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180 results for “Job”
Supplement Data to Manuscript "Allocating small transporters to large jobs"
<p><strong>Data Description</strong></p> <p>In the data file `instances.csv`, we provide the original data that was used for the manuscript `Allocating small transporters to large jobs` by Neil Jami, Neele Leithäuser and Christian Weiß from Fraunhofer ITWM. </p> <ul> <li>SimulationId: Identifier for each configuration (encoded by NumberJobs_NumberResources).</li> <li>InstanceIndex: Running index for each sample of a simulation configuration.</li> <li>NumberJobs: Number of jobs in the simulation configuration.</li> <li>NumberResources: Number of available resources (transporters) in the simulation configuration.</li> <li>JobReturnTimes: Array of return times for the individual jobs in this sample.</li> <li>NumberResourceWithCapacity_1: Number of resources in this sample that have Filling time =1.</li> <li>NumberResourceWithCapacity_2: Number of resources in this sample that have Filling time =2.</li> <li>NumberResourceWithCapacity_3: Number of resources in this sample that have Filling time =3.</li> <li>NumberResourceWithCapacity_4: Number of resources in this sample that have Filling time =4.</li> <li>NumberResourceWithCapacity_5: Number of resources in this sample that have Filling time =5.</li> </ul>
The Relationship between Nursing Job Satisfaction and Missed Nursing Care in Critical Care Units
<p>Data set for The Relationship between Nursing Job Satisfaction and Missed Nursing Care in Critical Care Units</p>
The Dream Job: CVs and Cover Letters | Researching Islam | iBrary
<p>This video introduces the module “The Dream Job: CVs and Cover Letters” from the course Researching Islam, taught by Prof. Shafique N. Virani. You can download the complete online course, including this module, for free from <a href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbkdlMWFaLVFnTnptVDV6OE1NZ192b1JCUC1OQXxBQ3Jtc0ttdE5tdUxQSEc5QmxIdm5XNVhuLWhDVHlVSnFQek9jdS10a1RmOXRUb0k3YjZwQ1I5S1k5R0dQa0ExeW03dTdodzhNS1hJYmVFMU16LU1LWVhmNjVwbmNZM3JxcnRCYTYzUVVqNDVkUkQwYkJ5amM1bw&q=https%3A%2F%2Fwww.ecampusontario.ca%2F&v=my0mcLpevVc">https://www.ecampusontario.ca/</a>.</p>
Job Shop Instances with Varying Job and Operation Entropy
<p>This dataset contains multiple sets of job shop problem instances with varying characteristics. Instances have been generated for various target inter-instance job entropies, intra-instance job entropies, inter-instance operation entropies, and intra-instance operation entropies. For reference, the dataset also contains randomly generated job shop instances. More information about the data generation and the used terminology can be found in the accompanying data publication.</p> <p>Each problem instance contains the following information in json-format:</p> <ul> <li>id: a unique id for each generated problem instance</li> <li>opt_time: the optimal makespan for the problem instance determined by Google ORTools</li> <li>intra_instance_operation_entropy: the intra-instance operation entropy of the instance</li> <li>num_ops_per_job: the number of operations of each job max_op_time: the maximum processing time of all operations</li> <li>machine_types: the type of machine required for each operation in each job</li> <li>durations: the processing time of each operation in each job</li> </ul>
"I was the class teacher at that time. It was a class trip, usually organized near the end of the schoolterm in summer. The pupils went there by bike to have a barbecue at the sandy banks of the river Rhine near Dusseldorf. The landscape around is mostly dominated by agriculture and glasshouse cultures. You find a mixture of former villages nowadays completely suburbanized. The population finds jobs in the nearby urban centers like Dusseldorf, Neuss and other big cities. The reason why Irecorded the scene is simply because Iam interested in collecting sounds in general by doing recordings in different surroundings like nature, cities and everything between. My memories about the event are that it was a relaxing and funny atmosphere, which is not always the case while teaching in a classroom" [Reinhard/reinsamba]15 in Collecting Sounds. Online Sharing of Field Recordings as Cultural Practice
"I was the class teacher at that time. It was a class trip, usually organized near the end of the schoolterm in summer. The pupils went there by bike to have a barbecue at the sandy banks of the river Rhine near Dusseldorf. The landscape around is mostly dominated by agriculture and glasshouse cultures. You find a mixture of former villages nowadays completely suburbanized. The population finds jobs in the nearby urban centers like Dusseldorf, Neuss and other big cities. The reason why Irecorded the scene is simply because Iam interested in collecting sounds in general by doing recordings in different surroundings like nature, cities and everything between. My memories about the event are that it was a relaxing and funny atmosphere, which is not always the case while teaching in a classroom" [Reinhard/reinsamba]15
Dataset from Paper: What does Power Consumption Behavior of HPC Jobs Reveal?
