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6,467 results for “process”
Data for: Scalable and Live Trace Processing with Kieker Utilizing Cloud Computing
<p>Knowledge of the internal behavior of applications often gets lost over the years. This circumstance can arise, for example, from missing documentation. Application-level monitoring, e.g., provided by Kieker, can help with the comprehension of such internal behavior. However, it can have large impact on the performance of the monitored system. High-throughput processing of traces is required by projects where millions of events per second must be processed live. In the cloud, such processing requires scaling by the number of instances.</p> <p>In this paper, we present our performance tunings conducted on the basis of the Kieker monitoring framework to support high-throughput and live analysis of application-level traces. Furthermore, we illustrate how our tuned version of Kieker can be used to provide scalable trace processing in the cloud.</p> <p>This is the dataset containing the results of our conducted benchmarks.</p>
Supplementary data for a study of Open Access Article Processing Charges - 2014
<p>Article Processing Charges levied by a set of Gold Open Access journals and hybrid journals in 2014, as collected from the publishers' web sites. Supplementary data to 10.2314/CERN/C26P.W9DT</p>
Vagrant Lives: 14,789 Vagrants Processed by Middlesex County, 1777-1786
<p><em><strong>This is no longer the most up to date version of this dataset. Please use version 1.1 (https://zenodo.org/record/31026) instead.</strong></em></p> <p>This dataset makes accessible the uniquely comprehensive records of vagrant removal from, through, and back to Middlesex, encompassing the details of some 14,789 men and women removed (either forcibly or voluntarily) as undesirables between 1777 and 1786. In includes people ejected from London as vagrants, and those sent back to London from counties beyond. Significant background material is available on the 'London Lives' website, which provides additional context for these records. The authors also recommend the following article:</p> <p> Tim Hitchcock, Adam Crymble, and Louise Falcini, ‘Loose, Idle and Disorderly: Vagrant Removal in Late Eighteenth-Century Middlesex’, _Social History_.</p> <p>Each record includes details on the name of the vagrant, his or her parish of legal settlement, where they were picked up by the vagrant contractor, where they were dropped off, as well as the name of the magistrate who had proclaimed them a vagrant. Each entry is georeferenced, to make it possible to follow the journeys of thousands of failed migrants and temporary Londoners back to their place of origin in the late eighteenth century.</p> <p>Each entry has 29 columns of data, all of which are described in the READ ME file.</p> <p>The original records were created by Henry Adams, the vagrant contractor of Middlesex who had - as had his father before him - conveyed vagrants from Middlesex gaols to the edge of the county where they would be sent onwards towards their parish of legal settlement. His role also involved picking up vagrants on their way back to Middlesex, expelled from elsewhere, as well as those being shepherded through to counties beyond, as part of the national network of removal. Eight times per year at each session of the Middlesex Bench, Adams submitted lists of vagrants conveyed as proof of his having transported these individuals, after which he would be paid for his services. The dataset contains all 42 surviving lists out of a possible 65.The gaps in the records are unfortunately not evenly spaced throughout the year. We know more, for example, about removal in October than in May.</p> <p>Spellings have been interpreted and standardized when possible. Georeferences have been added when they could be identified. This dataset was created for 21st century historians, and should not be construed as a true transcription of the original sources. Instead the goal was to use a limited vocabulary and to interpret the entries rather than recreate them verbatim. While this is undesirable for anyone interested in spelling variations of names and place names in the eighteenth century, it is the authors' hope that these interpretations will make it easier to conduct quantitative analysis and studies in historical geography.</p>
The Place of Signal processing
<p>“The Place of Signal processing” 2012. In: Workshop at Conference on Biomedical<br /> Science, by Scientific Society of Medical Engineering of Islamic Azad university of<br /> Tabriz. Presenter: Dr.Mirhadi Seyed Arabi, Dr.Ali Gouya and Dr.Hamid Mirzaei,<br /> 2012.</p>
Heatmaps of orthology and protein domain preservation in RNA Processing complexes throughout the fungal kingdom
<p>An analysis of the presence/absence of orthologues for Fungal RNA Processing protein complexes, and the presence/absence of the known PFAM protein domains within each protein within these complexes in the organism's proteome. </p> <p>Each image represents one RNA Processing protein complex.</p> <p>Orthology (far left panel in each image) is relative to Yeast, and taken from a query against the EnsEMBL orthology database (black = no orthologue; red = orthologue). <br> <br> Each orthologue was then queried for its PFAM domains, and the non-redundant set of PFAM domains representing each set of orthologous proteins, spanning all species, was then scanned against the complete proteome of each species. The resulting heatmap indicates the presence or absence of that PFAM domain anywhere in the proteome of that species. (black = absent; red = 1 copy; grey->blue = more than one copy)</p>
