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575 results for “Control systems”
BOOSTR: A Dataset for Accelerator Control Systems (Partial Release 2020)
<p>BOOSTR (Booster Operation Optimization Sequential Time-Series for Regression) was created to provide cycle-by-cycle time series of readings and settings from instruments and controllable devices of the Booster, the 15~Hz Rapid-Cycling Synchrotron (RCS) at Fermilab. We are preliminarily releasing one day of it in the hopes that it— and future versions of it— can be used as a dataset to demonstrate other aspects of artificial intelligence for advanced control systems. For more information, please see our accompanying Datasheet.</p>
New dataset obtained from 2D positioning system with distributed control
<p>The dataset contains the obtained trajectory (encoder measurements) of the 2D positioning system, as well as the reference (commanded) trajectory. The control task is distributed to the low-level controllers for x and y axes synchronized using IEEE 1588 Precision Time Protocol (PTP), where the movement of the axes is realized based on the data that the low-level controllers receive from the high-level controller. The dataset includes 60 signals (30 measurements for x and y axis) that represent obtained trajectories and 2 signals (x and y axes) that represent commanded trajectory, where the length of each signal is 61,000 samples. The system was designed and built by the Cyber-Physical Systems Lab at the Pratt School of Engineering, Duke University, where it is located. Table 1 shows the list of collected signals, whereas a detailed description of the system can be found in [1]. For more information, see [2, 3].</p>
Dataset for the publication: Molecularly-controlled high swirl combustion system for ethanol/1-octanol dual fuel combustion
<p>This dataset contains the research data featured in the publication "Molecularly-controlled high swirl combustion system for ethanol/1-octanol dual fuel combustion" in Fuel (DOI: 10.1016/j.fuel.2023.128184)</p>
Smart Locks Access Control System
<p>The smart locks access system (Outlock’s locking units) is based on the patented Knock Code technology, which transfers encrypted data by mechanical pulses to unlock the lock. Since there are no conventional keys, keyholes or external parts, locking units are highly resistant to break-ins, vandalism, and the toughest weather conditions. To unlock the lock, the user enters the code and simply holds the KnockKey against the opening’s surface. Additionally, LNLI lock application provides a sophisticated electronic locks’ management system.</p>
A Role-Based Access Control model in Modbus Scada systems. A centralized model approach
<p>A Role-Based Access Control model in Modbus Scada systems. A centralized model approach. The files included are:</p> <ul> <li>ASA configuration</li> <li>Router1 configuration</li> <li>Router2 configuration</li> <li>Router3 configuration</li> <li>RoleDB</li> <li>openssl.cnf arbitrary extension file</li> </ul>
Metabolomics data associated with "Glial swip-10 controls systemic mitochondrial function, oxidative stress, and neuronal viability via copper ion homeostasis"
<p>Raw feature tables used for metabolomic analysis of the <em>Caenorhabditis elegans</em> mutant <em>swip-10</em>. The data were generated using liquid chromatography coupled high-resolution mass spectrometry. Two different columns were used: HILIC (+ ESI) and C18 (-ESI), coupled to a Thermo Q-Exactive Orbitrap mass spectrometer. The feature tables were generated using open-source peak peaking and alignment R packages: apLCMS and xMAanalyzer. See more details in the associated manuscript.</p>
Data for paper "Parametric schedulability analysis of a launcher flight control system under reactivity constraints"
<p>This is the data set (models, sources and results) for the paper "Parametric schedulability analysis of a launcher flight control system under reactivity constraints" published in Informatica Fundamentae in 2021.</p>
Mapping of districts to control zones of German Transmission System Operators (TSOs)
