Search Results - (((((((kent OR kwantis) OR wantsi) OR markant) OR cantor) OR anne) OR shared) OR hints) algorithms.

Information Networking in Asia

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Lead generation for dummies by Rothman, Dayna

Table of Contents: “…Creating an Internal Blogging ProgramChapter 9: Creating Lasting Relationships Through Social Media; Sharing on Social Media; Getting the Most out of Facebook; Leveraging Twitter; Engaging Through LinkedIn; Building Your Google+ Presence; Getting Visual with Pinterest; Attracting Attention with SlideShare; Chapter 10: Getting Found Through Search Engine Optimization; Maximizing Different Traffic Sources; Knowing Your Search Engines; Making the Most out of Google Algorithm Updates; Choosing Your Keywords; Perfecting On-Page SEO; Utilizing Links in a Natural Way.…”
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Topology '90

Table of Contents: “…(p-1)/2Tangles in Prisms, Tangles in Cobordisms -- A Computational Algorithm of Spectral Flow in Floer Homology…”
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Global optimization methods in geophysical inversion by Sen, Mrinal K.

Table of Contents: “…5.6 Multimodal fitness functions, genetic drift, GA with sharing, and repeat (parallel) GA -- 5.7 Uncertainty estimates -- 5.8 Evolutionary programming -- a variant of GA -- 5.9 Summary -- 6 Other stochastic optimization methods -- 6.1 The neighborhood algorithm (NA) -- 6.1.1 Voronoi diagrams -- 6.1.2 Voronoi diagrams in SA and GA -- 6.1.3 Neighborhood sampling algorithm -- 6.2 Particle swarm optimization (PSO) -- 6.3 Simultaneous perturbation stochastic approximation (SPSA) -- 7 Geophysical applications of simulated annealing and genetic algorithms -- 7.1 1D seismic waveform inversion -- 7.1.1 Application of heat bath SA -- 7.1.2 Application of GAs -- 7.1.3 Real-data examples -- 7.1.4 Hybrid GA/LI inversion using different measures of fitness -- 7.1.5 Hybrid VFSA inversion using different strategies -- 7.2 Prestack migration velocity estimation -- 7.2.1 1D earth structure -- 7.2.2 2D earth structure -- 7.2.3 Multiple and simultaneous VFSA for imaging -- 7.3 Inversion of resistivity sounding data for 1D earth models -- 7.3.1 Exact parameterization -- 7.3.2 Overparameterization with smoothing -- 7.4 Inversion of resistivity profiling data for 2D earth models -- 7.4.1 Inversion of synthetic data -- 7.4.2 Inversion of field data -- 7.5 Inversion of magnetotelluric sounding data for 1D earth models -- 7.6 Stochastic reservoir modeling -- 7.7 Seismic deconvolution by mean field annealing (MFA) and Hopfield network -- 7.7.1 Synthetic example -- 7.7.2 Real-data example -- 7.8 Joint inversion -- 7.8.1 Joint travel time and gravity inversion -- 7.8.2 Time-lapse (4D) seismic and well production joint inversion -- 8 Uncertainty estimation -- 8.1 Methods of numerical integration -- 8.1.1 Grid search or enumeration -- 8.1.2 Monte Carlo integration -- 8.1.3 Importance sampling -- 8.1.4 Multiple MAP estimation -- 8.2 Simulated annealing: the Gibbs sampler.…”
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Limits, Limits Everywhere : the Tools of Mathematical Analysis by Applebaum, David, 1956-

Table of Contents: “…Continued Fractions; 9.1 Euclid's Algorithm; 9.2 Rational and Irrational Numbers as Continued Fractions; 10. …”
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Legitimate applications of peer to peer networks by Verma, Dinesh C.