An Uncertainty-Aware Approach to Optimal Configuration of Stream Processing Systems
<p>The datasets in this release support the results presented in the paper</p> <blockquote> <p>P. Jamshidi, G. Casale, "An Uncertainty-Aware Approach to Optimal Configuration of Stream Processing Systems", accepted for presentation at MASCOTS 2016.</p> </blockquote> <p>An open access to the paper is available at https://arxiv.org/abs/1606.06543</p> <blockquote> <p>Also open source code is available at https://github.com/dice-project/DICE-Configuration-BO4CO</p> </blockquote> <p>The archive contains 10 comma separated datasets representing performance measurements (throughput and latency) for 3 different stream benchmark applications. These have been experimentally collected on 5 different cloud cluster over the course of 3 months (24/7). Each row in the datasets represents a different configuration setting for the application and the last two columns represent the average performance of the application measured over the course of 10 minutes under that specific configuration setting. The datasets contains a full factorial and exhaustive measurements for all possible settings limited to a predetermined interval for each variable. Each dataset is named in the following format: "<em>benchmark_application-dimensions-cluster_name</em>". For example, "wc-6d-c1" refers to WordCount benchmark application with 6 dimensions (i.e., we varied 6 configuration parameters) and the application was deployed on c1 cluster (OpenNebula, see Appendix). This resulted in a dataset of size 2880, i.e., it has taken 2880*10m=480h=20days for collecting the data! </p> <p>For more information about the data refer to the appendix of the paper: https://arxiv.org/abs/1606.06543. </p> <p>When referring to the dataset or code please cite the paper above.</p>
Robot Self-Assembly as Adaptive Growth Process: Collective Selection of Seed Position and Self-Organizing Tree-Structures
<p>Autonomous self-assembly allows to create structures and scaffolds on demand and automatically. The desired structure may be predetermined or alternatively it is the result of an artificial growth process that adapts to environmental features and to the intermediate structure itself. In a self-organizing and decentralized control approach the robots interact only locally and form the structure collectively. Designing a complete approach that allows the robot group to collectively decide on where to start the self-assembly, that adapts at runtime to environmental conditions, and that guarantees the structural stability is challenging and does not yet exist. We present an approach to self-assembly inspired by diffusion-limited aggregation that generates an adaptive structure reacting to environmental conditions in an artificial growth process. During a preparatory stage the robots collectively decide where to start the self-assembly also depending on environmental conditions. In the actual self-assembly stage, the robots create tree-like structures that grow towards light. We report the results of robot self-assembly experiments with 50 Kilobots. Our results demonstrate how an adaptive growth process can be implemented in robots. We explain how our approach will be extended to a 3-d growth process and how robot self-assembly as an open-ended adaptive growth process opens up a multiplicity of future opportunities.</p>
Processed BraTS 2013 HG Data
<p>Real high grade glioma patient MRI data from the BraTS 2013 challenge with N3 bias field correction for T1, T1ce, T2, histogram-matched, normalized by mean CSF value and T1ce-T1 subtraction map as fifth channel. Data includes the following features for each of the 5 channels: Gaussian smoothing (0.7; 1.6), Gaussian gradient magnitude (0.7; 1.6), Laplacian of Gaussian (0.7; 1.6), 3 Hessian of Gaussian eigenvalues (0.7; 1.6), 3 structure tensor eigenvalues (0.7; 1.6). Format is HDF5, features along last axis.</p>
Processing a Quarter (68 folios) of the Syriac Galen Palimpsest http://www.digitalgalen.net
<p>This dataset contains approximately a quarter of the Syriac Galen Palimpsest (http://www.digitalgalen.net/) which was image processed with the Canonical Variates Analysis method and the software existent at this web link https://github.com/corneliu37/GalenProject with the scope of retrieving a sixth-century translation from Greek language to Syriac language of the 2nd century Greek Scientist Aelius Galen book's "On Simple Drugs", which translation was made by the 6th century scientist Sergius of Resh 'Ayna, which text exists presently as an undertext of an eleventh-century liturgical work (i.e. the overtext) and this is known once again as the Syriac Galen Palimpsest. This quarter of the Syriac Galen Palimpsest was processed by Dr Corneliu Arsene, University of Manchester, United Kingdom, 2016 (68 folios processed with the Canonical Variates Analysis software/method from the total of about 250 unprocessed folios). </p>
Spatial flood events and process types
Spatially clustered flood events from peak flows identified at selected GRDC sations. The data also shows the stations affected by each of the clustered eevents. The clustered events were classified into four different process types. Furthermore, five regions were defined across Europe and the regions affected by each flood event are identified. Further description and content of each data file can be seen in the included metadata.
