Search Results - (((((((ant OR kind) OR semantic) OR win) OR cantor) OR anne) OR share) OR hints) algorithms.

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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Quantum theory : a philosopher's overview by Cannavo, S. (Salvator)

Table of Contents: “…6. Explanatory and Algorithmic Nomologicals: Of Which Kind is Quantum Theory?…”
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Accelerating MATLAB with GPU computing : a primer with examples by Suh, Jung W., Kim, Youngmin

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Parallel Computing : Advances and Current Issues, Proceedings of the International Conference Parco2001. by Joubert, G. R.

Table of Contents: “…Committees ; Preface ; Invited Papers ; Deploying Parallel Numerical Library Routines to Cluster Computing in a Self Adapting Fashion ; 1 Overview ; 2 Numerical libraries in shared homogeneous distributed environments ; 3 Sample software implementation and results.…”
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Iterative learning control for multi-agent systems coordination by Yang, Shiping, 1987-, Xu, Jian-Xin, Li, Xuefang, 1985-, Shen, Dong, 1982-

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Methods for solving operator equations by Tanana, V. P. (Vitaliĭ Pavlovich)

Table of Contents: “…. -- Â3.2 Approximate solution of implicit operator equations of the first kind by the regularization method…”
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Advances in time series forecasting. Volume 2

Table of Contents: “…INTRODUCTION -- CLASSICAL TIME SERIES FORECASTING MODELS -- ARTIFICIAL NEURAL NETWORKS FOR FORECASTING TIME SERIES -- A NEW ARTIFICIAL NEURAL NETWORK WITH DETERMINISTIC COMPONENTS -- APPLICATIONS -- CONCLUSION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENTS -- REFERENCES -- A Fuzzy Time Series Approach Based on Genetic Algorithm with Single Analysis Process -- Ozge Cagcag Yolcu* -- INTRODUCTION -- FUZZY TIME SERIES -- RELATED METHODS -- Genetic Algorithm (GA) -- Single Multiplicative Neuron Model -- PROPOSED METHOD -- APPLICATIONS -- CONCLUSION AND DISCUSSION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENTS -- REFERENCES -- Forecasting Stock Exchanges with Fuzzy Time Series Approach Based on Markov Chain Transition Matrix -- Cagdas Hakan Aladag1,* and Hilal Guney2 -- INTRODUCTION -- FUZZY TIME SERIES -- TSAUR 'S FUZZY TIME SERIES MARKOV CHAIN MODEL -- THE IMPLEMENTATION -- CONCLUSION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENTS -- REFERENCES -- A New High Order Multivariate Fuzzy Time Series Forecasting Model -- Ufuk Yolcu* -- INTRODUCTION -- RELATED METHODOLOGY -- The Fuzzy C-Means (FCM) Clustering Method -- Single Multiplicative Neuron Model Artificial Neural Network (SMN-ANN) -- Fuzzy Time Series -- THE PROPOSED METHOD -- APPLICATIONS -- CONCLUSIONS AND DISCUSSION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENTS -- REFERENCES -- Fuzzy Functions Approach for Time Series Forecasting -- Ali Z. …”
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Automatic Text Summarization by Torres-Moreno, Juan-Manuel

Table of Contents: “…State-of-the-art approaches; 3.4. Latent semantic analysis; 3.5. Graph-based approaches; 3.6. …”
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Scientific computing with multicore and accelerators

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Stochastic Models in Reliability Engineering. by Cui, Lirong

Table of Contents: “…4.3.1 Run and Phrase -- 4.3.2 Multi-State Compression Algorithm -- 4.4 Proposed Multi-State Inference Algorithm -- 4.4.1 Rules for Calculating Intermediate Variables -- 4.4.2 Proposed Multi-State Inference Algorithm -- 4.5 Case Study -- 4.5.1 Case Background -- 4.5.2 Calculation and Analysis -- 4.6 Summary -- Appendix A -- Appendix B -- References -- Chapter 5 Reliability Analysis of Demand-Based Warm Standby System with Multi-State Common Bus -- 5.1 Introduction -- 5.2 Model Description for a DBWSS with Multi-State Common Bus Performance Sharing…”
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Engineering Internet QoS by Jha, Sanjay

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Empirical model building : data, models, and reality by Thompson, James R. (James Robert), 1938-

Table of Contents: “…Modular Data-Based Wargaming; 2.3.1. Herman Kahn and the Winning of the Cold War.…”
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PRINCIPLES OF QUANTUM ARTIFICIAL INTELLIGENCE. by Wichert, Andreas

Table of Contents: “…Computation; 2.1 Entscheidungsproblem; 2.1.1 Cantor's diagonal argument; 2.1.2 Reductio ad absurdum; 2.2 Complexity Theory; 2.2.1 Decision problems; 2.2.2 P and NP; 2.3 Church-Turing Thesis; 2.3.1 Church-Turing-Deutsch principle; 2.4 Computers; 2.4.1 Analog computers; 2.4.2 Digital computers; 2.4.3 Von Neumann architecture; 3. …”
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Hands-On Blockchain with Hyperledger : Building Decentralized Applications with Hyperledger Fabric and Composer. by Baset, Salman

