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14 results for “Internet Computer”
GECCO Industrial Challenge 2019 Dataset: A water quality dataset for the 'Internet of Things: Online Event Detection for Drinking Water Quality Control' competition at the Genetic and Evolutionary Computation Conference 2019, Prague, Czech Republic.
<p>Dataset of the 'Internet of Things: Online Event Detection for Drinking Water Quality Control' competition hosted at The Genetic and Evolutionary Computation Conference (GECCO) July 13th-17th 2019, Prague, Czech Republic</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>1. Original train dataset of water quality data provided to participants (identical to gecco2019_train_water_quality.csv)</p> <p>2. Call for Participation</p> <p>3. Rules and Description of the Challenge</p> <p>4. Resource Package provided to participants</p> <p>5. The complete dataset, consisting of train, test and validation merged together (gecco2019_all_water_quality.csv)</p> <p>6. The test dataset, which was used for creating the leaderboard on the server (gecco2019_test_water_quality.csv)</p> <p>7. The train dataset, which participants had available for training their models (gecco2019_train_water_quality.csv)</p> <p>8. The validation dataset, which was used for the end results for the challenge (gecco2019_valid_water_quality.csv)</p> <p> </p> <p>The challenge required the participants to submit a program for event detection. A training dataset was available to the participants (gecco2019_train_water_quality.csv). During the challenge the participants were able to upload a version of their program to out online platform, where this version was scored against the testing dataset (gecco2019_test_water_quality.csv), thus an intermediate leaderboard was available. To avoid overfitting against this dataset, at the end of the challenge, the end result was created from scoring with the validation dataset (gecco2019_valid_water_quality.csv). </p> <p>Train, Test, Validation dataset are from the same measuring station and are in chronological order. So the timestamps from the test dataset begin directly after the train timestamps, while the validation timestamps begin directly after the test timestamps. </p> <p> </p> <p>The competition was organized by:</p> <p>F. Rehbach, S. Moritz, 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> </p> <p>Internet of Things: Online Event Detection for Drinking Water Quality Control</p> <p> </p> <p>Description:</p> <p>For the 8th time in GECCO history, the SPOTSeven Lab is hosting an industrial challenge in cooperation with various industry partners. This years challenge, based on the 2018 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.</p> <p><br> Competition Opens: End of January/Start of February 2019<br> Final Submission: 30 June 2019</p> <p>Official webpage:</p> <p><a href="https://www.th-koeln.de/informatik-und-ingenieurwissenschaften/gecco-challenge-2019_63244.php">https://www.th-koeln.de/informatik-und-ingenieurwissenschaften/gecco-challenge-2019_63244.php</a></p> <p> </p>
Q5. Do you believe that the internet can be used with antisocial purpose?-Computer-Mediated Security Threats into the Web 2.0 Society
<p>With a median value of 7 it is obvious that a large part of the sample consider that the Internet can be used in a consistent manner for various antisocial purposes (59.3% evaluated this risk above 7). Even if this is a subjective evaluation, the focusing of answers on the high part of the scale confirms the relevance of this topic. Once again, without a direct experience in the security issues, the users that have answered to the questionnaire recognize that in the digital world can be infiltrated people, contents, information, actions, and applications with less ethical intentions.</p>
Q3. To what extent that information from the Internet should be censored?-Computer-Mediated Security Threats into the Web 2.0 Society
<p>Following this distribution, we can observe that a large part of the subjects (44,7%) consider that the information from the internet should be moderately censored (against various risks and social dangerous). Beside them, 26.6% evaluate that this process should be wider, and 28.7% think it should be lower. These two almost equal groups consolidate the central trend, and reflect a quite important worry concerning this perspective. The Internet has begun as an almost totally free of control medium, a quasi-anarchic structure, a symbol for the freedom of expression for any users. In time, it has become more and more accessible, and a large amount of information has become available inside the Info-sphere. Now, due to some negative consequences, it looks like starting to censure some information is not a prohibitive idea anymore, but rather a desirable one. We want to stress on the fact that the sample was formed by regular users that are not experts in security issues and thus, the recognizing of the importance of having a moderate censuring onto the Internet is a very significant conclusion. With an indirect connection to the previous item, the next question has directly approached a special topic related to the user’s knowledge about the dark web and/or deep web. These represent a quite particularly topic among the Internet users, and represent an area where the IP tracking is difficult or not-possible. Into this kind of sites and applications any user can remain anonymous, no matter what he/she does, posts or accesses.</p>
