Search Results - "sensor"

Advanced endovascular therapy of aortic disease

Table of Contents: “…Hodgson -- Aneurysm sac pressure measurement with a pressure sensor in endovascular aortic aneurysm repair / Lisandro Carnero & Ross Milner.…”
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Advanced endovascular therapy of aortic disease

Table of Contents: “…Hodgson -- Aneurysm sac pressure measurement with a pressure sensor in endovascular aortic aneurysm repair / Lisandro Carnero & Ross Milner.…”
An electronic book accessible through the World Wide Web; click to view

Liquid crystals beyond displays chemistry, physics, and applications /

Table of Contents: “…Liquid Crystal-Based Chemical Sensors Jacob T. Hunter and Nicholas L. Abbott Chapter 16. …”
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Liquid crystals beyond displays chemistry, physics, and applications /

Table of Contents: “…Liquid Crystal-Based Chemical Sensors Jacob T. Hunter and Nicholas L. Abbott Chapter 16. …”
An electronic book accessible through the World Wide Web; click to view

Advanced design and manufacturing technology I : special topic volume with invited papers only /

Table of Contents: “…Preface -- Technology and Characteristic of Wool Ring Spun Compound Yarn -- A Co-Evolutionary Contract Net-Based Framework for Distributed Manufacturing Execution Systems -- The Research on Cutting Force in High-Speed Milling Process of Aluminum Alloy Impeller -- Research of Asynchronous Multi-Type Sensors Data Fusion -- Researcher of Region Growing Medical Image Segmentation Based on Adaboost Algorithm -- Trail Investigation on Chip of High-Speed and Dry Cutting on Hardened Steel with PCBN Tool -- Simulate Measure for Spring Back of Autobody Panel's Edge -- Reconfigurable Clamping Device Based on Memory Alloy, Orientation Disc, Majority Column and Telescopic Pole -- Analysis of Mechanical Characteristics and Structural Options of Micro-Milling Cutter -- Study on Predictive Control of Ship Steering Gear System -- Research of Hydroforming Technology for Special-Shaped Cross-Section Pipe -- Design of CNC Grinding Machine Especially for C.V Joint Inner Race Spherical Raceway Processing -- Passivation of the Fe-Based Bulk Amorphous Alloy in HCl Solution -- Simulation of Temperature Field during 7022 Al Alloy Friction Stir Welding process Based on Dual-Source -- Study on Al-4.5Cu-3Ce Alloy Semi-Solid Slurry Prepared by Slope Vibration Casting -- Precision Control Research on DACS-Based Modern Digital Shipbuilding Technology -- Contact Stress Analysis of NCD Coating on Roll Ball of Ball Bearing -- Low Cycling Thermal Fatigue of Large-Scale Marine Diesel Engine Piston -- Study on Remote Monitoring and Control System for Construction Vehicle -- Research on New Structural Quay Container Crane -- Study on the Microstructure and Properties of Suspensory Wire in DVD CD-ROM Head -- Investigation of the Precipitation in Mg-Zr Alloys -- The Optimization of Cutting Parameter of Machining the Small Diameter Deep Hole on Austenitic Stainless Steel -- An Analysis of Drawing Process in Stamping Die Design for the Wheel Hub -- Effects of Residual Stress on Interfacial Bonding Strength of Zinc-Plated Film -- Friction and Wear of Polished Single Crystal Silicon at Different Area -- Numerical Simulation of the Machining Distortion of Aircraft Aluminum Part Caused by Redistribution of Residual Stress -- Study on Fuzzy D-S Evidence Theory Mathematics Foundation Based on the Form Prototype -- Study on the Influence of Internal Flow Field in Pipeline Elbow by the Guide Plate -- Research on Electrical Resistively of Wood Dust -- Primary Research of Bionic Design on Tools with Mouthpart of Larvae Long Horned Beetles -- Adsorption Analysis of Cr(VI) by Fly Ash Composite Material in Aqueous Medium -- Research of Controlling Heat Treatment Deformation for Powder Metallurgy Mechanical Structural Parts -- Influence of Vacuum Heat Treatment on Sintered W-Cu Alloy Performances -- Design on Numerical Control System of Glass Cutting Machine Based on PC -- Fast Frequency Hopping Signal Generator Based on DDS -- The Optimization of Material Thickness for Neutron Shielding with Monte Carlo Method -- A Method to Measure Rotary Speed and Torque Using JC Sensors -- Different Evaluation Approaches of Confusion Network in Chinese Spoken Classification -- Study on Mine-Used Battery Locomotive Charging System -- Steel Wire Rope Section Damage Detection System Based on Wavelet Multi-Resolution Analysis -- Three-Level SVPWM Controller Design Based on FPGA -- Phase Error Immunity Optical Measurement System -- A Stable Least Squares Ellipses Fitting Algorithm Based on Zernike Moments -- Accuracy Verification Method about Optical Three-Dimensional Measuring Instrument -- Contrast Research on Cutting Forces in 4-Axis and 5-Axis Blade Machining Process -- A Method to Center Extraction of Reference Point Algorithm in Reverse Engineering -- Optimal Design of Flexible Manufacturing System Based on Optical Measurement Principle -- Material Removal for Modal Effect on Impeller Blades by Finite Element Analysis -- Rotation Inertia Measurement Device Design of Winged Rigid Body Based on TRIZ Conflict Resolving Matrix -- Development of NC System of the 3-PUU Parallel Machine Tool Based on PMAC -- Finite Element Analysis and Dynamic Testing for Hard Gear Cutting by Gear Hobbing Machine -- Design and Stimulation of Hydraulic Servo System for Vehicle Test Equipment for Rubber Shock Absorber -- Research on Chip Breaking Mechanism of High-Temperature and High-Strength Steel 2.25Cr-1Mo-0.25V -- Research on the Machinability of Hydrogenated Cylindrical Shell Materials (2.25 Cr-1Mo-0.25V Steel) -- Applied Research of the Electric Spindle Technology on Sub-Nanometer Crusher with Cellulosine -- High-Speed Milling Toolpath Planning for Aviation Engines Impeller Using POWERMILL Software -- Finite Element Analysis of Cold Extrusion Combination Mold Interference Fit -- Coagulant Prepared by Gangue and its Application in Treatment of Coal Washing Wastewater -- Development and Oxidation of RexOy-Modified Aluminide Coating -- Design and Research on Two-Degree of Freedom Spherical Gear -- An Algorithm for Computation of Radial-Harmonic-Fourier Moments -- Applied Research on Synesthesia Theory in Industrial Design.…”
An electronic book accessible through the World Wide Web; click to view

Advanced design and manufacturing technology I : special topic volume with invited papers only /

