The road map to building new dreams : raising a child with developmental delay or disability

Research on early childhood education emphasises the importance of quality in early childhood intervention. This study examines the quality of Early Childhood Intervention Services based on parents’ experiences raising a child with developmental delay or disability. The study builds on the philosophy of Family-Centred Practice and professionals’ experiences with family-centred interventions. A qualitative case study approach was adopted to gain insight about families who are raising a child with additional needs. Nine in-depth parent-interviews and three focus groups with professionals were conducted in the first two terms of 2010. The case explicates the experiences of parents and professionals who were associated with Specialist Children’s Services in a metropolitan region of Victoria. The research concentrated on the first point of entry to early intervention, the referrals process and the waiting list. It also addressed parents' experiences, priorities and expectations. As a small-scale study, it examined parents’ and children’s needs as well as children’s access to therapy in early intervention. It also investigated community support and parent-professional relationships in the context of early childhood intervention services. The study found that family-centred intervention is beneficial to both parents and children with developmental delay or disability. However, to implement an effective family-centred approach, practitioner support in the form of professional development, supervision and peer mentorship is required to develop professionals’ reflexivity and self-efficacy in family-centred interventions. The study also identified strategies to promote effective practice, gaps in universal and specialised services, and implications for policy.

Social on the road: enabling secure and efficient social networking on highways

 This article presents SOR, a vehicular social network to enable social communications and interactions among users on the road during their highway travels. Motivated by the limited connection to Internet contents and services, the essential goal of SOR is to encourage distributed users on the road to spontaneously contribute as the information producer, assembler, and distributer in order to provide timely and localized infotainments to each other through low-cost inter-vehicle communications. To be specific, SOR enables individual users to maintain a personal blog, similar to one on Facebook and Twitter, over which users can create and share personal content information to the public such as travel blogs with pictures and videos. By accessing each other's SOR blogs and commenting on interesting topics, passengers can exchange messages and initiate social interactions. In the specific highway environment, SOR addresses two challenges in the context of vehicular social communications. First, vehicular social communications tend to be frequently interrupted by diverse vehicle mobility and intermittent intervehicle connections, which is annoying to users. To address this issue, SOR adopts a proactive mechanism by estimating the connection time between peer vehicles, and recommending vehicles with relatively long-lasting and stable intervehicle connections for social communications. Second, as users on the road are typically strangers to each other, they are reluctant to disclose personal information to others. This makes it challenging to identify users of shared interests and accordingly restricts the scale of users' social interactions. To remedy that, SOR provides a secured solution to protect sensitive user information during social communications. Lastly, we use simulations to verify the performance of SOR. © 2015 IEEE.

Real-time lane detection on suburban streets using visual cue integration

The detection of lane boundaries on suburban streets using images obtained from video constitutes a challenging task. This is mainly due to the difficulties associated with estimating the complex geometric structure of lane boundaries, the quality of lane markings as a result of wear, occlusions by traffic, and shadows caused by road-side trees and structures. Most of the existing techniques for lane boundary detection employ a single visual cue and will only work under certain conditions and where there are clear lane markings. Also, better results are achieved when there are no other onroad objects present. This paper extends our previous work and discusses a novel lane boundary detection algorithm specifically addressing the abovementioned issues through the integration of two visual cues. The first visual cue is based on stripe-like features found on lane lines extracted using a two-dimensional symmetric Gabor filter. The second visual cue is based on a texture characteristic determined using the entropy measure of the predefined neighbourhood around a lane boundary line. The visual cues are then integrated using a rulebased classifier which incorporates a modified sequential covering algorithm to improve robustness. To separate lane boundary lines from other similar features, a road mask is generated using road chromaticity values estimated from CIE L*a*b* colour transformation. Extraneous points around lane boundary lines are then removed by an outlier removal procedure based on studentized residuals. The lane boundary lines are then modelled with Bezier spline curves. To validate the algorithm, extensive experimental evaluation was carried out on suburban streets and the results are presented. 

Study of the road construction industry in Sri Lanka: emphasis on improving performance of the industry

Outcome of the research is to identify significant factors influencing the productivity and performance of the road construction industry in Sri Lanka and to compare the identified factors with the Australian construction industry. Also to recommend strategies to improve productivity and performance of the Sri Lankan Industry.

