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2,453 results for “Architecture”
Architectural panels, Sārnāth
<p>Drawing of architectural panels from Sārnāth by Markham Kittoe, now in the British Library (WD2876 folio 32), original sculpture in the British Museum, London, nos. 1880-12, 13 and 14 (Transferred from the India Museum).</p>
ISO TR 21965 Information and documentation -- Records management in enterprise architecture - Archi tool project file
<p>This file is a project file, in XML format, of the freeware too Archi (version 4.2.0) modeling the ArchiMate diagrams present in the ISO/DTR 21965:2019.</p> <p>Archi tool is freely available from https://www.archimatetool.com</p> <p>The purpose of the ISO/TR 21965:2019 is to provide a common reference for Records managers (or information managers in general) and Enterprise architects about requirements for records processes and systems. The goal is to establish the Records manager as a key stakeholder in Enterprise Architecture, by expressing the related Records Management Viewpoint.</p> <p>This viewpoint makes use of the concepts of “concerns” and “system of concerns” as defined in ISO/IEC/IEEE 42010:2011, and of the concepts of “stakeholders”, “viewpoint, “view” and “model” as also defined coherently in that standard and in the main Enterprise Architecture references of TOGAF and ArchiMate. With reference to ArchiMate, the main scope of this viewpoint is the Motivational aspect and the layers Strategy and Business, with minor considerations for the layers of Application and Implementation. The Open Group Architecture Framework (TOGAF) is used to inform how this Records Management Viewpoint relates to the Architecture Development Method (ADM).</p> <p>The edition of the file is work of the author, but the intelectual content of the file is the resulting of the work of the ISO working group responsible by the production of the Technical Report: ISO/TC 46/SC 11/WG 14 - Records requirements in Enterprise Architecture</p> <p> </p>
The molecular architecture of the yeast spindle pole body core determined by Bayesian integrative modeling
<p>This repository pertains to the molecular architecture of the yeast spindle pole body (SPB), the structural and functional equivalent of the metazoan centrosome. Data from in vivo FRET and yeast two-hybrid, along with SAXS, X-ray crystallography, and electron microscopy were integrated by a Bayesian structure modeling approach.</p> <p>For more information about how to reproduce this modeling, see the <a href="https://salilab.org/spb/">Sali lab website</a> or the README file.</p>
Tree inventory data such as tree identity, position in the plot, height, architecture and biomass on Mt. Kilimanjaro
<p>This dataset describes position and sizes of all trees above 10 cm diameter at breast height in all plots, also fruiting and flowering events and if it is a canopy tree or not in KiLi project. -999999 represents NA in numeric variables. </p> <p>Within each plot, all trees wider than 10 cm diameter at breast height (dbh) were marked with aluminium tags and their dbh and height were measured. The dbh was measured with a diameter tape (Forestry Suppliers, USA) at 1.3 m for normally shaped trees and 20 cm below or above when branches or irregular shapes impeded measurement at that height. The 1.3 m height was measured from the highest ground level around the stem to standardize measurements taken on slopes. For trees which were strongly buttressed or too big to measure by hand, a laser dendrometer (Criterion RD 1000 with TruPulse 200/200, Centennial, USA) was used to measure the tree above the buttresses and at 1.3 m. Lianas above 10 cm in diameter were also marked and their dbh was measured. Tree height was measured using an ultra-sonic hypsometer (Vertex IV Hypsometer, Haglöf, Langsele, Sweden) or a laser rangefinder (TruPulse 200/200). The tree inventories were carried out between December 2010 and March 2013.</p> <p>The KiLi project (2010-2018) is a German Science Foundation (DFG) funded research unit (DFG research unit FOR1246) that focuses on biodiversity and ecosystem processes along altitudinal and disturbance gradients on Mt. Kilimanjaro (Tanzania, Africa), capitalizing on its world-wide unique range of climatic and vegetation zones. The research unit comprises 2 central projects and 7 subprojects from various disciplines. On a total of 60 study sites in both natural and human-disturbed ecosystems biodiversity (e.g. plants, soil arthropods, ants, bees, frogs, lizards, bats, birds), related ecosystem processes (decomposition, seed dispersal, pollination, herbivory, predation), and biogeochemical processes and properties of ecosystems (climate, soil properties and nutrient status, regulation of water and carbon fluxes, trace gas emissions, primary productivity, functional diversity) are analyzed.</p>
