El-Anwar, Omar; Chen, Lei. (2013). Computing a Displacement Distance Equivalent to Optimize Plans for Postdisaster Temporary Housing Projects. Journal Of Construction Engineering And Management, 139(2), 174 – 184.
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Abstract
Residence in temporary housing is a critical period for the social, economic, and psychological recovery of displaced families following disasters. Temporary housing locations define the displacement distance between families and their essential needs. The objective of this paper is to develop a novel methodology to capture the specific proximity needs and preferences of displaced families. This paper proposes a displacement distance equivalent as an objective metric to evaluate the performance of temporary housing locations in meeting the needs of displaced families. Moreover, the paper describes the development of an integer programming optimization model capable of optimizing temporary housing assignments to minimize total displacement distance equivalent while meeting budget constraints. The main contribution of this paper to the body of knowledge is in transforming the purpose of temporary housing programs from offering general accommodation to providing customized housing solutions tailored to the individual proximity needs of each household using the proposed displacement metric. In addition, the proposed optimization model enables decision makers to set budget constraints to ensure the economic feasibility of identified temporary housing solutions. DOI: 10.1061/(ASCE)CO. 1943-7862.0000601. (C) 2013 American Society of Civil Engineers.
Keywords
Disasters; Emergency Management; Integer Programming; Social Sciences; Displaced Families; Customized Housing Solutions; Decision Makers; Displacement Metric; Budget Constraints; Integer Programming Optimization Model; Objective Metric; Temporary Housing Locations; Post-disaster Temporary Housing Projects; Displacement Distance Equivalent Computation; Multiobjective Optimization; Optimization; Temporary Housing; Disaster Recovery; Displacement Distance; Housing Sites
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
Hong, Jinhyun; Shen, Qing. (2013). Residential Density and Transportation Emissions: Examining the Connection by Addressing Spatial Autocorrelation and Self-Selection. Transportation Research Part D-transport And Environment, 22, 75 – 79.
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Abstract
This paper examines the effect of residential density on CO2 equivalent from automobile using more specific emission factors based on vehicle and trip characteristics, and by addressing problems of spatial autocorrelation and self-selection. Drawing on the 2006 Puget Sound Regional Council Household Activity Survey data, the 2005 parcel and building database, the 2000 US Census data, and emission factors estimated using the Motor Vehicle Emission Simulator, we analyze the influence of residential density on road-based transportation emissions. In addition, a Bayesian multilevel model with spatial random effects and instrumental variables is employed to control for spatial autocorrelation and self-selection. The results indicate that the effect of residential density on transportation emissions is influenced by spatial correlation and self-selection. Our results still show, however, that increasing residential density leads to a significant reduction in transportation emissions. (C) 2013 Elsevier Ltd. All rights reserved.
Keywords
Urban Form; Travel; Transportation Emissions; Residential Density; Confounding By Location; Self-selection
Kang, Bumjoon; Moudon, Anne V.; Hurvitz, Philip M.; Reichley, Lucas; Saelens, Brian E. (2013). Walking Objectively Measured: Classifying Accelerometer Data with GPS and Travel Diaries. Medicine & Science In Sports & Exercise, 45(7), 1419 – 1428.
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Abstract
Purpose: This study developed and tested an algorithm to classify accelerometer data as walking or nonwalking using either GPS or travel diary data within a large sample of adults under free-living conditions. Methods: Participants wore an accelerometer and a GPS unit and concurrently completed a travel diary for seven consecutive days. Physical activity (PA) bouts were identified using accelerometry count sequences. PA bouts were then classified as walking or nonwalking based on a decision-tree algorithm consisting of seven classification scenarios. Algorithm reliability was examined relative to two independent analysts' classification of a 100-bout verification sample. The algorithm was then applied to the entire set of PA bouts. Results: The 706 participants' (mean age = 51 yr, 62% female, 80% non-Hispanic white, 70% college graduate or higher) yielded 4702 person-days of data and had a total of 13,971 PA bouts. The algorithm showed a mean agreement of 95% with the independent analysts. It classified PA into 8170 walking bouts (58.5 %) and 5337 nonwalking bouts (38.2%); 464 bouts (3.3%) were not classified for lack of GPS and diary data. Nearly 70% of the walking bouts and 68% of the nonwalking bouts were classified using only the objective accelerometer and GPS data. Travel diary data helped classify 30% of all bouts with no GPS data. The mean + SD duration of PA bouts classified as walking was 15.2 + 12.9 min. On average, participants had 1.7 walking bouts and 25.4 total walking minutes per day. Conclusions: GPS and travel diary information can be helpful in classifying most accelerometer-derived PA bouts into walking or nonwalking behavior.
