Search Results - (((((((want OR wind) OR romantic) OR when) OR cantor) OR anne) OR shared) OR hints) algorithms.

Fast sequential Monte Carlo methods for counting and optimization by Rubinstein, Reuven Y.

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Advanced Control and Optimization Paradigms for Energy System Operation and Management. by Pal, Kirti

Table of Contents: “…3.4: Procedure -- 3.4.1: Solar Photovoltaic System -- 3.4.2: Wind Turbine -- 3.4.3: Battery Energy Storage System -- 3.4.4: Diesel Generator -- 3.5: Modelling of the HRES with Different kinds of Batteries -- 3.6: System Metrics -- 3.6.1: Economic Metrics -- 3.6.2: Technical Performance of the Overall System -- 3.6.3: Contribution of Solar PV -- 3.6.4: Contribution of Wind Turbine and Diesel Generator -- 3.6.5: Technical Specification of Different Batteries Used in HRES -- 3.7: State of Charge of Battery -- 3.8: Emissions through a Different System with Different Batteries -- 3.9: Conclusions…”
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Trends in Functional Programming. by Nilsson, Henrik

Table of Contents: “…Front Cover; Preliminary Pages; Contents; Preface; Proving Termination Using Dependent Types: The Case of Xor-Terms; Proving the Correctness of Algorithmic Debugging for Functional Programs; Systematic Synthesis of Functions; A Purely Functional Implementation of ROBDDs in Haskell; Efficient Interpretation by Transforming Data Types and Patterns to Functions; Object-Oriented Programming in Dependent Type Theory; A Sharing Analysis for SAFE; Memory Usage Improvement Using Runtime Alias Detection; A Model of Functional Programming with Dynamic Compilation and Optimization.…”
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Prognostics and Health Management of Engineering Systems : an Introduction. by Kim, Nam-Ho

Table of Contents: “…2.2.2 When a Degradation Model Is Available (Physics-Based Approaches)2.2.2.1 Problem Definition; 2.2.2.2 Parameter Estimation and Degradation Prediction; 2.2.2.3 Effect of Noise in Data; 2.2.3 When a Degradation Model Is NOT Available (Data-Driven Approaches); 2.2.3.1 Function Evaluation; 2.2.3.2 Overfitting; 2.2.3.3 Prognosis with More Training Data; 2.3 RUL Prediction; 2.3.1 RUL; 2.3.2 Prognostics Metrics; 2.3.2.1 Prognostic Horizon (PH); 2.3.2.2 varvec{ alpha { -- } lambda} Accuracy; 2.3.2.3 (Cumulative) Relative Accuracy (RA, CRA); 2.3.2.4 Convergence; 2.3.2.5 Results with MATLAB Code.…”
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Epistemological Foundations of Mathematical Experience

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Handbook for pandemic and mass-casualty planning and response

Table of Contents: “…Burn Injuries during Mass-Casualty IncidentsBlast Injuries; Section 3: Communication and Information Sharing; Information Sharing in Practice and for Practice: Mass-Casualty Cases; Communication between Emergency Medical Services and Media during Mass-Casualty Events in Croatia; Just-in-Time Information; Collaboration Topologies for Interdisciplinary and Interlevel Information Exchange; Networks and Their Role in Counteracting Contemporary Global Threats: A New Model; Architecture of R & D Project Management Systems at Medical Institutions; Lessons Learned; Lessons Learned; Subject Index…”
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Machine learning with R : learn how to use R to apply powerful machine learning methods and gain an insight into real-world applications by Lantz, Brett

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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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Rediscovering mathematics : you do the math by Simonson, Shai

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Data analytics and big data by Sedkaoui, Soraya

Table of Contents: “…When real time makes the difference; 4.4. What should data analytics address?…”
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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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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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DSP with Python Programming. by Charbit, Maurice

Table of Contents: “…Gaussian linear case: Kalman algorithm; 3.5. Discrete finite Markov case; 4 Monte-Carlo Methods; 4.1. …”
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Solutions in lidar profiling of the atmosphere by Kovalev, Vladimir A.

Table of Contents: “…1.6.1 Algorithm and Solution Uncertainty1.6.2 Numerical Simulations and Experimental Data; 1.7 Examination of the Remaining Offset in the Backscatter Signal by~Analyzing the Shape of the Integrated Signal; 1.8 Issues in the Examination of the Lidar Overlap Function; 1.8.1 Influence of Distortions in the Lidar Signal when Determining the~Overlap Function; 1.8.2 Issues of Lidar Signal Inversion within the Incomplete Overlap Area; Chapter 2 Essentials and Issues in Separating the Backscatter and Transmission Terms in The Lidar Equation.…”
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Artificial intelligence with Python : build real-world artificial intelligence applications with Python to intelligently interact with the world around you by Joshi, Prateek

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Empirical Evaluation Methods in Computer Vision. by Christensen, Henrik I.

Table of Contents: “…Foreword ; Chapter 1 Automated Performance Evaluation of Range Image Segmentation Algorithms ; 1.1. Introduction ; 1.2. Scoring the Segmented Regions ; 1.3. …”
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Reliability in biomechanics by Kharmanda, Ghias, El Hami, Abdelkhalak

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Foundations of constraint satisfaction by Tsang, Edward

Table of Contents: “…Solution synthesis; 9.1 Introduction; 9.2 Freuder's Solution Synthesis Algorithm; 9.3 Seidel's Invasion Algorithm; 9.4 The Essex Solution Synthesis Algorithms; 9.5 When to Synthesize Solutions; 9.6 Concluding Remarks; 9.7 Bibliographical Remarks; Chapter 10. …”
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Focus on artificial neural networks

Table of Contents: “…ARTIFICIAL NEURAL NETWORKS (ANNS) -- 3. MICROEMULSIONS -- 4. APPLICATION OF ANNS IN THE DEVELOPMENT OF MICROEMULSION DRUG DELIVERY SYSTEMS -- 4.1. …”
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Big Data and HPC. by Grandinetti, L.

Table of Contents: “…Analysis and Design of IoT Based Physical Location Monitoring SystemAutonomous Task Scheduling for Fast Big Data Processing; Adaptive Resource Management for Distributed Data Analytics; HPC Challenges; High-Performance Massive Subgraph Counting Using Pipelined Adaptive-Group Communication; Final Parallel and Distributed Computing Assignment for Master Students: Description of the Properties and Parallel Structure of Algorithms; Parallel Motion Estimation Based on GPU and Combined GPU-CPU; GPU-Based Iterative Hill Climbing Algorithm to Solve Symmetric Traveling Salesman Problem.…”
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