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101 results for “Digital twin”
Digital Twin based Control of a Mobile Knuckle Boom Crane, Video 2
<p>Supportive Material for the Publication: Digital Twin based Control of a Mobile Knuckle Boom Crane. Video shows moving the joints individual without collision detection.</p>
Digital Twin based Control of a Mobile Knuckle Boom Crane, Video 1
<p>Supportive Material for the Publication: Digital Twin based Control of a Mobile Knuckle Boom Crane. Video shows the simple PTP-motion of the crane without planner.</p>
Digital Twin based Control of a Mobile Knuckle Boom Crane, Video 3
<p>Supportive Material for the Publication: Digital Twin based Control of a Mobile Knuckle Boom Crane. Video shows the collision detection of DT-Software in simulation.</p>
Evaluating the potential of Digital Twin technology on pharmaceutical manufacturing efficiency in Ireland: An in-depth analysis of Machinery Validation
<p>The dissertation titled <strong>"Evaluating the Potential of Digital Twin Technology on Pharmaceutical Manufacturing Efficiency in Ireland: An In-depth Analysis of Machinery Validation"</strong> explores the transformative impact of Digital Twin (DT) technology within Ireland's pharmaceutical manufacturing sector. Conducted by MSc candidate Gayathri Gopakumar at Griffith College Dublin, the research focuses on how DT technology can enhance machinery validation processes, thereby improving operational efficiency and ensuring regulatory compliance.</p> <p>Employing a qualitative research methodology, the study includes semi-structured interviews with industry experts to gather insights into the current awareness, perceived benefits, and challenges associated with DT adoption in the pharmaceutical industry. The research aims to provide a comprehensive understanding of DT technology's role in machinery validation and its broader implications for manufacturing efficiency.</p> <p>This work contributes to the existing body of knowledge by offering a detailed analysis of DT technology's potential applications in pharmaceutical manufacturing, with a specific focus on the Irish context. It serves as a valuable resource for professionals and researchers interested in the integration of advanced digital technologies in the pharmaceutical sector.</p>
A Cross-Domain Systematic Mapping Study on Software Engineering for Digital Twins
<p><strong>A Systematic Cross-Domain Mapping Study on the Software Engineering of Digital Twins</strong></p> <p>Manuela Dalibor, Nico Jansen, Bernhard Rumpe, David Schmalzing, Louis Wachtmeister, Manuel Wimmer, and Andreas Wortmann</p> <p>Digital Twins are currently investigated as the technological backbone for providing an enhanced understanding and management of existing systems as well as for designing new systems in various domains, e.g., ranging from single manufacturing components such as sensors to large-scale systems such as smart cities. Given the diverse application domains of Digital Twins, it is not surprising that the characterization of the term Digital Twin, as well as the needs for developing and operating Digital Twins are multi-faceted. Providing a better understanding what the commonalities and differences of Digital Twins in different contexts are, may allow to build reusable support for developing, running, and managing Digital Twins by providing dedicated concepts, techniques, and tool support. In this paper, we aim to uncover the nature of Digital Twins based on a systematic mapping study which is not limited to a particular application domain or technological space. We systematically retrieved a set of 1471 unique publications of which 529 were identified as potentially relevant and of which finally 356 were selected for further investigation. In particular, we analyzed the types of research and contributions made for Digital Twins, the expected properties Digital Twins have to fulfill, how Digital Twins are realized and operated, as well as how Digital Twins are finally evaluated. Based on this analysis, we also contribute a novel feature model for Digital Twins as well as several observations to further guide future software engineering research in this area.</p>
FIGURE. Disc ovary in a taxon of Callilepis with imbricate involucral bracts. A. Digital image of the disc ovary of C. normae (Koekemoer 4573, PRE) showing the entire surface twin hairy. B. Scanning electron micrograph of the surface of the disc ovary of C. normae (Koekemoer 4573, PRE) showing the twin hairs on the surface. in A taxonomic revision of the genus Callilepis (Asteraceae) in South Africa
FIGURE. Disc ovary in a taxon of Callilepis with imbricate involucral bracts. A. Digital image of the disc ovary of C. normae (Koekemoer 4573, PRE) showing the entire surface twin hairy. B. Scanning electron micrograph of the surface of the disc ovary of C. normae (Koekemoer 4573, PRE) showing the twin hairs on the surface.