<p>The dataset in the tarball was used as job- and power-trace input for the paper "What does Power Consumption Behavior of HPC Jobs Reveal?", published at the International Parallel and Distributed Processing Symposium 2020 (IPDPS'20) in New Orleans, Louisiana.</p> <p>For more details on files, clusters, and data format, please see the README file in the archive.</p>
The functional role of sibling aggression and "best of a bad job" strategies in cichlid juveniles
Siblings often compete for limited resources such as food provided by their parents. However, although several functions of non-lethal sibling (non-siblicidal) aggression have been proposed, there is currently little empirical evidence for these, apart from food monopolization. Here, we investigated the functions of non-lethal sibling aggression in the biparental-caring territorial herbivorous cichlid Varibilichromis moorii. We found that the juveniles of this species are highly aggressive and that larger juveniles are more aggressive toward their smaller siblings. Larger juveniles feed on algae more frequently than smaller siblings, thereby indicating a dominance hierarchy. Sibling aggression decreased when algae in the nest was experimentally removed. Furthermore, removal of smaller juveniles decreased sibling aggression among the remaining larger juveniles, whereas removal of larger juveniles increased aggression among smaller juveniles. The algal feeding rate of juveniles only increased when larger individuals were removed from the nest. Moreover, larger juveniles attained higher growth rates and remained in natal nests longer than smaller individuals. Our results indicate that sibling aggression may facilitate the monopolization of resources by larger juveniles and extend the parental care period. Interestingly, a small sub-set of juveniles were observed to migrate to other nests. These juveniles were larger than those of the host brood, and their growth rate increased within the new nests. We suggest that subordinate juveniles may disperse from natal nests and sneak into new nests to enhance their rank, which may represent a novel example of a "best of a bad job" strategy associated with sibling competition.
Optimal Map Reduce Job Capacity Allocation in Cloud Systems - DATA
<p>The data part of this release support the results <br /> presented in the paper <br /> "Optimal Map Reduce Job Capacity Allocation in Cloud Systems", <br /> by M. Malekimajd, D. Ardagna, M. Ciavotta, A.M. Rizzi and Mauro Passacantando. Published on <br /> ACM SIGMETRICS Performance Evaluation Review. 42 (4), 50-60. 2015.</p> <p>When referring to the dataset or scripts please cite the paper above. </p>
Job metrics for Big Data Technologies
<p>This dataset contains metrics for a 10 minute job running on YARN. More specifically it contains metrics for:</p> <ul> <li>YARN</li> <li>HDFS</li> <li>System Metrics (CPU, RAM, HDD, Interface etc.)</li> </ul> <p> </p> <p> </p>
Data from: Effectiveness of Online Off-the-Job Training in Attracting Participants and Video-On-Demand Streaming in Improving Work-Life Balance: A Study Focusing on Medical Technologists
<p>The Nara Association of Medical Technologists has introduced online Off-Job Training (Off-JT) starting from FY2020 in response to the COVID-19 pandemic. This study aims to evaluate the online Off-JT, which differs from the traditional face-to-face format. Firstly, we compared the online format's ability to attract participants with the face-to-face format based on the number of training sessions and attendees. Despite having fewer training sessions (40.8% less), the online format had an average attendance of 105.4% higher (39.7 vs. 19.3) than the face-to-face format. To enhance participant convenience, we offered a limited number of live and video-on-demand (VOD) sessions on YouTube, evaluating their usefulness through an online survey focusing on work-life balance (WLB). The survey results showed that 81.9% (458/559) of respondents reported an improvement in WLB. The