Cyberbullying : the new face of workplace bullying?

While the subject of cyberbullying of children and adolescents has begun to be addressed, there has been less attention or research on cyberbullying in the workplace. Whilst male-dominated workplaces such as manufacturing settings have been found to have an increased risk of workplace bullying, the prevalence of cyberbullying in this sector is not known. This exploratory study investigated the prevalence and methods of face-to-face bullying and cyberbullying of males at work. One hundred and three surveys (a modified version of the NAQ-R1), were returned from randomly selected members of the Australian Manufacturing Worker’s Union (AMWU). The results showed that 34% of the respondents were bullied face-to-face, and 10.7% were cyberbullied. All victims of cyberbullying also experienced face-to-face bullying. The implications for organisations of their “duty of care” in regards to this new form of bullying are indicated.

Smart buildings for healthy and sustainable workplace: scoping study report

Deficiencies in the design and operation of office buildings can give rise to high social, environmental and economic (triple bottom line) costs. As a result, there are significant pressures and incentives to develop ‘smart building’ technologies that can facilitate improved indoor environment quality (IEQ), and more energy efficient operation of office buildings. IEQ indicators include lighting, ventilation, thermal comfort, indoor air quality and noise. In response to this, the CRC for Construction Innovation commissioned a six-month scoping study (Project no. 2002-043) to examine how different technologies could be used to improve the ‘triple bottom line’ for office buildings. The study was supported by three industry partners, Bovis Lend Lease, Arup, and The Queensland Department of Public Works. The objective of the study was to look at the history, trends, drivers, new technologies and potential application areas related to the operation of healthy and efficient office buildings. The key output from the study was a recommendation for a prototype system for intelligent monitoring and control of an office environment, based on identified market, technical and user requirements and constraints.

The reliability of information on work-related injuries available from hospitalisation data in Australia

Objective: To examine the reliability of work-related activity coding for injury-related hospitalisations in Australia. Method: A random sample of 4373 injury-related hospital separations from 1 July 2002 to 30 June 2004 were obtained from a stratified random sample of 50 hospitals across 4 states in Australia. From this sample, cases were identified as work-related if they contained an ICD-10-AM work-related activity code (U73) allocated by either: (i) the original coder; (ii) an independent auditor, blinded to the original code; or (iii) a research assistant, blinded to both the original and auditor codes, who reviewed narrative text extracted from the medical record. The concordance of activity coding and number of cases identified as work-related using each method were compared. Results: Of the 4373 cases sampled, 318 cases were identified as being work-related using any of the three methods for identification. The original coder identified 217 and the auditor identified 266 work-related cases (68.2% and 83.6% of the total cases identified, respectively). Around 10% of cases were only identified through the text description review. The original coder and auditor agreed on the assignment of work-relatedness for 68.9% of cases. Conclusions and Implications: The current best estimates of the frequency of hospital admissions for occupational injury underestimate the burden by around 32%. This is a substantial underestimate that has major implications for public policy, and highlights the need for further work on improving the quality and completeness of routine, administrative data sources for a more complete identification of work-related injuries.

Transformational learning in the workplace

Although transformative learning theory remains one of the most influential theories in the field of adult education, studies on fostering transformative learning, particularly in groups and in the workplace, remain sparse. This article summarises some evidence of transformational learning that influenced changes to practice, processes, and the organisational culture in a case study. It is based on a cohort of 12 worker-learners enrolled in a Graduate Certificate in Education (Executive Leadership) course offered by an Australian university (Queensland University of Technology). Data for this article were drawn from interviews with 10 participants, a focus group with 6 of them, their assessment presentations, and reflective notes of the course facilitators. Also included here are the effects on transformational learning of Taylor’s five elements of work-based learning design, Fuller and Unwins’ features of expansive learning, and Billett’s workplace pedagogies.

