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3D microelectronic packaging : from architectures to applications / / editors, Yan Li, Deepak Goyal
| 3D microelectronic packaging : from architectures to applications / / editors, Yan Li, Deepak Goyal |
| Edizione | [2nd edition 2021.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (XVII, 622 p. 299 illus., 205 illus. in color.) |
| Disciplina | 929.374 |
| Collana | Springer Series in Advanced Microelectronics |
| Soggetto topico |
Biotechnology
Electronics Electronics - Materials Microelectronics Microelectronics - Packaging Nanotechnology Electronic circuits Optical materials |
| ISBN | 981-15-7090-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. Introduction to 3D microelectronic packaging -- 2. 3D packaging architecture and assembly process design -- 3. Fundamentals of TSV processing and reliability -- 4. Mechanical properties of TSV -- 5. Atomistic View of TSV Protrusion/Intrusion -- 6. Fundamentals and failures in Die preparation for 3D packaging -- 7. Direct Cu to Cu bonding and other alternative interconnects in 3D packaging -- 8. Emerging hybrid bonding techniques for 3D packaging -- 9. Fundamental of Thermal Compressive Bonding process, advanced epoxy, and flux materials in 3D packaging -- 10. Fundamentals of solder alloys in 3D packaging -- 11. Fundamentals of electro migration in interconnects of 3D packages -- 12. Fundamentals of heat dissipation in 3D packaging -- 13. Fundamentals of advanced materials and process in substrate technology -- 14. New substrate technologies for 3D packaging. -15. Thermal mechanical and moisture modeling in 3D packaging -- 16. Stress and Strain measurements in 3D packaging -- 17.Processing and Reliability of Solder Interconnections in Stacked Packaging -- 18. Interconnect Quality and Reliability of 3D Packaging -- 19. Fundamentals of automotive reliability of 3D packages -- 20. Fault isolation and failure analysis of 3D packaging. |
| Record Nr. | UNINA-9910484726403321 |
| Singapore : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
3D Microelectronic Packaging [[electronic resource] ] : From Fundamentals to Applications / / edited by Yan Li, Deepak Goyal
| 3D Microelectronic Packaging [[electronic resource] ] : From Fundamentals to Applications / / edited by Yan Li, Deepak Goyal |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (IX, 463 p. 331 illus., 253 illus. in color.) |
| Disciplina | 621.381 |
| Collana | Springer Series in Advanced Microelectronics |
| Soggetto topico |
Electronics
Microelectronics Optical materials Electronic materials Electronic circuits Biotechnology Nanotechnology Metals Electronics and Microelectronics, Instrumentation Optical and Electronic Materials Electronic Circuits and Devices Microengineering Nanotechnology and Microengineering Metallic Materials |
| ISBN | 3-319-44586-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction to 3D Microelectronic Packaging.-3D packaging architecture and assembly process design.-Materials and Processing of TSV.-Microstructural and Reliability Issues of TSV -- Fundamentals and failures in Die preparation for 3D packaging.-Direct Cu to Cu bonding and other alternative bonding techniques in 3D packaging -- Fundamental of Thermal Compression Bonding Technology and Process Materials for 2.5/3D Packages -- Fundamentals of solder alloys in 3D packaging.-Fundamentals of Electromigration in interconnects of 3D packages.-Fundamentals of heat dissipation in 3D IC packaging -- Fundamentals of advanced materials and processes in organic substrate technology -- Die and Package Level Thermal and Thermal/Moisture Stresses in 3-D Packaging: Modeling and Characterization -- Processing and Reliability of Solder Interconnections in Stacked Packaging -- Interconnect Quality and Reliability of 3D Packaging -- Fault isolation and failure analysis of 3D packaging. . |
