OSCE online : making assessment of clinical competencies transparent, accountable & authentic

Creating an authentic assessment which at once assesses competencies, scene management, communication and overall patient care is challenging in the competitive tertiary education market. Increasing student numbers and the cost of evaluating scenario based competencies serve to ensure the need for consistent objectivity and need for timely feedback to students on their performance. Objective structured clinical examination (OSCE) is currently the most flexible approach to competency based formative and summative assessment and widely used within paramedic degree programs. Students are understandably compelled to perform well and can be frustrated by not receiving timely and appropriate feedback. Increasingly a number of products aimed at providing a more efficient and paperless approach have begun to enter the market. These products, it is suggested are aimed at medicine programs and not at allied health professions and limited to one operating system and therefore ignore issues surrounding equity and accessibility. OSCE Online aims to address this gap in the market and is tailored to these disciplines. The application will provide a service that can be both tailored and standardised from a pre-written bank, depending upon requirement to fit around the needs of clinical competency assessment. Delivering authentic assessments to address student milestones in their training to become paramedics is the cornerstone of OSCE Online. By not being restricted to a specific device it will address issues of functionality, adaptability, accessibility, authenticity and importantly: transparency and accountability by producing contemporaneous data allowing issues to be easily identified and rectified.

Investigative journalism in a socially networked world

This article explores how investigative journalists can join the network society by moving online, collaborating with other reporters and media outlets across regions and across national borders, yet publishing in newspapers which arguably remain the central stage of the public sphere (Carson, 2013). A better understanding of the potential of social media and web-based communications for undertaking journalistic investigations can lead to the adoption of a global perspective, enriching local, regional and national stories (Berglez, 2013). The research and collaboration for a transnational story published simultaneously in The Australian and collaboration in London in 2013 may provide insights into the potential for the use of social media platforms and web-based communications for finding stories, collaborating and following stories into the social media to find leads to follow-up stories. This article questions whether the synergies between mainstream media and social media platforms may yield potentially high impact stories for major masthead newspapers and thus contribute to their sustainability. Connectivity with news sources has always been an important resource for journalists. Online networks may have the potential to expand the range of voices that can be heard and the issues that can be covered.

Load leveling in LV network using coordianted Energy Storage Units

This paper proposes a new distributed coordination approach to make load leveling, using Energy Storage Units (ESUs) in LV network. The proposed distributed control strategy is based on consensus algorithm which shares the required active power equally among the ESUs with respect to their rating. To show the effectiveness of the proposed approach, a typical radial LV network is simulated as a case study.

A coordinated voltage support strategy for LV network with multiple DSTATCOMs

Voltage rise and drop are the main power quality challenges in Low Voltage (LV) network with Renewable Energy (RE) generators. This paper proposes a new voltage support strategy based on coordination of multiple Distribution Static Synchronous Compensators (DSTATCOMs) using consensus algorithm. The study focuses on LV network with PV as the RE source for customers. The proposed approach applied to a typical residential LV network and its advantages are shown comparing with other voltage control strategies.

Voltage regulation, power balancing and battery storage discharge control by smart demand side management and multi-objective decision making

A novel intelligent online demand side management system is proposed for peak load management. The method also regulates the network voltage, balances the power in three phases and coordinates the battery storage discharge within the network. This method uses low cost controllers with low bandwidth two-way communication installed in costumers' premises and at distribution transformers to manage the peak load while maximizing customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified through an event-based developed simulation in Matlab.

On-line Demand Management of Low Voltage Residential Distribution Networks in Smart Grids

A novel intelligent online demand management system is discussed in this chapter for peak load management in low voltage residential distribution networks based on the smart grid concept. The discussed system also regulates the network voltage, balances the power in three phases and coordinates the energy storage within the network. This method uses low cost controllers, with two-way communication interfaces, installed in costumers’ premises and at distribution transformers to manage the peak load while maximizing customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified by a MATLAB-based simulation which includes detailed modeling of residential loads and the network.

