This paper describes an empirical study aiming at identifying the main differences between different logistic regression models and collision data aggregation methods that are commonly applied in road safety literatur...This paper describes an empirical study aiming at identifying the main differences between different logistic regression models and collision data aggregation methods that are commonly applied in road safety literature for modeling collision severity. In particular, the research compares three popular multilevel logistic models (i.e., sequential binary logit models, ordered logit models, and multinomial logit models) as well as three data aggregation methods (i.e., occupant based, vehicle based, and collision based). Six years of collision data (2001-2006) from 31 highway routes from across the province of Ontario, Canada were used for this analysis. It was found that a multilevel multinomial logit model has the best fit to the data than the other two models while the results obtained from occupant-based data are more reliable than those from vehicle- and collision-based data. More importantly, while generally consistent in terms of factors that were found to be significant between different models and data aggregation methods, the effect size of each factor differ sub- stantially, which could have significant implications forevaluating the effects of different safety-related policies and countermeasures.展开更多
Integrating and sharing data from different data sources is one of the trends to make better use of data. However, data integration hampers data confidentiality where each data source has its own access control policy...Integrating and sharing data from different data sources is one of the trends to make better use of data. However, data integration hampers data confidentiality where each data source has its own access control policy. This paper includes a discussion on the issue about access control across multiple data sources when they arc combined together in the scenario of searching over these data. A method based on multilevel security for data integration is proposed. The proposed method allows the merging of policies and also tackles the issue of policy conflicts between different data sources.展开更多
This paper proposes a security policy model for mandatory access control in class B1 database management system whose level of labeling is tuple. The relation hierarchical data model is extended to multilevel relatio...This paper proposes a security policy model for mandatory access control in class B1 database management system whose level of labeling is tuple. The relation hierarchical data model is extended to multilevel relation hierarchical data model. Based on the multilevel relation hierarchical data model, the concept of upper lower layer relational integrity is presented after we analyze and eliminate the covert channels caused by the database integrity. Two SQL statements are extended to process polyinstantiation in the multilevel secure environment. The system is based on the multilevel relation hierarchical data model and is capable of integratively storing and manipulating multilevel complicated objects ( e.g., multilevel spatial data) and multilevel conventional data ( e.g., integer, real number and character string).展开更多
Based on the single sensor Kalman filtering equations, this paper presents two-level and three-level optimal centralized and distributed estimation algorithms for hierarchical multisensor systems. The solution shows t...Based on the single sensor Kalman filtering equations, this paper presents two-level and three-level optimal centralized and distributed estimation algorithms for hierarchical multisensor systems. The solution shows that when the correlated matrix, the mean of noise, the control input, and the measurement error are all zero, the result in this paper turns out to be the standard algorithm discussed. Simulation shows that the mean of noise, the control input, and the measurement error will not change the estimation covariance and the estimation covariance fluctuates greatly when the cross-correlated matrix is similar to the covariance of process noise.展开更多
This study applied multilevel modeling to investigate the impact of observed predictors and different levels or groups that households belong, on parents’ choice of discipline methods using data from 8156 households ...This study applied multilevel modeling to investigate the impact of observed predictors and different levels or groups that households belong, on parents’ choice of discipline methods using data from 8156 households derived from a nationwide survey by the Ghana Statistical Service (GSS) in 2011. The aim of the study is to provide in-depth information on why parents choose particular discipline methods as corrective measures to reduce unwanted child behaviour in the present and to increase desirable ones in the future. The results of the study show that, religion and age-group of household heads have significant effect on household’s likelihood to choose physical discipline methods whereas the wealth index of a household and ethnicity of the household head, have significant effect on households’ likelihood to choose non-physical and psychological aggression methods. The results further show significant contextual effect on the differences in choices of parents at the household and regional levels. The choice of physical discipline methods by parents was consistent across households and regional levels unlike non-physical and psychological aggression methods whose application varied across the regions. Households in the Northern, Eastern and Volta regions mostly chose to apply physical discipline methods whereas in the Upper West, Western and Northern regions the most chosen discipline methods were non-physical discipline methods. Psychological aggression discipline methods were predominantly applied in the Upper East, Central and Northern regions of the country.展开更多
基金supported by MTO in part through the Highway Infrastructure and Innovations Funding Program(HIIFP)
文摘This paper describes an empirical study aiming at identifying the main differences between different logistic regression models and collision data aggregation methods that are commonly applied in road safety literature for modeling collision severity. In particular, the research compares three popular multilevel logistic models (i.e., sequential binary logit models, ordered logit models, and multinomial logit models) as well as three data aggregation methods (i.e., occupant based, vehicle based, and collision based). Six years of collision data (2001-2006) from 31 highway routes from across the province of Ontario, Canada were used for this analysis. It was found that a multilevel multinomial logit model has the best fit to the data than the other two models while the results obtained from occupant-based data are more reliable than those from vehicle- and collision-based data. More importantly, while generally consistent in terms of factors that were found to be significant between different models and data aggregation methods, the effect size of each factor differ sub- stantially, which could have significant implications forevaluating the effects of different safety-related policies and countermeasures.
