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1,782 results for “algorithms”
Bug Report Analytics for Software Reliability Assessment using Hybrid Swarm-Evolutionary Algorithm
<p><span>There are in total 6 files.</span></p> <p><span><span>1.<span> </span></span></span><span>Out of these files three documents are related to datasets. Two are related to unrefined Eclipse and JDT files and third is refined data of Eclipse and JDT Project Failure Datasets which has been used for experimentation purpose.</span></p> <p><span><span>2.<span> </span></span></span><span>This package also includes code for all the models version wise for all versions of Eclipse and JDT projects.</span></p> <p><span><span>3.<span> </span></span></span><span>Sample Code has also been given for version 4.3 and 4.10. </span></p> <p><span>Steps to run </span></p> <p><span><span>a)<span> </span></span></span><span>In this code, Main ABCDE file needs to be run and different datasets could be executed on this file. This is for one type of datasets that is time domain dataset only. </span></p> <p><span><span>b)<span> </span></span></span><span>If anyone is interested in getting separate results for cumulative sum and failure intensity, separate file has been given. </span></p> <p><span><span>c)<span> </span></span></span><span>Code for ABCDE algorithm that is Swarm Evolutionary algorithm used in the paper has also been given in these files.</span></p>
Data: A 3/2-approximation algorithm for the Student-Project Allocation problem
<p>This data corresponds to the data and experiments described in Section 5 of<br> the following paper submitted to SEA conference 2018:</p> <p>A 3/2-approximation algorithm for the Student-Project Allocation problem<br> Authors: Frances Cooper and David Manlove</p> <p>The data is located at: https://doi.org/10.5281/zenodo.1186823<br> The software is located at: https://doi.org/10.5281/zenodo.1183221</p> <p>See the README for more information.</p>
Algorithm to Convert Raw Weight Data to Fuel Use
<p>Algorithm to Convert Raw Weight Data to Fuel Use</p>
FIGURE 6. Maximum likelihood tree constructed using COI sequences with GenBank accession numbers. Bootstrap support values were calculated with a rapid bootstrapping algorithm for 1000 in Branchinotogluma bipapillata n. sp., a new branchiate scale worm (Annelida: Polynoidae) from two hydrothermal fields on the Southwest Indian Ridge
FIGURE 6. Maximum likelihood tree constructed using COI sequences with GenBank accession numbers. Bootstrap support values were calculated with a rapid bootstrapping algorithm for 1000 replicates in Raxml, and only those higher than 50 were shown.
Structural files of algorithmically generated molybdenum oxide clusters
<p>Structural files of algorithmically generated molybdenum oxide clusters. The new clusters were generated to fit experimental pair distribution functions of molybdenum oxide surface layers supported on Al<sub>2</sub>O<sub>3 </sub>and zeolites. Results are published in article XXX</p>
A semi-implicit relaxed Douglas-Rachford algorithm (sDR) for Ptychography
<p>Alternating projection based methods, such as ePIE and rPIE, have been used widely in ptychography. However, they only work well if there are adequate measurements (diffraction patterns); in the case of sparse data (i.e. fewer measurements) alternating projection underperforms and might not even converge. In this paper, we propose semi-implicit relaxed Douglas-Rachford (sDR), an accelerated iterative method, to solve the classical ptychography problem. Using both simulated and experimental data, we show that sDR improves the convergence speed and the reconstruction quality relative to extended ptychographic iterative engine (ePIE) and regularized ptychographic iterative engine (rPIE). Furthermore, in certain cases when sparsity is high, sDR converges while ePIE and rPIE fail or encounter slow convergence. To facilitate others to use the algorithm, we post the Matlab source code of sDR on a public website (www.physics.ucla.edu/research/imaging/sDR) and data con zenodo. We anticipate that this algorithm can be generally applied to the ptychographic reconstruction of a wide range of samples in the physical and biological sciences.</p>
Source codes for preprint Newmark algorithm for dynamic analysis with generalized Maxwell model
<p>Snapshot of a GitLab repository, containing Python source codes of results presented in the preprint by the same authors.</p>
Dataset for: Sky pixel detection in outdoor imagery using an adaptive algorithm and machine learning.
