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1,393 results for “traces”
PARSEC 2.1 Traces for ChampSim
<p>This is a public release of ChampSim traces collected from <a href="https://www.cs.utexas.edu/~cart/parsec_m5/">PARSEC 2.1</a> workload suite. The compiler flags used to build the kernels are mentioned in each trace name.</p>
Methodology of diachronic analysis of old prints and its validation by tracing the changing meaning of key concepts in the intellectual debate of 16th century Italy
<p>This dataset in corpus.zip file contains OCR texts for 16th century Italian books available from BNF (folder gallica) and archive.org (folder internetarchive). Source URL is given in 1st line of each text file. The pages within each document may come in order different than in the source, however, the order of lines in each page is preserved. The archive is protected with password, which will be made public immediately after the publication of the related research paper under the same title.</p> <p>Samples of three documents along with images of their initial pages are provided at the current time.</p>
Cyber4OT: ICS network traces containing normal activity and full attack traffic
<p>The <em><strong>Cyber4OT</strong></em> dataset contains prepared in the test-bed environment packet traces from normal activity of OT network, as well as, full network attack. During recorded activity, the attacker performs full network reconnaissance, later disconnects legal Modbus TCP connection and performs PLC device hijacking.</p> <p>The dataset contains 96 files with more than 4,25 millions of packets.</p> <p><em><strong>ReadMe.txt</strong></em> file contains short description of each trace file content.</p> <p>Detailed description of the test bed, where data was prepared, is provided in the <em><strong>Cyber4OT_testbed_description.pdf</strong></em> file.</p>
Supplementary material S17: All instances of jolting pulses on honeycomb where the vibrational trace is clearly visible (spectrograms).
<p>A series of spectrograms demonstrating the most clearly visible <em>Varroa </em>jolting vibrational pulses registered on honeycomb. These spectrograms showcase the larger variation that is observed in jolting pulses on this substrate. Panels e, f and h provide evidence for the broad-band and generation of signal at the high-frequency bandwidth. The magnitude of acceleration is logarithmic (to the base 10), where the maximum is in red (1x10<sup>-3</sup> m/s<sup>2</sup>) and the minimum blue (and forced to be 1/20 of the maximum).</p>
Digital Contact Tracing: Overview of technological solutions for the fight against pandemics
<p>In late 2019, Covid-19 emerged and was soon declared a pandemic causing until now a massive health disruption and a huge impact on the global economy. Several governments around the world are still forced to take containment measures to curb the spread of the virus including partial or full lockdowns. At the same time, they rely heavily on human resources to perform manual Contact Tracing (CT) for alerting known contacts of the confirmed cases and breaking the infection chains early enough. However, CT does not scale well when the cases increase exponentially, due to the limited capacity of national public health authorities, and cannot identify possible <em>hidden</em> infections due to random encounters with strangers in crowded spaces such as restaurants, bars, theaters, public transportation, etc. To this end, Digital Contact Tracing (DCT) is becoming increasingly popular to enhance and empower CT, enabling automatic and faster identification and notification of exposed users. This presentation will first overview the different generations of DCT solutions from the privacy-invasive use of subscriber location data provided by cellular operators, to location monitoring mobile apps on GPS-equipped smartphones, to privacy-preserving mobile apps based on <em>proximity</em> sensing through Bluetooth. It will discuss the findings of recent studies with regards to the effectiveness of DCT and debate whether it has been – or has the potential to become – a game changer. Finally, it will outline the latest developments and trends in this active research field that are of interest to the IPIN community including <em>presence</em> tracing that aims to notify anonymously those users that have been in the same place (especially indoors) with an infected user, without necessarily satisfying the proximity constraint.</p>
BLE Ray-Tracing Simulation Dataset