Table of Contents: “…Preface -- Technology and Characteristic of Wool Ring Spun Compound Yarn -- A Co-Evolutionary Contract Net-Based Framework for Distributed Manufacturing Execution Systems -- The Research on Cutting Force in High-Speed Milling Process of Aluminum Alloy Impeller -- Research of Asynchronous Multi-Type Sensors Data Fusion -- Researcher of Region Growing Medical Image Segmentation Based on Adaboost Algorithm -- Trail Investigation on Chip of High-Speed and Dry Cutting on Hardened Steel with PCBN Tool -- Simulate Measure for Spring Back of Autobody Panel's Edge -- Reconfigurable Clamping Device Based on Memory Alloy, Orientation Disc, Majority Column and Telescopic Pole -- Analysis of Mechanical Characteristics and Structural Options of Micro-Milling Cutter -- Study on Predictive Control of Ship Steering Gear System -- Research of Hydroforming Technology for Special-Shaped Cross-Section Pipe -- Design of CNC Grinding Machine Especially for C.V Joint Inner Race Spherical Raceway Processing -- Passivation of the Fe-Based Bulk Amorphous Alloy in HCl Solution -- Simulation of Temperature Field during 7022 Al Alloy Friction Stir Welding process Based on Dual-Source -- Study on Al-4.5Cu-3Ce Alloy Semi-Solid Slurry Prepared by Slope Vibration Casting -- Precision Control Research on DACS-Based Modern Digital Shipbuilding Technology -- Contact Stress Analysis of NCD Coating on Roll Ball of Ball Bearing -- Low Cycling Thermal Fatigue of Large-Scale Marine Diesel Engine Piston -- Study on Remote Monitoring and Control System for Construction Vehicle -- Research on New Structural Quay Container Crane -- Study on the Microstructure and Properties of Suspensory Wire in DVD CD-ROM Head -- Investigation of the Precipitation in Mg-Zr Alloys -- The Optimization of Cutting Parameter of Machining the Small Diameter Deep Hole on Austenitic Stainless Steel -- An Analysis of Drawing Process in Stamping Die Design for the Wheel Hub -- Effects of Residual Stress on Interfacial Bonding Strength of Zinc-Plated Film -- Friction and Wear of Polished Single Crystal Silicon at Different Area -- Numerical Simulation of the Machining Distortion of Aircraft Aluminum Part Caused by Redistribution of Residual Stress -- Study on Fuzzy D-S Evidence Theory Mathematics Foundation Based on the Form Prototype -- Study on the Influence of Internal Flow Field in Pipeline Elbow by the Guide Plate -- Research on Electrical Resistively of Wood Dust -- Primary Research of Bionic Design on Tools with Mouthpart of Larvae Long Horned Beetles -- Adsorption Analysis of Cr(VI) by Fly Ash Composite Material in Aqueous Medium -- Research of Controlling Heat Treatment Deformation for Powder Metallurgy Mechanical Structural Parts -- Influence of Vacuum Heat Treatment on Sintered W-Cu Alloy Performances -- Design on Numerical Control System of Glass Cutting Machine Based on PC -- Fast Frequency Hopping Signal Generator Based on DDS -- The Optimization of Material Thickness for Neutron Shielding with Monte Carlo Method -- A Method to Measure Rotary Speed and Torque Using JC Sensors -- Different Evaluation Approaches of Confusion Network in Chinese Spoken Classification -- Study on Mine-Used Battery Locomotive Charging System -- Steel Wire Rope Section Damage Detection System Based on Wavelet Multi-Resolution Analysis -- Three-Level SVPWM Controller Design Based on FPGA -- Phase Error Immunity Optical Measurement System -- A Stable Least Squares Ellipses Fitting Algorithm Based on Zernike Moments -- Accuracy Verification Method about Optical Three-Dimensional Measuring Instrument -- Contrast Research on Cutting Forces in 4-Axis and 5-Axis Blade Machining Process -- A Method to Center Extraction of Reference Point Algorithm in Reverse Engineering -- Optimal Design of Flexible Manufacturing System Based on Optical Measurement Principle -- Material Removal for Modal Effect on Impeller Blades by Finite Element Analysis -- Rotation Inertia Measurement Device Design of Winged Rigid Body Based on TRIZ Conflict Resolving Matrix -- Development of NC System of the 3-PUU Parallel Machine Tool Based on PMAC -- Finite Element Analysis and Dynamic Testing for Hard Gear Cutting by Gear Hobbing Machine -- Design and Stimulation of Hydraulic Servo System for Vehicle Test Equipment for Rubber Shock Absorber -- Research on Chip Breaking Mechanism of High-Temperature and High-Strength Steel 2.25Cr-1Mo-0.25V -- Research on the Machinability of Hydrogenated Cylindrical Shell Materials (2.25 Cr-1Mo-0.25V Steel) -- Applied Research of the Electric Spindle Technology on Sub-Nanometer Crusher with Cellulosine -- High-Speed Milling Toolpath Planning for Aviation Engines Impeller Using POWERMILL Software -- Finite Element Analysis of Cold Extrusion Combination Mold Interference Fit -- Coagulant Prepared by Gangue and its Application in Treatment of Coal Washing Wastewater -- Development and Oxidation of RexOy-Modified Aluminide Coating -- Design and Research on Two-Degree of Freedom Spherical Gear -- An Algorithm for Computation of Radial-Harmonic-Fourier Moments -- Applied Research on Synesthesia Theory in Industrial Design.…”
An electronic book accessible through the World Wide Web; click to view

The Future Internet Future Internet Assembly 2013: Validated Results and New Horizons /

Table of Contents: “…Software Driven Networks, Virtualisation, Programmability and Autonomic Management -- Towards a Socially-Aware Management of New Overlay Application Traffic Combined with Energy Efficiency in the Internet (SmartenIT) -- The NEBULA Future Internet Architecture -- Open the Way to Future Networks – A Viewpoint Framework from ITU-T -- Towards a Minimal Core for Information-Centric Networking -- Managing QoS for Future Internet Applications over Virtual Sensor Networks -- High Availability in the Future Internet -- Integrating OpenFlow in IMS Networks and Enabling for Future Internet Research and Experimentation -- Computing and Networking Clouds Contrail: Distributed Application Deployment under SLA in Federated Heterogeneous Clouds -- Cloud–Based Evaluation Framework for Big Data -- Optimizing Service Ecosystems in the Cloud -- Resource Optimisation in IoT Cloud Systems by Using Matchmaking and Self-management Principles -- Towards a Secure Network Virtualization Architecture for the Future Internet -- Seeding the Cloud: An Innovative Approach to Grow Trust in Cloud Based Infrastructures -- Internet of Things -- IoT6 – Moving to an IPv6-Based Future IoT -- SmartSantander: Internet of Things Research and Innovation through Citizen Participation -- A Cognitive Management Framework for Empowering the Internet of Things -- Building Modular Middlewares for the Internet of Things with OSGi -- Towards an Architecture for Future Internet Applications -- ComVantage: Mobile Enterprise Collaboration Reference Framework and Enablers for Future Internet Information Interoperability -- Test-Enabled Architecture for IoT Service Creation and Provisioning -- Enabling Technologies and Economic Incentives Sustainable Wireless Broadband Access to the Future Internet -- The EARTH Project -- An Internet-Based Architecture Supporting Ubiquitous Application User Interfaces -- Cooperative Strategies for Power Saving in Multi-standard Wireless Devices -- Counting the Cost of FIRE: Overcoming Barriers to Sustainable Experimentation Facilities -- User Involvement in Future Internet Projects -- Design and Implementation of Cooperative Network Connectivity Proxy Using Universal Plug and Play -- Book Sponsoring Projects Overview 3DLife - Bringing the Media Internet to Life -- CONCORD Project Management of the Future Internet -- FLAMINGO NoE Project Management of the Future Internet -- The GEYSERS Concept and Major Outcomes -- iCore: A Cognitive Management Framework for the Internet of Things -- IoT6 Project in a Nutshell -- Mobile Cloud Networking: Mobile Network, Compute, and Storage as One Service On-Demand -- The SmartenIT STREP Project: Socially-Aware Management of New Overlay Application Traffic Combined with Energy Efficiency in the Internet -- The SmartSantander Project -- UniverSelf, Realizing Autonomics for Future Networks.…”
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The Future Internet Future Internet Assembly 2013: Validated Results and New Horizons /

Table of Contents: “…Software Driven Networks, Virtualisation, Programmability and Autonomic Management -- Towards a Socially-Aware Management of New Overlay Application Traffic Combined with Energy Efficiency in the Internet (SmartenIT) -- The NEBULA Future Internet Architecture -- Open the Way to Future Networks – A Viewpoint Framework from ITU-T -- Towards a Minimal Core for Information-Centric Networking -- Managing QoS for Future Internet Applications over Virtual Sensor Networks -- High Availability in the Future Internet -- Integrating OpenFlow in IMS Networks and Enabling for Future Internet Research and Experimentation -- Computing and Networking Clouds Contrail: Distributed Application Deployment under SLA in Federated Heterogeneous Clouds -- Cloud–Based Evaluation Framework for Big Data -- Optimizing Service Ecosystems in the Cloud -- Resource Optimisation in IoT Cloud Systems by Using Matchmaking and Self-management Principles -- Towards a Secure Network Virtualization Architecture for the Future Internet -- Seeding the Cloud: An Innovative Approach to Grow Trust in Cloud Based Infrastructures -- Internet of Things -- IoT6 – Moving to an IPv6-Based Future IoT -- SmartSantander: Internet of Things Research and Innovation through Citizen Participation -- A Cognitive Management Framework for Empowering the Internet of Things -- Building Modular Middlewares for the Internet of Things with OSGi -- Towards an Architecture for Future Internet Applications -- ComVantage: Mobile Enterprise Collaboration Reference Framework and Enablers for Future Internet Information Interoperability -- Test-Enabled Architecture for IoT Service Creation and Provisioning -- Enabling Technologies and Economic Incentives Sustainable Wireless Broadband Access to the Future Internet -- The EARTH Project -- An Internet-Based Architecture Supporting Ubiquitous Application User Interfaces -- Cooperative Strategies for Power Saving in Multi-standard Wireless Devices -- Counting the Cost of FIRE: Overcoming Barriers to Sustainable Experimentation Facilities -- User Involvement in Future Internet Projects -- Design and Implementation of Cooperative Network Connectivity Proxy Using Universal Plug and Play -- Book Sponsoring Projects Overview 3DLife - Bringing the Media Internet to Life -- CONCORD Project Management of the Future Internet -- FLAMINGO NoE Project Management of the Future Internet -- The GEYSERS Concept and Major Outcomes -- iCore: A Cognitive Management Framework for the Internet of Things -- IoT6 Project in a Nutshell -- Mobile Cloud Networking: Mobile Network, Compute, and Storage as One Service On-Demand -- The SmartenIT STREP Project: Socially-Aware Management of New Overlay Application Traffic Combined with Energy Efficiency in the Internet -- The SmartSantander Project -- UniverSelf, Realizing Autonomics for Future Networks.…”
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Guide to state-of-the-art electron devices

