Digital Commons Network^™

Tracing Learning Environment In Java Programming Language, Sarah Alhammad

School of Engineering, Computing and Mathematics Theses

The visualisation approach is one of the programming learning styles that has been taken into account in programming education. A collection of visualisation tools has emerged with the aim of assisting novice programmers in learning how to program. Each tool has its own set of features that may or may not be helpful in gaining a better understanding. The methods that we used in this study are focused on using memory referencing and visualisation to clarify what happens during individual program statement executions. Understanding the efficacy of current instructional resources is a critical component of gathering students' requirements and needs …

Investigating Privacy And Security Of Cloud-Connected Autonomous Vehicles, Sahand B. Murad

School of Engineering, Computing and Mathematics Theses

Autonomous cars are intelligent systems that can do Physical tasks without human interaction and are used in Industrial environments, transport, and the military, one of most powerful feature of this technology is that possess intelligent agents that can learn from their environment, furthermore, they have several sensors with connectivity between them. Nowadays most of the car manufacturer use autonomous features like lane-keeping, Adaptive Cruise Control (ACC), advance driver assistance system and automatic parking system resulting in a rapid increase in research of autonomous vehicles e.g. in 2004 and 2005 DARPA challenges for vehicles to autonomously navigate via desert terrain, moreover, …

Dynamic Generation Of Spatial Referring Expressions For Social Robots, Christopher Wallbridge

School of Engineering, Computing and Mathematics Theses

Robots are an increasing part of our daily lives. As robots become more pervasive it is important that we are able to interact with them naturally. The field of Human Robot Interaction (HRI) seeks to improve interactions between human and robot. People spend many years in their childhood learning to communicate the locations of objects naturally to other people. When trying to communicate the location of objects, people generate under-specified statements and then generate further repair if necessary to guide the listener as part of an interactive dialogue. The focus in HRI up until now has been on trying to …

Predictive Modeling Of Critical Temperatures In Superconducting Materials, Markus Hofmann, Natalia Sizochenko

Articles

n this study, we have investigated quantitative relationships between critical temperaturesof superconductive inorganic materials and the basic physicochemical attributes of these materials(also called quantitative structure-property relationships). We demonstrated that one of the mostrecent studies (titled "A data-driven statistical model for predicting the critical temperature of asuperconductor” and published in Computational Materials Science by K. Hamidieh in 2018) reportson models that were based on the dataset that contains 27% of duplicate entries. We aimed todeliver stable models for a properly cleaned dataset using the same modeling techniques (multiplelinear regression, MLR, and gradient boosting decision trees, XGBoost). The predictive ability ofour best …

Strain-, Curvature- And Twist-Independent Temperature Sensor Based On A Small Air Core Hollow Core Fiber Structure, Dejun Liu, Wei Li, Qiang Wu, Fengzi Ling, Ke Tian, Changyu Shen, Fangfang Wei, Gerald Farrell, Yuliya Semenova, Pengfei Wang

Articles

Cross-sensitivity (crosstalk) to multiple parameters is a serious but common issue for most sensors and can significantly decrease the usefulness and detection accuracy of sensors. In this work, a high sensitivity temperature sensor based on a small air core (10 µm) hollow core fiber (SACHCF) structure is proposed. Co-excitation of both anti-resonant reflecting optical waveguide (ARROW) and Mach-Zehnder interferometer (MZI) guiding mechanisms in transmission are demonstrated. It is found that the strain sensitivity of the proposed SACHCF structure is decreased over one order of magnitude when a double phase condition (destructive condition of MZI and resonant condition of ARROW) is …

Monitoring Stem Cell Differentiation Using Raman Microspectroscopy: Chondrogenic Differentiation, Towards Cartilage Formation, Francesca Ravera, Esen Efeoglu, Hugh Byrne

Articles

Mesenchymal Stem Cells (MSCs) have the ability to differentiate into chondrocytes, the only cellular components of cartilage and are therefore ideal candidates for cartilage and tissue repair technologies. Chondrocytes are surrounded by cartilage-like extracellular matrix (ECM), a complex network rich in glycosaminoglycans, proteoglycans, and collagen, which, together with a multitude of intracellular signalling molecules, trigger the chondrogenesis and allow the chondroprogenitor to acquire the spherical morphology of the chondrocytes. However, although the mechanisms of the differentiation of MSCs have been extensively explored, it has been difficult to provide a holistic picture of the process, in situ. Raman Micro Spectroscopy (RMS) …

