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180 results for “Job”
Job Shop Scheduling instances (SS + RD + EC)
<h1>Instance Structure</h1> <h2>📁 Definition:</h2> <p>For example, the filename `5_5_0_2_5_0.json` is defined as follows: 5 represents the number of jobs, 5 represents the number of machines, 0 indicates the type of distribution (0 = exponential, 1 = normal, 2 = uniform), 2 indicates the type of release and due date (0 = no restriction, 1 = by job, 2 = by operations), 5 denotes the quantity of speed scaling options for each machine, and 0 is the instance number.</p> <h2>📊 Job IDs: </h2> <p>An array of integers representing the job IDs (from 0 to 4).</p> <p><code>"nbJobs": [0, 1, 2, 3, 4]</code></p> <h2>🛠 Number of Machines: </h2> <p>An array of integers representing the number of machines (from 0 to 4). Each machine refeer an operation of a job that should be procedeed.</p> <p><code>"nbMchs": [0, 1, 2, 3, 4]</code></p> <p> </p> <h2>⏱️ Time and Energy:</h2> <p>An array of objects, each containing information about a job processed on a machine, including multiple speed-scaling options. Each job object includes the job ID, operations (with operation IDs as keys), and details such as processing time, energy consumption, release date, and due date.</p> <p><code>"timeEnergy": [</code><br><code> {</code><br><code> "jobId": 0,</code><br><code> "operations": {</code><br><code> "1": {</code><br><code> "speed-scaling": [</code><br><code> {"procTime": 209, "energyCons": 12},</code><br><code> ...</code><br><code> ],</code><br><code> "release-date": 0,</code><br><code> "due-date": 31</code><br><code> },</code><br><code> ...</code><br><code> }</code><br><code> },</code><br><code> ...</code><br><code>]</code></p> <h2>📅 Due Dates and Release Dates:</h2> <p>Within each operation in the `timeEnergy` array, the `release-date` represents the release date of the operation (in milliseconds) and the `due-date` represents the due date of the operation (in milliseconds).</p> <h2>🔄 Speed Scaling Options:</h2> <p> Each operation contains multiple speed-scaling options, providing different combinations of processing times and energy consumption levels.</p> <p><code>"speed-scaling": [</code><br><code> {"procTime": 209, "energyCons": 12},</code><br><code> {"procTime": 52, "energyCons": 59},</code><br><code> {"procTime": 40, "energyCons": 67},</code><br><code> {"procTime": 32, "energyCons": 72},</code><br><code> {"procTime": 30, "energyCons": 74}</code><br><code>]</code><br><br></p> <h2>🧩 Example:</h2> <p>Here is an example of how the data is structured for a specific job and its operations:</p> <p><br><code>{</code><br><code> "nbJobs": [0, 1, 2, 3, 4],</code><br><code> "nbMchs": [0, 1, 2, 3, 4],</code><br><code> "timeEnergy": [</code><br><code> {</code><br><code> "jobId": 0,</code><br><code> "operations": {</code><br><code> "1": {</code><br><code> "speed-scaling": [</code><br><code> {"procTime": 209, "energyCons": 12},</code><br><code> {"procTime": 52, "energyCons": 59},</code><br><code> {"procTime": 40, "energyCons": 67},</code><br><code> {"procTime": 32, "energyCons": 72},</code><br><code> {"procTime": 30, "energyCons": 74}</code><br><code> ],</code><br><code> "release-date": 0,</code><br><code> "due-date": 31</code><br><code> },</code><br><code> "3": {</code><br><code> "speed-scaling": [</code><br><code> {"procTime": 135, "energyCons": 25},</code><br><code> {"procTime": 40, "energyCons": 67},</code><br><code> {"procTime": 30, "energyCons": 74},</code><br><code> {"procTime": 28, "energyCons": 75},</code><br><code> {"procTime": 23, "energyCons": 79}</code><br><code> ],</code><br><code> "release-date": 32,</code><br><code> "due-date": 72</code><br><code> },</code><br><code> ...</code><br><code> }</code><br><code> },</code><br><code> ...</code><br><code> ]</code><br><code>}</code><br><br></p>
Ultimaker 2 sensor data for several print jobs
<p>This datasets were measured the same way as <a href="https://doi.org/10.5281/zenodo.54574">https://doi.org/10.5281/zenodo.54574</a>. But instead of capturing only events, the positions of the printer head and the printer plate were measured for all print jobs of Ultimaker 2 3D printer until 2016 and combined into one file.</p>
An Analysis of the 35+ Million Jobs of Travis CI
<p>This artifact contains a dataset of 35 793 144 TravisCI jobs configuration. This dataset has been created and used in the paper <a href="https://arxiv.org/abs/1904.09416"><em>An Analysis of 35+ Million Jobs of Travis CI </em></a>published at ICSME'19. </p> <p> </p> <blockquote> <pre>@inproceedings{durieuxTravis2019, title={An Analysis of 35+ Million Jobs of Travis CI}, author={Durieux, Thomas and Abreu, Rui and Monperrus, Martin and Bissyand{\'e}, Tegawend{\'e} F and CRUZ, LU{\'I}S}, booktitle={2019 IEEE International Conference on Software Maintenance and Evolution (ICSME)}, year={2019} }</pre> </blockquote>
