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129 results for “journal analysis”
BRAIN Journal-Sentiment Analysis on Embedded Systems Blended Courses-Figure 1. Semantria result
<p>In Figure 1 the Semantria output is presented, having a positive polarity, with a score of 0.218. What is interesting to note here are the keywords extracted from students’ feedback. They noticed the integration of MOOCs in the Embedded Systems course as positive due to the fact that the new information is perceived as easier and the gained knowledge seems to be valuable. Students are affected by too many concepts and also by the idea of paying for the course.</p>
BRAIN Journal-Novel Detection Features for SSVEP Based BCI: Coefficient of Variation and Variation Speed-Figure 1: Time vs frequency analysis of 10 Hz SSVEP response
<p>The stability of the SSVEP signal was examined by using wavelet analysis (Wu and Yao 2008). Since there is a trade-off between time and frequency resolution in wavelet analysis, examining the stability of SSVEP with wavelet analysis is getting harder in systems where the visual stimulus frequencies are close to each other, as shown in Figure 1. </p>
Codes and data related to the article: Renard et al. Floods and Heavy Precipitation at the Global Scale: 100-year Analysis and 180-year Reconstruction. Journal of Geophysical Research - Atmospheres.
<p>This package contains R codes and data related to the article:</p> <p>B. Renard, D. McInerney, S. Westra, M. Leonard, D. Kavetski, M. Thyer and J.-P. Vidal. Floods and Heavy Precipitation at the Global Scale: 100-year Analysis and 180-year Reconstruction. <em>Journal of Geophysical Research - Atmospheres</em>. DOI: <a href="https://doi.org/10.1029/2022JD037908">10.1029/2022JD037908</a></p> <p><strong>Analyses</strong></p> <p>This folder contains the R scripts used to set up models, analyse results and prepare figures. See README file for details.</p> <p><strong>ShinyApp</strong></p> <p>This folder contains an interactive Shiny App to explore the data and the results from the article.</p> <p>An online version can be found at <a href="https://hydroapps.recover.inrae.fr/HEGS-paper">https://hydroapps.recover.inrae.fr/HEGS-paper</a></p> <p> </p>
Data from: Business and publication model of surgical journals: A bibliometric analysis
<p>The dataset contains information about surgical journals included in the SCOPUS database used in our research. The following information is present in the data file:</p> <ol> <li>Title</li> <li>Journal sub-specialty</li> <li>Country Origin</li> <li>Continent</li> <li>SJR</li> <li>Publisher</li> <li>Types of Publisher</li> <li>Publication Model</li> <li>Language</li> </ol>
Data on soil variables (with plot IDs) and grassland species traits used for the analysis of grassland vegetation data by Pillar, V.D. (2024) Trait divergence in plant community assembly is generated by environmental factor interactions. Journal of Vegetation Science, 35, e13259. Available from: https://doi.org/10.1111/jvs.13259
<p>File <a href="../api/records/10983049/draft/files/Plot_IDs_990ua.txt/content" target="_blank" rel="noopener noreferrer">Plot_IDs_990ua.txt</a> contains the IDs of the 1-m2 plots used for the analysis of grassland vegetation data by Pillar, V.D. (2024) Trait divergence in plant community assembly is generated by environmental factor interactions. The plot data are stored in the sPlot database (PPBio South Brazilian Grassland Database).</p> <p>File <a href="../api/records/10983049/draft/files/E_990ua_21SoilVar.txt/content" target="_blank" rel="noopener noreferrer">E_990ua_21SoilVar.txt</a> contains data on soil variables evaluated in the 250 m transects, but here expanded to the 990 1-m2 plots (each transect was sampled using 10 1-m2 pots).</p> <p>File <a href="../api/records/10983049/draft/files/B_769spp_4t.txt/content" target="_blank" rel="noopener noreferrer">B_769spp_4t.txt</a> is the species trait database collected in the framework of several research projects in the Quantitative Ecology Lab (EcoQua) and Grassland Vegetation Studies Lab (LevCamp) of Universidade Federal do Rio Grande do Sul (UFRGS). Data gaps were filled by compiled from the TRY database and data imputation.</p> <p> </p> <p> </p>
