arXiv subjects

Paulo Silva

Publications and source records attributed to Paulo Silva.

13 recordsLinked to original sources

arXiv2026

WaterCopilot: An AI-Driven Virtual Assistant for Water Management

Sustainable water resource management in transboundary river basins is challenged by fragmented data, limited real-time access, and the complexity of integrating diverse information sources. This paper presents WaterCopilot-an AI-driven virtual assistant developed through collaboration between the International Water Management Institute (IWMI) and Microsoft Research for the Limpopo River Basin (LRB) to bridge these gaps through a unified, interactive platform. Built on Retrieval-Augmented Generation (RAG) and tool-calling architectures, WaterCopilot integrates static policy documents and real-time hydrological data via two custom plugins: the iwmi-doc-plugin, which enables semantic search over indexed documents using Azure AI Search, and the iwmi-api-plugin, which queries live databases to deliver dynamic insights such as environmental-flow alerts, rainfall trends, reservoir levels, water accounting, and irrigation data. The system features guided multilingual interactions (English, Portuguese, French), transparent source referencing, automated calculations, and visualization capabilities. Evaluated using the RAGAS framework, WaterCopilot achieves an overall score of 0.8043, with high answer relevancy (0.8571) and context precision (0.8009). Key innovations include automated threshold-based alerts, integration with the LRB Digital Twin, and a scalable deployment pipeline hosted on AWS. While limitations in processing non-English technical documents and API latency remain, WaterCopilot establishes a replicable AI-augmented framework for enhancing water governance in data-scarce, transboundary contexts. The study demonstrates the potential of this AI assistant to support informed, timely decision-making and strengthen water security in complex river basins.

cs.AI↗

arXiv2024

A System Development Kit for Big Data Applications on FPGA-based Clusters: The EVEREST Approach

Modern big data workflows are characterized by computationally intensive kernels. The simulated results are often combined with knowledge extracted from AI models to ultimately support decision-making. These energy-hungry workflows are increasingly executed in data centers with energy-efficient hardware accelerators since FPGAs are well-suited for this task due to their inherent parallelism. We present the H2020 project EVEREST, which has developed a system development kit (SDK) to simplify the creation of FPGA-accelerated kernels and manage the execution at runtime through a virtualization environment. This paper describes the main components of the EVEREST SDK and the benefits that can be achieved in our use cases.

cs.AR↗

arXiv2023

An Intelligent Mechanism for Monitoring and Detecting Intrusions in IoT Devices

The current amount of IoT devices and their limitations has come to serve as a motivation for malicious entities to take advantage of such devices and use them for their own gain. To protect against cyberattacks in IoT devices, Machine Learning techniques can be applied to Intrusion Detection Systems. Moreover, privacy related issues associated with centralized approaches can be mitigated through Federated Learning. This work proposes a Host-based Intrusion Detection Systems that leverages Federated Learning and Multi-Layer Perceptron neural networks to detected cyberattacks on IoT devices with high accuracy and enhancing data privacy protection.

cs.DC↗

arXiv2023

Impact of Geo-distribution and Mining Pools on Blockchains: A Study of Ethereum

Given the large adoption and economical impact of permissionless blockchains, the complexity of the underlying systems and the adversarial environment in which they operate, it is fundamental to properly study and understand the emergent behavior and properties of these systems. We describe our experience on a detailed, one-month study of the Ethereum network from several geographically dispersed observation points. We leverage multiple geographic vantage points to assess the key pillars of Ethereum, namely geographical dispersion, network efficiency, blockchain efficiency and security, and the impact of mining pools. Among other new findings, we identify previously undocumented forms of selfish behavior and show that the prevalence of powerful mining pools exacerbates the geographical impact on block propagation delays. Furthermore, we provide a set of open measurement and processing tools, as well as the data set of the collected measurements, in order to promote further research on understanding permissionless blockchains.

cs.DC↗

arXiv2023

Tunable and Portable Extreme-Scale Drug Discovery Platform at Exascale: the LIGATE Approach

Today digital revolution is having a dramatic impact on the pharmaceutical industry and the entire healthcare system. The implementation of machine learning, extreme-scale computer simulations, and big data analytics in the drug design and development process offers an excellent opportunity to lower the risk of investment and reduce the time to the patient. Within the LIGATE project, we aim to integrate, extend, and co-design best-in-class European components to design Computer-Aided Drug Design (CADD) solutions exploiting today's high-end supercomputers and tomorrow's Exascale resources, fostering European competitiveness in the field. The proposed LIGATE solution is a fully integrated workflow that enables to deliver the result of a virtual screening campaign for drug discovery with the highest speed along with the highest accuracy. The full automation of the solution and the possibility to run it on multiple supercomputing centers at once permit to run an extreme scale in silico drug discovery campaign in few days to respond promptly for example to a worldwide pandemic crisis.

cs.DC↗

arXiv2023

The quark propagator and quark-gluon vertex from lattice QCD at finite temperature

The quark-gluon vertex is an important object of QCD. Studies have shown that this quantity is relevant for the dynamical chiral symmetry breaking pattern in the vacuum. The goal of our project is to obtain the quark-gluon vertex at finite temperature around the deconfinement/chiral transition using the tools provided by lattice QCD. It will be the first time that the quark-gluon vertex at finite temperature is determined using lattice QCD. The propagators, which are a by-product of this project, are also of interest in themselves. The configurations used were generated by the FASTSUM collaboration. In this contribution, we describe our motivations and goals, some technical details of the determination and report on the status of the calculation.

