Rhew, Isaac C.; Hurvitz, Philip M.; Lyles-riebli, Rose; Lee, Christine M. (2022). Geographic Ecological Momentary Assessment Methods to Examine Spatio-temporal Exposures Associated with Marijuana Use Among Young Adults: A Pilot Study. Spatial And Spatio-temporal Epidemiology, 41.
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Abstract
Background: This study demonstrates the use of geographic ecological momentary assessment (GEMA) methods among young adult marijuana users. Method: Participants were 14 current marijuana users ages 21-27 living in Greater Seattle, Washington. They completed brief surveys four times per day for 14 consecutive days, including measures of marijuana use and desire to use. They also carried a GPS data logger that tracked their spatial movements over time. Results: Participants completed 80.1% of possible EMA surveys. Using the GPS data, we calculated daily number of exposures to (i.e., within 100-m of) marijuana retail outlets (mean = 3.9 times per day; SD = 4.4) and time spent per day in high poverty census tracts (mean = 7.3 h per day in high poverty census tracts; SD = 5.1). Conclusions: GEMA may be a promising approach for studying the role spatio-temporal factors play in marijuana use and related factors.
Keywords
Geographic Ecological Momentary Assessment; Spatio-temporal Factors; Marijuana; Young Adults; Geographic Information System; Poverty; Substance Use; Alcohol; Tracking
Pan, Haixiao; Shen, Qing; Xue, Song. (2010). Intermodal Transfer Between Bicycles and Rail Transit in Shanghai, China. Transportation Research Record, 2144, 181 – 188.
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Abstract
Large cities in China are building rail transit systems as part of a key strategy to address their pressing urban transportation problems. Because the high construction cost of subways and light rail limits the network density of rail transit, urban transport planners must seek effective intermodal connections between rail and other modes. This research examines the challenges and opportunities for improving the bicycle rail connection by using Shanghai as a case study. On the basis of two questionnaire surveys of rail transit riders, the research analyzes the existing mode shares of rail station access and egress trips, the underlying mechanisms for choosing among alternative modes, and the comparative advantages of the bicycle for trips that have certain distance and location characteristics. Empirical results suggest that the potential for travel improvement for rail transit riders lies primarily in the collection and distribution phases. Results point to several promising approaches to improving the bicycle rail connection and utilizing the bicycle more fully as an efficient supplement mode for the rapidly expanding urban rail transportation in China. In addition, the work can be a useful reference for cities in other countries in which rail transit development is accompanied by the continued importance of bicycles in residents' travel.
Moudon, Anne Vernez; Cook, Andrea J.; Ulmer, Jared; Hurvitz, Philip M.; Drewnowski, Adam. (2011). A Neighborhood Wealth Metric for Use in Health Studies. American Journal Of Preventive Medicine, 41(1), 88 – 97.
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Abstract
Background: Measures of neighborhood deprivation used in health research are typically based on conventional area-based SES. Purpose: The aim of this study is to examine new data and measures of SES for use in health research. Specifically, assessed property values are introduced as a new individual-level metric of wealth and tested for their ability to substitute for conventional area-based SES as measures of neighborhood deprivation. Methods: The analysis was conducted in 2010 using data from 1922 participants in the 2008-2009 survey of the Seattle Obesity Study (SOS). It compared the relative strength of the association between the individual-level neighborhood wealth metric (assessed property values) and area-level SES measures (including education, income, and percentage above poverty as single variables, and as the composite Singh index) on the binary outcome fair/poor general health status. Analyses were adjusted for gender, categoric age, race, employment status, home ownership, and household income. Results: The neighborhood wealth measure was more predictive of fair/poor health status than area-level SES measures, calculated either as single variables or as indices (lower DIC measures for all models). The odds of having a fair/poor health status decreased by 0.85 (95% CI=0.77, 0.93) per $50,000 increase in neighborhood property values after adjusting for individual-level SES measures. Conclusions: The proposed individual-level metric of neighborhood wealth, if replicated in other areas, could replace area-based SES measures, thus simplifying analyses of contextual effects on health. (Am J Prev Med 2011; 41(1): 88-97) (C) 2011 American Journal of Preventive Medicine
Keywords
Health -- Social Aspects; Social Status; Public Health Research; Home Ownership; Income; Real Property; Deprivation (psychology); Health Education; Disparities Geocoding Project; Body-mass Index; Socioeconomic-status; Ecological Fallacy; Built Environment; Deprivation Indexes; Multilevel Analysis; Individual-level; Social-class; Inequalities
Maliszewski, Paul J.; Larson, Elisabeth K.; Perrings, Charles. (2012). Environmental Determinants of Unscheduled Residential Outages in the Electrical Power Distribution of Phoenix, Arizona. Reliability Engineering & System Safety, 99, 161 – 171.
