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70 results for “Systems engineering”
Data of the article Analysis of the self-archiving policies of journals in the highest rank category of the Finnish journal classification system within computer science, physics and electronic engineering
<p>The publication forum level three journals representing the three fields of science of computer science, computer science and electrical engineering were identified by utilizing the MinEdu field search filter while searching for the top-ranked journals from the publication channel search (https://www.tsv.fi/julkaisufoorumi/haku.php?lang=en), which is based on Field of Science, Statistics Finland classification (https://www.stat.fi/meta/luokitukset/tieteenala/001-2010/index_en.html). The data were extracted during august 2017 consists of total of 127 individual journals. It is worth noting that circa 30 journals were classified into more than one fields of sciences under scrutiny. First, the journals were divided into representing gold and hybrid model journals. Second, green open access policies of the identified hybrid journals were analyzed using Laakso’s (2014) publisher policy coding framework. Also publishers of the individual journals were identified and subsequently added to the data.</p> <p>NOTE! The data includes the shortest embargo to either institutional or subject repositories. For example, Elsevier had no embargo to opening accepted manuscripts from arXiv subject repository and thus no embargoes to Elsevier's journals are included within this datasheet.</p> <p>Data is in CSV. format</p> <p> </p> <p> </p>
Modulation Engineering: Stimulation Design for Enhanced Kinetic Information from Modulation-Excitation Experiments on Catalytic Systems
<p>Dataset used in the publication "Modulation Engineering: Stimulation Design for Enhanced Kinetic Information from Modulation-Excitation Experiments on Catalytic Systems" (<a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.1021%2Facscatal.3c00646&data=05%7C01%7CValentijn.DeCoster%40UGent.be%7C2a7a2c81f646405654d308db2f58f8ec%7Cd7811cdeecef496c8f91a1786241b99c%7C1%7C0%7C638155831400735344%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=e%2Fyp50KsegsMtKcY9ijwh3AqUbrsxFLo%2BTXyGmzOLps%3D&reserved=0">https://doi.org/10.1021/acscatal.3c00646</a>).<br> A description document ("Data overview.docx") is included and provides an overview of the dataset.</p>
Dataset of the scientific paper " Multimodal robotic system for upper-limb rehabilitation in physical environment" (Advances in Mechanical Engineering)
<p>There are eight files with the following information:<br> - pos_stateXX.bin, binary file with information of the end effector position of the robot device in meters along the three axis (X, Y, Z) during state XX of the experiment<br> - target_stateXX.bin, binary file with information of the target position for the robot device in meters along the three axis (X, Y, Z) during state XX of the experiment<br> - emg_channelXX.bin, binary file with information of channel 1 of the EMG sensor in mV during during the whole time of the experiment<br> - color_stateXX.bin, binary file with information of color filter information during state XX of the experiment. This information is the percentage of pixels with the correct color (yellow, cyan or magenta) inside the region of interest</p> <p> </p>
Supplementary Material for "Formal methods in dependable systems engineering: a survey of professionals from Europe and North America"
<p>This report contains supplemental material for <a href="https://link.springer.com/article/10.1007%2Fs10664-020-09836-5">this paper</a>, including a detailed analysis of responses to certain questions, further visualizations of the collected data, details on our analysis of related work, and a copy of the whole questionnaire. This material was shared for the period of peer review and has been significantly updated, extended, and included in <a href="https://link.springer.com/article/10.1007%2Fs10664-020-09836-5">this journal publication</a>.</p>
Open dataset for publication "Systematic Mapping Study on Requirements Engineering for Regulatory Compliance of Software Systems"
<p>This publication contains open dataset for the journal publication "Systematic Mapping Study on Requirements Engineering for Regulatory Compliance of Software Systems".</p> <p>The dataset contains the data extracted from 280 selected primary studies.</p> <p>The dataset includes the following data:</p> <ul> <li>study metadata (title, venue, publication year, authors, authors’ affiliation, abstract);</li> <li>challenges to regulatory compliance (direct excerpts from studies);</li> <li>categories of challenges to compliance;</li> <li>principles and practices (direct excerpts from text);</li> <li>categories of principles and practices;</li> <li>types of automation of principles and practices;</li> <li>involved stakeholders (direct excerpts from studies);</li> <li>categories of involved stakeholders;</li> <li>phase of the principle and practice life cycle for which involvement of stakeholders was considered;</li> <li>SDLC process areas covered by the study;</li> <li>regulations considered in the study;</li> <li>fields of regulations that were considered;</li> <li>domains of application that were considered;</li> <li>assessment of rigor and relevance of the study.</li> </ul>
