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1,167 results for “real-world”
Real-World Signed Graphs Annotated for Whole Graph Classification
<p><strong>Description: </strong>this corpus was designed as an experimental benchmark for a task of signed graph classification. It is composed of three datasets derived from external sources and adapted to our needs:</p> <ul> <li><strong>SpaceOrigin Conversations [1]: </strong>set of conversational graphs, each one associated to a situation of verbal abuse vs. normal situation. These conversations model interactions happening in chatrooms hosted by an MMORPG/ The graphs were originally unsigned: we attributed signed to the edges based on the polarity of the exchanged messages. </li> <li><strong>Correlation Clustering Instances [2]: </strong>set of graph generated randomly as instances of the Correlation Clustering problem, which consists in partitioning signed graphs. These graphs are not associated in any class in the original paper. We proposed a class based on certain features of the space of optimal solutions explored in [2].</li> <li><strong>European Parliament Roll-Calls [3]: </strong>vote networks extracted from the activity of French Members of the European Parliament. The original data does not have any class associated to the networks: we proposed one based on the number of political factions identified in each network in [3]. </li> </ul> <p>These data were used in [4] in order to train and assess various representation learning methods. The authors proposed Signed Graph2vec, a signed variant of Graph2vec; WSGCN, a whole-graph variant of Signed Graph Convolutional Networks (SGCN), and use an aggregated version of Signed Network Embeddings (SiNE) as a baseline. The article provides more information regarding the properties of the datasets, and how they were constituted.</p> <p><strong>Software: </strong>the software used to train the representation learning methods and classifiers is publicly available online: <a href="https://github.com/CompNet/SWGE">SWGE</a>.</p> <p><strong>References:</strong></p> <ol> <li>Papegnies, É.; Labatut, V.; Dufour, R. & Linarès, G. Conversational Networks for Automatic Online Moderation. <em>IEEE Transactions on Computational Social Systems, </em>2019<em>, </em>6:38-55. DOI: <a href="http://doi.org/10.1109/TCSS.2018.2887240">10.1109/TCSS.2018.2887240</a> ⟨<a href="https://hal.science/hal-01999546">hal-01999546</a>⟩</li> <li>Arınık, N.; Figueiredo, R. & Labatut, V. Multiplicity and Diversity: Analyzing the Optimal Solution Space of the Correlation Clustering Problem on Complete Signed Graphs. <em>Journal of Complex Networks, </em>2020<em>, </em>8(6):cnaa025. DOI: <a href="http://doi.org/10.1093/comnet/cnaa025">10.1093/comnet/cnaa025</a> ⟨<a href="https://hal.science/hal-02994011">hal-02994011</a>⟩</li> <li>Arınık, N.; Figueiredo, R. & Labatut, V. Multiple partitioning of multiplex signed networks: Application to European parliament votes. <em>Social Networks, </em>2020<em>, </em>60:83-102. DOI: <a href="http://doi.org/10.1016/j.socnet.2019.02.001">10.1016/j.socnet.2019.02.001</a> ⟨<a href="https://hal.science/hal-02082574">hal-02082574</a>⟩</li> <li>Cécillon, N.; Labatut, V.; Dufour, R. & Arınık, N. Whole-Graph Representation Learning For the Classification of Signed Networks. <em>IEEE Access</em>, 2024, 12:151303-151316. DOI: <a href="https://dx.doi.org/10.1109/ACCESS.2024.3472474">10.1109/ACCESS.2024.3472474</a> <a href="https://hal.archives-ouvertes.fr/hal-04712854" rel="nofollow">⟨hal-04712854⟩</a></li> </ol> <p><strong>Funding: </strong>part of this work was funded by a grant from the <em>Provence-Alpes-Côte-d'Azur</em> region (PACA, France) and the <em>Nectar de Code</em> company.</p> <p><strong>Citation: </strong>If you use this data or the associated source code, please cite article [4]:</p> <p><code>@Article{Cecillon2024,</code><br><code> author = {Cécillon, Noé and Labatut, Vincent and Dufour, Richard and Arınık, Nejat},</code><br><code> title = {Whole-Graph Representation Learning For the Classification of Signed Networks},</code><br><code> journal = {IEEE Access},</code><br><code> year = {2024},</code><br><code> volume = {12},</code><br><code> pages = {151303-151316},</code><br><code> doi = {10.1109/ACCESS.2024.3472474},</code><br><code>}</code></p>
A Study of Real-world Data Races in Golang (Artifact)