tree architectural traits in adult trees subjected to stemflow
<p>Dataset containing key tree architectural traits from tree individuals of Maple and Ash subjected to stemflow and stemflow-supression conditions</p>
2D materials-based homogeneous transistor-memory architecture for neuromorphic hardware
<p>This dataset contains the raw data used for the publication:</p> <p><strong>2D materials-based homogeneous transistor-memory architecture for neuromorphic hardware</strong></p> <p>By Lei Tong<sup>1</sup>, Zhuiri Peng<sup>1</sup>, Runfeng Lin<sup>1</sup>, Zheng Li<sup>1</sup>, Yilun Wang<sup>1</sup>, Xinyu Huang<sup>1</sup>, Kan-Hao Xue<sup>1</sup>, Hangyu Xu<sup>2</sup>, Feng Liu<sup>3</sup>, Hui Xia<sup>2</sup>, Peng Wang<sup>2</sup>, Mingsheng Xu<sup>4</sup>, Wei Xiong<sup>1</sup>, Weida Hu<sup>2,</sup>*, Jianbin Xu<sup>5</sup>, Xinliang Zhang<sup>1</sup>, Lei Ye<sup>1,</sup>*, Xiangshui Miao<sup>1</sup></p> <p>Detailed descriptions for each file can be found in "Dataset description.docx".</p>
WikiChurches – A Fine-Grained Dataset of Architectural Styles with Real-World Challenges
<p>WikiChurches is a dataset for architectural style classification, consisting of 9,485 images of church buildings. Both images and style labels were sourced from Wikipedia. The dataset can serve as a benchmark for various research fields, as it combines numerous real-world challenges: fine-grained distinctions between classes based on subtle visual features, a comparatively small sample size, a highly imbalanced class distribution, a high variance of viewpoints, and a hierarchical organization of labels, where only some images are labeled at the most precise level. In addition, we provide 631 bounding box annotations of characteristic visual features for 139 churches from four major categories. These annotations can, for example, be useful for research on fine-grained classification, where additional expert knowledge about distinctive object parts is often available.</p> <p>Please refer to the README.md file for information about the different files contained in this dataset.</p>
MaMo online Webinar Cycle "Materializing Modernity - Landscape, Architecture and Anthropology intersections in 20th-century rurality"
<p>A dataset (WP2-B_Materials_1) containing the video recordings of the MaMo Webinar Cycle titled “Materializing Modernity: Landscape, Architecture and Anthropology intersections in 20th-century rurality” held on the ZOOM platform in April and May 2021. Activity developed under the Work Package 2 (WP2), Secondment period at Università degli Studi di Milano (UNIMI), Italy. All the events have been organized by Dr Federica Pompejano (MSCA-IF Fellow) in collaboration with the Laboratory of Ethnomusicology and Visual Anthropology (LEAV) of the Department of Cultural and Environmental Heritage (UNIMI) and the Institute of Cultural Anthropology and Art Studies (IAKSA) of the Akademia e Studimeve Albanologjike (ASA), Tirana, Albania.</p> <p>WP2-B_Materials_1 (PART 1) - Contents</p> <ul> <li>Programme of the MaMo Webinar Cycle "Materializing Modernity: Landscape, Architecture and Anthropology intersections in 20th-century rurality" held in April-May 2021 on ZOOM online platform</li> <li>Banner of the MaMo Webinar Cycle "Materializing Modernity: Landscape, Architecture and Anthropology intersections in 20th-century rurality" held in April-May 2021 on ZOOM online platform</li> <li>1st meeting - Introduction: MaMo - an introduction to Albanian Socialist and Post-Socialist rurality by Federica Pompejano, MSCA-IF Fellow, Department of Ethnology, Institute of Cultural Anthropology and Art Studies (IAKSA), Academy of Albanian Studies, Albania<br> Oral presentation: "The Albanian Village as an anthropological encounter of modernity" by Nebi Bardhoshi, Associate Professor and Director of the Institute of Cultural Anthropology and Art Studies (IAKSA), Academy of Albanian Studies, and Olsi Lelaj, Researcher, Department of Ethnology, IAKSA, Academy of Albanian Studies, Albania</li> <li>MaMo Webinar Cycle - 1st meeting banner</li> <li>MaMo