Table of Contents: “…Machine generated contents note: Foreword Preface Contributors and Acknowledgements Historic Timeline Part I - Basic Electron Devices 1 Bipolar Transistors 1.1 Motivation 1.2 The pn Junction and Its Electronic Applications 1.3 The Bipolar Junction Transistor and Its Electronic Applications 1.4 Optimization of Bipolar Transistors 1.5 SiGe Heterojunction Bipolar Transistors References 2 MOS Devices 2.1 Introduction 2.2 MOSFET Basics 2.3 The Evolution of MOSFET 2.4 Concluding Remarks References 3 Memory Devices 3.1 Introduction 3.2 Volatile Memories 3.3 Non-Volatile Memories 3.4 Future Perspectives of MOS Memories 3.5 Closing Remarks References 4 Passive Components 4.1 Discrete and integrated passive components 4.2 Application in Analog ICs and DRAM 4.3 The planar Spiral Inductor - A Case Study 4.4 Parasitics in Integrated Circuits References 5 Emerging Research Devices 5.1 Non-Charge Based Switching 5.2 Carbon as a Replacement for Silicon and the Rise of Moletronics 5.3 Conclusions References Part II - Aspects of Device and IC Manufacturing 6 Electronics Materials 6.1 Introduction 6.2 Silicon Device Technology 6.3 Compound Semiconductor Devices 6.4 Electronic Displays 6.5 Conclusions References 7 Compact Modeling 7.1 The Role of Compact Models 7.2 Bipolar Transistor Compact Modeling 7.3 MOS Transistor Compact Modeling 7.4 Compact Modeling of Passive Components 7.5 Benchmarking and Implementation References 8 Technology Computer Aided Design 8.1 Introduction 8.2 Drift-Diffusion Model 8.3 Microscopic Transport Models 8.4 Quantum Transport Models 8.5 Process and Equipment Simulation References 9 Device Reliability Physics 9.1 Introduction and Background 9.2 Device Reliability Issues 9.3 Interconnect Degradation Mechanisms 9.4 Circuit-Level Reliability Issues 9.5 Microscopic Approaches to Assuring Reliability of ICs References 10 Semiconductor Manufacturing 10.1 Introduction 10.2 Substrates 10.3 Lithography and Etching 10.4 Front-End Processing 10.5 Back-End Processing 10.6 Process Control 10.7 Assembly and Test 10.8 Future Directions References Part III - Applications based on Electron Devices 11 VLSI Logic Technology and Circuits 11.1 Introduction 11.2 MOSFET Scaling Trends 11.3 Low-Power and High-Speed Logic Design 11.4 Scaling-Driven technology Enhancements 11.5 Ultra-Low Voltage Transistors 11.6 Interconnects 11.7 Memory Design 11.8 System Integration References 12 VLSI Mixed-Signal Technology And Circuits 12.1 Introduction 12.2 Analog/Mixed-Signal Technologies in Scaled CMOS 12.3 Data Converter ICs 12.4 Mixed-Signal Circuits in Low-Power Display Applications 12.5 Image Sensor Technology and Circuits References 13 Memory Technologies 13.1 Semiconductor Memory History 13.2 State of Mainstream Semiconductor Memory Today 13.3 Emerging Memory Technologies 13.4 Conclusions References 14 RF&Microwave Semiconductor Technologies 14.1 III-V Based: GaAs and InP 14.2 Si and SiGe 14.3 Wide Bandgap Devices (Group III-Nitrides, SiC and Diamond) References 15 Power Devices and ICs 15.1 Overview of Power Devices & ICs 15.2 Two-Carrier and High-Power Devices 15.3 Power MOSFET Devices 15.4 High-Voltage and Power ICs 15.5 Wide Bandgap Power Devices References 16 Photovoltaic Device Applications 16.1 Introduction 16.2 Silicon Photovoltaics 16.3 Polycrystalline Thin-Film Photovoltaics 16.4 III-V Compound Photovoltaics 16.5 Future Concepts in Photovoltaics References 17 Large Area Electronics 17.1 Thin-Film Solar Cells 17.2 Large-Area Imaging 17.3 Flat-Panel Displays References 18 Microelectromechanical Systems (MEMS) 18.1 Introduction 18.2 The 1960's - First Micromachined Structures Envisioned 18.3 The 1970's - Integrated Sensors Started 18.4 The 1980's - Surface Micromachining Emerged 18.5 The 1990's - MEMS Impacted Various Fields 18.6 The 2000's - Diversified Sophisticated Systems Enabled By MEMS 18.7 Future Outlook References 19 Vacuum Device Applications 19.1 Traveling-Wave Devices 19.2 Klystrons 19.3 Inductive Output Tubes 19.4 Crossed-Field Devices 19.5 Gyro-Devices References 20 Optoelectronic Device Applications 20.1 Introduction 20.2 Light Emission in Semiconductors 20.3 Photodetectors 20.4 Integrated Optoelectronics 20.5 Optical Interconnects 20.6 Concluding Remarks References 21 Devices for the Post Silicon CMOS Era 21.1 Introduction 21.2 Devices for the 8-nm Node With Conventional Materials 21.3 New Channel Materials and Devices 21.4 Concluding Remarks References Index.…”
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Guide to state-of-the-art electron devices