Table of Contents: “…-- Organization of the Book -- 1 The Peer-to-Peer Architecture -- 1.1 Distributed Applications -- 1.1.1 A Distributed Computing Example -- 1.1.2 Client-Server Architecture -- 1.1.3 Peer-to-Peer Architecture -- 1.2 The Peer-to-Peer Software Structure -- 1.2.1 Base Overlay Layer -- 1.2.2 Middleware Functions -- 1.2.3 Application Layer -- 1.3 Comparison of Architectures -- 1.3.1 Ease of Development -- 1.3.2 Manageability -- 1.3.3 Scalability -- 1.3.4 Administrative Domains -- 1.3.5 Security -- 1.3.6 Reliability -- 2 Peer Discovery and Overlay Formation -- 2.1 Discovery -- 2.1.1 Static Configuration -- 2.1.2 Centralized Directory -- 2.1.3 Using the Domain Name Service -- 2.1.4 Member Propagation Techniques with Initial Member Discovery -- 2.2 Overlay Formation -- 2.2.1 Creating an Overlay Link -- 2.3 Topology Selection -- 2.3.1 Random Mesh Formation -- 2.3.2 Tiered Formation -- 2.3.3 Ordered Lattices -- 3 Application-Layer Multicast -- 3.1 General Multicast Techniques -- 3.1.1 Group Addressing -- 3.1.2 Group Maintenance -- 3.1.3 Message Forwarding Scheme -- 3.1.4 Multicast Routing -- 3.1.5 Secure Multicast -- 3.1.6 Reliable Multicast -- 3.1.7 Multicast Flow and Congestion Control -- 3.2 Network-Layer Multicast"IP Multicast -- 3.2.1 Problems with IP-Layer Multicast -- 3.3 Application-Layer Multicast -- 3.3.1 Broadcast Mechanisms in Peer-to-Peer Networks -- 3.3.2 Multicast in Peer-to-Peer Overlays -- 4 File-Sharing Applications -- 4.1 File-Sharing Overview -- 4.1.1 Disk Space Management -- 4.1.2 File Indexing -- 4.1.3 File Search/Retrieval -- 4.1.4 Access Control and Security -- 4.1.5 Anonymous File Retrieval -- 4.1.6 Search Acceleration Techniques -- 4.1.7 Digital Rights Management -- 4.2 Usage of File-Sharing Applications -- 4.2.1 Limitations of File-Sharing Applications -- 4.3 Preventing Unauthorized File Sharing -- 4.3.1 Firewall-Based Techniques -- 4.3.2 Asset Inventory -- 4.3.3 Port Scanning -- 4.3.4 Usage-Based Rate Control -- 4.3.5 Malicious Participation -- 5 File Storage Service -- 5.1 Handle Management -- 5.2 Retrieving Files with Handles -- 5.2.1 Circular Ring Routing -- 5.2.2 Plaxton Scheme -- 5.2.3 CAN Routing Algorithm -- 5.2.4 Modified Network Routing Schemes -- 5.2.5 Modified Broadcast -- 5.3 Miscellaneous Functions -- 5.3.1 Access Control -- 5.3.2 Availability and Reliability -- 5.4 Usage Scenarios -- 5.4.1 Distributed File Systems -- 5.4.2 Anonymous Publishing -- 6 Data Backup Service -- 6.1 The Traditional Data Management System -- 6.2 The Peer-to-Peer Data Management System -- 6.2.1 The Backup/Restore Manager -- 6.2.2 The Peer Searcher -- 6.2.3 The File Searcher -- 6.2.4 The Properties Manager -- 6.2.5 The Data Manager -- 6.2.6 The Schedule Manager -- 6.3 Security Issues -- 6.4 Hybrid Data Management Approach -- 6.5 Feasibility of Peer-to-Peer Data Backup Service -- 7 Peer-to-Peer Directory System -- 7.1 LDAP Dir.…”
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Digital journalism, drones, and automation : the language and abstractions behind the news by Dowd, Cate

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Microbiological sensors for the drinking water industry

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Multicriteria decision aid and artificial intelligence : links, theory and applications by Doumpos, Michael

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Combinatorial and Computational Mathematics : Present and Future.

