Search Results - (((((((ant OR canton) OR mkantis) OR wind) OR cantor) OR anne) OR share) OR hints) algorithms.

Research on Mechanical Engineering, Civil Engineering and Material Engineering : Selected, peer reviewed papers from the 2013 International Conference on Mechanical Engineering, Ci...

Table of Contents: “…Analysis of Working Condition and Load Direction for Tripod Substructure of Offshore Wind TurbineThe Rotation Speed Control of DC Servo Motor Based on Fuzzy-PI Dual Mode; Route Planning of Geomagnetic Aided Navigation for Vehicle under Matching Suitability Constraints; Risk Assessment of Gravity Dam with Machine Properties; Integral Sliding Mode Control Based on Exponential Approach Law for Brushless Double Fed Machines; Temperature Measurement Algorithm Research of Boiler Furnace Based on BP Network…”
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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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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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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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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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Code : Collaborative Ownership and the Digital Economy. by Ghosh, Rishab Aiyer

Table of Contents: “…Oral Traditions, Indigenous Rights, and Valuable Old Knowledge -- 7 From Keeping "Nature's Secrets" to the Institutionalization of "Open Science" -- 8 Benefit Sharing: Experiments in Governance -- 9 Trust among the Algorithms: Ownership, Identity, and the Collaborative Stewardship of Information -- 10 Cooking-Pot Markets and Balanced Value Flows -- 11 Coase's Penguin, or, Linux and the Nature of the Firm -- 12 Paying for Public Goods -- 13 Fencing Off Ideas: Enclosure and the Disappearance of the Public Domain -- 14 A Renaissance of the Commons: How the New Sciences and Internet are Framing a New Global Identity and Order -- 15 Positive Intellectual Rights and Information Exchanges -- 16 Copyright and Globalization in the Age of Computer Networks -- Contributors -- Index.…”
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Pattern Recognition in Computational Molecular Biology : Techniques and Approaches by Elloumi, Mourad, Iliopoulos, Costas, Wang, Jason T. L., Zomaya, Albert Y.

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Mechanisms and games for dynamic spectrum allocation

Table of Contents: “…7.3.10 Other equilibrium concepts -- 7.4 Learning equilibria -- 7.4.1 Learning Nash equilibria -- 7.4.2 Learning epsilon-equilibrium -- 7.4.3 Learning coarse correlated equilibrium -- 7.4.4 Learning satisfaction equilibrium -- 7.4.5 Discussion -- 7.5 Conclusion -- References -- II Cognitive radio and sharing of unlicensed spectrum -- 8 Cooperation in cognitiveradio networks: from accessto monitoring -- 8.1 Introduction -- 8.1.1 Cooperation in cognitive radio: mutual benefits and costs -- 8.2 An overview of coalitional game theory -- 8.3 Cooperative spectrum exploration and exploitation -- 8.3.1 Motivation -- 8.3.2 Basic problem -- 8.3.3 Joint sensing and access as a cooperative game -- 8.3.4 Coalition formation algorithm for joint sensing and access -- 8.3.5 Numerical results -- 8.4 Cooperative primary user activity monitoring -- 8.4.1 Motivation -- 8.4.2 Primary user activity monitoring: basic model -- 8.4.3 Cooperative primary user monitoring -- 8.4.4 Numerical results -- 8.5 Summary -- Acknowledgements -- Copyright notice -- References -- 9 Cooperative cognitive radios with diffusion networks -- 9.1 Introduction -- 9.2 Preliminaries -- 9.2.1 Basic tools in convex and matrix analysis -- 9.2.2 Graphs -- 9.3 Distributed spectrum sensing -- 9.4 Iterative consensus-based approaches -- 9.4.1 Average consensus algorithms -- 9.4.2 Acceleration techniques for iterative consensus algorithms -- 9.4.3 Empirical evaluation -- 9.5 Consensus techniques based on CoMAC -- 9.6 Adaptive distributed spectrum sensing based on adaptive subgradient techniques -- 9.6.1 Distributed detection with adaptive filters -- 9.6.2 Set-theoretic adaptive filters for distributed detection -- 9.6.3 Empirical evaluation -- 9.7 Channel probing -- 9.7.1 Introduction -- 9.7.2 Admissibility problem -- 9.7.3 Power and admission control algorithms.…”
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There's Something about Gödel : The Complete Guide to the Incompleteness Theorem. by Berto, Francesco