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Abstract
The sustainability of power infrastructures depends on their reliability. One test of the reliability of an infrastructure is its ability to function reliably in extreme environmental conditions. Effective planning for reliable electrical systems requires knowledge of unscheduled outage sources, including environmental and social factors. Despite many studies on the vulnerability of infrastructure systems, the effect of interacting environmental and infrastructural conditions on the reliability of urban residential power distribution remains an understudied problem. We model electric interruptions using outage data between the years of 2002 and 2005 across Phoenix, Arizona. Consistent with perceptions of increased exposure, overhead power lines positively correlate with unscheduled outages indicating underground cables are more resistant to failure. In the presence of overhead lines, the interaction between birds and vegetation as well as proximity to nearest desert areas and lakes are positive driving factors explaining much of the variation in unscheduled outages. Closeness to the nearest arterial road and the interaction between housing square footage and temperature are also significantly positive. A spatial error model was found to provide the best fit to the data. Resultant findings are useful for understanding and improving electrical infrastructure reliability. (C) 2011 Elsevier Ltd. All rights reserved.
Keywords
Determinants (mathematics); Electric Power Distribution; Reliability In Engineering; Social Factors; Temperature Effect; Phoenix (ariz.); Arizona; Distribution; Electricity; Interruption; Outage; Reliability; System Reliability Assessment; Maintenance; Overhead; Model; Interruptions; Regression; Flashover; Failures; Performance; Hurricanes
El-Anwar, Omar. (2013). Advancing Optimization of Hybrid Housing Development Plans Following Disasters: Achieving Computational Robustness, Effectiveness, and Efficiency. Journal Of Computing In Civil Engineering, 27(4), 358 – 369.
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Abstract
Following disasters, displaced families often face significant challenges to move from temporary to permanent housing. The Federal Emergency Management Agency is exploring alternative housing pilot programs to evaluate the possibility of providing quickly deployable, affordable housing that can serve both as temporary and permanent housing. Because of the complexities and costs associated with these programs, it is impractical to assume that accelerated permanent housing can fully replace the need for traditional temporary housing, especially in cases of large-scale displacements. A novel methodology was developed to evaluate the socioeconomic benefits of candidate configurations of hybrid housing plans, which incorporates both temporary and accelerated permanent housing developments. This paper presents the computational implementation and performance analysis of this novel methodology to offer a practical decision-support tool to emergency planners. To this end, genetic algorithms and integer-programming optimization models are formulated, and their performances are analyzed based on their effectiveness, efficiency, and robustness. In lieu of developing the integer-programming model, the paper also presents a linear formulation that overcomes the need to use logical operations to model fixed and variable cost components for developing housing projects. Results show the superior performance of integer programming, whereas genetic algorithms offer higher modeling flexibility.
Keywords
Decision Support Systems; Emergency Management; Genetic Algorithms; Integer Programming; Advancing Optimization; Hybrid Housing Development Plans Following Disasters; Achieving Computational Robustness; Achieving Computational Effectiveness; Achieving Computational Efficiency; Federal Emergency Management Agency; Housing Pilot Programs; Temporary Housing; Permanent Housing Developments; Decision-support Tool; Emergency Planners; Integer-programming Optimization Models; Logical Operations; Optimization; Disasters; Housing; Social Factors; Economic Factors; Computation; Hybrid Methods; Disaster Recovery; Accelerated Permanent Housing; Socioeconomic Welfare; Robustness; Effectiveness; Computational Efficiency; 0
Won, Jongsung; Lee, Ghang; Dossick, Carrie; Messner, John. (2013). Where to Focus for Successful Adoption of Building Information Modeling within Organization. Journal Of Construction Engineering And Management, 139(11).