Regulating online : participant-driven approaches

This thesis considers and evaluates different approaches to regulating online gaming communities, including traditional top-down regulation, as well as bottom-up and hybrid forms led by participants. I examine the regulatory environment in both the video game and gambling industries through case studies of the science fiction, massively multiplayer game Eve Online and offshore gambling platforms and their community sites. I identify that the participant driven approach to regulation sometimes used in the offshore gambling industry was dependent on a number of factors, notably the strength of the community and the risks to platform operators of negative publicity. By subsequently comparing this to the video gaming industry, I suggest that participant driven processes may be an appropriate way to resolve disputes in the games industry, and show how these are – to a limited extent – already being applied.

OnLine Ozonolysis Methods for the Determination of Double Bond Position in Unsaturated Lipids

Modern lipidomics relies heavily on mass spectrometry for the structural characterization and quantification of lipids of biological origins. Structural information is gained by tandem mass spectrometry (MS/MS) whereby lipid ions are fragmented to elucidate lipid class, fatty acid chain length, and degree of unsaturation. Unfortunately, however, in most cases double bond position cannot be assigned based on MS/MS data alone and thus significant structural diversity is hidden from such analyses. For this reason, we have developed two online methods for determining double bond position within unsaturated lipids; ozone electrospray ionization mass spectrometry (OzESI-MS) and ozone-induced dissociation (OzID). Both techniques utilize ozone to cleave C-C double bonds that result in chemically induced fragment ions that locate the position(s) of unsaturation

Sensor Network Based AUV Localisation

The operation of Autonomous Underwater Vehicles (AUVs) within underwater sensor network fields provides an opportunity to reuse the network infrastructure for long baseline localisation of the AUV. Computationally efficient localisation can be accomplished using off-the-shelf hardware that is comparatively inexpensive and which could already be deployed in the environment for monitoring purposes. This paper describes the development of a particle filter based localisation system which is implemented onboard an AUV in real-time using ranging information obtained from an ad-hoc underwater sensor network. An experimental demonstration of this approach was conducted in a lake with results presented illustrating network communication and localisation performance.

GNSS ambiguity resolution with controllable failure rate for long baseline network RTK

Many large-scale GNSS CORS networks have been deployed around the world to support various commercial and scientific applications. To make use of these networks for real-time kinematic positioning services, one of the major challenges is the ambiguity resolution (AR) over long inter-station baselines in the presence of considerable atmosphere biases. Usually, the widelane ambiguities are fixed first, followed by the procedure of determination of the narrowlane ambiguity integers based on the ionosphere-free model in which the widelane integers are introduced as known quantities. This paper seeks to improve the AR performance over long baseline through efficient procedures for improved float solutions and ambiguity fixing. The contribution is threefold: (1) instead of using the ionosphere-free measurements, the absolute and/or relative ionospheric constraints are introduced in the ionosphere-constrained model to enhance the model strength, thus resulting in the better float solutions; (2) the realistic widelane ambiguity precision is estimated by capturing the multipath effects due to the observation complexity, leading to improvement of reliability of widelane AR; (3) for the narrowlane AR, the partial AR for a subset of ambiguities selected according to the successively increased elevation is applied. For fixing the scalar ambiguity, an error probability controllable rounding method is proposed. The established ionosphere-constrained model can be efficiently solved based on the sequential Kalman filter. It can be either reduced to some special models simply by adjusting the variances of ionospheric constraints, or extended with more parameters and constraints. The presented methodology is tested over seven baselines of around 100 km from USA CORS network. The results show that the new widelane AR scheme can obtain the 99.4 % successful fixing rate with 0.6 % failure rate; while the new rounding method of narrowlane AR can obtain the fix rate of 89 % with failure rate of 0.8 %. In summary, the AR reliability can be efficiently improved with rigorous controllable probability of incorrectly fixed ambiguities.

