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Book SynopsisThe improvement of energy efficiency in electronics and computing systems is currently central to information and communication technology design; low-cost cooling, autonomous portable systems and functioning on recovered energy all need to be continuously improved to allow modern technology to compute more while consuming less. This book presents the basic principles of the origins and limits of heat dissipation in electronic systems. Mechanisms of energy dissipation, the physical foundations for understanding CMOS components and sophisticated optimization techniques are explored in the first half of the book, before an introduction to reversible and quantum computing. Adiabatic computing and nano-relay technology are then explored as new solutions to achieving improvements in heat creation and energy consumption, particularly in renewed consideration of circuit architecture and component technology. Concepts inspired by recent research into energy efficiency are brought together in this book, providing an introduction to new approaches and technologies which are required to keep pace with the rapid evolution of electronics.Table of ContentsIntroduction ix Chapter 1. Dissipation Sources in Electronic Circuits 1 1.1. Brief description of logic types 1 1.1.1. Boolean logic 1 1.1.2. Combinational and sequential logic 7 1.1.3. NMOS and PMOS transistors 15 1.1.4. Complementary CMOS logic 21 1.1.5. Pass-transistor logic 26 1.1.6. Dynamic logic 29 1.2. Origins of heat dissipation in circuits 32 1.2.1. Joule effect in circuits 32 1.2.2. Calculating dynamic power 34 1.2.3. Calculating static power and its origins 37 Chapter 2. Thermodynamics and Information Theory 39 2.1. Recalling the basics: entropy and information 39 2.1.1. Statistical definition of entropy 39 2.1.2. Macroscopic energy and entropy 42 2.1.3. Thermostat exchange, Boltzmann’s law and the equal division of energy 46 2.1.4. Summary and example of energy production in a conductor carrying a current 50 2.1.5. Information and the associated entropy 52 2.2. Presenting Landauer’s principle 57 2.2.1. Presenting Landauer’s principle and other examples 57 2.2.2. Experimental validations of Landauer’s principle 64 2.3. Adiabaticity and reversibility 66 2.3.1. Adiabatic principle of charging capacitors 66 2.3.2. Adiabaticity and reversibility: a circuit approach 82 Chapter 3. Transistor Models in CMOS Technology 91 3.1. Reminder on semiconductor properties 91 3.1.1. State densities and semiconductor properties 91 3.1.2. Currents in a semiconductor 100 3.1.3. Contact potentials 102 3.1.4. Metal-oxide semiconductor structure 103 3.1.5. Weak and strong inversion 109 3.2. Long- and short-channel static models 114 3.2.1. Basic principle and brief history of semiconductor technology 114 3.2.2. Transistor architecture and Fermi pseudo-potentials 117 3.2.3. Calculating the current in a long-channel static regime 120 3.2.4. Calculating the current in a short-channel regime 129 3.3. Dynamic transistor models 132 3.3.1. Quasi-static regime 132 3.3.2. Dynamic regime 135 3.3.3. “Small signals” transistor model 136 Chapter 4. Practical and Theoretical Limits of CMOS Technology 143 4.1. Speed–dissipation trade-off and limits of CMOS technology 143 4.1.1. From the transistor to the integrated circuit 143 4.1.2. Trade-off between speed and consumption 146 4.1.3. The trade-off between dynamic consumption and static consumption 149 4.2. Sub-threshold regimes 154 4.2.1. Recall of the weak inversion properties 154 4.2.2. Limits to sub-threshold CMOS technology 160 4.3. Practical and theoretical limits in CMOS technology 162 4.3.1. Economic considerations and evolving methodologies 162 4.3.2. Technological difficulties: dissipation, variability and interconnects 164 4.3.3. Theoretical limits and open questions 171 Chapter 5. Very Low Consumption at System Level 177 5.1. The evolution of power management technologies 177 5.1.1. Basic techniques for reducing dynamic power 177 5.1.2. Basic techniques for reducing static power 180 5.1.3. Designing in 90, 65 and 45 nm technology 185 5.2. Sub-threshold integrated circuits 186 5.2.1. Sub-threshold circuit features 186 5.2.2. Pipeline and parallelization 187 5.2.3. New SRAM structures 187 5.3. Near-threshold circuits 188 5.3.1. Optimization method 189 5.4. Chip interconnect and networks 194 5.4.1. Dissipation in the interconnect 194 5.4.2. Techniques for reducing dissipation in the interconnect 199 Chapter 6. Reversible Computing and Quantum Computing 203 6.1. The basis for reversible computing 203 6.1.1. Introduction 203 6.1.2. Group structure of reversible gates 205 6.1.3. Conservative gates, linearity and affinity 206 6.1.4. Exchange gates 207 6.1.5. Control gates 210 6.1.6. Two basic theorems: “no fan-out” and “no cloning” 213 6.2. A few elements for synthesizing a function 214 6.2.1. The problem and constraints on synthesis 214 6.2.2. Synthesizing a reversible function 215 6.2.3. Synthesizing an irreversible function 218 6.2.4. The adder example 219 6.2.5. Hardware implementation of reversible gates 222 6.3. Reversible computing and quantum computing 225 6.3.1. Principles of quantum computing 226 6.3.2. Entanglement 227 6.3.3. A few examples of quantum gates 229 6.3.4. The example of Grover’s algorithm 231 Chapter 7. Quasi-adiabatic CMOS Circuits 237 7.1. Adiabatic logic gates in CMOS 237 7.1.1. Implementing the principles of optimal charge and adiabatic pipeline 237 7.1.2. ECRL and PFAL in CMOS 244 7.1.3. Comparison to other gate technologies 250 7.2. Calculation of dissipation in an adiabatic circuit 251 7.2.1. Calculation in the normal regime 251 7.2.2. Calculation in sub-threshold regimes 259 7.3. Energy-recovery supplies and their contribution to dissipation 264 7.3.1. Capacitor-based supply 264 7.3.2. Inductance-based supply 273 7.4. Adiabatic arithmetic architecture 280 7.4.1. Basic principles 280 7.4.2. Adder example 281 7.4.3. The interest in complex gates 283 Chapter 8. Micro-relay Based Technology 285 8.1. The physics of micro-relays 285 8.1.1. Different computing technologies 285 8.1.2. Different actuation technologies 287 8.1.3. Dynamic modeling of microelectro-mechanical relays 290 8.1.4. Implementation examples and technological difficulties 297 8.2. Calculation of dissipation in a micro-relay based circuit 299 8.2.1. Optimization of micro-relays through electrostatic actuation 299 8.2.2. Adiabatic regime solutions 307 8.2.3. Comparison between CMOS logic and micro-relays 312 Bibliography 317 Index 321

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Book SynopsisThe Wave Concept Iterative Procedure (WCIP) method has found an increasing number of users within electromagnetic theory and applications to planar circuits, antennas and diffraction problems. This book introduces in detail this new formulation of integral methods, based on the use of a wave concept with two bounded operators, and applications in a variety of domains in electromagnetics. This approach presents a number of benefits over other integral methods, including overcoming the problem of singularity, and reduced computing time. Through the presentation of mathematical equations to characterize studied structures and explanation of the curves obtained, via validated examples, the authors provide a thorough background to electromagnetism as well as a professional reference to students and researchers.Table of ContentsPreface ix Chapter 1. General Principles of the Wave Concept Iterative Process 1Henri BAUDRAND, Med Karim AZIZI, Mohammed TITAOUINE 1.1. Introduction 1 1.2. The iterative wave method 3 1.3. General definition of waves 5 1.4. Application to planar circuits 5 1.5. Applications to quasi-periodic structures 6 1.6. Circuits with localized components 7 1.7. General principles of quasi-periodic circuits 7 1.8. The significance of using auxiliary sources 8 1.8.1. Description of the environment 9 1.9. Unidimensional circuits 9 1.10. Application: transmission line 14 1.11. Comparison of current density for different cell lengths 14 1.12. Bi-dimensional circuits 16 1.13. Two-source bi-dimensional circuits 16 1.14. Three-source bi-dimensional circuits 22 1.15. Validation examples 25 1.16. Lenses and meta-materials 34 1.17. Conclusion 41 Chapter 2. Formulation and Validation of the WCIP Applied to the Analysis of Multilayer Planar Circuits 43Alexandre Jean René SERRES and Georgina Karla DE FREITAS SERRES 2.1. Introduction 43 2.2. WCIP formulation 45 2.2.1. Multilayer formulation 45 2.2.2. Simulation results 48 2.3. Real and ideal polarizers within planar structures using WCIP 52 2.3.1. Formulation 52 2.3.2. Results 55 2.4. Amplifier structure of compact micro-waves 57 2.4.1. Formulation of the amplifier interface 57 2.4.2. The simulation results 59 Chapter 3. Applications of the WCIP Method to Frequency Selective Surfaces (FSS) 63Mohammed TITAOUINE and Henri BAUDRAND 3.1. Introduction 64 3.2. Formulation of the iterative WCIP method 65 3.2.1. Determining the diffraction operator 68 3.2.2. Determining the reflection operator 70 3.2.3. The fast modal transform FMT and its inverse FMT−1 72 3.2.4. FSS multilayer devices 72 3.2.5. Multi-level plated FSSs 72 3.3. Application of the iterative WCIP method to different FSSs 74 3.3.1. Dielectric short-circuited FSS rings 74 3.3.2. FSSs charged by lumped elements and active FSSs 76 3.3.3. Multi-frequency band FSSs 79 3.3.4. Double-layer FSS plating 80 3.3.5. Triple-layer plating 82 3.3.6. Thick FSSs 83 3.4. Anisotropic FSS 95 3.5. Measurement system 96 3.6. Conclusion 97 3.7. Acknowledgments 98 Chapter 4. WCIP Applied to Substrate Integrated Circuits: Substrate Integrated Waveguide (SIW) and Substrate Integrated Non-Radiative Dielectic (SINRD) Circuits 99Nathalie RAVEU and Ahmad ISMAIL ALHZZOURY 4.1. Introduction 99 4.2. Formulation of WCIP for SIC circuits 100 4.2.1. The definition of 103 4.2.2. The definition of 103 4.3. Results for SIW circuits 104 4.3.1. Waveguides 104 4.3.2. Bandpass filter 106 4.4. Results for the SINRD circuits 108 4.4.1. Waveguides 110 4.4.2. Bandpass filter 111 4.5. Conclusion 112 Chapter 5. WCIP Convergence 115Nathalie RAVEU 5.1. Introduction 115 5.2. Summary of WCIP 116 5.2.1. Representation of homogeneous materials around the interface 117 5.2.2. Description of boundary conditions at the interface 118 5.2.3. System to solve 118 5.3. Improvement of WCIP by mathematical techniques 119 5.3.1. Number of modes/number of meshes 120 5.3.2. GMRES/Richardson 121 5.3.3. Selecting the initial value 122 5.4. Improvement of WCIP by physical considerations 124 5.4.1. Simplification of waves at the interface 124 5.4.2. Choice of reference impedance 125 5.4.3. Boundary conditions on the metallic mesh 126 5.5. Conclusions 127 Chapter 6. Application of WCIP to Diffraction Problems 129Noemen AMMAR, Taoufik AGUILI and Henri BAUDRAND 6.1. Introduction 129 6.1.1. Diffraction by multilayer cylindrical structures 130 6.1.2. Descriptors for spectral components of reflection operators 132 6.1.3. The modal coefficients ext n Γ and int n Γ 133 6.1.4. Modal coefficients pass n Γ 134 6.1.5. Spatial diffraction operator 136 6.1.6. Excitation source 137 6.1.7. Iterative process 138 6.2. Application 138 6.2.1. Dielectric cylinder diffraction 139 6.2.2. Diffraction by metallic strips 143 6.2.3. Coaxial multi-strip structure 148 6.2.4. Diffraction by two dielectric co-axials 156 6.2.5. Diffraction by structures of any shape 159 6.3. Coupling simulation 160 6.3.1. Different operators involved 162 6.3.2. The case of two pixels on a single fictitious cylinder 163 6.3.3. The case where the two pixels are part of two coaxial cylinders 164 6.3.4. Spatial descriptors of diffraction operators 167 6.3.5. The iterative process 169 6.3.6. Computation of the remote location electric field 169 6.3.7. Application 170 6.4. Conclusion 183 Bibliography 185 List of Authors 195 Index 197

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Book SynopsisThis edited textbook brings together expert scholars and experienced practitioners to guide educators in structuring secondary learning experiences that promote college and career readiness. It emphasizes authentic learning that connects academic knowledge to real-world situations, helping students develop practical skills. Chapters illustrate examples of authentic learning experiences across English Language Arts, Mathematics, Sciences, and Social Studies. Each chapter provides a brief review of related theory and research, followed by examples of how disciplinary knowledge relates to specific occupations and professions. Ideal for secondary methods courses, this book models how to plan dynamic learning experiences for both individual assignments and whole class projects. The exciting new book asks teacher candidates to consider the purpose of specific subject matter in the curriculum, its significance to society, its application in studentâs everyday lives, and its impact on the professional world.

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Book SynopsisBuilding a Resilient and Responsible World A Psychological Perspective Building a Resilient and Responsible World A Psychological Perspective.- Integrating Psychosocial Well-Being in Development: Insights from a Disability-Inclusive Development Model.- Understanding Negative Reciprocity in a Syncretic Culture: How Do Cognitive and Affective Factors Explain It.- Collective Honour and Personal Dignity: Implications for Well-Being From an Indian Perspective.

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Book Synopsis The ultimate training resource for athletes and coaches includes more than 262 exercises and drills, programming, and exclusive access to online video library. Assessments provide parameters for individual programs and sport-specific training. Trade Review“Training for Speed, Agility, and Quickness is one of the books that I use frequently when designing training programs for my athletes.”Allen Hedrick, MA, CSCS, RSCC, FNSCA-- Head Strength and Conditioning Coach, Colorado State University at Pueblo, Author of Dumbbell Training“Training for Speed, Agility, and Quickness is a comprehensive resource that will benefit all readers. The recommendations are backed by research and are easily adjusted to the needs of each athlete.”Boyd Epley-- Founder of National Strength and Conditioning Association, U.S. Collegiate Strength and Conditioning, Coaches Hall of Fame, Nebraska Football Hall of Fame, Lindy’s Sports Top 100 Most Important College Football Sports Figures of the Century Table of ContentsPart I Training Essentials Chapter 1 How the Training Works Chapter 2 Athlete Assessment Chapter 3 Incorporating Mental Training Chapter 4 Speed Training Chapter 5 Agility Training Chapter 6 Quickness and Reaction Time Training Part II Training Programs Chapter 7 Developing a Customized Program Chapter 8 Baseball and Softball Chapter 9 Football and Rugby Chapter 10 Basketball and Netball Chapter 11 Combat Sports Chapter 12 Track and Field Chapter 13 Soccer Chapter 14 Lacrosse Chapter 15 Tennis and Badminton Chapter 16 Racquetball and Squash

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Book SynopsisIn order to create a reliable, safe and cost-effective electric vehicle with acceptable range, battery charging time, battery life and driving performance, it is important to design optimised and compatible components and charging systems. This book offers an overview of the design, modeling, simulation and control of electric vehicle components and charging technologies. Chapters address the fundamentals of electric vehicles and the essentials of their power electronics components, discuss the principles of design, modeling, simulation and control, and then apply those principles to electric machines, drives and battery management systems. Where relevant, MATLAB/Simulink models are included. Further topics include fault tolerant operation, wired and wireless charging systems, power quality control, and grid integration. Current regulations and standards are also addressed. Electric Vehicle Components and Charging Technologies: Design, modeling, simulation and control is intended to be suitable for newcomers to the field, though it assumes an engineering background. The discussions of emerging concepts, methods and realisation are also intended to be thought-provoking for more established researchers, engineers and industry professionals.Table of Contents Chapter 1: Electric vehicles and its components Chapter 2: Electric vehicle fundamentals Chapter 3: Electric energy sources and storage device Chapter 4: Power electronic essentials in electric vehicle Chapter 5: Design, modeling, simulation, and control of electric vehicle Chapter 6: Design, modelling, simulation and control of electric machines and drives used in electric vehicle Chapter 7: Battery management system for electric vehicle Chapter 8: Fault-tolerant operation of electric vehicles Chapter 9: Design, simulation, and control of battery charger for electric vehicle Chapter 10: Power quality control of battery charging system Chapter 11: Wireless power transfer for electric vehicle Chapter 12: Grid integration of electric vehicles Chapter 13: Regulations and standards of electric vehicles

