http://hdl.handle.net/20.500.11960/3964 2026-08-28T00:35:55Z 2026-08-28T00:35:55Z Jesus, Cristiano Lima, Rui M. Barretiri, Leandro Lopes, Sergio Ivan http://hdl.handle.net/20.500.11960/4986 2026-06-08T17:36:38Z 2022-06-25T00:00:00Z

Title: A maturity model proposal with readiness level assessment for organizational processes improvement Authors: Jesus, Cristiano; Lima, Rui M.; Barretiri, Leandro; Lopes, Sergio Ivan Abstract: The improvement of organizational processes typically relies on opportunities identified by a prior assessment procedure. For example, process digitalization improvement in organizations requires prior knowledge of its digital maturity, thus operating as a starting point for the adoption of a validated and systematized methodology. This work presents a proposal of a maturity model with a readiness level assessment that takes advantage of competencies development, to promote crossanalyses of social and technical conditions within an organization. The adopted methodology is based on a pilot study developed in a hospital located in northern Portugal, being driven by a literature review regarding Maturity Models and Process Engineering. The proposed model will be validated in future applied research projects with companies also located in northern Portugal from the automotive, heavy metalworking, chemical-industrial, and logistics sectors.

2022-06-25T00:00:00Z Melo, Rita Pinto, Pedro Pinto, António http://hdl.handle.net/20.500.11960/4927 2026-04-20T14:08:59Z 2023-01-01T00:00:00Z

Title: Severity analysis of web3 security vulnerabilities based on publicly bug reports Authors: Melo, Rita; Pinto, Pedro; Pinto, António Abstract: Web3 has its basis in blockchain and smart contract technologies, supporting secure, distributed, and decentralized applications. Nonetheless, Web3 is still in the process of evolution, and, as with any other software-based product, software bugs, security flaws, and other vulnerabilities are expected to appear. This paper performs a severity analysis of Web3 security vulnerabilities based on publicly available bug reports. Through this analysis, it is feasible to obtain an overview of the evolution and trends regarding the number of reports delivered, growth by platform, severity classification, and the amounts paid for discovering and reporting vulnerabilities.

2023-01-01T00:00:00Z Torres, Nuno Chaves, Ana Toscano, César Pinto, Pedro http://hdl.handle.net/20.500.11960/4924 2026-04-20T11:57:54Z 2022-01-01T00:00:00Z

Title: Prototyping the IDS security components in the context of industry 4.0 - A textile and clothing industry case study Authors: Torres, Nuno; Chaves, Ana; Toscano, César; Pinto, Pedro Abstract: With the introduction of Industry 4.0 technological concepts, suppliers and manufacturers envision new or improved products and services, cost reductions, and productivity gains. In this context, data exchanges between companies in the same or different activity sectors are necessary, while assuring data security and sovereignty. Thus, it is crucial to select and implement adequate standards which enable the interconnection requirements between companies and also feature security by design. The International Data Spaces (IDS) is a current standard that provides data sharing through data spaces mainly composed of homogeneous rules, certified data providers/consumers, and reliability between partners. Implementing IDS in sectors such as textile and clothing is expected to open new opportunities and challenges. This paper proposes a prototype for the IDS Security Components in the Textile and Clothing Industry context. This prototype assures data sovereignty and enables the interactions required by all participants in this supply chain industry using secure communications. The adoption of IDS as a base model in this activity sector fosters productive collaboration, lowers entry barriers for business partnerships, and enables an innovation environment.

2022-01-01T00:00:00Z Malta, Silvestre Pinto, Pedro Fernández Veiga, Manuel http://hdl.handle.net/20.500.11960/4923 2026-04-20T11:36:50Z 2021-01-01T00:00:00Z

Title: Using syntactic similarity to shorten the training time of deep learning models using time series datasets: A case study Authors: Malta, Silvestre; Pinto, Pedro; Fernández Veiga, Manuel Abstract: The process of building and deploying Machine Learning (ML) models includes several phases and the training phase is taken as one of the most time-consuming. ML models with time series datasets can be used to predict users positions, behaviours or mobility patterns, which implies paths crossing by well-defined positions, and thus, in these cases, syntactic similarity can be used to reduce these models training time. This paper uses the case study of a Mobile Network Operator (MNO) where users mobility are predicted through ML and the use of syntactic similarity with Word2Vec (W2V) framework is tested with Recurrent Neural Network (RNN), Gate Recurrent Unit (GRU), Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN) models. Experimental results show that by using framework W2V in these architectures, the training time task is reduced in average between 22% to 43%. Also an improvement on the validation accuracy of mobility prediction of about 3 percentage points in average is obtained.

2021-01-01T00:00:00Z