Strategic Management Practices in the Construction Industry : a Dynamic Capabilities View

This book is an empirical study of strategic management practices in the construction industry. It examines the dynamic capabilities paradigm within the context of the Indonesian construction industry. The characteristics of asset-capability combinations were found to be significant determinants of the competitive advantage of the Indonesian construction enterprises, and that such advantage sequentially contributes to organizational performance. In doing so, this study fills an important gap in the empirical literature and reinforces the dynamic capabilities framework’s recognition as a rigorous theory of strategic management. As the dynamic capabilities framework can work in the context of Indonesia, it suggests that the framework has potential applicability in other emerging and developing countries

Field-of-view, detection range, and false alarm trade-offs in vision-based aircraft detection

This paper presents a survey of previously presented vision based aircraft detection flight test, and then presents new flight test results examining the impact of camera field-of view choice on the detection range and false alarm rate characteristics of a vision-based aircraft detection technique. Using data collected from approaching aircraft, we examine the impact of camera fieldof-view choice and confirm that, when aiming for similar levels of detection confidence, an improvement in detection range can be obtained by choosing a smaller effective field-of-view (in terms of degrees per pixel).

Spatial and temporal clusters of Barmah Forest virus disease in Queensland, Australia

Objective To identify the spatial and temporal clusters of Barmah Forest virus (BFV) disease in Queensland in Australia, using geographical information systems (GIS) and spatial scan statistic (SaTScan). Methods We obtained BFV disease cases, population and statistical local areas boundary data from Queensland Health and Australian Bureau of Statistics respectively during 1992-2008 for Queensland. A retrospective Poisson-based analysis using SaTScan software and method was conducted in order to identify both purely spatial and space-time BFV disease high-rate clusters. A spatial cluster size of a proportion of the population and a 200km circle radius and varying time windows from 1 month to 12 months were chosen (for the space-time analysis). Results The spatial scan statistic detected a most likely significant purely spatial cluster (including 23 SLAs) and a most likely significant space-time cluster (including 24 SLAs) in approximately the same location. Significant secondary clusters were also identified from both the analyses in several locations. Conclusions This study provides evidence of the existence of statistically significant BFV disease clusters in Queensland, Australia. The study also demonstrated the relevance and applicability of SaTScan in analysing on-going surveillance data to identify clusters to facilitate the development of effective BFV disease prevention and control strategies in Queensland, Australia.

Phylogeography of Echinocladius martini Cranston (Diptera: Chironomidae) in closed forest streams of eastern Australia

The eastern Australian rainforests have experienced several cycles of range contraction and expansion since the late Miocene that are closely correlated with global glaciation events. Together with ongoing aridification of the continent, this has resulted in current distributions of native closed forest that are highly fragmented along the east coast. Several closed forest endemic taxa exhibit patterns of population genetic structure that are congruent with historical isolation of populations in discrete refugia and reflect evolutionary histories dramatically affected by vicariance. Currently, limited data are available regarding the impact of these past climatic fluctuations on freshwater invertebrate taxa. The non-biting midge species Echinocladius martini Cranston is distributed along the east coast and inhabits predominantly montane streams in closed forest habitat. Phylogeographic structure in E. martini was resolved here at a continental scale by incorporating data from a previous pilot study and expanding the sampling design to encompass populations in the Wet Tropics of north-eastern Queensland, south-east Queensland, New South Wales and Victoria. Patterns of phylogeographic structure revealed several deeply divergent mitochondrial lineages from central and south-eastern Australia that were previously unrecognised and were geographically endemic to closed forest refugia. Estimated divergence times were congruent with late Miocene onset of rainforest contractions across the east coast of Australia. This suggested that dispersal and gene flow among E. martini populations isolated in refugia has been highly restricted historically. Moreover, these data imply, in contrast to existing preconceptions about freshwater invertebrates, that this taxon may be acutely susceptible to habitat fragmentation.

Spatio-temporal patterns of Barmah Forest virus disease in Queensland, Australia

Background Barmah Forest virus (BFV) disease is a common and wide-spread mosquito-borne disease in Australia. This study investigated the spatio-temporal patterns of BFV disease in Queensland, Australia using geographical information system (GIS) tools and geostatistical analysis. Methods/Principal Findings We calculated the incidence rates and standardised incidence rates of BFV disease. Moran's I statistic was used to assess the spatial autocorrelation of BFV incidences. Spatial dynamics of BFV disease was examined using semi-variogram analysis. Interpolation techniques were applied to visualise and display the spatial distribution of BFV disease in statistical local areas (SLAs) throughout Queensland. Mapping of BFV disease by SLAs reveals the presence of substantial spatio-temporal variation over time. Statistically significant differences in BFV incidence rates were identified among age groups (χ2 = 7587, df = 7327,p<0.01). There was a significant positive spatial autocorrelation of BFV incidence for all four periods, with the Moran's I statistic ranging from 0.1506 to 0.2901 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. Conclusions/Significance This is the first study to examine spatial and temporal variation in the incidence rates of BFV disease across Queensland using GIS and geostatistics. The BFV transmission varied with age and gender, which may be due to exposure rates or behavioural risk factors. There are differences in the spatio-temporal patterns of BFV disease which may be related to local socio-ecological and environmental factors. These research findings may have implications in the BFV disease control and prevention programs in Queensland.

