Application of a building cost estimation model to the appraisal of the churches damaged by earthquakes in Lorca (Spain)

The objective of this paper is the development of a building cost estimation model whose purpose is to quickly and precisely evaluate rebuilding costs for historic heritage buildings affected by catastrophic events. Specifically, this study will be applied to the monumental buildings owned by the Catholic Church that were affected by two earthquakes on May 11, 2011 in the town of Lorca. To estimate the initial total replacement cost new, calculation model will be applied which, on the one hand, will use two-dimensional metric exterior parameters and, on the other, three-dimensional interior cubic parameters. Based on the total of the analyzed buildings, and considering damage caused by the seismic event, the final reconstruction cost for the building units ruined by the earthquakes can be estimated. The proposed calculation model can also be applied to other emergency scenarios and situations for the quick estimation of construction costs necessary for rebuilding historic heritage buildings which have been affected by catastrophic events that deteriorate or ruin their structural or constructive configuration.

Econometric techniques for estimating construction demand in Australia

This study aims to develop reliable demand estimation models, at both national and regional levels, for the Australia’s construction market. The developed models would benefit the industry by serving as a reliable aid to policy in the areas of tendering, pricing, resource allocating, labour and workload planning.

Organizational change in the public sector: augmenting the demand control model to predict employee outcomes under New Public Management

This study identifies the environmental and personal characteristics that predict employee outcomes within an Australian public sector organization that had, under New Public Management (NPM), implemented a variety of practices traditionally found in the private sector. These are more results-oriented, and their adoption can be accompanied by increased strain for employees. The current investigation was guided by two complementary theories, the Demand Control Support (DCS) model and Conservation of Resources (COR) theory, and sought to examine the benefits of building on the DCS to include both situation-specific stressors and internal coping resources. Survey responses from 1,155 employees were analysed. The hierarchical regression analyses indicated that both external and employee-centred variables made significant contributions to variations in psychological health, job satisfaction, and organizational commitment. The external resources, work based support and, to a lesser extent, job control, predicted relatively large proportions of the variance in the target variables. The situation-specific stressors, particularly those involving harmful management practices (e.g., insufficient time to do job as well as you would like, lack of recognition for good work), made significant contributions to the outcome measures and generally supported the process of augmenting the generic components of the DCS with more situation-specific variables. In terms of internal resources, problem and emotion-based coping improved the capacity of the model to predict psychological health. The results suggest that the impact of NPM can be ameliorated by incorporating the dimensions of the augmented DCS and coping resources into the change programme.

Improving work and life balance : building a multilevel model of work-life balance focusing on group structure and relational job design

One in five Australian workers believes that work doesn’t fit well with their family and social commitments. Concurrently, organisations are recognising that to stay competitive they need policies and practices that support the multiple aspects of employees’ lives. Many employees work in group environments yet there is currently little group level work-life balance research. This paper proposes a new theoretical framework developed to understand the design of work groups to better facilitate work-life balance. This new framework focuses on task and relational job designs, group structures and processes and workplace culture.

Advanced occupant behavioural features of the building-EXODUS evacuation model

The purpose of this paper is to describe and demonstrate some of the advanced behavioral features currently being developed for the building-EXODUS evacuation model. These advanced features involve the ability to specify roles for particular individuals during the evacuation. With these enhancements to the Behavioral Sub model of building-EXODUS, it is possible to include a number of procedural and behavioral aspects previously ignored in evacuation simulations. These include the behavioral aspect of group bonding, the procedural aspects involved with the role of the fire warden and rescue operations undertaken by the fire services. The importance of these enhancements are discussed and demonstrated through three simple simulations.

Rural nursing and health care reforms : building a social model

This article explores recent shifts in health-care policy and the implications for rural nursing in Australia. Health-care reforms have resulted in the implementation of a 'market forces' ideology, creating tensions between economic imperatives and the need for equity and greater access in rural service delivery. New models of health-service delivery have been developed that have significant implications for the way rural health care is defined, practised and received. The issues surrounding the context of rural nursing practice and service delivery are discussed.

Bias from ignoring price dispersion in demand estimation

Consumers often pay different prices for the same product bought in the same store at the same time. However, the demand estimation literature has ignored that fact using, instead, aggregate measures such as the “list” or average price. In this paper we show that this will lead to biased price coefficients. Furthermore, we perform simple comparative statics simulation exercises for the logit and random coefficient models. In the “list” price case we find that the bias is larger when discounts are higher, proportion of consumers facing discount prices is higher and when consumers are more unwilling to buy the product so that they almost only do it when facing discount. In the average price case we find that the bias is larger when discounts are higher, proportion of consumers that have access to discount are similar to the ones that do not have access and when consumers willingness to buy is very dependent on idiosyncratic shocks. Also bias is less problematic in the average price case in markets with a lot of bargain deals, so that prices are as good as individual. We conclude by proposing ways that the econometrician can reduce this bias using different information that he may have available.

