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Calculus - Concepts and Contexts, Volume 1 - Featuring an Introduction to Vectors
First published in 2009...
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Chiral approach to phi radiative decays
The radiative decays of the phi meson are known to be a good source of information about the a0(980) and f0(980) scalar mesons. We discuss these decays starting from a non-linear model Lagrangian whic...
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Understanding Machine Learning
From Theory to Algorithms...
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Error-Correction Coding and Decoding
Bounds, Codes, Decoders, Analysis and Applications...
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Efficient Estimation of the number of neighbours in Probabilistic K Nearest Neighbour Classification
Probabilistic k-nearest neighbour (PKNN) classification has been introduced to improve the performance of original k-nearest neighbour (KNN) classification algorithm by explicitly modelling uncertaint...
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Biodiversity and Health in the Face of Climate Change
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Finite Difference Computing with PDEs
A Modern Software Approach...
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Efficient Learning Machines
Theories, Concepts, and Applications for Engineers and System Designers...
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Generating and structuring terrain features on parallel vector architectures
First published in 1988...
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CKE Volume 2 Issue 2 Pages 2 8
Previous studies show that the incorporation of spatial features in the classification process of hyperspectral images (HSI) improves classification accuracy. Although different spatial-spectral metho...
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Using data mining techniques to extract students' attitudes toward e-learning
The rapid expansion of e-learning platforms, where students can share their opinions and express their thoughts, has become a rich source of data for opinion mining and sentiment analysis. This study ...
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Physical (A)Causality
Determinism, Randomness and Uncaused Events...
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Clinical Text Mining
Secondary Use of Electronic Patient Records...
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Regulating Content on Social Media
Copyright, Terms of Service and Technological Features...
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Intelligent Human Computer Interaction
9th International Conference, IHCI 2017, Evry, France, December 11-13, 2017, Proceedings...
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Ionospheric Multi-Spacecraft Analysis Tools
Approaches for Deriving Ionospheric Parameters...
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Fractional Graph Theory
A Rational Approach to the Theory of Graphs...
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On the Scalar Manifold of Exceptional Supergravity
We construct two parametrizations of the non compact exceptional Lie group G=E7(-25), based on a fibration which has the maximal compact subgroup K=(E6 x U(1))/Z_3 as a fiber. It is well known that G ...
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Bayesian Methods in the Search for MH370
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An Efficient Approach for Differentiating Alzheimer's Disease from Normal Elderly Based on Multicent
This article is from PLoS ONE , volume 9 . Abstract Machine learning techniques, along with imaging markers extracted from structural magnetic resonance images, have been shown to increase the accurac...
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Ambisonics
A Practical 3D Audio Theory for Recording, Studio Production, Sound Reinforcement, and Virtual Reality...
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Signal Computing
Digital Signals in the Software Domain...
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Automated feature selection with a distinction sensitive learning vector quantizer
First published in 1994...
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Annotated Algorithms in Python
With applications in Physics, Biology, and Finance...
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Pro TBB
C++ Parallel Programming with Threading Building Blocks...
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Variant Construction from Theoretical Foundation to Applications
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DTIC ADA458557: Application of Statistical Learning Theory to Plankton Image Analysis
A fundamental problem in limnology and oceanography is the inability to quickly identify and map distributions of plankton. This thesis addresses the problem by applying statistical machine learning t...
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50 Mandalas for Stress-Relief Adult Coloring Book
First published in 2020...
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DTIC ADA387275: Digital Mapping, Charting, and Geodesy Analysis Program: Technical Review DLA Electr
One of the functions of the Defense Logistics Agency (DLA) is to provide a supply channel for maps and charts to the DoD users. Currently the user is provided with a set of printed map index sheets th...
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Digital Video Concepts, Methods, and Metrics
Quality, Compression, Performance, and Power Trade-off Analysis...
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Heart disease prediction optimization using metaheuristic algorithms
This study explores metaheuristics hyperparameter tuning effectiveness in machine learning models for heart disease prediction. The optimized models are k-nearest neighbors (KNN) and support vector ma...
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Optimizing software in C++
An optimization guide for Windows, Linux and Mac platforms...
