LEADER 01495nam0 22003733i 450 001 CAG0978651 005 20170908093259.0 010 $a8804549572 100 $a20081007d2005 ||||0itac50 ba 101 | $aita 102 $ait 181 1$6z01$ai $bxxxe 182 1$6z01$an 200 1 $a˜Il ÂœSanto Graal$euna catena di misteri lunga duemila anni$fMichael Baigent, Richard Leigh, Henry Lincoln$gtraduzione di Roberta Rambelli 210 $a[Milano]$cMondadori$d2005 215 $a594 p.$cill.$d19 cm. 225 | $a˜I Âœmiti$v319 410 0$1001RMR0047277$12001 $a˜I Âœmiti$v319 500 10$a˜The Âœholy blood and the Holy Grail. -$3CFI0075221$9CFIV047726$920248 620 $aIT$dMilano$3MUSL002184 700 1$aBaigent$b, Michael$3CFIV047726$4070$0532737 701 1$aLeigh$b, Richard$f <1943-2007>$3CFIV047727$4070$0559768 701 1$aLincoln$b, Henry$3CFIV047728$4070$0615543 702 1$aRambelli$b, Roberta$3CFIV007617 790 1$aRainbell$b, Robert$3BVEV239000$zRambelli, Roberta 790 1$aRambelli Pollini$b, Roberta$3CFIV039207$zRambelli, Roberta 790 1$aPollini Rambelli$b, Roberta$3CFIV117860$zRambelli, Roberta 801 3$aIT$bIT-NA0079$c20081007 850 $aIT-AV0151 912 $aCAG0978651 950 0$aBiblioteca del Convento Frati Minori$d CFA 16.1.14$e CF 0000023505 B v. 1$fD $h20081007$i20081007 977 $a CF 996 $aHoly blood and the holy grail$920248 997 $aUNISANNIO LEADER 04096oam 22007095 450 001 9910785150903321 005 20231129201408.0 010 $a1-282-76700-3 010 $a9786612767005 010 $a1-4008-2357-9 024 7 $a10.1515/9781400823574 035 $a(CKB)2670000000044693 035 $a(EBL)668957 035 $a(OCoLC)51478992 035 $a(SSID)ssj0000433353 035 $a(PQKBManifestationID)12176528 035 $a(PQKBTitleCode)TC0000433353 035 $a(PQKBWorkID)10390324 035 $a(PQKB)10657737 035 $a(SSID)ssj0000106190 035 $a(PQKBManifestationID)11128651 035 $a(PQKBTitleCode)TC0000106190 035 $a(PQKBWorkID)10108186 035 $a(PQKB)11217124 035 $a(DE-B1597)446202 035 $a(OCoLC)979628985 035 $a(DE-B1597)9781400823574 035 $a(MiAaPQ)EBC668957 035 $a(EXLCZ)992670000000044693 100 $a20190708d2001 fy 0 101 0 $aeng 135 $aur|nu---|u||u 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 14$aThe artless Jew $emedieval and modern affirmations and denials of the visual /$fKalman P. Bland 205 $aCourse Book 210 1$aPrinceton, N.J. :$cPrinceton University Press,$d[2001] 210 4$d©2001 215 $a1 online resource (248 pages) $cillustrations 300 $aDescription based upon print version of record. 311 0 $a0-691-08985-X 320 $aIncludes bibliography and index. 327 $tFront matter --$tContents --$tAcknowledgments --$tIntroduction --$tOne. Modern Denials and Affirmations of Jewish Art: Germanophone Origins and Themes --$tTwo. Anglo-American Variations --$tThree. The Premodern Consensus --$tFour. The Well-Tempered Medieval Sensorium --$tFive. Medieval Beauty and Cultural Relativism --$tSix. Twelfth-Century Pilgrims, Golden Calves, and Religious Polemics --$tSeven. The Power and Regulation of Images in Late Medieval Jewish Society --$tNotes --$tBibliography --$tIndex 330 $aConventional wisdom holds that Judaism is indifferent or even suspiciously hostile to the visual arts due to the Second Commandment's prohibition on creating "graven images," the dictates of monotheism, and historical happenstance. This intellectual history of medieval and modern Jewish attitudes toward art and representation overturns the modern assumption of Jewish iconophobia that denies to Jewish culture a visual dimension. Kalman Bland