2,258 research outputs found
Minneapolis Safety In Numbers Investigation Data
No full textThe data consist of three publicly-available (but not simple to obtain) datasets procured from the City of Minneapolis and an additional spatial reference layer:
1) Turning Movement Counts (TMCs) at select intersections in Minneapolis between 1993 and 2014, broken down by vehicle or user type.
2) Most recently updated Average Annual Daily Traffic (AADT) levels on select street segments in Minneapolis; latest dates range from 2007 to 2014.
3) Crash reports data, from 2000 to 2013.
4) Shapefile of Minneapolis intersections. These points are based on OpenStreetMap street centerlines and provide locations for intersections observed in the turning movement count data.
These datasets were leveraged in research performed for the Roadway Safety Institute at the University of Minnesota's Center for Transportation Studies. The associated project information page is located here: http://www.roadwaysafety.umn.edu/research/search/projectdetail.html?id=2015038Murphy, Brendan; Levinson, David M; Owen, Andrew. (2017). Minneapolis Safety In Numbers Investigation Data. Retrieved from the University Digital Conservancy, https://doi.org/10.13020/D6WG6K
Significado tectónico de rocas del paleozoico superiormesozoico inferior y eventos tectono-termales en el sureste del Complejo Acatlán, sur de México :\ua0Tectonic significance of latest paleozoicearly mesozoic rocks and tectonothermal events in the southeastern Acatlán Complex, Southern México /
No full text\ua0tesis que para obtener el grado de Doctorado en Ciencias de la Tierra, presenta María Helbig ; tutor principal de tesis Duncan Keppie, Brendan Murphy, Luigi Solari. 157 páginas :\ua0ilustraciones
Advances in model based clustering for the social sciences
No full textThis dissertation attempts to gather the main research topics I engaged during my PhD, in collaboration with several national and international researchers. The primary focus of this work is to highlight the power of model based clustering for identifying latent structures in complex data and its usefulness in the social sciences. This methods have become increasingly popular in social science research as they allow for more accurate and nuanced understanding of complex data structures. In the thesis are presented 3 papers that contribute to the development and application of model-based clustering in social science research, covering a range of scenario. The thesis pays particular attention to the practical applications of the treated methods, providing insights that can improve our understanding of complex social phenomena.
The first chapter of this dissertation introduces the usefulness of clustering model to deal with the complexity of society, and aware of some of the main issues when analysing socio-economic data. Following this conceptual introduction, the second chapter delves more into the technical aspects of model based clustering and estimation. These first two chapters pave the road for the three developments presented thereafter. The third chapter includes the application of a Mixture of Matrix-Normals classification model to the Migrant Integration Policy Index (MIPEX), that measures and evaluates countries policies toward migrants’ integration over time. The used model is suitable for longitudinal data and allows for the identification of clusters of countries with similar patterns of migrant integration policies over time. The work is published in Alaimo et al. [2021a]. The fourth chapter uses MIPEX data too, but for a single year, and a finite mixtures of multivariate Gaussian is applied to identify groups of countries with a similar level of integration. Then, the relative proportion of immigrants held in prison among clusters is estimated, exploiting Fisher’s noncentral hypergeometric model. The aim of this work is test the existence of an association between countries’ level of integration of immigrants and the proportion of immigrants in prison. The work is currently in referral process. The fifth chapter introduce the work developed during my visiting research period at University of Lyon, Lyon 2. It specify the Bayesian partial membership model for soft clustering of multivariate data, namely when units have fractional membership to multiple groups. The model is specified for count data, and it is applied on the data of the bike sharing company of Washington DC and on the data of Serie A football players. The last chapter summarizes the main points of the dissertation, underlining the most relevant findings, the contributions, and stressing out how clustering models altogether yield a cohesive treatment of socio-economic data
Access Across America: Transit 2016 Data
No full textDownloads are available for individual metropolitan regions, as well as states, in CSV or Shapefile format. Combined ZIP files containing the data for all metropolitan regions are also available in CSV and Shapefile format, and are labeled as "All Metropolitan Regions." A combined ZIP file containing the data for all State regions is available only in CSV format.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.Sponsorship: Center for Transportation Studies, University of MinnesotaOwen, Andrew; Murphy, Brendan. (2018). Access Across America: Transit 2016 Data. Retrieved from the University Digital Conservancy, https://doi.org/10.13020/D6BT3X
A finite mixture latent trajectory model for modeling ultrarunners' behavior in a 24-hour race