Crunchbase in RDF: A Large Data Set About Jobs, Websites, Organizations, News, People, Products, and Acquisitions
<p><strong>CrunchBase</strong> in an online platform providing information about startups and technology companies, including related entities such as the products they sell, key people they employ, and investments they made and received.</p> <p>We provide here an <strong>RDF data set of Crunchbase</strong> as of October 2015. The data set contains information about</p> <ul> <li>1,946,435 jobs</li> <li>1,348,449 websites</li> <li>567,937 organizations</li> <li>519,763 news</li> <li>430,093 people</li> <li>60,076 products, and</li> <li>33,127 acquisitions.</li> </ul> <p>The data set has been used, among other things, for data integration with financial data sources to evaluate the performance of particular companies and for monitoring news to find statements that are not in Crunchbase as an RDF knowledge graph yet.</p> <p>Note that the provided data set was created in October 2015 when all Crunchbase data was <strong>licensed under Creative Commons Attribution-NonCommercial License 4.0 (CC-BY-NC) and partly under Creative Commons Attribution License 4.0 (CC-BY)</strong>. Also the provied<strong> data set is licensed under these licenses.</strong> Concerning licensing of current Crunchbase data, we can refer to <a href="https://about.crunchbase.com/terms-of-service/">https://about.crunchbase.com/terms-of-service/</a>.</p> <p>For <strong>more information</strong> about the data set, see our paper <a href="http://dbis.informatik.uni-freiburg.de/content/team/faerber/papers/CrunchBaseWrapper_SWJ2017.pdf">A Linked Data Wrapper for CrunchBase.</a></p> <p>When you use the data set, please <strong>cite</strong> us as follows:</p> <blockquote> <p>Michael Färber, Carsten Menne, Andreas Harth. “A Linked Data Wrapper for CrunchBase”. In: Semantic Web Journal 9(4). IOS Press, 2018, pp. 505–5015. (<a href="https://dblp.org/rec/bibtex/journals/semweb/FarberMH18">BibTeX entry at DBLP</a>)</p> </blockquote>
Soft skills found in job adverts in Cyprus from ESEM 2024 paper (analysis results)
<p>This dataset contains results from the analysis on Soft skills requested in the software industry found in job adverts in Cyprus collected in early 2023 and early 2024.</p> <p>The dataset contains the following:</p> <ul> <li>Soft skills found in all job adverts</li> <li>Soft skills differences between 2023 and 2024 job adverts</li> <li>Job positions categories in the job adverts</li> <li>Soft skills per job position category</li> <li>Soft skills per company size</li> </ul> <p>The relevant publication has been accepted in the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM 2024 - <a href="https://conf.researchr.org/track/esem-2024/esem-2024-technical-track#event-overview">https://conf.researchr.org/track/esem-2024/esem-2024-technical-track#event-overview</a>):</p> <p><em>Georgia Kapitsaki, Loukas Chatzivasili, Maria Papoutsoglou, Matthias Galster, "An Exploratory Study on Soft Skills present in Software Positions in Cyprus: a quasi-Replication Study", ESEM 2024.</em></p>
Replication materials for Schmutte (2014) "Free to Move? A Network Approach to the Analysis of Job Mobility"
<p>This folder contains datasets and coded needed to replicate results published in Schmutte, Ian M. (2014) "Free to Move? A Network Approach to the Analysis of Job Mobility, " Labour Economics vol.29 pp.49--61</p>
Job offers of remote and data-science related positions - Source: Remotive.com
<p>Most relevant job offers published in the categories of software development, data and sysadming and devops of the web Remotive.com</p>
CA Jobs Dataset: Comprehensive Job Count Information by Company - February, 2023
<p><a href="https://tarta.ai/open-data/datasets/number-of-jobs-by-company-in-CA-0223">This dataset</a> provides a comprehensive view of the job market, highlighting the companies and cities that have the highest number of job opportunities.</p> <p>The <a href="https://tarta.ai/open-data/datasets">Tarta.ai dataset</a> is a valuable resource for anyone interested in the job market and provides a comprehensive view of the employment landscape across different industries and regions.</p> <p>This dataset was created by Tarta.ai and contains information on the number of jobs by company and city in California, with features such as:</p> <p>• Company name<br> • City<br> • State<br> • Number of active jobs</p>
The Moderating Effect of Employee Agility on the Link between Employee Vitality, Digital Literacy and Transformational Leadership with Job Performance: An Empirical Study of HR Practitioners in the Manufacturing Sector of Northern Malaysia.
