Physical Sciences and Mathematics | Open Access Articles

Development Of An Optical Test Bed For The Fabrication And Characterisation Of An Analog Holographic Wavefront Sensor, Emma Branigan, Andreas Zepp, Suzanne Martin, Matthew Sheehan, Szymon Gladysz, Kevin Murphy

Conference Papers

A new holographic recording setup has been developed for the fabrication of single- and multi-mode photopolymer-based analog holographic wavefront sensors. A second setup has been built and used to characterise the sensor at several wavelengths.

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Poly-Gan: Regularizing Polygons With Generative Adversarial Networks, Lasith Niroshan, James Carswell

Conference Papers

Regularizing polygons involves simplifying irregular and noisy shapes of built environment objects (e.g. buildings) to ensure that they are accurately represented using a minimum number of vertices. It is a vital processing step when creating/transmitting online digital maps so that they occupy minimal storage space and bandwidth. This paper presents a data-driven and Deep Learning (DL) based approach for regularizing OpenStreetMap building polygon edges. The study introduces a building footprint regularization technique (Poly-GAN) that utilises a Generative Adversarial Network model trained on irregular building footprints and OSM vector data. The proposed method is particularly relevant for map features …

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Modelling Hoe Performance With An Extended Source; Experimental Investigation Using Misaligned Point Sources, Jorge Lasarte, Kevin Murphy, Izabela Naydenova, Jesús Atencia, Mª Victoria Collados, Suzanne Martin

Conference Papers

Holographic Optical Elements (HOEs) have the potential to enable more compact, versatile and lightweight optical designs, but many challenges remain. Volume HOE’s have the advantage of high diffraction efficiency but they present both chromatic selectivity and chromatic dispersion which impact on their use with wide spectrum light sources. Single-colour LED sources have a narrow spectrum that reduces these issues and this makes them better suited for use with volume HOEs. However, the LED source size must be taken into consideration for compact volume HOE-LED systems. To investigate the design limits for compact HOE-LED systems, a theoretical and experimental study was …

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Development Of Holographic Optical Elements For Use In Wound Monitoring, Pamela Stoeva, Tatsiana Mikulchyk, Brian Rogers, M. Oubaha, Suzanne Martin, Dervil Cody, M.A. Ferrara, G. Coppola, Izabela Naydenova

Conference Papers

Wounds that fail to heal impact the quality of life of 2.5 % of the total population. The costs of chronic wound care will reach $15–22 billion by 2024. These alarming statistics reveal the financial strain for both the medical industry and society. A solution can be found in compact and accessible sensors that offer real-time analysis of the wound site, facilitating continuous monitoring and immediate treatment, if required. Benefits of these sensors include reduction of cost and can extend the reach of healthcare to remote areas. The progression of a wound site can be closely monitored with holographic optical …

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Fabrication And Characterisation Of Large Area, Uniform And Controllable Surface Relief Patterns In Photopolymer Material, Owen Kearney, Izabela Naydenova

Conference Papers

As the risk of antibiotic resistant pathogens increases, development of convenient point of care devices is essential. Such devices would help avoid infection – ensure cleanliness of environments and assist in bacteria analysis. The ultimate aim of the research presented here is to develop a compact, cost effective, easy to use optical device which is capable of detecting and quantifying bacteria in an aqueous sample. The surface relief patterns have a dual role, they provide a diffracted light signal, and control the adhesion of the bacteria to the surface. The strength of the diffracted signal is expected to provide a …

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The Development Of Optomechanical Sensors—Integrating Diffractive Optical Structures For Enhanced Sensitivity, Faolan Radford Mcgovern, Aleksandra Hernik, Catherine M. Grogan, George Amarandei, Izabela Naydenova

Conference Papers

The term optomechanical sensors describes devices based on coupling the optical and mechanical sensing principles. The presence of a target analyte leads to a mechanical change, which, in turn, determines an alteration in the light propagation. Having higher sensitivity in comparison with the individual technologies upon which they are based, the optomechanical devices are used in biosensing, humidity, temperature, and gases detection. This perspective focuses on a particular class, namely on devices based on diffractive optical structures (DOS). Many configurations have been developed, including cantilever- and MEMS-type devices, fiber Bragg grating sensors, and cavity optomechanical sensing devices. These state-of-the-art sensors …

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Microfluidic Flowmeter Based On Liquid Crystal Filled Nested Capillary, Zhe Wang, Zhuochen Wang, Anuradha Rout, Qiang Wu, Yuliya Semenova