<p>BLE ray-tracing propagation data generated via Altair Feko WinProp software in a simulation environment of dimensions 14m x 7m. Four horizontal facing APs are placed in the corners of the room at 2.5m height and at 45 degrees azimuth rotation pointing towards the center of the room. The elevation angle of all APs is 45 degrees pointing downwards. Three transmitting frequencies are simulated i.e., 2402, 2426 and 2480 MHz, corresponding to the three advertising BLE channels (numbered 37, 38 and 39, respectively) and two antenna polarizations (omni-directional), i.e., horizontal and vertical. The tag is positioned at a fixed height of 1.5 m (z-dimension) and 2450 signal samples are collected per room configuration, evenly distributed across the room. Data was collected for 9 different room configurations with varying furniture, furniture material and anchor points positions and orientation as shown below. <br> </p> <table> <tbody> <tr> <td> <table> <thead> <tr> <th>Room Setup</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td>testbench_01</td> <td>No line-of-sight blocking furniture</td> </tr> <tr> <td>testbench_01_furniture_low</td> <td>One line-of-sight blocking furniture</td> </tr> <tr> <td>testbench_01_furniture_mid</td> <td>Three line-of-sight blocking furniture</td> </tr> <tr> <td>testbench_01_furniture_high</td> <td>Six line-of-sight blocking furniture</td> </tr> <tr> <td>testbench_01_furniture_low_concrete</td> <td>Same as low but with concrete furniture</td> </tr> <tr> <td>testbench_01_furniture_mid_concrete</td> <td>Same as mid but with concrete furniture</td> </tr> <tr> <td>testbench_01_furniture_high_concrete</td> <td>Same as high but with concrete furniture</td> </tr> <tr> <td>testbench_01_rotated_anchors</td> <td>Same as testbench_01 but the anchors have been rotated clockwise by 5 degrees</td> </tr> <tr> <td>testbench_01_translated_anchors</td> <td>Same as testbench_01 but the anchors have been translated by 10cm</td> </tr> </tbody> </table> </td> </tr> </tbody> </table> <p><br> For each room setup, data is split into 12 json files - 6 for the tag signal data collected from the 4 anchor points and 6 for the properties of each anchor point. The 6 different files correspond to the different channel-polarization combinations as indicated by their names. </p> <p>Each entry of the anchor json files contains the following information:</p> <ul> <li>anchor: anchor's index</li> <li>x_anchor, y_anchor, z_anchor: anchor point's coordinates</li> <li>az_anchor: anchor's horizontal rotation</li> <li>el_anchor: anchor's vertical rotation</li> <li>reference_power: received signal strength (RSS) reference value in dB</li> </ul> <p>Each entry of the tag json files contains the following information:</p> <ul> <li>anchor: anchor's index</li> <li>point: point's index</li> <li>x_tag, y_tag, z_tag: tag point's coordinates</li> <li>los: point is in line of sight of anchor {0=false,1=true}</li> <li>relative power: RSS value in dB</li> <li>pdda_input_real: in-phase components of the anchor's antennas' measurements</li> <li>pdda_input_image: quadrature-phase components of the anchor's antennas' measurements</li> <li>pdda_phi: pdda prediction for azimuth angle</li> <li>pdda_theta: pdda prediction for elevation angle</li> <li>pdda_out_az: pdda's spatial power spectrum for azimuth angle</li> <li>pdda_out_el: pdda's spatial power spectrum for elevation angle</li> <li>true_phi: actual azimuth angle</li> <li>true_theta: actual azimuth angle</li> </ul>
Twindroid - System calls traces - Android apps
<p>TwinDroid - a dataset of over 10 000 system calls traces, from both benign and infected Android apps. A large part of the dataset is composed of traces from pairs of benign and infected apps.</p> <p>For more traces you can visit https://zenodo.org/record/6465271#.Yls3F1yZNH4</p> <p>To trace Android application, you can use our script in https://github.com/RaphaelKhoury/automated-apk-tracing</p>
Quantitative assessment of trace and macro element compositions of Cassava (Manihot esculenta) storage roots enriched with Β-Carotene as influenced by genotypes and growing locations
Cassava's important mineral contents depends on some factors, including genetic and growing locational factors. The study aimed to evaluate the influence of genotype and growing locations on the mineral concentrations in yellow-fleshed cassava root genotypes. Twenty-five pipeline yellow-fleshed cassava genotypes and three white-fleshed varieties (check samples) were planted at five different experimental fields for two seasons, each representing the major agroecological zones in Nigeria. Standard laboratory protocols were employed in the sampling to ensure zero contamination, and the trace and macro elements were determined using the inductively coupled plasma optical emission spectroscopic method (ICPOES). The trace and macro elements identified in all the genotypes and varieties investigated were Fe, Mn, B, Cu, Mo, Co, Ni, Zn, and Al; Ca, Mg, Na, K. P, and S respectively. Genotype and growing location had a highly significant (p < 0.05) effect on all the trace elements except Ti and Cr. However, there was no interactive effect between genotype and growing location on all the trace elements except for Pb and Zn. Among the explanatory variables, the variable growing location was the most influential on macro and trace elements. Conclusively, genotypes 01/1442 and 01/1273 have outstanding trace and macro element concentrations.
