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arXiv 2025年

作者： Cardoso, Fabio Matos, Sérgio Pessoa, Luís M. Alexandropoulos, George C. Department of Information Science and Technology University Institute of Lisbon Portugal Instituto de Telecomunicações Portugal INESC TEC Portugal Faculty of Engineering University of Porto Portugal Department of Informatics and Telecommunications National and Kapodistrian University of Athens Greece Department of Electrical and Computer Engineering University of Illinois Chicago IL United States

The technology of Reconfigurable Intelligent Surfaces (RISs) is lately being considered as a boosting component for various indoor wireless applications, enabling wave propagation control and coverage extension. However, the incorporation of extremely large RISs, as recently being considered for ultrahigh capacity industrial environments at subTHz frequencies, imposes certain challenges for indoor channel characterization. In particular, such RISs contribute additional multipath components and their large sizes with respect to the signal wavelength lead to near-field propagation. To this end, ray tracing approaches become quite cumbersome and need to be rerun for different RIS unit cell designs. In this paper, we present a novel approach for the incorporation of RISs in indoor multipath environments towards their efficient channel characterization. An 100×100 RIS design with 2-bit resolution unit cells realizing a fixed anomalous reflection at 300 GHz is presented, whose radar cross section patterns are obtained via full-wave simulations. It is showcased that the RIS behavior can be conveniently approximated by a three-ray model, which can be efficiently incorporated within available ray tracing tools, and that the far-field approximation is valid for even very small distances from the RIS. © 2025, CC BY-NC-ND.

关键词： Radar reflection

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Evaluating YOLO Models for Grape Moth Detection in Insect Traps

Evaluating YOLO Models for Grape Moth Detection in Insect Tr...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Ana Cláudia Teixeira Gabriel Carneiro Raul Morais Joaquim J. Sousa António Cunha University of Trás-os-Montes and Alto Douro Vila Real Portugal Institute for Systems and Computer Engineering Technology and Science (INESC TEC) Porto Portugal Centre for the Research and Technology of Agro-Environmental and Biological Sciences University of Trás-os-Montes e Alto Douro Vila Real Portugal

The grape moth is a common pest that affects grapevines by consuming both fruit and foliage, rendering grapes deformed and unsellable. Integrated pest management for the grape moth heavily relies on pheromone traps, which serve a crucial function by identifying and tracking adult moth populations. This information is then used to determine the most appropriate time and method for implementing other control techniques. This study aims to find the best method for detecting small insects. We evaluate the following recent YOLO models: v5, v6, v7, and v8 for detecting and counting grape moths in insect traps. The best performance was achieved by YOLOv8, with an average precision of 92.4% and a counting error of 8.1%.

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Chest Radiography Few-Shot Image Synthesis for Automated Pathology Screening Applications

Chest Radiography Few-Shot Image Synthesis for Automated Pat...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Martim Quintas E Sousa João Pedrosa Joana Rocha Sofia Cardoso Pereira Ana Maria Mendonça Aurélio Campilho Institute for Systems and Computer Engineering Technology and Science (INESC TEC) Porto Portugal Faculty of Engineering University of Porto (FEUP) Porto Portugal

ISBN: (纸本)9781665429825

Chest radiography is one of the most ubiquitous imaging modalities, playing an essential role in screening, diagnosis and disease management. However, chest radiography interpretation is a time-consuming and complex task, requiring the availability of experienced radiologists. As such, automated diagnosis systems for pathology detection have been proposed aiming to reduce the burden on radiologists and reduce variability in image interpretation. While promising results have been obtained, particularly since the advent of deep learning, there are significant limitations in the developed solutions, namely the lack of representative data for less frequent pathologies and the learning of biases from the training data, such as patient position, medical devices and other markers as proxies for certain pathologies. The lack of explainability is also a challenge for the adoption of these solutions in clinical *** adversarial networks could play a significant role as a solution for these challenges as they allow to artificially create new realistic images. This way, new synthetic chest radiography images could be used to increase the prevalence of less represented pathology classes and decrease model biases as well as improving the explainability of automatic decisions by generating samples that serve as examples or counter-examples to the image being analysed, ensuring patient *** this study, a few-shot generative adversarial network is used to generate synthetic chest radiography images. A minimum Fréchet Inception Distance score of 17.83 was obtained, allowing to generate convincing synthetic images. Perceptual validation was then performed by asking multiple readers to classify a mixed set of synthetic and real images. An average accuracy of 83.5% was obtained but a strong dependency on reader experience level was observed. While synthetic images showed structural irregularities, the overall image sharpness was a major factor in the decision of rea