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Book SynopsisThis book explores how the technical upheavals of the 21st century have changed the structures and architecture of the creation, sharing and regulation of knowledge. From the new economic and technical models of production and dissemination of knowledge, the book deals with all new forms of valorisation. It also explains how the legislative deficit in the world and in Europe, around digital is being filled by new initiatives, such as the law for a Digital Republic, in France. It is therefore a book that provides a valuable follow-up to the book "The New Challenges of Knowledge", of which it constitutes the continuation and operational deepening.Table of ContentsPreface xiRenaud FABRE and Alain BENSOUSSAN Part 1. Scientific Resources and Data Economy 1 Chapter 1. Data Production and Sharing: Towards a Universal Right? 3Marie BLANQUART, Thomas DESCOUS and Ewen HUET 1.1. The right to knowledge today: between attempts at universalization and “self-regulation” by the GAFA 4 1.1.1. Towards the emergence of a universal right to knowledge subject to divergent economic thinking 5 1.1.2. The recognition of a universal right to knowledge: a “realistic utopia”? 6 1.2. Platform and scientific community rights: the absence of an upfront legal framework 7 1.2.1. A system partly caused by the development of the digital sector 7 1.2.2. The now-fragile law attempting to protect the results of research 8 1.2.3. Intellectual property rights 8 1.2.4. The notion of databases and protection by sui generis law 9 1.2.5. Problems with the legal statute of knowledge 11 1.3. The need to elaborate several types of legislation 12 1.3.1. Platform rights 12 1.3.2. Text and Data Mining: the great new stake 14 1.4. Open Science: an achievable goal? 15 Chapter 2. Data: a Simple Raw Material? 19Bertrand PELETIER and Thomas DESCOUS 2.1. The new generation of data: management issues arising from ownership rights 19 2.2. How to transform these data into knowledge? 20 2.3. A new knowledge economy is necessary 21 2.3.1. The information war and the stakes of data protection 21 2.4. International scientific publishing: high added-value services and researcher community 22 2.4.1. The open platform as the preferred tool for sharing and exploiting data 22 2.4.2. An undeniable added value in processing data brought about by platforms 24 Chapter 3. New Knowledge Tools 27Christoph LOHSCHELDER 3.1. Sharing and uncertainty 27 3.2. Platform construction 28 3.3. Machine learning 30 3.4. Promising progress to be qualified… 31 Part 2. The Knowledge Factory 33 Chapter 4. Economic Models of Knowledge Sharing 35Vincent GIACOBBI 4.1. A quick historic overview 35 4.2. Property and/or sharing 35 4.3. An immaterial good capable of fueling the production of material goods 37 4.4. The large stakes of knowledge production 38 4.4.1. Limits of this model: consistency, reliability and indistinction 39 4.4.2. Business models of knowledge sharing 39 4.4.3. Some numbers 40 4.5. Development prospects allowing for new fields of study and more nimbly integrating researchers into the economic chain 41 Chapter 5. From the Author to the Valorizer 43Lucile COLLIN 5.1. The author and the valorizer: conciliation and efficiency of the interaction 43 5.2. One point on patents 44 5.3. The innovation cycle 45 5.4. The law for a Digital Republic 46 5.5. Scientific openness surpassing ancient legal tools 48 Chapter 6. Valorization: a Global Geopolitical Stake 51Marie BLANQUART 6.1. A multispeed competition 51 6.1.1. The United States: a country losing its lead 51 6.1.2. French stagnation 53 6.1.3. The expanding Chinese model 54 6.2. International cooperation in the scientific sector 57 6.2.1. A developing European project 57 6.2.2. International organizations 58 Chapter 7. Focus: the Chinese Patent Strategy 61Vincent GIACOBBI 7.1. Chinese expansion 62 7.2. An inflation of Chinese patents 63 7.3. Some fallbacks in China nuancing its strategic position 65 7.3.1. A fallback in favor of applied research 66 7.3.2. Territorial withdrawal 66 7.3.3. A long certification process with uncertain ends 66 7.3.4. The procedure for submitting a dispute on a patent 67 7.4. Contestable and contested digital supremacy 68 Chapter 8. Artificial Intelligence Policies 71Maximilian NOMINACHER and Bertrand PELETIER 8.1. Policies concerning “strong” AI 72 8.2. Policies concerning “weak” AI 72 8.3. Policies concerning artificial intelligence safety 74 8.4. From practice to ethics: what is AI’s legal status? 75 Chapter 9. New Formulations of Results and New “Markets” 77Louki-Géronimo RICHOU 9.1. Making universal: establishing common standards of expression 78 9.1.1. Requirement of uniqueness 79 9.1.2. Hierarchy requirement 79 9.2. To adapt: from popularization to simplification 82 9.2.1. Versatility or specialization? 83 9.2.2. Simplifying rather than popularizing 84 9.2.3. Measures following the precautionary principle: archiving and protection 85 9.2.4. Preserving the researcher while optimizing knowledge for the general interest during the digital era 85 9.3. Developing the general state of knowledge with care 87 Chapter 10. Open Science: a Common Good that Needs to be Valued? 89Nicolas MASSEREAU 10.1. A global challenge that must take the economy into account 90 10.2. A wide variety of public policies respond to this challenge 90 10.2.1. Enterprises and States 90 10.2.2. Valorization as a junction point 91 10.2.3. Basic research: competing with applied research? 93 10.3. The French case and international rankings 94 10.4. The limits of the patent system and publication count 96 10.5. Investment tools aiming to correct these failures 98 10.6. How to measure innovation? 100 10.6.1. The university: the first knowledge production framework recognized by law 100 10.6.2. Research data: a new intangible “place” for producing knowledge 101 10.7. The application of research is not an end in itself 102 Conclusion 105Renaud FABRE and Alain BENSOUSSAN Appendices 109 Appendix 1. Extract from the CNRS White Paper: “The Work of Science and the Digital Field: Data, Publications, Platforms. A Systematic Analysis of the Law for a Digital Republic” 111 Appendix 2. Extract from the CNRS White Paper “Open Science in a Digital Republic: Studies and Proposals for Law Application. Strategic Application Guide” 161 Bibliography 179 List of Authors 183 Index 185

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Book SynopsisThis book provides an introduction to the theory and design of composite structures of steel and concrete. Material applicable to both buildings and bridges is included, with more detailed information relating to structures for buildings. Throughout, the design methods are illustrated by calculations in accordance with the Eurocode for composite structures, EN 1994, Part 1-1, General rules and rules for buildings' and Part 1-2, Structural fire design', and their cross-references to ENs 1990 to 1993. The methods are stated and explained, so that no reference to Eurocodes is needed. The use of Eurocodes has been required in the UK since 2010 for building and bridge structures that are publicly funded. Their first major revision began in 2015, with the new versions due in the early 2020s. Both authors are involved in the work on Eurocode 4. They explain the expected additions and changes, and their effect in the worked examples for a multi-storey framed structure for a building,Table of ContentsPreface xi Symbols, Terminology and Units xv 1 Introduction 1 1.1 Composite beams and slabs 1 1.2 Composite columns and frames 2 1.3 Design philosophy and the Eurocodes 3 1.3.1 Background 3 1.3.2 Limit state design philosophy 4 1.4 Properties of materials 8 1.4.1 Concrete 9 1.4.2 Reinforcing steel 10 1.4.3 Structural steel 10 1.4.4 Profiled steel sheeting 10 1.4.5 Shear connectors 11 1.5 Direct actions (loading) 11 1.6 Methods of analysis and design 12 1.6.1 Typical analyses 13 1.6.2 Non-linear global analysis 17 2 Shear Connection 19 2.1 Introduction 19 2.2 Simply-supported beam of rectangular cross-section 20 2.2.1 No shear connection 20 2.2.2 Full interaction 22 2.3 Uplift 24 2.4 Methods of shear connection 25 2.4.1 Bond 25 2.4.2 Shear connectors 25 2.4.3 Shear connection for profiled steel sheeting 29 2.5 Properties of shear connectors 29 2.5.1 Stud connectors used with profiled steel sheeting 33 2.5.2 Stud connectors in a ‘lying’ position 38 2.5.3 Example: stud connectors in a ‘lying’ position 39 2.6 Partial interaction 41 2.7 Effect of degree of shear connection on stresses and deflections 43 2.8 Longitudinal shear in composite slabs 44 2.8.1 The shear-bond test 45 2.8.2 Design by the m–k method 47 2.8.3 Defects of the m–k method 47 3 Simply-supported Composite Slabs and Beams 49 3.1 Introduction 49 3.2 Example: layout, materials and loadings 49 3.2.1 Properties of concrete 50 3.2.2 Properties of other materials 50 3.2.3 Resistance of the shear connectors 51 3.2.4 Permanent actions 51 3.2.5 Variable actions 51 3.3 Composite floor slabs 51 3.3.1 Resistance of composite slabs to sagging bending 54 3.3.2 Resistance of composite slabs to longitudinal shear by the partial-interaction method 56 3.3.3 Resistance of composite slabs to vertical shear 58 3.3.4 Punching shear 59 3.3.5 Bending moments from concentrated point and line loads 60 3.3.6 Serviceability limit states for composite slabs 62 3.4 Example: composite slab 63 3.4.1 Profiled steel sheeting as formwork 64 3.4.2 Composite slab – flexure and vertical shear 65 3.4.3 Composite slab – longitudinal shear 66 3.4.4 Local effects of point load 68 3.4.5 Composite slab – serviceability 69 3.4.6 Example: composite slab for a shallow floor using deep decking 70 3.4.7 Comments on the designs of the composite slab 73 3.5 Composite beams – sagging bending and vertical shear 73 3.5.1 Effective cross-section 73 3.5.2 Classification of steel elements in compression 74 3.5.3 Resistance to sagging bending 76 3.5.4 Resistance to vertical shear 84 3.5.5 Resistance of beams to bending combined with axial force 85 3.6 Composite beams – longitudinal shear 86 3.6.1 Critical lengths and cross-sections 86 3.6.2 Non-ductile, ductile and super-ductile stud shear connectors 87 3.6.3 Transverse reinforcement 90 3.6.4 Detailing rules 94 3.7 Stresses, deflections and cracking in service 95 3.7.1 Elastic analysis of composite sections in sagging bending 96 3.7.2 The use of limiting span-to-depth ratios 98 3.8 Effects of shrinkage of concrete and of temperature 99 3.9 Vibration of composite floor structures 99 3.9.1 Prediction of fundamental natural frequency 101 3.9.2 Response of a composite floor to pedestrian traffic 103 3.10 Hollow-core and solid precast floor slabs 104 3.10.1 Joints, longitudinal shear and transverse reinforcement 105 3.10.2 Design of composite beams that support precast slabs 105 3.11 Example: simply-supported composite beam 107 3.11.1 Composite beam – full-interaction flexure and vertical shear 108 3.11.2 Composite beam – partial shear connection, non-ductile connectors and transverse reinforcement 110 3.11.3 Composite beam – deflection and vibration 113 3.12 Shallow floor construction 117 3.13 Example: composite beam for a shallow floor using deep decking 119 3.14 Composite beams with large web openings 122 4 Continuous Beams and Slabs, and Beams in Frames 129 4.1 Types of global analysis and of beam-to-column joint 129 4.2 Hogging moment regions of continuous composite beams 133 4.2.1 Resistance to bending 133 4.2.2 Vertical shear, and moment-shear interaction 137 4.2.3 Longitudinal shear 138 4.2.4 Lateral buckling 139 4.2.5 Cracking of concrete 144 4.3 Global analysis of continuous beams 149 4.3.1 General 149 4.3.2 Elastic analysis 150 4.3.3 Rigid-plastic analysis 154 4.4 Stresses and deflections in continuous beams 156 4.5 Design strategies for continuous beams 157 4.6 Example: continuous composite beam 158 4.6.1 Data 158 4.6.2 Flexure and vertical shear 160 4.6.3 Lateral buckling 162 4.6.4 Shear connection and transverse reinforcement 164 4.6.5 Check on deflections 165 4.6.6 Control of cracking 168 4.7 Continuous composite slabs 169 5 Composite Columns and Frames 171 5.1 Introduction 171 5.2 Composite columns 173 5.3 Beam-to-column joints 173 5.3.1 Properties of joints 173 5.3.2 Classification of joints 179 5.4 Design of non-sway composite frames 180 5.4.1 Imperfections 180 5.4.2 Elastic stiffnesses of members 182 5.4.3 Methods of global analysis 183 5.4.4 First-order global analysis of braced frames 184 5.4.5 Outline sequence for design of a composite braced frame 186 5.5 Example: composite frame 187 5.5.1 Data 187 5.5.2 Design action effects and load arrangements 188 5.6 Simplified design method of EN 1994-1-1, for columns 189 5.6.1 Introduction 189 5.6.2 Detailing rules, and resistance to fire 190 5.6.3 Properties of column lengths 191 5.6.4 Resistance of a cross-section to combined compression and uniaxial bending 192 5.6.5 Verification of a column length 193 5.6.6 Transverse and longitudinal shear 195 5.6.7 Concrete-filled steel tubes 196 5.7 Example (continued): external column 197 5.7.1 Action effects 197 5.7.2 Properties of the cross-section, and y-axis slenderness 198 5.7.3 Resistance of the column length, for major-axis bending 201 5.7.4 Resistance of the column length, for minor-axis bending 202 5.7.5 Checks on shear, and closing comment 204 5.8 Example (continued): internal column 205 5.8.1 Global analysis 205 5.8.2 Resistance of an internal column 207 5.8.3 Comment on column design 207 5.9 Example (continued): design of frame for horizontal forces 207 5.9.1 Design loadings, ultimate limit state 208 5.9.2 Stresses and stiffness 209 5.10 Example (continued): joints between beams and columns 209 5.10.1 Nominally-pinned joint at external column 209 5.10.2 End-plate joint at internal column 210 5.11 Example: concrete-filled steel tube with high-strength materials 216 5.11.1 Loading 216 5.11.2 Action effects for the column length 216 5.11.3 Effect of creep 217 5.11.4 Slenderness 218 5.11.5 Bending moment 218 5.11.6 Interaction polygon, and resistance 218 5.11.7 Discussion 219 6 Fire Resistance 223 Yong C.Wang 6.1 General introduction and additional symbols 223 6.1.1 Fire resistance requirements 224 6.1.2 Fire resistance design procedure 225 6.1.3 Partial safety factors and material properties 226 6.2 Composite slabs 226 6.2.1 General calculation method 226 6.2.2 Tabulated data 227 6.2.3 Tensile membrane action 227 6.3 Composite beams 229 6.3.1 Critical temperature method 229 6.3.2 Temperature of protected steel 232 6.3.3 Load-carrying capacity calculation method 234 6.3.4 Appraisal of different calculation methods for composite beams 238 6.3.5 Shear resistance 238 6.4 Composite columns 239 6.4.1 General calculation method and methods for different types of columns 240 6.4.2 Concrete-filled tubes 241 6.4.3 Worked example for concrete-filled tubes with eccentric loading 244 A Partial-interaction theory 247 A.1 Theory for simply-supported beam 247 A.2 Example: partial interaction 250 References 253 Index 259

