Search Results - (((((((anti OR wkanting) OR mantis) OR wien) OR cantor) OR anne) OR shape) OR hints) algorithms.

6G Wireless Communications and Mobile Networking.

Table of Contents: “…Terminal-positioning and Other Novel Applications -- MASSIVE MIMO ANTENNA FOR MOBILE COMMUNICATIONS -- Massive MIMO Antenna Array Design and Synthesis -- Massive MIMO Antenna Decoupling Technology -- Large-Scale Antenna Beamforming Technology -- Null-notch Beamforming Algorithm Based on LMS Criterion -- DESIGN OF FEED NETWORK AND RF FRONT-END -- Feeding Technology of Base Station Antenna -- Design of RF Front-End for Large-Scale Active Antenna -- ANTENNA SELECTION TECHNOLOGY -- Antenna Selection Criteria and Classification -- Optimal Antenna Selection Algorithm -- Incremental Antenna Selection Algorithm -- Decreasing Antenna Selection Algorithm -- MEASUREMENT TECHNOLOGY OF MASSIVE MIMO ANTENNA -- OTA Testing Requirements for Massive MIMO Antenna -- Near-Field and Far-Field Measurement -- Far-Field Test -- Near-Field Test: -- OTA Testing Process -- SUMMARY -- CONSENT FOR PUBLICATION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENTS -- REFERENCES.…”
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Tracking with particle filter for high-dimensional observation and state spaces by Dubuisson, Séverine

Table of Contents: “…Application to tracking shapes; 3.4. Conjoint estimation of dynamic and static parameters; 3.5. …”
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Diatoms : ecology and life cycle

Table of Contents: “…""DIATOMS: ECOLOGY AND LIFE CYCLE""; ""DIATOMS: ECOLOGY AND LIFE CYCLE""; ""Contents""; ""Preface""; ""The Role of Environmental Factors in Shaping Diatom Frustule: Morphological Plasticity and Teratological Forms""; ""Abstract""; ""1. …”
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Moments and moment invariants in pattern recognition by Flusser, Jan

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Integration of swarm intelligence and artificial neural network

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Effective Theories for Brittle Materials : a Derivation of Cleavage Laws and Linearized Griffith Energies from Atomistic and Continuum Nonlinear Models. by Friedrich, Manuel

Table of Contents: “…6.4.1 Korn-Poincaré-type inequality6.4.2 SBD-rigidity; 6.4.3 Compactness and Gamma-convergence; 7 Preliminaries; 7.1 Geometric rigidity and Korn: Dependence on the set shape; 7.2 A trace theorem in SBV2; 8 A Korn-Poincaré-type inequality; 8.1 Preparations; 8.2 Modification of sets; 8.3 Neighborhoods of boundary components; 8.3.1 Rectangular neighborhood; 8.3.2 Dodecagonal neighborhood; 8.4 Proof of the Korn-Poincaré-inequality; 8.4.1 Conditions for boundary components and trace estimate; 8.4.2 Modification algorithm; 8.4.3 Proof of the main theorem; 8.5 Trace estimates for boundary components…”
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Machine Learning in Chemical Safety and Health : Fundamentals with Applications. by Wang, Qingsheng

