Objective:The paper aimed to explore the impact of work support and potential for career advancement on the nurse turnover intention in order to find an effective approach to curb high turnover.Methods:A cross-section...Objective:The paper aimed to explore the impact of work support and potential for career advancement on the nurse turnover intention in order to find an effective approach to curb high turnover.Methods:A cross-sectional survey of 526 nurses from eight teaching hospitals in Tianjin,China,was conducted to test the hypothesized multilevel model.The organizational career growth scale,work support scale,and the nurse turnover intention scale were used to measure the effect of organizational career growth and work support on nurse turnover intention.Finally,SPSS 17.0 and AMOS 17.0 software were used to analyse the relationship of these variables.Results:The score of the three scales nurse turnover,organizational career growth,and work support were 1.98±0.60,2.40±0.50,and 4.06±0.98,respectively.The total and direct effects of work support on turnover intention were0.361(p<0.01)and0.147(p<0.01),respectively.The indirect effect was0.169 with a 95%bootstrap confidence interval of0.257 to0.102.Conclusion:The study showed a lack of work support negatively and directly associated with nurse turnover intention.Additional opportunities for career growth within the organization may strengthen the effect of work support and consequently increase the retention of qualified nursing staff.展开更多
The case study describes longwall coal seam A in a hard coal mine,where longwall coal face stability loss and periodic roof fall occurrences had been registered.The authors have attempted to explain the situation base...The case study describes longwall coal seam A in a hard coal mine,where longwall coal face stability loss and periodic roof fall occurrences had been registered.The authors have attempted to explain the situation based on in-situ measurements and observations of the longwall working as well as numerical simulation.The calculations included several parameters,such as powered roof support geometry in the form of the canopy ratio,which is a factor that influences load distribution along the canopy.Numerical simulations were realized based on a rock mass model representing realistic mining and geological conditions at a depth of 600 m below surface for coal seam A.Numerical model assumptions are described,while the obtained results were compared with the in-situ measurements.The conclusions drawn from this work can complement engineering knowledge utilized at the stage of powered roof support construction and selection in order to improve both personnel safety and longwall working stability,and to achieve better extraction.展开更多
IPv6 is the foundation of the development of Next Generation Internet (NGI). An IPv6 network management and operations support system is necessary for real operable NGI. Presently there are no approved standards yet a...IPv6 is the foundation of the development of Next Generation Internet (NGI). An IPv6 network management and operations support system is necessary for real operable NGI. Presently there are no approved standards yet and relevant equipment interfaces are not perfect. A Network Management System (NMS) at the network layer helps implement the integrated management of a network with equipment from multiple vendors, including the network resources and topology, end-to-end network performance, network failures and customer Service Level Agreement (SLA) management. Though the NMS will finally realize pure IPv6 network management, it must be accommodated to the management of relevant IPv4 equipment. Therefore, modularized and layered structure is adopted for the NMS in order to implement its smooth transition.展开更多
Scientific workflows have gained the emerging attention in sophisti-cated large-scale scientific problem-solving environments.The pay-per-use model of cloud,its scalability and dynamic deployment enables it suited for ex...Scientific workflows have gained the emerging attention in sophisti-cated large-scale scientific problem-solving environments.The pay-per-use model of cloud,its scalability and dynamic deployment enables it suited for executing scientific workflow applications.Since the cloud is not a utopian environment,failures are inevitable that may result in experiencingfluctuations in the delivered performance.Though a single task failure occurs in workflow based applications,due to its task dependency nature,the reliability of the overall system will be affected drastically.Hence rather than reactive fault-tolerant approaches,proactive measures are vital in scientific workflows.This work puts forth an attempt to con-centrate on the exploration issue of structuring a nature inspired metaheuristics-Intelligent Water Drops Algorithm(IWDA)combined with an efficient machine learning approach-Support Vector Regression(SVR)for task failure prognostica-tion which facilitates proactive fault-tolerance in the scheduling of scientific workflow applications.The failure prediction models in this study have been implemented through SVR-based machine learning approaches and the precision accuracy of prediction is optimized by IWDA and several performance metrics were evaluated on various benchmark workflows.The experimental results prove that the proposed proactive fault-tolerant approach performs better compared with the other existing techniques.展开更多
