Search Results - (((((((anti OR want) OR mantis) OR when) OR cantor) OR anne) OR share) OR hints) algorithms.

Kaplan's clinical hypertension by Kaplan, Norman M., 1931-2020, Victor, Ronald G., Flynn, Joseph T.

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Materials Science and Intelligent Technologies Applications : Selected, Peer Reviewed Papers from the 2014 3rd International Conference on Key Engineering Materials and Computer Sc...

Table of Contents: “…Automatic Badminton Action Recognition Using RGB-D SensorKinect-Based Badminton Action Analysis System; A Review of Hot Topic Detection and Tracking Technology; Study on the Improvement of TFIDF Algorithm in Data Mining; A New Protocol for Secure Distributed Multiplication of Two Polynomial Shared Values; Human Posture Recognition Based on DAG-SVMS; The Design and Implementation of Astronomical Multi-Catalog Storage and Cross-Match Based on Hadoop; The Multi-Scale Hough Transform Lane Detection Method Based on the Algorithm of Otsu and Canny; Design of Heart Sound Analyzer.…”
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Fundamentals of Parallel Computing. by Razdan, Sanjay

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Learning concurrency in Kotlin : build highly efficient and robust applications by Castiblanco Torres, Miguel Angel

Table of Contents: “…; Processes, threads, and coroutines; Processes; Threads; Coroutines; Putting things together; Introduction to concurrency; Concurrency is not parallelism; CPU-bound and I/O-bound; CPU-bound; I/O-bound; Concurrency versus parallelism in CPU-bound algorithms; Single-core execution; Parallel execution; Concurrency versus parallelism in I/O-bound algorithms; Why concurrency is often feared; Race conditions; Atomicity violation; Deadlocks; Livelocks…”
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Insect media : an archaeology of animals and technology by Parikka, Jussi, 1976-

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Accelerating MATLAB with GPU computing : a primer with examples by Suh, Jung W., Kim, Youngmin

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Parallel Computing : Advances and Current Issues, Proceedings of the International Conference Parco2001. by Joubert, G. R.

Table of Contents: “…Committees ; Preface ; Invited Papers ; Deploying Parallel Numerical Library Routines to Cluster Computing in a Self Adapting Fashion ; 1 Overview ; 2 Numerical libraries in shared homogeneous distributed environments ; 3 Sample software implementation and results.…”
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Design in Crisis : New Worlds, Philosophies and Practices. by Fry, Tony

Table of Contents: “…Sacrifices that do not work in a crisis -- 3. When design goes south: from decoloniality, through declassification to dessobons -- 4. …”
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Iterative learning control for multi-agent systems coordination by Yang, Shiping, 1987-, Xu, Jian-Xin, Li, Xuefang, 1985-, Shen, Dong, 1982-

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Natural language processing with TensorFlow : teach language to machines using Python's deep learning library by Ganegedara, Thushan

Table of Contents: “…Implementing skip-gram with TensorFlowThe Continuous Bag-of-Words algorithm; Implementing CBOW in TensorFlow; Summary; Chapter 4: Advanced Word2vec; The original skip-gram algorithm; Implementing the original skip-gram algorithm; Comparing the original skip-gram with the improved skip-gram; Comparing skip-gram with CBOW; Performance comparison; Which is the winner, skip-gram or CBOW?…”
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Versatile Video Coding by Dominguez, Humberto Ochoa

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Advances in time series forecasting. Volume 2

Table of Contents: “…INTRODUCTION -- CLASSICAL TIME SERIES FORECASTING MODELS -- ARTIFICIAL NEURAL NETWORKS FOR FORECASTING TIME SERIES -- A NEW ARTIFICIAL NEURAL NETWORK WITH DETERMINISTIC COMPONENTS -- APPLICATIONS -- CONCLUSION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENTS -- REFERENCES -- A Fuzzy Time Series Approach Based on Genetic Algorithm with Single Analysis Process -- Ozge Cagcag Yolcu* -- INTRODUCTION -- FUZZY TIME SERIES -- RELATED METHODS -- Genetic Algorithm (GA) -- Single Multiplicative Neuron Model -- PROPOSED METHOD -- APPLICATIONS -- CONCLUSION AND DISCUSSION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENTS -- REFERENCES -- Forecasting Stock Exchanges with Fuzzy Time Series Approach Based on Markov Chain Transition Matrix -- Cagdas Hakan Aladag1,* and Hilal Guney2 -- INTRODUCTION -- FUZZY TIME SERIES -- TSAUR 'S FUZZY TIME SERIES MARKOV CHAIN MODEL -- THE IMPLEMENTATION -- CONCLUSION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENTS -- REFERENCES -- A New High Order Multivariate Fuzzy Time Series Forecasting Model -- Ufuk Yolcu* -- INTRODUCTION -- RELATED METHODOLOGY -- The Fuzzy C-Means (FCM) Clustering Method -- Single Multiplicative Neuron Model Artificial Neural Network (SMN-ANN) -- Fuzzy Time Series -- THE PROPOSED METHOD -- APPLICATIONS -- CONCLUSIONS AND DISCUSSION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENTS -- REFERENCES -- Fuzzy Functions Approach for Time Series Forecasting -- Ali Z. …”
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Process control : a practical approach by King, Myke, 1951-