<p><strong>Mapping of districts to control zones of German Transmission System Operators (TSOs)</strong></p> <p>This dataset provides a mapping of districts in Germany at NUTS3 level to control zones that are maintained by four transmission system operators (50Hertz, Amprion, TenneT, TransnetBW). A visualisation of the mapping is provided it GER_NUTS3_TSOs.png.</p> <p>I can provide no guarantee of the accuracy or completeness of the provided information. In case the control zones of the TSOs change, or an error is detected, I do not assume liability for the error. The output file(s) can also be re-generated with the provided python script (GER_NUTS3_TSOs.py), and manipulated if necessary. In case you detect an error, please reach out to me so we can correct it in order to provide as accurate information as possible.</p> <p><strong>Licensing</strong></p> <p>This dataset is created on top of a dataset of German political administrative boundaries at NUTS3 level covering Germany provided by geoBoundaries (DEU_ADM2.shp). geoBoundaries is an online, open license database of global political administrative boundaries (i.e., state, county). For further information, see https://www.geoboundaries.org/.</p> <p>For the processing, I am also using the dataset "Verwaltungsgebiete 1:2500000" (vg_12500.shp) provided by the "Bundesamt für Kartographie und Geodäsie". The dataset is licensed as "Data licence Germany - attribution - version 2.0", and can be retrieved at https://gdz.bkg.bund.de/index.php/default/verwaltungsgebiete-1-2-500-000-stand-31-12-vg2500-12-31.html. A reference to the license is provided under the following link: https://www.govdata.de/dl-de/by-2-0.</p> <p>The files GER_NUTS3_TSOs.png, GER_NUTS3_TSOs.shp, GER_NUTS3_TSOs.shx, GER_NUTS3_TSOs.prj, GER_NUTS3_TSOs.dbf and GER_NUTS3_TSOs.cpg are released under the Creative Commons 4.0 Attribution International (CC BY 4.0).</p> <p>The file GER_NUTS3_TSOs.py is released under a MIT license.</p>
Two metabolomics data sets (mouse kidney, mouse plasma), generated for the publication Bignon et al., 2023: "Multiomics reveals multilevel control of renal and systemic metabolism by the renal tubular circadian clock".
<p><strong>Publication: </strong>Bignon Y, Wigger L, Ansermet C, Weger BD, Lagarrigue S, Centeno G, Durussel F, Götz L, Ibberson M, Pradervand S, Quadroni M, Weger M, Amati F, Gachon F, Firsov D. Multiomics reveals multilevel control of renal and systemic metabolism by the renal tubular circadian clock. J Clin Invest. 2023 Mar 2:e167133. doi: 10.1172/JCI167133. Epub ahead of print. PMID: 36862511.</p> <p> </p> <p><strong>Abstract: </strong> Circadian rhythmicity in renal function suggests rhythmic adaptations in renal metabolism. To decipher the role of the circadian clock in renal metabolism, we studied diurnal changes in renal metabolic pathways using integrated transcriptomic, proteomic, and metabolomic analysis performed on control mice and mice with inducible deletion of the circadian clock regulator Bmal1 in the renal tubule (cKOt). With this unique resource, we demonstrated that ~30% RNAs, ~20% proteins and ~20% metabolites are rhythmic in kidneys of control mice. Several key metabolic pathways including NAD+ biosynthesis, fatty acid transport, carnitine shuttle,and b-oxidation displayed impairments in kidneys of cKOt, resulting in a perturbed mitochondrial activity. Carnitine reabsorption from the primary urine was one of the most impacted processes with a ~50% reduction in plasma carnitine levels and a parallel systemic decrease in tissues carnitine content. This suggests that the circadian clock in the renal tubule controls both kidney and systemic physiology.</p> <p> </p> <p><strong>This record contains two separate mass-spectrometry metabolomics data sets associated with this study:</strong></p> <ol> <li>Metabolic profile of renal tubules, MS/MS data, Metabolon, Morrisville, NC (N=60)</li> <li>Metabolic profile of blood plasma, MS/MS data, Biocrates, Innsbruck, Austria (N=60)</li> </ol> <p>For each data set, original data as received from the platforms and processed data as used in the data analysis are provided. Preprocessing of kidney data included removal of metabolites with more than 80% missing data values, median normalization, imputation and glog2 transformation. Preprocessing of plasma data included filtering of metabolites with any missing data and log2 transformation. Details of data processing are available in the STAR*methods of the publication.</p> <p> </p> <p><strong>Data sets in other repositories associated with the same study:</strong></p> <p>Additional data sets (transcriptomics, proteomics) pertaining to the same study have been deposited in public repositories:</p> <ul> <li>Gene Expression Omnibus (NCBI GEO), GSE216252</li> <li>PRIDE Archive (EMBL-EBI), PXD036803</li> </ul> <p> </p>
Data Repository Accompanying "Controllable single Cooper pair splitting in hybrid quantum dot systems"
<p>Code and datasets associated with the manuscript " Controllable single Cooper pair splitting in hybrid quantum dot systems". With the code and data included here, all necessary fits and analysis can be conducted to produce the figures given in the manuscript and its supplementary material. The only exception is that we include the results of the quantum dot stability diagram simulation, however this simulation involves no new physics and the procedure is described in detail in the manuscript's supplementary information.</p>
