Contents
Contributors
Preface

Chapter 1. Surface Plasmon Resonance Sensors: Fundamental Concepts, Selected Techniques, Materials and Applications

1.1. Introduction
1.2. Maxwell’s Equations at Metal/Dielectric Interface: A Tutorial
1.3. Sensor Development
1.4. Simulations
1.4.1. Fresnel’s Equations and MATLAB
1.4.2. The Noble Metal Thin Film Sensor
1.4.3. Bimetallic (Ag/Au) Sensors
1.4.4. Waveguide-Coupled Ag/Si3N4/Au Structures:
1.4.5. Electric Field Simulations
1.4.5.1. Evanescent Fields for Single-Metal Sensors
1.4.5.2. Evanescent Fields for Bimetallic Sensors
1.4.5.3. Evanescent Fields for Waveguide Coupled Sensors
1.4.5.4. Comparison of Evanescent Electric Fields for Single Metal, Bimetal, and Waveguide-Coupled Multilayer Structure Sensors
1.5. Experimental
1.5.1. Sensor Structures
1.5.2. Measurement Techniques
1.5.2.1. The Kretschmann-Otto (, 2 ) Goniometer Optical System with Prism Coupling
1.5.2.2. The Kretschmann Optical System without Goniometer (A Fixed Detector System)
1.5.2.3. Grating Coupling
1.6. Comparison between Simulations and Measurements
1.7. Selected SPR Sensor Platforms
1.7.1. Sensor for Liquid-Crystal Alignment and Periodic Structure on Surfaces
1.7.2. Sensor for Surface Defects
1.7.3. Sensor for Coupling between SPPs and Quantum Dot Emitters
1.7.4. SPR Sensors for Biotechnology Applications
1.8. Conclusions
Acknowledgments
References

Chapter 2. Diamond Detectors with Graphite Contacts

2.1. Introduction
2.2. Localized Phase Transformation of Diamond
2.2.1. Thermal Modification
2.2.2. Ion-Beam Processing
2.2.3. Laser Induced Surface and Bulk Transformation
2.2.3.1. Two-Dimensional Detectors with Laser Induced Graphite Electrodes
2.2.3.2. Three-Dimensional Detectors with Laser Induced Bulk-Graphite Pillars

2.3. Concluding Remarks
Acknowledgements
References

Chapter 3. Interferometric Photonic Crystal Fiber-Optic Gyroscope

3.1. Introduction
3.1.1. Solid-Core Photonic Crystal Fiber Optical Gyroscope (SC-PCFOG)
3.1.2. Hollow-Core Photonic Crystal Fiber Optical Gyroscope (HC-PCFOG)
3.2. Photonic Crystal Fiber and Components
3.2.1. Photonic Crystal Fiber for FOG Application
3.2.2. Photonic Crystal Fiber Coupler
3.3. Nonreciprocity Error and Noise in PCFOG
3.3.1. Backward Secondary-Wave Coherence (BSC) Error
3.3.1.1. BSC Error Principle
3.3.1.2. Measurement of BSC Error
3.3.1.3. Suppression of BSC Error
3.3.2. Reflection-Induced Noise
3.4. Prototypes of PCFOG
3.5. Conclusions
Acknowledgements
References

Chapter 4. Designs of Capacitance Sensor for Holdup Measurement in Two-phase Flow: A Finite Element Analysis

4.1. Introduction
4.2. Designs of the Capacitance Sensor
4.2.1. Concave Configuration
4.2.2. Helical Configuration
4.2.3. Ring Configuration
4.3. Methods
4.3.1. Modelling of Two-Phase Flow
4.3.2. Evaluation Criteria of the Capacitance Sensor
4.3.2.1. Sensitivity
4.3.2.2. Linearity of Response
4.3.2.3. Dependent Level of Phase Distribution
4.3.3. Setup Parameters of Two-Phase Flow
4.4. Results and Discussion
4.4.1. Analysis of Concave Configuration
4.4.2. Analysis of Helical Configuration
4.4.3. Analysis of Ring Configuration
4.4.4. Comparison between the Configurations
4.5. Conclusion
References