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Abstract
Suggestions abound for successful adoption of building information modeling (BIM); however, a company with limited resources cannot adopt them all. The factors that have top management priority for successful accomplishment of a task are termed critical success factors (CSFs). This paper aims to derive the CSFs for four questions commonly asked by companies in the first wave of BIM adoption: (1)What are the CSFs for adopting BIM in a company? (2)What are the CSFs for selecting projects to deploy BIM? (3)What are the CSFs for selecting BIM services? (4)What are the CSFs for selecting company-appropriate BIM software applications? A list of consideration factors was collected for each question, based on a literature review, and then refined through face-to-face interviews based on experiences of BIM experts. An international survey was conducted with leading BIM experts. From the 206 distributed surveys, 52 responses from four continents were collected. This study used quantitative data analysis to derive a manageable number (4-10) of CSFs for each category from dozens of anecdotal consideration factors. The derived CSFs are expected to be used as efficient metrics for evaluating and managing the level of BIM adoption and as a basis for developing BIM evaluation models in the future.
Keywords
Architectural Cad; Building Information Modeling; Bim; Critical Success Factors; Csf; Management; Building Information Models; Organizations; Computer Software; Building Information Modeling (bim); Critical Success Factor (csf); Organizational Strategy; Bim Software Application; Bim Service; Bim-assisted Project; Information Technologies
El-Anwar, Omar; Chen, Lei. (2014). Maximizing the Computational Efficiency of Temporary Housing Decision Support Following Disasters. Journal Of Computing In Civil Engineering, 28(1), 113 – 123.
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Abstract
Postdisaster temporary housing has long been a challenging problem because of its interlinked socioeconomic, political, and financial dimensions. A significant need for automated decision support was obvious to address this problem. Previous research achieved considerable advancements in developing optimization models that can quantify and optimize the impacts of temporary housing decisions on the socioeconomic welfare of displaced families and total public expenditures on temporary housing as well as other objectives. However, the computational complexity of these models hindered its practical use and adoption by emergency planners. This article analyzes the computational efficiency of the current implementation of the most advanced socioeconomic formulation of the temporary housing problem, which uses integer programming. Moreover, it presents the development of a customized variant of the Hungarian algorithm that has a superior computational performance while maintaining the highest quality of solutions. An application example is presented to demonstrate the unique capabilities of the new algorithm in solving large-scale problems.
Keywords
Decision Support Systems; Emergency Management; Integer Programming; Computational Efficiency; Temporary Housing Decision Support Following Disasters; Financial Dimensions; Political Dimensions; Socioeconomic Dimensions; Socioeconomic Welfare; Emergency Planners; Socioeconomic Formulation; Hungarian Algorithm; Multiobjective Optimization; Maeviz-hazturk; Housing; Computation; Disasters; Temporary Structures; Temporary Housing; Optimization; Disaster Management
Migliaccio, G. C.; Bogus, Susan M.; Cordova-Alvidrez, A. A. (2014). Techniques for Continuous Improvement of Quality of Data Collection in Systems of Capital Infrastructure Management. Journal Of Construction Engineering And Management, 140(4).