文摘Objective:The paper aimed to explore the impact of work support and potential for career advancement on the nurse turnover intention in order to find an effective approach to curb high turnover.Methods:A cross-sectional survey of 526 nurses from eight teaching hospitals in Tianjin,China,was conducted to test the hypothesized multilevel model.The organizational career growth scale,work support scale,and the nurse turnover intention scale were used to measure the effect of organizational career growth and work support on nurse turnover intention.Finally,SPSS 17.0 and AMOS 17.0 software were used to analyse the relationship of these variables.Results:The score of the three scales nurse turnover,organizational career growth,and work support were 1.98±0.60,2.40±0.50,and 4.06±0.98,respectively.The total and direct effects of work support on turnover intention were0.361(p<0.01)and0.147(p<0.01),respectively.The indirect effect was0.169 with a 95%bootstrap confidence interval of0.257 to0.102.Conclusion:The study showed a lack of work support negatively and directly associated with nurse turnover intention.Additional opportunities for career growth within the organization may strengthen the effect of work support and consequently increase the retention of qualified nursing staff.
基金research conducted within the Research Project:Productivity and Safety of Shield Support(PRASS Ⅲ)-co-financed by European Commission-Research Fund for Coal and Steel(No.752504)and Polish Ministry of Science and Higher Education
文摘The case study describes longwall coal seam A in a hard coal mine,where longwall coal face stability loss and periodic roof fall occurrences had been registered.The authors have attempted to explain the situation based on in-situ measurements and observations of the longwall working as well as numerical simulation.The calculations included several parameters,such as powered roof support geometry in the form of the canopy ratio,which is a factor that influences load distribution along the canopy.Numerical simulations were realized based on a rock mass model representing realistic mining and geological conditions at a depth of 600 m below surface for coal seam A.Numerical model assumptions are described,while the obtained results were compared with the in-situ measurements.The conclusions drawn from this work can complement engineering knowledge utilized at the stage of powered roof support construction and selection in order to improve both personnel safety and longwall working stability,and to achieve better extraction.
文摘IPv6 is the foundation of the development of Next Generation Internet (NGI). An IPv6 network management and operations support system is necessary for real operable NGI. Presently there are no approved standards yet and relevant equipment interfaces are not perfect. A Network Management System (NMS) at the network layer helps implement the integrated management of a network with equipment from multiple vendors, including the network resources and topology, end-to-end network performance, network failures and customer Service Level Agreement (SLA) management. Though the NMS will finally realize pure IPv6 network management, it must be accommodated to the management of relevant IPv4 equipment. Therefore, modularized and layered structure is adopted for the NMS in order to implement its smooth transition.
文摘Scientific workflows have gained the emerging attention in sophisti-cated large-scale scientific problem-solving environments.The pay-per-use model of cloud,its scalability and dynamic deployment enables it suited for executing scientific workflow applications.Since the cloud is not a utopian environment,failures are inevitable that may result in experiencingfluctuations in the delivered performance.Though a single task failure occurs in workflow based applications,due to its task dependency nature,the reliability of the overall system will be affected drastically.Hence rather than reactive fault-tolerant approaches,proactive measures are vital in scientific workflows.This work puts forth an attempt to con-centrate on the exploration issue of structuring a nature inspired metaheuristics-Intelligent Water Drops Algorithm(IWDA)combined with an efficient machine learning approach-Support Vector Regression(SVR)for task failure prognostica-tion which facilitates proactive fault-tolerance in the scheduling of scientific workflow applications.The failure prediction models in this study have been implemented through SVR-based machine learning approaches and the precision accuracy of prediction is optimized by IWDA and several performance metrics were evaluated on various benchmark workflows.The experimental results prove that the proposed proactive fault-tolerant approach performs better compared with the other existing techniques.
