LEADER 06183nam 2200697 450 001 9910145682103321 005 20221206105257.0 010 $a1-281-32292-X 010 $a9786611322922 010 $a0-470-75416-8 010 $a0-470-75415-X 024 7 $a10.1002/9780470754160 035 $a(CKB)1000000000415546 035 $a(EBL)351410 035 $a(SSID)ssj0000237925 035 $a(PQKBManifestationID)11218307 035 $a(PQKBTitleCode)TC0000237925 035 $a(PQKBWorkID)10221855 035 $a(PQKB)11760049 035 $a(MiAaPQ)EBC351410 035 $a(CaBNVSL)mat08040154 035 $a(IDAMS)0b00006485f0e5f3 035 $a(IEEE)8040154 035 $a(PPN)250784904 035 $a(OCoLC)264389630 035 $a(EXLCZ)991000000000415546 100 $a20171024d2008 uy 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aRFID for the optimization of business processes /$fWolf-Ruediger Hansen, Frank Gillert ; translated by Kenneth Cox ; with a contribution from Viola Schmid 210 1$aChichester, England ;$cJohn Wiley & Sons,$dc2008. 210 2$a[Piscataqay, New Jersey] :$cIEEE Xplore,$d[2008] 215 $a1 online resource (300 p.) 300 $aDescription based upon print version of record. 311 $a0-470-72422-6 320 $aIncludes bibliographical references (p. [257]-263) and index. 327 $aContents -- Preface -- Foreword -- 1 Introduction -- 2 Vision, Reality, and Market Drivers -- 2.1 Process Drivers -- 2.2 Security as a Driver -- 2.3 Mandates, Mentors and Sponsors -- 2.4 Technology Drivers -- 3 The RFID Market -- 3.1 The RFID Value Chain -- 3.2 Trends in the RFID Market -- 3.3 Application-Specific Trends in the RFID Market -- 4 Business Process Structures -- 4.1 Evolution from Supply Chain to Supply Net -- 4.2 Strategies for Supply Chain Integration -- 4.3 Business Processes in the Retail and Consumer Goods Industry -- 4.4 Business Processes in the Packaging Industry -- 4.5 Business Processes for Container Systems and Returnable Transport Packaging Systems -- 4.6 Economic Viability Analysis Methods -- 5 Virtual Identities -- 5.1 Object Websites -- 5.2 The EPCglobal Network -- 5.3 RFID Standards -- 5.4 GS1 EANCOM EDI Standard -- 6 IT Architectures and Services -- 6.1 RFID and Higher-Level IT Architectures -- 6.2 Software Agents -- 6.3 Real-time Enterprise Infrastructure -- 7 Auto-ID/RFID Infrastructure -- 7.1 RFID Tags -- 7.2 RFID Readers and Antennas -- 7.3 Near-Field Technology (NFC) -- 7.4 Prerequisites for RFID Infrastructure Implementation -- 7.5 Global Positioning with GPS/GPRS -- 8 Consumer Protection and Data Protection in RFID Applications -- 8.1 RFID and Data Protection -- 8.2 General Data Protection Aspects -- 8.3 Data Protection Legislation Aspects of Scenario 1 -- 8.4 Data Protection Legislation Aspects of Scenario 2 -- 8.5 Data Protection Legislation Aspects of Scenario 3 -- 9 RFID Legislation in a Global Perspective -- 9.1 RFID Scenarios -- 9.2 Fair Information Practices for Personal Data: Traditional Law -- 9.3 Fair Information Practices for RFID Data -- 9.4 RFID Law -- 9.5 RFID and Law: A Summary of the Situation in 2007 -- 10 Applications -- 10.1 Logistics Processes at Hewlett-Packard -- 10.2 Mobile Maintenance at Fraport -- 10.3 Locating Cars at Dat Autohus -- 10.4 Locating Persons in Hazard Areas -- 10.5 Electronic Ticketing in Public Transport Systems. 327 $a10.6 Application Scenarios for NFC Mobile Telephones -- 10.7 Monitoring Components in Computer Centres -- 10.8 Aircraft Seat Quick-Change at Lufthansa -- 10.9 Trolley Asset Management at the Finnish Post Office -- 10.10 Tracking Containers and Products at KPN in the Netherlands -- 10.11 RFID Optimizes Garment Logistics at gardeur -- 10.12 Agent Technology in Intralogistics Systems -- 11 Appendix -- 11.1 Bibliography -- 11.2 Information Sources on the Internet -- 11.3 Glossary -- Index. 