Webinar Cycle - 1st meeting poster with oral presentation abstract</li> <li>MaMo Webinar Cycle - 1st meeting poster with oral presenters short bio</li> <li>MaMo Webinar Cycle - 1st meeting Instagram post</li> <li>2nd meeting - Oral presentation: "Exploring Rurality in Southern Italy: the experience of 'Sonic Ethnography'" by Nicola Scaldaferri, Associate Professor, Department of Cultural and Environmental Heritage, Università Statale di Milano, Italy, and Lorenzo Ferrarini, Lecturer in Social and Visual Anthropology, Granada Centre for Visual Anthropology, University of Manchester, United Kingdom</li> <li>MaMo Webinar Cycle - 2nd meeting banner</li> <li>MaMo Webinar Cycle - 2nd meeting poster with oral presentation abstract</li> <li>MaMo Webinar Cycle - 2nd meeting poster with oral presenters short bio</li> <li>MaMo Webinar Cycle - 2nd meeting Instagram post</li> </ul>
MaMo Webinar Cycle "Materializing Modernity: Landscape, Architecture and Anthropology intersections in 20th-century rurality" - Part 2
<p>A dataset (WP2-B_Materials_2) containing the video recordings of the MaMo Webinar Cycle titled “Materializing Modernity: Landscape, Architecture and Anthropology intersections in 20th-century rurality” held on the ZOOM platform in April and May 2021. Activity developed under the Work Package 2 (WP2), Secondment period at Università degli Studi di Milano (UNIMI), Italy. All the events have been organized by Dr Federica Pompejano (MSCA-IF Fellow) in collaboration with the Laboratory of Ethnomusicology and Visual Anthropology (LEAV) of the Department of Cultural and Environmental Heritage (UNIMI) and the Institute of Cultural Anthropology and Art Studies (IAKSA) of the Akademia e Studimeve Albanologjike (ASA), Tirana, Albania.</p> <p>WP2-B_Materials_2 (PART 2) - Contents</p> <ul> <li>3rd meeting - Oral presentation 1: "Embedding the Past into Modernist Rural Landscapes" by Cristina Pallini, Associate Professor, Department of Architecture, Built Environment and Construction Engineering, Politecnico di Milano, Italy - Oral presentation 2: "Figures in a landscape: notes for a history of rural planning and village design in the Eastern bloc" by Axel Fischer, Associate Professor p.t., Université libre de Bruxelles, School of Architecture La Cambre Horta, hortence lab for architectural history, theory and criticism, Belgium (WP2-B_Webinar_03W.mpeg)</li> <li>MaMo Webinar Cycle - 3rd meeting banner (WP2-B_Webinar-03W_Banner.jpg)</li> <li>MaMo Webinar Cycle - 3rd meeting poster with oral presentation abstract - 1 (WP2-B_Webinar_03W-Poster1.jpg)</li> <li>MaMo Webinar Cycle - 3rd meeting poster with oral presentation abstract - 2 (WP2-B_Webinar_03W-Poster2.jpg)</li> <li>MaMo Webinar Cycle - 3rd meeting poster with oral presenters short bio (WP2-B_Webinar_03W-Poster3.jpg)</li> <li>MaMo Webinar Cycle - 3rd meeting Instagram post - 1 (WP2-B_Webinar_03W_IG1.jpg)</li> <li>MaMo Webinar Cycle - 3rd meeting Instagram post - 2 (WP2-B_Webinar_03W_IG2.jpg)</li> </ul>
MaMo Webinar Cycle "Materializing Modernity: Landscape, Architecture and Anthropology intersections in 20th-century rurality" - Part 3
<p>A dataset (WP2-B_Materials_3) containing the video recordings of the MaMo Webinar Cycle titled “Materializing Modernity: Landscape, Architecture and Anthropology intersections in 20th-century rurality” held on the ZOOM platform in April and May 2021. Activity developed under the Work Package 2 (WP2), Secondment period at Università degli Studi di Milano (UNIMI), Italy. All the events have been organized by Dr Federica Pompejano (MSCA-IF Fellow) in collaboration with the Laboratory of Ethnomusicology and Visual Anthropology (LEAV) of the Department of Cultural and Environmental Heritage (UNIMI) and the Institute of Cultural Anthropology and Art Studies (IAKSA) of the Akademia e Studimeve Albanologjike (ASA), Tirana, Albania.