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3. Digital Towns

Author

Lynn, Theo, Rosati, Pierangelo, Conway, Edel, Curran, Declan, Fox, Grace, and O'Gorman, Colm

Subjects
digital policy, public policy, urban rural divide, broadband, connectivity, Digital Citizen, technology management, Open access, bic Book Industry Communication::K Economics, finance, business & management::KJ Business & management, bic Book Industry Communication::K Economics, finance, business & management::KJ Business & management::KJQ Business mathematics & systems
Abstract

This open access book explores the digital transformation of small and rural towns, in particular, how to measure the evolution and development of digital towns. In addition to access to resources, competition from urban and global markets, and population trends, rural communities present lesser access and use of digital technologies and have lower digital competencies and skills than their urban counterparts. Consequently, they experience less beneficial outcomes from increased digitalisation than urban areas. This book defines what a digital town is and explores digitalisation from the perspective of the four basic economic sectors in towns - individuals and households, businesses, the public sector, and civil society - and three types of enabling infrastructure - digital connectivity, education, and governance. Particular attention is paid to how digitalisation efforts are measured by intergovernmental and international organisations for each sector and enabling infrastructure. The book concludes with a Digital Town Readiness Framework that offers local communities, policymakers, and scholars an initial set of indicators upon which to develop digital town initiatives, and measure progress. For those ready to embrace the opportunity, this book is a pathfinder on the road to a more equitable and impactful digital society and digital economy.

Published
2022
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4. Kicking Prejudice: Large Language Models for Racism Classification in Soccer Discourse on Social Media

Author

Santos, Guto Leoni, dos Santos, Vitor Gaboardi, Kearns, Colm, Sinclair, Gary, Black, Jack, Doidge, Mark, Fletcher, Thomas, Kilvington, Dan, Endo, Patricia Takako, Liston, Katie, Lynn, Theo, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, van Leeuwen, Jan, Series Editor, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Kobsa, Alfred, Series Editor, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Nierstrasz, Oscar, Series Editor, Pandu Rangan, C., Editorial Board Member, Sudan, Madhu, Series Editor, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Vardi, Moshe Y, Series Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Guizzardi, Giancarlo, editor, Santoro, Flavia, editor, Mouratidis, Haralambos, editor, and Soffer, Pnina, editor

Published
2024
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5. Identifying Citizen-Related Issues from Social Media Using LLM-Based Data Augmentation

Author

dos Santos, Vitor Gaboardi, Santos, Guto Leoni, Lynn, Theo, Benatallah, Boualem, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, van Leeuwen, Jan, Series Editor, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Kobsa, Alfred, Series Editor, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Nierstrasz, Oscar, Series Editor, Pandu Rangan, C., Editorial Board Member, Sudan, Madhu, Series Editor, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Vardi, Moshe Y, Series Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Guizzardi, Giancarlo, editor, Santoro, Flavia, editor, Mouratidis, Haralambos, editor, and Soffer, Pnina, editor

Published
2024
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6. Exploring the Performance of Machine Learning Models and Predictive Factors for Fetal Death: Preliminary Results

Author

de Mello, Maria Eduarda Ferro, da Silva Rocha, Élisson, de Morais, Flávio Leandro, de Queiroz Figueiroôa, Barbara, da Silva, Marília Santana, Neto, Waldemar Brandão, Lynn, Theo, Endo, Patricia Takako, Onwubiko, Cyril, editor, Rosati, Pierangelo, editor, Rege, Aunshul, editor, Erola, Arnau, editor, Bellekens, Xavier, editor, Hindy, Hanan, editor, and Jaatun, Martin Gilje, editor

Published
2024
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12. Predicting Short-term Mobile Internet Traffic from Internet Activity using Recurrent Neural Networks

Author

Santos, Guto Leoni, Rosati, Pierangelo, Lynn, Theo, Kelner, Judith, Sadok, Djamel, and Endo, Patricia Takako

Subjects
Computer Science - Networking and Internet Architecture
Abstract

Mobile network traffic prediction is an important input in to network capacity planning and optimization. Existing approaches may lack the speed and computational complexity to account for bursting, non-linear patterns or other important correlations in time series mobile network data. We compare the performance of two deep learning architectures - Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) - for predicting mobile Internet traffic using two months of Telecom Italia data for the metropolitan area of Milan. K-Means clustering was used a priori to group cells based on Internet activity and the Grid Search method was used to identify the best configurations for each model. The predictive quality of the models was evaluated using root mean squared error. Both Deep Learning algorithms were effective in modeling Internet activity and seasonality, both within days and across two months. We find variations in performance across clusters within the city. Overall, the LSTM outperformed the GRU in our experiments.

Published
2020

13. The Greatest Teacher, Failure is: Using Reinforcement Learning for SFC Placement Based on Availability and Energy Consumption

Author

Santos, Guto Leoni, Lynn, Theo, Kelner, Judith, and Endo, Patricia Takako

Subjects
Computer Science - Networking and Internet Architecture, Computer Science - Machine Learning
Abstract

Software defined networking (SDN) and network functions virtualisation (NFV) are making networks programmable and consequently much more flexible and agile. To meet service level agreements, achieve greater utilisation of legacy networks, faster service deployment, and reduce expenditure, telecommunications operators are deploying increasingly complex service function chains (SFCs). Notwithstanding the benefits of SFCs, increasing heterogeneity and dynamism from the cloud to the edge introduces significant SFC placement challenges, not least adding or removing network functions while maintaining availability, quality of service, and minimising cost. In this paper, an availability- and energy-aware solution based on reinforcement learning (RL) is proposed for dynamic SFC placement. Two policy-aware RL algorithms, Advantage Actor-Critic (A2C) and Proximal Policy Optimisation (PPO2), are compared using simulations of a ground truth network topology based on the Rede Nacional de Ensino e Pesquisa (RNP) Network, Brazil's National Teaching and Research Network backbone. The simulation results showed that PPO2 generally outperformed A2C and a greedy approach both in terms of acceptance rate and energy consumption. A2C outperformed PPO2 only in the scenario where network servers had a greater number of computing resources.

