Search Results - (((((((ant OR wanting) OR cantee) OR arts) OR cantor) OR anne) OR warte) OR mantis) algorithms.

Diagnostic Imaging of the Foot and Ankle. by Szeimies, Ulrike

Table of Contents: “…Diagnostic Imaging of the Foot and Ankle; Title Page; Copyright; Dedication; Contents; Preface; Contributors; Abbreviations; 1 Imaging Techniques; 1.1 Magnetic Resonance Imaging (MRI); 1.1.1 Imaging Strategy; 1.1.2 Post-Exercise MRI; 1.2 Multidetector-Row Spiral Computed Tomography (CT); 1.2.1 Positioning; 1.2.2 Protocol; 1.2.3 Indications; 1.2.4 Special Techniques; 1.3 Radiography; 1.3.1 Forefoot; 1.3.2 Hindfoot; 1.4 Ultrasound; 1.5 Bibliography; 2 Clinical Evaluation; 2.1 Diagnostic Algorithm; 2.1.1 Clinical Examination; 2.1.2 Imaging and Other Tests; 2.1.3 Referral for Further Evaluation.…”
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Principles of Quantum Computation and Information, Volume I : Basic Concepts. by Casati, Giulio, Strini, Giuliano

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Business Hack : the Wealth Dragon Way to Build a Successful Business in the Digital Age. by Lee, John

Table of Contents: “…; Disrupting the Market; The Power of Algorithms; Beyond the Digital Age; Chapter 12 Don't Become a Human Bot!…”
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Frontiers of Artificial Intelligence in Medical Imaging. by Razmjooy, Navid

Table of Contents: “…5.5 Electromagnetic field optimization algorithm -- 5.6 Developed electromagnetic field optimization algorithm -- 5.7 Simulation results -- 5.7.1 Image acquisition -- 5.7.2 Pre-processing stage -- 5.7.3 Processing stage -- 5.7.4 Classification -- 5.8 Final evaluation -- 5.9 Conclusions -- References -- Chapter 6 Evaluation of COVID-19 lesion from CT scan slices: a study using entropy-based thresholding and DRLS segmentation -- 6.1 Introduction -- 6.2 Context -- 6.3 Methodology -- 6.3.1 COVID-19 database -- 6.3.2 Image conversion and pre-processing -- 6.3.3 Image thresholding…”
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Handbook of biometrics for forensic science

Table of Contents: “…Preface; Contents; 1 Biometric Technologies for Forensic Science and Policing: State of the Art; Abstract; 1.1 A Short Historical Introduction and Forensic Context; 1.2 Recent Developments of Biometric Technologies in Forensic Science; 1.3 Challenges; 1.4 Conclusions; Acknowledgements; References; Analysis of Fingerprints and Fingermarks; 2 Capture and Analysis of Latent Marks; Abstract; 2.1 Introduction; 2.2 Fingerprint Characteristics; 2.3 Conventional Latent Mark Acquisition Techniques; 2.4 Contact-Less Latent Mark Acquisition Techniques; 2.5 Latent Mark Analysis Process.…”
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Natural language processing and computational linguistics. 1 : speech morphology and syntax by Kurdi, Mohamed Zakaria

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Pervasive computing and networking

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Human-assisted intelligent computing : modeling, simulations and applications

Table of Contents: “…1. Machine learning algorithms to improve crop evapotranspiration prediction covering a broad range of environmental gradients in agriculture 4.0 : a review / Parijata Majumdar, Diptendu Bhattacharya, Sanjoy Mitra and Mukhdeep Singh Manshahia -- 2. …”
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Machine Learning with Swift : Artificial Intelligence for iOS. by Sosnovshchenko, Oleksandr

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Hack proofing your network

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Mathematical programming and game theory for decision making

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Inside jokes : using humor to reverse-engineer the mind by Hurley, Matthew M., 1977-

Table of Contents: “…-- Emotions -- The rationality of emotions -- The irrationality of emotions -- Emotional algorithms -- A few implications.…”
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Fog computing : theory and practice

Table of Contents: “…Mobile Fog Computing: Architectures, Approaches and Open Challenges / Satish Narayana Srirama -- Edge Devices: A Survey, Use Cases and Future Challenges / Cosmin Avasalcai -- Deep Learning in the Era of Edge Computing: Opportunities and Challenges / Mi Zhang -- Caching, Security, and Mobility in Content Centric Networking / Osman Khalid -- Security and Privacy Issues in Fog Computing / Hasan Ali Khattak -- How Fog Computing Can Support Latency/Reliability-sensitive IoT Applications: An Overview and a Taxonomy of State-of-the-Art Solutions / Sajal Das -- Harnessing the Computing Continuum for Programming Our World / Jack Dongara -- Fog Computing for Energy Harvesting-Enabled Internet of Things / George K. …”
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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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Discrete element model and simulation of continuous materials behavior set. Volume 1, Discrete element method to model 3D continuous materials by Jebahi, Mohamed

Table of Contents: “…Organization; 1: State of the Art: Discrete Element Modeling; 1.1. Introduction; 1.2. …”
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Nonlinear estimation and applications to industrial systems control

Table of Contents: “…General Approach; Remarks; 5. Algorithm Description; FD Algorithm.…”
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MATLAB for Machine Learning. by Ciaburro, Giuseppe

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Fundamentals of patenting and licensing for scientists and engineers by Ma, Matthew Y.

Table of Contents: “…Innovation harvesting. 5.1. Knowing the art. 5.2. Patentability test. 5.3. Patenting beyond core algorithms. 5.4. …”
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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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