Fast pyrolysis for better utilization of tamarind seed from renewable energy point of view

The conversion of tamarind seeds into pyrolytic oil by fixed bed fire-tube heating reactor has been taken into consideration in this study. The major components of the system were fixed bed fire-tube heating reactor, liquid condenser and collectors. The raw and crushed tamarind seed in particle form was pyrolized in an electrically heated 10 cm diameter and 27 cm high fixed bed reactor. The products are oil, char and gases. The parameters varied were reactor bed temperature, running time, gas flow rate and feed particle size. The parameters were found to influence the product yields significantly. The maximum liquid yield was 45 wt% at 4000C for a feed size of 1.07cm3 at a gas flow rate of 6 liter/min with a running time of 30 minute. The pyrolysis oil was obtained at these optimum process conditions were analyzed for physical and chemical properties to be used as an alternative fuel.

A butterfly eye's view of birds

The striking color patterns of butterflies and birds have long interested biologists. But how these animals see color is less well understood. Opsins are the protein components of the visual pigments of the eye. Color vision has evolved in butterflies through opsin gene duplications, through positive selection at individual opsin loci, and by the use of filtering pigments. By contrast, birds have retained the same opsin complement present in early-jawed vertebrates, and their visual system has diversified primarily through tuning of the short-wavelength-sensitive photoreceptors, rather than by opsin duplication or the use of filtering elements. Butterflies and birds have evolved photoreceptors that might use some of the same amino acid sites for generating similar spectral phenotypes across approximately 540 million years of evolution, when rhabdomeric and ciliary-type opsins radiated during the early Cambrian period. Considering the similarities between the two taxa, it is surprising that the eyes of birds are not more diverse. Additional taxonomic sampling of birds may help clarify this mystery.

One-year delayed effect of fog on malaria transmission : a time-series analysis in the rain forest area of Mengla County, south-west China

Background: Malaria is a major public health burden in the tropics with the potential to significantly increase in response to climate change. Analyses of data from the recent past can elucidate how short-term variations in weather factors affect malaria transmission. This study explored the impact of climate variability on the transmission of malaria in the tropical rain forest area of Mengla County, south-west China. Methods: Ecological time-series analysis was performed on data collected between 1971 and 1999. Auto-regressive integrated moving average (ARIMA) models were used to evaluate the relationship between weather factors and malaria incidence. Results: At the time scale of months, the predictors for malaria incidence included: minimum temperature, maximum temperature, and fog day frequency. The effect of minimum temperature on malaria incidence was greater in the cool months than in the hot months. The fog day frequency in October had a positive effect on malaria incidence in May of the following year. At the time scale of years, the annual fog day frequency was the only weather predictor of the annual incidence of malaria. Conclusion: Fog day frequency was for the first time found to be a predictor of malaria incidence in a rain forest area. The one-year delayed effect of fog on malaria transmission may involve providing water input and maintaining aquatic breeding sites for mosquitoes in vulnerable times when there is little rainfall in the 6-month dry seasons. These findings should be considered in the prediction of future patterns of malaria for similar tropical rain forest areas worldwide.

Spatial and temporal analysis of Barmah Forest virus disease in Queensland, Australia

