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Articles 1 - 30 of 68
Full-Text Articles in Physical Sciences and Mathematics
A Framework Of Web-Based Dark Patterns That Can Be Detected Manually Or Automatically, Ioannis Stavrakakis, Andrea Curley, Dympna O'Sullivan, Damian Gordon, Brendan Tierney
A Framework Of Web-Based Dark Patterns That Can Be Detected Manually Or Automatically, Ioannis Stavrakakis, Andrea Curley, Dympna O'Sullivan, Damian Gordon, Brendan Tierney
Articles
This research explores the design and development of a framework for the detection of Dark Patterns, which are a series of user interface tricks that manipulate users into actions that they do not intend to do, for example, share more data than they want to, or spend more money than they plan to. The interface does this using either deception or other psychological nudges. User Interface experts have categorized a number of these tricks that are commonly used and have called them Dark Patterns. They are typically varied in their form and what they do, and the goal of this …
Explaining Deep Learning Models For Tabular Data Using Layer-Wise Relevance Propagation, Ihsan Ullah, Andre Rios, Vaibhov Gala, Susan Mckeever
Explaining Deep Learning Models For Tabular Data Using Layer-Wise Relevance Propagation, Ihsan Ullah, Andre Rios, Vaibhov Gala, Susan Mckeever
Articles
Trust and credibility in machine learning models are bolstered by the ability of a model to explain its decisions. While explainability of deep learning models is a well-known challenge, a further challenge is clarity of the explanation itself for relevant stakeholders of the model. Layer-wise Relevance Propagation (LRP), an established explainability technique developed for deep models in computer vision, provides intuitive human-readable heat maps of input images. We present the novel application of LRP with tabular datasets containing mixed data (categorical and numerical) using a deep neural network (1D-CNN), for Credit Card Fraud detection and Telecom Customer Churn prediction use …
Extending R2rml-F To Support Dynamic Datatype And Language Tags, Aparna Nayak, Bojan Bozic, Luca Longo
Extending R2rml-F To Support Dynamic Datatype And Language Tags, Aparna Nayak, Bojan Bozic, Luca Longo
Conference papers
Linked data is often generated from raw data with the help of mapping languages. Complex data transformation is one of the essential parts while uplifting data which either can be implemented as custom solutions or separated from the mapping process. In this paper, we propose an approach of separating complex data transformations from the mapping process that can still be reusable across the systems. In the proposed method, complex data transformations include the entailment of (i) language tag and (ii) datatype present at the data source. The proposed method also includes inferring missing datatype information. We extended R2RML-F to handle …
Notions Of Explainability And Evaluation Approaches For Explainable Artificial Intelligence, Giulia Vilone, Luca Longo
Notions Of Explainability And Evaluation Approaches For Explainable Artificial Intelligence, Giulia Vilone, Luca Longo
Articles
Explainable Artificial Intelligence (XAI) has experienced a significant growth over the last few years. This is due to the widespread application of machine learning, particularly deep learning, that has led to the development of highly accurate models that lack explainability and interpretability. A plethora of methods to tackle this problem have been proposed, developed and tested, coupled with several studies attempting to define the concept of explainability and its evaluation. This systematic review contributes to the body of knowledge by clustering all the scientific studies via a hierarchical system that classifies theories and notions related to the concept of explainability …
A Novel Parabolic Model Of Instructional Efficiency Grounded On Ideal Mental Workload And Performance, Luca Longo, Murali Rajendran
A Novel Parabolic Model Of Instructional Efficiency Grounded On Ideal Mental Workload And Performance, Luca Longo, Murali Rajendran
Articles