Conference Papers

A novel flowmeter composed of a liquid crystal-filled nested capillary is proposed and experimentally demonstrated. Whispering gallery modes (WGMs) in the nested capillary are excited by a tapered fiber coupled perpendicularly to the nested capillary. The WGM transmission spectrum of the fiber taper was optimized to achieve the highest possible quality (Q) factor by moving the capillary along the axis of the fiber taper. The air flowing through the capillary cools it down, which leads to a temperature-induced change of the refractive index of the nematic liquid crystal. This change in turn leads to a spectral shift of the WGM …

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Design And Fabrication Of Volume Holographic Optical Couplers For A Range Of Non-Normal Incidence Angles, Dipanjan Chakraborty, Rosen Georgiev, Sinead Aspell, Izabela Naydenova, Suzanne Martin

Conference Papers

A theoretical model has previously been developed to calculate the holographic recording beam angles required in air (at any recording wavelength) to produce a Volume Holographic Optical Element (VHOE) for operation as a coupler for different input and output angles. In this paper, the experimental study is extended to further validate the VHOE coupler design and fabrication approach for additional incident beam angles, comparing -40° -45° and -50° (in air). The output angle for each VHOE is +45° within the medium and the coupler operational wavelength is 633nm. Holographic recording in Bayfol HX 200 photopolymer at 532nm is used to …

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Identity Term Sampling For Measuring Gender Bias In Training Data, Nasim Sobhani, Sarah Jane Delany

Conference Papers

Predictions from machine learning models can reflect biases in the data on which they are trained. Gender bias has been identified in natural language processing systems such as those used for recruitment. The development of approaches to mitigate gender bias in training data typically need to be able to isolate the effect of gender on the output to see the impact of gender. While it is possible to isolate and identify gender for some types of training data, e.g. CVs in recruitment, for most textual corpora there is no obvious gender label. This paper proposes a general approach to measure …

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Ideating Xai: An Exploration Of User’S Mental Models Of An Ai-Driven Recruitment System Using A Design Thinking Approach, Helen Sheridan, Dympna O'Sullivan, Emma Murphy

Conference Papers

Artificial Intelligence (AI) is playing an important role in society including how vital, often life changing decisions are made. For this reason, interest in Explainable Artificial Intelligence (XAI) has grown in recent years as a means of revealing the processes and operations contained within what is often described as a black box, an often-opaque system whose decisions are difficult to understand by the end user. This paper presents the results of a design thinking workshop with 20 participants (computer science and graphic design students) where we sought to investigate users' mental models when interacting with AI systems. Using two personas, …

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An Investigation Of The Reconstruction Capacity Of Stacked Convolutional Autoencoders For Log-Mel-Spectrograms, Anastasia Natsiou, Luca Longo, Seán O'Leary

Conference Papers

In audio processing applications, the generation of expressive sounds based on high-level representations demonstrates a high demand. These representations can be used to manipulate the timbre and influence the synthesis of creative instrumental notes. Modern algorithms, such as neural networks, have inspired the development of expressive synthesizers based on musical instrument timbre compression. Unsupervised deep learning methods can achieve audio compression by training the network to learn a mapping from waveforms or spectrograms to low-dimensional representations. This study investigates the use of stacked convolutional autoencoders for the compression of time-frequency audio representations for a variety of instruments for a single …

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Exploring The Impact Of Gender Bias Mitigation Approaches On A Downstream Classification Task, Nasim Sobhani, Sarah Jane Delany

Conference Papers

Natural language models and systems have been shown to reﬂect gender bias existing in training data. This bias can impact on the downstream task that machine learning models, built on this training data, are to accomplish. A variety of techniques have been proposed to mitigate gender bias in training data. In this paper we compare diﬀerent gender bias mitigation approaches on a classiﬁcation task. We consider mitigation techniques that manipulate the training data itself, including data scrubbing, gender swapping and counterfactual data augmentation approaches. We also look at using de-biased word embeddings in the representation of the training data. We …

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Morton-Ordered Gpu Lattice Boltzmann Cfd Simulations With Application To Blood Flow, Gerald Gallagher, Fergal J. Boyle

Conference Papers

Computational fluid dynamics (CFD) is routinely used for numerically predicting cardiovascular-system medical device fluid flows. Most CFD simulations ignore the suspended cellular phases of blood due to computational constraints, which negatively affects simulation accuracy. A graphics processing unit (GPU) lattice Boltzmann-immersed boundary (LB-IB) CFD software package capable of accurately modelling blood flow is in development by the authors, focusing on the behaviour of plasma and stomatocyte, discocyte and echinocyte red blood cells during flow. Optimised memory ordering and layout schemes yield significant efficiency improvements for LB GPU simulations. In this work, comparisons of row-major-ordered Structure of Arrays (SoA) and Collected …

