Digital Commons Network^™

A Developmental Model Of Trust In Humanoid Robots, Massimiliano Patacchiola

School of Engineering, Computing and Mathematics Theses

Trust between humans and artificial systems has recently received increased attention due to the widespread use of autonomous systems in our society. In this context trust plays a dual role. On the one hand it is necessary to build robots that are perceived as trustworthy by humans. On the other hand we need to give to those robots the ability to discriminate between reliable and unreliable informants. This thesis focused on the second problem, presenting an interdisciplinary investigation of trust, in particular a computational model based on neuroscientific and psychological assumptions. First of all, the use of Bayesian networks for …

Contributions To Converters In Single Phase Distributed Photovoltaic Systems, Ali Hussein Abduljabbar Al-Omari

School of Engineering, Computing and Mathematics Theses

This thesis contributes to improve the photovoltaic Distributed Generation (DG) systems by proposing three novel methods to the system. On DC conversion side, a new integrated magnetic structure for interleaved converter and a new method to calculate the eddy current and hysteresis losses in the magnetic core were proposed. On inversion side, A new synchronisation method for grid tie inverters was suggested. The technique is using the Recursive Discrete Fourier Transform (RDFT) to find fundamental in grid waveform. On the DC converter side, the benefits of the new structure is to produce magnetic flux that alternate in the core across …

Numerical Modelling Of Extreme Waves: The Role Of Nonlinear Wave-Wave Interactions, Thomas Vyzikas

School of Engineering, Computing and Mathematics Theses

The real monsters of the ocean, extreme waves, haunted mariners since the early days of human activities in the sea. Despite having caused numerous accidents and casualties, their systematic study began only in 2000s. Many mechanisms have been proposed to simulate these rare but catastrophic events, with the most prominent being wave focusing. This is connected to the NewWave theory, which has been used extensively in experimental and numerical modelling. However, the majority of the studies fail to capture the distinguishing characteristics of extreme waves, due to the inherent high nonlinearity of the problem and shortcomings of the modelling practice, …

Research Methodology In Business: A Starter’S Guide, Mohamed Af Ragab, Amr Arisha

Articles

A cardinal requisite of successful research lies in the proper selection of the research methodology applied to achieve research objectives using the available resources. In addition to acquiring sufficient knowledge of their specific research topic, researchers are urged to develop good understanding of alternative research methodologies at their disposal to be able to identify the best-suited methods to address the research question. This, however, often poses a challenge for novice researchers who face difficulty in grasping the vast methodology landscape and its encompassing array of debates. The purpose of this paper is to provide new researchers with a comprehensive overview …

Understanding Market Inefficiency In The East Asian Region During Times Of Crisis, Lucia Morales, Bernadette Andreosso-O’Callaghan

Articles

The study of financial market efficiency has important implications in terms of global macroeconomic stability. The case of six selected East Asian stock markets (China, Japan, Hong Kong, Malaysia, Singapore and South Korea) during the Asian Financial Crisis (AFC) and Global Financial Crisis (GFC) is analysed here using a battery of well-known econometric techniques that starts with traditional unit root testing for random walk behaviour. The six countries were selected on the basis of market capitalization to offer insights into the behaviour of the most relevant markets in the region. The results show that during both crises, these markets exhibited …

Green Networking: Analyses Of Power Consumption Of Real And Complex Ifft/Fft Used In Next-Generation Networks And Optical Orthogonal Frequency Division Multiplexing, Sameer Sami Hassan Al-Obaidi

School of Engineering, Computing and Mathematics Theses

The Orthogonal Frequency Division Multiplexing is a promising technology for the Next Generation Networks. This technique was selected because of the flexibility for the various parameters, high spectral efficiency, and immunity to ISI. The OFDM technique suffers from significant digital signal processing, especially inside the Inverse/ Fast Fourier Transform IFFT/FFT. This part is used to perform the orthogonality/De-orthogonality between the subcarriers which the important part of the OFDM system. Therefore, it is important to understand the parameter effects on the increase or to decrease the FPGA power consumption for the IFFT/FFT. This thesis is focusing on the FPGA power consumption …

A Secure Quorum Based Multi-Tag Rfid System, Ayad Al-Adhami

School of Engineering, Computing and Mathematics Theses

Radio Frequency Identification (RFID) technology has been expanded to be used in different fields that need automatic identifying and verifying of tagged objects without human intervention. RFID technology offers a great advantage in comparison with barcodes by providing accurate information, ease of use and reducing of labour cost. These advantages have been utilised by using passive RFID tags. Although RFID technology can enhance the efficiency of different RFID applications systems, researchers have reported issues regarding the use of RFID technology. These issues are making the technology vulnerable to many threats in terms of security and privacy. Different RFID solutions, based …

Drivers Of Wearable Computing Adoption: An Empirical Study Of Success Factors Including It Security And Consumer Behaviour-Related Aspects, Lena Gribel

School of Engineering, Computing and Mathematics Theses

The recent advances in information technologies have dramatically changed the manner in which people understand, experience and use IT systems. Wearable computers are emerging new technologies in the evolution of mobile devices, which introduce a paradigm shift in the field of human computer-interaction. By equipping the user with computational capabilities, ‘wearables’ provide context-aware and seamlessly integrated on-the-fly computing across heterogeneous circumstances and irrespective of place and time. Not least the very promising market prospects for wearable devices imply various unprecedented business opportunities and a vast economic potential of these socio-technological gadgets. Nonetheless, analysis of the current market situation shows that …

Teaching Robots Social Autonomy From In Situ Human Supervision, Emmanuel Senft

School of Engineering, Computing and Mathematics Theses

Traditionally the behaviour of social robots has been programmed. However, increasingly there has been a focus on letting robots learn their behaviour to some extent from example or through trial and error. This on the one hand excludes the need for programming, but also allows the robot to adapt to circumstances not foreseen at the time of programming. One such occasion is when the user wants to tailor or fully specify the robot’s behaviour. The engineer often has limited knowledge of what the user wants or what the deployment circumstances specifically require. Instead, the user does know what is expected …

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.

