An evaluation of the impact of using authentic design and build industry projects in project-based learning

BACKGROUNDChisholm’s ‘first year experience’ is a significant feature of the new industry focused Bachelor of Engineering Technology program delivered in association with the South East Melbourne Manufacturers’ Alliance (SEMMA). This conceive-design-implement-operate (CDIO Initiative) program commenced as a full time program in first semester 2012. Whereas it is common for CDIO Initiative programs to have a first year experience program containing a project typical of the type of industry project they would complete as a graduate engineer or engineering technologist, this goes further by using real industry projects provided by SEMMA members.This design-and-build industry project runs across both semesters supporting project-based learning in three first year subjects. A concern is that the industry involvement of the projects adds substantially to an already heavy student workload. This has been further increased by the addition of two additional first year initiatives: writing workshops, and training in, and substantial use of, student oral presentations. It is recognised that an excessive workload could lead students to adopt surface learning approaches in other subjects.PURPOSEThe goal of the project is to evaluate student perceptions of the value and work load impact of the industry project and the other new first year initiatives.DESIGN/METHODCentral to this project is a student survey-based evaluation of the industry project based learning that is the core of the ‘first year experience’. The participants were limited to the small group of students who, in a single year, completed all three subjects that comprise the ‘first year experience’. To avoid compromising the results the survey was administered by Chisholm Institute’s Department of Strategy and Planning with no engineering technology degree program staff present. The survey included questions to enable responses to be linked with specific student demographics without identifying any of the respondents.RESULTSThe study showed the industry project-based learning had worthwhile outcomes but placed considerable time pressures on most respondents. For some, this also impacted on their other subjects. A first year oral presentation program was also shown to have worthwhile outcomes. However no conclusions could be reliably drawn on the third initiative – writing workshops.CONCLUSIONSThe results confirm that the authentic industry project is considered a worthwhile initiative but contributes significantly to student overload. This applies also – to a lesser extent – to the first year oral presentation program. Both also require new approaches to delivery as student numbers increase. Strategies to address these issues are discussed.

Sparse representation with multi-manifold analysis for texture classification from few training images

Texture classification is one of the most important tasks in computer vision field and it has been extensively investigated in the last several decades. Previous texture classification methods mainly used the template matching based methods such as Support Vector Machine and k-Nearest-Neighbour for classification. Given enough training images the state-of-the-art texture classification methods could achieve very high classification accuracies on some benchmark databases. However, when the number of training images is limited, which usually happens in real-world applications because of the high cost of obtaining labelled data, the classification accuracies of those state-of-the-art methods would deteriorate due to the overfitting effect. In this paper we aim to develop a novel framework that could correctly classify textural images with only a small number of training images. By taking into account the repetition and sparsity property of textures we propose a sparse representation based multi-manifold analysis framework for texture classification from few training images. A set of new training samples are generated from each training image by a scale and spatial pyramid, and then the training samples belonging to each class are modelled by a manifold based on sparse representation. We learn a dictionary of sparse representation and a projection matrix for each class and classify the test images based on the projected reconstruction errors. The framework provides a more compact model than the template matching based texture classification methods, and mitigates the overfitting effect. Experimental results show that the proposed method could achieve reasonably high generalization capability even with as few as 3 training images, and significantly outperforms the state-of-the-art texture classification approaches on three benchmark datasets. © 2014 Elsevier B.V. All rights reserved.

Towards designing an email classification system using multi-view based semi-supervised learning

The goal of email classification is to classify user emails into spam and legitimate ones. Many supervised learning algorithms have been invented in this domain to accomplish the task, and these algorithms require a large number of labeled training data. However, data labeling is a labor intensive task and requires in-depth domain knowledge. Thus, only a very small proportion of the data can be labeled in practice. This bottleneck greatly degrades the effectiveness of supervised email classification systems. In order to address this problem, in this work, we first identify some critical issues regarding supervised machine learning-based email classification. Then we propose an effective classification model based on multi-view disagreement-based semi-supervised learning. The motivation behind the attempt of using multi-view and semi-supervised learning is that multi-view can provide richer information for classification, which is often ignored by literature, and semi-supervised learning supplies with the capability of coping with labeled and unlabeled data. In the evaluation, we demonstrate that the multi-view data can improve the email classification than using a single view data, and that the proposed model working with our algorithm can achieve better performance as compared to the existing similar algorithms.

