Search Results - (((((((want OR manthe) OR wind) OR mantic) OR cantor) OR anne) OR halted) OR granting) algorithms.

Networks-on-chip : from implementations to programming paradigms by Ma, Sheng, Huang, Libo, 1976-, Lai, Mingche, Shi, Wei

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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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Learning Geospatial Analysis with Python - Second Edition. by Lawhead, Joel

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Deep Learning with Pytorch Quick Start Guide : Learn to Train and Deploy Neural Network Models in Python. by Julian, David

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Millimeter-wave digitally intensive frequency generation in CMOS by Wu, Wanghua, Staszewski, Robert Bogdan, 1965-, Long, John R. (John Robert), 1958-

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The next economic disaster : why it's coming and how to avoid it by Vague, Richard

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Oracle Primavera P6 version 8 : project and portfolio management : a comprehensive guide to managing projects, resources, and portfolios using Primavera P6, through version 8.2 by Williams, Daniel L.

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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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Listed Volatility and Variance Derivatives : a Python-based Guide. by Hilpisch, Yves

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Statistical learning from a regression perspective by Berk, Richard A.

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Exploratory data analysis with MATLAB by Martinez, Wendy L., Martinez, Angel R., Solka, Jeffrey

Table of Contents: “…3.4 Stochastic Neighbor Embedding3.5 Summary and Further Reading; Exercises; Chapter 4 Data Tours; 4.1 Grand Tour; 4.1.1 Torus Winding Method; 4.1.2 Pseudo Grand Tour; 4.2 Interpolation Tours; 4.3 Projection Pursuit; 4.4 Projection Pursuit Indexes; 4.4.1 Posse Chi-Square Index; 4.4.2 Moment Index; 4.5 Independent Component Analysis; 4.6 Summary and Further Reading; Exercises; Chapter 5 Finding Clusters; 5.1 Introduction; 5.2 Hierarchical Methods; 5.3 Optimization Methods- k-Means; 5.4 Spectral Clustering; 5.5 Document Clustering; 5.5.1 Nonnegative Matrix Factorization -- Revisited.…”
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IP multicast with applications to IPTV and mobile DVB-H by Minoli, Daniel, 1952-

Table of Contents: “…Cover -- TOC36;CONTENTS -- Preface -- About the Author -- CH36;1 INTRODUCTION TO IP MULTICAST -- 146;1 Introduction -- 146;2 Why Multicast Protocols are Wanted47;Needed -- 146;3 Basic Multicast Protocols and Concepts -- 146;4 IPTV and DVB45;H Applications -- 146;5 Course of Investigation -- Appendix 146;A58; Multicast IETF Request for Comments -- Appendix 146;B58; Multicast Bibliography -- References -- CH36;2 MULTICAST ADDRESSING FOR PAYLOAD -- 246;1 IP Multicast Addresses -- 246;146;1 Limited Scope Addresses -- 246;146;2 GLOP Addressing -- 246;146;3 Generic IPv4 Addressing -- 246;2 Layer 2 Multicast Addresses -- 246;246;1 Ethernet MAC Address Mapping -- 246;3 MPEG45;Layer Addresses -- References -- CH36;3 MULTICAST PAYLOAD FORWARDING -- 346;1 Multicasting on a LAN Segment -- 346;2 Multicasting between Network Segments -- 346;3 Multicast Distribution Trees -- 346;4 Multicast Forwarding58; Reverse Path Forwarding -- 346;5 Multicast Forwarding58; Center45;Based Tree Algorithm -- 346;6 Implementing IP Multicast in a Network -- References -- CH36;4 DYNAMIC HOST REGISTRATION8212;INTERNET GROUP MANAGEMENT PROTOCOL -- 446;1 IGMP Messages -- 446;2 IGMPv3 Messages -- 446;3 IGMP Operation -- Appendix 446;A58; Protocol Details for IGMPv2 -- 446;A46;1 Overview -- 446;A46;2 Protocol Description -- 446;A46;3 Receiver 40;Host41; State Diagram -- 446;A46;4 Router State Diagram -- Appendix 446;B58; IGMP Snooping Switches -- Appendix 446;C58; Example of Router Configurations -- References -- CH36;5 MULTICAST ROUTING8212;SPARSE45;MODE PROTOCOLS58; PROTOCOL INDEPENDENT MULTICAST -- 546;1 Introduction to PIM -- 546;2 PIM SM Details -- 546;246;1 Approach -- 546;246;2 PIM SM Protocol Overview -- 546;246;3 Detailed Protocol Description -- 546;246;4 Packet Formats -- References -- CH36;6 MULTICAST ROUTING8212;SPARSE45;MODE PROTOCOLS58; CORE45;BASED TREES -- 646;1 Motivation -- 646;2 Basic Operation -- 646;3 CBT Components and Functions -- 646;346;1 CBT Control Message Retransmission Strategy -- 646;346;2 Nonmember Sending -- 646;4 Core Router Discovery -- 646;5 Protocol Specification Details -- 646;546;1 CBT HELLO Protocol -- 646;546;2 JOIN_REQUEST Processing -- 646;546;3 JOIN_ACK Processing -- 646;546;4 QUIT_NOTIFICATION Processing -- 646;546;5 ECHO_REQUEST Processing -- 646;546;6 ECHO_REPLY Processing -- 646;546;7 FLUSH_TREE Processing -- 646;546;8 Nonmember Sending -- 646;546;9 Timers and Default Values -- 646;546;10 CBT Packet Formats and Message Types -- 646;546;11 Core Router Discovery -- 646;6 CBT Version 3 -- 646;646;1 The First Step58; Joining the Tree -- 646;646;2 Transient State -- 646;646;3 Getting 34;On Tree34; -- 646;646;4 Pruning and Prune State -- 646;646;5 The Forwarding Cache -- 646;646;6 Packet Forwarding -- 646;646;7 The 34;Keepalive34; Protocol -- 646;646;8 Control Message Precedence and Forwarding Criteria -- 646;646;9 Broadcast LANs -- 646;646;10 The 34;all45;cbt45;routers34; Group -- 646;646;11 Nonmember Sending -- References -- CH36;7 MULTICAST ROUTING8212;DENSE45;MODE PROTOCOLS58; PIM DM.…”
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Anesthesia student survival guide : a case-based approach