Food Contact Surfaces: Challenges, Legislation And Solutions, Shubham Sharma, Amit Jaiswal, Brendan Duffy, Swarna Jaiswal

Articles

Food contact surfaces (FCSs) include all surfaces that may come in contact with the food during production, processing, and packaging. Food processing industries encounter several challenges due to its microbial interaction with the FCSs, such as cross-contamination of pathogenic microorganisms or allergens in food, formation of biofilm, biodeterioration of food contact surface leads to food with reduced shelf-life and quality. A legal EU framework provides the fundamental postulates for the safety and inertness of all Food Contact Materials (FCMs). Legislations have an important role in providing regulatory guidance on the quality assurance systems and verifying their implementation as a means …

Semiclassical Backreaction On Asymptotically Anti–De Sitter Black Holes, Peter Taylor, Cormac Breen

Articles

We consider a quantum scalar field on the classical background of an asymptotically anti–de Sitter black hole and the backreaction the field’s stress-energy tensor induces on the black hole geometry. The backreaction is computed by solving the reduced-order semiclassical Einstein field equations sourced by simple analytical approximations for the renormalized expectation value of the scalar field stress-energy tensor. When the field is massless and conformally coupled, we adopt Page’s approximation to the renormalized stress-energy tensor, while for massive fields we adopt a modified version of the DeWitt-Schwinger approximation. The latter approximation must be modified so that it possesses the correct …

Collaborations In Environmental Initiatives For An Effective Gover- Nance Of Social-Ecological Systems: What The Scientific Literature Suggests., Elena Andriollo, Alberto Caimo, Laura Secco, Elena Pisani

Articles

Moving from the scientific literature on evaluation of environmental projects and programs, this study identifies how and under which conditions collaborations are considered effective for adaptive gover- nance of SES. The method adopted is a systematic literature review based on the quantitative and qualitative analysis of 56 articles selected through specific queries on the SCOPUS database and published from 2004 to 2020. Results of the quantitative analysis underline conditions able to make collaborations effective for adaptive governance of SES: the importance of transdisciplinary research tackling both environmental and social sciences, the perceived urgency of stakeholders to tackle environmental challenges and …

Sure 2021 Undergraduate Science Conference Booklet, Sure Network

Group Reports

The SURE 2021 Conference was the fourth series of Science Undergraduate Research Experience (SURE) Conferences and second online conference, following earlier face to face series in 2018 (with three conferences in Dublin, Athlone and Waterford) and in 2019 (with three conferences in Dublin, Sligo and Carlow). The 2021 virtual online conference was hosted by Waterford Institute of Technology (WIT), TUS:MM (Athlone Institute of Technology) and Dundalk Institute of Technology (Dundalk IT) and featured 23 oral presentations and 48 poster presentations across three thematic streams/break out rooms on zoom. An interactive virtual poster session took place using …

Does California’S Emfac2017 Vehicle Emissions Model Under-Predict California Light-Duty Gasoline Vehicle Nox Emissions?, Gary A. Bishop

Fuel Efficiency Automobile Test Publications

On-road remote sensing measurements of light and medium-duty gasoline vehicles collected within California’s South Coast Air Basin since 1999 generally fall within the range of observed summer ambient molar NO_x/CO measurements collected during morning rush hours. Compared with ambient and on-road emissions, the California Air Resources Board EMFAC model under predicts 2018 gasoline vehicle NO_x emission factors by more than a factor of 2.6. Contributing to these differences is that vehicles older than model year 2006 have NO_x emission deterioration rates that are up to 4 time’s higher on-road than predicted by the EMFAC model. A …

Virtual Tutor Personality In Computer Assisted Language Learning, Johanna Dobbriner, Cathy Ennis, Robert J. Ross

