Browsing by Subject "MACHINE LEARNING"
Now showing items 1-20 of 22
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Ambient Data Monitoring w/Generative Music Systems using EC & ML Techniques.
(2018)This is a position paper which describes work in progress to develop an AI/ML driven auditory ambient information system which incorporates generative music techniques and considers some of the factors involved the design ... -
Applying machine learning to model radon using topsoil geochemistry
(2023)Radon is classified as a Class 1 carcinogen, being the leading cause of lung cancer in non-smokers. Understanding the prominent sources of radon helps to mitigate against the adverse effects of radon exposure. Considering ... -
Artificial Intelligence for Dynamical Systems in Wireless Communications: Modeling for the Future
(2021)Dynamical systems are no strangers in wireless communications. Our story will necessarily involve chaos, but not in the terms secure chaotic communications have introduced it: we will look for the chaos, complexity and ... -
Custom precision accelerators for energy-efficient image-to-image transformations in motion picture workflows
(SPIE, 2023)Image to Image (I2I) transformations have been an integral part of video processing workflows with applications in Image Synthesis for Virtual Productions, Segmentation, and Matting, among others. Over the years, ... -
THE DESIGN OF A SMART CITY SONIFICATION SYSTEM USING A CONCEPTUAL BLENDING AND MUSICAL FRAMEWORK, WEB AUDIO AND DEEP LEARNING TECHNIQUES
(2021)This paper describes an auditory display system for smart city data for Dublin City, Ireland. It introduces and describes the different layers of the system and outlines how they operate individually and interact with ... -
An Evaluation Method for Diachronic Word Sense Induction
(Association for Computational Linguistics, 2020)The task of Diachronic Word Sense Induction (DWSI) aims to identify the meaning of words from their context, taking the temporal dimension into account. In this paper we propose an evaluation method based on large-scale ... -
Following the Trail of Source Languages in Literary Translations
(Springer, 2014)We build on past research in distinguishing English translations from originally English text, and in guessing the source language where the text is deemed to be a translation. We replicate an extant method in relation to ... -
The Importance of Age in the Prediction of Mortality by a Frailty Index: A Machine Learning Approach in the Irish Longitudinal Study on Ageing
(2021)The quantification of biological age in humans is an important scientific endeavor in the face of ageing populations. The frailty index (FI) methodology is based on the accumulation of health deficits and captures variations ... -
Improving palliative care with machine learning and routine data: a rapid review
(2019)Introduction: Improving palliative care is a priority worldwide as this population experiences poor outcomes and accounts disproportionately for costs. In clinical practice, physician judgement is the core method of ... -
Is It Dish Washer Safe? Automatically Answering "Yes/No'' Questions Using Customer Reviews
(2019)It has become commonplace for people to share their opinions about all kinds of products by posting reviews online. It has also become commonplace for potential customers to do research about the quality and limitations ... -
A Lightweight Multi-Attack CAN Intrusion Detection System on Hybrid FPGAs
(2022)Rising connectivity in vehicles is enabling new capabilities like connected autonomous driving and advanced driver assistance systems (ADAS) for improving the safety and reliability of next-generation vehicles. This ... -
Machine-learning semilocal density functional theory for many-body lattice models at zero and finite temperature
(2021)We introduce a machine-learning density-functional-theory formalism for the spinless Hubbard model in one dimension at both zero and finite temperature. In the zero-temperature case this establishes a one-to-one ... -
Meta-Hyperband: Hyperparameter optimization with meta-learning and Coarse-to-Fine
(2020)Hyperparameter optimization is one of the main pillars of machine learning algorithms. In this paper, we introduce Meta-Hyperband: a Hyperband based algorithm that improves the hyperparameter optimization by adding levels ... -
Physics-Informed Neural Network surrogate model for bypassing Blade Element Momentum theory in wind turbine aerodynamic load estimation
(2024)This paper proposes the use of Artificial Neural Networks (ANNs), specifically Physics-Informed Neural Networks (PINNs), for dynamic surrogate modelling of wind turbines. PINNs offer the flexibility to model complex ... -
Q. Can Knowledge Graphs be used to Answer Boolean Questions? A. It's complicated!
(Association for Computational Linguistics, 2020)In this paper we explore the problem of machine reading comprehension, focusing on the BoolQ dataset of Yes/No questions. We carryout an error analysis of a BERT-based machine reading comprehension model on this ... -
Semantic reranking of CRF label sequences for verbal multiword expression identification
(Language Science Press, 2018)Verbal multiword Expressions (VMWE) identification can be addressed successfully as a sequence labelling problem via conditional random fields (CRFs) by returning the one label sequence with maximal probability. This work ... -
Structural Characteristics of Knowledge Graphs Determine the Quality of Knowledge Graph Embeddings Across Model and Hyperparameter Choices
(2022)The realm of biomedicine is producing information at a rate far beyond the capacity of clinicians, researchers, and machine learning experts to analyse in full. Recently, developments in Knowledge Graphs (KGs) have ... -
Temporal predictive regression models for linguistic style analysis
(2018)This study focuses on modelling general and individual language change over several decades. A timeline prediction task was used to identify interesting temporal features. Our previous work achieved high accuracy in ...