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3,947 results for “Requirements”
MADFORWATER: WP3: Adaptation of technologies for efficient water management and treated wastewater reuse in agriculture: Task3.1: Reduction of crop water requirement and tools for irrigation management with treated WW: Subtask 3.1.1: Plant Growth Promotion (PGP) bacteria to enhance crop resistance to water stress and salinity: Subset1
<p>This dataset contains the data underlying the following publication: Mouna Mahjoubi, Simone Cappello, Yasmine Souissi, Atef Jaouani and Ameur Cherif (February 7th 2018). Microbial Bioremediation of Petroleum Hydrocarbon– Contaminated Marine Environments, Recent Insights in Petroleum Science and Engineering Mansoor Zoveidavianpoor, IntechOpen, DOI: 10.5772/intechopen.72207</p> <p> </p>
FN-RE: A Corpus of Requirements Documents Enriched with Semantic Frame Annotations
<p>FN-RE is a human-labelled dataset using FrameNet scheme. The dataset is distributed and can be viewed using a web-index page. For further details about the annotation procedures, please refer to the annotation guidelines included in the folder.</p>
Avoiding sedentary behaviors requires more cortical resources than avoiding physical activity
<p><strong>Dataset related to the paper entitled "Avoiding sedentary behaviors requires more cortical resources than avoiding physical activity". </strong></p> <p>This dataset includes:</p> <p>1) A workbook</p> <p>2) Raw data ("raw_data_eprime_zen.csv") of the behavioral outcomes of the manikin task</p> <p>3) Self-reported data ("data_self_report_R_subset_zen.csv").</p> <p>4) Electroencephalography data ("ERP_by_subject_by_condition_data.zip").</p> <p>5) R script for the data management of the behavioral outcomes (i.e., from the raw data to data ready to be analyzed)</p> <p>6) Images used in the manikin task</p> <p>7) Eprime script for the manikin task</p>
Frame Embeddings for Software and Requirements Engineering Domain
<p>This project is aimed to identify semantic relatedness of <a href="https://framenet2.icsi.berkeley.edu/">FrameNet </a>semantic frames in the domain of software and requirements engineering. The folder contains the frame embeddings that are obtained using the <strong>context-based method</strong> described in our ESEM paper*.</p> <p>Waad Alhoshan, Liping Zhao, and Riza Batista-Navarro. 2018. Using Semantic Frames to Identify Related Textual Requirements: An Initial Validation. In ACM / IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM) (ESEM ’18), October 11–12, 2018, Oulu, Finland. ACM, New York, NY, USA, 2 pages. https://doi.org/10.1145/3239235.3267441 </p> <p> </p> <p> </p>
Semantic Frame Embeddings for Detecting Relations between Software Requirements
<p><strong>FN-RE frame embeddings-is semantic resource built based on embedding-based representations of semantic frames in FrameNet, which was developed to support the detection of relations between software requirements. Our embeddings, which encapsulate contextual information at the semantic frame level, were trained on a large corpus of requirements (i.e., a collection of more than three million mobile application reviews). </strong></p>
Metadata on Articles Published at the Requirements Engineering Conference, REFSQ conference, or Requirements Engineering Journal from 2009 until 2018
<p>In the 1990s, it was recognized that Requirements Engineering lays the foundation for high quality software. A substantial research community has formed that set out to enable practitioners of the 21st century to systematically adopt proven strategies to common development challenges and to enable the engineering of innovative solutions and product features. But is contemporary RE Research delivering what it set out to deliver? In the article at IEEE Software 36(4) with DOI 10.1109/MS.2019.2909127, we provide a brief overview over the accomplishments of the past 10 years and identify open opportunities. The work at hand is the raw dataset of metadata, specifically keywords and author names, of articles published at the Requirements Engineering Conference, REFSQ conference, or Requirements Engineering Journal from 2009 until 2018 and supplements our article.</p>
Survey Data Set Part 1 - Attitudes Towards Videos as a Documentation Option for Communication in Requirements Engineering
