The Regional Appropriateness of Monetary Policy: An Application of Taylor’s Rule to Australian States and Territories

In recent years Taylor’s rule has become a widely used tool for assessing the stance of monetary policy. Not only has it been used to evaluate the U.S. Federal Reserve’s monetary policy, but also, for example, to evaluate the appropriateness of the European Central Bank’s monetary policy for each individual member nation of the European Monetary Union. This paper builds on this work and uses Taylor’s rule to evaluate the degree of appropriateness of Australia’s national monetary policy to each of Australia’s states and territories. National monetary policy is represented by the overnight cash rate and this is compared to a notional cash rate calculated for each individual state and territory. The aim is to illustrate the extent to which national monetary policy historically may have deviated from what might have been most appropriate for the economic conditions of each state and territory. To this end, three different recent monetary policy episodes are analysed from a regional perspective. Moreover, an analysis of the disparities between the Australian states’ and territories’ notional cash rates with the actual national cash rate suggests – perhaps not too surprisingly - that the Reserve Bank of Australia implicitly sets national cash rates in close accordance with the economic conditions of Australia’s two most populous states.Taylor’s rule, monetary policy, Reserve Bank of Australia, regional

FaceQnet: Quality Assessment for Face Recognition based on Deep Learning

In this paper we develop a Quality Assessment approach for face recognition based on deep learning. The method consists of a Convolutional Neural Network, FaceQnet, that is used to predict the suitability of a specific input image for face recognition purposes. The training of FaceQnet is done using the VGGFace2 database. We employ the BioLab-ICAO framework for labeling the VGGFace2 images with quality information related to their ICAO compliance level. The groundtruth quality labels are obtained using FaceNet to generate comparison scores. We employ the groundtruth data to fine-tune a ResNet-based CNN, making it capable of returning a numerical quality measure for each input image. Finally, we verify if the FaceQnet scores are suitable to predict the expected performance when employing a specific image for face recognition with a COTS face recognition system. Several conclusions can be drawn from this work, most notably: 1) we managed to employ an existing ICAO compliance framework and a pretrained CNN to automatically label data with quality information, 2) we trained FaceQnet for quality estimation by fine-tuning a pre-trained face recognition network (ResNet-50), and 3) we have shown that the predictions from FaceQnet are highly correlated with the face recognition accuracy of a state-of-the-art commercial system not used during development. FaceQnet is publicly available in GitHub.Comment: Preprint version of a paper accepted at ICB 201

Estimating Carotid Pulse and Breathing Rate from Near-infrared Video of the Neck

Objective: Non-contact physiological measurement is a growing research area that allows capturing vital signs such as heart rate (HR) and breathing rate (BR) comfortably and unobtrusively with remote devices. However, most of the approaches work only in bright environments in which subtle photoplethysmographic and ballistocardiographic signals can be easily analyzed and/or require expensive and custom hardware to perform the measurements. Approach: This work introduces a low-cost method to measure subtle motions associated with the carotid pulse and breathing movement from the neck using near-infrared (NIR) video imaging. A skin reflection model of the neck was established to provide a theoretical foundation for the method. In particular, the method relies on template matching for neck detection, Principal Component Analysis for feature extraction, and Hidden Markov Models for data smoothing. Main Results: We compared the estimated HR and BR measures with ones provided by an FDA-cleared device in a 12-participant laboratory study: the estimates achieved a mean absolute error of 0.36 beats per minute and 0.24 breaths per minute under both bright and dark lighting. Significance: This work advances the possibilities of non-contact physiological measurement in real-life conditions in which environmental illumination is limited and in which the face of the person is not readily available or needs to be protected. Due to the increasing availability of NIR imaging devices, the described methods are readily scalable.Comment: 21 pages, 15 figure

Recent developments in nuclear structure theory: an outlook on the muonic atom program

The discovery of the proton-radius puzzle and the subsequent deuteron-radius puzzle is fueling an on-going debate on possible explanations for the difference in the observed radii obtained from muonic atoms and from electron-nucleus systems. Atomic nuclei have a complex internal structure that must be taken into account when analyzing experimental spectroscopic results. Ab initio nuclear structure theory provided the so far most precise estimates of important corrections to the Lamb shift in muonic atoms and is well poised to also investigate nuclear structure corrections to the hyperfine splitting in muonic atoms. Independently on whether the puzzle is due to beyond-the-standard-model physics or not, nuclear structure corrections are a necessary theoretical input to any experimental extraction of electric and magnetic radii from precise muonic atom measurements. Here, we review the status of the calculations performed by the TRIUMF-Hebrew University group, focusing on the deuteron, and discuss preliminary results on magnetic sum rules calculated with two-body currents at next-to-leading order. Two-body currents will be an important ingredient in future calculations of nuclear structure corrections to the hyperfine splitting in muonic atoms.Comment: 10 pages, accepted proceedings of the "55th International Winter Meeting on Nuclear Physics", 23-27 January 2017, to appear on Po

A Comparative Evaluation of Heart Rate Estimation Methods using Face Videos

This paper presents a comparative evaluation of methods for remote heart rate estimation using face videos, i.e., given a video sequence of the face as input, methods to process it to obtain a robust estimation of the subjects heart rate at each moment. Four alternatives from the literature are tested, three based in hand crafted approaches and one based on deep learning. The methods are compared using RGB videos from the COHFACE database. Experiments show that the learning-based method achieves much better accuracy than the hand crafted ones. The low error rate achieved by the learning based model makes possible its application in real scenarios, e.g. in medical or sports environments.Comment: Accepted in "IEEE International Workshop on Medical Computing (MediComp) 2020