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Books on the topic 'Factor classification'

Author: Grafiati

Published: 7 June 2025

Last updated: 17 July 2025

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1

L, Lenskiĭ A., ed. Uskorennoe reshenie zadach klassifika͡tsii v faktornom prostranstve bez poteri tochnosti. V͡TS AN SSSR, 1990.

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2

Tidball, Ronald R. Geography of soil geochemistry of Missouri agricultural soils ; Geochemical classification by factor analysis of Missouri agricultural soils. U.S. Dept. of the Interior, Geological Survey, 1985.

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3

Mukherji, Shekhar. Functional classification of Indian towns by factor-cluster method, 1981 and 1991. International Institute for Population Sciences, 1994.

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4

United States. Environmental Protection Agency. Office of Air Quality Planning and Standards, ed. FIRE version 5.0 source classification codes and emission factor listing for criteria air pollutants. Office of Air Quality Planning and Standards, Office of Air and Radiation, U.S. Environmental Protection Agency, 1995.

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5

United States. Environmental Protection Agency. Office of Air Quality Planning and Standards., ed. FIRE version 5.0 source classification codes and emission factor listing for criteria air pollutants. Office of Air Quality Planning and Standards, Office of Air and Radiation, U.S. Environmental Protection Agency, 1995.

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6

United States. Environmental Protection Agency. Office of Air Quality Planning and Standards, ed. FIRE version 5.0 source classification codes and emission factor listing for criteria air pollutants. Office of Air Quality Planning and Standards, Office of Air and Radiation, U.S. Environmental Protection Agency, 1995.

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7

United States. Environmental Protection Agency. Office of Air Quality Planning and Standards, ed. FIRE version 5.0 source classification codes and emission factor listing for criteria air pollutants. Office of Air Quality Planning and Standards, Office of Air and Radiation, U.S. Environmental Protection Agency, 1995.

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8

United States. Environmental Protection Agency. Office of Air Quality Planning and Standards., ed. FIRE version 5.0 source classification codes and emission factor listing for criteria air pollutants. Office of Air Quality Planning and Standards, Office of Air and Radiation, U.S. Environmental Protection Agency, 1995.

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9

United States. Environmental Protection Agency. Office of Air Quality Planning and Standards., ed. FIRE version 5.0 source classification codes and emission factor listing for criteria air pollutants. Office of Air Quality Planning and Standards, Office of Air and Radiation, U.S. Environmental Protection Agency, 1995.

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10

T, Costa Paul, and Widiger Thomas A, eds. Personality disorders and the five-factor model of personality. American Psychological Association, 1994.

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11

Bunde, Armin. The Science of Disasters: Climate Disruptions, Heart Attacks, and Market Crashes. Springer Berlin Heidelberg, 2002.

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12

Salmi, Timo. On the classification of financial ratios: A factor and transformation analysis of accrual, cash flow, and market-based ratios. Universitas Wasaensis, 1990.

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13

Johansson, Ann-Katrin. On dental erosion and associated factors. Department of Cariology, Faculty of Odontology, Sahlgrenska Academy at Göteborg University, 2002.

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14

Shappell, Scott A. The human factors analysis and classification system--HFACS: Final report. Office of Aviation Medicine, U.S. Dept. of Transportation, Federal Aviation Administration, 2000.

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15

Sunteev, Anton. Management of internal reserves to reduce the cost of engineering products. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1141766.

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The monograph presents current trends in the management of internal reserves to reduce the cost of production of machine-building enterprises. The approaches of various scientists to the interpretation of the concept of "enterprise reserve" are analyzed. The classification of the types of reserves of the enterprise is given and supplemented by the classification of the resources that form the reserve. Methodological support for the management of internal reserves for reducing the cost of industrial products and methods for identifying them are presented. A technology for studying the cost of p

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16

P, Porcelli, and Sonino N, eds. Psychological factors affecting medical conditions: A new classification for DSM-V. Karger, 2007.

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17

Wiegmann, Douglas A. A human error analysis of commercial aviation accidents using the human factors analysis and classification system (HFACS): Final report. U.S. Dept. of Transportation, Federal Aviation Administration, Office of Aviation Medicine, 2001.

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18

Petr, Zima, ed. Areal and genetic factors in language classification and description: Africa south of the Sahara. Lincom Europa, 2000.

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19

Section, Texas Natural Resource Conservation Commission I&HW Permits. Guidelines for the classification and coding of industrial and hazardous wastes. 2nd ed. The Commission, 2000.

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20

Reddy, K. R. Final report on special waste categorization study to Hazardous Waste Research and Information Center, State Water Survey Division. Energy and Environmental Affairs Division, Dept. of Energy and Natural Resources, 1985.

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21

Mather, John Russell. The water budget and the distribution of climates, vegetation and soils. C. W. Thornthwaite Associates, Laboratory of Climatology, 1985.

