Digital Commons Network^™

The 2018 International Conference On Unmanned Aircraft Systems, R Polvara, M Patacchiola, S Sharma, J Wan, A Manning, R Sutton, A Cangelosi

School of Engineering, Computing and Mathematics

The autonomous landing of an unmanned aerial vehicle (UAV) is still an open problem. Previous work focused on the use of hand-crafted geometric features and sensor-data fusion for identifying a fiducial marker and guide the UAV toward it. In this article we propose a method based on deep reinforcement learning that only requires low-resolution images coming from a down looking camera in order to drive the vehicle. The proposed approach is based on a hierarchy of Deep Q-Networks (DQNs) that are used as high-end control policy for the navigation in different phases. We implemented various technical solutions, such as the …

Bottle House: A Case Study Of Transdisciplinary Research For Tackling Global Challenges, Muyiwa Oyinlola, T Whiteheadb, A Abuzeinabc, A Adefilad, Yewande Akinola, Fatai Anafi, Farukh Farukh, Oluyemi Jegede, Karthikeyan Kandan, Boksun Kim, Emmanuel Mosugu

School of Engineering, Computing and Mathematics

No abstract provided.

Non-Intrusive Appliance Load Monitoring Using Genetic Algorithms, D. Hock, M. Kappes, B. Ghita

School of Engineering, Computing and Mathematics

No abstract provided.

Starting A Wave Structure Interaction Cfd Simulation From An Advance Time: Hot-Start, P-H Musiedlak, Ej Ransley, S Brown, B Child, Mr Hann, G Iglesias, Dm Greaves

School of Engineering, Computing and Mathematics

No abstract provided.

Extreme Coastal Responses Using Focused Wave Groups: Overtopping And Horizontal Forces Exerted On An Inclined Seawall, C. N. Whittaker, C. J. Fitzgerald, A. C. Raby, P. H. Taylor, A. G.L. Borthwick

School of Engineering, Computing and Mathematics

No abstract provided.

Experimental Modal Analysis Of British Rock Lighthouses, James Mark William Brownjohn, Alison Raby, James Bassitt, Alessandro Antonini, Emma Hudson, Peter Dobson

School of Engineering, Computing and Mathematics

© 2018 The Authors Iconic lighthouses constructed on offshore reefs around the British Isles in the 19th century continue to play a crucial role in safe navigation, but the longevity of these historical structures is threatened by extreme weather. A program of experimental dynamic investigations has been carried out to support characterisation of extreme impulsive breaking wave loads on these structures, using monitored response data. This paper describes the procedures and outcomes of this program, which included modal tests of a collection of six of these lighthouses between June 2016 and October 2017. Five of the six lighthouses tested (Les …

Visualisation With Treemaps And Sunbursts In Evolutionary Many-Objective Optimisation, David J. Walker

School of Engineering, Computing and Mathematics

No abstract provided.

Bayesian Hierarchical Models For Linear Networks, Zainab A A Al-Kaabawi

School of Engineering, Computing and Mathematics Theses

A motorway network is handled as a linear network. The purpose of this study is to highlight dangerous motorways via estimating the intensity of accidents and study its pattern across the UK motorway network. Two mechanisms have been adopted to achieve this aim. The first, the motorway-specific intensity is estimated by modelling the point pattern of the accident data using a homogeneous Poisson process. The homogeneous Poisson process is used to model all intensities but heterogeneity across motorways is incorporated using two-level hierarchical models. The data structure is multilevel since each motorway consists of junctions that are joined by grouped …

Action Learning Experiments Using Spiking Neural Networks And Humanoid Robots, Ricardo De Azambuja

School of Engineering, Computing and Mathematics Theses

The way our brain works is still an open question, but one thing seems to be clear: biological neural systems are computationally powerful, robust and noisy. Natural nervous system are able to control limbs in different scenarios with high precision. As neural networks in living beings communicate through spikes, modern neuromorphic systems try to mimic them by using spike-based neuron models. This thesis is focused on the advancement of neurorobotics or brain inspired robotic arm controllers based on artificial neural network architectures. The architecture chosen to implement those controllers was the spike neuron version of Reservoir Computing framework, called Liquid …

Trust-Based Composition Of M2m Application Services, Besfort Shala, Ulrich Trick, Armin Lehmann, Besfort Shala, Bogdan Ghita, Stavros Shiaeles

School of Engineering, Computing and Mathematics

No abstract provided.

