Search Results - (((((((ante OR want) OR mantis) OR wien) OR cantor) OR anne) OR shape) OR hints) algorithms.

Java programming interviews exposed by Markham, Noel

Table of Contents: “…Chapter 18: Useful LibrariesRemoving Boilerplate Code with Apache Commons; Developing with Guava Collections; Using Joda Time; Summary; Chapter 19: Developing with Build Tools; Building Applications with Maven; Ant; Summary; Chapter 20: Android; Basics; User Interface; Persistence; Android Hardware; Summary; Appendix: Introducing Scala; Scala Basics; Functions as Values; Immutability; Summary; Index.…”
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An introduction to computational engineering with Matlab by Yang, Xin-She

Table of Contents: “…Optimization in Engineering -- 12.1 Introduction -- 12.2 Bioinspired Algorithms -- 12.2.1 Genetic Algorithms -- 12.2.2 Neural Networks…”
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Java Deep Learning Projects : Implement 10 Real-World Deep Learning Applications Using Deeplearning4j and Open Source APIs. by Karim, Rezaul

Table of Contents: “…; Artificial Neural Networks; Biological neurons; A brief history of ANNs; How does an ANN learn?; ANNs and the backpropagation algorithm; Forward and backward passes; Weights and biases; Weight optimization; Activation functions.…”
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Integrated and collaborative product development environment : technologies and implementations by Li, W. D.

Table of Contents: “…Intelligent Optimisation of Process Planning; 5.1 Intelligent Optimisation Strategies for CAPP Systems; 5.2 Knowledge Representation of Process Plans; 5.2.1 Process plan representation; 5.2.2 Machining cost criteria for process plans; 5.2.3 Precedence constraints; 5.3 A Hybrid GA/SA-based Optimisation Method; 5.3.1 Overview of the algorithm; 5.3.2 Genetic algorithm -- phase 1; 5.3.3 Simulated annealing algorithm -- phase 2; 5.3.4 Constraint handling algorithm.…”
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Deep Learning with TensorFlow : Explore neural networks and build intelligent systems with Python, 2nd Edition. by Zaccone, Giancarlo

Table of Contents: “…; Artificial neural networks; The biological neurons; The artificial neuron; How does an ANN learn?; ANNs and the backpropagation algorithm; Weight optimization; Stochastic gradient descent; Neural network architectures; Deep Neural Networks (DNNs); Multilayer perceptron; Deep Belief Networks (DBNs).…”
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Principles of Quantum Computation and Information, Volume I : Basic Concepts. by Casati, Giulio, Strini, Giuliano

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Advanced manufacturing technology and systems : selected, peer reviewed papers from the 2012 International Conference on Advanced Manufacturing Technology and Systems (AMTS 2012),...

Table of Contents: “…An Investigation into Machining Characteristics of Commercially Pure Titanium (Grade-2) Using CNC WEDMAntistatic TPU/PA6 Blends Prepared by Blending Modification; Based on SolidWorks COSMOS 2.5 Tons, 4ms-1 High Speed the Elevator Drive's Finite Element Analysis; Changing Direction Parallel Scan Path Generating Method through Matching Scan Space for Metal Laser Deposition Shaping; CuO Microspheres Synthesized via the Easy Hydrothermal Method; Customers Involved Digital NPD Method Based on Integrated CAX Technology…”
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Python unlocked : become more fluent in Python--learn strategies and techniques for smart and high-performance Python programming by Tigeraniya, Arun

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Java Data Mining - Strategy, Standard, and Practice : a Practical Guide for architecture, design, and implementation. by Hornick, Mark F.

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Seismic Data Interpretation using Digital Image Processing by Al-Shuhail, Abdullatif A., Al-Dossary, Saleh A., Mousa, Wail A.

Table of Contents: “…5.5 Two-Dimensional Second-Order Derivative Operator5.5.1 The Coherence Attribute; 5.5.2 The Dip Attribute; 5.6 The Curvature Attribute; 5.7 Curvature of the Surface; 5.7.1 Curve, Velocity, and Curvature; 5.7.2 Surface, Tangent Plane, and Norm; 5.8 Shape Operator, Normal Curvature, and Principal Curvature; 5.8.1 Normal Curvature; 5.8.2 Shape Operator; 5.8.3 The Principal Curvatures; 5.8.4 Calculation of the Principal Curvatures; 5.8.5 Summary of Calculation of Principal Curvature for a Surface; 5.9 The Randomness Attribute; 5.10 Technique for Two-Dimensional Images.…”
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Building Machine Learning Systems with Python. by Richert, Willi

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Ranking the Liveability of the World's Major Cities : the Global Liveable Cities Index (GLCI). by Tan, Khee Giap

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Data clustering in C++ : an object-oriented approach by Gan, Guojun, 1979-

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Revolutionary routines : the habits of social transformation by Pedwell, Carolyn

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Hes-2019. by Forzan, Michele

Table of Contents: “…Cover -- Guest editorial -- Optimization of electroslag melting towards to titanium morphology improvement in combined Kroll process -- Optimal design methods for the uniform heating of tube ends for stress relieving -- Numerical simulation and verification of MHD-vortex -- Shape optimization of soft magnetic composite inserts for electromagnetic stirrer with traveling magnetic field -- Cold crucible melting with bottom pouring nozzle -- Calibration of laser welding model based on optimization techniques -- Optimal heat induction treatment of titanium alloys…”
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Optimization and Inverse Problems in Electromagnetism. by Salvini, Alessandro