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Problems in Classical Electromagnetism
157 Exercises with Solutions...
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Detection of Cervical Cancer using ML Algorithms
Cervical cancer is one of the leading causes of cancer-related deaths among women worldwide, particularly in low- and middle-income regions where access to regular screening and early diagnostic servi...
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Russia's Turn to the East
Domestic Policymaking and Regional Cooperation...
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Geometry of Killing spinors in neutral signature
We classify the supersymmetric solutions of minimal $N=2$ gauged supergravity in four dimensions with neutral signature. They are distinguished according to the sign of the cosmological constant and w...
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Algorithmic Graph Theory and Sage
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Generalisations of the Laplace-Runge-Lenz vector
The characteristic feature of the Kepler Problem is the existence of the so-called Laplace--Runge--Lenz vector which enables a very simple discussion of the properties of the orbit for the problem. It...
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First published in 1991...
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Spatial Thinking in Planning Practice
An Introduction to GIS...
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Data Parallel C++
Mastering DPC++ for Programming of Heterogeneous Systems using C++ and SYCL...
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2
Microgrids are quickly becoming a great success for the future of electricity. The notion of the microgrid combines several microsources without interfering with the functioning of the larger utility ...
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Identifying and Categorizing Anomalies in Retinal Imaging Data
The identification and quantification of markers in medical images is critical for diagnosis, prognosis and management of patients in clinical practice. Supervised- or weakly supervised training enabl...
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Linear Selection Indices in Modern Plant Breeding
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Simultaneous Feature Learning and Hash Coding with Deep Neural Networks
Similarity-preserving hashing is a widely-used method for nearest neighbour search in large-scale image retrieval tasks. For most existing hashing methods, an image is first encoded as a vector of han...
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Statistics with Julia
Fundamentals for Data Science, Machine Learning and Artificial Intelligence...
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Fundamentals of Biomechanics
Equilibrium, Motion, and Deformation...
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Sensitivity Analysis: Matrix Methods in Demography and Ecology
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Introduction to Data Science
Data Analysis and Prediction Algorithms with R...
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Enhanced Living Environments
Algorithms, Architectures, Platforms, and Systems...
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GPU-FV: Realtime Fisher Vector and Its Applications in Video Monitoring
Fisher vector has been widely used in many multimedia retrieval and visual recognition applications with good performance. However, the computation complexity prevents its usage in real-time video mon...
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Foundations of Machine Learning
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Foundations of Quantum Theory
From Classical Concepts to Operator Algebras...
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Intel Xeon Phi Coprocessor Architecture and Tools
The Guide for Application Developers...
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Solving PDEs in Python
The FEniCS Tutorial I...
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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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Programming Computer Vision with Python
Tools and algorithms for analyzing images...
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Interface Oral Health Science 2016
Innovative Research on Biosis–Abiosis Intelligent Interface...
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Hybrid multi-layer Deep CNN/Aggregator feature for image classification
Deep Convolutional Neural Networks (DCNN) have established a remarkable performance benchmark in the field of image classification, displacing classical approaches based on hand-tailored aggregations ...
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Representation Learning for Natural Language Processing
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Absence of nematic ordering transition in a diamond lattice: Application to $FeSc_2S_4$
Recent neutron scattering observations by Plumb et al. [1] reveal that the ground state of $FeSc_2S_4$ is magnetic with two distinct Fe environments, instead of a quantum spin liquid as had been previ...
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LCNN: Low-level Feature Embedded CNN for Salient Object Detection
In this paper, we propose a novel deep neural network framework embedded with low-level features (LCNN) for salient object detection in complex images. We utilise the advantage of convolutional neural...
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Analysis for Computer Scientists
Foundations, Methods, and Algorithms...
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Programming for Computations - Python
A Gentle Introduction to Numerical Simulations with Python 3.6...
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Optimizing HPC Applications with Intel Cluster Tools
Hunting Petaflops...
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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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Seeing through bag-of-visual-word glasses: towards understanding quantization effects in feature ext
Vector-quantized local features frequently used in bag-of-visual-words approaches are the backbone of popular visual recognition systems due to both their simplicity and their performance. Despite the...
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