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Book SynopsisA comprehensive guide to the essential principles of image processing and pattern recognition Techniques and applications in the areas of image processing and pattern recognition are growing at an unprecedented rate. Containing the latest state-of-the-art developments in the field, Image Processing and Pattern Recognition presents clear explanations of the fundamentals as well as the most recent applications. It explains the essential principles so readers will not only be able to easily implement the algorithms and techniques, but also lead themselves to discover new problems and applications. Unlike other books on the subject, this volume presents numerous fundamental and advanced image processing algorithms and pattern recognition techniques to illustrate the framework. Scores of graphs and examples, technical assistance, and practical tools illustrate the basic principles and help simplify the problems, allowing students as well as professionals to easily gTable of ContentsPART I: FUNDAMENTALS. 1 INTRODUCTION. 1.1 The World of Signals. 1.2 Digital Image Processing. 1.3 Elements of an Image Processing System. Appendix 1.A Selected List of Books on Image Processing and Computer Vision from Year 2000. References. 2 MATHEMATICAL PRELIMINARIES. 2.1 Laplace Transform. 2.2 Fourier Transform. 2.3 Z-Transform. 2.4 Cosine Transform. 2.5 Wavelet Transform. 3 IMAGE ENHANCEMENT. 3.1 Grayscale Transformation. 3.2 Piecewise Linear Transformation. 3.3 Bit Plane Slicing. 3.4 Histogram Equalization. 3.5 Histogram Specification. 3.6 Enhancement by Arithmetic Operations. 3.7 Smoothing Filter. 3.8 Sharpening Filter. 3.9 Image Blur Types and Quality Measures. 4 MATHEMATICAL MORPHOLOGY. 4.1 Binary Morphology. 4.2 Opening and Closing. 4.3 Hit-or-Miss Transform. 4.4 Grayscale Morphology. 4.5 Basic Morphological Algorithms. 4.6 Morphological Filters. 5 IMAGE SEGMENTATION. 5.1 Thresholding. 5.2 Object (Component) Labeling. 5.3 Locating Object Contours by the Snake Model. 5.4 Edge Operators. 5.5 Edge Linking by Adaptive Mathematical Morphology. 5.6 Automatic Seeded Region Growing. 5.7 A Top-Down Region Dividing Approach. 6 DISTANCE TRANSFORMATION AND SHORTEST PATH PLANNING. 6.1 General Concept. 6.2 Distance Transformation by Mathematical Morphology. 6.3 Approximation of Euclidean Distance. 6.4 Decomposition of Distance Structuring Element. 6.5 The 3D Euclidean Distance. 6.6 The Acquiring Approaches. 6.7 The Deriving Approaches. 6.8 The Shortest Path Planning. 6.9 Forward and Backward Chain Codes for Motion Planning. 6.10 A Few Examples. 7 IMAGE REPRESENTATION AND DESCRIPTION. 7.1 Run-Length Coding. 7.2 Binary Tree and Quadtree. 7.3 Contour Representation. 7.4 Skeletonization by Thinning. 7.5 Medial Axis Transformation. 7.6 Object Representation and Tolerance. 8 FEATURE EXTRACTION. 8.1 Fourier Descriptor and Moment Invariants. 8.2 Shape Number and Hierarchical Features. 8.3 Corner Detection. 8.4 Hough Transform. 8.5 Principal Component Analysis. 8.6 Linear Discriminate Analysis. 8.7 Feature Reduction in Input and Feature Spaces. 9 PATTERN RECOGNITION. 9.1 The Unsupervised Clustering Algorithm. 9.2 Bayes Classifier. 9.3 Support Vector Machine. 9.4 Neural Networks. 9.5 The Adaptive Resonance Theory Network. 9.6 Fuzzy Sets in Image Analysis. PART II: APPLICATIONS. 10 FACE IMAGE PROCESSING AND ANALYSIS. 10.1 Face and Facial Feature Extraction. 10.2 Extraction of Head and Face Boundaries and Facial Features. 10.3 Recognizing Facial Action Units. 10.4 Facial Expression Recognition in JAFFE Database. 11 DOCUMENT IMAGE PROCESSING AND CLASSIFICATION. 11.1 Block Segmentation and Classification. 11.2 Rule-Based Character Recognition System. 11.3 Logo Identification. 11.4 Fuzzy Typographical Analysis for Character Preclassification. 11.5 Fuzzy Model for Character Classification. 12 IMAGE WATERMARKING. 12.1 Watermarking Classification. 12.2 Spatial Domain Watermarking. 12.3 Frequency-Domain Watermarking. 12.4 Fragile Watermark. 12.5 Robust Watermark. 12.6 Combinational Domain Digital Watermarking. 13 IMAGE STEGANOGRAPHY. 13.1 Types of Steganography. 13.2 Applications of Steganography. 13.3 Embedding Security and Imperceptibility. 13.4 Examples of Steganography Software. 13.5 Genetic Algorithm-Based Steganography. 14 SOLAR IMAGE PROCESSING AND ANALYSIS. 14.1 Automatic Extraction of Filaments. 14.2 Solar Flare Detection. 14.3 Solar Corona Mass Ejection Detection. INDEX.

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Book SynopsisThis important book by two leading scholars of Africa examines a series of issues that are central to the question of the postcolonial. The postcolonial paradigm, and the more recent decolonial paradigm, raise the issue of the universal: is the postcolonial the first phase of a new universalism, one which would be truly universal because it would be fully inclusive, or is it on the contrary the denial of all universalism, the triumph of the particular and of fragmentation? In addressing this issue Diagne and Amselle also tackle many related themes, such as the concepts of race, culture and identity, the role of languages in philosophy as practised in different cultural areas, the various conceptions of Islam, especially in West Africa, and the outlines of an Africa which can be thought of at the same time as singular and as plural. Each thinker looks back at his writings on these themes, comparing and contrasting them with those of his interlocutor. While Amselle seeks to expose the essentialist and culturalist logics that might underlie postcolonial and decolonial thought, Diagne consistently refuses to adopt the trappings of the Afrocentrist and particularist thinker. He argues instead for a total decentring of all thought, one that rejects all ‘centrisms’ and highlights instead branchings and connections, transfers, analogies and reciprocal influences between cultural places and intellectual fields that may be distant but are not distinct in space and time. This volume is a timely contribution to current debates on the postcolonial question and its new decolonial form. It will be of great interest to students and scholars in a variety of fields, from African studies and Black studies to philosophy, anthropology, sociology and cultural studies, as well as to anyone interested in the debates around postcolonial studies and decolonial thought

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Book SynopsisDigital traces, whether digitized (programs, notebooks, drawings, etc.) or born digital (emails, websites, video recordings, etc.), constitute a major challenge for the memory of the ephemeral performing arts.Digital technology transforms traces into data and, in doing so, opens them up to manipulation. This paradigm shift calls for a renewal of methodologies for writing the history of theater today, analyzing works and their creative process, and preserving performances. At the crossroads of performing arts studies, the history, digital humanities, conservation and archiving, these methodologies allow us to take into account what is generally dismissed, namely, digital traces that are considered too complex, too numerous, too fragile, of dubious authenticity, etc.With the analysis of Merce Cunningham’s digital traces as a guideline, and through many other examples, this book is intended for researchers and archivists, as well as artists and cultural institutions.Table of ContentsForeword ixBruno BACHIMONT Preface xiii Introduction xxxv Chapter 1. The Digital Trace: From Data to Metatrace 1 1.1. Tracing the ephemeral 2 1.1.1. An impossible history? 3 1.1.2. Relying on traces 4 1.2. The digital trace 8 1.2.1. Digitized traces 9 1.2.2. Born digital traces 10 1.2.3. Heterogeneous, numerous and fragile traces 11 1.3. Transforming traces into data 14 1.3.1. Analog trace and digital trace 14 1.3.2. From trace to data: the datatrace 16 1.3.3. Metatrace 22 1.4. Performing arts data 25 1.4.1. Performing arts data landscapes 25 1.4.2. The Semantic Web paradigm 27 1.4.3. Transforming the living archive into data 33 1.5. Conclusion 38 Chapter 2. Preserving the Impermanent 41 2.1. Note: scoring the representation 42 2.1.1. Notation of the performing arts 43 2.1.2. Scoring 49 2.1.3. From autography to allography: scoring digital works 52 2.1.4. The performing arts, between allography and autography 57 2.2. Diachronic documentation: reconnecting with the process 62 2.2.1. Making digital traces last 63 2.2.2. Taking the creation processes into account 66 2.3. Annotating: redocumentarizing traces 69 2.3.1. Digital as an annotation practice 71 2.3.2. The special case of video recording 73 2.3.3. Intra- and inter-documentary approaches 76 2.3.4. MemoRekall, a video annotation tool for redocumentarizing traces 79 2.4. Denote/connote: artistic intent and datatraces 83 2.4.1. Articulating close and distant reading 83 2.4.2. Rekall 90 2.5. Conclusion 95 Chapter 3. Writing the History of the Performing Arts 97 3.1. Sources and resources 99 3.1.1. Theater studies and digital humanities 100 3.1.2. Scrutinizing 105 3.1.3. Going back to the source 110 3.2. Exposing traces 113 3.2.1. Linking 114 3.2.2. Structuring 119 3.2.3. Reconstructing 124 3.3. Analyzing performing arts data 127 3.3.1. History 129 3.3.2. Literature 135 3.3.3. Shows 141 3.4. Conclusion 147 Conclusion 149 Glossary 153 References 163 Index of Names 179 Index of Terms 183

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Book SynopsisThroughout history, the study of sacred texts has focused almost exclusively on the content and meaning of these writings. Such a focus obscures the fact that sacred texts are always embodied in particular material forms—from ancient scrolls to contemporary electronic devices. Using the digital turn as a starting point, this volume highlights material dimensions of the sacred texts of Judaism, Christianity, and Islam. The essays in this collection investigate how material aspects have shaped the production and use of these texts within and between the traditions of Judaism, Christianity, and Islam, from antiquity to the present day. Contributors also reflect on the implications of transitions between varied material forms and media cultures. Taken together, the essays suggests that materiality is significant for the academic study of sacred texts, as well as for reflection on developments within and between these religious traditions. This volume offers insightful analysis on key issues related to the materiality of sacred texts in the traditions of Judaism, Christianity, and Islam, while also highlighting the significance of transitions between various material forms, including the current shift to digital culture.

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Book SynopsisChapter 1: Origins and Initial Concept.- Chapter 2: Architecture.- Chapter 3: The Build System.- Chapter 4: Being Part of the .NET Ecosystem.- Chapter 5: Interfacing with the Outside World.- Chapter 6: An IoT Embedded Device.- Chapter 7: Nano Devices Big-Time Connectivity.- Chapter 8: Testing for Embedded Success.- Chapter 9: Advanced Coding Topics.- Chapter 10: Beyond Connectivity - MCP in Embedded Devices.

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Book SynopsisApproximated ensemble learning driven boosting method for breast cancer prediction on multi-modal clinical datasets.- A Medical Image Encryption Technique using Tropical Semiring.- A robust key exchange scheme for the Internet of Medical Things.

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Book SynopsisPaul Luna is Emeritus Professor at the University of Reading, UK, and author of Typography: A Very Short Introduction (2018). He has written on the relationship between typography and lexicography, and for many years directed the design of English and bilingual dictionaries at Oxford University Press.Fiona Ross is Professor in Type Design at the University of Reading, UK. With a background in languages and Indian palaeography, she specializes in type design for Arabic, South Asian, and Thai writing systems. Fiona has received the SoTA Typography Award (2014) and the Type Director's Club Medal (2018).Aaris Sherin is an educator, writer, and designer. She is Professor of Graphic Design at St John's University, New York, USA, and the author of Sustainable Thinking (Bloomsbury, 2017) and Introduction to Graphic Design (Bloomsbury, 2017).Vaibhav Singh is an independent researcher, typographer, and type designer. Previously a British Academy Postdoctoral Fellow and chairman of the Printing Historical Society, he is the editor of the journal Contextual Alternate and co-editor of the Bloomsbury research series Notes on Typography.Sue Walker is co-director of the interdisciplinary Centre for Book Cultures and Publishing, and director of the Lettering, Printing, and Graphic Design Collections in the Department of Typography and Graphic Communication at the University of Reading, UK. Her research interests are in book design for young people and the relationship between typography and language.

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Book SynopsisYou were a happy coder, then the opportunity came to lead a team. Unfamiliar assignments come without warning, team members need care and attention, and then the organization demands that you take on roles you hadn't prepared for and work with people whom you have no idea what they do. It's a struggle to keep up and often feels like thrashing rather than success.And yet, you are the lynchpin. Software Managers are responsible for critical product delivery and information processing in the largest and most impactful global companies and across nearly every industry and public sector. Some of the fundamentals like project management and team leadership have been well documented but the world keeps getting more complicated.This book reveals the breadth of domains that a Software Manager will encounter as they progress from competent contributor to tech lead to manager to increasing levels of responsibility. Even experienced managers will find helpful new perspectives and insights. You will be challenged to think more deeply about the people you may manage, the processes of developing products so complex that no individual can keep it all in their head, and the often-mysterious organizational behaviors surrounding you. Tech companies don't have to throw good practitioners into hard management positions with no training and compound the error as people advance in their management careers; it has just been our habit. We can do better. Mastering the Complex World of Software Management provides realistic scope, attacks the nitty-gritty realities, and challenges the reader to think about their situation so they can solve the myriad technical, process, organizational, and business challenges coming their way. What You Will LearnMaster the fundamentals of managing technology teamsSee how operating teams navigate themselves within a larger organization Understand and work around the landmines in software developmentWho This Book is ForSoftware developers who are considering a management path for their career; senior tech leads that are responsible for much of a software team's operation; software development managers that want to improve their capabilities in order to take on more responsibilities and earn a promotion.

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Book Synopsis1. Overview of Distributed Systems.- 2. Distributed Communication Basics.- 3. NATS Fundamentals.- 4. A Working System.- 5. Anatomy of a Service.- 6. DDD (Domain-Driven Design).- 7. Hexagonal Architecture.- 8. Sample Service.- 9. A Whole System vs a Bunch of Services.- 10. DDD for Systems.- 11. Fully Synchronous Systems.- 12. Aynchronous Systems.- 13. Reactive Systems.- 14. A Working System.

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Book SynopsisNowadays, distributed systems are increasingly present, for public software applications as well as critical systems. software applications as well as critical systems. This title and Distributed Systems: Design and Algorithms – from the same editors – introduce the underlying concepts, the associated design techniques and the related security issues. The objective of this book is to describe the state of the art of the formal methods for the analysis of distributed systems. Numerous issues remain open and are the topics of major research projects. One current research trend consists of profoundly mixing the design, modeling, verification and implementation stages. This prototyping-based approach is centered around the concept of model refinement. This book is more specifically intended for readers that wish to gain an overview of the application of formal methods in the design of distributed systems. Master’s and PhD students, as well as engineers in industry, will find a global understanding of the techniques as well as references to the most up-to-date works in this area.Table of ContentsForeword 9 Claude GIRAULT Chapter 1. Introduction 17 Serge HADDAD, Fabrice KORDON, Laurent PAUTET and Laure PETRUCCI FIRST PART. FORMAL MODELS FOR DISTRIBUTED SYSTEMS 21 Chapter 2. Introduction to Formal Models 23 Laure PETRUCCI 2.1.Motivation 23 2.2.Semi-formalmodels 24 2.3.Formal models 27 2.4.After specification, verification 35 2.5. Outline of Part I 37 2.6.Bibliography 37 Chapter 3. Specification and Design Approaches 41 Christine CHOPPY and Laure PETRUCCI 3.1. Introduction 41 3.2.Criteria for developing specifications 42 3.3. Specification development methodologies 50 3.4.Conclusion 60 3.5.Bibliography 60 Chapter 4. Modeling Time 63 Béatrice BÉRARD 4.1. Introduction 63 4.2.Semantics of timed models 65 4.3.Classical timed models 68 4.4.Specification of timing requirements 85 4.5.Conclusion 90 4.6.Bibliography 90 Chapter 5. Architecture Description Languages 97 Pascal POIZAT and Thomas VERGNAUD 5.1. Introduction 97 5.2.Concepts 100 5.3.Formal ADLs 109 5.4.ADLs for actual implementation 117 5.5.Conclusion 130 5.6.Bibliography 130 SECOND PART. VERIFICATION TECHNIQUES FOR DISTRIBUTED SYSTEMS 135 Chapter 6. Introduction to Verification 137 Serge HADDAD 6.1. Introduction 137 6.2.Formal models for verification 138 6.3.Expression of properties 141 6.4. Verification methods 144 6.5. Outline of Part 2 151 6.6.Bibliography 151 Chapter 7. Verification of Finite-State Systems 155 Jean-François PRADAT-PEYRE and Yann THIERRY-MIEG 7.1. Introduction 155 7.2. Petri net definition 156 7.3.Structural approaches 158 7.4.Formal verification by model-checking 183 7.5.Classification of model-checking approaches 191 7.6.Decision diagram-based approaches 194 7.7.Partial order reductions 203 7.8. Reductions exploiting symmetry 212 7.9.Conclusion 214 7.10.Bibliography 215 Chapter 8. Verification of Infinite-State Systems 221 Stéphane DEMRI and Denis POITRENAUD 8.1. Introduction 221 8.2. Counter systems 225 8.3.Recursive Petri nets 233 8.4. Presburger arithmetic as symbolic representation 250 8.5.Concludingremarks 263 8.6.Bibliography 263 Chapter 9. Verification of Timed Systems 271 Pierre-Alain REYNIER 9.1. Introduction 271 9.2.Construction of the region graph 273 9.3.Handling infinite abstractions 284 9.4.Robustness issues in timed systems 293 9.5.Conclusion 303 9.6.Bibliography 303 Chapter 10. Distributed Control 307 Claude DUTHEILLET, Isabelle MOUNIER and Nathalie SZNAJDER 10.1. Introduction 307 10.2. Decentralized Control 311 10.3. Controller synthesis for distributed systems 323 10.4. Multi-player games 339 10.5.Conclusion 346 10.6.Bibliography 346 List of Authors 353 Index 355

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Book SynopsisThe critical situation in which our planet finds itself is no longer in doubt. Some things are already collapsing while others are beginning to do so, increasing the possibility of a global catastrophe that would mean the end of the world as we know it. As individuals, we are faced with a daily deluge of bad news about the worsening situation, preparing ourselves to live with years of deep uncertainty about the future of the planet and the species that inhabit it, including our own. How can we cope? How can we project ourselves beyond the present, think bigger and find ways not just to survive the collapse but to live it? In this book, the sequel to How Everything Can Collapse, the authors show that a change of course necessarily requires an inner journey and a radical rethinking of our vision of the world. Together these might enable us to remain standing during the coming storm, to develop a new awareness of ourselves and of the world and to imagine new ways of living in it. Perhaps then it will be possible to regenerate life from the ruins, creating new alliances in differing directions – with ourselves and our inner nature, between humans, with other living beings and with the earth on which we dwell.Trade Review"We need to get serious about living on the Earth. This deceptively simple truism is the starting-point for this utterly radical book by the three founders of “collapsology”. Here they address the question of how to live through an eco-driven societal collapse, laying out a path beyond our civilization’s chronic destructiveness into a more mature autonomy that will be found only in the joining together of interdependence and collapse-readiness. If you want to know what lies beyond survivalism, and how collapse might be navigable as something other than mass death and disaster, read this book!"Rupert Read, author of This Civilisation is Finished

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Book SynopsisIntroduction to Quantum Computing.- Fundamentals of Quantum Mechanics.- Quantum Algorithms.- Quantum Computing Hardware.- Introduction to Quantum AI.- Quantum Data Structures and Encoding.- Quantum Neural Networks.- Quantum Optimization Techniques.- Quantum Communication and Cryptography.- Tools and Platforms for Quantum Computing.- Industry Applications of Quantum Computing.- Future Trends in Quantum AI and Engineering.

