Teaching Compositionality to CNNs

Convolutional neural networks (CNNs) have shown great success in computer vision, approaching human-level performance when trained for specific tasks via application-specific loss functions. In this paper, we propose a method for augmenting and training CNNs so that their learned features are compositional. It encourages networks to form representations that disentangle objects from their surroundings and from each other, thereby promoting better generalization. Our method is agnostic to the specific details of the underlying CNN to which it is applied and can in principle be used with any CNN. As we show in our experiments, the learned representations lead to feature activations that are more localized and improve performance over non-compositional baselines in object recognition tasks.Comment: Preprint appearing in CVPR 201

Spontaneous extrusion of gallstones after percutaneous drainage

There have been reports of late discharge of gallstones through operative wounds after spillage into the peritoneal cavity during laparoscopic cholecystectomy and after the development of spontaneous cholecystocutaneous fistulae. However, spontaneous discharge of gallstones from the tract of a percutaneous cholecystostomy or percutaneous drainage of a perforated gall bladder has not, to the best of our knowledge, been reported previously. We report a case in which a patient who had a percutaneous drain inserted for a perforated gall bladder discharged 34 gallstones from the tract after removal of the 7-F pigtail catheter

Off-the-shelf Non-Intrusive Load Monitoring Devices Utilised in a Low Activity Detection Service

There is a growing awareness for the need to provide low cost solutions for the care of the elderly and in particular to allow them to keep living independent lives. In parallel to this there has also been significant advances in a number of technical areas including 1) monitoring electricity consumption for the purpose of reducing power costs, 2) non-intrusive load monitoring (NILM), 3) using sensors to determine activities of daily living and 4) cloud computing. The purpose of this work was to demonstrate that it is possible to use a readily available consumer off the shelf electricity monitor to provide a low intrusive activity monitor for older persons. This work uses the Design Science Research Methodology and builds on the results of our previous work that used raw electricity usage data. In this work we are trailing the use of a meter that uses NILM to identify individual appliances in the home. The information on appliance use was analysed by a cloud base program and alerts were sent to the carer when lower than expected activity was detected. Participants both in this work and those reported in the literature have mentioned the annoyance of having multiple sensors in a home, especially if they emit either constant or flashing light. In contrast NILM allows the use of multiple electrical appliances to be monitored without the need for a large number of sensors to be deployed – just one sensor at the meter or fuse board. The confluence of a number of technologies has enabled the creation of a low intrusive and low cost monitoring system to have become a reality. The initial trial of the system has been shown to be a mostly reliable alternative to a system built on multiple sensors. Based on previous work that involved the deployment of multiple sensors, the new system is expected to be more acceptable as it has the desired attribute of becoming invisible to the user

A minimally intrusive monitoring system that utilizes electricity consumption as a proxy for wellbeing

The purpose of this work was to test the hypothesis: `Off-the-shelf domestic electricity meters can be utilised to assist in monitoring the wellbeing of elderly people` Many studies have shown that it is, in theory, possible to use domestic electricity consumption to determine `activities of daily living` but the availability of systems for actual use is very limited. This work followed the Design Science Research Methodology to create a Java application running on the Google App Engine cloud service that interfaced with both electricity meters and voice and text services. The system was implemented and tested over a three month period with one older person and their carer. Results demonstrated that the technology readily succeeds in meeting the study`s initial objectives. The need for more sophisticated decision logic was apparent and a method to determine whether a home is currently occupied is likely to improve the ability to create more timely alerts

Assisted Living: Domestic Power Monitoring utilising Home Automation Products and Cloud Storage

This paper describes the development of a system for taking measurements of electrical power consumption in a domestic situation and using a web service to store the measurements in a cloud hosted database. This is part of a larger project to evaluate the potential for using power monitoring as a proxy for wellness as part of the assisted living projects at Wintec

Theory of noise suppression in {\Lambda}-type quantum memories by means of a cavity

Quantum memories, capable of storing single photons or other quantum states of light, to be retrieved on-demand, offer a route to large-scale quantum information processing with light. A promising class of memories is based on far-off-resonant Raman absorption in ensembles of $\Lambda$-type atoms. However at room temperature these systems exhibit unwanted four-wave mixing, which is prohibitive for applications at the single-photon level. Here we show how this noise can be suppressed by placing the storage medium inside a moderate-finesse optical cavity, thereby removing the main roadblock hindering this approach to quantum memory.Comment: 10 pages, 3 figures. This paper provides the theoretical background to our recent experimental demonstration of noise suppression in a cavity-enhanced Raman-type memory ( arXiv:1510.04625 ). See also the related paper arXiv:1511.05448, which describes numerical modelling of an atom-filled cavity. Comments welcom

Dyon Spectrum in Generic N=4 Supersymmetric Z_N Orbifolds

We find the exact spectrum of a class of quarter BPS dyons in a generic N=4 supersymmetric Z_N orbifold of type IIA string theory on K3\times T^2 or T^6. We also find the asymptotic expansion of the statistical entropy to first non-leading order in inverse power of charges and show that it agrees with the entropy of a black hole carrying same set of charges after taking into account the effect of the four derivative Gauss-Bonnet term in the effective action of the theory.Comment: LaTeX file, 39 pages; minor change

Adding Charges to N=4 Dyons

The spectrum of dyons in a class of N=4 supersymmetric string theories has been found for a specific set of electric and magnetic charge vectors. We extend the analysis to more general charge vectors by considering various charge carrying collective excitations of the original system.Comment: LaTeX file, 16 page

Dyon Spectrum in CHL Models

We propose a formula for the degeneracy of quarter BPS dyons in a class of CHL models. The formula uses a modular form of a subgroup of the genus two modular group Sp(2,Z). Our proposal is S-duality invariant and reproduces correctly the entropy of a dyonic black hole to first non-leading order for large values of the charges.Comment: LaTeX file, 38 pages, minor changes in section 3.3(v2), minor changes in introduction, appendix A and C(v3