LEADER 11061nam 2200529 450 001 9910488697303321 005 20231110223517.0 010 $a3-030-71198-6 035 $a(CKB)5590000000516500 035 $a(MiAaPQ)EBC6676159 035 $a(Au-PeEL)EBL6676159 035 $a(OCoLC)1257782102 035 $a(PPN)260307122 035 $a(EXLCZ)995590000000516500 100 $a20220328d2021 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aGeoComputation and public health $ea spatial approach /$fGouri Sankar Bhunia and Pravat Kumar Shit 210 1$aCham, Switzerland :$cSpringer,$d[2021] 210 4$d©2021 215 $a1 online resource (320 pages) 225 1 $aSpringer Geography 311 $a3-030-71197-8 327 $aIntro -- Foreword -- Preface -- Acknowledgements -- Disclaimer -- Contents -- About the Authors -- Abbreviation -- Chapter 1: Introduction to GeoComputation -- 1.1 Concept of GeoComputation -- 1.2 GeoComputation vs Geography -- 1.2.1 Geoposition -- 1.2.2 Geoprojection -- 1.2.3 Geodisplacement -- 1.2.4 Geodistance -- 1.2.5 Geonearest -- 1.2.6 Geoidentify -- 1.3 GeoComputation vs GIS -- 1.4 Advantages of GeoComputation -- 1.5 Future of GeoComputation -- 1.5.1 GeoQuantum Computation -- 1.5.2 Data Science -- 1.5.3 Data Science and GeoComputation -- 1.5.4 Internet of Things (IOT) and GeoComputation -- 1.5.5 Develop Project on Practical Interest -- 1.5.6 Must Develop Data Scientific Standards -- 1.5.7 Grab Bag of Problem-Solving Techniques of Varying Degrees of Practical Utility -- 1.5.8 Develop a Coherent Perspective on Geographical Space -- 1.5.9 Must Swap in Commands That Most Perceptively Analogus and Mutually Inspiring Computational Growths of the Information Age -- 1.6 Problems for GeoComputation -- 1.7 Conclusion -- References -- Chapter 2: GeoComputation and Spatial Data Operation -- 2.1 Spatial Data Operation -- 2.1.1 Spatial Subsetting -- 2.1.2 Topological Relations -- 2.1.3 Spatial Joining -- 2.1.4 Spatial Data Aggregation -- 2.1.5 Issues and Problems -- 2.2 Spatial Query in GeoComputation -- 2.3 Spatial Overlay -- 2.3.1 Types of Spatial Overlay -- 2.3.1.1 Spatial Overlay Operators -- 2.3.1.2 Buffer Operation -- 2.4 Voronoi Diagram -- 2.5 Map Algebra -- 2.5.1 Local Operations -- 2.5.2 Focal Operation -- 2.5.3 Zonal Operation -- 2.5.4 Global Operations -- 2.6 Data Formats -- 2.7 Web Services and GeoComputation -- References -- Chapter 3: E-Research and GeoComputation in Public Health -- 3.1 Introduction -- 3.2 Usefulness in E-Research in Public Health -- 3.2.1 Internet of Things (IoT) and Public Health -- 3.2.2 Cloud Computing for Healthcare. 327 $a3.2.3 Fog Computing for Healthcare -- 3.2.4 Internet of m-Health Things (mIoT) -- 3.2.5 Cognitive IoT (CioT) -- 3.2.6 Smartphone Solutions in Healthcare -- 3.3 Spatio-temporal Data Mining and Intelligent Service of Public Health -- 3.3.1 Spatial and Spatio-temporal Data -- 3.3.2 Data Attributes and Relationships -- 3.3.3 Spatial and Spatio-temporal Statistics for Public Health Data -- 3.3.4 Data and GeoComputational Analysis in Public Health -- 3.3.4.1 Clustering -- 3.3.4.2 Predictive Learning -- 3.3.4.3 Change Detection -- 3.3.4.4 Relationship Mining -- 3.4 Theories and Models of GeoComputation for Public Health -- 3.4.1 Spatial Microsimulation Model (SMM) -- 3.4.2 Agent-Based Model (ABM) -- 3.4.3 Local Intensity Estimation -- 3.4.4 Restricted and Unrestricted Monte Carlo Process -- 3.4.5 Unrestricted and Controlled Monte Carlo -- 3.4.6 Geographic Machine Analysis -- 3.4.6.1 Moran's Index -- 3.4.6.2 CUSUM Chart -- 3.4.6.3 Space-Time Accessibility -- 3.4.6.4 Spatio-temporal Conditional Autoregressive (STCAR) -- 3.5 Accuracy and Uncertainty of GeoComputational Models for Public Health -- 3.5.1 Data Error -- 3.5.2 Positional Error -- 3.5.3 Cartographic Confounding -- 3.5.4 Misclassification -- 3.5.5 Spatial Extent -- 3.5.6 Spatial Weights -- 3.5.7 Spatial Modelling -- 3.6 A Tiered Approach to Accuracy and Uncertainty -- 3.7 Conclusion -- References -- Chapter 4: GeoComputation and Geo-visualization in Public Health -- 4.1 Introduction -- 4.2 Exploratory Visual Analysis of Public Health Data -- 4.2.1 Visual Query -- 4.2.2 Temporal Pattern Mining -- 4.2.2.1 Frequent Pattern Miner -- 4.2.2.2 Statistical Pattern Analyser -- 4.2.3 Interactive Visualization -- 4.3 Exploration of Public Health Data on 2-D, 3-D and 4-D -- 4.4 Exploratory Analysis of Clustering of Public Health Data -- 4.4.1 Spatial Search Processes -- 4.4.2 Network-Based Cluster Detection. 327 $a4.4.3 Statistical Analysis and Modelling of Local Clusters -- 4.4.4 Space-Time Cluster Detection Methods -- 4.5 Mashups in Epidemiology -- 4.5.1 Basic Components of Mashups in Public Health Data -- 4.5.2 Geotagging -- 4.6 Visual Approaches to Data Exploration and Knowledge Construction -- 4.6.1 Population Mapping -- 4.6.2 Point Epi-units -- 4.6.3 Aggregated Mapping -- 4.6.4 Gridded Maps -- 4.7 Challenges of Geo-visualization and GeoComputational Analysis in Public Health -- 4.7.1 Data Containers -- 4.7.2 Data Privacy -- 4.7.3 Evolution Data Standards -- 4.7.4 Interface Challenges -- 4.7.5 Geography -- 4.7.6 Data Reporting -- 4.8 Conclusion -- References -- Chapter 5: GeoComputation and Disease Exploration -- 5.1 Introduction -- 5.2 Issues of Exploration in Public Health Through GeoComputation -- 5.3 Data Availability and Quality -- 5.4 Data Protection and Confidentiality -- 5.5 Exposure Assessment and Mapping -- 5.6 Application Services and Decision Modelling -- 5.7 The Ecologic Fallacy and the Atomistic Fallacy -- 5.8 Spatial Scale of Disease Exploration -- 5.8.1 Definitions of Spatial Scale -- 5.8.2 Cartographic Scale -- 5.8.3 Geographic Scale -- 5.8.4 Ecological Scale -- 5.8.5 Operational Scale -- 5.8.6 Modelling Scale -- 5.8.7 Policy Scale -- 5.9 GeoComputation in Epidemiological Analysis -- 5.10 GeoComputation and Spatio-temporal Trends -- 5.11 Spatio-temporal Analysis of Epidemic Phenomenon -- 5.11.1 Scan Statistics -- 5.11.2 Lattice Statistics -- 5.11.3 Topological Relationship Patterns -- 5.11.4 Spatio-temporal Neighbourhood -- 5.11.5 Collocation Pattern -- 5.12 Spatio-temporal Point Process -- 5.12.1 Gaussian Kernel Density Analysis (GKDA) -- 5.12.2 Average Nearest Neighbour (ANN) Distance -- 5.12.3 ST-DBSCAN -- 5.13 Spatio-temporal Outlier -- 5.13.1 Outliers in Spatial Time Series -- 5.13.2 Flow Anomalies. 327 $a5.13.3 Anomalous Moving Object Trajectories -- 5.14 Spatio-temporal Couplings and Tele-couplings -- 5.14.1 Spatio-temporal Sequential Pattern -- 5.14.2 Cascading Spatio-temporal Patterns -- 5.14.3 Spatial Time Series and Tele-connection -- 5.15 Spatio-temporal Prediction -- 5.15.1 Spatio-temporal Autoregressive Regression (STAR) -- 5.15.2 Spatio-temporal Kriging -- 5.15.3 Hierarchical Dynamic Spatio-temporal Models -- 5.16 Spatio-temporal Clustering -- 5.16.1 Spatio-temporal Event Partitioning -- 5.16.2 Spatial Time-Series Partitioning -- 5.16.3 Trajectory Data Partitioning -- 5.16.4 Spatio-temporal Summarization -- 5.17 Spatio-temporal Hotspots -- 5.17.1 Clustering-Based Approaches -- 5.17.1.1 Diagnostics for Spatio-temporal Clustering -- 5.17.1.2 Cylindrical Space-Time Analysis -- 5.17.2 Spatio-temporal Scan Statistics-Based Approaches -- 5.18 Spatio-temporal Analysis Tools -- 5.18.1 Softwares -- 5.18.2 Spatial Statistical Tools -- 5.18.3 Spatial Database Management Systems -- 5.18.4 Spatial Big Data Platform -- 5.19 Conclusion -- References -- Chapter 6: GeoComputation and Disease Ecology -- 6.1 