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80 results for “evaluation framework”
Framework and results of "Performance evaluation in the Inter-institutional collaboration context of hybrid smart cities"
<pre>Comparative study of the Lugano and Turin framework and policy and agenda elements.</pre>
Data set supplementing "A Use-Case Specific Framework for Designing Representative Vignettes (RepVig) and Evaluating Triage Accuracy of Laypeople and Symptom-Assessment Applications"
<p>This is the de-identified data set used to conduct the analyses of our study "A Use-Case Specific Framework for Designing Representative Vignettes (RepVig) and Evaluating Triage Accuracy of Laypeople and Symptom-Assessment Applications" (<a href="https://doi.org/10.1101/2024.04.02.24305193">https://doi.org/10.1101/2024.04.02.24305193</a>). The data comprises the answers to cases given by laypeople, symptom-assessment applications, and large language models and the corresponding solutions for each case. The cases were developed in the study with a focus on external validity.</p> <p>The dataset contains three datafiles: collected data for laypeople, for symptom-assessment applications, and for large language models. </p>
FIGURE 1 in Why Biogeographical Hypotheses Need A Well Supported Phylogenetic Framework: A Conceptual Evaluation
FIGURE 1: Relationship between species and species names in classifications. H‑K correspond to existing biological species (I, J, and K to subspecies in C); M‑P correspond to species names in biological classifications. A. Nominal species M corresponds to a monophyletic group of species. B. Nominal species M corresponds to a paraphyletic group of species. C. Nominal species N corresponds to a paraphyletic group of subspecies. D. All species names correspond to real species.
FIGURE 3 in Why Biogeographical Hypotheses Need A Well Supported Phylogenetic Framework: A Conceptual Evaluation
FIGURE 3: Areas A and B have the same number of species (10 species each). A. Distribution of species 16‑25 in area A. B. Distribution of species 2‑4, 8‑10 and 12‑15 in area B. C. Phylogenetic relationships including the taxa distributed in areas A and B showing that area B has a larger number of distantly related monophyletic groups than A.
FIGURE 2 in Why Biogeographical Hypotheses Need A Well Supported Phylogenetic Framework: A Conceptual Evaluation
FIGURE 2: The concept of the cactophilous "Drosophila serido" before and after the proper understanding of the phylogenetic relationships "below the species level". A. Distribution of D. serido and of its "sister species", D. borborema. B. Distribution patterns after the discovery of the species previously included as groups of D. serido and their relationships with D. borborema. C. Phylogenetic relationships in the group.
Dataset of the Article Evaluating a Framework of Conceptual Modelling Research
<p>Results and replication package of the article: <span>Evaluating a Framework of Conceptual Modelling Research</span></p>
Material Suplementar - Identifying Requirements for a Multimodal User Experience Evaluation Framework for Interactive Web Systems
<p>Esta planilha contém o detalhamento do processo de codificação realizado para a identificação dos requisitos apresentado no artigo "<em>Identifying Requirements for a Multimodal User Experience Evaluation Framework for Interactive Web Systems</em>". Este artigo está submetido no XXIX Simpósio Brasileiro de Sistemas Multimídia e Web (WebMedia).</p> <p>A primeira aba da planilha contém os trechos dos artigos que geraram os códigos e os respectivos requisitos. A segunda aba mostra o agrupamento dos códigos similares para definir o conjunto de requisitos.</p>
Benchmark files for thesis 'Extending the Framework JavaSMT with the SMT Solver Bitwuzla and Evaluation using CPAchecker'
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Digital Evaluation of Accuracy for Removable Partial Denture Frameworks
ClinicalTrials.gov study NCT06412159. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Evaluating the Clinical Cost-effectiveness of Two Primary Mental Health Service Frameworks in Yogyakarta, Indonesia
ClinicalTrials.gov study NCT02700490. IPD Sharing: YES. Countries: 1. Publications: 1.
AVANCE-Houston FRAMEWorks Program Evaluation
ClinicalTrials.gov study NCT05261802. IPD Sharing: NO. Countries: 1. Publications: 0.
Implementing Injury Prevention Training in Youth Handball (I-PROTECT) Using the RE-AIM Evaluation Framework
ClinicalTrials.gov study NCT05696119. IPD Sharing: NO. Countries: 1. Publications: 1.
