Search Results - (((((((ant OR wantsa) OR wkanted) OR art) OR cantor) OR anne) OR wares) OR mkantis) algorithms.

Ultrashort Pulse Laser Ablation of Bulk Materials Using Shaped Laser Beams. by Mikhaylov, Dmitriy

Table of Contents: “…Intro -- 1 Introduction -- 2 Theoretical principles and state of the art -- 2.1 Ultrashort pulse laser technology for materialprocessing -- 2.2 Laser beam shaping -- 2.3 Liquid crystal on silicon spatial light modulators -- 2.4 Phase retrieval algorithms -- 3 Materials and methods -- 3.1 Processed materials -- 3.2 System components -- 3.3 Characterization methods -- 4 Theoretical calculation of limits for theincrease of volumetric ablation rate -- 4.1 Heat accumulation modeling for spatially shapedbeams -- 4.2 Ideal requirements on laser sources as well as beamshaping and guiding optics…”
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Blind Identification and Separation of Complex-valued Signals by Moreau, Eric

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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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Advances in Pattern Recognition : Proceedings of the Sixth International Conference.

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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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Graph Partitioning. by Bichot, Charles-Edmond

Table of Contents: “…Hendrickson-Leland coarsening algorithm; 2.3.4. The Heavy Edge Matching (HEM) algorithm; 2.4. …”
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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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Optics and artificial vision by González-Acuäna, Rafael G., Chaparro-Romo, Héctor A., Melendez-Montoya, Israel

Table of Contents: “…Introduction -- 3.2. The Lucas-Kanade algorithm -- 3.3. Application of the Lucas-Kanade algorithm and its Python code -- 3.4. …”
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Handbook on semidefinite, conic and polynomial optimization

Table of Contents: “…Lasserre and Mihai Putinar -- Self-regular interior-point methods for semidefinite optimization / Maziar Salahi and Tamás Terlaky -- Elementary optimality conditions for nonlinear SDPs / Florian Jarre -- Recent progress in interior-point methods: cutting-plane algorithms and warm starts / Alexander Engau -- Exploiting sparsity in SDP relaxation of polynomial optimization problems / Sunyoung Kim and Masakazu Kojima -- Block coordinate descent methods for semidefinite programming / Zaiwen Wen, Donald Goldfarb, and Katya Scheinberg -- Projection methods in conic optimization / Didier Henrion and Jérôme Malick -- SDP relaxations for non-commutative polynomial optimization / Miguel Navascués, Stefano Pironio, and Antonio Acín -- Semidefinite programming and constraint programming / Willem-Jan van Hoeve -- The state-of-the-art in conic optimization software / Hans D. …”
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The virtual life of film by Rodowick, David Norman

Table of Contents: “…Film begets video -- The death of cinema and the birth of film studies -- A medium in all things -- Automatisms and art -- Automatism and photography -- Succession and the film strip -- Ways of worldmaking -- A world past -- An ethics of time -- III. …”
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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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The Fifth Decade of Cardiac Pacing. by Barold, S. Serge

Table of Contents: “…; 11 Permanent and Temporary Single-Lead VDD and DDD Pacing: State of the Art; 12 Pacemaker Memory: Basic Concepts and New Technology; 13 Future Trends in Pacemaker Technology; 14 Diagnosis of Supraventricular Tachyarrhythmias by Automatic Mode-Switching Algorithms of Dual-Chamber Pace.…”
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Integrated and collaborative product development environment : technologies and implementations by Li, W. D.

Table of Contents: “…5.4 Experimental Results5.4.1 Sample parts; 5.4.2 Computation results; 5.4.3 Comparisons of constraint handling methods; 5.4.4 Algorithm implementation; 5.5 Summary; 6. Collaborative Computer-Aided Design -- State-of-the-Art; 6.1 Introduction; 6.2 Visualisation-based Collaborative Systems; 6.2.1 3D representations for Web applications; 6.2.2 System architectures and implementation strategies; 6.3 Co-design Collaborative Systems; 6.3.1 System architectures; 6.3.2 Design coordination and team management; 6.3.3 Optimised feature and assembly-based representations.…”
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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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The NURBS Book by Piegl, Les

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Cryptography 101 : From Theory to Practice. by Oppliger, Rolf

Table of Contents: “…Intro -- Cryptography 101: From Theory to Practice -- Contents -- Foreword -- Preface -- References -- Acknowledgments -- Chapter 1 Introduction -- 1.1 CRYPTOLOGY -- 1.2 CRYPTOGRAPHIC SYSTEMS -- 1.2.1 Classes of Cryptographic Systems -- 1.2.2 Secure Cryptographic Systems -- 1.3 HISTORICAL BACKGROUND INFORMATION -- 1.4 OUTLINE OF THE BOOK -- References -- Chapter 2 Cryptographic Systems -- 2.1 UNKEYED CRYPTOSYSTEMS -- 2.1.1 Random Generators -- 2.1.2 Random Functions -- 2.1.3 One-Way Functions -- 2.1.4 Cryptographic Hash Functions -- 2.2 SECRET KEY CRYPTOSYSTEMS -- 2.2.1 Pseudorandom Generators -- 2.2.2 Pseudorandom Functions -- 2.2.3 Symmetric Encryption -- 2.2.4 Message Authentication -- 2.2.5 Authenticated Encryption -- 2.3 PUBLIC KEY CRYPTOSYSTEMS -- 2.3.1 Key Establishment -- 2.3.2 Asymmetric Encryption Systems -- 2.4 FINAL REMARKS -- References -- Part I UNKEYEDC RYPTOSYSTEMS -- Chapter 3 Random Generators -- 3.1 INTRODUCTION -- 3.2 REALIZATIONS AND IMPLEMENTATIONS -- 3.2.1 Hardware-Based Random Generators -- 3.2.2 Software-Based Random Generators -- 3.2.3 Deskewing Techniques -- 3.3 STATISTICAL RANDOMNESS TESTING -- References -- Chapter 4 Random Functions -- 4.1 INTRODUCTION -- 4.2 IMPLEMENTATION -- 4.3 FINAL REMARKS -- Chapter 5 One-Way Functions -- 5.1 INTRODUCTION -- 5.2 CANDIDATE ONE-WAY FUNCTIONS -- 5.2.1 Discrete Exponentiation Function -- 5.2.2 RSA Function -- 5.2.3 Modular Square Function -- 5.3 INTEGER FACTORIZATION ALGORITHMS -- 5.3.1 Special-Purpose Algorithms -- 5.3.2 General-Purpose Algorithms -- 5.3.3 State of the Art -- 5.4 ALGORITHMS FOR COMPUTING DISCRETE LOGARITHMS -- 5.4.1 Generic Algorithms -- 5.4.2 Nongeneric (Special-Purpose) Algorithms -- 5.4.3 State of the Art -- 5.5 ELLIPTIC CURVE CRYPTOGRAPHY -- 5.6 FINAL REMARKS -- References -- Chapter 6 Cryptographic Hash Functions -- 6.1 INTRODUCTION.…”
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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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Mobile opportunistic networks : architectures, protocols and applications

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Advanced reliability modeling II : reliability testing and improvement : proceedings of the 2nd Asian International Workshop (AIWARM 2006), Busan, Korea, 24-26 August 2006

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Co-Clustering. by Govaert, G?rard

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