Table of Contents: “…Machine generated contents note: Foreword Preface Contributors and Acknowledgements Historic Timeline Part I - Basic Electron Devices 1 Bipolar Transistors 1.1 Motivation 1.2 The pn Junction and Its Electronic Applications 1.3 The Bipolar Junction Transistor and Its Electronic Applications 1.4 Optimization of Bipolar Transistors 1.5 SiGe Heterojunction Bipolar Transistors References 2 MOS Devices 2.1 Introduction 2.2 MOSFET Basics 2.3 The Evolution of MOSFET 2.4 Concluding Remarks References 3 Memory Devices 3.1 Introduction 3.2 Volatile Memories 3.3 Non-Volatile Memories 3.4 Future Perspectives of MOS Memories 3.5 Closing Remarks References 4 Passive Components 4.1 Discrete and integrated passive components 4.2 Application in Analog ICs and DRAM 4.3 The planar Spiral Inductor - A Case Study 4.4 Parasitics in Integrated Circuits References 5 Emerging Research Devices 5.1 Non-Charge Based Switching 5.2 Carbon as a Replacement for Silicon and the Rise of Moletronics 5.3 Conclusions References Part II - Aspects of Device and IC Manufacturing 6 Electronics Materials 6.1 Introduction 6.2 Silicon Device Technology 6.3 Compound Semiconductor Devices 6.4 Electronic Displays 6.5 Conclusions References 7 Compact Modeling 7.1 The Role of Compact Models 7.2 Bipolar Transistor Compact Modeling 7.3 MOS Transistor Compact Modeling 7.4 Compact Modeling of Passive Components 7.5 Benchmarking and Implementation References 8 Technology Computer Aided Design 8.1 Introduction 8.2 Drift-Diffusion Model 8.3 Microscopic Transport Models 8.4 Quantum Transport Models 8.5 Process and Equipment Simulation References 9 Device Reliability Physics 9.1 Introduction and Background 9.2 Device Reliability Issues 9.3 Interconnect Degradation Mechanisms 9.4 Circuit-Level Reliability Issues 9.5 Microscopic Approaches to Assuring Reliability of ICs References 10 Semiconductor Manufacturing 10.1 Introduction 10.2 Substrates 10.3 Lithography and Etching 10.4 Front-End Processing 10.5 Back-End Processing 10.6 Process Control 10.7 Assembly and Test 10.8 Future Directions References Part III - Applications based on Electron Devices 11 VLSI Logic Technology and Circuits 11.1 Introduction 11.2 MOSFET Scaling Trends 11.3 Low-Power and High-Speed Logic Design 11.4 Scaling-Driven technology Enhancements 11.5 Ultra-Low Voltage Transistors 11.6 Interconnects 11.7 Memory Design 11.8 System Integration References 12 VLSI Mixed-Signal Technology And Circuits 12.1 Introduction 12.2 Analog/Mixed-Signal Technologies in Scaled CMOS 12.3 Data Converter ICs 12.4 Mixed-Signal Circuits in Low-Power Display Applications 12.5 Image Sensor Technology and Circuits References 13 Memory Technologies 13.1 Semiconductor Memory History 13.2 State of Mainstream Semiconductor Memory Today 13.3 Emerging Memory Technologies 13.4 Conclusions References 14 RF&Microwave Semiconductor Technologies 14.1 III-V Based: GaAs and InP 14.2 Si and SiGe 14.3 Wide Bandgap Devices (Group III-Nitrides, SiC and Diamond) References 15 Power Devices and ICs 15.1 Overview of Power Devices & ICs 15.2 Two-Carrier and High-Power Devices 15.3 Power MOSFET Devices 15.4 High-Voltage and Power ICs 15.5 Wide Bandgap Power Devices References 16 Photovoltaic Device Applications 16.1 Introduction 16.2 Silicon Photovoltaics 16.3 Polycrystalline Thin-Film Photovoltaics 16.4 III-V Compound Photovoltaics 16.5 Future Concepts in Photovoltaics References 17 Large Area Electronics 17.1 Thin-Film Solar Cells 17.2 Large-Area Imaging 17.3 Flat-Panel Displays References 18 Microelectromechanical Systems (MEMS) 18.1 Introduction 18.2 The 1960's - First Micromachined Structures Envisioned 18.3 The 1970's - Integrated Sensors Started 18.4 The 1980's - Surface Micromachining Emerged 18.5 The 1990's - MEMS Impacted Various Fields 18.6 The 2000's - Diversified Sophisticated Systems Enabled By MEMS 18.7 Future Outlook References 19 Vacuum Device Applications 19.1 Traveling-Wave Devices 19.2 Klystrons 19.3 Inductive Output Tubes 19.4 Crossed-Field Devices 19.5 Gyro-Devices References 20 Optoelectronic Device Applications 20.1 Introduction 20.2 Light Emission in Semiconductors 20.3 Photodetectors 20.4 Integrated Optoelectronics 20.5 Optical Interconnects 20.6 Concluding Remarks References 21 Devices for the Post Silicon CMOS Era 21.1 Introduction 21.2 Devices for the 8-nm Node With Conventional Materials 21.3 New Channel Materials and Devices 21.4 Concluding Remarks References Index.…”
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Handbook of biosurveillance

Table of Contents: “…Johnson, and Virginia Dato -- Physiologic and space-based sensors / Ron M. Aryel -- Data NOS (not otherwise specified) / Michael M. …”
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Understanding ultrasonic level measurement by Milligan, Stephen

Table of Contents: “…. -- The sound and the slurry -- Topics -- Transducers and ultrasonic systems -- Single systems -- Compound systems -- Transducers -- Temperature and transducer material -- Temperature sensors -- Sound and differential amplifiers -- Single-ended receiver -- Differential receiver -- Application temperature -- Housing material -- Range and power -- Conditions -- Dust -- Stilling wells -- Foam facing -- Moisture on transducer face -- Transducer selection -- Blanking distance and height placement -- Temperature -- Installation -- Transducer design: the heart of the matter -- Summary --…”
An electronic book accessible through the World Wide Web; click to view

Handbook of biosurveillance

Table of Contents: “…Johnson, and Virginia Dato -- Physiologic and space-based sensors / Ron M. Aryel -- Data NOS (not otherwise specified) / Michael M. …”
An electronic book accessible through the World Wide Web; click to view

Understanding ultrasonic level measurement by Milligan, Stephen

Table of Contents: “…. -- The sound and the slurry -- Topics -- Transducers and ultrasonic systems -- Single systems -- Compound systems -- Transducers -- Temperature and transducer material -- Temperature sensors -- Sound and differential amplifiers -- Single-ended receiver -- Differential receiver -- Application temperature -- Housing material -- Range and power -- Conditions -- Dust -- Stilling wells -- Foam facing -- Moisture on transducer face -- Transducer selection -- Blanking distance and height placement -- Temperature -- Installation -- Transducer design: the heart of the matter -- Summary --…”
An electronic book accessible through the World Wide Web; click to view

Principles of GNSS, inertial, and multisensor integrated navigation systems / by Groves, Paul D. (Paul David)

