Automating human thought processes for a UAV forced landing

This paper describes the current status of a program to develop an automated forced landing system for a fixed-wing Unmanned Aerial Vehicle (UAV). This automated system seeks to emulate human pilot thought processes when planning for and conducting an engine-off emergency landing. Firstly, a path planning algorithm that extends Dubins curves to 3D space is presented. This planning element is then combined with a nonlinear guidance and control logic, and simulated test results demonstrate the robustness of this approach to strong winds during a glided descent. The average path deviation errors incurred are comparable to or even better than that of manned, powered aircraft. Secondly, a study into suitable multi-criteria decision making approaches and the problems that confront the decision-maker is presented. From this study, it is believed that decision processes that utilize human expert knowledge and fuzzy logic reasoning are most suited to the problem at hand, and further investigations will be conducted to identify the particular technique/s to be implemented in simulations and field tests. The automated UAV forced landing approach presented in this paper is promising, and will allow the progression of this technology from the development and simulation stages through to a prototype system

Assessment by interview and portfolio in a Graduate School Program

Assessment plays an integral role in teaching and learning in Higher Education and teachers have a strong interest in debates and commentaries on assessment as and for learning. In a one-year graduate entry teacher preparation program, the temptation is to emphasize assessment in an attempt to ensure students “cover” everything as part of a robust preparation for the profession. The risk is that, for students, assessment drives curriculum, and time spent in the completion of assignments is no guarantee of either effective learning or authentic preparation for teaching. Interviews as assessment provide an opportunity for a learning experience as well as an authentic task, since students will shortly be interviewing for employment in a “real world” situation. This paper reports on a project experimenting with interview panels as authentic assessment with pre-service early childhood teachers. At the end of their first semester of study, students enrolled in the Graduate Diploma of Education program at the Queensland University of Technology in Australia were required to participate in a panel interview where they were graded by a panel made up of three faculty staff and one undergraduate student enrolled in the four-year Bachelor of Education program. Students and panel members completed a questionnaire on their experience after the interview. Results indicated that both students and staff valued the experience and felt it was authentic. Results are discussed in terms of how the assessment interview and portfolio presentation supports graduating students in their preparation for employment interviews, and how this authentic assessment task has benefits for both students and teaching staff.

Towards automatic power line detection for a UAV surveillance system using pulse coupled neural filter and an improved Hough transform

Spatial information captured from optical remote sensors on board unmanned aerial vehicles (UAVs) has great potential in automatic surveillance of electrical infrastructure. For an automatic vision-based power line inspection system, detecting power lines from a cluttered background is one of the most important and challenging tasks. In this paper, a novel method is proposed, specifically for power line detection from aerial images. A pulse coupled neural filter is developed to remove background noise and generate an edge map prior to the Hough transform being employed to detect straight lines. An improved Hough transform is used by performing knowledge-based line clustering in Hough space to refine the detection results. The experiment on real image data captured from a UAV platform demonstrates that the proposed approach is effective for automatic power line detection.

Towards automatic tree crown detection and delineation in spectral feature space using PCNN and morphological reconstruction

The application of object-based approaches to the problem of extracting vegetation information from images requires accurate delineation of individual tree crowns. This paper presents an automated method for individual tree crown detection and delineation by applying a simplified PCNN model in spectral feature space followed by post-processing using morphological reconstruction. The algorithm was tested on high resolution multi-spectral aerial images and the results are compared with two existing image segmentation algorithms. The results demonstrate that our algorithm outperforms the other two solutions with the average accuracy of 81.8%.

Classification of Airborne LIDAR Intensity Data Using Statistical Analysis and Hough Transform with Application to Power Line Corridors

Light Detection and Ranging (LIDAR) has great potential to assist vegetation management in power line corridors by providing more accurate geometric information of the power line assets and vegetation along the corridors. However, the development of algorithms for the automatic processing of LIDAR point cloud data, in particular for feature extraction and classification of raw point cloud data, is in still in its infancy. In this paper, we take advantage of LIDAR intensity and try to classify ground and non-ground points by statistically analyzing the skewness and kurtosis of the intensity data. Moreover, the Hough transform is employed to detected power lines from the filtered object points. The experimental results show the effectiveness of our methods and indicate that better results were obtained by using LIDAR intensity data than elevation data.