</p> <p>WP2-B_Materials_3 (PART 3) - Contents</p> <ul> <li>4th meeting - Oral presentation: "Concepts integrated conservation as inroads to sustainable management of cultural landscapes" by Bosse Lagerqvist, Associate Professor and Senior Lecturer, Department of Conservation, Göteborgs Universitet, Sweden (WP2-B_Webinar_04W.mpeg)</li> <li>MaMo Webinar Cycle - 4th meeting banner (WP2-B_Webinar_04W_Banner.jpg)</li> <li>MaMo Webinar Cycle - 4th meeting poster with oral presentation abstract (WP2-B_Webinar_04W_Poster1.jpg)</li> <li>MaMo Webinar Cycle - 4th meeting poster with oral presenter short bio (WP2-B_Webinar_04W_Poster2.jpg)</li> <li>MaMo Webinar Cycle - 4th meeting Instagram post (WP2-B_Webinar_04W_IG.jpg)</li> <li>5th meeting - Oral presentation: "Socialist Modernism in the former Eastern Bloc (1955-1991), The Socialist Modernism map at socialistmodernism.com" by Dumitru Rusu, President of B.A.C.U. Association - Birou pentru Art si Cercetare Urbană (Bureau for Art and Urban Research), Romania (WP2-B_Webinar_05W.mpeg)</li> <li>MaMo Webinar Cycle - 5th meeting banner (WP2-B_Webinar_05W_Banner.jpg)</li> <li>MaMo Webinar Cycle - 5th meeting poster with oral presentation abstract (WP2-B_Webinar_05W_Poster1.jpg)</li> <li>MaMo Webinar Cycle - 5th meeting poster with oral presenter short bio (WP2-B_Webinar_05W_Poster2.jpg)</li> <li>MaMo Webinar Cycle - 5th meeting Instagram post (WP2-B_Webinar_05W_IG.jpg)</li> </ul>
Phenotypic diversity of root architecture and genotypic variation in durum wheat under salt stress
<p>Supplementary data consists of Principal Components values for traits detected under salt and control conditions (S1); Markers' locations onto the durum wheat reference genome associated with QTL (S2); Markers associated with genes from NCBI database (S4); PCR results and alleles distribrution</p>
LOCATION DOMESTIC ARCHITECTURE AUGUSTA EMERITA (MERIDA, SPAIN)
<p>This dataset is based on houses from the Roman colony of <em>Augusta Emerita </em>(ca. B.C 25- A.D. 382)<sup> <a href="#_ftn1"><sup>[1]</sup></a></sup>. These dates are not chosen randomly: 25 B.C. saw the foundation <em>ex nihilo </em>of the settlement, according to Cass. Dio., <em>Hist</em>. 53.26.1<a href="#_ftn2"><sup><sup>[2]</sup></sup></a>, and A.D. 382, the last time a name of a <em>vicarius</em> is attested in the epigraphy<a href="#_ftn3"><sup><sup>[3]</sup></sup></a>. The remains from <em>Augusta Emerita </em>are particularity well suited to GIS analysis of this type because the site was occupied for more than two thousand years and was never abandoned, while also being occupied by several cultures over that time.</p> <p> </p> <p><a href="#_ftnref1">[1]</a> All documentation based on La arquitectura doméstica de Augusta Emerita (2015 Phd) https://dehesa.unex.es/handle/10662/2670# </p> <p><a href="#_ftnref2">[2]</a> The Duoviri's first couple is evidenced ca.20 B.C. from the fragment of the Fasti duovirales: A. Stylow and A. Ventura, “Los hallazgos epigráficos”, in R. Ayerbe, T. Barrientos and F. Palma (edd.), <em>El foro de Augusta Emerita. </em><em>Génesis y evolución de sus recintos monumentales</em> (Mérida 2009) 453-523.</p> <p><a href="#_ftnref3">[3]</a> L. Hidalgo and G. Méndez, “Octavius Clarus, un nuevo Vicarius Hispaniarum en Augusta Emerita”, <em>Mérida. Excavaciones Arqueológicas </em>8 (2005) 547-64.</p>
Data for: 'FAS: assessing the similarity between proteins using multi-layered feature architectures'
<p>Raw data and result data for the analyses made for the manuscript:</p> <p>'FAS: assessing the similarity between proteins using multi-layered feature architectures'</p> <p><a href="https://doi.org/10.1093/bioinformatics/btad226">https://doi.org/10.1093/bioinformatics/btad226</a></p> <p>This dataset contains raw data obtained from QFO Orthobench and Gene Ontology database. Analyses were made to showcase the different uses of the FAS algorithm.</p>
Replication package for Decomposition of Monolithic Applications into Microservices Architectures: A Systematic Review
<p><strong>Replication Package</strong></p> <p><strong>Title:</strong></p> <p>Replication package for Decomposition of Monolithic Applications into Microservices Architectures: A Systematic Review.</p> <p><strong>Authors:</strong></p> <p>Yalemisew Abgaz, Andrew McCarren, Peter Elger, David Solan, Neil Lapuz, Marin Bivol, Glenn Jackson, Murat Yilmaz, Jim Buckley, and Paul Clarke</p> <p><strong>Year</strong></p> <p>This replication package was initially generated in 2022 and following feedback from reviewers, it is revised in 2023.</p> <p>This package contains two files and three folders that provide additional insight for researchers who wish to replicate our work or who would like to expand the review in the future.</p> <p><strong>Files</strong></p> <ul> <li>The file contains a detailed description of the literature search outlining the steps and the results obtained.</li> <li>Readme.md: A readme file (this file).