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International Journal of Interactive Mobile Technologies 2024年第13期18卷 112-129页

作者： Corrêa, Ana Grasielle Dionísio Ravaglio, Anna de Souza Cruz Navikas, Flávio Hergersheimer Do Amaral, Jucelio Delmondes Filho, Paulo César Machado Cunha, Daniela Vieira Silva, Matheus Gois de Lima Rodrigues, Bruno da Silva Faculty of Computing and Informatics and the Postgraduate Program in Applied Computing Mackenzie Presbiterian University São Paulo Brazil

Peripheral facial paralysis (PFP) causes deficits in muscle and sensory functions of the face due to damage to the facial nerve. In this study, we evaluated the effectiveness of the "Fisiobem" app in rehabilitating patients with PFP through facial mimicry exercises. The app uses the device’s camera to identify the user and measure the range of motion during the exercises, applying the ARKit framework to quantify the intensity of the movements. We conducted a usability study with 34 participants unaffected by PFP, performing mimics with different amplitudes. Results show that glasses did not affect recognition accuracy in exercises such as raising eyebrows, frowning, and closing the eyes tightly. As for wrinkling the nose exercise, glasses impacted higher intensities. As for the beard or mustache, lower lip protrusion, compressing the lips, smiling, showing teeth and blowing out filling cheeks were not affected. However, when smiling with lips together, beard and mustache influenced intensities above 75%. It is important to highlight that this study has limitations, such as the sample size and lack of consideration for ethnic diversity among participants. Future research with larger and more diverse samples is needed to validate and generalize these findings and explore the nuances of interactions between facial features and facial recognition algorithms. Despite these limitations, the approach facilitated by the "Fisiobem" application offers significant benefits, especially for patients with PFP who face challenges in accessing specialized therapists. It allows patients to complement their treatment by performing guided facial mimicry exercises at home. The application helps individuals accurately perform the exercises and effectively track the progress of their rehabilitation. © 2024 by the authors of this article.

关键词： Glass

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An Improved Approach for Semantic Segmentation of Fundus Lesions using R2U-Net 46

An Improved Approach for Semantic Segmentation of Fundus Les...

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46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Pereira, Alejandro Santos, Carlos Aguiar, Marilton Welfer, Daniel Dias, Marcelo De Menezes, Rafaela Ferreira, Paulo Roberto Rossi, Fábio D'Ornellas, Marcos Haygert, Carlos Jesus Kazienko, Juliano Comim, Fabio Hoppe, Aurélio Weber, Juliano Tavares, Leandro Guths, Leonardo Guerra, Rodrigo Federal University of Pelotas - UFPel Postgraduate Program in Computing Pelotas Brazil Science and Technology Farroupilha - IFFar Federal Institute of Education Alegrete Brazil Federal University of Santa Maria - Ufsm Department of Applied Computing Santa Maria Brazil Federal University of Santa Maria - Ufsm Department of Clinical Medicine Santa Maria Brazil Federal University of Santa Maria - Ufsm Industrial Technical College Santa Maria Brazil Federal University of Minas Gerais - Ufmg Department of Clinical Medicine Belo Horizonte Brazil Regional University of Blumenau - Furb Department of Information Systems and Computing Blumenau Brazil Science and Technology Farroupilha - IFFar Federal Institute of Education Santo Ângelo Brazil Federal University of Rio Grande do Sul - Ufrgs Postgraduate Program in Computing Porto Alegre Brazil Federal University of Rio Grande - Furg Center of Computational Sciences Rio Grande Brazil

ISBN: (纸本)9798350371499

Diabetic Retinopathy (DR) is a microvascular complication related to diabetes that affects approximately 33% of individuals with this condition and, if not detected and treated early, can lead to irreversible vision loss. Fundus lesions such as Hard and Soft Exudates, Hemorrhages, and Microaneurysms typically identify DR. The development of computational methods to segment these lesions plays a fundamental role in the early diagnosis of the disease. This paper proposes a new approach that uses an R2U-Net combined with data augmentation techniques for segmenting fundus lesions. We trained, adjusted, and evaluated the proposed work in the DDR dataset, achieving an accuracy of 99.87% and a mean Intersection over Union (mIoU) equal 59.69%. Furthermore, we assessed it in the IDRiD dataset, achieving an mIoU of 49.92%. The results obtained in the experiments highlight the potential contribution of the model in the lesion annotations for creating new DR datasets, which is essential given the scarcity of annotations in publicly available datasets. © 2024 IEEE.

