Search Results - (((((((ant OR wantis) OR semantic) OR find) OR cantor) OR anne) OR plane) OR hints) algorithms.

Personality Revolution : Using AI to Understand Your Customers and Win More Business. by D'Agostino, Andrew

Table of Contents: “…Navigating a Complex, Biased, Hyper-connected WorldPART II Read Your Own User Manual: Understanding your personality and how to harness it; Chapter 6 Personality Differences Shape Every Relationship; Chapter 7 How to Find Your Personality Type; Chapter 8 Take a Personality Assessment; Using your personality at work; Chapter 9 The 16 Personality Types; Type D: The Captain; Type Di: The Driver; Type DI: The Initiator; Type ID: The Influencer; Type I: The Motivator; Type Is: The Encourager; Type IS: The Harmonizer; Type SI: The Counselor; Type S: The Supporter; Type Sc: The Planner…”
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Understanding ultrasonic level measurement by Milligan, Stephen

Table of Contents: “…. -- Ultrasonic instrumentation -- The transducer -- Transducer environments -- Transducer accuracy -- Transducer resolution and accuracy -- Impedance matching -- Axis of transmission -- Beam width -- Beam spreading -- Ringdown -- The controllers -- Digital filtering -- Averaging echoes -- Echo extraction algorithms -- Summary -- Notes.…”
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Blockchain and the Digital Economy : The Socio-Economic Impact of Blockchain Technology. by Steinmetz, Fred

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Fuzzy intelligent systems : methodologies, techniques, and applications

Table of Contents: “…7.1 Introduction -- 7.2 Existing Technology and its Review -- 7.3 Research Design -- 7.4 Findings or Result Discussion so for in the Area of GFS Hybridization -- 7.5 Conclusion -- References -- 8 Using Fuzzy Technique Management of Configuration and Status of VM for Task Distribution in Cloud System -- 8.1 Introduction -- 8.2 Literature Review -- 8.3 Logic System for Fuzzy -- 8.4 Proposed Algorithm -- 8.5 Results of Simulation -- 8.6 Conclusion -- References -- 9 Theorems on Fuzzy Soft Metric Spaces -- 9.1 Introduction -- 9.2 Preliminaries -- 9.3 FSMS -- 9.4 Main Results…”
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System : the shaping of modern knowledge by Siskin, Clifford

Table of Contents: “…7 SECRETLY SEEKING SYSTEM-INSTITUTING THE SOCIAL -- SUBJECTS FOR SYSTEMS-"THE PROSCRIBED LITTLE PERSONAGE-I" -- THE "CHARACTER OF MEMBERS"-CLUBS AS INTERFACES -- SYSTEM INCARNATE-DANCING INTO MODERNITY -- CODA -- Re:ENLIGHTENMENT (ALGORITHMICALLY ENHANCED SYSTEMS) -- "THE WHOLE ENCHILADA" -- THE PERSISTENCE OF SYSTEM -- APPENDIX A: NOTES ON VISUALIZATION -- THE SCATTER PLOTS -- THE TECTONIC DIAGRAMS -- TECHNICAL NOTES -- APPENDIX B: TITLES CONTAINING ESSAY(S) IN THE PLURAL VERSUS THE SINGULAR -- NOTES -- PROLOGUE -- CHAPTER 1 -- CHAPTER 2 -- CHAPTER 3 -- CHAPTER 4 -- CHAPTER 5 -- CHAPTER 6 -- CHAPTER 7 -- CODA -- REFERENCES -- INDEX.…”
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Analytics stories : using data to make good things happen by Winston, Wayne L.

Table of Contents: “…-- Value-Added Assessments of Teacher Effectiveness -- Berkeley, Buses, Cars, and Planes -- Is Carmelo Anthony a Hall of Famer? -- Was Derek Jeter a great fielder? …”
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Steel connection analysis by Rugarli, Paolo, 1963-

Table of Contents: “…2.3.1 Need for the Jnode Concept2.3.2 Jnode Definition; 2.4 Jnode Analytics; 2.4.1 Classification of Jnodes; 2.4.2 Simple Jnodes; 2.4.3 Hierarchical Jnodes; 2.4.4 Central Jnodes; 2.4.5 Cuspidal Jnodes; 2.4.6 Tangent Jnodes; 2.4.7 Constraints; 2.4.8 Summary of Jnode Classification; 2.4.9 Setting Connection Codes: Examples; 2.5 Equal Jnodes Detection; 2.5.1 Toponode; 2.5.2 Jnode Data Structure; 2.5.3 Superimposable Member Couples; 2.5.4 Criteria to Assess Jnodes Equality; 2.5.5 Algorithm to Find Equal Jnodes; 2.5.6 Examples; 2.6 Structural Connectivity Indices; 2.7 Particular Issues.…”
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Explorations in Computing : an Introduction to Computer Science. by Conery, John S.

