Carbon Free Boston: Transportation Technical Report

Part of a series of reports that includes: Carbon Free Boston: Summary Report; Carbon Free Boston: Social Equity Report; Carbon Free Boston: Technical Summary; Carbon Free Boston: Buildings Technical Report; Carbon Free Boston: Waste Technical Report; Carbon Free Boston: Energy Technical Report; Carbon Free Boston: Offsets Technical ReportOVERVIEW: Transportation connects Boston’s workers, residents and tourists to their livelihoods, health care, education, recreation, culture, and other aspects of life quality. In cities, transit access is a critical factor determining upward mobility. Yet many urban transportation systems, including Boston’s, underserve some populations along one or more of those dimensions. Boston has the opportunity and means to expand mobility access to all residents, and at the same time reduce GHG emissions from transportation. This requires the transformation of the automobile-centric system that is fueled predominantly by gasoline and diesel fuel. The near elimination of fossil fuels—combined with more transit, walking, and biking—will curtail air pollution and crashes, and dramatically reduce the public health impact of transportation. The City embarks on this transition from a position of strength. Boston is consistently ranked as one of the most walkable and bikeable cities in the nation, and one in three commuters already take public transportation. There are three general strategies to reaching a carbon-neutral transportation system: • Shift trips out of automobiles to transit, biking, and walking;1 • Reduce automobile trips via land use planning that encourages denser development and affordable housing in transit-rich neighborhoods; • Shift most automobiles, trucks, buses, and trains to zero-GHG electricity. Even with Boston’s strong transit foundation, a carbon-neutral transportation system requires a wholesale change in Boston’s transportation culture. Success depends on the intelligent adoption of new technologies, influencing behavior with strong, equitable, and clearly articulated planning and investment, and effective collaboration with state and regional partners.Published versio

Allegorie des verdrängten Mitläufertums: Carl Merz’ und Helmut Qualtingers Herr Karl als österreichische ‚Banalität des Bösen‘

With Der Herr Karl (1961), Carl Merz and Helmut Qualtinger created a folk play of a ‘critical, myth-destroying form’ (Bobinac 1992) which is unique in Austrian theatre history. The scandal which this one-hour monodrama caused when it was first broadcast on Austrian television was also due to the unmasking character drawing: In the behaviour of the titular fellow traveller and opportunist ‘Herr Karl’, the audience recognised itself – the post-war mentality of repressing, forgetting and relativising found itself shaken to its foundations. The article aims to examine to what extent Hannah Arendt’s reflections on the ‘Banality of Evil’ are actually applicable to Merz and Qualtinger’s play and which aspects of Austrian mentality history become visible in it. In particular, the Austrian remembrance culture and its way of dealing with the traumatic happenings could become evident – especially in a nation that tried to posit itself as the first ‘victim’ of Hitler’s Germany even before the end of the wa

Simulating service reliability of a high frequency bus route using automatically collected data

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2008.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references.High frequency bus routes are subject to a variety of influences that can affect the quality of service provided to passengers. Since they have short headways and high passenger demand interaction between buses can easily develop, causing degradation in service reliability. This, in turn, can prompt service interventions to correct service reliability. Transit agencies are implementing new technology that provide rich data sets for analysis and are also experimenting with a variety of operating policies to improve service reliability. This research develops a simulation model of high frequency bus service in order to study the causes of service unreliability and strategies to alleviate it. The model is designed to be used in conjunction with data recorded by the Automatic Voice Annunciation System (AVAS), Automatic Passenger Counting (APC), and Automatic Fare Collection (AFC) systems and is calibrated to represent route 63, a key bus route in the Chicago Transit Authority (CTA) network The simulation model is first used to conduct a sensitivity analysis of the factors influencing reliability, such as passenger demand, terminal departure behavior, and unfilled trips. Next, several operating strategies, including terminal departure and timepoint holding for schedule or headway, are modeled and evaluated for their potential to improve reliability. The sensitivity analysis and application testing support the use of passenger-centric metrics such as passenger-experienced waiting time and crowding over more aggregate headway measures such as large headways and bunching. Model results show that headway management strategies implemented at the terminal can significantly improve bus service reliability and ameliorate the impacts of unfilled trips on route 63, as measured by passenger waiting time, crowding, and big-gaps / bunches.(cont.) The simulation model is a valuable research tool for applications beyond those tested in this thesis. The model developed can be applied with from data collected by automatic collection systems which is a particularly useful feature for transit agencies.by Martin Nicholas Milkovits.S.M

City of Boston transportation baseline forecast (Carbon Free Boston Initiative) presentation

Presentation to the Transportation Analysis Group on the City of Boston Transportation Baseline Forecast

Doctor2Vec: Dynamic Doctor Representation Learning for Clinical Trial Recruitment

Massive electronic health records (EHRs) enable the success of learning accurate patient representations to support various predictive health applications. In contrast, doctor representation was not well studied despite that doctors play pivotal roles in healthcare. How to construct the right doctor representations? How to use doctor representation to solve important health analytic problems? In this work, we study the problem on {\it clinical trial recruitment}, which is about identifying the right doctors to help conduct the trials based on the trial description and patient EHR data of those doctors. We propose doctor2vec which simultaneously learns 1) doctor representations from EHR data and 2) trial representations from the description and categorical information about the trials. In particular, doctor2vec utilizes a dynamic memory network where the doctor's experience with patients are stored in the memory bank and the network will dynamically assign weights based on the trial representation via an attention mechanism. Validated on large real-world trials and EHR data including 2,609 trials, 25K doctors and 430K patients, doctor2vec demonstrated improved performance over the best baseline by up to $8.7\%$ in PR-AUC. We also demonstrated that the doctor2vec embedding can be transferred to benefit data insufficiency settings including trial recruitment in less populated/newly explored country with $13.7\%$ improvement or for rare diseases with $8.1\%$ improvement in PR-AUC.Comment: Accepted by AAAI 202