Extending life-cycle costing (LCC) analysis for sustainability considerations in road infrastructure projects

Sustainable development is about making societal investments. These investments should be in synchronization with the natural environment, trends of social development, as well as organisational and local economies over a long time span. Traditionally in the eyes of clients, project development will need to produce the required profit margins, with some degrees of consideration for other impacts. This is being changed as all citizens of our society are becoming more aware of concepts and challenges such as the climate change, greenhouse footprints, and social dimensions of sustainability, and will in turn demand answers to these issues in built facilities. A large number of R&D projects have focused on the technical advancement and environmental assessment of products and built facilities. It is equally important address the cost/benefit issue, as developers in the world would not want to loose money by investing in built assets. For infrastructure projects, due to its significant cost of development and lengthy delivery time, presenting the full money story of going green is of vital importance. Traditional views of life-cycle costing tend to focus on the pure economics of a construction project. Sustainability concepts are not broadly integrated with the current LCCA in the construction sector. To rectify this problem, this paper reports on the progress to date of developing and extending contemporary LCCA models in the evaluation of road infrastructure sustainability. The suggested new model development is based on sustainability indicators identified through previous research, and incorporating industry verified cost elements of sustainability measures. The on-going project aims to design and a working model for sustainability life-cycle costing analysis for this type of infrastructure projects.

Involvement of target contrast in visual masking location tasks deficients in myopia

Purpose: There have been few studies of visual temporal processing of myopic eyes. This study investigated the visual performance of emmetropic and myopic eyes using a backward visual masking location task. Methods: Data were collected for 39 subjects (15 emmetropes, 12 stable myopes, 12 progressing myopes). In backward visual masking, a target’s visibility is reduced by a mask presented in quick succession ‘after’ the target. The target and mask stimuli were presented at different interstimulus intervals (from 12 to 300 ms). The task involved locating the position of a target letter with both a higher (seven per cent) and a lower (five per cent) contrast. Results: Emmetropic subjects had significantly better performance for the lower contrast location task than the myopes (F2,36 = 22.88; p < 0.001) but there was no difference between the progressing and stable myopic groups (p = 0.911). There were no differences between the groups for the higher contrast location task (F2,36 = 0.72, p = 0.495). No relationship between task performance and either the magnitude of myopia or axial length was found for either task. Conclusions: A location task deficit was observed in myopes only for lower contrast stimuli. Both emmetropic and myopic groups had better performance for the higher contrast task compared to the lower contrast task, with myopes showing considerable improvement. This suggests that five per cent contrast may be the contrast threshold required to bias the task towards the magnocellular system (where myopes have a temporal processing deficit). Alternatively, the task may be sensitive to the contrast sensitivity of the observer.

Contributions of vision-proprioception interactions to the estimation of time-varying hand and target locations

We investigated the relative importance of vision and proprioception in estimating target and hand locations in a dynamic environment. Subjects performed a position estimation task in which a target moved horizontally on a screen at a constant velocity and then disappeared. They were asked to estimate the position of the invisible target under two conditions: passively observing and manually tracking. The tracking trials included three visual conditions with a cursor representing the hand position: always visible, disappearing simultaneously with target disappearance, and always invisible. The target’s invisible displacement was systematically underestimated during passive observation. In active conditions, tracking with the visible cursor significantly decreased the extent of underestimation. Tracking of the invisible target became much more accurate under this condition and was not affected by cursor disappearance. In a second experiment, subjects were asked to judge the position of their unseen hand instead of the target during tracking movements. Invisible hand displacements were also underestimated when compared with the actual displacement. Continuous or brief presentation of the cursor reduced the extent of underestimation. These results suggest that vision–proprioception interactions are critical for representing exact target–hand spatial relationships, and that such sensorimotor representation of hand kinematics serves a cognitive function in predicting target position. We propose a hypothesis that the central nervous system can utilize information derived from proprioception and/or efference copy for sensorimotor prediction of dynamic target and hand positions, but that effective use of this information for conscious estimation requires that it be presented in a form that corresponds to that used for the estimations.

Developing a life-cycle costing analysis model for sustainability enhancement in road infrastructure project

With increasing pressure to provide environmentally responsible infrastructure products and services, stakeholders are putting significant foci on the early identification of financial viability and outcome of infrastructure projects. Traditionally, there has been an imbalance between sustainable measures and project budget. On one hand, the industry tends to employ the first-cost mentality and approach to developing infrastructure projects. On the other, environmental experts and technology innovators often push for the ultimately green products and systems without much of a concern for cost. This situation is being quickly changed as the industry is under pressure to continue to return profit, while better adapting to current and emerging global issues of sustainability. For the infrastructure sector to contribute to sustainable development, it will need to increase value and efficiency. Thus, there is a great need for tools that will enable decision makers evaluate competing initiatives and identify the most sustainable approaches to procuring infrastructure projects. In order to ensure that these objectives are achieved, the concept of life-cycle costing analysis (LCCA) will play significant roles in the economics of an infrastructure project. Recently, a few research initiatives have applied the LCCA models for road infrastructure that focused on the traditional economics of a project. There is little coverage of life-cycle costing as a method to evaluate the criteria and assess the economic implications of pursuing sustainability in road infrastructure projects. To rectify this problem, this paper reviews the theoretical basis of previous LCCA models before discussing their inability to determinate the sustainability indicators in road infrastructure project. It then introduces an on-going research aimed at developing a new model to integrate the various new cost elements based on the sustainability indicators with the traditional and proven LCCA approach. It is expected that the research will generate a working model for sustainability based life-cycle cost analysis.

