Browsing Data Science Institute by Author "http://dx.doi.org/10.13039/501100001602"

Now showing items 21-40 of 113

    • A deep learning approach to genomics data for population scale clustering and ethnicity prediction 

      Karim, Md. Rezaul; Zappa, Achille; Sahay, Ratnesh; Rebholz-Schuhmann, Dietrich (CEUR-WS.org, 2017-05-28)
      The understanding of variations in genome sequences assists us in identifying people who are predisposed to common diseases, solving rare diseases, and finding corresponding population group of the individuals from a ...

    • Demonstrating a linked data platform for finite element biosimulations of cochlear mechanics 

      Mehdi, Muntazir; Khan, Yasar; Freitas, Andre; Jares, Joao; Hasapis, Panagiotis; Sahay, Ratnesh (CEUR-WS.org, 2015-10-11)
      Biosimulations employ Finite Element Method (FEM) to simulate complex biological systems in order to understand different aspects of human organs. The applications of FEM biosimulations range from human ear cochlear mechanics, ...

    • Demonstrating a linked data visualiser for finite element biosimulations 

      Mehdi, Muntazir; Khan, Yasar; Freitas, Andre; Jares, Joao; Raza, Saleem; Hasapis, Panagiotis; Sahay, Ratnesh (IEEE, 2016-02-04)
      Healthcare experts have recently turned towards the use of Biosimulation models to understand the multiple or different causative factors that cause impairment in human organs. The applications of biosimulations have been ...

    • Detecting bot behaviour in social media using digital DNA compression 

      Pasricha, Nivranshu; Hayes, Conor (AICS (Artificial Intelligence and Cognitive Science) 2019, 2019-12-05)
      A major challenge faced by online social networks such as Facebook and Twitter is the remarkable rise of fake and automated bot accounts over the last few years. Some of these accounts have been reported to engage in ...

    • Detecting inner-ear anatomical and clinical datasets in the linked open data (LOD) cloud 

      Mehdi, Muntazir; Iqbal, Aftab; Khan, Yasar; Decker, Stefan; Sahay, Ratnesh (CEUR-WS.org, 2015-10-15)
      Linked Open Data (LOD) Cloud is a mesh of open datasets coming from different domains. Among these datasets, a notable amount of datasets belong to the life sciences domain linked together forming an interlinked “Life ...

    • Discovering protein drug targets using knowledge graph embeddings 

      Mohamed, Sameh K.; Nováček, Vít; Nounu, Aayah (Oxford University Press, 2019-08-01)
      Motivation Computational approaches for predicting drug-target interactions (DTIs) can provide valuable insights into the drug mechanism of action. DTI predictions can help to quickly identify new promising (on-target) ...

    • Do city dashboards make sense? Conceptualising user experiences and challenges in using city dashboards. A case study 

      Vornhagen, Heike; Zarrouk, Manel; Davis, Brian; Young, Karen (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 ...

    • Drug target discovery using knowledge graph embeddings 

      Mohamed, Sameh K.; Nováček, Vít; Nounu, Aayah (Association for Computing Machinery, 2019-04-08)
      The field of drug discovery has entered a plateau stage lately. It is increasingly more expensive and time-demanding to introduce new drugs into the market. One of the main reasons is the slow progress in finding novel ...

    • Edge2Guard: Botnet attacks detecting offline models for resource-constrained IoT devices 

      Sudharsan, Bharath; Sundaram, Dineshkumar; Patel, Pankesh; Breslin, John G.; Ali, Muhammad Intizar (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 ...

    • Edge2Train: A framework to train machine learning models (SVMs) on resource-constrained IoT edge devices 

      Sudharsan, Bharath; Breslin, John G.; Ali, Muhammad Intizar (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 ...

    • The ELEXIS interface for interoperable lexical resources 

      McCrae, John P.; Tiberius, Carole; Khan, Anas Fahad; Kernerman, Ilan; Declerck, Thierry; Krek, Simon; Monachini, Monica; Ahmadi, Sina (eLex 2019, 2019-10-01)
      ELEXIS is a project that aims to create a European network of lexical resources, and one of the key challenges for this is the development of an interoperable interface for different lexical resources so that further ...

    • Enabling machine learning on the edge using SRAM conserving efficient neural networks execution approach 

      Sudharsan, Bharath; Patel, Pankesh; Breslin, John G.; Ali, Muhammad Intizar (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 ...

    • Engineering an aligned gold-standard corpus of human to machine oriented Controlled Natural Language 

      Hazem Safwat; Brian Davis; Manel Zarrouk (IEEE, 2018-12-03)
      Knowledge base creation and population are an essential formal backbone for a variety of intelligent applications, decision support and expert systems and intelligent search. While the abundance of unstructured text helps ...

    • Enhancing multiple-choice question answering with causal knowledge 

      Dalal, Dhairya; Arcan, Mihael; Buitelaar, Paul (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 ...

    • Enhancing statistical machine translation with bilingual terminology in a CAT environment 

      Arcan, Mihael; Turchi, Marco; Tonelli, Sara; Buitelaar, Paul (Association for Machine Translation in the Americas, 2014-10-22)
      In this paper, we address the problem of extracting and integrating bilingual terminology into a Statistical Machine Translation (SMT) system for a Computer Aided Translation (CAT) tool scenario. We develop a framework ...

    • Enrichment of blockchain transaction management with semantic triples 

      Yapa Bandara, Kosala; Thakur, Subhasis; Breslin, John (National University of Ireland Galway, 2020-11-02)
      Abstract—Enterprise business transactions have both public and private information; hence blockchain adaptation to an enterprise business application needs current blockchain platforms to support both public and private ...

    • ESSOT: an expert supporting system for ontology translation 

      Arcan, Mihael; Dragoni, Mauro; Buitelaar, Paul (Springer Verlag, 2016)
      To enable knowledge access across languages, ontologies, mostly represented only in English, need to be translated into different languages. The main challenge in translating ontologies with machine translation is to ...

    • Expanding wordnets to new languages with multilingual sense disambiguation 

      Arcan, Mihael; McCrae, John P.; Buitelaar, Paul (The COLING 2016 Organizing Committee, 2016-12-11)
      Princeton WordNet is one of the most important resources for natural language processing, but is only available for English. While it has been translated using the expand approach to many other languages, this is an ...

    • Experiments with term translation 

      Arcan, Mihael; Federmann, Christian; Buitelaar, Paul (Association for Computational Linguistics, 2012-12-08)
      In this article we investigate the translation of financial terms from English into German in the isolation of an ontology vocabulary. For this study we automatically built new domain-specific resources from the translation ...

    • Extending inner-ear anatomical concepts in the Foundational Model of Anatomy (FMA) ontology 

      Khan, Yasar; Mehdi, Muntazir; Jha, Alokkumar; Raza, Saleem; Freitas, Andre; Jones, Marggie; Sahay, Ratnesh (IEEE, 2015-11-02)
      The inner ear is physically inaccessible in living humans, which leads to unique difficulties in studying its normal function and pathology as in other human organs. Recently, biosimulation model has gained a significant ...