SUSTAINABLE TECHNOLOGIES FOR ENERGY EFFICIENT BUILDINGS

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Smart and power grid systems design challenges and paradigms

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Integration of Heterogeneous Manufacturing Machinery in Cells and Systems : Policies and Practices.

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Verb classes and aspect

Table of Contents: “…Conclusions -- References -- Appendix -- 14. Romance object-experiencer verbs: From aktionsart to activity hierarchy -- 1. …”
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Spectrum sharing in cognitive radio networks : towards highly connected environments by Thakur, Prabhat, Singh, Ghanshyam

Table of Contents: “…Preface xiii -- Special Acknowledgements xxi -- List of Acronyms xxiii -- List of Figures xxvii -- List of Tables xxxiii -- List of Symbols xxxv -- 1 Introduction 1 -- 1.1 Introduction 1 -- 1.1.1 Connected Environments 2 -- 1.1.2 Evolution of Wireless Communication 5 -- 1.1.3 Third Generation Partnership Project 10 -- 1.2 Cognitive Radio Technology 10 -- 1.2.1 Spectrum Accessing/Sharing Techniques 13 -- 1.2.1.1 Interweave Spectrum Access 14 -- 1.2.1.2 Underlay Spectrum Access 17 -- 1.2.1.3 Overlay Spectrum Access 17 -- 1.2.1.4 Hybrid Spectrum Access 17 -- 1.3 Implementation of CR Networks 20 -- 1.4 Motivation 22 -- 1.5 Organization of Book 23 -- 1.6 Summary 27 -- References 27 -- 2 Advanced Frame Structures in Cognitive Radio Networks 39 -- 2.1 Introduction 39 -- 2.2 Related Work 40 -- 2.2.1 Frame Structures 40 -- 2.2.2 Spectrum Accessing Strategies 41 -- 2.3 Proposed Frame Structures for HSA Technique 43 -- 2.4 Analysis of Throughput and Data Loss 45 -- 2.5 Simulations and Results 47 -- 2.6 Summary 50 -- References 51 -- 3 Cognitive Radio Network with Spectrum Prediction and Monitoring -- Techniques 55 -- 3.1 Introduction 55 -- 3.2 Related Work 57 -- 3.2.1 Spectrum Prediction 57 -- 3.2.2 Spectrum Monitoring 58 -- 3.3 System Models 59 -- 3.3.1 System Model for Approach-1 59 -- 3.3.2 System Model for Approach-2 60 -- 3.4 Performance Analysis 61 -- 3.4.1 Throughput Analysis Using Approach-1 61 -- 3.4.2 Analysis of Performance Metrics of the Approach-2 65 -- 3.5 Results and Discussion 67 -- 3.5.1 Proposed Approach-1 67 -- 3.5.2 Proposed Approach-2 69 -- 3.6 Summary 72 -- References 72 -- 4 Effect of Spectrum Prediction in Cognitive Radio Networks 77 -- 4.1 Introduction 77 -- 4.1.1 Spectrum Access Techniques 78 -- 4.2 System Model 80 -- 4.3 Throughput Analysis 87 -- 4.4 Simulation Results and Discussion 89 -- 4.5 Summary 93 -- References 94 -- 5 Effect of Imperfect Spectrum Monitoring on Cognitive Radio -- Networks 97 -- 5.1 Introduction 97 -- 5.2 Related Work 99 -- 5.2.1 Spectrum Sensing 99 -- 5.2.2 Spectrum Monitoring 100 -- 5.3 System Model 101 -- 5.4 Performance Analysis of Proposed System Using Imperfect Spectrum -- Monitoring 102 -- 5.4.1 Computation of Ratio of the Achieved Throughput to Data Loss 108 -- 5.4.2 Computation of Power Wastage 108 -- 5.4.3 Computation of Interference Efficiency 109 -- 5.4.4 Computation of Energy Efficiency 109 -- 5.5 Results and Discussion 110 -- 5.6 Summary 115 -- References 116 -- 6 Cooperative Spectrum Monitoring in Homogeneous and -- Heterogeneous Cognitive Radio Networks 121 -- 6.1 Introduction 121 -- 6.2 Background 122 -- 6.3 System Model 124 -- 6.4 Performance Analysis of Proposed CRN 126 -- 6.4.1 Computation of Achieved Throughput and Data Loss 