Digital Commons Network^™

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 …

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.

Fatigue Properties And Fracture Morphology Of Micronised Rubber Powder (Mrp) From Waste Tyres In Unfilled Elastomers, A.I.H. D Habibah, F Abraham, J Summerscales, P Brown

School of Engineering, Computing and Mathematics

Ground rubber from waste tyres may be added to elastomers with economic and environmental benefits. The untreated or treated fillers have been investigated in different types of virgin rubber matrix. A principal concern is their crosslinked structure and large particle sizes. These additives introduce flaws leading to micro-crack initiation especially under dynamic loading. The incorporation of smaller particles at a suitable concentration may avoid deterioration in the key properties. The present work studies the effect of commercial cryogenic micronised rubber particle (MRP) (apparent particle size diameter less than 100 μm) as filler at either 10 or 30 parts per hundred …

Distributed Nfv Orchestration In A Wmn-Based Disaster Network, G Frick, A. Paguem Tchinda, U Trick, A. Lehmann, G Frick, A. Paguem Tchinda, B. Ghita

School of Engineering, Computing and Mathematics

This publication deals with distributed NFV orchestration in a WMN-based disaster network. The NFV orchestrator defined by ETSI is designed as a central unit and therefore includes the possibility of a single point of failure. Due to the environment of a disaster, a WMN node hosting this centralized orchestrator might get destroyed at events such as aftershocks resulting in a breakdown of the NFV infrastructure as it cannot be maintained and orchestrated anymore. To eliminate this aspect, requirements for a distributed NFV orchestration are defined. The requirements are categorized into architectural and orchestration specific aspects and are derived from the …

Steam Programming (Science, Technology, Engineering, And Mathematics) Applications For Camp Adventure Child And Youth Services, Shannon Boseneiler

Dissertations and Theses @ UNI

The purpose of this study is to create a STEM/STEAM working resource for Camp Adventure Child and Youth Services TM (CACYS) in order to provide effective programming for summer day camp programs. Currently, there is a lack of STEM and STEAM resources for CACYS. STEM education is defined by science, technology, engineering, and mathematics education whereas STEAM education includes the integration of art education. This study will use Action Research in order to review and analyze a variety of successful STEM/STEAM programs. Elements from these programs will be incorporated into the resource for CACYS. Effective teaching strategies will also be …

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. …

Ferrite Assisted Geometry-Conformal Magnetic Induction Antenna And Subsea Communications For Auvs, Debing Wei, Li Yan, Xuanheng Li, Jie Wang, Jiefu Chen, Miao Pan, Yahong Rosa Zheng

Electrical and Computer Engineering Faculty Research & Creative Works

This paper designs a novel geometry-conformal antenna for Magnetic Induction (MI)-based subsea wireless communications for autonomous underwater vehicles (AUV). The designed tri-directional antennas can be wrapped directly on the surface of AUVs, such that the AUVs fluid dynamics are well maintained to ensure power efficiency of the vehicles. In addition, ferrite materials are added between the MI antenna and the metallic body surface of the AUVs to overcome the shielding effect and enhance the MI signal strength. The designed MI communication system is implemented in hardware and the effectiveness of the geometry-conformal MI antenna is demonstrated through COMSOL simulations and …

Surfactants, Thermal And Surface Energy Effects On Emulsions’ Transport Properties: A Study Using Lattice Boltzmann Method, Wessam Falih Hasan

Wayne State University Dissertations

This work aims to provide an efficient Gunstensen LBM based CFD model, capable of solving complex problems related to droplets behavior in shear and parabolic flows.

Thermal conditions determine the outcome of the physical and transport properties of emulsions during their various processing phases. A better understanding of the intricate relationship between thermal, surfactants and hydrodynamics can help in the optimization of these processes during the production of emulsions. To investigate the outcome of coupling thermal, surfactants and hydrodynamics on emulsions behavior, a robust quasi-steady thermal-surfactants numerical scheme is presented and used here. To validate the model, the rheological behavior …

Application Of Improved Fast Dynamic Allan Variance For The Characterization Of Mems Gyroscope On Uav, Qian Zhang, Xueyun Wang, Shiqian Wang, Chaoying Pei

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Microelectromechanical systems (MEMS) are core components in unmanned aerial vehicles (UAV). The precision of MEMS sensors is very important when the GPS signal is invalid. However, the precision and performance of MEMS sensors will be degraded by the changing of environment. Therefore, estimation and identification of the various noise terms existing in MEMS sensors are deemed to be necessary. The Allan variance is a common and standard method to analyze MEMS sensors, but it cannot be used to analyze the dynamic characteristics. The dynamic Allan variance (DAVAR) is a sliding version of the Allan variance. It is a practical tool …

On-Road Remote Sensing Of Automobile Emissions In The Denver Area: Winter 2017, Gary A. Bishop, Molly J. Haugen

Fuel Efficiency Automobile Test Publications

No abstract provided.

On-Road Remote Sensing Of Automobile Emissions In The Tulsa Area: Fall 2017, Gary A. Bishop

Fuel Efficiency Automobile Test Publications

No abstract provided.