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25 results for “information operations”
Telemedicine Control Tower for the Operating Room: Navigating Information, Care and Safety
ClinicalTrials.gov study NCT03923699. IPD Sharing: NO. Countries: 1. Publications: 4.
Optimizing Small Business Operations through Information Architecture and Enterprise Engineering
<p> </p> <p>This research paper investigates the critical significance of information architecture and enterprise engineering in streamlining small business operations for continued expansion and competitiveness. ( Carrasco Ramirez, J. G. (2024).</p> <p> With rapid technological developments and shifting customer demands, small businesses confront mounting challenges to adjust and flourish amid change. Drawing upon academic sources and practical findings, this study reveals how purposeful implementation of information ( Carrasco Ramirez, J. G. (2024) architecture enables effective data handling, knowledge sharing, and decision-making mechanisms within small organizations.Ramírez, J. G. C. (2023)</p> <p>Additionally, it outlines the tenets of enterprise engineering, stressing the need for creating coherent business frameworks, processes, and systems to maximize operational efficacy and resource allocation. By integrating information architecture and enterprise engineering approaches, small businesses can bolster their organizational resiliency and maintain a competitive edge in today's dynamic marketplace.</p> <p> Central to these strategies is the development and implementation of comprehensive business plans. This abstract explores the significance of business planning in driving effective management strategies, highlighting its role in guiding decision-making, fostering organizational alignment, and facilitating proactive adaptation to changing market conditions. (Carrasco Ramirez, J. G. (2024).</p> <p> </p> <p> </p> <p> </p> <p> </p>
Effect of Informative Cesarean Delivery Operative Steps Video to Maternal Anxiety Level: a Randomized Controlled Trial
<p>This is a SPSS data for analysis in "Effect of Informative Cesarean Delivery Operative Steps Video to Maternal Anxiety Level: a Randomized Controlled Trial" research, and video is used for intervention group.</p>
Twitter dataset about Information Operations in Honduras and UAE
<p>Dataset concerning coordinated behaviour in Information Operations in Honduras and United Arab Emirates, consisting of two parts:</p> <ul> <li>malicious tweets, provided by Twitter/X Moderation Research Consortium (TMRC), concerning well-known Information Operations (IOs).</li> <li>genuine enriching tweets, recovered using Twitter/X search APIs with Academic Elevated Access. Those tweets were published by "genuine" users (i.e. users not into the malicious dataset) and concerned the main topics of the IOs</li> </ul> <p>This dataset allows to explore meaningful patterns of coordination which could distinguish conversations with malicious intent from genuine conversations.</p> <ul> <li>1,2M malicious or genuine tweets about the Honduras IO, shared between 11 September 2019 and 8 January 2020</li> <li>2,8M malicious or genuine tweets about the UAE IO, shared between 27 January 2019 and 26 May 2019</li> </ul>
A three-year building operational performance dataset for informing energy efficiency
Open the record for dataset details and reuse information.
Information and influence operations in the cyberspace
<p>What are the main security threats affecting European liberal democracies in the digital era? Two graphics that show the current perceptions of threats (number of EU countries) and Perceptions of vulnerability and resilience against security threats (number of EU countries).</p> <p>video : https://www.youtube.com/watch?v=O8xGg-0ef2U&feature=youtu.be </p>
Last mile operational information
<p>Examples and actual Last mile delivery round data for 17-06-2021 for the Madrid region for multiple vehicles</p>
Optimizing Acute Post-Operative Dental Pain Management Using New Health Information Technology
ClinicalTrials.gov study NCT03881891. IPD Sharing: NO. Countries: 1. Publications: 1.
Operational Assessment of Laboratory Information System for MDR-TB in Lima, Peru
ClinicalTrials.gov study NCT01201941. IPD Sharing: Not stated. Countries: 1. Publications: 1.
