Browsing by Subject "Networks"

Now showing 1 - 20 of 33
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    Access Across America: Auto 2018 Data
    (2020-01-31) Murphy, Brendan; Owen, Andrew; aowen@umn.edu; Owen, Andrew; University of Minnesota Center for Transportation Studies, Accessibility Observatory
    These data were created as part of a study that examined the accessibility to jobs by auto in the 50 largest (by population) metropolitan areas in the United States. It is the most detailed evaluation to date of access to jobs by auto, and it allows for a direct comparison of the auto accessibility performance of America's largest metropolitan areas. These data are part of a longitudinal study. The data available describe access to jobs by auto in the states of Arkansas, California, District of Columbia, Florida, Illinois, Iowa, Maryland, Massachusetts, Minnesota, North Carolina, Tennessee, Washington, and Virginia, and the metropolitan areas within these states.
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    Access Across America: Auto 2021 Data
    (2023-09-21) Owen, Andrew; Liu, Shirley Shiqin; Jain, Saumya; Hockert, Matthew; Lind, Eric; owenx148@umn.edu; Owen, Andrew; University of Minnesota Center for Transportation Studies, Accessibility Observatory
    These data were created as part of a study that examined the accessibility to jobs by auto in the 50 largest (by population) metropolitan areas in the United States. The data include access at realistic observed driving speeds by time of day and road segment. The underlying speed data inputs restrict data sharing to participating sponsor states. The data available describe access to jobs by auto in the states/districts of California, Connecticut, District of Columbia, Florida, Illinois, Maryland, Massachusetts, Michigan, Minnesota, North Carolina, Texas; and the metropolitan areas within these states. These data are part of a longitudinal study. Auto data for additional years can be found in the Accessibility Observatory Data collection: http://hdl.handle.net/11299/200592
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    Access Across America: Bike 2017 Data
    (2020-02-03) Murphy, Brendan; Owen, Andrew; aowen@umn.edu; Owen, Andrew; University of Minnesota Center for Transportation Studies, Accessibility Observatory
    These data were created as part of a study that examined the accessibility to jobs by biking in the 50 largest (by population) metropolitan areas in the United States, on low-stress and higher-stress streets via a Level of Traffic Stress analysis process. It is the most detailed evaluation to date of access to jobs by bike nationally, and it allows for a direct comparison of the bicycle accessibility performance of America's largest metropolitan areas. These data are part of a longitudinal study.
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    Access Across America: Bike 2019 Data
    (2021-01-29) Owen, Andrew; Murphy, Brendan; aowen@umn.edu; Owen, Andrew; University of Minnesota Center for Transportation Studies, Accessibility Observatory
    These data were created as part of a study that examined the accessibility to jobs by bicycling in the 50 largest (by population) metropolitan areas in the United States. It is the most detailed evaluation to date of access to jobs by biking, and incorporates a Level of Traffic Stress analysis to allow calculation of access to jobs on bike networks of different traffic stress tolerances. This dataset allows for a direct comparison of the biking accessibility performance of America's largest metropolitan areas. These data are part of a longitudinal study. Access Across America: Bike 2017 data are available at https://conservancy.umn.edu/handle/11299/211418, however the 2017 version of this dataset was produced without implementation of Level of Traffic Stress analysis, and the methodologies differ substantially.
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    Access Across America: Bike 2021 Data
    (2023-08-28) Owen, Andrew; Liu, Shirley Shiqin; Jain, Saumya; Hockert, Matthew; Lind, Eric; owenx148@umn.edu; Owen, Andrew; University of Minnesota Center for Transportation Studies, Accessibility Observatory
    These data were created as part of a study that examined the accessibility to jobs by bicycling across the United States. It is the most detailed evaluation to date of access to jobs by biking, and incorporates a Level of Traffic Stress analysis to allow calculation of access to jobs on bike networks of different traffic stress tolerances. This dataset allows for a direct comparison of the biking accessibility performance of America's largest metropolitan areas. These data are part of a longitudinal study. Previous datasets (Access Across America: Bike 2019) are available at https://conservancy.umn.edu/handle/11299/218194.
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    Access Across America: Transit 2014 Data
    (2014-12-05) Owen, Andrew; Levinson, David M; aowen@umn.edu; Owen, Andrew; University of Minnesota Center for Transportation Studies, Accessibility Observatory
    This data was created as part of a study that examined the accessibility to jobs by transit in 46 of the 50 largest (by population) metropolitan areas in the United States. It is the most detailed evaluation to date of access to jobs by transit, and it allows for a direct comparison of the transit accessibility performance of America's largest metropolitan areas.