<p>This is a dataset for a study that examines the effects of employee vitality, digital literacy, and transformational leadership on job performance. Additionally, it investigates the moderating role of employee agility in these relationships. Data were collected from HR practitioners in manufacturing companies in the northern region of Malaysia for analysis. The results indicate that the job performance of HR practitioners is positively influenced by employee vitality, digital literacy and transformational leadership. </p>
A-10 Thunderbolt (Ukraine paint job)
A-10 Thunderbolt with Ukraine paint job. Painted in the colors of the Ukrainian flag to support Ukraine! Source: Objaverse 1.0 / Sketchfab
Effect of Ranitidine on Hyper-IgE Recurrent Infection (Job's) Syndrome
ClinicalTrials.gov study NCT00527878. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Effects of Acupressure on Nurses' Psychological Distress, Depression, Job Stress, Occupational Burnout, and Resilience
ClinicalTrials.gov study NCT06946888. IPD Sharing: NO. Countries: 1. Publications: 19.
Virtual Reality Job Interview Training in Severe Mental Illness
ClinicalTrials.gov study NCT03049813. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Leaving academia: Insights from evolutionary biologists on their career transitions and job satisfaction
Open the record for dataset details and reuse information.
The functional role of sibling aggression and “best of a bad job” strategies in cichlid juveniles
Open the record for dataset details and reuse information.
Impacts of life satisfaction, job satisfaction and Big Five personality traits on satisfaction with the indoor environment in Singapore
Open the record for dataset details and reuse information.
Do Ethnicity and Sex of Employers Affect Applicants' Job Interest? An Experimental Exploration
<p>Data and do-file supporting the results presented in the manuscript "Do Ethnicity and Sex of Employers Affect Applicants’ Job Interest? An Experimental Exploration."</p>
Bioinformatic Jobs
<p>This is a list of Bioinformatics Jobs posts in 2015-2016</p>
PM100: A Job Power Consumption Dataset of a Large-Scale HPC System
<p>The dataset is a collection of jobs extracted from the job_table data of M100 (<a href="https://doi.org/10.5281/zenodo.7588815">https://doi.org/10.5281/zenodo.7588815</a>), a collection of data extracted from a Tier-0 supercomputer hosted at CINECA (Marconi100, <a href="https://www.hpc.cineca.it/hardware/marconi100">https://www.hpc.cineca.it/hardware/marconi100</a>). The original job data present in M100 are filtered out by considering only the jobs running exclusively on the resources. Each job entry included in PM100 contains the power consumption of the job recorded at Node level, CPU level and Memory level. The final dataset contains 231116 jobs, executed on Marconi100 between May and October 2020. </p><p>The dataset is stored as a parquet file, where each entry contains the information on a job execution. </p><p>The structure of the data, as well as the code to generate them, is contained in the official GitHub repository of the project: <a href="https://github.com/francescoantici/PM100-data/">https://github.com/francescoantici/PM100-data/</a>.</p>
Job Opportunities in NGOs for Sustainable Development in Myanmar
<p>During the Sabai Webinar Series 6, hosted by the Shwetaungthagathu Reform Initiative Centre (SRIc), Burmese Young Experts, including Ms May Wah Htwe, Capacity Building Specialist, Ms Yoon Aeindra Aung, Freelance Communication Consultant, engaged in a discussion on Job Opportunities NGOs for Sustainable Development. </p> <p>They highlighted the prerequisites and essential preparations required for individuals seeking to engage in meaningful work with NGOs and international Non-Governmental Organisations (INGOs) in Myanmar. </p> <p>This Sabai Webinar Series was conducted under the Edu4SD project. </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.