Computer Engineering Commons^™

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 …

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 …

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 …

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 …

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 …

Expressing Trust With Temporal Frequency Of User Interaction In Online Communities, Ekaterina Yashkina, Arseny Pinigin, Jooyoung Lee, Manuel Mazzara, Akinlolu Solomon Adekotujo, Adam Zubair, Luca Longo

Conference papers

Reputation systems concern soft security dynamics in diverse areas. Trust dynamics in a reputation system should be stable and adaptable at the same time to serve the purpose. Many reputation mechanisms have been proposed and tested over time. However, the main drawback of reputation management is that users need to share private information to gain trust in a system such as phone numbers, reviews, and ratings. Recently, a novel model that tries to overcome this issue was presented: the Dynamic Interaction-based Reputation Model (DIBRM). This approach to trust considers only implicit information automatically deduced from the interactions of users within …

Mediaeval2019: Flood Detection In Time Sequence Satellite Images, Palavi Jain, Bianca Schoen-Phelan, Robert J. Ross

Conference papers

In this work, we present a flood detection technique from time series satellite images for the City-centered satellite sequences (CCSS) task in the MediaEval 2019 competition [1]. This work utilises a three channel feature indexing technique [13] along with a VGG16 pretrained model for automatic detection of floods. We also compared our result with RGB images and a modified NDWI technique by Mishra et al, 2015 [15]. The result shows that the three channel feature indexing technique performed the best with VGG16 and is a promising approach to detect floods from time series satellite images.

Multi-Element Long Distance Dependencies: Using Spk Languages To Explore The Characteristics Of Long-Distance Dependencies, Abhijit Mahalunkar, John Kelleher

Conference papers

In order to successfully model Long Distance Dependencies (LDDs) it is necessary to under-stand the full-range of the characteristics of the LDDs exhibited in a target dataset. In this paper, we use Strictly k-Piecewise languages to generate datasets with various properties. We then compute the characteristics of the LDDs in these datasets using mutual information and analyze the impact of factors such as (i) k, (ii) length of LDDs, (iii) vocabulary size, (iv) forbidden strings, and (v) dataset size. This analysis reveal that the number of interacting elements in a dependency is an important characteristic of LDDs. This leads us …

Distance-Based Cluster Head Election For Mobile Sensing, Ruairí De Fréin, Liam O'Farrell

Conference papers

Energy-efficient, fair, stochastic leader-selection algorithms are designed for mobile sensing scenarios which adapt the sensing strategy depending on the mobile sensing topology. Methods for electing a cluster head are crucially important when optimizing the trade-off between the number of peer-to- peer interactions between mobiles and client-server interactions with a cloud-hosted application server. The battery-life of mobile devices is a crucial constraint facing application developers who are looking to use the convergence of mobile computing and cloud computing to perform environmental sensing. We exploit the mobile network topology, specifically the location of mobiles with respect to the gateway device, to stochastically …

Evaluating Load Adjusted Learning Strategies For Client Service Levels Prediction From Cloud-Hosted Video Servers, Ruairí De Fréin, Obinna Izima, Mark Davis

Conference papers

Network managers that succeed in improving the accuracy of client video service level predictions, where the video is deployed in a cloud infrastructure, will have the ability to deliver responsive, SLA-compliant service to their customers. Meeting up-time guarantees, achieving rapid first-call resolution, and minimizing time-to-recovery af- ter video service outages will maintain customer loyalty.

To date, regression-based models have been applied to generate these predictions for client machines using the kernel metrics of a server clus- ter. The effect of time-varying loads on cloud-hosted video servers, which arise due to dynamic user requests have not been leveraged to improve prediction …

A Comparative Study Of Defeasible Argumentation And Non-Monotonic Fuzzy Reasoning For Elderly Survival Prediction Using Biomarkers, Lucas Rizzo, Ljiljana Majnaric, Luca Longo

Conference papers

Computational argumentation has been gaining momentum as a solid theoretical research discipline for inference under uncertainty with incomplete and contradicting knowledge. However, its practical counterpart is underdeveloped, with a lack of studies focused on the investigation of its impact in real-world settings and with real knowledge. In this study, computational argumentation is compared against non-monotonic fuzzy reasoning and evaluated in the domain of biological markers for the prediction of mortality in an elderly population. Different non-monotonic argument-based models and fuzzy reasoning models have been designed using an extensive knowledge base gathered from an expert in the field. An analysis of …

State Acquisition In Computer Networks, Ruairí De Fréin

Conference papers

We establish that State Acquisition should be per- formed in networks at a rate which is consistent with the rate-of-change of the element or service being observed. We demonstrate that many existing monitoring and service-level prediction tools do not acquire network state in an appropriate manner. To address this challenge: (1) we define the rate-of- change of different applications; (2) we use methods for analysis of unevenly spaced time series, specifically, time series arising from video and voice applications, to estimate the rate-of-change of these services; and finally, (3) we demonstrate how to acquire network state accurately for a number …