Table of Contents: “…Machine generated contents note: ch. 1 Introduction -- 1.1.Fundamental Concepts -- 1.2.Dead Reckoning -- 1.3.Position Fixing -- 1.3.1.Position-Fixing Methods -- 1.3.2.Signal-Based Positioning -- 1.3.3.Environmental Feature Matching -- 1.4.The Navigation System -- 1.4.1.Requirements -- 1.4.2.Context -- 1.4.3.Integration -- 1.4.4.Aiding -- 1.4.5.Assistance and Cooperation -- 1.4.6.Fault Detection -- 1.5.Overview of the Book -- References -- ch. 2 Coordinate Frames, Kinematics, and the Earth -- 2.1.Coordinate Frames -- 2.1.1.Earth-Centered Inertial Frame -- 2.1.2.Earth-Centered Earth-Fixed Frame -- 2.1.3.Local Navigation Frame -- 2.1.4.Local Tangent-Plane Frame -- 2.1.5.Body Frame -- 2.1.6.Other Frames -- 2.2.Attitude, Rotation, and Resolving Axes Transformations -- 2.2.1.Euler Attitude -- 2.2.2.Coordinate Transformation Matrix -- 2.2.3.Quaternion Attitude -- 2.2.4.Rotation Vector -- 2.3.Kinematics -- 2.3.1.Angular Rate -- 2.3.2.Cartesian Position -- 2.3.3.Velocity -- 2.3.4.Acceleration -- 2.3.5.Motion with Respect to a Rotating Reference Frame -- 2.4.Earth Surface and Gravity Models -- 2.4.1.The Ellipsoid Model of the Earth's Surface -- 2.4.2.Curvilinear Position -- 2.4.3.Position Conversion -- 2.4.4.The Geoid, Orthometric Height, and Earth Tides -- 2.4.5.Projected Coordinates -- 2.4.6.Earth Rotation -- 2.4.7.Specific Force, Gravitation, and Gravity -- 2.5.Frame Transformations -- 2.5.1.Inertial and Earth Frames -- 2.5.2.Earth and Local Navigation Frames -- 2.5.3.Inertial and Local Navigation Frames -- 2.5.4.Earth and Local Tangent-Plane Frames -- 2.5.5.Transposition of Navigation Solutions -- References -- ch. 3 Kalman Filter-Based Estimation -- 3.1.Introduction -- 3.1.1.Elements of the Kalman Filter -- 3.1.2.Steps of the Kalman Filter -- 3.1.3.Kalman Filter Applications -- 3.2.Algorithms and Models -- 3.2.1.Definitions -- 3.2.2.Kalman Filter Algorithm -- 3.2.3.System Model -- 3.2.4.Measurement Model -- 3.2.5.Kalman Filter Behavior and State Observability -- 3.2.6.Closed-Loop Kalman Filter -- 3.2.7.Sequential Measurement Update -- 3.3.Implementation Issues -- 3.3.1.Tuning and Stability -- 3.3.2.Algorithm Design -- 3.3.3.Numerical Issues -- 3.3.4.Time Synchronization -- 3.3.5.Kalman Filter Design Process -- 3.4.Extensions to the Kalman Filter -- 3.4.1.Extended and Linearized Kalman Filter -- 3.4.2.Unscented Kalman Filter -- 3.4.3.Time-Correlated Noise -- 3.4.4.Adaptive Kalman Filter -- 3.4.5.Multiple-Hypothesis Filtering -- 3.4.6.Kalman Smoothing -- 3.5.The Particle Filter -- References -- ch. 4 Inertial Sensors -- 4.1.Accelerometers -- 4.1.1.Pendulous Accelerometers -- 4.1.2.Vibrating-Beam Accelerometers -- 4.2.Gyroscopes -- 4.2.1.Optical Gyroscopes -- 4.2.2.Vibratory Gyroscopes -- 4.3.Inertial Measurement Units -- 4.4.Error Characteristics -- 4.4.1.Biases -- 4.4.2.Scale Factor and Cross-Coupling Errors -- 4.4.3.Random Noise -- 4.4.4.Further Error Sources -- 4.4.5.Vibration-Induced Errors -- 4.4.6.Error Models -- References -- ch. 5 Inertial Navigation -- 5.1.Introduction to Inertial Navigation -- 5.2.Inertial-Frame Navigation Equations -- 5.2.1.Attitude Update -- 5.2.2.Specific-Force Frame Transformation -- 5.2.3.Velocity Update -- 5.2.4.Position Update -- 5.3.Earth-Frame Navigation Equations -- 5.3.1.Attitude Update -- 5.3.2.Specific-Force Frame Transformation -- 5.3.3.Velocity Update -- 5.3.4.Position Update -- 5.4.Local-Navigation-Frame Navigation Equations -- 5.4.1.Attitude Update -- 5.4.2.Specific-Force Frame Transformation -- 5.4.3.Velocity Update -- 5.4.4.Position Update -- 5.4.5.Wander-Azimuth Implementation -- 5.5.Navigation Equations Optimization -- 5.5.1.Precision Attitude Update -- 5.5.2.Precision Specific-Force Frame Transformation -- 5.5.3.Precision Velocity and Position Updates -- 5.5.4.Effects of Sensor Sampling Interval and Vibration -- 5.5.5.Design Tradeoffs -- 5.6.Initialization and Alignment -- 5.6.1.Position and Velocity Initialization -- 5.6.2.Attitude Initialization -- 5.6.3.Fine Alignment -- 5.7.INS Error Propagation -- 5.7.1.Short-Term Straight-Line Error Propagation -- 5.7.2.Medium- and Long-Term Error Propagation -- 5.7.3.Maneuver-Dependent Errors -- 5.8.Indexed IMU -- 5.9.Partial IMU -- References -- ch. 6 Dead Reckoning, Attitude, and Height Measurement -- 6.1.Attitude Measurement -- 6.1.1.Magnetic Heading -- 6.1.2.Marine Gyrocompass -- 6.1.3.Strapdown Yaw-Axis Gyro -- 6.1.4.Heading from Trajectory -- 6.1.5.Integrated Heading Determination -- 6.1.6.Accelerometer Leveling and Tilt Sensors -- 6.1.7.Horizon Sensing -- 6.1.8.Attitude and Heading Reference System -- 6.2.Height and Depth Measurement -- 6.2.1.Barometric Altimeter -- 6.2.2.Depth Pressure Sensor -- 6.2.3.Radar Altimeter -- 6.3.Odometry -- 6.3.1.Linear Odometry -- 6.3.2.Differential Odometry -- 6.3.3.Integrated Odometry and Partial IMU -- 6.4.Pedestrian Dead Reckoning Using Step Detection -- 6.5.Doppler Radar and Sonar -- 6.6.Other Dead-Reckoning Techniques -- 6.6.1.Correlation-Based Velocity Measurement -- 6.6.2.Air Data -- 6.6.3.Ship's Speed Log -- References -- ch. 7 Principles of Radio Positioning -- 7.1.Radio Positioning Configurations and Methods -- 7.1.1.Self-Positioning and Remote Positioning -- 7.1.2.Relative Positioning -- 7.1.3.Proximity -- 7.1.4.Ranging -- 7.1.5.Angular Positioning -- 7.1.6.Pattern Matching -- 7.1.7.Doppler Positioning -- 7.2.Positioning Signals -- 7.2.1.Modulation Types -- 7.2.2.Radio Spectrum -- 7.3.User Equipment -- 7.3.1.Architecture -- 7.3.2.Signal Timing Measurement -- 7.3.3.Position Determination from Ranging -- 7.4.Propagation, Error Sources, and Positioning Accuracy -- 7.4.1.Ionosphere, Troposphere, and Surface Propagation Effects -- 7.4.2.Attenuation, Reflection, Multipath, and Diffraction -- 7.4.3.Resolution, Noise, and Tracking Errors -- 7.4.4.Transmitter Location and Timing Errors -- 7.4.5.Effect of Signal Geometry -- References -- ch. 8 GNSS: Fundamentals, Signals, and Satellites -- 8.1.Fundamentals of Satellite Navigation -- 8.1.1.GNSS Architecture -- 8.1.2.Signals and Range Measurement -- 8.1.3.Positioning -- 8.1.4.Error Sources and Performance Limitations -- 8.2.The Systems -- 8.2.1.Global Positioning System -- 8.2.2.GLONASS -- 8.2.3.Galileo -- 8.2.4.Beidou -- 8.2.5.Regional Systems -- 8.2.6.Augmentation Systems -- 8.2.7.System Compatibility -- 8.3.GNSS Signals -- 8.3.1.Signal Types -- 8.3.2.Global Positioning System -- 8.3.3.GLONASS -- 8.3.4.Galileo -- 8.3.5.Beidou -- 8.3.6.Regional Systems -- 8.3.7.Augmentation Systems -- 8.4.Navigation Data Messages -- 8.4.1.GPS -- 8.4.2.GLONASS -- 8.4.3.Galileo -- 8.4.4.SBAS -- 8.4.5.Time Base Synchronization -- 8.5.Satellite Orbits and Geometry -- 8.5.1.Satellite Orbits -- 8.5.2.Satellite Position and Velocity -- 8.5.3.Range, Range Rate, and Line of Sight -- 8.5.4.Elevation and Azimuth -- References -- ch. 9 GNSS: User Equipment Processing and Errors -- 9.1.Receiver Hardware and Antenna -- 9.1.1.Antennas -- 9.1.2.Reference Oscillator -- 9.1.3.Receiver Front End -- 9.1.4.Baseband Signal Processor -- 9.2.Ranging Processor -- 9.2.1.Acquisition -- 9.2.2.Code Tracking -- 9.2.3.Carrier Tracking -- 9.2.4.Tracking Lock Detection -- 9.2.5.Navigation-Message Demodulation -- 9.2.6.Carrier-Power-to-Noise-Density Measurement -- 9.2.7.Pseudo-Range, Pseudo-Range-Rate, and Carrier-Phase Measurements -- 9.3.Range Error Sources -- 9.3.1.Ephemeris Prediction and Satellite Clock Errors -- 9.3.2.Ionosphere and Troposphere Propagation Errors -- 9.3.3.Tracking Errors -- 9.3.4.Multipath, Nonline-of-Sight, and Diffraction -- 9.4.Navigation Processor -- 9.4.1.Single-Epoch Navigation Solution -- 9.4.2.Filtered Navigation Solution -- 9.4.3.Signal Geometry and Navigation Solution Accuracy -- 9.4.4.Position Error Budget -- References -- ch.…”
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Principles of GNSS, inertial, and multisensor integrated navigation systems / by Groves, Paul D. (Paul David)