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Abstract
oLa infraestructura del transporte es una de las mas grandes inversiones que realizan los gobiernos. Las agencias gubernamentales de transporte administran este capital y utilizan la informacion de las condiciones de este para decidir la programacion y tipo de mantenimiento y recursos a ejercer. Para recolectar la informacion pertinente, las agencias emplean evaluadores adiestrados para evaluar la infraestructura, ya sea en sitio o analizando fotografias y/o videos. Las evaluaciones visuales son empleadas para inspeccionar las condiciones de la infraestructura, incluyendo el desgaste de la superficie de los caminos y carreteras. Este articulo describe un Data Quality Assessment & Improvement Framework (DQAIF) (Sistema de Evaluacion y Mejora de la Calidad de la Informacion) para medir y controlar los datos de los evaluadores del deterioro de carreteras, al controlar el criterio de estos. El DQAIF es en un proceso ciclico de Mejora Continua de Calidad compuesto por: a)la evaluacion del nivel de acuerdo entre evaluadores -por medio del analisis estadistico (inter-rater agreement analysis), b)la evaluacion de la consistencia a traves del tiempo -mediante analisis de regresion lineal, y c)la implementacion de practicas gerenciales para mejorar los resultados mostrados en las evaluaciones anteriores. Se llevo a cabo un estudio de caso para validar el sistema propuesto. Los resultados mostraron que el DQAIF es efectivo para identificar y resolver problemas de la calidad de los datos obtenidos en las inspecciones de infraestructura. Con este sistema se garantiza la reduccion del riesgo de la subjetividad y asi aplicar acciones de mantenimiento mas oportunas. El DQAIF puede ser empleado en un programa de gerencia de infraestructura o en cualquier programa de ingenieria en donde la informacion esta sujeta al juicio o criterio personal de los individuos que realizan la evaluacion. Este proceso puede ser adaptado, incluso, para evaluar el desempeno de sistemas automatizados de evaluacion de pavimentos.
Keywords
Manual Pavement Distress; Quality Control; Pavement Management; Inspection; Quantitative Analysis; Data Collection; Assets; Reliability; Construction Materials And Methods
D’Incognito, Maria; Costantino, Nicola; Migliaccio, Giovanni C. (2015). Actors and Barriers to the Adoption of LCC And LCA Techniques in the Built Environment. Built Environment Project And Asset Management, 5(2), 202 – 216.
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Abstract
Purpose - The purpose of this paper is to evaluate the existing barriers to the slow adoption of Life Cycle Assessment (LCA) and Life Cycle Costing (LCC) in construction, and the main responsible actors. Design/methodology/approach - The research design is based on a two-phase approach. First, the existing literature was studied through a multiple-step content analysis (CA) approach, which combined unsupervised concept mapping with computer aided CA. Using a relational CA approach, statistical-based analysis tools were initially used to identify the relationships between actors and barriers. Later, a Delphi study was administered to a panel of experts, to triangulate, validate, and refine the initial results. Findings - The study revealed that organizational culture is the most relevant barrier, and that clients and professionals are the actors that predominantly influence the adoption of LCC and LCA in projects. Technical and financial barriers, such as the lack and quality of input data and the high costs of implementation are also deemed relevant. Research limitations/implications - The CA was performed by a single rater on a sample that included 50 papers in English language. Future research may focus on enlarging the sample, extending it to other languages, and linking the source (or the expert) to their professional context to evaluate geographical differences in barriers. Originality/value - The adopted approach gives new insights on the relationships behind the rejection of LCA and LCC suggesting that solutions at the organizational level may be more effective than technical ones.
Keywords
Construction; Innovation; Content Analysis; Sustainability; Organizational Culture; Lca; Lcc; Life Cycle Management; Innovations; Life Cycle Costs; Experts; Software; Corporate Culture; Concept Mapping; Urban Environments; Computer Aided Mapping; Life Cycles; Life Cycle Engineering; Decision Making; Organizational Aspects; Supply Chains; Research Design; Professionals; Construction Industry; Construction Costs; Life Cycle Analysis; Urban Areas; English Language; Barriers; Regulation Of Financial Institutions; Life Cycle Assessment
Vitro, Kristen A.; Whittington, Jan. (2015). The Cloud beneath the Clouds. Planning, 81(1), 35 – 35.
Abstract
The article discusses the proliferation of cloud computing data centers in Seattle, Washington. It also discusses the reasons behind the selection of the city by cloud computing data centers as site locations which include the availability of inexpensive but abundant sources of electricity, classification of dams as a critical infrastructure, and cooler climate. Another reason discussed is the planning and economic development practiced by municipalities to attract businesses in the area.
Keywords
Cloud Computing; Server Farms (computer Network Management); Industrial Location; Infrastructure (economics); Urban Planning; Economic Development; Seattle (wash.); Washington (state)