A hidden Markov model and relative entropy rate approach to vision-based dim target detection for UAV sense-and-avoid

Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.

Vitamin D intake needed to maintain target serum 25-Hydroxyvitamin D concentrations in participants with low sun exposure and dark skin pigmentation is substantially higher than current recommendations

Cutaneous cholecalciferol synthesis has not been considered in making recommendations for vitamin D intake. Our objective was to model the effects of sun exposure, vitamin D intake, and skin reflectance (pigmentation) on serum 25-hydroxyvitamin D (25[OH]D) in young adults with a wide range of skin reflectance and sun exposure. Four cohorts of participants (n = 72 total) were studied for 7-8 wk in the fall, winter, spring, and summer in Davis, CA [38.5° N, 121.7° W, Elev. 49 ft (15 m)]. Skin reflectance was measured using a spectrophotometer, vitamin D intake using food records, and sun exposure using polysulfone dosimeter badges. A multiple regression model (R^sup 2^ = 0.55; P < 0.0001) was developed and used to predict the serum 25(OH)D concentration for participants with low [median for African ancestry (AA)] and high [median for European ancestry (EA)] skin reflectance and with low [20th percentile, ~20 min/d, ~18% body surface area (BSA) exposed] and high (80th percentile, ~90 min/d, ~35% BSA exposed) sun exposure, assuming an intake of 200 IU/d (5 ug/d). Predicted serum 25(OH)D concentrations for AA individuals with low and high sun exposure in the winter were 24 and 42 nmol/L and in the summer were 40 and 60 nmol/L. Corresponding values for EA individuals were 35 and 60 nmol/L in the winter and in the summer were 58 and 85 nmol/L. To achieve 25(OH)D ≥75 nmol/L, we estimate that EA individuals with high sun exposure need 1300 IU/d vitamin D intake in the winter and AA individuals with low sun exposure need 2100-3100 IU/d year-round.

EduBuilding: material selection from life cycle costing sensitivity

Life Cycle Cost Analysis provides a form of synopsis of the initial and consequential costs of building related decisions. These cost figures may be implemented to justify higher investments, for example, in the quality or flexibility of building solutions through a long term cost reduction. The emerging discipline of asset mnagement is a promising approach to this problem, because it can do things that techniques such as balanced scorecards and total quantity cannot. Decisions must be made about operating and maintaining infrastructure assets. An injudicious sensitivity of life cycle costing is that the longer something lasts, the less it costs over time. A life cycle cost analysis will be used as an economic evaluation tool and collaborate with various numbers of analyses. LCCA quantifies incurring costs commonly overlooked (by property and asset managers and designs) as replacement and maintenance costs. The purpose of this research is to examine the Life Cycle Cost Analysis on building floor materials. By implementing the life cycle cost analysis, the true cost of each material will be computed projecting 60 years as the building service life and 5.4% as the inflation rate percentage to classify and appreciate the different among the materials. The analysis results showed the high impact in selecting the floor materials according to the potential of service life cycle cost next.

Decentralised particle filtering for multiple target tracking in wireless sensor networks

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Whole life cycle costing for Malaysia residential property development : the cultural environment

As knowledge of the residential development costing impact on resource and budgeting use increase, developers are moving towards more sustainable solution by implementing whole life cycle costing. Property management requires an understanding of infrastructure management, service life planning and quality management. Today, people are beginning to realize that effective property management in high-rise residential property can sustain the property value and maintain high returns on their investment. The continuous growth of high-rise residential properties indicates that there is a need for an effective property management system to provide a sustainable high-rise residential property development. For such reasons, this paper attempts to study the culture that have been applied due the residential property development in Malaysia as to improve to the best and sustainable practice in providing the best cost effectiveness management system in residential property development.

