Computer Engineering Commons^™

Poly-Gan: Regularizing Polygons With Generative Adversarial Networks, Lasith Niroshan, James Carswell

Conference Papers

Regularizing polygons involves simplifying irregular and noisy shapes of built environment objects (e.g. buildings) to ensure that they are accurately represented using a minimum number of vertices. It is a vital processing step when creating/transmitting online digital maps so that they occupy minimal storage space and bandwidth. This paper presents a data-driven and Deep Learning (DL) based approach for regularizing OpenStreetMap building polygon edges. The study introduces a building footprint regularization technique (Poly-GAN) that utilises a Generative Adversarial Network model trained on irregular building footprints and OSM vector data. The proposed method is particularly relevant for map features …

Combinedeepnet: A Deep Network For Multistep Prediction Of Near-Surface Pm2.5 Concentration, Prasanjit Dey, Soumyabrata Dev, Bianca Schoen-Phelan

Conference papers

PM2.5 is a type of air pollutant that can cause respiratory and cardiovascular problems. Precise PM2.5 ( μg/m3 ) concentration prediction may help reduce health concerns and provide early warnings. To better understand air pollution, a number of approaches have been presented for predicting PM2.5 concentrations. Previous research used deep learning models for hourly predictions of air pollutants due to their success in pattern recognition, however, these models were unsuitable for multisite, long-term predictions, particularly in regard to the correlation between pollutants and meteorological data. This article proposes the combine deep network (CombineDeepNet), which combines multiple deep networks, including a …

Bilstm−Bigru: A Fusion Deep Neural Network For Predicting Air Pollutant Concentration, Prasanjit Dey, Soumyabrata Dev, Bianca Schoen-Phelan

Conference papers

Predicting air pollutant concentrations is an efficient way to prevent incidents by providing early warnings of harmful air pollutants. A precise prediction of air pollutant concentrations is an important factor in controlling and preventing air pollution. In this paper, we develop a bidirectional long-short-term memory and a bidirectional gated recurrent unit (BiLSTM−BiGRU) to predict PM 2.5 concentrations in a target city for different lead times. The BiLSTM extracts preliminary features, and the BiGRU further extracts deep features from air pollutant and meteorological data. The fully connected (FC) layer receives the output and makes an accurate prediction of the PM 2.5 …

Formulating Automated Responses To Cognitive Distortions For Cbt Interactions, Ignacio De Toledo, Giancarlo Salton, Robert J. Ross

Conference papers

One of the key ideas of Cognitive Behavioural Therapy (CBT) is the ability to convert negative or distorted thoughts into more realistic alternatives. Although modern machine learning techniques can be successfully applied to a variety of Natural Language Processing tasks, including Cognitive Behavioural Therapy, the lack of a publicly available dataset makes supervised training difficult for tasks such as reforming distorted thoughts. In this research, we constructed a small CBT dataset via crowd-sourcing, and leveraged state of the art pre-trained architectures to transform cognitive distortions, producing text that is relevant and more positive than the original negative thoughts. In particular, …

Bayesian Adaptive Path Allocation Techniques For Intra-Datacenter Workloads, Ali Malik, Ruairí De Fréin, Chih-Heng Ke, Hasanen Alyasiri, Obinna Izima

Conference papers

Data center networks (DCNs) are the backbone of many cloud and Internet services. They are vulnerable to link failures, that occur on a daily basis, with a high frequency. Service disruption due to link failure may incur financial losses, compliance breaches and reputation damage. Performance metrics such as packet loss and routing flaps are negatively affected by these failure events. We propose a new Bayesian learning approach towards adaptive path allocation that aims to improve DCN performance by reducing both packet loss and routing flaps ratios. The proposed approach incorporates historical information about link failure and usage probabilities into its …

Examining The Modelling Capabilities Of Defeasible Argumentation And Non-Monotonic Fuzzy Reasoning, Luca Longo, Lucas Rizzo, Pierpaolo Dondio

