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470 results for “Evaluation dataset”
Supplementary dataset for "Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking"
<p>The supplementary dataset for the paper "Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking". We include the splits for cora, citeseer, and pubmed, the hard negative samples, and the node2vec embeddings. We also include a jupyter file <em>read_data.ipynb</em> to show how to read the non-txt file.</p> <ul> <li>heart_test_samples.npy, heart_valid_samples.npy: the heard negative samples</li> <li>*-n2v-embedding.pt: node2vec embeddings</li> <li>test_samples_index.pt, valid_samples_index.pt: the node index of the selected samples in ogbl-ppa under HeaRT</li> <li>gnn_feature: the input feature of cora, citeseer, pubmed</li> </ul> <p>More details for our code and how to use the dataset are on the code repository: https://github.com/Juanhui28/HeaRT .</p>
Datasets for Paper "BenchTemp: A General Benchmark for Evaluating Temporal Graph Neural Networks"
<p>Datasets for Paper "BenchTemp: A General Benchmark for Evaluating Temporal Graph Neural Networks"<br> URL: https://github.com/qianghuangwhu/benchtemp</p> <p>Openreview: https://openreview.net/forum?id=rnZm2vQq31</p> <p><br> There are 19 (15+4) benchmark temporal graph datasets:<br> reddit,<br> wikipedia,<br> mooc,<br> lastfm,<br> enron,<br> SocialEvo,<br> uci,<br> CollegeMsg,<br> TaobaoSmall,<br> CanParl,<br> Contacts,<br> Flights,<br> UNtrade,<br> USLegis,<br> UNvote,</p> <p>DGraphFin,</p> <p>TaobaoLarge,</p> <p>YoutubeReddit,</p> <p>YoutubeRedditLarge</p> <p> </p> <p><br> Each dataset has three files:<br> 1. ml_{data_name}.csv - the csv file of the Temporal Graph.</p> <p>This file have five columns with properties:</p> <p>'u': the id of the user.<br> 'i': the id of the item.<br> 'ts': the timestamp of the interaction (edge) between the user and the item.<br> 'label': the label of the interaction (edge).<br> 'idx': the index of the interaction (edge).<br> For example:</p> <p>,u,i,ts,label,idx<br> 0,1,2,0.0,0.0,1<br> 1,1,3,0.0,0.0,2<br> 2,1,4,0.0,0.0,3<br> 2. ml_{data_name}.npy - the edge features corresponding to the interactions (edges) in the the Temporal Graph..</p> <p>3. ml_{data_name}_node.npy - the initialization node features of the Temporal Graph.</p>
Evaluation results of the xMEN entity linking toolkit for multiple benchmark datasets
Open the record for dataset details and reuse information.
Dataset and R code: Genetic diversity of lion populations in Kenya: evaluating past management practices and recommendations for future conservation actions by Chege M et.al
Open the record for dataset details and reuse information.
The dataset for the research "Evaluation of Digital Supply Chain Technology’s Impact on Sustainability Under the Moderate Effect of Supply Chain Dynamism: An Empirical Research in the Chinese Energy Supply Chain"
In recent years, the topic of digitalisation and sustainability of supply chains has become increasingly important. In addition, as the environmental dynamism becomes more complex, it is essential to explore how technologies impacts on sustainability under the supply chain dynamism. Hence, there is a study to explore the relationship between technologies and sustainability under the supply chain dynamism in the energy supply chain. In this study, the author collects quantitative data from two Chinese companies, including China Resources Power Zhejiang Company and Hunan HuaDian Changsha Electric Co., Ltd. This is a questionnaire survey and it has 24 questions, including 3 general questions, 5 technologies dimension questions, 12 sustainability dimension questions and 4 supply chain dynamism questions. The author collected data from 30 May 2024 to 6 June May 2024, and there are totally 316 answers.
