Search Results - (((((((want OR wanton) OR semantic) OR wien) OR cantor) OR anne) OR shape) OR hints) algorithms.

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  1. 421
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    Electromagnetic nondestructive evaluation (XII)

    Published 2009
    Table of Contents: “…Elastic Properties of Thermally Aged Fe-Cu Model Alloys Measured by EMAR Method -- Nondestructive Evaluation of Ferromagnetic Structural Materials Using FG Sensor -- Inverse Problem and Imaging -- Standoff Detection and Imaging of Suspicious and Concealed Objects with Electromagnetic Waves in the Centimetre and Millimetre Range -- Pulsed Terahertz Imaging for Nondestructive Evaluation -- On the Imaging of Two-Dimensional Thin Inclusions by a MUSIC-Type Algorithm from Boundary Measurements -- Chance-Constrained Programming: A Tool for Solving Linear Eddy Current Inverse Problem -- A Multiple Frequency Strategy for Reconstruction of Stress Corrosion Crack from ECT Signals -- Estimation Theory Metrics in Electromagnetic NDE -- Three Dimensional Shape Recovery of Fatigue Crack Using Eddy Current Testing Signals -- Application of Electromagnetic Nondestructive Techniques -- Development of Strong Magnetizer and Robust Sensor Mount System to Increase Performance in Detecting Defects on Pipeline -- Electromagnetic Evaluation of Honeycomb Composite Materials -- An Electromagnetic Method for Evaluation of Fatigue and for Detection of Damage at Bjork-Shiley Convexo-Concave Prosthetic Heart Valves -- Electromagnetic Evaluation of Soil Condition -- Investigation of Cu-Pc Thin Films on ITO Substrate by Using a Near-Field Microwave Microprobe -- Noncontact Characterization of Electric Carriers Density at Heterojunction Interfaces -- Electromagnetic Field Interaction with Aqueous Glucose Solution in Dielectric Resonator -- Quantitative Evaluation of Corrosion Shape on Back Surface of SUS Samples by EMAT -- Inspection of 3D Flaws Using EMAT -- Nondestructive Evaluation of Beryllium to Copper Joining for ITER by Using an Electromagnetic Acoustic Transducer (EMAT) -- Subject Index -- Author Index.…”
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    Electronic Conference Proceeding eBook
  3. 423

    Ultra-wideband signals and systems in communication engineering by Ghavami, M.

    Published 2004
    Table of Contents: “…Ultra Wideband Signals and Systems in Communication Engineering; Contents; Preface; Acknowledgments; List of Figures; List of Tables; Introduction; I.1 Ultra wideband overview; I.2 A note on terminology; I.3 Historical development of UWB; I.4 Key benefits of UWB; I.5 UWB and Shannon's theory; I.6 Challenges for ultra wideband; I.7 Summary; 1 Basic properties of UWB signals and systems; 1.1 Introduction; 1.2 Power spectral density; 1.3 Pulse shape; 1.4 Pulse trains; 1.5 Spectral masks; 1.6 Multipath; 1.7 Penetration characteristics; 1.8 Spatial and spectral capacities…”
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    Artificial intelligence research and development : current challenges, new trends and applications

    Published 2018
    Table of Contents: “…Step 1: DrugBank -- Unsupervised Systems-Level Learning Mechanism Based on Bayesian-Inference -- Towards a Universal Neural Network Encoder for Time Series -- Determining Classic Versus Modern Style in Fashion -- Data Science, Recommender Systems and Case-Based Reasoning -- Big Data Analytics for Obesity Prediction -- A Method to Integrate Semantic Criteria into a Recommender System Based on ELECTRE Outranking Relations -- A Study on Contextual Influences on Automatic Playlist Continuation.…”
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    Electronic Conference Proceeding eBook
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    Microwave and millimeter wave circuits and systems : emerging design, technologies, and applications

    Published 2012
    Table of Contents: “…1.1.7 MBF Model -- the Memoryless PA Behavioural Model of ChoiceAcknowledgements; References; 2 Artificial Neural Network in Microwave Cavity Filter Tuning; 2.1 Introduction; 2.2 Artificial Neural Networks Filter Tuning; 2.2.1 The Inverse Model of the Filter; 2.2.2 Sequential Method; 2.2.3 Parallel Method; 2.2.4 Discussion on the ANN's Input Data; 2.3 Practical Implementation -- Tuning Experiments; 2.3.1 Sequential Method; 2.3.2 Parallel Method; 2.4 Influence of the Filter Characteristic Domain on Algorithm Efficiency; 2.5 Robots in the Microwave Filter Tuning; 2.6 Conclusions; Acknowledgement…”
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    Exact methods in low-dimensional statistical physics and quantum computing : École d'été de physique des Houches, session LXXXIX, 30 June-1 August 2008, École thématique du CNRS...