</li> </ul> <p><strong>Folders</strong></p> <ul> <li>A folder containing the search results and the refinement steps. It contains four files listing studies included in the refinement process (Refinement_Step_1 to Refinement_Step_4) and a master file combining all the steps in one file. The master file contains detailed information about how the refinement steps are executed and all the intermediate results following each refinement step. Users may explore by expanding the filters in Refinement Step 2 (J), Refinement Step 3 (M) and Refinement Step 4 § columns in the master sheet. Readers can also directly go to the sheets that contain the selected studies in any of the refinement stages. A description of each file is also included in the Literature_Search_Strategy.pdf file.</li> <li>This folder contains the list of studies included in the snowballing process, including the last two refinement steps (Refinement_Step_5 and Refinement_Step_6). The snowballing master sheet contains studies extracted using the snowballing process and the data cleaning and filtering criteria used. The different sheets also contain the selected studies at each stage of the snowballing process.</li> </ul> <ul> <li>This folder contains the data extracted from the selected literature by employing the Systematic Review and Ground Theory. The two files included in this folder contain the data extraction template and the data extracted from the 35 selected studies including some intermediate notes.</li> </ul> <p>If you have further questions regarding the survey, feel free to contact us via e-mail. <a href="mailto:Yalemisewm.abgaz@dcu.ie">Yalemisewm.abgaz@dcu.ie</a>.</p> <p> </p>
Thinking about Vector Symbolic Architectures (video recording)
<p>Video recording of the keynote presentation "Thinking about Vector Symbolic Architectures" given on 2023-06-15 at the <a href="https://sites.google.com/ltu.se/midnightvsa/home?authuser=0">Midnight Sun Workshop on Vector Symbolic Architectures</a> in Luleå, Sweden.</p> <p><strong>Abstract</strong></p> <p>Vector Symbolic Architectures are defined in terms of a very small set of operators acting on a vector space. The task of the VSA researcher is to discover the implications that follow from the definition in terms of the systems that can be implemented with VSAs. The VSA definitions are the researcher’s raw materials, but they also need tools to transform those raw materials into useful hypotheses and system designs. One important tool for a researcher is a conceptual framework, which specifies how the researcher thinks about VSAs and relates them to the other things they know. It is the researcher’s mental model of how VSAs work. The primary requirement for a conceptual framework is that it is productive; it should make it easy for the researcher to generate interesting hypotheses and designs. These hypotheses and designs don’t have to be correct, just plausible. Beating them into shape is a different part of the research process. Most VSA research papers contain a statement of the VSA definition. Very few mention the researcher’s conceptual framework. In this talk I will sketch out my conceptual framework - how I think about Vector Symbolic Architectures - in the hope that it might be interesting and useful to other researchers.</p>
Domain-Driven Design for Microservices Architecture Systems Development: A Systematic Mapping Study
<p>This repository contains all artifacts related to the study: Domain-Driven Design for Microservices Architecture Systems Development: A<br> Systematic Mapping Study</p>
Phloem anatomy constraints root system architecture development: theoretical clues from in silico experiments [software and dataset]
<p>Simulation software and results for "<strong>Phloem anatomy constraints root system architecture development: theoretical clues from in silico experiments</strong>"</p>
TrainTicket microservice testbench extracted information for our work: Evaluating ChatGPT's Proficiency in Understanding and Answering Microservice Architecture Queries Using Source Code Insights
<p>It contains the CSV file output of our tool implemented in the paper: "Evaluating ChatGPT’s Proficiency in Understanding and Answering Microservice Architecture Queries Using Source Code Insights." applied to the TrainTicket microservice testbench. The information in this CSV was used for In-Context-Learning for ChatGPT.</p>
From a Monolithic Big Data System to a Microservices Event-Driven Architecture
