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Articles 1 - 16 of 16
Full-Text Articles in Engineering
The Smart Dementia Care Project, Dympna O'Sullivan, Jonathan Turner, Ciaran Nugent, Damon Berry, Michael Wilson, Julie Doyle
The Smart Dementia Care Project, Dympna O'Sullivan, Jonathan Turner, Ciaran Nugent, Damon Berry, Michael Wilson, Julie Doyle
Articles
No abstract provided.
Monitoring Activities Of Daily Living For Maintaining Independent Living In Dementia, Jonathan Turner, Ciaran Nugent, Damon Berry, Dympna O'Sullivan, Michael Wilson, Julie Doyle
Monitoring Activities Of Daily Living For Maintaining Independent Living In Dementia, Jonathan Turner, Ciaran Nugent, Damon Berry, Dympna O'Sullivan, Michael Wilson, Julie Doyle
Articles
Our ability to live independent meaningful lives depends on our ability to perform various activities and to maintain our cognitive functions. Maintaining independent living is important for persons with dementia, it increases selfworth and allows to remain independent and in their own homes for longer. We describe the activities established as being important for the maintenance of independent living, and methods for monitoring these activities using technology.
Morton-Ordered Gpu Lattice Boltzmann Cfd Simulations With Application To Blood Flow, Gerald Gallagher, Fergal J. Boyle
Morton-Ordered Gpu Lattice Boltzmann Cfd Simulations With Application To Blood Flow, Gerald Gallagher, Fergal J. Boyle
Conference Papers
Computational fluid dynamics (CFD) is routinely used for numerically predicting cardiovascular-system medical device fluid flows. Most CFD simulations ignore the suspended cellular phases of blood due to computational constraints, which negatively affects simulation accuracy. A graphics processing unit (GPU) lattice Boltzmann-immersed boundary (LB-IB) CFD software package capable of accurately modelling blood flow is in development by the authors, focusing on the behaviour of plasma and stomatocyte, discocyte and echinocyte red blood cells during flow. Optimised memory ordering and layout schemes yield significant efficiency improvements for LB GPU simulations. In this work, comparisons of row-major-ordered Structure of Arrays (SoA) and Collected …
Accessdesign: An Inclusive Co-Design Toolkit For The Creation Of Accessible Digital Tools., Claudia Fernandez-Rivera, Sarah Boland, Eamon Aswad, John Gilligan, Dympna O'Sullivan, Emma Murphy
Accessdesign: An Inclusive Co-Design Toolkit For The Creation Of Accessible Digital Tools., Claudia Fernandez-Rivera, Sarah Boland, Eamon Aswad, John Gilligan, Dympna O'Sullivan, Emma Murphy
Articles
Existing toolkits and resources to support co-design are not always accessible to designers and co-designers with disabilities. In this paper we present a study based on an innovative co-design programme, in collaboration with St John of God Community Services, where 3rd year computer science students work with service users with intellectual disabilities to create digital applications together. We conducted a series of co-design focus group sessions involving the service users who were previously involved in the co-design collaboration with SJOG Services and TU Dublin. The data collected during these design sessions has been integrated to form an accessible design toolkit …
Create Research Symposium 2022 Book Of Abstracts, Ursa Benedicic, Brian Bowe Prof, Michael Carr Dr, Shannon Chance, Steen Hyldgaard Christensen, Eddie Conlon, Sandra Cruz, Gavin Duffy Dr, Fiona Faulkner Dr, Stella Malkogeorgou, John Mchugh, Mike Murphy Prof, Colm O'Kane Dr, Jye Benjamin O Sullivan, Marianna Pagkratidou Dr, Sheryl Sorby, Marten Westerhof
Create Research Symposium 2022 Book Of Abstracts, Ursa Benedicic, Brian Bowe Prof, Michael Carr Dr, Shannon Chance, Steen Hyldgaard Christensen, Eddie Conlon, Sandra Cruz, Gavin Duffy Dr, Fiona Faulkner Dr, Stella Malkogeorgou, John Mchugh, Mike Murphy Prof, Colm O'Kane Dr, Jye Benjamin O Sullivan, Marianna Pagkratidou Dr, Sheryl Sorby, Marten Westerhof
Other
This is the book of Abstracts for a recent symposium held by the CREATE research Group in TU Dublin.
