High-density street-level reliable landmarks are one of the important foundations for street-level geolocation.However,the existing methods cannot obtain enough street-level landmarks in a short period of time.In this...High-density street-level reliable landmarks are one of the important foundations for street-level geolocation.However,the existing methods cannot obtain enough street-level landmarks in a short period of time.In this paper,a street-level landmarks acquisition method based on SVM(Support Vector Machine)classifiers is proposed.Firstly,the port detection results of IPs with known services are vectorized,and the vectorization results are used as an input of the SVM training.Then,the kernel function and penalty factor are adjusted for SVM classifiers training,and the optimal SVM classifiers are obtained.After that,the classifier sequence is constructed,and the IPs with unknown service are classified using the sequence.Finally,according to the domain name corresponding to the IP,the relationship between the classified server IP and organization name is established.The experimental results in Guangzhou and Wuhan city in China show that the proposed method can be as a supplement to existing typical methods since the number of obtained street-level landmarks is increased substantially,and the median geolocation error using evaluated landmarks is reduced by about 2 km.展开更多
Street-level health bureaucrats have actively contributed to implementing the COVID-19 prevention,control,and treatment policies of the Myanmar government.However,the need for bureaucrats on the frontlines of policy i...Street-level health bureaucrats have actively contributed to implementing the COVID-19 prevention,control,and treatment policies of the Myanmar government.However,the need for bureaucrats on the frontlines of policy implementation to maintain a safe distance from others to prevent the spread of COVID-19 has posed challenges for the sharing and exchange of information related to health risks.In this context,this study examined what health risk communication patterns have emerged and developed among streetlevel health bureaucrats during the COVID-19 pandemic,and how this risk communication has been affected by streetlevel health bureaucrats'perceptions of client meaningfulness and willingness to implement COVID-19 policies.The results reveal that street-level health bureaucrats in the health risk communication network are embedded in reciprocally or transitively connected discussion relationships that sustain their health risk communication over time.Moreover,when specific healthcare staffmembers perceive more benefits of COVID-19 policies for their patients and are more willing to care for patients,other healthcare staffavoid them to protect themselves from COVID-19 infection.Due to their higher level of understanding of the adopted measures,healthcare staffmembers who are highly willing to implement COVID-19 policies are frequently approached by other staffmembers to communicate about COVID-19 issues.This study empirically contributes to the literature on street-level bureaucrats in times of pandemic crisis by examining the formation of health risk communications in the context of street-level health bureaucrats'responses to and participation in public healthcare policy implementation processes.展开更多
自利普斯基提出街头官僚概念以来,它便成为公共行政学研究的重要议题之一,相关研究繁多,但缺乏系统性梳理。本文运用系统性综述法并基于PRISMA声明的文献筛选标准,从来自中国知网与Web of science的1 462篇相关文献中选取了45篇作为街...自利普斯基提出街头官僚概念以来,它便成为公共行政学研究的重要议题之一,相关研究繁多,但缺乏系统性梳理。本文运用系统性综述法并基于PRISMA声明的文献筛选标准,从来自中国知网与Web of science的1 462篇相关文献中选取了45篇作为街头官僚研究的核心文献,并分析其议题演进、研究方法变迁并展望未来趋势。研究发现,自由裁量、行动逻辑、责任控制、信息技术与街头官僚是国内外街头官僚研究中的四大核心议题。对街头官僚研究运用的研究方法经历了规范研究与案例研究为主、定量研究成为主流、迈向方法论的多元主义三个阶段。在国内外相关研究的对比中可以发现议题同构、差距明显、精细化导向与方法趋同四大特征。研究议题的演进与方法变迁共同构成了街头官僚研究知识生产的脉络与图谱,也进一步指明了未来研究的可能方向。展开更多
基金The work presented in this paper is supported by the National Key R&D Program of China[Nos.2016YFB0801303,2016QY01W0105]the National Natural Science Foundation of China[Nos.U1636219,U1804263,61602508,61772549,U1736214,61572052]Plan for Scientific Innovation Talent of Henan Province[No.2018JR0018].
文摘High-density street-level reliable landmarks are one of the important foundations for street-level geolocation.However,the existing methods cannot obtain enough street-level landmarks in a short period of time.In this paper,a street-level landmarks acquisition method based on SVM(Support Vector Machine)classifiers is proposed.Firstly,the port detection results of IPs with known services are vectorized,and the vectorization results are used as an input of the SVM training.Then,the kernel function and penalty factor are adjusted for SVM classifiers training,and the optimal SVM classifiers are obtained.After that,the classifier sequence is constructed,and the IPs with unknown service are classified using the sequence.Finally,according to the domain name corresponding to the IP,the relationship between the classified server IP and organization name is established.The experimental results in Guangzhou and Wuhan city in China show that the proposed method can be as a supplement to existing typical methods since the number of obtained street-level landmarks is increased substantially,and the median geolocation error using evaluated landmarks is reduced by about 2 km.
文摘Street-level health bureaucrats have actively contributed to implementing the COVID-19 prevention,control,and treatment policies of the Myanmar government.However,the need for bureaucrats on the frontlines of policy implementation to maintain a safe distance from others to prevent the spread of COVID-19 has posed challenges for the sharing and exchange of information related to health risks.In this context,this study examined what health risk communication patterns have emerged and developed among streetlevel health bureaucrats during the COVID-19 pandemic,and how this risk communication has been affected by streetlevel health bureaucrats'perceptions of client meaningfulness and willingness to implement COVID-19 policies.The results reveal that street-level health bureaucrats in the health risk communication network are embedded in reciprocally or transitively connected discussion relationships that sustain their health risk communication over time.Moreover,when specific healthcare staffmembers perceive more benefits of COVID-19 policies for their patients and are more willing to care for patients,other healthcare staffavoid them to protect themselves from COVID-19 infection.Due to their higher level of understanding of the adopted measures,healthcare staffmembers who are highly willing to implement COVID-19 policies are frequently approached by other staffmembers to communicate about COVID-19 issues.This study empirically contributes to the literature on street-level bureaucrats in times of pandemic crisis by examining the formation of health risk communications in the context of street-level health bureaucrats'responses to and participation in public healthcare policy implementation processes.
文摘自利普斯基提出街头官僚概念以来,它便成为公共行政学研究的重要议题之一,相关研究繁多,但缺乏系统性梳理。本文运用系统性综述法并基于PRISMA声明的文献筛选标准,从来自中国知网与Web of science的1 462篇相关文献中选取了45篇作为街头官僚研究的核心文献,并分析其议题演进、研究方法变迁并展望未来趋势。研究发现,自由裁量、行动逻辑、责任控制、信息技术与街头官僚是国内外街头官僚研究中的四大核心议题。对街头官僚研究运用的研究方法经历了规范研究与案例研究为主、定量研究成为主流、迈向方法论的多元主义三个阶段。在国内外相关研究的对比中可以发现议题同构、差距明显、精细化导向与方法趋同四大特征。研究议题的演进与方法变迁共同构成了街头官僚研究知识生产的脉络与图谱,也进一步指明了未来研究的可能方向。