synthesizes evidence from medieval Jewish philosophy, mysticism, poetry, biblical commentaries, travelogues, and law, concluding that premodern Jewish intellectuals held a positive, liberal understanding of the Second Commandment and did, in fact, articulate a certain Jewish aesthetic. He draws on this insight to consider modern ideas of Jewish art, revealing how they are inextricably linked to diverse notions about modern Jewish identity that are themselves entwined with arguments over Zionism, integration, and anti-Semitism. Through its use of the past to illuminate the present and its analysis of how the present informs our readings of the past, this book establishes a new assessment of Jewish aesthetic theory rooted in historical analysis. Authoritative and original in its identification of authentic Jewish traditions of painting, sculpture, and architecture, this volume will ripple the waters of several disciplines, including Jewish studies, art history, medieval and modern history, and philosophy. 606 $aJudaism and art$xHistory of doctrines 606 $aJewish art 606 $aJewish aesthetics 606 $aJews$xIntellectual life 615 0$aJudaism and art$xHistory of doctrines. 615 0$aJewish art. 615 0$aJewish aesthetics. 615 0$aJews$xIntellectual life. 676 $a296.4/6/09 676 $a296.46 700 $aBland$b Kalman P.$f1942-$01527127 801 0$bDE-B1597 801 1$bDE-B1597 906 $aBOOK 912 $a9910785150903321 996 $aThe artless Jew$93769672 997 $aUNINA LEADER 12283nam 2200553 450 001 9910830287903321 005 20231213075707.0 010 $a1-119-98559-5 010 $a1-119-98561-7 035 $a(MiAaPQ)EBC30977889 035 $a(Au-PeEL)EBL30977889 035 $a(EXLCZ)9929095267700041 100 $a20231213d2024 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 14$aThe Power of Artificial Intelligence for the Next-Generation Oil and Gas Industry $eEnvisaging AI-Inspired Intelligent Energy Systems and Environments /$fPethuru Raj Chelliah [and four others] 205 $aFirst edition. 210 1$aHoboken, New Jersey :$cJohn Wiley & Sons, Inc.,$d[2024] 210 4$d©2024 215 $a1 online resource (513 pages) 225 1 $aIEEE Press Series on Power and Energy Systems Series 311 08$aPrint version: Chelliah, Pethuru Raj The Power of Artificial Intelligence for the Next-Generation Oil and Gas Industry Newark : John Wiley & Sons, Incorporated,c2023 9781119985587 320 $aIncludes bibliographical references and index. 327 $aCover -- Title Page -- Copyright Page -- Contents -- About the Authors -- Foreword -- Preface -- Chapter 1 A Perspective of the Oil and Gas Industry -- 1.1 Exploration and Production -- 1.1.1 Onshore -- 1.1.2 Offshore -- 1.1.3 Hydraulic Fracturing -- 1.2 Midstream Transportation -- 1.3 Downstream - Refining and Marketing -- 1.3.1 Hydrotreating -- 1.4 Meaning of Different Terms of Products Produced by the Oil and Gas Industry -- 1.4.1 Natural Gas -- 1.4.2 Extraction -- 1.4.3 Advantages and Disadvantages -- 1.4.4 Types -- 1.4.5 Types of Natural Gas Deposits -- 1.4.6 Conventional Natural Gas Deposits -- 1.4.7 Coal Bed Methane -- 1.4.8 Shale Gas -- 1.4.9 Tight Gas -- 1.4.10 Environmental Impacts of Natural Gas -- 1.4.11 The Future of Natural Gas -- 1.4.12 CNG vs. Liquid Fuels -- 1.4.13 Unconventional Oil and Gas -- 1.5 Oil and Gas Pricing -- 1.6 A Note on Renewable Energy Sources -- 1.6.1 Biomass -- 1.6.2 Hydropower -- 1.6.3 