Barmah Forest virus (BFV) disease is one of the most widespread mosquito-borne diseases in Australia. The number of outbreaks and the incidence rate of BFV in Australia have attracted growing concerns about the spatio-temporal complexity and underlying risk factors of BFV disease. A large number of notifications has been recorded continuously in Queensland since 1992. Yet, little is known about the spatial and temporal characteristics of the disease. I aim to use notification data to better understand the effects of climatic, demographic, socio-economic and ecological risk factors on the spatial epidemiology of BFV disease transmission, develop predictive risk models and forecast future disease risks under climate change scenarios. Computerised data files of daily notifications of BFV disease and climatic variables in Queensland during 1992-2008 were obtained from Queensland Health and Australian Bureau of Meteorology, respectively. Projections on climate data for years 2025, 2050 and 2100 were obtained from Council of Scientific Industrial Research Organisation. Data on socio-economic, demographic and ecological factors were also obtained from relevant government departments as follows: 1) socio-economic and demographic data from Australian Bureau of Statistics; 2) wetlands data from Department of Environment and Resource Management and 3) tidal readings from Queensland Department of Transport and Main roads. Disease notifications were geocoded and spatial and temporal patterns of disease were investigated using geostatistics. Visualisation of BFV disease incidence rates through mapping reveals the presence of substantial spatio-temporal variation at statistical local areas (SLA) over time. Results reveal high incidence rates of BFV disease along coastal areas compared to the whole area of Queensland. A Mantel-Haenszel Chi-square analysis for trend reveals a statistically significant relationship between BFV disease incidence rates and age groups (ƒÓ2 = 7587, p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. A cluster analysis was used to detect the hot spots/clusters of BFV disease at a SLA level. Most likely spatial and space-time clusters are detected at the same locations across coastal Queensland (p<0.05). The study demonstrates heterogeneity of disease risk at a SLA level and reveals the spatial and temporal clustering of BFV disease in Queensland. Discriminant analysis was employed to establish a link between wetland classes, climate zones and BFV disease. This is because the importance of wetlands in the transmission of BFV disease remains unclear. The multivariable discriminant modelling analyses demonstrate that wetland types of saline 1, riverine and saline tidal influence were the most significant risk factors for BFV disease in all climate and buffer zones, while lacustrine, palustrine, estuarine and saline 2 and saline 3 wetlands were less important. The model accuracies were 76%, 98% and 100% for BFV risk in subtropical, tropical and temperate climate zones, respectively. This study demonstrates that BFV disease risk varied with wetland class and climate zone. The study suggests that wetlands may act as potential breeding habitats for BFV vectors. Multivariable spatial regression models were applied to assess the impact of spatial climatic, socio-economic and tidal factors on the BFV disease in Queensland. Spatial regression models were developed to account for spatial effects. Spatial regression models generated superior estimates over a traditional regression model. In the spatial regression models, BFV disease incidence shows an inverse relationship with minimum temperature, low tide and distance to coast, and positive relationship with rainfall in coastal areas whereas in whole Queensland the disease shows an inverse relationship with minimum temperature and high tide and positive relationship with rainfall. This study determines the most significant spatial risk factors for BFV disease across Queensland. Empirical models were developed to forecast the future risk of BFV disease outbreaks in coastal Queensland using existing climatic, socio-economic and tidal conditions under climate change scenarios. Logistic regression models were developed using BFV disease outbreak data for the existing period (2000-2008). The most parsimonious model had high sensitivity, specificity and accuracy and this model was used to estimate and forecast BFV disease outbreaks for years 2025, 2050 and 2100 under climate change scenarios for Australia. Important contributions arising from this research are that: (i) it is innovative to identify high-risk coastal areas by creating buffers based on grid-centroid and the use of fine-grained spatial units, i.e., mesh blocks; (ii) a spatial regression method was used to account for spatial dependence and heterogeneity of data in the study area; (iii) it determined a range of potential spatial risk factors for BFV disease; and (iv) it predicted the future risk of BFV disease outbreaks under climate change scenarios in Queensland, Australia. In conclusion, the thesis demonstrates that the distribution of BFV disease exhibits a distinct spatial and temporal variation. Such variation is influenced by a range of spatial risk factors including climatic, demographic, socio-economic, ecological and tidal variables. The thesis demonstrates that spatial regression method can be applied to better understand the transmission dynamics of BFV disease and its risk factors. The research findings show that disease notification data can be integrated with multi-factorial risk factor data to develop build-up models and forecast future potential disease risks under climate change scenarios. This thesis may have implications in BFV disease control and prevention programs in Queensland.

The backfilled GEI : a cross-capture modality gait feature for frontal and side-view gait recognition

In this paper, we propose a novel direction for gait recognition research by proposing a new capture-modality independent, appearance-based feature which we call the Back-filled Gait Energy Image (BGEI). It can can be constructed from both frontal depth images, as well as the more commonly used side-view silhouettes, allowing the feature to be applied across these two differing capturing systems using the same enrolled database. To evaluate this new feature, a frontally captured depth-based gait dataset was created containing 37 unique subjects, a subset of which also contained sequences captured from the side. The results demonstrate that the BGEI can effectively be used to identify subjects through their gait across these two differing input devices, achieving rank-1 match rate of 100%, in our experiments. We also compare the BGEI against the GEI and GEV in their respective domains, using the CASIA dataset and our depth dataset, showing that it compares favourably against them. The experiments conducted were performed using a sparse representation based classifier with a locally discriminating input feature space, which show significant improvement in performance over other classifiers used in gait recognition literature, achieving state of the art results with the GEI on the CASIA dataset.