effect on WLB improvement varied depending on the viewing method, with VOD sessions showing 84.1% (376/447) and live sessions showing 73.2% (82/112). We believe that the increased ability to attract participants in the online Off-JT is mainly due to the elimination of travel burdens through internet-connected devices. The combination of live and VOD sessions on YouTube allowed participants to adjust their viewing time, leading to better allocation of free time and improved WLB. The online Off-JT and VOD delivery have shown to enhance convenience for participants by removing geographical and time constraints, resulting in positive effects.</p>
Job_offer/Companies_information
<p><strong>Dataset Job_offer:</strong></p><p>En este dataset hemos recopilado la información principal sobre <strong>1251</strong> ofertas de trabajo en diferentes ciudades (Madrid, Kiev, Um Bada, Buenos Aires, Tokio, Nueva Delhi) que incluye la ubicación, requisitos, puesto y salario de la oferta. Los datos que contiene el dataset corresponden a las ofertas de empleo del año 2023.</p><p><strong>Dataset Companies_information:</strong></p><p>En este dataset hemos recopilado la información principal sobre </p><p><strong>227 </strong></p><p>empresas que ofrecen trabajo en la plataforma LinkedIn en diferentes ciudades/países (Madrid, Kiev, Um Bada, Buenos Aires, Tokio, Nueva Delhi), que incluye la ubicación, descripción, sector, número de empleados y etc. Los datos que contiene el dataset corresponden a los datos sobre las empresas en el año 2023.</p><p> </p><p><strong>Dataset Job_offer:</strong></p><p>El dataset contiene las siguientes columnas:</p><ul><li>Job_title - describe el nombre del puesto</li><li>Company - nombre de la empresa de la oferta</li><li>Location - ciudad y país de la oferta de trabajo</li><li>Presence - tipo de presencialidad (presencial/remoto/híbrido)</li><li>Workday - tipo de jornada</li><li>Responsibility - nivel de experiencia o responsabilidad</li><li>Num_application - número de las solicitudes ya enviadas para la oferta</li><li>Description - descripción de la oferta</li><li>Publish_date - dia de publicación</li><li>Salary - salario</li></ul><p>Los datos han sido recopilados durante y para el año 2023.</p><p><strong>Dataset Companies_information:</strong></p><p>El dataset contiene las siguientes columnas:</p><ul><li>Name - nombre de la empresa</li><li>Sector - industria/categoría a la que pertenece la empresa</li><li>Headquarters - ubicación de la sede/oficina principal</li><li>Description - descripción de la empresa</li><li>Num_employees - número de los empleados de la empresa</li><li>Website - dirección al sitio web de la empresa</li><li>Specialties - áreas específicas de los servicios que ofrece la empresa</li><li>Founded_on - fecha de fundación</li></ul><p>Los datos han sido recopilados durante y para el año 2023.</p>
Job Prediction based on Skills and Years of experience
<h2><strong>Purpose:</strong></h2><p>This dataset was meticulously collected by me during my academic journey. It comprises information on various attributes related to individuals' academic backgrounds, programming skills, work experiences, and roles in the field of technology. The dataset is specifically designed for job prediction purposes, helping to analyze and forecast potential job roles based on individuals' qualifications.</p>
Job 1:21
Naked I came from my mother's womb, and naked I will depart. The Lord gave and the Lord has taken away, may the name of the Lord be praised. Source: Objaverse 1.0 / Sketchfab
Bank Job 3D
The best part about a career in banking is that you can ultimately choose from a wide range of [jobs bank](https://www.recutran.com/jobs) titles beyond the classic bank teller or loan officer roles. You might give small companies the chance to grow and thrive, or help families get their finances and futures in order. Source: Objaverse 1.0 / Sketchfab
Dataset Internal Communication and Job Satisfaction 2019-2024
Open the record for dataset details and reuse information.
