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997 results for “Awareness”
Dam Break Videos and Outputs of the Paper "Increasing flood awareness through dam-break serious games"
<p>This is the repository of the Dam-Break output results of the dams simulated in the paper "Increasing flood awareness through dam-break serious games".</p> <p> </p> <p>This repository contains .csv of modeling results of the dams simulated in the paper. In addition, it contains videos showing the evolution of the simulated states (e.g., flood depths, velocities, and forces) for all dams. </p> <p> </p> <p>For the Brumadinho analysis, we show the cross-section data used to simulate the dam.</p> <p> </p> <p>If you have any questions, please reach em out in marcusnobrega.engcivil@gmail.com.</p>
Media Bias Aware Simulation Dataset
<p>We utilized the Hyperpartisan News Detection Dataset, released with the SemEval-2019 Task 4 Hyperpartisan detection task, due to its extensive bias labels. To ensure accurate bias labels, we used the Overlap-checking (1:1) model, retaining only articles where the distant supervision bias labels matched the model's predictions. This validation process resulted in 409,757 articles.</p> <p>These articles span from 1960 to 2018, with a sparse distribution in earlier years. We focused on articles from May 1, 2017, to December 31, 2017, resulting in a subset of 72,940 news articles, ensuring a consistent daily news flow. We processed this subset by removing HTML tags and special characters and generating news summaries using PEGASUS. We used Latent Dirichlet Allocation (LDA) to categorize the articles into 20 news themes, based on perplexity scores.</p> <p>This dataset was then fed into the simulation framework, with a cut-off date of June 24, 2017.</p> <ul> <li><strong>News Recommendation Dataset</strong>: Includes user-item interaction records from May 1 to June 24, providing users' reading histories and interacted news articles. <ul> <li><strong>Training Split</strong>: Data from May 1 to June 17, used to train news recommendation algorithms.</li> <li><strong>Evaluation Split</strong>: Data from June 17 to June 24, used to evaluate the trained recommendation algorithms.</li> </ul> </li> <li> <p><strong>Candidate News Dataset</strong>: News articles published from June 25 to December 31, presented to users during simulations.</p> </li> </ul> <p>For more information, please visit <a href="https://github.com/ruanqin0706/UserRecSimulation" target="_new" rel="noreferrer">https://github.com/ruanqin0706/UserRecSimulation</a>.</p>
Fig. 3 in The Implementation Of Nature Management Plans For Specially Protected Nature Territories In Latvia: Stakeholder Awareness, Applying Gis Tools, Indicators For Management
Fig. 3. Map of the landscape terrain at Nature park "Dridža ezers" ("Lake Dridža")
Fig. 1 in The Implementation Of Nature Management Plans For Specially Protected Nature Territories In Latvia: Stakeholder Awareness, Applying Gis Tools, Indicators For Management
Fig. 1. Interactive map of recreation sites at Nature park "Dridža ezers" ("Lake Dridža")
Data for Isotype-aware Inference of B cell Clonal Lineage Trees from Single-cell Sequencing Data
<p>This is the accompanying data to the manuscript titled<em> Isotype-aware Inference of B cell Clonal Lineage Trees from Single-cell Sequencing Data</em>. To reproduce the TRIBAL output please use this <a href="https://doi.org/10.5281/zenodo.12741290">code repository</a> as the arguments and codebase may have changed since release. </p>
Inverse Design of Metamaterials with Manufacturing-Aware Spectrum-to-Shape Diffusion Models
<p>The dataset includes detailed information on the MIM tri-layer metamaterial structures designed and used for training the DiffMeta framework. Specifically, it contains 60000 data:</p> <p>Structural Data: Detailed geometric patterns and composition parameters of the designed MIM tri-layer metamaterial structures.</p> <p>Spectral Data: Spectral measurements on MIM tri-layer metamaterial structures, including emissivity, reflectivity and transmittance spectra across a range of wavelengths.<br><br>The dataset is meticulously organized to facilitate the replication of our study and support further research in the field of metamaterial design. </p>
Write-only File System for Privacy-aware Wireless Sensor Networks Evaluation Dataset
<p>Evaluation dataset for the paper <strong>"WoFS: A Write-only File System for Privacy-aware Wireless Sensor Networks"</strong> published at the <em>49th IEEE Conference on Local Computer Networks (2024)</em></p>
A Power-Aware, Self-Adaptive Macro Data Flow Framework
<p><em><strong>Abstract: </strong>The dataflow programming model has been extensively used as an effective solution to implement efficient parallel programming frameworks. However, the amount of resources allocated to the runtime support is usually fixed once by the programmer or the runtime, and kept static during the entire execution. While there are cases where such a static choice may be appropriate, other scenarios may require to dynamically change the parallelism degree during the application execution. In this paper we propose an algorithm for multicore shared memory platforms, that dynamically selects the optimal number of cores to be used as well as their clock frequency according to either the workload pressure or to explicit user requirements. We implement the algorithm for both structured and unstructured parallel applications and we validate our proposal over three real applications, showing that it is able to save a significant amount of power, while not impairing the performance and not requiring additional effort from the application programmer.</em></p> <p>This dataset contains the raw data of the experiments and the scripts used to plot them.</p> <p> </p>
