Search Results - (((((((ant OR went) OR semantic) OR wind) OR cantor) OR anne) OR shape) OR hints) algorithms.

Advanced mathematical & computational tools in metrology & testing VIII

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The method of the generalised eikonal : new approaches in the Diffraction Theory. by Vesnik, Michael V.

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Credit securitizations and derivatives : challenges for the global markets

Table of Contents: “…Market Credit Risk Pricing -- Regulation -- Developments in Structured Finance Markets -- Impairments of Asset-Backed Securities and Outstanding Ratings -- Issuance of Asset-backed Securities and Outstanding Volume -- Global CDO Issuance and Outstanding Volume -- PART II CREDIT PORTFOLIO RISK MEASUREMENT -- Mortgage Credit Risk -- Five C's of Credit and Mortgage Credit Risk -- Determinants of Mortgage Default, Loss Given Default and Exposure at Default -- Determinants of Mortgage Default -- Determinants of Mortgage LGD -- Determinants of Mortgage EAD -- Modeling Methods for Default, LGD and EAD -- Model Risk Management -- Credit Portfolio Correlations and Uncertainty -- Introduction -- Gaussian and Semi-Gaussian Single Risk Factor Model -- Individual and Simultaneous Confidence Bounds and Intervals -- Confidence Intervals for Asset Correlations -- Confidence Intervals for Default and Survival Time Correlations -- Confidence Intervals for Default Correlations -- Confidence Intervals for Survival Time Correlations -- Credit Portfolio Correlations with Dynamic Leverage Ratios -- The Hui et al. (2007) Model -- The Method of Images for Constant Coefficients -- The Method of Images for Time-Varying Coefficients -- Modelling Default Correlations in a Two-Firm Model -- Default Correlations -- A Two-Firm Model with Dynamic Leverage Ratios -- Method of Images for Constant Coefficients -- Method of Images for Time-Varying Coefficients -- Alternative Methodologies for General Values -- Numerical Results -- Accuracy -- The Impact of Correlation between Two Firms -- The Impact of Different Credit Quality Paired Firms -- The Impact of Volatilities -- The Impact of Drift Levels -- The Impact of Initial Value of Leverage Ratio Levels -- Impact of Correlation between Firms and Interest Rates -- The Price of Credit-Linked Notes -- A Hierarchical Model of Tail-Dependent Asset Returns -- The Variance Compound Gamma Model -- Multivariate Process for Logarithmic Asset Returns -- Dependence Structure -- Sampling -- Copula Properties -- An Application Example -- Portfolio Setup -- Test Portfolios -- Parameter Setup -- Simulation Results -- Importance Sampling Algorithm -- Conclusions -- Appendix A: The VCG Probability Distribution Function Appendix B: HAC Representation for the VCG Framework -- Monte Carlo Methods for Portfolio Credit Risk -- Modeling Credit Portfolio Losses -- Risk Measures -- Modeling Dependency -- Estimating Risk Measures via Monte Carlo -- Crude Monte Carlo Estimators -- Importance Sampling -- Specific Models -- The Bernoulli Mixture Model -- Factor Models -- Copula Models -- Intensity Models -- An Example Point Process Model -- Appendix A: A Primer on Rare-event Simulation -- Efficiency -- Importance Sampling -- The Choice of g -- Adaptive Importance Sampling -- Importance Sampling for Stochastic Processes -- Credit Portfolio Risk and Diversification -- Introduction -- Model Setup -- Independent Asset Values -- Correlated Asset Values -- Large Portfolio Limit -- Correlated Diffusion -- Correlated GARCH Process -- Applications of the Structural Recovery Rate -- Conclusions -- PART III CREDIT PORTFOLIO RISK SECURITIZATION AND TRANCHING -- Differences in Tranching Methods: Some Results and Implications -- Defining a Tranche -- The Mathematics of Tranching -- PD-based Tranching -- EL-based Tranching -- The EL of a Tranche Necessarily Increases When Either the Attachment Point or the Detachment Point is Decreased -- Upper Bound on Tranche Expected LGD (LGDt) Assumption Given EL-based Tranches -- Skipping of Some Tranches in the EL-based Approach -- Global Structured Finance Rating -- Asset-Backed Securities -- The ABS Structure for the Experiment -- Cash Flow Modeling -- Modeling and Simulating Defaults -- Expected Loss Rating -- Global Sensitivity Analysis -- Elementary Effects -- Variance-based Method -- Global Sensitivity Analysis Results -- Uncertainty Analysis -- Sensitivity Analysis -- Global Rating -- PART IV CREDIT DERIVATIVES -- Analytic Dynamic Factor Copula Model -- Pricing Equations -- One-factor Copula Model -- Multi-period Factor Copula Models -- Calibration -- Dynamic Modeling of Credit Derivatives -- General Model Choice -- Modeling Option Prices -- Modeling Credit Risk -- Portfolio Credit Derivatives -- Modeling Asset Dynamics -- The Market Model -- The Asset-value Model -- Empirical Analysis -- Elementary Data -- Implied Dividends -- Market Dynamics -- Asset Value Model -- Tranche Pricing -- Out-of-time Application -- Pricing and Calibration in Market Models -- Basic notions -- The model -- Modeling Assumptions -- Absence of Arbitrage -- An affine specification -- Pricing -- Calibration -- Calibration Procedure -- Calibration Results -- Appendix A: Computations -- Counterparty Credit Risk and Clearing of Derivatives -- From the Perspective of an Industrial Corporate with a Focus on Commodity Markets -- Credit exposures in commodity business -- Settlement Exposure -- Performance Exposure -- Example of Fixed Price Deal with Performance Exposure -- Example of a Floating Price Deal with Performance Exposure -- General Remarks on Credit Exposure Concepts -- Ex Ante exposure-reducing techniques -- Payment Terms -- Material Adverse Change Clauses -- Master Agreements -- Netting -- Margining -- Close Out Exposure and Threshold -- Ex Ante risk-reducing techniques -- Credit Enhancements in General -- Parent Company Guarantees -- Letters of Credit -- Credit Insurance -- Clearing via a Central Counterparty -- Ex Post risk-reducing techniques -- Factoring -- Novation -- Risk-reducing Trades -- Hedging with CDS -- Hedging with Contingent-CDS -- Hedging with Puts on Equity -- Ex Post work out considerations -- Practical credit risk management and pricing Peculiarities of commodity markets -- Peculiarities of commodity related credit portfolios -- Credit Risk Capital for a commodity related portfolio measured with an extension of CreditMetrics -- CreditRisk+ study: applied to a commodity related credit portfolio -- CDS Industrial Sector Indices, Credit and Liquidity Risk -- The Data -- Methodology and Results -- Preliminary Analysis -- Common Factor Analysis -- Stability of Relations -- Risk Transfer and Pricing of Illiquid Assets with Loan CDS -- Shipping Market -- Loan Credit Default Swaps -- LCDS Pricing -- Modeling LCDS Under the Intensity-based Model -- Valuation Framework for LCDS -- The Structural Approach -- Credit Risk in Shipping Loans -- Valuation of LCDS on Shipping Loans -- Simulation Model -- Numerical Results -- Appendix A: Monte Carlo Parameterization PART V REGULATION -- Regulatory Capital Requirements for Securitizations -- Regulatory Approaches for Securitizations -- Ratings Based Approach (RBA) -- Supervisory Formula Approach (SFA) -- Standardized Approach (SA) -- Post-crisis Revisions to the Basel Framework -- Regulating OTC Derivatives -- The Wall Street Transparency and Accountability Part of the Dodd-Frank Act of 2010 -- Which Derivatives Will Be Affected? …”
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Security, Privacy and Reliability in Computer Communications and Networks. by Sha, Kewei