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22

Maes, Dominiek, Marina Sibila, and Maria Pieters, eds. Mycoplasmas in swine. CABI, 2021. http://dx.doi.org/10.1079/9781789249941.0000.

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Abstract This book contains 14 chapters that discuss the genetics, epidemiology, prevalence, pathogenesis, clinical signs, diagnosis, treatment, prevention and control of Mycoplasma infections in pigs. Chapter 1 discusses the phylogenetics and classification of Mycoplasma species in pigs; Chapter 2 describes the genomic diversity and antigenic variation of Mycoplasma hyopneumoniae strains; Chapter 3 discusses the pathogenesis, virulence factor and pathogenicity of Mycoplasma hyopneumoniae; Chapter 4 discusses the molecular epidemiology, risk factors, transmission and prevalence of Mycoplasma h

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23

United States. National Park Service and Geological Survey (U.S.), eds. Hydrogeomorphic classification of wetlands on Mt. Desert Island, Maine, including hydrologic susceptibility factors for wetlands in Acadia National Park. U.S. Dept. of the Interior, U.S. Geological Survey, 2006.

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24

Great Britain. Office of Population Censuses and Surveys., ed. A 1981 socio-economic classification of local and health authorities of Great Britain. H.M.S.O., 1985.

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25

A, Shappell Scott, and United States. Office of Aviation Medicine., eds. A human error analysis of commercial aviation accidents using the human factors analysis and classification system (HFACS). Office of Aviation Medicine, U.S. Dept. of Transportation, Federal Aviation Administration, 2001.

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26

Richardson, D. E. Automated spatial and thematic generalization using a context transformation model: Integrating steering parameters, classification and aggregation hierarchies, reduction factors, and topological structures for multiple abstractions. R&B Publications, 1993.

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27

Workshop on Disability in America, a New Look (2005 Washington, D.C.). Workshop on Disability in America, a New Look: Summary and papers : based on a workshop of the Committee on Disability in America: a New Look, Board on Health Sciences Policy. Edited by Field Marilyn J, Jette Alan M, Martin Linda G. 1947-, and Institute of Medicine (U.S.). Committee on Disability in America: a New Look. National Academies Press, 2006.

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28

Makutchev, Aleksandr. Confederations of the past and present: historical and legal analysis. INFRA-M Academic Publishing LLC., 2024. https://doi.org/10.12737/2138104.

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The monograph is devoted to the study of confederation as a form of government. Based on the analysis of the historical experience of the formation, functioning and disintegration of confederations, the author concretizes the characteristic features of confederations, provides a variant of the classification of confederations, and also highlights the prerequisites for the formation and factors of the disintegration of the most significant confederations of the world from antiquity to the present day, which became the basis for assessing the viability and prospects of this form of government. I

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29

(Editor), J. I. Sprent, and D. Mckey (Editor), eds. Advances in Legume Systematics: The Nitrogen Factor. Royal Botanic Gardens Kew, 1994.

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30

Socio-economic indicators and classification of Arab economies. American University in Cairo Press, 1999.

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31

FIRE version 5.0 source classification codes and emission factor listing for criteria air pollutants. Office of Air Quality Planning and Standards, Office of Air and Radiation, U.S. Environmental Protection Agency, 1995.

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32

Ordered Logit and the Behavioral Risk Factor Surveillance System (2013): Body Mass Index (BMI) Classification. SAGE Publications, Ltd., 2015. http://dx.doi.org/10.4135/9781473961968.

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33

Gordon, Kathryn H., Jill M. Holm-Denoma, Valerie J. Douglas, Ross Crosby, and Stephen A. Wonderlich. The Classification of Eating Disorders. Edited by W. Stewart Agras and Athena Robinson. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190620998.013.1.

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The purpose of this chapter is to elucidate the key issues regarding the classification of eating disorders. To this end, a review of nosological research in the area of eating disorders is presented, with a particular focus on empirically based techniques such as taxometric analysis, latent class analysis, and factor mixture modeling. This is followed by a section outlining areas of overlap between the current Diagnostic and Statistical Manual of Mental Disorders–Fifth Edition (DSM-5) eating disorder categories and their symptoms. Next, eating disorder classification models that are alternati

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34

Bunde, Armin, Hans-Joachim Schellnhuber, and Jürgen Kropp. Science of Disasters: Climate Disruptions, Heart Attacks, and Market Crashes. Springer London, Limited, 2012.

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35

Roth, Martin, and Russell Noyes. Classification, Etiological Factors and Associated Disturbances. Elsevier Science Publishing Company, 1989.

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36

Pneumothorax: Classification, Treatment and Prognostic Factors. Nova Science Pub Inc, 2013.

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37

Aguilar, Elmira. Retinopathy of Prematurity: Classification, Risk Factors and Treatment. Nova Science Publishers, Incorporated, 2015.