State-Aware Concurrency Throttling
<p><em><strong>Abstract:</strong> Reconfiguration of parallel applications has gained traction with the increasing emphasis on energy/performance trade-off. The ability to dynamically change </em><em>the amount of</em><em> resources used by an application allows </em><em>reaction</em><em> to changes in the environment, in the application behavior or in the user's requirements. A popular technique consists in changing the number of threads used by the application (Dynamic Concurrency Throttling). Although this provides good control of application performance and power consumption, managing the technique can impose a significant burden on </em><em>the application</em><em> programmer, mainly due to state management and redistribution following the addition or removal of a thread. Nevertheless, some common state access patterns have been identified in some popular applications. By leveraging on this knowledge, we will describe how it is possible </em><em>to simplify</em><em> the state management procedures following a Concurrency Throttling operation.</em></p> <p>This dataset contains the raw data of the experiments and the scripts used to plot them.</p>
Nornir: A Customizable Framework for Autonomic and Power-Aware Applications
<p><strong><em>Abstract: </em></strong><em>A desirable characteristic of modern parallel applications is the ability to dynamically select the amount of resources to be used to meet requirements on performance or power consumption. In many cases, providing explicit guarantees on performance is of paramount importance. In streaming applications, this is related with the concept of elasticity, i.e. being able to allocate the proper amount of resources to match the current demand as closely as possible. Similarly, in other scenarios, it may be useful to limit the maximum power consumption of an application to do not exceed the power budget. In this paper we propose Nornir, a customizable C++ framework for autonomic and power-aware parallel applications on shared memory multicore machines. Nornir can be used by autonomic strategy designers to implement new algorithms and by application users to enforce requirements on applications.</em></p> <p>This dataset contains the raw data of the experiments and the scripts used to plot them.</p>
A Reconfiguration Algorithm for Power-Aware Parallel Applications
<p><strong><em>Abstract: </em></strong><em>In current computing systems, many applications require guarantees on their maximum power consumption to not exceed the available power budget. On the other hand, for some applications, it could be possible to decrease their performance, yet maintaining an acceptable level, in order to reduce their power consumption. To provide such guarantees, a possible solution consists in changing the number of cores assigned to the application, their clock frequency and the placement of application threads over the cores. However, power consumption and performance have different trends depending on the application considered and on its input. Finding a configuration of resources satisfying user requirements is in the general case a challenging task. In this paper we propose Nornir, an algorithm to automatically derive, without relying on historical data about previous executions, performance and power consumption models of an application in different configurations. By using these models, we are able to select a close to optimal configuration for the given user requirement, either performance or power consumption. The configuration of the application will be changed on-the-fly throughout the execution to adapt to workload fluctuations, external interferences and/or application's phase changes. We validate the algorithm by simulating it over the applications of the PARSEC benchmark suite. Then, we implement our algorithm and we analyse its accuracy and overhead over some of these applications on a real execution environment. Eventually, we compare the quality of our proposal with that of the optimal algorithm and of some state of the art solutions.</em></p> <p>This dataset contains the raw data of the experiments and the scripts used to plot them.</p> <p> </p>
Optimizing Quality-Aware Big Data Applications in the Cloud — Supporting Data
<p>Supporting experimental data for the paper "Optimizing Quality-Aware Big Data Applications in the Cloud", submitted to IEEE TCC.</p>
Awareness creation, dissemination and stakeholder engagement dataset
<p>This dataset has been developed with a view to assessing the results and impact of the awareness creation, dissemination and stakeholder engagement activities of INNO-4-AGRIFOOD project.</p>
Dataset used in the article: Cunico, G., Aivazidou, E., Mollona, E. (2019), "European Cohesion Policy performance and citizens' awareness: A holistic System Dynamics framework", Investigaciones Regionales – Journal of Regional Research (In Press)