330 $aRFID, complemented by other Auto-ID technologies such as Barcode, NFC and sensor technology, can unlock huge benefits for enterprises and users, creating successful businesses with the combination of technology and processes. It is important to have an understanding of all aspects and properties o the technology, in order to see its potential. This solution-oriented book contains a comprehensive overview of RFID, explaining which elements can be applied with respect to specific project environments, and how RFID systems can be integrated into existing IT systems. It includes chapters and project guidelines written by top experts in the industry, covering global privacy issues and the history of EPCglobal, as well as: . a discussion on current trends and developments in the RFID market, and the process-based and technological driers behind it; . a chapter on RFID legislation with a global perspective; . descriptions of practical applications and twelve application scenarios, demonstrating the possibilities that have already been discovered with RFID. RFID for the Optimization of Business Process is a descriptive introduction to the technology for business and technical managers, IT consulting experts and business process designers, as well as marketers of RFID technologies. The text will also be of great use to technical experts interested in business processes and also students studying the subject. 606 $aRadio frequency identification systems$xEconomic aspects 606 $aBar coding 606 $aBusiness logistics$xTechnological innovations 606 $aElectronic data processing 615 0$aRadio frequency identification systems$xEconomic aspects. 615 0$aBar coding. 615 0$aBusiness logistics$xTechnological innovations. 615 0$aElectronic data processing. 676 $a658.05 676 $a658.7/87 700 $aHansen$b Wolf-Ru?diger$0861215 701 $aGillert$b Frank$0861216 801 0$bCaBNVSL 801 1$bCaBNVSL 801 2$bCaBNVSL 906 $aBOOK 912 $a9910145682103321 996 $aRFID for the optimization of business processes$91922079 997 $aUNINA LEADER 05425nam 2200649Ia 450 001 996201249503316 005 20170814180908.0 010 $a1-282-30775-4 010 $a9786612307751 010 $a0-470-31702-7 010 $a0-470-31786-8 035 $a(CKB)1000000000687572 035 $a(EBL)469989 035 $a(OCoLC)476291655 035 $a(SSID)ssj0000343236 035 $a(PQKBManifestationID)11264961 035 $a(PQKBTitleCode)TC0000343236 035 $a(PQKBWorkID)10288447 035 $a(PQKB)11428037 035 $a(MiAaPQ)EBC469989 035 $a(PPN)159316480 035 $a(EXLCZ)991000000000687572 100 $a19981030d1999 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aStatistical modeling by wavelets$b[electronic resource] /$fBrani Vidakovic 210 $aNew York $cWiley$d1999 215 $a1 online resource (410 p.) 225 1 $aWiley series in probability and mathematical statistics. Applied probability and statistics section 300 $a"A Wiley-Interscience publication." 311 $a0-471-29365-2 320 $aIncludes bibliographical references (p. 345-370) and indexes. 327 $aStatistical Modeling by Wavelets; Contents; Preface; Acknowledgments; 1. Introduction; 1.1. Wavelet Evolution; 1.2. Wavelet Revolution; 1.3. Wavelets and Statistics; 1.4. An Appetizer: California Earthquakes; 2. Prerequisites; 2.1. General; 2.2. Hilben Spaces; 2.2.1. Projection Theorem; 2.2.2. 