hep-lat↗

arXiv2023

Deconfinement in pure gauge SU(3) Yang-Mills theory: the ghost propagator

The ghost propagator in Landau gauge is studied at finite temperature below and above $T_c$ using lattice QCD simulations. For high temperatures, we find that the ghost propagator is enhanced, compared to the confined phase. The results suggest that the ghost propagator can be used to identify the phase transition, similarly to the gluon propagator case.

hep-lat↗

arXiv2022

NimbleChain: Speeding up cryptocurrencies in general-purpose permissionless blockchains

Nakamoto's seminal work gave rise to permissionless blockchains -- as well as a wide range of proposals to mitigate their performance shortcomings. Despite substantial throughput and energy efficiency achievements, most proposals only bring modest (or marginal) gains in transaction commit latency. Consequently, commit latencies in today's permissionless blockchain landscape remain prohibitively high. This paper proposes NimbleChain, a novel algorithm that extends permissionless blockchains based on Nakamoto consensus with a fast path that delivers causal promises of commitment, or simply promises. Since promises only partially order transactions, their latency is only a small fraction of the totally-ordered commitment latency of Nakamoto consensus. Still, the weak consistency guarantees of promises are strong enough to correctly implement cryptocurrencies. To the best of our knowledge, NimbleChain is the first system to bring together fast, partially-ordered transactions with consensus-based, totally-ordered transactions in a permissionless setting. This hybrid consistency model is able to speed up cryptocurrency transactions while still supporting smart contracts, which typically have (strong) sequential consistency needs. We implement NimbleChain as an extension of Ethereum and evaluate it in a 500-node geo-distributed deployment. The results show NimbleChain can promise a cryptocurrency transactions up to an order of magnitude faster than a vanilla Ethereum implementation, with marginal overheads.

cs.DC↗

arXiv2021

Quark-gluon vertex with 2 flavours of O(a) improved Wilson fermions

We study the Landau-gauge quark-gluon vertex with 2 flavours of O(a)improved Wilson fermions, for several lattice spacings and quark masses. In the limit of vanishing gluon momentum, we find that all nonzero form factors have a significant infrared strength, and that the leading form factor lambda_1, multiplying the tree-level vertex structure, is significantly enhanced in the infrared compared to the quenched case. We find that all form factors are further enhanced in the infrared as the chiral and continuum limits are approached.

hep-lat↗

arXiv2021

Performance Evaluation of Snapshot Methods to Warm the Serverless Cold Start

The serverless computing model strengthens the cloud computing tendency to abstract resource management. Serverless platforms are responsible for deploying and scaling the developer's applications. Serverless also incorporated the pay-as-you-go billing model, which only considers the time spent processing client requests. Such a decision created a natural incentive for improving the platform's efficient resource usage. This search for efficiency can lead to the cold start problem, which represents a delay to execute serverless applications. Among the solutions proposed to deal with the cold start, those based on the snapshot method stand out. Despite the rich exploration of the technique, there is a lack of research that evaluates the solution's trade-offs. In this direction, this work compares two solutions to mitigate the cold start: Prebaking and SEUSS. We analyzed the solution's performance with functions of different levels of complexity: NoOp, a function that renders Markdown to HTML, and a function that loads 41 MB of dependencies. Preliminary results indicated that Prebaking showed a 33% and 25% superior performance to startup the NoOp and Markdown functions, respectively. Further analysis also revealed that Prebaking's warmup mechanism reduced the Markdown first request processing time by 69%.

cs.DC↗

arXiv2020

Spectral representation of lattice gluon and ghost propagators at zero temperature

We consider the analytic continuation of Euclidean propagator data obtained from 4D simulations to Minkowski space. In order to perform this continuation, the common approach is to first extract the Källén-Lehmann spectral density of the field. Once this is known, it can be extended to Minkowski space to yield the Minkowski propagator. However, obtaining the Källén-Lehmann spectral density from propagator data is a well known ill-posed numerical problem. To regularize this problem we implement an appropriate version of Tikhonov regularization supplemented with the Morozov discrepancy principle. We will then apply this to various toy model data to demonstrate the conditions of validity for this method, and finally to zero temperature gluon and ghost lattice QCD data. We carefully explain how to deal with the IR singularity of the massless ghost propagator. We also uncover the numerically different performance when using two ---mathematically equivalent--- versions of the Källén-Lehmann spectral integral.

hep-lat↗

arXiv2016

TapDrag: An Alternative Dragging Technique on Medium-Sized MultiTouch Displays Reducing Skin Irritation and Arm Fatigue

Medium-sized touch displays, sized 30 to 50 inches, are becoming more affordable and more widely available. Prolonged use of such displays can result in arm fatigue or skin irritation, especially when multiple long distance drags are involved. To address this issue, we present TapDrag, an alternative dragging technique that complements traditional dragging with a simple tapping gesture on both ends of the intended dragging path. Our experimental evaluation suggests that TapDrag is a viable alternative to traditional dragging with faster task completion times for long distances. Qualitative user feedback indicates that TapDrag helps prevent skin irritation. A reduction in arm fatigue remains unconfirmed.

cs.HC↗

arXiv2014

Gluon mass at finite temperature in Landau gauge

Using lattice results for the Landau gauge gluon propagator at finite temperature, we investigate its interpretation as a massive type bosonic propagator. In particular, we estimate a gluon mass from Yukawa-like fits to the lattice data and study its temperature dependence.

hep-lat↗