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Book SynopsisCommunication and artificial intelligence (AI) are closely related. It is communication – particularly interpersonal conversational interaction – that provides AI with its defining test case and experimental evidence. Likewise, recent developments in AI introduce new challenges and opportunities for communication studies. Technologies such as machine translation of human languages, spoken dialogue systems like Siri, algorithms capable of producing publishable journalistic content, and social robots are all designed to communicate with users in a human-like way. This timely and original textbook provides educators and students with a much-needed resource, connecting the dots between the science of AI and the discipline of communication studies. Clearly outlining the topic's scope, content and future, the text introduces key issues and debates, highlighting the importance and relevance of AI to communication studies. In lively and accessible prose, David Gunkel provides a new generation with the information, knowledge, and skills necessary to working and living in a world where social interaction is no longer restricted to humans. The first work of its kind, An Introduction to Communication and Artificial Intelligence is the go-to textbook for students and scholars getting to grips with this crucial interdisciplinary topic.Trade Review“Gunkel’s book is an accessible but technically savvy monograph introducing students and scholars of communication and computer science to the intersections between AI and communication. … Gunkel’s book will also be a particularly useful resource to instructors, not only due to its accessible language and wide- reaching scope, but also thanks to the five ‘Maker exercises’ included in the last section. These provide useful entry points for students that are not versed in computer programming for experimenting with simple computer programs.”Communication Theory “An introduction to communication and artificial intelligence aims and succeeds in making sense of AI for students and scholars in social sciences.”CommunicationsTable of ContentsPreface Part I: Introduction and Orientation 1 Introduction 2 Communication and AI 3 Basic Concepts and Terminology Part II: Applications 4 Machine Translation 5 Natural Language Processing 6 Computational Creativity 7 Social Robots Part III: Impact and Consequences 8 Social Issues 9 Social Responsibility and Ethics Part IV: Maker Exercises Introduction Exercise 1 – Demystifying ELIZA Exercise 2 – Algorithms Exercise 3 – Machine Translation Exercise 4 – Chatbot and Quasi-Loebner Prize Exercise 5 – Template NLG Notes References Index

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Book SynopsisThis groundbreaking book provides a comprehensive analysis of digital transformation and strategic leadership from both management and technical perspectives. While organizations strive to enhance productivity through digital transformation and emerging technologies like AI, many struggle to understand the requirements for successful implementation. Drawing on decades of industry experience as a technologist and consultant, the book delivers actionable guidance on: -- Developing integrated organizational and digital transformation strategies -- Navigating the challenges and opportunities presented by emerging technologies -- Implementing best practices for sustainable digital transformation -- Maximizing benefits while mitigating potential risks -- Driving business growth and improving profitability through technology adoption Through extensive case studies, the book demonstrates the tangible benefits of effective transformation across various organizational functions. It serves as a practical roadmap for leaders seeking to harness the power of digital technologies while avoiding common pitfalls in the transformation journey.

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Book SynopsisSince its commercialization in 1971, the microprocessor, a modern and integrated form of the central processing unit, has continuously broken records in terms of its integrated functions, computing power, low costs and energy saving status. Today, it is present in almost all electronic devices. Sound knowledge of its internal mechanisms and programming is essential for electronics and computer engineers to understand and master computer operations and advanced programming concepts. This book in five volumes focuses more particularly on the first two generations of microprocessors, those that handle 4- and 8- bit integers. Microprocessor 1 – the first of five volumes – presents the computation function, recalls the memory function and clarifies the concepts of computational models and architecture. A comprehensive approach is used, with examples drawn from current and past technologies that illustrate theoretical concepts, making them accessible.Table of ContentsQuotation vii Preface ix Introduction xiii Chapter 1. The Function of Computation 1 1.1. Beginnings 2 1.2. Classes of computers 10 1.3. Analog approach 36 1.4. Hardware–software relationship 37 1.5. Integration and its limits 43 1.6. Conclusion 47 Chapter 2. The Function of Memory 49 2.1. Definition 50 2.2. Related concepts 56 2.2.1. A story of endianness 56 2.2.2. Alignment 56 2.3. Modeling 57 2.4. Classification 59 2.5. Conclusion 61 Chapter 3. Computation Model and Architecture: Illustration with the von Neumann Approach 63 3.1. Basic concepts 64 3.1.1. The idea of a program 64 3.1.2. Control and data flows and mechanisms 65 3.1.3. Models of computation 67 3.1.4. Architectures 72 3.1.5. The semantic gap 80 3.2. The original von Neumann machine 81 3.2.1. von Neumann’s computation model 81 3.2.2. von Neumann’s (machine) architecture 82 3.2.3. Control 89 3.3. Modern von Neumann machines 90 3.3.1. Abstraction level 91 3.3.2. Base execution outline 97 3.3.3. Possible transfers 100 3.3.4. Summary: advantages and disadvantages of this model 102 3.4. Variations on a theme 104 3.4.1. Classification by bus 104 3.4.2. Harvard architectures 111 3.4.3. Parallelism 113 3.5. Instruction set architecture 117 3.5.1. Storage components 118 3.5.2. Data format and type 126 3.5.3. Instruction set 126 3.5.4. Memory model 127 3.5.5. Execution modes 128 3.5.6. Miscellaneous 128 3.6. Basic definitions for this book 128 3.7. Conclusion 129 Conclusion of Volume 1 131 Exercises 133 Acronyms 135 References 153 Index 173

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Book SynopsisThis book provides students with the skills to develop their own models for application in conservation biology and wildlife management. Assuming no special mathematical expertise, the computational models used are kept simple and show how to develop models in both spreadsheet and programming language format. Develops thought-provoking applications which emphasize the value of modeling as a learning tool Examines basic descriptive equations, matrix representations, consumer-resources interactions, applications in simulation, scenarios, harvesting, population viability, metapopulation dynamics, disease outbreaks, vegetation stage and state dynamics, habitat suitability assessment, and model selection statistics Includes a wide range of examples relating to birds, fish, plants and large African mammals Trade Review"This is consequently very much a hands-on work and ideal as a basic manual for a course on the topic. At the same time, it will be of value to conservationists who wish to understand the basis of some modeling approach they find in a paper directly pertinent to their particular interests." (Biodivers Conserv, 2011) An easy approach to modelling." (Mammalia, April 2009) "This is a very interesting text. ... The focus on method and theory as well as programming means that the text encourages the reader to question even basic assumptions." (Ecological and Environmental Education)Table of ContentsPreface. 1 Introduction: why learn modeling?. 1.1 Introduction. 1.2 Structure of the book. 1.3 Supporting computer software. Recommended supporting reading. Supporting file on the CD. 2 A starting problem: conservation of the dodo. 2.1 Introduction. 2.2 Conservation of the dodo. 3 Descriptive models: choosing an equation. 3.1 Introduction. 3.2 Dynamic equations. 3.3 Geometric and exponential growth. 3.4 Adding a population ceiling. 3.5 Basic density-dependent models. 3.6 Curvilinear density dependence. 3.7 Delayed density dependence. 3.8 Depensation or Allee effect. 3.9 Incorporating environmental variability. 3.10 Overview. Recommended supporting reading. Programs on the accompanying CD. Exercises. 4 Structured population models: age, size, or stage. 4.1 Introduction. 4.2 Age-structured models. 4.3 Stage-structured models. 4.4 Projection versus prediction. 4.5 Overview. Recommended supporting reading. Programs on the accompanying CD. Exercises. 5 Consumer–resource models: population interactions. 5.1 Introduction. 5.2 Coupling population equations. 5.3 Simple interactive model. 5.4 Incorporating competitive interference. 5.5 Ratio-dependent intake response and time frames. 5.6 Accommodating environmental variability. 5.7 Overview. Recommended supporting reading. Programs on the accompanying CD. Exercises. 6 Simulation models: assessing understanding. 6.1 Introduction. 6.2 Adding density dependence to an age-structured model. 6.3 Aspecific example: the kudu model. 6.4 Simplification for management. 6.5 Generalizing the model for other species. 6.6 Overview. Recommended supporting reading. Programs on the accompanying CD. Exercises. 7 Harvesting models: adaptive management. 7.1 Introduction. 7.2 Principles of “maximum sustained yield”. 7.3 Surplus production model accommodating environmental variability. 7.4 Stock-recruitment model. 7.5 Policies for setting the harvest quota. 7.6 Adaptive management responses. 7.7 Stock-recruitment models for fish populations. 7.8 Overview. Recommended supporting reading. Programs on the accompanying CD. Exercises. 8 Population viability models: risk analysis. 8.1 Introduction. 8.2 Demographic stochasticity. 8.3 Environmental variability and catastrophes. 8.4 Genetic stochasticity. 8.5 Population viability models. 8.6 Overview. Recommended supporting reading. Programs on the accompanying CD. Exercises. 9 Metapopulation models: spreading the risk. 9.1 Introduction. 9.2 Basic patch incidence model. 9.3 Correlated migration and extinction. 9.4 Variable patch size and spacing. 9.5 Source and sink populations. 9.6 Mainland–island habitats. 9.7 Examples of vertebrate metapopulations. 9.8 Overview. Recommended supporting reading. Exercises. 10 Modeling infectious diseases: outbreak dynamics. 10.1 Introduction. 10.2 Basic infection model. 10.3 Cyclic outbreak dynamics: measles. 10.4 Slowly spreading sexually transmitted disease: HIV–AIDS. 10.5 Controlling the spread of wildlife diseases. 10.6 Overview. Recommended supporting reading. Exercises. 11 Scenario models: exploring options. 11.1 Introduction. 11.2 Background situation. 11.3 Theoretical concepts. 11.4 Modeling the white rhino–grassland system. 11.5 Exploring management options. 11.6 Overview. Recommended supporting reading. Program on the accompanying CD. Exercises. 12 Vegetation models: biomass to gap dynamics. 12.1 Introduction. 12.2 Seasonal biomass dynamics of vegetation supporting herbivores. 12.3 Size-structured dynamics of a tree population. 12.4 Gap dynamics model. 12.5 Overview. Recommended supporting reading. Programs on the accompanying CD. Exercises. 13 State transition models: habitat patch dynamics. 13.1 Introduction. 13.2 Vegetation successional dynamics. 13.3 Managing savanna vegetation for livestock. 13.4 Spatially explicit grid model. 13.5 Overview. Recommended supporting reading. Programs on the accompanying CD. Exercises. 14 Habitat suitability models: adaptive behavior. 14.1 Introduction. 14.2 Shifting habitat use by overwintering geese. 14.3 Habitat suitability for a browsing antelope from vegetation composition. 14.4 General principles. 14.5 Overview. Recommended supporting reading. Programs on the accompanying CD. Exercises. 15 Reconciling models with data: statistical diagnosis. 15.1 Introduction. 15.2 Model selection statistics. 15.3 Diagnosing the causes of antelope population declines. 15.4 Overview. Recommended supporting reading. Programs on the accompanying CD. Exercise. Appendices. References. Index

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Book SynopsisUnderstand and apply the design patterns outlined in this book to design, develop, and deploy scalable AI solutions that meet your organization's needs and drive innovation in the era of intelligent automation. This book begins with an overview of scalable AI systems and the importance of design patterns in creating robust intelligent solutions. It covers fundamental concepts and techniques for achieving scalability in AI systems, including data engineering practices and strategies. The book also addresses scalable algorithms, models, infrastructure, and architecture considerations. Additionally, it discusses deployment, productionization, real-time and streaming data, edge computing, governance, and ethics in scalable AI. Real-world case studies and best practices are presented, along with insights into future trends and emerging technologies. The book focuses on scalable AI and design patterns, providing an understanding of the challenges involved in developing AI systems that can handle large amounts of data, complex algorithms, and real-time processing. By exploring scalability, you will be empowered to design and implement AI solutions that can adapt to changing data requirements. What You Will LearnDevelop scalable AI systems that can handle large volumes of data, complex algorithms, and real-time processingKnow the significance of design patterns in creating robust intelligent solutionsUnderstand scalable algorithms and models to handle extensive data and computing requirements and build scalable AI systemsBe aware of the ethical implications of scalable AI systemsWho This Book Is ForAI practitioners, data scientists, and software engineers with intermediate-level AI knowledge and experience

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Book SynopsisGeomedia offers critical analysis of the new possibilities and power relations emerging in the public space of contemporary cities. As ubiquitous digital networks enable embedded and mobile devices to integrate place-specific data with real-time feedback circuits, everyday experience of public space has become subject to new demands.Trade Review"This book is a reflexive navigation of the changing meanings and uses of public space at times of intense mediation. Through the concept of geomedia, McQuire skilfully brings the media back to the city and to the public space where sociality and politics are negotiated and contested." Myria Georgiou, London School of Economics and Political Science "Scott McGuire�s scholarly tour takes the reader from mimesis to urban screens, from the magic of the street to global interpersonal civics. His creative insights are rooted in an impressively diversified body of work from communication, urban, and architectural theorists. GeoMedia is an absolute primer in urban communication." Gary Gumpert, Queens College of the City University of New YorkTable of ContentsContents00 Introduction01 Transforming Media and Public Space02 Googling the City03 Participatory Public Space04 Urban Screens and Urban Media Events05 Recomposing Public SpaceNotesReferencesIndex

