Kang, Mingyu; Moudon, Anne Vernez; Kim, Haena; Boyle, Linda Ng. (2019). Intersections and Non-Intersections: A Protocol for Identifying Pedestrian Crash Risk Locations in GIS. International Journal Of Environmental Research And Public Health, 16(19).
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Abstract
Intersection and non-intersection locations are commonly used as spatial units of analysis for modeling pedestrian crashes. While both location types have been previously studied, comparing results is difficult given the different data and methods used to identify crash-risk locations. In this study, a systematic and replicable protocol was developed in GIS (Geographic Information System) to create a consistent spatial unit of analysis for use in pedestrian crash modelling. Four publicly accessible datasets were used to identify unique intersection and non-intersection locations: Roadway intersection points, roadway lanes, legal speed limits, and pedestrian crash records. Two algorithms were developed and tested using five search radii (ranging from 20 to 100 m) to assess the protocol reliability. The algorithms, which were designed to identify crash-risk locations at intersection and non-intersection areas detected 87.2% of the pedestrian crash locations (r: 20 m). Agreement rates between algorithm results and the crash data were 94.1% for intersection and 98.0% for non-intersection locations, respectively. The buffer size of 20 m generally showed the highest performance in the analyses. The present protocol offered an efficient and reliable method to create spatial analysis units for pedestrian crash modeling. It provided researchers a cost-effective method to identify unique intersection and non-intersection locations. Additional search radii should be tested in future studies to refine the capture of crash-risk locations.
Keywords
Traffic Crash; Walking; Collisions; Accidents; Models; Pedestrian Safety; Spatial Autocorrelation; Algorithm
Cheng, Renée. (2020). Opinion: Change Agency, Value Change. Architect, 109(9), 20 – 20.
Keywords
Attitude Change (psychology); Air Flow; Hand Washing
Shang, Luming; Aziz, Ahmed M. Abdel. (2020). Stackelberg Game Theory-Based Optimization Model for Design of Payment Mechanism in Performance-Based PPPs. Journal Of Construction Engineering And Management, 146(4).
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Abstract
Payment mechanisms lie at the heart of public-private partnership (PPP) contracts. A good design of the payment mechanism should consider the owner's goals in the project, allocate risks appropriately to stakeholders, and assure satisfactory performance by providing reasonable compensation to the private developer. This paper proposes a Stackelberg game theory-based model to assist public agencies in designing payment mechanisms for PPP transportation projects. The interests of both public and private sectors are considered and reflected by a bilevel objective function. The model aims to search for solutions that maximize a project's overall performance for the sake of social welfare while simultaneously maximizing return for the sake of private investment. A variable elimination method and genetic algorithm are used to solve the optimization model. A case study based on a real PPP project is discussed to validate the effectiveness of the proposed model. The solutions provided by the model reveal that the optimal payment mechanism structure could be established such that it would satisfy owners' requirements for overall project performance while optimizing project total payments to contractors.
Keywords
Construction Industry; Contracts; Financial Management; Game Theory; Genetic Algorithms; Investment; Optimisation; Organisational Aspects; Project Management; Public Administration; Transportation; Public-private Partnership Contracts; Good Design; Private Developer; Stackelberg Game Theory-based Model; Ppp Transportation Projects; Public Sectors; Private Sectors; Private Investment; Ppp Project; Optimal Payment Mechanism Structure; Project Performance; Project Total Payments; Stackelberg Game Theory-based Optimization Model; Performance-based Ppps; Public-private Partnerships; Analytic Hierarchy Process; Weighted Sum Method; Multiobjective Optimization; Algorithm; Incentives; Projects; Network; Success; Branch
Wang, Lan; Zhang, Surong; Yang, Zilin; Zhao, Ziyu; Moudon, Anne Vernez; Feng, Huasen; Liang, Junhao; Sun, Wenyao; Cao, Buyang. (2021). What County-level Factors Influence Covid-19 Incidence in the United States? Findings from the First Wave of the Pandemic. Cities, 118.
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Abstract
Effective control of the COVID-19 pandemic via appropriate management of the built environment is an urgent issue. This study develops a research framework to explore the relationship between COVID-19 incidence and influential factors related to protection of vulnerable populations, intervention in transmission pathways, and provision of healthcare resources. Relevant data for regression analysis and structural equation modeling is collected during the first wave of the pandemic in the United States, from counties with over 100 confirmed cases. In addition to confirming certain factors found in the existing literature, we uncover six new factors significantly associated with COVID-19 incidence. Furthermore, incidence during the lockdown is found to significantly affect incidence after the reopening, highlighting that timely quarantining and treating of patients is essential to avoid the snowballing transmission over time. These findings suggest ways to mitigate the negative effects of subsequent waves of the pandemic, such as special attention of infection prevention in neighborhoods with unsanitary and overcrowded housing, minimization of social activities organized by neighborhood associations, and contactless home delivery service of healthy food. Also worth noting is the need to provide support to people less capable of complying with the stay-at-home order because of their occupations or socio-economic disadvantage.
Keywords
Pandemics; Covid-19; Covid-19 Pandemic; Infection Prevention; Stay-at-home Orders; Structural Equation Modeling; United States; Communicable Disease Prevention; Influential Factors; Lockdown; Structural Equation Modeling (sem); Prevalence; Disease; Healthy Food; Social Activities; Counties; Neighborhoods; Housing; Built Environment; Prevention; Minimization; Socioeconomic Factors; Intervention; Health Care; Vulnerability; Occupations; Coronaviruses; Food Service; Disease Transmission; United States--us
Van Den Wymelenberg, Kevin; Inanici, Mehlika; Johnson, Peter. (2010). The Effect of Luminance Distribution Patterns on Occupant Preference in a Daylit Office Environment. Leukos, 7(2), 103 – 122.
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Abstract
New research in daylighting metrics and developments in validated digital High Dynamic Range (HDR) photography techniques suggest that luminance based lighting controls have the potential to provide occupant satisfaction and energy saving improvements over traditional illuminance based lighting controls. This paper studies occupant preference and acceptance of patterns of luminance using HDR imaging and a repeated measures design methodology in a daylit office environment. Three existing luminance threshold analysis methods [method1: predetermined absolute luminance threshold (for example, 2000 cd/m(2)), method2: scene based mean luminance threshold, and method3: task based mean luminance threshold] were studied along with additional candidate metrics for their ability to explain luminance variability of 18 participant assessments of 'preferred' and 'just disturbing' scenes under daylighting conditions. Per-pixel luminance data from each scene were used to calculate Daylighting Glare Probability (DGP), Daylight Glare Index (DGI), and other candidate metrics using these three luminance threshold analysis methods. Of the established methods, the most consistent and effective metrics to explain variability in subjective responses were found to be; mean luminance of the task (using method3; (adj)r(2) = 0.59), mean luminance of the entire scene (using method2; (adj)r(2) = 0.44), and DGP using 2000 cd/m(2) as a glare source identifier (using method1; (adj)r(2) = 0.41). Of the 150 candidate metrics tested, the most effective was the 'mean luminance of the glare sources', where the glare sources were identified as 7* the mean luminance of the task position ((adj)r(2) = 0.64). Furthermore, DGP consistently performed better than DGI, confirming previous findings. 'Preferred' scenes never had more than similar to 10 percent of the field of view (FOV) that exceeded 2000 cd/m(2). Standard deviation of the entire scene luminance also proved to be a good predictor of satisfaction with general visual appearance.
Keywords
Glare; Daylight Metrics; Luminance Based Lighting Controls; Discomfort Glare; Occupant Preference; High Dynamic Range
Gatti, U.; Migliaccio, G.; Bogus, S.M.; Priyadarshini, S.; Scharrer, A. (2013). Using Workforce’s Physiological Strain Monitoring to Enhance Social Sustainability of Construction. Journal Of Architectural Engineering, 19(3), 179 – 85.
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Abstract
Sustainability is often described in terms of the triple bottom line, which refers to its environmental, economic, and social dimensions. However, the economic and environmental impacts of decisions have been easier to determine than have been the social impacts. One area of social sustainability that is particularly applicable to construction projects is that of construction workforce safety and well-being. This is a critical part of sustainability, and a socially sustainable construction industry needs to consider the safety and well-being of construction workers. However, construction activities are generally physically demanding and performed in harsh environments. Monitoring workers' physical strain may be an important step toward enhancing the social sustainability of construction. Recently introduced physiological status monitors (PSMs) have overcome the past limitations, allowing physical strain to be monitored without hindering workers' activities. Three commercially available PSMs have been selected and tested to assess their reliability in monitoring a construction workforce during dynamic activities. The results show that two of the PSMs are suitable candidates for monitoring the physiological conditions of construction workers. A survey was also conducted among industry practitioners to gain insight into industry needs and challenges for physical strain monitoring.