Using Regular Languages To Explore The Representational Capacity Of Recurrent Neural Architectures, Abhijit Mahalunkar, John D. Kelleher

Conference papers

The presence of Long Distance Dependencies (LDDs) in sequential data poses significant challenges for computational models. Various recurrent neural architectures have been designed to mitigate this issue. In order to test these state-of-the-art architectures, there is growing need for rich benchmarking datasets. However, one of the drawbacks of existing datasets is the lack of experimental control with regards to the presence and/or degree of LDDs. This lack of control limits the analysis of model performance in relation to the specific challenge posed by LDDs. One way to address this is to use synthetic data having the properties of subregular languages. …

Review Of The Effectiveness Of Impulse Testing For The Evaluation Of Cable Insulation Quality And Recommendations For Quality Testing, Adrian Coughlan, Joseph Kearney, Tom Looby

Conference papers

Abstract— This project investigates impulse breakdown testing as a means of determining the as constructed standard of MV power cable. A literature survey is undertaken to elucidate the place of this test in an overall cable test regime and to determine the factors that impact on the performance of the test method. Testing was undertaken on ESB Networks cables to establish if a merit order ranking was feasible based on this test and to determine if the test could detect defects in the inner semiconducting layer. Based on this, conclusions and recommendations are made regarding the overall applicability and usefulness …

Is It Worth It? Budget-Related Evaluation Metrics For Model Selection, Filip Klubicka, Giancarlo Salton, John D. Kelleher

Conference papers

Projects that set out to create a linguistic resource often do so by using a machine learning model that pre-annotates or filters the content that goes through to a human annotator, before going into the final version of the resource. However, available budgets are often limited, and the amount of data that is available exceeds the amount of annotation that can be done. Thus, in order to optimize the benefit from the invested human work, we argue that the decision on which predictive model one should employ depends not only on generalized evaluation metrics, such as accuracy and F-score, but …

Human Performance Modelling For Adaptive Automation, Maria Chiara Leva, M. Wilkins, F. Coster

Conference papers

The relentless march of technology is increasingly opening new possibilities for the application of automation and new horizons for human machine interaction. However there is insufficient scientific evidence on human factors for modern socio-technical systems supporting the guidelines currently used to design Human Machine Interfaces (HMI) (ISA 2014). This dearth of knowledge presents a particular risk in safety critical industries. The continuing 60–90% of accidents currently that are rooted in Human Factors (HF) and the rapid developments in the Internet of Things (IoT) and its novel automation archetypes means that the requirements for new interfaces are becoming more demanding, and …

Ambiqual – A Full Reference Objective Quality Metric For Ambisonic Spatial Audio, Miroslaw Narbutt, Andrew Allen, Jan Skoglund, Michael Chinen, Andrew Hines

Conference papers

Streaming spatial audio over networks requires efficient encoding techniques that compress the raw audio content without compromising quality of experience. Streaming service providers such as YouTube need a perceptually relevant objective audio quality metric to monitor users’ perceived quality and spatial localization accuracy. In this paper we introduce a full reference objective spatial audio quality metric, AMBIQUAL, which assesses both Listening Quality and Localization Accuracy. In our solution both metrics are derived directly from the B-format Ambisonic audio. The metric extends and adapts the algorithm used in ViSQOLAudio, a full reference objective metric designed for assessing speech and audio quality. …

Ranking Semantics Based On Subgraphs Analysis, Pierpaolo Dondio

Conference papers

An abstract argumentation framework [15] consists of a direct graph where nodes represent arguments and arrows represent an attack relation among arguments. A semantics is used to evaluate arguments’ acceptability. In the labelling approach [7], this evaluation is done by assigning to each argument a label in, out or undec, meaning that the argument is considered consistently acceptable, non-acceptable or undecided (i.e. no decision can be taken on arguments’ acceptability).

On The Reliability, Validity And Sensitivity Of Three Mental Workload Assessment Techniques For The Evaluation Of Instructional Designs: A Case Study In A Third-Level Course, Luca Longo

Conference papers

Cognitive Load Theory (CLT) has been conceived for instructional designers eager to create instructional resources that are presented in a way that encourages the activities of the learners and optimise their performance, thus their learning. Although it has been researched for many years, it has been criticised because of its theoretical clarity and its methodological approach. In particular, one fundamental and open problem is the measurement of its cognitive load types and the measurement of the overall cognitive load of learners during learning tasks. This paper is aimed at investigating the reliability, validity and sensitivity of existing mental workload assessment …

Examining A Hate Speech Corpus For Hate Speech Detection And Popularity Prediction, Filip Klubicka, Raquel Fernandez