GECCO Industrial Challenge 2015 Dataset: A heating system dataset for the 'Recovering missing information in heating system operating data' competition at the Genetic and Evolutionary Computation Conference 2015, Madrid, Spain
<p>Dataset of the 'Industrial Challenge: Recovering missing information in heating system operating data' competition hosted at The Genetic and Evolutionary Computation Conference (GECCO) July 11th-15th 2015, Madrid, Spain</p> <p> </p> <p>The task of the competition was to recover (impute) missing information in heating system operation time series'.</p> <p> </p> <p>Included in zenodo: </p> <p>- dataset of heating system operational time series with missing values</p> <p>- additional material and descriptions provided for the competition</p> <p> </p> <p>The competition was organized by:</p> <p>M. Friese, A. Fischbach, C. Schlitt, T. Bartz-Beielstein (TH Köln)</p> <p> </p> <p>The dataset was provided by:</p> <p>Major German heating systems supplier (S. Moritz)</p> <p> </p> <p> </p> <p>Industrial Challenge: Recovering missing information in heating system operating data</p> <p> </p> <p>The Industrial Challenge will be held in the competition session at the Genetic and Evolutionary Computation Conference. It poses difficult real-world problems provided by industry partners from various fields. Highlights of the Industrial Challenge include interesting problem domains, real-world data and realistic quality measurement</p> <p>Overview</p> <p>In times of accelerating climate change and rising energy costs, increasing energy efficiency and reducing expenses becomes a high priority goal for businesses and private households alike. Modern heating systems record detailed operating data and report this data to a central system. Here, the operating data can be correlated and analyzed to detect potential optimization opportunities or anomalies like unusually high energy consumption. Due to various difficulties this data might be incomplete which makes accurate forecasting even harder.</p> <p>Goal of the GECCO 2015 Industrial Challenge is to develop capable procedures to recover missing information in heating system operating data. Adequate recovery of the missing data enables more accurate forecastings which allow for intelligent control of the heating systems, and therefore contributes to a positive energy balance and reduced expenses.</p> <p> </p> <p><strong>Submission deadline:</strong><br> June 22, 2015</p> <p><strong>Official Webpage:</strong><br> <a href="http://www.spotseven.de/gecco-challenge/gecco-challenge-2015/">www.spotseven.de/gecco-challenge/gecco-challenge-2015/</a></p> <p> </p>
Evaluation of User Experience for Dashboard Project Management Information System within the Project Operation Unit of a Telecommunication Company
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Physics-informed Partitioned Coupled Neural Operator for Complex Networks Datasets
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Pre-Operative Window of Adjuvant Endocrine Therapy to Inform RT Decisions in Older Women With Early-Stage Breast Cancer
ClinicalTrials.gov study NCT04272801. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Impact of Pre-Operative Web-based Breast Cancer Information on the Quality of Patient Decision-Making
ClinicalTrials.gov study NCT03116035. IPD Sharing: NO. Countries: 0. Publications: 1.
Labeled Datasets for Research on Information Operations
