824 resultados para Energy Management Applications


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As computer applications become more available—both technically and economically—construction project managers are increasingly able to access advanced computer tools capable of transforming the role that project managers have typically performed. Competence at using these tools requires a dual commitment in training—from the individual and the firm. Improving the computer skills of project managers can provide construction firms with a competitive advantage to differentiate from others in an increasingly competitive international market. Yet, few published studies have quantified what existing level of competence construction project managers have. Identification of project managers’ existing computer application skills is a necessary first step to developing more directed training to better capture the benefits of computer applications. This paper discusses the yet to be released results of a series of surveys undertaken in Malaysia, Singapore, Indonesia, Australia and the United States through QUT’s School of Construction Management and Property and the M.E. Rinker, Sr. School of Building Construction at the University of Florida. This international survey reviews the use and reported competence in using a series of commercially-available computer applications by construction project managers. The five different country locations of the survey allow cross-national comparisons to be made between project managers undertaking continuing professional development programs. The results highlight a shortfall in the ability of construction project managers to capture potential benefits provided by advanced computer applications and provide directions for targeted industry training programs. This international survey also provides a unique insight to the cross-national usage of advanced computer applications and forms an important step in this ongoing joint review of technology and the construction project manager.

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A Wireless Sensor Network (WSN) is a set of sensors that are integrated with a physical environment. These sensors are small in size, and capable of sensing physical phenomena and processing them. They communicate in a multihop manner, due to a short radio range, to form an Ad Hoc network capable of reporting network activities to a data collection sink. Recent advances in WSNs have led to several new promising applications, including habitat monitoring, military target tracking, natural disaster relief, and health monitoring. The current version of sensor node, such as MICA2, uses a 16 bit, 8 MHz Texas Instruments MSP430 micro-controller with only 10 KB RAM, 128 KB program space, 512 KB external ash memory to store measurement data, and is powered by two AA batteries. Due to these unique specifications and a lack of tamper-resistant hardware, devising security protocols for WSNs is complex. Previous studies show that data transmission consumes much more energy than computation. Data aggregation can greatly help to reduce this consumption by eliminating redundant data. However, aggregators are under the threat of various types of attacks. Among them, node compromise is usually considered as one of the most challenging for the security of WSNs. In a node compromise attack, an adversary physically tampers with a node in order to extract the cryptographic secrets. This attack can be very harmful depending on the security architecture of the network. For example, when an aggregator node is compromised, it is easy for the adversary to change the aggregation result and inject false data into the WSN. The contributions of this thesis to the area of secure data aggregation are manifold. We firstly define the security for data aggregation in WSNs. In contrast with existing secure data aggregation definitions, the proposed definition covers the unique characteristics that WSNs have. Secondly, we analyze the relationship between security services and adversarial models considered in existing secure data aggregation in order to provide a general framework of required security services. Thirdly, we analyze existing cryptographic-based and reputationbased secure data aggregation schemes. This analysis covers security services provided by these schemes and their robustness against attacks. Fourthly, we propose a robust reputationbased secure data aggregation scheme for WSNs. This scheme minimizes the use of heavy cryptographic mechanisms. The security advantages provided by this scheme are realized by integrating aggregation functionalities with: (i) a reputation system, (ii) an estimation theory, and (iii) a change detection mechanism. We have shown that this addition helps defend against most of the security attacks discussed in this thesis, including the On-Off attack. Finally, we propose a secure key management scheme in order to distribute essential pairwise and group keys among the sensor nodes. The design idea of the proposed scheme is the combination between Lamport's reverse hash chain as well as the usual hash chain to provide both past and future key secrecy. The proposal avoids the delivery of the whole value of a new group key for group key update; instead only the half of the value is transmitted from the network manager to the sensor nodes. This way, the compromise of a pairwise key alone does not lead to the compromise of the group key. The new pairwise key in our scheme is determined by Diffie-Hellman based key agreement.

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This paper demonstrates the capabilities of wavelet transform (WT) for analyzing important features related to bottleneck activations and traffic oscillations in congested traffic in a systematic manner. In particular, the analysis of loop detector data from a freeway shows that the use of wavelet-based energy can effectively identify the location of an active bottleneck, the arrival time of the resulting queue at each upstream sensor location, and the start and end of a transition during the onset of a queue. Vehicle trajectories were also analyzed using WT and our analysis shows that the wavelet-based energies of individual vehicles can effectively detect the origins of deceleration waves and shed light on possible triggers (e.g., lane-changing). The spatiotemporal propagations of oscillations identified by tracing wavelet-based energy peaks from vehicle to vehicle enable analysis of oscillation amplitude, duration and intensity.

