of property tax in Japan, and the computer-assisted mass appraisal (CAMA) method generally adopted in North America focusing on education and training of valuators. In Chap. 10.1007/978-981-15-8848-8_10, Yamazaki (Jpn J Real Estate Sci 31:97–101, 2018) argues that one of the major causes for relatively low density use of land in the city in Japan is the land tax syst
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Lowe, David. "Radial Basis Function Networks and Statistics." In Statistics and Neural Networks. Oxford University PressOxford, 2000. http://dx.doi.org/10.1093/oso/9780198524229.003.0003.

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Abstract The class of neural network architectures known as radial basis functions has a structure and history which has produced strong links with various areas in the statistical sciences. This chapter reviews some of the more salient aspects, which include the links with conditional and unconditional density estimation (such as Gaussian mixture models), regression problems and links with kernel estimators and linear smooths, supervised feature extraction and discriminant analysis, and topographic feature extraction and links to multidimensional scaling, Sammon mappings and nonlinear princip
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Harbaugh, John W., and Johannes Wendebourg. "Risk Analysis Of Petroleum Prospects." In Computers in Geology - 25 Years of Progress. Oxford University Press, 1994. http://dx.doi.org/10.1093/oso/9780195085938.003.0012.

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Risk analysis of an oil or gas prospect requires a probability distribution with two components, a dry-hole probability plus a distribution of oil or gas volumes if there is a discovery. While these components should be estimated objectively, risk analysis as currently practiced is mostly guesswork. Geologists assign outcome probabilities without appropriate procedures or data for objective estimation. Valid estimates require frequency data on regional exploratory drilling-success ratios, frequency distributions of oil and gas field volumes, and systematic tabulations of geological variables o
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Finkelstein Joseph and Jeong In cheol. "Using Heart Rate Variability for Automated Identification of Exercise Exertion Levels." In Studies in Health Technology and Informatics. IOS Press, 2015. https://doi.org/10.3233/978-1-61499-488-6-137.

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Heart rate monitoring is being used to estimate activity of autonomous nervous system by analysing heart rate variability (HRV). HRV has been recently shown to be effective means to monitor efficacy of exercise in patients with cardiovascular conditions and older adults. Whether HRV can be used to identify exercise exertion levels is unknown. There are multiple approaches to analyse HRV however it is not clear which approach is optimal in assessing cycling exercise. Previous studies demonstrated potential of analysis of short-term sequences of beat-by-beat heart rate data in a time domain for
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Patlasov, Oleg Y., and Olga K. Mzhelskaya. "Scoring Modeling in Estimating the Financial Condition of Russian Agro-Industrial Companies." In Global Trends of Modernization in Budgeting and Finance. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7760-7.ch008.

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The chapter presents the authors' estimations according to the scoring modeling techniques; also, internationally spread models of bankruptcy forecasting are systematized. Advantages and disadvantages of dynamic modelling methods as applied to financial condition assessment are presented here. Methodological problems of financial modelling are explained here in detail. Regression, logit-regression, and discriminant models are built on the basis of data on the Rosselkhozbank and Sberbank of Russia regulations, taking into account the agrarian specifics of organizations and regional specificity
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Goyani, Mahesh. "Nonverbal Communication through Facial Expression in Diverse Conditions." In Types of Nonverbal Communication [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.95109.

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In this chapter, we investigated computer vision technique for facial expression recognition, which increase both - the recognition rate and computational efficiency. Local and global appearance-based features are combined in order to incorporate precise local texture and global shapes. We proposed Multi-Level Haar (MLH) feature based system, which is simple and fast in computation. The driving factors behind using the Haar were its two interesting properties - signal compression and energy preservation. To depict the importance of facial geometry, we first segmented the facial components like
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Intrator, Nathan. "Robust Prediction in Many-parameter Models." In Statistics and Neural Networks. Oxford University PressOxford, 2000. http://dx.doi.org/10.1093/oso/9780198524229.003.0004.

