Enhancing medical named entity recognition with an extended segment representation technique

Objective : The objective of this paper is to formulate an extended segment representation (SR) technique to enhance named entity recognition (NER) in medical applications.

Methods : An extension to the IOBES (Inside/Outside/Begin/End/Single) SR technique is formulated. In the proposed extension, a new class is assigned to words that do not belong to a named entity (NE) in one context but appear as an NE in other contexts. Ambiguity in such cases can negatively affect the results of classification-based NER techniques. Assigning a separate class to words that can potentially cause ambiguity in NER allows a classifier to detect NEs more accurately; therefore increasing classification accuracy.

Results : The proposed SR technique is evaluated using the i2b2 2010 medical challenge data set with eight different classifiers. Each classifier is trained separately to extract three different medical NEs, namely treatment, problem, and test. From the three experimental results, the extended SR technique is able to improve the average F1-measure results pertaining to seven out of eight classifiers. The kNN classifier shows an average reduction of 0.18% across three experiments, while the C4.5 classifier records an average improvement of 9.33%.

Extended conversation pieces

Extended Conversation Pieces brings together conversations about art, and conversation as art. The exhibition features collaborative works by six Brisbane emerging artists, Catherine or Kate (Catherine Sagin and Kate Woodcroft), Scott Ferguson (Erika Scott and Brooke Ferguson) and Courtney Coombs and Caitlin Franzmann. These artists engage with ideas of contemporary feminism through processes of dialogue and exchange; exploring subjectivity, humour and intimacy in performance and installation works. Extended Conversation Pieces showcases the distinctive approach to contemporary practice at Boxcopy, an artist run initiative focused on supporting and commissioning new experimental works by Australian artists, and engaging with collaborative processes and practices.

External impact of arts management research: An extended analysis

Arts management is a discipline whose research domain has grown in impact over the last quarter century.This study provides an external thematic, content and citation analysis of arts management articles in top-tiermainstream management and marketing journals between 1987 and 2010. It explicates article, author andcitation frequencies based on author information, publication patterns and thematic citation metrics, thuscontributing to the development of the arts management body of knowledge. Specifically, the study examinesthe function of arts management research as a bridging mechanism to its parent disciplines in managementand marketing. The authors identify thematic citation metrics of research published in mainstream journalsas well as frequencies and publication patterns, so that scholars can make decisions affecting their futureresearch directions. The authors conclude that there is little correlation between age/rank of journal andfrequency of citations, with younger journals becoming established as key players within relatively shortperiods.

Searching Baxter's URDF robot joint and link tree for active serial chains

Teleoperation is integral to society's uptake of modern robotic systems. Given the wide array of readily available robots, ranging from simple mobile platforms and UAVs to advanced humanoid robots such as ASIMO and PR2, teleoperation is required in many different forms. The recent advances in virtual reality systems, interactive input controls and even haptic devices facilitate a wide range of new approaches to teleoperation control. This paper considers a dynamic user interface for improving the operator's ability to teleoperate heterogeneous robotic systems in dynamic and challenging environments. In order to achieve the proposed dynamic user interface the robot(s) comprising the heterogeneous robotic system and their active components need to be categorized. The recent uptake of ROS means that many robots are now represented within the standardized Unified Robot Descriptive Format (URDF), and this paper proposes a method for searching the URDF for active serial chains in individual robot systems. Results demonstrate the ability of the approach to determine active serial chains and associated kinematic information for the Baxter torso robot.

The extended Infant Feeding, Activity and Nutrition Trial (InFANT Extend) Program : a cluster-randomized controlled trial of an early intervention to prevent childhood obesity

BACKGROUND: Understanding how we can prevent childhood obesity in scalable and sustainable ways is imperative. Early RCT interventions focused on the first two years of life have shown promise however, differences in Body Mass Index between intervention and control groups diminish once the interventions cease. Innovative and cost-effective strategies seeking to continue to support parents to engender appropriate energy balance behaviours in young children need to be explored. METHODS/DESIGN: The Infant Feeding Activity and Nutrition Trial (InFANT) Extend Program builds on the early outcomes of the Melbourne InFANT Program. This cluster randomized controlled trial will test the efficacy of an extended (33 versus 15 month) and enhanced (use of web-based materials, and Facebook® engagement), version of the original Melbourne InFANT Program intervention in a new cohort. Outcomes at 36 months of age will be compared against the control group. DISCUSSION: This trial will provide important information regarding capacity and opportunities to maximize early childhood intervention effectiveness over the first three years of life. This study continues to build the evidence base regarding the design of cost-effective, scalable interventions to promote protective energy balance behaviors in early childhood, and in turn, promote improved child weight and health across the life course. TRIAL REGISTRATION: ACTRN12611000386932 . Registered 13 April 2011.

Application of extended multivariate modeling for information flow analysis of event related responses

Event related potential (ERP) analysis is one of the most widely used methods in cognitive neuroscience research to study the physiological correlates of sensory, perceptual and cognitive activity associated with processing information. To this end information flow or dynamic effective connectivity analysis is a vital technique to understand the higher cognitive processing under different events. In this paper we present a Granger causality (GC)-based connectivity estimation applied to ERP data analysis. In contrast to the generally used strictly causal multivariate autoregressive model, we use an extended multivariate autoregressive model (eMVAR) which also accounts for any instantaneous interaction among variables under consideration. The experimental data used in the paper is based on a single subject data set for erroneous button press response from a two-back with feedback continuous performance task (CPT). In order to demonstrate the feasibility of application of eMVAR models in source space connectivity studies, we use cortical source time series data estimated using blind source separation or independent component analysis (ICA) for this data set.