Introduction -- 6.2 Basics of Host-Parasite Ecology -- 6.3 Emerging Infectious Diseases -- 6.4 History of Development -- 6.5 Role of GeoComputation in Disease Ecology -- 6.5.1 Progress and Improvement in Remote Sensing Satellites and Sensors for Environmental Assessment -- 6.5.2 Airborne Remote Sensing Era -- 6.5.3 Rudimentary Space-Borne Satellite Remote Sensing Era -- 6.5.4 Spy Satellite Remote Sensing Era -- 6.5.5 Meteorological Satellite Sensor Remote Sensing Era -- 6.5.6 Landsat Era -- 6.5.7 Earth Observing System Era -- 6.5.8 New Millennium Era -- 6.5.9 Private Industry Era -- 6.5.10 Analysis of Environmental Variables from Remote Sensing Data -- 6.6 Weather Variables and Disease Ecology: Case Study Through GeoComputation Technique. 327 $a6.6.1 Climate and Pathogens -- 6.6.1.1 Temperature -- 6.6.1.2 Precipitation -- 6.6.1.3 Relative Humidity -- 6.6.1.4 Sunshine -- 6.6.1.5 Wind -- 6.6.2 Climate and Vectors/Hosts -- 6.6.2.1 Temperature -- 6.6.2.2 Rainfall -- 6.6.2.3 Relative Humidity -- 6.6.2.4 Wind -- 6.6.2.5 Sunshine -- 6.6.3 Climate and the Spread of Diseases -- 6.6.3.1 Temperature -- 6.6.3.2 Wind and Dust Storms -- 6.6.4 Climate and Disease Transmission -- 6.6.5 Extreme Weather Events and Disease Transmission -- 6.6.6 Role of GeoComputation for Climatic Data Acquisition and Analysis -- 6.6.6.1 Precipitation -- 6.6.6.2 Air Temperature -- 6.7 Case Study: Association with Kala-Azar Incidence and Climate -- 6.7.1 Temperature and Kala-Azar Incidence -- 6.7.2 Relative Humidity and Kala-Azar Incidence -- 6.7.3 Association Between Rainfall and Kala-Azar Incidence -- 6.8 Topography and Disease Ecology: Case Study Through GeoComputation Technique -- 6.8.1 Vector-Borne Disease Transmission vs. Topography -- 6.8.2 Waterborne Disease vs. Topography -- 6.8.3 Neurological Infections vs. Topography -- 6.8.4 Respiratory Infections vs. Topography -- 6.8.5 Other Infections vs. Topography -- 6.8.6 Identification of Topographic Variables and GeoComputational Technology -- 6.9 Case Study: Spatial Association Between Kala-Azar Incidence and Absolute Relief -- 6.10 Surface Water Bodies and Disease Ecology: Case Study Through GeoComputation Technique -- 6.11 Identification of Surface Water Bodies Using GeoComputation -- 6.11.1 Case Study: Automatic Detection of Open Water Bodies to Map Malaria Incidence -- 6.12 Green Biomass and Disease Ecology: Case Study Through GeoComputation Technique -- 6.12.1 Malaria Transmission and Green Biomass Ecology -- 6.12.2 Filariasis and Green Biomass Ecology -- 6.13 Satellite-Derived Vegetation Indices and Disease Pattern. 327 $a6.13.1 Case Study: Acute Encephalitis Syndromes (AES) and Green Biomass. 410 0$aSpringer Geography 606 $aPublic health$xGeographic information systems 606 $aCommunicable diseases$xPrevention$xGeographic information systems 615 0$aPublic health$xGeographic information systems. 615 0$aCommunicable diseases$xPrevention$xGeographic information systems. 676 $a362.1 700 $aBhunia$b Gouri Sankar$0913309 702 $aShit$b Pravat Kumar 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910488697303321 996 $aGeoComputation and public health$92819003 997 $aUNINA LEADER 03989nam 2200661 450 001 9910806237703321 005 20230124194012.0 010 $a1-5015-0575-0 010 $a1-5015-0581-5 024 7 $a10.1515/9781501505751 035 $a(CKB)3710000001091946 035 $a(DE-B1597)477970 035 $a(OCoLC)979743573 035 $a(DE-B1597)9781501505751 035 $a(Au-PeEL)EBL4822115 035 $a(CaPaEBR)ebr11360472 035 $a(OCoLC)979153849 035 $a(CaSebORM)9781501505812 035 $a(MiAaPQ)EBC4822115 035 $a(EXLCZ)993710000001091946 100 $a20170327h20172017 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aHarnessing the UEFI shell $emoving the platform beyond DOS /$fMichael Rothman, Vincent Zimmer, Tim Lewis 205 $aSecond edition. 