Design Methodologies and Engineering Applications for Ecosystem Biomimicry: An Interdisciplinary Review Spanning Cyber, Physical, and Cyber-Physical Systems
<p>This is the data for the interdisciplinary review on ecosystem biomimicry for engineering applications. </p>
A Hybrid Feature Location Technique for Re-engineering Single Systems into Software Product Lines
<p>The dataset used for evaluating the hybrid feature location technique presented in the paper: "A Hybrid Feature Location Technique for Re-engineering Single Systems into Software Product Lines". This enables reproducibility, evaluation, and comparison of our study.</p> <p>_________________________________________________________________________________________________________</p> <p>Folder "Dataset" contains for each subject system used:</p> <p>(i) the artificial variants and their configurations;</p> <p>(ii) the ECCO repository containing the traces;</p> <p>(iii) the ground truth and composed variants;</p> <p>(iv) the metrics results.</p> <p>_________________________________________________________________________________________________________</p> <p>Folder "Scenarios" contains for each subject system used:</p> <p>(i) the videos recorded from exercising features on GUI.</p>
Unveiling Hurdles in Software Engineering Education: The Role of Learning Management Systems
<p>Learning management systems (LMSs) are established tools in higher education, especially in the field of software engineering (SE). The onset of the COVID-19 pandemic further amplified the utilization of these systems, which necessitated their integration into educational curricula for both lecturers and students. However, adopting LMSs within SE education has presented distinctive challenges impeding their seamless incorporation into the courses. This paper aims to scrutinize the challenges and requirements encountered by professors, lecturers, and students in the domain of SE education when using LMSs. We conducted an empirical study that included (i) a survey with 47 professors/lecturers and 133 students, (ii) an analysis of the ensuing data, and (iii) 18 additional interviews conducted with professors and lecturers to delve into nuanced variations in viewpoints. The findings derived from our study reveal that the challenges and requirements pertaining to LMSs are rather specific depending on the scope and size of the respective courses. Nevertheless, many participants have a consensus on numerous challenges and requirements for improving certain features of LMSs in order to improve their usage in SE education. The findings are valuable for advancing research and development in the field of LMSs and provide guidance for lecturers in SE education.</p>
ADAPTING SYSTEMS ENGINEERING TO EVALUATE TECH STARTUPS: AN INNOVATIVE FRAMEWORK BASED ON OMG ESSENCE
<p>The adaptation of system engineering to evaluate technical startups through an innovative framework based on the OMG Essence standard is a modern approach to simplify the process of analyzing and managing startups at various stages of their development. In this study, a universal framework was proposed that allows evaluating technical startups from the point of view of system engineering. This approach takes into account key aspects of startup development, such as requirements, stakeholders, technology, and team, which makes it an important tool for evaluating innovative projects.</p> <p>The main purpose of the proposed framework is to apply the principles of systems engineering to the evaluation of startups, focusing on technical aspects such as system architecture, integration capabilities, and the ability of the team to solve complex tasks. Traditional methods of evaluating startups, often focusing on business aspects, may not always take into account all the technical difficulties and risks that arise when developing software products. The OMG Essence-based framework fills this gap by providing a more comprehensive tool for analyzing and managing startup development.</p> <p>OMG Essence, as a standardized method, acts as a basis for formalizing practices and facilitating interaction between various project participants. The framework based on it offers the possibility of modular adaptation, which allows you to evaluate startups regardless of their complexity and current stage of development. An important feature of OMG Essence is the ability to integrate with other methodologies, which makes it universal for various fields. The application of this standard in the evaluation of startups allows you to obtain more objective results and improve the decision-making process.</p>
