Learning Design and Service Oriented Architectures:a mutual dependency?

This paper looks at how the concept of reusability has gained currency in e-learning. Initial attention was focused on reuse of content, but recently attention has focused on reusable software tools and reusable activity structures. The former has led to the proposal of service-oriented architectures, and the latter has seen the development of the Learning Design specification. The authors suggest that there is a mutual dependency between the success of these two approaches, as complex Learning Designs require the ability to call on a range of tools, while remaining technology neutral. The paper describes a project at the UK Open University, SLeD, which sought to develop a Learning Design player that would utilise the service-oriented approach. This acted both as a means of exploring some of the issues implicit within both approaches and also provided a practical tool. The SLeD system was successfully implemented in a different university, Liverpool Hope, demonstrating some of the principles of re-use

Calibration of sound source localisation for robots using multiple adaptive filter models of the cerebellum

The aim of this research was to investigate the calibration of Sound Source Localisation (SSL) for robots using the adaptive filter model of the cerebellum and how this could be automatically adapted for multiple acoustic environments. The role of the cerebellum has mainly been identified in the context of motor control, and only in recent years has it been recognised that it has a wider role to play in the senses and cognition. The adaptive filter model of the cerebellum has been successfully applied to a number of robotics applications but so far none involving auditory sense. Multiple models frameworks such as MOdular Selection And Identification for Control (MOSAIC) have also been developed in the context of motor control, and this has been the inspiration for adaptation of audio calibration in multiple acoustic environments; again, application of this approach in the area of auditory sense is completely new. The thesis showed that it was possible to calibrate the output of an SSL algorithm using the adaptive filter model of the cerebellum, improving the performance compared to the uncalibrated SSL. Using an adaptation of the MOSAIC framework, and specifically using responsibility estimation, a system was developed that was able to select an appropriate set of cerebellar calibration models and to combine their outputs in proportion to how well each was able to calibrate, to improve the SSL estimate in multiple acoustic contexts, including novel contexts. The thesis also developed a responsibility predictor, also part of the MOSAIC framework, and this improved the robustness of the system to abrupt changes in context which could otherwise have resulted in a large performance error. Responsibility prediction also improved robustness to missing ground truth, which could occur in challenging environments where sensory feedback of ground truth may become impaired, which has not been addressed in the MOSAIC literature, adding to the novelty of the thesis. The utility of the so-called cerebellar chip has been further demonstrated through the development of a responsibility predictor that is based on the adaptive filter model of the cerebellum, rather than the more conventional function fitting neural network used in the literature. Lastly, it was demonstrated that the multiple cerebellar calibration architecture is capable of limited self-organising from a de-novo state, with a predetermined number of models. It was also demonstrated that the responsibility predictor could learn against its model after self-organisation, and to a limited extent, during self-organisation. The thesis addresses an important question of how a robot could improve its ability to listen in multiple, challenging acoustic environments, and recommends future work to develop this ability

Mythologies of Loss

This Unit of Learning supports a six-week topic called “Mythologies of Loss” within a second year HE module “Twentieth-Century Readings”, which was run in a blended-learning situation at LHU. Learners were registered at LHU and studied part time at a satellite centre. Through this approach, course materials and group discussion took place online as well as at weekly evening sessions at the satellite centre. In creating the Unit of Learning an English tutor at Liverpool Hope University was supported in using the Reload IMS LD editor. The work was funded by the JISC project Learning Design for Practitioners, within the Design for Learning programme.JISC Design for Learning, LD4

High electrical conductance enhancement in Au-nanoparticle decorated sparse single-wall carbon nanotube networks

The authors thank the Engineering and Physical Science Research Council for funding through the Imperial College London/Queen Mary Unive

G96-1277 Pine Moths

Pine moths can seriously damage pine trees. This NebGuide helps you recognize damage and symptoms, identify the pest, and choose a control. Pine moths are serious pests of pines in Nebraska. Larvae (caterpillars) damage trees by tunneling just beneath the bark of the trunk and branches (Figure 1), most commonly on the trunk just below a branch. The tunnels they make can girdle the trunk or branches or physically weaken them so they are easily broken by wind or snow (Figure 2). Heavily infested trees are often deformed and are sometimes killed

Automatic Location of Blood Vessel Bifurcations in Digital Eye Fundus Images

Retinal blood vessels are linked with hypertension and cardiovascular disease. It is generally known that vascular bifurcation is mainly involved in varying blood flow velocity as well as its pressure. This paper presents an efficient method for automatic location of blood vessel bifurcations in digital eye fundus images. The proposed algorithm comprised of three main steps: image enhancement, fuzzy clustering, and searching vascular bifurcation. The purposed algorithm revealed successful detection of bifurcations upon test images. Results showed improved diagnostic accuracy in identifying bifurcations with use of the proposed algorithm and encourage its use for further applications such as image registration, personal identification and pre-clinical scanning of retina diagnosis

Audio Localization for Robots Using Parallel Cerebellar Models

© 2016 IEEE. A robot audio localization system is presented that combines the outputs of multiple adaptive filter models of the Cerebellum to calibrate a robot's audio map for various acoustic environments. The system is inspired by the MOdular Selection for Identification and Control (MOSAIC) framework. This study extends our previous work that used multiple cerebellar models to determine the acoustic environment in which a robot is operating. Here, the system selects a set of models and combines their outputs in proportion to the likelihood that each is responsible for calibrating the audio map as a robot moves between different acoustic environments or contexts. The system was able to select an appropriate set of models, achieving a performance better than that of a single model trained in all contexts, including novel contexts, as well as a baseline generalized cross correlation with phase transform sound source localization algorithm. The main contribution of this letter is the combination of multiple calibrators to allow a robot operating in the field to adapt to a range of different acoustic environments. The best performances were observed where the presence of a Responsibility Predictor was simulated

Self-adaptive context aware audio localization for robots using parallel cerebellar models

An audio sensor system is presented that uses multiple cerebellar models to determine the acoustic environment in which a robot is operating, allowing the robot to select appropriate models to calibrate its audio-motor map for the detected environment. The use of the adaptive filter model of the cerebellum in a variety of robotics applications has demonstrated the utility of the so-called cerebellar chip. This paper combines the notion of cerebellar calibration of a distorted audio-motor map with the use of multiple parallel models to predict the context (acoustic environment) within which the robot is operating. The system was able to correctly predict seven different acoustic contexts in almost 70% of cases tested

Continuous flow based catch and release protocol for the synthesis of alpha-ketoesters

Using a combination of commercially available mesofluidic flow equipment and tubes packed with immobilised reagents and scavengers, a new synthesis of α-ketoesters is reported