Towards A Conceptual Framework For The Development Of Immersive Experiences To Negotiate Meaning And Identify In Irish Language Learning, Naoise Collins, Brian Vaughan, Keith Gardiner, Charlie Cullen

Conference papers

The onset of virtual reality systems allows for new immersive content which provides users with a sense of presence in their virtual environment. This paper provides the conceptual framework for a larger study examining how designed virtual reality experiences can be utilised to transform Irish language meaning making and a user's personal Irish language identity.

Introduction To Laser Induced Breakdown Spectroscopy Imaging In Food: Salt Diffusion In Meat, Yash Dixit, Carl Sullivan, Patrick J. Cullen

Articles

This study illustrates the ability of laser induced breakdown spectroscopy (LIBS) to detect and map 22 minerals in food. A LIBS system was used to spatially collect spectra of beef samples. Samples were 23 brined in a 6% salt solution for 2h and 24h along with a control sample. Samples were measured by 24 scanning the cross-section of each sample in a 90 X 90 square grid. Sodium (Na) distribution images 25 with respect to emission peak at 589.05 nm were generated after pre-processing the spectral data which 26 directly corresponds to salt levels. As expected, the control sample showed …

Unprecedented In Vitro Antitubercular Activitiy Of Manganese(Ii) Complexes Containing 1,10- Phenanthroline And Dicarboxylate Ligands: Increased Activity, Superior Selectivity, And Lower Toxicity In Comparison To Their Copper(Ii) Analogs, Pauraic Mccarron, Malachy Mccann, Michael Devereux, Kevin Kavanagh, Ciaran M. Skerry, Petros C. Karakousis, Ana Carolina Aor, Thaís P. Mello, Dos Santos, André Luis Souza Dos Santos, André Luis Souza, Débora Leite Campos, Fernando R. Pavan

Articles

Mycobacterium tuberculosis is the etiologic agent of tuberculosis. The demand for new chemotherapeutics with unique mechanisms of action to treat (multi)resistant strains is an urgent need. The objective of this work was to test the effect of manganese(II) and copper(II) phenanthroline/dicarboxylate complexes against M. tuberculosis. The water-soluble Mn(II) complexes, [Mn2(oda)(phen)4(H2O)2][Mn2(oda)(phen)4(oda)2]·4H2O (1) and ([Mn(3,6,9-tdda)(phen)2]·3H2O·EtOH)n (3) (odaH2 = octanedioic acid, phen = 1,10-phenanthroline, tddaH2 = 3,6,9-trioxaundecanedioic acid), and water-insoluble complexes, [Mn(ph)(phen)(H2O)2] (5), [Mn(ph)(phen)2(H2O)]·4H2O (6), [Mn2(isoph)2(phen)3]·4H2O (7), ([Mn(phen)2(H2O)2])2(isoph)2(phen)·12H2O (8) and [Mn(tereph)(phen)2]·5H2O (9) (phH2 = phthalic acid, isophH2 = isophthalic acid, terephH2 = terephthalic acid), robustly inhibited the viability of M. tuberculosis strains, H37Rv …

Significance Of A Non-Thermal Plasma Treatment On Ldpe Biodegradation With Pseudomonas Aeruginosa, Laurence Scally, Miroslav Gulan, Lars Weigang, Vladimir Milosavljević, Patrick J. Cullen