Geothermal -- 1.6.4 Wind -- 1.6.5 A Note About Hydrogen -- 1.6.6 How is Hydrogen Produced -- 1.6.7 Production of Hydrogen -- 1.6.8 Electrolysis -- 1.6.9 Biological Processes -- 1.6.10 Converting Hydrogen to Hydrogen-Based Fuels -- 1.7 Environmental Impact -- 1.8 Uses of Hydrogen -- 1.8.1 Challenges in Using Hydrogen as a Fuel -- Bibliography -- Chapter 2 Artificial Intelligence (AI) for the Future of the Oil and Gas (O& -- G) Industry -- 2.1 Introduction -- 2.2 The Emergence of Digitization Technologies and Tools -- 2.3 Demystifying Digitalization Technologies and Tools -- 2.4 Briefing the Potentials of Artificial Intelligence (AI) -- 2.5 AI for the Oil and Gas (O& -- G) Industry -- 2.5.1 Automate and Optimize Inspection -- 2.5.2 Defect Detection and Enhance Quality Assurance -- 2.5.3 Monitoring -- 2.5.4 Reduce Production and Maintenance Costs -- 2.5.5 Accurate Decision-Making. 327 $a2.5.6 Improve Supply Chain and Logistics Efficiency -- 2.5.7 Geoscience Data Analytics -- 2.5.8 Predictive Models for Oil Field Development -- 2.5.9 Predictive Analytics for Reservoir Engineering -- 2.5.10 AI for Oil and Gas Production -- 2.5.11 AI in Midstream -- 2.5.12 AI in Downstream -- 2.6 Computer Vision (CV)-Enabled Use Cases -- 2.7 Natural Language Processing (NLP) Use Cases -- 2.8 Robots in the Oil and Gas Industry -- 2.9 Drones in the Oil and Gas Industry -- 2.9.1 Drones in Upstream Activities -- 2.9.2 Drones in Midstream Activities -- 2.9.3 Drones in Downstream Activities -- 2.10 AI Applications for the Oil and Gas (O& -- G) Industry -- 2.10.1 Optimizing Production and Scheduling -- 2.10.2 Asset Tracking and Maintenance Through AI-enabled Digital Twins (DT) -- 2.10.3 AI-led Cybersecurity -- 2.11 Better Decision-Making Using AI -- 2.11.1 Predictive Maintenance -- 2.11.2 Identifying Optimal Operating Condition -- 2.11.3 Well Logging -- 2.11.4 Detecting Contaminant Concentrations -- 2.11.5 Ensuring the People and Property Safety -- 2.11.6 Energy Efficiency -- 2.11.7 Equipment Inspection -- 2.12 Cloud AI vs. Edge AI for the Oil and Gas Industry -- 2.13 AI Model Optimization Techniques -- 2.14 Conclusion -- Bibliography -- Chapter 3 Artificial Intelligence for Sophisticated Applications in the Oil and Gas Industry -- 3.1 Introduction -- 3.2 Oil and Gas Industry -- 3.2.1 Upstream: Production and Exploration -- 3.2.2 Midstream: Transportation -- 3.2.3 Downstream: Refining and Marketing -- 3.3 Artificial Intelligence -- 3.4 Lifecycle of Oil and Gas Industry -- 3.4.1 Exploration -- 3.4.2 Appraisal -- 3.4.3 Development -- 3.4.4 Production -- 3.4.5 Decommissioning -- 3.5 Applications of AI in Oil and Gas industry -- 3.6 Chatbots -- 3.7 Optimized Procurement -- 3.8 Drilling, Production, and Reservoir Management -- 3.9 Inventory Management. 327 $a3.10 Well Monitoring -- 3.11 Process Excellence and Automation -- 3.12 Asset Tracking and Maintenance/Digital Twins -- 3.13 Optimizing Production and Scheduling -- 3.14 Emission Tracking -- 3.15 Logistics Network Optimizations -- 3.16 Conclusion -- References -- Chapter 4 Demystifying the Oil and Gas Exploration and Extraction Process -- 4.1 Process of Crude Oil Formation -- 4.2 Composition of Crude Oil -- 4.3 Crude Oil Classification -- 4.3.1 Other Types of Crude Oil -- 4.4 Crude Oil Production