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Found 23 result(s)
The Alternative Fuels Data Center (AFDC) is a comprehensive clearinghouse of information about advanced transportation technologies. The AFDC offers transportation decision makers unbiased information, data, and tools related to the deployment of alternative fuels and advanced vehicles. The AFDC launched in 1991 in response to the Alternative Motor Fuels Act of 1988 and the Clean Air Act Amendments of 1990. It originally served as a repository for alternative fuel performance data. The AFDC has since evolved to offer a broad array of information resources that support efforts to reduce petroleum use in transportation. The AFDC serves Clean Cities stakeholders, fleets regulated by the Energy Policy Act, businesses, policymakers, government agencies, and the general public.
>>>!!!<<< 2018-01-18: no data nor programs can be found >>>!!!<<< These archives contain public domain programs for calculations in physics and other programs that we suppose about will help during work with computer. Physical constants and experimental or theoretical data as cross sections, rate constants, swarm parameters, etc., that are necessary for physical calculations are stored here, too. Programs are mainly dedicated to computers compatible with PC IBM. If programs do not use graphic units it is possible to use them on other computers, too. It is necessary to reprogram the graphic parts of programs in the other cases.
Specification Patterns is an online repository for information about property specification for finite-state verification. The intent of this repository is to collect patterns that occur commonly in the specification of concurrent and reactive systems.
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This is Haldimand County's public platform for exploring and downloading open data, discovering and building apps, and engaging to solve important local issues. You can analyze and combine Open Datasets using maps, as well as develop new web and mobile applications.
<<<!!!<<< The repository is offline >>>!!!>>> A collection of open content name datasets for Information Centric Networking. The "Content Name Collection" (CNC) lists and hosts open datasets of content names. These datasets are either derived from URL link databases or web traces. The names are typically used for research on Information Centric Networking (ICN), for example to measure cache hit/miss ratios in simulations.
Academic Torrents is a distributed data repository. The academic torrents network is built for researchers, by researchers. Its distributed peer-to-peer library system automatically replicates your datasets on many servers, so you don't have to worry about managing your own servers or file availability. Everyone who has data becomes a mirror for those data so the system is fault-tolerant.
<<<!!!<<< The repository is no longer available. This record is out-dated. >>>!!!>>>- GEON is an open collaborative project that is developing cyberinfrastructure for integration of 3 and 4 dimensional earth science data. GEON will develop services for data integration and model integration, and associated model execution and visualization. Mid-Atlantic test bed will focus on tectonothermal, paleogeographic, and biotic history from the late-Proterozoicto mid-Paleozoic. Rockies test bed will focus on integration of data with dynamic models, to better understand deformation history. GEON will develop the most comprehensive regional datasets in test bed areas.
The Cooperative Association for Internet Data Analysis (CAIDA) is a collaborative undertaking among organizations in the commercial, government, and research sectors aimed at promoting greater cooperation in the engineering and maintenance of a robust, scalable global Internet infrastructure.It is an independent analysis and research group with particular focus on: Collection, curation, analysis, visualization, dissemination of sets of the best available Internet data, providing macroscopic insight into the behavior of Internet infrastructure worldwide, improving the integrity of the field of Internet science, improving the integrity of operational Internet measurement and management, informing science, technology, and communications public policies.
Cell phones have become an important platform for the understanding of social dynamics and influence, because of their pervasiveness, sensing capabilities, and computational power. Many applications have emerged in recent years in mobile health, mobile banking, location based services, media democracy, and social movements. With these new capabilities, we can potentially be able to identify exact points and times of infection for diseases, determine who most influences us to gain weight or become healthier, know exactly how information flows among employees and productivity emerges in our work spaces, and understand how rumors spread. In an attempt to address these challenges, we release several mobile data sets here in "Reality Commons" that contain the dynamics of several communities of about 100 people each. We invite researchers to propose and submit their own applications of the data to demonstrate the scientific and business values of these data sets, suggest how to meaningfully extend these experiments to larger populations, and develop the math that fits agent-based models or systems dynamics models to larger populations. These data sets were collected with tools developed in the MIT Human Dynamics Lab and are now available as open source projects or at cost.