Hybrid Water Demand Forecasting Model Associating Artificial Neural Network with Fourier Series

This paper addressed the problem of water-demand forecasting for real-time operation of water supply systems. The present study was conducted to identify the best fit model using hourly consumption data from the water supply system of Araraquara, Sa approximate to o Paulo, Brazil. Artificial neural networks (ANNs) were used in view of their enhanced capability to match or even improve on the regression model forecasts. The ANNs used were the multilayer perceptron with the back-propagation algorithm (MLP-BP), the dynamic neural network (DAN2), and two hybrid ANNs. The hybrid models used the error produced by the Fourier series forecasting as input to the MLP-BP and DAN2, called ANN-H and DAN2-H, respectively. The tested inputs for the neural network were selected literature and correlation analysis. The results from the hybrid models were promising, DAN2 performing better than the tested MLP-BP models. DAN2-H, identified as the best model, produced a mean absolute error (MAE) of 3.3 L/s and 2.8 L/s for training and test set, respectively, for the prediction of the next hour, which represented about 12% of the average consumption. The best forecasting model for the next 24 hours was again DAN2-H, which outperformed other compared models, and produced a MAE of 3.1 L/s and 3.0 L/s for training and test set respectively, which represented about 12% of average consumption. DOI: 10.1061/(ASCE)WR.1943-5452.0000177. (C) 2012 American Society of Civil Engineers.

Beyond the tree of texts: Building an empirical model of scribal variation through graph analysis of texts and stemmata

Stemmatology, or the reconstruction of the transmission history of texts, is a field that stands particularly to gain from digital methods. Many scholars already take stemmatic approaches that rely heavily on computational analysis of the collated text (e.g. Robinson and O’Hara 1996; Salemans 2000; Heikkilä 2005; Windram et al. 2008 among many others). Although there is great value in computationally assisted stemmatology, providing as it does a reproducible result and allowing access to the relevant methodological process in related fields such as evolutionary biology, computational stemmatics is not without its critics. The current state-of-the-art effectively forces scholars to choose between a preconceived judgment of the significance of textual differences (the Lachmannian or neo-Lachmannian approach, and the weighted phylogenetic approach) or to make no judgment at all (the unweighted phylogenetic approach). Some basis for judgment of the significance of variation is sorely needed for medieval text criticism in particular. By this, we mean that there is a need for a statistical empirical profile of the text-genealogical significance of the different sorts of variation in different sorts of medieval texts. The rules that apply to copies of Greek and Latin classics may not apply to copies of medieval Dutch story collections; the practices of copying authoritative texts such as the Bible will most likely have been different from the practices of copying the Lives of local saints and other commonly adapted texts. It is nevertheless imperative that we have a consistent, flexible, and analytically tractable model for capturing these phenomena of transmission. In this article, we present a computational model that captures most of the phenomena of text variation, and a method for analysis of one or more stemma hypotheses against the variation model. We apply this method to three ‘artificial traditions’ (i.e. texts copied under laboratory conditions by scholars to study the properties of text variation) and four genuine medieval traditions whose transmission history is known or deduced in varying degrees. Although our findings are necessarily limited by the small number of texts at our disposal, we demonstrate here some of the wide variety of calculations that can be made using our model. Certain of our results call sharply into question the utility of excluding ‘trivial’ variation such as orthographic and spelling changes from stemmatic analysis.

Spatially-Explicit Testing of a General Aboveground Carbon Density Estimation Model in aWestern Amazonian Forest Using Airborne LiDAR

Mapping aboveground carbon density in tropical forests can support CO2 emissionmonitoring and provide benefits for national resource management. Although LiDAR technology has been shown to be useful for assessing carbon density patterns, the accuracy and generality of calibrations of LiDAR-based aboveground carbon density (ACD) predictions with those obtained from field inventory techniques should be intensified in order to advance tropical forest carbon mapping. Here we present results from the application of a general ACD estimation model applied with small-footprint LiDAR data and field-based estimates of a 50-ha forest plot in Ecuador?s Yasuní National Park. Subplots used for calibration and validation of the general LiDAR equation were selected based on analysis of topographic position and spatial distribution of aboveground carbon stocks. The results showed that stratification of plot locations based on topography can improve the calibration and application of ACD estimation using airborne LiDAR (R2 = 0.94, RMSE = 5.81 Mg?C? ha?1, BIAS = 0.59). These results strongly suggest that a general LiDAR-based approach can be used for mapping aboveground carbon stocks in western lowland Amazonian forests.

Users guide for the wettime exposure estimation model.

Federal Highway Administration, Office of Engineering and Highway Operations Research and Development, McLean, Va.