Chapter 5. An Overview of Sensors for Low-Milliliter Hydrodynamic Applications such as Hydrocephalus

5.1. Objective
5.2. A Brief History of Shunts
5.3. Introduction to Sensitive Sensors
5.4. Capacitive Sensors
5.5. Capacitor Details and Assembly
5.6. Experimental Apparatus and Its Variations
5.7. Double-Membrane Sensors
5.8. Single-Membrane Sensors
5.9. Angstrom-Sensitivity of the Sensors
5.10. Temperature Dependence
5.11. Conclusions
References

Chapter 6. Silicon Micro Piezoresistive Pressure Sensors

6.1. Summary
6.2. State of the Art Silicon Pressure Sensors
6.2.1. Piezoresistive Effect
6.2.2. Selected Manufacturing Technologies Silicon Pressure Sensors
6.2.2.1. Silicon Doping
6.2.2.2. MEMS Micromaching
6.2.3. Piezoresistive Silicon Pressure Sensors - State of the Art
6.2.3.1. Most Common Types of Piezoresistive Silicon Pressure Sensors
6.2.3.2. Signal Conditioning for Silicon Piezoresistive Pressure Sensors
6.2.4. Packaging for Silicon Piezoresistive Pressure Sensors
References

Chapter 7. Carbon Black/Polydimethylsiloxane Electrodes for Underwater Cardiac Electrical Activity Collection

7.1. Introduction
7.2. Materials and Methods
7.2.1. Fabrication of Copper Mesh CB/PDMS Electrodes
7.2.2. Characterizing the CB/PDMS Electrodes
7.2.2.1. Electrode-Skin Contact Impedance Measurements
7.2.2.2. Mechanical Properties of CB/PDMS Electrodes
7.2.2.3. Cytotoxicity Test of Copper Mesh CB/PDMS Electrodes
7.2.3. Performance Evaluation of ECG Measurements Underwater
7.2.3.1. Signal Processing
7.2.3.2. Copper mesh CB/PDMS vs. Other Dry Electrodes in Fresh, Chlorinated, and Salt Water
7.2.3.3. Performance in Long Term Underwater ECG Recordings
7.3. Results
7.3.1. Electrode-Skin Impedance Measurements. CB/PDMS vs. Other Dry Electrodes
7.3.2. Mechanical Properties after Aging in Aqueous Environments
7.3.3. Cytotoxicity Test
7.3.3.1. Copper Mesh CB/PDMS Electrodes
7.3.3.2. Cytotoxic Effect of Electrodes on L929 Cells
7.3.3.3. Cytotoxic Effect of Electrodes on NHEK Cells
7.3.4. Performance of CB/PDMS Electrodes Underwater
7.3.4.1. Copper Mesh CB/PDMS vs. Other Dry Electrodes in Fresh, Chlorinated, and Salt Water
7.3.4.2. Performance of CB/PDMS Electrodes in Long Term Underwater ECG Recordings
7.4. Discussion
7.5. Conclusions
References

Chapter 8. Lithium Batteries Monitoring with Fiber Bragg Gratings

8.1. Introduction
8.2. Theoretical Considerations
8.3. Sensors Fabrication
8.4. Li-Ion Polymer Battery Monitoring
8.5. Coin Cell Monitoring
8.6. Li-Ion Pouch Cells Monitoring with Integrated FBG Sensors
8.7. Final Remarks
Acknowledgements
References

Chapter 9. Optoelectronic Design of a 2045 m Coil, Closed Loop-Based, Depolarized IFOG with Square-Wave Bias and Sawtooth-Wave Feedback Optical Phase Modulations: Parametric Modeling, Simulation and Performance Test