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Technical Debt Is An Ethical Issue, Paul John Gibson, Yannis Stavrakakis, Massamaesso Narouwa, Damian Gordon, Dympna O'Sullivan, Jonathan Turner, Michael Collins

Conference Papers

We introduce the problem of technical debt, with particular focus on critical infrastructure, and put forward our view that this is a digital ethics issue. We propose that the software engineering process must adapt its current notion of technical debt – focusing on technical costs – to include the potential cost to society if the technical debt is not addressed, and the cost of analysing, modelling and understanding this ethical debt. Finally, we provide an overview of the development of educational material – based on a collection of technical debt case studies - in order to teach about technical debt …

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Modelling Spherical Aberration Detection In An Analog Holographic Wavefront Sensor, Emma Branigan, Suzanne Martin, Matthew Sheehan, Kevin Murphy

Conference Papers

The analog holographic wavefront sensor (AHWFS) is a simple and robust solution to wavefront sensing in turbulent environments. Here, the ability of a photopolymer based AHWFS to detect refractively generated spherical aberration is modelled and verified.

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Machine Learning With Kay, Lasith Niroshan, James Carswell

Conference Papers

Computational power is very important when training Deep Learning (DL) models with large amounts of data (Wooldridge, 2021). Hence, High-Performance Computing (HPC) can be leveraged to reduce computational cost, and the Irish Centre for High-End Computing (ICHEC) provides significant infrastructure and services for research and development to both academia and industry. A portion of ICHEC's HPC system has been allocated for institutional access, and this paper presents a case study of how to use Kay (Ireland's national supercomputer) in the remote sensing domain. Specifically, this study uses clusters of Kay Graphics Processing Units (GPUs) for training DL models to extract …

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Post-Analysis Of Osm-Gan Spatial Change Detection, Lasith Niroshan Kottawa Hewa Manage, James Carswell

Conference Papers

Keeping crowdsourced maps up-to-date is important for a wide range of location-based applications (route planning, urban planning, navigation, tourism, etc.).We propose a novelmap updatingmechanism that combines the latest freely available remote sensing data with the current state of online vector map data to train a Deep Learning (DL) neural network. It uses a GenerativeAdversarial Network (GAN) to perform image-to-image translation, followed by segmentation and raster-vector comparison processes to identify changes to map features (e.g. buildings, roads, etc.) when compared to existing map data. This paper evaluates various GAN models trained with sixteen different datasets designed for use by our change …

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"What's In A Name?”: The Use Of Instructional Design In Overcoming Terminology Barriers Associated With Dark Patterns, Andrea Curley, Damian Gordon, Dympna O'Sullivan

Conference Papers

Many users experience a phenomena when they are shopping on-line where they feel they are being pressured to either spend more money than they had intended, or to share more personal data than they wanted. In academic circles we use the term “Dark Patterns” to describe these deceptive practices, and categorize them as being within the discipline of User Experience (Narayanan, 2020). As academics it is important to name phenomena, and to categorize them, so that we can discuss and analyze these issues. However, this particular topic is one that all users should be made aware of when interacting online, …

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Feature Engineering Vs Feature Selection Vs Hyperparameter Optimization In The Spotify Song Popularity Dataset, Alan Cueva Mora, Brendan Tierney

Conference Papers

Research in Featuring Engineering has been part of the data pre-processing phase of machine learning projects for many years. It can be challenging for new people working with machine learning to understand its importance along with various approaches to find an optimized model. This work uses the Spotify Song Popularity dataset to compare and evaluate Feature Engineering, Feature Selection and Hyperparameter Optimization. The result of this work will demonstrate Feature Engineering has a greater effect on model efficiency when compared to the alternative approaches.