基金Supported by the China MOE-China Mobile Research Fund(MCM20121051,MCM20130651)China MOE Doctoral Research Fund(20134407120017)+2 种基金Natural Science Foundation of Guangdong Province(S2012030006242)Guangdong Industry Development Fund(S2014-007)Guangzhou Industry Cooperation Fund(2014Y2-00004,2014Y2-00006)
文摘Integrating and sharing data from different data sources is one of the trends to make better use of data. However, data integration hampers data confidentiality where each data source has its own access control policy. This paper includes a discussion on the issue about access control across multiple data sources when they arc combined together in the scenario of searching over these data. A method based on multilevel security for data integration is proposed. The proposed method allows the merging of policies and also tackles the issue of policy conflicts between different data sources.
文摘This paper proposes a security policy model for mandatory access control in class B1 database management system whose level of labeling is tuple. The relation hierarchical data model is extended to multilevel relation hierarchical data model. Based on the multilevel relation hierarchical data model, the concept of upper lower layer relational integrity is presented after we analyze and eliminate the covert channels caused by the database integrity. Two SQL statements are extended to process polyinstantiation in the multilevel secure environment. The system is based on the multilevel relation hierarchical data model and is capable of integratively storing and manipulating multilevel complicated objects ( e.g., multilevel spatial data) and multilevel conventional data ( e.g., integer, real number and character string).
文摘Based on the single sensor Kalman filtering equations, this paper presents two-level and three-level optimal centralized and distributed estimation algorithms for hierarchical multisensor systems. The solution shows that when the correlated matrix, the mean of noise, the control input, and the measurement error are all zero, the result in this paper turns out to be the standard algorithm discussed. Simulation shows that the mean of noise, the control input, and the measurement error will not change the estimation covariance and the estimation covariance fluctuates greatly when the cross-correlated matrix is similar to the covariance of process noise.
文摘This study applied multilevel modeling to investigate the impact of observed predictors and different levels or groups that households belong, on parents’ choice of discipline methods using data from 8156 households derived from a nationwide survey by the Ghana Statistical Service (GSS) in 2011. The aim of the study is to provide in-depth information on why parents choose particular discipline methods as corrective measures to reduce unwanted child behaviour in the present and to increase desirable ones in the future. The results of the study show that, religion and age-group of household heads have significant effect on household’s likelihood to choose physical discipline methods whereas the wealth index of a household and ethnicity of the household head, have significant effect on households’ likelihood to choose non-physical and psychological aggression methods. The results further show significant contextual effect on the differences in choices of parents at the household and regional levels. The choice of physical discipline methods by parents was consistent across households and regional levels unlike non-physical and psychological aggression methods whose application varied across the regions. Households in the Northern, Eastern and Volta regions mostly chose to apply physical discipline methods whereas in the Upper West, Western and Northern regions the most chosen discipline methods were non-physical discipline methods. Psychological aggression discipline methods were predominantly applied in the Upper East, Central and Northern regions of the country.