<p>In the context of the abovementioned article, interviews with experts about EU funding, as well as a workshop, were performed to find any missing factors or links in the conceptual model developed. This dataset provides detailed information about the interviews and the workshop. The related research is conducted in the context of the Horizon 2020 project PERCEIVE (www.perceiveproject.eu).</p>
Resources for "BMF CP 100: Engaging children with nature to cultivate their environmental awareness and protection"
<p><span>The current study is conducted to examine the following research questions:</span></p> <ul> <li><span>How is engaging children with nature associated with their environmental awareness?</span></li> <li><span><span><span> </span></span></span><span>How is engaging children with nature associated with their environmental protection participation?</span></li> </ul>
Implementation of an adaptive bias-aware extended Kalman filter for sea-ice data assimilation in the HARMONIE-AROME numerical weather prediction system: numerical experiments
<p>This data set provides the post-processed output of the numerical experiments performed to assess the possible effects of applying sea ice data assimilation within the surface analysis procedure of the HARMONIE-AROME NWP system. Results of five numerical experiments are provided:</p> <ul> <li>HA-REF – reference experiment <em>without</em> sea ice data assimilation applied, and with blending for upper-air initialization</li> <li>HA-EKF – sensitivity experiment with sea ice data assimilation applied, and with blending for upper-air initialization</li> <li>3DVAR-REF – reference experiment <em>without</em> sea ice data assimilation applied, and with 3DVAR for the upper-air analysis</li> <li>3DVAR-EKF – sensitivity experiment with sea ice data assimilation applied, and with 3DVAR for the upper-air analysis</li> <li>3DVAR-EKF-TS – sensitivity experiment with sea ice data assimilation, and with 3DVAR for the upper-air analysis using coupled surface and atmospheric data assimilation procedures</li> </ul> <p>For the HA-REF and HA-EKF experiments a subset of the gridded model output is provided; for the 3DVAR-REF, 3DVAR-EKF and 3DVAR-EKF-TS experiments a subset of the gridded model output and model data extracted at the positions of the SYNOP and TEMP stations within the model domain are provided. Additionally, in-situ observations, covering the same time period as the 3DVAR-REF, 3DVAR-EKF, 3DVAR-EKF-TS experiments, are provided.</p>
Graphine: A Dataset for Graph-aware Terminology Definition Generation
<p>This is the dataset of our EMNLP 2021 paper:</p> <p>Graphine: A Dataset for Graph-aware Terminology Definition Generation. </p> <p>Please read the "readme.md" in it for the format of the dataset.</p>
The awareness, visibility and support for young carers across Europe: a Delphi study
<p>Across Europe, young carers (YCs) and their need for support receive limited attention in the media, policy and empirical research, even though, similar to adult carers, they also provide care to ill family members. The Delphi study, a qualitative research methodology, which provides the focus for this article, had the overall aim of exploring existing successful strategies to support YCs. Compared to YCs, even less is known about adolescent young carers (AYCs), a group that is in a critical life transition phase. The study forms part of an EU Horizon 2020 funded research project on AYCs aged 15–17 years old. A two-round Delphi study was conducted with 66 experts on YCs from 10 European countries. Topics included: (i) visibility and awareness-raising of YCs at local, regional, and national levels, (ii) current interventions to support YCs, and (iii) future strategies to support YCs. Experts reported a lack of visibility and awareness about YCs in general, and AYCs in particular. Although awareness is slowly increasing in most countries, with the UK ranked highest, experts acknowledged that it remains challenging to identify YCs in many countries. Furthermore, the level and type of support available for YCs differs, with most countries mainly offering support on a local level. Diverse views were expressed regarding future strategies to support YCs. Experts highlighted the importance of specific legislation to formalise the rights of YCs, and the issue of whether young people should be safeguarded from caregiving or if this should be considered part of regular family life. They also emphasised the relevance of available integrated support services for YCs, including schools, family, health and social care. In most European countries, there is a lack of awareness and visibility on YCs. Identification of YCs is a crucial first step and there is need for a common definition of YCs, together with greater opportunities for young adults to identify themselves as YCs.</p>
Privacy-Enhancing Technology and Everyday Augmented Reality: Understanding Bystanders' Varying Needs for Awareness and Consent
<p>This data is for our ACM IMWUT 2022 paper "Privacy-Enhancing Technology and Everyday Augmented Reality: Understanding Bystanders' Varying Needs for Awareness and Consent". See the README for more details.</p>
Tampere - Awareness of citizens regarding urban nature and ecosystem services
<p>Results of the awareness of citizens regarding urban nature and ecosystem services survey among residents of Vuores neighbourhood in Tampere.</p>
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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.