Contributions Of Vibrational Spectroscopy To Virology: A Review, Iqra Chaudhary, Naomi Jackson, Denise Denning, Luke O'Neill, Hugh Byrne
Contributions Of Vibrational Spectroscopy To Virology: A Review, Iqra Chaudhary, Naomi Jackson, Denise Denning, Luke O'Neill, Hugh Byrne
Articles
Vibrational spectroscopic techniques, both infrared absorption and Raman scattering, are high precision, label free analytical techniques which have found applications in fields as diverse as analytical chemistry, pharmacology, forensics and archeometrics and, in recent times, have attracted increasing attention for biomedical applications. As analytical techniques, they have been applied to the characterisation of viruses as early as the 1970s, and, in the context of the coronavirus disease 2019 (COVID-19) pandemic, have been explored in response to the World Health Organisation as novel methodologies to aid in the global efforts to implement and improve rapid screening of viral infection. This review …
Limits Of Detection Of Mycotoxins By Laminar Flow Strips: A Review, Xinyi Zhao, Hugh Byrne, Christine M. O’Connor, James Curtin, Furong Tian
Limits Of Detection Of Mycotoxins By Laminar Flow Strips: A Review, Xinyi Zhao, Hugh Byrne, Christine M. O’Connor, James Curtin, Furong Tian
Articles
Mycotoxins are secondary metabolic products of fungi. They are poisonous, carcinogenic, and mutagenic in nature and pose a serious health threat to both humans and animals, causing severe illnesses and even death. Rapid, simple and low-cost methods of detection of mycotoxins are of immense importance and in great demand in the food and beverage industry, as well as in agriculture and environmental monitoring, and, for this purpose, lateral flow immunochromatographic strips (ICSTs) have been widely used in food safety and environmental monitoring. The literature to date describing the development of ICSTs for the detection of different types of mycotoxins using …
Dark Patterns: Effect On Overall User Experience And Site Revisitation, Deon Soul Calawen
Dark Patterns: Effect On Overall User Experience And Site Revisitation, Deon Soul Calawen
Dissertations
Dark patterns are user interfaces purposefully designed to manipulate users into doing something they might not otherwise do for the benefit of an online service. This study investigates the impact of dark patterns on overall user experience and site revisitation in the context of airline websites. In order to assess potential dark pattern effects, two versions of the same airline website were compared: a dark version containing dark pattern elements and a bright version free of manipulative interfaces. User experience for both websites were assessed quantitatively through a survey containing a User Experience Questionnaire (UEQ) and a System Usability Scale …
Towards Plasmon Mapping Of Sers-Active Ag Dewetted Nanostructures Using Spels, Mohamed Beshr, E. Dexter, Paul E. Tierney, Aidan Meade, Shane Murphy, George Amarandei
Towards Plasmon Mapping Of Sers-Active Ag Dewetted Nanostructures Using Spels, Mohamed Beshr, E. Dexter, Paul E. Tierney, Aidan Meade, Shane Murphy, George Amarandei
Articles
Thermal dewetting of silver thin flm can lead to SERS-active Ag nanoparticles. Here, we report our progress towards using scanning probe energy loss spectroscopy (SPELS) to map the plasmonic behaviour of SERS-active Ag nanoparticles (NP) by investigating NPs produced through the dewetting study of Ag thin flms on SiO2/Si and Ti/SiO2/Si substrates. The nanoparticles size and spatial distribution were controlled by the deposition and thermal annealing parameters. The results of preliminary SPELS measurements of these structures, alongside SERS data show that there is a correlation between the Raman enhancement and the nanoparticle size and interparticle spacing.
Data Driven Bayesian Network To Predict Critical Alarm, Joseph Mietkiewicz, Anders Madsen
Data Driven Bayesian Network To Predict Critical Alarm, Joseph Mietkiewicz, Anders Madsen
Articles
Modern industrial plants rely on alarm systems to ensure their safe and effective functioning. Alarms give the operator knowledge about the current state of the industrial plants. Trip alarms indicating a trip event indicate the shutdown of systems. Trip events in power plants can be costly and critical for the running of the operation.This paper demonstrates how trips events based on an alarm log from an offshore gas production can be reliably predicted using a Bayesian network. If a trip event is reliably predicted and the main cause of it is identified, it will allow the operator to prevent it. …
Application Of Climate-Smart Forestry – Forest Manager Response To The Relevance Of European Definition And Indicators, Euan Bowditch, Giovanni Santopuoli, Boyżdar Neroj, Jan Svetlik Jan Svetlik, Mark Tominlson, Vivien Pohl, Admir Avdagić, Miren Del Rio, Tzetvan Zlatanov Tzetvan Zlatanov, Höhn Maria, Gabriela Jamnická, Yusuf Serengil, Murat Sarginci, Sigríður Júlía Brynleifsdóttir, Jerzy Lesinki, João C. Azevedo
Application Of Climate-Smart Forestry – Forest Manager Response To The Relevance Of European Definition And Indicators, Euan Bowditch, Giovanni Santopuoli, Boyżdar Neroj, Jan Svetlik Jan Svetlik, Mark Tominlson, Vivien Pohl, Admir Avdagić, Miren Del Rio, Tzetvan Zlatanov Tzetvan Zlatanov, Höhn Maria, Gabriela Jamnická, Yusuf Serengil, Murat Sarginci, Sigríður Júlía Brynleifsdóttir, Jerzy Lesinki, João C. Azevedo
Articles
