published journal article
Eliminate the mortgage interest deduction or tax imputed rent? Leveling the real-estate playing field
Cityscape (Washington, D.C.)
Publication Date
January 1, 2014
Area of Expertise: Unspecified
published journal article
Traffic-related air pollution and Parkinson’s disease in central California
ISEE Conference Abstracts
Publication Date
September 17, 2023
Author(s)
Beate Ritz, Dayoon Kwon, Jeff M Bronstein, Jun Wu, Kimberly C Paul
Abstract
BACKGROUND AND AIM: Air pollution exposure may increase the risk of Parkinson’s Disease (PD). We assessed associations between long-term traffic-related air pollution exposures and PD in central California. METHOD: We generated air pollution exposures for 688 PD patients and 851 population controls enrolled in the Parkinson’s, Environment and Genes (PEG) studies 1 and 2. First, we estimated annual average carbon monoxide (CO) concentrations between 1981-2016 using the California Line Source Dispersion Model, version 4 (CALINE4) to model local traffic sources and, additionally, fine particulate matter (PM2.5) concentrations between 2000-2016 based on a high-resolution geoscience-derived model. Exposures were assessed as 10-year averaged CO and 5-year averaged PM2.5 prior to a PD diagnosis and a reference date in controls. We used logistic regression models to estimate odds ratios (OR) and 95% confidence intervals (95%CI), adjusting for age, sex, race, education, and study wave. RESULTS: For CO, each interquartile range (IQR) increase in 10-year average exposure prior to diagnosis was found to be associated with an OR of 1.06 (95% CI: 1.01-1.11) for residential and of 1.08 (0.99-1.18) for occupational address-based exposures. A per IQR increase in 5-year average PM2.5 prior to PD also increased the OR for PD at occupational address (OR=1.26; 95% CI 0.96-1.67). Associations were similar for 5- and 15-year exposure averages and were robust to adjustment for smoking or pesticide exposures. CONCLUSIONS: We found consistent evidence for positive associations between PD and long-term exposure to local traffic-related air pollution in central California measured by CO and PM2.5 at home and workplace addresses.
Suggested Citation
Beate Ritz, Dayoon Kwon, Jeff M Bronstein, Jun Wu and Kimberly C Paul (2023) “Traffic-related air pollution and Parkinson’s disease in central California”, ISEE Conference Abstracts, 2023(1). Available at: 10.1289/isee.2023.OP-277. published journal article
Real-time vehicle classification using inductive loop signature data
Transportation Research Record
Publication Date
January 1, 2008
Author(s)
Suggested Citation
Shin-Ting (Cindy) Jeng and Stephen G. Ritchie (2008) “Real-time vehicle classification using inductive loop signature data”, Transportation Research Record, 2086(1), pp. 8–22. Available at: 10.3141/2086-02.
conference paper
Impacts of information technology on personal travel and commercial vehicle operations : Research challenges and opportunities
Proceedings of the 80th annual meeting of the transportation research board
Publication Date
January 1, 2001
Author(s)
Abstract
Travel, like many other aspects of daily life is being transformed by the information technology revolution. Accessibility can no longer be measured only in terms of travel time, distance or generalized travel cost. Information technology gives people virtual accessibility to a rapidly growing range of activities. E-commerce has become a catalyst for structural changes in the freight transportation industry and is changing where freight moves, the size of typical shipments and the time within which goods must be delivered. In this paper we explore some of the potential effects of information technology on transportation, both personal and freight
Suggested Citation
Thomas F. Golob and Amelia C. Regan (2001) “Impacts of information technology on personal travel and commercial vehicle operations : Research challenges and opportunities”, in Proceedings of the 80th annual meeting of the transportation research board, p. 45 p.. conference paper
DeepOpp: Context-aware mobile access to social media content on underground metro systems
2017 IEEE 37th international conference on distributed computing systems (ICDCS)
Publication Date
June 1, 2017
Author(s)
Suggested Citation
Di Wu, Dmitri I. Arkhipov, Thomas Przepiorka, Qiang Liu, Julie A. McCann and Amelia C. Regan (2017) “DeepOpp: Context-aware mobile access to social media content on underground metro systems”, in 2017 IEEE 37th international conference on distributed computing systems (ICDCS). IEEE, pp. 1219–1229. Available at: 10.1109/icdcs.2017.269. published journal article
OAK-TREE: One-of-a-kind traffic research and education experiment
Transportation Research Record
Publication Date
January 1, 1997
Author(s)
Abstract
The creation and progress of OAK-TREE (One-of-a-Kind Traffic Research and Education Experiment) are chronicled. OAK-TREE is a traffic educational laboratory experiment that was developed and conducted at the University of California at Irvine (UCI) during the spring quarter of 1996. This project involved a cooperative effort between the academic community and public-sector transportation operating agencies in developing a comprehensive field and laboratory educational experience for undergraduate students in transportation engineering. The agencies involved in this effort were the Department of Civil and Environmental Engineering at the University of California at Irvine, the Advanced Traffic Surveillance and Control Center of the city of Los Angeles, the Transportation Management Center of the city of Anaheim, and the Irvine Traffic Research and Control Center of the city of Irvine. These agencies were instrumental in creating an innovative laboratory experience for academic training in the use of state-of-the-practice resources and methods for traffic engineering. The results were the development of a state-of-the-art traffic-control educational laboratory at UCI and the genesis of a unique traffic-control course that fulfilled the requirements of both fundamental academic education and rigorous professional training.
