Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
10,553
datasets available to search
ShareScore release 0.7.1
Dataset results
10,553 results for “measurements”
Datasets for "Precision and accuracy of single-molecule FRET measurements – a multi-laboratory benchmark study"
<p>Supplementary material (raw data) for Fig. 2 in "<strong>Precision and accuracy of single-molecule FRET measurements – a multi-laboratory benchmark study</strong>" to be published with Nature Methods</p> <p>The confocal data is given in ht3 and hdf5 format.</p> <p>For the TIRF data the original TIFF-stacks are uploaded including the calibration files.</p>
Review of Recent Trends in Measuring the Computing Systems Intelligence-igure 2. Intelligence of different living creature (accessed 01.11.2017). 2.1. A crow solving a complex task (https://www.disclose.tv/spooky-genius-crow-had-to-be-removed-from-scientific-experiment- 314886). 2.2. A group of dolphins with a social behaviour (http://www.sciencemag.org/news/2012/04/teamwork-builds-big-brains); 2.3. An orangutan that use a spear to fish (https://primatology.net/2008/04/29/orangutan-photographed-using-tool-as-spear-to-fish)
<p>Some species of birds have been shown capable of using different tools. Many studies consider the crows as very intelligent. Smirnova, Lazareva, and Zorina (2000) suggested that crows have some kind of numerical ability. Figure 2.1 presents a crow that uses a tool, a small stone in order to catch a worm from a glass of water.The dolphins in many studies are considered intelligent at the individual level. An advanced ability of dolphins is the self-awareness. Marten and Psarakos (1995) presented an interesting study based on self-view television to distinguish between self-examination and social behavior in the Bottlenose dolphin. The most well-known abilities of dolphins are to teach, learn and cooperate. Dolphins have a complex communication and social behaviour. Figure 2.2 presents the image of a common group of dolphins. Some studies prove that primates are one of the most intelligent in the class of animals (Reader, Hager, & Laland, 2011). Orangutans are one of the most intelligent primates. The ability of orangutans to use different types of tools in order to perform tasks is well-known. Figure 2.3 presents an orangutan that uses a spear to catch fish. The orangutans can be considered intelligent at individual level.</p>
Review of Recent Trends in Measuring the Computing Systems Intelligence-Figure 1. Intelligence of different simple living creature (accessed 01.11.2017). 1.1. A carnivorous plants catching an insect (https://phys.org/news/2016-05-colombia-peace-reveal-jungle-species.html); 1.2. A colony of ants solving a very complex task (https://mappingignorance.org/2016/05/27/rafting-ants); 1.3. The collective behaviour of a school of fish (https://simple.wikipedia.org/wiki/Shoaling_and_schooling)
<p>The biological intelligence of different life forms, ranging from very simple (such as plants) to very complex (such as humans) is the subject of many studies and a large amount of research. Frequent studies related to different kind of biological intelligence include: the intelligence of horses (Krueger, & Heinze, 2008; Krueger, Farmer, & Heinze, 2014; Schuetz, Farmer, & Krueger, 2016), intelligence of pigs (Broom, Sena, & Moynihan, 2009), intelligence of dogs (Coren, 1995), intelligence of primates (Reader, Hager, & Laland, 2011) and so one. Figures 1, 2, and 3 present some biological life forms that are frequently considered intelligent. Trewavas (2002; 2005) considered that plants intelligence should be based on principles such as their ability to adjust their morphology, and phenotype accordingly to ensure self- preservation and reproduction. Figure 1.1 presents an intelligent plant (carnivorous) that uses a strategy for catching very fast flying insects. In order to eat the insect, it makes a movement. Figure 1.1 presents the catching of an insect by a carnivorous plant. The intelligence of colonies of ants, termites and other insects that live in large colonies is considered at the colony level (Brady, Fisher, Schultz, & Ward, 2014; Johnson, Borowiec, Chiu, Lee, Atallah, & Ward, 2013). Figure 1.2 presents the coherent intelligent surviving behaviour of a colony of a species of ants. The ants make a structural reorganization in order to move on the surface of the water. Figure 1.3 presents a very large school of fish with an intelligent coherent collective feeding and self-protecting behaviour. Each individual fish has a very simple behavior. Based on this it cannot be considered intelligent. The intelligence in large schools of fish emerges at the collective level (Shaw, 1978; Parrish, Viscedo, & Grunbaum, 2002).</p>