Data set of paper Model-Driven System-Performance Engineering for Cyber-Physical Systems
<p>This data set contains the raw and processed data of the paper <em>Model-Driven System-Performance Engineering for Cyber-Physical Systems</em>, published in the proceedings of ESWEEK’21.</p>
Scripts from: Controlling evolution in genetically engineered systems through repeated introduction
<p>Genetically engineered transgenes evolve in the same way as other genetic material. However, evolution in engineered genes is often undesirable and can negatively affect their stability, frequency, and efficacy over time. Methods that maintain the stability of engineered genomes are therefore critical to the successful design and use of genetically engineered organisms. One potential method to limit unwanted evolution is by taking advantage of the ability of gene-flow to counter local adaption, a process of supplementation. Here we investigate the feasibility of supplementation as a mechanism to offset the evolutionary degradation of a transgene in three model systems: a bioreactor, a gene drive, and a transmissible vaccine. In each model, continual introduction from a stock is used to balance mutation and selection against the transgene. Each system has its unique features. The bioreactor system is especially tractable and has a simple answer: the level of supplementation required to maintain the transgene at a frequency is approximately , where <i>s</i> is the selective disadvantage of the transgene. Supplementation is also feasible in the transmissible vaccine case but is probably not practical to prevent the evolution of resistance against a gene drive. We note, however, that the continual replacement of even a small fraction of a large population can be challenging, limiting the usefulness of supplementation as a means of controlling unwanted evolution.</p>
HPC-GAP: Engineering a 21st-Century High-Performance Computer Algebra System
<p>Data for the experiments conducted in the paper</p>
Inconsistency Situations in Engineering of Cyber-Physical Systems
<p>This dataset provided describes inconsistency situation descriptions in the Engineering of Cyber-Physical Systems found in industry environments. It includes 19 situations from 17 industry participants. The participants are mostly from automotive engineering, but also special machine construction and production automation are represented as industries. The 9 involved companies equaly represent Original Equipment Manufacturers (OEM) and Tier-1 suppliers. This dataset will be extended within our future work.</p>
Replication Package: Pandemic Startup Software Engineering: An Experience Report on the Development of a COVID-19 Certificate Verification System
<p><strong>Welcome to the public repository for the additional content of the paper "Pandemic Startup Software Engineering: An Experience Report on the Development of a COVID-19 Certificate Verification System" (Journal of Systems and Software)<br></strong></p> <p>This repository provides additional information to the experience report, including the following files:</p> <ul> <li>survey_questions_de.txt: sheet containing the online questionnaire in German (original language)</li> <li>survey_questions_en.txt: sheet containing the online questionnaire translated into English</li> <li>survey_answers_original.csv: sheet containing the extracted questionnaire data of the participants in German (original language)</li> <li>survey_analysis.csv: sheet containing the analysis of the extracted questionnaire data in English</li> </ul>
Data for: An advanced systems biology framework of feature engineering for cold tolerance genes discovery from integrated omics and non-omics data in soybean
<p><span>Soybean [<em>Glycine max (L.) Merr.</em>] </span><span>serves as one of the most economically valuable crops globally, but it is sensitive to low temperatures during the crop growing season. Currently, agriculture around the world has faced more serious abiotic stresses due to climate change, so there is an urgent need to breed cold-tolerant cultivars to resist the changing environment. The cold-tolerant trait is a complex and quantitative trait controlled by multiple genes, environmental factors, and their interaction. A total of 56 soybean samples were used, including 28 resistant varieties and 28 susceptible varieties, in the field experiments. We selected 55 SNPs (which were mapped to 39 CTgenes) from the CTgenes for distinguishing cold-tolerant lines from cold-susceptible lines. The SNP data can be applied for soybean's cold-tolerant experiment, such as soybean marker-assisted selection, soybean varieties clustering, the systems biology analysis, and further validation. </span></p>