关键词： Semantic Segmentation

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Low Complexity Broadband Array Processing in Dynamic Scenarios with Jamming

Low Complexity Broadband Array Processing in Dynamic Scenari...

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IEEE Conference on Vehicular Technology (VTC)

作者： Daniel V. De Lima João Paulo J. Da Costa Ricardo K. Miranda Antonio Arlis S. Da Silva Giovanni A. Santos José Alfredo R. Vargas Auzuir R. De Alexandria Postgraduate Program in Telecommunications Engineering (PPGET) IFCE Fortaleza Brazil Hamm-Lippstadt University of Applied Sciences (HSHL) Lippstadt Germany Graduate School for Applied Research in North Rhine-Westphalia (PKNRW) Bochum Germany Karlsruhe Institute of Technology (KIT) Karlsruhe Germany Graduate Program in Computing (PPGC) UFRGS Porto Alegre Brazil Postgraduate Program in Mechatronics Engineering (PPMEC) UnB Brasilia Brazil

ISBN: (数字)9798350387414

ISBN: (纸本)9798350387421

Vehicle-to-Everything (V2X) networks require low-latency communications utilizing a broad spectrum while operating under jamming. In this sense, low complexity antenna array-based broadband jamming mitigation schemes are crucial in order to allow low latency communication and low-cost hardware. In this paper we propose low-complexity algorithms for signal recovery in broadband processing scenario applied to V2X. Numerical simulation of a jamming scenario demonstrate the proposed algorithm achieving the same performance in terms of signal-to-interference plus noise ratio (SINR) as the state-of-the-art while taking signiflcantly less time to compute.

关键词： Heuristic algorithms Prevention and mitigation Interference Numerical simulation Broadband communication Broadband antennas Jamming

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Broadband Beamforming via Frequency Invariance Transformation and PARAFAC Decomposition for Jamming Mitigation in V2X Scenarios

Broadband Beamforming via Frequency Invariance Transformatio...

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IEEE Conference on Vehicular Technology (VTC)

作者： Daniel V. de Lima João Paulo J. da Costa Antonio Arlis S. da Silva Giovanni A. Santos José Alfredo R. Vargas Auzuir R. de Alexandria Postgraduate Program in Telecommunications Engineering (PPGET) IFCE Fortaleza Brazil Hamm-Lippstadt University of Applied Sciences (HSHL) Lippstadt Germany Graduate School for Applied Research in North Rhine-Westphalia (PKNRW) Bochum Germany Karlsruhe Institute of Technology (KIT) Karlsruhe Gennany Graduate Program in Computing (PPGC) UFRGS Porto Alegre Brazil Department of Electrical Engineering UnB Brasilia Brazil

ISBN: (数字)9798350387414

ISBN: (纸本)9798350387421

Vehicle-to-Everything (V2X) communication can considerably improve the efficiency and safety of autonomous driving and advanced driver-assistance systems (ADASs). However, V2X communication can be considerably degraded in the presence of cyberattacks, such as radio jamming. Traditionally, beamforming techniques can be applied to increase the signal-to-interference plus noise ratio (SINR). This paper evaluates broadband beamforming in the mmWave spectrum against radio jamming in V2X communication. The exploitation of the mm Wave spectrum in 5G-V2X communication has a natural advantage against radio jamming. First, attenuation is stronger in the mmWave spectrum in the range of 40 GHz or higher than in the traditional 5.9 GHz. Second, to generate broadband radio jamming, the radio jammer requires much more complex hardware and energy consumption. Third, by using broadband beamforming, broadband radio jamming can be considerably attenuated, limiting the degradation of the spectrum by the radio jamming. According to our numerical results, gains of close to 30 dB SINR can be achieved. We propose a broad-band beamforming technique based on the canonical polyadic decomposition via generalized eigenvalue decomposition (CPD-GEVD). The CPD-GEVD broadband beamforming outperforms state-of-the-art beamforming algorithms in most V2X scenarios presented in this paper.