130 -- 6.4.2 Computation of Interference Efficiency 131 -- 6.4.3 Computation of Energy Efficiency 131 -- 6.5 Results and Discussion 132 -- 6.5.1 Homogeneous Cognitive Radio Network 132 -- 6.5.2 Heterogeneous Cognitive Radio Networks 134 -- 6.6 Summary 143 -- References 143 -- 7 Spectrum Mobility in Cognitive Radio Networks Using Spectrum -- Prediction and Monitoring Techniques 147 -- 7.1 Introduction 147 -- 7.2 System Model 151 -- 7.3 Performance Analysis 153 -- 7.4 Results and Discussion 156 -- 7.5 Summary 162 -- References 163 -- 8 Hybrid Self-Scheduled Multichannel Medium Access Control Protocol -- in Cognitive Radio Networks 167 -- 8.1 Introduction 167 -- 8.2 Related Work 169 -- 8.2.1 CR-MAC Protocols 169 -- 8.2.2 Interference at PU 171 -- 8.3 System Model and Proposed Hybrid Self-Scheduled Multichannel -- MAC Protocol 172 -- 8.3.1 System Model 172 -- 8.3.2 Proposed HSMC-MAC Protocol 173 -- 8.4 Performance Analysis 174 -- 8.4.1 With Perfect Spectrum Sensing 176 -- 8.4.2 With Imperfect Spectrum Sensing 178 -- 8.4.3 More Feasible Scenarios 180 -- 8.5 Simulations and Results Analysis 182 -- 8.5.1 With Perfect Spectrum Sensing 182 -- 8.5.2 With Imperfect Spectrum Sensing 185 -- 8.6 Summary 190 -- References 190 -- 9 Frameworks of Non-Orthogonal Multiple Access Techniques in -- Cognitive Radio Networks 195 -- 9.1 Introduction 195 -- 9.1.1 Related Work 196 -- 9.1.2 Motivation 199 -- 9.1.3 Organization 199 -- 9.2 CR Spectrum Accessing Strategies 199 -- 9.3 Functions of NOMA System for Uplink and Downlink Scenarios 204 -- 9.3.1 Downlink Scenario for Cellular-NOMA 204 -- 9.3.2 Uplink Scenario for Cellular-NOMA 207 -- 9.4 Proposed Frameworks of CR with NOMA 208 -- 9.4.1 Framework-1 209 -- 9.4.2 Framework-2 210 -- 9.5 Simulation Environment and Results 212 -- 9.6 Research Potentials for NOMA and CR-NOMA Implementations 213 -- 9.6.1 Imperfect CSI 214 -- 9.6.2 Spectrum Hand-off Management 215 -- 9.6.3 Standardization 215 -- 9.6.4 Less Complex and Cost-Effective Systems 215 -- 9.6.5 Energy-Efficient Design and Frameworks 216 -- 9.6.6 Quality-of-Experience Management 216 -- 9.6.7 Power Allocation Strategy for CUs to Implement NOMA Without -- Interfering PU 217 -- 9.6.8 Cooperative CR-NOMA 217 -- 9.6.9 Interference Cancellation Techniques 217 -- 9.6.10 Security Aspects in CR-NOMA 218 -- 9.6.11 Role of User Clustering and Challenges 218 -- 9.6.12 Wireless Power Transfer to NOMA 219 -- 9.6.13 Multicell NOMA with Coordinated Multipoint Transmission 220 -- 9.6.14 Multiple-Carrier NOMA 221 -- 9.6.15 Cross-Layer Design 221 -- 9.6.16 MIMO-NOMA-CR 222 -- 9.7 Summary 222 -- References 223 -- 10 Performance Analysis of MIMO-Based CR-NOMA Communication -- Systems 229 -- 10.1 Introduction 229 -- 10.2 Related Work for Several Combinations of CR, NOMA, and MIMO -- Systems 231 -- 10.3 System Model 234 -- 10.3.1 Downlink Scenarios 236 -- 10.3.2 Uplink Scenario 238 -- 10.4 Performance Analysis 238 -- 10.4.1 Downlink Scenario 238 -- 10.4.1.1 Throughput Computation for MIMO-CR-NOMA 239 -- 10.4.1.2 Throughput Computation for CR-NOMA Systems 240 -- 10.4.1.3 Sum Throughput for CR-OMA, CR-NOMA, CR-MIMO, and -- CR-NOMA-MIMO Frameworks 240 -- 10.4.2 Uplink Scenario 241 -- 10.4.2.1 Throughput Computation for MIMO-CR-NOMA 241 -- 10.4.2.2 Throughput Calculation for CR-NOMA Systems 242 -- 10.4.2.3 Sum Throughput for CR-OMA, CR-NOMA, CR-MIMO, and -- CR-NOMA-MIMO Frameworks 242 -- 10.4.2.4 Computation of Interference Efficiency of CU-4 In Case of -- CR-MIMO-NOMA 