Articles

Knowledge-representation and reasoning methods have been extensively researched within Artificial Intelligence. Among these, argumentation has emerged as an ideal paradigm for inference under uncertainty with conflicting knowledge. Its value has been predominantly demonstrated via analyses of the topological structure of graphs of arguments and its formal properties. However, limited research exists on the examination and comparison of its inferential capacity in real-world modelling tasks and against other knowledge-representation and non-monotonic reasoning methods. This study is focused on a novel comparison between defeasible argumentation and non-monotonic fuzzy reasoning when applied to the representation of the ill-defined construct of human mental workload …

The Entanglement Of Influential Technology Channels In Practice And Design, Ciarán O'Leary

Doctoral

Design for academic practice is an important phenomenon in Higher Education. This is the practice through which informal, non-professional designers operating in a variety of roles in academic institutions carry out the design of systems, resources, activities and processes that are intended to enhance academic practice. Despite its importance, the area has not received sufficient attention in studies of academic practice, quality enhancement and digital transformation. This thesis argues that the absence of insight into how designers for academic practice engage with digital technology in their design practice contributes to the mismatch between the ambitions for digital transformation in higher …

Intelligent Sdn Traffic Classification Using Deep Learning: Deep-Sdn, Ali Malik, Ruairí De Fréin, Mohammed Al-Zeyadi, Javier Andreu-Perez

Conference papers

Accurate traffic classification is fundamentally important for various network activities such as fine-grained network management and resource utilisation. Port-based approaches, deep packet inspection and machine learning are widely used techniques to classify and analyze network traffic flows. However, over the past several years, the growth of Internet traffic has been explosive due to the greatly increased number of Internet users. Therefore, both port-based and deep packet inspection approaches have become inefficient due to the exponential growth of the Internet applications that incurs high computational cost. The emerging paradigm of software-defined networking has reshaped the network architecture by detaching the control …

Investigation Of The Effects Of A Situated Learning Digital Game On Mathematics Education At The Primary School Level, Mariana Rocha

Doctoral

Previous research suggests games can improve learning outcomesand students’ motivation. However, there still exists insufficient clarity on the design principles and pedagogical approach that should underpinmathematics educational games. This thesis is aimed at evaluating the effects of an educationalgame on the learningperformance and levels of anxiety promoted by mathematics activities of primary school students. The game was designed based on theprinciples of situated learning, following acombination of an in-depth literature review, a collection of teachers’ perceptions about educational games, and features ofclassroom games. Empirical evaluation of the game was performed through a 5-weeks experiment carried out in three Irish schools, …

A Hybrid Agent-Based And Equation Based Epidemiological Model For The Spread Of Infectious Diseases, Elizabeth Hunter

Doctoral

Infectious disease models are essential in understanding how an outbreak might occur and how best to mitigate an outbreak. One of the most important factors in modelling a disease is choosing an appropriate model and determining the assump tions needed to create the model. The main research questions this thesis addresses are how do we create a model for the spread of infectious diseases that captures heterogeneous agents without using an inordinate amount of computing power and how can we use that model to plan for future infectious disease outbreaks. We start our work by analysing and comparing equation based …

Brexit Election: Forecasting A Conservative Party Victory Through The Pound Using Arima And Facebook's Prophet, James Usher, Pierpaolo Dondio

Conference papers

On the 30th October, 2019, the markets watched as British Prime Minister, Boris Johnson, took a massive political gamble to call a general election to break the Withdrawal Agreement stalemate in the House of Commons to “Get BREXIT Done”. The pound had been politically sensitive owing to BREXIT uncertainty. With the polls indicating a Conservative win on 4thDecember, 2019, the margin of victory could be observed through increases in the pound. The outcome of a Conservative party victory would benefit the pound by removing the current market turbulence. We look to provide a short-term forecast of the pound. Our approach …

Promoting A Growth Mindset In Cs1: Does One Size Fit All? A Pilot Study, Keith Quille, Susan Bergin