Job offers from Lanbide Basque Country Public Employment Portal
<p>Based on the provided sample from the "Job_offers_from_Lanbide_Basque_Country_Public_Employment_Portal" dataset, here is a summarized description in English:</p> <p>The dataset compiles various job listings, including local offers from Lanbide, wider European offers, public sector job listings, and offers from other job portals managed within the Lanbide web platform. Each record in the dataset appears to represent a unique job offer with a range of attributes detailing the position. Common attributes for each job listing include:</p> <p>- <strong>Extraction_timestamp</strong>: The date and time when the job offer was last updated, reflecting the currency of the data.<br>- <strong>Source</strong>: A numerical or categorical identifier that may correspond to the origin of the job offer, such as Lanbide, other European job portals, public offers, etc.<br>- <strong>Title</strong>: The name or title of the job position.<br>- <strong>AddressLocality</strong>: The local town or city where the job is located.<br>- <strong>AddressRegion</strong>: The broader region, province, or administrative area where the job is located.<br>- <strong>Description</strong>: A detailed description of the job, including responsibilities, requirements, and other relevant information such as contract type, shifts, start date, salary, and any specific qualifications like a disability percentage or certifications.<br>- <strong>DatePosted</strong>: The date the job was originally posted.<br>- <strong>Offer_Number</strong>: A unique identifier for the job offer.<br>- <strong>EmploymentType</strong>: The type of employment contract offered (e.g., temporary labor).<br>- <strong>Collective</strong>: Any specific community or group the job is targeting, such as people with disabilities.<br>- <strong>OccupationalCategory</strong>: The category or sector of employment, potentially aligning with standard occupational classification systems.<br>- <strong>Workday</strong>: Details regarding the work schedule.<br>- <strong>NumberPositions</strong>: The number of positions available.<br>- <strong>Participants</strong>: Possibly the number of current applicants or participants<br>- <strong>EmploymentSituation</strong>: This field could detail the employment status required.<br>- <strong>Age</strong>: Any age requirements.<br>- <strong>EducationRequirements</strong>: Educational or training requirements necessary for applicants.<br>- <strong>DriverLicense</strong>: Information on whether a driver's license is required.<br>- <strong>ExperienceRequirements</strong>: The amount of experience required.<br>- <strong>ContactInformation</strong>: Details for contacting the employer or recruiter.</p> <p>Each job listing encapsulates comprehensive information that would aid job seekers in understanding the requirements and expectations of each role and for employers or recruiters in managing the recruitment process.</p>
101K workflow jobs dataset (1.2 million tasks); a composition of Epigenomics and Montage workflows
<p>This dataset contains detailed information about more than 101 thousand jobs with 1.2 million tasks. This dataset can be used in various simulation, training, and modelling processes. various information about each job is recorded and the underlying environment was based on IoT/Fog/Cloud in which IoT nodes only generate requests and Fog and Cloud nodes process these requests.</p>
Digital Transformation and Its Relationship to the Job Performance of Employees at a Private University in Peru
<p><span>Private universities in Peru still need to implement digital transformation models to enhance the job performance of faculty and staff, achieving consistent improvement in the performance levels of university teachers by deploying technological and didactic tools for students. Therefore, the study aims to determine the relationship between digital transformation and the job performance of employees at a Private University. The research approach was quantitative, employing a non-experimental, longitudinal correlational design. The technique used was a survey, applied to a sample of 104 employees (school heads, faculty, and a director) from the university on a national level from a total population of 144. The findings highlight that organizational motivation to achieve high performance significantly affects job performance. This motivation creates pressure to achieve the desired outcomes. According to over 90% of the surveyed faculty, these demands foster a sense of urgency, though sometimes exceeding the capabilities of the employee. Therefore, creating an innovative culture across all hierarchical levels and identifying key technologies that add value to the learning flow can meet the needs of an increasingly demanding society.</span></p> <p><strong><span>Keywords: </span></strong><span>digital transformation, job performance, virtual education, digital tools, educational quality.</span></p>
Job Ads in Retail and E-commerce sectors for INAIR project countries
<p><strong>INAIR</strong> (<a href="https://www.ai4retail.eu/en/">Increasing the Uptake of AI in Retail</a>) is a Coordination and Support Action funded by the European Union'’s Horizon Europe Research and Innovation programme - Grant Agreement No. 101133847. The project aims to contribute to reducing the AI skills gap of European MSMEs in Retail, to let them exploit the potential of AI for greening their businesses, support their competitiveness in the global market and ultimately contribute to reaching the digital decade target of 75%+ European companies adopting AI technologies by 2030. </p> <p>This dataset contains job advertisements from the retail and e-commerce sectors in Cyprus, Germany, Italy, Poland, and Romania, collected as part of the INAIR Horizon Europe project. This resource supports analyses of digital skill requirements and helps identify trends and gaps in the labor market for the retail and e-commerce sectors.</p> <p>Data was collected three times during the period from March to May 2024, resulting in a total of 44,494 job offers.</p>
Galaxy job runtime measurements with Encrypted and plain storage volumes on Cloud deployments.
<p>Storage volume performance measurement on Cloud environment using Galaxy and Mapping tools: Bowtie2, STAR and Salmon. Galaxy job runtime for encrypted and not ecrypted storage volumes are reported.</p> <p>Scripts and Documentation on GitHub.</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.