Table of Contents: “…Chapter 3 Flammability Characteristics Prediction Using QSPR Modeling -- 3.1 Introduction -- 3.1.1 Flammability Characteristics -- 3.1.2 QSPR Application -- 3.1.2.1 Concept of QSPR -- 3.1.2.2 Trends and Characteristics of QSPR -- 3.2 Flowchart for Flammability Characteristics Prediction -- 3.2.1 Dataset Preparation -- 3.2.2 Structure Input and Molecular Simulation -- 3.2.3 Calculation of Molecular Descriptors -- 3.2.4 Preliminary Screening of Molecular Descriptors -- 3.2.5 Descriptor Selection and Modeling -- 3.2.6 Model Validation -- 3.2.6.1 Model Fitting Ability Evaluation -- 3.2.6.2 Model Stability Analysis -- 3.2.6.3 Model Predictivity Evaluation -- 3.2.7 Model Mechanism Explanation -- 3.2.8 Summary of QSPR Process -- 3.3 QSPR Review for Flammability Characteristics -- 3.3.1 Flammability Limits -- 3.3.1.1 LFLT and LFL -- 3.3.1.2 UFLT and UFL -- 3.3.2 Flash Point -- 3.3.3 Auto-ignition Temperature -- 3.3.4 Heat of Combustion -- 3.3.5 Minimum Ignition Energy -- 3.3.6 Gas-liquid Critical Temperature -- 3.3.7 Other Properties -- 3.4 Limitations -- 3.5 Conclusions and Future Prospects -- References -- Chapter 4 Consequence Prediction Using Quantitative Property-Consequence Relationship Models -- 4.1 Introduction -- 4.2 Conventional Consequence Prediction Methods -- 4.2.1 Empirical Method -- 4.2.2 Computational Fluid Dynamics (CFD) Method -- 4.2.3 Integral Method -- 4.3 Machine Learning and Deep Learning-Based Consequence Prediction Models -- 4.4 Quantitative Property-Consequence Relationship Models -- 4.4.1 Consequence Database -- 4.4.2 Property Descriptors -- 4.4.3 Machine Learning and Deep Learning Algorithms -- 4.5 Challenges and Future Directions -- References -- Chapter 5 Machine Learning in Process Safety and Asset Integrity Management -- 5.1 Opportunities and Threats -- 5.2 State-of-the-Art Reviews -- 5.2.1 Artificial Neural Networks (ANNs).…”
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Computational neuroanatomy : the methods by Chung, Moo K.

Table of Contents: “…5.3.3 Laplace-Beltrami Shape Descriptors5.3.4 Second Eigenfunctions; 5.3.5 Dirichlet Energy; 5.3.6 Fiedler's Vector; 5.4 Finite Element Methods; 5.4.1 Pieacewise Linear Functions; 5.4.2 Mass and Stiffness Matrices; 6. …”
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Computational models of argument : Proceedings of COMMA 2012

Table of Contents: “…Simari -- Automated Deployment of Argumentation Protocols / Michael Rovatsos -- On Preferred Extension Enumeration in Abstract Argumentation / Katie Atkinson -- Towards Experimental Algorithms for Abstract Argumentation / Katie Atkinson.…”
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Handbook of convex optimization methods in imaging science

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Intelligent computational systems : a multi-disciplinary perspective

Table of Contents: “…3.2.1. Genetic Algorithm (GA) -- 3.2.2. Particle Swarm Optimization Algorithm (PSO) -- 3.3. …”
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Design optimization of fluid machinery : applying computational fluid dynamics and numerical optimization by Kim, Kwang-Yong, 1956-, Samad, Abdus, Benini, Ernesto

Table of Contents: “…2.2.5.3 Periodic/Cyclic Boundary Conditions2.2.5.4 Symmetry Boundary Conditions; 2.2.6 Moving Reference Frame (MRF); 2.2.7 Verification and Validation; 2.2.8 Commercial CFD Software; 2.2.9 Open Source Codes; 2.2.9.1 OpenFOAM; References; Chapter 3 Optimization Methodology; 3.1 Introduction; 3.1.1 Engineering Optimization Definition; 3.1.2 Design Space; 3.1.3 Design Variables and Objectives; 3.1.4 Optimization Procedure; 3.1.5 Search Algorithm; 3.2 Multi-Objective Optimization (MOO); 3.2.1 Weighted Sum Approach; 3.2.2 Pareto-Optimal Front…”
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Data Analysis and Applications 1 : New and Classical Approaches. by Skiadas, Christos

Table of Contents: “…Similarity to homogeneous distributional shapes1.3.11. Stability; 1.3.12. Further Aspects; 1.4. …”
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Advanced mathematical & computational tools in metrology & testing VIII

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The Dictionary of Critical Social Sciences. by Young, T. R.