Review of Recent Trends in Measuring the Computing Systems Intelligence-Figure 4. Intelligent robots (accessed 01.11.2017). 4.1. Erica, a humanoid robot (https://www.tech-review.com/erica-is-the-latest-japanese-robot-with-human-appearance.html). 4.2. Atlas, a bipedal humanoid robot developed by Boston Dynamics (https://en.wikipedia.org/wiki/Atlas_(robot))
<p>One of the most highly quoted and interesting definitions of machine intelligence was presented by Alan Turing (1950). Turing considered a computing system intelligent if a human assessor could not decide the nature of the system (being human or artificial) based on questions asked from a room hidden from a human assessor. Until recently there were performed different discussions and comments on the Turing test. Hernández-Orallo (2000) presents an interesting study related to the Turing Test. Dowe and Hajek, (1998) propose a computational extension of the Turing Test. The design and development of intelligent systems are historically very recent. But, even if the advance of hardware and software is very fast, it will take a longer time until the artificial computing systems will attain a similar intelligence with the humans. Based on this fact, we consider that is not appropriate to formulate the problem of the direct comparison at a general level of human intelligence with the machine intelligence. Different definitions were proposed for the intelligence of the agents (Russell, & Norvig, 2003; Iantovics, & Zamfirescu, 2013). Many authors (Russell, & Norvig, 2003; Iantovics, 2005) argue that the intelligence of the agents cannot be defined universally. The impossibility to give a universal definition to the human intelligence is based mostly on the enormous complexity of the human brain and complexity of the human thinking and decision making. Similarly, we may consider the impossibility of universal definition of intelligence of the agents based on the very large variety (by type and complexity) of intelligent agents. The machine intelligence frequently is defined based on different abilities such as (Iantovics, 2005; Sharkey, 2006): autonomous learning, self-adaptation, and evolution. These principles of considering the intelligence are inspired by biological life forms able to learn autonomously during their life cycle, to adapt to the environment and to evolve during more generations. We would like to outline that not all the designed agents are intelligent. There is not a required property of an agent to be intelligent.</p>
Review of Recent Trends in Measuring the Computing Systems Intelligence-Figure 5. What machine intelligence is (accessed 01.11.2017) http://www.ibmbigdatahub.com/blog/measuring-artificial-intelligence-quotient)
<p>There are many developed cooperative systems composed of very simple agents that at the system’s level are considered intelligent. Yang, Galis, Guo, and Liu (2003) presented an intelligent cooperative mobile multiagent system composed of simple reactive agents. The mobile agents are specialized in a computer network administration. They are endowed with knowledge retained as a set of rules which describe network administration tasks. The multiagent system could be considered intelligent based on the fact that it simulates the behavior of a human network administrator. In some cooperative systems, the member agents can organize themselves into cooperative coalitions/groups. Each coalition being able to solve cooperatively problems. Iantovics and Zamfirescu (2013) presented such an adaptive cooperative multiagent system, able to reorganize autonomously the coalitions in order to solve more intelligently problems. The biological and artificial intelligence are by a completely different type (Figure 5). Recently, the biological intelligence is the source of inspiration for the development of many intelligent artificial systems and different problem-solving algorithms.</p>