9.1. Introduction
9.2. Electro-Optical System Configuration
9.3. Electronic Subsystem Configuration
9.4. Calculations and Estimations
9.5. Simulation Results
9.6. Conclusions
References

Chapter 10. Development and Performance Analysis of a New Magnetorheological Damper with Displacement Differential Self-Induced Capability

10.1. Introduction
10.2. Design Consideration and Self-Induced Performance Analysis
10.2.1. Structure Design and Principle Description
10.2.2. Analysis of the Self-Induced Performance
10.3. Simulation Analysis of the Proposed MR Damper
10.3.1. Magnetic Properties of MR Fluid and Steel Used in the Proposed MR Damper
10.3.2. Static Magnetic Field Simulations
10.3.3. Simulation of Harmonic Magnetic Field
10.4. Static Experimental Analysis of Self-Induced Performance
10.5. Dynamic Experimental Analysis of Self-Induced Performance
10.5.1. Test Rig of Dynamic Self-Induced Performance
10.5.2. Self-Induced Performance under Different Direct Current Inputs
10.5.3. Self-Induced Performance under Different Damper Displacements
10.5.4. Analysis of Dynamic Damping Performances
10.6. Conclusion
Acknowledgements
References

Chapter 11. Measurements of Vacuum in Microsystems

11.1. Vacuum MEMS
11.2. Vacuum Nanoelectronics Devices
11.3. A New Concept of a Miniature High Vacuum Instrument
11.4. MEMS Vacuum Pumps
11.5. MEMS Vacuum Sensors
11.5.1. Membrane Vacuum Sensors
11.5.2. Thermal-Conductive Vacuum Sensors
11.5.3. Resonant Vacuum Sensors
11.5.4. Ionization Vacuum Sensors
11.6. New MEMS Ionization Vacuum Sensor
11.6.1. Technology and Working Principle
11.6.2. Low Vacuum Measurements
11.6.3. Medium and High Vacuum Measurements
11.6.3.1. Calibration of the Sensor
11.6.3.2. Vacuum Sensor Properties with Different Dosed Gases
11.6.3.3. Measurements of Vacuum Sealed Device
11.7. Conclusions
Acknowledgements
References

Chapter 12. Gaussian Function Generator for a Perceptron ANN with FGMOS Transistors in an Integrated Circuit

12.1. Introduction
12.2. Development
12.2.1. USB 6009 Data Acquisition Device by NI
12.3. Tests Performed to the FGMOS Transistors of the Prototype
12.3.1. Charge Inside Floating Gate
12.3.2. Final Tests
12.4. Layout
12.5. Conclusions
Acknowledgements
References

Chapter 13. High-Resolution Thermal Imaging Based on the Fluorescence of Erbium/Ytterbium Co-Doped Ceramic

13.1. Introduction
13.2. Materials and Methods
13.2.1. The Fluorescent Material
13.2.2. Confocal Fluorescence Microscopy System
13.2.3. Experimental Procedure
13.2.4. Experimental Procedure
13.3. Results and Discussion
13.4. Conclusions
Acknowledgements
References

Chapter 14. Stopping of Transport Vehicles Using Electromagnetic Weapons

14.1. Introduction
14.1.1. Direct Energy Weapons
14.2. Electromagnetic Systems for Stopping Vehicles
14.2.1. HPEMcarStop
14.2.2. HPEMcheckPoint
14.2.3. RF System Safe Stop
14.2.4. HPEMS
14.2.5. EMWS Engine Stopper
14.2.6. Multi – Frequency Vehicle Stopper
14.2.7. SAVELEC
14.2.8. Electrical Vehicle Stopper
14.3. Electromagnetic Compatibility of Automotive Technology
14.3.1. Legislative Requirements
14.3.2. Regulation No. 10 of the Economic Commission for Europe of the United Nations
14.3.2.1. Electromagnetic Immunity
14.3.3. Technical Standards for Electromagnetic Compatibility of Vehicles
14.3.4. Technical Specifications of Vehicle Manufacturers
14.4. Conclusions
Acknowledgements
References