<p>The concurrent programming literature is rich with tools and techniques for data race detection. Less, however, has been known about real-world, industry-scale deployment, experience, and insights about data races. Golang (Go for short) is a modern programming language that makes concurrency a first-class citizen. Go offers both message passing and shared memory for communicating among concurrent threads. Go is gaining popularity in modern microservice-based systems. Data races in Go stand in the face of its emerging popularity.</p> <p>In this paper, using our industrial codebase as an example, we demonstrate that Go developers embrace concurrency and show how the abundance of concurrency alongside language idioms and nuances make Go programs highly susceptible to data races. <br> Google's Go distribution ships with a built-in dynamic data race detector based on ThreadSanitizer. Dynamic race detectors pose scalability and flakiness challenges; we discuss various software engineering trade-offs to scale this detector to work effectively at scale.</p> <p>We have deployed this detector in our 50-million lines of Go codebase hosting 2100 distinct microservices, found over 2000 data races, fixed over 1000 data races, spanning 790 distinct code patches submitted by 210 unique developers over a six-month period. Based on a detailed investigation of these data race patterns in Go, we make seven high-level observations relating to the complex interplay between the Go language paradigm and data races. </p>
Can we use hydraulic handbooks in blind trust? Two examples from a real-world complex hydraulic system
<p>This database includes the data used to produce the results for the following article:</p> <p>Bellos, V., Kossieris, P., Efstratiadis, A., Papakonstantis, I., Papanicolaou, P., Dimas, P., Makropoulos, C. 2022. Can we use hydraulic handbooks in blind trust? Two examples from a real-world complex hydraulic system. 7th IAHR Europe Congress, September 7th – 9th, 2022, Athens, Greece (accepted paper for oral presentation, in press).</p>
Real-world comprehensive genomic and immune profiling reveals distinct age- and sex-based genomic and immune landscapes in tumors of patients with non-small cell lung cancer
<p>Wallen ZD, Ko H, Nesline MK, Hastings SB, Strickland KC, Previs RA, Zhang S, Pabla S, Conroy J, Jackson JB, Saini KS, Jensen TJ, Eisenberg M, Caveney B, Sathyan P, Severson EA, Ramkissoon SH. <strong>Real-world comprehensive genomic and immune profiling reveals distinct age- and sex-based genomic and immune landscapes in tumors of patients with non-small cell lung cancer.</strong> <em>Front Immunol.</em> 2024 Jun 21;15:1413956. doi: <a href="https://doi.org/10.3389/fimmu.2024.1413956">10.3389/fimmu.2024.1413956</a>. PMID: <a href="https://pubmed.ncbi.nlm.nih.gov/38975340/">38975340</a>; PMCID: <a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC11224431/">PMC11224431</a>.</p> <p><strong>ABSTRACT</strong></p> <p>Younger patients with non-small cell lung cancer (NSCLC) (<50 years) represent a significant patient population with distinct clinicopathological features and enriched targetable genomic alterations compared to older patients. However, previous studies of younger NSCLC suffer from inconsistent findings, few studies have incorporated sex into their analyses, and studies targeting age-related differences in the tumor immune microenvironment are lacking. We performed a retrospective analysis of 8,230 patients with NSCLC, comparing genomic alterations and immunogenic markers of younger and older patients while also considering differences between male and female patients. We defined older patients as those ≥65 years and used a 5-year sliding threshold from <45 to <65 years to define various groups of younger patients. Additionally, in an independent cohort of patients with NSCLC, we use our observations to inform testing of the combinatorial effect of age and sex on survival of patients given immunotherapy with or without chemotherapy. We observed distinct genomic and immune microenvironment profiles for tumors of younger patients compared to tumors of older patients. Younger patient tumors were enriched in clinically relevant genomic alterations and had gene expression patterns indicative of reduced immune system activation, which was most evident when analyzing male patients. Further, we found younger male patients treated with immunotherapy alone had significantly worse survival compared to male patients ≥65 years, while the addition of chemotherapy reduced this disparity. Contrarily, we found younger female patients had significantly better survival compared to female patients ≥65 years when treated with immunotherapy plus chemotherapy, while treatment with immunotherapy alone resulted in similar outcomes. These results show the value of comprehensive genomic and immune profiling (CGIP) for informing clinical treatment of younger patients with NSCLC and provides support for broader coverage of CGIP for younger patients with advanced NSCLC.