关键词： Vehicular and wireless technologies Array signal processing Interference Attenuation Broadband communication Jamming Millimeter wave communication

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Detection of retinal microlesions through YOLOR-CSP architecture and image slicing with the SAHI algorithm

Detection of retinal microlesions through YOLOR-CSP architec...

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International Joint Conference on Neural Networks (IJCNN)

作者： Alejandro Pereira Carlos Santos Marilton Aguiar Daniel Welfer Marcelo Dias Marcelo Ribeiro Reza Ahmadi Computer Science Federal University of Pelotas - UFPel Pelotas Brazil Federal Institute of Education Science and Technology Farroupilha - IFFar Alegrete Brazil Postgraduate Program in Computing Federal University of Pelotas - UFPel Pelotas Brazil Department of Applied Computing Federal University of Santa Maria - UFSM Santa Maria Brazil Geobotica Brisbane Australia

Diabetic retinopathy affects millions of working-age people worldwide. Of the countries in Latin America, Brazil has the highest incidence of cases. Diabetic retinopathy is detected through images of the fundus that contain lesions such as hard exudates, soft exudates, microaneurysms, and hemorrhages. Early identification of these lesions prevents the progression of the disease, which leads to a decrease in visual capacity. In addition, the early identification of these lesions allows the screening of patients who need priority care. The detection of these lesions occurs through the processing and analysis of fundus images using deep learning models. In this work, we present a new method that uses the You Only Learn One Representation with Cross Stage Partial Network (YOLOR-CSP) architecture combined with the Slicing Aided Hyper Inference (SAHI) framework to detect lesions. The proposed method was trained, adjusted, and evaluated using the Dataset for Diabetic Retinopathy (DDR) and the Indian Diabetic Retinopathy Image Dataset (IDRiD). The proposed method obtained in the data set DDR mAP equal to 38.08%, in the validation set, and 22.25% in the test set with SGD optimizer. The presented results were superior in the detection of eye fundus lesions in comparison with similar works found in the state-of-the-art literature.

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An Improved Approach for Semantic Segmentation of Fundus Lesions using R2U-Net

An Improved Approach for Semantic Segmentation of Fundus Les...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Alejandro Pereira Carlos Santos Marilton Aguiar Daniel Welfer Marcelo Dias Rafaela de Menezes Paulo Roberto Ferreira Fábio Rossi Marcos d’Ornellas Carlos Jesus Haygert Juliano Kazienko Fábio Comim Aurélio Hoppe Juliano Weber Leandro Tavares Leonardo Guths Rodrigo Guerra Postgraduate Program in Computing Federal University of Pelotas - UFPel Pelotas Brazil Federal Institute of Education Science and Technology Farroupilha - IFFar Alegrete Brazil Department of Applied Computing Federal University of Santa Maria - UFSM Santa Maria Brazil Department of Clinical Medicine Federal University of Santa Maria - UFSM Santa Maria Brazil Industrial Technical College Federal University of Santa Maria - UFSM Santa Maria Brazil Department of Clinical Medicine Federal University of Minas Gerais - UFMG Belo Horizonte Brazil Department of Information Systems and Computing Regional University of Blumenau - FURB Blumenau Brazil Federal Institute of Education Science and Technology Farroupilha - IFFar Santo Ângelo Brazil Postgraduate Program in Computing Federal University of Rio Grande do Sul - UFRGS Porto Alegre Brazil Center of Computational Sciences Federal University of Rio Grande - FURG Rio Grande Brazil

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

关键词： Measurement Diabetic retinopathy Accuracy Annotations Semantic segmentation Feature extraction Data augmentation Data models Lesions Hemorrhaging

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A New Method Based on Deep Learning to Detect Lesions in Retinal Images using YOLOv5