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The Design Of A Framework For The Detection Of Web-Based Dark Patterns, Andrea Curley, Dympna O'Sullivan, Damian Gordon, Brendan Tierney, Ioannis Stavrakakis

Conference Papers

In the theories of User Interfaces (UI) and User Experience (UX), the goal is generally to help understand the needs of users and how software can be best configured to optimize how the users can interact with it by removing any unnecessary barriers. However, some systems are designed to make people unwillingly agree to share more data than they intend to, or to spend more money than they plan to, using deception or other psychological nudges. User Interface experts have categorized a number of these tricks that are commonly used and have called them Dark Patterns. Dark Patterns are varied …

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Particle Acceleration At The Discontinuous Flow Boundary Of Collimated Cylindrical Jets, Stephen O'Sullivan, Andrew M. Taylor, Brian Reville

Conference Papers

We revisit the issue of particle acceleration at the interface between a collimated laminar jet and a static ambient medium. The contrast between standard diffusive scattering treatments and anomalous transport in synthetic field constructions is explored. A particular emphasis is placed on the necessity for physically consistent particle transport considerations. The temporal, spatial and spectral features of the process are discussed, in the context of potential UHECR production, as well as further observational consequences.

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Fairer Evaluation Of Zero Shot Action Recognition In Videos, Kaiqiang Huang, Sarah Jane Delany, Susan Mckeever

Conference Papers

Zero-shot learning (ZSL) for human action recognition (HAR) aims to recognise video action classes that have never been seen during model training. This is achieved by building mappings between visual and semantic embeddings. These visual embeddings are typically provided via a pre-trained deep neural network (DNN). The premise of ZSL is that the training and testing classes should be disjoint. In the parallel domain of ZSL for image input, the widespread poor evaluation protocol of pre-training on ZSL test classes has been highlighted. This is akin to providing a sneak preview of the evaluation classes. In this work, we investigate …

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Direct Multiplexing Of Low Order Aberration Modes In A Photopolymerbased Holographic Element For Analog Holographic Wavefront Sensing, Emma Branigan, Suzanne Martin, Matthew Sheehan, Kevin Murphy

Conference Papers

The fabrication of an analog holographic wavefront sensor, capable of detecting the low order defocus aberration, was achieved in an acrylamide-based photopolymer. While other implementations of holographic wavefront sensors have been carried out digitally, this process utilises a recording setup consisting only of conventional refractive elements so the cost and complexity of holographic optical element (HOE) production could be much reduced. A pair of diffraction spots, corresponding to a maximum and minimum amount of defocus, were spatially separated in the detector plane by multiplexing two HOEs with different carrier spatial frequencies. For each wavefront with a known aberration that was …

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Hublinked: A Curriculum Mapping Framework For Industry, Paul Doyle, Cathy Ennis, Anna Becevel, Stephane Maag, Radu Dobrin, Mojca Ciglarič, Yunia Choi, Alan Fahey, Deirdre Lillis

Conference Papers

A key aim of HubLinked is to improve the effectiveness of University-Industry linkages between CS faculties and ICT companies. One of the problems identified as core to the Project was to match Learning Outcomes from different curricula with the requirements dictated by the ICT industry with the final aim to enhance students Graduate Skills and employability. Based on agreed core U-I linkage attributes, lower-level curriculum L0s have been designed and reviewed by industry partners. To enable the replication of this process, a tool was designed to make the comparison of graduates' skills from different institutions easily accessible. Using this tool …

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Sustainable International Engagement Using A Partner Co-Hosted Teaching Model, Brian Gillespie, Paul Doyle, Zy Jiang, Derryl Humble

Conference Papers

Internationalisation is a significant activity of Higher Education Institutions (HEIs) worldwide and is typically embedded within the aims, ambitions, vision, and strategy of the institution. It incorporates the policies and procedures required to facilitate participation within a global academic environment, and is often considered to be a transformative process that impacts practices in teaching and learning, research, and administration. With formal protocols to establish partnerships, such as memoranda of understanding and articulation agreements, the business of formally creating international partnerships is well defined. However, the motivations, corresponding metrics and key performance indicators (KPIs) of successful partnerships are not as well …

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Competencies For Educators In Delivering Digital Accessibility In Higher Education, John Gilligan

Conference Papers

The aim of this paper is to critically review the capabilities of the European Framework for the Digital Competence of Educators (DigCompEdu) and the UNESCO ICT Competency Framework for in delivering greater accessibility for students with disabilities in a Higher Education landscape undergoing Digital Transformation. These frameworks describe what it means for educators to be digitally competent. However are there other competencies required to deliver Digital Accessibility in education. The particular focus of this paper is the role of the teachers in delivering Digital Accessibility in higher education. What should be expected of them and what are the required competencies …

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An International Pilot Study Of K-12 Teachers’Computer Science Self-Esteem, Rebecca Vivian, Katrina Falkner, Leonard Busuttil, Keith Quille, Sue Sentance, Elizabeth Cole, Francesco Maiorana, Monica M. Mcgil, Sarah Barksdale, Christine Liebe