Table of Contents: “…2 LIST OF APPLICABLE MATHEMATICS IN SOCIAL SCIENCE3 SOCIAL WELFARE FUNCTIONS (SWF); 4 PROSPECTS; 5 OPEN PROBLEMS; References; Twelve Views of Matroid Theory; INTRODUCTION; 1 LINEAR DEPENDENCE WITHOUT SCALARS; 2 BASIS EXCHANGE PROPERTIES; 3 GEOMETRIC LATTICES; 4 GRAPH THEORY WITHOUT VERTICES; 5 GRAPH THEORY AND LEAN LINEAR ALGEBRA; 6 VARIETIES OF FINITE MATROIDS; 7 SECRET-SHARING MATROIDS; 8 GREEDY ALGORITHMS, MATROID INTERSECTION, AND MATROID PARTITION; 9 MATRIX MULTIPLICATION AND THE CAUCHY-BINET IDENTITY; 10 BASIS GENERATING FUNCTIONS AND THE MATRIX-TREE THEOREM…”
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Entity information life cycle for big data : master data management and information integration by Talburt, John R., Zhou, Yinle, 1986-

Table of Contents: “…CLUSTER-TO-CLUSTER CLASSIFICATIONSELECTING AN APPROPRIATE ALGORITHM; CONCLUDING REMARKS; Chapter 9 -- Blocking; BLOCKING; BLOCKING BY MATCH KEY; DYNAMIC BLOCKING VERSUS PRERESOLUTION BLOCKING; BLOCKING PRECISION AND RECALL; MATCH KEY BLOCKING FOR BOOLEAN RULES; MATCH KEY BLOCKING FOR SCORING RULES; CONCLUDING REMARKS; Chapter 10 -- CSRUD for Big Data; LARGE-SCALE ER FOR MDM; THE TRANSITIVE CLOSURE PROBLEM; DISTRIBUTED, MULTIPLE-INDEX, RECORD-BASED RESOLUTION; AN ITERATIVE, NONRECURSIVE ALGORITHM FOR TRANSITIVE CLOSURE; ITERATION PHASE: SUCCESSIVE CLOSURE BY REFERENCE IDENTIFIER.…”
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Systemic Risk from Global Financial Derivatives. by Markose, Sheri M.

Table of Contents: “…FDIC FIs as Participants in the Five Financial Derivatives Markets; Tables; 1. Value and Market Share of Financial Derivatives for 202 FIs; B. Market Data Based Systemic Risk Measures and Financial Network Perspective; III. …”
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Advanced wireless networks : technology and business models by Glisic, Savo G.

