Vertical infrastructure inspection using a quadcopter and shared autonomy control

This paper presents a shared autonomy control scheme for a quadcopter that is suited for inspection of vertical infrastructure — tall man-made structures such as streetlights, electricity poles or the exterior surfaces of buildings. Current approaches to inspection of such structures is slow, expensive, and potentially hazardous. Low-cost aerial platforms with an ability to hover now have sufficient payload and endurance for this kind of task, but require significant human skill to fly. We develop a control architecture that enables synergy between the ground-based operator and the aerial inspection robot. An unskilled operator is assisted by onboard sensing and partial autonomy to safely fly the robot in close proximity to the structure. The operator uses their domain knowledge and problem solving skills to guide the robot in difficult to reach locations to inspect and assess the condition of the infrastructure. The operator commands the robot in a local task coordinate frame with limited degrees of freedom (DOF). For instance: up/down, left/right, toward/away with respect to the infrastructure. We therefore avoid problems of global mapping and navigation while providing an intuitive interface to the operator. We describe algorithms for pole detection, robot velocity estimation with respect to the pole, and position estimation in 3D space as well as the control algorithms and overall system architecture. We present initial results of shared autonomy of a quadrotor with respect to a vertical pole and robot performance is evaluated by comparing with motion capture data.

On the statistical determination of optimal camera configurations in large scale surveillance networks

The selection of optimal camera configurations (camera locations, orientations etc.) for multi-camera networks remains an unsolved problem. Previous approaches largely focus on proposing various objective functions to achieve different tasks. Most of them, however, do not generalize well to large scale networks. To tackle this, we introduce a statistical formulation of the optimal selection of camera configurations as well as propose a Trans-Dimensional Simulated Annealing (TDSA) algorithm to effectively solve the problem. We compare our approach with a state-of-the-art method based on Binary Integer Programming (BIP) and show that our approach offers similar performance on small scale problems. However, we also demonstrate the capability of our approach in dealing with large scale problems and show that our approach produces better results than 2 alternative heuristics designed to deal with the scalability issue of BIP.

The influence of online reviews on consumers’ attributions of service quality and control for service standards in hotels

Online travel reviews are emerging as a powerful source of information affecting tourists' pre-purchase evaluation of a hotel organization. This trend has highlighted the need for a greater understanding of the impact of online reviews on consumer attitudes and behaviors. In view of this need, we investigate the influence of online hotel reviews on consumers' attributions of service quality and firms' ability to control service delivery. An experimental design was used to examine the effects of four independent variables: framing; valence; ratings; and target. The results suggest that in reviews evaluating a hotel, remarks related to core services are more likely to induce positive service quality attributions. Recent reviews affect customers' attributions of controllability for service delivery, with negative reviews exerting an unfavorable influence on consumers' perceptions. The findings highlight the importance of managing the core service and the need for managers to act promptly in addressing customer service problems.

Approaches to access control under uncertainty

The ultimate goal of an access control system is to allocate each user the precise level of access they need to complete their job - no more and no less. This proves to be challenging in an organisational setting. On one hand employees need enough access to the organisation’s resources in order to perform their jobs and on the other hand more access will bring about an increasing risk of misuse - either intentionally, where an employee uses the access for personal benefit, or unintentionally, through carelessness or being socially engineered to give access to an adversary. This thesis investigates issues of existing approaches to access control in allocating optimal level of access to users and proposes solutions in the form of new access control models. These issues are most evident when uncertainty surrounding users’ access needs, incentive to misuse and accountability are considered, hence the title of the thesis. We first analyse access control in environments where the administrator is unable to identify the users who may need access to resources. To resolve this uncertainty an administrative model with delegation support is proposed. Further, a detailed technical enforcement mechanism is introduced to ensure delegated resources cannot be misused. Then we explicitly consider that users are self-interested and capable of misusing resources if they choose to. We propose a novel game theoretic access control model to reason about and influence the factors that may affect users’ incentive to misuse. Next we study access control in environments where neither users’ access needs can be predicted nor they can be held accountable for misuse. It is shown that by allocating budget to users, a virtual currency through which they can pay for the resources they deem necessary, the need for a precise pre-allocation of permissions can be relaxed. The budget also imposes an upper-bound on users’ ability to misuse. A generalised budget allocation function is proposed and it is shown that given the context information the optimal level of budget for users can always be numerically determined. Finally, Role Based Access Control (RBAC) model is analysed under the explicit assumption of administrators’ uncertainty about self-interested users’ access needs and their incentives to misuse. A novel Budget-oriented Role Based Access Control (B-RBAC) model is proposed. The new model introduces the notion of users’ behaviour into RBAC and provides means to influence users’ incentives. It is shown how RBAC policy can be used to individualise the cost of access to resources and also to determine users’ budget. The implementation overheads of B-RBAC is examined and several low-cost sub-models are proposed.