Cipher System T310/50, control unit (Inv. 1997-15T3)
<p>This dataset represents the computed tomography image acquisition of a historical cipher machine from the collection of the Deutsches Museum. It is composed of CT reconstructed image stacks in the DICOM (.dcm) format.<br> It can be imported in any free or propietary CT-Viewer that supports the DICOM standard to generated 2D and 3D imaging.<br> If segmentations/ROIs are availabe, they are uploaded in a seperate image stacks and are a subset of the scanned cipher machine.</p> <p>object details:<br> name: Cipher System T310/50, control unit<br> Inv.-No. of the Deutsches Museum: 1997-15T3</p> <p>file object details:<br> file format: image/dcm<br> pixel spacing unit: mm<br> X pixel spacing: 0.126<br> Y pixel spacing: 0.126<br> Z pixel spacing: 0.126<br> grid size x: 2415<br> grid size y: 2362<br> grid size z: 1695<br> color depth: 16Bit</p> <p>ownership & image acquisition:<br> project: <a href="https://digital.deutsches-museum.de/en/projects/3d-cipher">3D-Cipher</a><br> collection: <a href="https://digital.deutsches-museum.de">Deutsches Museum</a><br> IP holder: Deutsches Museum<br> license: <a href="https://creativecommons.org/licenses/by/4.0/deed.en">Creative Commons BY-SA 4.0</a><br> scanning facility: <a href="https://www.iis.fraunhofer.de/en/ff/zfp.html">Fraunhofer Development Center X-ray Technology EZRT/Fraunhofer IIS</a><br> scanning device: High Energy CT XXL-CT<br> Funding attribution: <a href="https://www.bmbf.de/bmbf/en">German Federal Ministry of Education and Research</a><br> acknowledgement: <a href="https://www.cryptomuseum.com">CryptoMuseum</a> (as main source for informations about the cipher machines)</p>
Dataset for "Architectural Security Weaknesses in Industrial Control Systems: An Empirical Study Based on Security Advisories' Vulnerability Reports"
<p>Supplementary artifacts to "<em>Architectural Security Weaknesses in Industrial Control Systems (ICS): An Empirical Study based on Disclosed Software Vulnerabilities</em>"</p> <p>Published in the Proceedings from the 2019 IEEE International Conference on Software Architecture (ICSA)</p> <p>Package Contains:</p> <p>- Raw output showing Components, CAWEs, and CVEs per report</p> <p>- Frequency Data (# of reports) for those concerns</p> <p>- ICS Component - Term Dictionary </p> <p>- HTML versions of reports studied in paper</p>
Data from: warming and top-down control of stage-structured prey: linking theory to patterns in natural systems
<p>Warming has broad and often nonlinear impacts on organismal physiology and traits, allowing it to impact species interactions like predation through a variety of pathways that may be difficult to predict. Predictions are commonly based on short-term experiments and models, and these studies often yield conflicting results depending on the environmental context, spatiotemporal scale, and the predator and prey species considered. Thus, the accuracy of predicted changes in interaction strength, and their importance to the broader ecosystems they take place in, remain unclear. Here, we attempted to link one such set of predictions generated using theory, modeling, and controlled experiments to patterns in the natural abundance of prey across a broad thermal gradient. To do so, we first predicted how warming will impact a stage-structured predator-prey interaction in riverine rock pools between Pantala spp. dragonfly nymph predators and Aedes atropalpus mosquito larval prey. We then described temperature variation across a set of hundreds of riverine rock pools (n = 775) and leveraged this natural gradient to look for evidence for or against our model's predictions. Our model's predictions suggested that warming should weaken predator control of mosquito larval prey by accelerating their development and shrinking the window of time that aquatic dragonfly nymphs could consume them in. This was consistent with data collected in rock pool ecosystems, where the negative effects of dragonfly nymph predators on mosquito larval abundance were weaker in warmer pools. Our findings provide additional evidence to substantiate our model-derived predictions, while emphasizing the importance of assessing similar predictions using natural gradients of temperature whenever possible.</p>
ThermoCyte: an inexpensive open-source temperature control system for in vitro live cell imaging