Q1. How do you assess the evolution of the Internet in the last 5 years?-Computer-Mediated Security Threats into the Web 2.0 Society
<p>The answers at this question indicated a quasi-total trend of increasing into the evolution of the Internet during the last 5 years (96% for “increased” and “high increased”) with a median value of 5 (corresponding to “high increased”). This public perception is strictly related to the current developing of the Internet applications, utilizations and related behaviors. In accordance with the above theoretical framework can be expected that this extensive evolution will include soon or later various antisocial content and negative manifestation. This is not a compulsory trend but only a natural extension, after the digitalization of almost all regular domains (education, mass-media, transportation, health, public administration, government, culture and so on) the areas of human manifestations that are at the law limits or beyond these will become on-line. At this moment the extension of the Internet is a quite solid fact.</p>
Research data from the two surveys on IoT implementation for Article "User and Professional Aspects for Sustainable Computing Based on the Internet of Things in Europe"
<p>The file includes data collected through two online surveys linked to the article "User and Professional Aspects for Sustainable Computing Based on the nternet of Things in Europe" published by journal Sensors in January 2023:</p> <ul> <li>Survey on factors that inlfuence IoT Adoption by non technical users</li> <li>Survey on recommended profile focused on IoT implementation for two professional roles in the context of Smart Cities (SC) projects: SC engineer and SC technician.</li> </ul>
Monitoring the Internet Computer (Artifact)
<p>This artifact accompanies the paper <em>Monitoring the Internet Computer</em>, which will be presented at the 25th International Symposium on Formal Methods (FM 2023). It provides the policy formulas described in Section 3.2 of the paper, the raw log files that were used in the evaluation, and all tools necessary to reproduce the experimental results, specifically those reported in Table 2 and Figure 5 in the paper.</p> <p>See README.md for additional information and instructions.</p> <p><strong>Erratum</strong> (August 14, 2023): Unlike stated in Table 1 of the paper, the block-validation-latency policy included in this artifact does not contain a future operator. The operator was present in an earlier version of the policy. It was removed because it was not required given the structure of the log data. The future operator can be added by inserting</p> <pre>EVENTUALLY [0,0]</pre> <p>at the end of line 50 of the file policy-monitoring/mfotl-policies/block_validation_latency/formula.mfotl. We did not observe a meaningful change in the results when we repeated the experiments using both the included and the modified policy.</p>
Effects of a Manualized Short-term Treatment of Internet and Computer Game Addiction
ClinicalTrials.gov study NCT01434589. IPD Sharing: Not stated. Countries: 2. Publications: 3.
Promoting Responsible Drinking: An Internet-based, Interactive Computer Tailored Intervention
ClinicalTrials.gov study NCT02126163. IPD Sharing: NO. Countries: 1. Publications: 1.
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>
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.
Data from: Modeling the internet of things, self-organizing and other complex adaptive communication networks: a cognitive agent-based computing approach
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OxIGen: Oxford Imagery Generation: Investigating the Effects of an Internet Based Computer Program in Depression
ClinicalTrials.gov study NCT01443234. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Comparison of Face to Face Lecture, Interactive Internet Based and Computer Based Teaching
ClinicalTrials.gov study NCT01269775. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Code for the lecture notes: "Green Computing for the Internet of Things"
<p>This dataset contains the supplementary files for the lecture and practical "Green Computing for the Internet of Things" that was given at the SusTrainable Summer School 2022, Rijeka, Croatia, July 4–5, 2022.</p> <p>This work acknowledges the support of the ERASMUS+ project “SusTrainable—Promoting<br> Sustainability as a Fundamental Driver in Software Development Training and Education”, no.<br> 2020–1–PT01–KA203–078646.</p> <p>https://sustrainable.uniri.hr/</p> <p>It was originally uploaded at: https://ftp.cs.ru.nl/Clean/mTask/SUSTRAINABLE2022/</p> <p>The dataset contains the following files:</p> <ul> <li>slides.pdf: the slides for the the lecture.</li> <li>exercises.zip: the installation instructions and assignments.</li> <li>exercises.pdf: the reader for the exercises done during the practical.</li> <li>exercises-oob.zip: a copy of exercises.zip but this includes all packages, dependencies, and binaries for the build system nitrile.</li> </ul>
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