An efficient online secondary path estimation for feedback active noise control systems

In practical cases for active noise control (ANC), the secondary path has usually a time varying behavior. For these cases, an online secondary path modeling method that uses a white noise as a training signal is required to ensure convergence of the system. The modeling accuracy and the convergence rate are increased when a white noise with a larger variance is used. However, the larger variance increases the residual noise, which decreases performance of the system and additionally causes instability problem to feedback structures. A sudden change in the secondary path leads to divergence of the online secondary path modeling filter. To overcome these problems, this paper proposes a new approach for online secondary path modeling in feedback ANC systems. The proposed algorithm uses the advantages of white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the algorithm and to prevent the instability effect of the white noise. In this approach, instead of continuous injection of the white noise, a sudden change in secondary path during the operation makes the algorithm to reactivate injection of the white noise to correct the secondary path estimation. In addition, the proposed method models the secondary path without the need of using off-line estimation of the secondary path. Considering the above features increases the convergence rate and modeling accuracy, which results in a high system performance. Computer simulation results shown in this paper indicate effectiveness of the proposed method.

A reliable real-time transport protocol for networked control systems over wireless networks

Deploying wireless networks in networked control systems (NCSs) has become more and more popular during the last few years. As a typical type of real-time control systems, an NCS is sensitive to long and nondeterministic time delay and packet losses. However, the nature of the wireless channel has the potential to degrade the performance of NCS networks in many aspects, particularly in time delay and packet losses. Transport layer protocols could play an important role in providing both reliable and fast transmission service to fulfill NCS’s real-time transmission requirements. Unfortunately, none of the existing transport protocols, including the Transport Control Protocol (TCP) and the User Datagram Protocol (UDP), was designed for real-time control applications. Moreover, periodic data and sporadic data are two types of real-time data traffic with different priorities in an NCS. Due to the lack of support for prioritized transmission service, the real-time performance for periodic and sporadic data in an NCS network is often degraded significantly, particularly under congested network conditions. To address these problems, a new transport layer protocol called Reliable Real-Time Transport Protocol (RRTTP) is proposed in this thesis. As a UDP-based protocol, RRTTP inherits UDP’s simplicity and fast transmission features. To improve the reliability, a retransmission and an acknowledgement mechanism are designed in RRTTP to compensate for packet losses. They are able to avoid unnecessary retransmission of the out-of-date packets in NCSs, and collisions are unlikely to happen, and small transmission delay can be achieved. Moreover, a prioritized transmission mechanism is also designed in RRTTP to improve the real-time performance of NCS networks under congested traffic conditions. Furthermore, the proposed RRTTP is implemented in the Network Simulator 2 for comprehensive simulations. The simulation results demonstrate that RRTTP outperforms TCP and UDP in terms of real-time transmissions in an NCS over wireless networks.

Screening in early childhood for risk of later mental health problems : a longitudinal study

Depression in childhood or adolescence is associated with increased rates of depression in adulthood. Does this justify efforts to detect (and treat) those with symptoms of depression in early childhood or adolescence? The aim of this study was to determine how well symptoms of anxiety/depression (A-D) in early childhood and adolescence predict adult mental health. The study sample is taken from a population-based prospective birth cohort study. Of the 8556 mothers initially approached to participate 8458 agreed, of whom 7223 mothers gave birth to a live singleton baby. Children were screened using modified Child Behaviour Checklist (CBCL) scales for internalizing and total problems (T-P) at age 5 and the CBCL and Youth Self Report (YSR) A-D subscale and T-P scale at age 14. At age 21, a sub-sample of 2563 young adults in this cohort were administered the CIDI-Auto. Results indicated that screening at age 5 would detect few later cases of significant mental ill-health. Using a cut-point of 20% for internalizing at child age 5 years the CBCL had sensitivities of only 25% and 18% for major depression and anxiety disorders at 21 years, respectively. At age 14, the YSR generally performed a little better than the CBCL as a screening instrument, but neither performed at a satisfactory level. Of the children who were categorised as having YSR A-D at 14 years 30% and 37% met DSM-IV criteria for major depression and anxiety disorders, respectively, at age 21. Our findings challenge an existing movement encouraging the detection and treatment of those with symptoms of mental illness in early childhood.

