Search Results - (((((((anti OR wkant) OR semantic) OR wind) OR cantor) OR anne) OR shape) OR hints) algorithms.

  1. 521

    Handbook of safety principles

    Published 2018
    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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  2. 522

    Introduction to OFDM receiver design and simulation by Liu, Y. J.

    Published 2020
    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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  3. 523

    Lippincott's primary care orthopaedics

    Published 2014
    Table of Contents: “…The Use of Nonsteroidal Anti-Inflammatory Drugs / Chadwick R. Johr -- 66. …”
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  4. 524

    Mechanical, Information and Industrial Engineering by Wang, Li

    Published 2015
    Full text (MFA users only)
    Electronic Conference Proceeding eBook
  5. 525

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

    Published 2012
    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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  6. 526
  7. 527

    Designing and Researching of Machines and Technologies for Modern Manufacture.

    Published 2015
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    Electronic Conference Proceeding eBook
  8. 528

    Danforth's obstetrics and gynecology.

    Published 2008
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  9. 529

    Artificial intelligence and data mining approaches in security frameworks

    Published 2021
    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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  10. 530

    Evolutionary Robust Control. by Feyel, Philippe

    Published 2017
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  11. 531

    Ecological modelling for sustainable development

    Published 2013
    Table of Contents: “…Ismail -- Modelling of Climatological Wind-Driven Circulation and Thermohaline Structures of Peninsular Malaysia's Eastern Continental Shelf using Princeton Ocean Model-Halimatun Muhamad , Fredolin T. …”
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  12. 532

    Stirling Cycle Engines : Inner Workings and Design. by Organ, Allan J.

    Published 2013
    Table of Contents: “…-- 3.6 The way forward -- 4 Equivalence conditions for volume variations -- 4.1 Kinematic configuration -- 4.2 'Additional' dead space -- 4.3 Net swept volume -- 5 The optimum versus optimization -- 5.1 An engine from Turkey rocks the boat -- 5.2 ... and an engine from Duxford -- 5.3 Schmidt on Schmidt -- 5.3.1 Volumetric compression ratio rv -- 5.3.2 Indicator diagram shape -- 5.3.3 More from the re-worked Schmidt analysis -- 5.4 Crank-slider mechanism again -- 5.5 Implications for engine design in general -- 6 Steady-flow heat transfer correlations -- 6.1 Turbulent -- or turbulent? …”
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  13. 533

    Non-alcoholic fatty liver disease : a practical guide

    Published 2013
    Table of Contents: “…Genetic modifiers of fibrogenesis and disease progression -- Conclusions -- Multiple choice questions -- References -- Answers to multiple choice questions -- Chapter 15: NAFLD in children -- Epidemiology -- Natural history -- Signs and symptoms -- Diagnosis -- Liver biopsy -- Blood biomarkers -- Imaging techniques -- Treatment -- Nonpharmacological interventions -- Medications -- Insulin-sensitizing agents -- Hepatoprotective anti-oxidant therapy -- Other therapies -- Conclusions -- Multiple choice questions -- References -- Answers to multiple choice questions -- Chapter 16: The pointy end of the NAFLD iceberg: cirrhosis, portal hypertension, and liver failure -- Disclaimer -- Introduction -- Epidemiology -- Progression of NASH to cirrhosis -- Cryptogenic cirrhosis -- Histopathology of late NAFLD and cirrhosis -- Clinical outcomes of advanced NAFLD and cirrhosis -- Diagnosis and presentation -- Treatment of NAFLD cirrhosis and complications -- Transplant considerations -- Conclusions and future directions -- Multiple choice questions -- References -- Answers to multiple choice questions -- Chapter 17: Non-alcoholic fatty liver disease, hepatocellular cancer, and other cancers -- Incidence and epidemiology of HCC -- Risk factors for HCC -- NAFLD, metabolic syndrome, and HCC -- HCC can develop in noncirrhotic NAFLD -- NAFLD, the metabolic syndrome, and other cancers -- Obesity and cancer -- Diabetes and cancer -- The pathogenesis of HCC in NAFLD -- The management of HCC arising in patients with the metabolic syndrome -- Surveillance -- The diagnosis of HCC -- Staging of HCC -- Treatment options for HCC -- Surgical resection -- Liver transplantation -- Percutaneous treatments -- Transcatheter arterial chemoembolization (TACE) -- Medical management of HCC -- A modified BCLC algorithm for patients with NAFLD and the metabolic syndrome.…”
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  14. 534