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    Access Across America: Transit 2015 Data
    (2017-02-02) Owen, Andrew; Levinson, David M; Murphy, Brendan; aowen@umn.edu; Owen, Andrew
    These data were created as part of a study that examined the accessibility to jobs by transit in 49 of the 50 largest (by population) metropolitan areas in the United States. It is the most detailed evaluation to date of access to jobs by transit, and it allows for a direct comparison of the transit accessibility performance of America's largest metropolitan areas. These data are part of a longitudinal study; Access Across America: Transit 2014 data are available at http://hdl.handle.net/11299/168064.
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    Access Across America: Transit 2016 Data
    (2018-03-28) Owen, Andrew; Murphy, Brendan; aowen@umn.edu; Owen, Andrew; University of Minnesota Center for Transportation Studies, Accessibility Observatory
    These data were created as part of a study that examined the accessibility to jobs by transit in 49 of the 50 largest (by population) metropolitan areas in the United States. It is the most detailed evaluation to date of access to jobs by transit, and it allows for a direct comparison of the transit accessibility performance of America's largest metropolitan areas. These data are part of a longitudinal study; Access Across America: Transit 2015 data are available at https://conservancy.umn.edu/handle/11299/183801. Access Across America: Transit 2014 data are available at http://hdl.handle.net/11299/168064.
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    Access Across America: Transit 2017 Data
    (2018-10-08) Owen, Andrew; Murphy, Brendan; aowen@umn.edu; Owen, Andrew; University of Minnesota Center for Transportation Studies, Accessibility Observatory
    These data were created as part of a study that examined the accessibility to jobs by transit in 49 of the 50 largest (by population) metropolitan areas in the United States. It is the most detailed evaluation to date of access to jobs by transit, and it allows for a direct comparison of the transit accessibility performance of America's largest metropolitan areas. These data are part of a longitudinal study. Access Across America: Transit 2016 data are available at https://conservancy.umn.edu/handle/11299/195065. Access Across America: Transit 2015 data are available at https://conservancy.umn.edu/handle/11299/183801. Access Across America: Transit 2014 data are available at http://hdl.handle.net/11299/168064.
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    Access Across America: Transit 2018 Data
    (2020-01-31) Owen, Andrew; Murphy, Brendan; aowen@umn.edu; Owen, Andrew; University of Minnesota Center for Transportation Studies, Accessibility Observatory
    These data were created as part of a study that examined the accessibility to jobs by transit in the 50 largest (by population) metropolitan areas in the United States. It is the most detailed evaluation to date of access to jobs by transit, and it allows for a direct comparison of the transit accessibility performance of America's largest metropolitan areas. These data are part of a longitudinal study. Transit data for additional years can be found in the Accessibility Observatory Data collection: http://hdl.handle.net/11299/200592
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    Access Across America: Transit 2019 Data
    (2021-01-26) Murphy, Brendan; Owen, Andrew; aowen@umn.edu; Owen, Andrew; University of Minnesota Center for Transportation Studies, Accessibility Observatory
    These data were created as part of a study that examined the accessibility to jobs by transit in the 50 largest (by population) metropolitan areas in the United States. It is the most detailed evaluation to date of access to jobs by transit, and it allows for a direct comparison of the transit accessibility performance of America's largest metropolitan areas. These data are part of a longitudinal study. Transit data for additional years can be found in the Accessibility Observatory Data collection: http://hdl.handle.net/11299/200592
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    Access Across America: Transit 2021 Data
    (2023-08-31) Owen, Andrew; Liu, Shirley Shiqin; Jain, Saumya; Hockert, Matthew; Lind, Eric; owenx148@umn.edu; Owen, Andrew; University of Minnesota Center for Transportation Studies, Accessibility Observatory
    These data were created as part of a study that examined the accessibility to jobs by transit across the United States. It is the most detailed evaluation to date of access to jobs by transit, and it allows for a direct comparison of the transit accessibility performance of America's metropolitan areas. These data are part of a longitudinal study. Transit data for additional years can be found in the Accessibility Observatory Data collection: http://hdl.handle.net/11299/200592
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    Accessibility and the evaluation of investments on the Beijing subway
    (Journal of Transport and Land Use, 2017) Jiang, Haibing; Levinson, David
    This study measures the job and population accessibility via transit for Beijing using the cumulative opportunity metric. It is shown that transit accessibility varies widely across Beijing, but is highly focused on subway stations. Early lines added far more accessibility than more recently planned lines.