<p>In 2017, we conducted an online survey to explore software professionals' attitudes towards videos as a documentation option for communication in requirements engineering. The survey covered the following topics:</p> <ul> <li>Demographics</li> <li>Attitude towards videos as a medium in RE including its strengths, weaknesses, opportunities, and threats</li> <li>Current production and use of videos in RE, respectively the obstacles that prevent the production and use of videos</li> </ul> <p>64 out of 106 software professionals from industry and academia completed the survey. The survey was implemented in LimeSurvey and distributed across several communication channels such as LinkedIn, ResearchGate, and a mailing list of a German RE professionals group.</p> <p>This dataset includes the following files:</p> <ul> <li>"Raw and analyzed data.xlsx" contains the raw and analyzed survey responses which are anonymized <ul> <li>This data includes <em>demographics </em>and <em>attitude</em>.</li> <li>The data on <em>video production and use</em> are included in: <a href="https://zenodo.org/record/4064741">Survey Data Set Part 2 - Attitudes Towards Videos as a Documentation Option for Communication in Requirements Engineering</a>.</li> </ul> </li> <li>"Survey - Offline version.docx" contains the questions and possible answers of the survey</li> <li>"Survey - Offline version.pdf" contains the questions and possible answers of the survey</li> </ul> <p>This survey was designed, conducted, and analyzed by Oliver Karras (<a href="https://twitter.com/KarrasOliver">@KarrasOliver</a>).</p>
Figure 3 in A new record of the freshwater turtle Mauremys rivulata (Valenciennes, 1833) in the Ofkos river, Cyprus: Conservation actions required
Figure 3. Turtle trap used for the research (upper right and lower left). Trap with two trapped individuals (upper left).
Fig. 1 in Threshold temperatures and thermal requirements of Psyllaphycus diaphorinae (Hymenoptera: Encyrtidae), a hyperparasitoid of Diaphorencyrtus aligarhensis (Hymenoptera: Encyrtidae) and Tamarixia radiata (Hymenoptera: Eulophidae)
Fig. 1. Predicted rate of total development as a function of temperature for Psyllaphycus diaphorinae (pooled males and females) at different constant and fluctuating temperatures using linear (a), Performance-2 (b), and Ratkowsky (c) models. In the linear and Perfomance-2 charts, the ordinate is the rate of development (1/D, per d), and the abscissa is temperature (°C). In the Ratkowsky chart (c) the ordinate is the square root of development rate (, per d), and the abscissa is temperature (°C). Symbols represent mean observed data. Solid lines represent model predictions for fluctuating temperatures and dashed lines for constant temperatures. For linear regression (a), data values for 32 °C were omitted because of significant deviation from rectilinearity.
Fig. 9 in Morphological requirements in limulid and decapod gills: A case study in deducing the function of lamellipedian exopod lamellae
Fig. 9. Conceptual figure showing growth accompanied amplification of pyramidial shaped multi−foliated gills. A. Limulid type of gills with low−relief conical profile. B. Decapod type of gills with high relief.
Fig. 8 in Morphological requirements in limulid and decapod gills: A case study in deducing the function of lamellipedian exopod lamellae
Fig. 8. Body−weight specific lamellar numbers and average single lamellar area in bi−logarithmic coefficients. A. Bi−logarithmic graph of total number of lamellae with respect to dry−body weight in Limulus polyphemus (close circle), Tachypleus rotundicauda (open circle), Callinectes sapidus (solid square) and Libinia dubia (open square). B. Results of allometric analysis shown in Fig. 5A. Sample size (N), correlation coefficient (r), reduced major axis of logW = αlogNL + logβ, and K = α – α / [(s)2 + (s)2]1/2 where s is the standard deviation of α. K is a statistic with the standard normal distribution used for 1 2 α1 α2 α discrimination of the differences of α significant or not. If K>1.96 or K <−1.96, the difference is significant. See also Fig. 7 for the abbreviations of W and NL. C. Bi−logarithmic graph of average area per lamella with respect to dry−body weight. Abbreviations as in Fig. 5A. D. Results of allometric analysis shown in Fig. 5C. Same abbreviations as in Fig. 5B. The data of two decapods are referred to Hughes (1983), which presented average, maximum and minimum specific dry−body weight and lamellar number among the examined samples as well as α and logβ of the allometric analysis with respect to their dry−body weight. Readers are referred to the results of T. rotundicauda as reference data, because too small numbers have been examined. This is to show the trend that the results of a species fall in a neighboring area to that of a taxonomically close species.
