Towards automated content analysis of discussion transcripts: A cognitive presence case

In this paper, we present the results of an exploratory study that examined the problem of automating content analysis of student online discussion transcripts. We looked at the problem of coding discussion transcripts for the levels of cognitive presence, one of the three main constructs in the Community of Inquiry (CoI) model of distance education. Using Coh-Metrix and LIWC features, together with a set of custom features developed to capture discussion context, we developed a random forest classification system that achieved 70.3% classification accuracy and 0.63 Cohen's kappa, which is significantly higher than values reported in the previous studies. Besides improvement in classification accuracy, the developed system is also less sensitive to overfitting as it uses only 205 classification features, which is around 100 times less features than in similar systems based on bag-of-words features. We also provide an overview of the classification features most indicative of the different phases of cognitive presence that gives an additional insights into the nature of cognitive presence learning cycle. Overall, our results show great potential of the proposed approach, with an added benefit of providing further characterization of the cognitive presence coding scheme.

Designing against boredom in automated driving

I draw on four years of experience in mobility and transport research. I was part of a research project with Siemens, for which we identified global trends in urban mobility and explored future business opportunities through scenario planning methods. Some of the proposed solutions for personal and public transport included driverless vehicles. In collaboration with BMW Design I explored the potential of new materials for automotive user interfaces...

A randomized controlled trial protocol testing a decision support intervention for older patients with advanced kidney disease

Aim To assess the effectiveness of a decision support intervention using a pragmatic single blind Randomized Controlled Trial. Background Worldwide the proportion of older people (aged 65 years and over) is rising. This population is known to have a higher prevalence of chronic diseases including chronic kidney disease. The resultant effect of the changing health landscape is seen in the increase in older patients (aged ≥65 years) commencing on dialysis. Emerging evidence suggests that for some older patients dialysis may provide minimal benefit. In a majority of renal units non-dialysis management is offered as an alternative to undertaking dialysis. Research regarding decision-making support that is required to assist this population in choosing between dialysis or non-dialysis management is limited. Design. A multisite single blinded pragmatic randomized controlled trial is proposed. Methods Patients will be recruited from four Queensland public hospitals and randomizd into either the control or intervention group. The decision support intervention is multimodal and includes counselling provided by a trained nurse. The comparator is standard decision-making support. The primary outcomes are decisional regret and decisional conflict. Secondary outcomes are improved knowledge and quality of life. Ethics approval obtained November 2014. Conclusion This is one of the first randomized controlled trials assessing a decision support intervention in older people with advance chronic kidney disease. The results may provide guidance for clinicians in future approaches to assist this population in decision-making to ensure reduced decisional regret and decisional conflict.

Infrared thermal imaging for automated detection of diabetic foot complications

Background Although thermal imaging can be a valuable technology in the prevention and management of diabetic foot disease, it is not yet widely used in clinical practice. Technological advancement in infrared imaging increases its application range. The aim was to explore the first steps in the applicability of high-resolution infrared thermal imaging for noninvasive automated detection of signs of diabetic foot disease. Methods The plantar foot surfaces of 15 diabetes patients were imaged with an infrared camera (resolution, 1.2 mm/pixel): 5 patients had no visible signs of foot complications, 5 patients had local complications (e.g., abundant callus or neuropathic ulcer), and 5 patients had difuse complications (e.g., Charcot foot, infected ulcer, or critical ischemia). Foot temperature was calculated as mean temperature across pixels for the whole foot and for specified regions of interest (ROIs). Results No diferences in mean temperature >1.5 °C between the ipsilateral and the contralateral foot were found in patients without complications. In patients with local complications, mean temperatures of the ipsilateral and the contralateral foot were similar, but temperature at the ROI was >2 °C higher compared with the corresponding region in the contralateral foot and to the mean of the whole ipsilateral foot. In patients with difuse complications, mean temperature diferences of >3 °C between ipsilateral and contralateral foot were found. Conclusions With an algorithm based on parameters that can be captured and analyzed with a high-resolution infrared camera and a computer, it is possible to detect signs of diabetic foot disease and to discriminate between no, local, or difuse diabetic foot complications. As such, an intelligent telemedicine monitoring system for noninvasive automated detection of signs of diabetic foot disease is one step closer. Future studies are essential to confirm and extend these promising early findings.