Instructional efficiency within education is a measurable concept and models have been proposed to assess it. The main assumption behind these models is that efficiency is the capacity to achieve established goals at the minimal expense of resources. This article challenges this assumption by contributing to the body of Knowledge with a novel model that is grounded on ideal mental workload and performance, namely the parabolic model of instructional efficiency. A comparative empirical investigation has been constructed to demonstrate the potential of this model for instructional design evaluation. Evidence demonstrated that this model achieved a good concurrent validity with the …
Provenance: An Intermediary-Free Solution For Digital Content Verification, Bilal Yousuf, M. Atif Qureshi, Brendan Spillane, Gary Munnelly, Oisin Carroll, Matthew Runswick, Kirsty Park, Eileen Culloty, Owen Conlan, Jane Suiter
Provenance: An Intermediary-Free Solution For Digital Content Verification, Bilal Yousuf, M. Atif Qureshi, Brendan Spillane, Gary Munnelly, Oisin Carroll, Matthew Runswick, Kirsty Park, Eileen Culloty, Owen Conlan, Jane Suiter
Articles
The threat posed by misinformation and disinformation is one of the defining challenges of the 21st century. Provenance is designed to help combat this threat by warning users when the content they are looking at may be misinformation or disinformation. It is also designed to improve media literacy among its users and ultimately reduce susceptibility to the threat among vulnerable groups within society. The Provenance browser plugin checks the content that users see on the Internet and social media and provides warnings in their browser or social media feed. Unlike similar plugins, which require human experts to provide evaluations and …
Towards A Framework For Comparing Functionalities Of Multimorbidity Clinical Decision Support: A Literature-Based Feature Set And Benchmark Cases., Dympna O'Sullivan, William Van Woensel, Szymon Wilk, Samson Tu, Wojtek Michalowski, Samina Abidi, Marc Carrier, Ruth Edry, Irit Hochberg, Stephen Kingwell, Alexandra Kogan, Martin Michalowski, Hugh O'Sullivan, Mor Peleg
Towards A Framework For Comparing Functionalities Of Multimorbidity Clinical Decision Support: A Literature-Based Feature Set And Benchmark Cases., Dympna O'Sullivan, William Van Woensel, Szymon Wilk, Samson Tu, Wojtek Michalowski, Samina Abidi, Marc Carrier, Ruth Edry, Irit Hochberg, Stephen Kingwell, Alexandra Kogan, Martin Michalowski, Hugh O'Sullivan, Mor Peleg
Articles
Multimorbidity, the coexistence of two or more health conditions, has become more prevalent as mortality rates in many countries have declined and their populations have aged. Multimorbidity presents significant difficulties for Clinical Decision Support Systems (CDSS), particularly in cases where recommendations from relevant clinical guidelines offer conflicting advice. A number of research groups are developing computer-interpretable guideline (CIG) modeling formalisms that integrate recommendations from multiple Clinical Practice Guidelines (CPGs) for knowledge-based multimorbidity decision support. In this paper we describe work towards the development of a framework for comparing the different approaches to multimorbidity CIG-based clinical decision support (MGCDS). We present …
A Quantitative Evaluation Of Global, Rule-Based Explanations Of Post-Hoc, Model Agnostic Methods, Giulia Vilone, Luca Longo
A Quantitative Evaluation Of Global, Rule-Based Explanations Of Post-Hoc, Model Agnostic Methods, Giulia Vilone, Luca Longo
Articles
Understanding the inferences of data-driven, machine-learned models can be seen as a process that discloses the relationships between their input and output. These relationships consist and can be represented as a set of inference rules. However, the models usually do not explicit these rules to their end-users who, subsequently, perceive them as black-boxes and might not trust their predictions. Therefore, scholars have proposed several methods for extracting rules from data-driven machine-learned models to explain their logic. However, limited work exists on the evaluation and comparison of these methods. This study proposes a novel comparative approach to evaluate and compare the …
Check Your Tech - The Ethics Of Deepfakes In A Political Context, Dympna O'Sullivan, Damian Gordon, Ioannis Stavrakakis, Michael Collins
Check Your Tech - The Ethics Of Deepfakes In A Political Context, Dympna O'Sullivan, Damian Gordon, Ioannis Stavrakakis, Michael Collins
Conference papers
No abstract provided.