Effectiveness of dual-task functional power training for preventing falls in older people: study protocol for a cluster randomised controlled trial

BACKGROUND: Falls are a major public health concern with at least one third of people aged 65 years and over falling at least once per year, and half of these will fall repeatedly, which can lead to injury, pain, loss of function and independence, reduced quality of life and even death. Although the causes of falls are varied and complex, the age-related loss in muscle power has emerged as a useful predictor of disability and falls in older people. In this population, the requirements to produce explosive and rapid movements often occurs whilst simultaneously performing other attention-demanding cognitive or motor tasks, such as walking while talking or carrying an object. The primary aim of this study is to determine whether dual-task functional power training (DT-FPT) can reduce the rate of falls in community-dwelling older people. METHODS/DESIGN: The study design is an 18-month cluster randomised controlled trial in which 280 adults aged ≥65 years residing in retirement villages, who are at increased risk of falling, will be randomly allocated to: 1) an exercise programme involving DT-FPT, or 2) a usual care control group. The intervention is divided into 3 distinct phases: 6 months of supervised DT-FPT, a 6-month 'step down' maintenance programme, and a 6-month follow-up. The primary outcome will be the number of falls after 6, 12 and 18 months. Secondary outcomes will include: lower extremity muscle power and strength, grip strength, functional assessments of gait, reaction time and dynamic balance under single- and dual-task conditions, activities of daily living, quality of life, cognitive function and falls-related self-efficacy. We will also evaluate the cost-effectiveness of the programme for preventing falls. DISCUSSION: The study offers a novel approach that may guide the development and implementation of future community-based falls prevention programmes that specifically focus on optimising muscle power and dual-task performance to reduce falls risk under 'real life' conditions in older adults. In addition, the 'step down' programme will provide new information about the efficacy of a less intensive maintenance programme for reducing the risk of falls over an extended period. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry: ACTRN12613001161718 . Date registered 23 October 2013.

Nutrition competencies in health professionals' education and training: a new paradigm

Most health care professionals are not adequately trained to address diet and nutrition-related issues with their patients, thus missing important opportunities to ameliorate chronic diseases and improve outcomes in acute illness. In this symposium, the speakers reviewed the status of nutrition education for health care professionals in the United States, United Kingdom, and Australia. Nutrition education is not required for educating and training physicians in many countries. Nutrition education for the spectrum of health care professionals is uncoordinated, which runs contrary to the current theme of interprofessional education. The central role of competencies in guiding medical education was emphasized and the urgent need to establish competencies in nutrition-related patient care was presented. The importance of additional strategies to improve nutrition education of health care professionals was highlighted. Public health legislation such as the Patient Protection and Affordable Care Act recognizes the role of nutrition, however, to capitalize on this increasing momentum, health care professionals must be trained to deliver needed services. Thus, there is a pressing need to garner support from stakeholders to achieve this goal. Promoting a research agenda that provides outcome-based evidence on individual and public health levels is needed to improve and sustain effective interprofessional nutrition education.

Neuromuscular mechanics and hopping training in elderly

Purpose: The present study examined the effects of repetitive hopping training on muscle activation profiles and fascicle–tendon interaction in the elderly. Methods: 20 physically active elderly men were randomly assigned for training (TG) and control groups (CG). TG performed supervised bilateral short contact hopping training with progressively increasing training volume. Measurements were performed before the training period (BEF) as well as after 2 weeks (2 W) and 11 weeks (11 W) of training. During measurements, the gastrocnemius medialis–muscle (GaM) fascicle and its outer Achilles tendon length changes during hopping were examined by ultrasonography together with electromyographic (EMG) activities of calf muscles, kinematics, and kinetics. Results: At 2 W, the ankle joint stiffness was increased by 21.0 ± 19.3 % and contact time decreased by 9.4 ± 7.8 % in TG. Thereafter, from 2–11 W the jumping height increased 56.2 ± 18.1 % in TG. Simultaneously, tendon forces increased 24.3 ± 19.0 % but tendon stiffness did not change. GaM fascicles shifted to shorter operating lengths after training without any changes in their length modifications during the contact phase of hopping. Normalized EMG amplitudes during hopping did not change with training. Conclusions: The present study shows that 11 W of hopping training improves the performance of physically active elderly men. This improvement is achieved with shorter GaM operating lengths and, therefore, increased fascicle stiffness and improved tendon utilization after training. Based on these results, hopping training could be recommended for healthy fit elderly to retain and improve rapid force production capacity.

