Toward automated power line corridor monitoring using advanced aircraft control and multisource feature fusion

The conventional manual power line corridor inspection processes that are used by most energy utilities are labor-intensive, time consuming and expensive. Remote sensing technologies represent an attractive and cost-effective alternative approach to these monitoring activities. This paper presents a comprehensive investigation into automated remote sensing based power line corridor monitoring, focusing on recent innovations in the area of increased automation of fixed-wing platforms for aerial data collection, and automated data processing for object recognition using a feature fusion process. Airborne automation is achieved by using a novel approach that provides improved lateral control for tracking corridors and automatic real-time dynamic turning for flying between corridor segments, we call this approach PTAGS. Improved object recognition is achieved by fusing information from multi-sensor (LiDAR and imagery) data and multiple visual feature descriptors (color and texture). The results from our experiments and field survey illustrate the effectiveness of the proposed aircraft control and feature fusion approaches.

Fat and thin adaptive HMM filters for vision based detection of moving targets

Computer vision is an attractive solution for uninhabited aerial vehicle (UAV) collision avoidance, due to the low weight, size and power requirements of hardware. A two-stage paradigm has emerged in the literature for detection and tracking of dim targets in images, comprising of spatial preprocessing, followed by temporal filtering. In this paper, we investigate a hidden Markov model (HMM) based temporal filtering approach. Specifically, we propose an adaptive HMM filter, in which the variance of model parameters is refined as the quality of the target estimate improves. Filters with high variance (fat filters) are used for target acquisition, and filters with low variance (thin filters) are used for target tracking. The adaptive filter is tested in simulation and with real data (video of a collision-course aircraft). Our test results demonstrate that our adaptive filtering approach has improved tracking performance, and provides an estimate of target heading not present in previous HMM filtering approaches.

Vision based control for fixed wing UAVs inspecting locally linear infrastructure using skid-to-turn maneuvers

The following paper proposes a novel application of Skid-to-Turn maneuvers for fixed wing Unmanned Aerial Vehicles (UAVs) inspecting locally linear infrastructure. Fixed wing UAVs, following the design of manned aircraft, traditionally employ Bank-to-Turn maneuvers to change heading and thus direction of travel. Commonly overlooked is the effect these maneuvers have on downward facing body fixed sensors, which as a result of bank, point away from the feature during turns. By adopting Skid-to-Turn maneuvers, the aircraft is able change heading whilst maintaining wings level flight, thus allowing body fixed sensors to maintain a downward facing orientation. Eliminating roll also helps to improve data quality, as sensors are no longer subjected to the swinging motion induced as they pivot about an axis perpendicular to their line of sight. Traditional tracking controllers that apply an indirect approach of capturing ground based data by flying directly overhead can also see the feature off center due to steady state pitch and roll required to stay on course. An Image Based Visual Servo controller is developed to address this issue, allowing features to be directly tracked within the image plane. Performance of the proposed controller is tested against that of a Bank-to-Turn tracking controller driven by GPS derived cross track error in a simulation environment developed to simulate the field of view of a body fixed camera.

Adaptive and optimal under frequency load shedding

Power systems in many countries are stressed towards their stability limit. If these stable systems experience any unexpected serious contingencies, or disturbances, there is a significant risk of instability, which may lead to wide-spread blackout. Frequency is a reliable indicator for such instability condition exists on the power system; therefore under-frequency load shedding technique is used to stable the power system by curtail some load. In this paper, the SFR-UFLS model redeveloped to generate optimal load shedding method is that optimally shed load following one single particular contingency event. The proposed optimal load shedding scheme is then tested on the 39-bus New England test system to show the performance against random load shedding scheme.

Towards testing a new first-order decision making model for the procurement of public sector major infrastructure

Given global demand for new infrastructure, governments face substantial challenges in funding new infrastructure and simultaneously delivering Value for Money (VfM). As background to this challenge, a brief review is given of current practice in the selection of major public sector infrastructure in Australia, along with a review of the related literature concerning the Multi-Attribute Utility Approach (MAUA) and the effect of MAUA on the role of risk management in procurement selection. To contribute towards addressing the key weaknesses of MAUA, a new first-order procurement decision making model is mentioned. A brief summary is also given of the research method and hypothesis used to test and develop the new procurement model and which uses competition as the dependent variable and as a proxy for VfM. The hypothesis is given as follows: When the actual procurement mode matches the theoretical/predicted procurement mode (informed by the new procurement model), then actual competition is expected to match optimum competition (based on actual prevailing capacity vis-à-vis the theoretical/predicted procurement mode) and subject to efficient tendering. The aim of this paper is to report on progress towards testing this hypothesis in terms of an analysis of two of the four data components in the hypothesis. That is, actual procurement and actual competition across 87 road and health major public sector projects in Australia. In conclusion, it is noted that the Global Financial Crisis (GFC) has seen a significant increase in competition in public sector major road and health infrastructure and if any imperfections in procurement and/or tendering are discernible, then this would create the opportunity, through the deployment of economic principles embedded in the new procurement model and/or adjustments in tendering, to maintain some of this higher level post-GFC competition throughout the next business cycle/upturn in demand including private sector demand. Finally, the paper previews the next steps in the research with regard to collection and analysis of data concerning theoretical/predicted procurement and optimum competition.

A taint marking approach to confidentiality violation detection

This article presents a novel approach to confidentiality violation detection based on taint marking. Information flows are dynamically tracked between applications and objects of the operating system such as files, processes and sockets. A confidentiality policy is defined by labelling sensitive information and defining which information may leave the local system through network exchanges. Furthermore, per application profiles can be defined to restrict the sets of information each application may access and/or send through the network. In previous works, we focused on the use of mandatory access control mechanisms for information flow tracking. In this current work, we have extended the previous information flow model to track network exchanges, and we are able to define a policy attached to network sockets. We show an example application of this extension in the context of a compromised web browser: our implementation detects a confidentiality violation when the browser attempts to leak private information to a remote host over the network.

