Digital Commons Network^™

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 …

Sustainability Of Rewards-Based Crowdfunding: A Quasi-Experimental Analysis Of Funding Targets And Backer Satisfaction, Michael Wessel, Rob Gleasure, Robert John Kauffman

Research Collection School Of Computing and Information Systems

Rewards-based crowdfunding presents an information asymmetry for participants due to the funding mechanism used. Campaign-backers trust creators to complete projects and deliver rewards as outlined prior to the fundraising process, but creators may discover better opportunities as they progress with a project. Despite this, the all-or-nothing (AON) mechanism on crowdfunding platforms incentivizes creators to set meager funding-targets that are easier to achieve but may offer limited slack when creators wish to simultaneously pursue emerging opportunities later in the project. We explore the related issues of how funding targets seem to be selected by the creators, and how dissatisfaction with the …

Mobile Commerce, Crowd Commerce, And Stage Models: Reviewing And Expanding On Tp Liang’S Research, Sihua Chen, Mikko Siponen, Wael Soliman, Cao Xin, Keng Siau

Research Collection School Of Computing and Information Systems

In this paper, we review a few key themes of Ting-Peng (TP) Liang’s research. We first discuss some of his major contributions to information systems (IS) in the areas of electronic commerce, mobile commerce, and crowd commerce. Future research directions for these three themes are also discussed in the paper. TP Liang is also an early proponent of stage models although this stream of research has yet to receive the importance it deserves in the IS community. Previous seminal theoretical accounts in IS have generally separated variance and process models, the latter is useful in modeling changes in the explanatory …

Managing Risks In The Improved Model Of Rolling Mill Loading: A Case Study, Nelli V. Syreyshchikova, Danil Y. Pimenov, Elena N. Yaroslavova, Munish K. Gupta, Muhammad Aamir, Khaled Giasin

Research outputs 2014 to 2021

This article reflects the main sources of risks for metallurgical enterprises in Russia, presenting the implementation of an innovative approach to increasing the competitiveness of an industrial enterprise, which is a typical representative of large enterprises of the metallurgical industry, based on the development of risk-oriented thinking when loading rolling mills with orders of intersecting assortment according to a new model. To reduce the emerging risks of a new model of the loading process of rolling mills of a metallurgical enterprise, it is proposed to take into account the risks in a complex way, taking into account their interactions with …

An Evolutionary Approach To Balancing And Disrupting Real-Time Strategy Games, Jacob Snell, Martin Masek, Chiou Peng Lam

Research outputs 2014 to 2021

In most computer games, the level of challenge experienced by a player is dependent on a range of variable factors defined within the game environment. When the end goal of such games is entertainment, the variables are carefully tuned by the designers to achieve a sense of fair, balanced gameplay. For military force design and wargaming applications, where the purpose is to explore elements of a real scenario, the question turns to how the variables can be exploited so as to provide the maximum advantage, and to disrupt the balance in favour of a particular side. In this paper, an …

Interpretable, Not Black-Box, Artificial Intelligence Should Be Used For Embryo Selection, Michael Anis Mihdi Afnan, Yanhe Liu, Vincent Conitzer, Cynthia Rudin, Abhishek Mishra, Julian Savulescu, Masoud Afnan

Research outputs 2014 to 2021

Artificial intelligence (AI) techniques are starting to be used in IVF, in particular for selecting which embryos to transfer to the woman. AI has the potential to process complex data sets, to be better at identifying subtle but important patterns, and to be more objective than humans when evaluating embryos. However, a current review of the literature shows much work is still needed before AI can be ethically implemented for this purpose. No randomized controlled trials (RCTs) have been published, and the efficacy studies which exist demonstrate that algorithms can broadly differentiate well between ‘good-’ and ‘poor-’ quality embryos but …

Novel Adaptive Sampling Algorithm For Pod-Based Non-Intrusive Reduced Order Model, Jiachen Wang, Xiaosong Du, Joaquim R.R.A. Martins

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The proper orthogonal decomposition (POD) based reduced-order model (ROM) has been an effective tool for flow field prediction in the engineering industry. The sample selection in the design space for POD basis construction affects the ROM performance sensitively. Adaptive sampling can significantly reduce the number of samples to achieve the required model accuracy. In this work, we propose a novel adaptive sampling algorithm, called conjunction sampling strategy, which is based on proven strategies. The conjunction sampling strategy is demonstrated on airfoil flow field prediction within the transonic regime. We demonstrate the performance of the proposed strategy by running 10 trials …

Nanostructured Copper Selenide As An Ultrasensitive And Selective Non-Enzymatic Glucose Sensor, Siddesh Umapathi, Harish Singh, Jahangir Masud, Manashi Nath

Chemistry Faculty Research & Creative Works

CuSe nanostructures exhibit high-efficiency for glucose detection with high sensitivity (19.419 mA mM-1 cm-2) and selectivity at a low applied potential of +0.15 V vs. Ag|AgCl, a low detection limit of 0.196 μM and a linear range of glucose detection from 100 nm. to 40 μM. This journal is

Exploring The Experiences Of One Team Of Teachers: Well-Being And Navigating The Demands Of The Education Profession, Abby Weiland

Dissertations and Theses @ UNI

Much is changing in K-12 education contexts, including an emphasis on performativity and accountability (Au, 2016; Connell, 2009). Against this backdrop, teacher burnout and attrition have been the focus of numerous studies, including examination of organizational structures and factors contributing to burnout (Buckley et al., 2005; Konu et al., 2010). Insufficient attention has been given to how teachers are able to navigate the demands of this profession (Matteucci et al., 2017; Wilcox & Lawson, 2018). Efforts to retain teachers should not only emphasize factors associated with burnout or attrition, but also how they are affected by the systems in place, …