Place-based initiatives to tackle mature-age workers’ long-term unemployment in Australia, drawing on successful Nordic precedents

In order to tackle unemployment for the at-risk group of mature-age workers displaced by industry sector restructuring, exemplary place-based initiatives are needed focusing on a selected area of high disadvantage identified by Professor Tony Vinson’s 2015 Jesuit Social Services report Dropping off the Edge, with an Australian state government committed to supporting the initiative, as that report recommends. In order to make such a place-based initiative exemplary in its outcomes, so that it leads to uptake in other areas of high disadvantage, it needs to be thoroughly informed by successful Nordic precedents. In particular, the new Australian place-based initiative needs to be informed by Danish regionally-focused large-scale job skills programs involving transition into a proximate sector of employment growth; and by Norwegian measures for more even population distribution outside capital cities or in particular hard-hit regions within capital cities. An advantage of the proposed initiative is that it will also produce measurable results for children in families in which neither parent works, whose needs are normally tackled (if at all) by separate policy actions in separate tiers or departments of government. Australian children are disproportionately disadvantaged by the internationally extreme concentration of joblessness. Denmark’s Løntilskud and Virksomhedspraktik job training programs subsidised by municipalities and the national government, and supported by Danish trade unions, will be discussed in this paper for the positive effects they have for participants, including establishing or re-establishing unemployed people’s structured work habits and routines, improving their networks along with their social skills, and boosting their confidence. This paper will outline in detail the types of features the proposed new Australian place-based initiative will require, drawing on and drilling down further into data and analysis presented in the author’s recent book: Northern Lights: The Positive Policy Example of Sweden, Finland, Denmark and Norway.

A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings

Electrical load forecasting plays a vital role in order to achieve the concept of next generation power system such as smart grid, efficient energy management and better power system planning. As a result, high forecast accuracy is required for multiple time horizons that are associated with regulation, dispatching, scheduling and unit commitment of power grid. Artificial Intelligence (AI) based techniques are being developed and deployed worldwide in on Varity of applications, because of its superior capability to handle the complex input and output relationship. This paper provides the comprehensive and systematic literature review of Artificial Intelligence based short term load forecasting techniques. The major objective of this study is to review, identify, evaluate and analyze the performance of Artificial Intelligence (AI) based load forecast models and research gaps. The accuracy of ANN based forecast model is found to be dependent on number of parameters such as forecast model architecture, input combination, activation functions and training algorithm of the network and other exogenous variables affecting on forecast model inputs. Published literature presented in this paper show the potential of AI techniques for effective load forecasting in order to achieve the concept of smart grid and buildings.

Validity and reliability of field-based measures for assessing movement skill competency in lifelong physical activities: a systematic review

Background: It has been suggested that young people should develop competence in a variety of ‘lifelong physical activities’ to ensure that they can be active across the lifespan. Objective: The primary aim of this systematic review is to report the methodological properties, validity, reliability, and test duration of field-based measures that assess movement skill competency in lifelong physical activities. A secondary aim was to clearly define those characteristics unique to lifelong physical activities. Data Sources: A search of four electronic databases (Scopus, SPORTDiscus, ProQuest, and PubMed) was conducted between June 2014 and April 2015 with no date restrictions. Study Selection: Studies addressing the validity and/or reliability of lifelong physical activity tests were reviewed. Included articles were required to assess lifelong physical activities using process-oriented measures, as well as report either one type of validity or reliability. Study Appraisal and Synthesis Methods: Assessment criteria for methodological quality were adapted from a checklist used in a previous review of sport skill outcome assessments. Results: Movement skill assessments for eight different lifelong physical activities (badminton, cycling, dance, golf, racquetball, resistance training, swimming, and tennis) in 17 studies were identified for inclusion. Methodological quality, validity, reliability, and test duration (time to assess a single participant), for each article were assessed. Moderate to excellent reliability results were found in 16 of 17 studies, with 71 % reporting inter-rater reliability and 41 % reporting intra-rater reliability. Only four studies in this review reported test–retest reliability. Ten studies reported validity results; content validity was cited in 41 % of these studies. Construct validity was reported in 24 % of studies, while criterion validity was only reported in 12 % of studies. Limitations: Numerous assessments for lifelong physical activities may exist, yet only assessments for eight lifelong physical activities were included in this review. Generalizability of results may be more applicable if more heterogeneous samples are used in future research. Conclusion: Moderate to excellent levels of inter- and intra-rater reliability were reported in the majority of studies. However, future work should look to establish test–retest reliability. Validity was less commonly reported than reliability, and further types of validity other than content validity need to be established in future research. Specifically, predictive validity of ‘lifelong physical activity’ movement skill competency is needed to support the assertion that such activities provide the foundation for a lifetime of activity.