</p> <p><strong>DATA AVAILABILITY: </strong></p> <p>De-identified, individual-level patient data, genomic variants, and individual immune gene expression data used in the manuscript can be found in this repository (https://zenodo.org/record/11396552). An R markdown file with R code used to perform the analyses and generate figures is also provided in the repository along with the data. All versions of software used are provided in the Methods section of the manuscript. Raw sequencing data were derived from routine clinical testing of real-world patients and cannot be shared publicly. Data for immune gene expression signatures are not publicly available due to a non‑provisional patent filing covering the methods used to generate and analyze these data but are available from the corresponding author on reasonable request.</p>
Real-world Optimization Benchmark from Vehicle Dynamics - Data and Code
<p>Data and Code of five 2D single-objective optimization problems from vehicle dynamics design for benchmarking</p> <p>Conference Paper at ECTA Real-world Optimization Benchmark from Vehicle Dynamics: Specification of Problems in 2D and Methodology for Transferring (Meta-)Optimized Algorithm Parameters</p>
Improving triaging from primary care into secondary care using heterogeneous data-driven hybrid machine learning: A real-world case study of decision support system using blood test & GP referral letters - Bing Wang and Prof Weizi (Vicky) Li (University of Reading)
<p>This video is the sixth talk from our two day Future Blood Testing: Challenges & Opportunities Event that took place on the 13/09/2022.</p> <p>Improving triaging from primary care into secondary care using heterogeneous data-driven hybrid machine learning: A real-world case study of decision support system using blood test & GP referral letters - Bing Wang and Prof Weizi (Vicky) Li (University of Reading)</p> <p>Bio: Dr Weizi (Vicky) Li is the PI of the Future Blood Testing Network, an Associate Professor of Informatics and Digital Health, Deputy Director in Informatics Research Centre, Henley Business School, University of Reading. She is an interdisciplinary researcher focusing on using informatics, data science, machine learning, and digital information systems to solve real-world healthcare challenges. She is the academic lead of a large collaborative project of Improving the Quality of Healthcare through an Integrated Clinical Pathway Management Approach and Cloud based Digital Data Integration Platform, which was awarded ESRC O2RB Excellence in Impact Award in 2018 for her research impact on healthcare quality improvement. She is the academic lead of machine learning based decision support system for outpatient management which has successfully been implemented in Royal Berkshire NHS Foundation Trust and has received Research Engagement and Impact award in 2020. She has been PI on projects funded by ESRC, EPSRC, The Health Foundation, NHS and companies, working on data-driven decision support systems that use real-world data (under privacy preserving framework) from multiple sources including Electronic Patient Record in acute, community hospital and primary care settings, remote health monitoring and patient reported outcomes to develop novel technologies (including AI based methods) to support clinical and operational decision makings in patient pathway. Bing Wang is currently a PhD candidate in informatics and system science at the Informatics Research Center, Henley Business School, University of Reading. Bing’s research interests are Natural Language Processing, Machine Learning and Graph Machine Learning. Bing been working as a data scientist at Royal Berkshire NHS Foundation Trust since December 2019 during his PhD.</p> <p>Further details on this event can be found at: https://futurebloodtesting.org/event/13-14-09-2022/</p> <p>This video is an output from the Future Blood Testing Network which is funded by EPSRC under Grant Number EP/W000652/1</p> <p>YouTube Link: https://youtu.be/W6EH5l80NmU</p>
Health Record Hiccups - 5526 real-world time series with change points labelled by crowd-sourced visual inspection
