Blast response and safety evaluation of a composite column for use as key element in structural systems

This paper presents the blast response, damage mechanism and evaluation of residual load capacity of a concrete–steel composite (CSC) column using dynamic computer simulation techniques. This study is an integral part of a comprehensive research program which investigated the vulnerability of structural framing systems to catastrophic and progressive collapse under blast loading and is intended to provide design information on blast mitigation and safety evaluation of load bearing vulnerable columns that are key elements in a building. The performance of the CSC column is compared with that of a reinforced concrete (RC) column with the same dimensions and steel ratio. Results demonstrate the superior performance of the CSC column, compared to the RC column in terms of residual load carrying capacity, and its potential for use as a key element in structural systems. The procedure and results presented herein can be used in the design and safety evaluation of key elements of multi-storey buildings for mitigating the impact of blast loads.

Evaluation of robust autonomy and implications on UAS certification and design

As the number of potential applications of Unmanned Aircraft Systems (UAS) grows in civilian operations and national security, National Airworthiness Authorities are under increasing pressure to provide a path for certification and allow UAS integration into the national airspace. The success of this integration depends on developments in improved UAS reliability and safety, regulations for certification, and technologies for operational performance and safety assessment. This paper focusses on the latter and describes the use of a framework for evaluating robust autonomy of UAS, namely, the autonomous system’s ability to either continue operation in the presence of faults or safely shut down. The paper draws parallels between the proposed evaluation framework and the evaluation of pilots during the licensing process. It also discusses how the data from the proposed evaluation can be uses as an aid for decision making in certification and UAS designs.

On evaluation of robust autonomy for uninhabited vehicles and systems

This paper discusses a method to quantify robust autonomy of Uninhabited Vehicles and Systems (UVS) in aerospace, marine, or land applications. Based on mission-vehicle specific performance criteria, we define an system utility function that can be evaluated using simulation scenarios for an envelope of environmental conditions. The results of these evaluations are used to compute a figure of merit or measure for operational efectiveness (MOE). The procedure is then augmented to consider faults and the performance of mechanisms to handle these faulty operational modes. This leads to a measure of robust autonomy (MRA). The objective of the proposed figures of merit is to assist in decision making about vehicle performance and reliability at both vehicle development stage (using simulation models) and at certification stage (using hardware-in-the-loop testing). Performance indices based on dynamic and geometric tasks associated with vehicle manoeuvring problems are proposed, and an example of a two- dimensional y scenario is provided to illustrate the use of the proposed figures of merit.

Evaluation of resonant damping techniques for Z-source current-type inverter

For the renewable energy sources whose outputs vary continuously, a Z-source current-type inverter has been proposed as a possible buck-boost alternative for grid-interfacing. With a unique X-shaped LC network connected between its dc power source and inverter topology, Z-source current-type inverter is however expected to suffer from compounded resonant complications in addition to those associated with its second-order output filter. To improve its damping performance, this paper proposes the careful integration of Posicast or three-step compensators before the inverter pulse-width modulator for damping triggered resonant oscillations. In total, two compensators are needed for wave-shaping the inverter boost factor and modulation ratio, and they can conveniently be implemented using first-in first-out stacks and embedded timers of modern digital signal processors widely used in motion control applications. Both techniques are found to damp resonance of ac filter well, but for cases of transiting from current-buck to boost state, three-step technique is less effective due to the sudden intermediate discharging interval introduced by its non-monotonic stepping (unlike the monotonic stepping of Posicast damping). These findings have been confirmed both in simulations and experiments using an implemented laboratory prototype.

Blood transfer devices for malaria rapid diagnostic tests : evaluation of accuracy, safety and ease of use

Background: Malaria rapid diagnostic tests (RDTs) are increasingly used by remote health personnel with minimal training in laboratory techniques. RDTs must, therefore, be as simple, safe and reliable as possible. Transfer of blood from the patient to the RDT is critical to safety and accuracy, and poses a significant challenge to many users. Blood transfer devices were evaluated for accuracy and precision of volume transferred, safety and ease of use, to identify the most appropriate devices for use with RDTs in routine clinical care. Methods: Five devices, a loop, straw-pipette, calibrated pipette, glass capillary tube, and a new inverted cup device, were evaluated in Nigeria, the Philippines and Uganda. The 227 participating health workers used each device to transfer blood from a simulated finger-prick site to filter paper. For each transfer, the number of attempts required to collect and deposit blood and any spilling of blood during transfer were recorded. Perceptions of ease of use and safety of each device were recorded for each participant. Blood volume transferred was calculated from the area of blood spots deposited on filter paper. Results: The overall mean volumes transferred by devices differed significantly from the target volume of 5 microliters (p < 0.001). The inverted cup (4.6 microliters) most closely approximated the target volume. The glass capillary was excluded from volume analysis as the estimation method used is not compatible with this device. The calibrated pipette accounted for the largest proportion of blood exposures (23/225, 10%); exposures ranged from 2% to 6% for the other four devices. The inverted cup was considered easiest to use in blood collection (206/ 226, 91%); the straw-pipette and calibrated pipette were rated lowest (143/225 [64%] and 135/225 [60%] respectively). Overall, the inverted cup was the most preferred device (72%, 163/227), followed by the loop (61%, 138/227). Conclusions: The performance of blood transfer devices varied in this evaluation of accuracy, blood safety, ease of use, and user preference. The inverted cup design achieved the highest overall performance, while the loop also performed well. These findings have relevance for any point-of-care diagnostics that require blood sampling.

