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118 results for “Software Modelling”
CAP22 Tomographic model: Data, Software, Plotting
<p>CAP22 (Boyce et al., 2023), is an absolute P-wavespeed tomographic model with focus on North American, specifically Canadian and Alaskan, mantle structure, provided with and without crustal correction.</p> <p>Please cite the following work when using this data set:</p> <p>Boyce, A., Liddell, M. V., Pugh, S., Brown, J., McMurchie, E., Parsons, A., Estève, C., Burdick, S., Darbyshire, F. A., Cottaar, S. Bastow, I. D., Schaeffer, A. J., Audet, P., Schutt, D. L., Aster, R. C. (2023). A new P-wave tomographic model (CAP22) for North America: Implications for the subduction and cratonic metasomatic modification history of western Canada and Alaska. <em>Journal of Geophysical Research: Solid Earth</em>, 128, e2022JB025745. <a href="https://doi.org/10.1029/2022JB025745">https://doi.org/10.1029/2022JB025745</a></p> <p>This repository accompanies the publication of the tomographic model on the IRIS-EMC that can be found here: https://ds.iris.edu/ds/products/emc-cap22/ or with the following doi: 10.17611/dp/emc.2023.cap22.1. Please find CAP22 and its related files for a detailed description of the distributed model.</p> <p>The CAP22_TOMO_SHARE.tar repository contains:</p> <ul> <li>Raw_data: Hand-picked and processed seismic data (.SAC) from western Canada and Alaskan seismic networks.</li> <li>Original_documentation: Documentation for original distribution of inversion code from MIT global seismology group.</li> <li>Tomography_CAP22: Implementation of MIT inversion algorithm used to produce CAP22 including formatted data.</li> <li>Plotting: Codes and necessary files to reproduce figures in main manuscript.</li> </ul> <p>The following authors contributed to this work:</p> <p>A. Boyce: University of Cambridge, Department of Earth Science, Bullard Laboratories, Madingley Road, Cambridge, UK.<br> M. V. Liddell: Centre de recherche Geotop, Université du Québec à Montréal, QC, Canada.<br> S. Pugh: University of Cambridge, Department of Earth Science, Bullard Laboratories, Madingley Road, Cambridge, UK.<br> J. Brown: University of Cambridge, Department of Earth Science, Bullard Laboratories, Madingley Road, Cambridge, UK.<br> E. McMurchie: University of Cambridge, Department of Earth Science, Bullard Laboratories, Madingley Road, Cambridge, UK.<br> A. Parsons: University of Cambridge, Department of Earth Science, Bullard Laboratories, Madingley Road, Cambridge, UK.<br> C. Estève: Department of Meteorology and Geophysics, University of Vienna, Vienna, Austria.<br> S. Burdick: Wayne State University, Geology Department, Detroit, MI, USA.<br> F. A. Darbyshire: Centre de recherche Geotop, Université du Québec à Montréal, QC, Canada.<br> S. Cottaar: University of Cambridge, Department of Earth Science, Bullard Laboratories, Madingley Road, Cambridge, UK.<br> I. D. Bastow: Department of Earth Science and Engineering, Royal School of Mines, Prince Consort Road, Imperial College London, London, UK.<br> A. J. Schaeffer: Geological Survey of Canada Pacific Division, Sidney, BC, Canada.<br> P. Audet: University of Ottawa, Department of Earth and Environmental Sciences, Ottawa, ON, Canada.<br> D. L. Schutt: Colorado State University, Department of Geosciences and Warner College of Natural Resources, Fort Collins, CO, USA.<br> R. C. Aster: Colorado State University, Department of Geosciences and Warner College of Natural Resources, Fort Collins, CO, USA.</p> <p> </p> <p> </p>
Modeling software processes from different domains using SPEM and BPMN notations: An experience report of teaching software processes
<p>In a current application development scenario in different environments, technologies and contexts, such as IoT, Blockchain, Machine Learning and Cloud Computing, there is a need for particular solutions for domain-specific software development processes. The proper definition of software processes requires understanding the involved teams and organization’s particularities and specialized technical knowledge in Software Engineering. Although it is an essential part of Software Engineering, many university curricula do not dedicate as much effort to teach software processes, focusing more on the basic principles of Software Engineering, such as requirements, architecture and programming languages. Another important aspect of software processes is modeling. The modeling of a software process provides a basis for managing, automating and supporting the software process improvement. In this context, teaching software process modeling becomes challenging, mainly due to the great emphasis on theory and few practices. This work presents an experience report teaching the definition and modeling of software processes in different domains. We applied in the discipline of software processes a practice for defining and modeling processes in various application domains, such as: IoT, cloud, mobile, critical systems, self-adaptive systems, machine learning, blockchain and games. The processes were modeled in the Software & Systems Process Engineering Metamodel (SPEM) and Business Process Model and Notation (BPMN) notations based on references from the literature for each domain. We evaluated the process modeling practice with the SPEM and BPMN in 3 classes of the software processes discipline and compared the use of the two notations applied to the different domains. We concluded that the modeling tool and the maturity in the domain are essential for the excellent performance of the process.</p>
An approach using performance models for supporting energy analysis of software systems
<p>Replication package of the paper titled "An approach using performance models for supporting energy analysis of software systems". Usage instructions are contained in the README.md file.</p>
Latest model for the particle picking software "TomoTwin"