No full textA finite mixture latent trajectory model is developed to study the performance and strategy of runners in a 24-h long ultra running race. The model facilitates clustering of runners based on their speed and propensity to rest and thus reveals the strategies used in the race. Inference for the adopted latent trajectory model is achieved using an expectation-maximization algorithm. Fitting the model to data from the 2013 World Championships reveals three clearly separated clusters of runners who exhibit different strategies throughout the race. The strategies show that runners can be grouped in terms of their average moving speed and their propensity to rest during the race. The effect of age and gender on the probability of belonging to each cluster is also investigated.Science Foundation IrelandItalian Governmen
Access Across America: Transit 2015 Data
No full textDownloads are available for individual metropolitan regions, as well as states, in CSV or Shapefile format. Combined ZIP files containing the data for all metropolitan regions are also available in CSV and Shapefile format, and are labeled as "All Metropolitan Regions." A combined ZIP file containing the data for all State regions is available only in CSV format.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.Center for Transportation Studies, University of MinnesotaOwen, Andrew; Levinson, David M; Murphy, Brendan. (2017). Access Across America: Transit 2015 Data. Retrieved from the University Digital Conservancy, https://doi.org/10.13020/D63G6F
Finding Aid to the Collection of James Brendan Connolly Materials
No full textThe Connolly Collection contains the writings and personal library of James Brendan Connolly (1868-1957). The collection includes Connolly\u27s reminiscences, newspaper articles, and galley and page proofs as well as scrapbook clippings. There are also notebooks containing holograph notes on schooners and the navy, letters from Connolly\u27s personal correspondence, and books from Connolly\u27s personal library. James Brendan Connolly (1868-1957) was an Irish-American author of sea-related stories, novels, and nonfiction such as The Book of the Gloucester Fishermen. Born in South Boston, he attended Harvard and was a medal-winning athlete in the first modern Olympics, held in Athens in 1896. He participated in the Siege of Santiago as a member of the 9th Regiment, ran for the 12th Congressional District (South Boston) seat as a member of the Progressive Party in 1914, and worked as a correspondent for such publications as Scribner\u27s, Harper\u27s and Collier\u27s
Latent space modelling of multidimensional networks with application to the exchange of votes in Eurovision song contest
No full textThe Eurovision Song Contest is a popular TV singing competition held annually among country members of the European Broadcasting Union. In this competition, each member can be both contestant and jury, as it can participate with a song and/or vote for other countries’ tunes. During the years, the voting system has repeatedly been accused of being biased by tactical voting; votes would represent strategic interests rather than actual musical preferences of the voting countries. In this work, we develop a latent space model to investigate the presence of a latent structure underlying the exchange of votes. Focusing on the period from 1998 to 2015, we represent the vote exchange as a multivariate network: each edition is a network, where countries are the nodes and two countries are linked by an edge if one voted for the other. The different networks are taken to be independent replicates of a conditional Bernoulli distribution, with success probability specified as a function of a common latent space capturing the overall relationships among the countries. Proximity denotes similarity, and countries close in the latent space are more likely to exchange votes. If the exchange of votes depends on the similarity between countries, the quality of the competing songs might not be a relevant factor in the determination of the voting preferences, and this would suggest the presence of some bias. A Bayesian hierarchical modelling approach is employed to estimate the parameters, where the probability of a connection between any two countries is a function of their distance in the latent space, network-specific parameters and edge-specific covariates. The estimated latent space is found to be relevant in the determination of edge probabilities, however, the positions of the countries in such space only partially correspond to their actual geographical positions
Prize Winning Entries in the 1983 Arts and Letters Competition
No full textWinning Entries was an annual publication created in 1955 that announced and showcased the winners of the government sponsored Arts and Letters Awards. It ceased in print in 2000.On Their Own / Leanne Michelle Penney -- Tribulations / Pamela L. Snow -- Chances / Peter Rogers -- The Cat That Walked By Herself / David S. Artiss -- The Letter / Michael J. McCarthy -- Popplestone / James C. Feltham -- The Quidi Vidi Murder / Michael J. McCarthy -- Jim (Painting) / Ruth Maunder -- The Cold House (graphic art) / Jacob Kennedy -- Evening Birches (construction/ assemblage/ sculpture) / Brendan Blackmore -- A Still Life, circa 1756 / Brendan L. Murphy -- Jaws (b/w photography) / Lydia Smellen -- The Promotion of World Peace & Harmony / Karl Samuelso
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