Demonstration of closed-­loop airborne sense-­and-­avoid using machine vision

This paper describes a vision-based airborne collision avoidance system developed by the Australian Research Centre for Aerospace Automation (ARCAA) under its Dynamic Sense-and-Act (DSA) program. We outline the system architecture and the flight testing undertaken to validate the system performance under realistic collision course scenarios. The proposed system could be implemented in either manned or unmanned aircraft, and represents a step forward in the development of a “sense-and-avoid” capability equivalent to human “see-and-avoid”.

Web 2.0 applications in enterprises and education

Web 2.0 technology and concepts are being used increasingly by organisations to enhance knowledge, efficiency, engagement and reputation. Understanding the concepts of Web 2.0, its characteristics, and how the technology and concepts can be adopted, is essential to successfully reap the potential benefits. In fact, there is a debate about using the Web 2.0 idiom to refer to the concept behind it; however, this term is widely used in literature as well as in industry. In this paper, the definition of Web 2.0 technology, its characteristics and the attributes, will be presented. In addition, the adoption of such technology is further explored through the presentation of two separate case examples of Web 2.0 being used: to enhance an enterprise; and to enhance university teaching. The similarities between these implementations are identified and discussed, including how the findings point to generic principles of adoption.

The Use of Social Technology to Support Organisational Knowledge

In the current economy, knowledge has been recognized to be a valuable organisational asset, a crucial factor that aids organisations to succeed in highly competitive environments. Many organisations have begun projects and special initiatives aimed at fostering better knowledge sharing amongst their employees. Not surprisingly, information technology (IT) has been a central element of many of these projects and initiatives, as the potential of emerging information technologies such as Web 2.0 for enabling the process of managing organisational knowledge is recognised. This technology could be used as a collaborative system for knowledge management (KM) within enterprises. Enterprise 2.0 is the application of Web 2.0 in an organisational context. Enterprise 2.0 technologies are web-based social software that facilitate collaboration, communication and information flow in a bidirectional manner: an essential aspect of organisational knowledge management. This chapter explains how Enterprise 2.0 technologies (Web 2.0 technologies within organisations) can support knowledge management. The chapter also explores how such technologies support the codifying (technology-centred) and social network (people-centred) approaches of KM, towards bridging the current gap between these two approaches.

Acoustic component detection for automatic species recognition in environmental monitoring

Automatic species recognition plays an important role in assisting ecologists to monitor the environment. One critical issue in this research area is that software developers need prior knowledge of specific targets people are interested in to build templates for these targets. This paper proposes a novel approach for automatic species recognition based on generic knowledge about acoustic events to detect species. Acoustic component detection is the most critical and fundamental part of this proposed approach. This paper gives clear definitions of acoustic components and presents three clustering algorithms for detecting four acoustic components in sound recordings; whistles, clicks, slurs, and blocks. The experiment result demonstrates that these acoustic component recognisers have achieved high precision and recall rate.

Building information modeling in the Australian architecture engineering and construction industry

Building Information Modeling (BIM) is a modern approach to the design, documentation, delivery, and life cycle management of buildings through the use of project information databases coupled with object-based parametric modeling. BIM has the potential to revolutionize the Architecture, Engineering and Construction (AEC) industry in terms of the positive impact it may have on information flows, working relationships between project participants from different disciplines and the resulting benefits it may achieve through improvements to conventional methods. This chapter reviews the development of BIM, the extent to which BIM has been implemented in Australia, and the factors which have affected the up-take of BIM. More specifically, the objectives of this chapter are to investigate the adoption of BIM in the Australian AEC industry and factors that contribute towards the uptake (or non uptake) of BIM. These objectives are met by a review of the related literature in the first instance, followed by the presentation of the results of a 2007 postal questionnaire survey and telephone interviews of a random sample of professionals in the Australian AEC industry. The responses suggest that less than 25 percent of the sample had been involved in BIM – rather less than might be expected from reading the literature. Also, of those who have been involved with BIM, there has been very little interdisciplinary collaboration. The main barriers impeding the implementation of BIM widely across the Australian AEC industry are also identified. These were found to be primarily a lack of BIM expertise, lack of awareness and resistance to change. The benefits experienced as a result of using BIM are also discussed. These include improved design consistency, better coordination, cost savings, higher quality work, greater productivity and increased speed of delivery. In terms of conclusion, some suggestions are made concerning the underlying practical reasons for the slow up-take of BIM and the successes for those early adopters. Prospects for future improvement are discussed and proposals are also made for a large scale worldwide comparative study covering industry-wide participants

Attachment Security and Alexithymia in a Heavy Drinking Population

Attachment difficulties have been proposed as a key risk factor for the development of alexithymia, a multifaceted personality trait characterised by difficulties identifying and describing feelings, a lack of imagination and an externally oriented thinking style. The present study investigated the relationship between attachment and alexithymia in an alcohol dependent population. Participants were 210 outpatients in a Cognitive Behavioural Treatment Program assessed on the Toronto Alexithymia Scale (TAS-20) and the Revised Adult Attachment Scale (RAAS). Significant relationships between anxious attachment and alexithymia factors were confirmed. Furthermore, alexithymic alcoholics reported significantly higher levels of anxious attachment and significantly lower levels of closeness (secure attachment) compared to non-alexithymic alcoholics. These findings highlight the importance of assessing and targeting anxious attachment among alexithymic alcoholics in order to improve alcohol treatment outcomes. Keywords: Attachment, alexithymia, alcohol dependence.