Published
2020

15. Digital Education

Author

Lynn, Theo, Rosati, Pierangelo, Conway, Edel, Curran, Declan, Fox, Grace, O’Gorman, Colm, Lynn, Theo, Rosati, Pierangelo, Conway, Edel, Curran, Declan, Fox, Grace, and O'Gorman, Colm

Published
2022
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17. Digital Technologies and Civil Society

Author

Lynn, Theo, Rosati, Pierangelo, Conway, Edel, Curran, Declan, Fox, Grace, O’Gorman, Colm, Lynn, Theo, Rosati, Pierangelo, Conway, Edel, Curran, Declan, Fox, Grace, and O'Gorman, Colm

Published
2022
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18. The Digital Citizen

Author

Lynn, Theo, Rosati, Pierangelo, Conway, Edel, Curran, Declan, Fox, Grace, O’Gorman, Colm, Lynn, Theo, Rosati, Pierangelo, Conway, Edel, Curran, Declan, Fox, Grace, and O'Gorman, Colm

Published
2022
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20. Digital Public Services

Author

Lynn, Theo, Rosati, Pierangelo, Conway, Edel, Curran, Declan, Fox, Grace, O’Gorman, Colm, Lynn, Theo, Rosati, Pierangelo, Conway, Edel, Curran, Declan, Fox, Grace, and O'Gorman, Colm

Published
2022
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22. Infrastructure for Digital Connectivity

Author

Lynn, Theo, Rosati, Pierangelo, Conway, Edel, Curran, Declan, Fox, Grace, O’Gorman, Colm, Lynn, Theo, Rosati, Pierangelo, Conway, Edel, Curran, Declan, Fox, Grace, and O'Gorman, Colm

Published
2022
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24. Right Scaling for Right Pricing: A Case Study on Total Cost of Ownership Measurement for Cloud Migration

Author

Rosati, Pierangelo, Fowley, Frank, Pahl, Claus, Taibi, Davide, and Lynn, Theo

Subjects
Computer Science - Software Engineering
Abstract

Cloud computing promises traditional enterprises and independent software vendors a myriad of advantages over on-premise installations including cost, operational and organizational efficiencies. The decision to migrate software configured for on-premise delivery to the cloud requires careful technical consideration and planning. In this chapter, we discuss the impact of right-scaling on the cost modelling for migration decision making and price setting of software for commercial resale. An integrated process is presented for measuring total cost of ownership, taking in to account IaaS/PaaS resource consumption based on forecast SaaS usage levels. The process is illustrated with a real world case study.

Published
2019
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35. Simulating Across the Cloud-to-Edge Continuum

Author

Spanopoulos-Karalexidis, Minas, Filelis Papadopoulos, Christos K., Giannoutakis, Konstantinos M., Gravvanis, George A., Tzovaras, Dimitrios, Bendechache, Malika, Svorobej, Sergej, Endo, Patricia Takako, Lynn, Theo, Lynn, Theo, Series Editor, Mooney, John G., Series Editor, Domaschka, Jörg, editor, and Ellis, Keith A., editor

Published
2020
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43. "Let the tournament for the woke begin!": Euro 2020 and the reproduction of Cultural Marxist conspiracies in online criticisms of the "take the knee" protest.

Author

Black, Jack, Fletcher, Thomas, Doidge, Mark, Kearns, Colm, Kilvington, Daniel, Liston, Katie, Lynn, Theo, Rosati, Pierangelo, and Sinclair, Gary

Subjects
SOCIAL reproduction, SOCIAL media, BLACK Lives Matter movement, CONSPIRACIES, CONSPIRACY theories, PROTEST movements, KNEE
Abstract

Exploring online criticisms of the "take the knee" protest during "Euro 2020", this article examines how alt- and far-right conspiracies were both constructed and communicated via the social media platform, Twitter. By providing a novel exploration of alt-right conspiracies during an international football tournament, a qualitative thematic analysis of 1,388 original tweets relating to Euro 2020 was undertaken. The findings reveal how, in criticisms levelled at both "wokeism" and the Black Lives Matter movement, anti-white criticisms of the "take the knee" protest were embroiled in alt-right conspiracies that exposed an assumed Cultural Marxist, "woke agenda" in the tournament's organisation and mainstream media coverage. In conclusion, it is argued that conspiratorial discourses, associated with the alt-right, provided a framework through which the protest could be understood. This emphasises how the significance of conspiracy functions to promote the wider dissemination of alt-right ideology across popular cultural contexts, such as sport. [ABSTRACT FROM AUTHOR]

Published
2024
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46. Digital Towns

Author

Lynn, Theo, primary, Rosati, Pierangelo, additional, Conway, Edel, additional, Curran, Declan, additional, Fox, Grace, additional, and O'Gorman, Colm, additional

Published
2022
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49. RECAP (Reliable Capacity Provisioning and Enhanced Remediation for Distributed Cloud Applications): The Simulation Approach

Author

Endo, Patricia Takako, Filelis-Papadopoulos, Christos, Svorobej, Sergej, Gourinovitch, Anna, Giannoutakis, Konstantinos, Gravvanis, George, Tzovaras, Dimitrios, Elango, Divyaa Manimaran, Byrne, James, Lynn, Theo, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Fazio, Maria, editor, and Zimmermann, Wolf, editor

Published
2020
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