| Record Nr. | UNINA-9910163046303321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advanced driver assistance systems and autonomous vehicles : from fundamentals to applications / / Yan Li and Hualiang Shi, editors
| Advanced driver assistance systems and autonomous vehicles : from fundamentals to applications / / Yan Li and Hualiang Shi, editors |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (628 pages) |
| Disciplina | 629.2 |
| Soggetto topico |
Automated vehicles
Driver assistance systems Artificial intelligence |
| ISBN | 981-19-5053-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Contents -- Introduction -- 1 Reshape the Future of Transportation -- 2 Challenges -- 2.1 New Technologies -- 2.2 Requalification of Non-Auto-Grade Components -- 2.3 New Mission Profiles for Existing Auto-Grade Components -- 3 Overview of Chapters -- 4 Summary -- References -- Basics and Applications of AI in ADAS and Autonomous Vehicles -- 1 Introduction -- 1.1 Advanced Driver-Assistance Systems (ADASs) -- 1.2 Autonomous Vehicles (AVs) and Automation Levels -- 1.3 Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) -- 2 Applications of AI in ADAS -- 2.1 Supervised Learning -- 2.2 Unsupervised Learning -- 2.3 Reinforcement Learning -- 2.4 Deep Learning (DL) -- 3 Safety in ADAS and AV Based on AI -- 3.1 Safety Standards and Methodologies -- 3.2 AI Safety Challenges: Edge Cases and Heavy Tail Distribution -- 3.3 Safety in AI System Design, Validation, Testing and Implementation -- 4 Datasets, Simulators, and Infrastructures for AI Systems -- 4.1 Publicly Available Training and Testing Datasets -- 4.2 Open-source Simulators -- 4.3 Infrastructures for AI Systems -- 5 Summary -- References -- Computing Technology in Autonomous Vehicle -- 1 Introduction -- 2 Compute and ADAS Technology -- 2.1 Levels of Autonomous Driving -- 2.2 Platform for Autonomous Driving System -- 2.3 Perception and Localization -- 2.4 Prediction, Planning, and Control -- 2.5 Functional Safety -- 3 Advanced Computer System -- 3.1 Architecture Solution and Comparisons -- 3.2 Environment Perception Sensors -- 3.3 System on Chip (SoC) -- 3.4 Memory -- 3.5 Storage -- 3.6 Network -- 3.7 Real-Time Operating System -- 3.8 Management, Failure Detection, and Diagnostics -- 3.9 Security and Middleware -- 4 Electrical Functional and Reliability Validation -- 4.1 Automotive Level EE Functional Tests.
4.2 Reliability Validation Tests Based on AV Mission Profiles -- 4.3 EMC/ESD Validation -- 5 Challenges to Safe Deployment at Scale -- 5.1 Artificial Intelligence: Perception and Prediction -- 5.2 Power Consumption -- 5.3 Thermal Management -- 5.4 Manufacturing, Assembly, and Quality Control -- 5.5 Size and Cost -- 5.6 Quality and Reliability -- 5.7 Security and Safety -- 6 Summary -- References -- Overview of Packaging Technologies and Cooling Solutions in ADAS Market -- 1 Introduction -- 1.1 Market Opportunity and Trends -- 1.2 Road to Autonomy: ADAS Architecture -- 2 Package Technology and AD Requirements -- 2.1 Role of Advantage Packaging Technology in AD Market -- 2.2 Smaller System Level Footprints -- 3 Thermal Management -- 3.1 ECU Thermal Fundamentals -- 3.2 Component Level Fundamentals -- 3.3 Vehicle Operating Environment -- 3.4 ADAS ECU Thermal Management -- 4 ADAS Product Reliability Requirements -- 4.1 Qualification Requirements -- 4.2 ADAS Performance Requirements and Implications-ADAS Mission Profile -- 4.3 Failure Regimes-Quality and Wear-Out Failures -- 4.4 Package Reliability Challenges -- 5 Summary -- References -- Flash Memory and NAND -- 1 NAND Flash-The Perfect Storage Medium -- 