Suggested Citation
Carlos Sun, Wilfred Recker, Stephen Ritchie, Brian Gallagher, Eric Shen and John Thai (1997) “OAK-TREE: One-of-a-kind traffic research and education experiment”, Transportation Research Record, 1603(1), pp. 106–111. Available at: 10.3141/1603-14. conference paper
Accessibility in a metropolis - Toward a better understanding of land use and travel
Land development and public involvement in transportation: Planning and administration
Publication Date
January 1, 2001
Author(s)
R Kitamura, T Akiyama, T Yamamoto, Thomas Golob
Abstract
An attempt was made to determine how accessibility affects aspects of long-term and short-term travel behavior. The accessibility indices that were used represent the ease with which opportunities for engagement in activities can be reached from a geographical zone in an urban area. The behavioral aspects examined include engagement in activities, automobile ownership and use, and travel patterns as represented by the number of trips, number of trip chains, and total travel time expenditure. Data from the Kyoto-Osaka-Kobe metropolitan area of Japan and the southern California coast are used to examine the following conjectures: time availability is more closely associated with engagement in activities than accessibility; accessibility no longer affects automobile ownership or use in the metropolises of industrialized countries where motorization has matured; and given automobile ownership and use, travel patterns are conditionally independent of accessibility.
Suggested Citation
R Kitamura, T Akiyama, T Yamamoto and TF Golob (2001) “Accessibility in a metropolis - Toward a better understanding of land use and travel”, in Land development and public involvement in transportation: Planning and administration. TRANSPORTATION RESEARCH BOARD NATL RESEARCH COUNCIL / Transportat Res Board, pp. 64–75. Available at: 10.3141/1780-08. published journal article
Projecting use of electric vehicles from household vehicle trials
Transportation Research Part B: Methodological
Publication Date
September 1, 1998
Author(s)
Abstract
Vehicle trials are an important source of information about how households would use battery electric vehicles. However, trial data are potentially biased because the novelty of the trial can introduce short-term changes in driving patterns and a positive effect for the technology can result from giving respondents special attention. In this study we examine these methodological issues using data collected from travel diaries and pre-trial and post-trial surveys as part of an extensive trial of prototype electric vehicles conducted by a major vehicle manufacturer. Households demonstrated that they can use the electric vehicle to make most of the everyday trips that were previously made on a conventional-fuel vehicle, but some trips will be shifted to other vehicles in the household’s fleet. However, experience with electric vehicles does not change perceptions of desired vehicle range. Keeping a travel diary gave users direct feedback that they were usually travelling less than 50 miles per day, but there remained an expectation that vehicles should have a range of 100 miles or more. (C) 1998 Elsevier Science Ltd. All rights reserved.
Suggested Citation
Thomas F. Golob and Jane Gould (1998) “Projecting use of electric vehicles from household vehicle trials”, Transportation Research Part B: Methodological, 32(7), pp. 441–454. Available at: 10.1016/s0191-2615(98)00001-0. conference paper
Online classification using a voted RDA method
Proceedings of the twenty-eighth aaai conference on artificial intelligence
Publication Date
January 1, 2014
Author(s)
Tianbing Xu, Jianfeng Gao, Lin Xiao, Amelia Regan
Abstract
We propose a voted dual averaging method for online classification problems with explicit regularization. This method employs the update rule of the regularized dual averaging (RDA) method proposed by Xiao, but only on the subsequence of training examples where a classification error is made. We derive a bound on the number of mistakes made by this method on the training set, as well as its generalization error rate. We also introduce the concept of relative strength of regularization, and show how it affects the mistake bound and generalization performance. We examine the method using l(1)-regularization on a large-scale natural language processing task, and obtained state-of-the-art classification performance with fairly sparse models.
Suggested Citation
Tianbing Xu, Jianfeng Gao, Lin Xiao and Amelia C. Regan (2014) “Online classification using a voted RDA method”, in Proceedings of the twenty-eighth aaai conference on artificial intelligence. ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE, pp. 2170–2176. published journal article
Understanding the effects of socioeconomic factors on housing price appreciation using explainable AI
Applied Geography
Publication Date
August 1, 2024
Author(s)
Abstract
Housing price appreciation is an important socioeconomic phenomenon that captures the complex socioeconomic dynamics of a city. Variation in housing price appreciation across neighborhoods reflects localized housing demand and supply-side factors. This study develops quality-adjusted, census tract-level housing price indices using a fine-grained big dataset containing a total of 140,289 housing transactions in the County of Los Angeles. We employ the SHapley Additive exPlanations (SHAP) technique, an explainable artificial intelligence framework, to examine the underlying demographic and socioeconomic factors that help in explaining the variance in tract-level housing price appreciation from 2012 through 2018 in the County of Los Angeles. The novelty of the methodology lies in the local interpretation of spatial patterns it provides from big data in the urban context and in assessing how the factors influencing housing price appreciation vary geographically. The modeling framework could help planners in making informed decisions about local geographic contexts that contribute to variability in housing price appreciation in cities.