<p>Latest model for the particle picking software <a href="https://tomotwin-cryoet.readthedocs.io/">TomoTwin</a><br> </p> <p><strong>Changelog:</strong></p> <ul> <li>09.2023: Retrained only, but with improved performance on tomograms reconstructed by software other than 3dmod (warp/relion).</li> <li>05.2022: Initial model based on 120 proteins.</li> </ul> <p> </p>
Lituya Bay 1958 Tsunami – pre-event bathymetry reconstruction and 3D-numerical modelling utilizing the CFD software Flow-3D
<p>Simulation video, Model code, STL.File of the solid bodies</p>
Building DEVS Models from the Functional Design of Software Architecture Components to Estimate Quality
<p>Presentation of the paper titled "Building DEVS Models from the Functional Design of Software Architecture Components to Estimate Quality".</p>
Joint Autoregressive and Graph Models for Software and Developer Social Networks
<p>This zip contains three CSV files and one folder. This dataset contains information for the recent ten distributions.</p> <ul> <li><strong>developer_attributes.csv</strong>: There are seven columns in this file. "distro" (str) represents distribution name. "source" (str) denotes source package name. "person_id" (str) indicates developer identity. "closes" (int), "high" (int), "medium" (int), "low" (int) are the features.</li> <li><strong>source_bugs.csv</strong>: In this file, three columns are present. "distro" (str) represents the distribution name. "source" (str) represents the source package name. "bug_count" (int) denotes the number of bugs that source package has at a particular distribution.</li> <li><strong>source_sizes.csv</strong>: In this file, three columns are present. "distro" (str) represents the distribution name. "source" (str) represents source package name. "size" (int) denotes the size of the package.</li> <li><strong>Dependency folder:</strong> Within this folder, ten dependency lists are present. Each file contains two columns i.e "start" (str) and "target" (str). Both of them represent source packages. So, we read as the "start" source package depends on "target" source package. </li> </ul> <p>Here is the arxiv version of our paper: <a href="https://arxiv.org/abs/2101.08729">https://arxiv.org/abs/2101.08729</a>. </p> <p>Here is the portal link: <a href="https://sites.google.com/view/rima-hazra/swnet">https://sites.google.com/view/rima-hazra/swnet</a></p>
Towards a Quantitative Model to Deal with Uncertainty Management in Software Projects
<p>The evolution of thinking in project management has raised interest in areas not yet explored by researchers and practitioners of project management, including the management of uncertainties associated with risk management. The correct risk and uncertainty management in software projects can represent a competitive differential for the software development industry. Despite the increasing use of uncertainty management strategies, many projects still fail. Some recent studies show that the current techniques used to manage uncertainties organize the project's known information, but give little or no indication of the unknown information or uncertainties associated with the project. These techniques do not take into account the impact of existing dependency and interdependence relationships between the various sources of uncertainties in the project. This work will apply Action Research to develop a model with a focus on uncertainty quantification techniques. This work aims to present a model with a focus on uncertainty quantification techniques that take into account the relationships of dependencies and interdependence that exist between the sources of risks and uncertainties in software projects and as a result, contribute with the advance of state of the art in the practice of risk and uncertainty management in project software.</p>
Data from: Evaluating conservation and fisheries management strategies by linking spatial prioritisation software and ecosystem and fisheries modelling tools
1. Well-designed marine protected area (MPA) networks can deliver a range of ecological, economic and social benefits, and so a great deal of research has focused on developing spatial conservation prioritization tools to help identify important areas. 2. However, whilst these software tools are designed to identify MPA networks that both represent biodiversity and minimize impacts on stakeholders, they do not consider complex ecological processes. Thus, it is difficult to determine the impacts that proposed MPAs could have on marine ecosystem health, fisheries and fisheries sustainability. 3. Using the eastern English Channel as a case study, this paper explores an approach to address these issues by identifying a series of MPA networks using the Marxan and Marxan with Zones conservation planning software and linking them with a spatially explicit ecosystem model developed in Ecopath with Ecosim. We then use these to investigate potential trade-offs associated with adopting different MPA management strategies. 4. Limited-take MPAs, which restrict the use of some fishing gears, could have positive benefits for conservation and fisheries in the eastern English Channel, even though they generally receive far less attention in research on MPA network design. 5. Our findings, however, also clearly indicate that no-take MPAs should form an integral component of proposed MPA networks in the eastern English Channel, as they not only result in substantial increases in ecosystem biomass, fisheries catches and the biomass of commercially valuable target species, but are fundamental to maintaining the sustainability of the fisheries. 6. Synthesis and applications. Using the existing software tools Marxan with Zones and Ecopath with Ecosim in combination provides a powerful policy-screening approach. This could help inform marine spatial planning by identifying potential conflicts and by designing new regulations that better balance conservation objectives and stakeholder interests. In addition, it highlights that appropriate combinations of no-take and limited-take marine protected areas might be the most effective when making trade-offs between long-term ecological benefits and short-term political acceptability.