关键词： Training Pathology Privacy Medical devices Image synthesis Training data Detectors

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An Energy-Aware RIoT System: Analysis, Modeling and Prediction in the SUPERIOT Framework

arXiv

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arXiv 2025年

作者： Bocus, Mohammud J. Häkkinen, Juha Fontes, Hélder Drzewiecki, Marcin Qiu, Senhui Eder, Kerstin Piechocki, Robert School of Computer Science University of Bristol Bristol United Kingdom Circuits and Systems Research Unit University of Oulu Oulu Finland MpicoSys Embedded Pico Systems Sp. z o. o. Gdynia Poland Faculty of Electrical and Control Engineering Gdańsk University of Technology Gdansk Poland INESC TEC Porto Portugal Faculty of Engineering University of Porto Porto Portugal

his paper presents a comprehensive analysis of the energy consumption characteristics of a Silicon (Si)-based Reconfigurable IoT (RIoT) node developed in the initial phase of the SUPERIOT project, focusing on key operating states, including Bluetooth Low Energy (BLE) communication, Narrow-Band Visible Light Communication (NBVLC), sensing, and E-ink display. Extensive measurements were conducted to establish a detailed energy profile, which serves as a benchmark for evaluating the effectiveness of subsequent optimizations and future node iterations. To minimize the energy consumption, multiple optimizations were implemented at both the software and hardware levels, achieving a reduction of over 60% in total energy usage through software modifications alone. Further improvements were realized by optimizing the E-ink display driving waveform and implementing a very low-power mode for non-communication activities. Based on the measured data, three measurement-based energy consumption models were developed to characterize the energy behavior of the node under: (i) normal, unoptimized operation, (ii) low-power, software-optimized operation, and (iii) very low-power, hardware-optimized operation. These models, validated with new measurement data, achieved an accuracy exceeding 97%, confirming their reliability for predicting energy consumption in diverse configurations. © 2025, CC BY.

关键词： Digital storage

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Characterization of an Hollow Core PCF for Endoscopy Applications: A Proof Concept

Characterization of an Hollow Core PCF for Endoscopy Applica...

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Telecoms Conference (ConfTELE)

作者： João Marques Susana Novais Susana Silva Orlando Frazão Faculty of Sciences of University of Porto Porto Portugal INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal

Two distinct optical fibers for endoscope-based configurations are demonstrated and studied in this work. The fibers used for the experiment consist of: a conventional single-mode fiber (SMF 28e) and a hollow core photonic crystal fiber (HC-PCF) based on silica. Two studies that allowed the characterization of these fibers, according to their optical output power and when subjected to curvature, were carried out. The intensity power profile was also analysed in relation to the propagation distance, transversal displacement and incidence angle. After this study it can be concluded that the most suitable solution for the endoscope is the HC-PCF fiber working as a transmission probe. For the proof of concept of the fiber-based endoscope, a cleaved multimode fiber (MMF) tip was used as a reception probe and its reflection efficiency was also analysed.

关键词： Optical fibers Silicon compounds Power measurement Endoscopes Displacement measurement Reflection Telecommunications

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An automL-based approach to multimodal image sentiment analysis

arXiv

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arXiv 2021年

作者： Ferrinho, Vasco Lopes Gaspar, António Alexandre, Luís A. Cordeiro, João NOVA LINCS Universidade da Beira Interior Portugal LIAAD INESC TEC – Institute for Systems and Computer Engineering Technology and Science Portugal

Sentiment analysis is a research topic focused on analysing data to extract information related to the sentiment that it causes. Applications of sentiment analysis are wide, ranging from recommendation systems, and marketing to customer satisfaction. Recent approaches evaluate textual content using Machine Learning techniques that are trained over large corpora. However, as social media grown, other data types emerged in large quantities, such as images. Sentiment analysis in images has shown to be a valuable complement to textual data since it enables the inference of the underlying message polarity by creating context and connections. Multimodal sentiment analysis approaches intend to leverage information of both textual and image content to perform an evaluation. Despite recent advances, current solutions still flounder in combining both image and textual information to classify social media data, mainly due to subjectivity, inter-class homogeneity and fusion data differences. In this paper, we propose a method that combines both textual and image individual sentiment analysis into a final fused classification based on AutoML, that performs a random search to find the best model. Our method achieved state-of-the-art performance in the B-T4SA dataset, with 95.19% accuracy. © 2021, CC BY.