Table of Contents: “…5.6 Threats Analysis and Future Trends -- 5.7 Conclusion -- References -- PART III -- Cryptographic Algorithms -- Chapter 6 -- Quasigroup-Based Encryption for Low-Powered Devices -- Abstract -- 6.1 Introduction -- 6.2 Background-Low Energy Cryptosystems -- 6.3 Overview of Quasigroup Encryption -- 6.4 The Preliminary Block Cipher Design -- 6.5 Overview of Software Implementation -- 6.6 Overview of Three FPGA Implementations -- 6.6.1 The Quasigroup Implementation -- 6.6.2 Comparison Design-Parallel AES -- 6.6.3 Hybrid Front-End/AES Design -- 6.7 Experimental Results -- 6.8 Toward a Single-Chip Implementation -- 6.9 Algorithm Results for B = 2 to 8 -- 6.10 Generating Quasigroups Fast -- 6.11 Our Quasigroup Block Cipher Algorithm -- 6.12 Cryptanalysis and Improvements in the Block Cipher -- 6.13 Overview of a General Linear Cryptanalytical Attack -- 6.14 The LAT Design -- 6.15 Pilingup Attempts for N = 16, 32, and 64 -- 6.16 Analysis of the Attack on the Quasigroup -- 6.17 The Issue of a Total Linear Bias of 1/2 -- 6.18 Attack Complexity -- 6.19 Possible Changes that Could Be Made in the Design of This Attack Model -- 6.20 Which Quasigroup Order Is Best? …”
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Advanced wireless communications & Internet : future evolving technologies by Glisic, Savo G.