Table of Contents: “…Machine generated contents note: ch. 1 Introduction -- 1.1.Fundamental Concepts -- 1.2.Dead Reckoning -- 1.3.Position Fixing -- 1.3.1.Position-Fixing Methods -- 1.3.2.Signal-Based Positioning -- 1.3.3.Environmental Feature Matching -- 1.4.The Navigation System -- 1.4.1.Requirements -- 1.4.2.Context -- 1.4.3.Integration -- 1.4.4.Aiding -- 1.4.5.Assistance and Cooperation -- 1.4.6.Fault Detection -- 1.5.Overview of the Book -- References -- ch. 2 Coordinate Frames, Kinematics, and the Earth -- 2.1.Coordinate Frames -- 2.1.1.Earth-Centered Inertial Frame -- 2.1.2.Earth-Centered Earth-Fixed Frame -- 2.1.3.Local Navigation Frame -- 2.1.4.Local Tangent-Plane Frame -- 2.1.5.Body Frame -- 2.1.6.Other Frames -- 2.2.Attitude, Rotation, and Resolving Axes Transformations -- 2.2.1.Euler Attitude -- 2.2.2.Coordinate Transformation Matrix -- 2.2.3.Quaternion Attitude -- 2.2.4.Rotation Vector -- 2.3.Kinematics -- 2.3.1.Angular Rate -- 2.3.2.Cartesian Position -- 2.3.3.Velocity -- 2.3.4.Acceleration -- 2.3.5.Motion with Respect to a Rotating Reference Frame -- 2.4.Earth Surface and Gravity Models -- 2.4.1.The Ellipsoid Model of the Earth's Surface -- 2.4.2.Curvilinear Position -- 2.4.3.Position Conversion -- 2.4.4.The Geoid, Orthometric Height, and Earth Tides -- 2.4.5.Projected Coordinates -- 2.4.6.Earth Rotation -- 2.4.7.Specific Force, Gravitation, and Gravity -- 2.5.Frame Transformations -- 2.5.1.Inertial and Earth Frames -- 2.5.2.Earth and Local Navigation Frames -- 2.5.3.Inertial and Local Navigation Frames -- 2.5.4.Earth and Local Tangent-Plane Frames -- 2.5.5.Transposition of Navigation Solutions -- References -- ch. 3 Kalman Filter-Based Estimation -- 3.1.Introduction -- 3.1.1.Elements of the Kalman Filter -- 3.1.2.Steps of the Kalman Filter -- 3.1.3.Kalman Filter Applications -- 3.2.Algorithms and Models -- 3.2.1.Definitions -- 3.2.2.Kalman Filter Algorithm -- 3.2.3.System Model -- 3.2.4.Measurement Model -- 3.2.5.Kalman Filter Behavior and State Observability -- 3.2.6.Closed-Loop Kalman Filter -- 3.2.7.Sequential Measurement Update -- 3.3.Implementation Issues -- 3.3.1.Tuning and Stability -- 3.3.2.Algorithm Design -- 3.3.3.Numerical Issues -- 3.3.4.Time Synchronization -- 3.3.5.Kalman Filter Design Process -- 3.4.Extensions to the Kalman Filter -- 3.4.1.Extended and Linearized Kalman Filter -- 3.4.2.Unscented Kalman Filter -- 3.4.3.Time-Correlated Noise -- 3.4.4.Adaptive Kalman Filter -- 3.4.5.Multiple-Hypothesis Filtering -- 3.4.6.Kalman Smoothing -- 3.5.The Particle Filter -- References -- ch. 4 Inertial Sensors -- 4.1.Accelerometers -- 4.1.1.Pendulous Accelerometers -- 4.1.2.Vibrating-Beam Accelerometers -- 4.2.Gyroscopes -- 4.2.1.Optical Gyroscopes -- 4.2.2.Vibratory Gyroscopes -- 4.3.Inertial Measurement Units -- 4.4.Error Characteristics -- 4.4.1.Biases -- 4.4.2.Scale Factor and Cross-Coupling Errors -- 4.4.3.Random Noise -- 4.4.4.Further Error Sources -- 4.4.5.Vibration-Induced Errors -- 4.4.6.Error Models -- References -- ch. 5 Inertial Navigation -- 5.1.Introduction to Inertial Navigation -- 5.2.Inertial-Frame Navigation Equations -- 5.2.1.Attitude Update -- 5.2.2.Specific-Force Frame Transformation -- 5.2.3.Velocity Update -- 5.2.4.Position Update -- 5.3.Earth-Frame Navigation Equations -- 5.3.1.Attitude Update -- 5.3.2.Specific-Force Frame Transformation -- 5.3.3.Velocity Update -- 5.3.4.Position Update -- 5.4.Local-Navigation-Frame Navigation Equations -- 5.4.1.Attitude Update -- 5.4.2.Specific-Force Frame Transformation -- 5.4.3.Velocity Update -- 5.4.4.Position Update -- 5.4.5.Wander-Azimuth Implementation -- 5.5.Navigation Equations Optimization -- 5.5.1.Precision Attitude Update -- 5.5.2.Precision Specific-Force Frame Transformation -- 5.5.3.Precision Velocity and Position Updates -- 5.5.4.Effects of Sensor Sampling Interval and Vibration -- 5.5.5.Design Tradeoffs -- 5.6.Initialization and Alignment -- 5.6.1.Position and Velocity Initialization -- 5.6.2.Attitude Initialization -- 5.6.3.Fine Alignment -- 5.7.INS Error Propagation -- 5.7.1.Short-Term Straight-Line Error Propagation -- 5.7.2.Medium- and Long-Term Error Propagation -- 5.7.3.Maneuver-Dependent Errors -- 5.8.Indexed IMU -- 5.9.Partial IMU -- References -- ch. 6 Dead Reckoning, Attitude, and Height Measurement -- 6.1.Attitude Measurement -- 6.1.1.Magnetic Heading -- 6.1.2.Marine Gyrocompass -- 6.1.3.Strapdown Yaw-Axis Gyro -- 6.1.4.Heading from Trajectory -- 6.1.5.Integrated Heading Determination -- 6.1.6.Accelerometer Leveling and Tilt Sensors -- 6.1.7.Horizon Sensing -- 6.1.8.Attitude and Heading Reference System -- 6.2.Height and Depth Measurement -- 6.2.1.Barometric Altimeter -- 6.2.2.Depth Pressure Sensor -- 6.2.3.Radar Altimeter -- 6.3.Odometry -- 6.3.1.Linear Odometry -- 6.3.2.Differential Odometry -- 6.3.3.Integrated Odometry and Partial IMU -- 6.4.Pedestrian Dead Reckoning Using Step Detection -- 6.5.Doppler Radar and Sonar -- 6.6.Other Dead-Reckoning Techniques -- 6.6.1.Correlation-Based Velocity Measurement -- 6.6.2.Air Data -- 6.6.3.Ship's Speed Log -- References -- ch. 7 Principles of Radio Positioning -- 7.1.Radio Positioning Configurations and Methods -- 7.1.1.Self-Positioning and Remote Positioning -- 7.1.2.Relative Positioning -- 7.1.3.Proximity -- 7.1.4.Ranging -- 7.1.5.Angular Positioning -- 7.1.6.Pattern Matching -- 7.1.7.Doppler Positioning -- 7.2.Positioning Signals -- 7.2.1.Modulation Types -- 7.2.2.Radio Spectrum -- 7.3.User Equipment -- 7.3.1.Architecture -- 7.3.2.Signal Timing Measurement -- 7.3.3.Position Determination from Ranging -- 7.4.Propagation, Error Sources, and Positioning Accuracy -- 7.4.1.Ionosphere, Troposphere, and Surface Propagation Effects -- 7.4.2.Attenuation, Reflection, Multipath, and Diffraction -- 7.4.3.Resolution, Noise, and Tracking Errors -- 7.4.4.Transmitter Location and Timing Errors -- 7.4.5.Effect of Signal Geometry -- References -- ch. 8 GNSS: Fundamentals, Signals, and Satellites -- 8.1.Fundamentals of Satellite Navigation -- 8.1.1.GNSS Architecture -- 8.1.2.Signals and Range Measurement -- 8.1.3.Positioning -- 8.1.4.Error Sources and Performance Limitations -- 8.2.The Systems -- 8.2.1.Global Positioning System -- 8.2.2.GLONASS -- 8.2.3.Galileo -- 8.2.4.Beidou -- 8.2.5.Regional Systems -- 8.2.6.Augmentation Systems -- 8.2.7.System Compatibility -- 8.3.GNSS Signals -- 8.3.1.Signal Types -- 8.3.2.Global Positioning System -- 8.3.3.GLONASS -- 8.3.4.Galileo -- 8.3.5.Beidou -- 8.3.6.Regional Systems -- 8.3.7.Augmentation Systems -- 8.4.Navigation Data Messages -- 8.4.1.GPS -- 8.4.2.GLONASS -- 8.4.3.Galileo -- 8.4.4.SBAS -- 8.4.5.Time Base Synchronization -- 8.5.Satellite Orbits and Geometry -- 8.5.1.Satellite Orbits -- 8.5.2.Satellite Position and Velocity -- 8.5.3.Range, Range Rate, and Line of Sight -- 8.5.4.Elevation and Azimuth -- References -- ch. 9 GNSS: User Equipment Processing and Errors -- 9.1.Receiver Hardware and Antenna -- 9.1.1.Antennas -- 9.1.2.Reference Oscillator -- 9.1.3.Receiver Front End -- 9.1.4.Baseband Signal Processor -- 9.2.Ranging Processor -- 9.2.1.Acquisition -- 9.2.2.Code Tracking -- 9.2.3.Carrier Tracking -- 9.2.4.Tracking Lock Detection -- 9.2.5.Navigation-Message Demodulation -- 9.2.6.Carrier-Power-to-Noise-Density Measurement -- 9.2.7.Pseudo-Range, Pseudo-Range-Rate, and Carrier-Phase Measurements -- 9.3.Range Error Sources -- 9.3.1.Ephemeris Prediction and Satellite Clock Errors -- 9.3.2.Ionosphere and Troposphere Propagation Errors -- 9.3.3.Tracking Errors -- 9.3.4.Multipath, Nonline-of-Sight, and Diffraction -- 9.4.Navigation Processor -- 9.4.1.Single-Epoch Navigation Solution -- 9.4.2.Filtered Navigation Solution -- 9.4.3.Signal Geometry and Navigation Solution Accuracy -- 9.4.4.Position Error Budget -- References -- ch.…”
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Intelligent surfaces in biotechnology scientific and engineering concepts, enabling technologies, and translation to bio-oriented applications /