243 -- 10.5 Simulation and Results Analysis 243 -- 10.5.1 Simulation Results for Downlink Scenario 243 -- 10.5.2 Simulation Results for Uplink Scenario 245 -- 10.6 Summary 249 -- References 250 -- 11 Interference Management in Cognitive Radio Networks 255 -- 11.1 Introduction 255 -- 11.1.1 White space 257 -- 11.1.2 Grey Spaces 257 -- 11.1.3 Black Spaces 257 -- 11.1.4 Interference Temperature 257 -- 11.2 Interfering and Non-interfering CRN 258 -- 11.2.1 Interfering CRN 258 -- 11.2.2 Non-Interfering CRN 259 -- 11.3 Interference Cancellation Techniques in the CRN 261 -- 11.3.1 At the CU Transmitter 261 -- 11.3.2 At the CR-Receiver 264 -- 11.4 Cross-Layer Interference Mitigation in Cognitive Radio Networks 268 -- 11.5 Interference Management in Cognitive Radio Networks via Cognitive -- Cycle Constituents 269 -- 11.5.1 Spectrum Sensing 269 -- 11.5.2 Spectrum Prediction 269 -- 11.5.3 Transmission Below PUs' Interference Tolerable Limit 271 -- 11.5.4 Using Advanced Encoding Techniques 271 -- 11.5.5 Spectrum Monitoring 272 -- 11.6 Summary 274 -- References 274 -- 12 Simulation Frameworks and Potential Research Challenges for -- Internet-of-Vehicles Networks 281 -- 12.1 Introduction 281 -- 12.1.1 Consumer IoT 283 -- 12.1.2 Industrial IoT 283 -- 12.2 Applications of CIoT 284 -- 12.2.1 Smart Home and Automation 284 -- 12.2.2 Smart Wearables 284 -- 12.2.3 Home Security and Smart Domestics 285 -- 12.2.4 Smart Farming 285 -- 12.3 Applications of Industrial IoT 285 -- 12.3.1 Smart Industry 286 -- 12.3.2 Smart Grid/Utilities 286 -- 12.3.3 Smart Communication 286 -- 12.3.4 Smart City 287 -- 12.3.5 Smart Energy Management 287 -- 12.3.6 Smart Retail Management 288 -- 12.3.7 Robotics 288 -- 12.3.8 Smart Cars/Connected Vehicles 289 -- 12.4 Communication Frameworks for IoVs 289 -- 12.4.1 Vehicle-to-Vehicle (V2V) Communication 291 -- 12.4.2 Vehicle to Infrastructure (V2I) Communication 292 -- 12.4.3 Infrastructure to Vehicles (I2V) Communication 293 -- 12.4.4 Vehicle-to-Broadband (V2B) Communication 293 -- 12.4.5 Vehicle-to-Pedestrians (V2P) Communication 293 -- 12.5 Simulation Environments for Internet-of-Vehicles 295 -- 12.5.1 SUMO 296 -- 12.5.2 Network Simulator (NetSim) 296 -- 12.5.3 Ns-2 297 -- 12.5.4 Ns-3 297 -- 12.5.5 OMNeT++ 298 -- 12.6 Potential Research Challenges 299 -- 12.6.1 Social Challenges 299 -- 12.6.2 Technical Challenges 300 -- 12.7 Summary 302 -- References 302 -- 13 Radio Resource Management in Internet-of-Vehicles 311 -- 13.1 Introduction 311 -- 13.1.1 Dedicated Short-Range Communication 313 -- 13.1.2 Wireless Access for Vehicular Environments 314 -- 13.1.3 Communication Access for Land Mobile (CALM) 314 -- 13.2 Cellular Communication 315 -- 13.2.1 3GPP Releases 315 -- 13.2.2 Long-Term Evolution 317 -- 13.2.3 New Radio 317 -- 13.2.4 Dynamic Spectrum Access 318 -- 13.3 Role of Cognitive Radio for Spectrum Management 319 -- 13.4 Effect of Mobile Nature of Vehicles/Nodes on the Networking 320 -- 13.5 Spectrum Sharing in IoVs 322 -- 13.5.1 Spectrum Sensing Scenarios 322 -- 13.5.2 Spectrum Sharing Scenarios 324 -- 13.5.3 Spectrum Mobility/Handoff Scenarios 325 -- 13.6 Frameworks of Vehicular Networks with Cognitive Radio 326 -- 13.6.1 CR-Based IoVs Networks Architecture 327 -- 13.7 Key Potentials and Research Challenges 328 -- 13.7.1 Key Potentials 328 -- 13.7.2 Research Challenges 329 -- 13.8 Summary 333 -- References 333 -- Index 000.…”
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Handbook of spectroscopy