关键词： Sentiment analysis

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A Data logger for educational purposes of a laboratory chemical reactor: an IoT approach

A Data logger for educational purposes of a laboratory chemi...

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Electrical, computer, Communications and Mechatronics engineering (ICECCME), International Conference on

作者： José Lima Thadeu Brito Olga Ferreira Maria J. Afonso Vítor H. Pinto José A. Carvalho Paulo Costa Research Centre in Digitalization and Intelligent Robotics (CeDRI) Instituto Politécnico de Bragança Bragança Portugal Laboratório Para a Sustentabilidade e Tecnologia em Regiões de Montanha (SusTEC) Instituto Politécnico de Bragança Bragança Portugal Centre for Robotic in Industry and Intelligent Systems Institute for Systems and Computer Engineering Technology and Science (INESC-TEC) Porto Portugal CeDRI SusTEC INESC-TEC Faculty of Engineering of University of Porto (FEUP) Porto Portugal SusTEC ESTiG Instituto Politécnico de Bragança Bragança Portugal ARISE & ECE Dept. Research Center for Systems and Technologies (SYSTEC) FEUP CeDRI SusTEC INESC-TEC FEUP

This paper presents the development of an acquisition system and data logger from an existing set of three continuous stirred-tank reactors in series. The reactors are currently used in chemical engineering educational laboratories to perform kinetic and tracer experiments. In this sense, to accomplish the store data process, the volumetric flow rate and the concentration of tracer, reactants and/or products of the reaction must be acquired as a function of time. In the original experimental setup, only the signal conditioning system was operational, while the acquisition, visualization, and control systems were obsolete and damaged. Thus, a new system composed of an interface and real-time acquisition data is proposed alongside preserving the main reactor structure. A graphical user interface and the automation of the various actuators were developed based on worldwide usage and low cost, respectively. This system, based on a common 8-bit microcontroller and an application developed in Lazarus, allows the storage of the acquired data in a time-series database. In this way, students can analyze the results later or in real time. Moreover, remote access allows controlling the reactor and getting data by the Internet of Things (IoT) resources. Additionally, the proposed system using IoT allows data to be shared with the community as a dataset.

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Floating Music Score: System Design

Floating Music Score: System Design

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International Conference on Computational science and its Applications (ICCSA)

作者： Gilberto Ferreira Marisa Pinheiro J. C. Silva School of Technology Polytechnic Institute of Cávado and Ave Barcelos Portugal INESC TEC Institute for Systems and Computer Engineering Porto Portugal 2Ai - School of Technology Polytechnic Institute of Cávado and Ave Barcelos Portugal

This paper aims to describe an approach to create a useful and effective solution to facilitate the reading of musical scores during the performance or study of pieces, using the aid of Mixed Reality (MR), mobile devices, digital scores, and Data Musical Instrument Digital Interface (MIDI). MR can be defined as a system that combines physical objects with virtual objects. MIDI is a digital file containing musical notation information that can be interpreted by electronic devices. In this project, we aim to use HoloLens glasses and mobile devices, such as tablets or smartphones. The HoloLens are devices that can be used to create realistic holograms to visually represent the scores. The use of the various devices is intended to make the performance easier. The proposed approach aims to interpret scores in MIDI format and present them in hologram format to the MR glasses and graphical format to the mobile devices. In parallel, the system should be able to synchronize the presentation between different devices.

关键词： Performance evaluation Scientific computing Instruments Virtual reality Glass Software Synchronization

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Tuning bimetallic Au@Ag nanorods Localized Surface Plasmon Resonance on side-polished optical fiber sensing configurations at near-infrared wavelengths

Tuning bimetallic Au@Ag nanorods Localized Surface Plasmon R...