Check Your Tech - The Ethics Of Gamification In Education, Dympna O'Sullivan, Ioannis Stavrakakis, Damian Gordon, Anna Becevel
Check Your Tech - The Ethics Of Gamification In Education, Dympna O'Sullivan, Ioannis Stavrakakis, Damian Gordon, Anna Becevel
Conference papers
No abstract provided.
The Future Of Medicine Is Digital: Developing Educational Materials To Explore The Ethics Of Digital Pills., Dympna O'Sullivan, J. Paul Gibson, Yael Jacob, Ioannis Stavrakakis, Damian Gordon
The Future Of Medicine Is Digital: Developing Educational Materials To Explore The Ethics Of Digital Pills., Dympna O'Sullivan, J. Paul Gibson, Yael Jacob, Ioannis Stavrakakis, Damian Gordon
Conference papers
Digital Pills are a drug-device technology that permit to combine traditional medications with a monitoring system that automatically records data about medication adherence and patients’ physiological data. They are a promising innovation in digital medicine, however their use has raised a number of ethical concerns. In this paper, we outline some of the main Digital Pills technologies and explore key ethical challenges surrounding their use. In this paper, we introduce educational materials we have developed that provide an insight into the technologies and ethical aspects that underpin Digital Pills.
Cleanpage: Fast And Clean Document And Whiteboard Capture, Jane Courtney
Cleanpage: Fast And Clean Document And Whiteboard Capture, Jane Courtney
Articles
The move from paper to online is not only necessary for remote working, it is also significantly more sustainable. This trend has seen a rising need for the high-quality digitization of content from pages and whiteboards to sharable online material. However, capturing this information is not always easy nor are the results always satisfactory. Available scanning apps vary in their usability and do not always produce clean results, retaining surface imperfections from the page or whiteboard in their output images. CleanPage, a novel smartphone-based document and whiteboard scanning system, is presented. CleanPage requires one button-tap to capture, identify, crop, and …
(Linked) Data Quality Assessment: An Ontological Approach, Aparna Nayak, Bojan Bozic, Luca Longo
(Linked) Data Quality Assessment: An Ontological Approach, Aparna Nayak, Bojan Bozic, Luca Longo
Conference papers
The effective functioning of data-intensive applications usually requires that the dataset should be of high quality. The quality depends on the task they will be used for. However, it is possible to identify task-independent data quality dimensions which are solely related to data themselves and can be extracted with the help of rule mining/pattern mining. In order to assess and improve data quality, we propose an ontological approach to report data quality violated triples. Our goal is to provide data stakeholders with a set of methods and techniques to guide them in assessing and improving data quality
Human Or Robot?: Investigating Voice, Appearance And Gesture Motion Realism Of Conversational Social Agents, Ylva Ferstl, Sean Thomas, Cédric Guiard, Cathy Ennis, Rachel Mcdonnell
Human Or Robot?: Investigating Voice, Appearance And Gesture Motion Realism Of Conversational Social Agents, Ylva Ferstl, Sean Thomas, Cédric Guiard, Cathy Ennis, Rachel Mcdonnell
Conference papers
Research on creation of virtual humans enables increasing automatization of their behavior, including synthesis of verbal and nonverbal behavior. As the achievable realism of different aspects of agent design evolves asynchronously, it is important to understand if and how divergence in realism between behavioral channels can elicit negative user responses. Specifically, in this work, we investigate the question of whether autonomous virtual agents relying on synthetic text-to-speech voices should portray a corresponding level of realism in the non-verbal channels of motion and visual appearance, or if, alternatively, the best available realism of each channel should be used. In two perceptual …
The Development Of Teaching Case Studies To Explore Ethical Issues Associated With Computer Programming, Michael Collins, Damian Gordon, Dympna O'Sullivan
The Development Of Teaching Case Studies To Explore Ethical Issues Associated With Computer Programming, Michael Collins, Damian Gordon, Dympna O'Sullivan
Conference papers
In the past decade software products have become pervasive in many aspects of people’s lives around the world. Unfortunately, the quality of the experience an individual has interacting with that software is dependent on the quality of the software itself, and it is becoming more and more evident that many large software products contain a range of issues and errors, and these issues are not known to the developers of these systems, and they are unaware of the deleterious impacts of those issues on the individuals who use these systems. The authors of this paper are developing a new digital …
Exploring The Personality Of Virtual Tutors In Conversational Foreign Language Practice, Johanna Dobbriner, Cathy Ennis, Robert J. Ross
Exploring The Personality Of Virtual Tutors In Conversational Foreign Language Practice, Johanna Dobbriner, Cathy Ennis, Robert J. Ross
Conference papers
Fluid interaction between virtual agents and humans requires the understanding of many issues of conversational pragmatics. One such issue is the interaction between communication strategy and personality. As a step towards developing models of personality driven pragmatics policies, in this paper, we present our initial experiment to explore differences in user interaction with two contrasting avatar personalities. Each user saw a single personality in a video-call setting and gave feedback on the interaction. Our expectations, that a more extroverted outgoing positive personality would be a more successful tutor, were only partially confirmed. While this personality did induce longer conversations in …
Sediqa: Sound Emitting Document Image Quality Assessment In A Reading Aid For The Visually Impaired, Jane Courtney
Sediqa: Sound Emitting Document Image Quality Assessment In A Reading Aid For The Visually Impaired, Jane Courtney
Articles
For visually impaired people (VIPs), the ability to convert text to sound can mean a new level of independence or the simple joy of a good book. With significant advances in optical character recognition (OCR) in recent years, a number of reading aids are appearing on the market. These reading aids convert images captured by a camera to text which can then be read aloud. However, all of these reading aids suffer from a key issue—the user must be able to visually target the text and capture an image of sufficient quality for the OCR algorithm to function—no small task …
Classification Of Explainable Artificial Intelligence Methods Through Their Output Formats, Giulia Vilone, Luca Longo
Classification Of Explainable Artificial Intelligence Methods Through Their Output Formats, Giulia Vilone, Luca Longo
Articles
Machine and deep learning have proven their utility to generate data-driven models with high accuracy and precision. However, their non-linear, complex structures are often difficult to interpret. Consequently, many scholars have developed a plethora of methods to explain their functioning and the logic of their inferences. This systematic review aimed to organise these methods into a hierarchical classification system that builds upon and extends existing taxonomies by adding a significant dimension—the output formats. The reviewed scientific papers were retrieved by conducting an initial search on Google Scholar with the keywords “explainable artificial intelligence”; “explainable machine learning”; and “interpretable machine learning”. …
Adaptable And Reusable Educational ‘Bricks’ For Teaching Computer Science Ethics, Andrea Curley, Damian Gordon, Ioannis Stavrakakis, Anna Becevel, J.P. Gibson, Dympna O'Sullivan
Adaptable And Reusable Educational ‘Bricks’ For Teaching Computer Science Ethics, Andrea Curley, Damian Gordon, Ioannis Stavrakakis, Anna Becevel, J.P. Gibson, Dympna O'Sullivan
Conference papers
No abstract provided.
Multi-Modal Self-Supervised Representation Learning For Earth Observation, Pallavi Jain, Bianca Schoen Phelan, Robert J. Ross
Multi-Modal Self-Supervised Representation Learning For Earth Observation, Pallavi Jain, Bianca Schoen Phelan, Robert J. Ross
Conference papers
Self-Supervised learning (SSL) has reduced the performance gap between supervised and unsupervised learning, due to its ability to learn invariant representations. This is a boon to the domains like Earth Observation (EO), where labelled data availability is scarce but unlabelled data is freely available. While Transfer Learning from generic RGB pre-trained models is still common-place in EO, we argue that, it is essential to have good EO domain specific pre-trained model in order to use with downstream tasks with limited labelled data. Hence, we explored the applicability of SSL with multi-modal satellite imagery for downstream tasks. For this we utilised …
A Health Elearning Ontology And Procedural Reasoning Approach For Developing Personalized Courses To Teach Patients About Their Medical Condition And Treatment, Martin Michalowski, Szymon Wilk, Wojtek Michalowski, Dympna O'Sullivan, Silvia Bonaccio, Enea Parimbelli, Marc Carrier, Grégoire Le Gal, Stephen Kingwell, Mor Peleg
A Health Elearning Ontology And Procedural Reasoning Approach For Developing Personalized Courses To Teach Patients About Their Medical Condition And Treatment, Martin Michalowski, Szymon Wilk, Wojtek Michalowski, Dympna O'Sullivan, Silvia Bonaccio, Enea Parimbelli, Marc Carrier, Grégoire Le Gal, Stephen Kingwell, Mor Peleg
Articles
We propose a methodological framework to support the development of personalized courses that improve patients’ understanding of their condition and prescribed treatment. Inspired by Intelligent Tutoring Systems (ITSs), the framework uses an eLearning ontology to express domain and learner models and to create a course. We combine the ontology with a procedural reasoning approach and precompiled plans to operationalize a design across disease conditions. The resulting courses generated by the framework are personalized across four patient axes—condition and treatment, comprehension level, learning style based on the VARK (Visual, Aural, Read/write, Kinesthetic) presentation model, and the level of understanding of specific …
The Design Of A Framework For The Detection Of Web-Based Dark Patterns, Andrea Curley, Dympna O'Sullivan, Damian Gordon, Brendan Tierney, Ioannis Stavrakakis
The Design Of A Framework For The Detection Of Web-Based Dark Patterns, Andrea Curley, Dympna O'Sullivan, Damian Gordon, Brendan Tierney, Ioannis Stavrakakis
Conference Papers
In the theories of User Interfaces (UI) and User Experience (UX), the goal is generally to help understand the needs of users and how software can be best configured to optimize how the users can interact with it by removing any unnecessary barriers. However, some systems are designed to make people unwillingly agree to share more data than they intend to, or to spend more money than they plan to, using deception or other psychological nudges. User Interface experts have categorized a number of these tricks that are commonly used and have called them Dark Patterns. Dark Patterns are varied …
Flying Free: A Research Overview Of Deep Learning In Drone Navigation Autonomy, Thomas Lee, Susan Mckeever, Jane Courtney
Flying Free: A Research Overview Of Deep Learning In Drone Navigation Autonomy, Thomas Lee, Susan Mckeever, Jane Courtney
Articles
With the rise of Deep Learning approaches in computer vision applications, significant strides have been made towards vehicular autonomy. Research activity in autonomous drone navigation has increased rapidly in the past five years, and drones are moving fast towards the ultimate goal of near-complete autonomy. However, while much work in the area focuses on specific tasks in drone navigation, the contribution to the overall goal of autonomy is often not assessed, and a comprehensive overview is needed. In this work, a taxonomy of drone navigation autonomy is established by mapping the definitions of vehicular autonomy levels, as defined by the …
Adapting An Agent-Based Model Of Infectious Disease Spread In An Irish County To Covid-19, Elizabeth Hunter, John D. Kelleher
Adapting An Agent-Based Model Of Infectious Disease Spread In An Irish County To Covid-19, Elizabeth Hunter, John D. Kelleher
Articles
The dynamics that lead to the spread of an infectious disease through a population can be characterized as a complex system. One way to model such a system, in order to improve preparedness, and learn more about how an infectious disease, such as COVID-19, might spread through a population, is agent-based epidemiological modelling. When a pandemic is caused by an emerging disease, it takes time to develop a completely new model that captures the complexity of the system. In this paper, we discuss adapting an existing agent-based model for the spread of measles in Ireland to simulate the spread of …
Check Your Tech, Whose Responsibility Is It When Cyberharassment Occurs?, Dympna O'Sullivan, Damian Gordon, Michael Collins, Emma Murphy
Check Your Tech, Whose Responsibility Is It When Cyberharassment Occurs?, Dympna O'Sullivan, Damian Gordon, Michael Collins, Emma Murphy
Conference papers
Social media has become a dominant aspect of many people’s lives in many countries. Unfortunately that resulted in widespread issues of bullying and harassment. While frequently this harrassment is intentional, there have been occasions where automated processes have been inadvertently responsible for this sort of harassment. The software tools that allow people to harass others could have further features added to them to reduce the amount of harassment that occurs, but more often than not, where programmers are developing these systems then don’t anticipate the range of ways that these technologies will be used (this is called “consequence scanning”). The …
Monitoring Quality Of Life Indicators At Home From Sparse And Low-Cost Sensor Data., Dympna O'Sullivan, Rilwan Basaru, Simone Stumpf, Neil Maiden
Monitoring Quality Of Life Indicators At Home From Sparse And Low-Cost Sensor Data., Dympna O'Sullivan, Rilwan Basaru, Simone Stumpf, Neil Maiden
Conference papers
Supporting older people, many of whom live with chronic conditions or cognitive and physical impairments, to live independently at home is of increasing importance due to ageing demographics. To aid independent living at home, much effort is being directed at reliably detecting activities from sensor data to monitor people’s quality of life or to enhance self-management of their own health. Current efforts typically leverage smart homes which have large numbers of sensors installed to overcome challenges in the accurate detection of activities. In this work, we report on the results of machine learning models based on data collected with a …
Is Twitter A Bad Place? The Responsibility That Social Media May Have Had In The 2021 Storming Of Capitol Hill., Ioannis Stavrakakis, Damian Gordon, Dympna O'Sullivan, Andrea Curley
Is Twitter A Bad Place? The Responsibility That Social Media May Have Had In The 2021 Storming Of Capitol Hill., Ioannis Stavrakakis, Damian Gordon, Dympna O'Sullivan, Andrea Curley
Conference papers
The events of 6 th January 2021 in the United States of America, where rioters stormed the heart of their democracy, the US Capitol Complex (which houses their bicameral parliament) were shocking to see. The reasons for this riot were myriad, including to protest the outcomes of the presidential elections and two senate elections, as well as to prevent the counting that day of the electoral votes that formally certify the election result. These events will be analysed and reflected upon for years to come, and blame will be placed at many people’s doors, and inevitability one that has already …
Internet Of Medical Things (Iomt): Overview, Emerging Technologies, And Case Studies, Sahshanu Razdan, Sachin Sharma
Internet Of Medical Things (Iomt): Overview, Emerging Technologies, And Case Studies, Sahshanu Razdan, Sachin Sharma
Articles
No abstract provided.
Pothole Detection Under Diverse Conditions Using Object Detection Models, Ibrahim Hassan Syed, Dympna O'Sullivan, Susan Mckeever
Pothole Detection Under Diverse Conditions Using Object Detection Models, Ibrahim Hassan Syed, Dympna O'Sullivan, Susan Mckeever
Conference papers
One of the most important tasks in road maintenance is the detection of potholes. This process is usually done through manual visual inspection, where certified engineers assess recorded images of pavements acquired using cameras or professional road assessment vehicles. Machine learning techniques are now being applied to this problem, with models trained to automatically identify road conditions. However, approaching this real-world problem with machine learning techniques presents the classic problem of how to produce generalisable models. Images and videos may be captured in different illumination conditions, with different camera types, camera angles, and resolutions. In this paper, we present our …
The Effects Of Differences In Vaccination Rates Across Socioeconomic Groups On The Size Of Measles Outbreaks, Elizabeth Hunter, John D. Kelleher
The Effects Of Differences In Vaccination Rates Across Socioeconomic Groups On The Size Of Measles Outbreaks, Elizabeth Hunter, John D. Kelleher
Conference papers
Vaccination rates are often presented at the level of a country or region. However, within those areas there might be geographic or demographic pockets that have higher or lower vaccination rates. We use an agent-based model designed to simulate the spread of measles in Irish towns to examine if the effectiveness of vaccination rates to reduce disease at a population level is sensitive to the uniformity of vaccinations across socioeconomic groups. We find that when vaccinations are not applied evenly across socioeconomic groups we see more outbreaks and outbreaks with larger magnitudes.