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Book SynopsisUnderstanding Minimalist Syntax introduces the logic of the Minimalist Program by analyzing well-known descriptive generalizations about long-distance dependencies. An introduction to the logic of the minimalist program - arguably the most important branch of syntax Proposes a new theory of how long-distance dependencies are formed, with implications for theories of locality, and the minimalist program as a whole Introduces the logic of the minimalist program by analyzing well-known descriptive generalizations about long-distance dependencies, and asks why they should be true of natural languages Rich in empirical coverage, which will be welcomed by experts in the field, yet accessible enough for students looking for an introduction to the minimalist program. Trade Review“In the space of just 150 pages Boeckx provides an accessible and assured introduction to minimalism; a terrific critical review of the evidence for cyclic movement; a sympathetic yet powerful critique of phase theory; and a new approach to the cycle based on an intuitively natural version of Least Effort. This really is a tour de force and can be read profitably by expert and neophyte alike.” Norbert Hornstein, University of Maryland “The book investigates the venerable topic of successive cyclic movement in order to shed light on the nature of the minimalist program. It is a truly impressive achievement which draws important conclusions regarding the most fundamental issues of the minimalist program and puts back the phenomenon of successive cyclic movement in the center of syntactic theorizing. It should have a strong impact on the field.” Željko Bošković, University of Connecticut “This is a concise study of how locality and anti-locality effects can be handled within minimalism: it is up-to-date, thought-provoking and full of insightful and original ideas – ideal for use as a ‘specialist topic’ on an advanced syntax course.” Andrew Radford, University of EssexTable of ContentsAcknowledgments xi 1 Introductory Remarks 1 1.1 The Framework 1 1.2 Outline of the Book: Goals and Structure 4 2 The Marks of Successive Cyclicity (The What-Question) 9 2.1 Subjacency and the Emergence of Successive Cyclicity 9 2.2 The Evidence 11 2.2.1 Syntax 11 2.2.2 Morphology 14 2.2.3 Phonology 22 2.2.4 Semantics 23 2.2.5 Morpho-syntactic evidence from overtly stranded pieces 26 2.3 A-movement 29 2.4 Conclusion 34 3 The Distribution of Intermediate Landing Sites (The Where-Question) 39 3.1 Punctuated vs. Uniform Paths 40 3.2 The Difficulties Faced by Punctuated Path Hypotheses 43 3.2.1 Phases: an overview 44 3.2.2 Conceptual arguments for phases 46 3.2.3 Arguments against phases 48 3.2.4 Old problems for phases 50 3.2.5 No empirical argument for phases 54 3.3 Conclusion 61 4 The Timing of Intermediate Steps of Movement (The When-Question) 64 4.1 Early vs. Late Successive Cyclicity 64 4.2 Takahashi (1994) 66 4.3 The Evidence for Early Successive Cyclic Movement 70 4.3.1 Background information on applicatives 71 4.3.2 The need for early successive cyclic movement 76 4.4 Potential Arguments for Late Successive Cyclic Movement 80 4.4.1 Sub-extraction out of a moved element 80 4.4.2 Intervening traces 82 4.4.3 Object agreement 83 4.5 Conclusion 86 5 The Motivation for Intermediate Movement Steps (The Why-Question) 90 5.1 Last Resort 90 5.2 Problematic Cases 91 5.2.1 Concord 91 5.2.2 Successive cyclicity 92 5.3 Anti-locality 101 5.4 Anti-locality and Successive Cyclicity 106 5.5 Anti-locality and Last Resort 110 5.6 The Why-Question 113 5.7 Conclusion 117 6 Alternative Views on Successive Cyclicity 119 6.1 TAG-based Accounts 119 6.2 An Agreement-based Account 125 6.3 Prolific Domains 129 6.4 Greed-based Approaches 129 6.5 Conclusion 132 7 Successive Cyclicity and Other Aspects of Locality 133 7.1 The Standard View on Islands 134 7.2 Puzzles for the Standard View 136 7.2.1 Movement, freezing, and escape hatch 136 7.2.2 Island by default? 137 7.2.3 Island-obviation 137 7.3 Ross’s View 145 7.4 Agreement and Islandhood 145 7.5 Conclusion 148 8 Concluding Remarks 150 References 152 Index 167

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Book SynopsisIn Steiner-Waldorf schools around the world, painting is an essential part of the curriculum from the kindergarten through to Class 12 (3-18 years). Digesting history, geography, maths and the sciences through artistic work helps children to deepen comprehension and make the key aspects of everything learned more memorable.Van James has captured in this book his years of Waldorf teaching experience to help students to build artistic skills. Engagement with colour, as well as the opportunity for self-expression, enhance a student's self-confidence and capacities for self-expression. This valuable resource offers teachers step-by-step approaches to help build their students' artistic confidence. This inspiring resource will be a valuable addition to Steiner-Waldorf teachers' shelves.

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Book SynopsisMathematical morphology has developed a powerful methodology for segmenting images, based on connected filters and watersheds. We have chosen the abstract framework of node- or edge-weighted graphs for an extensive mathematical and algorithmic description of these tools. Volume 1 is devoted to watersheds. The topography of a graph appears by observing the evolution of a drop of water moving from node to node on a weighted graph, along flowing paths, until it reaches regional minima. The upstream nodes of a regional minimum constitute its catchment zone. The catchment zones may be constructed independently of each other and locally, in contrast with the traditional approach where the catchment basins have to be constructed all at the same time. Catchment zones may overlap, and thus, a new segmentation paradigm is proposed in which catchment zones cover each other according to a priority order. The resulting partition may then be corrected, by local and parallel treatments, in order to achieve the desired precision. Table of ContentsNotations xiii Introduction xxvii Part 1. Getting Started 1 Chapter 1. A Primer to Flooding, Razing and Watersheds 3 1.1. Topographic reliefs and topographic features 3 1.1.1. Images seen as topographic reliefs and inversely 3 1.1.2. Topographic features 5 1.1.3. Modeling a topographic relief as a weighted graph 8 1.2. Flooding, razing and morphological filters 10 1.2.1. The principle of duality 10 1.2.2. Dominated flooding and razing 10 1.2.3. Flooding, razing and catchment zones of a topographic relief 16 1.3. Catchment zones of flooded surfaces 18 1.3.1. Filtering and segmenting 18 1.3.2. Reducing the oversegmentation with markers 19 1.4. The waterfall hierarchy 26 1.4.1. Overflows between catchment basins 26 1.5. Size-driven hierarchies 28 1.6. Separating overlapping particles in n dimensions 31 1.7. Catchment zones and lakes of region neighborhood graphs 33 1.8. Conclusion 37 Chapter 2. Watersheds and Flooding: a Segmentation Golden Braid 39 2.1. Watersheds, offsprings and parallel branches 40 2.2. Flooding and connected operators 43 2.3. Connected operators and hierarchies 45 2.4. Hierarchical segmentation: extinction values 47 Chapter 3. Mathematical Notions 49 3.1. Summary of the chapter 49 3.2. Complete lattices 49 3.2.1. Partial order and partially ordered sets 49 3.2.2. Upper and lower bounds 50 3.2.3. Complete lattices 50 3.2.4. Dyadic relations on a complete lattice 51 3.3. Operators between complete lattices 51 3.3.1. Definition of an operator 51 3.3.2. Properties of the operators 52 3.3.3. Erosion and dilation 52 3.3.4. Opening and closing 53 3.4. The adjunction: a cornerstone of mathematical morphology 53 3.4.1. Adjoint erosions and dilations 53 3.4.2. Increasingness 53 3.4.3. Unicity 53 3.4.4. Composition 54 3.4.5. Dual operators 54 3.5. Openings and closings 54 3.5.1. Definitions 54 3.5.2. Elements with the same erosion or the same dilation 55 3.5.3. The invariants of an opening or a closing 55 3.6. Complete lattices of functions 55 3.6.1. Definitions 55 3.6.2. Infimum and supremum 56 Part 2. The Topography of Weighted Graphs 57 Chapter 4. Weighted Graphs 59 4.1. Summary of the chapter 59 4.2. Reminders on graphs 60 4.2.1. Directed and undirected graphs 60 4.3. Weight distributions on the nodes or edges of a graph 62 4.3.1. Duality 63 4.3.2. Erosions and dilations, openings, closings 63 4.3.3. Labels 66 4.4. Exploring the topography of graphs by following a drop of water 66 4.5. Node-weighted graphs 67 4.5.1. Flat zones and regional minima 67 4.5.2. Flowing paths and catchment zones 67 4.6. Edge-weighted graphs 69 4.6.1. Flat zones and regional minima 69 4.6.2. Flowing paths and catchment zones 69 4.6.3. Even zones and regional minima 71 4.7. Comparing the topography of node-weighted graphs and edge-weighted graphs 72 Chapter 5. Flowing Graphs 73 5.1. Summary of the chapter 73 5.2. Towards a convergence between node- and edge-weighted graphs 74 5.2.1. The flowing edges in a node-weighted graph G(ν, nil) 74 5.2.2. The flowing edges in an edge-weighted graph G(nil, η) 75 5.2.3. Flowing graphs 76 5.3. The flowing adjunction 76 5.4. Flowing edges under closer scrutiny 77 5.4.1. Relations between the flowing edges of G(ν, nil) and G(nil, δenν) 77 5.4.2. Relations between the flowing edges of G(nil, η) and G(εneη, nil) 78 5.4.3. Chaining the inclusions between flowing edges 78 5.4.4. Criteria characterizing flowing graphs 79 5.4.5. Transforming a node- or edge-weighted graph into a flowing graph 81 5.4.6. The invariance domains of γe and ϕn 83 5.4.7. Particular flowing graphs 87 5.5. Illustration as a hydrographic model 88 5.5.1. A hydrographic model of tanks and pipes 88 5.5.2. Associating an “edge unstable” tank network with an arbitrary node-weighted graph G(ν, nil) 90 5.5.3. Associating a “node unstable” tank network with an arbitrary edge-weighted graph G(nil, η) 91 5.5.4. Chaining the operations 92 Chapter 6. The Topography of Digraphs 97 6.1. Summary of the chapter 97 6.1.1. General digraphs 98 6.1.2. Digraphs without perpetuum mobile configurations 98 6.2. Status report 98 6.2.1. Case of node-weighted graphs 99 6.2.2. Case of edge-weighted graphs 99 6.3. The topography of unweighted digraphs 100 6.3.1. Notations 100 6.3.2. Smooth zones, dead ends, flat zones and black holes of digraphs 101 6.4. The topography of gravitational digraphs 105 6.4.1. No “perpetuum mobile” 105 6.4.2. Defining and propagating labels 107 6.4.3. A dead leaves model of catchment zones 113 6.4.4. Examples of gravitational graphs 122 6.4.5. The topography of weighted graphs interpreted in the light of the derived digraphs 122 Part 3. Reducing the Overlapping of Catchment Zones 125 Chapter 7. Measuring the Steepness of Flowing Paths 127 7.1. Summary of the chapter 127 7.2. Why do the catchment zones overlap? 128 7.2.1. Relation between the catchment zones and the flowing paths 128 7.2.2. Comparing the steepness of flowing paths 128 7.2.3. The redundancy between node and edge weights 129 7.2.4. General flow digraphs 130 7.3. The lexicographic pre-order relation of length k 131 7.3.1. Prolonging flowing paths into paths of infinite length 131 7.3.2. Comparing the steepness of two flowing paths 132 7.3.3. Properties of ∞ − steep paths 134 Chapter 8. Pruning a Flow Digraph 137 8.1. Summary of the chapter 137 8.1.1. Transforming a node- or edge-weighted graph into a node-weighted flowing digraph (reminder) 137 8.1.2. Global pruning 138 8.1.3. Local pruning 138 8.2. The pruning operator 138 8.2.1. Two operators on flow digraphs 139 8.2.2. Pruning by concatenating both operators 140 8.2.3. Properties of pruning 142 8.2.4. A variant of pruning 146 8.2.5. Local pruning 8.3. Evolution of catchment zones with pruning 147 8.3.1. Analyzing a digital elevation model 148 Chapter 9. Constructing an ∞ - steep Digraph by Flooding 155 9.1. Summary of the chapter 155 9.2. Characterization of ∞ − steep graphs 156 9.3. The core-expanding flooding algorithm 156 9.3.1. The first version of the core-expanding algorithm 157 9.3.2. The second version of the core-expanding algorithm 160 9.3.3. The third version of the core-expanding algorithm 164 9.3.4. The last version of the core-expanding algorithm, constructing a partial ∞ − steep flowing graph 167 Chapter 10. Creating Steep Watershed Partitions 169 10.1. Summary of the chapter 169 10.2. Creating watershed partitions with the core-expanding algorithm 169 10.2.1. Illustration of the HQ algorithm applied to node-weighted graphs 171 10.3. Propagating labels while pruning the digraph 172 10.3.1. Constructing a watershed partition during pruning 173 10.4. Pruning or flooding: two ways for catchment zones to grow 176 Chapter 11. An Historical Intermezzo 179 11.1. Watersheds: the early days 179 11.1.1. The level-by-level construction of watersheds 180 11.1.2. A hierarchical queue watershed algorithm 181 11.2. A watershed as the SKIZ for the topographic distance 181 11.2.1. The topographic distance 181 11.3. Convergence into a unique algorithm of three research streams 182 11.3.1. Three formulations of watershed partitions, one algorithm 182 11.3.2. Discussion 183 Part 4. Segmenting with Dead Leaves Partitions 185 Chapter 12. Intermezzo: Encoding the Digraph Associated with an Image 187 12.1. Summary of the theoretical developments seen so far 187 12.2. Summary of the chapter 188 12.3. Representing a node-weighted digraph as two images 188 12.3.1. The encoding of the digraph associated with an image 188 12.3.2. Operators acting on node-weighted digraphs 190 12.4. Defining labels 192 12.4.1. Operators on unweighted unlabeled digraphs 193 12.4.2. Operators on labeled unweighted digraphs 194 12.4.3. Operators on weighted and labeled digraphs 198 Chapter 13. Two Paradigms for Creating a Partition or a Partial Partition on a Graph 203 13.1. Summary of the chapter 203 13.2. Setting up a common stage for node- and edge-weighted graphs 203 13.3. A brief tool inventory 204 13.3.1. Operators making no use of the node weights 204 13.3.2. Operators propagating labels 204 13.3.3. Operators making use of the node weights and the graph structure 205 13.4. Dead leaves tessellations versus tilings: two paradigms 205 13.5. Extracting catchment zones containing a particular node 206 13.5.1. Core expansion versus pruning algorithms 206 13.5.2. Illustration of the pruning algorithm 207 13.6. Catchment zones versus catchment basins 209 Chapter 14. Dead Leaves Segmentation 211 14.1. Summary of the chapter 211 14.2. Segmenting with a watershed 211 14.2.1. Segmenting with watershed partitions 211 14.2.2. A crossroad of several methods 213 14.3. The evolution of a dead leaves tessellation with pruning 214 14.4. Local correction of overlapping zones 217 14.4.1. Pruning analysis 217 14.4.2. Local pruning for reducing overlapping zones 219 14.4.3. A local core-expanding algorithm for reducing overlapping zones 221 14.5. Local correction of the overlapping zones on a DEM 221 14.5.1. Local core-expanding algorithm for reducing overlapping zones 225 14.5.2. Advantage of the two-step construction of a dead leaves tessellation 227 14.6. Segmentation of some marked regions 231 14.6.1. Segmenting the domain and extracting the objects of interest 232 14.6.2. Extraction of the marked catchment zones and local correction of errors 233 Chapter 15. Propagating Segmentations 241 15.1. Summary of the chapter 241 15.2. Step-by-step segmentation 241 15.2.1. Principle of the method 241 15.2.2. Segmentation of blood cells 242 15.2.3. Segmentation of an electronic circuit 243 15.3. Marker-based segmentation 245 Appendix 247 References 259 Index 267