Pulse-coupled neural network performance for real-time identification of vegetation during forced landing

Safety concerns in the operation of autonomous aerial systems require safe-landing protocols be followed during situations where the mission should be aborted due to mechanical or other failure. This article presents a pulse-coupled neural network (PCNN) to assist in the vegetation classification in a vision-based landing site detection system for an unmanned aircraft. We propose a heterogeneous computing architecture and an OpenCL implementation of a PCNN feature generator. Its performance is compared across OpenCL kernels designed for CPU, GPU, and FPGA platforms. This comparison examines the compute times required for network convergence under a variety of images to determine the plausibility for real-time feature detection.

Preventing pollution attacks in multi-source network coding

Network coding is a method for achieving channel capacity in networks. The key idea is to allow network routers to linearly mix packets as they traverse the network so that recipients receive linear combinations of packets. Network coded systems are vulnerable to pollution attacks where a single malicious node floods the network with bad packets and prevents the receiver from decoding correctly. Cryptographic defenses to these problems are based on homomorphic signatures and MACs. These proposals, however, cannot handle mixing of packets from multiple sources, which is needed to achieve the full benefits of network coding. In this paper we address integrity of multi-source mixing. We propose a security model for this setting and provide a generic construction.

University of Glasgow (qirdcsuog) at TREC Crowdsourcing 2011 : TurkRank-network-based worker ranking in crowdsourcing

For TREC Crowdsourcing 2011 (Stage 2) we propose a networkbased approach for assigning an indicative measure of worker trustworthiness in crowdsourced labelling tasks. Workers, the gold standard and worker/gold standard agreements are modelled as a network. For the purpose of worker trustworthiness assignment, a variant of the PageRank algorithm, named TurkRank, is used to adaptively combine evidence that suggests worker trustworthiness, i.e., agreement with other trustworthy co-workers and agreement with the gold standard. A single parameter controls the importance of co-worker agreement versus gold standard agreement. The TurkRank score calculated for each worker is incorporated with a worker-weighted mean label aggregation.

Mid-Holocene sea-level and coral reef demise : U-Th dating of subfossil corals in Moreton Bay, Australia

It is increasingly apparent that sea-level data (e.g. microfossil transfer functions, dated coral microatolls and direct observations from satellite and tidal gauges) vary temporally and spatially at regional to local scales, thus limiting our ability to model future sea-level rise for many regions. Understanding sealevel response at ‘far-field’ locations at regional scales is fundamental for formulating more relevant sea-level rise susceptibility models within these regions under future global change projections. Fossil corals and reefs in particular are valuable tools for reconstructing past sea levels and possible environmental phase shifts beyond the temporal constraints of instrumental records. This study used abundant surface geochronological data based on in situ subfossil corals and precise elevation surveys to determine previous sea level in Moreton Bay, eastern Australia, a far-field site. A total of 64 U-Th dates show that relative sea level was at least 1.1 m above modern lowest astronomical tide (LAT) from at least ˜6600 cal. yr BP. Furthermore, a rapid synchronous demise in coral reef growth occurred in Moreton Bay ˜5800 cal. yr BP, coinciding with reported reef hiatus periods in other areas around the Indo-Pacific region. Evaluating past reef growth patterns and phases allows for a better interpretation of anthropogenic forcing versus natural environmental/climatic cycles that effect reef formation and demise at all scales and may allow better prediction of reef response to future global change.

Combining recommender and reputation systems to produce better online advice

Although recommender systems and reputation systems have quite different theoretical and technical bases, both types of systems have the purpose of providing advice for decision making in e-commerce and online service environments. The similarity in purpose makes it natural to integrate both types of systems in order to produce better online advice, but their difference in theory and implementation makes the integration challenging. In this paper, we propose to use mappings to subjective opinions from values produced by recommender systems as well as from scores produced by reputation systems, and to combine the resulting opinions within the framework of subjective logic.