1.1 What is NAND Flash -- 1.2 NOR Versus NAND -- 1.3 Evolution of NAND Flash -- 2 NAND Fundamentals -- 2.1 NAND Arrays in 2D and 3D -- 2.2 Basic NAND Operations -- 2.3 Multi-Bit-Per-Cell Technologies -- 2.4 Anatomy of a NAND Product -- 2.5 3D NAND Technology Basics -- 3 3D NAND Technology and Design Challenges -- 3.1 Cost-Performance-Reliability Tradeoffs -- 3.2 3D NAND Technology Challenges -- 3.3 3D NAND Design Challenges -- 4 NAND Reliability Issues -- 4.1 Write Errors -- 4.2 Disturb Errors -- 4.3 Data Retention Errors -- 5 3D NAND Future Outlook -- References -- Interconnect -- 1 Interconnects for Applications Under the Hood. 1.1 Nanoparticle Sintering Method -- 1.2 Transient Liquid Phase Bonding Technology -- 1.3 Electrochemical Migration Phenomenon -- 2 Solder Joint Technology for Applications Under the Hood -- 2.1 Low Melting Point Solders -- 2.2 Low-Temperature Assembly -- 3 Introduction for Low-Temperature Cu to Cu Direct Bonding -- 3.1 Cu-Cu Bonding by Surface-Activated Bonding Process -- 3.2 Cu-Cu Bonding by Chemical Pretreatment -- 3.3 Cu-Cu Bonding by Thermal Compressive Bonding -- 3.4 Low-Temperature Cu-Cu Bonding by (111) Nanotwinned Structure -- 3.5 Low-Temperature Cu to Cu Bonding with Ag Passivation Under Atmosphere -- 3.6 Hybrid Bonding -- References -- Cameras in Advanced Driver-Assistance Systems and Autonomous Driving Vehicles -- 1 Introduction -- 2 Camera System Overview -- 3 Camera System Hardware -- 3.1 Image Sensor -- 3.2 Optics -- 3.3 Electronics -- 3.4 Image Signal Processor (ISP) -- 4 Image Processing -- 4.1 Image Processing Pipeline -- 4.2 Calibration -- 4.3 ISP Tuning -- 5 Camera Product Development -- 5.1 Product Definition -- 5.2 Camera Design -- 5.3 Prototype -- 5.4 Validation -- 5.5 Manufacturing -- 5.6 Implementation -- 5.7 Support -- 6 Summary -- References -- Lidar Technology -- 1 Introduction -- 2 Overview of Current Lidar Technology for Automotive Application -- 3 Important Performance Metrics for Lidar -- 3.1 Range -- 3.2 Field of View -- 3.3 Angular Resolution/Accuracy -- 3.4 Frame Rate -- 3.5 Eye Safety -- 4 Transmitter and Receiver -- 5 Distance Calculation -- 5.1 Range of Time of Flight -- 5.2 Signal-To-Noise Ratio -- 5.3 Factors that Affect Range Detection -- 6 Future Direction of Lidar Developments -- 6.1 Frequency-Modulated Continuous Wave (FMCW) -- 7 Mapping Methods -- 7.1 Mechanical Spinning Scanner -- 7.2 Opto-Mechanical Scanning -- 7.3 MEMS Scanning -- 7.4 Flash -- 7.5 Optical Phased Array (OPA) -- 8 Discussion -- References. Radar Technology -- 1 Introduction -- 2 Radar Physical Design -- 2.1 Radar Architecture -- 2.2 Radar Categories -- 3 Waveform Design -- 3.1 Pulse Radar -- 3.2 Pulse Coded Radar -- 3.3 FMCW Radar -- 4 Link Budget Analysis for FMCW Radar -- 4.1 Radar Equation -- 4.2 Target Reflectivity -- 4.3 Processing Gain -- 5 Challenges and Solutions for Automotive Radars -- 5.1 Interference -- 5.2 Under- and Overclustering -- 5.3 Classification -- 5.4 Lack of Resolution -- 5.5 Data Fusion -- 5.6 Radar Integration -- 6 Summary -- References -- Electrochemical Power Systems for Advanced Driver-Assistant Vehicles -- 1 Introduction -- 2 Batteries -- 2.1 Introduction -- 2.2 Types of Battery Cells -- 2.3 Battery Cell Internal Structure -- 2.4 Battery Cell Manufacturing Process -- 2.5 Chemistry Choices for Li-Ion Battery for EV Applications -- 2.6 Next-Generation Li-Ion Battery for EV Applications -- 2.7 Battery Management System -- 2.8 Battery Testing Methods and Industrial Standards -- 2.9 Battery Failure Mode and Effects Analysis (FMEA) -- 3 Fuel Cells -- 3.1 Major Types of Fuel Cells -- 3.2 Fuel Cells for EV Application -- 4 Capacitors -- 5 Summary -- References -- In-Vehicle Display Technology -- 1 Introduction -- 2 In-Vehicle Display