Robotics and Digital Systems Engineering at the Tec de Monterrey
<p><b>Abstract</b></p><p class="dhik-abstract-content">This talk addresses the core competencies of Robotics and Digital Systems Engineers nowadays as well as their integration into undergraduate-level curriculum. Background, curricular map, and examples of international collaboration are detailed based on the experience of Tecnológico de Monterrey.</p><p></p><p><b>Weitere Beiträge aus dem DHIK-Forum 2022 auf Zenodo:</b></p><p class="dhik-session-list"></p><ul><li>Session #1: Viktor Sigrist: Internationalisierung - Partnerschaften für den Ausbau von Forschung und Entwicklung (DOI:<a href="https://zenodo.org/record/7123701">10.5281/zenodo.7123701</a>)</li><li>Session #2: Dieter Leonhard: DHIK- Strategien der internationalen Zusammenarbeit in Forschung und Lehre (DOI:<a href="https://zenodo.org/record/7123456">10.5281/zenodo.7123456</a>)</li><li>Session #3: Stephen Wittkopf: Wissens- und Innovationstransfer - Interdisziplinäre Zusammenarbeit mit Unternehmen und Institutionen (DOI:<a href="https://zenodo.org/record/7025707">10.5281/zenodo.7025707</a>)</li><li>Session #4: Xiao Feng: CDHAW - Chinesisch-Deutsche Hochschule für Angewandte Wissenschaften (DOI:<a href="https://zenodo.org/record/7123458">10.5281/zenodo.7123458</a>)</li><li>Session #5: Antonio Pita und Isabel Kreiner: Academy-Industry-Collaboration - Outreach Strategy (DOI:<a href="https://zenodo.org/record/7123460">10.5281/zenodo.7123460</a>)</li><li>Session #6: Martin Sternberg: Promotionsrecht – aktueller Stand an deutschen Hochschulen für angewandte Wissenschaften (DOI:<a href="https://zenodo.org/record/7123757">10.5281/zenodo.7123757</a>)</li><li>Session #7: Adrian Derungs: Duo mit Innovationskraft - Zusammenspiel von Forschung und Wirtschaft in der Zentralschweiz (DOI:<a href="https://zenodo.org/record/7123767">10.5281/zenodo.7123767</a>)</li><li>Session #8: Theres Paulsen: Transdisziplinäre Forschung - komplexe gesellschaftliche Herausforderungen erfordern diverse Ansätze (DOI:<a href="https://zenodo.org/record/7123769">10.5281/zenodo.7123769</a>)</li><li>Session #9: Jörg Schneider: International research collaboration - New funding opportunities for universities of applied sciences (DOI:<a href="https://zenodo.org/record/7123771">10.5281/zenodo.7123771</a>)</li><li>Session #10: Cornelia Spycher und Matthew Whellens: Horizon Europe - overview of funding opportunities for your research and innovation (DOI:<a href="https://zenodo.org/record/7123773">10.5281/zenodo.7123773</a>)</li><li>Session #11: Janique Siffert: Eureka Eurostars - erfolgreiche Förderung für internationale Innovationsprojekte (DOI:<a href="https://zenodo.org/record/7123777">10.5281/zenodo.7123777</a>)</li><li>Session #12: Ludger Fischer: Energy Lab - ein Netzwerk für innovative Lösungen im Energiebereich (DOI:<a href="https://zenodo.org/record/7123779">10.5281/zenodo.7123779</a>)</li><li>Session #13: Jörg Worlitschek: Thermal energy storage - heating the north, cooling the south (DOI:<a href="https://zenodo.org/record/7123781">10.5281/zenodo.7123781</a>)</li><li>Session #14: Jonas Mühlethaler: Neues DC Microgrid-Konzept – netzunabhängige Elektrifizierung in Entwicklungsländern (DOI:<a href="https://zenodo.org/record/7123783">10.5281/zenodo.7123783</a>)</li><li>Session #15: Tommy Claussen: Dekarbonisierung des Gebäudesektors - digitale Transformation in der Gebäudetechnik und im Gebäudemanagement (DOI:<a href="https://zenodo.org/record/7123785">10.5281/zenodo.7123785</a>)</li><li>Session #16: Christoph Imboden: Flexibility solutions - making the power grid fit for the future (DOI:<a href="https://zenodo.org/record/7123787">10.5281/zenodo.7123787</a>)</li><li>Session #17: Uwe Schulz: Spielerisches Sarnetz - Simulationen für die fossile Unabhängigkeit einer Ortschaft (DOI:<a href="https://zenodo.org/record/7123790">10.5281/zenodo.7123790</a>)</li><li>Session #18: Jana Koehler: Künstliche Intelligenz – Erfolg durch Erwünschtheit, Machbarkeit und Wirtschaftlichkeit (DOI:<a href="https://zenodo.org/record/7123792">10.5281/zenodo.7123792</a>)</li><li>Session #19: Rolf Kamps: KI in der Prävention - Befragungsmethoden und Schulungen trainieren, Krankheitserreger erkennen (DOI:<a href="https://zenodo.org/record/7123794">10.5281/zenodo.7123794</a>)</li><li>Session #20: Gwendolyne Pascua: Artificial Intelligence in Space - CIMON assisting astronauts on the International Space Station (DOI:<a