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3 results for “numerical feature”
NEMO: A Tool to Support Feature Models with Numerical Features and Arithmetic Constraints
<p><strong>Your can watch this video in my Youtube channel:</strong></p> <p><a href="https://youtu.be/V-ONW8PftwM">https://youtu.be/V-ONW8PftwM</a></p> <p><strong>This is a Live Conference Presentation, please access and cite the published version of the respective publication:</strong></p> <p><a href="https://youtu.be/V-ONW8PftwM">https://doi.org/10.1007/978-3-031-08129-3_4</a></p> <p>Real-world <em>Software Product Lines</em> (SPLs) need <em>Numerical Feature Models</em> (NFMs) whose features not only have boolean values satisfying boolean constraints, but also have numeric attributes satisfying arithmetic constraints. A key operation on NFMs finds near-optimal performing products, which requires counting the number of SPL products. Typical constraint satisfaction solvers perform poorly on counting.</p> <p>Nemo (<strong>N</strong>umbers, f<strong>e</strong>atures, <strong>mo</strong>dels) supports NFMs by <em>bit-blasting</em>, the technique that encodes arithmetic as boolean clauses. Nemo translates NFMs to propositional formulas whose products can be counted efficiently by #SAT solvers, enabling near-optimal products to be found. We evaluate Nemo with a diverse set of real-world NFMs, complex arithmetic constraints, and counting experiments in this paper.</p>
Defining Categorical Reasoning of Numerical Feature Models with Feature-Wise and Variant-Wise Quality Attributes
<p><strong>To watch it in Youtube:</strong></p> <p><a href="https://youtu.be/Uq2qtb4_K2U">https://youtu.be/Uq2qtb4_K2U</a></p> <p><strong>This is a pre-print, please access and cite the published version:</strong></p> <p><a href="https://doi.org/10.1145/3503229.3547057">https://doi.org/10.1145/3503229.3547057</a></p> <p>Automatic analysis of variability is an important stage of <em>Software Product Line</em> (SPL) engineering. Incorporating quality information into this stage poses a significant challenge. However, quality-aware automated analysis tools are rare, mainly because in existing solutions variability and quality information are not unified under the same model.</p> <p>In this paper, we make use of the <em>Quality Variability Model</em> (QVM), based on <em>Category Theory</em> (CT), to redefine reasoning operations. We start defining and composing the six most common operations in SPL, but now as quality-based queries, which tend to be unavailable in other approaches. Consequently, QVM supports interactions between variant-wise and feature-wise quality attributes. As a proof of concept, we present, implement and execute the operations as lambda reasoning for CQL IDE -- the state-of-the-art CT tool.</p>
Spatio-temporal Features of Intra-seasonal Oceanic Variability in the Philippine Sea from Mooring Observations and Numerical Simulations
<p>This dataset contains the NPOCE (http://npoce.org.cn) data used in the following submission for Journal of Geophysical Research: Oceans:</p> <p>Hu, S., J. Sprintall, C. Guan, B. Sun, F. Wang, G. Yang, F. Jia, J. Wang, D. Hu, and F. Chai (2018), Spatio-temporal Features of Intra-seasonal Oceanic Variability in the Philippine Sea from Mooring Observations and Numerical Simulations, Journal of Geophysical Research: Oceans.</p> <p>Variables in this dataset are eddy kinetic energy (EKE) observed by the NPOCE moorings, longitudes, latitudes, depths and dates.</p> <p> </p> <p> </p>
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Allen Brain Atlas
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.