Conference papers

The use of intelligent virtual agents in language learning has increased in recent years. Studies into several aspects of personalisation aiming to increase user engagement are an ongoing research topic with avatar personality being one such aspect. As a step towards our development of intelligent virtual avatars, we present two of our initial experiments to explore differences in user interaction with two contrasting avatar personalities -- P1: open-minded, friendly and sociable and P2: closed-off, curt and distant. Each user interacted with a single personality in a video-call setting and gave feedback on the interaction. Our expectations, that P1 would be …

Physiological Measurements For Real-Time Fatigue Monitoring In Train Drivers: Review Of The State Of The Art And Reframing The Problem, Bojana Bjegojevic, Maria Chiara Leva, Nora Balfe, Sam D. Cromie, Luca Longo

Conference papers

The impact of fatigue on train drivers is one of the most important safety-critical issues in rail. It affects drivers’ performance, significantly contributing to railway incidents and accidents. To address the issue of real-time fatigue detection in drivers, most reliable and applicable psychophysiological indicators of fatigue need to be identified. Hence, this paper aims to examine and present the current state of the art in physiological measures for real-time fatigue monitoring that could be applied in the train driving context. Three groups of such measures are identified: EEG, eye-tracking and heart-rate measures. This is the first paper to provide the …

Just-In-Time Biomass Yield Estimation With Multi-Modal Data And Variable Patch Training Size, Patricia O'Byrne, Patrick Jackman Dr., Damon Dr. Berry Dr., Thomas Lee, Michael French, Robert J. Ross

Conference papers

The just-in-time estimation of farmland traits such as biomass yield can aid considerably in the optimisation of agricultural processes. Data in domains such as precision farming is however notoriously expensive to collect and deep learning driven modelling approaches need to maximise performance but also acknowledge this reality. In this paper we present a study in which a platform was deployed to collect data from a heterogeneous collection of sensor types including visual, NIR, and LiDAR sources to estimate key pastureland traits. In addition to introducing the study itself we address two key research questions. The first of these was the …

Interactive Learning Approach For Arabic Target-Based Sentiment Analysis, Husamelddin Balla, Marisa Llorens, Sarah Jane Delany

Conference papers

Recently, the majority of sentiment analysis researchers focus on target-based sentiment analysis because it delivers in-depth analysis with more accurate results as compared to traditional sentiment analysis. In this paper, we propose an interactive learning approach to tackle a target-based sentiment analysis task for the Arabic language. The proposed IALSTM model uses an interactive attentionbased mechanism to force the model to focus on different parts (targets) of a sentence. We investigate the ability to use targets, right and left contexts, and model them separately to learn their own representations via interactive modeling. We evaluated our model on two different datasets: …

K-Nearest Neighbour Classifiers - A Tutorial, Padraig Cunningham, Sarah Jane Delany

Conference papers

Perhaps the most straightforward classifier in the arsenal or Machine Learning techniques is the Nearest Neighbour Classifier – classification is achieved by identifying the nearest neighbours to a query example and using those neighbours to determine the class of the query. This approach to classification is of particular importance because issues of poor run-time performance is not such a problem these days with the computational power that is available. This paper presents an overview of techniques for Nearest Neighbour classification focusing on; mechanisms for assessing similarity (distance), computational issues in identifying nearest neighbours and mechanisms for reducing the dimension of …

A Comparison Of Instructional Efficiency Models In Third Level Education, Murali Rajendran

Dissertations

This study investigates the validity and sensitivity of a novel model of instructional efficiency: the parabolic model. The novel model is compared against state-of-the-art models present in instructional design today; Likelihood model, Deviational model and Multidimensional model. This models is based on the assumption that optimal mental workload and high performance leads to high efficiency, while other models assume that low mental workload and high performance leads to high efficiency. The investigation makes use of two instructional design conditions: a direct instructions approach to learning and its extension with a collaborative activity. A control group received the former instructional design …

Stellar Classification Of Folded Spectra Using The Mk Classification Scheme And Convolutional Neural Networks, John Magee

Dissertations

The year 1943 saw the introduction of the Morgan-Keenan (MK) classification scheme and this replaced the existing Harvard Classification scheme. Both stellar classification scheme are fundamentally grounded in the field of spectroscopy. The Harvard Classification scheme classified stars based on stellar surface temperature. The MK Classification scheme introduced the concept of a luminosity class that is intrinsically linked to the surface gravity of a star. Temperature and luminosity class values are estimated directly from the stellar spectrum.