Dataset for "Definition and rationale for placebo composition: Cross-sectional analysis of randomized trials and protocols published in high-impact medical journals"
<p>Contains our data extraction sheets</p>
Metadata of the Top 40 Journals in Distance Education: A Bibliometric Analysis of Impact 2018-2022
<p>This file contains metadata from the 40 most impactful journals in the field of distance education, selected through a rigorous bibliometric analysis using the SCImago Journal Rank (SJR) indicator provided by SCImago. Two main criteria guided the selection: the first targeted journals ranked in Q1 and Q2 in the specific category of "e-learning" within the social sciences and education area, highlighting publications that demonstrate high impact and relevance in the academic community according to the selected indicator. The second criterion was based on keyword searches in the journal titles, selecting those that include terms like e-learning, online, Distance Education, Technology Learning, Communications in Information, and Information Education and their variants (e.g., plural), also positioned in Q1 or Q2.</p> <p>The metadata, extracted from the Scopus database, covers publications from the period 2018 to 2022 and includes vital information such as document type, authors' names, article title, journal name, publication year, pages, volume, and issue number. Additionally, each article is identified by a Digital Object Identifier (DOI) and URLs for direct access to the full text online, along with abstracts and keywords. These elements together provide a comprehensive and accessible view of the articles, facilitating bibliometric analyses and related academic research.</p> <p>This compilation serves as an essential resource for researchers and educators interested in understanding the dynamics and development of the field of distance education, offering a solid foundation for future investigations and the formulation of evidence-based educational policies.</p>
Fig. 4 in The correlations between certain features of the journal Neotropical Ichthyology and its impact factor: a comparative analysis at the thematic and national levels
Fig. 4. Uncitedness rate of articles published in the Brazilian journals in Sample 2.
Fig. 1 in The correlations between certain features of the journal Neotropical Ichthyology and its impact factor: a comparative analysis at the thematic and national levels
Fig. 1. Brazilian journals and their corresponding self-cited rates between 2006 and 2011.
Fig. 2 in The correlations between certain features of the journal Neotropical Ichthyology and its impact factor: a comparative analysis at the thematic and national levels
Fig. 2. Brazilian journals and their corresponding self-citing rates between 2006 and 2011.
Dataset for Spence et al., "Availability of study protocols for randomized trials published in high-impact medical journals: cross-sectional analysis" (CITATION)
<p>Contains our extraction sheets (as SAS data files), code to calculate the values in the tables in our manuscript, and a supplemental file with additional notes on methods used in our study.</p>
Additional climate information for research paper «Ecological and Geographical Analysis of Distribution of Heracleum persicum, H. mantegazzianum and H. sosnowskyi on The Northern Limit of Its Invaded Range in Europe» submitted to Russian Journal of Biological Invasions
<p><strong>Additional climate information for research paper «Ecological and Geographical Analysis of Distribution of Heracleum persicum, H. mantegazzianum and H. sosnowskyi on The Northern Limit of Its Invaded Range in Europe» submitted to Russian Journal of Biological Invasions </strong></p>