A Structured Review on the Human Digital Twin (until March 2024)
<p>This bibliography is related to the paper "Perspectives-Observer-Transparency - Structured Review of the Human Digital Twin and Novel Paradigm for Modelling the Human in Human-To-Anything Interaction" by Nils Mandischer, Alexander Atanasyan, Michael Schluse, Jürgen Roßmann, and Lars Mikelsons, currently under submission to the IEEE International Conference on Systems, Man, and Cybernetics as of April 2024.<br> <br>The references are collected as part of a structured literature review on modelling approaches for humans and artificial agents and the perspectives taken on them. Particular interest lays on the (Human) Digital Twin which proved to be a relatively nascent approach that quickly gained interest at the time of writing. Please refer to the publication for a more detailed description of the review method.<br> <br>The conference paper DOI will be provided to Zenodo upon publication. For updates, additional context, or inquiries, please contact Alexander Atanasyan [Atanasyan@mmi.rwth-aachen.de] or Nils Mandischer [nils.mandischer@uni-a.de].</p>
A digital twin model of urban utility tunnels and its application:One-dimensional comparison verification
<div> <div> <div> <div> <div> </div> 重点词汇</div> <div> <div>93<em>/</em>5000</div> </div> </div> </div> </div> <div> </div> <div> <div> <div> <div> <div> <div>通用场景</div> <div> </div> </div> </div> </div> </div> <div> <div> <p><span>论文《城市综合管廊数字孪生模型及其应用》中一维综合管廊中天然气浓度分布快速预测模型结果对比</span></p> </div> </div> </div>
Modeling Languages for Digital Twins - A Survey Among the German Automotive Industry
<p>This repository contains the replication package for the paper _Modeling Languages for Digital Twins: A Survey Among the German Automotive Industry_ by Jérôme Pfeiffer, Dominik Fuchß, Thomas Kühn, Robin Liebhart, Dirk Neumann, Christer Neimöck, Christian Seiler, Anne Koziolek, and Andreas Wortmann. <br>The paper has been submitted to the practice track of [MODELS 2024](https://conf.researchr.org/track/models-2024/models-2024-technical-track#Practice-Track).</p> <h3>Data</h3> <p>This replication package contains all information from the survey:<br>- `results.csv`: A csv version of all data exported from LimeSurvey (German). Personal information from the participants has been removed. This file can be imported to reproduce the extraction results described in our paper.<br>- `survey_german.pdf`: The pdf version of the original survey in German. <br>- `survey_german.md`: A markdown version of the original survey in German. <br>- `survey_english.md`: A markdown version of the survey translated into English. </p> <h3>Selection of participants and distribution</h3> <p>With both versions, the survey can be executed again with a different target audience in English or German. In our case we wanted to reach as much participants from diverse work areas as possible, where we invited the participants by email via an internal mailing list of 189 members of the SofDCar project. To improve the response rate, we implemented two deadline extensions from the initial one-month-long time frame with 2 weeks of additional response time. Together with the deadline extension, we sent a mail to inform and remind the members of the consortium of the survey.</p> <h3>Data extraction</h3> <p>In total, we had 96 participants, of which 43 completed the questionnaire. For incomplete survey responses, we took only the available answers and did not include the missing answers in our data analysis. For data analysis we utilized the commercial Tool IBM SPSS and custom python scripts.</p> <h2>Research Questions </h2> <p>- RQ1: How is the DT understood in the automotive industry?<br> - RQ1.1: For which phases of automotive development are DTs<br>important?<br> - RQ1.2: What are desired properties of DTs?<br> - RQ1.3: What are desired purposes of using DTs?<br> - RQ1.4: How do these purposes change in relation to different phases of automotive development?<br>- RQ2: Which modeling languages and modeling tools are currently employed in the automotive industry?<br> - RQ2.1: Which kinds of models are important during automotive development?<br> - RQ2.2: How important are which models in the phases of automotive development?<br> - RQ2.3: Which tools are used to create and maintain these models?</p>
Dataset for "Learning Scene Semantics from Vehicle-centric Data for City-scale Digital Twins", Fürntratt et al.