My road ahead study protocol: a randomised controlled trial of an online psychological intervention for men following treatment for localised prostate cancer

There is a need for psychosocial interventions for men with prostate cancer to promote adaptive coping with the challenges and distress associated with diagnosis, treatment and recovery. In addition, interventions are needed that help to overcome barriers to psychosocial treatment such as limited face-to-face psychosocial support services, a shortage of adequately trained professionals, geographical distance, perceived and personal stigma and a preference for consumer-centric and self-directed learning. My Road Ahead is an online cognitive behaviour therapy (CBT) intervention for prostate cancer. This protocol describes a randomised controlled trial (RCT) that will evaluate the efficacy of this online intervention alone, the intervention in combination with a moderated online forum, and the moderated online forum alone.

Development, feasibility and usability of an online psychological intervention for men with prostate cancer: my road ahead

Men with prostate cancer are not routinely offered psychosocial support despite strong evidence that being diagnosed with prostate cancer poses significant quality of life concerns and places the patient at elevated risk of developing a range of mental health disorders. The objective of this study was to develop an online psychological intervention for men with prostate cancer and to pilot test the feasibility and acceptability of the intervention. Development of the intervention involved a multidisciplinary collaboration, adapting face-to-face and group intervention strategies for an online format. The full online intervention and moderated forum were pilot tested with 64 participants who were recruited from urology practices in Melbourne, Victoria, Australia. After consenting to participate and creating a personal account in the online programme, participants completed baseline demographic questionnaires. Participants were provided access to the programme for 6-12. weeks. After completing the programme participants completed an online survey to assess intervention and forum utilisation and satisfaction, as well as suggest intervention refinements following their use of the intervention. Patient satisfaction was calculated using mean responses to the satisfaction questionnaire. The intervention was received positively with 47.82% of participants highly satisfied with the programme, and 78.26% said they would recommend it to a friend. Participants' qualitative feedback indicated good acceptability of the online intervention. A number of technical and participant engagement issues were identified and changes recommended as a result of the feasibility testing.

Fast road detection and tracking in aerial videos

 We propose a fast approach for detecting and tracking a specific road in aerial videos. It combines adaptive Gaussian Mixture Models (GMMs) to describe road colour distributions, and homography based tracking to track road geometries, where an efficient technique is developed to estimate homography transformations between two frames. Experiments are conducted on videos captured by our unmanned aerial vehicles. All the results demonstrate the effectiveness of our proposed method. We test 1755 frames from 5 videos. Our approach can achieve 0.032 seconds per frame and 2.64% segmentation error for images with 908 × 513 resolutions, on average.

Efficient road detection and tracking for unmanned aerial vehicle

Abstract - An unmanned aerial vehicle (UAV) has many applications in a variety of fields. Detection and tracking of a specific road in UAV videos play an important role in automatic UAV navigation, traffic monitoring, and ground–vehicle tracking, and also is very helpful for constructing road networks for modeling and simulation. In this paper, an efficient road detection and tracking framework in UAV videos is proposed. In particular, a graph-cut–based detection approach is given to accurately extract a specified road region during the initialization stage and in the middle of tracking process, and a fast homography-based road-tracking scheme is developed to automatically track road areas. The high efficiency of our framework is attributed to two aspects: the road detection is performed only when it is necessary and most work in locating the road is rapidly done via very fast homography-based tracking. Experiments are conducted on UAV videos of real road scenes we captured and downloaded from the Internet. The promising results indicate the effectiveness of our proposed framework, with the precision of 98.4% and processing 34 frames per second for 1046 x 595 videos on average.

Do the numbers and locations of road-killed anuran carcasses accurately reflect impacts of vehicular traffic?

Road-killed animals are easy and inexpensive to survey, and may provide information about species distributions, abundances, and mortality rates. As with any sampling method, however, we need to explore methodological biases in such data. First, how does an animal's behavior (e.g., use of the center vs. periphery of the road) influence its vulnerability to vehicular traffic? Second, how rapidly do post-mortem processes (scavenging by other animals, destruction or displacement by subsequent vehicles) change the numbers and locations of roadkills? Our surveys of anurans on a highway in tropical Australia show that different anuran species are distributed in different ways across the width of the road, and that locations of live versus dead animals sometimes differ within a species. Experimental trials show that location on the road affects the probability of being hit by a vehicle, with anurans in the middle of the road begin hit 35% more often than anurans on the edges; thus, center-using species are more likely to be hit than edge-using taxa. The magnitude of post-mortem displacement and destruction by subsequent vehicles depended on anuran species and body size. The mean parallel displacement distance was 122.7 cm, and carcasses of thin-skinned species exhibited greater post-mortem destruction. Scavenging raptors removed 73% of carcasses, most within a few hours of sunrise. Removal rates were biased with respect to size and species. Overall, our studies suggest that investigators should carefully evaluate potential biases before using roadkill counts to estimate underlying animal abundances or mortality rates.