Machine learning is a well-established technique in astronomy. Traditionally, a spectrum is treated as a one-dimensional sequence of data. Techniques such as artificial …

Human Age And Gender Classification Using Convolutional Neural Networks, Eamon Kelliher

Dissertations

In a world relying ever more on human classification, this papers aims to improve on age and gender image classification through the use of Convolutional Neural Networks (CNN). Age and gender classification has become a popular area of study in the past number of years however there are still improvements to be made, particularly in the area of age classification. This research paper aims to test the currently accepted fact that CNN models are the superior model type for image classification by comparing CNN performance against Support Vector Machine performance on the same dataset. Using the Adience image classification dataset, …

Pothole Detection Under Diverse Conditions Using Object Detection Model, Ibrahim Hassan Syed, Dympna O'Sullivan, Susan Mckeever

Datasets

One of the most important tasks in road maintenance is the detection of potholes. This process is usually done through manual visual inspection, where certified engineers assess recorded images of pavements acquired using cameras or professional road assessment vehicles. Machine learning techniques are now being applied to this problem, with models trained to automatically identify road conditions. However, approaching this real-world problem with machine learning techniques presents the classic problem of how to produce generalizable models. Images and videos may be captured in different illumination conditions, with different camera types, camera angles and resolutions. In this paper we present our …

What Impact Does Teaching In Outreach Activities Have On Medical Students Own Teaching Skills? A Pilot Study, Louise Alldridge, Enam Haque, Andy Kardaz

Peninsula Medical School

No abstract provided.

Intraspecific Variation In Leaf Traits Facilitates The Occurrence Of Trees At The Amazonia–Cerrado Transition, Igor Araújo, Beatriz S. Marimon, Marina C. Scalon, Wesley J.A. Cruz, Sophie Fauset, Tiffani C.S. Vieira, David R. Galbraith, Manuel U. Gloor

School of Geography, Earth and Environmental Sciences

The ability of plant species to adjust key functional traits through intraspecific variation may determine their success in persisting on our planet in the future, especially in unstable habitats, such as the Amazonia–Cerrado transition zone. We assessed intraspecific variation in 12 leaf morphological and anatomical traits for four tree species along a savanna–forest gradient, including rocky cerrado, typical cerrado and woodland savanna. Generally, all evaluated species showed great intraspecific variation. Our findings demonstrate that trees occurring in the woodland savanna are potentially more vulnerable to climate change, while in the cerrado the individuals presented higher tolerance to water deficit and …

Novel Pin Geometry Improves Turbine Blade Trailing Edge Cooling, Nadim Reza

Electronic Theses and Dissertations Archive

The motivation for the present research is to improve gas turbine efficiency by improving turbine blade trailing edge cooling. State-of-the-art trailing edge cooling deploys an array of pins inside a cavity in the trailing edge through which air passes to carry away heat. A novel pin shape is proposed in which a slot aligned with the bulk flow direction is added to the conventional pin shape in the center of each pin to increase the rate of heat transfer to the air and to decrease the pressure drop across the cavity.Computational simulations (using ANSYS FLUENT) of cooling flows through pin …

Open Data From The First And Second Observing Runs Of Advanced Ligo And Advanced Virgo, R. Abbott, T. D. Abbott, Marco Cavaglia, For Full List Of Authors, See Publisher's Website.

Physics Faculty Research & Creative Works

Advanced LIGO and Advanced Virgo are monitoring the sky and collecting gravitational-wave strain data with sufficient sensitivity to detect signals routinely. In this paper we describe the data recorded by these instruments during their first and second observing runs. The main data products are gravitational-wave strain time series sampled at 16384 Hz. The datasets that include this strain measurement can be freely accessed through the Gravitational Wave Open Science Center at http://gw-openscience.org, together with data-quality information essential for the analysis of LIGO and Virgo data, documentation, tutorials, and supporting software.