An evaluation of crowd counting methods, features and regression models

Existing crowd counting algorithms rely on holistic, local or histogram based features to capture crowd properties. Regression is then employed to estimate the crowd size. Insufficient testing across multiple datasets has made it difficult to compare and contrast different methodologies. This paper presents an evaluation across multiple datasets to compare holistic, local and histogram based methods, and to compare various image features and regression models. A K-fold cross validation protocol is followed to evaluate the performance across five public datasets: UCSD, PETS 2009, Fudan, Mall and Grand Central datasets. Image features are categorised into five types: size, shape, edges, keypoints and textures. The regression models evaluated are: Gaussian process regression (GPR), linear regression, K nearest neighbours (KNN) and neural networks (NN). The results demonstrate that local features outperform equivalent holistic and histogram based features; optimal performance is observed using all image features except for textures; and that GPR outperforms linear, KNN and NN regression

From policy borrowing to implementation : an illuminative evaluation of learning and teaching in higher education in Australia (2002 to 2008)

This study documents and theorises the consequences of the 2003 Australian Government Reform Package focussed on learning and teaching in Higher Education during the period 2002 to 2008. This is achieved through the perspective of program evaluation and the methodology of illuminative evaluation. The findings suggest that the three national initiatives of that time, Learning and Teaching Performance Fund (LTPF), Australian Learning and Teaching Council (ALTC), and Australian Universities Quality Agency (AUQA), were successful in repositioning learning and teaching as a core activity in universities. However, there were unintended consequences brought about by international policy borrowing, when the short-lived nature of LTPF suggests a legacy of quality compliance rather than one of quality enrichment.

The development and evaluation of a medical imaging training immersive environment

Introduction A novel realistic 3D virtual reality (VR) application has been developed to allow medical imaging students at Queensland University of Technology to practice radiographic techniques independently outside the usual radiography laboratory. Methods A flexible agile development methodology was used to create the software rapidly and effectively. A 3D gaming environment and realistic models were used to engender presence in the software while tutor-determined gold standards enabled students to compare their performance and learn in a problem-based learning pedagogy. Results Students reported high levels of satisfaction and perceived value and the software enabled up to 40 concurrent users to prepare for clinical practice. Student feedback also indicated that they found 3D to be of limited value in the desktop version compared to the usual 2D approach. A randomised comparison between groups receiving software-based and traditional practice measured performance in a formative role play with real equipment. The results of this work indicated superior performance with the equipment for the VR trained students (P = 0.0366) and confirmed the value of VR for enhancing 3D equipment-based problem-solving skills. Conclusions Students practising projection techniques virtually performed better at role play assessments than students practising in a traditional radiography laboratory only. The application particularly helped with 3D equipment configuration, suggesting that teaching 3D problem solving is an ideal use of such medical equipment simulators. Ongoing development work aims to establish the role of VR software in preparing students for clinical practice with a range of medical imaging equipment.

Evaluation of assessment in the context of work-based learning: Qualitative perspectives of new graduates

Aim Evaluation or assessment of competence is an important step to ensure the safety and efficacy of health professionals, including dietitians. Most competency-based assessment studies are focussed on valid and reliable methods of assessment for the preparation of entry-level dietitians, few papers have explored student dietitians’ perceptions of these evaluations. This study aimed to explore the perceptions of recent graduates from accredited nutrition and dietetics training programs in Australia. It also aimed to establish the relevance of competency-based assessment to adequately prepare them for entry-level work roles. Methods A purposive sample of newly-graduated dietitians with a range of assessment experiences and varied employment areas was recruited. A qualitative approach, using in-depth interviews with 13 graduates, with differing assessment experiences was undertaken. Graduates were asked to reflect upon their competency-based assessment experiences whilst a student. Data was thematically analysed by multiple authors. Results Four themes emerged from the data analysis: (i) Transparency and consistency are critical elements of work-based competency assessment. (ii) Students are willing to take greater responsibility in their assessment process. (iii) Work-based competency assessment prepares students for employment. (iv) The relationship between students and their assessors can impact on the student experience and their assessment performance. Conclusions Understanding this unique perspective of students can improve evaluation of future health professionals and assist in designing valid competency-based assessment approaches.