<h1><strong>Labeled Datasets for Research on Information Operations</strong></h1> <h2><strong>Compliance with Platform Terms<br></strong></h2> <p>To comply with the platform terms, we ask that you download one data file per researcher, per day. By requesting access, you agree to abide by these rules.</p> <h2><strong>Data Sharing Policy</strong></h2> <p>Following university, security, and ethical guidelines, we are unable to respond to data requests from research institutions that are affiliated with foreign military organizations or from a list of countries of concern (currently China, North Korea, Iran, Russia, Cuba, Syria, and Venezuela).</p> <h2><strong>README</strong></h2> <p>19-November-2024<br>Contact: <a href="https://osome.iu.edu/">Observatory on Social Media</a></p> <p><strong>Dataset Articles</strong><br>This dataset is collected and processed according to the paper "<a href="https://doi.org/10.48550/arXiv.2411.10609">Labeled Datasets for Research on Information Operations</a>."</p> <p><strong>Description</strong><br>These datasets contain data curated for research on information operations (IO) and includes both labeled IO and control data. The datasets cover 26 verified IO campaigns from various countries and provide comprehensive records of posts from IO accounts alongside control posts from legitimate accounts discussing similar topics during the same periods. The datasets enable the development and benchmarking of IO detection methods by comparing coordinated versus organic accounts.</p> <p><strong>License</strong><br>This dataset is available under the <a href="https://creativecommons.org/licenses/by-nc-nd/4.0/">Attribution-NonCommercial-NoDerivatives 4.0 International</a> license. If you use this data, please cite the original paper.</p> <p><strong>Dataset Content</strong><br>The dataset includes anonymized fields to preserve privacy, and is structured with the following columns:</p> <ul> <li>postid: Unique identifier for each post within the dataset.</li> <li>post_text: The textual content of the post. The PII inside post_text such as mentions and URLs are hashed</li> <li>application_name: Hashed version of the name of the application or platform from which the post was made.</li> <li>post_language: Language in which the post was written.</li> <li>in_reply_to_postid: Anonymized ID of the post this entry is replying to, if applicable.</li> <li>in_reply_to_accountid: Anonymized ID of the account the post is replying to, if applicable.</li> <li>post_time: Timestamp indicating when the post was made.</li> <li>accountid: Unique anonymized ID for the account that created the post.</li> <li>account_profile_description: Description provided by the account holder in their profile.</li> <li>follower_count: Number of followers the account had at the time of data collection.</li> <li>following_count: Number of accounts the user was following at the time of data collection.</li> <li>account_creation_date: Date when the account was created.</li> <li>is_repost: Boolean indicator if the post is a repost.</li> <li>reposted_accountid: Anonymized ID of the original account that made the reposted post, if applicable.</li> <li>reposted_postid: Anonymized ID of the original post that was reposted, if applicable.</li> <li>hashtags: Hashtags included in the post content, if any.</li> <li>urls: Hashed URLs shared within the post, if any.</li> <li>account_mentions: Anonymized ID of accounts mentioned within the post, if any.</li> <li>is_control: Boolean indicator marking whether the post is from a control (True) or IO (False) account.</li> </ul> <p>Data for different campaigns are organized in separate versions of this repository, which can be also found below or in the excel file shared.</p> <table> <tbody> <tr> <td><strong>Campaign Name</strong></td> <td><strong>URL</strong></td> </tr> <tr> <td>Armenia</td> <td><a href="https://doi.org/10.5281/zenodo.14141550">https://doi.org/10.5281/zenodo.14141550</a></td> </tr> <tr> <td>Bangladesh</td> <td><a href="https://doi.org/10.5281/zenodo.14188947">https://doi.org/10.5281/zenodo.14188947</a></td> </tr> <tr> <td>Catalonia</td> <td><a href="https://doi.org/10.5281/zenodo.14188959">https://doi.org/10.5281/zenodo.14188959</a></td> </tr> <tr> <td>China_1</td> <td><a href="https://doi.org/10.5281/zenodo.14188970">https://doi.org/10.5281/zenodo.14188970</a></td> </tr> <tr> <td>China_2</td> <td><a href="https://doi.org/10.5281/zenodo.14188975">https://doi.org/10.5281/zenodo.14188975</a></td> </tr> <tr> <td>Cuba