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Book SynopsisChoosing and Using Statistics remains an invaluable guide for students using a computer package to analyse data from research projects and practical class work. The text takes a pragmatic approach to statistics with a strong focus on what is actually needed. There are chapters giving useful advice on the basics of statistics and guidance on the presentation of data. The book is built around a key to selecting the correct statistical test and then gives clear guidance on how to carry out the test and interpret the output from four commonly used computer packages: SPSS, Minitab, Excel, and (new to this edition) the free program, R. Only the basics of formal statistics are described and the emphasis is on jargon-free English but any unfamiliar words can be looked up in the extensive glossary. This new 3rd edition of Choosing and Using Statistics is a must for all students who use a computer package to apply statistics in practical and project work. Features neTrade Review"Written in a concise and direct style, this book presents a selection of some of the most widely used statistical tests and data exploration techniques." (Biological Conservation, 1 March 2012) "Written in a concise and direct style, this book presents a selection of some of the most widely used statistical tests and data exploration techniques ... In general, this book is a very good primer for students with no statistical expertise." (Biological Conservation Reviews, 2011) "This book makes everything so easy. Complicated tests are effortlessly condensed, and the instructions are almost too easy to follow. Diagrams and sample data sets are used frequently so you can practise using tests before applying them to your own data sets, whilst the logical layout guides you toward the correct test for both your data, and what you want to prove (or disprove)." (Animals & Men, February 2011)Table of ContentsPreface xiii The third edition xiv How to use this book xiv Packages used xv Example data xv Acknowledgements for the first edition xv Acknowledgements for the second edition xv Acknowledgements for the third edition xvi 1 Eight steps to successful data analysis 1 2 The basics 2 Observations 2 Hypothesis testing 2 P-values 3 Sampling 3 Experiments 4 Statistics 4 Descriptive statistics 5 Tests of difference 5 Tests of relationships 5 Tests for data investigation 6 3 Choosing a test: a key 7 Remember: eight steps to successful data analysis 7 The art of choosing a test 7 A key to assist in your choice of statistical test 8 4 Hypothesis testing, sampling and experimental design 23 Hypothesis testing 23 Acceptable errors 23 P-values 24 Sampling 25 Choice of sample unit 25 Number of sample units 26 Positioning of sample units to achieve a random sample 26 Timing of sampling 27 Experimental design 27 Control 28 Procedural controls 28 Temporal control 28 Experimental control 29 Statistical control 29 Some standard experimental designs 29 5 Statistics, variables and distributions 32 What are statistics? 32 Types of statistics 33 Descriptive statistics 33 Parametric statistics 33 Non-parametric statistics 33 What is a variable? 33 Types of variables or scales of measurement 34 Measurement variables 34 Continuous variables 34 Discrete variables 35 How accurate do I need to be? 35 Ranked variables 35 Attributes 35 Derived variables 36 Types of distribution 36 Discrete distributions 36 The Poisson distribution 36 The binomial distribution 37 The negative binomial distribution 39 The hypergeometric distribution 39 Continuous distributions 40 The rectangular distribution 40 The normal distribution 40 The standardized normal distribution 40 Convergence of a Poisson distribution to a normal distribution 41 Sampling distributions and the 'central limit theorem' 41 Describing the normal distribution further 41 Skewness 41 Kurtosis 43 Is a distribution normal? 43 Transformations 43 An example 44 The angular transformation 44 The logit transformation 45 The t-distribution 46 Confidence intervals 47 The chi-square distribution 47 The exponential distribution 47 Non-parametric 'distributions' 48 Ranking, quartiles and the interquartile range 48 Box and whisker plots 48 6 Descriptive and presentational techniques 49 General advice 49 Displaying data: summarizing a single variable 49 Box and whisker plot (box plot) 49 Displaying data: showing the distribution of a single variable 50 Bar chart: for discrete data 50 Histogram: for continuous data 51 Pie chart: for categorical data or attribute data 52 Descriptive statistics 52 Statistics of location or position 52 Arithmetic mean 53 Geometric mean 53 Harmonic mean 53 Median 53 Mode 53 Statistics of distribution, dispersion or spread 55 Range 55 Interquartile range 55 Variance 55 Standard deviation (SD) 55 Standard error (SE) 56 Confidence intervals (CI) or confidence limits 56 Coefficient of variation 56 Other summary statistics 56 Skewness 57 Kurtosis 57 Using the computer packages 57 General 57 Displaying data: summarizing two or more variables 62 Box and whisker plots (box plots) 62 Error bars and confidence intervals 63 Displaying data: comparing two variables 63 Associations 63 Scatterplots 64 Multiple scatterplots 64 Trends, predictions and time series 65 Lines 65 Fitted lines 67 Confidence intervals 67 Displaying data: comparing more than two variables 68 Associations 68 Three-dimensional scatterplots 68 Multiple trends, time series and predictions 69 Multiple fitted lines 69 Surfaces 70 7 The tests 1: tests to look at differences 72 Do frequency distributions differ? 72 Questions 72 G-test 72 An example 73 Chi-square test 75 An example 76 Kolmogorov–Smirnov test 86 An example 87 Anderson–Darling test 89 Shapiro–Wilk test 90 Graphical tests for normality 90 Do the observations from two groups differ? 92 Paired data 92 Paired t-test 92 Wilcoxon signed ranks test 96 Sign test 99 Unpaired data 103 t-test 103 One-way ANOVA 111 Mann–Whitney U 119 Do the observations from more than two groups differ? 123 Repeated measures 123 Friedman test (for repeated measures) 123 Repeated-measures ANOVA 127 Independent samples 128 One-way ANOVA 129 Post hoc testing: after one-way ANOVA 138 Kruskal–Wallis test 142 Post hoc testing: after the Kruskal–Wallis test 145 There are two independent ways of classifying the data 145 One observation for each factor combination (no replication) 146 Friedman test 146 Two-way ANOVA (without replication) 152 More than one observation for each factor combination (with replication) 160 Interaction 160 Two-way ANOVA (with replication) 163 An example 164 Scheirer–Ray–Hare test 175 An example 175 There are more than two independent ways to classify the data 182 Multifactorial testing 182 Three-way ANOVA (without replication) 183 Three-way ANOVA (with replication) 184 An example 184 Multiway ANOVA 191 Not all classifications are independent 192 Non-independent factors 192 Nested factors 192 Random or fixed factors 193 Nested or hierarchical designs 193 Two-level nested-design ANOVA 193 An example 193 8 The tests 2: tests to look at relationships 199 Is there a correlation or association between two variables? 199 Observations assigned to categories 199 Chi-square test of association 199 An example 200 Cramér coefficient of association 208 Phi coefficient of association 209 Observations assigned a value 209 'Standard' correlation (Pearson's product-moment correlation) 210 An example 210 Spearman's rank-order correlation 214 An example 215 Kendall rank-order correlation 218 An example 218 Regression 219 An example 220 Is there a cause-and-effect relationship between two variables? 220 Questions 220 'Standard' linear regression 221 Prediction 221 Interpreting r2 222 Comparison of regression and correlation 222 Residuals 222 Confidence intervals 222 Prediction interval 223 An example 223 Kendall robust line-fit method 230 Logistic regression 230 An example 231 Model II regression 235 Polynomial, cubic and quadratic regression 235 Tests for more than two variables 236 Tests of association 236 Questions 236 Correlation 236 Partial correlation 237 Kendall partial rank-order correlation 237 Cause(s) and effect(s) 237 Questions 237 Regression 237 Analysis of covariance (ANCOVA) 238 Multiple regression 242 Stepwise regression 242 Path analysis 243 9 The tests 3: tests for data exploration 244 Types of data 244 Observation, inspection and plotting 244 Principal component analysis (PCA) and factor analysis 244 An example 245 Canonical variate analysis 251 Discriminant function analysis 251 An example 251 Multivariate analysis of variance (MANOVA) 256 An example 256 Multivariate analysis of covariance (MANCOVA) 259 Cluster analysis 259 DECORANA and TWINSPAN 263 Symbols and letters used in statistics 264 Greek letters 264 Symbols 264 Upper-case letters 265 Lower-case letters 266 Glossary 267 Assumptions of the tests 282 What if the assumptions are violated? 284 Hints and tips 285 Using a computer 285 Sampling 286 Statistics 286 Displaying the data 287 A table of statistical tests 289 Index 291

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Book SynopsisPRINCIPLES OF MODERN DIGITAL DESIGN FROM UNDERLYING PRINCIPLES TO IMPLEMENTATIONA THOROUGH INTRODUCTION TO DIGITAL LOGIC DESIGN With this book, readers discover the connection between logic design principles and theory and the logic design and optimization techniques used in practice. Therefore, they not only learn how to implement current design techniques, but also how these techniques were developed and why they work. With a deeper understanding of the underlying principles, readers become better problem-solvers when faced with new and difficult digital design challenges. Principles of Modern Digital Design begins with an examination of number systems and binary code followed by the fundamental concepts of digital logic. Next, readers advance to combinational logic design. Armed with this foundation, they are then introduced to VHDL, a powerful language used to describe the function of digital circuits and systems. All the major topics needed for a thorough undersTable of Contents1. Number Systems and Binary Codes. 2. Fundamental Concepts of Digital Logic. 3. Combinational Logic Design. 4. Fundamentals of Synchronous Sequential Circuits. 5. VHDL in Digital Design. 6. Combinational Logic Design using VHDL. 7. Synchronous Sequential Circuit Design. 8. Counter Design. 9. Sequential Circuit Design using VHDL. 10. Asynchronous Sequential Circuits. Appendix A. CMOS Logic. Index.

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Book SynopsisSchofield & Sims Grammar and Punctuation is a comprehensive programme for teaching grammar and punctuation while also building on vocabulary, reading and writing skills. The Grammar 5 Teacher's Guide supports the explicit teaching of grammar and punctuation through structured lessons, stimulating focus texts and easy-to-use assessment.

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Book SynopsisData analysis as an area of importance has grown exponentially, especially during the past couple of decades. This can be attributed to a rapidly growing computer industry and the wide applicability of computational techniques, in conjunction with new advances of analytic tools. This being the case, the need for literature that addresses this is self-evident. New publications are appearing, covering the need for information from all fields of science and engineering, thanks to the universal relevance of data analysis and statistics packages. This book is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians who have been working at the forefront of data analysis. The chapters included in this volume represent a cross-section of current concerns and research interests in these scientific areas. The material is divided into two parts: Computational Data Analysis, and Classification Data Analysis, with methods for both - providing the reader with both theoretical and applied information on data analysis methods, models and techniques and appropriate applications.Table of ContentsPart 1. Computational Data Analysis and Methods 1. Semi-supervised Learning Based on Distributionally Robust Optimization, Jose Blanchet and Yang Kang. 2. Updating of PageRank in Evolving Treegraphs, Benard Abola, Pitos Seleka Biganda, Christopher Engstörm, John Magero Mango, Godwin Kakuba and Sergei Silvestrov. 3. Exploring The Relationship Between Ordinary PageRank, Lazy PageRank and Random Walk with Backstep PageRank for Different Graph Structures, Pitos Seleka Biganda, Benard Abola, Christopher Engstörm, John Magero Mango, Godwin Kakuba and Sergei Silvestrov. 4. On the Behavior of Alternative Splitting Criteria for CUB Model-based Trees, Carmela Cappelli, Rosaria Simone and Francesca Di Iorio. 5. Investigation on Life Satisfaction Through (Stratified) Chain Regression Graph Models, Federica Nicolussi and Manuela Cazzaro. Part 2. Classification Data Analysis and Methods 6. Selection of Proximity Measures for a Topological Correspondence Analysis, Rafik Abdelssam. 7. Support Vector Machines: A Review and Applications in Statistical Process Monitoring, Anastasios Apsemidis and Stelios Psarakis. 8. Binary Classification Techniques: An Application on Simulated and Real Bio-medical Data, Fragkiskos G. Bersimis, Iraklis Varlamis, Malvina Vamvakari and Demosthenes B. Panagiotakos. 9. Some Properties of the Multivariate Generalized Hyperbolic Models, Stergios B. Fotopoulos, Venkata K. Jandhyala and Alex Paparas. 10. On Determining the Value of Online Customer Satisfaction Ratings – A Case-based Appraisal, Jim Freeman. 11. Projection Clustering Unfolding: A New Algorithm for Clustering Individuals or Items in a Preference Matrix, Mariangela Sciandra, Antonio D�Ambrosio and Antonella Plaia.