Brain networks subserving the evaluation of static and dynamic facial expressions

Because moving depictions of face emotion have greater ecological validity than their static counterparts, it has been suggested that still photographs may not engage ‘authentic’ mechanisms used to recognize facial expressions in everyday life. To date, however, no neuroimaging studies have adequately addressed the question of whether the processing of static and dynamic expressions rely upon different brain substrates. To address this, we performed an functional magnetic resonance imaging (fMRI) experiment wherein participants made emotional expression discrimination and Sex discrimination judgements to static and moving face images. Compared to Sex discrimination, Emotion discrimination was associated with widespread increased activation in regions of occipito-temporal, parietal and frontal cortex. These regions were activated both by moving and by static emotional stimuli, indicating a general role in the interpretation of emotion. However, portions of the inferior frontal gyri and supplementary/pre-supplementary motor area showed task by motion interaction. These regions were most active during emotion judgements to static faces. Our results demonstrate a common neural substrate for recognizing static and moving facial expressions, but suggest a role for the inferior frontal gyrus in supporting simulation processes that are invoked more strongly to disambiguate static emotional cues.

Evaluation of features for leaf classification in challenging conditions

Fine-grained leaf classification has concentrated on the use of traditional shape and statistical features to classify ideal images. In this paper we evaluate the effectiveness of traditional hand-crafted features and propose the use of deep convolutional neural network (ConvNet) features. We introduce a range of condition variations to explore the robustness of these features, including: translation, scaling, rotation, shading and occlusion. Evaluations on the Flavia dataset demonstrate that in ideal imaging conditions, combining traditional and ConvNet features yields state-of-theart performance with an average accuracy of 97:3%�0:6% compared to traditional features which obtain an average accuracy of 91:2%�1:6%. Further experiments show that this combined classification approach consistently outperforms the best set of traditional features by an average of 5:7% for all of the evaluated condition variations.

Implementation and evaluation of open source unified communications for SMBs

Unified Communication (UC) is the integration of two or more real time communication systems into one platform. Integrating core communication systems into one overall enterprise level system delivers more than just cost saving. These real-time interactive communication services and applications over Internet Protocol (IP) have become critical in boosting employee accessibility and efficiency, improving customer support and fostering business agility. However, some small and medium-sized businesses (SMBs) are far from implementing this solution due to the high cost of initial deployment and ongoing support. In this paper, we will discuss and demonstrate an open source UC solution, viz. “Asterisk” for use by SMBs, and report on some performance tests using SIPp. The contribution from this research is the provision of technical advice to SMBs in deploying UC, which is manageable in terms of cost, ease of deployment and support.

Design, construction and evaluation of systems to predict risk in obstetrics

We present a systematic, practical approach to developing risk prediction systems, suitable for use with large databases of medical information. An important part of this approach is a novel feature selection algorithm which uses the area under the receiver operating characteristic (ROC) curve to measure the expected discriminative power of different sets of predictor variables. We describe this algorithm and use it to select variables to predict risk of a specific adverse pregnancy outcome: failure to progress in labour. Neural network, logistic regression and hierarchical Bayesian risk prediction models are constructed, all of which achieve close to the limit of performance attainable on this prediction task. We show that better prediction performance requires more discriminative clinical information rather than improved modelling techniques. It is also shown that better diagnostic criteria in clinical records would greatly assist the development of systems to predict risk in pregnancy. We present a systematic, practical approach to developing risk prediction systems, suitable for use with large databases of medical information. An important part of this approach is a novel feature selection algorithm which uses the area under the receiver operating characteristic (ROC) curve to measure the expected discriminative power of different sets of predictor variables. We describe this algorithm and use it to select variables to predict risk of a specific adverse pregnancy outcome: failure to progress in labour. Neural network, logistic regression and hierarchical Bayesian risk prediction models are constructed, all of which achieve close to the limit of performance attainable on this prediction task. We show that better prediction performance requires more discriminative clinical information rather than improved modelling techniques. It is also shown that better diagnostic criteria in clinical records would greatly assist the development of systems to predict risk in pregnancy.

An evaluation of the neocognitron

We describe a sequence of experiments investigating the strengths and limitations of Fukushima's neocognitron as a handwritten digit classifier. Using the results of these experiments as a foundation, we propose and evaluate improvements to Fukushima's original network in an effort to obtain higher recognition performance. The neocognitron's performance is shown to be strongly dependent on the choice of selectivity parameters and we present two methods to adjust these variables. Performance of the network under the more effective of the two new selectivity adjustment techniques suggests that the network fails to exploit the features that distinguish different classes of input data. To avoid this shortcoming, the network's final layer cells were replaced by a nonlinear classifier (a multilayer perceptron) to create a hybrid architecture. Tests of Fukushima's original system and the novel systems proposed in this paper suggest that it may be difficult for the neocognitron to achieve the performance of existing digit classifiers due to its reliance upon the supervisor's choice of selectivity parameters and training data. These findings pertain to Fukushima's implementation of the system and should not be seen as diminishing the practical significance of the concept of hierarchical feature extraction embodied in the neocognitron. © 1997 IEEE.

Evaluation of channel congestion in dedicated short-range communication networks

This thesis presents a novel idea for an adaptive prioritized cross-layer design (APCLD) control algorithm to achieve comprehensive channel congestion control for vehicular safety communication based on DSRC technology. An appropriate evaluation metric and two control parameters have been established. Simulation studies have evaluated the DSRC network performance in different traffic scenario and under different channel conditions. The APCLD algorithm is derived from the results of the simulation analysis.