Dataset for Generative Model of Software Dependency Graphs
<p>Data set for the paper entitled "A Generative Model of Software Dependency Graphs to Better Understand Software Evolution".</p> <p>Available files are:</p> <ul> <li>Sources archives (102 MB),</li> <li>Extracted dependencies (3.5 MB) and</li> <li>Generated graphs (15 MB).</li> </ul>
Gastroplus software data and model
<p>Gastroplus software data and model screen print for the software data for both nasal and oral routes. The taken photo including all the data and information and graphs.</p>
Software file and numerical results of Modelling heat transfer for assessing the convection length in ventilated caves
<p>The Comsol file corresponding to the reference case as shown in Figures 4-6 as well as all the numerical results for the rest of the figures are available here.</p>
Data and software for article: "Lava delta formation: Mathematical modelling and laboratory experiments"
<p>Experimental and numerical data and scripts required to reproduce the results of Taylor-West, Balmforth, & Hogg 2024 "Lava delta formation: Mathematical modelling and laboratory experiments". Accepted to JGR: Earth Surfaces. doi:10.1029/2023JF007505</p>
Research Software focus area Maturity Model (RSMM) dataset
<p><span>The Research Software project focus area Maturity Model (RSMM) dataset provides a comprehensive description of 79 practices of RSMM. </span><span>This description includes </span><span>when the practices are implemented and is organized based</span><span> on the MoSCoW prioritization (Must have, Should </span><span>have, Could have, Won’t have). Additionally, it details </span><span>the resources required for execution, dependencies among </span><span>neighboring practices, and references.</span></p>
Extracting Enhanced Artifical Intelligence Model Metadata from Software Repositories
<p>Replication set for evaluations performed in EMSE submission "Extracting Enhanced Artifical Intelligence Model Metadata from Software Repositories" </p>
Replication package for "Blended Modeling in Commercial and Open-source Model-Driven Software Engineering Tools: A Systematic Study"
<p>Replication package for the paper <em>Blended Modeling in Commercial and Open-source Model-Driven Software Engineering Tools: A Systematic Study</em>.</p> <p>Protocol</p> <ul> <li><code>/01-protocol/protocol.pdf</code></li> </ul> <p>Data & analysis scripts</p> <p>This replication package is structured as follows:</p> <ul> <li><code>/02-search</code> - Detailed data on the <code>/academic</code> and <code>/grey literature</code> search.</li> <li><code>/03-tools</code> - Identified tools and inclusion/exclusion decisions.</li> <li><code>/04-classification_schema</code> - Classification framework and the corresponding data extraction form.</li> <li><code>/05-data</code> - Clean data in a processable form.</li> <li><code>/06-analysis</code> - Analysis scripts and results.</li> </ul>
Data & parsing software for CMB Topographic Model
<p>Datasets and associated code for reading the data (and generating tomographic models) for the CMB topography / lowermost mantle tomographic model of Muir et al. </p>
Data and software in support of article submitted to Journal Geophy. Res. Atmos., titled "Self lofting increases altitude of black carbon in a climate model""
<p>The collection provides data and software to support a journal article submission to the Journal of Geophysical Research Atmospheres. The contents will allow potential future investigators to explore the simulation data and reproduce the analyses in the submitted article.</p> <p>This dataset includes 7 tarred files that when expanded will contain a set of netcdf data files and a collection of python programs to read and analyze the data. The data provided in the netcdfs are model outputs from the UK Earth System Model (UKESM1) from a pair of simulations that explored the impact of black carbon aerosol on atmospheric motion.</p> <p> </p>
Replication Package for "Classifying Open-Source Pre-Trained Models and Datasets for Software Engineering"
<p>The replication package for the short paper titled 'Classifying Open-Source Pre-Trained Models and Datasets for Software Engineering' is provided. It includes a README file and accompanying scripts with comprehensive instructions to facilitate the replication of the analysis presented in the paper.</p>
Topic modeling in software engineering research
<p>Data extracted from 111 papers applying topic modeling techniques in software engineering studies.</p>
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.