Technologies and Architectures -- 2.1 LCD -- 2.2 TFT LCD -- 2.3 OLED -- 2.4 LED, Mini-/Micro-LED -- 2.5 Head-Up Display -- 2.6 Flexible and Free-Form -- 2.7 Touch Technology -- 3 In-Vehicle Display Requirements -- 3.1 Optical Performance Requirement -- 3.2 Appearance -- 3.3 Integration and Fabrication -- 3.4 Color Measurement and Characterization -- 3.5 Mura, Defect, Inspection, and Demura -- 3.6 Visibility in Bright Light and Complete Darkness -- 3.7 Improvement of Image and Touch Quality -- 3.8 Reliability and Durability -- 3.9 Functional Safety -- 4 In-Vehicle Display Challenges -- 4.1 Specification and Functionality Challenges. 4.2 Quality, Reliability, and Validation Challenges -- 4.3 EMC/EMI Challenges -- 4.4 ESD and High-Transient Voltage Challenges -- 5 Common LED LCD Reliability Testing Failure Modes and Effects Case Studies -- 5.1 FOS Spotlighting Failure Mechanism and Risk Assessment -- 5.2 BLU Film Buckling/Waving/Wrinkle Failure Mechanism Study -- 5.3 Metal Oxide TFT Panel-Level VGH and VGL Reliability Modeling -- 5.4 LCD Panel UV Irradiation Aging Reliability Modeling -- 5.5 Polarizer Edge Bleaching Failure Mechanism and Reliability Modeling -- 5.6 Free-Fall Object Impact Test and LCD Glass Crack Failure Risk Assessment -- 5.7 LED Lumen Degradation Reliability Modeling -- 6 Summary -- References -- Disk Drive for Data Center Storage -- 1 Introduction -- 2 Hard Disk Drive Application in Data Center -- 2.1 Data Storage for Autonomous Vehicle -- 2.2 Data Storage Configurations in Data Center -- 2.3 Hard Disk Drive Versus Solid-State Drive in Data Center -- 3 Hard Disk Drive Design -- 3.1 Hard Disk Drive System -- 3.2 Components in Recording Head -- 3.3 Next Generation Hard Disk Drive -- 4 Challenges in the Performance and Reliability -- 4.1 The Need for Higher Areal Data Density -- 4.2 Microwave-Assisted Magnetic Recording (MAMR) -- 4.3 Heat-Assisted Magnetic Recording (HAMR) -- 4.4 The Future of High-Volume Hard Disk Drive -- 5 Summary -- References -- Role and Responsibility of Hardware Reliability Engineer -- 1 Introduction -- 2 Risk Assessment Methodologies -- 2.1 Failure Mode and Effect Analysis (FMEA) -- 2.2 Fault Tree Analysis (FTA) -- 2.3 Stress-Strength Analysis -- 3 Accelerated Life Testing (ALT) and Highly Accelerated Life Testing (HALT) -- 3.1 Introduction -- 3.2 Identify Field Stress Factors -- 3.3 Determine Stress Levels -- 3.4 Acceleration Models and Acceleration Factor -- 3.5 Case Study -- 4 Reliability Statistics -- 4.1 Sample Size. 4.2 Life Distribution Analysis. |
| Record Nr. | UNISA-996495560303316 |
| Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Advanced driver assistance systems and autonomous vehicles : from fundamentals to applications / / Yan Li and Hualiang Shi, editors
| Advanced driver assistance systems and autonomous vehicles : from fundamentals to applications / / Yan Li and Hualiang Shi, editors |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (628 pages) |
| Disciplina | 629.2 |
| Soggetto topico |
Automated vehicles
Driver assistance systems Artificial intelligence |
| ISBN | 981-19-5053-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Contents -- Introduction -- 1 Reshape the Future of Transportation -- 2 Challenges -- 2.1 New Technologies -- 2.2 Requalification of Non-Auto-Grade Components -- 2.3 New Mission Profiles for Existing Auto-Grade Components -- 3 Overview of Chapters -- 4 Summary -- References -- Basics and Applications of AI in ADAS and Autonomous Vehicles -- 1 Introduction -- 1.1 Advanced Driver-Assistance Systems (ADASs) -- 1.2 Autonomous Vehicles (AVs) and Automation Levels -- 1.3 Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) -- 2 Applications of AI in ADAS -- 2.1 Supervised Learning -- 2.2 Unsupervised Learning -- 2.3 Reinforcement Learning -- 2.4 Deep Learning (DL) -- 3 Safety in ADAS and AV Based on AI -- 3.1 Safety Standards and Methodologies -- 3.2 AI Safety Challenges: Edge Cases and Heavy Tail Distribution -- 3.3 Safety in AI System Design, Validation, Testing and Implementation -- 4 Datasets, Simulators, and Infrastructures for AI Systems -- 4.1 Publicly Available Training and Testing Datasets -- 4.2 Open-source Simulators -- 4.3 Infrastructures for AI Systems -- 5 Summary -- References -- Computing Technology in Autonomous Vehicle -- 1 Introduction -- 2 Compute and ADAS Technology -- 2.1 Levels of Autonomous Driving -- 2.2 Platform for Autonomous Driving System -- 2.3 Perception and Localization -- 2.4 Prediction, Planning, and Control -- 2.5 Functional Safety -- 3 Advanced Computer System -- 3.1 Architecture Solution and Comparisons -- 3.2 Environment Perception Sensors -- 3.3 System on Chip (SoC) -- 3.4 Memory -- 3.5 Storage -- 3.6 Network -- 3.7 Real-Time Operating System -- 3.8 Management, Failure Detection, and Diagnostics -- 3.9 Security and Middleware -- 4 Electrical Functional and Reliability Validation -- 4.1 Automotive Level EE Functional Tests.
4.2 Reliability Validation Tests Based on AV Mission Profiles -- 4.3 EMC/ESD Validation -- 5 Challenges to Safe Deployment at Scale -- 5.1 Artificial Intelligence: Perception and Prediction -- 5.2 Power Consumption -- 5.3 Thermal Management -- 5.4 Manufacturing, Assembly, and Quality Control -- 5.5 Size and Cost -- 5.6 Quality and Reliability -- 5.7 Security and Safety -- 6 Summary -- References -- Overview of Packaging Technologies and Cooling Solutions in ADAS Market -- 1 Introduction -- 1.1 Market Opportunity and Trends -- 1.2 Road to Autonomy: ADAS Architecture -- 2 Package Technology and AD Requirements -- 2.1 Role of Advantage Packaging Technology in AD Market -- 2.2 Smaller System Level Footprints -- 3 Thermal Management -- 3.1 ECU Thermal Fundamentals -- 3.2 Component Level Fundamentals -- 3.3 Vehicle Operating Environment -- 3.4 ADAS ECU Thermal Management -- 4 ADAS Product Reliability Requirements -- 4.1 Qualification Requirements -- 4.2 ADAS Performance Requirements and Implications-ADAS Mission Profile -- 4.3 Failure Regimes-Quality and Wear-Out Failures -- 4.4 Package Reliability Challenges -- 5 Summary -- References -- Flash Memory and NAND -- 1 NAND Flash-The Perfect Storage Medium -- 1.1 What is NAND Flash -- 1.2 NOR Versus NAND -- 1.3 Evolution of NAND Flash -- 2 NAND Fundamentals -- 2.1 NAND Arrays in 2D and 3D -- 2.2 Basic NAND Operations -- 2.3 Multi-Bit-Per-Cell Technologies -- 2.4 Anatomy of a NAND Product -- 2.5 3D NAND Technology Basics -- 3 3D NAND Technology and Design Challenges -- 3.1 Cost-Performance-Reliability Tradeoffs -- 3.2 3D NAND Technology Challenges -- 3.3 3D NAND Design Challenges -- 4 NAND Reliability Issues -- 4.1 Write Errors -- 4.2 Disturb Errors -- 4.3 Data Retention Errors -- 5 3D NAND Future Outlook -- References -- Interconnect -- 1 Interconnects for Applications Under the Hood. 1.1 Nanoparticle Sintering Method -- 1.2 Transient Liquid Phase Bonding Technology -- 1.3 Electrochemical Migration Phenomenon -- 2 Solder Joint Technology for Applications Under the Hood -- 2.1 Low Melting Point Solders -- 2.2 Low-Temperature Assembly -- 3 Introduction for Low-Temperature Cu to Cu Direct Bonding -- 3.1 Cu-Cu Bonding by Surface-Activated Bonding Process -- 3.2 Cu-Cu Bonding by Chemical Pretreatment -- 3.3 Cu-Cu Bonding by Thermal Compressive Bonding -- 3.4 Low-Temperature Cu-Cu Bonding by (111) Nanotwinned Structure -- 3.5 Low-Temperature Cu to Cu Bonding with Ag Passivation Under Atmosphere -- 3.6 Hybrid Bonding -- References -- Cameras in Advanced Driver-Assistance Systems and Autonomous Driving