Burnout and perceived health in medical residents after the COVID-19 pandemic: a single-center cross-sectional study. [PDF]
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Impact of artificial intelligence and work digitalization on mental health and occupational well-being: a scoping review. [PDF]
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Integrating machine learning and explainable AI for employee attrition prediction in HR analytics. [PDF]
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Influence of person-organization fit on job satisfaction among pre-service preschool teachers of China: Mediation of teaching self-efficacy and perceived teacher competence. [PDF]
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Burnout and posttraumatic stress among nurses in German care homes: a cross-sectional survey during the COVID-19 pandemic. [PDF]
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Related searches:
The Job-Shop Problem and Immediate Selection
Annals of Operations Research, 1994For solving job-shop problems using a branch-and-bound method it is important to introduce order relations before the branching starts in order to reduce the computational effort. This may be done by using immediate selection methods to fix as many order relations as possible.
Peter Brucker +2 more
openaire +3 more sources
Summary form only given. Few decisions in one's life are as important as choosing the right job. This conundrum combined with deciding whether to accept a new job in a different city, is surely a thought provoking and soul-searching choice. Emotions can run high in such a situation, and the wrong outcome could result if proper attention is not paid to ...
C. Duarte, R. Gilmore, C. Yang
openaire +1 more source
From a preselected list of 20 items that may influence students' impressions of potential employers, 550 U.S. hospitality students from 19 schools ranked those factors and assigned those involving personal interaction the highest ratings. The most influential factors were (1) Experience with the company as a consumer; (2) Word of mouth from faculty ...
Michael P. Sciarini, Robert H. Woods
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Intelligent job selection for distributed scheduling
[1993] Proceedings. The 13th International Conference on Distributed Computing Systems, 2002A key issue in distributed scheduling is selecting appropriate jobs to transfer. A job selection policy that considers the diversity of job behaviors is proposed. A mechanism used in artificial neural networks, called weight climbing, is employed. Using this mechanism, a distributed scheduler can learn the behavior of a job from its past executions and
Chang-Jia Wang +2 more
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