Keyboard control method for virtual reality micro-robotic cell injection training

The rapid development of virtual reality offers significant potential for skills training applications. Our ongoing work proposes virtual reality operator training for the micro-robotic cell injection procedure. The interface between the operator and the system can be achieved in many different ways. The computer keyboard is ubiquitous in its use for everyday computing applications and also commonly utilized in virtual reality systems. Based on the premise that most people have experience in using a computer keyboard, as opposed to more sophisticated input devices, this paper considers the feasibility of using a keyboard to control the micro-robot for cell injection. In this study, thirteen participants underwent the experimental evaluation. The participants were asked to perform three simulated trial sessions in a virtual micro-robotic cell injection environment. Each session consisted of ten cell injection trials and relevant data for each trial were recorded and analyzed. Results showed participants' performance improvement after the three sessions. It was also observed that participants intuitively controlled multiple axes of the micro-robot simultaneously despite the absence of instruction on how to do so. This continued throughout the experiments and suggests skills transfer from other keyboard based interactions. Based on the results provided, it is suggested that keyboard control is a feasible, simple and low-cost control method for the virtual micro-robot.

A systematic evaluation of field-based screening methods for the assessment of anterior cruciate ligament (ACL) injury risk

BACKGROUND: Laboratory-based measures provide an accurate method to identify risk factors for anterior cruciate ligament (ACL) injury; however, these methods are generally prohibitive to the wider community. Screening methods that can be completed in a field or clinical setting may be more applicable for wider community use. Examination of field-based screening methods for ACL injury risk can aid in identifying the most applicable method(s) for use in these settings. OBJECTIVE: The objective of this systematic review was to evaluate and compare field-based screening methods for ACL injury risk to determine their efficacy of use in wider community settings. DATA SOURCES: An electronic database search was conducted on the SPORTDiscus™, MEDLINE, AMED and CINAHL databases (January 1990-July 2015) using a combination of relevant keywords. A secondary search of the same databases, using relevant keywords from identified screening methods, was also undertaken. STUDY SELECTION: Studies identified as potentially relevant were independently examined by two reviewers for inclusion. Where consensus could not be reached, a third reviewer was consulted. Original research articles that examined screening methods for ACL injury risk that could be undertaken outside of a laboratory setting were included for review. STUDY APPRAISAL AND SYNTHESIS METHODS: Two reviewers independently assessed the quality of included studies. Included studies were categorized according to the screening method they examined. A description of each screening method, and data pertaining to the ability to prospectively identify ACL injuries, validity and reliability, recommendations for identifying 'at-risk' athletes, equipment and training required to complete screening, time taken to screen athletes, and applicability of the screening method across sports and athletes were extracted from relevant studies. RESULTS: Of 1077 citations from the initial search, a total of 25 articles were identified as potentially relevant, with 12 meeting all inclusion/exclusion criteria. From the secondary search, eight further studies met all criteria, resulting in 20 studies being included for review. Five ACL-screening methods-the Landing Error Scoring System (LESS), Clinic-Based Algorithm, Observational Screening of Dynamic Knee Valgus (OSDKV), 2D-Cam Method, and Tuck Jump Assessment-were identified. There was limited evidence supporting the use of field-based screening methods in predicting ACL injuries across a range of populations. Differences relating to the equipment and time required to complete screening methods were identified. LIMITATIONS: Only screening methods for ACL injury risk were included for review. Field-based screening methods developed for lower-limb injury risk in general may also incorporate, and be useful in, screening for ACL injury risk. CONCLUSIONS: Limited studies were available relating to the OSDKV and 2D-Cam Method. The LESS showed predictive validity in identifying ACL injuries, however only in a youth athlete population. The LESS also appears practical for community-wide use due to the minimal equipment and set-up/analysis time required. The Clinic-Based Algorithm may have predictive value for ACL injury risk as it identifies athletes who exhibit high frontal plane knee loads during a landing task, but requires extensive additional equipment and time, which may limit its application to wider community settings.

