Research Institutes and Centres
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Recent Submissions
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NUIG at TIAD 2021: Cross-lingual word embeddings for translation inference
(2021-09-01)Inducing new translation pairs across dictionaries is an important task that facilitates processing and maintaining lexicographical data. This paper describes our submissions to the Translation Inference Across Dictionaries ... -
Do city dashboards make sense? Conceptualising user experiences and challenges in using city dashboards. A case study
(Association for Computing Machinery (ACM), 2021-06-09)City dashboards present information about a city to a broad audience with some thought given as to how some of these audiences might understand the information. However, little research has looked at how ’citizens’ make ... -
Understanding my city through dashboards. How hard can it be?
(International Federation for Information Processing (IFIP) and eJournal of eDemocracy and Open Government (JeDEM), 2019-09-02)This paper describes research into how current city dashboards support users' sensemaking processes. It uses criteria identified in previous research concerning visualisation and applies these to a number of city dashboards ... -
Is downloading this App consistent with my values? Conceptualizing a value-centered privacy assistant
(Springer, Cham, 2021-08-25)Digital privacy notices aim to provide users with information to make informed decisions. They are, however, fraught with difficulties. Instead, I propose that data privacy decisions can be understood as an expression of ... -
Sensemaking of complex sociotechnical systems: the case of governance dashboards
(Association for Computing Machinery (ACM), 2018-05-30)This research project is concerned with developing a suitable visualization model to depict a complex socio-technical system such as a city. It focuses on governance dashboards as the main starting point as these aim to ... -
Knowledge graph driven approach to represent video streams for spatiotemporal event pattern matching in complex event processing
(World Scientific Publishing, 2020)Complex Event Processing (CEP) is an event processing paradigm to perform real-time analytics over streaming data and match high-level event patterns. Presently, CEP is limited to process structured data stream. Video ... -
Developing, implementing and critiquing an evaluation framework to assess the extent to which a child’s right to be heard is embedded at an organisational level
(Springer, 2021-08-10)The national Child and Family Agency in Ireland, in 2015, undertook an ambitious three-year programme of work to embed a child s right to be heard in its culture and operations. In parallel to its implementation, the authors ... -
Query-driven video event processing for the internet of multimedia things
(VLDB Endowment, 2021-08)Advances in Deep Neural Network (DNN) techniques have revolutionized video analytics and unlocked the potential for querying and mining video event patterns. This paper details GNOSIS, an event processing platform to ... -
Traffic prediction framework for OpenStreetMap using deep learning based complex event processing and open traffic cameras
(Dagstuhl Research Online Publication Server (DROPS), 2020-09-25)Displaying near-real-time traffic information is a useful feature of digital navigation maps. However, most commercial providers rely on privacy-compromising measures such as deriving location information from cellphones ... -
Human monocyte subset distinctions and function: Insights from gene expression analysis
(Frontiers Media, 2020-06-04)Monocytes are a highly plastic innate immune cell population that displays significant heterogeneity within the circulation. Distinct patterns of surface marker expression have become accepted as a basis for distinguishing ... -
Burden of chronic kidney disease and rapid decline in renal function among adults attending a hospital-based diabetes center in Northern Europe
(BMJ Publishing Group, 2021-06-14)Introduction This study aimed to determine the prevalence of diabetic kidney disease (DKD) and rapid renal function decline and to identify indices associated with this decline among adults attending a diabetes center in ... -
NUIG-DSI’s submission to the GEM Benchmark 2021
(Association for Computational Linguistics, 2021-08-05)This paper describes the submission by NUIG-DSI to the GEM benchmark 2021. We participate in the modeling shared task where we submit outputs on four datasets for data-to-text generation, namely, DART, WebNLG (en), E2E and ... -
VID-WIN: Fast video event matching with query-aware windowing at the edge for the internet of multimedia things
(Institute of Electrical and Electronics Engineers (IEEE), 2021-04-23)Efficient video processing is a critical component in many IoMT applications to detect events of interest. Presently, many window optimization techniques have been proposed in event processing with an underlying assumption ... -
Toward distributed, global, deep learning using IoT devices
(Institute of Electrical and Electronics Engineers (IEEE), 2021-07-20)Deep learning (DL) using large scale, high-quality IoT datasets can be computationally expensive. Utilizing such datasets to produce a problem-solving model within a reasonable time frame requires a scalable distributed ... -
End-to-end tracing and congestion in a blockchain: A supply chain use case in hyperledger fabric
(IGI Global, 2021)Modern supply chain applications are complex systems that play an important role in many different sectors. Supply chain management systems are implemented to handle increasing complexity and flows of goods. However, most ... -
RCE-NN: a five-stage pipeline to execute neural networks (CNNs) on resource-constrained IoT edge devices
(Association for Computing Machinery (ACM), 2020-10-06)Microcontroller Units (MCUs) in edge devices are resource constrained due to their limited memory footprint, fewer computation cores, and low clock speeds. These limitations constrain one from deploying and executing machine ... -
Edge2Train: A framework to train machine learning models (SVMs) on resource-constrained IoT edge devices
(Association for Computing Machinery (ACM), 2020-10-06)In recent years, ML (Machine Learning) models that have been trained in data centers can often be deployed for use on edge devices. When the model deployed on these devices encounters unseen data patterns, it will either ... -
Enabling machine learning on the edge using SRAM conserving efficient neural networks execution approach
(National University of Ireland Galway, 2021-09-13)Edge analytics refers to the application of data analytics and Machine Learning (ML) algorithms on IoT devices. The concept of edge analytics is gaining popularity due to its ability to perform AI-based analytics at the ... -
Improved diagnosis of SARS-CoV-2 by using nucleoprotein and spike protein fragment 2 in quantitative dual ELISA tests
(Cambridge University Press, 2021-06-08)The novel coronavirus, severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), is the causative agent of the 2020 worldwide coronavirus pandemic. Antibody testing is useful for diagnosing historic infections of a ... -
Enhancing multiple-choice question answering with causal knowledge
(Association for Computational Linguistics, 2021-06-10)The task of causal question answering aims to reason about causes and effects over a provided real or hypothetical premise. Recent approaches have converged on using transformer-based language models to solve question ...