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Abstract When parameter estimation is based on a set of training patterns with size that is of the order of the number of free parameters, estimation may become very unreliable. Until recently, estimation in such cases had sounded unrealistic, but it has now been accepted that such estimation is possible under certain conditions. For example, linear discriminant analysis (Fisher, 1936) requires some adjustment when the input dimensionality is large (Buckheit and Donoho, 1995) to account for the added variability of the covariance matrices. In simple terms, innovative ways to reduce the varianc
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Conference papers on the topic "Conditional discriminant analysis"

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Hao, Xiaobo, Donghui Pan, and Yongbin Liu. "A Domain Generalization Network with Discriminant Domain-Common Features for Fault Diagnosis Under Unseen Working Conditions." In 2024 International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD). IEEE, 2024. https://doi.org/10.1109/icsmd64214.2024.10920583.

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Newton-Young, Daniel, Mark White, and Neale Watson. "Ship Helicopter Operations: A Machine Learning Approach for Workload Prediction Using Linear Discriminant Analysis." In Vertical Flight Society 81st Annual Forum and Technology Display. The Vertical Flight Society, 2025. https://doi.org/10.4050/f-0081-2025-177.

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This paper demonstrates the training, optimisation, and predictive capabilities of Machine Learning (ML) for helicopter-ship certification. The work focuses on the development of a Linear Discriminant Analysis (LDA) model, trained specifically on pilot control activity data recorded during the hover phase of a recovery to a ship, to determine an operational boundary driven by pilot workload. The certification process currently relies heavily on embarked trials and the subjective workload assessment of test pilots. Modelling and Simulation (M&amp;S), however, offers a potentially more efficient
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Dawson, J. L., R. G. Miller, D. G. John, D. Gearey, and R. A. King. "Inhibitor Evaluation Methodology for Oil Field Applications." In CORROSION 1988. NACE International, 1988. https://doi.org/10.5006/c1988-88361.

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Abstract Many corrosion control programmes in oil and gas production rely on chemical treatments. Inhibitor selection is therefore an important technical and economic aspect of the total corrosion engineering system. However, at present there are no widely accepted procedures which both an operator and chemical supplier could use to mutual advantage for the assessment of inhibitors in sweet, mildly sour and high velocity systems. This paper considers the requirements of various inhibitor evaluation procedures with respect to their ease of laboratory testing and ultimate field applications. Of
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Eckert, Richard B., Henry C. Aldrich, Chris A. Edwards, and Bruce A. Cookingham. "Microscopic Differentiation of Internal Corrosion Initiation Mechanisms in Natural Gas Pipeline Systems." In CORROSION 2003. NACE International, 2003. https://doi.org/10.5006/c2003-03544.

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Abstract An analytical approach that can discriminate between various forms of microscopic corrosion initiation has been successfully employed in natural gas gathering and storage facilities. Subjected to a combination of analytical techniques, steel test coupons for electron microscopy, "EM coupons", provided information about the surface microbiology and internal corrosion of the systems monitored. Optical microscopy, scanning electron microscopy (SEM), Nomarski Differential Interference Contrast (DIC), phase-contrast and epifluorescence microscopy were employed in the coupon analysis protoc
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Loog, M. "Conditional Linear Discriminant Analysis." In 18th International Conference on Pattern Recognition (ICPR'06). IEEE, 2006. http://dx.doi.org/10.1109/icpr.2006.402.

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Huang, Xiaxi, and Nikolaos V. Boulgouris. "Gait recognition using Linear Discriminant Analysis with artificial walking conditions." In 2010 17th IEEE International Conference on Image Processing (ICIP 2010). IEEE, 2010. http://dx.doi.org/10.1109/icip.2010.5652564.

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Hatzopoulos, S. D., and C. S. Lessard. "Discriminant analysis of heart valve sounds during respiratory static volume conditions." In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 1988. http://dx.doi.org/10.1109/iembs.1988.94462.

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Indrawan, Natarianto, Rupendranath Panday, Lawrence J. Shadle, and Umesh K. Chitnis. "Data Analytics Applied to Coal Fired Boilers for Detecting Leaks." In ASME 2020 Power Conference collocated with the 2020 International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/power2020-16912.