Keywords
Walking; Algorithms; Decision Trees; Geographic Information Systems; Research Funding; Travel; Accelerometry; Diary (literary Form); Descriptive Statistics; Algorithm; Classification; Physical Activity; Walk Trip; Global Positioning Systems; Physical-activity; Environment; Behaviors; Validity; Location
Kim, Yong-Woo; Azari-N, Rahman; Yi, June-Seong; Bae, Jinwoo. (2013). Environmental Impacts Comparison between On-site vs. Prefabricated Just-in-Time (Prefab-JIT) Rebar Supply in Construction Projects. Journal Of Civil Engineering And Management, 19(5), 647 – 655.
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Abstract
In the on-site rebar delivery system, as the common method of rebar supply in the construction industry, reinforced steel bars are delivered in large batches from supplier's facilities through contractor's warehouse to the construction site. Rebars are then fabricated on-site and installed after assembly. In the new delivery system, called prefabrication Just-In-Time (prefab-JIT) system, the off-site cut and bend along with frequent rebar delivery to the site are applied in order to improve the process and increase its efficiency. The main objective of this paper is to assess and compare the environmental impacts resulting from the air emissions associated with the two rebar delivery systems in a case study construction project. Environmental impact categories of interest include global warming, acidification, eutrophication, and smog formation. A process-based cradle-to-gate life cycle assessment methodology is applied to perform the analysis. The results show that the prefab-JIT rebar delivery system causes less contribution to all mentioned environmental impact categories compared with a traditional on-site delivery system.
Keywords
Environmental Impact Analysis; Comparative Studies; Microfabrication; Construction Industry; Reinforcing Bars; Contractors; Product Life Cycle; Environmental Impacts; Life Cycle; On-site Rebar Delivery System; Prefab-jit; Bars; Contracts; Global Warming; Just-in-time; Prefabricated Construction; Product Life Cycle Management; Project Management; Rebar; Steel; Warehousing; Waste Reduction; Smog Formation; Eutrophication; Acidification; Air Emissions; Prefab-jit System; Construction Site; Contractors Warehouse; Reinforced Steel Bars; Construction Projects; Prefabricated Just-in-time Rebar Supply; Environmental Impacts Comparison; Process-based Cradle-to-gate Life Cycle Assessment Methodology; Energy; Products; Wood
Lee, Namhun; Dossick, Carrie S.; Foley, Sean P. (2013). Guideline for Building Information Modeling in Construction Engineering and Management Education. Journal Of Professional Issues In Engineering Education And Practice, 139(4), 266 – 274.
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Keywords
Buildings (structures); Computer Aided Instruction; Construction Industry; Educational Courses; Management Education; Structural Engineering Computing; Building Information Modeling; Construction Engineering And Management Education; Cem Education; Bim; Cem Curriculum
Maliszewski, Paul; Larson, Elisabeth; Perrings, Charles. (2013). Valuing the Reliability of the Electrical Power Infrastructure: A Two-Stage Hedonic Approach. Urban Studies, 50(1), 72 – 87.
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Abstract
The reliability of electrical power supply is amongst the conditions that inform house purchase decisions in all urban areas. Reliability depends in part on the conditions of the power generation and distribution infrastructures involved, and in part on environmental conditions. Its value to homeowners may be capitalised into the value of the house. In this paper, a hedonic pricing approach is used to estimate the capitalised value of the reliability offered by distribution infrastructures and the environmental conditions with which they interact in Phoenix, Arizona. A first stage estimates the impact of infrastructure and environmental conditions on reliability. In a second stage, the capitalised value of reliability from the marginal willingness to pay for reliability revealed by house purchase decisions is estimated and used to infer the value of both infrastructural characteristics and environmental conditions.
Keywords
Willingness-to-pay; Residential Property-values; Economic Valuation; Choice Experiment; Urban Wetlands; Air-quality; Benefits; Identifiability; Specification; Determinants
Migliaccio, Giovanni C.; Guindani, Michele; D’Incognito, Maria; Zhang, Linlin. (2013). Empirical Assessment of Spatial Prediction Methods for Location Cost-Adjustment Factors. Journal Of Construction Engineering & Management, 139(7), 858 – 869.