Part 1</td> <td><a href="https://doi.org/10.5281/zenodo.14188984">https://doi.org/10.5281/zenodo.14188984</a></td> </tr> <tr> <td>Cuba Part 2</td> <td><a href="https://doi.org/10.5281/zenodo.14189008">https://doi.org/10.5281/zenodo.14189008</a></td> </tr> <tr> <td>Ecuador</td> <td><a href="https://doi.org/10.5281/zenodo.14189015">https://doi.org/10.5281/zenodo.14189015</a></td> </tr> <tr> <td>Egypt_UAE</td> <td><a href="https://doi.org/10.5281/zenodo.14189018">https://doi.org/10.5281/zenodo.14189018</a></td> </tr> <tr> <td>Ghana_Nigeria</td> <td><a href="https://doi.org/10.5281/zenodo.14189028">https://doi.org/10.5281/zenodo.14189028</a></td> </tr> <tr> <td>Iran_1</td> <td><a href="https://doi.org/10.5281/zenodo.14189037">https://doi.org/10.5281/zenodo.14189037</a></td> </tr> <tr> <td>Iran_2</td> <td><a href="https://doi.org/10.5281/zenodo.14189038">https://doi.org/10.5281/zenodo.14189038</a></td> </tr> <tr> <td>Iran_3</td> <td><a href="https://doi.org/10.5281/zenodo.14189041">https://doi.org/10.5281/zenodo.14189041</a></td> </tr> <tr> <td>Iran_4</td> <td><a href="https://doi.org/10.5281/zenodo.14189047">https://doi.org/10.5281/zenodo.14189047</a></td> </tr> <tr> <td>Iran_5</td> <td><a href="https://doi.org/10.5281/zenodo.14189048">https://doi.org/10.5281/zenodo.14189048</a></td> </tr> <tr> <td>Iran_6</td> <td><a href="https://doi.org/10.5281/zenodo.14189053">https://doi.org/10.5281/zenodo.14189053</a></td> </tr> <tr> <td>Qatar</td> <td><a href="https://doi.org/10.5281/zenodo.14189058">https://doi.org/10.5281/zenodo.14189058</a></td> </tr> <tr> <td>Russia_1</td> <td><a href="https://doi.org/10.5281/zenodo.14189061">https://doi.org/10.5281/zenodo.14189061</a></td> </tr> <tr> <td>Russia_2</td> <td><a href="https://doi.org/10.5281/zenodo.14189072">https://doi.org/10.5281/zenodo.14189072</a></td> </tr> <tr> <td>Russia_3</td> <td><a href="https://doi.org/10.5281/zenodo.14189075">https://doi.org/10.5281/zenodo.14189075</a></td> </tr> <tr> <td>Russia_4</td> <td><a href="https://doi.org/10.5281/zenodo.14189078">https://doi.org/10.5281/zenodo.14189078</a></td> </tr> <tr> <td>Russia_5</td> <td><a href="https://doi.org/10.5281/zenodo.14189081">https://doi.org/10.5281/zenodo.14189081</a></td> </tr> <tr> <td>Spain</td> <td><a href="https://doi.org/10.5281/zenodo.14189086">https://doi.org/10.5281/zenodo.14189086</a></td> </tr> <tr> <td>Thailand</td> <td><a href="https://doi.org/10.5281/zenodo.14189095">https://doi.org/10.5281/zenodo.14189095</a></td> </tr> <tr> <td>UAE</td> <td><a href="https://doi.org/10.5281/zenodo.14189098">https://doi.org/10.5281/zenodo.14189098</a></td> </tr> <tr> <td>Venezuela_1</td> <td><a href="https://doi.org/10.5281/zenodo.14189107">https://doi.org/10.5281/zenodo.14189107</a></td> </tr> <tr> <td>Venezuela_2</td> <td><a href="https://doi.org/10.5281/zenodo.14189110">https://doi.org/10.5281/zenodo.14189110</a></td> </tr> </tbody> </table>
Pharmacogenomics Information in Enhancing Post-operative Total Joint Replacement Pain Management: a Pilot Study
ClinicalTrials.gov study NCT02711592. IPD Sharing: NO. Countries: 1. Publications: 0.
Individualized Data-based High Simulation of Bronchoscopy Operations in Preoperative Bronchoscopy Informed Consent
ClinicalTrials.gov study NCT06441149. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Is Any Additional Information Gained Regarding Margins Using 3D Tomosynthesis Vs 2D Conventional Digital Imaging When Imaging Operative Breast Specimens?
ClinicalTrials.gov study NCT02096185. IPD Sharing: Not stated. Countries: 1. Publications: 0.
The Effect of Information About the Operating Room Environment With Virtual Reality Glasses on the Anxiety Level
ClinicalTrials.gov study NCT05899790. IPD Sharing: NO. Countries: 1. Publications: 0.
Patients' Readings of Pre-operative Informed Consent Forms
ClinicalTrials.gov study NCT03555760. IPD Sharing: UNDECIDED. 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.