Evaluating the use of hair as a non-invasive indicator of trace mineral status in woodland caribou (Rangifer tarandus caribou)
<p>Trace mineral imbalances can have significant effects on animal health, reproductive success, and survival. Monitoring their status in wildlife populations is, therefore, important for management and conservation. Typically, livers and kidneys are sampled to measure mineral status, but biopsies and lethal-sampling are not always possible, particularly for Species at Risk. We aimed to: 1) determine baseline mineral levels in Northern Mountain caribou (<em>Rangifer tarandus caribou</em>; Gmelin, 1788) in northwestern British Columbia, Canada, and 2) determine if hair can be used as an effective indicator of caribou mineral status by evaluating associations between hair and organ mineral concentrations. Hair, liver, and kidney samples from adult male caribou (n<sub>Hair</sub>= 31; n<sub>Liver</sub>, n<sub>Kidney</sub>= 43) were collected by guide-outfitters in 2016-2018 hunting seasons. Trace minerals and heavy metals were quantified using inductively-coupled plasma mass spectrometry, and organ and hair concentrations of same individuals were compared. Some organ mineral concentrations differed from other caribou populations, though no clinical deficiency or toxicity symptoms were reported in our population. Significant correlations were found between liver and hair selenium (rho=0.66, p<0.05), kidney and hair cobalt (rho=0.51, p<0.05), and liver and hair molybdenum (rho=0.37, p<0.10). These findings suggest that hair trace mineral assessment may be used as a non-invasive and easily-accessible way to monitor caribou selenium, cobalt, and molybdenum status, and may be a valuable tool to help assess overall caribou health.</p>
Supplementary Material 1 : Monitoring Hydrothermal Activity Using Major and Trace Elements in Low-Temperature Fumarolic Condensates, The Case of La Soufriere de Guadeloupe Volcano, by Inostroza et al.
<p>Supplementary Material 1 - Monitoring hydrothermal activity using major and trace elements in low-temperature fumarolic condensates, the case of La Soufriere de Guadeloupe volcano, by Manuel Inostroza, Séverine Moune, Roberto Moretti, Vincent Robert, Magali Bonifacie, Elodie Chilin-Eusebe, Arnaud Burtin, Pierre Burckel</p>
Monte Carlo ray tracing code and simulations for photons scattered by an optically thin slab
<p>This directory contains code and data used to simulate photon path length distributions in an optically thin slab.<br> This material was used to prepare the manuscript "Photon Path Distributions in Optically Thin Slabs" by Quentin Libois and Anthony B. Davis, submitted to Optics Express</p>
Terminus Traces for publication 'Ocean-forcing and glacier-specific factors drive differing glacier response across the 69 oN boundary, east Greenland' (Version 1)
<p>Dataset supporting publication 'Brough, S., Carr, J.R., Ross, N., Lea, J.M. (2023) Ocean-forcing and glacier-specific factors drive differing glacier response across the 69 <sup>o</sup>N boundary, east Greenland. J. Geophys. Res. Earth Surf. <a href="https://doi.org/10.1029/2022JF006857">https://doi.org/10.1029/2022JF006857</a>.'</p> <p>This dataset provides GIS ready shapefiles of mapped terminus traces for 24 east Greenland glaciers between 2013 and 2020 for the aforementioned publication. Data are provided in both geographic (EPSG: 4326; WGS84) and projected (EPSG:3413; NSIDC Sea Ice Polar Stereographic North) coordinate systems. As each terminus trace has metadata appended, including the unique path identifier, it is possible to directly and easily identify the original image used in the mapping process. Both shapefiles are compatible for ingestion into the Google Earth Digitisation Tool (GEEDiT) Reviewer (<a href="https://liverpoolgee.wordpress.com/">https://liverpoolgee.wordpress.com/</a>) for reviewing and sub-setting the dataset (see Lea, J.M. [2018] Earth Surf. Dynam. 