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Book SynopsisIntroduces basic concepts in probability and statistics to data science students, as well as engineers and scientists Aimed at undergraduate/graduate-level engineering and natural science students, this timely, fully updated edition of a popular book on statistics and probability shows how real-world problems can be solved using statistical concepts. It removes Excel exhibits and replaces them with R software throughout, and updates both MINITAB and JMP software instructions and content. A new chapter discussing data miningincluding big data, classification, machine learning, and visualizationis featured. Another new chapter covers cluster analysis methodologies in hierarchical, nonhierarchical, and model based clustering. The book also offers a chapter on Response Surfaces that previously appeared on the book's companion website. Statistics and Probability with Applications for Engineers and Scientists using MINITAB, R and JMP, Second Edition is broken iTable of ContentsPreface xvii Acknowledgments xxi About The Companion Site xxiii 1 Introduction 1 1.1 Designed Experiment 2 1.1.1 Motivation for the Study 2 1.1.2 Investigation 3 1.1.3 Changing Criteria 3 1.1.4 A Summary of the Various Phases of the Investigation 5 1.2 A Survey 6 1.3 An Observational Study 6 1.4 A Set of Historical Data 7 1.5 A Brief Description of What is Covered in this Book 7 Part I Fundamentals of Probability and Statistics 2 Describing Data Graphically and Numerically 13 2.1 Getting Started with Statistics 14 2.1.1 What is Statistics? 14 2.1.2 Population and Sample in a Statistical Study 14 2.2 Classification of Various Types of Data 18 2.2.1 Nominal Data 18 2.2.2 Ordinal Data 19 2.2.3 Interval Data 19 2.2.4 Ratio Data 19 2.3 Frequency Distribution Tables for Qualitative and Quantitative Data 20 2.3.1 Qualitative Data 21 2.3.2 Quantitative Data 24 2.4 Graphical Description of Qualitative and Quantitative Data 30 2.4.1 Dot Plot 30 2.4.2 Pie Chart 31 2.4.3 Bar Chart 33 2.4.4 Histograms 37 2.4.5 Line Graph 44 2.4.6 Stem-and-Leaf Plot 45 2.5 Numerical Measures of Quantitative Data 50 2.5.1 Measures of Centrality 51 2.5.2 Measures of Dispersion 56 2.6 Numerical Measures of Grouped Data 67 2.6.1 Mean of a Grouped Data 67 2.6.2 Median of a Grouped Data 68 2.6.3 Mode of a Grouped Data 69 2.6.4 Variance of a Grouped Data 69 2.7 Measures of Relative Position 70 2.7.1 Percentiles 71 2.7.2 Quartiles 72 2.7.3 Interquartile Range (IQR) 72 2.7.4 Coefficient of Variation 73 2.8 Box-Whisker Plot 75 2.8.1 Construction of a Box Plot 75 2.8.2 How to Use the Box Plot 76 2.9 Measures of Association 80 2.10 Case Studies 84 2.10.1 About St. Luke’s Hospital 85 2.11 Using JMP 86 Review Practice Problems 87 3 Elements of Probability 97 3.1 Introduction 97 3.2 Random Experiments, Sample Spaces, and Events 98 3.2.1 Random Experiments and Sample Spaces 98 3.2.2 Events 99 3.3 Concepts of Probability 103 3.4 Techniques of Counting Sample Points 108 3.4.1 Tree Diagram 108 3.4.2 Permutations 110 3.4.3 Combinations 110 3.4.4 Arrangements of n Objects Involving Several Kinds of Objects 111 3.5 Conditional Probability 113 3.6 Bayes’s Theorem 116 3.7 Introducing Random Variables 120 Review Practice Problems 122 4 Discrete Random Variables and Some Important Discrete Probability Distributions 128 4.1 Graphical Descriptions of Discrete Distributions 129 4.2 Mean and Variance of a Discrete Random Variable 130 4.2.1 Expected Value of Discrete Random Variables and Their Functions 130 4.2.2 The Moment-Generating Function-Expected Value of a Special Function of X 133 4.3 The Discrete Uniform Distribution 136 4.4 The Hypergeometric Distribution 137 4.5 The Bernoulli Distribution 141 4.6 The Binomial Distribution 142 4.7 The Multinomial Distribution 146 4.8 The Poisson Distribution 147 4.8.1 Definition and Properties of the Poisson Distribution 147 4.8.2 Poisson Process 148 4.8.3 Poisson Distribution as a Limiting Form of the Binomial 148 4.9 The Negative Binomial Distribution 153 4.10 Some Derivations and Proofs (Optional) 156 4.11 A Case Study 156 4.12 Using JMP 157 Review Practice Problems 157 5 Continuous Random Variables and Some Important Continuous Probability Distributions 164 5.1 Continuous Random Variables 165 5.2 Mean and Variance of Continuous Random Variables 168 5.2.1 Expected Value of Continuous Random Variables and Their Functions 168 5.2.2 The Moment-Generating Function and Expected Value of a Special Function of X 171 5.3 Chebyshev’s Inequality 173 5.4 The Uniform Distribution 175 5.4.1 Definition and Properties 175 5.4.2 Mean and Standard Deviation of the Uniform Distribution 178 5.5 The Normal Distribution 180 5.5.1 Definition and Properties 180 5.5.2 The Standard Normal Distribution 182 5.5.3 The Moment-Generating Function of the Normal Distribution 187 5.6 Distribution of Linear Combination of Independent Normal Variables 189 5.7 Approximation of the Binomial and Poisson Distributions by the Normal Distribution 193 5.7.1 Approximation of the Binomial Distribution by the Normal Distribution 193 5.7.2 Approximation of the Poisson Distribution by the Normal Distribution 196 5.8 A Test of Normality 196 5.9 Probability Models Commonly used in Reliability Theory 201 5.9.1 The Lognormal Distribution 202 5.9.2 The Exponential Distribution 206 5.9.3 The Gamma Distribution 211 5.9.4 The Weibull Distribution 214 5.10 A Case Study 218 5.11 Using JMP 219 Review Practice Problems 220 6 Distribution of Functions Of Random Variables 228 6.1 Introduction 229 6.2 Distribution Functions of Two Random Variables 229 6.2.1 Case of Two Discrete Random Variables 229 6.2.2 Case of Two Continuous Random Variables 232 6.2.3 The Mean Value and Variance of Functions of Two Random Variables 233 6.2.4 Conditional Distributions 235 6.2.5 Correlation between Two Random Variables 238 6.2.6 Bivariate Normal Distribution 241 6.3 Extension to Several Random Variables 244 6.4 The Moment-Generating Function Revisited 245 Review Practice Problems 249 7 Sampling Distributions 253 7.1 Random Sampling 253 7.1.1 Random Sampling from an Infinite Population 254 7.1.2 Random Sampling from a Finite Population 256 7.2 The Sampling Distribution of the Sample Mean 258 7.2.1 Normal Sampled Population 258 7.2.2 Nonnormal Sampled Population 258 7.2.3 The Central Limit Theorem 259 7.3 Sampling from a Normal Population 264 7.3.1 The Chi-Square Distribution 264 7.3.2 The Student t-Distribution 271 7.3.3 Snedecor’s F-Distribution 276 7.4 Order Statistics 279 7.4.1 Distribution of the Largest Element in a Sample 280 7.4.2 Distribution of the Smallest Element in a Sample 281 7.4.3 Distribution of the Median of a Sample and of the kth Order Statistic 282 7.4.4 Other Uses of Order Statistics 284 7.5 Using JMP 286 Review Practice Problems 286 8 Estimation of Population Parameters 289 8.1 Introduction 290 8.2 Point Estimators for the Population Mean and Variance 290 8.2.1 Properties of Point Estimators 292 8.2.2 Methods of Finding Point Estimators 295 8.3 Interval Estimators for the Mean μ of a Normal Population 301 8.3.1 σ2 Known 301 8.3.2 σ2 Unknown 304 8.3.3 Sample Size is Large 306 8.4 Interval Estimators for The Difference of Means of Two Normal Populations 313 8.4.1 Variances are Known 313 8.4.2 Variances are Unknown 314 8.5 Interval Estimators for the Variance of a Normal Population 322 8.6 Interval Estimator for the Ratio of Variances of Two Normal Populations 327 8.7 Point and Interval Estimators for the Parameters of Binomial Populations 331 8.7.1 One Binomial Population 331 8.7.2 Two Binomial Populations 334 8.8 Determination of Sample Size 338 8.8.1 One Population Mean 339 8.8.2 Difference of Two Population Means 339 8.8.3 One Population Proportion 340 8.8.4 Difference of Two Population Proportions 341 8.9 Some Supplemental Information 343 8.10 A Case Study 343 8.11 Using JMP 343 Review Practice Problems 344 9 Hypothesis Testing 352 9.1 Introduction 353 9.2 Basic Concepts of Testing a Statistical Hypothesis 353 9.2.1 Hypothesis Formulation 353 9.2.2 Risk Assessment 355 9.3 Tests Concerning the Mean of a Normal Population Having Known Variance 358 9.3.1 Case of a One-Tail (Left-Sided) Test 358 9.3.2 Case of a One-Tail (Right-Sided) Test 362 9.3.3 Case of a Two-Tail Test 363 9.4 Tests Concerning the Mean of a Normal Population Having Unknown Variance 372 9.4.1 Case of a Left-Tail Test 372 9.4.2 Case of a Right-Tail Test 373 9.4.3 The Two-Tail Case 374 9.5 Large Sample Theory 378 9.6 Tests Concerning the Difference of Means of Two Populations Having Distributions with Known Variances 380 9.6.1 The Left-Tail Test 380 9.6.2 The Right-Tail Test 381 9.6.3 The Two-Tail Test 383 9.7 Tests Concerning the Difference of Means of Two Populations Having Normal Distributions with Unknown Variances 388 9.7.1 Two Population Variances are Equal 388 9.7.2 Two Population Variances are Unequal 392 9.7.3 The Paired t-Test 395 9.8 Testing Population Proportions 401 9.8.1 Test Concerning One Population Proportion 401 9.8.2 Test Concerning the Difference Between Two Population Proportions 405 9.9 Tests Concerning the Variance of a Normal Population 410 9.10 Tests Concerning the Ratio of Variances of Two Normal Populations 414 9.11 Testing of Statistical Hypotheses using Confidence Intervals 418 9.12 Sequential Tests of Hypotheses 422 9.12.1 A One-Tail Sequential Testing Procedure 422 9.12.2 A Two-Tail Sequential Testing Procedure 427 9.13 Case Studies 430 9.14 Using JMP 431 Review Practice Problems 431 Part II Statistics in Actions 10 Elements of Reliability Theory 445 10.1 The Reliability Function 446 10.1.1 The Hazard Rate Function 446 10.1.2 Employing the Hazard Function 455 10.2 Estimation: Exponential Distribution 457 10.3 Hypothesis Testing: Exponential Distribution 465 10.4 Estimation: Weibull Distribution 467 10.5 Case Studies 472 10.6 Using JMP 474 Review Practice Problems 474 11 On Data Mining 476 11.1 Introduction 476 11.2 What is Data Mining? 477 11.2.1 Big Data 477 11.3 Data Reduction 478 11.4 Data Visualization 481 11.5 Data Preparation 490 11.5.1 Missing Data 490 11.5.2 Outlier Detection and Remedial Measures 491 11.6 Classification 492 11.6.1 Evaluating a Classification Model 493 11.7 Decision Trees 499 11.7.1 Classification and Regression Trees (CART) 500 11.7.2 Further Reading 511 11.8 Case Studies 511 11.9 Using JMP 512 Review Practice Problems 512 12 Cluster Analysis 518 12.1 Introduction 518 12.2 Similarity Measures 519 12.2.1 Common Similarity Coefficients 524 12.3 Hierarchical Clustering Methods 525 12.3.1 Single Linkage 526 12.3.2 Complete Linkage 531 12.3.3 Average Linkage 534 12.3.4 Ward’s Hierarchical Clustering 536 12.4 Nonhierarchical Clustering Methods 538 12.4.1 K-Means Method 538 12.5 Density-Based Clustering 544 12.6 Model-Based Clustering 547 12.7 A Case Study 552 12.8 Using JMP 553 Review Practice Problems 553 13 Analysis of Categorical Data 558 13.1 Introduction 558 13.2 The Chi-Square Goodness-of-Fit Test 559 13.3 Contingency Tables 568 13.3.1 The 2 × 2 Case with Known Parameters 568 13.3.2 The 2 × 2 Case with Unknown Parameters 570 13.3.3 The r × s Contingency Table 572 13.4 Chi-Square Test for Homogeneity 577 13.5 Comments on the Distribution of the Lack-of-Fit Statistics 581 13.6 Case Studies 583 13.7 Using JMP 584 Review Practice Problems 585 14 Nonparametric Tests 591 14.1 Introduction 591 14.2 The Sign Test 592 14.2.1 One-Sample Test 592 14.2.2 The Wilcoxon Signed-Rank Test 595 14.2.3 Two-Sample Test 598 14.3 Mann–Whitney (Wilcoxon) W Test for Two Samples 604 14.4 Runs Test 608 14.4.1 Runs above and below the Median 608 14.4.2 The Wald–Wolfowitz Run Test 611 14.5 Spearman Rank Correlation 614 14.6 Using JMP 618 Review Practice Problems 618 15 Simple Linear Regression Analysis 622 15.1 Introduction 623 15.2 Fitting the Simple Linear Regression Model 624 15.2.1 Simple Linear Regression Model 624 15.2.2 Fitting a Straight Line by Least Squares 627 15.2.3 Sampling Distribution of the Estimators of Regression Coefficients 631 15.3 Unbiased Estimator of σ2 637 15.4 Further Inferences Concerning Regression Coefficients (β0, β1), E(Y ), and Y 639 15.4.1 Confidence Interval for β1 with Confidence Coefficient (1 − α) 639 15.4.2 Confidence Interval for β0 with Confidence Coefficient (1 − α) 640 15.4.3 Confidence Interval for E(Y |X) with Confidence Coefficient (1 − α) 642 15.4.4 Prediction Interval for a Future Observation Y with Confidence Coefficient (1 − α) 645 15.5 Tests of Hypotheses for β0 and β1 652 15.5.1 Test of Hypotheses for β1 652 15.5.2 Test of Hypotheses for β0 652 15.6 Analysis of Variance Approach to Simple Linear Regression Analysis 659 15.7 Residual Analysis 665 15.8 Transformations 674 15.9 Inference About ρ 681 15.10A Case Study 683 15.11 Using JMP 684 Review Practice Problems 684 16 Multiple Linear Regression Analysis 693 16.1 Introduction 694 16.2 Multiple Linear Regression Models 694 16.3 Estimation of Regression Coefficients 699 16.3.1 Estimation of Regression Coefficients Using Matrix Notation 701 16.3.2 Properties of the Least-Squares Estimators 703 16.3.3 The Analysis of Variance Table 704 16.3.4 More Inferences about Regression Coefficients 706 16.4 Multiple Linear Regression Model Using Quantitative and Qualitative Predictor Variables 714 16.4.1 Single Qualitative Variable with Two Categories 714 16.4.2 Single Qualitative Variable with Three or More Categories 716 16.5 Standardized Regression Coefficients 726 16.5.1 Multicollinearity 728 16.5.2 Consequences of Multicollinearity 729 16.6 Building Regression Type Prediction Models 730 16.6.1 First Variable to Enter into the Model 730 16.7 Residual Analysis and Certain Criteria for Model Selection 734 16.7.1 Residual Analysis 734 16.7.2 Certain Criteria for Model Selection 735 16.8 Logistic Regression 740 16.9 Case Studies 745 16.10 Using JMP 748 Review Practice Problems 748 17 Analysis of Variance 757 17.1 Introduction 758 17.2 The Design Models 758 17.2.1 Estimable Parameters 758 17.2.2 Estimable Functions 760 17.3 One-Way Experimental Layouts 761 17.3.1 The Model and Its Analysis 761 17.3.2 Confidence Intervals for Treatment Means 767 17.3.3 Multiple Comparisons 773 17.3.4 Determination of Sample Size 780 17.3.5 The Kruskal–Wallis Test for One-Way Layouts (Nonparametric Method) 781 17.4 Randomized Complete Block (RCB) Designs 785 17.4.1 The Friedman Fr-Test for Randomized Complete Block Design (Nonparametric Method) 792 17.4.2 Experiments with One Missing Observation in an RCB-Design Experiment 794 17.4.3 Experiments with Several Missing Observations in an RCB-Design Experiment 795 17.5 Two-Way Experimental Layouts 798 17.5.1 Two-Way Experimental Layouts with One Observation per Cell 800 17.5.2 Two-Way Experimental Layouts with r > 1 Observations per Cell 801 17.5.3 Blocking in Two-Way Experimental Layouts 810 17.5.4 Extending Two-Way Experimental Designs to n-Way Experimental Layouts 811 17.6 Latin Square Designs 813 17.7 Random-Effects and Mixed-Effects Models 820 17.7.1 Random-Effects Model 820 17.7.2 Mixed-Effects Model 822 17.7.3 Nested (Hierarchical) Designs 824 17.8 A Case Study 831 17.9 Using JMP 832 Review Practice Problems 832 18 The 2k Factorial Designs 847 18.1 Introduction 848 18.2 The Factorial Designs 848 18.3 The 2k Factorial Designs 850 18.4 Unreplicated 2k Factorial Designs 859 18.5 Blocking in the 2k Factorial Design 867 18.5.1 Confounding in the 2k Factorial Design 867 18.5.2 Yates’s Algorithm for the 2k Factorial Designs 875 18.6 The 2k Fractional Factorial Designs 877 18.6.1 One-half Replicate of a 2k Factorial Design 877 18.6.2 One-quarter Replicate of a 2k Factorial Design 882 18.7 Case Studies 887 18.8 Using JMP 889 Review Practice Problems 889 19 Response Surfaces 897 19.1 Introduction 897 19.1.1 Basic Concepts of Response Surface Methodology 898 19.2 First-Order Designs 903 19.3 Second-Order Designs 917 19.3.1 Central Composite Designs (CCDs) 918 19.3.2 Some Other First-Order and Second-Order Designs 928 19.4 Determination of Optimum or Near-Optimum Point 936 19.4.1 The Method of Steepest Ascent 937 19.4.2 Analysis of a Fitted Second-Order Response Surface 941 19.5 Anova Table for a Second-Order Model 946 19.6 Case Studies 948 19.7 Using JMP 950 Review Practice Problems 950 20 Statistical Quality Control—Phase I Control Charts 958 21 Statistical Quality Control—Phase II Control Charts 960 Appendices 961 Appendix A Statistical Tables 962 Appendix B Answers to Selected Problems 969 Appendix C Bibliography 992 Index 1003

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Book SynopsisTwo top specialists in profitable growth and innovative customer-supplier relationships show companies of all sizes how to compete with the tech giantsâby choosing the right customer and providing peerless value to them for long-term success.Every year, managers at companies large and small are finding it harder to compete with the likes of Google and Amazon, who are muscling into their businesses, stealing their customers, and cornering every conceivable market and service. There is, however, a way for companies to surviveâand winâin this era of digital behemoths. Choose Your Customer is a powerful, customer-targeted guide that can help managers level the playing field against their biggest competitors.Written by Jonathan Byrnes, the legendary MIT-based expert on profits, pricing, and strategy, and John Wass, a key member of the team that made Staples a major national brand, Choose Your Customer shows you how to:Identify the custom

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Book SynopsisOptimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from the extraction of noise signals. Moreover, it is a fundamental feature in a range of applications, such as in navigation in aerospace and aeronautics, filter processing in the telecommunications industry, etc. This book provides a comprehensive overview of this area, discussing random and Gaussian vectors, outlining the results necessary for the creation of Wiener and adaptive filters used for stationary signals, as well as examining Kalman filters which are used in relation to non-stationary signals. Exercises with solutions feature in each chapter to demonstrate the practical application of these ideas using Matlab.Table of ContentsPreface xi Introduction xiii Chapter 1. Random Vectors 1 1.1. Definitions and general properties 1 1.2. Spaces L1(dP) and L2(dP) 20 1.2.1. Definitions 20 1.2.2. Properties 22 1.3. Mathematical expectation and applications 23 1.3.1. Definitions 23 1.3.2. Characteristic functions of a random vector 34 1.4. Second order random variables and vectors 39 1.5. Linear independence of vectors of L2(dP) 47 1.6. Conditional expectation (concerning random vectors with density function) 51 1.7. Exercises for Chapter 1 57 Chapter 2. Gaussian Vectors 63 2.1. Some reminders regarding random Gaussian vectors 63 2.2. Definition and characterization of Gaussian vectors 66 2.3. Results relative to independence 68 2.4. Affine transformation of a Gaussian vector 72 2.5. The existence of Gaussian vectors 74 2.6. Exercises for Chapter 2 85 Chapter 3. Introduction to Discrete Time Processes 93 3.1. Definition 93 3.2. WSS processes and spectral measure 105 3.2.1. Spectral density 106 3.3. Spectral representation of a WSS process 110 3.3.1. Problem 110 3.3.2. Results 111 3.3.2.1. Process with orthogonal increments and associated measurements 111 3.3.2.2. Wiener stochastic integral 113 3.3.2.3. Spectral representation 114 3.4. Introduction to digital filtering 115 3.5. Important example: autoregressive process 128 3.6. Exercises for Chapter 3 134 Chapter 4. Estimation 141 4.1. Position of the problem 141 4.2. Linear estimation 144 4.3. Best estimate – conditional expectation 156 4.4. Example: prediction of an autoregressive process AR (1) 165 4.5. Multivariate processes 166 4.6. Exercises for Chapter 4 175 Chapter 5. The Wiener Filter 181 5.1. Introduction 181 5.1.1. Problem position 182 5.2. Resolution and calculation of the FIR filter 183 5.3. Evaluation of the least error 185 5.4. Resolution and calculation of the IIR filter 186 5.5. Evaluation of least mean square error 190 5.6. Exercises for Chapter 5 191 Chapter 6. Adaptive Filtering: Algorithm of the Gradient and the LMS 197 6.1. Introduction 197 6.2. Position of problem 199 6.3. Data representation 202 6.4. Minimization of the cost function 204 6.4.1. Calculation of the cost function 208 6.5. Gradient algorithm 211 6.6. Geometric interpretation 214 6.7. Stability and convergence 218 6.8. Estimation of gradient and LMS algorithm 222 6.8.1. Convergence of the algorithm of the LMS 225 6.9. Example of the application of the LMS algorithm 225 6.10. Exercises for Chapter 6 234 Chapter 7. The Kalman Filter 237 7.1. Position of problem 237 7.2. Approach to estimation 241 7.2.1. Scalar case 241 7.2.2. Multivariate case 244 7.3. Kalman filtering 245 7.3.1. State equation 245 7.3.2. Observation equation 246 7.3.3. Innovation process 248 7.3.4. Covariance matrix of the innovation process 248 7.3.5. Estimation 250 7.3.6. Riccati’s equation 258 7.3.7. Algorithm and summary 260 7.4. Exercises for Chapter 7 262 Table of Symbols and Notations 281 Bibliography 283 Index 285

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Book SynopsisThis textbook offers an interdisciplinary, comprehensive and state-of-the-art overview of the media linguistics approaches to explain and understand digital communication and multimodality. Linking the fields of communication studies, applied linguistics and journalism, it grounds communication practices in a deep understanding of the social and societal implications of language use in digital media. The tools to analyse multimodal texts are analysed in light of the advantages and constraints that different communication modes pose, both individually and in combination. Aimed at upper level undergraduates and graduates in applied linguistics, communication and media studies, including journalism and PR, this textbook contains case studies and professional examples highlighting the interplay between language use and digital communication and encouraging the reader to reflect on the themes covered, and put the acquired knowledge into practice. Online resources for students include videosTable of ContentsAcknowledgements; Preface; 1. Starting Point: Digital Society and Media Linguistics; 2. Theoretical Context: Understanding Public Digital Communication; 3. Practical Context: From Writing to Multimodal Communication; 4. Professional Context: Journalism, PR, and Community Communication; 5. Doing Media Linguistic Research; 6. Doing Media Linguistic Analysis; 7. Case Studies; 8. Public Communication in Transformation: Algorithmic Culture; References; Appendix; Glossary; Index.