Table of Contents: “…Cover; EDITORIAL ADVISORY BOARD; Analytical and numerical models of the magnetoacoustic tomography with magnetic induction; Application of PSO and TLBO algorithms with neural network for optimal design of electrical machines; Comparison of three space mapping techniques on electromagnetic design optimization; Optimal shape design of multi layered IPMSM using adaptive dynamic Taylor Kriging model; Design by optimization of controlled static converters with EMC filters in aeronautics.…”
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Active Spanwise Lift Control. by Dias, Joaquim Neto

Table of Contents: “…4.4 Physical Interpretation of Aerodynamic Modes -- 4.5 Effects of Varying Wing Planform on the Mode Shapes and Eigenvalues -- 4.6 Chapter Summary -- Chapter 5: Spatial Control of Spanwise Lift Distribution -- 5.1 Model Output Expansion into Mode Shapes -- 5.2 Threshold for Model Truncation -- 5.3 Spatial-Temporal Controller Synthesis -- 5.4 Shape Control Problem -- 5.5 Gust Load Alleviation Problem -- 5.6 Gust Load Alleviation Problem with Gust Estimation -- 5.7 Chapter Summary -- 5.8 Future Developments of This Methodology -- Appendix A -- References -- Index -- Supporting Materials…”
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Applied mechatronics and android robotics : selected, peer reviewed papers from the International Conference on Applied Mechatronics and Android Robotics (ICAMAR 2013), July 13-14,...

Table of Contents: “…Applied Mechatronics and Android Robotics; Preface, Committees and Sponsors; Table of Contents; Chapter 1: Robot Design, Motion Planning and Robot Control; Design of a Master Manipulator with Dynamical Simplification for Master-Slave Robot; Parameter Self-Adjusting Path Tracking Algorithm of Mobile Robots; Global Path Planning for Mobile Robot Based on Improved Ant Colony Algorithms; A Study of Robot Platform Based on WiFi Remote Control; Fire Detection System Based-On Mobile Robots; Phase Plane Analysis of Battery Series Balancing on Robot…”
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Electromechanical and systems engineering : selected, peer reviewed papers from the 5th International Congress of Electromechanical and Systems Engineering, 10th-14th November 2008...

Table of Contents: “…Theoretical and Experimental Analysis of Turbulent Liquid Film Flowing down a Vertical Surface -- Study of Flow over a Step Cylinder -- Experimental Study of Water Filtering Using Textiles as in Traditional Methods -- Laminar Flow through a Rectangular Horizontal Channel with Asymmetrical Contraction -- Influence of the Alignment of Two Airfoils in the Losses Generation -- Inverse Heat Transfer Using Levenberg-Marquardt and Particle Swarm Optimization Methods for Heat Source Estimation -- Effect of Maximum Temperature and Heating-Cooling Repeated Cycles on Thermal Contact Resistance of a Composite Tube -- Pneumatic Artificial Mini-Muscles Conception: Medical Robotics Applications -- Synthesis Optimization of Planar Mechanisms -- Resolution of a 3 RRR Planar Parallel Mechanism -- Synthesis of 4C Mechanism for Generation of a Dual Mathematic Function -- Trajectory Generation of Robot Manipulators Using an Artificial Potential Function and Genetic Algorithms -- Stress and Vibration Analysis of a Lathe Bed Made of Aluminum-Copper Alloy for High Speed Machining -- Model Derivation and Numerical Simulation for a Pivoted Rigid Rotor-Bearing System -- Algorithm for Estimating Natural Frequencies and Mode Shapes of Cantilever MEMS Microbeams -- Tensile Strength of Fibers Extracted from the Leaves of the angustifolia Haw Agave in Function of their Length -- Assessment of the Crack Compliance Method and the Introduction of Residual Stresses by Shot Peening Using the Finite Element Method -- Fractal Analysis of the Solar Radiation in Mexico City -- Fractal Analysis of Tissue Biocompatible Neuroreservoir -- Fractal Analysis of EEG Signals in the Brain of Epileptic Rats, with and without Biocompatible Implanted Neuroreservoirs -- Parametric Analysis of Perfect Matched Layer Model of Finite Difference Time Domain Method.…”
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Probabilistic finite element model updating using Bayesian statistics : applications to aeronautical and mechanical engineering by Marwala, Tshilidzi, 1971-, Boulkaibet, Ilyes, 1981-, Adhikari, Sondipon

Table of Contents: “…3.8.2 Markov Chain Monte Carlo Method3.8.3 Simulated Annealing; 3.8.4 Gibbs Sampling; 3.9 Comparison between Approaches; 3.9.1 Numerical Example; 3.10 Conclusions; References; Chapter 4 Metropolis-Hastings and Slice Sampling for Finite Element Updating ; 4.1 Introduction; 4.2 Likelihood, Prior and the Posterior Functions; 4.3 The Metropolis-Hastings Algorithm; 4.4 The Slice Sampling Algorithm; 4.5 Statistical Measures; 4.6 Application 1: Cantilevered Beam; 4.7 Application 2: Asymmetrical H-Shaped Structure; 4.8 Conclusions; References.…”
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