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    Accessibility, Network Structure, and Consumers’ Destination Choice: A GIS Analysis of GPS Travel Data and the CLUSTER Simulation Module for Retail Location Choice
    (Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota, 2012-10) Huang, Arthur; Levinson, David
    Anecdotal and empirical evidence has shown strong associations between the built environment and individuals’ travel decision. To date, data about individuals’ travel behavior and the nature of the retail environment have not been linked at the fine-grained level for verifying such relationships. GPS and GIS have revolutionized how we measure and monitor land use and individual travel behavior. Compared with traditional travel survey methods, GPS technologies provide more accurate and detailed information about individuals’ trips. Based the GPS travel data in the Twin Cities we analyze the impact of individuals’ interactions with road network structure and the destinations’ accessibility on individuals’ destination choice for home-based non-work retail trips. The results reveal that higher accessibility and diversity of services make the destination more attractive. Further, accessibility and diversity of establishments in a walking zone are often highly correlated. A destination reached via a more circuitous or discontinuous route dampens its appeal. In addition, we build an agent-based simulation tool to study retail location choice on a supply chain network consisting of suppliers, retailers, and consumers. The simulation software illustrates that the clustering of retailers can emerge from the balance of distance to suppliers and the distance to consumers. We further applied this tool in the Transportation Geography and Networks course (CE 5180) at the University of Minnesota. Student feedback reveals that it is a useful active learning tool for transportation and urban planning education. The software also has the potential of being extended for an integrated regional transportation-land use forecasting model.
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    Community design and how much we drive
    (Journal of Transport and Land Use, 2012) Marshall, Wesley; Garrick, Norman
    The preponderance of evidence suggests that denser and more connected communities with a higher degree of mixed land uses results in fewer vehicle kilometers traveled (VKT). However, there is less agreement as the size of the effect. Also, there is no clear understanding as to the aspects of community design that are most important in contributing to lower VKT. One reason why there is some confusion on this point is that past studies have not always made a clear distinction between different community and street network design characteristics such as density, connectivity, and configuration. In this research, care was taken to fully characterize the different features of the street network including a street pattern classification system that works at the neighborhood level but also focuses on the citywide street network as a separate entity. We employ a spatial kriging analysis of NHTS data in combination with a generalized linear regression model in order to examine the extent to which community design and land use influence VKT in 24 California cities of populations from 30,000 to just over 100,000. Our results suggest that people living in denser street network designs tended to drive less. Connectivity, however, played an adverse role in performance.
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    Data Cycling in Networks: Thoughts and Experiments
    (2016-11) Desai, Vaibhav
    Communication systems rely on underlying networks and networking infrastructure to send information from one participating node to another. In this process of data transmission, the sent information experiences delays in the network. The amount of network delay depends on the underlying network, the processing elements (such as routers, switches etc.) and time taken for physical transmission. These delays are constituted by various paths that transmitted packets take and queues that they wait in before arriving at the destination. The delays ``emulate'' temporary data storage. This study explores and analyzes this transient storage in different types of networks. The study introduces transient storage and data cycling from the perspective of physics and in electro-optical computer networks. Such transient storage can be used to solve problems where data storage and data validity is ephemeral. For example, handling packets from new flows at an OpenFlow switch while it awaits handling rules from the controller or distribution of data generated by a sensor network where data becomes invalid after a short time. Furthermore, transient data storage can be used to manage context in fast changing networks where central control or storage is hard to implement. Transient data storage in networks utilizes the network bandwidth which would otherwise simply remain unused. In this work, transient storage, leveraging networking and queuing delays is used to build an ephemeral storage system by creating loops of networked nodes. Data can be cycled on loops for temporary storage before being used. A loop of nodes is used to demonstrate the idea of data cycling and transient storage. Data cycling experiments are setup to characterize and study its effects on network traffic. Further, applications of transient storage are discussed. A novel application of transient data storage for accumulative counting in vehicular networks is developed and analyzed in detail. This application is implemented and simulated on a network simulator to study its performance and sensitivity to variation of tunable parameters.
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    Defining land use intensity based on roadway level of service targets
    (Journal of Transport and Land Use, 2011) Iravani, Hamid; Mirhoseini, Arash; Rasoolzadeh, Maziar
    Traditionally, master planners develop an initial land use scenario for an undeveloped site, which is then forwarded to transportation planners for modeling purposes. On the basis of travel demand forecast, several alternatives are provided to master planners and, accordingly, different land use proposals are examined until, finally, a preferred option is chosen. Such trial and error process is inherently cumbersome, time consuming and an optimal outcome is rarely achieved. Usually, by increasing land use intensity, roads will be overly congested, beyond acceptable levels, and under-utilized when lower levels of land use intensity is planned. Hence, defining optimum land use intensity to target traffic level of service on roads is never achieved. The aim of this paper is to introduce an innovative approach, based on a “reverse engineering” process, to define final land use intensity based on desired target volume on roads. This method significantly reduces the number of model runs required for “what if” analysis. It also brings the results of travel demand forecast models closer to the desired outcome.