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Abstract Data analytics were used to detect boiler leaks from five different coal-fired boilers including both subcritical and supercritical systems. Discriminant functions were developed that detected leaks up to two weeks prior to forced plant shutdowns for repairs. The leaks were identified to occur at different sections of the boiler for each plant, including waterwalls, economizer and superheater using conventional process measurement data. Leaking conditions were detected with a high degree of confidence (≪ 1% misclassified observations) and were able to distinguish normal operations fro
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Wang, Ke, Jinzhong Li, Shuqi Zhang, et al. "A new group of image features derived from two-dimensional linear discriminant analysis for partial discharge pattern recognition." In 2016 International Conference on Condition Monitoring and Diagnosis (CMD). IEEE, 2016. http://dx.doi.org/10.1109/cmd.2016.7757967.

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Khandaker, Noman, Ruxin Zhang, Shuzhi Dong, Bin Xu, Zhifeng Zhang, and Guangrui Wen. "Application of unsupervised linear discriminant analysis for condition monitoring of rotating machinery." In 2017 9th International Conference on Modelling, Identification and Control (ICMIC). IEEE, 2017. http://dx.doi.org/10.1109/icmic.2017.8321687.

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Reports on the topic "Conditional discriminant analysis"

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Stuart, Nicole, Karina Dorrington, Andrew Sheridan, and Carmela Pestell. The Neuropsychological Correlates of Sluggish Cognitive Tempo: A Systematic Review Protocol. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2022. http://dx.doi.org/10.37766/inplasy2022.8.0102.

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Review question / Objective: The objective the current review is to delineate the cognitive profile of SCT, particularly where it is similar to or different from ADHD-related inattention. In addition, the review will provide an analysis of methodological factors that might account for discrepancies in research findings and guidance for future studies. Condition being studied: Sluggish cognitive tempo (SCT) is a constellation of symptoms originally identified among children with the inattentive subtype of attention deficit hyperactivity disorder (ADHD-I). These symptoms include daydreaming, inc
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Zhao, George, Grang Mei, Bulent Ayhan, Chiman Kwan, and Venu Varma. DTRS57-04-C-10053 Wave Electromagnetic Acoustic Transducer for ILI of Pipelines. Pipeline Research Council International, Inc. (PRCI), 2005. http://dx.doi.org/10.55274/r0012049.

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In this project, Intelligent Automation, Incorporated (IAI) and Oak Ridge National Lab (ORNL) propose a novel and integrated approach to inspect the mechanical dents and metal loss in pipelines. It combines the state-of-the-art SH wave Electromagnetic Acoustic Transducer (EMAT) technique, through detailed numerical modeling, data collection instrumentation, and advanced signal processing and pattern classifications, to detect and characterize mechanical defects in the underground pipeline transportation infrastructures. The technique has four components: (1) thorough guided wave modal analysis
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Borgonovi, Sara Margherita, Stefania Iametti, and Mattia Di Nunzio. Docosahexaenoic acid as master regulator of cellular antioxidant defenses: a systematic review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2023. http://dx.doi.org/10.37766/inplasy2023.6.0017.

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Review question / Objective: Evaluate the potential effect of DHA in regulating cellular antioxidant enzymes and hypothesizes possible molecular scenarios between DHA and Nrf2 in regulating cellular antioxidant defenses. Eligibility criteria: Chosen studies were published between 1998 and 2021 without restriction regarding pe-riod or publication status. Exclusion criteria were: (i) titles irrelevant to the research topic; (ii) abstract inappropriate or not related to the research topic; (iii) studies that used n-3 PUFAs rich oils which not allowed to discriminate the effect of DHA from other n
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Gantzer, Clark J., Shmuel Assouline, and Stephen H. Anderson. Synchrotron CMT-measured soil physical properties influenced by soil compaction. United States Department of Agriculture, 2006. http://dx.doi.org/10.32747/2006.7587242.bard.

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Methods to quantify soil conditions of pore connectivity, tortuosity, and pore size as altered by compaction were done. Air-dry soil cores were scanned at the GeoSoilEnviroCARS sector at the Advanced Photon Source for x-ray computed microtomography of the Argonne facility. Data was collected on the APS bending magnet Sector 13. Soil sample cores 5- by 5-mm were studied. Skeletonization algorithms in the 3DMA-Rock software of Lindquist et al. were used to extract pore structure. We have numerically investigated the spatial distribution for 6 geometrical characteristics of the pore structure of
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