The Caucasus-Economic and Social Analysis Journal of Southern Caucasus
<p>AGRICULTURAL, ENVIRONMENTAL & NATURAL SCIENCES</p> <p>SOCIAL, PEDAGOGY SCIENCES & HUMANITIES</p> <p>MEDICINE, VETERINARY MEDICINE, PHARMACY AND BIOLOGY SCIENCES</p> <p>TECHNICAL AND APPLIED SCIENCES</p> <p>REGIONAL DEVELOPMENT AND INFRASTRUCTURE</p> <p>ECONOMIC, MANAGEMENT & MARKETING SCIENCES</p> <p>LEGAL, LEGISLATION AND POLITICAL SCIENCES</p>
The Caucasus-Economic and Social Analysis Journal of Southern Caucasus
<p>AGRICULTURAL, ENVIRONMENTAL & NATURAL SCIENCES</p> <p>SOCIAL, PEDAGOGY SCIENCES & HUMANITIES</p> <p>MEDICINE, VETERINARY MEDICINE, PHARMACY AND BIOLOGY SCIENCES</p> <p>TECHNICAL AND APPLIED SCIENCES</p> <p>REGIONAL DEVELOPMENT AND INFRASTRUCTURE</p> <p>ECONOMIC, MANAGEMENT & MARKETING SCIENCES</p> <p>LEGAL, LEGISLATION AND POLITICAL SCIENCES</p>
The Caucasus-Economic and Social Analysis Journal of Southern Caucasus
<p>AGRICULTURAL, ENVIRONMENTAL & NATURAL SCIENCES</p> <p>SOCIAL, PEDAGOGY SCIENCES & HUMANITIES</p> <p>MEDICINE, VETERINARY MEDICINE, PHARMACY AND BIOLOGY SCIENCES</p> <p>TECHNICAL AND APPLIED SCIENCES</p> <p>REGIONAL DEVELOPMENT AND INFRASTRUCTURE</p> <p>ECONOMIC, MANAGEMENT & MARKETING SCIENCES</p> <p>LEGAL, LEGISLATION AND POLITICAL SCIENCES</p>
The Caucasus-Economic and Social Analysis Journal of Southern Caucasus
<p>AGRICULTURAL, ENVIRONMENTAL & NATURAL SCIENCES</p> <p>SOCIAL, PEDAGOGY SCIENCES & HUMANITIES</p> <p>MEDICINE, VETERINARY MEDICINE, PHARMACY AND BIOLOGY SCIENCES</p> <p>TECHNICAL AND APPLIED SCIENCES</p> <p>REGIONAL DEVELOPMENT AND INFRASTRUCTURE</p> <p>ECONOMIC, MANAGEMENT & MARKETING SCIENCES</p> <p>LEGAL, LEGISLATION AND POLITICAL SCIENCES</p>
The Caucasus-Economic and Social Analysis Journal of Southern Caucasus
<p>AGRICULTURAL, ENVIRONMENTAL & NATURAL SCIENCES</p> <p>SOCIAL, PEDAGOGY SCIENCES & HUMANITIES</p> <p>MEDICINE, VETERINARY MEDICINE, PHARMACY AND BIOLOGY SCIENCES</p> <p>TECHNICAL AND APPLIED SCIENCES</p> <p>REGIONAL DEVELOPMENT AND INFRASTRUCTURE</p> <p>ECONOMIC, MANAGEMENT & MARKETING SCIENCES</p> <p>LEGAL, LEGISLATION AND POLITICAL SCIENCES</p>
THE CAUCASUS ECONOMIC & SOCIAL ANALYSIS JOURNAL OF SOUTHERN CAUCASUS
<h2>THE CAUCASUS ECONOMIC & SOCIAL ANALYSIS JOURNAL OF SOUTHERN CAUCASUS</h2>
Metadata of sampling strategy during metabarcoding analysis (Journal publication supplement)
<p>The table presents supplementary materials and contains metadata of sampling strategy during metabarcoding analysis of four types of substrates in two ombrotrophic bog habitats, with other experimental and environmental parameters included in analyses. </p>
Data for Airlines network analysis on an air-rail multimodal system. Journal of Open Aviation Science, 1(2)
<h2>About</h2> <p>This dataset contains all the input data required to generate the analysis and results of the article Delgado, L., Trapote-Barreira, C., Montlaur, A., Bolić, T., & Gurtner, G. (2023). <em>Airlines’ network analysis on an air-rail multimodal system</em>. Journal of Open Aviation Science, 1(2). <a href="https://doi.org/10.59490/joas.2023.7223" rel="nofollow">https://doi.org/10.59490/joas.2023.7223</a></p> <p>The code used is available on GitHub: <a href="https://github.com/UoW-ATM/joas_air_rail_network_analysis">https://github.com/UoW-ATM/joas_air_rail_network_analysis</a></p> <p>The path to the input data can be modified in the scripts provided in the GitHub repository. With the default setting, the input is in a folder called data.