href="https://zenodo.org/record/7123796">10.5281/zenodo.7123796</a>)</li><li>Session #21: Tobias Matter et.al.: Augmented Reality Soundscapes - mit maschinellem Lernen Klangkulissen von zukünftigen Bauvorhaben generieren (DOI:<a href="https://zenodo.org/record/7123798">10.5281/zenodo.7123798</a>)</li><li>Session #22: Angela Nicoara: Internet of Things - transforming businesses, people's lives and driving growth in the coming years (DOI:<a href="https://zenodo.org/record/7123800">10.5281/zenodo.7123800</a>)</li><li>Session #23: Adrian Koller: Feldrobotik - unermüdliche und zunehmend intelligentere Hilfe in der Landwirtschaft (DOI:<a href="https://zenodo.org/record/7123802">10.5281/zenodo.7123802</a>)</li><li>Session #24: Widar von Arx et.al.: Realisierung der Verkehrswende - Einfluss der Preispolitik in der Mobilität (DOI:<a href="https://zenodo.org/record/7124000">10.5281/zenodo.7124000</a>)</li><li>Session #25: Andreas Liebrich: Tourismusdateninfrastruktur - Was die Schweiz von Europa lernen kann (DOI:<a href="https://zenodo.org/record/7123806">10.5281/zenodo.7123806</a>)</li><li>Session #26: Frank Pöhlau und Stefan May: Find life on Mars - Schülerprojekte zur mobilien Robotik (DOI:<a href="https://zenodo.org/record/7123808">10.5281/zenodo.7123808</a>)</li><li>Session #27: Jiayun Shen: Open Innovation - Innovationsmanagement bei der Schweizerischen Post (DOI:<a href="https://zenodo.org/record/7123810">10.5281/zenodo.7123810</a>)</li><li>Session #28: Tobias Specker: Interkulturelles Management – innovative Konzepte zum Ausbau der China-Kompetenzen an Hochschulen (DOI:<a href="https://zenodo.org/record/7123812">10.5281/zenodo.7123812</a>)</li><li>Session #29: Elena Algorri: Swimming robots - exploring the unterwater from the surface (DOI:<a href="https://zenodo.org/record/7123814">10.5281/zenodo.7123814</a>)</li><li><b>Session #30: Sergio Camacho: Robotics and Digital Systems Engineering at the Tec de Monterrey (<a href="#collapseTwo">Video</a>)</b></li><li>Session #31: Thomas Dorn: Industrie 4.0 - Forschungskooperationen mit der CDHAW und der Tongji Universität Shanghai (DOI:<a href="https://zenodo.org/record/7123818">10.5281/zenodo.7123818</a>)</li><li>Session #32: Walter Reichert et.al.: Kollaboration und Unterstützung - Mobile Robotik und Exoskelette in der flexiblen Produktion (DOI:<a href="https://zenodo.org/record/7123820">10.5281/zenodo.7123820</a>)</li><li>Session #33: Louis Palmer: Solar Butterfly - climate pioneer world tour supported by HSLU (DOI:<a href="https://zenodo.org/record/7123822">10.5281/zenodo.7123822</a>)</li></ul><p></p>
On a Microservice System Benchmark with Multiple Architected Variants for Software Engineering Research
Open the record for dataset details and reuse information.
Assessing the Resilience of Software Systems by Application of Chaos Engineering - A Case Study
<p>This repo contains all supplementary data sets that I have created and used throughout my bachelor's thesis. In particular, it contains<br> - JMeter configuration file<br> - CSV files of measured JMeter runs<br> - Chaos Experiments declared in JSON<br> - Created boxplots and ecdf plots based on the CSV files<br> - Kubernetes deployments<br> - Bash scripts <br> </p>
Dataset for article Development of Vancomycin Delivery Systems Based on Autologous 3D Platelet-Rich Fibrin Matrices for Bone Tissue Engineering
<p>This is a dataset related to the article "Development of Vancomycin Delivery Systems Based on Autologous 3D Platelet-Rich Fibrin Matrices for Bone Tissue Engineering". Dubnika, A.; Egle, K.; Skrinda-Melne, M.; Skadins, I.; Rajadas, J.; Salma, I.</p> <p> </p>
A Case Study on AI Engineering Practices: Developing an Autonomous Stock Trading System
<p>The field note data related to a case study on AI engineering practices. During the case study, an autonomous stock trading system was developed, while 10 AI engineering practices were applied. We used field notes to document the application of each practice. Additionally, we documented any challenges we experienced.</p> <ul> <li>field-notes-practices.csv: the documented experiences with the AI engineering practices containing the name of the practice, the perceived effectiveness of the practice on an ordinal scale (--, -, 0, +, ++), a description of how it was applied and its effects, and the date when it was applied (in DD.MM.YYYY format).</li> <li>field-notes-challenges.csv: the documented challenges experiences during the case study containing the date (in DD.MM.YYYY format), a description of the challenge, the source that made us became aware of the challenge, the solution we used to overcome the challenge, and a description of the frequency of occurrence.</li> </ul>
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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.