Search Results - (((((((want OR wants) OR semantic) OR when) OR cantor) OR anne) OR blaney) OR hints) algorithms.

Learning Boost C++ libraries : solve practical programming problems using powerful, portable, and expressive libraries from Boost by Mukherjee, Arindam

Table of Contents: “…Shared ownership semanticsboost::shared_ptr and std::shared_ptr; Intrusive smart pointers -- boost::intrusive_ptr; shared_array; Managing non-memory resources using smart pointers; Self-test questions; Summary; References; Chapter 4: Working with Strings; Text processing with Boost String Algorithms library; Using Boost String Algorithms; Find algorithms; Case-conversion and trimming algorithms; The replace and erase algorithms; The split and join algorithms; Splitting text using the Boost Tokenizer library; Tokenizing based on separators…”
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Handbook of Modal Logic. by Blackburn, Patrick

Table of Contents: “…13 Quantified Modal Logic13.1 Syntax and Semantics; 13.2 Constant Domain Tableaus; 13.3 Soundness and Completeness; 13.4 Variations; 14 Conclusion; Bibliography; Chapter 3 Complexity of Modal Logic; 1 Introduction; 1.1 Examples of decision problems in modal logic; 1.2 A simple and a hard problem; 1.3 The model checking problem; 1.4 The consequence problem; 1.5 A tiling logic; 2 Decision algorithms; 2.1 Selection of points; 2.2 Filtration; 2.3 Hintikka set elimination; 2.4 Hintikka set elimination without constraints; 2.5 Forcing exponentially deep paths; 2.6 Tree automata; 2.7 Pseudo-models.…”
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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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Enterprise artificial intelligence transformation : a playbook for the next generation of business and technology leaders by Haq, Rashed

Table of Contents: “…Types of Uses for Machine Learning -- Types of Machine Learning Algorithms -- Supervised, Unsupervised, and Semisupervised Learning -- Making Data More Useful -- Semantic Reasoning -- Applications of AI -- PART II Artificial Intelligence in the Enterprise -- Chapter 3 AI in E-Commerce and Retail -- Digital Advertising -- Marketing and Customer Acquisition -- Cross-Selling, Up-Selling, and Loyalty -- Business-to-Business Customer Intelligence -- Dynamic Pricing and Supply Chain Optimization -- Digital Assistants and Customer Engagement -- Chapter 4 AI in Financial Services -- Anti-Money Laundering.…”
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Differential algebra and related topics - proceedings of the international workshop. by SIT, WILLIAM Y.

Table of Contents: “…6 Reduction Algorithms 7 Rosenfeld Properties of an Autoreduced Set ; 8 Coherence and Rosenfeld's Lemma ; 9 Ritt-Raudenbush Basis Theorem ; 10 Decomposition Problems ; 11 Component Theorems ; 12 The Low Power Theorem ; Appendix: Solutions and hints to selected exercises ; References…”
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Energy Psychology : Explorations at the Interface of Energy, Cognition, Behavior, and Health. by Gallo, Fred P.

Table of Contents: “…Manual Muscle Testing and KinesiologyApplied Kinesiology Offshoots; Empirical Research on Manual Muscle Testing; Muscle Testing Proficiency; Integrity and Muscle Testing; Therapy and Diagnosis; Self-Testing; Therapeutic Algorithms vs. Causal Diagnostics; Energy Psychology and Manual Muscle Testing; Abuses of Manual Muscle Testing and Algorithms; Manual Muscle Testing and Intuition; Unwarranted Uses; When We're Stumped; Systemic Manual Muscle Testing.…”
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Applications of digital signal processing to audio and acoustics

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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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Ivor Horton's beginning Visual C++ 2012 by Horton, Ivor

Table of Contents: “…When to Overload Functions --…”
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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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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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Advanced Methods and Technologies for Agent and Multi-Agent Systems. by Edited by

Table of Contents: “…""Role and Member Selection in Team Formation Using Resource Estimation""""Incorporating Explicit Coordination Mechanisms by Agents to Obtain Green Waves""; ""Communication Leading to Coalition Nash Equilibrium I""; ""Agent-Based Optimization""; ""An Agent-Based Cooperative Population Learning Algorithm for Vehicle Routing Problem with Time Windows""; ""Mobile Agent-based Dynamic Resource Allocation Method for Query Optimization in Data Grid Systems""; ""Memetic Multi-Agent Computing in Difficult Continuous Optimisation""; ""Web Services and Semantic Web""…”
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Regression Analysis with Python. by Massaron, Luca, Boschetti, Alberto

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Mastering D3.js. by Castillo, Pablo Navarro

Table of Contents: “…Updating the datasetFixing the enter and exit transitions; Using the barcode chart; Creating a layout algorithm; The radial layout; Computing the angles; Using the layout; Summary; Chapter 3: Creating Visualizations without SVG; SVG support in the browser market; Visualizations without SVG; Loading and sorting the data; The force layout method; Setting the color and size; Creating a legend; Polyfilling; Feature detection; The canvg example; Using canvas and D3; Creating figures with canvas; Creating shapes; Integrating canvas and D3; Summary; Chapter 4: Creating a Color Picker with D3.…”
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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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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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Advanced Analytics with R and Tableau. by Stirrup, Jen

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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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