Since 2010,there has been a new round of drug crises in the United States.The abuse of opioids has led to a sharp increase in the number of people involved in drug crimes in the United States.There is an urgent need t...Since 2010,there has been a new round of drug crises in the United States.The abuse of opioids has led to a sharp increase in the number of people involved in drug crimes in the United States.There is an urgent need to explore solutions to the drug crisis in the United States.In this paper,the model of in-depth analysis is established under the condition of obtaining the opioid data and the influence factor data of the large sample of five state[1].In the first part,we use the Highway Safety Research Institute model based on the differential equation model to predict the initial value,find the initial position of the drug transfer,and obtain the curve of the number of different groups over time by fitting the data,so that the curves can be predicted the changing trends of the groups in the future.It was found that in Kentucky State,the county’s most likely to start using opioids were Pike and Bale.In Ohio,the county’s most likely to start using opioids are Jackson and Scioto.In Pennsylvania State,Mercer and Lackawanna are the counties most likely to start using opioids.Martinsville and Galax are the counties where Virginia State is most likely to start using opioids.Logan and Mingo are the counties where West Virginia State is most likely to start using opioids.In the second part,the gray prediction model is used to further analyze the time series of each factor,the maximum likelihood estimation method is used to obtain the weight of each factor,and the weight coefficient matrix is used to simulate the multivariate regression equation,and the factors that have the greatest influence on opioid abuse are educational background and family composition.In the third part,the hypothesis test model of two groups(the data type is proportional)is used to verify the difference between the influence factors(including the predicted values)in the first two parts of the states,thus verifying the feasibility between them.At the same time,we put forward a few suggestions to combine the current situation in the United States with the CDC data.We believe that in order to address the opium crisis,the U.S.government needs to strengthen not only oversight of doctors'prescriptions,but also make joint efforts of all sectors of society to fundamentally reduce the barriers to the use of opioids.展开更多
Since 2010,there has been a new round of drug crises in the United States.The abuse of opioids has led to a sharp increase in the number of people involved in drug crimes in the United States.There is an urgent need t...Since 2010,there has been a new round of drug crises in the United States.The abuse of opioids has led to a sharp increase in the number of people involved in drug crimes in the United States.There is an urgent need to explore solutions to the drug crisis in the United States.In this paper,the model of in-depth analysis is established under the condition of obtaining the opioid data and the influence factor data of the large sample of five state[1].In the first part,we use the Highway Safety Research Institute model based on the differential equation model to predict the initial value,find the initial position of the drug transfer,and obtain the curve of the number of different groups over time by fitting the data,so that the curves can be predicted the changing trends of the groups in the future.It was found that in Kentucky State,the county's most likely to start using opioids were Pike and Bale.In Ohio,the county's most likely to start using opioids are Jackson and Scioto.In Pennsylvania State,Mercer and Lackawanna are the counties most likely to start using opioids.Martinsville and Galax are the counties where Virginia State is most likely to start using opioids.Logan and Mingo are the counties where West Virginia State is most likely to start using opioids.In the second part,the gray prediction model is used to further analyze the time series of each factor,the maximum likelihood estimation method is used to obtain the weight of each factor,and the weight coefficient matrix is used to simulate the multivariate regression equation,and the factors that have the greatest influence on opioid abuse are educational background and family composition.In the third part,the hypothesis test model of two groups(the data type is proportional)is used to verify the difference between the influence factors(including the predicted values)in the first two parts of the states,thus verifying the feasibility between them.At the same time,we put forward a few suggestions to combine the current situation in the United States with the CDC data.We believe that in order to address the opium crisis,the U.S.government needs to strengthen not only oversight of doctors'prescriptions,but also make joint efforts of all sectors of society to fundamentally reduce the barriers to the use of opioids.展开更多