The utility and challenges of using ICD codes in child maltreatment research : a review of existing literature

Objective: The objectives of this article are to explore the extent to which the International Statistical Classification of Diseases and Related Health Problems (ICD) has been used in child abuse research, to describe how the ICD system has been applied and to assess factors affecting the reliability of ICD coded data in child abuse research.----- Methods: PubMed, CINAHL, PsychInfo and Google Scholar were searched for peer reviewed articles written since 1989 that used ICD as the classification system to identify cases and research child abuse using health databases. Snowballing strategies were also employed by searching the bibliographies of retrieved references to identify relevant associated articles. The papers identified through the search were independently screened by two authors for inclusion, resulting in 47 studies selected for the review. Due to heterogeneity of studies metaanalysis was not performed.----- Results: This paper highlights both utility and limitations of ICD coded data. ICD codes have been widely used to conduct research into child maltreatment in health data systems. The codes appear to be used primarily to determine child maltreatment patterns within identified diagnoses or to identify child maltreatment cases for research.----- Conclusions: A significant impediment to the use of ICD codes in child maltreatment research is the under-ascertainment of child maltreatment by using coded data alone. This is most clearly identified and, to some degree, quantified, in research where data linkage is used. Practice Implications: The importance of improved child maltreatment identification will assist in identifying risk factors and creating programs that can prevent and treat child maltreatment and assist in meeting reporting obligations under the CRC.

Robust video stabilisation algorithm using feature point selection and delta optical flow

In this study, the authors propose a novel video stabilisation algorithm for mobile platforms with moving objects in the scene. The quality of videos obtained from mobile platforms, such as unmanned airborne vehicles, suffers from jitter caused by several factors. In order to remove this undesired jitter, the accurate estimation of global motion is essential. However it is difficult to estimate global motions accurately from mobile platforms due to increased estimation errors and noises. Additionally, large moving objects in the video scenes contribute to the estimation errors. Currently, only very few motion estimation algorithms have been developed for video scenes collected from mobile platforms, and this paper shows that these algorithms fail when there are large moving objects in the scene. In this study, a theoretical proof is provided which demonstrates that the use of delta optical flow can improve the robustness of video stabilisation in the presence of large moving objects in the scene. The authors also propose to use sorted arrays of local motions and the selection of feature points to separate outliers from inliers. The proposed algorithm is tested over six video sequences, collected from one fixed platform, four mobile platforms and one synthetic video, of which three contain large moving objects. Experiments show our proposed algorithm performs well to all these video sequences.

Social inequalities and parent involvement in children’s education in the early years of school

Strengthening cooperation between schools and parents is critical to improving learning outcomes for children. The chapter focuses on parental engagement in their children’s education in the early years of school. It considers issues of social and cultural capital as important to whether, or not, parents are involved in their children’s schooling. Analyses of data from a national representative sample of children and their families who participate in Growing up in Australia: The Longitudinal Study of Australian Children are presented. Results indicated that higher family socio-economic position was associated with higher levels of parental involvement and higher expectations about children’s future level of education.

Enhancement of DNA repair using topical T4 endonuclease V does not inhibit melanoma formation in Cdk4R24C/R24C/Tyr-NrasQ61K mice following neonatal UVR

To further investigate the use of DNA repair-enhancing agents for skin cancer prevention, we treated Cdk4R24C/R24C/NrasQ61K mice topically with the T4 endonuclease V DNA repair enzyme (known as Dimericine) immediately prior to neonatal ultraviolet radiation (UVR) exposure, which has a powerful effect in exacerbating melanoma development in the mouse model. Dimericine has been shown to reduce the incidence of basal-cell and squamous cell carcinoma. Unexpectedly, we saw no difference in penetrance or age of onset of melanoma after neonatal UVR between Dimericine-treated and control animals, although the drug reduced DNA damage and cellular proliferation in the skin. Interestingly, epidermal melanocytes removed cyclobutane pyrimidine dimers (CPDs) more efficiently than surrounding keratinocytes. Our study indicates that neonatal UVR-initiated melanomas may be driven by mechanisms other than solely that of a large CPD load and/or their inefficient repair. This is further suggestive of different mechanisms by which UVR may enhance the transformation of keratinocytes and melanocytes.