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Raspberry Pi 2 Server Essentials. by Kula, Piotr J.

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HTML5, JavaScript, and jQuery 24-hour trainer by Cameron, Dane

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Towards 5G : applications, requirements & candidate technologies

Table of Contents: “…List of Contributors xv -- List of Acronyms xix -- About the Companion Website xxxi -- Part I Overview of 5G 1 -- 1 Introduction 3 / Shilpa Talwar and Rath Vannithamby -- 1.1 Evolution of Cellular Systems through the Generations 3 -- 1.2 Moving Towards 5G 4 -- 1.3 5G Networks and Devices 5 -- 1.4 Outline of the Book 7 -- References 8 -- 2 5G Requirements 9 / Anass Benjebbour, Yoshihisa Kishiyama, and Takehiro Nakamura -- 2.1 Introduction 9 -- 2.2 Emerging Trends in Mobile Applications and Services 10 -- 2.3 General Requirements 15 -- References 21 -- 3 Collaborative 5G Research within the EU Framework of Funded Research 23 / Michael Faerber -- 3.1 Rationale for 5G Research and the EU's Motivation 23 -- 3.2 EU Research 25 -- References 33 -- 4 5G: Transforming the User Wireless Experience 34 / David Ott, Nageen Himayat, and Shilpa Talwar -- 4.1 Introduction 34 -- 4.2 Intel's Vision of 5G Technologies 34 -- 4.3 Intel Strategic Research Alliance on 5G 40 -- 4.4 ISRA 5G Technical Objectives and Goals 40 -- 4.5 ISRA 5G Project Summaries 42 -- References 50 -- Part II Candidate Technologies -- Evolutionary 53 -- 5 Towards Green and Soft 55 / Chih-Lin I and Shuangfeng Han -- 5.1 Chapter Overview 55 -- 5.2 Efforts on Green and Soft 5G Networks 56 -- 5.3 Rethink Shannon: EE and SE Co-design for a Green Network 57 -- 5.4 "No More Cell" for a Green and Soft Network 67 -- 5.5 Summary 75 -- Acknowledgments 76 -- References 76 -- 6 Proactive Caching in 5G Small Cell Networks 78 / Ejder Baştuğ, Mehdi Bennis, and Mérouane Debbah -- 6.1 Small Cell Networks: Past, Present and Future Trends 78 -- 6.2 Cache-enabled Proactive Small Cell Networks 80 -- 6.3 System Model 81 -- 6.4 Proactive Caching at Base Stations 82 -- 6.5 Proactive Caching at User Terminals 85 -- 6.6 Related Work and Research Directions 90 -- 6.7 Conclusions 95 -- Acknowledgments 95 -- References 95 -- 7 Modeling Multi-Radio Coordination and Integration in Converged Heterogeneous Networks 99 / Olga Galinina, Sergey Andreev, Alexander Pyattaev, Mikhail Gerasimenko, Yevgeni Koucheryavy, Nageen Himayat, Kerstin Johnsson, and Shu-ping Yeh.…”
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City logistics : mapping the future