Table of Contents: “…Glisic -- 11.1 Introduction 585 -- 11.2 Background and Related Work 586 -- 11.3 Cooperative Communications 593 -- 11.4 Relay-Assisted Communications 616 -- 11.5 Two-Way Relay-Assisted Communications 646 -- 11.6 Relay-Assisted Communications With Reuse of Resources 651 -- Appendices 668 -- 12 Biologically Inspired Paradigms inWireless Networks 683 -- 12.1 Biologically Inspired Model for Securing Hybrid Mobile Ad Hoc Networks 683 -- 12.2 Biologically Inspired Routing in Ad Hoc Networks 687 -- 12.3 Analytical Modeling of AntNet as Adaptive Mobile Agent Based Routing 691 -- 12.4 Biologically Inspired Algorithm for Optimum Multicasting 697 -- 12.5 Biologically Inspired (BI) Distributed Topology Control 703 -- 12.6 Optimization of Mobile Agent Routing in Sensor Networks 708 -- 12.7 Epidemic Routing 710 -- 12.8 Nano-Networks 715 -- 12.9 Genetic Algorithm Based Dynamic Topology Reconfiguration in Cellular Multihop Wireless Networks 718 -- References 739 -- 13 Positioning in Wireless Networks 743 -- 13.1 Mobile Station Location in Cellular Networks 743.…”
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Spam : a Shadow History of the Internet by Brunton, Finn, 1980-

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Essential principles for autonomous robotics by Hexmoor, Henry, 1960-

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Computer aided design and manufacturing by Bi, Zhuming, Wang, Xiaoqin (Writer on manufacturing)

Table of Contents: “…Evaluate Platform Solutions 159; 4.11 Computer Aided Tools (CAD) for Platform Technologies 160; 4.11.1 Modelling Techniques of Product Variants 163; 4.11.2 Design Toolboxes 163; 4.11.3 Custom Design Libraries 164; 4.12 Summary 165; 4.13 Design Projects 166; References 169; 5 Computer Aided Reverse Engineering 173; 5.1 Introduction 173; 5.2 RE as Design Methodology 175; 5.3 RE Procedure 178; 5.4 Digital Modelling 179; 5.4.1 Types of Digital Models 180; 5.4.2 Surface Reconstruction 181; 5.4.3 Algorithms for Surface Reconstruction 181; 5.4.4 Limitations of Existing Algorithms 182; 5.4.5 Data Flow in Surface Reconstruction 183; 5.4.6 Surface Reconstruction Algorithm 184; 5.4.7 Implementation Examples 186; 5.5 Hardware Systems for Data Acquisition 188; 5.5.1 Classification of Hardware Systems 191; 5.5.2 Positioning of Data Acquisition Devices 197; 5.5.3 Control of Scanning Processes 199; 5.5.4 Available Hardware Systems 200; 5.6 Software Systems for Data Processing 201; 5.6.1 Data Filtering 201; 5.6.2 Data Registration and Integration 204; 5.6.3 Feature Detection 205; 5.6.4 Surface Reconstruction 205; 5.6.5 Surface Simplification 205; 5.6.6 Segmentation 206; 5.6.7 Available Software Tools 206; 5.7 Typical Manufacturing Applications 206; 5.8 Computer Aided Reverse Engineering (CARE) 208; 5.8.1 Recap to Convert Sensed Data into Polygonal Models 209; 5.8.2 ScanTo3D for Generation of Parametric Models 211; 5.8.3 RE of Assembled Products 212; 5.9 RE -- Trend of Development 213; 5.10 Summary 213; 5.11 Design Project 214; References 215; 6 Computer Aided Machine Design 219; 6.1 Introduction 219; 6.2 General Functional Requirements (FRs) of Machines 222; 6.3 Fundamentals of Machine Design 223; 6.3.1 Link Types 223; 6.3.2 Joint Types and Degrees of Freedom (DoFs) 223; 6.3.3 Kinematic Chains 225; 6.3.4 Mobility of Mechanical Systems 226; 6.4 Kinematic Synthesis 230; 6.4.1 Type Synthesis 230; 6.4.2 Number Synthesis 230; 6.4.3 Dimensional Synthesis 232; 6.5 Kinematics 233; 6.5.1 Positions of Particles, Links, and Bodies in 2D and 3D Space 233; 6.5.2 Motions of Particles, Links, and Bodies 235; 6.5.3 Vector-Loop Method for Motion Analysis of a Plane Mechanism 240; 6.5.4 Kinematic Modelling Based on Denavit-Hartenberg (D-H) Parameters 246; 6.5.5 Jacobian Matrix for Velocity Relations 248; 6.6 Dynamic Modelling 259; 6.6.1 Inertia and Moments of Inertia 259; 6.6.2 Newton-Euler Formulation 261; 6.6.3 Lagrangian Method 266; 6.7 Kinematic and Dynamics Modelling in Virtual Design 269; 6.7.1 Motion Simulation 269; 6.7.2 Model Preparation 271; 6.7.3 Creation of a Simulation Model 271; 6.7.4 Define Motion Variables 274; 6.7.5 Setting Simulation Parameters 275; 6.7.6 Run Simulation and Visualize Motion 275; 6.7.7 Analyse Simulation Data 276; 6.7.8 Structural Simulation Using Motion Loads 277; 6.8 Summary 278; 6.9 Design Project 279; References 279; Part II Computer Aided Manufacturing (CAM) 281; 7 Group Technology and Cellular Manufacturing 283; 7.1 Introduction 283; 7.2 Manufacturing System and Components 2…”
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Fog and fogonomics : challenges and practices of fog computing, communication, networking, strategy, and economics