0rthonomal Sets; 2.2.3. Reproducing Kernel Hilberf Spaces; 2.3. Fourier Transformation; 2.3.1. Basic Properties; 2.3.2. Poisson Summation Formula and Sampling Theorem; 2.3.3. Fourier Series; 2.3.4. Discrete Fourier Transform; 2.4. Heisenberg's Uncertainty Principle; 2.5. Some Important Function Spaces 327 $a2.6. Fundanzentals of Signal Processing2.7. Exercises; 3. Wavelets; 3.1. Continuous Wavelet Transformation; 3.1.1. Basic Properties; 3.1.2. Wavelets for Continuous Transfonnations; 3.2. Discretization of the Continuous Wavelet Transform; 3.3. Multiresolution Analysis; 3.3.1. Derivation of a Wavelet Function; 3.4. Same Important Wavelet Bases; 3.4.1. Haar's Wavelets; 3.4.2. Shannon's Wavelets; 3.4.3. Meyer's Wavelets; 3.4.4. Franklin s Wavelets; 3.4.5. Daubechies ' Conzpactly Supporled Wavelets; 3.5. Some Extensions; 3.5.1. Regularity of Wavelets 327 $a3.5.2. The Least Asytnmetric Daubechies ' Wavelets: Symrnlets3.5.3. Approxintations and Characterizations of Functional Spaces; 3.5.4. Daubechies-Lagarias Algorithm; 3.5.5. Moment Conditions; 3.5.6. Interpolating (Cardinal) Wavelets; 3.5.7. Pollen-Type Parameterization of Wavelets; 3.6. Exercises; 4. Discrete Wavelet Transformations; 4.1. Introduction; 4.2. The Cascade Algorithnt; 4.3. The Operator Notation of DWT; 4.3.1. Discrete Wavelet Transfomiations as Linear Transfonnations; 4.4. Exercises; 5. Some Generalizations; 5.1. Coiflets; 5.1.1. Construction of Coifrets 327 $a5.2. Biorthogonal Wavelets5.2.1. Construction of Biorthogonal Wavelets; 5.2.2. B-Spline Wavelets; 5.3. Wavelet Packets; 5.3.1. Basic Properties of Wavelet Packets; 5.3.2. Wavelet Packet Tables; 5.4. Best Basis Selection; 5.4.1. Some Cost Measures and the Best Basis Algorithm; 5.5. ?-Decimated and Stationary Wavelet Transformations; 5.5.1. ?-Decimated Wavelet Transformation; 5.5.2. Stationary (Non-Decimated) Wavelet Transformation; 5.6. Periodic Wavelet Transformations; 5.7. Multivariate Wavelet Transfornations; 5.8. Discussion; 5.9. Exercises; 6. Wavelet Shrinkage; 6.1. Shrinkage Method 327 $a6.2. Lineur Wavelet Regression Estimators6.2.1. Wavelet Kernels; 6.2.2. Local Constant Fit Estimators; 6.3. The Simplest Non-Linear Wavelet Shrinkage: Tliresholding; 6.3.1. Variable Selection and Thresholding; 6.3.2. Oracular Risk for Thresholding Rules; 6.3.3. Why the Wavelet Shrinkage Works; 6.3.4. Almost Sure Convergence of Wavelet Sh rinkuge Est imaf ors; 6.4. General Minimax Paradigm; 6.4.1. Translation of Minimaxity Results to the Wavelet Domain; 6.5. Thresholding Policies and Thresholdkg Rides; 6.5.1. Exact Risk Analysis of Thresholding Rules; 6.5.2. Large Sample Properties 327 $a6.5.3. Some Orher Shrinkage Rules 330 $aA comprehensive, step-by-step introduction to wavelets in statistics.What are wavelets? What makes them increasingly indispensable in statistical nonparametrics? Why are they suitable for ""time-scale"" applications? How are they used to solve such problems as denoising, regression, or density estimation? Where can one find up-to-date information on these newly ""discovered"" mathematical objects? These are some of the questions Brani Vidakovic answers in Statistical Modeling by Wavelets. Providing a much-needed introduction to the latest tools afforded statisticians by wavelet theory, 410 0$aWiley series in probability and mathematical statistics.$pApplied probability and statistics. 606 $aMathematical statistics 606 $aWavelets (Mathematics) 615 0$aMathematical statistics. 615 0$aWavelets (Mathematics) 676 $a515.2433 676 $a519.5 700 $aVidakovic$b Brani$f1955-$0288619 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996201249503316 996 $aStatistical modeling by wavelets$9866473 997 $aUNISA