Conference Papers

This paper describes a pilot intervention conducted in CS1, in the
academic year of 2016-2017. The intervention was based on the
work of Dweck, promoting a growth Mindset in an effort to in-
crease performance in introductory programming. The study also
examined data from a previous year (as a control group) to compare
and contrast the results. Multiple factors related to programming
performance were recorded with the control and treatment group,
which were measured at multiple intervals throughout the course,
to monitor changes as the pilot intervention was implemented.
This study found a significant increase in programming perfor-
mance when …

Evaluating The Impact Of Defeasible Argumentation As A Modelling Technique For Reasoning Under Uncertainty, Lucas Rizzo

Doctoral

Limited work exists for the comparison across distinct knowledge-based approaches in Artificial Intelligence (AI) for non-monotonic reasoning, and in particular for the examination of their inferential and explanatory capacity. Non-monotonicity, or defeasibility, allows the retraction of a conclusion in the light of new information. It is a similar pattern to human reasoning, which draws conclusions in the absence of information, but allows them to be corrected once new pieces of evidence arise. Thus, this thesis focuses on a comparison of three approaches in AI for implementation of non-monotonic reasoning models of inference, namely: expert systems, fuzzy reasoning and defeasible argumentation. …

Ambiqual: Towards A Quality Metric For Headphone Rendered Compressed Ambisonic Spatial Audio, Miroslaw Narbutt, Jan Skoglund, Andrew Allen, Michael Chinen, Dan Barry, Andrew Hines

Articles

Spatial audio is essential for creating a sense of immersion in virtual environments. Efficient encoding methods are required to deliver spatial audio over networks without compromising Quality of Service (QoS). Streaming service providers such as YouTube typically transcode content into various bit rates and need a perceptually relevant audio quality metric to monitor users’ perceived quality and spatial localization accuracy. The aim of the paper is two-fold. First, it is to investigate the effect of Opus codec compression on the quality of spatial audio as perceived by listeners using subjective listening tests. Secondly, it is to introduce AMBIQUAL, a full …

Improving The Sustainability Of The Built Environment By Training Its Workforce In More Efficient And Greener Ways Of Designing And Constructing Through The Horizon2020 Bimcert Project, Barry Mcauley, Avril Behan

Conference papers

The construction industry consumes up to 50% of mineral resources excavated from nature, generates about 33% of CO2 present in the atmosphere and is responsible for 40% of total global energy through both construction and operation of buildings. The realisation that current pervasive construction practices now face globalization, sustainability, and environmental concerns, as well as ever-changing legislation requirements and new skills needed for the information age has resulted in technologies such as Building Information Modelling (BIM) becoming a key enabler in navigating these barriers. To assist in overcoming these barriers, a number of funding initiatives have been put in place …

Centres Of Excellence And Roadmaps For Digital Transition: Lessons For Ireland’S Construction Industry, Barry Mcauley, Alan Hore, Roger West

Conference papers

Like most sectors in today’s working world, construction businesses are challenged to work in an increasingly digitised world with sophisticated demands from intelligent clients. So much has been written about the inefficiencies of the construction industry, its fragmentation, lack of collaboration, low margins, adversarial pricing, poor productivity, financial fragility, lack of research and development, poor industry image and relatively weak use of digital solutions. The Irish government recognises the importance of digital innovation to address many of the challenges the construction industry faces. With recent high profile reports of escalating spend on signature public sector projects and weak productivity performance …

Bim In Ireland 2019: A Study Of Bim Maturity And Diffusion In Ireland, Barry Mcauley, Alan Hore, Roger West

Conference papers

In 2017, the BIM Innovation Capability Programme team applied five macro BIM maturity conceptual models to capture the capability of the Irish construction industry and assess its BIM maturity. The results found that while Ireland is mature for modelling processes, it is less developed with regards to collaboration processes and policies. Ireland also ranked poorly when it came to regulatory frameworks, measurements and benchmarks compared to a number of countries which also applied the same conceptual models. At the time, the findings highlighted that Ireland’s diffusion dynamic was middle out, meaning that larger organisations or industry associations were pushing the …