<p>Dataset for "Learning Scene Semantics from Vehicle-centric Data for City-scale Digital Twins", Fürntratt et al.</p> <p>Data are anonymized and provided with segmentation mask ground truths. </p>
Raw Data of the Survey on Practitioners' Perspectives on Using & Developing Digital Twin Systems
<p>Here, we present the documents regarding our survey on understanding practitioners' perspectives on using & developing digital twin systems. Our survey has attracted 131 participants from diverse industries. Here, we attached the survey questions and the raw data for the survey responses. </p>
Dataset for generation of LOD4 models for buildings towards the automated 3D modeling of BIMs and digital twins
<div> <div>This repository contains the dataset used for the automated image-based generation of LOD4 models for buildings, along with the corresponding results. The methodology utilizing this dataset was presented in the paper "Generation of LOD4 models for buildings towards the automated 3D modeling of BIMs and digital twins" by Pantoja-Rosero et., al. (2024) (https://doi.org/10.1016/j.autcon.2024.105822).</div> </div>
Digital Twin-based Out-of-Distribution Detection in Autonomous Vessels
<p>This folder contains datasets, code, and analysis scripts for reproducing the results in the paper "Digital Twin-based Out-of-Distribution Detection in Autonomous Vessels". Specifically, it contains the following folders: </p> <ol> <li>Datasets <ol> <li>Dataset for each Vessel model in different maneuvers and conditions, i.e., waypoint, zigzag, ocean current (including IND and OOD).</li> <li>Configurations (Configurations used to train the DTM for each vessel in different maneuvers).</li> </ol> </li> <li>Results <ol> <li>Raw results for RQ1 and RQ2 for each vessel in different maneuvers, including the results from DTM-R and DTM-E.</li> <li>Results for RQ3 (statistical tests) derived from the above results. </li> </ol> </li> <li>Scripts and Code <ol> <li>Scripts used for statistical tests.</li> <li>DTC implementation (shown with one vessel as example).</li> <li>Code used for hyperparameter optimization.</li> <li>Inference class used for integration of DTM and DTC.</li> </ol> </li> </ol>
Data for: Using a digital twin of an electrical stimulation device to monitor and control the electrical stimulation of cells in vitro
<p>Replication data for "Using a digital twin of an electrical stimulation device to monitor and control the electrical stimulation of cells in vitro".</p>
Dataset for image-based geometric digital twinning for stone masonry elements
<p>This is the dataset used to assess the performance of the geometrical digital twinning algorithm proposed by Pantoja-Rosero et, al (2023) in the article "Image-based geometric digital twinning for stone masonry elements" (<a href="https://doi.org/10.1016/j.autcon.2022.104632">https://doi.org/10.1016/j.autcon.2022.104632</a>)</p>
Dataset for image-based geometric digital twinning for stone masonry elements - part 2
<p>This is the dataset used to assess the performance of the geometrical digital twinning algorithm proposed by Pantoja-Rosero et, al (2023) in the article "Image-based geometric digital twinning for stone masonry elements" (<a href="https://doi.org/10.1016/j.autcon.2022.104632">https://doi.org/10.1016/j.autcon.2022.104632</a>)</p>
Dataset for Digital Twin paper
<p>Description for each folder:</p> <p>1) The "raw_signal_data" folder contains original sensor data. The origigital sensor data is named as "ACF-x-x.xlsx". In each excel document, three directions of vibration, current and force sensor data is included. Naming rules is as follows: "ACF-1-2.xlsx" represents the orginal sensor data from first layler's second slot in. "ACF-2-3.xlsx" represents the orginal sensor data from second layler's third slot.</p> <p>2) The original real measured surface roughness is in the "Ra.xlsx". The corresponding cutting parameters for every raw signal data of each slot are shown in "Ra.xlsx" document as well. <br> 3) The prediction results from different models are save in "prediction_results". The detalies are listed below.