Articles

The use of plastics has spanned across almost all aspects of day to day life. Although their uses are invaluable, they contribute to the generation of a lot of waste products that end up in the environment and end up polluting natural habitats such as forests and the ocean. By treating low-density polyethylene (LDPE) samples with non-thermal plasma in ambient air and with an addition of ≈4% CO2, the biodegradation of the samples can be increased due to an increase in oxidative species causing better cell adhesion and acceptance on the polymer sample surface. It was, however, found that the …

Targeting The Folate Receptor: Improving Efficacy In Inorganic Medicinal Chemistry, Pauraic Mccarron, Aisling Crowley, Denis O'Shea, Malachy Mccann, Orla L. Howe, Mary Hunt, Michael Devereux

Articles

The discovery of the high-affinity, high-specificity folate receptor in mamalian kidney cells, coupled with the ability of folate to enter cells by folate receptor-mediated endocytosis and the subsequent elucidation of the folate receptor’s overexpression in specific cancer cell types; heralded the arrival of the area of chemotherapeutic folate targeting. The application of purely organic folate-based small-molecule drug conjugates that selectively target the folate receptor, which is over expressed in several diseases such as cancer, is well established. The application of inorganic folate-targeted drugs offers significant potential to expand and enhance this therapeutic approach. From the data made available to date, …

Chemical Modifications Of Lipids And Proteins By Nonthermal Food Processing Technologies, Juan M. PéRez-AndréS, CléMentine Charoux, Patrick J. Cullen, Brijesh K. Tiwari

Articles

A range of nonthermal techniques have demonstrated process efficacy in ensuring product safety, extension of shelf life, and in general a retention of key quality attributes. However, various physical, chemical and biochemical effects of nonthermal techniques on macro and micro nutrients are evident, leading to both desirable and undesirable changes in food products. The objective of this review is to outline the effects of nonthermal techniques on food chemistry and the associated degradation mechanisms with the treatment of foods. Oxidation is one of the key mechanisms responsible for undesirable effects induced by nonthermal techniques. Degradation of key macromolecules largely depends …

Spectroscopic Study Of Excited Molecular Nitrogen Generation Due To Interactions Of Metastable Noble Gas Atoms, Laurence Scally, James Lalor, Miroslav Gulan, Patrick J. Cullen, Vladimir Milosavljevic

Articles

This work provides an insight into the generation of excited nitrogen species by allowing noble gases to interact both with one another and ambient air. He and Ar were utilized to generate the optimum selectivity process to create reactive nitrogen species. An optimum setting for the generation of excited molecular nitrogen species, based on their excited energy levels, was obtained when using a mixture of Ar-He at a ratio of 10:1. At that point, when a voltage of 27 kV is applied to the system, it reached the maximum efficiency for selectivity processes to occur which allowed for a greater …

Menstrual Cycle And The Temporal Discrimination Threshold, Eavan M. Mc Govern, Emer O'Connor, Ines Beiser, Laura Williams, John Butler, Brendan Quinlivan, Shruti Narasimham, Rebecca Beck, Richard B. Reilly, Sean O'Riordan, Michael Hutchinson

Articles

The temporal discrimination threshold (TDT) is a proposed pre-clinical biomarker (endophenotype) for adult onset isolated focal dystonia (AOIFD). Age- and sex-related effects on temporal discrimination demonstrate that women, before the age of 40 years, have faster temporal discrimination than men but their TDTs worsen with age at almost three times the rate of men. Thus after 40 years the TDT in women is progressively worse than in men. AOIFD is an increasingly female-predominant disorder after the age of 40; it is not clear whether this age-related sexually-dimorphic difference observed for both the TDT and sex ratio at disease onset in …

Cognitive Load Reduces The Effects Of Optic Flow On Gait And 2 Electrocortical Dynamics During Treadmill Walking 3, Brenda Malcolm, John J. Foxe, John Butler, Sophie Molholm, Pierfilippo De Sanctis