An Investigation Into Current Procurement Strategies That Promote Collaboration Through Early Contractor Involvement With Regards To Their Suitability For Irish Public Work Projects, Barry Mcauley, Frederic Lefebvre

Conference papers

Previous research has established that multi-disciplinary collaboration will benefit a construction project throughout its lifecycle. While Lean Construction, Building Information Modelling (BIM), and Integrated Project Delivery (IPD) can all be viewed as separate processes which add independent value to a project, they are more effective when used in partnership with each other. In order to ensure the high levels of collaboration expected for these processes to work in unison, the early involvement of the Contractor is paramount. Early contractor involvement within the design process can ensure a more focused integrated project team, improvement of both constructability and cost certainty, as …

From Roadmap To Implementation: Lessons For Ireland’S Digital Construction Programme, Barry Mcauley, Alan Hore, Roger West

Conference papers

As part of their Future of Construction initiative in 2018 the World Economic Forum published an action plan to accelerate Building Information Modelling adoption. The WEF report highlighted actions that companies, industry organisations and governments are advised to implement to accelerate BIM adoption and better capitalise on delivering better project outcomes. According the authors of the report BIM is seen as the centrepiece of the construction industry’s digital transformation, however they acknowledged that BIM adoption globally remain slow. Anecdotal experience would suggest that BIM usage in Ireland is also very low and that a similar initiative or an adaptation of …

Predicting The Hardness Of Turf Surfaces From A Soil Moisture Sensor Using Iot Technologies, Ann Marie Mckeon

Other

In horseracing, “the going” is a term to describe the racetrack ground conditions. In Ireland presently, a groundskeeper or course clerk walks the racecourse poking it with a blackthorn stick, assesses conditions, and declares the going – it is a subjective measurement.

This thesis will propose using remote low-cost soil moisture sensors to gather high frequency data about the soil water content in the ground and to enable informed decisions to be made. This will remove the subjective element from the ground hardness, and look at the data in an objective way.

The soil moisture sensor will systematically collect high …

Visualising The Complex Features Of Source Code, Ivan Bacher

Doctoral

Software development is a complex undertaking composed of several activities that include reading, writing, and modifying source code. Indeed, previous studies have shown that the majority of the effort invested in software development is dedicated to understanding code. This includes understanding the static structure, dynamic behaviour, and evolution of the code. Given these particular characteristics, as well as the high complexity of source code, it is reasonable to consider how visualisation can facilitate source code understanding. This work proposes to extend existing software development tools with visualisations that can be used to encode the various complex features within a source …

Bespoke Mobile Application Development: Facilitating Transition Of Foundation Students To Higher Education, Nevan Bermingham, Mark Prendergast

Books/Book Chapters

Smartphone usage by students has increased rapidly over the last number of years, and it is expected that the utilisation of mobile applications in educational environments will continue to increase. This chapter focuses on a bespoke mobile application which aims to facilitate the transition of Foundation students to Higher Education in an Irish setting. Foundation students comprise of Access and International Students participating on pre-degree foundation courses. These students experience a major life change in making this transition and it is important that efforts are made to ensure a successful adjustment experience. Research suggests that mobile technologies can play a …

Bim+Blockchain: A Solution To The Trust Problem In Collaboration?, Malachy Mathews, Dan Robles, Brian Bowe

Conference papers

This paper provides an overview of historic and current organizational limitations emerging in the Architecture, Engineering, Construction, Building Owner / Operations (AECOO) Industry. It then provides an overview of new technologies that attempt to mitigate these limitations. However, these technologies, taken together, appear to be converging and creating entirely new organizational structures in the AEC industries. This may be characterized by the emergence of what is called the Network Effect and it’s related calculus. This paper culminates with an introduction to Blockchain Technology (BT) and it’s integration with the emergence of groundbreaking technologies such as Internet of Things (IoT), Artificial …