Conference papers

As research on hate speech becomes more and more relevant every day, most of it is still focused on hate speech detection. By attempting to replicate a hate speech detection experiment performed on an existing Twitter corpus annotated for hate speech, we highlight some issues that arise from doing research in the field of hate speech, which is essentially still in its infancy. We take a critical look at the training corpus in order to understand its biases, while also using it to venture beyond hate speech detection and investigate whether it can be used to shed light on other …

Tiled Time Delay Estimation In Mobile Cloud Computing Environments, Ruairí De Fréin

Conference papers

We present a tiled delay estimation technique in the context of Mobile Cloud Computing (MCC) environments. We examine its accuracy in the presence of multiple sources for (1) sub-sample delays and also (2) in the presence of phase-wrap around. Phase wrap-around is prevalent in MCC because the separation of acoustic sources may be large. We show that tiling a histogram of instantaneous phase estimates can improve delay estimates when phase-wrap around is sig- nificantly present and also when multiple sources are present. We report that error in the delay estimator is generally less than 5% of a sample, when the …

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 …

Key Inference From Irish Traditional Music Scores And Recordings, Pierre Beauguitte, Bryan Duggan, John D. Kelleher

Conference papers

The aim of this paper is to present techniques and results for identifying the key of Irish traditional music melodies, or tunes. Several corpora are used, consisting of both symbolic and audio representations. Monophonic and heterophonic recordings are present in the audio datasets. Some particularities of Irish traditional music are discussed, notably its modal nature. New key-profiles are defined, that are better suited to Irish music.

Chaos-Based Cryptography For Cloud Computing, Paul Tobin, Lee Tobin, Michael Mckeever, Jonathan Blackledge

Conference papers

Cloud computing and poor security issues have quadrupled over the last six years and with the alleged presence of backdoors in common encryption ciphers, has created a need for personalising the encryption process by the client. In 2007, two Microsoft employees gave a presentation ``On the Possibility of a backdoor in the NIST SP800-90 Dual Elliptic Curve Pseudo Random Number Generators'' and was linked in 2013 by the New York Times with notes leaked by Edward Snowden. This confirmed backdoors were placed, allegedly, in a number of encryption systems by the National Security Agency, which if true creates an urgent …

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 …

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 …

Propagating Degrees Of Truth On An Argumentation Framework: An Abstract Account Of Fuzzy Argumentation, Pierpaolo Dondio

Conference papers

This paper proposes a computational framework to reason with conflicting and gradual evidence. The framework is a synthesis of Dung’s seminal work in argumentation semantics with multi-valued logic. Abstract grounded semantics is used to identify the conditions under which a conclusion can be accepted, while multi-valued logic operators are used to quantify the degree of truth of such conditions. We propose a truth-compositional recursive computation based on the notion of irrelevant arguments, and we discuss examples using the major multi-valued logics: Godel’s, Zadeh’s and Łukasiewicz's logic.

On The Development Of A One-Time Pad Generator For Personalising Cloud Security, Paul Tobin, Lee Tobin, Michael Mckeever, Jonathan Blackledge

Conference papers

Cloud computing security issues are being reported in newspapers, television, and on the Internet, on a daily basis. Furthermore, in 2013, Edward Snowden alleged backdoors were placed in a number of encryption systems by the National Security Agency causing confidence in public encryption to drop even further. Our solution allows the end-user to add a layer of unbreakable security by encrypting the data locally with a random number generator prior to uploading data to the Cloud. The prototype one-time pad generator is impervious to cryptanalysis because it generates unbreakable random binary sequences from chaos sources initiated from a natural noise. …

A Hardware One-Time Pad Prototype Generator For Localising Cloud Security, Jonathan Blackledge, Paul Tobin, Lee Tobin, Mick Mckeever

Conference papers

Abstract: In this paper, we examine a system for encrypting data before storing in the Cloud. Adopting this system gives excellent security to stored data and complete control for accessing data by the client at different locations. The motivation for developing this personal encryption came about because of poor Cloud security and doubts over the safety of public encryption algorithms which might contain backdoors. However, side-channel attacks and other unwanted third-party interventions in Cloud security, probably contribute more to the poor security record history. These factors led to the development of a prototype for personalising security locally which defeats cryptanalysis. …

Application Of Artificial Intelligence For Detecting Computing Derived Viruses, Jonathan Blackledge, Omotayo Asiru, Moses Dlamini

Conference papers

Computer viruses have become complex and operates in a stealth mode to avoid detection. New viruses are argued to be created each and every day. However, most of these supposedly ‘new’ viruses are not completely new. Most of the supposedly ‘new’ viruses are not necessarily created from scratch with completely new (something novel that has never been seen before) mechanisms. For example, most of these viruses just change their form and signatures to avoid detection. But their operation and the way they infect files and systems is still the same. Hence, such viruses cannot be argued to be new. In …