CIIC - Artigos em Revistas com Peer Review
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Browsing CIIC - Artigos em Revistas com Peer Review by Sustainable Development Goals (SDG) "09:Indústria, Inovação e Infraestruturas"
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- Decrypting messages: Extracting digital evidence from signal desktop for windowsPublication . Paulino, Gonçalo; Negrão, Miguel; Frade, Miguel; Domingues, PatrícioWith growing concerns over the security and privacy of personal conversations, end-to-end encrypted instant messaging applications have become a key focus of forensic research. This study presents a detailed methodology along with an automated Python script for decrypting and analyzing forensic artifacts from Signal Desktop for Windows. The methodology is divided into two phases: i) decryption of locally stored data and ii) analysis and documentation of forensic artifacts. To ensure data integrity, the proposed approach enables retrieval without launching Signal Desktop, preventing potential alterations. Additionally, a reporting module organizes extracted data for forensic investigators, enhancing usability. Our approach is effective in extracting and analyzing encrypted Signal artifacts, providing a reliable method for forensic investigations.
- Driving Behavior Classification Using a ConvLSTMPublication . Pingo, Alberto; Castro, João; Loureiro, Paulo; Mendes, Silvio; Bernardino, Anabela; Miragaia, Rolando; Husyeva, IrynaThis work explores the classification of driving behaviors using a hybrid deep learning model that combines Convolutional Neural Networks (CNNs) with Long Short-Term Memory (LSTM) networks (ConvLSTM). Sensor data are collected from a smartphone application and undergo a preprocessing pipeline, including data normalization, labeling, and feature extraction, to enhance the model’s performance. By capturing temporal and spatial dependencies within driving patterns, the proposed ConvLSTM model effectively differentiates between normal and aggressive driving behaviors. The model is trained and evaluated against traditional stacked LSTM and Bidirectional LSTM (BiLSTM) architectures, demonstrating superior accuracy and robustness. Experimental results confirm that the preprocessing techniques improve classification performance, ensuring high reliability in driving behavior recognition. The novelty of this work lies in a simple data preprocessing methodology combined with the specific application scenario. By enhancing data quality before feeding it into the AI model, we improve classification accuracy and robustness. The proposed framework not only optimizes model performance but also demonstrates practical feasibility, making it a strong candidate for real-world deployment.
- High dynamic range - a gateway for predictive ancient lightingPublication . Gonçalves, Alexandrino José Marques; Magalhães, Luís; Moura, João; Chalmers, AlanIn the last few years, the number of projects involving historical reconstruction has increased significantly. Recent technologies have proven a powerful tool for a better understanding of our cultural heritage through which to attain a glimpse of the environments in which our ancestors lived. However, to accomplish such a purpose, these reconstructions should be presented to us as they may really have been perceived by a local inhabitant, according to the illumination and materials used back then and, equally important, the characteristics of the human visual system. The human visual system has a remarkable ability to adjust itself to almost all everyday scenarios. This is particularly evident in extreme lighting conditions, such as bright light or dark environments. However, a major portion of the visible spectra captured by our visual system cannot be represented in most display devices. High dynamic range imagery is a field of research which is developing techniques to correct such inaccuracies. This new viewing paradigm is perfectly suited for archaeological interpretation, since its high contrast and chromaticity can present us with an enhanced viewing experience, closer to what an inhabitant of that era may have seen. In this article we present a case study of the reconstruction of a Roman site. We generate high dynamic range images of mosaics and frescoes from one of the most impressive monuments in the ruins of Conimbriga, Portugal, an ancient city of the Roman Empire. To achieve the requisite level of precision, in addition to having a precise geometric 3D model, it is crucial to integrate in the virtual simulation authentic physical data of the light used in the period under consideration. Therefore, in order to create a realistic physical-based environment, we use in our lighting simulations real data obtained from simulated Roman luminaries of that time.
- Long-Range RFID Indoor Positioning System for an Autonomous WheelchairPublication . Pereira, JoãoA new Radio-Frequency Identification (RFID) indoor positioning system (IPS) has been developed to operate in environments where the Global Positioning System (GPS) is unavailable. Traditional RFID tracking systems, such as anti-theft systems in clothing stores, typically work within close proximity to exit doors. This paper presents a novel RFID IPS capable of locating and tracking passive RFID tags over a larger area with greater precision. These tags, costing approximately EUR 0.10 each, are in the form of small stickers that can be attached to any item requiring tracking. The proposed system is designed for an autonomous wheelchair, built from scratch, which will be identified and monitored using passive RFID tags. Our new RFID IPS, with a 12 m range, is implemented in this “smart” wheelchair.
- Reconstruction and generation of virtual heritage sitesPublication . Rodrigues, Nuno; Magalhães, L.; Moura, J.; Chalmers, A.Traditionally procedural modelling techniques are commonly used to generate new structures and are presently established in several areas such as video games and computer animated movies. However they may also be used in heritage applications to efficiently produce models of non-existing worlds for which there is some kind of knowledge (e.g. floor plans, photographs) to support the reconstruction of realistic environments. Similarly they may also be used to support the generation of distinct possibilities that allow experts to draw some conclusions or conceive different hypotheses about lost worlds. The present paper shows the benefits and constraints that may arise from the use of such techniques in virtual heritage applications. Furthermore, a whole method is proposed, for the reconstruction and generation of virtual heritage traversable house models, provided through the means of a grammar, demonstrated with the reconstruction and generation of several Roman houses from the heritage site of Conimbriga, Portugal.
- A review on the use of additive manufacturing to produce lower limb orthosesPublication . Alqahtani, Mohammed S.; Al-Tamimi, Abdulsalam; Almeida, Henrique; Cooper, Glen; Bartolo, PauloOrthoses (exoskeletons and fracture fixation devices) enhance users’ ability to function and improve their quality of life by supporting alignment correction, restoring mobility, providing protection, immobilisation and stabilisation. Ideally, these devices should be personalised to each patient to improve comfort and performance. Production costs have been one of the main constraints for the production of personalised orthoses. However, customisation and personalisation of orthoses are now possible through the use of additive manufacturing. This paper presents the current state of the art of additive manufacturing for the fabrication of orthoses, providing several examples, and discusses key research challenges to be addressed to further develop this field.