Data Science Institute: Recent submissions
Now showing items 21-40 of 544
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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 ... -
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 ... -
Ultra-fast machine learning classifier execution on IoT devices without SRAM consumption
(Institute of Electrical and Electronics Engineers (IEEE), 2021-05-25)With the introduction of edge analytics, IoT devices are becoming smart and ready for AI applications. A few modern ML frameworks are focusing on the generation of small-size ML models (often in kBs) that can directly be ... -
Porting and execution of anomalies detection models on embedded systems in IoT: Demo abstract
(Association for Computing Machinery (ACM), 2021-05-18)In the Industry 4.0 era, Microcontrollers (MCUs) based tiny embedded sensor systems have become the sensing paradigm to interact with the physical world. In 2020, 25.6 billion MCUs were shipped, and over 250 billion MCUs ... -
SRAM optimized porting and execution of machine learning classifiers on MCU-based IoT devices: Demo abstract
(Association for Computing Machinery (ACM), 2021-05-19)With the introduction of edge analytics, IoT devices are becoming smarter and ready for AI applications. However, any increase in the training data results in a linear increase in the space complexity of the trained Machine ... -
TinyML benchmark: Executing fully connected neural networks on commodity microcontrollers
(National University of Ireland Galway, 2021-06-20)Recent advancements in the field of ultra-low-power machine learning (TinyML) promises to unlock an entirely new class of edge applications. However, continued progress is restrained by the lack of benchmarking Machine ... -
Edge2Guard: Botnet attacks detecting offline models for resource-constrained IoT devices
(National University of Ireland Galway, 2021-03-22)In today's IoT smart environments, dozens of MCU-based connected device types exist such as HVAC controllers, smart meters, smoke detectors, etc. The security conditions for these essential IoT devices remain unsatisfactory ... -
Utilising knowledge graph embeddings for data-to-text generation
(Association for Computational Linguistics, 2020-12-18)Data-to-text generation has recently seen a move away from modular and pipeline architectures towards end-to-end architectures based on neural networks. In this work, we employ knowledge graph embeddings and explore their ... -
NUIG-DSI at the WebNLG+ challenge: Leveraging transfer learning for RDF-to-text generation
(Association for Computational Linguistics, 2020-12-18)This paper describes the system submitted by NUIG-DSI to the WebNLG+ challenge 2020 in the RDF-to-text generation task for the English language. For this challenge, we leverage transfer learning by adopting the T5 model ... -
Uncovering semantic bias in neural network models using a knowledge graph
(ACM, 2020-10-19)While neural networks models have shown impressive performance in many NLP tasks, lack of interpretability is often seen as a disadvantage. Individual relevance scores assigned by post-hoc explanation methods are not ... -
The data ethics challenges of explainable AI and their knowledge-based solutions
(IOS Press, 2020-05)Abstract. Explainable AI has recently gained momentum as an approach to overcome some of the more obvious ethical implications of the increasingly widespread application of AI (mostly machine learning). It is however not ... -
Synergy between embedding and protein functional association networks for drug label prediction using harmonic function
(ACM and IEEE, 2020-10-16)Semi-Supervised Learning (SSL) is an approach to machine learning that makes use of unlabeled data for training with a small amount of labeled data. In the context of molecular biology and pharmacology, one can take advantage ... -
Smart speaker design and implementation with biometric authentication and advanced voice interaction capability
(CEUR-WS.org, 2019-12-05)Advancements in semiconductor technology have reduced dimensions and cost while improving the performance and capacity of chipsets. In addition, advancement in the AI frameworks and libraries brings possibilities to ... -
Unsupervised method to analyze playing styles of EPL teams using ball possession-position data
(IEEE, 2020-03-06)In the English Premier League (EPL) matches, a network of advanced systems gathers sports data in real-time to build a possession-position dataset. In this work, data fields from the sophisticated raw possession-position ... -
NUIG-Panlingua-KMI Hindi-Marathi MT Systems for Similar Language Translation Task @ WMT 2020
(Association for Computational Linguistics, 2020-11-19)NUIG-Panlingua-KMI submission to WMT 2020 seeks to push the state-of-the-art in the Similar language translation task for the Hindi ↔ Marathi language pair. As part of these efforts, we conducted a series of experiments to ... -
Findings of the LoResMT 2020 shared task on zero-shot for low-resource languages
(Association for Computational Linguistics, 2020-12-04)This paper presents the findings of the LoResMT 2020 Shared Task on zero-shot translation for low resource languages. This task was organised as part of the 3rd Workshop on Technologies for MT of Low Resource Languages ... -
Towards automatic linking of lexicographic data: the case of a historical and a modern Danish dictionary
(European Association for Lexicography, 2020)Given the diversity of lexical-semantic resources, particularly dictionaries, integrating such resources by aligning various types of information is an important task, both in e-lexicography and natural language processing. ...