Table of Contents: “…. -- 6 ... and the unsatisfied logicists, Frege and Russell -- 7 Bits of set theory -- 8 The Abstraction Principle -- 9 Bytes of set theory -- 10 Properties, relations, functions, that is, sets again -- 11 Calculating, computing, enumerating, that is, the notion of algorithm…”
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Randomness through computation : some answers, more questions

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Calculating the Secrets of Life : Contributions of the Mathematical Sciences to Molecular Biology. by Lander, Eric S.

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R High Performance Programming. by Lim, Aloysius

Table of Contents: “…Data parallelism versus task parallelismImplementing data parallel algorithms; Implementing task parallel algorithms; Running the same task on workers in a cluster; Running different tasks on workers in a cluster; Executing tasks in parallel on a cluster of computers; Shared memory versus distributed memory parallelism; Optimizing parallel performance; Summary; Chapter 9: Offloading Data Processing to Database Systems; Extracting data into R versus processing data in a database; Preprocessing data in a relational database using SQL; Converting R expressions into SQL; Using dplyr…”
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Mathematics and Multi-Ethnic Students : Exemplary Practices. by Germain- Mc Carthy, Yvelyne

Table of Contents: “…LYNNE GODFREY: AFRICAN AMERICANS AND THE ALGEBRA PROJECT; Engaging Students; Warm-Up; Group Work; The Winding Game; Discussion between Colleagues; Commentary; Unit Overview: The Chinese Zodiac and the Division Algorithm; 5. …”
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Hands-On Reinforcement Learning with Python : Master Reinforcement and Deep Reinforcement Learning Using OpenAI Gym and TensorFlow. by Ravichandiran, Sudharsan

Table of Contents: “…Solving the taxi problem using Q learningSARSA; Solving the taxi problem using SARSA; The difference between Q learning and SARSA; Summary; Questions; Further reading; Chapter 6: Multi-Armed Bandit Problem; The MAB problem; The epsilon-greedy policy; The softmax exploration algorithm; The upper confidence bound algorithm; The Thompson sampling algorithm; Applications of MAB; Identifying the right advertisement banner using MAB; Contextual bandits; Summary; Questions; Further reading; Chapter 7: Deep Learning Fundamentals; Artificial neurons; ANNs; Input layer; Hidden layer; Output layer.…”
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Cryptography 101 : From Theory to Practice. by Oppliger, Rolf