Fully automatic localization and segmentation of 3D vertebral bodies from CT/MR images via a learning-based method

In this paper, we address the problems of fully automatic localization and segmentation of 3D vertebral bodies from CT/MR images. We propose a learning-based, unified random forest regression and classification framework to tackle these two problems. More specifically, in the first stage, the localization of 3D vertebral bodies is solved with random forest regression where we aggregate the votes from a set of randomly sampled image patches to get a probability map of the center of a target vertebral body in a given image. The resultant probability map is then further regularized by Hidden Markov Model (HMM) to eliminate potential ambiguity caused by the neighboring vertebral bodies. The output from the first stage allows us to define a region of interest (ROI) for the segmentation step, where we use random forest classification to estimate the likelihood of a voxel in the ROI being foreground or background. The estimated likelihood is combined with the prior probability, which is learned from a set of training data, to get the posterior probability of the voxel. The segmentation of the target vertebral body is then done by a binary thresholding of the estimated probability. We evaluated the present approach on two openly available datasets: 1) 3D T2-weighted spine MR images from 23 patients and 2) 3D spine CT images from 10 patients. Taking manual segmentation as the ground truth (each MR image contains at least 7 vertebral bodies from T11 to L5 and each CT image contains 5 vertebral bodies from L1 to L5), we evaluated the present approach with leave-one-out experiments. Specifically, for the T2-weighted MR images, we achieved for localization a mean error of 1.6 mm, and for segmentation a mean Dice metric of 88.7% and a mean surface distance of 1.5 mm, respectively. For the CT images we achieved for localization a mean error of 1.9 mm, and for segmentation a mean Dice metric of 91.0% and a mean surface distance of 0.9 mm, respectively.

Study protocol: the registrar clinical encounters in training (ReCEnT) study

Background
Patient encounters are the core learning activity of Australian general practice (family practice) training. Exposure to patient demographics and presentations may vary from one general practice registrar (vocational trainee) to another. This can affect comprehensiveness of training. Currently, there is no mechanism to systematically capture the content of GP registrar consultations. The aim of the Registrar Clinical Encounters in Training (ReCEnT) study is to document longitudinally the nature and associations of consultation-based clinical and educational experiences of general practice registrars.
Methods/design
This is an ongoing prospective multi-site cohort study of general practice registrars’ consultations, entailing paper-based recording of consultation data. The study setting is general practices affiliated with three geographically-based Australian general practice regional training providers. Registrars record details of 60 consecutive consultations. Data collected includes registrar demographics, details of the consultation, patient demographics, reasons for encounter and problems managed. Problems managed are coded with the International Classification of Primary Care (second edition) classification system. Additionally, registrars record educational factors related to the encounter. The study will follow the clinical exposure of each registrar six-monthly over the 18 months to two years (full-time equivalent) of their general practice training program.
Conclusions
The study will provide data on a range of factors (patient, registrar and consultation factors). This data will be used to inform a range of educational decisions as well as being used to answer educational research questions. We plan to use ReCEnT as a formative assessment tool for registrars and help identify and address educational needs. The study will facilitate program evaluation by the participating training providers and thus improve articulation of educational programs with practice experience. From the research point of view it will address an evidence gap – the in-practice clinical and educational experience of general practice trainees, determinants of these experiences, and the determinants of registrars’ patterns of practice (for example, prescribing practice) over the course of their training.

Delivering mental health first aid training in Australian workplaces: exploring instructors' experiences

 The impact of common mental illnesses in the workplace can be reduced by encouraging support from co-workers and promoting early professional help-seeking. The Mental Health First Aid (MHFA) course is an evidence-based effective program designed to encourage social support and early help-seeking in the general community. However, little is known about whether the course meets the needs of workplaces. The current study aimed to gain a better understanding of how the course is being delivered in Australian workplaces and invite feedback on how it could be tailored for this delivery setting. This study used a purpose-designed survey to explore 120 MHFA instructors’ experiences of delivering the course in workplaces. The results indicated that MHFA is most commonly deployed in the human service and education sectors to assist workers with helping clients, rather than helping co-workers. The results also suggest ways in which the MHFA course could be tailored for workplaces, as well as further support instructors require to deliver courses in workplace settings.

Design of a virtual reality training system for micro-robotic cell injection

This paper discusses the design of a virtual reality (VR) training system for micro-robotic cell injection. A brief explanation of cell injection and the challenges associated with the procedure are first presented. This is followed by discussion of the skills required by the bio-operator to achieve successful injection, such as accuracy, trajectory and applied force. The design of the VR system which includes the visual display, input controllers, mapping strategies, haptic guidance and output data is then discussed. Initial evaluation of the VR system is presented including analysis and discussion based on conducted user evaluations. Finally, given the findings of the initial evaluation, this paper concludes that an effective haptically-enabled virtual cell injection training system is feasible, and recommendations for improvement and future work are given.