Gerontechnology Evaluation Framework: Outcome Validation
ClinicalTrials.gov study NCT06146868. IPD Sharing: NO. Countries: 1. Publications: 1.
Data from: Evaluating population receptive field estimation frameworks in terms of robustness and reproducibility
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Toward a Metamodel Quality Evaluation Framework: Requirements, Model, Measures, and Process
<p>The quality of metamodel considerably affects the models and transformations that conform to it. Despite that, there is still little discussion about a comprehensive form to evaluate the quality of metamodels and its consequences in model-driven development processes. This paper proposes a metamodel quality evaluation framework called MQuaRE (Metamodel Quality Requirements and Evaluation). MQuaRE comprises metamodel quality requirements and measures, a quality model, and an evaluation process, with the evident influence of international standards for software product quality, such as ISO/IEC 25000 series. We present a simple use case of MQuaRE describing how requirements, measures, and the quality model should be used during the evaluation process of a metamodel for software patterns. Among other benefits, MQuaRE can help determine final metamodel quality, decide on the acceptance of a metamodel, and also assess the positive and negative aspects of a metamodel, contributing to its quality evolution.</p>
Proteo Dataset (2023) for article "Proteo: A Framework for the Generation and Evaluation of Malleable MPI Applications"
<p>This dataset is the one used by the publication "Proteo: A Framework for the Generation and Evaluation of Malleable MPI Applications". The data are the data processed after the experiments to obtain the graphs and perform the analysis of the two applications shown.</p><p>On the one hand, there are data from the conjugate gradient (CG) execution and on the other hand, data from the Proteo framework, configured to emulate the CG.</p><p>The set is divided into 4 sections, each representing the results obtained for each result section of the article:</p><ul><li><strong>5.3</strong>: Similarity results between CG and Proteo configured to emulate CG. These results were obtained from the previous paper "Configurable synthetic application for studying malleability in HPC" at the PDP2023 conference. It consists of 4 datasheets:<ul><li><i>Nasp CG-VS-Proteo.xlsx</i>: Datasheet showing the total execution, iteration and computation times of Nasp (System_1) with the CG and Proteo. Used to create Figures 7 and 8.</li><li><i>JupiterThor CG-VS-Proteo.xlsx: </i>Datasheet showing the total execution, iteration and computation times of Jupiter (System_2) and Thor (System_3) with the CG and Proteus. Used to create Figures 7 and 8.</li><li><i>Comparison Comms CG Only.xlsx</i>: Datasheet showing MPI_Allgatherv communication times for different sizes on Nasp, Jupiter and Thor systems (System_1, System_2 and System_3). Used to create Table 1.</li><li><i>Comms CV_VS_Proteo.xlsx</i>: Datasheet showing MPI_Allgatherv communication times between the CG and Proteo for different sizes in Nasp, Jupiter and Thor systems (System_1, System_2 and System_3). Used to create Table 2.</li></ul></li><li><strong>5.4.1</strong>: Evaluation of the reconfiguration techniques in isolation of Proteo for synchronous methods. Used to create Figure 9. It is divided into three files:<ul><li><i>dataG.pkl</i>: Contains data on the complete runtimes in Proteo. The description can be found in the file <i>Proteo_dataG_description.txt</i></li><li><i>dataM.pkl</i>: Contains data on reconfiguration times in Proteo. The description can be found in the file <i>Proteo_dataM_description.txt</i></li><li><i>dataL.pkl</i>: Contains data on iteration times in Proteo. The description can be found in the file <i>Proteo_dataL_description.txt</i></li></ul></li><li><strong>5.4.2</strong>: Evaluation of the reconfiguration in a malleable application, CG against Proteo. Used to create Figure 10 and 11. It is divided into two directories, differentiating between CG and Proteus. In total there are the following 5 files:<ul><li><i>dataG.pkl</i>: Contains data on the complete runtimes in Proteo. The description can be found in the file <i>Proteo_dataG_description.txt</i></li><li><i>dataM.pkl</i>: Contains data on reconfiguration times in Proteo. The description can be found in the file <i>Proteo_dataM_description.txt</i></li><li><i>dataL.pkl</i>: Contains data on iteration times in Proteo. The description can be found in the file <i>Proteo_dataL_description.txt</i></li><li><i>dataCG_G.pkl</i>: Contains data on the complete execution times in the CG. The description can be found in the CG<i>_dataG_description.txt</i></li><li><i>dataCG_M.pkl</i>: Contains data on reconfiguration times in the CG. The description can be found in the CG<i>_dataM_description.txt</i></li></ul></li><li><strong>5.4.3</strong>: Evaluation of a malleable emulated application, CG against Proteo. Used to create Figure 12, 13 and 14. It is divided into two directories, differentiating between CG and Proteus. In total there are the following 5 files:<ul><li><i>dataG.pkl</i>: Contains data on the complete runtimes in Proteo. The description can be found in the file <i>Proteo_dataG_description.txt</i></li><li><i>dataM.pkl</i>: Contains data on reconfiguration times in Proteo. The description can be found in the file <i>Proteo_dataM_description.txt</i></li><li><i>dataL.pkl</i>: Contains data on iteration times in Proteo. The description can be found in the file <i>Proteo_dataL_description.txt</i></li><li><i>dataCG_G.pkl</i>: Contains data on the complete execution times in the CG. The description can be found in the CG<i>_dataG_description.txt</i></li><li><i>dataCG_M.pkl</i>: Contains data on reconfiguration times in the CG. The description can be found in the CG<i>_dataM_description.txt</i></li></ul></li></ul>
TimberTracer: A Comprehensive Framework for the Evaluation of Carbon Sequestration by Forest Management and Substitution of Harvested Wood Products.
<p><strong><em>Background</em></strong></p> <p>Harvested wood products (HWPs) have a pivotal role in climate change mitigation, a recognition solidified in many Nationally Determined Contributions (NDCs) under the Paris Agreement. Integrating HWPs' greenhouse gas (GHG) emissions and removals into accounting requirements relies on typical decision-oriented tools known as wood product models (WPMs). The study introduces the 'TimberTracer' (TT) framework, designed to simulate HWP carbon stock, substitution effects, and emissions from wood decay and bioenergy. </p> <p><strong><em>Results</em></strong></p> <p>Coupled with the 3D-CMCC-FEM forest growth model, <em>TimberTracer </em>was applied to Laricio Pine (<em>Pinus nigra</em> subsp. <em>laricio</em>) in Italy's Bonis watershed, evaluating three forest management practices (clearcut, selective thinning, and shelterwood) and four wood-use scenarios (business as usual, increased recycling rate, extended average lifespan, and a simultaneous increase in both the recycling rate and the average lifespan) over a 140-year planning horizon, to assess the overall carbon balance of HWPs. Furthermore, this study evaluates the consequences of disregarding landfill methane emissions and relying on static substitution factors, assessing their impact on the mitigation potential of various options. This investigation, covering HWPs stock, carbon (C) emissions, and the substitution effect, revealed that selective thinning emerged as the optimal forest management scenario. Additionally, the simultaneous increase in both the recycling rate and the half-life time proved to be the optimal wood-use scenario. Finally, the analysis shows that failing to account for landfill methane emissions and the use of dynamic substitution can significantly overestimate the mitigation potential of various forest management and wood-use options, which underscores the critical importance of a comprehensive accounting in climate mitigation strategies involving HWPs.</p> <p><strong><em>Conclusion</em></strong></p> <p>Our study highlights the critical role of harvested wood products (HWPs) in climate change mitigation, as endorsed by multiple Nationally Determined Contributions (NDCs) under the Paris Agreement. Utilizing the 'TimberTracer' framework coupled with the 3D-CMCC-FEM forest growth model, we identified selective thinning as the optimal forest management practice. Additionally, enhancing recycling rates and extending product lifespans effectively bolstered the carbon balance. Moreover, this study emphasizes the necessity of accounting for landfill methane emissions and dynamic product substitution, as failing to do so may significantly overestimate the mitigation potential of implemented projects. These findings offer actionable insights to optimize forest management strategies and advance climate change mitigation efforts.</p>
Dynamics Information Mapped In The Evaluation Framework
<p>Dynamics Information Mapped In The Evaluation Framework.</p>
An exploration of an evaluation framework for digital storytelling outcomes in the AI age
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Dataset of the Article Evaluating a Framework of Conceptual Modelling Research
<p>Excel files with the raw data of the article Evaluating a Framework of Conceptual Modelling Research</p>
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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.