Table of Contents: “…Decentralization with systemic governanceEnterprise support; Use case-driven pluggability choices; Shared ledger technology; Consensus; Crypto algorithms and encryption technology; Use case-driven pluggable choices; Enterprise integration and designing for extensibility; Other considerations; Consensus, ACID property, and CAP; CAP; ACID; Attestation -- SSCs are signed and encrypted; Use of HSMs; Summary; Chapter 2: Exploring Hyperledger Fabric; Building on the foundations of open computing; Fundamentals of the Hyperledger project; The Linux Foundation ; Hyperledger.…”
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Power and energy systems III : selected, peer reviewed papers from the 2013 3rd International Conference on Power and Energy Systems (ICPES 2013), November 23-24, Bangkok, Thailand

Table of Contents: “…Appropriate Electric Energy Conservation Measures for Big Mosques in Riyadh CityBayesian Algorithm Based on Airborne Power Supply System; Study on the Cooling System of Super-Capacitors for Hybrid Electric Vehicle; A Charging Management of Electric Vehicles Based on Campus Survey Data; Back-EMF Position Detection Technology for Brushless DC Motor; Stress State of Turbine Blade Root and Rim Considering Manufacturing Variations; Analysis on a Gas Turbine Sealing Disk Structure and Material Strength; A Kind of Adjustable Electric Heating Pipe Power Electrode Preparation Equipment.…”
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Methods and Interdisciplinarity

Table of Contents: “…Towards a win-win collaboration; 2.3.3. Geography in all digital objects; 2.4. …”
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Aggregating Dialectology, Typology, and Register Analysis : Linguistic Variation in Text and Speech

Table of Contents: “…Kretzschmar -- A weakly supervised multivariate approach to the study of language variation / Sascha Diwersy, Stefan Evert, and Stella Neumann -- Semantic weighting mechanisms in scalable lexical sociolectometry / Tom Ruette, Dirk Geeraerts, Yves Peirsman and Dirk Speelman -- Temperature in the word space : Sense exploration of temperature expressions using word-space modelling / Maria Koptjevskaja-Tamm and Magnus Sahlgren -- The perfect map : Investigating the cross-linguistic distribution of TAME categories in a parallel corpus / Östen Dahl -- Explorations into variation across Slavic : Taking a bottom-up approach / Ruprecht von Waldenfels -- Where Alice fell into : Motion events from a parallel corpus / Annemarie Verkerk -- Algorithmic typology and going from known to similar unknown categories within and across languages / Bernhard Wälchli -- Inducing place distinctions of consonants from their distribution in words / Thomas Mayer -- Laws of language and text in quantitative and synergetic linguistics / Reinhard Köhler.…”
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Goliath's revenge : how established companies turn the tables on digital disruptors by Hewlin, Todd, Snyder, Scott A. (Scott Andrew), 1965-

Table of Contents: “…Chapter 6 Rule 3: Use Your Data as CurrencySome Historical Context; Entertainment Goes Left Brain; Moneyball Wins Games; Build Your Data Balance Sheet; Think Broadly about Your Data Assets; Understand Your Data Liabilities; Rate the Quality of Each Data Asset; Pay Special Attention to the Edge; Value Data Optionality; Maximize Return on Data; Digital Customer Segments; Master Machine Learning; The Weather Channel; Rule 3: Company and Career Readiness; Company Readiness Self-Assessment; Career Readiness Self-Assessment; Rule 3 Readiness Summary; Note…”
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Cognitive Electronic Warfare : An Artificial Intelligence Approach. by Haigh, Karen

Table of Contents: “…-- 1.5 Reader's Guide -- 1.6 Conclusion -- References -- 2 Objective Function -- 2.1 Observables That Describe the Environment -- 2.1.1 Clustering Environments -- 2.2 Control Parameters to Change Behavior -- 2.3 Metrics to Evaluate Performance -- 2.4 Creating a Utility Function -- 2.5 Utility Function Design Considerations -- 2.6 Conclusion -- References -- 3 ML Primer -- 3.1 Common ML Algorithms -- 3.1.1 SVMs -- 3.1.2 ANNs -- 3.2 Ensemble Methods -- 3.3 Hybrid ML -- 3.4 Open-Set Classification -- 3.5 Generalization and Meta-learning -- 3.6 Algorithmic Trade-Offs -- 3.7 Conclusion -- References -- 4 Electronic Support -- 4.1 Emitter Classification and Characterization -- 4.1.1 Feature Engineering and Behavior Characterization -- 4.1.2 Waveform Classification -- 4.1.3 SEI -- 4.2 Performance Estimation -- 4.3 Multi-Intelligence Data Fusion -- 4.3.1 Data Fusion Approaches -- 4.3.2 Example: 5G Multi-INT Data Fusion for Localization -- 4.3.3 Distributed-Data Fusion -- 4.4 Anomaly Detection -- 4.5 Causal Relationships -- 4.6 Intent Recognition -- 4.6.1 Automatic Target Recognition and Tracking -- 4.7 Conclusion -- References -- 5 EP and EA -- 5.1 Optimization -- 5.1.1 Multi-Objective Optimization -- 5.1.2 Searching Through the Performance Landscape -- 5.1.3 Optimization Metalearning -- 5.2 Scheduling -- 5.3 Anytime Algorithms -- 5.4 Distributed Optimization -- 5.5 Conclusion.…”
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Pulmonary arterial hypertension : diagnosis and evidence-based treatment

Table of Contents: “…Combination therapy in pulmonary arterial hypertension / Anne Keogh and Marius Hoeper -- Interventional and surgical modalities of treatment for pulmonary arterial hypertension / Julio Sandoval and Ramona Doyle -- End points and clinical trial design in pulmonary arterial hypertension : clinical and regulatory perspectives / Andrew J. …”
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