Fig. 7 in Morphological requirements in limulid and decapod gills: A case study in deducing the function of lamellipedian exopod lamellae
Fig. 7. Allometric relationships between respiratory surface and dry−body weight in Limulus polyphemus (dots and solid regression line) in bi−logarithmic coefficients. Abbreviations are: correlation coefficients (r); drybody weight (W); total area for respiratory surface (A); allometric scaling exponent (α). For comparisons, the results on the gills of decapod crustaceans Callinectes sapidus and Libinia dubia are shown in dashed lines, the data are referred to Hughes (1983).
Fig. 6 in Morphological requirements in limulid and decapod gills: A case study in deducing the function of lamellipedian exopod lamellae
Fig. 6. Phyllobranchiate gill of a decapod crustacean Atergatris sp. Top one−fourth is shown. SEM photo.
Fig. 5 in Morphological requirements in limulid and decapod gills: A case study in deducing the function of lamellipedian exopod lamellae
Fig. 5. The area of every gill lamella of selected first branchial appendages. A. Instar stage 4 of dry−body weight 0.01 g. B. Instar stage 10 of dry−body weight 0.43 g. C. Instar stage 14 of dry−body weight 6.7 g. D. Instar stage 18 of dry body weight 177.09 g. Grey shaded area corresponds to possible newly established lamellae in each instar stage. Darker shade ranges to minimum established number, while lighter maximum. Total respiratory area (T), respiratory area for newly established lamellae of minimum (Nmin) and maximum value (Nmax) are also noted. These ratios relative to the total area are shown in parentheses. The lamellae left to dashed lines lack an osmoregulatory area.
Fig. 4 in Morphological requirements in limulid and decapod gills: A case study in deducing the function of lamellipedian exopod lamellae
Fig. 4. Growth−related change in gill morphology of Limulus polyphemus shown in instar−stage series. A. Mean total respiratory (white bars) and osmoregulatory area for each instar stage (grey bars) and their increment rates (black and grey line graph denotes respiratory and osmoregulatory area, respectively). B. Average total lamellar number for each instar stage (bar graph) and its increment rates (line graph). C. Average area per single lamellae for each instar stage (bar graph) and its increment rates (line graph). The bar graphs should refer to left indexes shown in exponential form (A and C) or in actual numbers (B), and the line graphs right indexes. Error bars denote the maximum and the minimum lamellar numbers. Numbers shown above the columns represent the numbers of examined specimens.
Fig. 10 in Morphological requirements in limulid and decapod gills: A case study in deducing the function of lamellipedian exopod lamellae
Fig. 10. Lamellipedian exopod of the trilobite Olenoides serratus. A. Camera lucida drawing; traced from Whittington (1980: text−fig. 6). B. Estimated area of each exite shown in A.
Fig. 3 in Morphological requirements in limulid and decapod gills: A case study in deducing the function of lamellipedian exopod lamellae
Fig. 3. Posterior view of first instar stage of Limulus polyphemus Linnaeus, 1758. Only five gill lamellae (gl) are visible between the operculate division of first (ba1) and second branchial appendage (ba2). Other abbreviations: op, operculum; pr, prosoma. SEM photo.
Fig. 2 in Morphological requirements in limulid and decapod gills: A case study in deducing the function of lamellipedian exopod lamellae
Fig. 2. Book gill of Limulus polyphemus Linnaeus, 1758. A. Dorsal view of left first branchial appendage of instar stage 14. Endopod and exopod of the operculate division of branchial appendage as well as lamellae of book gill are shown. SEM photo. B. Dorsal view of left first branchial appendage of instar stage 4. SEM photo. C. Transparent microscopic photo of a gill lamella dyed with toluidine blue, showing osmoregulatory and respiratory area.
Data sets accompanying "Methodological and reporting inconsistencies in land-use requirements misguide future renewable energy planning"
<p>This data sets accompany the publication "Methodological and reporting inconsistencies in land-use requirements misguide future renewable energy planning" in One Earth.</p> <ul> <li>lur-db-output-zenodo.xlsx: contains all land use requirement estimates for renewable energies reviewed in the publication. Meta-data is reported in one sheet, the other sheet contains the original data.</li> <li>authorship-tree-zenodo.xlsx: contains the information necessary to derive the authorship tree shown in the supplementary information. Meta-data is reported in one sheet, the other sheet contains the original data.<br><br><br></li> </ul>
Fitness App Ethical Requirements Stack
<p>An image of the Fitness App Ethical Requirements Stack</p>
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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.