Table of Contents: “…5.5.2 Survivability, Availability, and Reliability 122 -- 5.6 Sovereignty, Privacy, Security, Interoperability, and Management 123 -- 5.6.1 Data Sovereignty 123 -- 5.6.2 Privacy and Security 123 -- 5.6.3 Heterogeneity and Interoperability 124 -- 5.6.4 Monitoring, Orchestration, and Management 124 -- 5.7 Trade-Offs 125 -- 5.8 Conclusion 126 -- References 126 -- 6 Incentive Schemes for User-Provided Fog Infrastructure 129 /George Iosifidis, Lin Gao, Jianwei Huang, and Leandros Tassiulas -- 6.1 Introduction 129 -- 6.2 Technology and Economic Issues in UPIs 132 -- 6.2.1 Overview of UPI models for Network Connectivity 132 -- 6.2.2 Technical Challenges of Resource Allocation 134 -- 6.2.3 Incentive Issues 135 -- 6.3 Incentive Mechanisms for Autonomous Mobile UPIs 137 -- 6.4 Incentive Mechanisms for Provider-assisted Mobile UPIs 140 -- 6.5 Incentive Mechanisms for Large-Scale Systems 143 -- 6.6 Open Challenges in Mobile UPI Incentive Mechanisms 145 -- 6.6.1 Autonomous Mobile UPIs 145 -- 6.6.1.1 Consensus of the Service Provider 145 -- 6.6.1.2 Dynamic Setting 146 -- 6.6.2 Provider-assisted Mobile UPIs 146 -- 6.6.2.1 Modeling the Users 146 -- 6.6.2.2 Incomplete Market Information 147 -- 6.7 Conclusions 147 -- References 148 -- 7 Fog-Based Service Enablement Architecture 151 /Nanxi Chen, Siobhán Clarke, and Shu Chen -- 7.1 Introduction 151 -- 7.1.1 Objectives and Challenges 152 -- 7.2 Ongoing Effort on FogSEA 153 -- 7.2.1 FogSEA Service Description 156 -- 7.2.2 Semantic Data Dependency Overlay Network 158 -- 7.2.2.1 Creation and Maintenance 159 -- 7.2.2.2 Semantic-Based Service Matchmarking 161 -- 7.3 Early Results 164 -- 7.3.1 Service Composition 165 -- 7.3.1.1 SeDDON Creation in FogSEA 167 -- 7.3.2 Related Work 168 -- 7.3.2.1 Semantic-Based Service Overlays 169 -- 7.3.2.2 Goal-Driven Planning 170 -- 7.3.2.3 Service Discovery 171 -- 7.3.3 Open Issue and Future Work 172 -- References 174 -- 8 Software-Defined Fog Orchestration for IoT Services 179 /Renyu Yang, Zhenyu Wen, David McKee, Tao Lin, Jie Xu, and Peter Garraghan.…”
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At a distance : precursors to art and activism on the Internet

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Nano-Biomedical Engineering 2009 : Proceedings of the Tohoku University Global Centre of Excellence Programme Global Nano-Biomedical Engineering Education and Research Network Cent...