Spatial technologies, such as Geographic Information Systems (GIS), are particularly appropriate for integrating road- way data and enhancing the use and presentation of these data for highway management and operation...Spatial technologies, such as Geographic Information Systems (GIS), are particularly appropriate for integrating road- way data and enhancing the use and presentation of these data for highway management and operation by using spatial relationships to relate geographic and geometric objects and events. To different degrees, roadway management problems, such as pavement management, involve relations between objects and events located in different spatial positions. Because the data used in the decision-making process have spatial components, the use of spatial technologies emerges as a very appealing alternative. Spatial technologies may enhance the analysis of several transportation-related issues and may improve the quality of the decision-making process. This paper built a GIS based system that provides information for use as a platform on which all aspects of the Pavement Maintenance and Management System (PMMS) process can be built. The resulting system, GPMMS, represents a significant enhancement of all aspects of the PMMS process. A variety of spatially integrated data are important to pavement management decision making. GIS technology is shown to be the most logical way of relating these diverse, but relevant, data. In this paper, 23 sections is selected along the roadways of Nahrain University and all these sections are distresses due to different causes like weathering, ageing, traffic load, and also the bad maintenance, etc. The PSI of these sections in the range between 1 to 4, and most of these sections in the low range (between 1 to 2). That cause of need to future developments including other elements of a road maintenance management system should be considered. Completion of the whole roads database with all the types of surveys recorded i.e. all distresses, construction and maintenance history and so on.展开更多
Highway agencies have been using many of the elements of asset management with the support of various decision-making tools.To determine the most effective investment strategy with scarce resources,the integration,and...Highway agencies have been using many of the elements of asset management with the support of various decision-making tools.To determine the most effective investment strategy with scarce resources,the integration,and hence better utilization,of existing tools and practices across asset classes is generally lacking.This paper applies data envelopment analysis(DEA)to benchmark different highway investment scenarios using existing data or data readily available through existing models.Three asset types,pavements,bridges,and traffic signage,are investigated.Asset investment analysis results from the Highway Economic Requirements System State Version(HERS-ST)application,the PONTIS bridge management system software,and purpose-built traffic signage spreadsheet are obtained to capture the changes of performance measures under various budget scenarios and are further used as the inputs for the DEA process to benchmark investment scenarios for each individual asset.Subsequently,the performance measures and budget levels are assembled in the Asset Manager-NT software,whose results are input into DEA to benchmark cross-assets resource allocation scenarios.Planning for the management of highway network is addressed via case studies in a systematic manner that recognizes the tradeoffs among different funding periods and objectives such as preserving existing investments,safety,roughness and user costs.This study has established a preliminary implementable framework of highway asset management by linking DEA approach and current widely used decision-making tools for more efficient investments within and cross assets,and better understand of the tradeoffs,costs and consequences of various asset management decisions.展开更多
文摘Since 2010,there has been a new round of drug crises in the United States.The abuse of opioids has led to a sharp increase in the number of people involved in drug crimes in the United States.There is an urgent need to explore solutions to the drug crisis in the United States.In this paper,the model of in-depth analysis is established under the condition of obtaining the opioid data and the influence factor data of the large sample of five state[1].In the first part,we use the Highway Safety Research Institute model based on the differential equation model to predict the initial value,find the initial position of the drug transfer,and obtain the curve of the number of different groups over time by fitting the data,so that the curves can be predicted the changing trends of the groups in the future.It was found that in Kentucky State,the county’s most likely to start using opioids were Pike and Bale.In Ohio,the county’s most likely to start using opioids are Jackson and Scioto.In Pennsylvania State,Mercer and Lackawanna are the counties most likely to start using opioids.Martinsville and Galax are the counties where Virginia State is most likely to start using opioids.Logan and Mingo are the counties where West Virginia State is most likely to start using opioids.In the second part,the gray prediction model is used to further analyze the time series of each factor,the maximum likelihood estimation method is used to obtain the weight of each factor,and the weight coefficient matrix is used to simulate the multivariate regression equation,and the factors that have the greatest influence on opioid abuse are educational background and family composition.In the third part,the hypothesis test model of two groups(the data type is proportional)is used to verify the difference between the influence factors(including the predicted values)in the first two parts of the states,thus verifying the feasibility between them.At the same time,we put forward a few suggestions to combine the current situation in the United States with the CDC data.We believe that in order to address the opium crisis,the U.S.government needs to strengthen not only oversight of doctors'prescriptions,but also make joint efforts of all sectors of society to fundamentally reduce the barriers to the use of opioids.