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 …

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 …

An Investigation Into Factors Which Explain The Scores And Voting Patterns Of The Eurovision Song Contest., Oisín Leonard

Dissertations

The Eurovision Song Contest (ESC) is an annual international television song competition. Participating countries send a group or individual artist to perform an original song at the competition. The winner is decided by all participating countries using a voting system that incorporates both a public televote and an expert jury vote. Countries are excluded from voting for their entry and the country with the highest score wins. A high scoring performance and the voting patterns of the ESC can be explained by a complex set of factors. These factors can be divided into three groups; performance factors, competition factors and …

Image Classification Using Bag-Of-Visual-Words Model, Kaiqiang Huang

Dissertations

Recently, with the explosive growth of digital technologies, there has been a rapid proliferation of the size of image collection. The technique of supervised image clas sification has been widely applied in many domains in order to organize, search, and retrieve images. However, the traditional feature extraction approaches yield the poor classification accuracy. Therefore, the Bag-of-visual-words model, inspired by Bag-of Words model in document classification, was used to present images with the local descriptors for image classification, and also it performs well in some fields. This research provides the empirical evidence to prove that the BoVW model outperforms the traditional …

A Javascript Framework Comparison Based On Benchmarking Software Metrics And Environment Configuration, Jefferson Ferreira

Dissertations

JavaScript is a client-side programming language that can be used in multi-platform applications. It controls HTML and CSS to manipulate page behaviours and is widely used in most websites over the internet. JavaScript frameworks are structures made to help web developers build web applications faster by offering features that enhance the user interaction with the web page. An increasing number of JavaScript frameworks have been released in recent years in the market to help front-end developers build applications in a shorter space of time. Decision makers in software companies have been struggling to determine which frameworks are best suited for …

That Seems Made Up: Deep Learning Classifiers For Fiction & Non Fiction Book Reviews, Clement Manger

Dissertations

The thesis aims to take the first step towards automated extraction of the information found in book reviews, by using machine learning tools to assign a label of fiction or non fiction to the text. The thesis makes use of neural networks and performs experiments around architecture, hyper-parameters and text processing from which an optimized model is produced. The thesis enjoys certain successes; it was possible to match the state of the art achieved by (Kim, 2014) and computation was sped up considerably from the default to the optimized model by 13.8 seconds per 50 steps. Further it is confirmed …

Identifying Expert Investors On Financial Microblog Via Artificial Neural Networks, Pierluca Del Buono

Dissertations

In the recent years, thanks to social media platform, a plethora of information has been available to financial investors, that were traditionally dependent from financial institutions advisors. Strategies are now shared among web users, performances of stocks are commented in web communities and hints and suggestions are travelling on the internet with a fast pace, in a way that was unthinkable few years before. Several attempts have been made in the recent past, to predict Market movements and trends from activity of Financial Social Networks participants, and to evaluate if contributions from individuals with high level of expertise distinguish themselves …

A Systems Approach To Research And Innovation For Food System Transformation, M. Gill, A.C.L. Den Boer, K.P. Kok, Jean Cahill, C. Callenius, P. Caron, Z. Damianova, M.A. Gurinovic, L. Lahteenmaki, T. Lang, A. Lappiere, C. Mango, J. Ryder, R. Sonnino, H. Westhoek, B.J. Regeer, J.E.W. Broerse

Research and Innovation - Other

This policy brief of the European Union (EU) Think Tank – part of the FIT4FOOD2030 Coordination and Support Action (CSA) of the FOOD 2030 initiative – is a response and contribution to growing pleas for a ‘systems approach’ to transform food systems for Food and Nutrition Security (FNS) for present and future generations. This policy brief specifically focusses on the necessity of the adoption of a systems approach to Research and Innovation (R&I) in order to foster the transformation of food systems.

The Oral Writing-Revision Space: Identifying A New And Common Discourse Feature Of Writing Center Consultations, Melody Denny

The Writing Center Journal

No abstract provided.

Addressing The Proton Radius Puzzle Using Qed-Nrqed Effective Field Theory, Steven Patrick Dye

Wayne State University Dissertations

In 2010 the first extraction of the proton charge radius from muonic hydrogen was found to be five standard deviations away from the regular hydrogen value. Seven years later, this proton radius puzzle still persists, and challenges our understanding of the structure of the proton. An effective field theory analysis using Non-Relativistic Quantum Electrody- namics (NRQED) indicates that the muonic hydrogen result can be interpreted as a large, compared to some model estimates, muon-proton spin-independent contact interaction. The muonic hydrogen result can be tested by a muon-proton scattering experiment, MUSE, that is planned at the Paul Scherrer Institute in Switzerland. …