Circuit complexity in interacting QFTs and RG flows

We consider circuit complexity in certain interacting scalar quantum field theories, mainly focusing on the $\phi^4$ theory. We work out the circuit complexity for evolving from a nearly Gaussian unentangled reference state to the entangled ground state of the theory. Our approach uses Nielsen's geometric method, which translates into working out the geodesic equation arising from a certain cost functional. We present a general method, making use of integral transforms, to do the required lattice sums analytically and give explicit expressions for the $d=2,3$ cases. Our method enables a study of circuit complexity in the epsilon expansion for the Wilson-Fisher fixed point. We find that with increasing dimensionality the circuit depth increases in the presence of the $\phi^4$ interaction eventually causing the perturbative calculation to breakdown. We discuss how circuit complexity relates with the renormalization group.Comment: 50 pages, 2 figures; references updated; version to appear in JHE

Multivariate Correlation Analysis for Supervised Feature Selection in High-Dimensional Data

The main theme of this dissertation focuses on multivariate correlation analysis on different data types and we identify and define various research gaps in the same. For the defined research gaps we develop novel techniques that address relevance of features to the target and redundancy of features amidst themselves. Our techniques aim at handling homogeneous data, i.e., only continuous or categorical features, mixed data, i.e., continuous and categorical features, and time serie

Building robust prediction models for defective sensor data using Artificial Neural Networks

Predicting the health of components in complex dynamic systems such as an automobile poses numerous challenges. The primary aim of such predictive systems is to use the high-dimensional data acquired from different sensors and predict the state-of-health of a particular component, e.g., brake pad. The classical approach involves selecting a smaller set of relevant sensor signals using feature selection and using them to train a machine learning algorithm. However, this fails to address two prominent problems: (1) sensors are susceptible to failure when exposed to extreme conditions over a long periods of time; (2) sensors are electrical devices that can be affected by noise or electrical interference. Using the failed and noisy sensor signals as inputs largely reduce the prediction accuracy. To tackle this problem, it is advantageous to use the information from all sensor signals, so that the failure of one sensor can be compensated by another. In this work, we propose an Artificial Neural Network (ANN) based framework to exploit the information from a large number of signals. Secondly, our framework introduces a data augmentation approach to perform accurate predictions in spite of noisy signals. The plausibility of our framework is validated on real life industrial application from Robert Bosch GmbH.Comment: 16 pages, 7 figures. Currently under review. This research has obtained funding from the Electronic Components and Systems for European Leadership (ECSEL) Joint Undertaking, the framework programme for research and innovation Horizon 2020 (2014-2020) under grant agreement number 662189-MANTIS-2014-

Supplementary_2.pdf

ECML PKDD supplementary<br

Data_AppliedDataScience

Data for MANTIS-Bosch collaboration paper submitted for ECML-PKDD 2018.<div><br><div><div><br></div></div></div

The Catalan Teaching Tool – A Learning Process Design for Supplemental Instruction and Learning Process Facilitation

<div><p>ABSTRACT</p><p>This paper is based on a supplemental instruction technique aimed at disseminating a difficult concept at the undergraduate level. The software developed as a teaching tool attacks the problem from an intuitive perspective with the aid of visual tools. The tool, run as an experiment, conclusively proves that the original problem of calculating the number of paths from a point (0, 0) to any point (<i>n</i>, <i>n</i>) on a graph might be better understood. The moves can only be east and north in whole number increments and cannot exceed the <i>x</i> = <i>y</i> line at any point. A program is written to produce the graph. Incrementing the value of (<i>n</i>, <i>n</i>), the Catalan number series is produced. Another program is written using the formula which produces the Catalan numbers, and the growth of the series is determined. The teaching tool is created based on the algorithm. A robot is designed which follows the Catalan path is also demonstrated. A survey conducted using this teaching tool shows that it enhances the learning and understanding of Catalan numbers.</p></div

Personal protective equipment preparedness in Asia-Pacific intensive care units during the coronavirus disease 2019 pandemic: A multinational survey