Dataset for WP6 KPI evaluation
<p>Performance of all WP6 use cases was evaluated through KPIs which were defined (together with the methodology) in the beginning of the InterFlex project. The detail definition of WP6 KPIs is included in deliverable D6.1 Design of solution as KPI annex. Following KPIs for WP6 were defined:<br> 1. KPI6_1: Increasing DER hosting capacity</p> <p>2. KPI6_2: Power quality (according to the standard EN 50160)3. KPI6_</p> <p>3: EV charging stations load curtailment in emergency situations</p> <p>4. KPI6_4: PV production peak shaving</p> <p><br> Dataset for each KPI evaluation is included in list of this excel sheet.<br> KPI evaluation conclusionAll expectations in terms of WP6 KPIs were fulfilled. Based on KPIs evaluation it is obvious that WP6 solutions are very promising to increase the DER hosting capacity and control EV charging. KPI evaluation for WP6 is an important input for Scalability and Replicability Analysis and for Cost Benefit Analysis which are further key inputs for the definition of viable business models part of the D6.3 deliverable.</p>
A dataset for evaluating one-shot categorization of novel object classes
<p>From just a single example, we can derive quite precise intuitions about what other class members look like. This stands in stark contrast to machine learning algorithms, which typically require tens or even hundreds of thousands of examples to learn a new category. One of the most important open questions in our field is: How do humans achieve this? The stimuli and data provided here (in MATLAB format) are from thousands of crowd-sourced human responses to novel objects. The data can be used to test machine learning generalization as compared to human and also can be used as a test bed for various kinds of category learning models. </p>
Learning Unsupervised Knowledge-Enhanced Representations to Reduce the Semantic Gap in Information Retrieval (Evaluation datasets)
<p>This dataset contains all the runs, pools, plots and analyses to reproduce the results presented in the paper: "Learning Unsupervised Knowledge-Enhanced Representations to Reduce the Semantic Gap in Information Retrieval ", 2020.</p>
Hakea vegetation dataset for training and evaluating segmentation network
<p>This dataset is the version used for both training and evaluation of the models discussed the (in press) publication in Methods in Ecology and Evolution, "Detecting plant species in the field with deep learning and drone technology".</p> <p>Also included in this upload, results_inference_images.tar includes the output predictions for each of the trained models on the unseen test set.</p>
Associated dataset for "Instrumental Evaluation of Sensor Self-Noise in Binaural Rendering of Spherical Microphone Array Signals"
<p>The conducted instrumental evaluation utilizes the Real-Time Spherical Microphone Renderer (<a href="https://github.com/AppliedAcousticsChalmers/ReTiSAR">ReTiSAR</a>) for binaural reproduction in Python. The at that time employed code state should be used in order to exactly reproduce the rendering results in this data set. The frozen code state for this data set is available at:<br> <a href="https://github.com/AppliedAcousticsChalmers/ReTiSAR/releases/tag/v2020.FA">https://github.com/AppliedAcousticsChalmers/ReTiSAR/releases/tag/v2020.FA</a></p> <p>Download the rendering pipeline and follow the setup instructions! Use the here included Conda environment file when setting up the Python environment. In this way, you will obtain exactly the same Python setup as utilized in the instrumental evaluation in the publication:</p> <pre><code class="language-bash">conda env create --file ReTiSAR_environment_freeze.yml</code></pre> <pre><code class="language-bash">source activate ReTiSAR_FA_freeze</code></pre> <p>Directory "SMA sampling grids":</p> <ul> <li>Visualization of spatial arrangement (like Figure 4) for all investigated spherical microphone array rendering configurations (Table 1)</li> </ul> <p>Shell script "record_snr.sh":</p> <ul> <li>Record the input and output signals of the rendering pipeline for sound field (target / wanted) and self-noise (unwanted) components for all configurations at multiple head orientations</li> <li>All captured signals are contained in the "SNR" directory</li> </ul> <p>Matlab script "calculate_snr.m":</p> <ul> <li>Visualize the raw captured input and output signals (like Figure 1 for all configurations)</li> <li>Visualize the resulting signal-to-noise ratio (like Figure 2 for all configurations)</li> <li>Visualize the comparison of the resulting signal-to-noise ratio of all configurations (Figure 3, also for the resulting SNR from signals with A-weighting)</li> <li>All generated plots are contained in the "SNR" directory</li> </ul> <p>Shell script "record_noise.sh":</p> <ul> <li>Record the calibration and noise signals of the mh acoustic Eigenmike 32 spherical microphone array in the anechoic chamber at Chalmers University of Technology (Appendix)</li> <li>All captured signals are contained in the "EM32 measurements" directory</li> <li>Pictures of the measurement setup are contained in the "Pictures" subdirectory</li> </ul> <p>Matlab script "calculate_EM32_noise_levels.m":</p> <ul> <li>Determine the resulting target signal sensitivity and equivalent input noise levels for the investigated pre-amplification gains (Table 2)</li> <li>Visualize the statistical distribution of the individual raw and weighted SMA channels (like Figure 6 for all configurations)</li> <li>Visualize the spatial distribution of the individual raw and weighted SMA channels for all configurations</li> <li>Visualize the smoothed and averaged magnitude spectra of the individual raw and weighted SMA channels (like Figure 5 for all configurations)</li> </ul>