One-To-Cloud One-Time Pad Data Encryption: Introducing Virtual Prototyping With Pspice, Paul Tobin, Lee Tobin, Roberto Gandia Blanquer Dr, Michael Mckeever, Jonathan Blackledge

Conference papers

In this paper, we examine the design and application of a one-time pad encryption system for protecting data stored in the Cloud. Personalising security using a one-time pad generator at the client-end protects data from break-ins, side-channel attacks and backdoors in public encryption algorithms. The one-time pad binary sequences were obtained from modified analogue chaos oscillators initiated by noise and encoded client data locally. Specific ``one-to-Cloud'' storage applications returned control back to the end user but without the key distribution problem normally associated with one-time pad encryption. Development of the prototype was aided by ``Virtual Prototyping'' in the latest version …

Developing A Distributed Java-Based Speech Recognition Engine, Tony Ayers, Brian Nolan

The ITB Journal

The development of speech recognition engines has traditionally been the territory of low-level development languages such as C. Until recently Java may not have been considered a candidate language for the development of such a speech engine, due to its security restrictions which limited its sound processing features. The release of the Java Sound API as part of the Java Media Framework and the subsequent integration of the Sound API into the standard Java development kit provides the necessary sound processing tools to Java to perform speech recognition. This paper documents our development of a speech recognition engine using the …

Design And Implementation Of An Archetype Based Interoperable Knowledge Eco-System For Data Buoys, Paul Stacey, Damon Berry

Conference papers

This paper describes the ongoing work of the authors in translating two-level system design techniques used in Health Informatics to the Earth Systems Science domain. Health informaticians have developed a sophisticated two-level systems design approach for electronic health documentation over many years, and with the use of archetypes, have shown how knowledge interoperability among heterogeneous systems can be achieved. Translating two-level modelling techniques to a new domain is a complex task. A proof-of-concept archetype enabled data buoy eco-system is presented. The concept of operational templates-as-a service is proposed. Design recommendations and implementation experiences of re-working the proposed architecture to run …

Pathfinding In Computer Games, Ross Graham, Hugh Mccabe, Stephen Sheridan

The ITB Journal

One of the greatest challenges in the design of realistic Artificial Intelligence (AI) in computer games is agent movement. Pathfinding strategies are usually employed as the core of any AI movement system. This report will highlight pathfinding algorithms used presently in games and their shortcomings especially when dealing with real-time pathfinding. With the advances being made in other components, such as physics engines, it is AI that is impeding the next generation of computer games. This report will focus on how machine learning techniques such as Artificial Neural Networks and Genetic Algorithms can be used to enhance an agents ability …

Web Services Technology Infrastructure, Geraldine Gray, Kieran O’Connor

The ITB Journal

Web Services using eXtensible Markup Language (XML) based standards are becoming the new archetype for enabling business to business collaborations. This paper describes the conceptual architecture and semantics of constructing and consuming Web Services. It describes how Web Services fit into the enterprise application environment. It discusses Web Services security. Finally, it outlines the flaws of Web Services in their current state.

Xml For Business To Business Data Exchange, Geraldine Gray, David Kerwick

The ITB Journal

This paper examines to use of XML for business to business data exchange. Starting with creating an XML document from an existing data source and transmitting that document, we explain some of the supporting standards for XML which facilitate automated processing and transformation of an XML document. Finally we look at the advantages of using XML, and why it is expected to revolutionise electronic data interchange.

An Exploration Of The Effects Of Enhanced Compiler Error Messages For Computer Programming Novices, Brett A. Becker

Theses

Computer programming is an essential skill that all computing students must master and is increasingly important in many diverse disciplines. It is also difficult to learn. One of the many challenges novice programmers face from the start are notoriously cryptic compiler error messages. These report details on errors made by students and are essential as the primary source of information used to rectify those errors. However these difficult to understand messages are often a barrier to progress and a source of discouragement. A high number of student errors, and in particular a high frequency of repeated errors – when a …