<<<!!!<<< The repository is no longer available. This record is out-dated. The Matter lab provides the archived database version of 2012 and 2013 at https://www.matter.toronto.edu/basic-content-page/data-download. Data linked from the World Community Grid - The Clean Energy Project see at https://www.worldcommunitygrid.org/research/cep1/overview.do and on fighshare https://figshare.com/articles/dataset/moldata_csv/9640427 >>>!!!>>> The Clean Energy Project Database (CEPDB) is a massive reference database for organic semiconductors with a particular emphasis on photovoltaic applications. It was created to store and provide access to data from computational as well as experimental studies, on both known and virtual compounds. It is a free and open resource designed to support researchers in the field of organic electronics in their scientific pursuits. The CEPDB was established as part of the Harvard Clean Energy Project (CEP), a virtual high-throughput screening initiative to identify promising new candidates for the next generation of carbon-based solar cell materials.
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The version 1.0 of the open database contains 1,151,268 brain signals of 2 seconds each, captured with the stimulus of seeing a digit (from 0 to 9) and thinking about it, over the course of almost 2 years between 2014 & 2015, from a single Test Subject David Vivancos. All the signals have been captured using commercial EEGs (not medical grade), NeuroSky MindWave, Emotiv EPOC, Interaxon Muse & Emotiv Insight, covering a total of 19 Brain (10/20) locations. In 2014 started capturing brain signals and released the first versions of the "MNIST" of brain digits, and in 2018 released another open dataset with a subset of the "IMAGENET" of The Brain. Version 0.05 (last update 09/28/2021) of the open database contains 24,000 brain signals of 2 seconds each, captured with the stimulus of seeing a real MNIST digit (from 0 to 9) 6,000 so far and thinking about it, + the same amout of signals with another 2 seconds of seeing a black screen, shown in between the digits, from a single Test Subject David Vivancos in a controlled still experiment to reduce noise from EMG & avoiding blinks.
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>>>!!!<<<VENUS coastal network, is now part of the Ocean Networks Canada Observatory>>>!!!<<< VENUS is a cabled undersea laboratory for ocean researchers and explorers. VENUS delivers real time information from seafloor instruments via fibre optic cables to the University of Victoria, BC. You can see ocean data live, recent and archived as well as learn more about on-going research
OpenML is an open ecosystem for machine learning. By organizing all resources and results online, research becomes more efficient, useful and fun. OpenML is a platform to share detailed experimental results with the community at large and organize them for future reuse. Moreover, it will be directly integrated in today’s most popular data mining tools (for now: R, KNIME, RapidMiner and WEKA). Such an easy and free exchange of experiments has tremendous potential to speed up machine learning research, to engender larger, more detailed studies and to offer accurate advice to practitioners. Finally, it will also be a valuable resource for education in machine learning and data mining.
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Town of Canmore Open Data Catalogue is a publicly available data sharing in ArcGIS Online portal where anyone can access and utilize data relating to the Town of Canmore, Alberta, Canada. You can browse, search, preview, and download a variety of municipal geospatial datasets.
This is the KONECT project, a project in the area of network science with the goal to collect network datasets, analyse them, and make available all analyses online. KONECT stands for Koblenz Network Collection, as the project has roots at the University of Koblenz–Landau in Germany. All source code is made available as Free Software, and includes a network analysis toolbox for GNU Octave, a network extraction library, as well as code to generate these web pages, including all statistics and plots. KONECT contains over a hundred network datasets of various types, including directed, undirected, bipartite, weighted, unweighted, signed and rating networks. The networks of KONECT are collected from many diverse areas such as social networks, hyperlink networks, authorship networks, physical networks, interaction networks and communication networks. The KONECT project has developed network analysis tools which are used to compute network statistics, to draw plots and to implement various link prediction algorithms. The result of these analyses are presented on these pages. Whenever we are allowed to do so, we provide a download of the networks.
GitHub is the best place to share code with friends, co-workers, classmates, and complete strangers. Over three million people use GitHub to build amazing things together. With the collaborative features of GitHub.com, our desktop and mobile apps, and GitHub Enterprise, it has never been easier for individuals and teams to write better code, faster. Originally founded by Tom Preston-Werner, Chris Wanstrath, and PJ Hyett to simplify sharing code, GitHub has grown into the largest code host in the world.