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The handbook of children, media, and development

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Beginning teachers : reviewing disastrous lessons

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Misdiagnosis : woman as a disease

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Historicising gender and sexuality

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GAMIFICATION FOR PRODUCT EXCELLENCE make your product stand out with higher user engagement, retention, and innovation by Hyzy, Mike, Wardle, Bret

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From Edward Brooke to Barack Obama : African American political success, 1966-2008 by Nordin, Dennis S. (Dennis Sven), 1942-

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Dashboard design by Burch, Michael, 1976-, Schmid, Marco

Table of Contents: “…Preface xi List of Figures xv List of Tables xxi List of Abbreviations/Acronyms xxiii 1 Introduction 1 1.1 A Visualization Pipeline 2 1.2 Human Users and Tasks 5 1.3 Programming Directions and Solutions 8 2 Creating Powerful Dashboards 13 2.1 Data Handling 15 2.1.1 Data types 16 2.1.2 Data reading and parsing 20 2.1.3 Data storage 22 2.1.4 Data preprocessing 23 2.1.5 Data transformation 24 2.2 Visualization and Visual Analytics 26 2.2.1 Visual variables 28 2.2.2 Perception and cognition 30 2.2.3 The role of the human users 35 2.2.4 Algorithmic concepts 36 2.3 Examples of Visualization Techniques 38 2.3.1 Visualizing simple data types 39 2.3.2 Graph/network visualization 42 2.3.3 Hierarchy visualization 44 2.3.4 Multivariate data visualization 46 2.3.5 Trajectory visualization 48 2.3.6 Text visualization 49 2.4 Design and Prototyping 51 2.4.1 Visual design rules 53 2.4.2 No-goes and bad smells 55 2.4.3 Interface design rules 58 2.4.4 Creating a graphical user interface 61 2.5 Interaction 63 2.5.1 Interaction categories 64 2.5.2 Interaction modalities 66 2.5.3 Displays 68 2.5.4 Multiple coordinated views 70 3 Python, Dash, Plotly, and More 73 3.1 General Background Information 74 3.1.1 Python 75 3.1.2 Dash 76 3.1.3 Plotly and Plotly Express 77 3.1.4 Further ingredients and concepts 80 3.2 Installations and Options 82 3.2.1 Interactive mode 83 3.2.2 Jupyter Notebook mode 84 3.2.3 Integrated development environment (IDE) 85 3.2.4 GitHub 87 3.3 Interplay between Dash, Plotly, and Python 88 3.3.1 Reading and parsing in a dashboard 90 3.3.2 Data transformation in a dashboard 91 3.3.3 Dash core components 93 3.3.4 Dash HTML components 94 3.3.5 Cascading style sheets (CSS) 96 3.3.6 Plotly in a dashboard 97 3.3.7 Callbacks 98 3.4 Deploying 101 3.4.1 Heroku 102 3.4.2 International users 103 3.4.3 Online user evaluation 105 3.4.4 Benefits and drawbacks of online dashboards 106 4 Coding in Python 109 4.1 Expressions 110 4.1.1 Arithmetic expressions 111 4.1.2 Relational expressions 113 4.1.3 Boolean or logical expressions 114 4.1.4 Bitwise expressions 116 4.1.5 Mixed expressions 116 4.2 Data Types and Variables 118 4.2.1 Basic data types 118 4.2.2 Composite data types 120 4.2.3 Conversion between data types 123 4.2.4 Variables 