Systematic PSI processing over Santorini volcano: the 2011-2012 unrest period
<p>In the framework of the ESA funded project “Disaster Risk Reduction using innovative data exploitation methods and space assets”, the National Observatory of Athens together with Terradue customized a GEP implementation of the StaMPS suite of s/w modules, to automatically process stacks of SAR imagery using Persistent Scatterer Interferometry. The engine is now able to seamlessly and timely process data from Envisat, ERS-1,2, TerraSAR-X, COSMO-SkyMed and Radarsat-2 platforms, for user-defined Regions Of Interest. Hence, the concept of project’s “Trial Case VO-1” is to modify, customize, execute and test a fully automatic processing chain over the GEP, starting from raw/SLC SAR data, to ground velocities generation.</p> <p>The new capabilities have been tested for an historic volcano in Santorini island, Greece, aiming to create a unique database of diachronic InSAR measurements spanning from 1992 to 2015 (~23 years of data). The processing of the five different SAR stacks was done entirely within the GEP environment, in the context of the Trial Case VO-1. The thematic map included herein contains the estimated Line-Of-Sight ground velocities (mm/yr) for the <strong>period 2011-2012, based on 12 descending ASAR Envisat images</strong>. Kindly note that the product is raw and has not gone through any manual post-processing. Therefore, adjustments may need to be made to address reference point issues, isolated phase unwrapping errors, etc. </p>
Systematic PSI processing over Santorini volcano: the 2012-2013 post unrest period
<p>In the framework of the ESA funded project “Disaster Risk Reduction using innovative data exploitation methods and space assets”, the National Observatory of Athens together with Terradue customized a GEP implementation of the StaMPS suite of s/w modules, to automatically process stacks of SAR imagery using Persistent Scatterer Interferometry. The engine is now able to seamlessly and timely process data from Envisat, ERS-1,2, TerraSAR-X, COSMO-SkyMed and Radarsat-2 platforms, for user-defined Regions of Interest. Hence, the concept of project’s “Trial Case VO-1” is to modify, customize, execute and test a fully automatic processing chain over the GEP, starting from raw/SLC SAR data, to ground velocities generation. The new capabilities have been tested for an historic volcano in Santorini island, Greece, aiming to create a unique database of diachronic InSAR measurements spanning from 1992 to 2015 (~23 years of data). The processing of the five different SAR stacks was done entirely within the GEP environment, in the context of the Trial Case VO-1. The thematic map included herein contains the estimated Line-Of-Sight ground velocities (mm/yr) for the period 2012-2013, based on 25 descending TerraSAR-X images. Kindly note that the product is raw and has not gone through any manual post-processing. Therefore, adjustments may need to be made to address reference point issues, isolated phase unwrapping errors, etc. </p>
Data from Hesse et al. 2017: Preattentive Processing of Numerical Visual Information, Front Hum Neurosci., 11:70, 2017. doi: 10.3389/fnhum.2017.00070.