Table of Contents: “…Design of intelligent surface modifications and optimal liquid handling for nanoscale bioanalytical sensors Laurent Feuz, Fredrik Höök and Erik Reimhult 3.1 Introduction 3.2 Orthogonal small (nano) scale surface modification using molecular self-assembly 3.3 Alternative surface patterning strategies 3.4 The challenge of analytic transport 3.5 Concluding remarks Chapter 4. …”
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Intelligent surfaces in biotechnology scientific and engineering concepts, enabling technologies, and translation to bio-oriented applications /

Table of Contents: “…Design of intelligent surface modifications and optimal liquid handling for nanoscale bioanalytical sensors Laurent Feuz, Fredrik Höök and Erik Reimhult 3.1 Introduction 3.2 Orthogonal small (nano) scale surface modification using molecular self-assembly 3.3 Alternative surface patterning strategies 3.4 The challenge of analytic transport 3.5 Concluding remarks Chapter 4. …”
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Statistical monitoring of complex multivariate processes with applications in industrial process control / by Krüger, Uwe, Dr

Table of Contents: “…Machine generated contents note: Preface Introduction I Fundamentals of Multivariate Statistical Process Control 1 Motivation for Multivariate Statistical Process Control 1.1 Summary of Statistical Process Control 1.1.1 Roots and Evolution of Statistical Process Control 1.1.2 Principles of Statistical Process Control 1.1.3 Hypothesis Testing, Type I and II errors 1.2 Why Multivariate Statistical Process Control 1.2.1 Statistically Uncorrelated Variables 1.2.2 Perfectly Correlated Variables 1.2.3 Highly Correlated Variables 1.2.4 Type I and II Errors and Dimension Reduction 1.3 Tutorial Session 2 Multivariate Data Modeling Methods 2.1 Principal Component Analysis 2.1.1 Assumptions for Underlying Data Structure 2.1.2 Geometric Analysis of Data Structure 2.1.3 A Simulation Example 2.2 Partial Least Squares 2.2.1 Assumptions for Underlying Data Structure 2.2.2 Deflation Procedure for Estimating Data Models 2.2.3 A Simulation Example 2.3 Maximum Redundancy Partial Least Squares 2.3.1 Assumptions for Underlying Data Structure 2.3.2 Source Signal Estimation 2.3.3 Geometric Analysis of Data Structure 2.3.4 A Simulation Example 2.4 Estimating the Number of Source Signals 2.4.1 Stopping Rules for PCA Models 2.4.2 Stopping Rules for PLS Models 2.5 Tutorial Session 3 Process Monitoring Charts 3.1 Fault Detection 3.1.1 Scatter Diagrams 3.1.2 Nonnegative Quadratic Monitoring Statistics 3.2 Fault Isolation and Identification 3.2.1 Contribution Charts 3.2.2 Residual-Based Tests 3.2.3 Variable Reconstruction 3.3 Geometry of Variable Projections 3.3.1 Linear Dependency of Projection Residuals 3.3.2 Geometric Analysis of Variable Reconstruction 3.4 Tutorial Session II Application Studies 4 Application to a Chemical Reaction Process 4.1 Process Description 4.2 Identification of a Monitoring Model 4.3 Diagnosis of a Fault Condition 5 Application to a Distillation Process 5.1 Process Description 5.2 Identification of a Monitoring Model 5.3 Diagnosis of a Fault Condition III Advances in Multivariate Statistical Process Control 6 Further Modeling Issues 6.1 Accuracy of Estimating PCA Models 6.1.1 Revisiting the Eigendecomposition of Sz0z0 6.1.2 Two Illustrative Examples 6.1.3 Maximum Likelihood PCA for Known Sgg 6.1.4 Maximum Likelihood PCA for Unknown Sgg 6.1.5 A Simulation Example 6.1.6 A Stopping Rule for Maximum Likelihood PCA Models 6.1.7 Properties of Model and Residual Subspace Estimates 6.1.8 Application to a Chemical Reaction Process - Revisited 6.2 Accuracy of Estimating PLS Models 6.2.1 Bias and Variance of Parameter Estimation 6.2.2 Comparing Accuracy of PLS and OLS Regression Models 6.2.3 Impact of Error-in-Variables Structure upon PLS Models 6.2.4 Error-in-Variable Estimate for Known See 6.2.5 Error-in-Variable Estimate for Unknown See 6.2.6 Application to a Distillation Process - Revisited 6.3 Robust Model Estimation 6.3.1 Robust Parameter Estimation 6.3.2 Trimming Approaches 6.4 Small Sample Sets 6.5 Tutorial Session 7 Monitoring Multivariate Time-Varying Processes 7.1 Problem Analysis 7.2 Recursive Principal Component Analysis 7.3 MovingWindow Principal Component Analysis 7.3.1 Adapting the Data Correlation Matrix 7.3.2 Adapting the Eigendecomposition 7.3.3 Computational Analysis of the Adaptation Procedure 7.3.4 Adaptation of Control Limits 7.3.5 Process Monitoring using an Application Delay 7.3.6 MinimumWindow Length 7.4 A Simulation Example 7.4.1 Data Generation 7.4.2 Application of PCA 7.4.3 Utilizing MWPCA based on an Application Delay 7.5 Application to a Fluid Catalytic Cracking Unit 7.5.1 Process Description 7.5.2 Data Generation 7.5.3 Pre-analysis of Simulated Data 7.5.4 Application of PCA 7.5.5 Application of MWPCA 7.6 Application to a Furnace Process 7.6.1 Process Description 7.6.2 Description of Sensor Bias 7.6.3 Application of PCA 7.6.4 Utilizing MWPCA based on an Application Delay 7.7 Adaptive Partial Least Squares 7.7.1 Recursive Adaptation of Sx0x0 and Sx0y0 7.7.2 MovingWindow Adaptation of Sv0v0 and Sv0y0 7.7.3 Adapting The Number of Source Signals 7.7.4 Adaptation of the PLS Model 7.8 Tutorial Session 8 Monitoring Changes in Covariance Structure 8.1 Problem Analysis 8.1.1 First Intuitive Example 8.1.2 Generic Statistical Analysis 8.1.3 Second Intuitive Example 8.2 Preliminary Discussion of Related Techniques 8.3 Definition of Primary and Improved Residuals 8.3.1 Primary Residuals for Eigenvectors 8.3.2 Primary Residuals for Eigenvalues 8.3.3 Comparing both Types of Primary Residuals 8.3.4 Statistical Properties of Primary Residuals 8.3.5 Improved Residuals for Eigenvalues 8.4 Revisiting the Simulation Examples in Section 8.1 8.4.1 First Simulation Example 8.4.2 Second Simulation Example 8.5 Fault Isolation and Identification 8.5.1 Diagnosis of Step-Type Fault Conditions 8.5.2 Diagnosis of General Deterministic Fault Conditions 8.5.3 A Simulation Example 8.6 Application Study to a Gearbox System 8.6.1 Process Description 8.6.2 Fault Description 8.6.3 Identification of a Monitoring Model 8.6.4 Detecting a Fault Condition 8.7 Analysis of Primary and Improved Residuals 8.7.1 Central Limit Theorem 8.7.2 Further Statistical Properties of Primary Residuals 8.7.3 Sensitivity of Statistics based on Improved Residuals 8.8 Tutorial Session IV Description of Modeling Methods 9 Principal Component Analysis 9.1 The Core Algorithm 9.2 Summary of the PCA Algorithm 9.3 Properties of a PCA Model 10 Partial Least Squares 10.1 Preliminaries 10.2 The Core Algorithm 10.3 Summary of the PLS Algorithm10.4 Properties of PLS 10.5 Properties of Maximum Redundancy PLS References Index.…”
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Statistical monitoring of complex multivariate processes with applications in industrial process control / by Krüger, Uwe, Dr

