Search Results - (((((((ant OR alter) OR find) OR kkantor) OR cantor) OR anne) OR halted) OR wanting) algorithms.

Machine Learning with Swift : Artificial Intelligence for iOS. by Sosnovshchenko, Oleksandr

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Airline industry : strategies, operations and safety

Table of Contents: “…4.6. Problem Solving Algorithms 5. EXPERIMENTAL SETUP ; 6. RESULTS AND DISCUSSION ; 7. …”
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Predictive Analytics For Dummies. by Bari, Anasse

Table of Contents: “…Recognizing Your Data TypesStructured and unstructured data; Static and streamed data; Identifying Data Categories; Attitudinal data; Behavioral data; Demographic data; Generating Predictive Analytics; Data-driven analytics; User-driven analytics; Connecting to Related Disciplines; Statistics; Data mining; Machine learning; Chapter 4 Complexities of Data; Finding Value in Your Data; Delving into your data; Data validity; Data variety; Constantly Changing Data; Data velocity; High volume of data; Complexities in Searching Your Data; Keyword-based search; Semantic-based search.…”
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Advanced Python Programming : Build High Performance, Concurrent, and Multi-Threaded Apps with Python Using Proven Design Patterns. by Lanaro, Gabriele

Table of Contents: “…Cover; Title Page; Copyright; About Packt; Contributors; Table of Contents; Preface; Chapter 1: Benchmarking and Profiling; Designing your application; Writing tests and benchmarks; Timing your benchmark; Better tests and benchmarks with pytest-benchmark; Finding bottlenecks with cProfile; Profile line by line with line_profiler; Optimizing our code; The dis module; Profiling memory usage with memory_profiler; Summary; Chapter 2: Pure Python Optimizations; Useful algorithms and data structures; Lists and deques; Dictionaries; Building an in-memory search index using a hash map; Sets; Heaps…”
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Artificial Intelligence in Radiation Therapy. by Sumida, Iori

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Advanced deep learning with R : become an expert at designing, building, and improving advanced neural network models using R by Rai, Bharatendra K.

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Power and energy systems III : selected, peer reviewed papers from the 2013 3rd International Conference on Power and Energy Systems (ICPES 2013), November 23-24, Bangkok, Thailand

Table of Contents: “…Appropriate Electric Energy Conservation Measures for Big Mosques in Riyadh CityBayesian Algorithm Based on Airborne Power Supply System; Study on the Cooling System of Super-Capacitors for Hybrid Electric Vehicle; A Charging Management of Electric Vehicles Based on Campus Survey Data; Back-EMF Position Detection Technology for Brushless DC Motor; Stress State of Turbine Blade Root and Rim Considering Manufacturing Variations; Analysis on a Gas Turbine Sealing Disk Structure and Material Strength; A Kind of Adjustable Electric Heating Pipe Power Electrode Preparation Equipment.…”
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Smart Cities, Smart Future : Technology, Security and Prosperity in the Connected Metropolis. by Barlow, Mike

Table of Contents: “…Cybersecurity by DesignThe Smart-City CISO; Hierarchies and Networks; A Universe of Connected People and Devices; Endnotes; Chapter 10 Finding a Balance; Data for Good; Location, Location, Location; Hard Questions; Algorithmic Bias; Can We Prevent Crime Before It Happens?…”
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Image-Guided Therapy Systems. by Vaezy, Shahram

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Bayesian Analysis with Python. by Osvaldo Martin

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Recent advances in computational sciences : selected papers from the International Workshop on Computational Sciences and its Education, Beijing, China, 29-31 August 2005

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Mathematical Methods in Interdisciplinary Sciences. by Chakraverty, Snehashish

Table of Contents: “…1.2.2.1 Architecture of Single-Layer LgNN Model -- 1.2.2.2 Training Algorithm of Laguerre Neural Network (LgNN) -- 1.2.2.3 Gradient Computation of LgNN -- 1.3 Methodology for Solving a System of Fredholm Integral Equations of Second Kind -- 1.3.1 Algorithm -- 1.4 Numerical Examples and Discussion -- 1.4.1 Differential Equations and Applications -- 1.4.2 Integral Equations -- 1.5 Conclusion -- References -- Chapter 2 Deep Learning in Population Genetics: Prediction and Explanation of Selection of a Population -- 2.1 Introduction -- 2.2 Literature Review -- 2.3 Dataset Description…”
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Disobedient Aesthetics : Surveillance, Bodies, Control by Stagliano, Anthony, 1973-

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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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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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FX barrier options : a comprehensive guide for industry quants by Dadachanji, Zareer

Table of Contents: “…Stupid; 4.10 Five things we want from a model; 4.11 Stochastic volatility (SV) models; 4.11.1 SABR model; 4.11.2 Heston model; 4.12 Mixed local/stochastic volatility (lsv) models; 4.12.1 Term structure of volatility of volatility; 4.13 Other models and methods; 4.13.1 Uncertain Volatility (UV) models; 4.13.2 Jump-diffusion models; 4.13.3 Vanna-volga methods; 5 Smile Risk Management; 5.1 Black-Scholes with term structure; 5.2 Local volatility model; 5.3 Spot risk under smile models; 5.4 Theta risk under smile models; 5.5 Mixed local/stochastic volatility models; 5.6 Static hedging; 5.7 Managing risk across businesses; 6 Numerical Methods; 6.1 Finite-difference (FD) methods; 6.1.1 Grid geometry; 6.1.2 Finite-difference schemes; 6.2 Monte Carlo (MC) methods; 6.2.1 Monte Carlo schedules; 6.2.2 Monte Carlo algorithms; 6.2.3 Variance reduction; 6.2.4 The Brownian Bridge; 6.2.5 Early…”
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