Conference Papers

Computer Science (CS) is a new subject area for many K-12 teachersaround the world, requiring new disciplinary knowledge and skills.Teacher social-behavioral factors (e.g. self-esteem) have been foundto impact learning and teaching, and a key part of CS curriculumimplementation will need to ensure teachers feel confident to de-liver CS. However, studies about CS teacher self-esteem are lacking.This paper presents an analysis of publicly available data (n=219)from a pilot study using a Teacher CS Self-Esteem scale. Analy-sis revealed significant differences, including 1) females reportedsignificantly lower CS self-esteem than males, 2) primary teachersreported lower levels of CS self-esteem than secondary teachers, 3)those with …

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A Collaborative Online Micro: Bit K-12 Teacher Pd Workshop, Roisin Faherty, Karen Nolan, Keith Quille

Conference Papers

This poster describes the use of online technology to deliver K12 teacher professional development (PD) during the COVID-19 pandemic in Ireland. Traditionally these sessions are delivered in person, with a focus on hand-on activities, but the sudden changes faced by the closures in Ireland required an alternative approach for delivering these sessions. The PD session presented in this poster was a more technically challenging micro:bit workshop, which was delivered online using the micro:bit classroom. This is typically used as an in-class, one to many instructor tool, and trialing this as a PD collaborative tool, was a novel approach. This poster …

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Gmdh-Based Models For Mid-Term Forecast Of Cryptocurrencies (On Example Of Waves), Pavel Mogilev, Anna Boldyreva, Mikhail Alexandrov, John Cardiff

Conference Papers

Cryptocurrencies became one of the main trends in modern economy. However by the moment the forecast of cryptocurrencies values is an open problem, which is almost non-reflected in publications related to finance market. Reasons consist in its novelty, large volatility and its strong dependence on subjective factors. In this experimental research we show possibilities of GMDH-technology to give weekly and monthly forecast for values of cryptocurrency 'Waves' (waves/euro rate). The source information is week data covering the period 2017-2019. We tests 4 algorithms from the GMDH Shell platform on the whole period and on the crisis period 4-th quarter 2017 …

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Poincaré Embeddings In The Task Of Named Entity Recognition, David Muñoz, Fernando Pérez Téllez, David Pinto

Conference Papers

Hyperbolic embeddings have become important in many natural language processing tasks due to their great ability to capture latent hierarchical data and to encode valuable syntactic and semantic information. We study and consider the ability of Poincaré embeddings to get the most similar nodes to a given node when trying to recognize named entities in a set of text documents. In this paper, we propose a classifier model for the NER (Named Entity Recognition) task by implementing Poincaré embeddings and by using the most frequent n-grams and their Part-of-Speech (POS) structures from the training dataset. We found that POS structures …

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Full-Text Articles in Physical Sciences and Mathematics

Development Of An Optical Test Bed For The Fabrication And Characterisation Of An Analog Holographic Wavefront Sensor, Emma Branigan, Andreas Zepp, Suzanne Martin, Matthew Sheehan, Szymon Gladysz, Kevin Murphy

Conference Papers

Poly-Gan: Regularizing Polygons With Generative Adversarial Networks, Lasith Niroshan, James Carswell

Conference Papers

Modelling Hoe Performance With An Extended Source; Experimental Investigation Using Misaligned Point Sources, Jorge Lasarte, Kevin Murphy, Izabela Naydenova, Jesús Atencia, Mª Victoria Collados, Suzanne Martin

Conference Papers

Development Of Holographic Optical Elements For Use In Wound Monitoring, Pamela Stoeva, Tatsiana Mikulchyk, Brian Rogers, M. Oubaha, Suzanne Martin, Dervil Cody, M.A. Ferrara, G. Coppola, Izabela Naydenova

Conference Papers

Fabrication And Characterisation Of Large Area, Uniform And Controllable Surface Relief Patterns In Photopolymer Material, Owen Kearney, Izabela Naydenova

Conference Papers

The Development Of Optomechanical Sensors—Integrating Diffractive Optical Structures For Enhanced Sensitivity, Faolan Radford Mcgovern, Aleksandra Hernik, Catherine M. Grogan, George Amarandei, Izabela Naydenova

Conference Papers

Microfluidic Flowmeter Based On Liquid Crystal Filled Nested Capillary, Zhe Wang, Zhuochen Wang, Anuradha Rout, Qiang Wu, Yuliya Semenova