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Objective To describe the impact of a parent-led, family focused child weight management program on the food intake and activity patterns of pre-pubertal children. Methods n assessor-blinded, randomized controlled trial involving 111 (64% female) overweight, pre-pubertal children 6 to 9 years of age randomly assigned to parenting-skills training plus intensive lifestyle education, parenting-skills training alone, or a 12-month wait-listed control. Study outcomes were assessed at baseline, 6 months, and 12 months. This paper presents data on food intake assessed via a validated 54-item parent completed dietary questionnaire and activity behaviours assessed via a parent-report 20-item activity questionnaire. Results Intake of energy-dense nutrient poor foods was lower in both intervention groups at 6 months (mean difference, P+DA -1.5 serves [CI -2.0;-1.0]; P -1.0 serves [-2.0;-0.5]) and 12 months (mean difference P+DA -1.0 serves [CI -2.0;-0.5]; P -1.0 serves [-1.5; 0.0]) compared to baseline. Intake of vegetables, fruit, breads and cereals, meat and alternatives and dairy foods remained unchanged. Regardless of study group there were significant reductions over time in the reported time spent engaged in small screen activities and an increase in the time reported spent in active play. Conclusion Child weight management intervention that promotes food intake in line with national dietary guidelines achieves a reduction in children’s intake of energy dense, nutrient poor foods. This was achieved without compromising intake of nutrient-rich food and changes in were maintained even once the intervention ceased.

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A stage model for knowledge management systems in policing financial crime is developed in this paper. Stages of growth models enable identification of organizational maturity and direction. Information technology to support knowledge work of police officers is improving. For example, new information systems supporting police investigations are evolving. Police investigation is an information-rich and knowledge-intensive practice. Its success depends on turning information into evidence. This paper presents an organizing framework for knowledge management systems in policing financial crime. Future case studies will empirically have to illustrate and validate the stage hypothesis developed in this paper.

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As the sustainability awareness rises globally, the construction industry is under increasing pressure to improve efficiency and project delivery. The implementation of Industrialised Building Systems (IBS), for which utility components are built offsite, has the potential of promoting sustainability deliverables. This can be achieved by better control of production environment, minimising construction waste, using efficient building material energy, and stabilising work conditions. As a unique building technology, IBS has not been effectively implemented in Malaysia. Possible reasons may include limited understanding among stakeholders on the IBS potential and its relevance to sustainability. This warrants studies on the sustainability issues of IBS design, construction, operation and maintenance, A framework is being developed through research to assess performance criteria related to sustainability, which should be considered during IBS design and application in the most consistent and systematic way. This paper discusses how these sustainability performance criteria are examined in a continuing research project and the processes conducive to implementing sustainable IBS in Malaysia. Existing tools, indicators and guidelines are reviewed, analysed and grouped according to characteristics and application. The research also hopes to produce guidelines for stakeholders to incorporate sustainability issues and concepts into IBS applications.

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The paper presents a demand side response scheme,which assists electricity consumers to proactively control own demands in such a way to deliberately avert congestion periods on the electrical network. The scheme allows shifting loads from peak to low demand periods in an attempt to flattening the national electricity requirement. The scheme can be concurrently used to accommodate the utilization of renewable energy sources,that might be available at user’s premises. In addition the scheme allows a full-capacity utilization of the available electrical infrastructure by organizing a wide-use of electric vehicles. The scheme is applicable in the Eastern and Southern States of Australia managed by the Australian Energy Market Operator. The results indicate the potential of the scheme to achieve energy savings and release capacity to accommodate renewable energy and electrical vehicle technologies.

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This thesis investigates profiling and differentiating customers through the use of statistical data mining techniques. The business application of our work centres on examining individuals’ seldomly studied yet critical consumption behaviour over an extensive time period within the context of the wireless telecommunication industry; consumption behaviour (as oppose to purchasing behaviour) is behaviour that has been performed so frequently that it become habitual and involves minimal intentions or decision making. Key variables investigated are the activity initialised timestamp and cell tower location as well as the activity type and usage quantity (e.g., voice call with duration in seconds); and the research focuses are on customers’ spatial and temporal usage behaviour. The main methodological emphasis is on the development of clustering models based on Gaussian mixture models (GMMs) which are fitted with the use of the recently developed variational Bayesian (VB) method. VB is an efficient deterministic alternative to the popular but computationally demandingMarkov chainMonte Carlo (MCMC) methods. The standard VBGMMalgorithm is extended by allowing component splitting such that it is robust to initial parameter choices and can automatically and efficiently determine the number of components. The new algorithm we propose allows more effective modelling of individuals’ highly heterogeneous and spiky spatial usage behaviour, or more generally human mobility patterns; the term spiky describes data patterns with large areas of low probability mixed with small areas of high probability. Customers are then characterised and segmented based on the fitted GMM which corresponds to how each of them uses the products/services spatially in their daily lives; this is essentially their likely lifestyle and occupational traits. Other significant research contributions include fitting GMMs using VB to circular data i.e., the temporal usage behaviour, and developing clustering algorithms suitable for high dimensional data based on the use of VB-GMM.

