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Publications

2024

Federated Online Learning for Heavy Hitter Detection

Authors
Silva, P; Vinagre, J; Gama, J;

Publication
ECAI 2024

Abstract
Effective anomaly detection in telecommunication networks is essential for securing digital transactions and supporting the sustainability of our global information ecosystem. However, the volume of data in such high-speed distributed environments imposes strict latency and scalability requirements on anomaly detection systems. This study focuses on distributed heavy hitter detection in telephone networks - a critical component of network traffic analysis and fraud detection. We propose a federated version of the Lossy Counting algorithm and compare it to its centralized version. Our experimental results reveal that the federated approach can detect considerably more unique heavy hitters than the centralized method while enhancing privacy. Furthermore, Federated Lossy Counting does not need a large amount of centralized processing power since it can leverage the networked infrastructure with minimal impact on bandwidth and computing power.

2024

Nautilus: An autonomous surface vehicle with a multilayer software architecture for offshore inspection

Authors
Campos, DF; Goncalves, EP; Campos, HJ; Pereira, MI; Pinto, AM;

Publication
JOURNAL OF FIELD ROBOTICS

Abstract
The increasing adoption of robotic solutions for inspection tasks in challenging environments is becoming increasingly prevalent, particularly in the offshore wind energy industry. This trend is driven by the critical need to safeguard the integrity and operational efficiency of offshore infrastructure. Consequently, the design of inspection vehicles must comply with rigorous requirements established by the offshore Operation and Maintenance (O&M) industry. This work presents the design of an autonomous surface vehicle (ASV), named Nautilus, specifically tailored to withstand the demanding conditions of offshore O&M scenarios. The design encompasses both hardware and software architectures, ensuring Nautilus's robustness and adaptability to the harsh maritime environment. It presents a compact hull capable of operating in moderate sea states (wave height up to 2.5 m), with a modular hardware and software architecture that is easily adapted to the mission requirements. It has a perception payload and communication system for edge and real-time computing, communicates with a Shore Control Center and allows beyond visual line-of-sight operations. The Nautilus software architecture aims to provide the necessary flexibility for different mission requirements to offer a unified software architecture for O&M operations. Nautilus's capabilities were validated through the professional testing process of the ATLANTIS Test Center, involving operations in both near-real and real-world environments. This validation process culminated in Nautilus's reaching a Technology Readiness Level 8 and became the first ASV to execute autonomous tasks at a floating offshore wind farm located in the Atlantic.

2024

Supervised and unsupervised techniques in textile quality inspections

Authors
Ferreira, HM; Carneiro, DR; Guimaraes, MA; Oliveira, FV;

Publication
5TH INTERNATIONAL CONFERENCE ON INDUSTRY 4.0 AND SMART MANUFACTURING, ISM 2023

Abstract
Quality inspection is a critical step in ensuring the quality and efficiency of textile production processes. With the increasing complexity and scale of modern textile manufacturing systems, the need for accurate and efficient quality inspection and defect detection techniques has become paramount. This paper compares supervised and unsupervised Machine Learning techniques for defect detection in the context of industrial textile production, in terms of their respective advantages and disadvantages, and their implementation and computational costs. We explore the use of an autoencoder for the detection of defects in textiles. The goal of this preliminary work is to find out if unsupervised methods can successfully train models with good performance without the need for defect labelled data. (c) 2023 The Authors. Published by Elsevier B.V.

2024

Work-from-home impacts on software project: A global study on software development practices and stakeholder perceptions

Authors
Duc, AN; Khanna, D; Le, GH; Greer, D; Wang, X; Zaina, LM; Matturro, G; Melegati, J; Guerra, E; Kettunen, P; Hyrynsalmi, S; Edison, H; Sales, A; Chanin, R; Rutitis, D; Kemell, KK; Aldaeej, A; Mikkonen, T; Garbajosa, J; Abrahamsson, P;

Publication
Softw. Pract. Exp.

Abstract
ContextThe COVID-19 pandemic has had a disruptive impact on how people work and collaborate across all global economic sectors, including software business. While remote working is not new for software engineers, forced WFH situations come with both limitations and opportunities. As the ‘new normal’ for working might be based on the current state of Work-from-home (WFH), it is useful to understand what has happened and learn from that.ObjectiveThis study aims to gain insights into how their WFH arrangement impacts project management and software engineering. We are also interested in exploring these impacts in different contexts, such as startups and established companies.MethodWe conducted a global-scale, cross-sectional survey during the spring and summer 2021. Our results are based on quantitative and qualitative analysis of 297 valid responses.ResultsWe characterize the profile of WFH in both spatial and temporal aspects, together with a set of common collaborative tools and coordination and control mechanisms. We revealed some areas of project management that are relatively more challenging during WFH situations, such as coordination, communication and project planning. We also revealed a mixed picture of the perceived impact of WFH on different software engineering activities.ConclusionWFH is a situational phenomenon which can have both negative and positive impact on software teams. For practitioners, we suggest a unified approach to consider the context of WFH, collaborative tools, associated coordination and control approaches and a process that resolve those aspects that are sensitive to physical interaction.

2024

Synergetic Cooperation between Robots and Humans

Authors
Youssef, ESE; Tokhi, MO; Silva, MF; Rincon, LM;

Publication
Lecture Notes in Networks and Systems

Abstract

2024

Variable Message Signs in Traffic Management: A Systematic Review of User Behavior and Future Innovations

Authors
Lagoa, P; Galvao, T; Ferreira, MC;

Publication
INFRASTRUCTURES

Abstract
Effective traffic management is crucial in addressing the growing complexities of urban mobility, and variable message signs (VMSs) play a vital role in delivering real-time information to road users. Despite their widespread application, there is limited comprehensive understanding of how VMS influence user behavior and optimize traffic flow. This systematic literature review aims to address this gap by examining the effectiveness of VMS in shaping user interactions and enhancing traffic management systems. Using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) methodology, a thorough analysis of relevant studies was conducted to identify key factors influencing VMS impact, including message content and characteristics, complementary sources of information, user demographics, VMS location, and users' reliance on these signs. Additionally, the review explores the implications of displaying non-critical information on VMS and introduces virtual dynamic message signs (VDMSs) as an innovative approach for delivering public traveler information. The study identifies several research gaps, such as the integration of VMS with vehicle-to-everything (V2X) technologies, navigation systems, the need for validation in real-world scenarios, and understanding behavioral responses to non-critical information on VMS. This review highlights the importance of optimizing VMS for improved user engagement and traffic management, providing valuable insights and directions for future research in this evolving field.

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