Conference Papers

Design And Fabrication Of Volume Holographic Optical Couplers For A Range Of Non-Normal Incidence Angles, Dipanjan Chakraborty, Rosen Georgiev, Sinead Aspell, Izabela Naydenova, Suzanne Martin

Conference Papers

Identity Term Sampling For Measuring Gender Bias In Training Data, Nasim Sobhani, Sarah Jane Delany

Conference Papers

Ideating Xai: An Exploration Of User’S Mental Models Of An Ai-Driven Recruitment System Using A Design Thinking Approach, Helen Sheridan, Dympna O'Sullivan, Emma Murphy

Conference Papers

An Investigation Of The Reconstruction Capacity Of Stacked Convolutional Autoencoders For Log-Mel-Spectrograms, Anastasia Natsiou, Luca Longo, Seán O'Leary

Conference Papers

Exploring The Impact Of Gender Bias Mitigation Approaches On A Downstream Classification Task, Nasim Sobhani, Sarah Jane Delany

Conference Papers

Morton-Ordered Gpu Lattice Boltzmann Cfd Simulations With Application To Blood Flow, Gerald Gallagher, Fergal J. Boyle

Conference Papers

Technical Debt Is An Ethical Issue, Paul John Gibson, Yannis Stavrakakis, Massamaesso Narouwa, Damian Gordon, Dympna O'Sullivan, Jonathan Turner, Michael Collins

Conference Papers

Modelling Spherical Aberration Detection In An Analog Holographic Wavefront Sensor, Emma Branigan, Suzanne Martin, Matthew Sheehan, Kevin Murphy

Conference Papers

Machine Learning With Kay, Lasith Niroshan, James Carswell

Conference Papers

Post-Analysis Of Osm-Gan Spatial Change Detection, Lasith Niroshan Kottawa Hewa Manage, James Carswell

Conference Papers

"What's In A Name?”: The Use Of Instructional Design In Overcoming Terminology Barriers Associated With Dark Patterns, Andrea Curley, Damian Gordon, Dympna O'Sullivan

Conference Papers

Feature Engineering Vs Feature Selection Vs Hyperparameter Optimization In The Spotify Song Popularity Dataset, Alan Cueva Mora, Brendan Tierney

Conference Papers

The Design Of A Framework For The Detection Of Web-Based Dark Patterns, Andrea Curley, Dympna O'Sullivan, Damian Gordon, Brendan Tierney, Ioannis Stavrakakis

Conference Papers

Particle Acceleration At The Discontinuous Flow Boundary Of Collimated Cylindrical Jets, Stephen O'Sullivan, Andrew M. Taylor, Brian Reville

Conference Papers

Fairer Evaluation Of Zero Shot Action Recognition In Videos, Kaiqiang Huang, Sarah Jane Delany, Susan Mckeever

Conference Papers

Direct Multiplexing Of Low Order Aberration Modes In A Photopolymerbased Holographic Element For Analog Holographic Wavefront Sensing, Emma Branigan, Suzanne Martin, Matthew Sheehan, Kevin Murphy

Conference Papers

Hublinked: A Curriculum Mapping Framework For Industry, Paul Doyle, Cathy Ennis, Anna Becevel, Stephane Maag, Radu Dobrin, Mojca Ciglarič, Yunia Choi, Alan Fahey, Deirdre Lillis

Conference Papers

Sustainable International Engagement Using A Partner Co-Hosted Teaching Model, Brian Gillespie, Paul Doyle, Zy Jiang, Derryl Humble

Conference Papers

Competencies For Educators In Delivering Digital Accessibility In Higher Education, John Gilligan

Conference Papers

An International Pilot Study Of K-12 Teachers’Computer Science Self-Esteem, Rebecca Vivian, Katrina Falkner, Leonard Busuttil, Keith Quille, Sue Sentance, Elizabeth Cole, Francesco Maiorana, Monica M. Mcgil, Sarah Barksdale, Christine Liebe

Conference Papers

A Collaborative Online Micro: Bit K-12 Teacher Pd Workshop, Roisin Faherty, Karen Nolan, Keith Quille

Conference Papers

Gmdh-Based Models For Mid-Term Forecast Of Cryptocurrencies (On Example Of Waves), Pavel Mogilev, Anna Boldyreva, Mikhail Alexandrov, John Cardiff

Conference Papers

Poincaré Embeddings In The Task Of Named Entity Recognition, David Muñoz, Fernando Pérez Téllez, David Pinto

Conference Papers