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Abstract
In the feasibility stage of a project, location cost-adjustment factors (LCAFs) are commonly used to perform quick order-of-magnitude estimates. Nowadays, numerous LCAF data sets are available in North America, but they do not include all locations. Hence, LCAFs for unsampled locations need to be inferred through spatial interpolation or prediction methods. Using a commonly used set of LCAFs, this paper aims to test the accuracy of various spatial prediction methods and spatial interpolation methods in estimating LCAF values for unsampled locations. Between the two regression-based prediction models selected for the study, geographically weighted regression analysis (GWR) resulted the most appropriate way to model the city cost index as a function of multiple covariates. As a direct consequence of its spatial nonstationarity, the influence of each single covariate differed from state to state. In addition, this paper includes a first attempt to determine if the observed variability in cost index values could be at least partially explained by independent socioeconomic variables. (C) 2013 American Society of Civil Engineers.
Keywords
Construction Industry; Interpolation; Regression Analysis; Socio-economic Effects; Spatial Prediction Methods; Location Cost-adjustment Factors; Empirical Assessment; Lcaf; Order-of-magnitude Estimates; North America; Unsampled Locations; Spatial Interpolation Methods; Geographically Weighted Regression Analysis; Gwr; Independent Socioeconomic Variables; Inflation; Indexes; Estimation; Geostatistics; Construction Costs; Planning; Budgeting
Armbruster, Ginger; Endicott-Popovsky, Barbara; Whittington, Jan. (2013). Threats to Municipal Information Systems Posed by Aging Infrastructure. International Journal Of Critical Infrastructure Protection, 6(3-4), 123 – 131.
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Abstract
State and local governments across the United States are leveraging the Internet and associated technologies to dramatically change the way they offer public services. While they are motivated to capture efficiencies, the public entities increasingly rely on information systems that are dependent on energy and related civil structures. This reliance is incongruous with the widespread awareness of aging infrastructure - decaying for lack of investment - in cities across the United States. Important questions that come up in this environment of persistent expansion of the use of digital assets are the following: What threat does aging infrastructure pose to governmental reliance on computing infrastructures? How are local governments responding to this threat? Are the solutions posed appropriate to the problem, or do they pose new and different threats? This paper uses a case involving the disruption of a local government data center due to the failure of an electrical bus to illustrate how the threats of aging infrastructure grow, quietly and steadily, into emergencies, on par with the catastrophic events encountered in the context of critical infrastructure protection. The decisions precipitating the disruption are routine, borne of circumstances shared by agencies that are pressed to maintain services with scarce resources. Patterns of capital investment and management explain the emergence of crises in routine operations. If, as in the case described in this paper, deferred maintenance motivates public agents to explore private cloud services, then governments may solve several problems, but may also be exposed to new risks as they enter into arrangements from which they are unable to exit. (C) 2013 Elsevier B.V. All rights reserved.
Keywords
Aging Infrastructure; Municipal Data Center; Capital Improvement; Interdependence
Moudon, Anne Vernez; Drewnowski, Adam; Duncan, Glen E.; Hurvitz, Philip M.; Saelens, Brian E.; Scharnhorst, Eric. (2013). Characterizing the Food Environment: Pitfalls and Future Directions. Public Health Nutrition, 16(7), 1238 – 1243.
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Abstract
Objective: To assess a county population's exposure to different types of food sources reported to affect both diet quality and obesity rates. Design: Food permit records obtained from the local health department served to establish the full census of food stores and restaurants. Employing prior categorization schemes which classified the relative healthfulness of food sources based on establishment type (i.e. supermarkets v. convenience stores, or full-service v. fast-food restaurants), food establishments were assigned to the healthy, unhealthy or undetermined groups. Setting: King County, WA, USA. Subjects: Full census of food sources. Results: According to all categorization schemes, most food establishments in King County fell into the unhealthy and undetermined groups. Use of the food permit data showed that large stores, which included supermarkets as healthy food establishments, contained a sizeable number of bakery/delis, fish/meat, ethnic and standard quick-service restaurants and coffee shops, all food sources that, when housed in a separate venue or owned by a different business establishment, were classified as either unhealthy or of undetermined value to health. Conclusions: To fully assess the potential health effects of exposure to the extant food environment, future research would need to establish the health value of foods in many such common establishments as individually owned grocery stores and ethnic food stores and restaurants. Within-venue exposure to foods should also be investigated.
Keywords
Food Chemistry; Obesity; Health Boards; Dietary Supplements; Food Cooperatives; Restaurant Reviews; Coffee Shops; Food Consumption; Food Quality; Census Of Food Sources; Exposure; Health Value; Neighborhood Characteristics; Store Availability; Racial Composition; Physical-activity; Weight Status; Restaurants; Association; Proximity; Access; Business Enterprises; Fast Food Restaurants; Fish; Grocery Stores; Healthy Diet; Meat; Nutritional Adequacy; Supermarkets