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1,041
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Dataset results
1,041 results for “Internet”
Scale-up of an Internet-Delivered Study for HIV+ Men
ClinicalTrials.gov study NCT02023580. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Internet-based CBIT for Children With Chronic Tics
ClinicalTrials.gov study NCT04087616. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Feasibility and Efficacy of a Brief Mindfulness-Based Intervention SMOKING INTERVENTION VIA THE INTERNET
ClinicalTrials.gov study NCT04572126. IPD Sharing: NO. Countries: 1. Publications: 3.
Targeting Fear of Cancer Recurrence in Cancer Survivors: Evaluation of Internet-Based Emotional Freedom Techniques and Internet-Based Mindfulness Meditation as Intervention Strategies
ClinicalTrials.gov study NCT06175208. IPD Sharing: NO. Countries: 1. Publications: 1.
Internet-delivered Psychodynamic Therapy for Social Anxiety Disorder (SOFIA)
ClinicalTrials.gov study NCT02105259. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Internet Delivered CBT for Body Dysmorphic Disorder
ClinicalTrials.gov study NCT02010619. IPD Sharing: Not stated. Countries: 1. Publications: 4.
Recurrent pain symptoms in adolescents with generalized and specific problematic Internet use: Associations analysis, confounding and mediating effects of comorbid psychosocial problems
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Data from: Internet-delivered therapist-guided physical activity for mild to moderate depression: a randomized controlled trial
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Internet images reveal bumblebee-mimicking hoverflies follow models in preferring blue flowers, but retain the typical hoverfly attraction to yellow
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Data for: Monitoring the effects of ovariectomy on seasonal movement behavior in suburban female white-tailed deer using Internet of Things-enabled devices
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GECCO Industrial Challenge 2018 Dataset: A water quality dataset for the 'Internet of Things: Online Anomaly Detection for Drinking Water Quality' competition at the Genetic and Evolutionary Computation Conference 2018, Kyoto, Japan.
<p>Dataset of the 'Internet of Things: Online Anomaly Detection for Drinking Water Quality' competition hosted at The Genetic and Evolutionary Computation Conference (GECCO) July 15th-19th 2018, Kyoto, Japan</p> <p> </p> <p>The task of the competition was to develop an anomaly detection algorithm for a water- and environmental data set.</p> <p> </p> <p>Included in zenodo: </p> <p>- dataset of water quality data</p> <p>- additional material and descriptions provided for the competition</p> <p> </p> <p>The competition was organized by:</p> <p>F. Rehbach, M. Rebolledo, S. Moritz, S. Chandrasekaran, T. Bartz-Beielstein (TH Köln)</p> <p> </p> <p>The dataset was provided by:</p> <p>Thüringer Fernwasserversorgung and IMProvT research project</p> <p> </p> <p>GECCO Industrial Challenge: 'Internet of Things: Online Anomaly Detection for Drinking Water Quality'</p> <p>Description:</p> <p>For the 7th time in GECCO history, the SPOTSeven Lab is hosting an industrial challenge in cooperation with various industry partners. This years challenge, based on the 2017 challenge, is held in cooperation with "Thüringer Fernwasserversorgung" which provides their real-world data set. The task of this years competition is to develop an anomaly detection algorithm for the water- and environmental data set. Early identification of anomalies in water quality data is a challenging task. It is important to identify true undesirable variations in the water quality. At the same time, false alarm rates have to be very low.<br> Additionally to the competition, for the first time in GECCO history we are now able to provide the opportunity for all participants to submit 2-page algorithm descriptions for the GECCO Companion. Thus, it is now possible to create publications in a similar procedure to the Late Breaking Abstracts (LBAs) directly through competition participation!</p> <p> </p> <p>Accepted Competition Entry Abstracts<br> - Online Anomaly Detection for Drinking Water Quality Using a Multi-objective Machine Learning Approach (Victor Henrique Alves Ribeiro and Gilberto Reynoso Meza from the Pontifical Catholic University of Parana)<br> - Anomaly Detection for Drinking Water Quality via Deep BiLSTM Ensemble (Xingguo Chen, Fan Feng, Jikai Wu, and Wenyu Liu from the Nanjing University of Posts and Telecommunications and Nanjing University)<br> - Automatic vs. Manual Feature Engineering for Anomaly Detection of Drinking-Water Quality (Valerie Aenne Nicola Fehst from idatase GmbH)</p> <p>Official webpage:</p> <p><a href="http://www.spotseven.de/gecco/gecco-challenge/gecco-challenge-2018/">http://www.spotseven.de/gecco/gecco-challenge/gecco-challenge-2018/</a></p>
Coverage and Deployment Analysis of Narrowband Internet of Things in the Wild - Dataset
<p>Coverage and Deployment Narrowband Internet of Things (NBIoT) measurements in Oslo and Rome.</p>
Lidando com Componentes Resistentes a Mudanças no Contexto de Internet das Coisas
<p>Vídeo de apresentação de trabalho para o CTIC@SBES 2020.</p>
Data from: Modeling the internet of things, self-organizing and other complex adaptive communication networks: a cognitive agent-based computing approach
Background: Computer Networks have a tendency to grow at an unprecedented scale. Modern networks involve not only computers but also a wide variety of other interconnected devices ranging from mobile phones to other household items fitted with sensors. This vision of the "Internet of Things" (IoT) implies an inherent difficulty in modeling problems. Purpose: It is practically impossible to implement and test all scenarios for large-scale and complex adaptive communication networks as part of Complex Adaptive Communication Networks and Environments (CACOONS). The goal of this study is to explore the use of Agent-based Modeling as part of the Cognitive Agent-based Computing (CABC) framework to model a Complex communication network problem. Method: We use Exploratory Agent-based Modeling (EABM), as part of the CABC framework, to develop an autonomous multi-agent architecture for managing carbon footprint in a corporate network. To evaluate the application of complexity in practical scenarios, we have also introduced a company-defined computer usage policy. Results: The conducted experiments demonstrated two important results: Primarily CABC-based modeling approach such as using Agent-based Modeling can be an effective approach to modeling complex problems in the domain of IoT. Secondly, the specific problem of managing the Carbon footprint can be solved using a multiagent system approach.
THE IMPORTANCE OF USING INTERNET TECHNOLOGIES IN EDUCATION.
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INVESTIGATION OF INTERNET JARGONS IN UZBEK AND ENGLISH
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INTERNET SAFETY AND DIGITAL LITERACY: ONE OF THE CORE COMPETENCIES OF MODERN EDUCATION
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Does Internet Use Benefit Health? - PSM-DID Evidence from China's CHARLS
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Figures 1–6 in Internet-based data platforms re-define the distributions of some large crabronid wasps in Arkansas (Hymenoptera: Crabronidae)
Figures 1–6. Photographs of three species of crabronid wasps occurring in Arkansas. 1–2) Sphecius speciosus. 1) Lateral (Andy Reago and Chrissy McClarren_Flickr 50202938888_CC BY 2.0 DEED). 2) Dorsal. 3–4) Stictia carolina. 3) Lateral (Gordon C. Snelling_iNaturalist_43558725_CC by 4.0 DEED). 4) Dorsal. 5–6. Stizus brevipennis. 5) Lateral (Cara Flinn_ used with permission). 6) Dorsal.
Internet Use among Chinese Women Entrepreneurs
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Allen Brain Atlas
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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.