Chapter 15. A Multifunctional Tri-Colour Light Emitting Diode Based Spectrometric Detector for Virtual Instruments

15.1. Introduction
15.2. Detector Design
15.3. Virtual Instruments
15.3.1. A Flow-Analysis VI
15.3.2. A Microtitrator VI
15.3.3. Execution of the Microtitrator VI
15.4. Spectrometric Characteristics of the Detector for Discrete and Flow-Based Analytical Methods
15.5. Multifunctional Performance
15.5.1. A Spectrometric Microtitrator
15.5.2. A Microdiffusion Based Spectrometric Reactor for Volatile Species
15.5.3. A Spectrometric Detector with an Ascending Glass-Coil Cell for Flow or Sequential Injection Analysis
15.6. Conclusions
Acknowledgements
References

Chapter 16. GPS-Enabled Hybrid Sensor Network System for Emergency Monitoring of Environmental Radiation

16.1. Introduction
16.2. Related Works
16.2.1. Environmental Radiation Monitoring System
16.2.2. Environmental Radiation Emergency Monitoring
16.3. Wireless Nuclear Radiation Detection Node Design
16.4. Methods
16.4.1. Interactive Protocol Design
16.4.2. ZigBee Networking Scheme
16.4.3. Working Mode
16.4.4. Emergency Monitoring
16.4.5. System Control Software Design
16.5. System Implementation
16.6. Conclusions
Acknowledgements
References

Chapter 17. Power Control-Based Routing in Wireless Sensor Networks: An Overview

17.1. Introduction
17.1.1. An Overview of Wireless Sensor Networks
17.1.2. The Architecture of Wireless Sensor Networks
17.1.3. Design Challenges of Wireless Sensor Networks
17.1.4. Applications of Wireless Sensor Networks
17.2. Introduction of Routing Protocols in Wireless Sensor Networks
17.2.1. Some Terms Related to Routing Evaluation
17.2.2. Traffic Patterns in Wireless Sensor Networks
17.2.3. Classification of Routing Protocols in Wireless Sensor Networks
17.2.4. Challenges of Routing Design in Wireless Sensor Networks
17.3. Introduction of Power Control-Based Routing in Wireless Sensor Networks
17.3.1. Overview of Power Control in Wireless Sensor Networks
17.3.2. Representative Power Control-Based Routing Protocols in Wireless Sensor Networks
17.3.2.1. ASTRL
17.3.2.2. UMM
17.3.2.3. ODTS
17.3.2.4. MMBEC
17.3.2.5. RTHS
17.3.2.6. ETP
17.3.2.7. ETP/DTP
17.3.2.8. RORRT
17.3.3. Comparison of Power Control-Based Routing Protocols in Wireless Sensor Networks
17.4. Future Directions
Acknowledgements
References

Chapter 18. Study of the FGM Application Peculiarities on Mobile Carriers

18.1. Introduction
18.2. Reduction of the Moving Magnetometer Axes Direction to the Reference Magnetometer Axes
18.3. Flux-Gate Magnetometer Design for Mobile Carrier
18.4. Drone-Mounted FGM Flight Experiment
18.4.1. LEMI-026 Magnetometer Dynamic Parameters Analysis in Flight
18.4.2. Example of Localization of a Small Ferromagnetic Anomaly
18.5. Evaluation of the Possibility of Obtaining Data about the Anomalous Magnetic Field Components Using an Inclinometer
18.6. Conclusion
References

Chapter 19. Review of Environmental Detection Based on Microwave Technologies of Resonators, Transmission Lines, Radiometers and Radars Sensors

