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QuantPlorer: Exploration of Quantities in Text
Quantities play an important role in documents of various domains such as finance, business, and medicine. Despite the role of quantities, only a...
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B-Trees
This chapter covers one of the more important data structures of the last thirty years. B-Trees are primarily used by relational databases to...
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From Identities to Quantities: Introducing Items and Decoupling Points to Object-Centric Process Mining
Logistics processes ensure that the right product is at the right location at the right time in the right quantity. Their efficiency is crucial to...
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A Unified Technique for Prediction and Optimization of Future Outcomes under Parametric Uncertainty via Pivotal Quantities and Ancillary Statistics
AbstractStatistical prediction and optimization of future outcomes on the basis of the past and present knowledge represent a fundamental problem of...
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Dynamic Ball B-Spline Curves
A ball B-spline curve (BBSC) is a skeleton-based 3D geometric representation, which can represent 3D tubular objects with varying radius, such as...
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Iterated Conditionals, Trivalent Logics, and Conditional Random Quantities
We consider some notions of iterated conditionals by checking the validity of some desirable basic logical and probabilistic properties, which are...
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Numerical solutions of the EW and MEW equations using a fourth-order improvised B-spline collocation method
A fourth-order improvised cubic B-spline collocation method (ICSCM) is proposed to numerically solve the equal width (EW) equation and the modified...
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Unsuitability of NOTEARS for Causal Graph Discovery when Dealing with Dimensional Quantities
Causal discovery methods aim to identify a DAG structure that represents causal relationships from observational data. In this article, we stress...
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A novel deformable B-spline curve model based on elasticity
The physically based deformable curve models are widely used to simulate thin one-dimensional objects in computer graphics, interactive simulation,...
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Maintaining Trust in Reduction: Preserving the Accuracy of Quantities of Interest for Lossy Compression
As the growth of data sizes continues to outpace computational resources, there is a pressing need for data reduction techniques that can...
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A variational approach for feature-aware B-spline curve design on surface meshes
Robust curve design on surface meshes with flexible controls is useful in a wide range of applications but remains challenging. Most existing methods...
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A Novel Unified Computational Approach to Constructing Shortest-Length or Equal Tails Confidence Intervals in Terms of Pivotal Quantities and Quantile Functions
AbstractA confidence interval is a range of values that gives the user a sense of how precisely a statistic estimates a parameter. In the present...
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LR B-Splines for Representation of Terrain and Seabed: Data Fusion, Outliers, and Voids
Performing surface approximation of geospatial point clouds with locally refined (LR) B-splines comes with several challenges: (i) Point clouds have...
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Data Architecture & Management: Phase B
This phase of the Salesforce Platform Governance Method tackles the data architecture and management aspects of your project’s Salesforce solution.
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Adaptive Regularization of B-Spline Models for Scientific Data
B-spline models are a powerful way to represent scientific data sets with a functional approximation. However, these models can suffer from spurious...
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A Statistical Criterion to Judge the Goodness of Fit of LR B-Splines Surface Approximation
The surface approximation obtained with adaptive strategies using locally refined (LR) B-splines depends on the degrees of freedom of the spline...
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A New Technique of Invariant Statistical Embedding and Averaging Via Pivotal Quantities for Intelligent Constructing Efficient Statistical Decisions under Parametric Uncertainty
AbstractIn the present paper, a new technique of invariant embedding of sample statistics in a decision criterion (performance index) and averaging...
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Searching B-Smooth Numbers Using Quantum Annealing: Applications to Factorization and Discrete Logarithm Problem
Integer factorization and discrete logarithm problem, two problems of classical public-key cryptography, are vulnerable to quantum attacks,...
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Modelling Concerns
This chapter explains how concerns are modelled in Affinity. There is a unique representation of numerical quantities in the form of distributions,...
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Causal Entropy and Information Gain for Measuring Causal Control
Artificial intelligence models and methods commonly lack causal interpretability. Despite the advancements in interpretable machine learning (IML)...