    Aerospace Sensors. by Nebylov, Alexander

    Published 2012
    Table of Contents: “…Principles and examples of sensor integration -- 9.1 Sensor systems -- 9.1.1 The sensor system concept -- 9.1.2 Joint processing of readings from identical sensors -- 9.1.3 Joint processing of readings from cognate sensors with different measurement ranges -- 9.1.4 Joint processing of diverse sensors readings -- 9.1.5 Linear and nonlinear sensor integration algorithms -- 9.2 Fundamentals of integrated measuring system synthesis -- 9.2.1 Synthesis problem statement -- 9.2.2 Classes of dynamic system realization -- 9.2.3 Measurement accuracy indices -- 9.2.4 Excitation properties -- 9.2.5 Objective functions for robust system optimisation -- 9.2.6 Methods of dynamic system accuracy index analysis under excitation with given numerical characteristics of derivatives -- 9.2.6.1 Estimation of error variance -- 9.2.6.2 Example of error variance analysis -- 9.2.6.3 Use of equivalent harmonic excitation -- 9.2.6.4 Estimation of error maximal value -- 9.2.7 System optimization under maximum accuracy criteria -- 9.2.8 Procedures for the dimensional reduction of a measuring system -- 9.2.8.1 Determination of an optimal set of sensors -- 9.2.8.2 Analysis of the advantages of invariant system construction -- 9.2.8.3 Advantages of the zeroing of several system parameters -- 9.2.9 Realization and simulation of integration algorithms -- 9.3 Examples of two-component integrated navigation systems -- 9.3.1 Noninvariant robust integrated speed meter -- 9.3.2 Integrated radio-inertial measurement -- 9.3.3 Airborne gravimeter integration -- 9.3.4 The orbital verticant -- References…”
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  15. 535
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  17. 537

    Power system monitoring and control by Bevrani, Hassan

    Published 2014
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  18. 538

    XML for DB2 information integration

    Published 2004
    Table of Contents: “…-- 3.4 Creating an XML schema from a database schema -- 3.4.1 The algorithm.…”
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  19. 539
  20. 540

    Software engineering for embedded systems : methods, practical techniques, and applications

    Published 2013
    Table of Contents: “…-- Kinds of software reuse -- Implementing reuse by layers -- Going to the next level -- Introducing the component factory -- Factory hardware configuration -- Factory software configuration -- How the factory aids reusability -- RTOS agnosticism -- Arbitrary extensibility -- Conclusion -- References -- Example: latency vs. throughput in an eNodeB application -- Performance patterns and anti-patterns -- References -- The code optimization process -- Using the development tools -- Compiler optimization -- Basic compiler configuration -- Enabling optimizations -- Additional optimization configurations -- Using the profiler -- Background -- understanding the embedded architecture -- Resources -- Basic C optimization techniques -- Choosing the right data types -- Functions calling conventions -- Pointers and memory access -- Restrict and pointer aliasing -- Loops -- Additional tips and tricks -- General loop transformations -- Loop unrolling -- Multisampling -- Partial summation -- Software pipelining -- Example application of optimization techniques: cross-correlation -- Setup -- Original implementation -- Step 1: use intrinsics for fractional operations and specify loop counts -- Step 2: specify data alignment and modify for multisampling algorithm -- Step 3: assembly-language optimization -- Introduction -- Code size optimizations -- Compiler flags and flag mining -- Target ISA for size and performance tradeoffs -- Tuning the ABI for code size -- Caveat emptor: compiler optimization orthogonal to code size! …”
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