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    Eco-epidemiology of tuberculosis in Maasai Mara Kenya: Conceptualizing sociocultural practices for One Health
    (2021-06) Paul, George
    The control of tuberculosis has proven an ongoing challenge for public health. For pastoralists, those defined by their fundamental cultural relationship with livestock and migration in search of pasture and water, the complexity of tuberculosis control intersects with social and cultural practices that should be considered when designing interventions not as binary attributes of the community, but as a continuum within which the community lives and operates. The goal of the work contained within this thesis is to characterize Mycobacterium tuberculosis complex species (MTBC) in a high-exposure human-animal interface; explore the relevance of social and cultural factors; and evaluate the potential role of livestock movement in the transmission and control of zoonotic tuberculosis in the Mara ecosystem. In this dissertation, I document the co-circulation of multiple MTBC species in this ecosystem, with zoonotic tuberculosis substantially contributing to the overall burden, especially in villages adjacent to the Maasai Mara National Reserve, a protected wildlife area. Further, this work demonstrates that livestock movements not only mediate connectivity between villages within this ecosystem, but also interact with other factors to shape household tuberculosis patterns. Specifically, consumption of raw animal products, and movement of livestock for grazing or trade influence household tuberculosis occurrence, and reinforce the importance of zoonotic tuberculosis. Using data on livestock movement, this study demonstrates that dry season grazing patterns are important for enhancing the embeddedness of households’ in their community social networks, with villages adjacent to the Maasai Mara National Reserve as the most common destination for grazing. Overall, the work presented here reinforce the complexity of this issue within this ecosystem, and demonstrates that network-based control measures aimed at highly connected villages, have the potential to enhance the proactive development of targeted disease control programs as traditional and/or narrowly focused approaches for tuberculosis control are unlikely to work. Thus, in accordance with the current global wave of thinking, One Health approaches are also necessary and even required in this system. However, the operationalization of One Health approaches need to be culturally appropriate and tailored specifically to the characteristics of a locality and contextualized to its practices and structures.
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    Essays in Macroeconomics
    (2024-05) Perez Perez, Luis
    Over the course of the past five decades, several puzzling macroeconomic trends have caught the eye of economists and policymakers alike. The rise of market power, the decline of the labor share, and the decline of productivity growth are simply some prominent examples. Given their importance, much has been written and discussed about these topics, yet little is still known about their underlying causes. In addition to these phenomena, in recent years economists have turned their attention to the Covid-19 pandemic, grappling with understanding its economic ramifications and with formulating optimal policy interventions. My doctoral dissertation, titled "Essays in Macroeconomics," consists of four distinct yet interconnected chapters. These chapters delve into the topics outlined above, with Economic Growth and Public Finance serving as unifying themes. The first two chapters fall within the scope of Economic Growth, while the last two center on Public Finance. Methodologically, each chapter combines economic theory with empirical or quantitative analysis, if not both, to shed light on important macroeconomic questions.
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    Essays On Racial Inequality In The Labor Market
    (2024-04) Treanor, Caitlin
    This dissertation studies issues related to racial inequality in the labor market. The first two chapters focus on the impact of racially segregated referral networks on inequality and aggregate welfare, while the final chapter focuses on differences in returns to work experience and the supply of labor between black and white workers in recent decades. The first chapter shows that there are racial differences in the composition of referral networks and the use of referral networks by occupation. In particular, non-college black and white workers in the United States who obtain a job via referral display substantial social segregation, using same-race contacts around 90% of the time. While non-college black and white workers use referrals at a similar rate overall, black workers use referrals for higher-skill and higher-paying occupations at a lower rate than white workers. I also document racial differences in occupational choice, with white workers sorting into higher-skill occupations. The following chapter connects and rationalize these observations by incorporating a referral-based matching function into a standard search and match model with occupational choice, heterogeneous ability levels, free entry, and wages determined by Nash bargaining. Social segregation can lead to differences in occupational choice by race, and thus wage and employment inequality, in the steady state. After calibrating the model to examine black and white workers in the United States, the estimates show that racially biased networks alone can generate a black-white wage gap of 1.66 percent and an employment gap of 0.74 percentage points. Moving from the segregated to the desegregated steady state harms the majority white workers while helping the minority black workers, resulting in a decrease in aggregate welfare. In the final chapter I utilize individual fixed effects combined with an instrumental variables approach to document the extent to which returns to work experience differ for black and white workers; I then use a life-cycle model with a learning-by-doing human capital production function to assess the consequences of these differences for the supply of labor. Returns to an extra thousand hours of work experience for the typical white worker are 23 cents per hour in 2012 USD (amounting to an additional $478 per year of full time work), compared to 12 cents for an otherwise identical black worker (amounting to an additional $250 per year). Using a life-cycle model, differences in returns to experience combined with simulated differences in choices of hours worked can account for approximately 10 percent of the measured difference in average wages over the life-cycle between black and white workers.