文摘Since 2010,there has been a new round of drug crises in the United States.The abuse of opioids has led to a sharp increase in the number of people involved in drug crimes in the United States.There is an urgent need to explore solutions to the drug crisis in the United States.In this paper,the model of in-depth analysis is established under the condition of obtaining the opioid data and the influence factor data of the large sample of five state[1].In the first part,we use the Highway Safety Research Institute model based on the differential equation model to predict the initial value,find the initial position of the drug transfer,and obtain the curve of the number of different groups over time by fitting the data,so that the curves can be predicted the changing trends of the groups in the future.It was found that in Kentucky State,the county's most likely to start using opioids were Pike and Bale.In Ohio,the county's most likely to start using opioids are Jackson and Scioto.In Pennsylvania State,Mercer and Lackawanna are the counties most likely to start using opioids.Martinsville and Galax are the counties where Virginia State is most likely to start using opioids.Logan and Mingo are the counties where West Virginia State is most likely to start using opioids.In the second part,the gray prediction model is used to further analyze the time series of each factor,the maximum likelihood estimation method is used to obtain the weight of each factor,and the weight coefficient matrix is used to simulate the multivariate regression equation,and the factors that have the greatest influence on opioid abuse are educational background and family composition.In the third part,the hypothesis test model of two groups(the data type is proportional)is used to verify the difference between the influence factors(including the predicted values)in the first two parts of the states,thus verifying the feasibility between them.At the same time,we put forward a few suggestions to combine the current situation in the United States with the CDC data.We believe that in order to address the opium crisis,the U.S.government needs to strengthen not only oversight of doctors'prescriptions,but also make joint efforts of all sectors of society to fundamentally reduce the barriers to the use of opioids.
文摘Spatial technologies, such as Geographic Information Systems (GIS), are particularly appropriate for integrating road- way data and enhancing the use and presentation of these data for highway management and operation by using spatial relationships to relate geographic and geometric objects and events. To different degrees, roadway management problems, such as pavement management, involve relations between objects and events located in different spatial positions. Because the data used in the decision-making process have spatial components, the use of spatial technologies emerges as a very appealing alternative. Spatial technologies may enhance the analysis of several transportation-related issues and may improve the quality of the decision-making process. This paper built a GIS based system that provides information for use as a platform on which all aspects of the Pavement Maintenance and Management System (PMMS) process can be built. The resulting system, GPMMS, represents a significant enhancement of all aspects of the PMMS process. A variety of spatially integrated data are important to pavement management decision making. GIS technology is shown to be the most logical way of relating these diverse, but relevant, data. In this paper, 23 sections is selected along the roadways of Nahrain University and all these sections are distresses due to different causes like weathering, ageing, traffic load, and also the bad maintenance, etc. The PSI of these sections in the range between 1 to 4, and most of these sections in the low range (between 1 to 2). That cause of need to future developments including other elements of a road maintenance management system should be considered. Completion of the whole roads database with all the types of surveys recorded i.e. all distresses, construction and maintenance history and so on.
基金supported by the University of DelawareUniversity Transportation Center+1 种基金Delaware Center for TransportationDelaware Department of Transportation。
文摘Highway agencies have been using many of the elements of asset management with the support of various decision-making tools.To determine the most effective investment strategy with scarce resources,the integration,and hence better utilization,of existing tools and practices across asset classes is generally lacking.This paper applies data envelopment analysis(DEA)to benchmark different highway investment scenarios using existing data or data readily available through existing models.Three asset types,pavements,bridges,and traffic signage,are investigated.Asset investment analysis results from the Highway Economic Requirements System State Version(HERS-ST)application,the PONTIS bridge management system software,and purpose-built traffic signage spreadsheet are obtained to capture the changes of performance measures under various budget scenarios and are further used as the inputs for the DEA process to benchmark investment scenarios for each individual asset.Subsequently,the performance measures and budget levels are assembled in the Asset Manager-NT software,whose results are input into DEA to benchmark cross-assets resource allocation scenarios.Planning for the management of highway network is addressed via case studies in a systematic manner that recognizes the tradeoffs among different funding periods and objectives such as preserving existing investments,safety,roughness and user costs.This study has established a preliminary implementable framework of highway asset management by linking DEA approach and current widely used decision-making tools for more efficient investments within and cross assets,and better understand of the tradeoffs,costs and consequences of various asset management decisions.