Vehicles -- 1 Introduction -- 2 Camera System Overview -- 3 Camera System Hardware -- 3.1 Image Sensor -- 3.2 Optics -- 3.3 Electronics -- 3.4 Image Signal Processor (ISP) -- 4 Image Processing -- 4.1 Image Processing Pipeline -- 4.2 Calibration -- 4.3 ISP Tuning -- 5 Camera Product Development -- 5.1 Product Definition -- 5.2 Camera Design -- 5.3 Prototype -- 5.4 Validation -- 5.5 Manufacturing -- 5.6 Implementation -- 5.7 Support -- 6 Summary -- References -- Lidar Technology -- 1 Introduction -- 2 Overview of Current Lidar Technology for Automotive Application -- 3 Important Performance Metrics for Lidar -- 3.1 Range -- 3.2 Field of View -- 3.3 Angular Resolution/Accuracy -- 3.4 Frame Rate -- 3.5 Eye Safety -- 4 Transmitter and Receiver -- 5 Distance Calculation -- 5.1 Range of Time of Flight -- 5.2 Signal-To-Noise Ratio -- 5.3 Factors that Affect Range Detection -- 6 Future Direction of Lidar Developments -- 6.1 Frequency-Modulated Continuous Wave (FMCW) -- 7 Mapping Methods -- 7.1 Mechanical Spinning Scanner -- 7.2 Opto-Mechanical Scanning -- 7.3 MEMS Scanning -- 7.4 Flash -- 7.5 Optical Phased Array (OPA) -- 8 Discussion -- References. Radar Technology -- 1 Introduction -- 2 Radar Physical Design -- 2.1 Radar Architecture -- 2.2 Radar Categories -- 3 Waveform Design -- 3.1 Pulse Radar -- 3.2 Pulse Coded Radar -- 3.3 FMCW Radar -- 4 Link Budget Analysis for FMCW Radar -- 4.1 Radar Equation -- 4.2 Target Reflectivity -- 4.3 Processing Gain -- 5 Challenges and Solutions for Automotive Radars -- 5.1 Interference -- 5.2 Under- and Overclustering -- 5.3 Classification -- 5.4 Lack of Resolution -- 5.5 Data Fusion -- 5.6 Radar Integration -- 6 Summary -- References -- Electrochemical Power Systems for Advanced Driver-Assistant Vehicles -- 1 Introduction -- 2 Batteries -- 2.1 Introduction -- 2.2 Types of Battery Cells -- 2.3 Battery Cell Internal Structure -- 2.4 Battery Cell Manufacturing Process -- 2.5 Chemistry Choices for Li-Ion Battery for EV Applications -- 2.6 Next-Generation Li-Ion Battery for EV Applications -- 2.7 Battery Management System -- 2.8 Battery Testing Methods and Industrial Standards -- 2.9 Battery Failure Mode and Effects Analysis (FMEA) -- 3 Fuel Cells -- 3.1 Major Types of Fuel Cells -- 3.2 Fuel Cells for EV Application -- 4 Capacitors -- 5 Summary -- References -- In-Vehicle Display Technology -- 1 Introduction -- 2 In-Vehicle Display Technologies and Architectures -- 2.1 LCD -- 2.2 TFT LCD -- 2.3 OLED -- 2.4 LED, Mini-/Micro-LED -- 2.5 Head-Up Display -- 2.6 Flexible and Free-Form -- 2.7 Touch Technology -- 3 In-Vehicle Display Requirements -- 3.1 Optical Performance Requirement -- 3.2 Appearance -- 3.3 Integration and Fabrication -- 3.4 Color Measurement and Characterization -- 3.5 Mura, Defect, Inspection, and Demura -- 3.6 Visibility in Bright Light and Complete Darkness -- 3.7 Improvement of Image and Touch Quality -- 3.8 Reliability and Durability -- 3.9 Functional Safety -- 4 In-Vehicle Display Challenges -- 4.1 Specification and Functionality Challenges. 4.2 Quality, Reliability, and Validation Challenges -- 4.3 EMC/EMI Challenges -- 4.4 ESD and High-Transient Voltage Challenges -- 5 Common LED LCD Reliability Testing Failure Modes and Effects Case Studies -- 5.1 FOS Spotlighting Failure Mechanism and Risk Assessment -- 5.2 BLU Film Buckling/Waving/Wrinkle Failure Mechanism Study -- 5.3 Metal Oxide TFT Panel-Level VGH and VGL Reliability Modeling -- 5.4 LCD Panel UV Irradiation Aging Reliability Modeling -- 5.5 Polarizer Edge Bleaching Failure Mechanism and Reliability Modeling -- 5.6 Free-Fall Object Impact Test and LCD Glass Crack Failure Risk Assessment -- 5.7 LED Lumen Degradation Reliability Modeling -- 6 Summary -- References -- Disk Drive for Data Center Storage -- 1 Introduction -- 2 Hard Disk Drive Application in Data Center -- 2.1 Data Storage for Autonomous Vehicle -- 2.2 Data Storage Configurations in Data Center -- 2.3 Hard Disk Drive Versus Solid-State Drive in Data Center -- 3 Hard Disk Drive Design -- 3.1 Hard Disk Drive System -- 3.2 Components in Recording Head -- 3.3 Next Generation Hard Disk Drive -- 4 Challenges in the Performance and Reliability -- 4.1 The Need for Higher Areal Data Density -- 4.2 Microwave-Assisted Magnetic Recording (MAMR) -- 4.3 Heat-Assisted Magnetic Recording (HAMR) -- 4.4 The Future of High-Volume Hard Disk Drive -- 5 Summary -- References -- Role and Responsibility of Hardware Reliability Engineer -- 1 Introduction -- 2 Risk Assessment Methodologies -- 2.1 Failure Mode and Effect Analysis (FMEA) -- 2.2 Fault Tree Analysis (FTA) -- 2.3 Stress-Strength Analysis -- 3 Accelerated Life Testing (ALT) and Highly Accelerated Life Testing (HALT) -- 3.1 Introduction -- 3.2 Identify Field Stress Factors -- 3.3 Determine Stress Levels -- 3.4 Acceleration Models and Acceleration Factor -- 3.5 Case Study -- 4 Reliability Statistics -- 4.1 Sample Size. 4.2 Life Distribution Analysis. |
| Record Nr. | UNINA-9910624393803321 |
| Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
EEG Signal Analysis and Classification [[electronic resource] ] : Techniques and Applications / / by Siuly Siuly, Yan Li, Yanchun Zhang
| EEG Signal Analysis and Classification [[electronic resource] ] : Techniques and Applications / / by Siuly Siuly, Yan Li, Yanchun Zhang |
| Autore | Siuly Siuly |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (257 pages) |
| Disciplina | 530.82 |
| Collana | Health Information Science |
| Soggetto topico |
Signal processing
Image processing Speech processing systems Health informatics Artificial intelligence Biomedical engineering Optical data processing Application software Signal, Image and Speech Processing Health Informatics Artificial Intelligence Biomedical Engineering and Bioengineering Image Processing and Computer Vision Information Systems Applications (incl. Internet) |
| ISBN | 3-319-47653-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Electroencephalogram (EEG) and its background -- Significance of EEG signals in medical and health research -- Objectives and structures of the book -- Random sampling in the detection of epileptic EEG signals -- A novel clustering technique for the detection of epileptic seizures -- A statistical framework for classifying epileptic seizure from multi-category EEG signals -- Injecting principal component analysis with the OA scheme in the epileptic EEG signal classification -- Cross-correlation aided logistic regression model for the identification of motor imagery EEG signals in BCI applications -- Modified CC-LR Algorithm for identification of MI based EEG signals -- Improving prospective performance in the MI recognition: LS-SVM with tuning hyper parameters -- Comparative study: Motor area EEG and All-channels EEG -- Optimum allocation aided Naive Bayes based learning process for the detection of MI tasks -- Summary discussions on the methods, future directions and conclusions. |
| Record Nr. | UNINA-9910158672803321 |
Siuly Siuly
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Inclusive finance in China / / Yan Li and Lin Wang (editors)
| Inclusive finance in China / / Yan Li and Lin Wang (editors) |
| Pubbl/distr/stampa | Gateway East, Singapore : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (416 pages) |
| Disciplina | 332 |
| Soggetto topico |
Microfinance - China
Financial services industry Financial services industry - China |
| ISBN | 981-16-1788-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910483068903321 |