    Published 2010
    Table of Contents: “…7.11 The Legendre transform of the free energy7.12 The limit shape phenomenon -- 7.13 Semiclassical limits -- 7.14 The free-fermionic point and dimer models -- 7.A Appendix -- References -- 8 Mathematical aspects of 2D phase transitions -- PART II: SHORT LECTURES -- 9 Numerical simulations of quantum statistical mechanical models -- 9.1 Introduction -- 9.2 A rapid survey of methods -- 9.3 Path integral and related methods -- 9.4 Classical worm algorithm -- 9.5 Projection methods -- 9.6 Valence bond projection method -- References…”
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    Spatial control of vibration : theory and experiments by Moheimani, S. O. Reza, 1967-, Fleming, Andrew J., 1977-

    Published 2003
    Table of Contents: “…System Identification for Spatially Distributed Systems; 7.1 Introduction; 7.2 Modeling; 7.3 Spatial sampling; 7.4 Identifying the system matrix; 7.5 Identifying the mode shapes and feed-through function; 7.6 Experimental results; 7.7 Conclusions; Appendix A Frequency domain subspace system identification; A.1 Introduction; A.2 Frequency Domain Subspace Algorithm; Bibliography; Index.…”
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  16. 436

    Kotlin standard library cookbook : master the powerful Kotlin standard library through practical code examples by Urbanowicz, Samuel

    Published 2018
    Table of Contents: “…. ; See also; Applying sequences to solve algorithmic problems; Getting ready; How to do it ... ; How it works ... ; Chapter 2: Expressive Functions and Adjustable Interfaces; Introduction; Declaring adjustable functions with default parameters; How to do it ... ; How it works ... ; See also; Declaring interfaces containing default implementations; Getting ready…”
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  17. 437

    D Cookbook. by D. Ruppe, Adam

    Published 2014
    Table of Contents: “…Performing type conversionsFinding the largest files in a directory; Creating a network client and server; Using Base64 to create a data URI; Generating random numbers; Normalizing a string and performing Unicode comparisons; Searching with regular expressions; Writing a digest utility; Using std.zlib compression; Using the std.json module; Chapter 3: Ranges; Introduction; Using ranges when implementing an algorithm; Creating an input range; Creating an output range; Creating a higher-order range; Putting a range interface on a collection; Creating an input range over a tree structure…”
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  18. 438

    Towards Cognitive Autonomous Networks : Network Management Automation for 5G and Beyond. by Mwanje, Stephen S.

    Published 2020
    Table of Contents: “…Cover -- Title Page -- Copyright -- Contents -- List of Contributors -- Foreword I -- Foreword II -- Preface -- Chapter 1 The Need for Cognitive Autonomy in Communication Networks -- 1.1 Complexity in Communication Networks -- 1.1.1 The Network as a Graph -- 1.1.2 Planes, Layers, and Cross-Functional Design -- 1.1.3 New Network Technology -- 5G -- 1.1.4 Processes, Algorithms, and Automation -- 1.1.5 Network State Changes and Transitions -- 1.1.6 Multi-RAT Deployments -- 1.2 Cognition in Network Management Automation -- 1.2.1 Business, Service and Network Management Systems…”
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  19. 439

    What to Do When Machines Do Everything : Five Ways Your Business Can Thrive in an Economy of Bots, AI, and Data. by Frank, Malcolm

    Published 2017
    Table of Contents: “…What to Do When Machines Do Everything: How to Get Ahead in a World of AI, Algorithms, Bots, and Big Data; Contents; Preface; 1: When Machines Do Everything; Like It or Not, This Is Happening; Digital That Matters; Playing the New Game; But Will I Be Automated Away?…”
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    Exploratory data analysis with MATLAB by Martinez, Wendy L., Martinez, Angel R., Solka, Jeffrey

    Published 2017
    Table of Contents: “…5.5.2 Probabilistic Latent Semantic Analysis5.6 Minimum Spanning Trees and Clustering; 5.6.1 Definitions; 5.6.2 Minimum Spanning Tree Clustering; 5.7 Evaluating the Clusters; 5.7.1 Rand Index; 5.7.2 Cophenetic Correlation; 5.7.3 Upper Tail Rule; 5.7.4 Silhouette Plot; 5.7.5 Gap Statistic; 5.7.6 Cluster Validity Indices; 5.8 Summary and Further Reading; Exercises; Chapter 6 Model-Based Clustering; 6.1 Overview of Model-Based Clustering; 6.2 Finite Mixtures; 6.2.1 Multivariate Finite Mixtures; 6.2.2 Component Models -- Constraining the Covariances; 6.3 Expectation-Maximization Algorithm.…”
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