Dynamic robot path planning using an enhanced simulated annealing approach

Evolutionary computation is an effective tool for solving optimization problems. However, its significant computational demand has limited its real-time and on-line applications, especially in embedded systems with limited computing resources, e.g., mobile robots. Heuristic methods such as the genetic algorithm (GA) based approaches have been investigated for robot path planning in dynamic environments. However, research on the simulated annealing (SA) algorithm, another popular evolutionary computation algorithm, for dynamic path planning is still limited mainly due to its high computational demand. An enhanced SA approach, which integrates two additional mathematical operators and initial path selection heuristics into the standard SA, is developed in this work for robot path planning in dynamic environments with both static and dynamic obstacles. It improves the computing performance of the standard SA significantly while giving an optimal or near-optimal robot path solution, making its real-time and on-line applications possible. Using the classic and deterministic Dijkstra algorithm as a benchmark, comprehensive case studies are carried out to demonstrate the performance of the enhanced SA and other SA algorithms in various dynamic path planning scenarios.

Attitudinal, normative, and control beliefs underlying people’s curbside household waste recycling decisions

This study examined the beliefs underlying people’s decision-making, from a theory of planned behaviour (TPB) framework, in the prediction of curbside household waste recycling. Community members in Brisbane, Australia (N = 148) completed a questionnaire assessing the belief based TPB measures of attitudinal beliefs (costs and benefits), normative beliefs (important referents), and control beliefs (barriers) in relation to engaging in curbside household waste recycling for a 2-week period. Two weeks later, participants completed self report measures of recycling behaviour for the previous fortnight. The results revealed that the attitudinal, normative, and control beliefs for people who performed higher and lower levels of recycling differed significantly. A regression analysis identified both normative and control beliefs as the main determinants of recycling behaviour. For normative beliefs, high level recyclers perceived more approval from referents such as partners, friends, and neighbours to recycle all eligible materials. In addition, the strong results for control beliefs indicated that barriers such as forgetfulness, lack of time, and laziness were rated as more likely to hamper optimal recycling performance for low level recyclers. These findings provide important applied information about beliefs to target in the development of future community recycling campaigns.

Nursing research : the Australian College of Nursing position statement

Background Nursing perspectives play an important role in addressing the health priorities of today’s society. The Australian College of Nursing (ACN) acknowledges the significant contribution that nursing research has made since the first nurse researcher, Florence Nightingale, documented the factors that affected the morbidity and mortality of soldiers wounded in the Crimean war in the 1800s. The nursing profession continues to celebrate the significant contribution nursing research made to improving nursing practice and health outcomes. These significant contributions over recent years include, but are not limited to: 1. Health services research that has demonstrated the importance of nursing services and how such services are designed/organised to ensure safety and quality of care (Duffield, et al., 2011; Fernandez, et al., 2012; Middleton, et al., 2011); 2. Clinical research that has demonstrated the value of specific nursing interventions to improved health outcomes, including enhanced survival, reduced morbidity, and improved quality of life and consumer engagement (Cancer Australia and Cancer Voices Australia, 2011; Kitson, et al., 2013; Middleton, et al., 2012; Rickard, et al., 2012; Zeitz, et al., 2011); 3. Basic science research that has advanced discoveries in terms of understanding the biological mechanisms underpinning nursing interventions (Illi, et al., 2012; Kim, et al., 2012; Miaskowski, et al., 2010; Simonova, et al., 2012); 4. Epidemiological research that has advanced understanding about how individuals and populations respond to health problems (Carrington, et al., 2012); 5. Qualitative research that has advanced understanding about experiences of and responses to health and illness and the processes of care that are important to optimal outcomes (Schulman-Green, et al., 2012; Scott, et al., 2011).