Table of Contents: “…16.1 Introduction 523 -- 16.2 Layering as Optimization Decomposition 524 -- 16.3 Cross-Layer Optimization 533 -- 16.4 Optimization Problem Decomposition Methods 543 -- References 554 -- 17 Network Information Theory 557 -- 17.1 Capacity of Ad Hoc Networks 557 -- 17.2 Information Theory and Network Architectures 569 -- 17.3 Cooperative Transmission in Wireless Multihop Ad Hoc Networks 577 -- References 584 -- 18 Stability of Advanced Network Architectures 585 -- 18.1 Stability of Cooperative Cognitive Wireless Networks 585 -- 18.2 System Model 586 -- 18.4 Optimal Control Policy 592 -- 18.5 Achievable Rates 594 -- 18.6 Stabilizing Transmission Policies 598 -- References 605 -- 19 Multi-Operator Spectrum Sharing 607 -- 19.1 Business Models for Spectrum Sharing 607 -- 19.2 Spectrum Sharing in Multi-hop Networks 638 -- References 656 -- 20 Large Scale Networks and Mean Field Theory 659 -- 20.1 MFT for Large Heterogeneous Cellular Networks 659 -- 20.2 Large Scale Network Model Compression 664 -- 20.3 Mean Field Theory Model of Large Scale DTN Networks 668 -- 20.4 Mean Field Modeling of Adaptive Infection Recovery in Multicast DTN Networks 674 -- 20.5 Mean Field Theory for Scale-Free Random Networks 701 -- 20.6 Spectrum Sharing and MFT 709 -- 20.7 Modeling Dynamics of Complex System 711 -- Appendix A.20 Iterative Algorithm to Solve Systems of Nonlinear ODEs (DiNSE-Algorithm) 721 -- Appendix B.20 Infection Rate of Destinations for DNCM 722 -- Appendix C.20 Infection Rate for Basic Epidemic Routing 722 -- References 722 -- 21 mmWave Networks 726 -- 21.1 mmWave Technology in Subcellular Architecture 726 -- 21.2 Microeconomics of Dynamic mmWave Networks 737 -- References 747 -- 22 Cloud Computing in Wireless Networks 750 -- 22.1 Technology Background 750 -- 22.2 System Model 752 -- 22.3 System Optimization 756 -- 22.4 Dynamic Control Algorithm 758 -- 22.5 Achievable Rates 761 -- 22.6 Stabilizing Control Policies 763 -- References 769 -- 23 Wireless Networks and Matching Theory 771.…”
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Reconfigurable computing : the theory and practice of FPGA-based computation

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Wireless sensor systems for extreme environments : space, underwater, underground and industrial

Table of Contents: “…Chapter 4 On Improving Connectivity-based Localization in Wireless Sensor Networks4.1 Introduction; 4.2 Connectivity-based Localization in One-hop Networks; 4.2.1 The Centroid Algorithm; 4.2.2 Improved Centroid Algorithms; 4.3 Connectivity-based Localization in Multi-hop Networks; 4.3.1 The DV-hop Algorithm; 4.3.2 Mathematics of Hop-count-based Localization; 4.4 On Improving Connectivity-based Localization; 4.4.1 Improvements by Adjusting Correction Factor; 4.4.2 Improvements by Exploiting Neighborhood Information; 4.5 Summary; References.…”
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Debates in the digital humanities 2016

Table of Contents: “…Father Busa Female Punch Card Operatives / Melissa Terras and Julianne Nyhan -- On the Origin of "Hack" and "Yack" / Bethany Nowviskie -- Reflections on a Movement: #transformDH, Growing Up / Moya Bailey, Anne Cong-Huyen, Alexis Lothian, and Amanda Phillips.…”
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Multi-processor system-on-chip. 1, Architectures

Table of Contents: “…Matrix multiplication algorithm on the Plural architecture…”
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Informatics and technology in clinical care and public health

Table of Contents: “…Intro -- Title Page -- Preface -- ICIMTH 2021 Scientific Programme Committee and Reviewers -- Contents -- Using Artificial Intelligence to Develop a Lexicon-Based African American Tweet Detection Algorithm to Inform Culturally Sensitive Twitter-Based Social Support Interventions for African American Dementia Caregivers -- A Comparison of Word Embeddings to Study Complications in Neurosurgery -- Gulf Cooperation Council Clinical Trials in the Pursuit of Medications for COVID-19…”
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Emerging engineering approaches and applications : selected, peer reviewed papers from the 2011 International Conference on Information Engineering for Mechanics and Materials, Aug...

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Deep Learning with TensorFlow : Explore neural networks and build intelligent systems with Python, 2nd Edition. by Zaccone, Giancarlo

Table of Contents: “…; Artificial neural networks; The biological neurons; The artificial neuron; How does an ANN learn?; ANNs and the backpropagation algorithm; Weight optimization; Stochastic gradient descent; Neural network architectures; Deep Neural Networks (DNNs); Multilayer perceptron; Deep Belief Networks (DBNs).…”
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