Background There has been a surge in coronavirus disease 2019 admissions to intensive care units (ICUs) in Asia-Pacific countries. Because ICU healthcare workers are exposed to aerosol-generating procedures, ensuring optimal personal protective equipment (PPE) preparedness is important. Objective The aim of the study was to evaluate PPE preparedness across ICUs in six Asia-Pacific countries during the initial phase of the coronavirus disease 2019 pandemic, which is defined by the World Health Organization as guideline adherence, training healthcare workers, procuring stocks, and responding appropriately to suspected cases. Methods A cross-sectional Web-based survey was circulated to 633 level II/III ICUs of Australia, New Zealand (NZ), Singapore, Hong Kong (HK), India, and the Philippines. Findings Two hundred sixty-three intensivists responded, representing 231 individual ICUs eligible for analysis. Response rates were 68-100% in all countries except India, where it was 24%. Ninety-seven percent of ICUs either conformed to or exceeded World Health Organization recommendations for PPE practice. Fifty-nine percent ICUs used airborne precautions irrespective of aerosol generation procedures. There were variations in negative-pressure room use (highest in HK/Singapore), training (best in NZ), and PPE stock awareness (best in HK/Singapore/NZ). High-flow nasal oxygenation and noninvasive ventilation were not options in most HK (66.7% and 83.3%, respectively) and Singapore ICUs (50% and 80%, respectively), but were considered in other countries to a greater extent. Thirty-eight percent ICUs reported not having specialised airway teams. Showering and 'buddy systems' were underused. Clinical waste disposal training was suboptimal (38%). Conclusions Many ICUs in the Asia-Pacific reported suboptimal PPE preparedness in several domains, particularly related to PPE training, practice, and stock awareness, which requires remediation. Adoption of low-cost approaches such as buddy systems should be encouraged. The complete avoidance of high-flow nasal oxygenation reported by several intensivists needs reconsideration. Consideration must be given to standardise PPE guidelines to minimise practice variations. Urgent research to evaluate PPE preparedness and severe acute respiratory syndrome coronavirus 2 transmission is required

Personal protective equipment preparedness in intensive care units during the coronavirus disease 2019 pandemic: An Asia-Pacific follow-up survey

Background Personal-protective equipment (PPE)-preparedness, defined as adherence to guidelines, healthcare worker (HCW) training, procuring PPE stocks and responding appropriately to suspected cases, is crucial to prevent HCW-infections. Objective To perform a follow-up survey to assess changes in PPE-preparedness across six Asia-Pacific countries during the COVID-19 pandemic. Design Prospective follow-up cross-sectional, web-based survey between 10/08/2020 to 01/09/2020, five months after the initial Phase 1 survey. Setting The same six Asia-Pacific countries (Australia, Hong Kong, India, New Zealand, Philippines, and Singapore) that participated in Phase 1. Participants Intensivists from 231 ICUs across these six countries. Main outcome measures Changes in PPE-preparedness between Phases 1 and 2. Results Phase 2 had responses from 132 ICUs (57%). Compared to Phase 1 respondents reported increased use of PPE-based practices such as powered air-purifying respirator (40.2% vs. 6.1%), N95-masks at all times (86.4% vs. 53.7%) and double-gloving (87.9% vs. 42.9%). The reported awareness of PPE stocks (85.6% vs. 51.9%), mandatory showering policies following PPE-breach (31.1% vs. 6.9%) and safety perception amongst HCWs (60.6% vs. 28.4%) improved significantly during Phase 2. Despite reported statistically similar adoption rate of the buddy system in both phases (42.4% vs. 37.2%), there was a reported reduction in donning/doffing training in Phase 2 (44.3% vs. 60.2%). There were no reported differences HCW training in other areas, such as tracheal intubation, intra-hospital transport and safe waste disposal, between the 2 phases. Conclusions Overall reported PPE-preparedness improved between the two survey periods, particularly in PPE use, PPE inventory and HCW perceptions of safety. However, the uptake of HCW training and implementation of low-cost safety measures continued to be low and the awareness of PPE breach management policies were suboptimal. Therefore, the key areas for improvement should focus on regular HCW training, implementing low-cost buddy-system and increasing awareness of PPE-breach management protocols