Control, shift, insert : living and enacting policy in teachers' day/night work

This thesis investigates the experiences of teachers who trialled an electronic curriculum and assessment tool in the wider context of text-mediated ruling relations organising their work. Problematised as policy and text, this tool is interrogated as a 'solution' to problems perceived in teachers' work in an era of increased accountability. It provides evidence that teachers' work is shaped by forces operating outside their control and mediated by the policy discourses and subjectivities available to them.

Optimal camera planning under versatile user constraints in multi-camera image processing systems

The selection of optimal camera configurations (camera locations, orientations, etc.) for multi-camera networks remains an unsolved problem. Previous approaches largely focus on proposing various objective functions to achieve different tasks. Most of them, however, do not generalize well to large scale networks. To tackle this, we propose a statistical framework of the problem as well as propose a trans-dimensional simulated annealing algorithm to effectively deal with it. We compare our approach with a state-of-the-art method based on binary integer programming (BIP) and show that our approach offers similar performance on small scale problems. However, we also demonstrate the capability of our approach in dealing with large scale problems and show that our approach produces better results than two alternative heuristics designed to deal with the scalability issue of BIP. Last, we show the versatility of our approach using a number of specific scenarios.

A hybrid constructive heuristic and simulated annealing for railway crew scheduling

Railway crew scheduling problem is the process of allocating train services to the crew duties based on the published train timetable while satisfying operational and contractual requirements. The problem is restricted by many constraints and it belongs to the class of NP-hard. In this paper, we develop a mathematical model for railway crew scheduling with the aim of minimising the number of crew duties by reducing idle transition times. Duties are generated by arranging scheduled trips over a set of duties and sequentially ordering the set of trips within each of duties. The optimisation model includes the time period of relief opportunities within which a train crew can be relieved at any relief point. Existing models and algorithms usually only consider relieving a crew at the beginning of the interval of relief opportunities which may be impractical. This model involves a large number of decision variables and constraints, and therefore a hybrid constructive heuristic with the simulated annealing search algorithm is applied to yield an optimal or near-optimal schedule. The performance of the proposed algorithms is evaluated by applying computational experiments on randomly generated test instances. The results show that the proposed approaches obtain near-optimal solutions in a reasonable computational time for large-sized problems.

Coordinated control of grid connected photovoltaic reactive power and battery energy storage systems to improve the voltage profile of a residential distribution feeder

Increasing penetration of photovoltaic (PV) as well as increasing peak load demand has resulted in poor voltage profile for some residential distribution networks. This paper proposes coordinated use of PV and Battery Energy Storage (BES) to address voltage rise and/or dip problems. The reactive capability of PV inverter combined with droop based BES system is evaluated for rural and urban scenarios (having different R/X ratios). Results show that reactive compensation from PV inverters alone is sufficient to maintain acceptable voltage profile in an urban scenario (low resistance feeder), whereas, coordinated PV and BES support is required for the rural scenario (high resistance feeder). Constant as well as variable droop based BES schemes are analyzed. The required BES sizing and associated cost to maintain the acceptable voltage profile under both schemes is presented. Uncertainties in PV generation and load are considered, with probabilistic estimation of PV generation and randomness in load modeled to characterize the effective utilization of BES. Actual PV generation data and distribution system network data is used to verify the efficacy of the proposed method.

The optimal temperature of first aid treatment for partial thickness burn injuries

Using our porcine model of deep dermal partial thickness burn injury, various cooling techniques (15 degrees C running water, 2 degrees C running water, ice) of first aid were applied for 20 minutes compared with a control (ambient temperature). The subdermal temperatures were monitored during the treatment and wounds observed and photographed weekly for 6 weeks, observing reepithelialization, wound surface area and cosmetic appearance. Tissue histology and scar tensile strength were examined 6 weeks after burn. The 2 degrees C and ice treatments decreased the subdermal temperature the fastest and lowest, however, generally the 15 and 2 degrees C treated wounds had better outcomes in terms of reepithelialization, scar histology, and scar appearance. These findings provide evidence to support the current first aid guidelines of cold tap water (approximately 15 degrees C) for 20 minutes as being beneficial in helping to heal the burn wound. Colder water at 2 degrees C is also beneficial. Ice should not be used.