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In recent years, development of Unmanned Aerial Vehicles (UAV) has become a significant growing segment of the global aviation industry. These vehicles are developed with the intention of operating in regions where the presence of onboard human pilots is either too risky or unnecessary. Their popularity with both the military and civilian sectors have seen the use of UAVs in a diverse range of applications, from reconnaissance and surveillance tasks for the military, to civilian uses such as aid relief and monitoring tasks. Efficient energy utilisation on an UAV is essential to its functioning, often to achieve the operational goals of range, endurance and other specific mission requirements. Due to the limitations of the space available and the mass budget on the UAV, it is often a delicate balance between the onboard energy available (i.e. fuel) and achieving the operational goals. This thesis presents an investigation of methods for increasing the energy efficiency on UAVs. One method is via the development of a Mission Waypoint Optimisation (MWO) procedure for a small fixed-wing UAV, focusing on improving the onboard fuel economy. MWO deals with a pre-specified set of waypoints by modifying the given waypoints within certain limits to achieve its optimisation objectives of minimising/maximising specific parameters. A simulation model of a UAV was developed in the MATLAB Simulink environment, utilising the AeroSim Blockset and the in-built Aerosonde UAV block and its parameters. This simulation model was separately integrated with a multi-objective Evolutionary Algorithm (MOEA) optimiser and a Sequential Quadratic Programming (SQP) solver to perform single-objective and multi-objective optimisation procedures of a set of real-world waypoints in order to minimise the onboard fuel consumption. The results of both procedures show potential in reducing fuel consumption on a UAV in a ight mission. Additionally, a parallel Hybrid-Electric Propulsion System (HEPS) on a small fixedwing UAV incorporating an Ideal Operating Line (IOL) control strategy was developed. An IOL analysis of an Aerosonde engine was performed, and the most efficient (i.e. provides greatest torque output at the least fuel consumption) points of operation for this engine was determined. Simulation models of the components in a HEPS were designed and constructed in the MATLAB Simulink environment. It was demonstrated through simulation that an UAV with the current HEPS configuration was capable of achieving a fuel saving of 6.5%, compared to the ICE-only configuration. These components form the basis for the development of a complete simulation model of a Hybrid-Electric UAV (HEUAV).

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Calibration process in micro-simulation is an extremely complicated phenomenon. The difficulties are more prevalent if the process encompasses fitting aggregate and disaggregate parameters e.g. travel time and headway. The current practice in calibration is more at aggregate level, for example travel time comparison. Such practices are popular to assess network performance. Though these applications are significant there is another stream of micro-simulated calibration, at disaggregate level. This study will focus on such micro-calibration exercise-key to better comprehend motorway traffic risk level, management of variable speed limit (VSL) and ramp metering (RM) techniques. Selected section of Pacific Motorway in Brisbane will be used as a case study. The discussion will primarily incorporate the critical issues encountered during parameter adjustment exercise (e.g. vehicular, driving behaviour) with reference to key traffic performance indicators like speed, land distribution and headway; at specific motorway points. The endeavour is to highlight the utility and implications of such disaggregate level simulation for improved traffic prediction studies. The aspects of calibrating for points in comparison to that for whole of the network will also be briefly addressed to examine the critical issues such as the suitability of local calibration at global scale. The paper will be of interest to transport professionals in Australia/New Zealand where micro-simulation in particular at point level, is still comparatively a less explored territory in motorway management.