<p>The data presented in this article is related to the research article entitled ``Sky pixel detection in outdoor imagery using an adaptive algorithm and machine learning." \citep{Nice2019UC}.</p> <p>The dataset consists of a trained Inception V3 neural network model as well as the configuration files to train the neural network and run the inferences. The dataset also contains two sets of outdoor imagery (from Skyfinder and Google Street View) used to train the neural network and validate the sky pixel detection system in the linked article. The original images are included as well as rescaled imagery used to train the neural network, and sky masks used for validation.</p>
The 4D mesh generated by the 'satori' algorithm, and Voronoi regions of its nodes
<p>The data contained in the archive is the 4D mesh containing 5^4 translation units, that are 2^4 points of tesseract shifted with 'satori' algorithm (total 10 000 nodes), and Voronoi diagram calculated using the qhull package for these points.</p> <p>It is used to demonstrate the shape uniqueness of the 4096 diagram's inner regions. The tessellation of inner regions is a candidate to be a solution of Kelvin problem in 4D version, offering possible minimal interface hyper-area to hyper-volume ratio. The structure posesses PT-symmetry so it might have applications in particle physics. For instance, its 3D layers can be used as CPT-compatible cellular automata for 3D simulations in chiral space.</p> <p>Presumably, the structure can be self-assembling in conditions near to critical point of second order phase transitions.<br> </p>
Algorithmic identification of the precursory scale increase phenomenon in earthquake catalogues
<p>This repository includes the code and data used in the paper " Algorithmic identification of the precursory scale increase (PSI) phenomenon in earthquake catalogues". There are four folders, two for the data, and one each for the "Circular algorithm" and for the "Rectangular algorithm", respectively. Each folder has a Readme.txt file explaining its content.</p>
Data for the article "A fully-coupled algorithm with implicit surface tension treatment for interfacial flows with large density ratios"
<p>This folder contains representative data generated for each case demonstrated in the paper entitled "A fully-coupled algorithm with implicit surface tension treatment for interfacial flows with large density ratios".<br>Authors: Romain Janodet, Berend van Wachem, and Fabian Denner.</p> <p>A readme file is included to help the navigation within the folder.</p> <p>This research was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), grant numbers 452036112, 452916560, and 458610925.</p>
Data and script for "Characterizing Wet Season Precipitation in the Central Amazon Using a Mesoscale Convective System Tracking Algorithm"
<p>This is a placeholder for Data and script for "<strong>Characterizing Wet Season Precipitation in the Central Amazon Using a Mesoscale Convective System Tracking Algorithm</strong>" submitted to JGR-atmosphere.</p>
An Improved QEM Algorithm Based on Salient Feature Sampling Points
Open the record for dataset details and reuse information.
Supplementary data for the article: "Towards an widely applicable earthquake detection algorithm for fibreoptic and hybrid fibreoptic-seismometer networks"
<p>Repository of supporting data associated with the article submitted to GJI, titled: "Towards an widely applicable earthquake detection algorithm for fibreoptic and hybrid fibreoptic-seismometer networks".</p> <p> </p> <p>Contents include:</p> <ol> <li>A full working example of modified QuakeMigrate version and seismic time-series data used to detect an earthquake.</li> <li>Earthquake catalogues for the three datasets described in the publication.</li> </ol>
Research data supporting article on "Point containment algorithms for constructive solid geometry with unbounded primitives"
<p>This file contains an archive of all research data that supports the article on "Point containment algorithms for constructive solid geometry with unbounded primitives".</p>
Identification of Kidney Cell Types in scRNA-seq and snRNA-seq Data Using Machine Learning Algorithms
<p>Metadata files for our final analysis as part of the "<span><span>Identification of Kidney Cell Types in scRNA-seq and snRNA-seq Data Using Machine Learning Algorithms" study.</span></span></p>
Multi-omics with dynamic network biomarker algorithm prefigures organ-specific metastasis of lung adenocarcinoma
<p><span>Efficacious strategies for early detection of lung cancer metastasis are of significance for improving the survival of lung cancer patients. Utilizing two clinical cohorts of four major types of lung cancer distant metastases, with single-cell RNA sequencing (scRNA-seq) of primary lesions and liquid chromatography mass spectrometry data of sera, we identified the marker genes and serum secretome foreshadowing the lung cancer site-specific metastasis through dynamic network biomarker (DNB)</span> <span>algorithm. Also, we located the intermediate status of cancer cells, along with its gene signatures, in each metastatic state trajectory that cancer cells at this stage still had no specific organotropism. Furthermore, an integrated neural network model based on the filtered scRNA-seq data was successfully constructed and validated to predict the metastatic state trajectory of cancer cells. Overall, our study provided a new insight to locate the pre-metastasis status of lung cancer and primarily examined its clinical application value, contributing to the early detection of lung cancer metastasis in a more feasible and efficacious way.</span></p>
The SNP dataset tested for constructing HITSNP algorithm
<p>The SNP dataset tested for constructing HITSNP algorithm</p>
Algorithm Ownership
<p>Ferramentas com a proposta de calcular a propriedade de código de sistemas, a partir de dados minerados da plataforma GitHub, e de analisar os resultados gerados.</p>
Deep-sea observatories images labeled by citizen for object detection algorithms
<div>All information is available from the original publication page: <a href="https://doi.org/10.17882/101899">https://doi.org/10.17882/101899</a>.</div>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.