<p>Live-cell imaging is a common technique in microscopy to investigate dynamic cellular behaviour and permits the accurate and relevant analysis of a wide range of cellular and tissue parameters, such as motility, cell division, wound healing responses, and calcium (Ca2+) signalling in cell lines, primary cell cultures, and ex vivo preparations. Furthermore, this can take place under many experimental conditions, making live-cell imaging indispensable for biological research. Systems which maintain cells at physiological conditions outside of a CO<sub>2</sub> incubator are often bulky, expensive, and use proprietary components. Here we present an inexpensive, open-source temperature control system for in vitro live cell imaging. Our system 'ThermoCyte', which is constructed from standard electronic components, enables precise tuning, control, and logging of a temperature 'set point' for imaging cells at physiological temperature. We achieved stable thermal dynamics, with reliable temperature cycling and a standard deviation of 0.42°C over 1 hour. Furthermore, the device is modular in nature, and is adaptable to the researcher's specific needs. This represents simple, inexpensive, and reliable tool for laboratories to carry out custom live-cell imaging protocols, on a standard lab bench, at physiological temperature.</p>
Dataset related to article "Phantom‑based analysis of variations in automatic exposure control across three mammography systems: implications for radiation dose and image quality in mammography, DBT, and CEM"
<p>The dataset comprises information from several DICOM tags extracted from digital mammography (DM), digital breast tomosynthesis (DBT), and contrast-enhanced mammography (CEM) images acquired in a phantom study aimed at characterizing the automatic exposure control (AEC) behavior of diverse mammography equipment. The final ten columns of the datasets encompass signal (mena pixel values, MPV) and noise (standard deviation, SD) measurements derived from phantom images. These measurements are used to compute several image quality metrics, including contrast, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), CNR relative difference in comparison to the 45 mm reference thickness, and a figure of merit (FOM) obtained by diving the squared CNR by the mean glandular dose (MGD).</p>
Empowering Coffee Farming Using Counterfactual Recommendation based RNN-IoT Integrated Soil Fertility Control System
Open the record for dataset details and reuse information.
Supplementary Material for "Intrusion Tolerance for Networked Systems Through Two-Level Feedback Control"
<h2>Supplementary material for the paper "Intrusion Tolerance for Networked Systems Through Two-Level Feedback Control" </h2><p>The paper is submitted to "International Conference on Dependable Systems and Networks, 2024". Author names withheld for double-blind reviewing.</p><ul><li>The file <strong>proofs_and_hyperparameters.pdf </strong>contains proofs of Theorem 1--2 and Corollary 1 in the paper. It also includes formulas for computing the belief state (Eq. 4) and for computing the curves in Fig. 6. It also includes a complete list of hyperparameters used for all experiments detailed in the paper.</li><li>The file <strong>ids_alerts_statistics.json</strong> contains the statistics used to produce Fig. 10 in the paper and to define the parameter Z for the experiments in section VIII.<ul><li>The JSON file contains a single object with the following keys: 'conditionals_counts', 'conditionals_kl_divergences', 'conditionals_probs', 'conditions', 'descr', 'emulation_name', 'id', 'initial_distributions_counts', 'initial_distributions_probs', 'initial_maxs', 'initial_means', 'initial_mins', 'initial_stds', 'maxs', 'means', 'metrics', 'mins', 'num_conditions', 'num_measurements', 'num_metrics', 'stds'. </li><li>The key "conditionals_counts" leads to another object with the following keys: 'A:CVE-2010-0426 exploit_D:Continue_M:[]', 'A:CVE-2015-3306 exploit_D:Continue_M:[]', 'A:CVE-2015-5602 exploit_D:Continue_M:[]', 'A:CVE-2016-10033 exploit_D:Continue_M:[]', 'A:Continue_D:Continue_M:[]', 'A:DVWA SQL Injection Exploit_D:Continue_M:[]', 'A:FTP dictionary attack for username=pw_D:Continue_M:[]', 'A:Ping Scan_D:Continue_M:[]', 'A:SSH dictionary attack for username=pw_D:Continue_M:[]', 'A:Sambacry Explolit_D:Continue_M:[]', 'A:ShellShock Explolit_D:Continue_M:[]', 'A:TCP SYN (Stealth) Scan_D:Continue_M:[]', 'A:Telnet dictionary attack for username=pw_D:Continue_M:[]', 'intrusion', 'no_intrusion'</li><li>The above keys correspond to different types of intrusions, see Table 6 in the paper.</li><li>Each of the keys listed above leads to a new object with 1551 keys which correspond to different types of metrics collected from the infrastructure. The metric used for produce Fig. 10 in the paper is called "alerts_weighted_by_priority". This key leads to another object where the keys correspond to the number of alerts weighted by priority and the values correspond to the measurements from the system.