Table of Contents: “…Achievement of mechanical assistance by an artificial myocardium using shape memory alloy fibre / Yasuyuki Shiraishi, Tomoyuki Yambe, Dai Homma. …”
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Handbook of safety principles

Table of Contents: “…Success or Failure / Ann Enander -- 30.8. Relations to Other Safety Principles / Ann Enander -- References / Ann Enander -- Further Reading / Ann Enander -- 31. …”
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Introduction to OFDM receiver design and simulation by Liu, Y. J.

Table of Contents: “…2.2 Data Transmission Rate -- 2.3 Bandpass Signals -- 2.4 Digitally Modulated Signals -- 2.4.1 PAM -- 2.4.2 PSK -- 2.4.3 QAM -- 2.4.4 FSK -- 2.5 Pulse Shaping -- 2.6 Summary -- References -- 3 Multicarrier Modulation -- 3.1 Introduction -- 3.2 OFDM Waveform -- 3.3 OFDM Characteristics -- 3.3.1 Orthogonality -- 3.3.2 OFDM Spectrum -- 3.3.3 PAPR -- 3.3.4 Cyclic Prefix -- 3.3.5 FFT -- 3.4 Time and Frequency Parameters -- 3.5 Window Function -- 3.6 Digital Modulation -- 3.7 OFDM Waveform Properties -- 3.8 Summary -- References -- 4 OFDM Transmission -- 4.1 Introduction…”
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Mechanical, Information and Industrial Engineering by Wang, Li

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Thermal Management of Electronics : an Experimental Approach Using Phase-Change-Based Materials in Composite Heat Sinks. by Baby, Rajesh

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Cognitive radio communication and networking : principles and practice by Qiu, Robert C., 1966-

Table of Contents: “…10.3.3 Game Formulation 369 -- 10.3.4 Bayesian Equilibrium 370 -- 10.3.5 Numerical Results 371 -- 10.4 Games in Collaborative Spectrum Sensing 372 -- 10.4.1 False Report Attack 373 -- 10.4.2 Game Formulation 373 -- 10.4.3 Elements of Game 374 -- 10.4.4 Bayesian Equilibrium 376 -- 10.4.5 Numerical Results 379 -- 11 Cognitive Radio Network 381 -- 11.1 Basic Concepts of Networks 381 -- 11.1.1 Network Architecture 381 -- 11.1.2 Network Layers 382 -- 11.1.3 Cross-Layer Design 384 -- 11.1.4 Main Challenges in Cognitive Radio Networks 384 -- 11.1.5 Complex Networks 385 -- 11.2 Channel Allocation in MAC Layer 386 -- 11.2.1 Problem Formulation 386 -- 11.2.2 Scheduling Algorithm 387 -- 11.2.3 Solution 389 -- 11.2.4 Discussion 390 -- 11.3 Scheduling in MAC Layer 391 -- 11.3.1 Network Model 391 -- 11.3.2 Goal of Scheduling 393 -- 11.3.3 Scheduling Algorithm 393 -- 11.3.4 Performance of the CNC Algorithm 395 -- 11.3.5 Distributed Scheduling Algorithm 396 -- 11.4 Routing in Network Layer 396 -- 11.4.1 Challenges of Routing in Cognitive Radio 397 -- 11.4.2 Stationary Routing 398 -- 11.4.3 Dynamic Routing 402 -- 11.5 Congestion Control in Transport Layer 404 -- 11.5.1 Congestion Control in Internet 404 -- 11.5.2 Challenges in Cognitive Radio 405 -- 11.5.3 TP-CRAHN 406 -- 11.5.4 Early Start Scheme 408 -- 11.6 Complex Networks in Cognitive Radio 417 -- 11.6.1 Brief Introduction to Complex Networks 418 -- 11.6.2 Connectivity of Cognitive Radio Networks 421 -- 11.6.3 Behavior Propagation in Cognitive Radio Networks 423 -- 12 Cognitive Radio Network as Sensors 427 -- 12.1 Intrusion Detection by Machine Learning 429 -- 12.2 Joint Spectrum Sensing and Localization 429 -- 12.3 Distributed Aspect Synthetic Aperture Radar 429 -- 12.4 Wireless Tomography 433 -- 12.5 Mobile Crowdsensing 434 -- 12.6 Integration of 3S 435 -- 12.7 The Cyber-Physical System 435 -- 12.8 Computing 436 -- 12.8.1 Graphics Processor Unit 437 -- 12.8.2 Task Distribution and Load Balancing 437 -- 12.9 Security and Privacy 438.…”
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Acoustic emission and durability of composite materials by Godin, Nathalie, Reynaud, Pascal, Fantozzi, G.