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Convergence of Communications, Navigation, Sensing and Services. by Ligthart, L. P.

Table of Contents: “…5.5.1 Formulation of the Problem for Finding a GeneralizedP-median Set as a Linear Programming5.5.2 ADD/DROP Heuristics Algorithm; 5.6 Example of Application of ADD/DROP Heuristics for Solving the Cascade Problem of Hierarchically Connected Sets; 5.7 Conclusion; References; Biographies; 6 Machine-to-Machine Communications for CONASENSE; 6.1 Introduction; 6.2 Wireless Infrastructure; 6.2.1 Ubiquitous Connections via 3GPP Heterogeneous Network (HetNet) Architecture; 6.2.2 D2D Empowered Group Based Operations of MTC Devices; 6.2.3 Cognitive Operations of MTC Devices.…”
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Mastering OpenCV with Practical Computer Vision Projects. by Emami, Shervin

Table of Contents: “…Marker-less Augmented Reality; Marker-based versus marker-less AR; Using feature descriptors to find an arbitrary image on video; Feature extraction; Definition of a pattern object.…”
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Trading the Measured Move : a Path to Trading Success in a World of Algos and High Frequency Trading. by Halsey, David

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Securing SQL server : protecting Your database from attackers by Cherry, Denny

Table of Contents: “…Server FirewallsWindows Firewall Inbound Rules; Windows Firewall Outbound Rules; Special Requirements for Clustering; Direct Internet Access; Public IP addresses versus private IP addresses; vLANs; Accessing SQL server from home; Setting up Routing and Remote Access; Allowing Users to VPN in to the Network; Setting up Client VPN Connection; Physical security; Keep Your Hands Off My Box; Open Network Ports; Unlocked Workstations; Automatically Locking Computers; Social engineering; Finding the instances; Testing the network security; Antivirus installation on SQL servers; Summary; References.…”
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Pattern discovery in biomolecular data : tools, techniques, and applications

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Asymptotic models of fields in dilute and densely packed composites by Movchan, A. B. (Alexander B.)

Table of Contents: “…Motivation; 1.1.2 Asymptotic algorithm involving a boundary layer; 1.1.2.1 Formulation of the problem; 1.1.2.2 The leading-order approximation; 1.1.2.3 Asymptotic formula for the energy; 1.1.3 The dipole matrix; 1.1.3.1 Definition of the dipole matrix; 1.1.3.2 Symmetry of the dipole matrix; 1.1.3.3 The energy asymptotics for a body with a small void; 1.1.4 Dipole matrix for a 2D void in an infinite plane.…”
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Biological computation by Lamm, Ehud

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Radar for Fully Autonomous Driving. by Markel, Matt

Table of Contents: “…4.2.1 Waveform Orthogonality via TDM -- 4.2.2 Waveform Orthogonality via DDM -- 4.2.3 Waveform Orthogonality via FDM -- 4.3 Angle Finding in Automotive MIMO Radar -- 4.3.1 High Resolution Angle Finding with ULA -- 4.3.2 High Resolution Angle Finding with SLA -- 4.4 High Resolution Imaging Radar for Autonomous Driving -- 4.4.1 Cascade of Multiple Radar Transceivers -- 4.4.2 Examples of Cascaded Imaging Radars -- 4.4.3 Design Challenges of Imaging Radar -- 4.5 Challenges in Automotive MIMO Radar -- 4.5.1 Angle Finding in the Presence of Multipath Reflections -- 4.5.2 Waveform Orthogonality in Automotive MIMO Radar -- 4.5.3 Efficient, High Resolution Angle Finding Algorithms Are Needed -- References -- Chapter 5 Synthetic Aperture Radar for Automotive Applications -- 5.1 Introduction -- 5.1.1 Historical Background -- 5.1.2 Comparison to Traditional Radar Systems -- 5.1.3 SAR and Point Cloud Imaging Performance -- 5.1.4 Applications for Automotive Use -- 5.2 Mathematical Foundation -- 5.2.1 Key Assumptions -- 5.2.2 Signal Model -- 5.2.3 Slow Time -- 5.3 Building an Automotive SAR -- 5.3.1 Measuring Ego-Motion -- 5.3.2 SAR Image Formation -- 5.3.3 Coexistence with Point Cloud Pipeline -- 5.3.4 Elevation Information -- 5.4 Future Directions -- 5.4.1 Forward-Facing SAR -- 5.4.2 SAR for Moving Objects -- 5.4.3 Gapped SAR -- 5.5 Conclusion -- References -- Chapter 6 Radar Transceiver Technologies -- 6.1 Background and Introduction to Automotive Radar -- 6.2 Block Diagram Overview of an FMCW Radar Transceiver -- 6.3 Challenges with Deeply Scaled CMOS -- 6.4 Active Devices in CMOS -- 6.5 Passives in CMOS -- 6.6 Circuit Architectures Suitable for Advanced CMOS -- 6.6.1 The Transmit Power Amplifier -- 6.6.2 The TX Phase Shifter -- 6.7 The LO/FMCW Chirp Generator -- 6.8 The Receiver Signal Chain -- 6.8.1 RX Frontend -- 6.8.2 Radar RX Baseband -- 6.9 Summary.…”
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A Primer on Machine Learning Applications in Civil Engineering by Deka, Paresh Chandra

