01394nam a2200397 i 4500991000292789707536090616s2007 sz b 001 0 eng d9783037190333b13837114-39ule_instDip.to Matematicaeng515.353AMS 34D05AMS 35B25AMS 35B40AMS 35J20AMS 35J70AMS 35K55AMS 35K65LC QA378.D37Daskalopoulos, Panagiota471521Degenerate diffusions :initial value problems and local regularity theory /Panagiota Daskalopoulos, Carlos E. KenigZurich :European Mathematical Society,c2007vii, 198 p.;25 cmEMS tracts in mathematics ;1Includes bibliographical references (p. [187]-193) and indexReaction-diffusion equationsCauchy problemDirichlet problemPorous materialsMathematical modelsKenig, Carlos E..b1383711428-01-1416-06-09991000292789707536LE013 34D DAS11 (2007)12013000210728le013pE48.00-l- 01010.i1498293616-06-09Degenerate diffusions229130UNISALENTOle01316-06-09ma -engsz 0000957nam0 2200253 450 00003799120250508130116.088-453-1183-X20250508d2002----km-y0itay50------baitaITy-------001yy«La »gestione delle risorse umane nei distretti industrialilavoro e partecipazione nelle piccole e medie impreseSergio AlbertiniMilanoEtas2002VII, 241 p. ; 24 cm.2001«La »gestione delle risorse umane nei distretti industriali4373321338.6042094522Organizzazione della produzione. Localizzazione. Italia.Albertini,Sergio116941ITUNIPARTHENOPE20250508REICATUNIMARC000037991DISAE 511/2058479 ex St.Az.NAVA22025«La »gestione delle risorse umane nei distretti industriali4373321UNIPARTHENOPE05465nam 22007094a 450 991102043910332120200520144314.0978661026968697804706676060470667605978047086324404708632429781280269684128026968597804708457450470845740(CKB)1000000000355613(EBL)158117(SSID)ssj0000120641(PQKBManifestationID)11134570(PQKBTitleCode)TC0000120641(PQKBWorkID)10102333(PQKB)10034379(MiAaPQ)EBC158117(OCoLC)85819892(Perlego)2755350(EXLCZ)99100000000035561320020628d2003 uy 0engur|n|---|||||txtccrChemometrics data analysis for the laboratory and chemical plant /Richard BreretonChichester, West Sussex, England ;Hoboken, NJ Wileyc20031 online resource (505 p.)Description based upon print version of record.9780471489771 0471489778 9780471489788 0471489786 Includes bibliographical references (p. 12-13) and index.Chemometrics; Contents; Preface; Supplementary Information; Acknowledgements; 1 Introduction; 1.1 Points of View; 1.2 Software and Calculations; 1.3 Further Reading; 1.3.1 General; 1.3.2 Specific Areas; 1.3.3 Internet Resources; 1.4 References; 2 Experimental Design; 2.1 Introduction; 2.2 Basic Principles; 2.2.1 Degrees of Freedom; 2.2.2 Analysis of Variance and Comparison of Errors; 2.2.3 Design Matrices and Modelling; 2.2.4 Assessment of Significance; 2.2.5 Leverage and Confidence in Models; 2.3 Factorial Designs; 2.3.1 Full Factorial Designs; 2.3.2 Fractional Factorial Designs2.3.3 Plackett-Burman and Taguchi Designs2.3.4 Partial Factorials at Several Levels: Calibration Designs; 2.4 Central Composite or Response Surface Designs; 2.4.1 Setting Up the Design; 2.4.2 Degrees of Freedom; 2.4.3 Axial Points; 2.4.4 Modelling; 2.4.5 Statistical Factors; 2.5 Mixture Designs; 2.5.1 Mixture Space; 2.5.2 Simplex Centroid; 2.5.3 Simplex Lattice; 2.5.4 Constraints; 2.5.5 Process Variables; 2.6 Simplex Optimisation; 2.6.1 Fixed Sized Simplex; 2.6.2 Elaborations; 2.6.3 Modified Simplex; 2.6.4 Limitations; Problems; 3 Signal Processing; 3.1 Sequential Signals in Chemistry3.1.1 Environmental and Geological Processes3.1.2 Industrial Process Control; 3.1.3 Chromatograms and Spectra; 3.1.4 Fourier Transforms; 3.1.5 Advanced Methods; 3.2 Basics; 3.2.1 Peakshapes; 3.2.2 Digitisation; 3.2.3 Noise; 3.2.4 Sequential Processes; 3.3 Linear Filters; 3.3.1 Smoothing Functions; 3.3.2 Derivatives; 3.3.3 Convolution; 3.4 Correlograms and Time Series Analysis; 3.4.1 Auto-correlograms; 3.4.2 Cross-correlograms; 3.4.3 Multivariate Correlograms; 3.5 Fourier Transform Techniques; 3.5.1 Fourier Transforms; 3.5.2 Fourier Filters; 3.5.3 Convolution Theorem; 3.6 Topical Methods3.6.1 Kalman Filters3.6.2 Wavelet Transforms; 3.6.3 Maximum Entropy (Maxent) and Bayesian Methods; Problems; 4 Pattern Recognition; 4.1 Introduction; 4.1.1 Exploratory Data Analysis; 4.1.2 Unsupervised Pattern Recognition; 4.1.3 Supervised Pattern Recognition; 4.2 The Concept and Need for Principal Components Analysis; 4.2.1 History; 4.2.2 Case Studies; 4.2.3 Multivariate Data Matrices; 4.2.4 Aims of PCA; 4.3 Principal Components Analysis: the Method; 4.3.1 Chemical Factors; 4.3.2 Scores and Loadings; 4.3.3 Rank and Eigenvalues; 4.3.4 Factor Analysis4.3.5 Graphical Representation of Scores and Loadings4.3.6 Preprocessing; 4.3.7 Comparing Multivariate Patterns; 4.4 Unsupervised Pattern Recognition: Cluster Analysis; 4.4.1 Similarity; 4.4.2 Linkage; 4.4.3 Next Steps; 4.4.4 Dendrograms; 4.5 Supervised Pattern Recognition; 4.5.1 General Principles; 4.5.2 Discriminant Analysis; 4.5.3 SIMCA; 4.5.4 Discriminant PLS; 4.5.5 K Nearest Neighbours; 4.6 Multiway Pattern Recognition; 4.6.1 Tucker3 Models; 4.6.2 PARAFAC; 4.6.3 Unfolding; Problems; 5 Calibration; 5.1 Introduction; 5.1.1 History and Usage; 5.1.2 Case Study; 5.1.3 Terminology5.2 Univariate CalibrationThis book is aimed at the large number of people who need to use chemometrics but do not wish to understand complex mathematics, therefore it offers a comprehensive examination of the field of chemometrics without overwhelming the reader with complex mathematics. * Includes five chapters that cover the basic principles of chemometrics analysis.* Provides two chapters on the use of Excel and MATLAB for chemometrics analysis.* Contains 70 worked problems so that readers can gain a practical understanding of the use of chemometrics.ChemometricsData processingChemical processesStatistical methodsData processingChemometricsData processing.Chemical processesStatistical methodsData processing.543/.007/27Brereton Richard G283014MiAaPQMiAaPQMiAaPQBOOK9911020439103321Chemometrics86912UNINA