Table of Contents: “…Cover -- Half Title -- Title -- Copyright -- Dedication -- Preface -- Authors' Note -- Acknowledgments -- A -- AARP -- Abduction -- Abolitionism -- Abortion -- Abuse, Child -- Abuse, Spousal -- Accenting the Sign -- Act -- Act, Philosophy of -- Acton, Lord (1834-1902) -- Actor -- Adolescence -- Adorno, Theodor (1903-1969) -- Adventist Religious Groups -- Advertising -- Aesthetics -- Aesthetics (Socialist) -- Affect -- Age -- Aged, Immiseration of -- Age Grades -- Agency, Human -- Agitation -- Agnosticism -- Agrarian Society -- Agriculture -- Agriculture, Hydraulic Societies -- Agrippa -- Ahistoricism -- Algorithm -- Alienation -- Alienation, Assumptions of -- Alienation, Psychological -- Allegory -- Analogy -- Analysis -- Anarchy -- Androcentricism -- Animal Functions -- Anomia -- Anomie -- Anthropocentrism -- Anthropology -- Anthropomorphism -- Anti-Foundationalism -- Anti-Semitism -- Apathy -- Apollonian -- Apology -- Apple, and Temptation to Knowledge -- Appropriation -- Appropriation, Mechanisms of -- Aquinas, Thomas, St. (1225-1274) -- Archaeology -- Archetype -- Aristocracy -- Aristotle (384-322 B.C.E.) -- Art -- Artificial Intelligence -- Artificial Stupidity -- Asceticism -- Ascribed Status -- Ashby's Law of Requisite Variety -- Assimilation -- Atheism -- Attitude -- Attractor -- Attractor, Strange -- Augustine, St. (354-430) -- Author -- Authoritarianism -- Authoritarian Personality -- Authority -- Automation -- Autonomy -- Away(s) -- Axiology -- Axiom -- B -- Back Stage -- Bacon, Francis (1561-1626) -- Bakunin, Mikhail (1814-1876) -- Balance of Payments -- Balance of Trade -- Banditry, Social -- Barbarism -- Barthes, Roland (1915-1980) -- Base -- Baseball -- Base Communities -- Bastard -- Baudrillard, Jean (1929- ) -- Beauvoir, Simone de (1908-1986) -- Behavior -- Behaviorism -- Behavior Modification -- Belief.…”
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The method of the generalised eikonal : new approaches in the Diffraction Theory. by Vesnik, Michael V.

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Security, Privacy and Reliability in Computer Communications and Networks. by Sha, Kewei

Table of Contents: “…5.6 Threats Analysis and Future Trends -- 5.7 Conclusion -- References -- PART III -- Cryptographic Algorithms -- Chapter 6 -- Quasigroup-Based Encryption for Low-Powered Devices -- Abstract -- 6.1 Introduction -- 6.2 Background-Low Energy Cryptosystems -- 6.3 Overview of Quasigroup Encryption -- 6.4 The Preliminary Block Cipher Design -- 6.5 Overview of Software Implementation -- 6.6 Overview of Three FPGA Implementations -- 6.6.1 The Quasigroup Implementation -- 6.6.2 Comparison Design-Parallel AES -- 6.6.3 Hybrid Front-End/AES Design -- 6.7 Experimental Results -- 6.8 Toward a Single-Chip Implementation -- 6.9 Algorithm Results for B = 2 to 8 -- 6.10 Generating Quasigroups Fast -- 6.11 Our Quasigroup Block Cipher Algorithm -- 6.12 Cryptanalysis and Improvements in the Block Cipher -- 6.13 Overview of a General Linear Cryptanalytical Attack -- 6.14 The LAT Design -- 6.15 Pilingup Attempts for N = 16, 32, and 64 -- 6.16 Analysis of the Attack on the Quasigroup -- 6.17 The Issue of a Total Linear Bias of 1/2 -- 6.18 Attack Complexity -- 6.19 Possible Changes that Could Be Made in the Design of This Attack Model -- 6.20 Which Quasigroup Order Is Best? …”
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Essential principles for autonomous robotics by Hexmoor, Henry, 1960-

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Computer aided design and manufacturing by Bi, Zhuming, Wang, Xiaoqin (Writer on manufacturing)

Table of Contents: “…Evaluate Platform Solutions 159; 4.11 Computer Aided Tools (CAD) for Platform Technologies 160; 4.11.1 Modelling Techniques of Product Variants 163; 4.11.2 Design Toolboxes 163; 4.11.3 Custom Design Libraries 164; 4.12 Summary 165; 4.13 Design Projects 166; References 169; 5 Computer Aided Reverse Engineering 173; 5.1 Introduction 173; 5.2 RE as Design Methodology 175; 5.3 RE Procedure 178; 5.4 Digital Modelling 179; 5.4.1 Types of Digital Models 180; 5.4.2 Surface Reconstruction 181; 5.4.3 Algorithms for Surface Reconstruction 181; 5.4.4 Limitations of Existing Algorithms 182; 5.4.5 Data Flow in Surface Reconstruction 183; 5.4.6 Surface Reconstruction Algorithm 184; 5.4.7 Implementation Examples 186; 5.5 Hardware Systems for Data Acquisition 188; 5.5.1 Classification of Hardware Systems 191; 5.5.2 Positioning of Data Acquisition Devices 197; 5.5.3 Control of Scanning Processes 199; 5.5.4 Available Hardware Systems 200; 5.6 Software Systems for Data Processing 201; 5.6.1 Data Filtering 201; 5.6.2 Data Registration and Integration 204; 5.6.3 Feature Detection 205; 5.6.4 Surface Reconstruction 205; 5.6.5 Surface Simplification 205; 5.6.6 Segmentation 206; 5.6.7 Available Software Tools 206; 5.7 Typical Manufacturing Applications 206; 5.8 Computer Aided Reverse Engineering (CARE) 208; 5.8.1 Recap to Convert Sensed Data into Polygonal Models 209; 5.8.2 ScanTo3D for Generation of Parametric Models 211; 5.8.3 RE of Assembled Products 212; 5.9 RE -- Trend of Development 213; 5.10 Summary 213; 5.11 Design Project 214; References 215; 6 Computer Aided Machine Design 219; 6.1 Introduction 219; 6.2 General Functional Requirements (FRs) of Machines 222; 6.3 Fundamentals of Machine Design 223; 6.3.1 Link Types 223; 6.3.2 Joint Types and Degrees of Freedom (DoFs) 223; 6.3.3 Kinematic Chains 225; 6.3.4 Mobility of Mechanical Systems 226; 6.4 Kinematic Synthesis 230; 6.4.1 Type Synthesis 230; 6.4.2 Number Synthesis 230; 6.4.3 Dimensional Synthesis 232; 6.5 Kinematics 233; 6.5.1 Positions of Particles, Links, and Bodies in 2D and 3D Space 233; 6.5.2 Motions of Particles, Links, and Bodies 235; 6.5.3 Vector-Loop Method for Motion Analysis of a Plane Mechanism 240; 6.5.4 Kinematic Modelling Based on Denavit-Hartenberg (D-H) Parameters 246; 6.5.5 Jacobian Matrix for Velocity Relations 248; 6.6 Dynamic Modelling 259; 6.6.1 Inertia and Moments of Inertia 259; 6.6.2 Newton-Euler Formulation 261; 6.6.3 Lagrangian Method 266; 6.7 Kinematic and Dynamics Modelling in Virtual Design 269; 6.7.1 Motion Simulation 269; 6.7.2 Model Preparation 271; 6.7.3 Creation of a Simulation Model 271; 6.7.4 Define Motion Variables 274; 6.7.5 Setting Simulation Parameters 275; 6.7.6 Run Simulation and Visualize Motion 275; 6.7.7 Analyse Simulation Data 276; 6.7.8 Structural Simulation Using Motion Loads 277; 6.8 Summary 278; 6.9 Design Project 279; References 279; Part II Computer Aided Manufacturing (CAM) 281; 7 Group Technology and Cellular Manufacturing 283; 7.1 Introduction 283; 7.2 Manufacturing System and Components 2…”
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At a distance : precursors to art and activism on the Internet

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