Abstractions and exemplars: the measure noun phrase alternation in German
<p>This is the data set and scripts used in "Abstractions and exemplars: the measure noun phrase alternation in German" as accepted for publication in Cognitive Linguistics as of 29 may 2018.</p> <p>In this paper, an alternation in German measure noun phrases is examined under a varying-abstraction perspective. In a specific measure NP construction, the embedded kind-denoting noun either agrees in case with the measure noun ("eine Tasse guter Kaffee" 'a cup of good coffee') or it stands in the genitive ("eine Tasse guten Kaffees"). Each of the two alternants is syntactically similar to a non-alternating construction. I propose a prototype model which assigns a common prototypical meaning to each of the alternants and its corresponding non-alternating construction. Based on this, I argue that lexical, morpho-syntactic, and stylistic features help to predict the choice of the alternant. A large corpus study is presented which supports this analysis. However, in addition to the prototype effects, an exemplar effect is also shown to influence the choice, namely the relative frequencies with which lemmas occur in the non-alternating constructions. I argue that allowing both prototype and exemplar effects is more adequate than following radical prototype or exemplar approaches. It is also verified in two experiments that the corpus-derived model corresponds to the behaviour of native speakers. The weak effect size of the experimental validation is discussed in the context of corpus-based cognitive linguistics and the validation of corpus-derived models.</p>
Coupled High Frequency Measurements of Swash Sediment Transport and Morphodynamic data set produced at the CIEM flume, Hydralab IV
<p>The data set here presented aims to increase the understanding of the nearshore sediment dynamics. The experiments aimed at obtaining high quality data of hydrodynamics, sediment concentration and beach-face evolution with an intra-wave time scale. The specific objectives of CoSSedM access project were i) to obtain information of the effect of the wave group periods on the beach morphological evolution; ii) To obtain detailed sediment transport information at the inner surf and swash zones with different bi-chromatic wave conditions and iii) To obtain intra-wave measurements of beach-face evolution.</p> <p>The present work was developed in the framework of the HYDRALAB IV Transnational Access projects. The experiments were carried out in the large scale wave flume CIEM at Universitat Politècnica de Catalunya (UPC), Barcelona. This is a wave flume 100 m long, 3 m wide, and 4.5 m deep. The working water depth was at around 2.5 m over the horizontal flume section and was varied slightly depending on the wave test. A beach was installed made of commercial well-sorted sand (d50 = 0.25 mm) with an overall mean beach gradient of approximately 1:15.</p> <p>Due to its size, the data set can not be placed on this repository and will be provided on demand. Please contact with the authors or with the data manager of the CIEM installation.</p> <p>More information can be found on the published papers:</p> <p>Alsina, J.M., Padilla, E.M. and Cáceres, I., 2016. Sediment transport and beach profile evolution induced by bi-chromatic wave groups with different group periods. Coastal Engineering, Vol. 114, 325-340.</p> <p>Van der Zanden, J.; Alsina, J.; Caceres, I.; Buijsrogge, R. H.; Ribberink, J. , 2015. Bed level motions and sheet flow processes in the swash zone : observations with a new conductivity-based concentration measuring technique (CCM+) . Coastal Engineering, Vol. 105, 47-65.</p>
Photoplethysmography in dogs and cats: selection of measurement sites for pet monitor
<p>The PPG measurements of the study Cugmas et al, 2018.</p> <p>Notes.txt include all information about the dataset.</p>
High-throughput poly(A) length measurement of HeLa and NIH 3T3 cells using TAIL-seq with MiSeq
<p>This dataset contains the full raw data directory from Illumina MiSeq generated for Chang et al. (2014, DOI: 10.1016/j.molcel.2014.02.007). Please refer to the original paper and its supplementary materials for further details.</p>