Process -- 4.5 Oil Exploration -- 4.6 Oil Extraction -- 4.6.1 Bringing Extracted Crude Oil to the Surface -- 4.6.2 Enhanced Oil Recovery -- 4.7 Processing of Crude Oil -- 4.7.1 Oil and Natural Gas Storage -- 4.7.2 Oil and Gas Transportation -- 4.7.3 Tanker Ships -- 4.7.4 Railcars -- 4.7.5 Tank Trucks -- 4.8 Overview of Refining -- 4.8.1 Separation/Distillation -- 4.8.2 Conversion -- 4.8.3 Enhancement -- 4.8.4 Blending/Finishing -- 4.8.5 Types of Refineries -- 4.9 Marketing and Distribution of Oil and Gas -- 4.10 End of Production -- 4.11 Factors Influencing the Timing of Oil and Gas Exploration and Production -- 4.11.1 Physical and Technical Factors -- 4.11.2 Social and Political Factors -- 4.11.3 Business Coordination Factors -- 4.12 Non-revenue Benefits of the Oil and Gas Industry -- 4.13 Conclusion -- References -- Chapter 5 Explaining the Midstream Activities in the Oil and Gas Domain -- 5.1 Introduction -- 5.2 Role of Midstream Sector in Oil and Gas Industry -- 5.3 Midstream Oil and Gas Operations -- 5.3.1 Field Processing -- 5.3.2 Storage -- 5.3.3 Transportation -- 5.4 Technological Advancements in Midstream Sector -- 5.4.1 Cloud Computing -- 5.4.2 Internet of Things -- 5.4.3 Robotics and Automation -- 5.4.4 3D Technology -- 5.4.5 Manufacturing and Execution Systems -- 5.5 Midstream Sector Challenges -- 5.5.1 Cyber-Attacks. 327 $a5.5.2 Environmental Considerations -- 5.5.3 Social Concerns -- 5.5.4 Regulations -- 5.6 Conclusion -- References -- Chapter 6 The Significance of the Industrial Internet of Things (IIoT) for the Oil and Gas Space -- 6.1 Overview of IIoT -- 6.1.1 Functioning of Internet of Things -- 6.1.2 IIOT Viewpoints -- 6.1.3 Benefits of IIoT -- 6.1.4 Security in IIoT -- 6.2 Technical Innovators of Industrial Internet -- 6.2.1 Industrial Control Systems (ICS) -- 6.2.2 Supervisory Control and Data Acquisition (SCADA) -- 6.3 IoT for Oil and Gas Sector -- 6.3.1 Utilizing IIoT in Oil and Gas -- 6.3.2 Excellence in Operations -- 6.3.3 Device Management -- 6.3.4 Device Connectivity -- 6.3.5 Transformation and Storage -- 6.3.6 Presentation and Action -- 6.3.7 Microsoft Azure -- 6.4 Rebellion of IoT in the Oil and Gas Sector -- 6.4.1 Improved Operational Efficiency -- 6.4.2 Optimize Inventory Levels Based on Actual Usage -- 6.4.3 Improve Stockroom Management -- 6.4.4 Return on Investment (ROI)/Revenue -- 6.4.5 Real-Time Monitoring -- 6.4.6 Removing Manual Measuring Processes -- 6.4.7 Reduction of Safety Risk -- 6.4.8 Hurdles in the Oil and Gas Sector -- 6.5 Oil and Gas Remote Monitoring Systems -- 6.5.1 Sensors -- 6.5.2 Smart Algorithms -- 6.5.3 Prognostic and Preemptive Maintenance -- 6.5.4 Robots and Drones -- 6.5.5 Smart Accessories -- 6.5.6 Wearable Watches -- 6.5.7 Wearable Glasses -- 6.5.8 Drones -- 6.5.9 Monitoring Critical Systems 24/7 -- 6.5.10 PLC Emergency Alert Notification Systems -- 6.5.11 Independent Verification -- 6.5.12 Oil and Gas Survey and Manufacturing Process -- 6.6 Advantages of IIOT for the Oil and Gas Industry -- 6.6.1 Monitoring Pipelines -- 6.6.2 Risk Mitigation -- 6.6.3 Environmental Impact -- 6.6.4 Managing Emergency Conditions -- 6.6.5 Establishing Workers Healthy and Safety -- 6.6.6 Supply Chain Management -- 6.7 Conclusion -- Bibliography. 