Objective: To determine whether permutation scan statistics was more efficient in finding prospective spatial-temporal outbreaks for cutaneous leishmaniasis(CL) or for malaria in Fars province, Iran in 2016. Methods: ...Objective: To determine whether permutation scan statistics was more efficient in finding prospective spatial-temporal outbreaks for cutaneous leishmaniasis(CL) or for malaria in Fars province, Iran in 2016. Methods: Using time-series data including 29 177 CL cases recorded during 2010-2015 and 357 malaria cases recorded during 2010-2015, CL and malaria cases were predicted in 2016. Predicted cases were used to verify if they followed uniform distribution over time and space using space-time analysis. To testify the uniformity of distributions, permutation scan statistics was applied prospectively to detect statistically significant and non-significant outbreaks. Finally, the findings were compared to determine whether permutation scan statistics worked better for CL or for malaria in the area. Prospective permutation scan modeling was performed using SatScan software. Results: A total of 5 359 CL and 23 malaria cases were predicted in 2016 using time-series models. Applied timeseries models were well-fitted regarding auto correlation function, partial auto correlation function sample/model, and residual analysis criteria(Pv was set to 0.1). The results indicated two significant prospective spatial-temporal outbreaks for CL(P<0.5) including Most Likely Clusters, and one non-significant outbreak for malaria(P>0.5) in the area. Conclusions: Both CL and malaria follow a space-time trend in the area, but prospective permutation scan modeling works better for detecting CL spatial-temporal outbreaks. It is not far away from expectation since clusters are defined as accumulation of cases in specified times and places. Although this method seems to work better with finding the outbreaks of a high-frequency disease; i.e., CL, it is able to find non-significant outbreaks. This is clinically important for both high-and low-frequency infections; i.e., CL and malaria.展开更多
Oil spills cause environmental pollution with a serious threat to local communities and sustainable development.Accidental oil spills can be modelled as a stochastic process where each oil spill event is described by ...Oil spills cause environmental pollution with a serious threat to local communities and sustainable development.Accidental oil spills can be modelled as a stochastic process where each oil spill event is described by its spatial locations and incidence-time and hence allow for space-time cluster analysis.Spacetime cluster analysis can detect space-time pattern distribution of oil spills which can be useful for implementing preventive measures and evidence-based decision making.This study aims to detect the space-time clusters of accidental oil spills in Rivers state,Nigeria through the Space-time Scan Statistic.The Space-time Scan Statistic was applied under the permutation model to the oil spill data(each for sabotage and operational oil spills)collected at Local Government Area(LGA)-level during the period from 2011 to 2019.The results show that the sabotage oil spill clusters have covered most of the LGAs in the southern part of the state at the start of the study period and then in 2018–2019,it moved to the west covering a single LGA.The operational oil spill clusters covered two neighboring LGAs in the south.In addition,the temporal cluster of sabotage oil spills was seen in 2019 and operational oil spills in 2011–2012.The sabotage oil spills show an increasing trend with the maximum in 2019 while the operational oil spills show a decreasing trend with the minimum in 2019.These findings assist in more effective decision-making for combating the environmental problems and controlling the future spill incidence in the cluster-regions.展开更多
Aiming at the time redundancy in the fiat panel display （FPD） imaging process, the paper studied some problems for FPD gray scale controlling based on the fraetal theory, dissertates the construction of the space-ti...Aiming at the time redundancy in the fiat panel display （FPD） imaging process, the paper studied some problems for FPD gray scale controlling based on the fraetal theory, dissertates the construction of the space-time mapping topology architecture, the proposition of optimal scanning structure for FPD＇s gray imaging, and the creation of the fractal theoretic model. Then the logic implementation and system application are presented based on the fraetal model of the optimal scan architecture, and the application results achieved target of eliminating time redundancy and increasing the scanning availability. The novel control mode that the fractal scanning IP core described with Verilog language embedded in the FPGA hardware frame can efficiently increase the imaging gray scales and quality in the FPDs scanning controller and speed up the frame frequency of display system.展开更多
Community recovery from a major natural hazard-related disaster can be a long process, and rebuilding likely does not occur uniformly across space and time. Spatial and temporal clustering may be evident in certain da...Community recovery from a major natural hazard-related disaster can be a long process, and rebuilding likely does not occur uniformly across space and time. Spatial and temporal clustering may be evident in certain data types that can be used to frame the progress of recovery following a disaster. Publically available building permit data from the city of Joplin, Missouri, were gathered for four permit types, including residential, commercial, roof repair, and demolition. The data were used to(1) compare the observed versus expected frequency(chi-square) of permit issuance before and after the EF5 2011 tornado;(2), determine if significant space-time clusters of permits existed using the SaTScan^(TM) cluster analysis program(version 9.7);and(3) fit any emergent cluster data to the widely-cited Kates 10-year recovery model. All permit types showed significant increases in issuance for at least 5 years following the event,and one(residential) showed significance for nine of the 10years. The cluster analysis revealed a total of 16 significant clusters across the 2011 damage area. The results of fitting the significant cluster data to the Kates model revealed that those data closely followed the model, with some variation in the residential permit data path.展开更多
