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9 results for “Time awareness”
Dataset and source code for ICSME2017 paper "Supervised vs Unsupervised Models: A Holistic Look at Effort-Aware Just-in-Time Defect Prediction"
<p>Dataset and source code for ICSME2017 paper “Supervised vs Unsupervised Models: A Holistic Look at Effort-Aware Just-in-Time Defect Prediction”</p> <p>There are four different models in the paper (i.e., EALR, LT, CBS and OneWay). Each model was implemented in a single Java file in the model package. To reproduce the experiment results of each model in the paper, just run the main method in the corresponding Java file. </p> <p> </p>
Energy consumption, execution time and fail requests rate of a proactive energy-aware auto-scaling solution for edge-based infrastructures applied to real-world workload.
<p>Spreadsheet of the results obtained with our horizontal auto-scaling proposal presented in "A proactive energy-aware auto-scaling solution for edge-based infrastructures". In that research, we present a proactive horizontal auto-scaling framework for edge infrastructures, which considers both the base (idle) and dynamic (due to application execution) energy consumption of edge nodes and the node scaling mechanism. Simulations were performed with the EdgeCloudSim simulator with a workload provided by Shanghai Telecom and the results show up to a 92.5% decrease in energy consumption, a failed request rate of up to 0%, and reasonable execution times of the auto-scaling process for different problem sizes.</p> <p>Proactive auto-scaling mechanisms in edge-based infrastructures can anticipate user service requests by allocating computing resources while supporting the quality of service needed by a vast range of applications requiring, e.g., a low latency or response time. </p> <p>This work is supported by the European Union's H2020 research and innovation program under grant agreement DAEMON 101017109 and by the projects co-financed by FEDER funds LEIA UMA18-FEDERJA-15, MEDEA RTI2018-099213-B-I00 (MCI/AEI) and RHEA P18-FR-1081.</p>
Silver Linings in Covid-19: increased appreciation of relationships and self-awareness are associated with wellbeing at different times in the pandemic
<p>Dataset</p>
The replication page for paper: Revisiting Supervised and Unsupervised Models for Effort-Aware Just-in-Time Defect Prediction
<p>The replication page for the paper submitted to EMSE: Revisiting Supervised and Unsupervised Models for Effort-Aware Just-in-Time Defect Prediction.</p> <p>There are four java files in the package named "model". Each file corresponds to one specific model (CBS and CBS+ are in the same file). Each file has a main function and you will get the experiment results when running the main function.</p> <p> </p>
The relation between deviation from the balanced time perspective and quality of life among older people. The mediating role of death anxiety and the moderating role of awareness of aging
<p><em><span>Objectives</span></em><span>. In the current study, one of the objectives was to check if the deviation from a balanced time perspective (DBTP) is a predictor of the quality of life of the elderly. Another objective investigated whether awareness of aging is a moderator and death anxiety a mediator of the relationship between PTSD and quality of life. <em>Method.</em> 436 elderly people participated in this research (M = 68.27; SD= 6.56; 66.7% female, 33.3% male). They completed 4 instruments to evaluate the variables included in the study: World Health Organization Quality of Life, Zimbardo Time Perspective Inventory - Short version, Death Anxiety Scale and Awareness of Age-Related Change 10-Item Short Form (awareness of aging). <em>Results</em>. Statistical analyzes highlighted the fact that DBTP is not a predictor of quality of life, but it can positively predict death anxiety. Also, awareness of aging does not moderate the relationship between DBTP and quality of life. Finally, death anxiety negatively predicts quality of life, but also mediates the relationship between DBTP and quality of life. <em>Discussion</em>. This study brought to the fore some concepts less addressed in the case of the elderly population in Romania, which could lead to the identification of some benefits for improving the quality of life of the elderly. Starting from the conclusions obtained, promotion and intervention plans can be developed to improve mental and physical health services. The inclusion process of the elderly in as many social activities as possible can also be considered.</span></p> <p><strong><span> </span></strong></p>
Impact on Hypoglycaemia Awareness of Real Time CGM and Intermittent Continuous Glucose Data
ClinicalTrials.gov study NCT03028220. IPD Sharing: NO. Countries: 0. Publications: 2.
Time Aware Simulated Annealing Experimental Results
Open the record for dataset details and reuse information.
Study to Determine if Patients Exposed to General Anesthesia Significant Numbers of Times Would Increase the Risk for Intraoperative Awareness.
ClinicalTrials.gov study NCT05857618. IPD Sharing: NO. Countries: 1. Publications: 0.
How Does Task Loading in PICU Impact on Clinician Situational Awareness and Awareness of the Passage of Time?
ClinicalTrials.gov study NCT05383222. IPD Sharing: NO. Countries: 1. Publications: 0.
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.