Validation Gating for Non-Linear Non-Gaussian Target Tracking

This paper develops a general theory of validation gating for non-linear non-Gaussian mod- els. Validation gates are used in target tracking to cull very unlikely measurement-to-track associa- tions, before remaining association ambiguities are handled by a more comprehensive (and expensive) data association scheme. The essential property of a gate is to accept a high percentage of correct associ- ations, thus maximising track accuracy, but provide a su±ciently tight bound to minimise the number of ambiguous associations. For linear Gaussian systems, the ellipsoidal vali- dation gate is standard, and possesses the statistical property whereby a given threshold will accept a cer- tain percentage of true associations. This property does not hold for non-linear non-Gaussian models. As a system departs from linear-Gaussian, the ellip- soid gate tends to reject a higher than expected pro- portion of correct associations and permit an excess of false ones. In this paper, the concept of the ellip- soidal gate is extended to permit correct statistics for the non-linear non-Gaussian case. The new gate is demonstrated by a bearing-only tracking example.

Review of the under the limit drink driving rehabilitation program

The combination of alcohol and driving is a major health and economic burden to most communities in industrialised countries. The total cost of crashes for Australia in 1996 was estimated at approximately 15 billion dollars and the costs for fatal crashes were about 3 billion dollars (BTE, 2000). According to the Bureau of Infrastructure, Transport and Regional Development and Local Government (2009; BITRDLG) the overall cost of road fatality crashes for 2006 $3.87 billion, with a single fatal crash costing an estimated $2.67 million. A major contributing factor to crashes involving serious injury is alcohol intoxication while driving. It is a well documented fact that consumption of liquor impairs judgment of speed, distance and increases involvement in higher risk behaviours (Waller, Hansen, Stutts, & Popkin, 1986a; Waller et al., 1986b). Waller et al. (1986a; b) asserts that liquor impairs psychomotor function and therefore renders the driver impaired in a crisis situation. This impairment includes; vision (degraded), information processing (slowed), steering, and performing two tasks at once in congested traffic (Moskowitz & Burns, 1990). As BAC levels increase the risk of crashing and fatality increase exponentially (Department of Transport and Main Roads, 2009; DTMR). According to Compton et al. (2002) as cited in the Department of Transport and Main Roads (2009), crash risk based on probability, is five times higher when the BAC is 0.10 compared to a BAC of 0.00. The type of injury patterns sustained also tends to be more severe when liquor is involved, especially with injuries to the brain (Waller et al., 1986b). Single and Rohl (1997) reported that 30% of all fatal crashes in Australia where alcohol involvement was known were associated with Breadth Analysis Content (BAC) above the legal limit of 0.05gms/100ml. Alcohol related crashes therefore contributes to a third of the total cost of fatal crashes (i.e. $1 billion annually) and crashes where alcohol is involved are more likely to result in death or serious injury (ARRB Transport Research, 1999). It is a major concern that a drug capable of impairment such as is the most available and popular drug in Australia (Australian Institute of Health and Welfare, 2007; AIHW). According to the AIHW (2007) 89.9% of the approximately 25,000 Australians over the age of 14 surveyed had consumed at some point in time, and 82.9% had consumed liquor in the previous year. This study found that 12.1% of individuals admitted to driving a motor vehicle whilst intoxicated. In general males consumed more liquor in all age groups. In Queensland there were 21503 road crashes in 2001, involving 324 fatalities and the largest contributing factor was alcohol and or drugs (Road Traffic Report, 2001). 23438 road crashes in 2004, involving 289 fatalities and the largest contributing factor was alcohol and or drugs (DTMR, 2009). Although a number of measures such as random breath testing have been effective in reducing the road toll (Watson, Fraine & Mitchell, 1995) the recidivist drink driver remains a serious problem. These findings were later supported with research by Leal, King, and Lewis (2006). This Queensland study found that of the 24661 drink drivers intercepted in 2004, 3679 (14.9%) were recidivists with multiple drink driving convictions in the previous three years covered (Leal et al., 2006). The legal definition of the term “recidivist” is consistent with the Transport Operations (Road Use Management) Act (1995) and is assigned to individuals who have been charged with multiple drink driving offences in the previous five years. In Australia relatively little attention has been given to prevention programs that target high-risk repeat drink drivers. However, over the last ten years a rehabilitation program specifically designed to reduce recidivism among repeat drink drivers has been operating in Queensland. The program, formally known as the “Under the Limit” drink driving rehabilitation program (UTL) was designed and implemented by the research team at the Centre for Accident Research and Road Safety in Queensland with funding from the Federal Office of Road Safety and the Institute of Criminology (see Sheehan, Schonfeld & Davey, 1995). By 2009 over 8500 drink-drivering offenders had been referred to the program (Australian Institute of Crime, 2009).

PTZ camera pose estimation by tracking a 3D target

We present a technique for estimating the 6DOF pose of a PTZ camera by tracking a single moving target in the image with known 3D position. This is useful in situations where it is not practical to measure the camera pose directly. Our application domain is estimating the pose of a PTZ camerso so that it can be used for automated GPS-based tracking and filming of UAV flight trials. We present results which show the technique is able to localize a PTZ after a short vision-tracked flight, and that the estimated pose is sufficiently accurate for the PTZ to then actively track a UAV based on GPS position data.