124 4.2.5 Constants 125 4.3 Strings and Characters 126 4.3.1 String methods 126 4.3.2 ASCII code and table 128 4.3.3 User input and regular expressions 129 4.3.4 Comments 131 4.4 Conditionals and Exceptions 132 4.4.1 If and else 133 4.4.2 Pattern matching 134 4.4.3 Exceptions 135 4.5 Loops 136 4.5.1 Definite iteration 137 4.5.2 Indefinite iteration 139 4.5.3 Nested loops 140 4.6 Functions 141 4.6.1 Defining a function 141 4.6.2 Calling a function 142 4.6.3 Nesting of functions 144 4.6.4 Local and global variables 145 4.7 More Complex Functions 146 4.7.1 Recursion versus tail recursion 146 4.7.2 Higher-order functions 149 4.7.3 Lambda expressions 150 4.8 Reading and Writing Data 151 4.8.1 User input 152 4.8.2 Reading from a file 153 4.8.3 Writing on a file 155 4.8.4 Reading web content 156 4.9 Object-Oriented Programming 157 4.9.1 Classes 157 4.9.2 Objects and instances 159 4.9.3 Methods 160 4.9.4 Inheritance 161 5 Dashboard Examples 163 5.1 Modifying the Color in a Diagram 164 5.1.1 A simple dashboard with a histogram 165 5.1.2 Coding details 166 5.1.3 Dashboard in action 169 5.2 Two Diagrams, Bootstrap, and Value Filter 170 5.2.1 Extension with a scatter plot and slider 171 5.2.2 Coding details 172 5.2.3 Dashboard in action 176 5.3 Dashboard with Tabs, CSS, and Plotly Template 177 5.3.1 Histogram and scatter plot separately 177 5.3.2 Coding details 179 5.3.3 Dashboard in action 184 5.4 Inputs from a Plot and Plotly Go 185 5.4.1 Selecting point clouds for an overview 185 5.4.2 Coding details 187 5.4.3 Dashboard in action 193 5.5 Two Tabs, Three Plots in One Tab, and Several Inputs 194 5.5.1 Scatter plot as a density heatmap 195 5.5.2 Coding details 196 5.5.3 Dashboard in action 211 6 Challenges and Limitations 213 6.1 Design Issues 214 6.1.1 Interface design challenges 215 6.1.2 Visual design challenges 216 6.1.3 Aesthetics criteria 217 6.2 Implementation Challenges 219 6.2.1 Software and libraries 220 6.2.2 Integrated development environments (IDEs) 221 6.2.3 Developers and experience levels 222 6.2.4 Operating systems 223 6.2.5 Internet connection and servers 224 6.2.6 Web browsers 225 6.3 Challenges during runtime 227 6.3.1 Data scalability 228 6.3.2 Algorithmic scalability 229 6.3.3 Visual scalability 230 6.3.4 Perceptual scalability 231 6.4 Testing Challenges 233 6.4.1 Online accessibility 234 6.4.2 Runtime performance 235 6.4.3 User performance and evaluation 236 7 Conclusion 239 References 241 Index 269 About the Authors 289.…”
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A Companion to Plutarch

Table of Contents: “…Visiting Rome: The Immersion Experience -- 3. Roman Friends -- 4. Evaluating Emperors, Past and Present -- 5. …”
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Craft beers : fortification, processing, and production by Nehra, Manju, Gahlawat, Suresh Kumar, Grover, Nishant

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Acoustics, aeroacoustics and vibrations by Anselmet, Fabien

Table of Contents: “…Identification of experimental resonance frequencies -- 7.2.2.8. Clamped circular plate -- 7.2.2.9. …”
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