Optimal Bidding Strategy For Physical Market Participants With Virtual Bidding Capability In Day-Ahead Electricity Markets, Hossein Mehdipourpicha, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

Virtual bidding provides a mechanism for financial players to participate in wholesale day-ahead (DA) electricity markets. The price difference between DA and real-time (RT) markets creates financial arbitrage opportunities for financial players. Physical market participants (MP), referred to as participants with physical assets, can also take advantage of virtual bidding but in a different way, which is to further amplify the value of their physical assets. Therefore, this work proposes a model for such physical MPs to maximize the profits. This model employs a bi-level optimization approach, where the upper-level subproblem maximizes the total profit from both physical generations and …

Enthesis Strength, Toughness And Stiffness: An Image-Based Model Comparing Tendon Insertions With Varying Bony Attachment Geometries, Mikhail Golman, Victor Birman, Stavros Thomopoulos, Guy M. Genin

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Tendons of the body differ dramatically in their function, mechanics and range of motion, but all connect to bone via an enthesis. Effective force transfer at the enthesis enables joint stability and mobility, with strength and stiffness arising from a fibrous architecture. However, how enthesis toughness arises across tendons with diverse loading orientations remains unclear. To study this, we performed simultaneous imaging of the bone and tendon in entheses that represent the range of tendon-to-bone insertions and extended a mathematical model to account for variations in insertion and bone geometry. We tested the hypothesis that toughness, across a range of …

Modeling And Simulation Of Resistive Superconducting Fault Current Limiter In Pscad/Emtdc™, Fahd Hariri, Mariesa Crow

Electrical and Computer Engineering Faculty Research & Creative Works

Energy networks are facing significant challenges as the result of increasing electrical loads. To meet this rapid increase in demand for electricity, new generating units are being added to support the stability and reliability of the network. This change in network structure requires a comprehensive analysis of the effect of that increase on the protection system. Limiting the fault current to safe levels prevents replacing the high-cost network components that may be subjected to damage due to exceeding the rated short-circuit current values for which they were designed. A fault analysis often requires extensive modeling and simulation of the system, …

Sizing Energy Storage System For Energy Arbitrage In Extreme Fast Charging Station, Waqas Ur Rehman, Rui Bo, Hossein Mehdipourpicha, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes a non-linear programming (NLP) model to optimally size the energy storage system (ESS) and obtain an optimal energy management for energy arbitrage of an extreme fast charging station (XFCS) for electric vehicles (EVs), with minimized total cost of XFCS operation and ESS investment. Different from most reported work on sizing the ESS for EV charging stations, this paper proposes a pragmatic approach to model the ESS life degradation and accurately count the ESS cycles. Moreover, this work incorporates the peak demand charges in the operational cost of the charging station which are often overlooked in the literature. …

Package Power Distribution Current Density In Applications With Large Transient Currents, Matthew Doyle, Wiren D. Becker, Matteo Cocchini, Kyle Schoneck, Samuel Connor, Layne Berge, Siqi Bai, James L. Drewniak

Electrical and Computer Engineering Faculty Research & Creative Works

A method to model, measure, and characterize a high-transient current in an electrical packaging solution is described herein. These methods help overcome the challenge of generating model to hardware correlation in high current applications. A specialized test platform is developed and used to characterize current density in test hardware. The measurements are used to characterize a custom power distribution network and verify validity of current density predictions. This data is critical in high-current applications for finding and measuring current density through plane pinch points that can cause early failures in the field due to electromigration and delamination.

Automated Cervical Digitized Histology Whole-Slide Image Analysis Toolbox, Sudhir Sornapudi, Ravitej Addanki, R. Joe Stanley, William V. Stoecker, Rodney Long, Rosemary Zuna, Shellaine R. Frazier, Sameer Antani

Electrical and Computer Engineering Faculty Research & Creative Works

Background: Cervical intraepithelial neoplasia (CIN) is regarded as a potential precancerous state of the uterine cervix. Timely and appropriate early treatment of CIN can help reduce cervical cancer mortality. Accurate estimation of CIN grade correlated with human papillomavirus type, which is the primary cause of the disease, helps determine the patient's risk for developing the disease. Colposcopy is used to select women for biopsy. Expert pathologists examine the biopsied cervical epithelial tissue under a microscope. The examination can take a long time and is prone to error and often results in high inter-and intra-observer variability in outcomes. Methodology: We propose …