17837 research outputs found
Sort by
Centrifugal Pump Fault Detection with Convolutional Neural Network Transfer Learning
Get PDFThe centrifugal pump is the workhorse of many industrial and domestic applications, such as water supply, wastewater treatment and heating. While modern pumps are reliable, their unexpected failures may jeopardise safety or lead to significant financial losses. Consequently, there is a strong demand for early fault diagnosis, detection and predictive monitoring systems. Most prior work on machine-learning based centrifugal pump fault detection is based on either synthetic data, simulation or data from test rigs in controlled laboratory conditions. In this research paper, we attempt to detect centrifugal pump faults using data collected from real operational pumps deployed in various places in collaboration with a specialist pump engineering company. The detection is done by binary classifying visual features of DQ/Concordia patterns with residual networks. Besides using a real dataset, the paper employs transfer learning from image detection domain to systematically solve a real-life problem in engineering domain. By feeding DQ image data to popular and high-performance residual network (e.g ResNet-34), the proposed approach achieved up to 85.51% of classification accuracy.<br/
Nanofluidic Platform for Studying the First-Order Phase Transitions in Superfluid Helium-3
Get PDFThe symmetry-breaking first-order phase transition between superfluid phases 3He-A and 3He-B can be triggered extrinsically by ionising radiation or heterogeneous nucleation arising from the details of the sample cell construction. However, the role of potential homogeneous intrinsic nucleation mechanisms remains elusive. Discovering and resolving the intrinsic processes may have cosmological consequences, since an analogous first-order phase transition, and the production of gravitational waves, has been predicted for the very early stages of the expanding Universe in many extensions of the Standard Model of particle physics. Here we introduce a new approach for probing the phase transition in superfluid 3He. The setup consists of a novel stepped-height nanofluidic sample container with close to atomically smooth walls. The 3He is confined in five tiny nanofabricated volumes and assayed non-invasively by NMR. Tuning of the state of 3He by confinement is used to isolate each of these five volumes so that the phase transitions in them can occur independently and free from any obvious sources of heterogeneous nucleation. The small volumes also ensure that the transitions triggered by ionising radiation are strongly suppressed. Here we present the preliminary measurements using this setup, showing both strong supercooling of 3He-A and superheating of 3He-B, with stochastic processes dominating the phase transitions between the two. The objective is to study the nucleation as a function of temperature and pressure over the full phase diagram, to both better test the proposed extrinsic mechanisms and seek potential parallel intrinsic mechanisms
Transdiagnostic Psychological Interventions for Symptoms of Common Mental Disorders Delivered by Non-specialist Providers in Low- and Middle-Income Countries:A Systematic Review and Meta-Analysis
Get PDFPalaeoproteomic identification of the original binder and modern contaminants in distemper paints from Uvdal stave church, Norway
Get PDFUnleashed: walking dogs off the lead greatly increases habitat disturbance in UK lowland heathlands
Get PDFHuman population growth is associated with increased disturbance to wildlife. This effect is particularly acute in urban and periurban areas, where the area of effective disturbance extends beyond that of human presence by the roaming behaviour of pet dogs. Dogs are globally the dominant companion animal, with a population of ~ 12 million in the UK. As urban areas extend, dogs are exercised in green space close to housing. In southeast and southern England these areas include lowland heath, a habitat of high conservation value. To quantify disturbance caused by dog walkers and their dogs, we used GPS units to track the movement of people and their dogs across four lowland heath sites, used a questionnaire to ask about dog walking habits, and mapped potential areas of disturbance caused by dog walkers. Questionnaires were completed by 798 dog walkers and the walks of 162 owners and their 185 dogs were recorded. Mean (± SE) walk time was 56 ± 23 min, walk distance 3.75 ± 1.68 km and dogs were a median distance of 20 m from the owner during walks. Dogs were walked once (44%) or twice (56%) a day. Most (always: 85%; always or occasionally: 95%) dogs were walked off the lead even when signs were present requesting that dogs were kept on a lead. This resulted in up to a 21% increase in reserve area disturbed. In one reserve (Snelsmore Common), > 90% of the area was disturbed by dogs, greatly eroding its conservation value. This work highlights the importance of considering how dog ownership can exacerbate levels of disturbance in sensitive periurban habitats when housing developments are planned
ZKP Enabled Identity and Reputation Verification in P2P Marketplaces
Get PDFIn the realm of Distributed Ledger Technology, privacy and regulatory challenges loom large for marketplaces. Regulation requires to conduct Know Your Customer (KYC) procedures to verify the identity of participants, while privacy concerns necessitate the protection of personal data. Current approaches to KYC are inefficient and are potentially even harmful to privacy due to centralization and data exposure.This paper proposes a zero-knowledge proof enabled KYC scheme, utilizing Soulbound Tokens (SBT) to create a discreet, compliant, and secure KYC process. We present a privacy-preserving mechanism that shares only essential information while adhering to Self-Sovereign Identity (SSI) principles, placing users in the full control of their data. The proposed scheme further introduces the usage of SBTs for reputation to incentivize good conduct and build trust within marketplaces
The Influence of Technology Use on Learning Skills Among Generation Z:A Gender and Cross-country Analysis
Get PDFThis inquiry flags the shortage of evidence on the distinctive effect of technology use on defined learning skills. To tackle this inertia, it identifies (1) video gaming, (2) internet searching and (3) smartphone usage as ubiquitous forms of technology. Then, it characterises (1) abstract conceptualisation, (2) concrete experience and (3) reflective observation and active experimentation as dominant learning skills. Investigating a Nigeria and UK sample of 240 generation Z students, the associations are examined alongside the effects of gender and country. Based on a structural equation model, the analysis showed that although alternate uses of technology have mostly significant influences, their impact is largely negative with only internet searching having a positive effect on learning. The findings are explained through a cognitive load lens and insights are offered to learning providers to temper the appetite for technology use in instructional designs with thought and caution
Data sources:
Access Repository Dashboard
Do you manage Royal Holloway - Pure? Access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard!