Computer Sciences Commons^™

The World Is Our Classroom: Developing A Model For International Virtual Internships - The Global Innovations Project, Paul Doyle, Brian Keegan, Damian Gordon, Anna Becevel, Paul J. Gibson, Zhiying Jiang Phd, Dympna O'Sullivan

Articles

In the aftermath of COVID-19, remote working has become the norm, and graduates now need an even wider range of skills, which traditional classrooms and internships do not always provide. Working in multiple time zones, within global multi-cultural teams, and only ever meeting colleagues through online technology are just some of the challenges, which require a new type of global graduate. Transversal skills including leadership, collaboration, innovation, digital, green, organization and communication skills are critical. The disruption from COVID-19 also presents unprecedented opportunities to develop more inclusive approaches to internships and international experiences, to level the playing field for students …

Towards An Ethical Framework For The Design And Development Of Inclusive Home-Based Smart Technology For Smart Spaces For Older Adults And People With Disabilities, Emma Murphy, Julie Doyle, Ioannis Stavrakakis, Damian Gordon, Brian Keegan, Dympna O'Sullivan

Articles

Unique ethical, privacy and safety implications arise for people who are reliant on home-based smart technology due to health conditions or disabilities. As a result we need to carefully reflect on our approaches to ethical issues over the life cycle of smart home technology design and the wider living context for end users and relevant stakeholders. In this position paper we highlight a need for a reflective, inclusive ethical framework for the design of inclusive smart spaces. We present key ethical considerations in the design, development and deployment of smart home-based technology for older adults and people with disabilities. We …

Detecting Patches On Road Pavement Images Acquired With 3d Laser Sensors Using Object Detection And Deep Learning, Syed Ibrahim Hassan, Dympna O'Sullivan, Susan Mckeever, Kieran Feighan, David Power, Ray Mcgowan

Articles

Regular pavement inspections are key to good road maintenance and road defect corrections. Advanced pavement inspection systems such as LCMS (Laser Crack Measurement System) can automatically detect the presence of different defects using 3D lasers. However, such systems still require manual involvement to complete the detection of pavement defects. This paper proposes an automatic patch detection system using object detection technique. To our knowledge, this is the first time state-of-the-art object detection models Faster RCNN, and SSD MobileNet-V2 have been used to detect patches inside images acquired by LCMS. Results show that the object detection model can successfully detect patches …

Linked Data Quality Assessment: A Survey, Aparna Nayak, Bojan Bozic, Luca Longo

Conference papers

Data is of high quality if it is fit for its intended use in operations, decision-making, and planning. There is a colossal amount of linked data available on the web. However, it is difficult to understand how well the linked data fits into the modeling tasks due to the defects present in the data. Faults emerged in the linked data, spreading far and wide, affecting all the services designed for it. Addressing linked data quality deficiencies requires identifying quality problems, quality assessment, and the refinement of data to improve its quality. This study aims to identify existing end-to-end frameworks for …

Learning Fruit Class From Short Wave Near Infrared Spectral Features, An Ai Approach Towards Determining Fruit Type, Ayesha Zeb, Waqar Shahid Qureshi, Abdul Ghafoor, Dympna O'Sullivan

Conference papers

This paper analyzes the potential of using shortwave NIRS (near-infrared spectroscopy) for fruit classification problems. The research focuses on O-H and C-H overtone features of fruit and its correlation with NIRS and therefore opens a new dimension of fruit classification problems using NIRS. Eleven fruits, which include apple, cherry, hass, kiwi, grapes, mango, melon, orange, loquat, plum, and apricot, were used in this study to cover physical characteristics such as peel thinness, pulp, seed thickness, and size. NIR spectral data is collected using the industry-standard F-750 fruit quality meter (wavelength range 300-1100nm) for all fruit mentioned above. Different shallow machine …

Assessing Feature Representations For Instance-Based Cross-Domain Anomaly Detection In Cloud Services Univariate Time Series Data, Rahul Agrahari, Matthew Nicholson, Clare Conran, Haytham Assem, John D. Kelleher

Articles

In this paper, we compare and assess the efficacy of a number of time-series instance feature representations for anomaly detection. To assess whether there are statistically significant differences between different feature representations for anomaly detection in a time series, we calculate and compare confidence intervals on the average performance of different feature sets across a number of different model types and cross-domain time-series datasets. Our results indicate that the catch22 time-series feature set augmented with features based on rolling mean and variance performs best on average, and that the difference in performance between this feature set and the next best …

Assessing Feature Representations For Instance-Based Cross-Domain Anomaly Detection In Cloud Services Univariate Time Series Data, Rahul Agrahari, Matthew Nicholson, Clare Conran, Haythem Assem, John D. Kelleher

Articles

In this paper, we compare and assess the efficacy of a number of time-series instance feature representations for anomaly detection. To assess whether there are statistically significant differences between different feature representations for anomaly detection in a time series, we calculate and compare confidence intervals on the average performance of different feature sets across a number of different model types and cross-domain time-series datasets. Our results indicate that the catch22 time-series feature set augmented with features based on rolling mean and variance performs best on average, and that the difference in performance between this feature set and the next best …

Evaluating A Peer Assisted Learning Programme For Mature Access Foundation Students Undertaking Computer Programming At An Irish University, Nevan Bermingham, Frances Boylan, Barry J. Ryan

Articles

Access Foundation Programmes are a widening-participation initiative designed to encourage engagement in higher education among under-represented groups. This includes socioeconomic and educational disadvantage. Mature students in particular enrolled on these programmes experience greater difficulties making the transition to tertiary education, especially when they opt to study disciplines traditionally considered difficult. Computer programming is perceived as a traditionally difficult subject with lower pass rates and progression rates typically than other subjects.

This paper describes the first of a three-cycle action research study examining the perceived effects of a structured Peer Assisted Learning (PAL) Programme for mature students enrolled on a computer …

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 …

Shapley Idioms: Analysing Bert Sentence Embeddings For General Idiom Token Identification, Vasudevan Nedumpozhimana, Filip Klubicka, John Kelleher

Articles

This article examines the basis of Natural Language Understanding of transformer based language models, such as BERT. It does this through a case study on idiom token classification. We use idiom token identification as a basis for our analysis because of the variety of information types that have previously been explored in the literature for this task, including: topic, lexical, and syntactic features. This variety of relevant information types means that the task of idiom token identification enables us to explore the forms of linguistic information that a BERT language model captures and encodes in its representations. The core of …

Detecting Road Intersections Automatically From Satellite Images Using A Deep Learning Approach, Fatmaelzahraa Eltaher, Luis Miralles-Pechuán, Jane Courtney, Susan Mckeever

Datasets

Automatic detection of road intersections is an important task in various domains such as navigation, route planning, traffic prediction, and road network extraction. Road intersections range from simple three-way T-junctions (degree 3) to complex large-scale junctions with many branches. The location of intersections and their complexity is an important consideration in route planning, such as the requirement to avoid complex intersections on pedestrian journeys. This is relevant to vulnerable road users such as People with Blindness or Visually Impairment (PBVI) or children. Route planning applications, however, do not give information about the location or complexity of intersections as this information …

The Locus Algorithm: A Novel Technique For Identifying Optimised Pointings For Differential Photometry, Oisin Creaner, Kevin Nolan Mr, E. Hickey, N. Smith

Articles

Studies of the photometric variability of astronomical sources from ground-based telescopes must overcome atmospheric extinction effects. Differential photometry by reference to an ensemble of reference stars which closely match the target in terms of magnitude and colour can mitigate these effects. This Paper describes the design, implementation, and operation of a novel algorithm – The Locus Algorithm – which enables optimised differential photometry. The Algorithm is intended to identify, for a given target and observational parameters, the Field of View (FoV) which includes the target and the maximum number of reference stars similar to the target. A collection of objects …

An Odd-Protocol For Agent-Based Model For The Spread Of Covid-19 In Ireland, Elizabeth Hunter, John D. Kelleher

Reports

No abstract provided.

Patient Generated Health Data And Electronic Health Record Integration, Governance And Socio-Technical Issues: A Narrative Review, Abdullahi Abubakar Kawu, Lucy Hederman, Julie Doyle, Dympna O'Sullivan

Articles

Patients’ health records have the potential to include patient generated health data (PGHD), which can aid in the provision of personalized care. Access to these data can allow healthcare professionals to receive additional information that will assist in decision-making and the provision of additional support. Given the diverse sources of PGHD, this review aims to provide evidence on PGHD integration with electronic health records (EHR), models and standards for PGHD exchange with EHR, and PGHD-EHR policy design and development. The review also addresses governance and socio-technical considerations in PGHD management. Databases used for the review include PubMed, Scopus, ScienceDirect, IEEE …

Business Intelligence Trends: A Review Of Mobile Business Intelligence, Shanika Edirisinghe

Articles

The early stages of Decision Support Systems evolved with the technological improvements and availability of massive amounts of data. The concept of Business Intelligence became apparent along with this evolution which incorporates a range of fields and supports decision making in business organizations. Mobile business intelligence is a popular trend in the domain of business intelligence at present. Business organizations employ mobile business intelligence as an extension to the existing business intelligence systems. This study intends to present a review of mobile business intelligence while addressing its benefits, challenges, and limitations. Moreover, this study provides details of several use cases …

Methods And Means For Registration, Measurement, Processing And Evaluation Of Thermographic Information With Application In Systems For Medical Diagnostics And Ecology, Stanyo Kolev

Books

Chapter 1. General principles in methods and means for recording, measuring and processing thermographic information. Applications of thermography, mainly in the fields of medicine and ecology, are presented. Problems related to the accuracy of measurement with an infrared camera are discussed. External (Atmosphere, Physical characteristics of body coverings, Geometric factors, Environment, Infrared characteristics of the object under study and Behavioral factors) and internal (Stressor, Blood circulation, Physical activity, Sweating, etc.) factors that affect the accuracy of measurement are described. The causes leading to errors in thermographic measurements are analyzed, the main ones being: water vapor, ozone and carbon dioxide in …

Towards Exchanging Wearable-Pghd With Ehrs: Developing A Standardized Information Model For Wearable-Based Patient Generated Health Data, Abdullahi Abubakar Kawu, Dympna O'Sullivan, Lucy Hederman

Articles

Wearables have become commonplace for tracking and making sense of patient lifestyle, wellbeing and health data. Most of this tracking is done by individuals outside of clinical settings, however some data from wearables may be useful in a clinical context. As such, wearables may be considered a prominent source of Patient Generated Health Data (PGHD). Studies have attempted to maximize the use of the data from wearables including integrating with Electronic Health Records (EHRs). However, usually a limited number of wearables are considered for integration and, in many cases, only one brand is investigated. In addition, we find limited studies …

Interconnection And Damping Assignment Passivity-Based Non-Linear Observer Control For Efficiency Maximization Of Permanent Magnet Synchronous Motor, Youcef Belkhier, Abelyazid Achour, Miroslav Bures, Nasim Ullah, Mohit Bajaj, Hossam Zawbaa, Salah Kamel

Articles

The permanent magnet synchronous motor (PMSM) has several advantages over the DC motor and is gradually replacing it in the industry. The dynamics of the PMSM are described by non-linear equations; it is sensitive to unknown external disturbances (load), and its characteristics vary over time. All of these restrictions complicate the control task. Non-linear controls are required to adjust for non-linearities and the drawbacks mentioned above. This paper investigates an interconnection and damping assignment (IDA) passivity-based control (PBC) combined with a non-linear observer approach for the PMSM using the model represented in the dq-frame. The IDA-PBC approach has the inherent …

Does Information And Communication Technology Impede Environmental Degradation? Fresh Insights From Non-Parametric Approaches, Tomiwa Sunday Adebayo, Ephraim Bonah Agyekum, Mehmet Altuntas, Sadriddin Khudoyqulov, Hossam Zawbaa, Salah Kamel

Articles

Although ICT has played a critical role in the socio-economic growth of human cultures, it has also brought with it significant environmental risks. Nevertheless, scholars remain divided on this topic; some believe that ICT has had a positive influence on the quality of the environment, while others believe that ICT has created major environmental issues. Hence, this research is another effort to assess the effects of ICT on CO2 emissions in the top 10 ICT nations (Denmark, Japan, Luxemburg, South Korea, Netherlands, Iceland, Norway, Sweden, Switzerland, and the United Kingdom) using a dataset from the period between 1986Q1 and 2019Q4. …

Residential Demand Side Management Model, Optimization And Future Perspective: A Review, Subhasis Panda, Sarthak Mohanty, Pravat Kumar Rout, Binod Kumar Sahu, Mohit Bajaj, Dr Hossam Zawbaa, Salah Kamel

Articles

The residential load sector plays a vital role in terms of its impact on overall power balance, stability, and efficient power management. However, the load dynamics of the energy demand of residential users are always nonlinear, uncontrollable, and inelastic concerning power grid regulation and management. The integration of distributed generations (DGs) and advancement of information and communication technology (ICT) even though handles the related issues and challenges up to some extent, till the flexibility, energy management and scheduling with better planning are necessary for the residential sector to achieve better grid stability and efficiency. To address these issues, it is …

Modeling And Sensitivity Analysis Of Grid-Connected Hybrid Green Microgrid System, Sumit Sharma, Yog Raj Sood, Naveen Kumar Sharma, Mohit Bajaj, Hossam Zawbaa, Rania A. Turky, Salah Kamel

Articles

The demonstrated research work analyses the technoeconomic modelling and sensitivity analysis of the available resources for the rural community in India. The various resources used in this study are solar, wind, hydro, battery and utility grid-connected system. The usefulness of the on-grid system in the rural sector is that excess amount of electricity produced through renewable energy sources (RES) could be sold back to the utility grid. A total of 12 possible configurations of various resources with and without a grid-connected system was analyzed for minimum Levelized Cost of Energy (LCOE) and Total Net Present Cost (TNPC). Further, sensitivity analysis …

An Image Processing Based Classifier To Support Safe Dropping For Delivery-By-Drone, Assem A. Abdelhak, Alan Hicks, Dan Moss, Susan Mckeever

Articles

Autonomous delivery-by-drone of packages is an active area of research and commercial development. However, the assessment of safe dropping/ delivery zones has received limited attention. Ensuring that the dropping zone is a safe area for dropping, and continues to stay safe during the dropping process is key to safe delivery. This paper proposes a simple and fast classifier to assess the safety of a designated dropping zone before and during the dropping operation, using a single onboard camera. This classifier is, as far as we can tell, the first to address the problem of safety assessment at the point of …

All Things Merge Into One, And A River Runs Through It: Exploring The Dimensions Of Blended Learning By Developing A Case Study Template For Blended Activities, Damian Gordon, Paul Doyle, Anna Becevel, Tina Baloh

Articles

The BLITT (Blended Learning International Train the Trainer) Project is focused on developing a training programme to equip teachers to become proficient in championing the use of Blended Learning in the classroom. The training programme will be developed in two phases, in the first phase involves the development of a series of case studies relevant to Blended Learning, followed by a second phase where the BLITT training programme will be designed and developed, using input from these cases. In developing the blended learning case studies, two key documents were identified as being essential, first, a case study tracking template to …

Probing With Noise: Unpicking The Warp And Weft Of Taxonomic And Thematic Meaning Representations In Static And Contextual Embeddings, Filip Klubička

Doctoral

The semantic relatedness of words has two key dimensions: it can be based on taxonomic information or thematic, co-occurrence-based information. These are captured by different language resources—taxonomies and natural corpora—from which we can build different computational meaning representations that are able to reflect these relationships. Vector representations are arguably the most popular meaning representations in NLP, encoding information in a shared multidimensional semantic space and allowing for distances between points to reflect relatedness between items that populate the space. Improving our understanding of how different types of linguistic information are encoded in vector space can provide valuable insights to the …

Power, Passion And Politics: A Grounded Theory Study Of Academic Experiences In Policy Development And Implementation In Higher Education, Marie Brennan

Doctoral

This research study is designed to investigate the lived experiences and perspectives of the academic community on policy development in Irish higher education. A review of the current policy landscape in Ireland and Europe and in particular empirical studies concerning policy implementation provided the focus of the study. The initial study focused on contemporary literature on policy development practices affected by globalisation and subsequently the issues at a national level. Where the gaps in knowledge were identified were in terms of policy implementation at the local level and where the study is aligned. The participants in the study are academics …

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 …

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 …

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 …

Effect Of Cryogenic Treatment On Drill Tool For Enhancing Metal Cutting Operation Of Aluminium Alloy Is737.Gr19000, G. Navaneethakrishnan, B. Sureshkumar, R. Palanisamy, Mohit Bajaj, Hossam Zawbaa, Salah Kamel

Articles

Drilling is the hole making process on the component face with the aid of a twisted drillbit. Normal drill bits easily wear out through penetration of drill bit into the workpiece material due to force generated in the drilling operation. So this work tries to investigate the machining parameters with cryogenically treated drill bits on various responses. Cryogenic treatment is one of the thermal engineering processes, which is used to cool the material from the temperature of −150 °C to −273 °C. This research work utilizes cryogenically treated drill tools for investigating the drilling performance on aluminium alloy (IS737.Gr19000) workpiece …

Image-Based Malware Classification Hybrid Framework Based On Space-Filling Curves, Stephen O Shaughnessy, Stephen Sheridan

Articles

There exists a never-ending “arms race” between malware analysts and adversarial malicious code developers as malevolent programs evolve and countermeasures are developed to detect and eradicate them. Malware has become more complex in its intent and capabilities over time, which has prompted the need for constant improvement in detection and defence methods. Of particular concern are the anti-analysis obfuscation techniques, such as packing and encryption, that are employed by malware developers to evade detection and thwart the analysis process. In such cases, malware is generally impervious to basic analysis methods and so analysts must use more invasive techniques to extract …