Table of Contents: “…Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Contents -- Preface -- Acknowledgments -- A Primer on Machine Learning Applications in Civil Engineering -- Author -- 1: Introduction -- 1.1 Machine Learning -- 1.2 Learning from Data -- 1.3 Research in Machine Learning: Recent Progress -- 1.4 Artificial Neural Networks -- 1.5 Fuzzy Logic (FL) -- 1.6 Genetic Algorithms -- 1.7 Support Vector Machine (SVM) -- 1.8 Hybrid Approach (HA) -- Bibliography -- 2: Artificial Neural Networks -- 2.1 Introduction to Fundamental Concepts and Terminologies -- 2.2 Evolution of Neural Networks -- 2.3 Models of ANN -- 2.4 McCulloch-Pitts Model -- 2.5 Hebb Network -- 2.6 Summary -- 2.7 Supervised Learning Network -- 2.7.1 Perceptron Network -- 2.7.2 Adaptive Linear Neuron -- 2.7.3 Back-Propagation Network -- 2.7.4 Radial Basis Function Network -- 2.7.5 Generalized Regression Neural Networks -- 2.7.6 Summary -- 2.8 Unsupervised Learning Networks -- 2.8.1 Introduction -- 2.8.2 Kohonen Self-Organizing Feature Maps -- 2.8.3 Counter Propagation Network -- 2.8.4 Adaptive Resonance Theory Network -- 2.8.5 Summary -- 2.9 Special Networks -- 2.9.1 Introduction -- 2.9.2 Gaussian Machine -- 2.9.3 Cauchy Machine -- 2.9.4 Probabilistic Neural Network -- 2.9.5 Cascade Correlation Neural Network -- 2.9.6 Cognitive Network -- 2.9.7 Cellular Neural Network -- 2.9.8 Optical Neural Network -- 2.9.9 Summary -- 2.10 Working Principle of ANN -- 2.10.1 Introduction -- 2.10.2 Types of Activation Function -- 2.10.3 ANN Architecture -- 2.10.4 Learning Process -- 2.10.5 Feed-Forward Back Propagation -- 2.10.6 Strengths of ANN -- 2.10.7 Weaknesses of ANN -- 2.10.8 Working of the Network -- 2.10.9 Summary -- Bibliography -- 3: Fuzzy Logic -- 3.1 Introduction to Classical Sets and Fuzzy Sets -- 3.1.1 Classical Sets -- 3.1.2 Fuzzy Sets -- 3.1.3 Summary.…”
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Artificial intelligence research and development : current challenges, new trends and applications

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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Blockchain-based peer-to-peer transactions in energy systems by Nwulu, Nnamdi, Damisa, Uyikumhe

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Power system dynamics by Guruprasada, Rau V.

Table of Contents: “…18.1 Concept of Lyapunov Stability, Asymptotic Stability and Instability -- 18.2 Lyapunov's Asymptotic Stability Theorem -- References -- Chapter 19 Methods of Construction of Lyapunov Functions -- 19.1 Sylvester's Criteria for Definiteness and Semi-Definiteness -- 19.2 Construction of Lyapunov Functions for a Power System -- References -- Chapter 20 Generation of Lyapunov Functions -- 20.1 Energy Metric Algorithm for Generation of Lyapunov Functions -- 20.2 Application to Power System -- 20.3 Evaluation of Region of Asymptotic Stability -- 20.4 Application of Lyapunov Method to Linear System -- References -- Chapter 21 Exercise Problems -- 21.1 Problems with Solutions -- 21.2 Unsolved Problems -- References.…”
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