随着网络威胁的不断演化,传统的安全运营方式面临检测能力不足、响应效率低下等问题。为此,研究将结合当前网络安全运营需求,聚焦安全编排、自动化与响应(Security Orchestration, Automation and Response,SOAR)技术,以流程编排优化为...随着网络威胁的不断演化,传统的安全运营方式面临检测能力不足、响应效率低下等问题。为此,研究将结合当前网络安全运营需求,聚焦安全编排、自动化与响应(Security Orchestration, Automation and Response,SOAR)技术,以流程编排优化为核心,探索如何通过自动化、智能化的安全运营实现快速响应与闭环管理。研究提出了一套面向多场景、多角色的SOAR技术解决方案,并结合具体案例验证其有效性,为网络安全运营体系化建设提供了重要参考。展开更多
Closed-loop neuromodulation,especially using the phase of the electroencephalography(EEG)rhythm to assess the real-time brain state and optimize the brain stimulation process,is becoming a hot research topic.Because t...Closed-loop neuromodulation,especially using the phase of the electroencephalography(EEG)rhythm to assess the real-time brain state and optimize the brain stimulation process,is becoming a hot research topic.Because the EEG signal is non-stationary,the commonly used EEG phase-based prediction methods have large variances,which may reduce the accuracy of the phase prediction.In this study,we proposed a machine learning-based EEG phase prediction network,which we call EEG phase prediction network(EPN),to capture the overall rhythm distribution pattern of subjects and map the instantaneous phase directly from the narrow-band EEG data.We verified the performance of EPN on pre-recorded data,simulated EEG data,and a real-time experiment.Compared with widely used state-of-the-art models(optimized multi-layer filter architecture,auto-regress,and educated temporal prediction),EPN achieved the lowest variance and the greatest accuracy.Thus,the EPN model will provide broader applications for EEG phase-based closed-loop neuromodulation.展开更多
目的:基于美国医疗信息与管理协会(Healthcare Information and Management System Society)的理念,建立新型PIVAS药品闭环管理流程。方法:上海交通大学附属第六人民医院PIVAS实现了全流程药品条码化管理,通过条码扫描识别错误。结果:...目的:基于美国医疗信息与管理协会(Healthcare Information and Management System Society)的理念,建立新型PIVAS药品闭环管理流程。方法:上海交通大学附属第六人民医院PIVAS实现了全流程药品条码化管理,通过条码扫描识别错误。结果:本院正式通过HIMSS电子病历模型六级现场评审,PIVAS药品闭环管理提高了医务人员的工作效率、药品调配效率和准确性,踪近差错率由传统管理(2016年1月-6月)的0.17‰下降至信息化管理(2017年1月-6月)的0.08‰,降低了52.9%。结论:PIVAS药品闭环管理有利于保证病人的安全用药。展开更多
文摘随着网络威胁的不断演化,传统的安全运营方式面临检测能力不足、响应效率低下等问题。为此,研究将结合当前网络安全运营需求,聚焦安全编排、自动化与响应(Security Orchestration, Automation and Response,SOAR)技术,以流程编排优化为核心,探索如何通过自动化、智能化的安全运营实现快速响应与闭环管理。研究提出了一套面向多场景、多角色的SOAR技术解决方案,并结合具体案例验证其有效性,为网络安全运营体系化建设提供了重要参考。
基金supported by the Key Collaborative Research Program of the Alliance of International Science Organizations(ANSO-CR-KP-2022-10)Science and Technology Innovation 2030-Brain Science and Brain-Inspired Intelligence Project(2021ZD0200200)+2 种基金Natural Science Foundation of China(82151307,82202253,and 31620103905)Strategic Priority Research Program of the Chinese Academy of Sciences(XDB32030207)Science Frontier Program of the Chinese Academy of Sciences(QYZDJ-SSW-SMCO19).
文摘Closed-loop neuromodulation,especially using the phase of the electroencephalography(EEG)rhythm to assess the real-time brain state and optimize the brain stimulation process,is becoming a hot research topic.Because the EEG signal is non-stationary,the commonly used EEG phase-based prediction methods have large variances,which may reduce the accuracy of the phase prediction.In this study,we proposed a machine learning-based EEG phase prediction network,which we call EEG phase prediction network(EPN),to capture the overall rhythm distribution pattern of subjects and map the instantaneous phase directly from the narrow-band EEG data.We verified the performance of EPN on pre-recorded data,simulated EEG data,and a real-time experiment.Compared with widely used state-of-the-art models(optimized multi-layer filter architecture,auto-regress,and educated temporal prediction),EPN achieved the lowest variance and the greatest accuracy.Thus,the EPN model will provide broader applications for EEG phase-based closed-loop neuromodulation.
文摘目的:基于美国医疗信息与管理协会(Healthcare Information and Management System Society)的理念,建立新型PIVAS药品闭环管理流程。方法:上海交通大学附属第六人民医院PIVAS实现了全流程药品条码化管理,通过条码扫描识别错误。结果:本院正式通过HIMSS电子病历模型六级现场评审,PIVAS药品闭环管理提高了医务人员的工作效率、药品调配效率和准确性,踪近差错率由传统管理(2016年1月-6月)的0.17‰下降至信息化管理(2017年1月-6月)的0.08‰,降低了52.9%。结论:PIVAS药品闭环管理有利于保证病人的安全用药。