Dataset for pilot evaluation of an enzymatic assay for rapid measurement of antiretroviral drug concentrations
<p>Liquid chromatography tandem mass spectrometry (LC-MS/MS) data, and REverSe TRanscrIptase Chain Termination (RESTRICT) assay data for pilot evaluation study of enzymatic RESTRICT assay for rapid measurement of antiretroviral drug concentrations among people receiving oral pre-exposure prophylaxis (PrEP).</p>
Dataset accompanying paper submission for "Toward data-driven generation and evaluation of model structure for integrated representations of human behavior in water resources systems"
<p>This data set accompanies code archived at DOI: <a href="https://doi.org/10.5281/zenodo.3833186">10.5281/zenodo.3833186</a>, which was used in the experiments for the paper submission "Toward data-driven generation and evaluation of model structure for integrated representations of human behavior in water resources systems"</p>
Dataset related to article "Evaluation of cell metabolic adaptation in wound and tumour by fluorescence Lifetime imaging Microscopy"
<p>This record contains data related to article "Evaluation of cell metabolic adaptation in wound and tumour by fluorescence Lifetime imaging Microscopy"</p> <p>Abstract</p> <p>Acidic pH occurs in acute wounds progressing to healing as consequence of a cell metabolic adaptation in response to injury-induced tissue hypoperfusion. In tumours, high metabolic rate leads to acidosis affecting cancer progression. Acidic pH affects activities of remodelling cells in vitro. The pH measurement predicts healing in pathological wounds and success of surgical treatment of burns and chronic ulcers. However, current methods are limited to skin surface or based on detection of fluorescence intensity of specific sensitive probes that suffer of microenvironment factors. Herein, we ascertained relevance in vivo of cell metabolic adaptation in skin repair by interfering with anaerobic glycolysis. Moreover, a custom-designed skin imaging chamber, 2-Photon microscopy (2PM), fluorescence lifetime imaging (FLIM) and data mapping analyses were used to correlate maps of glycolytic activity in vivo as measurement of NADH intrinsic lifetime with areas of hypoxia and acidification in models of skin injury and cancer. The method was challenged by measuring the NADH profile by interfering with anaerobic glycolysis and oxidative phosphorylation in the mitochondrial respiratory chain. Therefore, intravital NADH FLIM represents a tool for investigating cell metabolic adaptation occurring in wounds, as well as the relationship between cell metabolism and cancer.</p>
Dataset of Paper: "Evaluation of membranes performance for microplastic removal in a simple and low-cost filtration system"
<p>Dataset of Paper: "Evaluation of membranes performance for microplastic removal in a simple and low-cost filtration system":</p> <ul> <li>Zeta potential curves as a function of pH</li> <li>Results of transmembrane pressure (TMP) and flow rate of the filtration experiments. Average transmembrane pressure drop (ΔTMP) and flux (J) after 10 min of operation.</li> <li>Total number of unremoved microplastic particles per litre (NTMP), average size (DMP), and mass removal efficiency (MRE%) of each membrane when filtering water with 100 mg/L of PA and PS</li> </ul>
Denul Evaluation Dataset
<p>Partial dataset of the evaluation results of my master thesis, showing the results of the simulator. Remaining data and additional information can be found at https://github.com/DenulApp/data</p>
Temporal and spatial evaluation of satellite-based rainfall estimates across the complex topographical and climatic gradients of Chile (datasets)
<p>This file contains the <strong>dataset</strong> (both raw observed precipitation data and figures obtained as output of the analysis) accompanying the manuscript '<strong>hess-2016-453'</strong> submitted to the HESS journal (http://www.hydrology-and-earth-system-sciences.net/).</p> <p> </p> <p><strong>Title</strong>: "Temporal and spatial evaluation of satellite-based rainfall estimates across the complex topographical and climatic gradients of Chile"</p> <p> </p> <p><strong>Abstract</strong></p> <p>Accurate representation of the real spatio-temporal variability of catchment rainfall inputs is currently severely limited. Moreover, spatially interpolated catchment precipitation is subject to large uncertainties, particularly in developing countries and regions which are difficult to access (e.g., high elevation zones). Recently, satellite-based rainfall estimates (SRE) provide an unprecedented opportunity for a wide range of hydrological applications, from water resources modelling to monitoring of extreme events such as droughts and floods. </p> <p>This study attempts to exhaustively evaluate -for the first time- the suitability of seven state-of-the-art SRE products (TMPA 3B42v7, CHIRPSv2, CMORPH, PERSIANN-CDR, PERSIAN-CCS-adj, MSWEPv1.1 and PGFv3) over the complex topography and diverse climatic gradients of Chile. Different temporal scales (daily, monthly, seasonal, annual) are used in a point to-pixel comparison between precipitation time series measured at 366 stations (from sea level to 4600 m a.s.l. in the Andean Plateau) and the corresponding grid cell of each SRE. The modified Kling-Gupta efficiency was used to identify possible sources of systematic errors in each SRE. In addition, several categorical indices were used to assess the ability of each SRE to correctly identify different precipitation intensities.