</p> <p> "BPNN_all_signal.xlsx" is the prediction result from BPNN used the combination of all sensors data as the model input <br> "BPNN_current_signal.xlsx" is the prediction result from BPNN used only the current sensor data as the model input <br> "BPNN_force_signal.xlsx" is the prediction results from BPNN used only the force sensor data as the model input <br> "BPNN_vibration_signal.xlsx" is the prediction result from BPNN used only the vibration sensor data as the model input<br> "ELM.xlsx" is the prediction result from ELM used the combination of all sensors data as the model input <br> "GPR.xlsx" is the prediction result from GPR used the combination of all sensors data as the model input<br> "LASSO.xlsx" is the prediction result from LASSO used the combination of all sensors data as the model input<br> "MLR.xlsx" is the prediction result from MLR used the combination of all sensors data as the model input<br> "SVR.xlsx" is the prediction result from SVR used the combination of all sensors data as the model input<br> "cnn_all_signal.xlsx" is the prediction result from CNN used the combination of all sensors data as the model input <br> "cnn_current.xlsx" is the prediction result from CNN used only the current sensor data as the model input <br> "cnn_force.xlsx" is the prediction results from CNN used only the force sensor data as the model input <br> "cnn_vibration.xlsx" is the prediction result from CNN used only the vibration sensor data as the model input<br> "real_ytest.xlsx" is the real-measured surface roughness data for testing models.</p>
Risk and Equity Metrics for the NYC Flood Risk Digital Twin
<p>These datasets contain the Risk and Equity metrics used to quantify the impact of pluvial flooding in NYC. They are obtained combining several sources (US Census data, New York State Traffic data, etc.) with the NYC Stormwater Flood Map corresponding to an extreme rain event.</p>
Dataset for damage-augmented digital twins towards the automated inspection of buildings
<p>This repository contains the dataset used for computing damage augmented digital twins for buildings via image-based approach. The method that uses this data set was presented in the paper "Damage-augmented digital twins towards the automated inspection of buildings" by Pantoja-Rosero et., al. (2023)" https://doi.org/10.1016/j.autcon.2023.104842</p> <p> </p> <p> </p> <p> </p>
Emotion Recognition for Affective human digital twin by means of virtual reality enabling technologies
<pre>We introduce a new bimodal dataset recorded during affect elicitation by means of audio-visual stimuli for human emotion recognition based on facial and corporal expressions. Our dataset was collected using three devices: an RGB camera, Kinect 1, and Kinect 2. The Kinect 1 and Kinect 2 sensors provide 121 and 1347 face key points, respectively, offering a more comprehensive analysis of facial expressions. Additionally, for the 2D RGB sequences, we utilized the feature points provided by the open-source OpenFace, which includes 2D 68 facial landmarks. From these landmarks, we selected 26 facial points that were most relevant for our emotion recognition task. To gather the data, we conducted experiments involving 17 participants. We captured both facial and skeleton keypoints, allowing for a comprehensive understanding of the participants' emotional expressions. By combining the RGB and RGB-D data from the various devices, our dataset provides a rich and diverse set of information for human emotion recognition research. This new dataset not only expands the available resources for studying human emotions but also offers a more detailed analysis with the increased number of facial keypoints provided by the Kinect sensors. Researchers can leverage this dataset to develop and evaluate more accurate and robust models for human emotion recognition, ultimately advancing our understanding of how emotions are expressed through facial and corporal cues. Please cite as: K. Amara, O. Kerdjidj and N. Ramzan, "Emotion Recognition for Affective human digital twin by means of virtual reality enabling technologies," in <em>IEEE Access</em>, doi: 10.1109/ACCESS.2023.3285398. </pre> <p> </p> <p>Please state your name, contact details (e-mail), institution, and position, as well as the reason for requesting access to our database.</p> <p>For additional info contact:</p> <p>kahina.amara88@gmail.com or kamara@cdta.dz</p> <p>Naeem.Ramzan@uws.ac.uk</p> <p>okerdjidj@ud.ac.ae</p>
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International Brain Laboratory public data
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OpenNeuro
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