<p><strong>Data related to the following publication: </strong></p> <p>Hesse Philipp N., Schmitt Constanze, Klingenhoefer Steffen, Bremmer Frank (2017). Preattentive Processing of Numerical Visual Information. Frontiers in Human Neuroscience, 11: 70. doi: 10.3389/fnhum.2017.00070</p> <p><strong>Brief description of dataset:</strong></p> <p>The stimulus was presented on a TFT monitor (size: 41,8° x 24,3°) 52 cm in front of the participants in a dark, sound attenuated and electrically shielded room. During the experiment EEG was recorded continuously. We used 64 Ag/AgCl active electrodes located according to the extended international 10-20 system. </p> <p>The numerosity stimulus consisted of a continuously displayed black fixation target in the center of the gray screen. Additionally in each trial either one, two or three circular white patches were shown 200 ms after trial onset. These were presented for a random duration between 400 ms and 500 ms either in the left or right visual field. Two different types of patches were presented: i) the radius of the patches had the same value (0.65°) and therefore the patch size was the same (“SizeCon”) ii) the total area of the patches was conserved which resulted in the same total luminance independent of the number of patches (“LumCon”). After a random time between 400 ms and 700 ms after stimulus offset the trials ended.</p> <p>In this study we conducted an oddball experiment with an oddball-ratio of 1:4. In each block consisting of 30 trials a standard-amount of patches (one, two or three) was presented in 80% of all trials (24 trials). The two remaining quantities of patches were shown in 10% (3 trials) of the trials each. This presentation scheme allowed us to compare trials with identical physical properties because each amount of patches served as deviant and standard trial in different blocks. Attention of the participants was drawn off the white patches by a demanding detection task at the fixation target. A total number of 432 blocks consisting of 30 trials was presented to each of the 10 participants.</p> <p>EEG data were evaluated offline. The mastoids (TP9 and TP10) were chosen as new reference. A second-order, zero phase shift Butterworth filter with cutoff frequencies 0.5 and 40 Hz was applied to the continuously recorded data before it was sliced in individual trials that had a time range from 200 ms before to 500 ms after stimulus onset. A baseline correction was performed using with the signals from -110 ms to 0 ms. As a last step trials with eye movement artifacts or electrode signals that exceeded a difference of ±100 µV within an interval of 100 ms were excluded in an artifact rejection step.</p> <p> </p>
Systematic PSI processing over Santorini volcano: the 1992-2000 pre-unrest period
<p>In the framework of the ESA funded project “Disaster Risk Reduction using innovative data exploitation methods and space assets”, the National Observatory of Athens together with Terradue customized a GEP implementation of the StaMPS suite of s/w modules, to automatically process stacks of SAR imagery using Persistent Scatterer Interferometry. The engine is now able to seamlessly and timely process data from Envisat, ERS-1,2, TerraSAR-X, COSMO-SkyMed and Radarsat-2 platforms, for user-defined Regions Of Interest. Hence, the concept of project’s “Trial Case VO-1” is to modify, customize, execute and test a fully automatic processing chain over the GEP, starting from raw/SLC SAR data, to ground velocities generation.</p> <p>The new capabilities have been tested for an historic volcano in Santorini island, Greece, aiming to create a unique database of diachronic InSAR measurements spanning from 1992 to 2015 (~23 years of data). The processing of the five different SAR stacks was done entirely within the GEP environment, in the context of the Trial Case VO-1. The thematic map included herein contains the estimated Line-Of-Sight ground velocities (mm/yr) for the <strong>period 1992-2000, based on 37 descending ERS-1,2 images</strong>. Kindly note that the product is raw and has not gone through any manual post-processing. Therefore, adjustments may need to be made to address reference point issues, isolated phase unwrapping errors, etc. </p>
Systematic PSI processing over Santorini volcano: the 2015 post unrest period
<p>In the framework of the ESA funded project “Disaster Risk Reduction using innovative data exploitation methods and space assets”, the National Observatory of Athens together with Terradue customized a GEP implementation of the StaMPS suite of s/w modules, to automatically process stacks of SAR imagery using Persistent Scatterer Interferometry. The engine is now able to seamlessly and timely process data from Envisat, ERS-1,2, TerraSAR-X, COSMO-SkyMed and Radarsat-2 platforms, for user-defined Regions Of Interest. Hence, the concept of project’s “Trial Case VO-1” is to modify, customize, execute and test a fully automatic processing chain over the GEP, starting from raw/SLC SAR data, to ground velocities generation.</p> <p>The new capabilities have been tested for an historic volcano in Santorini island, Greece, aiming to create a unique database of diachronic InSAR measurements spanning from 1992 to 2015 (~23 years of data). The processing of the five different SAR stacks was done entirely within the GEP environment, in the context of the Trial Case VO-1. The thematic map included herein contains the estimated Line-Of-Sight ground velocities (mm/yr) for the <strong>period 2015, based on 30 ascending COSMO-SkyMed</strong> <strong>images</strong>. Kindly note that the product is raw and has not gone through any manual post-processing. Therefore, adjustments may need to be made to address reference point issues, isolated phase unwrapping errors, etc. </p>