Principals of audit: Testing, data and ‘implicated advocacy’

Historically, school leaders have occupied a somewhat ambiguous position within networks of power. On the one hand, they appear to be celebrated as what Ball (2003) has termed the ‘new hero of educational reform'; on the other, they are often ‘held to account’ through those same performative processes and technologies. These have become compelling in schools and principals are ‘doubly bound’ through this. Adopting a Foucauldian notion of discursive production, this paper addresses the ways that the discursive ‘field’ of ‘principal’ (within larger regimes of truth such as schools, leadership, quality and efficiency) is produced. It explores how individual principals understand their roles and ethics within those practices of audit emerging in school governance, and how their self-regulation is constituted through NAPLAN – the National Assessment Program, Literacy and Numeracy. A key effect of NAPLAN has been the rise of auditing practices that change how education is valued. Open-ended interviews with 13 primary and secondary school principals from Western Australia, South Australia and New South Wales asked how they perceived NAPLAN's impact on their work, their relationships within their school community and their ethical practice.

Visual detection of occluded crop: For automated harvesting

This paper presents a novel crop detection system applied to the challenging task of field sweet pepper (capsicum) detection. The field-grown sweet pepper crop presents several challenges for robotic systems such as the high degree of occlusion and the fact that the crop can have a similar colour to the background (green on green). To overcome these issues, we propose a two-stage system that performs per-pixel segmentation followed by region detection. The output of the segmentation is used to search for highly probable regions and declares these to be sweet pepper. We propose the novel use of the local binary pattern (LBP) to perform crop segmentation. This feature improves the accuracy of crop segmentation from an AUC of 0.10, for previously proposed features, to 0.56. Using the LBP feature as the basis for our two-stage algorithm, we are able to detect 69.2% of field grown sweet peppers in three sites. This is an impressive result given that the average detection accuracy of people viewing the same colour imagery is 66.8%.

Malaria rapid diagnostic test performance: Results of WHO product testing of malaria RDTs: Round 6 (2014-2015)

Overview This report, published in conjunction with a summary overview of results of rounds 1–6, is the sixth in a series of laboratory-based evaluations of rapid diagnostic tests (RDTs) for malaria. It provides a comparative measure of their performance in a standardized way to distinguish between well and poorly performing tests. It can be used by malaria control programmes and guide WHO procurement recommendations for these diagnostic tools. The evaluation reported here was a joint project of the WHO Global Malaria Programme, the Foundation for Innovative New Diagnostics (FIND) and the United States Centers for Disease Control and Prevention (CDC) within the WHO-FIND Malaria RDT Evaluation Programme. The project was financed by FIND through a grant from UNITAID.

Pastoral care in times of high stakes testing and accountability

The unknown future is a challenge to educators in preparing young people for life post school. While history can be said to repeat itself, the reality is that each generation is faced with new challenges and threats. Therefore, the challenge for contemporary schooling is to prepare students to live in a fast paced, complex world where threats such as terrorism, cyberbullying and depleted resources are juggled with high stakes testing and curriculum accountability. This presentation draws on the notion of a future of supercomplexity while critically examining current pastoral care delivery in schools to develop a new model of practice in preparing students for an unknown future.

Functional Imagery Training to reduce snacking: Testing a novel motivational intervention based on Elaborated Intrusion theory

Functional Imagery Training (FIT) is a new theory-based, manualized intervention that trains positive goal imagery. Multisensory episodic imagery of proximal personal goals is elicited and practised, to sustain motivation and compete with less functional cravings. This study tested the impact of a single session of FIT plus a booster phone call on snacking. In a stepped-wedge design, 45 participants who wanted to lose weight or reduce snacking were randomly assigned to receive a session of FIT immediately or after a 2-week delay. High-sugar and high-fat snacks were recorded using timeline follow back for the previous 3 days, at baseline, 2 and 4 weeks. At 2 weeks, snacking was lower in the immediate group than in the delayed group, and the reduction after FIT was replicated in the delayed group between 2 and 4 weeks. Frequencies of motivational thoughts about snack reduction rose following FIT for both groups, and this change correlated with reductions in snacking and weight loss. By showing that FIT can support change in eating behaviours, these findings show its potential as a motivational intervention for weight management.