| Gateway East, Singapore : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Introduction to environmental mineralogy / / Anhuai Lu, Yan Li, Changqiu Wang, Hongrui Ding
| Introduction to environmental mineralogy / / Anhuai Lu, Yan Li, Changqiu Wang, Hongrui Ding |
| Autore | Lu Anhuai |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (xv, 265 pages) |
| Disciplina | 549 |
| Altri autori (Persone) |
LiYan
WangChangqiu DingHongrui |
| Soggetto topico | Mineralogy |
| ISBN | 981-19-7792-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1 Environmental Property of Minerals-1205 -- Chapter 2 Environmental Effects of Tunnel Structure Minerals-0113 -- Chapter 3 Photoactivity of Mn Oxides on Earth’s Surface-1230 -- Chapter 4 Redox Activity of Iron Sulfide and Mn Oxide-0106 -- Chapter 5 Interaction Between Fe & Mn-Bearing Minerals and Microbes-1230 -- Chapter 6 Photocatalytic reduction effects of sphalerite and native sulfur-1213 -- Chapter 7 Photocatalytic oxidation effects of rutile-1213 -- Chapter 8 Interactions between Semiconducting Minerals and Microbes-1209 -- Chapter 9 Human Pathological Mineral Features-1213 -- Chapter 10 Infrared Effect of Minerals-0107. |
| Record Nr. | UNINA-9910726287803321 |
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Lu Anhuai
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Management Innovation and Big Data / / Zheng Qin, Yan Li, and Yinzhou Yang
| Management Innovation and Big Data / / Zheng Qin, Yan Li, and Yinzhou Yang |
| Autore | Qin Zheng, Dr. |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (XV, 217 p. 14 illus., 9 illus. in color.) |
| Disciplina | 005.7 |
| Collana | Management for Professionals Series |
| Soggetto topico |
Big data
Management - Data processing |
| ISBN | 981-19-9231-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Decision-making -- Organization -- Leadership -- Control -- Innovation -- Basic Concepts -- Decision-making -- Management Practice Cases. |
| Record Nr. | UNINA-9910717421703321 |
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Qin Zheng, Dr.
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| Singapore : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Spatial Big Data and AI for Industrial Applications / / Edited by Jinmeng Rao, Song Gao, Heba Aly, Emre Eftelioglu, Yan Li, Yiqun Xie
| Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Spatial Big Data and AI for Industrial Applications / / Edited by Jinmeng Rao, Song Gao, Heba Aly, Emre Eftelioglu, Yan Li, Yiqun Xie |
| Pubbl/distr/stampa | Association for Computing Machinery, 2023 |
| Descrizione fisica | 1 online resource (59 p.;) |
| Altri autori (Persone) |
RaoJinmeng
GaoSong AlyHeba EfteliogluEmre LiYan XieYiqun |
| Collana | ACM Conferences |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | ||| |
| Altri titoli varianti | GeoIndustry '23 |
| Record Nr. | UNISA-996566865003316 |
| Association for Computing Machinery, 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Spatial Big Data and AI for Industrial Applications / / Edited by Jinmeng Rao, Song Gao, Heba Aly, Emre Eftelioglu, Yan Li, Yiqun Xie
| Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Spatial Big Data and AI for Industrial Applications / / Edited by Jinmeng Rao, Song Gao, Heba Aly, Emre Eftelioglu, Yan Li, Yiqun Xie |
| Pubbl/distr/stampa | Association for Computing Machinery, 2023 |
| Descrizione fisica | 1 online resource (59 p.;) |
| Altri autori (Persone) |
RaoJinmeng
GaoSong AlyHeba EfteliogluEmre LiYan XieYiqun |
| Collana | ACM Conferences |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | ||| |
| Altri titoli varianti | GeoIndustry '23 |
| Record Nr. | UNINA-9910765623903321 |
| Association for Computing Machinery, 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