</p> <p><br> Results revealed that most SRE products performed better for the humid South (36.4-43.7ºS) and Central Chile (32.18-36.4ºS), in particular at low- and mid-elevation zones (0-1000 m a.s.l.) compared to the arid northern regions and the Far South. Seasonally, all products performed best during the wet seasons (MAM-JJA) compared to summer (DJF) and autumn (SON). In addition, all SREs were able to correctly identify the occurrence of no rain events, but they presented a low skill in classifying precipitation intensities during rainy days. Overall, PGFv3 exhibited the best performance everywhere and for all time scales, which can be clearly attributed to its bias-correction procedure using 213 stations from Chile. Good results were also obtained by CHIRPSv2, TMPA 3B42v7 and MSWEPv1.1, while CMORPH, PERSIANN-CDR and PERSIANN-CCS-adj were not able to represent observed rainfall. While PGFv3 (currently available up to 2010) might be used in Chile for historical analyses and calibration of hydrological models, the high spatial resolution, low latency and long data records of CHIRPS and TMPA 3B42v7 (in transition to IMERG) show promising potential to be used in meteorological studies and water resources assessments. We finally conclude that despite improvements of most SRE products, a site-specific calibration is still needed before any use in catchment-scale hydrological studies.</p>
TUT Acoustic scenes 2016, Evaluation dataset
<p>TUT Acoustic Scenes 2016, evaluation dataset consists of 30-seconds audio segments from 15 acoustic scenes:</p> <ul> <li>Bus - traveling by bus in the city (vehicle)</li> <li>Cafe / Restaurant - small cafe/restaurant (indoor)</li> <li>Car - driving or traveling as a passenger, in the city (vehicle)</li> <li>City center (outdoor)</li> <li>Forest path (outdoor)</li> <li>Grocery store - medium size grocery store (indoor)</li> <li>Home (indoor)</li> <li>Lakeside beach (outdoor)</li> <li>Library (indoor)</li> <li>Metro station (indoor)</li> <li>Office - multiple persons, typical work day (indoor)</li> <li>Residential area (outdoor)</li> <li>Train (traveling, vehicle)</li> <li>Tram (traveling, vehicle)</li> <li>Urban park (outdoor)</li> </ul> <p>Each acoustic scene has 26 segments totaling 13 minutes of audio.</p>
Aberystwyth Leaf Evaluation Dataset
<p>We are releasing the dataset acquired to support the work of the EPSRC funded project “Dynamic Modelling of Plant Growth with Computer Vision” (grant code EP/LO17253/1) in the hope that its availability will help further advance the state of the art in the use of image analysis for plant sciences. It is a visible light, top down, timelapse image dataset of Arabidopsis thaliana (Arabidopsis). It incorporates the original images, some with leaf-level ground truth annotations, harvested plant ground truth data and scanned images together with supporting software.</p> <ul> <li>4 sets of 20 Arabidopsis Thaliana plants have been grown in trays</li> <li>Images of each tray are taken in a 15 minute timelapse sequence using a robotic greenhouse system</li> <li>Periodically, plants from each tray are sacrificed to record destructive measurements</li> <li>A subset of these images have been hand-annotated to provide leaf-based image <em>ground truth</em>. <ul> <li>In total, there are 56 annotated ground truth images containing 916 hand-marked up individual arabidopsis plants</li> </ul> </li> <li>We also release software to help with the analysis of these images</li> </ul>
APIBench: A Benchmark Dataset for Evaluating API Recommendation Approaches in Python and Java
<p>APIBench is the benchmark dataset APIBench released in the paper "<a href="https://yunpeng.site/files/apirec.pdf"><em>Revisiting, Benchmarking and Exploring APIRecommendation: How Far Are We?</em></a>". </p> <p>APIBench contains two sub-dataset for evaluating the performance of query-based and code-based API recommendation approaches, namely APIBench-Q and APIBench-C. Each sub-dataset has a Java version and a Python version.</p> <p>APIBench-Q contains 4,309 Python queries and 6,563 Java queries collected from Stack Overflow posts generated from Aug 2008 to Feb 2021 and tutorial websites Geeks4Geeks, Java2s, and Kode Java in April 2021.</p> <p>APIBench-C contains 2,361 Python projects and 1,477 Java projects mined from GitHub in April 2021.</p> <p>Please read the <strong>README.md</strong> file for detailed information about the benchmark.</p> <p>The evaluation results of existing API recommendation approaches can be found in <a href="https://github.com/JohnnyPeng18/APIBench">this GitHub repository</a>.</p>
2DVD dataset for GMD publication - Simulated prognostic approach of graupel density in a bulk-type cloud microphysics scheme and evaluation during the ICE-POP field campaign
<p>This archive contains the 2DVD measurement of graupel particles used in the GMD paper "Simulated prognostic approach of graupel density in a bulk-type cloud microphysics scheme and evaluation during the ICE-POP field campaign".</p><p>For each identified graupel particle, the following are included:</p><ul><li>Volume-equivalent diameter (mm)</li><li>Density (g cm-3)</li><li>Fall velocity (m s-1)</li></ul>
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.