Land use at privatized Australian airports : classification and analyses

In recent years the air transport industry has experienced unprecedented growth, driven by strong local and global economies. Whether this growth can continue in the face of anticipated oil crises; international economic forecasts and recent influenza outbreaks is yet to be seen. One thing is certain, airport owners and operators will continue to be faced with challenging environments in which to do business. In response, many airports recognize the value in diversifying their revenue streams through a variety of landside property developments within the airport boundary. In Australia it is the type and intended market of this development that is a point of contention between private airport corporations and their surrounding municipalities. The aim of this preliminary research is to identify and categorize on-airport development occurring at the twenty-two privatized Australian airports which are administered under the Airports Act [1996]. This new knowledge will assist airport and municipal planners in understanding the current extent and category of on-airport land use, allowing them to make better decisions when proposing development both within airport master plans and beyond the airport boundary in local town and municipal plans.

Experimental and theoretical studies of the redox potentials of cyclic nitroxides

The redox potentials of 25 cyclic nitroxides from four different structural classes (pyrrolidine, piperidine, isoindoline, and azaphenalene) were determined experimentally by cyclic voltammetry in acetonitrile, and also via high-level ab initio molecular orbital calculations. It is shown that the potentials are influenced by the type of ring system, ring substituents and/or groups surrounding the radical moiety. For the pyrrolidine, piperidine, and isoindolines there is excellent agreement (mean absolute deviation of 0.05 V) between the calculated and experimental oxidation potentials; for the azaphenalenes, however, there is an extraordinary discrepancy (mean absolute deviation of 0.60 V), implying that their one-electron oxidation might involve additional processes not considered in the theoretical calculations. This recently developed azaphenalene class of nitroxide represents a new variant of a nitroxide ring fused to an aromatic system and details of the synthesis of five derivatives involving differing aryl substitution are also presented.

Plasma ATP concentration and venous oxygen content in the forearm during dynamic handgrip exercise

Background: It has been proposed that adenosine triphosphate (ATP) released from red blood cells (RBCs) may contribute to the tight coupling between blood flow and oxygen demand in contracting skeletal muscle. To determine whether ATP may contribute to the vasodilatory response to exercise in the forearm, we measured arterialised and venous plasma ATP concentration and venous oxygen content in 10 healthy young males at rest, and at 30 and 180 seconds during dynamic handgrip exercise at 45% of maximum voluntary contraction (MVC). Results: Venous plasma ATP concentration was elevated above rest after 30 seconds of exercise (P < 0.05), and remained at this higher level 180 seconds into exercise (P < 0.05 versus rest). The increase in ATP was mirrored by a decrease in venous oxygen content. While there was no significant relationship between ATP concentration and venous oxygen content at 30 seconds of exercise, they were moderately and inversely correlated at 180 seconds of exercise (r = -0.651, P = 0.021). Arterial ATP concentration remained unchanged throughout exercise, resulting in an increase in the venous-arterial ATP difference. Conclusions: Collectively these results indicate that ATP in the plasma originated from the muscle microcirculation, and are consistent with the notion that deoxygenation of the blood perfusing the muscle acts as a stimulus for ATP release. That ATP concentration was elevated just 30 seconds after the onset of exercise also suggests that ATP may be a contributing factor to the blood flow response in the transition from rest to steady state exercise.

Evaluation of aerial remote sensing techniques for vegetation management in power line corridors

The following paper presents an evaluation of airborne sensors for use in vegetation management in powerline corridors. Three integral stages in the management process are addressed including, the detection of trees, relative positioning with respect to the nearest powerline and vegetation height estimation. Image data, including multi-spectral and high resolution, are analyzed along with LiDAR data captured from fixed wing aircraft. Ground truth data is then used to establish the accuracy and reliability of each sensor thus providing a quantitative comparison of sensor options. Tree detection was achieved through crown delineation using a Pulse-Coupled Neural Network (PCNN) and morphologic reconstruction applied to multi-spectral imagery. Through testing it was shown to achieve a detection rate of 96%, while the accuracy in segmenting groups of trees and single trees correctly was shown to be 75%. Relative positioning using LiDAR achieved a RMSE of 1.4m and 2.1m for cross track distance and along track position respectively, while Direct Georeferencing achieved RMSE of 3.1m in both instances. The estimation of pole and tree heights measured with LiDAR had a RMSE of 0.4m and 0.9m respectively, while Stereo Matching achieved 1.5m and 2.9m. Overall a small number of poles were missed with detection rates of 98% and 95% for LiDAR and Stereo Matching.