</li></ul></li><li>The file <strong>intrusion_traces.zip</strong> contains 6400 intrusion traces. Each trace contains a list of attacker actions and the corresponding measurements from the system. When unzipped, it is a directory with 64 files which take up 1500GB. Each file contains 100 traces in JSON format.</li><li>The file <strong>source_code_and_docker_files.zip </strong>contains the source code and the docker containers used for the experiments. It is a system we have developed for 3 years. It includes 225,000 lines of Python, 40,000 lines of JavaScript, 3000 lines of Dockerfiles, 2500 lines of Makefile, and 1800 lines of Bash. When unzipped one can find documentation about the source code in a file called "documentation.pdf" and in the README file.</li></ul>
Operating diagram of hatching module in Zoug jars, this system consists of a 300-litre temperature-controlled isothermal enclosure containing 10 one-litre Zoug jars, each able to accommodate several hundred eggs. An ascending current holds the eggs in suspension and carries the larvae to the surface. Another bottle connected to this device collects the larvae. The water circulating in the jars is independent of that used in the filtration circuit. A cooling unit and UV sterilizer complete the installation. in Reproduction of Zingel asper (Linnaeus, 1758) in controlled conditions: an assessment of the experiences realized since 2005 at the Besançon Natural History Museum
Operating diagram of hatching module in Zoug jars, this system consists of a 300-litre temperature-controlled isothermal enclosure containing 10 one-litre Zoug jars, each able to accommodate several hundred eggs. An ascending current holds the eggs in suspension and carries the larvae to the surface. Another bottle connected to this device collects the larvae. The water circulating in the jars is independent of that used in the filtration circuit. A cooling unit and UV sterilizer complete the installation.
Operating diagram of DR1/DR2 double riffle; it consists of two independent sections (DR1 and DR2), each containing 630 litres of water and measuring 2.5 x 0.6 m. Each section contains a filtration system separate from the fish, a cooling unit and an ultraviolet sterilizer. An 80 W UQL lamp completes the lighting of the module lit during the day. in Reproduction of Zingel asper (Linnaeus, 1758) in controlled conditions: an assessment of the experiences realized since 2005 at the Besançon Natural History Museum
Operating diagram of DR1/DR2 double riffle; it consists of two independent sections (DR1 and DR2), each containing 630 litres of water and measuring 2.5 x 0.6 m. Each section contains a filtration system separate from the fish, a cooling unit and an ultraviolet sterilizer. An 80 W UQL lamp completes the lighting of the module lit during the day.
METHODS OF TRAINING AND ADAPTATION OF AI AGENTS IN COMPLEX PROCESS CONTROL SYSTEMS
<p>The article presents a study of modern methods of training and adaptation of artificial agents used in managing complex processes, which are characterized by a high level of uncertainty and the need for prompt response to changes. Key methodological approaches such as machine learning and neuroevolution are discussed. These approaches allow AI agents to accumulate knowledge about the behavior of systems continuously, analyze external changes, and adjust the management strategy depending on environmental conditions, which significantly increases their ability to predict and prevent possible failures in management.</p> <p>In the course of the study, models were considered that allow automating the execution of complex, multitasking processes, minimizing human intervention, and reducing the likelihood of errors. In addition, the presented methods provide high flexibility and scalability of systems, which is especially important in industrial and technological industries, where stability and reliability are critical. The results showed that AI agents with adaptive learning capabilities can increase operational efficiency while reducing costs and optimizing resource use. The conclusion highlights the prospects of using artificial intelligence to build highly autonomous control systems capable of responding to dynamic challenges, which opens up new horizons for automation and intellectual support in industrial production, logistics, and other key areas.</p> <p>Thus, the article makes a significant contribution to understanding the role of AI in management modernization, offering practical recommendations on the implementation of intelligent agents in real-world scenarios to increase productivity and sustainability.</p>
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.