210 1$aBoston, [Massachusetts] ;$aBerlin, [Germany] :$cDe|G Press,$d2017. 210 4$d?2017 215 $a1 online resource (326 pages) $cillustrations 300 $aIncludes index. 311 $a1-5015-1480-6 327 $tFrontmatter -- $tPreface -- $tContents -- $tChapter 1. Introduction -- $tChapter 2. Under the UEFI Shell -- $tChapter 3. What Is the UEFI Shell? -- $tChapter 4. Why We Need an Execution Environment before the OS -- $tChapter 5. Manufacturing -- $tChapter 6. Bare Metal Provisionig -- $tChapter 7. Configuration of Provisioned Material -- $tChapter 8. The Use of UEFI for Diagnostics -- $tChapter 9. UEFI Shell Scripting -- $tChapter 10. UEFI Shell Programming -- $tChapter 11. Managing UEFI Drivers Using the Shell -- $tAppendix A. Security Considerations -- $tAppendix B. Command Reference -- $tAppendix C. Programming Reference -- $tAppendix D. UEFI Shell Library -- $tIndex 330 $aFocusing on the use of the UEFI Shell and its recently released formal specification, this book unlocks a wide range of usage models which can help people best utilize the shell solutions. This text also expands on the obvious intended utilization of the shell and explains how it can be used in various areas such as security, networking, configuration, and other anticipated uses such as manufacturing, diagnostics, etc. Among other topics, Harnessing the UEFI Shell demonstrates how to write Shell scripts, how to write a Shell application, how to use provisioning options and more. Since the Shell is also a UEFI component, the book will make clear how the two things interoperate and how both Shell developers as well as UEFI developers can dip into the other's field to further expand the power of their solutions. Harnessing the UEFI Shell is authored by the three chairs of the UEFI working sub-teams, Michael Rothman (Intel, chair of the UEFI Configuration and UEFI Shell sub-teams), Vincent Zimmer (Intel, chair of the UEFI networking sub-team and security sub-team), and Tim Lewis (Insyde Software, chair of the UEFI security sub-team). This book is perfect for any OEMs that ship UEFI-based solutions (which is all of the MNCs such as IBM, Dell, HP, Apple, etc.), software developers who are focused on delivering solutions targeted to manufacturing, diagnostics, hobbyists, or stand-alone kiosk environments. 606 $aComputer firmware 606 $aCommand languages (Computer science) 610 $aBIOS. 610 $aBoot. 610 $aEFI. 610 $aFirmware. 610 $aRegistry. 610 $aUEFI. 610 $aUnified Extensible Firmware Interface. 615 0$aComputer firmware. 615 0$aCommand languages (Computer science) 676 $a005.434 686 $aCOM011000$2bisacsh 700 $aRothman$b Michael$f1969-$01639404 702 $aZimmer$b Vincent 702 $aLewis$b Tim$f1968- 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910806237703321 996 $aHarnessing the UEFI shell$93982357 997 $aUNINA LEADER 00985nam0 22002531i 450 001 UON00332965 005 20231205104227.914 100 $a20090923d1949 |0itac50 ba 101 $aspa 102 $aMX 105 $a|||| ||||| 200 1 $aAmerica en el espiritu francés del siglo XVIII$fSilvio Zavala 210 $aMaxico$cEdicion de el Colegio Nacional$d1949 215 $a314 p.$d25 cm. 606 $aAmerica$xStudi generali$3UONC038430$2FI 620 $aMX$dCiudad de México$3UONL003354 700 1$aZAVALA$bSilvio A.$3UONV116897$0254737 712 $aEdicion de el Colegio Nacional$3UONV276158$4650 801 $aIT$bSOL$c20250815$gRICA 899 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$2UONSI 912 $aUON00332965 950 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$dSI EUR C B 0107 $eSI MR 52478 5 0107 996 $aAmerica en el espiritu francés del siglo XVIII$91366153 997 $aUNIOR