<p>5526 real-world time series with labels for the location of all abrupt changes in level, variability, trend, presence/absence of data points, and irregular outliers. The time series were produced from a range of electronic health record data extracts from a large UK hospital group. Values in each data field were aggregated by day/week/month, and numeric summary values calculated for each timepoint from the (often non-numeric) data by applying simple functions (e.g. number of values present, percentage of missing values, number of distinct values, median value). Labels were produced by visual inspection of time series plots from ~2000 volunteers, via the Health Record Hiccups project on the Zooniverse platform (https://www.zooniverse.org/projects/phuongquan/health-record-hiccups). Volunteers drew a vertical line on the image wherever they saw a change point (green line if they were certain, yellow line if they were unsure). Consensus labels per image were calculated using density based clustering with noise (R v3.6.3, dbscan v1.1-5), and converted back to a date.</p>
6TiSCH traces in real-world network deployment
<p><strong>Introduction</strong></p> <p>This data set includes the detailed logs of the 6TiSCH network created with the Contiki-NG OS running on LOG-a-TEC testbed, which is located in the park area of the Jožef Stefan Institute, Ljubljana. The data set can be used to analyze the operation of the 6TiSCH network in a real-world outdoor environment, to detect network anomalies or environmental changes, to classify network uptime, throughput and traffic volume, etc. The generated logs contain all metrics (RSSI, LQI, SQN, ASN, IPv6 address, frequency channel, timestamp) for in-depth analysis.<br> <br> <strong>Network setup</strong></p> <p>6TiSCH network was set up with 15 testbed devices which and operated for 5 days. To generate additional traffic, the devices sent a UDP packet (size 10B) to the root of the network at intervals of 10 seconds (+ random jitter). Besides application packets (UDP), the devices also exchanged packets for network maintenance - UDP packets can be identified by searching for a packet length.</p> <p><strong>Data set structure</strong></p> <p>The included folder contains the logs from all devices used. The suffix of the folder name represents the last 3 digits of the device's IP address. Each folder contains several files. The prefix of a file stands for the order of the collected logs - after 1 hour elapsed, the measurements are saved in a new file.</p> <p> </p>
Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium
<p>Dataset includes 2.5 hours real-world data, for one participant from each of the technical validation study cohorts: ongestive heart failure (CHF), chronic obstructive pulmonary disease (COPD), healthy adult (HA), multiple sclerosis (MS), Parkinson’s (PD) and proximal femoral facture (PFF) linked to the manuscript entitled ‘Assessing real-world gait with digital technology? Validation, insights, and recommendations from the Mobilise-D consortium’. The attached documentation has 6 datasets and a README document.</p> <p>The MOBILISE-D project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No. 820820. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation program and the European Federation of Pharmaceutical Industries and Associations (EFPIA).</p> <p>Content on this publication reflects the author’s view and neither IMI nor the European Union, EFPIA, or any Associated Partners are responsible for any use that may be made of the information contained herein.</p>
Dataset on comparison of use of problem list versus a real-world patient record
<p>This dataset contains information about performance of clinicians interacting with two versions of a patient record, where time spent and successful completion of the task are captured.</p><p>The research has been published in:</p><p><a href=" https://doi.org/10.1016/j.ijmedinf.2023.105264">Klappe ES, Heijmans J, Groen K, ter Schure J, Cornet R, de Keizer NF</a><br><a href=" https://doi.org/10.1016/j.ijmedinf.2023.105264">Correctly structured problem lists lead to better and faster clinical decision-making in electronic health records compared to non-curated problem lists: a single-blinded crossover randomized controlled trial </a><br><a href=" https://doi.org/10.1016/j.ijmedinf.2023.105264">International Journal of Medical Informatics, 2023;180:105264.</a></p><p> </p>
Associated data underlying the publication "Flipped Classroom Real-World Activities for Learning Open Computing Concepts"