Table of Contents: “…Title Page ; Copyright Page; Contents; Preface; About the Author; Chapter 1 Introduction; Chapter 2 Process Dynamics; 2.1 Definition; 2.2 Cascade Control; 2.3 Model Identification; 2.4 Integrating Processes; 2.5 Other Types of Process; 2.6 Robustness; Chapter 3 PID Algorithm; 3.1 Definitions; 3.2 Proportional Action; 3.3 Integral Action; 3.4 Derivative Action; 3.5 Versions of Control Algorithm; 3.6 Interactive PID Controller; 3.7 Proportional-on-PV Controller ; 3.8 Nonstandard Algorithms; 3.9 Tuning; 3.10 Ziegler-Nichols Tuning Method ; 3.11 Cohen-Coon Tuning Method.…”
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Scientific computing with multicore and accelerators

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Stochastic Models in Reliability Engineering. by Cui, Lirong

Table of Contents: “…4.3.1 Run and Phrase -- 4.3.2 Multi-State Compression Algorithm -- 4.4 Proposed Multi-State Inference Algorithm -- 4.4.1 Rules for Calculating Intermediate Variables -- 4.4.2 Proposed Multi-State Inference Algorithm -- 4.5 Case Study -- 4.5.1 Case Background -- 4.5.2 Calculation and Analysis -- 4.6 Summary -- Appendix A -- Appendix B -- References -- Chapter 5 Reliability Analysis of Demand-Based Warm Standby System with Multi-State Common Bus -- 5.1 Introduction -- 5.2 Model Description for a DBWSS with Multi-State Common Bus Performance Sharing…”
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The book of Qt 4 : the art of building Qt applications by Molkentin, Daniel

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PRINCIPLES OF QUANTUM ARTIFICIAL INTELLIGENCE. by Wichert, Andreas

Table of Contents: “…Computation; 2.1 Entscheidungsproblem; 2.1.1 Cantor's diagonal argument; 2.1.2 Reductio ad absurdum; 2.2 Complexity Theory; 2.2.1 Decision problems; 2.2.2 P and NP; 2.3 Church-Turing Thesis; 2.3.1 Church-Turing-Deutsch principle; 2.4 Computers; 2.4.1 Analog computers; 2.4.2 Digital computers; 2.4.3 Von Neumann architecture; 3. …”
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Hands-On Blockchain with Hyperledger : Building Decentralized Applications with Hyperledger Fabric and Composer. by Baset, Salman

Table of Contents: “…Decentralization with systemic governanceEnterprise support; Use case-driven pluggability choices; Shared ledger technology; Consensus; Crypto algorithms and encryption technology; Use case-driven pluggable choices; Enterprise integration and designing for extensibility; Other considerations; Consensus, ACID property, and CAP; CAP; ACID; Attestation -- SSCs are signed and encrypted; Use of HSMs; Summary; Chapter 2: Exploring Hyperledger Fabric; Building on the foundations of open computing; Fundamentals of the Hyperledger project; The Linux Foundation ; Hyperledger.…”
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The attacker's advantage : turning uncertainty into breakthrough opportunities by Charan, Ram

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Data mining techniques : for marketing, sales, and customer relationship management by Linoff, Gordon, Berry, Michael J. A.

Table of Contents: “…-- Data mining applications in marketing and customer relationship management -- The data mining process -- Statistics 101: What you should know about data -- Descriptions and prediction: profiling and predictive modeling -- Data mining using classic statistical techniques -- Decision trees -- Artificail neural networks -- Nearest neighbor approaches: Memory-based reasoning and collaborative filtering -- Knowing when to worry: Using survival analysis to understand customers -- Genetic algorithms and swarm intelligence -- Tell me something new: Pattern discovery and data mining -- Finding islands of similarity: Automatic cluster detection -- Alternative approaches to cluster detection -- Market basket analysis and association rules -- Link analysis -- Data warehousing, OLAP, analytic sandboxes, and data mining -- Building customer signatures -- Derived variables: Making the data mean more -- Too much of a good thing? …”
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