Towards continuous surveillance of fruit flies using sensor networks and machine vision

In Australia, the Queensland fruit fly (B. tryoni), is the most destructive insect pest of horticulture, attacking nearly all fruit and vegetable crops. This project has researched and prototyped a system for monitoring fruit flies so that authorities can be alerted when a fly enters a crop in a more efficient manner than is currently used. This paper presents the idea of our sensor platform design as well as the fruit fly detection and recognition algorithm by using machine vision techniques. Our experiments showed that the designed trap and sensor platform is capable to capture quality fly images, the invasive flies can be successfully detected and the average precision of the Queensland fruit fly recognition is 80% from our experiment.

Optimising learning in the workplace

There are three bodies of research that suggest ways in which learning in the workplace can be optimised. The first is evident in the emergent literature endorsing the need to include workplace pedagogies as useful epistemological tools for learners. It is now widely recognised that the workplace provides various pedagogies that facilitate and support learning.

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.

Improved detection and tracking of objects in surveillance video

Surveillance networks are typically monitored by a few people, viewing several monitors displaying the camera feeds. It is then very difficult for a human operator to effectively detect events as they happen. Recently, computer vision research has begun to address ways to automatically process some of this data, to assist human operators. Object tracking, event recognition, crowd analysis and human identification at a distance are being pursued as a means to aid human operators and improve the security of areas such as transport hubs. The task of object tracking is key to the effective use of more advanced technologies. To recognize an event people and objects must be tracked. Tracking also enhances the performance of tasks such as crowd analysis or human identification. Before an object can be tracked, it must be detected. Motion segmentation techniques, widely employed in tracking systems, produce a binary image in which objects can be located. However, these techniques are prone to errors caused by shadows and lighting changes. Detection routines often fail, either due to erroneous motion caused by noise and lighting effects, or due to the detection routines being unable to split occluded regions into their component objects. Particle filters can be used as a self contained tracking system, and make it unnecessary for the task of detection to be carried out separately except for an initial (often manual) detection to initialise the filter. Particle filters use one or more extracted features to evaluate the likelihood of an object existing at a given point each frame. Such systems however do not easily allow for multiple objects to be tracked robustly, and do not explicitly maintain the identity of tracked objects. This dissertation investigates improvements to the performance of object tracking algorithms through improved motion segmentation and the use of a particle filter. A novel hybrid motion segmentation / optical flow algorithm, capable of simultaneously extracting multiple layers of foreground and optical flow in surveillance video frames is proposed. The algorithm is shown to perform well in the presence of adverse lighting conditions, and the optical flow is capable of extracting a moving object. The proposed algorithm is integrated within a tracking system and evaluated using the ETISEO (Evaluation du Traitement et de lInterpretation de Sequences vidEO - Evaluation for video understanding) database, and significant improvement in detection and tracking performance is demonstrated when compared to a baseline system. A Scalable Condensation Filter (SCF), a particle filter designed to work within an existing tracking system, is also developed. The creation and deletion of modes and maintenance of identity is handled by the underlying tracking system; and the tracking system is able to benefit from the improved performance in uncertain conditions arising from occlusion and noise provided by a particle filter. The system is evaluated using the ETISEO database. The dissertation then investigates fusion schemes for multi-spectral tracking systems. Four fusion schemes for combining a thermal and visual colour modality are evaluated using the OTCBVS (Object Tracking and Classification in and Beyond the Visible Spectrum) database. It is shown that a middle fusion scheme yields the best results and demonstrates a significant improvement in performance when compared to a system using either mode individually. Findings from the thesis contribute to improve the performance of semi-automated video processing and therefore improve security in areas under surveillance.