Table of Contents: “…12.2.3 Asymmetric Encryption-Based Key Distribution Protocol -- 12.3 KEY AGREEMENT -- 12.4 QUANTUM CRYPTOGRAPHY -- 12.4.1 Basic Principles -- 12.4.2 Quantum Key Exchange Protocol -- 12.4.3 Historical and Recent Developments -- 12.5 FINAL REMARKS -- References -- Chapter 13 Asymmetric Encryption -- 13.1 INTRODUCTION -- 13.2 PROBABILISTIC ENCRYPTION -- 13.2.1 Algorithms -- 13.2.2 Assessment -- 13.3 ASYMMETRIC ENCRYPTION SYSTEMS -- 13.3.1 RSA -- 13.3.2 Rabin -- 13.3.3 Elgamal -- 13.3.4 Cramer-Shoup -- 13.4 IDENTITY-BASED ENCRYPTION -- 13.5 FULLY HOMOMORPHIC ENCRYPTION -- 13.6 FINAL REMARKS -- References -- Chapter 14 Digital Signatures -- 14.1 INTRODUCTION -- 14.2 DIGITAL SIGNATURE SYSTEMS -- 14.2.1 RSA -- 14.2.2 PSS and PSS-R -- 14.2.3 Rabin -- 14.2.4 Elgamal -- 14.2.5 Schnorr -- 14.2.6 DSA -- 14.2.7 ECDSA -- 14.2.8 Cramer-Shoup -- 14.3 IDENTITY-BASED SIGNATURES -- 14.4 ONE-TIME SIGNATURES -- 14.5 VARIANTS -- 14.5.1 Blind Signatures -- 14.5.2 Undeniable Signatures -- 14.5.3 Fail-Stop Signatures -- 14.5.4 Group Signatures -- 14.6 FINAL REMARKS -- References -- Chapter 15 Zero-Knowledge Proofs of Knowledge -- 15.1 INTRODUCTION -- 15.2 ZERO-KNOWLEDGE AUTHENTICATION PROTOCOLS -- 15.2.1 Fiat-Shamir -- 15.2.2 Guillou-Quisquater -- 15.2.3 Schnorr -- 15.3 NONINTERACTIVE ZERO-KNOWLEDGE -- 15.4 FINAL REMARKS -- References -- Part IV CONCLUSIONS -- Chapter 16 Key Management -- 16.1 INTRODUCTION -- 16.1.1 Key Generation -- 16.1.2 Key Distribution -- 16.1.3 Key Storage -- 16.1.4 Key Destruction -- 16.2 SECRET SHARING -- 16.2.1 Shamir's System -- 16.2.2 Blakley's System -- 16.2.3 Verifiable Secret Sharing -- 16.2.4 Visual Cryptography -- 16.3 KEY RECOVERY -- 16.4 CERTIFICATE MANAGEMENT -- 16.4.1 Introduction -- 16.4.2 X.509 Certificates -- 16.4.3 OpenPGP Certificates -- 16.4.4 State of the Art -- 16.5 FINAL REMARKS -- References -- Chapter 17 Summary.…”
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Smart buildings, smart communities and demand response

Table of Contents: “…Demand Response in Smart Zero Energy Buildings and Grids / Nikos Kampelis -- DR in Smart and Near-zero Energy Buildings: The Leaf Community / Nikos Kampelis, Konstantinos Gobakis, Vagias Vagias, Denia Kolokotsa, Laura Standardi, Daniela Isidori, Cristina Cristalli, Fabio Maria Montagnino, Filippo Paredes, Pietro Muratore, Luca Venezia, Marina Kyprianou Dracou, Alaric Montenon, Andri Pyrgou, Theoni Karlessi, Mattheos Santamouris -- Performance of Industrial and Residential Near-zero Energy Buildings / Nikos Kampelis, Konstantinos Gobakis, Vagias Vagias, Denia Kolokotsa, Laura Standardi, Daniela Isidori, Cristina Cristalli, Fabio Maria Montagnino, Filippo Paredes, Pietro Muratore, Luca Venezia, Marina Kyprianou Dracou, Alaric Montenon, Andri Pyrgou, Theoni Karlessi, Mattheos Santamouris -- HVAC Optimization Genetic Algorithm for Industrial Near-Zero Energy Building Demand Response / Nikos Kampelis, Nikolaos Sifakis, Denia Kolokotsa, Konstantinos Gobakis, Konstantinos Kalaitzakis, Daniela Isidori, Cristina Cristalli -- Smart Grid/Community Load Shifting GA Optimization Based on Day-ahead ANN Power Predictions / Nikos Kampelis, Elisavet Tsekeri, Denia Kolokotsa, Konstantinos Kalaitzakis, Daniela Isidori, Cristina Cristalli -- Conclusions and Recommendations.…”
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Short-Circuit Withstand Capability of Power Transformers. by Geißler, Daniel Hermann

Table of Contents: “…4.5.3 FEA Model Validation4.5.4 FEA Model for Bonded CTCs; 5 Dynamic Short-Circuit Forces Test Stand; 5.1 Design and Principal Functionality; 5.2 Deformation Measurement Systems; 5.2.1 Acceleration Sensors; 5.2.1.1 Immunity to Magnetic Fields; 5.2.1.2 Mounting to the Windings; 5.2.1.3 Signal Processing; 5.2.2 High-Speed Camera-Based Deformation Tracking; 5.2.2.1 Principal Functionality; 5.2.2.2 Marker Mounting and Image Calibration; 5.2.2.3 Displacement Calculation Algorithm; 5.2.3 Comparison of Both Systems; 5.3 Measurement Data Evaluation; 5.4 Experimental Results.…”
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