Climate change impacts are an increasing threat to forests and current approaches to management. In 2020, Climate-smart Forestry (CSF) definition and set of indicators was published. This study further developed this work by testing the definition and indicators through a forest manager survey across fifteen member European countries. The survey covered topic areas of demographics, climate change impacts, definition and indicators assessment, as well as knowledge and communication. Overall, forest managers considered the threat of climate change to their forests as high or critical and 62% found the CSF definition clear and concise; however, the minority suggested greater simplification or …
Advancing Competency In Managing Risk And Knowledge: Steps Toward Operationalisation Of The Risk-Knowledge Infinity Cycle (Rki Cycle) Part 3: Uncovering Knowledge For Qrm Through Knowledge Mapping At Node 1, Martin Lipa, Valerie Mulholland, Anne Greene
Advancing Competency In Managing Risk And Knowledge: Steps Toward Operationalisation Of The Risk-Knowledge Infinity Cycle (Rki Cycle) Part 3: Uncovering Knowledge For Qrm Through Knowledge Mapping At Node 1, Martin Lipa, Valerie Mulholland, Anne Greene
Articles
To date, literature on the Risk-Knowledge Infinity Cycle (RKI Cycle) has mainly been theoretical. This paper series intent is to focus on the operationalisation of the RKI Cycle by describing a series of steps – the “How to” – for RKI Cycle deployment, to help move the RKI Cycle from theory to practice. The third paper in this series focuses on ensuring the best available knowledge flows into QRM through a case study demonstrating knowledge mapping to support effective quality risk assessment during commissioning and qualification activities.
An Analysis On Network Flow-Based Iot Botnet Detection Using Weka, Cian Porteous
An Analysis On Network Flow-Based Iot Botnet Detection Using Weka, Cian Porteous
Dissertations
Botnets pose a significant and growing risk to modern networks. Detection of botnets remains an important area of open research in order to prevent the proliferation of botnets and to mitigate the damage that can be caused by botnets that have already been established. Botnet detection can be broadly categorised into two main categories: signature-based detection and anomaly-based detection. This paper sets out to measure the accuracy, false-positive rate, and false-negative rate of four algorithms that are available in Weka for anomaly-based detection of a dataset of HTTP and IRC botnet data. The algorithms that were selected to detect botnets …
Evaluating The Performance Of Vision Transformer Architecture For Deepfake Image Classification, Devesan Govindasamy
Evaluating The Performance Of Vision Transformer Architecture For Deepfake Image Classification, Devesan Govindasamy
Dissertations
Deepfake classification has seen some impressive results lately, with the experimentation of various deep learning methodologies, researchers were able to design some state-of-the art techniques. This study attempts to use an existing technology “Transformers” in the field of Natural Language Processing (NLP) which has been a de-facto standard in text processing for the purposes of Computer Vision. Transformers use a mechanism called “self-attention”, which is different from CNN and LSTM. This study uses a novel technique that considers images as 16x16 words (Dosovitskiy et al., 2021) to train a deep neural network with “self-attention” blocks to detect deepfakes. It creates …
Measuring And Comparing Social Bias In Static And Contextual Word Embeddings, Alan Cueva Mora
Measuring And Comparing Social Bias In Static And Contextual Word Embeddings, Alan Cueva Mora
Dissertations
Word embeddings have been considered one of the biggest breakthroughs of deep learning for natural language processing. They are learned numerical vector representations of words where similar words have similar representations. Contextual word embeddings are the promising second-generation of word embeddings assigning a representation to a word based on its context. This can result in different representations for the same word depending on the context (e.g. river bank and commercial bank). There is evidence of social bias (human-like implicit biases based on gender, race, and other social constructs) in word embeddings. While detecting bias in static (classical or non-contextual) word …
Investigating How Speech And Animation Realism Influence The Perceived Personality Of Virtual Characters And Agents, Sean A. Thomas, Ylva Ferstl, Rachel Mcdonnell, Cathy Ennis
Investigating How Speech And Animation Realism Influence The Perceived Personality Of Virtual Characters And Agents, Sean A. Thomas, Ylva Ferstl, Rachel Mcdonnell, Cathy Ennis
Articles
The portrayed personality of virtual characters and agents is understood to influence how we perceive and engage with digital applications. Understanding how the features of speech and animation drive portrayed personality allows us to intentionally design characters to be more personalized and engaging. In this study, we use performance capture data of unscripted conversations from a variety of actors to explore the perceptual outcomes associated with the modalities of speech and motion. Specifically, we contrast full performance-driven characters to those portrayed by generated gestures and synthesized speech, analysing how the features of each influence portrayed personality according to the Big …