The use of narrative text for injury surveillance research : a systematic review

Objective: To summarise the extent to which narrative text fields in administrative health data are used to gather information about the event resulting in presentation to a health care provider for treatment of an injury, and to highlight best practise approaches to conducting narrative text interrogation for injury surveillance purposes.----- Design: Systematic review----- Data sources: Electronic databases searched included CINAHL, Google Scholar, Medline, Proquest, PubMed and PubMed Central.. Snowballing strategies were employed by searching the bibliographies of retrieved references to identify relevant associated articles.----- Selection criteria: Papers were selected if the study used a health-related database and if the study objectives were to a) use text field to identify injury cases or use text fields to extract additional information on injury circumstances not available from coded data or b) use text fields to assess accuracy of coded data fields for injury-related cases or c) describe methods/approaches for extracting injury information from text fields.----- Methods: The papers identified through the search were independently screened by two authors for inclusion, resulting in 41 papers selected for review. Due to heterogeneity between studies metaanalysis was not performed.----- Results: The majority of papers reviewed focused on describing injury epidemiology trends using coded data and text fields to supplement coded data (28 papers), with these studies demonstrating the value of text data for providing more specific information beyond what had been coded to enable case selection or provide circumstantial information. Caveats were expressed in terms of the consistency and completeness of recording of text information resulting in underestimates when using these data. Four coding validation papers were reviewed with these studies showing the utility of text data for validating and checking the accuracy of coded data. Seven studies (9 papers) described methods for interrogating injury text fields for systematic extraction of information, with a combination of manual and semi-automated methods used to refine and develop algorithms for extraction and classification of coded data from text. Quality assurance approaches to assessing the robustness of the methods for extracting text data was only discussed in 8 of the epidemiology papers, and 1 of the coding validation papers. All of the text interrogation methodology papers described systematic approaches to ensuring the quality of the approach.----- Conclusions: Manual review and coding approaches, text search methods, and statistical tools have been utilised to extract data from narrative text and translate it into useable, detailed injury event information. These techniques can and have been applied to administrative datasets to identify specific injury types and add value to previously coded injury datasets. Only a few studies thoroughly described the methods which were used for text mining and less than half of the studies which were reviewed used/described quality assurance methods for ensuring the robustness of the approach. New techniques utilising semi-automated computerised approaches and Bayesian/clustering statistical methods offer the potential to further develop and standardise the analysis of narrative text for injury surveillance.

Info-gap theory and robust design of surveillance for invasive species : the case study of Barrow Island

Surveillance for invasive non-indigenous species (NIS) is an integral part of a quarantine system. Estimating the efficiency of a surveillance strategy relies on many uncertain parameters estimated by experts, such as the efficiency of its components in face of the specific NIS, the ability of the NIS to inhabit different environments, and so on. Due to the importance of detecting an invasive NIS within a critical period of time, it is crucial that these uncertainties be accounted for in the design of the surveillance system. We formulate a detection model that takes into account, in addition to structured sampling for incursive NIS, incidental detection by untrained workers. We use info-gap theory for satisficing (not minimizing) the probability of detection, while at the same time maximizing the robustness to uncertainty. We demonstrate the trade-off between robustness to uncertainty, and an increase in the required probability of detection. An empirical example based on the detection of Pheidole megacephala on Barrow Island demonstrates the use of info-gap analysis to select a surveillance strategy.

Biosecurity threats : the design of surveillance systems, based on power and risk

We consider the problem of designing a surveillance system to detect a broad range of invasive species across a heterogeneous sampling frame. We present a model to detect a range of invertebrate invasives whilst addressing the challenges of multiple data sources, stratifying for differential risk, managing labour costs and providing sufficient power of detection.We determine the number of detection devices required and their allocation across the landscape within limiting resource constraints. The resulting plan will lead to reduced financial and ecological costs and an optimal surveillance system.

University and workplace culture : lifelong learning in nursing students

Lifelong learning in nursing is an essential if the individual is to remain a competent professional. It becomes apparent that whilst the university culture is supportive of the concept or lifelong learning, the workplace culture is not. Students are discouraged from challenging the norms despite a collaborative partnership that promotes lifelong learning.