6, 551–561. <a href="https://doi.org/10.5194/esurf-6-551-2018">https://doi.org/10.5194/esurf-6-551-2018</a>).</p> <p> </p> <p>When using this data product in a publication, please include the following citations:</p> <p>Brough, S., Carr, J.R., Ross, N., Lea, J.M. (2023). Terminus Traces for publication 'Ocean-forcing and glacier-specific factors drive differing glacier response across the 69 <sup>o</sup>N boundary, east Greenland' (Version 1) [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.6904219">https://doi.org/10.5281/zenodo.6904219</a>.</p> <p>Brough, S., Carr, J.R., Ross, N., Lea, J.M. (2023) Ocean-forcing and glacier-specific factors drive differing glacier response across the 69 <sup>o</sup>N boundary, east Greenland. J. Geophys. Res. Earth Surf. <a href="https://doi.org/10.1029/2022JF006857">https://doi.org/10.1029/2022JF006857</a>.</p>
First responders' mobile phone traces during a search-and-rescue exercise scenario
<p>This dataset is collected during a search-and-rescue exercise scenario in the framework of the ARTION project. </p> <p>The operation took place on the 22nd of May 2022 in Paphos district (near the beach at Mandria village). The exercise was organized and conducted by the Cyprus Civil Defence and data collection was performed by the KIOS Research and Innovation Center of Excellence of the University of Cyprus. </p> <p>The data is saved in an .xlsx file. It consists of 9 first responders' traces captured during a search-and-rescue operation. The responders were moving on foot holding their mobile phones, which were used for capturing their traces. By means of the ARTION mobile app, the locations of the mobile phones were captured by the build-in GPS receiver of the phone approximately every 5 seconds. </p> <p> </p> <p> </p>
Manually mapped traces from UAV-acquired images of Loviisa shoreline outcrops
<p>This dataset contains manually mapped two-dimensional bedrock fracture traces from shoreline outcrop orthomosaics generated from UAV-acquired images (https://doi.org/10.5281/zenodo.7077518). The outcrops are located along the shoreline of Loviisa, South-East Finland. Mapping has been done in ArcGIS with snapping toggled on to document the topological abutment relationships between traces.</p> <p>Data is published as ESRI Shapefiles in the ETRS-TM35FIN (EPSG:3067) coordinate system. </p> <p>The work in manual mapping was done as part of a Geological Survey of<br> Finland project, KYT KARIKKO, with funding from Finnish National Nuclear Waste<br> Management Fund (KYT) during the years 2019 and 2020.</p> <p>This dataset has been previously used as part of a Master's Thesis, which can be located here: <a href="https://urn.fi/URN:NBN:fi-fe202003259211">https://urn.fi/URN:NBN:fi-fe202003259211</a>, and in a Journal of Structural Geology article (OG1 target area), located here: https://doi.org/10.1016/j.jsg.2021.104304.</p>
Automatically mapped traces from UAV-acquired images of Loviisa shoreline outcrops
<p>This dataset contains automatically mapped two-dimensional bedrock fracture traces from shoreline outcrop orthomosaics generated from UAV-acquired images (https://doi.org/10.5281/zenodo.7077518). The outcrops are located along the shoreline of Loviisa, South-East Finland. Code for automatic mapping is available on GitHub (https://github.com/nialov/ALSA).</p> <p>Data is published as ESRI Shapefiles in the ETRS-TM35FIN (EPSG:3067) coordinate system. </p> <p>The work in automatic mapping was done as part of a Geological Survey of<br> Finland project, Kallioperän Rikkonaisuus, during 2021-2022.</p>
Decoding the metabolic response of Escherichia coli for sensing trace heavy metals in water
<p>As: Raman spectra from E. coli lysate sample after exposing to As in DI water</p> <p>Cr: Raman spectra from E. coli lysate sample after exposing to Cr in DI water</p> <p>As_TapWater: Raman spectra from E. coli lysate sample after exposing to As in tap water</p> <p>WasteWater_FineTune_Dataset: Raman spectra from E. coli lysate sample after exposing to As in waste water</p> <p>WasteWater 'Unknow' Dataset: Raman spectra from E. coli lysate sample after exposing to waste water</p>