327 $aChapter 7 The Power of Edge AI Technologies for Real-Time Use Cases in the Oil and Gas Domain -- 7.1 Introduction -- 7.2 Demystifying the Paradigm of Artificial Intelligence (AI) -- 7.3 Describing the Phenomenon of Edge Computing -- 7.4 Delineating Edge Computing Advantages -- 7.4.1 The Formation of Edge Device Clouds -- 7.4.2 Real-Time Computing -- 7.4.3 Real-Time Analytics -- 7.4.4 Scalable Computing -- 7.4.5 Secured Computing -- 7.4.6 Automated Analytics and Action -- 7.4.7 Reduced Costs -- 7.5 Demarcating the Move Toward Edge AI -- 7.5.1 How Edge AI Helps to Generate Better Business -- 7.6 Why Edge AI Gains Momentum? -- 7.6.1 The Growing Device Ecosystem -- 7.6.2 Federated Learning -- 7.6.3 Optimization Techniques to Run AI Models in Edge Devices -- 7.6.4 Neural Network (NN) Pruning -- 7.6.5 L2 and L1 Regularization -- 7.7 The Enablers of Edge AI -- 7.8 5G-Advanced Communication -- 7.8.1 Industrial 5G -- 7.8.2 Edge Computing -- 7.8.3 Massive Amounts of Edge Devices Data -- 7.8.4 The Emergence of Accelerators and Specialized Engines -- 7.8.5 Cyber Physical Systems (CPS) -- 7.8.6 Digital Twins (DT) -- 7.9 Why Edge AI is Being Pursued with Alacrity? -- 7.9.1 The Need for Customer Delight -- 7.9.2 Unearthing Fresh Use Cases for Edge AI Across Industrial Verticals -- 7.10 Edge AI Frameworks and Accelerators -- 7.11 Conclusion -- Bibliography -- Chapter 8 AI-Enabled Robots for Automating Oil and Gas Operations -- 8.1 Briefing the Impending Digital Era -- 8.2 Depicting the Digital Power -- 8.2.1 The Emergence of Advanced Drones -- 8.2.2 The Grandiose Arrival of the State-of-the-Art Robots -- 8.3 Robotics: The Use Cases -- 8.3.1 Upstream Oil and Gas -- 8.3.2 Midstream Oil and Gas -- 8.3.3 Downstream Oil and Gas -- 8.4 Real-Life Examples of Robotic Solutions in the Oil and Gas Industry -- 8.5 The Advantages of Robotic Solutions. 327 $a8.6 The Dawn of the Internet of Robotic Things. 330 $a"This book describes the proven and promising digital technologies and tools available to empower the oil and gas industry to be future-ready. How the widely reported limitations of the oil and gas industry are getting nullified through the apt and adroit application of breakthrough digital technologies is explained in this book. The book also describes how the above-mentioned convergence of digital technologies helps to envision newer possibilities and opportunities to take this industry to its next level. This book on AI-inspired oil and gas industry differentiates and delivers sophisticated use cases for the various stakeholders. The book provides easy-to-understand and use information in accurately utilizing the proven technologies towards achieving the real and sustainable industry transformation."--$cProvided by publisher. 410 0$aIEEE Press series on RF and microwave technology. 606 $aArtificial intelligence$xIndustrial applications 606 $aOil fields$xData processing 606 $aPetroleum engineering$xData processing 615 0$aArtificial intelligence$xIndustrial applications. 615 0$aOil fields$xData processing. 615 0$aPetroleum engineering$xData processing. 676 $a060 700 $aRaj$b Pethuru$0786064 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910830287903321 996 $aThe Power of Artificial Intelligence for the Next-Generation Oil and Gas Industry$94110002 997 $aUNINA