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Optical Sensors 2023

作者： dos Santos, Paulo S.S. Mendes, João de Almeida, José M.M.M. Pastoriza-Santos, Isabel Coelho, Luís C.C. INESC TEC Institute for Systems and Computer Engineering Technology and Science Rua Dr. Roberto Frias Porto4200-465 Portugal Faculty of Engineering University of Porto Rua Dr. Roberto Frias Porto4200-465 Portugal Department of Physics School of Science and Technology University of Trás-os-Montes e Alto Douro Vila Real5001-801 Portugal CINBIO Universidad de Vigo Campus Universitario Lagoas Marcosende Vigo36310 Spain Vigo36312 Spain FCUP University of Porto Rua do Campo Alegre Porto4169-007 Portugal CIQUP Chemistry Research Unit FCUP Univ. of Porto Porto4169-007 Portugal

ISBN: (数字)9781510662650

ISBN: (纸本)9781510662643

The increasing demand for precise chemical and biological sensing has led to the development of highly efficient plasmonic optical fiber sensors. Therefore, it is essential to optimize and match the operating wavelength region of both the optical fiber configuration and localized surface plasmon resonance of nanoparticles (NPs). This can be achieved by developing NPs that can reach resonance at near-infrared wavelengths, where refractive index sensitivity is enhanced, and silica optical fibers have lower losses. High aspect-ratio bimetallic Au@Ag nanorods and different side-polished fiber structures are tested using numerical simulations. The selected optical fiber configuration was based on a side-polished fiber with a 1 mm polished section. It is compared power losses and power at the NP interface for two configurations: a step-index single-mode fiber (SMF) with core/cladding diameters of 8.2/125 µm and a multimode graded-index fiber (GIF) with 62.5/125 µm at various polishing depths. The results showed that the best performance for both configurations was achieved at similar polishing depths, namely 59.5 and 55.2 µm for the SMF and GIF, respectively. The optical impact of retardation effects due to the proximity with the fiber structure were also observed, which caused a reduction in sensitivity from 1750 nm/RIU to 1500 nm/RIU and a red-shift of around 70 nm. © 2023 SPIE.

关键词： Single mode fibers

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State-of-the-art AI-based Learning Approaches for Deepfake Generation and Detection, Analyzing Opportunities, Threading through Pros, Cons, and Future Prospects

arXiv

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arXiv 2025年

作者： Goyal, Harshika Wajid, Mohammad Saif Wajid, Mohd Anas Khanday, Akib Mohi Ud Din Neshat, Mehdi Gandomi, Amir Indian Institute of Technology Kharagpur India Department of Computer Science and Intelligent Systems Tecnológico de Monterrey Monterrey Mexico Institute for the Future of Education TEC de Monterrey Monterrey Mexico Department of Computer Science and Software Engineering United Arab Emirates University Al Ain Abu Dhabi United Arab Emirates Department of Computer Science Samarkand International University of Technology Samarkand Uzbekistan Faculty of Engineering and Information Technology University of Technology Sydney Ultimo SydneyNSW2007 Australia Obuda University Budapest1034 Hungary School of Computer and Mathematical Sciences University of Adelaide Adelaide5005 Australia

The rapid expansion and advancement of deepfake technology, which is specifically designed to create incredibly lifelike facial imagery and video content, has ignited a remarkable level of interest and curiosity across a multitude of fields, including but not limited to the realms of the entertainment industry, forensic analysis, cybersecurity and the innovative creation of digital characters. By harnessing the latest breakthroughs in deep learning methodologies, especially through the implementation of techniques such as Generative Adversarial Networks, Variational Autoencoders, Few-Shot Learning Strategies, and Transformer Neural Networks, the outcomes achieved in the generation of deepfakes have been nothing short of astounding and transformative. Furthermore, the recent advancements in diffusion models have served to invigorate and catalyze ongoing research efforts in this fascinating domain. At the same time, the ongoing evolution of detection technologies is being developed to counteract the potential for misuse associated with deepfakes, effectively addressing critical concerns that range from political manipulation to the dissemination of fake news and the ever-growing issue of cyberbullying. This comprehensive review paper meticulously investigates the most recent developments in both deepfake generation and detection, including around 400 publications, providing an in-depth analysis of the cutting-edge innovations that are shaping this rapidly evolving landscape. Starting with a thorough examination of systematic literature review methodologies, we embark on a journey that delves into the complex technical intricacies inherent in the various techniques used for deepfake generation, comprehensively addressing the challenges faced, potential solutions available, and the nuanced details surrounding manipulation formulations. Besides, task definitions are standardized to ensure clarity, while datasets and metrics are diligently introduced, paving the way for a

关键词： Generative adversarial networks

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