Auditory stream segregation and selective attention for cochlear implant listeners: Evidence from behavioral measures and event-related potentials
<p>Data set generated for the study "Auditory stream segregation and selective attention for cochlear implant listeners: Evidence from behavioral measures and event-related potentials" </p> <ol> <li><strong>behavioral.txt</strong>: d' scores obtained by the listeners on the deviant detection task. <ul> <li>subject: listener ID</li> <li>distractor: Electrode separation condition</li> <li>deviant: Deviant triplet</li> <li>d: d' scores</li> <li>exp: experimental session (BEH / ERP)</li> </ul> </li> <li><strong>ERP_by_condition.txt</strong>: <ul> <li>Subject: listener ID</li> <li>Type: Sound type (Target / Distractor)</li> <li>Dev: Deviant condition. Early = deviant triplets 1 or 2. Late = deviant triplet 3 or <em>none.</em></li> <li>rep: Triplet number</li> <li>sound: sound number within the triplet</li> <li>amplitude: amplitude difference between the active and the passive listening conditions.</li> </ul> </li> </ol> <p> </p>
Ammonia emission measurements of an intensively grazed pasture - Dataset
<p>Dataset presented and referenced in the corresponding Biogeosciences publication by Voglmeier et al. (2018) [see Related identifiers]. The dataset results from a field experiment in Posieux, Switzerland. During that experiment ammonia emissions of two pasture systems were measured over an entire grazing season in 2016. The spreadsheet file contains half-hourly values of measured ammonia concentration data, computed ammonia emissions, weather and turbulence data. Additionally the calculated nitrogen in the excretion of the cows and the grazing management is given. Detailed information on the measurement methods and the data evaluation is presented in Voglmeier et al. (2018).</p>
Time-averaged simulation results and in vivo measurements to show the impact of red blood cells on the flow field in the cortical microvasculature
<p>The dataset contains 5 files. 4 of them are time-averaged results of blood flow simulations with discrete red blood cell (RBC) tracking in realistic microvascular networks. The 5th file contains median values of RBC velocity measurements at capillary bifurcations in the somatosensory cortex of the mouse.</p> <p>Further notes on the simulation results:<br> - The realistic microvascular networks are from the mouse parietal cortex and have first been published in Blinder et al., 2013, Nature Neuroscience (<a href="https://doi.org/10.1038/nn.3426">https://doi.org/10.1038/nn.3426</a>).<br> - The numerical model to simulate blood flow in realistic microvascular networks has been described in Schmid et al., 2017, PLOS Computational Biology (<a href="https://doi.org/10.1371/journal.pcbi.1005392">https://doi.org/10.1371/journal.pcbi.1005392</a>).<br> - MVN1 and MVN2 stands for microvascular network 1 and 2, respectively.<br> - wRBCs and wpPs stands for 'with red blood cells' and 'with passive particles'. These terms describe two different numerical models: The wRBC-model accounts for all RBC related flow phenomena. The wpP neglects the phase-separation and the Fahraeus-Lindqvist effect, i.e. RBCs and flow are decoupled. Further details are available from Schmid et al. (2019, <a href="https://doi.org/10.1371/journal.pcbi.1007231">https://doi.org/10.1371/journal.pcbi.1007231</a>)</p> <p><strong>File format: </strong>pickle (Python)</p> <p><strong>Files 1 - 4 </strong>(Time-averaged simulation results):<br> Filenames: MVN1_wpPs.tar.bz2, MVN2_wpPs.tar.bz2, MVN1_wRBCs.tar.bz2, MVN2_wRBCs.tar.bz2</p> <p>Each compressed folder contains two files:<br> <br> edgesDict.pkl: dictionary with edge/vessel related data: </p> <ul> <li>flow: Flow rate in vessel [um^3/ms]</li> <li>length: Vessel length [um] (Tortuosity is considered)</li> <li>htt: Tube hematocrit in vessel [-]</li> <li>diameter: Effective vessel diameter [um]</li> <li>connectivity: Vertex indices, e.g. start and end vertex of the corresponding vessel</li> </ul> <p>verticesDict.pkl: dictionary with vertex/bifurcation related data:</p> <ul> <li>index: Index of the current vertex </li> <li>coords: Coordinates to describe the position of the vertex [um]</li> <li>pressure: Pressure at the vertex [mmHg]</li> </ul> <p> </p> <p><strong>File 5</strong> (in vivo RBC velocity measurements):<br> Filename: measurementDict.pkl</p> <p>keys:</p> <ul> <li>divergent_d1: divergent bifurcation, RBC velocity measurement in daughter vessel 1</li> <li>divergent_d2: divergent bifurcation, RBC velocity measurement in daughter vessel 2</li> <li>convergent_m1: convergent bifurcation, RBC velocity measurement in mother vessel 1</li> <li>convergent_m2: convergent bifurcation, RBC velocity measurement in mother vessel 2</li> </ul> <p><br> Data structure: list of list,<br> e.g. daughter vessel 1:<br> [[bif.1 - measure.1, bif.1 - measure.2, bif.1 - measure.3], [bif.2 - measure.1, bif.2 - measure.2, bif.2 - measure.3],...]<br> bif.: bifurcation, measure.: measurement.<br> The order of bifurcations is the same for 'divergent_d1' and 'divergent_d2' (and for 'convergent_m1' and 'convergent_m2'). </p> <p> </p>
A ferrofluid-based sensor to measure bottom shear stresses under currents and waves. Data set: VelocityProfilies_2018_Musumarra
<p>The experimental campaign was devoted to study the velocity profile inside the small scale flume for several bottom configurations. In particular, the following configurations were considered: thin sand (D<sub>50</sub>=0.25 mm); coarse sand (D<sub>50</sub>=0.56 mm); mixed sand: 10% coarse sand and 90% thin sand; mixed sand: 20% coarse sand and 80% thin sand; mixed sand: 30% coarse sand and 70% thin sand; mixed sand: 40% coarse sand and 60% thin sand; small gravel (diameter between 3 and 5 mm); gravel (diameter between 9 and 14 mm); small gravel and thin sand; gravel and thin sand.</p>
Compressive Strength of Model Ice Measurements
<p>This data package contain a detailed measurement report and the measurements data from the mechanical property measurements conducted in HSVA Large Ice Tank.<br>This work is part of HYDRALAB+ Adaptation for Climate Change – project that was supported by the European Community's Horizon 2020 Programme through the <br>grant to the budget of the Integrated Infrastructure Initiative HYDRALAB+, Contract no. 654110. The measurements are a part of the deliverable D9.5 Collection of Benchmark data sets of Joint Research Activities (JRA) 2 – COMPLEX (Cross disciplinary Observations of Morphodynamics and Protective structures, Linked to Ecology and eXtreme events) within Hydralab+ project.</p> <p>The focus of the tests was to provide compressive strength measurement data when the target flexural strength and aspect ratio (length to width ratio) is varied. The Young's modulus, flexural strength, salinity, and density are reported along previous lines. Additionally, the measurement data, raw and filtered, from the compressive strength measurements is provided. The provided measurement data was saved in ASCII format in .txt files. The files are named according to the number of the test, 001.txt etc. The first column in the files is the time stamp in seconds. The second column is the raw unfiltered data in Newtons. The third column is the filtered measurement data in Newtons.</p>
Data and results for manuscript: "Imaging and functional characterization of crop root systems using spectroscopic electrical impedance measurements"
<p>This package contains measured raw EIT data, electrical imaging results, spectral results from the Debye decomposition, and the Python scripts used to generate the plots in the manuscript titled:<br> <br> Imaging and functional characterization of crop root systems using spectroscopic electrical impedance measurement</p>
Fig. 6. Female genital morphology. See Table 1 for localities and Table 3 for measurements. A in Cochlostoma revised: the subgenus Lovcenia Zallot et al., 2015 (Caenogastropoda, Cochlostomatidae)
Fig. 6. Female genital morphology. See Table 1 for localities and Table 3 for measurements. A. Cochlostoma (Lovcenia) erika (A.J. Wagner, 1906) (HNHM 86387). B. Cochlostoma (Lovcenia) dalmatinum (L. Pfeiffer, 1863) (NHMW 110430/MN/0162). C. Cochlostoma (Lovcenia) tropojanum sp. nov. (NHMW 111248). D1. Cochlostoma (Lovcenia) jakschae sp. nov., Bugarska Peak population (NHMW 111249). D2. Cochlostoma (Lovcenia) jakschae sp. nov., Pejë Pass population (HNHM 97221). E. Cochlostoma (Lovcenia) lanatum sp. nov. (HNHM 99861).