19.1. Introduction
19.2. Classification of Each Type of Microwave Sensor and Operating Principle
19.2.1. Transmission Sensors
19.2.1.1. Description
19.2.1.2. Operating Principle
19.2.1.3. Environmental Sensing Application
19.2.2. Resonator Sensors
19.2.2.1. Description
19.2.2.2. Operating Principle
19.2.2.3. Environmental Sensing Application
19.2.3. Radiometer Sensors
19.2.3.1. Description
19.2.3.2. Operating Principle
19.2.3.3. Environmental Sensing Application
19.2.4. Radar Sensors
19.2.4.1. Description
19.2.4.2. Operating Principle
19.2.4.3. Environmental Sensing Application
19.3. Future Directions and Challenges
19.4. Conclusion
References

Chapter 20. Developments in Compact HF-Radar Ocean Wave Measurement

20.1. Introduction
20.2. Radar Spectral Theory
20.2.1. Narrow-Beam Radar Cross Section
20.2.2. Broad-Beam Radar Cross Spectra
20.2.3. The Effects of Varying Ocean Surface Currents
20.3. Using Measured Antenna Patterns in Wave Extraction
20.4. Interpretation of the Radar Doppler Spectrum Using the Pierson/Moskowitz Ocean Wave Model
20.4.1. Definition of the Ocean Wave Spectral Model
20.4.2. Steps in the Analysis Procedure
20.5. Results
20.5.1. Bodega Marine Lab., California
20.5.2. New Jersey, USA
20.5.2.1. Effects of Wind Turning Offshore
20.5.2.2. Wave-height and Wind-Direction Observations that Reflect the Passage of a Front
20.5.2.3. Examples of Measured Wave Results 482
20.6. Interpretation of the Radar Doppler Spectrum Using a Bimodal Ocean Wave Model
20.7. Conclusion
Acknowledgments
References
Appendix

Chapter 21. Physical Deterministic Sea Surface Temperature Retrieval Suite for Satellite Infrared Measurement

21.1. Introduction
21.2. Physical Deterministic Retrieval Method
21.2.1. Least Squares (LS) Method
21.2.2. Modified Total Least Squares (MTLS)
21.2.3. Truncated Total Least Squares (TTLS)
21.3. Data and Methods
21.4. Channels Selection Using EXF
21.5. Sensitivity of MTLS and TTLS
21.6. Cloud Detection for IR SST
21.7. Limitations of Operational Cloud Algorithm
21.8. Cloud and Error Mask (CEM) Algorithm
21.9. Validation
21.10. Time Series Analysis
21.11. Conclusions 526
Acknowledgments
References

Chapter 22. Pasture Monitoring Using SAR Satellite Image with COSMO-SkyMed, ENVISAT ASAR and ALOS PALSAR in Otway, Victoria, Australia

22.1. Introduction
22.1.1. Study Site and Data
22.1.2. SAR Image Pre-Processing to Get Backscattering Coefficient (dB)
22.1.3. Calculation of NDVI, NDWI
22.1.4. Soil Moisture Index (M.I) Estimated from Climate Data
22.1.5. Classification of Study Area Using Decision Tree Method
22.1.6. Statistical Analysis
22.2. Results
22.2.1. Classification
22.2.2. COSMO-SkyMed Results
22.2.3. ENVISAT ASAR Results
22.2.3.1. Temporal Analysis of ENVISAT ASAR HH Backscattering Coefficient against MODIS NDVI, NDWI and Soil Moisture Index (M.I)
22.2.3.2. Spatial Analysis of ENVISAT ASAR HH dB against Landsat 5 TM NDVI and NDWI
22.2.4. ALOS PALSAR Results
22.2.4.1. Temporal Analysis of ALOS PALSAR HH dB against MODIS NDVI, NDWI, and Soil Moisture Index (M.I)
22.2.4.2. Spatial Analysis of ALOS PALSAR HH dB against Landsat 5 TM NDVI and NDWI
22.3. Discussions
22.4. Conclusions
References

Index