Search Results - (((((((want OR wind) OR manthe) OR carter) OR cantor) OR anne) OR maarten) OR mantis) algorithms.

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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Machine Learning with Swift : Artificial Intelligence for iOS. by Sosnovshchenko, Oleksandr

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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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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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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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Visible Business : Uncover the Blindspots and Engage the World's Female Economy. by Brideson, RJ

Table of Contents: “…Blind Spots; Contents; Foreword; About the Author; Acknowledgements; To my community; To my village; Preface; Introduction; Chapter 1 From history to herstory; The birth of business marketing; Things have changed -- or have they?; Women want more; The wo-man algorithm; Become conscious of the bias; From reject to results; Chapter 2 Are you blind?…”
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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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Calculating the Secrets of Life : Contributions of the Mathematical Sciences to Molecular Biology. by Lander, Eric S.

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Architecture-aware optimization strategies in real-time image processing by Li, Chao, Balla-Arabe, Souleymane, Yang, Fan

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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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Machine Learning for Asset Management New Developments and Financial Applications

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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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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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OpenCV Android Programming By Example. by Muhammad, Amgad

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Apache Spark for Data Science Cookbook. by Chitturi, Padma Priya

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Innovation Manufacturing and Engineering Management : Selected, peer reviewed papers from the International Conference on Innovation Manufacturing and Engineering Management (IMEM)...

Table of Contents: “…Solder Selection of Lead-Free Reflow Soldering and Optimization of Craft CurveLow Reflectivity ErAlO Film on Si as Anti-Reflecting Coating in Solar Cells; Genesis Analysis of Common Defects of Reflow Soldering and Research for Solutions; Key Parameter Optimization in Wave Soldering; A Dynamic Clustering Querying Algorithm Based on Grid in Manufacturing System; Design of Accelerator in Wind Power Generator with Creative Mechanical Design Methodology; Analyze of Traditional Clothing Manufacturing Technology and Five Traditional Colors Based on Management Principle…”
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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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Two-degree-of-freedom control systems : the Youla Parameterization approach by Keviczky, László, Bányász, Csilla

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MATLAB for Machine Learning. by Ciaburro, Giuseppe

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Database technology for life sciences and medicine

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