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The Johns Hopkins guide to digital media

Table of Contents: “…Berry -- Cognitive implications of new media / Anne Mangen and Jean-Luc Velay -- Collaborative narrative / Scott Rettberg -- Collective intelligence / John Duda -- Combinatory and automatic text generation / Philippe Bootz and Christopher Funkhouser -- Computational linguistics / Inderjeet Mani -- Conceptual writing / Darren Wershler -- Copyright / Benjamin J. …”

Fuzzy Multiple Attribute Decision Making : Methods and Applications by Chen, Shu-Jen

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Swift 2 design patterns : build robust and scalable iOS and Mac OS X game applications by Lange, Julien

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Nonlinear science and complexity

Table of Contents: “…Bruzón -- Applying a new algorithm to derive nonclassical symmetries / M.S. …”
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Handbook of safety principles

Table of Contents: “…Success or Failure / Ann Enander -- 30.8. Relations to Other Safety Principles / Ann Enander -- References / Ann Enander -- Further Reading / Ann Enander -- 31. …”
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Decision Intelligence for Dummies by Baker, Pamela

Table of Contents: “…Preventing Wrong Influences from Affecting Decisions -- Bad influences in AI and analytics -- The blame game -- Ugly politics and happy influencers -- Risk Factors in Decision Intelligence -- DI and Hyperautomation -- Part 5 The Part of Tens -- Chapter 17 Ten Steps to Setting Up a Smart Decision -- Check Your Data Source -- Track Your Data Lineage -- Know Your Tools -- Use Automated Visualizations -- Impact = Decision -- Do Reality Checks -- Limit Your Assumptions -- Think Like a Science Teacher -- Solve for Missing Data -- Partial versus incomplete data -- Clues and missing answers -- Take Two Perspectives and Call Me in the Morning -- Chapter 18 Bias In, Bias Out (and Other Pitfalls) -- A Pitfalls Overview -- Relying on Racist Algorithms -- Following a Flawed Model for Repeat Offenders -- Using A Sexist Hiring Algorithm -- Redlining Loans -- Leaning on Irrelevant Information -- Falling Victim to Framing Foibles -- Being Overconfident -- Lulled by Percentages -- Dismissing with Prejudice -- Index -- EULA.…”
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Medical and Care Compunetics 2 : Medical and Care Compunetics 2. by Bos, L.

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