Accountable care organizations (ACOs) and hospitals are facing additional requirements and financial rewards for improving population health. Therefore, ACOs and hospitals will need tools to understand the relationshi...Accountable care organizations (ACOs) and hospitals are facing additional requirements and financial rewards for improving population health. Therefore, ACOs and hospitals will need tools to understand the relationship between their patients and social determinants and health. We demonstrate the use of hot spotting for identifying geographical sources of high hospital costs and examining links between social determinants of health and these high-cost areas, known as hot spots. In 2012, using hospital data, we generated maps of inpatient costs from 2011 throughout New Haven and within an example neighborhood, Dixwell. We defined hot spots as addresses where costs were in the top 25%. We also overlaid data on concerns and assets in the community. Finally, we calculated the number of concerns and assets that fall within the 250 and 500 ft radii of the defined hot spots. We found that 34 addresses in Dixwell accounted for 70% of total costs for Dixwell. Hot spotting is a straightforward, approachable, and easily understood method for ACOs and hospitals to begin to address population health.展开更多
An increasing number of drivers are relying on digital map navigation systems in vehicles or mobile phones to select optimal driving routes in order to save time and improve safety. In the near future, digital map nav...An increasing number of drivers are relying on digital map navigation systems in vehicles or mobile phones to select optimal driving routes in order to save time and improve safety. In the near future, digital map navigation systems are expected to play more important roles in transportation systems. In order to extend current navigation systems to more applications, two fundamental problems must be resolved: the lane-level map model and lane-level route planning. This study proposes solutions to both problems. The current limitation of the lane-level map model is not its accuracy but its flexibility;this study proposes a novel seven-layer map structure, called as Tsinghua map model, which is able to support autonomous driving in a flexible and efficient way. For lane-level route planning, we propose a hierarchical route-searching algorithm to accelerate the planning process, even in the presence of complicated lane networks. In addition, we model the travel costs allocated for lane-level road networks by analyzing vehicle maneuvers in traversing lanes, changing lanes, and turning at intersections. Tests were performed on both a grid network and a real lane-level road network to demonstrate the validity and efficiency of the proposed algorithm.展开更多
Cloud computing has created a paradigm shift that affects the way in which business applications are developed. Many business organizations use cloud infrastructures as platforms on which to deploy business applicatio...Cloud computing has created a paradigm shift that affects the way in which business applications are developed. Many business organizations use cloud infrastructures as platforms on which to deploy business applications. Increasing numbers of vendors are supplying the cloud marketplace with a wide range of cloud products. Different vendors offer cloud products in different formats. The cost structures for consuming cloud products can be complex. Finding a suitable set of cloud products that meets an application’s requirements and budget can be a challenging task. In this paper, an ontology-based resource mapping mechanism is proposed. Domain-specific ontologies are used to specify high-level application’s requirements. These are then translated into high-level infrastructure ontologies which then can be mapped onto low-level descriptions of cloud resources. Cost ontologies are proposed for cloud resources. An exemplar media transcoding and delivery service is studied in order to illustrate how high-level requirements can be modeled and mapped onto cloud resources within a budget constraint. The proposed ontologies provide an application-centric mechanism for specifying cloud requirements which can then be used for searching for suitable resources in a multi-provider cloud environment.展开更多
文摘Accountable care organizations (ACOs) and hospitals are facing additional requirements and financial rewards for improving population health. Therefore, ACOs and hospitals will need tools to understand the relationship between their patients and social determinants and health. We demonstrate the use of hot spotting for identifying geographical sources of high hospital costs and examining links between social determinants of health and these high-cost areas, known as hot spots. In 2012, using hospital data, we generated maps of inpatient costs from 2011 throughout New Haven and within an example neighborhood, Dixwell. We defined hot spots as addresses where costs were in the top 25%. We also overlaid data on concerns and assets in the community. Finally, we calculated the number of concerns and assets that fall within the 250 and 500 ft radii of the defined hot spots. We found that 34 addresses in Dixwell accounted for 70% of total costs for Dixwell. Hot spotting is a straightforward, approachable, and easily understood method for ACOs and hospitals to begin to address population health.
基金the National Key Research and Development Program of China (2018YFB0105000)the National Natural Science Foundation of China (61773234 and U1864203)+2 种基金the Project of Tsinghua University and Toyota Joint Research Center for AI Technology of Automated Vehicle (TT2018-02)the International Science and Technology Cooperation Program of China (2016YFE0102200)the software developed in the Beijing Municipal Science and Technology Program (D171100005117001 and Z181100005918001).
文摘An increasing number of drivers are relying on digital map navigation systems in vehicles or mobile phones to select optimal driving routes in order to save time and improve safety. In the near future, digital map navigation systems are expected to play more important roles in transportation systems. In order to extend current navigation systems to more applications, two fundamental problems must be resolved: the lane-level map model and lane-level route planning. This study proposes solutions to both problems. The current limitation of the lane-level map model is not its accuracy but its flexibility;this study proposes a novel seven-layer map structure, called as Tsinghua map model, which is able to support autonomous driving in a flexible and efficient way. For lane-level route planning, we propose a hierarchical route-searching algorithm to accelerate the planning process, even in the presence of complicated lane networks. In addition, we model the travel costs allocated for lane-level road networks by analyzing vehicle maneuvers in traversing lanes, changing lanes, and turning at intersections. Tests were performed on both a grid network and a real lane-level road network to demonstrate the validity and efficiency of the proposed algorithm.
文摘Cloud computing has created a paradigm shift that affects the way in which business applications are developed. Many business organizations use cloud infrastructures as platforms on which to deploy business applications. Increasing numbers of vendors are supplying the cloud marketplace with a wide range of cloud products. Different vendors offer cloud products in different formats. The cost structures for consuming cloud products can be complex. Finding a suitable set of cloud products that meets an application’s requirements and budget can be a challenging task. In this paper, an ontology-based resource mapping mechanism is proposed. Domain-specific ontologies are used to specify high-level application’s requirements. These are then translated into high-level infrastructure ontologies which then can be mapped onto low-level descriptions of cloud resources. Cost ontologies are proposed for cloud resources. An exemplar media transcoding and delivery service is studied in order to illustrate how high-level requirements can be modeled and mapped onto cloud resources within a budget constraint. The proposed ontologies provide an application-centric mechanism for specifying cloud requirements which can then be used for searching for suitable resources in a multi-provider cloud environment.