<p>Various “open” concepts in Computing, such as open standards, open data, open licenses or system interoperability are becoming more important in the professional lives of software engineers. However, students usually do not receive a systematic education about these concepts ; rather they sporadically learn about a subset of these topics. This paper presents the revised version of the Open Computing course in the University of Zagreb, Faculty of Electrical Engineering and Computing (FER), which teaches a clear set of current topics focused on open data and correlating concepts. The new e-learning course is carried out using the “flipped classroom” educational method ; students construct their knowledge in a set of real-world mini-activities throughout the course, instead of passively learning from the official course resources. In this paper, we discuss our flipped classroom activities, their relation to revised Bloom’s taxonomy of educational objectives, and present the evaluation of the first course instance us- ing this model. Students’ feedback shows they welcome this change in approach, finding the course useful and interesting, and preferring this method to the traditional full lecture setting.</p>
Towards a real-world technical test battery for remote microphone systems used with hearing prostheses
<p>Wav format audio files of both source and response for 5 different wireless remote microphone systems under various test conditions, as reported in the paper :</p> <p>Stone M.A., Lough M., Whiston H., Wilbraham K., Dillon H. (2023) Towards a real-world technical test battery for remote microphone systems used with hearing prostheses. Trends in Hearing DOI: 10.1177/23312165231182518</p> <p>Also includes the MATLAB script used to analyse the recordings.</p>
Datasets of paper "Towards Assessing the Real-World Impact of Defects in Blockchain-based Smart Contracts"
<p>Datasets of paper "Towards Assessing the Real-World Impact of Defects in Blockchain-based Smart Contracts" published on the 1st International Workshop on Software Defect Datasets (SDD 2023).</p> <p>The GitHub repository is available here: <a href="https://github.com/MichaelHettmer/sdd23">https://github.com/MichaelHettmer/sdd23</a></p>
Real-world human-robot interaction data with robotic pets in user homes in the United States and South Korea
<p>Socially-assistive robots (SARs) hold significant potential to transform the management of chronic healthcare conditions (e.g. diabetes, Alzheimer's, dementia) outside the clinic walls. However doing so entails embedding such autonomous robots into people's daily lives and home living environments, which are deeply shaped by the cultural and geographic locations within which they are situated. That begs the question of whether we can design autonomous interactive behaviors between SARs and humans based on universal machine learning (ML) and deep learning (DL) models of robotic sensor data that would work across such diverse environments. To investigate this, we conducted a long-term user study with 26 participants across two diverse locations (the United States and South Korea) with SARs deployed in each user's home for several weeks. We collected robotic sensor data every second of every day, combined with sophisticated ecological momentary assessment (EMA) sampling techniques, to generate a large-scale dataset of over 270 million data points representing 173 hours of randomly-sampled naturalistic interaction data between the human and robot pet. Interaction behaviors included activities like playing, petting, talking, cooking, etc.</p>
A Study to Observe Vedolizumab and Anti-tumour Necrosis Factors (Anti-TNFs) Outcomes in Real-world Biologic Ulcerative Colitis (UC) and Crohn's Disease (CD) Participants
ClinicalTrials.gov study NCT03710486. IPD Sharing: YES. Countries: 2. Publications: 1.
Clinical Effectiveness of Body Fat Distribution Imaging in Real-World Practice: The BODY-REAL Study
ClinicalTrials.gov study NCT04763772. IPD Sharing: YES. Countries: 1. Publications: 1.
Illustrating potential effects of alternate control populations on real-world evidence-based statistical analyses
Open the record for dataset details and reuse information.
RadCases evaluation results: Evaluating acute image ordering for real-world patient cases via language model alignment with radiological guidelines
Open the record for dataset details and reuse information.
Real-world human-robot interaction data with robotic pets in user homes in the United States and South Korea
Open the record for dataset details and reuse information.
Nationwide real-world implementation of AI for cancer detection in population-based mammography screening (PRAIM)
Open the record for dataset details and reuse information.
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.