</p> <h2>Dataset structure</h2> <ul> <li>data_computed <ul> <li><em>rail_used_emissions.csv</em></li> <li><em>rail_used_emissions_2.csv</em></li> <li><em>routes_emissinos_v2.csv</em></li> </ul> </li> <li>flights_data4 <ul> <li>year=2023 <ul> <li>month=05 <ul> <li><em>1st_week_0523.csv</em></li> </ul> </li> </ul> </li> </ul> </li> <li>renfe <ul> <li>renfe_mid_long <ul> <li><em>agency.txt</em></li> <li><em>calendar.txt</em></li> <li><em>calendar_dates.txt</em></li> <li><em>routes.txt</em></li> <li><em>stops.txt</em></li> <li><em>stop_times.txt</em></li> <li><em>trips.txt</em></li> </ul> </li> </ul> </li> <li><em>aircraftDatabase.csv</em></li> <li><em>airport_static.csv</em></li> <li><em>code_seats.csv</em></li> <li><em>manual_fixed_airports.csv</em></li> <li><em>mat_corrected.csv</em></li> <li><em>type_code_missing.csv</em></li> </ul> <h2>Data description</h2> <h3>data_computed</h3> <p>This folder contains pre-computed values by the authors on rail and air emissions. These are estimated:</p> <ul> <li>For rail using <a href="http://ecopassenger.hafas.de/" rel="nofollow">EcoPassenger</a>.</li> <li>For flights based on the emission model from Montlaur, A., Delgado, L., & Trapote-Barreira, C. (2021). <a href="https://doi.org/10.3390/su131810401" rel="nofollow"><em>Analytical Models for CO<sub>2</sub> Emissions and Travel Time for Short-to-Medium-Haul Flights Considering Available Seats</em></a>. Sustainability 13.18 (2021) and from some specific flights using EUROCONTROL's <a href="https://www.eurocontrol.int/platform/integrated-aircraft-noise-and-emissions-modelling-platform">IMPACT </a>model.</li> </ul> <h3>flights_data4</h3> <p>Information from flights_data4 table from <a href="https://opensky-network.org/data/impala">OpenSky</a>. Please refer to the <a href="https://opensky-network.org/about/terms-of-use">terms of use of OpenSky</a> for the restrictions on the further use of these data.</p> <p>The file <em>1st_week_0523.csv </em>contains the information of the table flights_data4 from OpenSky for the week of the 1st May 2023 (01/05/2023 to 07/05/2003). This was downloaded with the SQL query </p> <p>SELECT * FROM flights_data4 WHERE lastseen >= 1682899200 AND firstseen <= 1683504000;</p> <p>Note that the lastseen and firstseen are in UnixTime and correspond to 2023-05-01 00:00:00 UTC and 2023-05-08 00:00:00 UTC respectively. This ensures capturing all flights landing on 01/05/2023 even if they departed the day before and departing on 07/05/2023 even if landing the day after.</p> <h3>renfe</h3> <p>renfe folder contains the General Transit Feed Specification (GTFS) data from the <a href="https://data.renfe.com/dataset/horarios-de-alta-velocidad-larga-distancia-y-media-distancia">Renfe</a> rail operator with the high-speed, long and medium distances timetables. Note that Renfe provides the data under a <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank" rel="noopener">Creative Commons Attribution 4.0</a> license. </p> <h3>Other datasets</h3> <ul> <li><em>aircraftDatabase.csv </em>: Database containing information on aircraft information (type, manufacturer, license, etc.) as a function of their transponder icao24 code. Obtained from <a href="https://opensky-network.org/aircraft-database">OpenSky</a>.</li> <li><em>airport_static.csv</em>: Airport ICAO code, latitude and longitude.</li> <li><em>code_seats.csv</em>: allows each aircraft model to be related to the seats in the cabin. It has been extracted from airline websites and other sources.</li> <li><em>manual_fixed_airports.csv</em>: List of manually modified airports for arrival/departure to fix wrong rotations from OpenSky data. For each airport ICAO code, it provides the one that should be used instead and some information on that airport (e.g., name)</li> <li><em>mat_corrected.csv</em>: identifies the rotation of each aircraft in the week of study. This is especially relevant for fleet analysis as it is necessary to know the start and end airport of each rotation for each day. It has been identified with an ad-hoc algorithm, and some data has been corrected with <a href="https://www.flightradar24.com/">FlightRadar24</a> data support.</li> <li><em>type_code_missing.csv</em>: relates the transponders' icao24 identifiers missing from OpenSky to the aircraft type (complement aircraftDatabase), compiled from <a href="https://www.flightradar24.com/" rel="nofollow">FlightRadar24</a>.</li> </ul>
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.