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Designing and Researching of Machines and Technologies for Modern Manufacture.

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Danforth's obstetrics and gynecology.

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Artificial intelligence and data mining approaches in security frameworks

Table of Contents: “…87 -- 5.1.2 Purpose of Spamming 88 -- 5.1.3 Spam Filters Inputs and Outputs 88 -- 5.2 Content-Based Spam Filtering Techniques 89 -- 5.2.1 Previous Likeness–Based Filters 89 -- 5.2.2 Case-Based Reasoning Filters 89 -- 5.2.3 Ontology-Based E-Mail Filters 90 -- 5.2.4 Machine-Learning Models 90 -- 5.2.4.1 Supervised Learning 90 -- 5.2.4.2 Unsupervised Learning 90 -- 5.2.4.3 Reinforcement Learning 91 -- 5.3 Machine Learning–Based Filtering 91 -- 5.3.1 Linear Classifiers 91 -- 5.3.2 Naïve Bayes Filtering 92 -- 5.3.3 Support Vector Machines 94 -- 5.3.4 Neural Networks and Fuzzy Logics–Based Filtering 94 -- 5.4 Performance Analysis 97 -- 5.5 Conclusion 97 -- References 98 -- 6 Artificial Intelligence in the Cyber Security Environment 101 Jaya Jain -- 6.1 Introduction 102 -- 6.2 Digital Protection and Security Correspondences Arrangements 104 -- 6.2.1 Operation Safety and Event Response 105 -- 6.2.2 AI2 105 -- 6.2.2.1 CylanceProtect 105 -- 6.3 Black Tracking 106 -- 6.3.1 Web Security 107 -- 6.3.1.1 Amazon Macie 108 -- 6.4 Spark Cognition Deep Military 110 -- 6.5 The Process of Detecting Threats 111 -- 6.6 Vectra Cognito Networks 112 -- 6.7 Conclusion 115 -- References 115 -- 7 Privacy in Multi-Tenancy Frameworks Using AI 119 Shweta Solanki -- 7.1 Introduction 119 -- 7.2 Framework of Multi-Tenancy 120 -- 7.3 Privacy and Security in Multi-Tenant Base System Using AI 122 -- 7.4 Related Work 125 -- 7.5 Conclusion 125 -- References 126 -- 8 Biometric Facial Detection and Recognition Based on ILPB and SVM 129 Shubhi Srivastava, Ankit Kumar and Shiv Prakash -- 8.1 Introduction 129 -- 8.1.1 Biometric 131 -- 8.1.2 Categories of Biometric 131 -- 8.1.2.1 Advantages of Biometric 132 -- 8.1.3 Significance and Scope 132 -- 8.1.4 Biometric Face Recognition 132 -- 8.1.5 Related Work 136 -- 8.1.6 Main Contribution 136 -- 8.1.7 Novelty Discussion 137 -- 8.2 The Proposed Methodolgy 139 -- 8.2.1 Face Detection Using Haar Algorithm 139 -- 8.2.2 Feature Extraction Using ILBP 141 -- 8.2.3 Dataset 143 -- 8.2.4 Classification Using SVM 143 -- 8.3 Experimental Results 145 -- 8.3.1 Face Detection 146 -- 8.3.2 Feature Extraction 146 -- 8.3.3 Recognize Face Image 147 -- 8.4 Conclusion 151 -- References 152 -- 9 Intelligent Robot for Automatic Detection of Defects in Pre-Stressed Multi-Strand Wires and Medical Gas Pipe Line System Using ANN and IoT 155 S K Rajesh Kanna, O. …”
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