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Developing Graphics Frameworks with Python and OpenGL
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Byte Magazine Volume 06 Number 05 - Software Piracy
A rescan for this item is available here . Features p.36 Extended Color BASIC for the TRS-80 Color Computer [author Stan Miastkowski] Fast, easy. and inexpensive graphics are finally available for per...
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Russia's Turn to the East
Domestic Policymaking and Regional Cooperation...
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Ambisonics
A Practical 3D Audio Theory for Recording, Studio Production, Sound Reinforcement, and Virtual Reality...
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Understanding Machine Learning
From Theory to Algorithms...
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Clinical Text Mining
Secondary Use of Electronic Patient Records...
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Interface Oral Health Science 2016
Innovative Research on Biosis–Abiosis Intelligent Interface...
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Solving PDEs in Python
The FEniCS Tutorial I...
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Foundations of Machine Learning
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Finite element solution of nonlinear eddy current problems with periodic excitation and its industri
This article is from Applied Numerical Mathematics , volume 79 . Abstract An efficient finite element method to take account of the nonlinearity of the magnetic materials when analyzing three-dimensio...
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Error-Correction Coding and Decoding
Bounds, Codes, Decoders, Analysis and Applications...
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Ionospheric Multi-Spacecraft Analysis Tools
Approaches for Deriving Ionospheric Parameters...
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Spectral and High Order Methods for Partial Differential Equations ICOSAHOM 2018
Selected Papers from the ICOSAHOM Conference, London, UK, July 9-13, 2018...
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Annotated Algorithms in Python
With applications in Physics, Biology, and Finance...
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Health of People, Health of Planet and Our Responsibility
Climate Change, Air Pollution and Health...
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Ensemble-driven support vector clustering: From ensemble learning to automatic parameter estimation
Support vector clustering (SVC) is a versatile clustering technique that is able to identify clusters of arbitrary shapes by exploiting the kernel trick. However, one hurdle that restricts the applica...
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Fractional Graph Theory
A Rational Approach to the Theory of Graphs...
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Data Parallel C++
Mastering DPC++ for Programming of Heterogeneous Systems using C++ and SYCL...
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Intelligent Human Computer Interaction
9th International Conference, IHCI 2017, Evry, France, December 11-13, 2017, Proceedings...
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Introduction to Data Science
Data Analysis and Prediction Algorithms with R...
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Problems in Classical Electromagnetism
157 Exercises with Solutions...
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Pro TBB
C++ Parallel Programming with Threading Building Blocks...
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Notes on the Paranormal
here I supply information related to the paranormal....
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Spatial Thinking in Planning Practice
An Introduction to GIS...
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Navigating predictive landscapes of cloud burst prediction approaches: insights from comparative res
Cloud burst forecasting remains an evolving field that grapples with the complexities of atmospheric phenomena and their impact on local environments. Cloud bursts in hilly regions demand robust predi...
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Software for Exascale Computing - SPPEXA 2016-2019
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Fundamentals of Biomechanics
Equilibrium, Motion, and Deformation...
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Finite Difference Computing with PDEs
A Modern Software Approach...
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Intelligent mobile detection of cracks in concrete utilising an unmanned aerial vehicle
Cracks in constructions may result in negative consequences in terms of expenditure and safety. This in turn highlights the importance of finding ways to detect these cracks easily and effectively. He...
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Biodiversity and Health in the Face of Climate Change
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Enhanced Living Environments
Algorithms, Architectures, Platforms, and Systems...
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Optimizing software in C++
An optimization guide for Windows, Linux and Mac platforms...
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Optimizing HPC Applications with Intel Cluster Tools
Hunting Petaflops...
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Analysis for Computer Scientists
Foundations, Methods, and Algorithms...
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International Symposium on Mathematics, Quantum Theory, and Cryptography
Proceedings of MQC 2019...
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Algorithmic Graph Theory and Sage
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Byte Magazine Volume 06 Number 05 - Software Piracy (RESCAN)
Features p.36 Extended Color BASIC for the TRS-80 Color Computer [author Stan Miastkowski] Fast, easy. and inexpensive graphics are finally available for personal computers with this new system from R...
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The Structurally Smoothed Graphlet Kernel
A commonly used paradigm for representing graphs is to use a vector that contains normalized frequencies of occurrence of certain motifs or sub-graphs. This vector representation can be used in a vari...
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Efficient Learning Machines
Theories, Concepts, and Applications for Engineers and System Designers...
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Physical (A)Causality
Determinism, Randomness and Uncaused Events...
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Bayesian Methods in the Search for MH370
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Statistics with Julia
Fundamentals for Data Science, Machine Learning and Artificial Intelligence...
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Language Technologies for the Challenges of the Digital Age
27th International Conference, GSCL 2017, Berlin, Germany, September 13-14, 2017, Proceedings...
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Linear Selection Indices in Modern Plant Breeding
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Foundations of Quantum Theory
From Classical Concepts to Operator Algebras...
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Digital Video Concepts, Methods, and Metrics
Quality, Compression, Performance, and Power Trade-off Analysis...
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Programming Computer Vision with Python
Tools and algorithms for analyzing images...
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Variant Construction from Theoretical Foundation to Applications
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Signal Computing
Digital Signals in the Software Domain...
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Intel Xeon Phi Coprocessor Architecture and Tools
The Guide for Application Developers...
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Anisotropy Across Fields and Scales
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Representation Learning for Natural Language Processing
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Dot-Product Join: An Array-Relation Join Operator for Big Model Analytics
Big Model analytics tackles the training of massive models that go beyond the available memory of a single computing device, e.g., CPU or GPU. It generalizes Big Data analytics which is targeted at ho...
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Programming for Computations - Python
A Gentle Introduction to Numerical Simulations with Python 3.6...
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Nonparametric estimation of extremal dependence
There is an increasing interest to understand the dependence structure of a random vector not only in the center of its distribution but also in the tails. Extreme-value theory tackles the problem of ...
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Sensitivity Analysis: Matrix Methods in Demography and Ecology
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Semi-Orthogonal Multilinear PCA with Relaxed Start
Principal component analysis (PCA) is an unsupervised method for learning low-dimensional features with orthogonal projections. Multilinear PCA methods extend PCA to deal with multidimensional data (t...
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