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In Australia, it has been increasingly accepted that sustainability needs to be at the top of the agenda when contemplating infrastructure development. In practice however, many companies struggle to find effective ways to embrace sustainable ideas and implement them in real projects beyond minimum compliance. One of the reasons is the lack of underpinning knowledge and evidence to demonstrate and measure the linkage between sustainability implementations and the relevant outcomes. This is compounded by the fact that very often there are no common understandings between the stakeholders on sustainability and there is a big divide between research advancement and real-life applications. Therefore it is both feasible and timely to develop and expand the body of sustainability knowledge on infrastructure development and investigate better ways of communicating with and managing it within the infrastructure sector. Although knowledge management (KM) is a relatively new and emerging discipline, it has shown its value and promise in existing applications in the construction industry. Considering the existing KM mechanisms and tools employed in practice, this research is aimed at establishing a specific KM approach to facilitate sustainability knowledge identification, acquisition, sharing, maintenance and application within the infrastructure sector, and promote integrated decision-making for sustainable infrastructure development. A triangulation of questionnaire survey, semi-structured interviews and case studies was employed in this research to collect required qualitative and quantitative data. The research studied the unique characteristics of the infrastructure sector, the nature of sustainability knowledge, and evaluated and validated the critical elements, key processes, and priority issues of KM for the Australian infrastructure sector. A holistic KM framework was developed to set the overall context for managing sustainability knowledge in the infrastructure sector by outlining (1) the main aims and outcomes of managing sustainability knowledge, (2) the key knowledge activities, (3) effective KM strategies and instruments, and (4) KM enablers. Because of the highly project-oriented nature of the infrastructure sector, knowledge can only add value when it is being used in real projects. Implementation guidelines were developed to help the industry practitioners and project teams to apply sustainability knowledge and implement KM in infrastructure project scenarios. This research provides the Australian infrastructure sector with tools to better understand KM, helps the industry practitioners to prioritize attention on relevant sustainability issues, and recommends effective practices to manage sustainability knowledge, especially in real life implementation of infrastructure projects.

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Eating behaviour traits, namely Disinhibition and Restraint, have the potential to exert an effect on food intake and energy balance. The effectiveness of exercise as a method of weight management could be influenced by these traits. Fifty eight overweight and obese participants completed 12-weeks of supervised exercise. Each participant was prescribed supervised exercise based on an expenditure of 500 kcal/session, 5 d/week for 12-weeks. Following 12-weeks of exercise there was a significant reduction in mean body weight (-3.26 ± 3.63 kg), fat mass (FM: -3.26 ± 2.64 kg), BMI (-1.16 ± 1.17 kg/m2)and waist circumference (WC: -5.0 ± 3.23 cm). Regression analyses revealed a higher baseline Disinhibition score was associated with a greater reduction in BMI and WC, while Internal Disinhibition was associated with a larger decrease in weight, %FM and WC. Neither baseline Restraint or Hunger were associated with any of the anthropometric markers at baseline or after 12-weeks. Furthermore, after 12-weeks of exercise, a decrease in Disinhibition and increase in Restraint were associated with a greater reduction in WC, whereas only Restraint was associated with a decrease in weight. Post-hoc analysis of the sub-factors revealed a decrease in External Disinhibition and increase in Flexible Restraint were associated with weight loss. However, an increase in Rigid Restraint was associated with a reduction in %FM and WC. These findings suggest that exercise-induced weight loss is more marked in individuals with a high level of Disinhibition. These data demonstrate the important roles that Disinhibition and Restraint play in the relationship between exercise and energy balance.

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The idea of body weight regulation implies that a biological mechanism exerts control over energy expenditure and food intake. This is a central tenet of energy homeostasis. However, the source and identity of the controlling mechanism have not been identified, although it is often presumed to be some long-acting signal related to body fat, such as leptin. Using a comprehensive experimental platform, we have investigated the relationship between biological and behavioural variables in two separate studies over a 12-week intervention period in obese adults (total n 92). All variables have been measured objectively and with a similar degree of scientific control and precision, including anthropometric factors, body composition, RMR and accumulative energy consumed at individual meals across the whole day. Results showed that meal size and daily energy intake (EI) were significantly correlated with fat-free mass (FFM, P values ,0·02–0·05) but not with fat mass (FM) or BMI (P values 0·11–0·45) (study 1, n 58). In study 2 (n 34), FFM (but not FM or BMI) predicted meal size and daily EI under two distinct dietary conditions (high-fat and low-fat). These data appear to indicate that, under these circumstances, some signal associated with lean mass (but not FM) exerts a determining effect over self-selected food consumption. This signal may be postulated to interact with a separate class of signals generated by FM. This finding may have implications for investigations of the molecular control of food intake and body weight and for the management of obesity.

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In this paper we consider the implementation of time and energy efficient trajectories onto a test-bed autonomous underwater vehicle. The trajectories are losely connected to the results of the application of the maximum principle to the controlled mechanical system. We use a numerical algorithm to compute efficient trajectories designed using geometric control theory to optimize a given cost function. Experimental results are shown for the time minimization problem.