Code used in exporting calcium imaging data from raw traces for Veit et al. 2022
<p>This contains scripts and functions used in extracting stimulus responses from raw calcium imaging traces stored in HDF5 format. Note the current version does not contain the HDF5 files with raw traces.</p>
Tracings of root centreline
<p>Root Trajectories grown under 0 - 0.5 and 1 MPa</p>
COD: A Dataset of Commercial Building Occupancy Traces
<p>The Commercial Occupancy Dataset (COD) is a high-resolution long-term dataset of occupancy traces in a commercial office building spanning 9 months and covering room-level occupancy for three different spaces (two conference rooms and one open-plan space) containing more than 90,000 enter/exit events over this time period. Occupancy data in a building contains rich spatial-temporal information about the users and their usage of the space and facilities. However, obtaining accurate occupancy data is a very challenging task due to the limitation of existing sensing technologies. A novel depth-imaging based solution to estimate occupancy counts was deployed in four doorways of an office building to generate the dataset. We envision the dataset being used for diverse applications such as building energy simulation, occupancy modeling and human-in-the-loop HVAC control which enhance energy efficiency and human comfort.</p> <p>Each folder in the dataset represents data from a single building. Inside the folder there will be separate comma-separated value (CSV) files, one for each monitored room within the building. Each CSV file contains an entry for every entrance and exit events that was estimated by the sensor(s) corresponding to the room in question. In turn, each one of these entries in the dataset (i.e., each line in the file) contains three fields in this order: date (m/dd/yy), time (HH:MM:SS) and occupancy count. </p>
Nearness sensing and interest traces
<p>performed with psychology students, in two different institutions, where the purpose was to study interest influence in psychological proximity. NSense has been installed in Android smartphones carried by a population of 50 students of the two different universities, numbered User1 to User50. The students carried NSense around during their daily routines, for 2 days: 05.04.2017-06.04.2017. The readings obtained show a total of 15 students out of the original universe of 50. The traces collected comprise the following fields: - date: DD/MM HH:mm - own_device_name: unique identifier of the device, Userx - connected_device_name: peer observed via Wi-Fi Direct (range of 0 to 100 meters) at date. - latitude, longitude: GPS coordinates of the device - distance: relative distance computed in meters via Wi-Fi Direct. - sound: discrete value for the surrounding sound activity: ALERT, NORMAL, QUIET - physical activity: discrete value for the type of activity (MOVING or STATIONARY) - tct: total contact time. Starts counting after 1 day of use. Corresponds to the sum of contact duration between i and j on a time window of duration h. - social_strength_minute: level of social interaction derived from our work NSense: A People-centric, non-intrusive Opportunistic Sensing Tool for Contextualizing Social Interaction, IEEE Healthcom2016.Social strength of node i towards node j, in a specific hourly sample h, for day d. Node i computes the social strength towards j by adding the different weighted ADs. t has been set for 24 hours - si: Social interaction of node i towards j, computed at instant t - p: propinquity: measures the probability of social interaction occurring over time. - ema_cd. Exponential moving average of the total contact duration between nodes i and j - additional columns: types of interests defined in NSense.</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.