Articles

While navigating complex environments the brain must continuously adapt to both external demands such as fluctuating sensory inputs, as well as internal demands, such as engagement in a cognitively demanding task. Previous studies have demonstrated changes in behavior and gait with increased sensory and cognitive load, but the underlying cortical mechanisms remain largely unknown. Here, in a Mobile Brain/Body Imaging (MoBI) approach sixteen young adults walked on a treadmill with high-density EEG while 3D motion capture tracked kinematics of the head and feet. Visual load was manipulated with the presentation of optic flow with and without continuous mediolateral perturbations. The …

An Investigation Of The Impact Of Language Runtime On The Performance And Cost Of Serverless Functions, David Jackson, Gary Clynch

Conference Papers

Serverless, otherwise known as “Function-as-a- Service” (FaaS), is a compelling evolution of cloud computing that is highly scalable and event-driven. Serverless applications are composed of multiple independent functions, each of which can be implemented in a range of programming languages. This paper seeks to understand the impact of the choice of language runtime on the performance and subsequent cost of serverless function execution. It presents the design and implementation of a new serverless performance testing framework created to analyse performance and cost metrics for both AWS Lambda and Azure Functions. For optimum performance and cost management of serverless applications, Python …

Programming: Predicting Student Success Early In Cs1. A Re-Validation And Replication Study, Keith Quille, Susan Bergin

Articles

This paper describes a large, multi-institutional revalidation study conducted in the academic year 2015-16. Six hundred and ninetytwo students participated in this study, from 11 institutions (ten institutions in Ireland and one in Denmark). The primary goal was to validate and further develop an existing computational prediction model called Predict Student Success (PreSS). In doing so, this study addressed a call from the 2015 ITiCSE working group (the second "Grand Challenge"), to "systematically analyse and verify previous studies using data from multiple contexts to tease out tacit factors that contribute to previously observed outcomes". PreSS was developed and validated in …

Rhythm Inference From Audio Recordings Of Irish Traditional Music, Pierre Beauguitte, Bryan Duggan, John D. Kelleher

Conference papers

A new method is proposed to infer rhythmic information from audio recordings of Irish traditional tunes. The method relies on he repetitive nature of this musical genre. Low-level spectral features and autocorrelation are used to obtain a low-dimensional representation, on which logistic regression models are trained. Two experiments are conducted to predict rhythmic information at different levels of precision. The method is tested on a collec- ion of session recordings, and high accuracy scores are reported.

A new method is proposed to infer rhythmic information from audio recordings of Irish traditional tunes. The method relies on he repetitive nature of …

An Investigation Of The Impact Of A Social Constructivist Teaching Approach, Based On Trigger Questions, Through Measures Of Mental Workload And Efficiency, Federico Gobbo, Luca Longo, Declan O'Sullivan, Giuliano Orru

Conference papers

Social constructivism is grounded on the construction of information with a focus on collaborative learning through social interactions. However, it tends to ignore the human mental architecture, pillar of cognitivism. A characteristic of cognitivism is that instructional designs built upon it are generally explicit, contrarily to constructivism. This position paper proposes a novel learning task that is aimed at combining both the approaches through the use of trigger questions in a collaborative activity executed after a traditional delivery of instructions. To evaluate this new task, a metric of efficiency based upon a measure of mental workload and a measure of …

A Comparison Of Classical Versus Deep Learning Techniques For Abusive Content Detection On Social Media Sites, Hao Che, Susan Mckeever, Sarah Jane Delany

Conference papers

The automated detection of abusive content on social media websites faces a variety of challenges including imbalanced training sets, the identification of an appropriate feature representation and the selection of optimal classifiers. Classifiers such as support vector machines (SVM), combined with bag of words or ngram feature representation, have traditionally dominated in text classification for decades. With the recent emergence of deep learning and word embeddings, an increasing number of researchers have started to focus on deep neural networks. In this paper, our aim is to explore cutting-edge techniques in automated abusive content detection. We use two deep learning approaches: …