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38

Hoste, Eric A. J., John A. Kellum, and Norbert Lameire. Definitions, classification, epidemiology, and risk factors of acute kidney injury. Edited by Norbert Lameire. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199592548.003.0220_update_001.

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The lack of a precise biochemical definition of acute kidney injury (AKI) resulted in at least 35 definitions in the medical literature, which gave rise to a wide variation in reported incidence and clinical significance of AKI, impeded a meaningful comparison of studies.The first part of this chapter describes and discusses different definitions and classification systems of AKI. Patient outcome and the need for renal replacement therapy are directly related to the severity of AKI, an observation that supports the use of a categorical staging system rather than a simple binary descriptor. The

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39

Tanislav, Christian, and Manfred Kaps. Classification. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198722366.003.0003.

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The classification of a cerebrovascular event distils information obtained in the workup and other related case history to a category indicating a specific pathophysiology, with direct implications for the subsequent secondary prevention management. A minimum standard of diagnostics is required for a precise classification. In young stroke victims, the conventional Trial of Org 10172 in Acute Stroke Treatment (TOAST) stroke subtype classification may only address the aetiopathogenesis in 30–60% of the individuals who are affected by vascular risk factors. Applying the criteria defined by TOAST

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40

Hinks, Anne, and Wendy Thomson. Genetics of juvenile rheumatic diseases. Oxford University Press, 2013. http://dx.doi.org/10.1093/med/9780199642489.003.0043.

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Juvenile rheumatic diseases are heterogeneous, complex genetic diseases; to date only juvenile idiopathic arthritis (JIA) has been extensively studied in terms of identifying genetic risk factors. The MHC region is a well-established risk factor but in the last few years candidate gene and genome-wide association studies have been utilized in the search for non-HLA risk factors. There are now an additional 12 JIA susceptibility loci with evidence for association in more than one study. In addition, some subtype-specific associations are emerging. These risk loci now need to be investigated fur

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41

Thomas John I'anson 1875-1 Bromwich. Quadratic Forms and Their Classification by Means of Invariant-Factors. Creative Media Partners, LLC, 2022.

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42

Bromwich, T. J. I'a, J. G. Leathem, and E. T. Whittaker. Quadratic Forms: And Their Classification by Means of Invariant-Factors. Independently Published, 2019.

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43

Sesselmann, Jörg. Empowering Brands with Customer Integration: Classification, Benefits and Success Factors. Springer Gabler. in Springer Fachmedien Wiesbaden GmbH, 2015.

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44

Garcia, Christopher M. Lopez. Handbook on Metabolic Syndrome: Classification, Risk Factors and Health Impact. Nova Science Publishers, Inc., 2012.

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45

Sesselmann, Jörg. Empowering Brands with Customer Integration: Classification, Benefits and Success Factors. Springer Gabler, 2015.

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46

Masuda, Toshihiko, and Reiji Tomatsu. Classification of Actions of Discrete Kac Algebras on Injective Factors. American Mathematical Society, 2017.

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47

Thomas John I'anson 1875-1 Bromwich. Quadratic Forms and Their Classification by Means of Invariant-Factors. Creative Media Partners, LLC, 2022.

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48

Hinks, Anne, and Wendy Thomson. Genetics of juvenile rheumatic diseases. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199642489.003.0043_update_002.

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Juvenile rheumatic diseases are heterogeneous, complex genetic diseases; to date only juvenile idiopathic arthritis (JIA) has been extensively studied in terms of identifying genetic risk factors. The MHC region is a well-established risk factor but in the last few years candidate gene and large-scale genome-wide association studies have been utilized in the search for non-HLA risk factors. There are now 17 JIA susceptibility loci which reach the genome-wide significance threshold for association and a further 7 regions with evidence for association in more than one study. In addition, some su

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49

Hinks, Anne, and Wendy Thomson. Genetics of juvenile rheumatic diseases. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199642489.003.0043_update_003.

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Juvenile rheumatic diseases are heterogeneous, complex genetic diseases; to date only juvenile idiopathic arthritis (JIA) has been extensively studied in terms of identifying genetic risk factors. The MHC region is a well-established risk factor but in the last few years candidate gene and large-scale genome-wide association studies have been utilized in the search for non-HLA risk factors. There are now 17 JIA susceptibility loci which reach the genome-wide significance threshold for association and a further 7 regions with evidence for association in more than one study. In addition, some su

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50

Coates, Laura C., and William J. Taylor. Diagnosis and classification criteria. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198737582.003.0020.

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This chapter covers diagnosis and classification of psoriatic arthritis (PsA). Firstly the difference between diagnosis and classification criteria in terms of their design, function, and performance is discussed. The diagnostic clues of PsA are summarized: risk factors for development of arthritis amongst patients with psoriasis, signs, and symptoms of articular, entheseal and axial disease, and relevant investigations. Older classification criteria for PsA are discussed along with later modifications. The development of the CASPAR criteria is described and subsequent studies assessing the ac

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