<p>[Context] Data-intensive systems, a.k.a. big data systems (BDS), are software systems that handle a large volume of data in the presence of performance quality attributes, such as scalability and availability. Before the advent of big data management systems (e.g. Cassandra) and frameworks (e.g. Spark), organizations had to cope with large data volumes with custom-tailored solutions. In particular, a decade ago, Tecgraf/PUC-Rio developed a system to monitor truck fleet in real-time and proactively detect events from the positioning data received. Over the years, the system evolved into a complex and large obsolescent code base involving a hard maintenance process. [Goal] We report our experience on replacing a legacy BDS with a microservice-based event-driven system. [Method] We applied action research, investigating the reasons that motivate the adoption of a microservice-based event-driven architecture, intervening to define the new architecture, and documenting the challenges and lessons learned. [Results] We perceived that the resulting architecture enabled easier maintenance and fault-isolation. However, the myriad of technologies and the complex data flow were perceived as drawbacks. Based on the challenges faced, we highlight opportunities to improve the design of big data reactive systems. [Conclusions] We believe that our experience provides helpful takeaways for practitioners modernizing systems with data-intensive requirements.</p>
Training dataset used in the magazine paper entitled "A Flexible Machine Learning-Aware Architecture for Future WLANs"
<p><a href="https://arxiv.org/pdf/1910.03510.pdf"><strong>A Flexible Machine Learning-Aware Architecture for Future WLANs</strong></a></p> <p><strong>Authors: </strong>Francesc Wilhelmi, Sergio Barrachina-Muñoz, Boris Bellalta, Cristina Cano, Anders Jonsson & Vishnu Ram.</p> <p><strong>Abstract: </strong>Lots of hopes have been placed in Machine Learning (ML) as a key enabler of future wireless networks. By taking advantage of the large volumes of data generated by networks, ML is expected to deal with the ever-increasing complexity of networking problems. Unfortunately, current networking systems are not yet prepared for supporting the ensuing requirements of ML-based applications, especially for enabling procedures related to data collection, processing, and output distribution. This article points out the architectural requirements that are needed to pervasively include ML as part of future wireless networks operation. To this aim, we propose to adopt the International Telecommunications Union (ITU) unified architecture for 5G and beyond. Specifically, we look into Wireless Local Area Networks (WLANs), which, due to their nature, can be found in multiple forms, ranging from cloud-based to edge-computing-like deployments. Based on ITU's architecture, we provide insights on the main requirements and the major challenges of introducing ML to the multiple modalities of WLANs.</p> <p><strong>Dataset description: </strong>This is the dataset generated for training a Neural Network (NN) in the Access Point (AP) (re)association problem in IEEE 802.11 Wireless Local Area Networks (WLANs). </p> <p>In particular, the NN is meant to output a prediction function of the throughput that a given station (STA) can obtain from a given Access Point (AP) after association. The features included in the dataset are:</p> <ol> <li>Identifier of the AP to which the STA has been associated.</li> <li>RSSI obtained from the AP to which the STA has been associated.</li> <li>Data rate in bits per second (bps) that the STA is allowed to use for the selected AP.</li> <li>Load in packets per second (pkt/s) that the STA generates.</li> <li>Percentage of data that the AP is able to serve before the user association is done.</li> <li>Amount of traffic load in pkt/s handled by the AP before the user association is done.</li> <li>Airtime in % that the AP enjoys before the user association is done.</li> <li>Throughput in pkt/s that the STA receives after the user association is done.</li> </ol> <p>The dataset has been generated through random simulations, based on the model provided in <a href="https://github.com/toniadame/WiFi_AP_Selection_Framework">https://github.com/toniadame/WiFi_AP_Selection_Framework</a>. More details regarding the dataset generation have been provided in <a href="https://github.com/fwilhelmi/machine_learning_aware_architecture_wlans">https://github.com/fwilhelmi/machine_learning_aware_architecture_wlans</a>.</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.