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Titlebook: Health Care Systems Engineering; HCSE, Florence, Ital Paola Cappanera,Jingshan Li,Filippo Visintin Conference proceedings 2017 Springer Int

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發(fā)表于 2025-3-23 12:17:00 | 只看該作者
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發(fā)表于 2025-3-23 14:11:18 | 只看該作者
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發(fā)表于 2025-3-23 18:09:08 | 只看該作者
Springer Proceedings in Mathematics & Statisticshttp://image.papertrans.cn/h/image/424645.jpg
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發(fā)表于 2025-3-23 23:55:30 | 只看該作者
2194-1009 Italy from May 29 to 31, 2017.Discusses statistical processe.This book presents statistical processes for health care delivery and covers new ideas, methods and technologies used to improve health care organizations. It gathers the proceedings of the Third International Conference on Health Care Sys
15#
發(fā)表于 2025-3-24 04:43:32 | 只看該作者
How to Protect a Hospital Against Cyber Attacksequences are constructed. By studying these scenarios, we suggest mitigation countermeasures, based on a reorganization of the digital information system into isolated sub-systems. Our objective is to be more resilient to cyber attacks, by increasing the required complexity for hacker’s crimes and by limiting the damages of attacks.
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發(fā)表于 2025-3-24 10:07:52 | 只看該作者
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發(fā)表于 2025-3-24 13:37:32 | 只看該作者
Handling Time-Related Demands in the Home Care Nurse-to-Patient Assignment Problem with the Implemen-dependency of the demands in the HC nurse-to-patient assignment problem, based on the implementor-adversarial framework. Results from a relevant test case show the appropriateness of the approach and the capability to contain costs while respecting the continuity of care constraints.
18#
發(fā)表于 2025-3-24 18:52:02 | 只看該作者
A Decision-Making Tool for the Calculation of a Robust Planning for Home Service Employeesravel time of the employees, and replacing an absence. For the first one, we propose a local search heuristic, and for the second one, we develop a dedicated heuristic. A tool with these two proposals has been implemented and has been tested with real data.
19#
發(fā)表于 2025-3-24 22:15:31 | 只看該作者
20#
發(fā)表于 2025-3-25 02:21:39 | 只看該作者
A Simulation Model for Optimizing Staffing in the Emergency Departmentity groups. The simulation model also used for optimizing the staffing allocations in three different shifts. The methodological contributions are exemplified using real ED data from a major teaching hospital.
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