Keywords
Construction Industry; Environmental Factors; Labour Resources; Occupational Safety; Socio-economic Effects; Sustainable Development; Workforce Physiological Strain Monitoring; Social Sustainability; Socioeconomic Impacts; Environmental Impacts; Social Impacts; Construction Projects; Construction Workforce Safety; Physical Strain
Kim, Sang-Chul; Kim, Yong-Woo. (2014). Computerized Integrated Project Management System for a Material Pull Strategy. Journal Of Civil Engineering And Management, 20(6), 849 – 863.
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Abstract
The purpose of this paper is to present a computerized integrated project management system and report results of a survey on the effectiveness of the system. The system consists of a scheduling system, material management system, labor/equipment system, and safety/quality control system. The backbone system is a scheduling system that adopts a production planning system and a project scheduling system. The lowest level in the scheduling system is a daily work management system, which is linked to each functional management system (i.e. material management system, labor/equipment system, and safety/quality control system). The paper focuses on the material management and scheduling systems to implement a material pull system to reduce material inventories on site. Details of material management and scheduling systems are discussed, and a sample application is presented to demonstrate the features of the proposed computer application system. The paper presents practitioners and researchers with a practical tool to integrate material management and scheduling systems for site personnel.
Keywords
Construction; Lean Construction; Material Management System; Integrated System; Daily Work Management
Sprague, Tyler S. (2015). Products of Place the Era of Reinforced-Concrete Skyscrapers in Seattle, 1921-1931. Pacific Northwest Quarterly, 106(3), 107 – 119.
Ochsner, Jeffrey Karl. (2016). Meditations on the Empty Chair: The Form of Mourning and Reverie. American Imago, 73(2), 131 – 163.
Keywords
Vietnam-veterans-memorial; Photography; Thoughts
Shakouri, Mahmoud; Lee, Hyun Woo; Kim, Yong-woo. (2017). A Probabilistic Portfolio-Based Model for Financial Valuation of Community Solar. Applied Energy, 191, 709 – 726.
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Abstract
Community solar has emerged in recent years as an alternative to overcome the limitations of individual rooftop photovoltaic (PV) systems. However, there is no existing model available to support probabilistic valuation and design of community solar based on the uncertain nature of system performance over time. In response, the present study applies the Mean-Variance Portfolio Theory to develop a probabilistic model that can be used to increase electricity generation or reduce volatility in community solar. The study objectives include identifying the sources of uncertainties in PV valuation, developing a probabilistic model that incorporates the identified uncertainties into portfolios, and providing potential investors in community solar with realistic financial indicators. This study focuses on physical, environmental, and financial uncertainties to construct a set of optimized portfolios. Monte Carlo simulation is then performed to calculate the return on investment (ROI) and the payback period of each portfolio. Lastly, inclusion vs. exclusion of generation and export tariffs are compared for each financial indicator. The results show that the portfolio with the maximum output offers the highest ROI and shortest payback period while the portfolio with the minimum risk indicates the lowest ROI and longest payback period. This study also reveals that inclusion of tariffs can significantly influence the financial indicators, even more than the other identified uncertainties. (C) 2017 Elsevier Ltd. All rights reserved.
Keywords
Solar Energy; Photovoltaic Power Systems; Monte Carlo Method; Market Volatility; Energy Economics; Community Solar; Monte Carlo Simulation; Photovoltaic Systems; Portfolio Theory; Uncertainty; Environmental Uncertainties; Financial Indicator; Financial Uncertainties; Physical Uncertainties; Identified Uncertainties; Probabilistic Model; Mean-variance Portfolio Theory; Probabilistic Valuation; Individual Rooftop Photovoltaic Systems; Financial Valuation; Probabilistic Portfolio-based Model; Investment; Monte Carlo Methods; Photovoltaic Cells; Risk Analysis; Tariffs; Resolution Lidar Data; Electricity Consumption; Pv Systems; Autoregressive Models; Potential Assessment; Generation Systems; Neural-networks; Energy; Buildings; Economic Theory; Electricity; Exports; Probabilistic Models; Risk