文摘Objective: To determine whether permutation scan statistics was more efficient in finding prospective spatial-temporal outbreaks for cutaneous leishmaniasis(CL) or for malaria in Fars province, Iran in 2016. Methods: Using time-series data including 29 177 CL cases recorded during 2010-2015 and 357 malaria cases recorded during 2010-2015, CL and malaria cases were predicted in 2016. Predicted cases were used to verify if they followed uniform distribution over time and space using space-time analysis. To testify the uniformity of distributions, permutation scan statistics was applied prospectively to detect statistically significant and non-significant outbreaks. Finally, the findings were compared to determine whether permutation scan statistics worked better for CL or for malaria in the area. Prospective permutation scan modeling was performed using SatScan software. Results: A total of 5 359 CL and 23 malaria cases were predicted in 2016 using time-series models. Applied timeseries models were well-fitted regarding auto correlation function, partial auto correlation function sample/model, and residual analysis criteria(Pv was set to 0.1). The results indicated two significant prospective spatial-temporal outbreaks for CL(P<0.5) including Most Likely Clusters, and one non-significant outbreak for malaria(P>0.5) in the area. Conclusions: Both CL and malaria follow a space-time trend in the area, but prospective permutation scan modeling works better for detecting CL spatial-temporal outbreaks. It is not far away from expectation since clusters are defined as accumulation of cases in specified times and places. Although this method seems to work better with finding the outbreaks of a high-frequency disease; i.e., CL, it is able to find non-significant outbreaks. This is clinically important for both high-and low-frequency infections; i.e., CL and malaria.
基金a Yayasan Universiti Teknologi PETRONAS-Fundamental Research Grant(YUTP-FRG)with a cost center of 015LC0-013.
文摘Oil spills cause environmental pollution with a serious threat to local communities and sustainable development.Accidental oil spills can be modelled as a stochastic process where each oil spill event is described by its spatial locations and incidence-time and hence allow for space-time cluster analysis.Spacetime cluster analysis can detect space-time pattern distribution of oil spills which can be useful for implementing preventive measures and evidence-based decision making.This study aims to detect the space-time clusters of accidental oil spills in Rivers state,Nigeria through the Space-time Scan Statistic.The Space-time Scan Statistic was applied under the permutation model to the oil spill data(each for sabotage and operational oil spills)collected at Local Government Area(LGA)-level during the period from 2011 to 2019.The results show that the sabotage oil spill clusters have covered most of the LGAs in the southern part of the state at the start of the study period and then in 2018–2019,it moved to the west covering a single LGA.The operational oil spill clusters covered two neighboring LGAs in the south.In addition,the temporal cluster of sabotage oil spills was seen in 2019 and operational oil spills in 2011–2012.The sabotage oil spills show an increasing trend with the maximum in 2019 while the operational oil spills show a decreasing trend with the minimum in 2019.These findings assist in more effective decision-making for combating the environmental problems and controlling the future spill incidence in the cluster-regions.
基金supported by the Key Laboratory of Advanced Display and System Applications(Shanghai University),Ministry of Education,China(Grant No.P200803)the Science and Technology Commission of Shanghai Municipality(Grant No.09ZR1412000)
文摘Aiming at the time redundancy in the fiat panel display （FPD） imaging process, the paper studied some problems for FPD gray scale controlling based on the fraetal theory, dissertates the construction of the space-time mapping topology architecture, the proposition of optimal scanning structure for FPD＇s gray imaging, and the creation of the fractal theoretic model. Then the logic implementation and system application are presented based on the fraetal model of the optimal scan architecture, and the application results achieved target of eliminating time redundancy and increasing the scanning availability. The novel control mode that the fractal scanning IP core described with Verilog language embedded in the FPGA hardware frame can efficiently increase the imaging gray scales and quality in the FPDs scanning controller and speed up the frame frequency of display system.
文摘Community recovery from a major natural hazard-related disaster can be a long process, and rebuilding likely does not occur uniformly across space and time. Spatial and temporal clustering may be evident in certain data types that can be used to frame the progress of recovery following a disaster. Publically available building permit data from the city of Joplin, Missouri, were gathered for four permit types, including residential, commercial, roof repair, and demolition. The data were used to(1) compare the observed versus expected frequency(chi-square) of permit issuance before and after the EF5 2011 tornado;(2), determine if significant space-time clusters of permits existed using the SaTScan^(TM) cluster analysis program(version 9.7);and(3) fit any emergent cluster data to the widely-cited Kates 10-year recovery model. All permit types showed significant increases in issuance for at least 5 years following the event,and one(residential) showed significance for nine of the 10years. The cluster analysis revealed a total of 16 significant clusters across the 2011 damage area. The results of fitting the significant cluster data to the Kates model revealed that those data closely followed the model, with some variation in the residential permit data path.
