Computer Science: Recent submissions
Now showing items 201-220 of 2149
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A Measurement Study of Offloading Virtual Network Functions to the Edge
(2022)The deployment of virtual network functions (VNFs) at edge servers potentially impairs the performance of latency-sensitive applications due to their computational cost. This work considers a new approach to addressing ... -
Game-Based Learning of Data Structures Based onAnalogies: Learning Gains andIntrinsic Motivation in Higher Education Environments
(Trinity College Dublin. School of Computer Science & Statistics. Discipline of Computer Science, 2022)Many researchers have considered video games as effective learning tools. According to them, video games can increase intrinsic motivation and promote active learning. However, video games are a flexible medium, and they ... -
A hybrid agent-based and equation based model for the spread of infectious diseases
(2020)Both agent-based models and equation-based models can be used to model the spread of an infectious disease. Equation-based models have been shown to capture the overall dynamics of a disease outbreak while agent-based ... -
Hybrid modelling for stroke care: Review and suggestions of new approaches for risk assessment and simulation of scenarios
(2021)Stroke is an example of a complex and multi-factorial disease involving multiple organs, timescales, and disease mechanisms. To deal with this complexity, and to realize Precision Medicine of stroke, mathematical models ... -
The impact of body mass index on functional rehabilitation outcomes of working-age inpatients with stroke
(2021)Background: Stroke is the most relevant cause of acquired persistent disability in adulthood. The relationship between patient's weight during rehabilitation and stroke functional outcome is controversial, previous research ... -
Adapting an agent-based model of infectious disease spread in an Irish county to COVID-19
(2021)The dynamics that lead to the spread of an infectious disease through a population can be characterized as a complex system. One way to model such a system, in order to improve preparedness, and learn more about how an ... -
Using a hybrid agent-based and equation based model to test school closure policies during a measles outbreak
(2021)In order to be prepared for an infectious disease outbreak it is important to know what interventions will or will not have an impact on reducing the outbreak. While some interventions might have a greater effect in ... -
Capturing and measuring thematic relatedness
(2020)In this paper we explain the difference between two aspects of semantic relatedness: taxonomic and thematic relations. We notice the lack of evaluation tools for measuring thematic relatedness, identify two datasets that ... -
A model for the spread of infectious diseases in a region
(2020)In understanding the dynamics of the spread of an infectious disease, it is important to understand how a town’s place in a network of towns within a region will impact how the disease spreads to that town and from that ... -
Mutual Information Decay Curves and Hyper-parameter Grid Search Design for Recurrent Neural Architectures
(2020)We present an approach to design the grid searches for hyper-parameter optimization for recurrent neural architectures. The basis for this approach is the use of mutual information to analyze long distance dependencies ... -
F-Measure Optimisation and Label Regularisation for Energy-Based Neural Dialogue State Tracking Models
(2020)In recent years many multi-label classification methods have exploited label dependencies to improve performance of classification tasks in various domains, hence casting the tasks to structured prediction problems. We ... -
Local Alignment of Frame of Reference Assignment in English and Swedish Dialogue
(2020)In this paper we examine how people assign, interpret, negotiate and repair the frame of reference (FoR) in online text-based dialogues discussing spatial scenes in English and Swedish. We describe our corpus and data ... -
Update Frequency and Background Corpus Selection in Dynamic TF-IDF Models for First Story Detection
(2020)First Story Detection (FSD) requires a system to detect the very first story that mentions an event from a stream of stories. Nearest neighbour-based models, using the traditional term vector document representations like ... -
Expectations of artificial intelligence and the performativity of ethics: Implications for communication governance
(2020)This article draws on the sociology of expectations to examine the construction of expectations of ‘ethical AI’ and considers the implications of these expectations for communication governance. We first analyse a range ... -
Language Model Co-occurrence Linking for Interleaved Activity Discovery
(2020)As ubiquitous computer and sensor systems become abundant, the potential for automatic identification and tracking of human behaviours becomes all the more evident. Annotating complex human behaviour datasets to achieve ... -
Hobbit: A Tool for Contextual Equivalence Checking Using Bisimulation Up-to Techniques
(2021)We present a bounded equivalence verification tool called Hobbit for higher-order programs with local state—based on a subset of OCaml—that combines fully abstract symbolic environmental bisimulations, novel up-to techniques, ... -
From Bounded Checking to Verification of Equivalence via Symbolic Up-to Techniques
(Springer, 2022)We present a bounded equivalence verification technique for higher-order programs with local state. This technique combines fully abstract symbolic environmental bisimulations similar to symbolic game semantics, novel up-to ... -
Standardization and the Governance of Artificial Intelligence Standards
(Springer, 2021)The topic of trustworthy Artificial Intelligence (AI) has attracted wide attention from governments, companies and international bodies as they strive to address the ethical and societal risks that emerge as performance ... -
Consent Recipts for a Usage And Auditable Web of Personal Data
(2022)Consenting on the Web, in the context of online privacy and data protection, is universally accepted as a difficult problem, mainly because of its cross-disciplinarity. For example, any approach to online Consenting needs ... -
Automatic program generation for convolutional neural networks on resource constrained devices
(Trinity College Dublin. School of Computer Science & Statistics. Discipline of Computer Science, 2022)Convolutional Neural Networks (CNNs) are both arithmetically and memory intensive when performing inference. This is a problem when executing CNNs on resource constrained machines, such as small embedded devices. This ...