ESA SEOM-IAS – Measurement and ACS database SO2 UV region
<p>The database contains measurements and absorption cross sections generated within the framework of the ESA project SEOM-IAS (Scientific Exploitation of Operational Missions - Improved Atmospheric Spectroscopy Databases), ESA/AO/1-7566/13/I-BG. Details on the project can be found at http://www.wdc.dlr.de/seom-ias/.</p> <p>The measurements were recorded at the German Aersopace Center (DLR) to provide a new absorption cross section database for SO2 according to the needs of the TROPOMI instrument aboard the Sentinel 5-P satellite. The data are compiled in two zip files, one for the measurements (SO2_UV_region_measurement_database_20112018.zip), one for the absorption cross sections (SO2_UV_region_absorption_cross_section_database_20112018.zip) and a readme file (ESA_SEOM_IAS_spectra_SO2UVRegion_readme.docx).</p>
Multimodal optical measurement for study of lower limb tissue viability in patients with diabetes mellitus
<p>According to the International Diabetes Federation, the challenges of early stage diagnosis and treatment effectiveness monitoring in diabetes is currently one of the highest priorities in modern healthcare. In this experimental study, the potential of combined measurements of skin fluorescence and blood perfusion by the laser Doppler flowmetry method in diagnostics of low limb diabetes complications was evaluated. With the use of Monte Carlo probabilistic modelling, the diagnostic volume and depth of the diagnosis were evaluated. The experimental study involved 76 patients with type 2 diabetes mellitus. These patients were divided into two groups depending on the degree of complications. The control group consisted of 48 healthy volunteers. The local thermal stimulation was selected as a stimulus on the blood microcirculation system. Experimental studies have shown that diabetic patients have elevated values of normalised fluorescence amplitudes, as well as a lower perfusion response to local heating. In the group of people with diabetes with trophic ulcers, these parameters also significantly differ from the control and diabetes only groups. Thus, the intensity of skin fluorescence and level of tissue blood perfusion can act as markers for various degrees of complications from the beginning of diabetes to the formation of trophic ulcers.</p>
Snow depth and density measurements with different snow core samplers in HARMOSNOW Field Campaigns
<p>The data correspond to snow bulk density and snow depth measured with different snow core sampler in three field campaigns carried out in mountains of Turkey, Iceland and Finland in order to assess the uncertainty of using different snow core samplers and different observers. The field campaigns were carried out in the frame of the COST project HARMOSNOW ES1404 <a href="http://harmosnow.eu/">http://harmosnow.eu/</a></p>
Robot navigation measurements driving in and out of the van
<p>This dataset is a rosbag which contains the laser scans and the pose of a Husky mobile robot, using the robot's odometry and two SICK S300 laser scans to navigate.</p> <p><strong>List of available topics:</strong></p> <ol> <li>/colrobot/hardware/scan_pointcloud</li> <li>/colrobot/navigation/perfect_match/debug/LaserScanfiltered</li> <li>/colrobot/navigation/perfect_match/LocalisationPoseResult</li> <li>/colrobot/navigation/map</li> <li>/tf</li> <li>/tf_static</li> </ol> <p><strong>Topics contents:</strong></p> <ol> <li>Pointcloud containing the merge of the two laser scans </li> <li>Pointcloud containing the laser scans which matched with the given map</li> <li>Robot's pose estimate</li> <li>Map of the van (robot's working area)</li> <li>6. Transforms of the system</li> </ol>
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.