Systematic PSI processing over Santorini volcano: the 2012-2016 post unrest period
<p>In the framework of the ESA funded project “Disaster Risk Reduction using innovative data exploitation methods and space assets”, the National Observatory of Athens together with Terradue customized a GEP implementation of the StaMPS suite of s/w modules, to automatically process stacks of SAR imagery using Persistent Scatterer Interferometry. The engine is now able to seamlessly and timely process data from Envisat, ERS-1,2, TerraSAR-X, COSMO-SkyMed and Radarsat-2 platforms, for user-defined Regions Of Interest. Hence, the concept of project’s “Trial Case VO-1” is to modify, customize, execute and test a fully automatic processing chain over the GEP, starting from raw/SLC SAR data, to ground velocities generation.</p> <p>The new capabilities have been tested for an historic volcano in Santorini island, Greece, aiming to create a unique database of diachronic InSAR measurements spanning from 1992 to 2015 (~23 years of data). The processing of the five different SAR stacks was done entirely within the GEP environment, in the context of the Trial Case VO-1. The thematic map included herein contains the estimated Line-Of-Sight ground velocities (mm/yr) for the <strong>period 2012-2016, based on 20 descending Radarsat-2 images</strong>. Kindly note that the product is raw and has not gone through any manual post-processing. Therefore, adjustments may need to be made to address reference point issues, isolated phase unwrapping errors, etc. </p>
Impact of Antipatterns on Software systems- Snowballing Process
<p> This study presents a systematic literature review that accumulates, summarizes, and reports the results of 97 relevant Primary Studies (PSs) concerning the impact of APs on Object Oriented (OO), Service Oriented (SO), and mobile Oriented (MO) software applications from 2005 to 2024 while considering several internal and external quality attributes. The PSs are classified based on the techniques used to find the impact of APs, type of datasets, evaluation measures, and tool support. </p>
Structured Literature Review on Traditional Approaches in Current Natural Lanugage Processing
<p>These files contain the foundation for the structured literature review (SLR) on traditional models, approaches and techniques in Natural Language Processing.</p> <p>In order to reproduce the results obtained in this SLR, we have uploaded two files:</p> <ul> <li><em>slr_traditionalmodelsNLP.xlsx</em>:<br>The search strings as well as applied filters used in the SLR can be found in this attached Excel-file.<br>Furthermore, the results of the SLR are also located in this Excel file.</li> <li><em>urls.txt<br></em>Additional URLs for a quantitative analysis are located in this text-file.</li> </ul>
European database of processing factors for pesticides residues in food
<p>EFSA is regularly evaluating pesticide occurrence data in food generated under the official monitoring programs of Member States with respect to consumer exposure and risk assessment. Most of these data refer to raw commodities (RAC) because maximum residue levels established under European legislation reflect pesticide residues only in the RAC. However, food processing operations can have decisive effects on pesticide residue levels and therefore consumer exposure. This database has been developed to compile validated processing factors for pesticide residues in food in line with the EFSA food classification and description system (FoodEx2).</p> <p>This update fixes a problem that caused some median processing factors to display a "<" qualifier when it was not necessary. The calculated values for the processing factors were not affected by this error and remain unchanged from the previous release</p> <p>The database is complemented by the following publications:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.6564213">Background Document on the EU Database of Processing Factors for Pesticide Residues</a></li> <li><a href="https://doi.org/10.5281/zenodo.6564207">Compendium of Representative Processing Techniques Investigated in Regulatory Studies for Pesticides</a></li> <li><a href="https://doi.org/10.5281/zenodo.6564209">Linking Processed Foods and Processing Techniques to the FoodEx2 Coding System</a></li> </ul>
Linking Processed Foods and Processing Techniques to the FoodEx2 Coding System
<p>This excel file complements the <a href="https://doi.org/10.5281/zenodo.1488652">EU database of processing factors for pesticide residues</a> by providing the mapping between processed food/feed listed in the database and the FoodEx2 coding system.</p>
ScienceDex guides
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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.