The LOFAR Transients Pipeline

Current and future astronomical survey facilities provide a remarkably rich opportunity for transient astronomy, combining unprecedented fields of view with high sensitivity and the ability to access previously unexplored wavelength regimes. This is particularly true of LOFAR, a recently-commissioned, low-frequency radio interferometer, based in the Netherlands and with stations across Europe. The identification of and response to transients is one of LOFAR's key science goals. However, the large data volumes which LOFAR produces, combined with the scientific requirement for rapid response, make automation essential. To support this, we have developed the LOFAR Transients Pipeline, or TraP. The TraP ingests multi-frequency image data from LOFAR or other instruments and searches it for transients and variables, providing automatic alerts of significant detections and populating a lightcurve database for further analysis by astronomers. Here, we discuss the scientific goals of the TraP and how it has been designed to meet them. We describe its implementation, including both the algorithms adopted to maximize performance as well as the development methodology used to ensure it is robust and reliable, particularly in the presence of artefacts typical of radio astronomy imaging. Finally, we report on a series of tests of the pipeline carried out using simulated LOFAR observations with a known population of transients.Comment: 30 pages, 11 figures; Accepted for publication in Astronomy & Computing; Code at https://github.com/transientskp/tk

Stability and sensitivity of Learning Analytics based prediction models

Learning analytics seek to enhance the learning processes through systematic measurements of learning related data and to provide informative feedback to learners and educators. Track data from Learning Management Systems (LMS) constitute a main data source for learning analytics. This empirical contribution provides an application of Buckingham Shum and Deakin Crick’s theoretical framework of dispositional learning analytics: an infrastructure that combines learning dispositions data with data extracted from computer-assisted, formative assessments and LMSs. In two cohorts of a large introductory quantitative methods module, 2049 students were enrolled in a module based on principles of blended learning, combining face-to-face Problem-Based Learning sessions with e-tutorials. We investigated the predictive power of learning dispositions, outcomes of continuous formative assessments and other system generated data in modelling student performance and their potential to generate informative feedback. Using a dynamic, longitudinal perspective, computer-assisted formative assessments seem to be the best predictor for detecting underperforming students and academic performance, while basic LMS data did not substantially predict learning. If timely feedback is crucial, both use-intensity related track data from e-tutorial systems, and learning dispositions, are valuable sources for feedback generation

Reducing the Barrier to Entry of Complex Robotic Software: a MoveIt! Case Study

Developing robot agnostic software frameworks involves synthesizing the disparate fields of robotic theory and software engineering while simultaneously accounting for a large variability in hardware designs and control paradigms. As the capabilities of robotic software frameworks increase, the setup difficulty and learning curve for new users also increase. If the entry barriers for configuring and using the software on robots is too high, even the most powerful of frameworks are useless. A growing need exists in robotic software engineering to aid users in getting started with, and customizing, the software framework as necessary for particular robotic applications. In this paper a case study is presented for the best practices found for lowering the barrier of entry in the MoveIt! framework, an open-source tool for mobile manipulation in ROS, that allows users to 1) quickly get basic motion planning functionality with minimal initial setup, 2) automate its configuration and optimization, and 3) easily customize its components. A graphical interface that assists the user in configuring MoveIt! is the cornerstone of our approach, coupled with the use of an existing standardized robot model for input, automatically generated robot-specific configuration files, and a plugin-based architecture for extensibility. These best practices are summarized into a set of barrier to entry design principles applicable to other robotic software. The approaches for lowering the entry barrier are evaluated by usage statistics, a user survey, and compared against our design objectives for their effectiveness to users

Model-based target sonification on mobile devices

We investigate the use of audio and haptic feedback to augment the display of a mobile device controlled by tilt input. We provide an example of this based on Doppler effects, which highlight the user's approach to a target, or a target's movement from the current state, in the same way we hear the pitch of a siren change as it passes us. Twelve participants practiced navigation/browsing a state-space that was displayed via audio and vibrotactile modalities. We implemented the experiment on a Pocket PC, with an accelerometer attached to the serial port and a headset attached to audio port. Users navigated through the environment by tilting the device. Feedback was provided via audio displayed via a headset, and by vibrotactile information displayed by a vibrotactile unit in the Pocket PC. Users selected targets placed randomly in the state-space, supported by combinations of audio, visual and vibrotactile cues. The speed of target acquisition and error rate were measured, and summary statistics on the acquisition trajectories were calculated. These data were used to compare different display combinations and configurations. The results in the paper quantified the changes brought by predictive or 'quickened' sonified displays in mobile, gestural interaction

The interaction of lean and building information modeling in construction

Lean construction and Building Information Modeling are quite different initiatives, but both are having profound impacts on the construction industry. A rigorous analysis of the myriad specific interactions between them indicates that a synergy exists which, if properly understood in theoretical terms, can be exploited to improve construction processes beyond the degree to which it might be improved by application of either of these paradigms independently. Using a matrix that juxtaposes BIM functionalities with prescriptive lean construction principles, fifty-six interactions have been identified, all but four of which represent constructive interaction. Although evidence for the majority of these has been found, the matrix is not considered complete, but rather a framework for research to explore the degree of validity of the interactions. Construction executives, managers, designers and developers of IT systems for construction can also benefit from the framework as an aid to recognizing the potential synergies when planning their lean and BIM adoption strategies

A review of human factors principles for the design and implementation of medication safety alerts in clinical information systems.

The objective of this review is to describe the implementation of human factors principles for the design of alerts in clinical information systems. First, we conduct a review of alarm systems to identify human factors principles that are employed in the design and implementation of alerts. Second, we review the medical informatics literature to provide examples of the implementation of human factors principles in current clinical information systems using alerts to provide medication decision support. Last, we suggest actionable recommendations for delivering effective clinical decision support using alerts. A review of studies from the medical informatics literature suggests that many basic human factors principles are not followed, possibly contributing to the lack of acceptance of alerts in clinical information systems. We evaluate the limitations of current alerting philosophies and provide recommendations for improving acceptance of alerts by incorporating human factors principles in their design

Supporting security-oriented, collaborative nanoCMOS electronics research

Grid technologies support collaborative e-Research typified by multiple institutions and resources seamlessly shared to tackle common research problems. The rules for collaboration and resource sharing are commonly achieved through establishment and management of virtual organizations (VOs) where policies on access and usage of resources by collaborators are defined and enforced by sites involved in the collaboration. The expression and enforcement of these rules is made through access control systems where roles/privileges are defined and associated with individuals as digitally signed attribute certificates which collaborating sites then use to authorize access to resources. Key to this approach is that the roles are assigned to the right individuals in the VO; the attribute certificates are only presented to the appropriate resources in the VO; it is transparent to the end user researchers, and finally that it is manageable for resource providers and administrators in the collaboration. In this paper, we present a security model and implementation improving the overall usability and security of resources used in Grid-based e-Research collaborations through exploitation of the Internet2 Shibboleth technology. This is explored in the context of a major new security focused project at the National e-Science Centre (NeSC) at the University of Glasgow in the nanoCMOS electronics domain