Validation Of Tagging Suggestion Models For A Hotel Ticketing Corpus, Bojan Bozic, Andre Rios, Sarah Jane Delany

Conference papers

This paper investigates methods for the prediction of tags on a textual corpus that describes hotel staff inputs in a ticketing system. The aim is to improve the tagging process and find the most suitable method for suggesting tags for a new text entry. The paper consists of two parts: (i) exploration of existing sample data, which includes statistical analysis and visualisation of the data to provide an overview, and (ii) evaluation of tag prediction approaches. We have included different approaches from different research fields in order to cover a broad spectrum of possible solutions. As a result, we have …

Non-Linear Machine Learning With Active Sampling For Mox Drift Compensation, Tamara Matthews, Muhammad Iqbal, Horacio Gonzalez-Velez

Conference papers

Abstract—Metal oxide (MOX) gas detectors based on SnO2 provide low-cost solutions for real-time sensing of complex gas mixtures for indoor ambient monitoring. With high sensitivity under ideal conditions, MOX detectors may have poor longterm response accuracy due to environmental factors (humidity and temperature) along with sensor aging, leading to calibration drifts. Finding a simple and efficient solution to correct such calibration drifts has been the subject of numerous studies but remains an open problem. In this work, we present an efficient approach to MOX calibration using active and transfer sampling techniques coupled with non-linear machine learning algorithms, namely neural networks, …

Sensory Seduction And Narrative Pull, Nina Lyons, Matt Smith, Hugh Mccabe

Conference papers

User experience design is a process that has been defined, developed and refined over the last few decades. It is a process of shaping a user's movements through a website or mobile application. It is user-focussed, prioritising utility, ease-of-use and efficiency. It is widely used and has helped advance the way in which users interact with websites and mobile applications, making it far less frustrating. User experience design is a key element in how the internet and mobile technology have become ubiquitous in our daily lives. Given this success, it would seem that continuing to use this process for new …

Use Of Hyperspectral Images (Hsi) And Convolutional Neural Network (Cnn) To Identify Normal, Precancerous And Cancerous Tissues, Pallavi Jain

Dissertations

Cancer detection has been a great topic of research for a long time, as early detection of cancer can help in increasing the survival rate of patients by providing on time better treatment. A robust system is required in order to detect early-stage cancer as its difficult to identify early-stage cancer from the normal clinical process. The computer vision techniques provide a new way to understand the challenges related to the medical image analysis. This thesis presents the medical image analysis using a combination of Convolutional Neural Network and Hyperspectral Images of cancer patient's tissues. The idea behind choosing the …

Predicting Happiness - Comparison Of Supervised Machine Learning Techniques Performance On A Multiclass Classification Problem, Dorota Nieciecka

Dissertations

In the modern world, especially in contemporary economies and politics, a population's subjective well-being is a frequent subject of the public debate. As comparisons of happiness levels in different countries are published, different circumstances and their effect on the value of the subjective well-being reported by people are also analysed. However, a significant amount of the research related to subjective well-being and its determinants is still based upon survey answers and employing conventional statistical methods providing details regarding correlations and causality between different factors and subjective well-being. Application of Supervised Machine Learning techniques for prediction of subjective well-being may provide …

A Demographic Analysis To Determine User Vulnerability Among Several Categories Of Phishing Attacks., Robert Griffin

Dissertations

Phishing attacks have been on a meteoric rise in the last number of years, with 2016 seeing a 65% increase. The attacks range from targeting individuals with personalised messages to spam attacks from bot accounts. With the chances of being targeted by a phishing attack increasing, it is important to identify who is most at risk in order to help alleviate this threat. The aim of this study is to examine members from several demographics and their vulnerability to three types of phishing using data collected from a survey (n = 198). The survey tested the participant’s ability to recognise …