Table of Contents: “…Machine generated contents note: Preface Introduction I Fundamentals of Multivariate Statistical Process Control 1 Motivation for Multivariate Statistical Process Control 1.1 Summary of Statistical Process Control 1.1.1 Roots and Evolution of Statistical Process Control 1.1.2 Principles of Statistical Process Control 1.1.3 Hypothesis Testing, Type I and II errors 1.2 Why Multivariate Statistical Process Control 1.2.1 Statistically Uncorrelated Variables 1.2.2 Perfectly Correlated Variables 1.2.3 Highly Correlated Variables 1.2.4 Type I and II Errors and Dimension Reduction 1.3 Tutorial Session 2 Multivariate Data Modeling Methods 2.1 Principal Component Analysis 2.1.1 Assumptions for Underlying Data Structure 2.1.2 Geometric Analysis of Data Structure 2.1.3 A Simulation Example 2.2 Partial Least Squares 2.2.1 Assumptions for Underlying Data Structure 2.2.2 Deflation Procedure for Estimating Data Models 2.2.3 A Simulation Example 2.3 Maximum Redundancy Partial Least Squares 2.3.1 Assumptions for Underlying Data Structure 2.3.2 Source Signal Estimation 2.3.3 Geometric Analysis of Data Structure 2.3.4 A Simulation Example 2.4 Estimating the Number of Source Signals 2.4.1 Stopping Rules for PCA Models 2.4.2 Stopping Rules for PLS Models 2.5 Tutorial Session 3 Process Monitoring Charts 3.1 Fault Detection 3.1.1 Scatter Diagrams 3.1.2 Nonnegative Quadratic Monitoring Statistics 3.2 Fault Isolation and Identification 3.2.1 Contribution Charts 3.2.2 Residual-Based Tests 3.2.3 Variable Reconstruction 3.3 Geometry of Variable Projections 3.3.1 Linear Dependency of Projection Residuals 3.3.2 Geometric Analysis of Variable Reconstruction 3.4 Tutorial Session II Application Studies 4 Application to a Chemical Reaction Process 4.1 Process Description 4.2 Identification of a Monitoring Model 4.3 Diagnosis of a Fault Condition 5 Application to a Distillation Process 5.1 Process Description 5.2 Identification of a Monitoring Model 5.3 Diagnosis of a Fault Condition III Advances in Multivariate Statistical Process Control 6 Further Modeling Issues 6.1 Accuracy of Estimating PCA Models 6.1.1 Revisiting the Eigendecomposition of Sz0z0 6.1.2 Two Illustrative Examples 6.1.3 Maximum Likelihood PCA for Known Sgg 6.1.4 Maximum Likelihood PCA for Unknown Sgg 6.1.5 A Simulation Example 6.1.6 A Stopping Rule for Maximum Likelihood PCA Models 6.1.7 Properties of Model and Residual Subspace Estimates 6.1.8 Application to a Chemical Reaction Process - Revisited 6.2 Accuracy of Estimating PLS Models 6.2.1 Bias and Variance of Parameter Estimation 6.2.2 Comparing Accuracy of PLS and OLS Regression Models 6.2.3 Impact of Error-in-Variables Structure upon PLS Models 6.2.4 Error-in-Variable Estimate for Known See 6.2.5 Error-in-Variable Estimate for Unknown See 6.2.6 Application to a Distillation Process - Revisited 6.3 Robust Model Estimation 6.3.1 Robust Parameter Estimation 6.3.2 Trimming Approaches 6.4 Small Sample Sets 6.5 Tutorial Session 7 Monitoring Multivariate Time-Varying Processes 7.1 Problem Analysis 7.2 Recursive Principal Component Analysis 7.3 MovingWindow Principal Component Analysis 7.3.1 Adapting the Data Correlation Matrix 7.3.2 Adapting the Eigendecomposition 7.3.3 Computational Analysis of the Adaptation Procedure 7.3.4 Adaptation of Control Limits 7.3.5 Process Monitoring using an Application Delay 7.3.6 MinimumWindow Length 7.4 A Simulation Example 7.4.1 Data Generation 7.4.2 Application of PCA 7.4.3 Utilizing MWPCA based on an Application Delay 7.5 Application to a Fluid Catalytic Cracking Unit 7.5.1 Process Description 7.5.2 Data Generation 7.5.3 Pre-analysis of Simulated Data 7.5.4 Application of PCA 7.5.5 Application of MWPCA 7.6 Application to a Furnace Process 7.6.1 Process Description 7.6.2 Description of Sensor Bias 7.6.3 Application of PCA 7.6.4 Utilizing MWPCA based on an Application Delay 7.7 Adaptive Partial Least Squares 7.7.1 Recursive Adaptation of Sx0x0 and Sx0y0 7.7.2 MovingWindow Adaptation of Sv0v0 and Sv0y0 7.7.3 Adapting The Number of Source Signals 7.7.4 Adaptation of the PLS Model 7.8 Tutorial Session 8 Monitoring Changes in Covariance Structure 8.1 Problem Analysis 8.1.1 First Intuitive Example 8.1.2 Generic Statistical Analysis 8.1.3 Second Intuitive Example 8.2 Preliminary Discussion of Related Techniques 8.3 Definition of Primary and Improved Residuals 8.3.1 Primary Residuals for Eigenvectors 8.3.2 Primary Residuals for Eigenvalues 8.3.3 Comparing both Types of Primary Residuals 8.3.4 Statistical Properties of Primary Residuals 8.3.5 Improved Residuals for Eigenvalues 8.4 Revisiting the Simulation Examples in Section 8.1 8.4.1 First Simulation Example 8.4.2 Second Simulation Example 8.5 Fault Isolation and Identification 8.5.1 Diagnosis of Step-Type Fault Conditions 8.5.2 Diagnosis of General Deterministic Fault Conditions 8.5.3 A Simulation Example 8.6 Application Study to a Gearbox System 8.6.1 Process Description 8.6.2 Fault Description 8.6.3 Identification of a Monitoring Model 8.6.4 Detecting a Fault Condition 8.7 Analysis of Primary and Improved Residuals 8.7.1 Central Limit Theorem 8.7.2 Further Statistical Properties of Primary Residuals 8.7.3 Sensitivity of Statistics based on Improved Residuals 8.8 Tutorial Session IV Description of Modeling Methods 9 Principal Component Analysis 9.1 The Core Algorithm 9.2 Summary of the PCA Algorithm 9.3 Properties of a PCA Model 10 Partial Least Squares 10.1 Preliminaries 10.2 The Core Algorithm 10.3 Summary of the PLS Algorithm10.4 Properties of PLS 10.5 Properties of Maximum Redundancy PLS References Index.…”
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