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Book SynopsisETpedia Grammar provides English language teachers with a wide range of techniques, tips, ideas and activities to help you plan and deliver lessons with grammar. With 50 units covering key areas of grammar, each unit contains a set of 10 preparation-friendly activities which provide the perfect starting point for new teachers and offer inspiration to more experienced teachers. This resource also contains printable worksheets and space to write your own tips.Table of Contents1. Introduction. 2. The basics. 3. Pronouns and clauses. 4. Adjectives and adverbs. 5. Present forms. 6. Modal verbs (present). 7. Past forms. 8. Future forms. 9. Conditionals. 10. Other verbs forms. Appendix.

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Book SynopsisA guide to the art of jewelry making, it shows readers how to do various things from basic bead stringing to wire wrapping. It includes 20 patterns for making earrings, necklaces, bracelets, and more.Table of ContentsChapter 1: Introduction to Jewelry Making and Beading.Become a Jewelry Artisan.Beads and Beading Supplies.Wire and Wirework Supplies.Macrame Knotting and Braiding Supplies.Jewelry Findings.Chapter 2: The Art of Design.Color Harmony.Weight, Texture, and Proportion.Motif and Pattern.Keep Track of Ideas.Chapter 3: Basic Bead Stringing Techniques.Lay Out a Design.Select a Stringing Material.Select a Finishing Method.String and Finish Beading Wire.String and Finish Beading Cord.String and Finish Beading Thread.String and Finish Memory Wire.Chapter 4: More Advanced Bead Stringing Techniques.String Multiple Strands.Knot Between Beads.Create Beaded Lace, Drops, Fringe, and Tassels.Use Beads or Buttons in Place of Findings.Chapter 5: Bead Weaving.Bead Weaving Patterns.Select Beads, Thread, and Needle.Work with Beading Thread for Bead Weaving.Weave the Basic Off-Loom Stitches.Weave on a Loom.Common Finishing Techniques.Chapter 6: Basic Wirework.Select Your Wire.Wirework Safety.Make Jump Rings, Eye Pins, and Head Pins.Create Wire-and-Bead Drops and Links.Make Wire Hook Clasps.Assemble Some Basic Wire Chains.Chapter 7: More Advanced Wirework Techniques.Make a Wrapped Briolette Drop.Use Double Wire.Wrap Beads Within a Framework.Create More Wire Clasps.Construct Elaborate Wire Chain.Make a Wire Finger Ring.Chapter 8: Using a Wire Jig.Basic Technique.Make Wire Connectors.Form Ear Wires.Wire Jig Patterns.Chapter 9: Macrame Knotting and Beading.Cord Terminology.Set Up a Knotting Board.Learn the Basic Macrame Knots.Add Beads Between Macrame Knots.Braid Cords Together.Chapter 10: Easy Projects.Funky Beaded Stretch Bracelet Set.Hill Tribe Silver and Gemstone Necklace.Memory Wire and Crystal Heart Finger Ring.Beaded Square Knot Hemp Bracelet.Cosmic Crystal Drop Earrings.Men's Rugged Leather and Bead Necklace.Celtic Wirework Charm Bracelet.Even-Count Flat Peyote Stitch Finger Ring.Dancing Bell Daisy Chain Bookmark.Chapter 11: Intermediate Projects.Multi-Strand Tin Cup Anklet.Beaded Multi-Knot Hemp Choker.Briolette Pendant Ribbon Necklace.Gothic Bead Lace Collar Necklace.Cherry Blossom Loomwork Bracelet.Byzantine and Turquoise Drop Earrings.Wirework Bead Cuff Bracelet.Modern Square Stitch Table Mat.Beaded Framework Link Bracelet.Four-Strand Braided Leather Bracelet.Chapter 12: Expanding Your Horizons.Choose a Specialized Path.Find Advanced Help and Training.Turn Your Hobby into a Business.Appendix: Reference Materials.Index.

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Book SynopsisExplore advanced techniques in AI image generation with a focus on enhancing creativity and producing unique styles using the Midjourney platform, an AI image-generating (text-to-image) program unparalleled in the aesthetics of images it can produce. This book is for anyone ready to push their AI art further, with guidance straight from a seasoned AI artist and user of Midjourney. Unlike a basic tutorial, this book focuses on advanced prompt crafting strategies, understanding Midjourney's evolving algorithms, and harnessing these tools to produce art that resonates on personal and communal levels. Author Irina Shamaeva shares insights gained from creating and sharing art that has captivated over 8,000 followers on social media in a year. You'll see how to think out of the box with AI art creation and gain practical tips and techniques for drawing. Expect practical tips on making the most of Midjourney for your art, insights from the author's experience, and stories from the AI art world. This book is not just about how to use Midjourney; it's about creating art that matters to you and others. Advanced Styles and Insights with Midjourney will allow you to channel your creativity with more sophisticated drawing techniques, concepts, and new complementary tools. What You Will LearnCombine the features of two recent Midjourney versions, getting the best qualities of each. Explore a hidden unofficial version of Midjourney that has a wild imagination. Use the Vary(Subtle), Vary(Strong), and Vary(Region) functions to manipulate your images. Work with multimedia - images along with text - as image prompts and style references. Who This Book Is ForGraphic designers, architects, book illustrators, product photographers, game developers, fashion and interior designers, educators, AI researchers using text-to-image software, and any Midjourney user wanting to enhance their prompting skills.

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Book SynopsisThis book, presented in three volumes, examines �environmental� disciplines in relation to major players in contemporary science: Big Data, artificial intelligence and cloud computing. Today, there is a real sense of urgency regarding the evolution of computer technology, the ever-increasing volume of data, threats to our climate and the sustainable development of our planet. As such, we need to reduce technology just as much as we need to bridge the global socio-economic gap between the North and South; between universal free access to data (open data) and free software (open source). In this book, we pay particular attention to certain environmental subjects, in order to enrich our understanding of cloud computing. These subjects are: erosion; urban air pollution and atmospheric pollution in Southeast Asia; melting permafrost (causing the accelerated release of soil organic carbon in the atmosphere); alert systems of environmental hazards (such as forest fires, prospective modeling of socio-spatial practices and land use); and web fountains of geographical data. Finally, this book asks the question: in order to find a pattern in the data, how do we move from a traditional computing model-based world to pure mathematical research? After thorough examination of this topic, we conclude that this goal is both transdisciplinary and achievable.Table of ContentsPreface xiii Part 1. Integrated Analysis in Geography: The Way to Cloud Computing xix Introduction to Part 1 xxiDominique LAFFLY Chapter 1. Geographical Information and Landscape, Elements of Formalization 1Dominique LAFFLY Chapter 2. Sampling Strategies 7Dominique LAFFLY 2.1. References 18 Chapter 3. Characterization of the Spatial Structure 19Dominique LAFFLY Chapter 4. Thematic Information Structures 27Dominique LAFFLY Chapter 5. From the Point to the Surface, How to Link Endogenous and Exogenous Data 35Dominique LAFFLY 5.1. References 44 Chapter 6. Big Data in Geography 45Dominique LAFFLY Conclusion to Part 1 55Dominique LAFFLY Part 2. Basic Mathematical, Statistical and Computational Tools 59 Chapter 7. An Introduction to Machine Learning 61Hichem SAHLI 7.1. Predictive modeling: introduction 61 7.2. Bayesian modeling61 7.2.1. Basic probability theory 62 7.2.2. Bayes rule 63 7.2.3. Parameter estimation 63 7.2.4. Learning Gaussians 64 7.3. Generative versus discriminative models 66 7.4. Classification 67 7.4.1. Naïve Bayes 68 7.4.2. Support vector machines 69 7.5. Evaluation metrics for classification evaluation 71 7.5.1. Confusion matrix-based measures 71 7.5.2. Area under the ROC curve (AUC) 73 7.6. Cross-validation and over-fitting 73 7.7. References 74 Chapter 8. Multivariate Data Analysis 75Astrid JOURDAN and Dominique LAFFLY 8.1. Introduction 75 8.2. Principal component analysis 77 8.2.1. How to measure the information 78 8.2.2. Scalar product and orthogonal variables 80 8.2.3. Construction of the principal axes 81 8.2.4. Analysis of the principal axes 84 8.2.5. Analysis of the data points 86 8.3. Multiple correspondence analysis 88 8.3.1. Indicator matrix 89 8.3.2. Cloud of data points 90 8.3.3. Cloud of levels 92 8.3.4. MCA or PCA? 94 8.4. Clustering 96 8.4.1. Distance between data points 97 8.4.2. Dissimilarity criteria between clusters 98 8.4.3. Variance (inertia) decomposition 99 8.4.4. k-means method 101 8.4.5. Agglomerative hierarchical clustering 104 8.5. References 105 Chapter 9. Sensitivity Analysis 107Astrid JOURDAN and Peio LOUBIÈRE 9.1. Generalities 107 9.2. Methods based on linear regression 109 9.2.1. Presentation 109 9.2.2. R practice 111 9.3. Morris’ method 114 9.3.1. Elementary effects method (Morris’ method) 114 9.3.2. R practice 117 9.4. Methods based on variance analysis 119 9.4.1. Sobol’ indices 120 9.4.2. Estimation of the Sobol’ indices 122 9.4.3. R practice 123 9.5. Conclusion 126 9.6. References 127 Chapter 10. Using R for Multivariate Analysis 129Astrid JOURDAN 10.1. Introduction 129 10.1.1. The dataset 131 10.1.2. The variables 134 10.2. Principal component analysis 136 10.2.1. Eigenvalues 137 10.2.2. Data points (Individuals) 139 10.2.3. Supplementary variables 143 10.2.4. Other representations 143 10.3. Multiple correspondence analysis 144 10.4. Clustering 145 10.4.1. k-means algorithm 145 10.5. References 151 Part 3. Computer Science 153 Chapter 11. High Performance and Distributed Computing 155Sebastiano Fabio SCHIFANO, Eleonora LUPPI, Didin Agustian PERMADI, Thi Kim Oanh NGUYEN, Nhat Ha Chi NGUYEN and Luca TOMASSETTI 11.1. High performance computing 155 11.2. Systems based on multi-core CPUs 157 11.2.1. Systems based on GPUs 159 Chapter 12. Introduction to Distributed Computing 163Eleonora LUPPI 12.1. Introduction 163 12.1.1. A brief history 163 12.1.2. Design requirements165 12.1.3. Models 168 12.1.4. Grid computing 171 12.2. References 176 Chapter 13. Towards Cloud Computing 179Peio LOUBIÈRE and Luca TOMASSETTI 13.1. Introduction 179 13.1.1. Generalities 179 13.1.2. Benefits and drawbacks 180 13.2. Service model 180 13.2.1. Software as a Service 181 13.2.2. Platform as a Service 182 13.2.3. Infrastructure as a Service 182 13.2.4. And many more: XaaS 182 13.3. Deployment model 183 13.3.1. Public cloud 183 13.3.2. Private cloud 183 13.3.3. Hybrid cloud 184 13.4. Behind the hood, a technological overview 184 13.4.1. Structure 184 13.4.2. Virtualization 185 13.4.3. Scalability 186 13.4.4. Web-Oriented Architecture 187 13.5. Conclusion 187 13.6. References 188 Chapter 14. Web-Oriented Architecture – How to design a RESTFull API 191Florent DEVIN 14.1. Introduction 191 14.2. Web services 192 14.2.1. Introduction 192 14.2.2. SOAP web services 193 14.2.3. REST web services 195 14.3. Web-Oriented Applications – Microservice applications 198 14.3.1. Stateless and scalabilty 199 14.3.2. API 200 14.3.3. HTTP Methods 201 14.3.4. Example of an API 202 14.4. WSDL example 203 14.5. Conclusion 205 14.6. References 205 Chapter 15. SCALA – Functional Programming 207Florent DEVIN 15.1. Introduction 207 15.1.1. Programming languages 208 15.1.2. Paradigm 208 15.2. Functional programming 212 15.2.1. Introduction 212 15.2.2. Why now? 212 15.2.3. High order function 213 15.2.4. Basic functional blocks 215 15.3. Scala 217 15.3.1. Types systems 218 15.3.2. Basic manipulation of collection 222 15.4. Rational 224 15.5. Why immutability matters? 224 15.6. Conclusion 226 15.7. References 227 Chapter 16. Spark and Machine Learning Library 229Yannick LE NIR 16.1. Introduction 229 16.2. Spark 230 16.2.1. Spark introduction 230 16.2.2. RDD presentation 230 16.2.3. RDD lifecycle 231 16.2.4. Operations on RDD 232 16.2.5. Exercises for environmental sciences 236 16.3. Spark machine learning library 237 16.3.1. Local vectors 237 16.3.2. Labeled points 237 16.3.3. Learning dataset 238 16.3.4. Classification and regression algorithms in Spark 238 16.3.5. Exercises for environmental sciences 239 16.4. Conclusion 242 Chapter 17. Database for Cloud Computing 245Peio LOUBIÈRE 17.1. Introduction 245 17.2. From myGlsrdbms to NoSQL 245 17.2.1. CAP theorem 246 17.2.2. From ACID to BASE 247 17.3. NoSQL database storage paradigms 248 17.3.1. Column-family oriented storage 249 17.3.2. Key/value-oriented storage 249 17.3.3. Document-oriented storage 250 17.3.4. Graph-oriented storage 251 17.4. SQL versus NoSQL, the war will not take place 251 17.5. Example: a dive into MongoDB 252 17.5.1. Presentation 253 17.5.2. First steps 254 17.5.3. Database level commands 254 17.5.4. Data types 255 17.5.5. Modifying data 255 17.6. Conclusion 273 17.7. References 273 Chapter 18. WRF Performance Analysis and Scalability on Multicore High Performance Computing Systems 275Didin Agustian PERMADI, Sebastiano Fabio SCHIFANO, Thi Kim Oanh NGUYEN, Nhat Ha Chi NGUYEN, Eleonora LUPPI and Luca TOMASSETTI 18.1. Introduction 276 18.2. The weather research and forecast model and experimental set-up 276 18.2.1. Model architecture 276 18.3. Architecture of multicore HPC system 282 18.4. Results 283 18.4.1. Results of experiment E1 283 18.4.2. Results of experiment E2 286 18.5. Conclusion 288 18.6. References 288 List of Authors 291 Index 293 Summaries of other volumes 295

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Book SynopsisTechnology mediates how we know and experience cities, and the nature of this mediation has always been deeply political. Today, the production and deployment of data is at the forefront of projects to grasp and reshape urban life. Ways of Knowing Cities considers the role of technology in generating, materializing, and contesting urban epistemologies—tracing an arc from ubiquitous sites of “smart” urbanism, to discrete struggles over infrastructural governance, to forgotten histories of segregation now naturalized in urban algorithms, to exceptional territories of border policing. Bringing together architects, urbanists, artists, and scholars of critical migration studies, media theory, geography, anthropology, and literature, the essays stage a deeply interdisciplinary conversation, interrogating the ways in which certain ways of knowing are predicated on the erasure of others. In this opening, the book engages the information systems that structure urban space and social life in it, historically and in the present moment, to imagine alternative practices and generate new critical perspectives on spatial research.Ways of Knowing Cities includes texts by Eve Blau, Simone Browne, Maribel Casas-Cortes, Wendy Chun, Sebastian Cobarrubias, Beth Coleman, V. Mitch McEwen, Orit Halpern, Charles Heller, Shannon Mattern, Leah Meisterlin, Tinashe Mushakavanhu, Nontsikelelo Mutiti, Dietmar Offenhuber, Lorenzo Pezzani, Anita Say Chan, and Matthew W. Wilson.

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