Prostate cancer organoids: A potential new tool for testing drug sensitivity

Recent technical advances have enabled for the first time, reliable in vitro culture of prostate cancer samples as prostate cancer organoids. This breakthrough provides the significant possibility of high throughput drug screening covering the spectrum of prostate cancer phenotypes seen clinically. These advances will enable precision medicine to become a reality, allowing patient samples to be screened for effective therapeutics ex vivo, with tailoring of treatments specific to that individual. This will hopefully lead to enhanced clinical outcomes, avoid morbidity due to ineffective therapies and improve the quality of life in men with advanced prostate cancer.

Experimental investigation on lateral impact response of concrete-filled double-skin tube columns using horizontal-impact-testing system

This paper presents an experimental investigation on the lateral impact performance of axially loaded concrete-filled double-skin tube (CFDST) columns. These columns have desirable structural and constructional properties and have been used as columns in building, legs of off shore platforms and as bridge piers. Since they could be vulnerable to impact from passing vessels or vehicles, it is necessary to understand their behaviour under lateral impact loads. With this in mind, an experimental method employing an innovative instrumented horizontal impact testing system (HITS) was developed to apply lateral impact loads whilst the column maintained a static axial pre-loading to examine the failure mechanism and key response parameters of the column. These included the time histories of impact force, reaction forces, global lateral deflection and permanent local buckling profile. Eight full scale columns were tested for key parameters including the axial load level and impact location. Based on the test data, the failure mode, peak impact force, impact duration, peak reaction forces, reaction force duration, column maximum and residual global deflections and column local buckling length, depth and width under varying conditions are analysed and discussed. It is evident that the innovative HITS can successfully test structural columns under the combination of axial pre-loading and impact loading. The findings on the lateral impact response of the CFDST columns can serve as a benchmark reference for their future analysis and design.

Developing and testing readability measurements for second language learners

This research constructed a readability measurement for French speakers who view English as a second language. It identified the true cognates, which are the similar words from these two languages, as an indicator of the difficulty of an English text for French people. A multilingual lexical resource is used to detect true cognates in text, and Statistical Language Modelling to predict the predict the readability level. The proposed enhanced statistical language model is making a step in the right direction by improving the accuracy of readability predictions for French speakers by up to 10% compared to state of the art approaches. The outcome of this study could accelerate the learning process for French speakers who are studying English. More importantly, this study also benefits the readability estimation research community, presenting an approach and evaluation at sentence level as well as innovating with the use of cognates as a new text feature.

Testing against changing correlation

A test for time-varying correlation is developed within the framework of a dynamic conditional score (DCS) model for both Gaussian and Student t-distributions. The test may be interpreted as a Lagrange multiplier test and modified to allow for the estimation of models for time-varying volatility in the individual series. Unlike standard moment-based tests, the score-based test statistic includes information on the level of correlation under the null hypothesis and local power arguments indicate the benefits of doing so. A simulation study shows that the performance of the score-based test is strong relative to existing tests across a range of data generating processes. An application to the Hong Kong and South Korean equity markets shows that the new test reveals changes in correlation that are not detected by the standard moment-based test.

Automated Discovery of Structured Process Models: Discover Structured vs. Discover and Structure

This paper addresses the problem of discovering business process models from event logs. Existing approaches to this problem strike various tradeoffs between accuracy and understandability of the discovered models. With respect to the second criterion, empirical studies have shown that block-structured process models are generally more understandable and less error-prone than unstructured ones. Accordingly, several automated process discovery methods generate block-structured models by construction. These approaches however intertwine the concern of producing accurate models with that of ensuring their structuredness, sometimes sacrificing the former to ensure the latter. In this paper we propose an alternative approach that separates these two concerns. Instead of directly discovering a structured process model, we first apply a well-known heuristic technique that discovers more accurate but sometimes unstructured (and even unsound) process models, and then transform the resulting model into a structured one. An experimental evaluation shows that our “discover and structure” approach outperforms traditional “discover structured” approaches with respect to a range of accuracy and complexity measures.