A New Method Based on Deep Learning to Detect Lesions in Ret...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Carlos Santos Marilton Aguiar Daniel Welfer Bruno Belloni Federal Institute of Education Science and Technology Farroupilha Alegrete Brazil Postgraduate Program in Computing (PPGC) Federal University of Pelotas Pelotas Brazil Departament of Applied Computing Federal University of Santa Maria Santa Maria Brazil Federal Institute of Education Science and Technology Sul-Rio-Grandense Passo Fundo Brazil

ISBN: (纸本)9781665429825

Diabetic Retinopathy is one of the leading causes of vision loss and presents in its initial phase retinal lesions, such as microaneurysms, hemorrhages, and hard and soft exudates. Therefore, computational models capable of detecting these lesions can help in the early diagnosis of the disease and prevent the manifestation of more severe forms of lesions, helping define the best form of treatment. This work proposes a method based on deep neural network models that perform one-stage object detection, using state-of-the-art data augmentation and transfer learning techniques to present a model that aids in the medical diagnosis of fundus lesions. The model was trained, adjusted, and evaluated using the DDR Diabetic Retinopathy Dataset, and implemented based on the YOLOv5 architecture and the PyTorch framework, achieving values for mAP of 0.1040 and 0.0283 for IoU threshold of 0.5 and 0.5:0.95 respectively, in the validation set. The results obtained in the experiments demonstrate that the proposed method presented superior results to equivalent works found in the literature.

关键词： Deep learning Training Retinopathy Neural networks Computer architecture Retina Data models

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Blended learning and media centers: A bibliometric analysis

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Social Sciences and Humanities Open 2024年 10卷

作者： Challco, Geiser Chalco Silva, Wesley Vieira da Setton Gonçalves, Bruno de Almeida Levino, Natallya Bittencourt, Ibsen Mateus Kaczam, Fabíola de Oliveira, Elaine Harada Teixeira Martins, Flavio Pinheiro de Lima Filho, Walter Araujo de Araújo, Ronaldo Ferreira Bittencourt, Ig Ibert Paiva, Ranilson Oscar Araújo Department of Engineering and Technology (DETEC) Federal Rural University of Semi-Árido (UFERSA) RN Pau dos Ferros 59900-000 Brazil Scholarship CNPq Research Productivity (D Level) and Professor Faculty of Economics Administration and Accounting Federal University of Alagoas (UFAL) Maceió 57072-900 Brazil Faculty of Economics Administration and Accounting Federal University of Alagoas (UFAL) Maceió 57072-900 Brazil Leader of the Laboratory of Applied Public Administration (LAPA) of the Public Administration Course Campus Arapirca Federal University of Alagoas Arapiraca 57309-005 Brazil Faculty of Economics Business and Accounting Federal University of Alagoas Maceio 57072-900 Brazil Postgraduate Program in Administration Federal University Santa Maria (UFSM) Building 74C 2nd floor Room 4209 97105-900 Brazil Institute of Computing Federal University of Amazonas Amazonas Manaus Brazil The Bartlett School of Sustainable Construction University College London—UCL London WC1E 6BT United Kingdom Visiting Researcher at Leiden University ou Pesquisador Visitante na Universidade de Leiden Institute of Human Sciences Communication and Arts Federal University of Alagoas Alagoas Maceio 57072-900 Brazil Harvard Graduate School of Education Harvard University Cambridge MA United States Center of Excellence for Social Technologies Federal University of Alagoas Brazil Universidade Federal de Alagoas - Instituto de Computação Brazil

Blended learning can be considered an approach that combines face-to-face and online periods in education through the integration of some technological resources, such as media centers. The present research sought to investigate the panorama of scientific production on blended learning and identify evidence of how media centers are used to support this type of teaching. This is a bibliometric study carried out based on the principles of the Systematic Literature Review (SLR). Although the results indicate an increase in production, a high rate of authors with only one published work was identified, which can be interpreted as an expanding topic. The United States stood out as the country that contributed the most with research and the areas of Computer Science and Education among the fields of research with the highest number of articles. © 2024 The Author(s)

关键词： Blended learning Hybrid education Media centers Systematic review

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FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

arXiv

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arXiv 2023年

作者： Lekadir, Karim Feragen, Aasa Fofanah, Abdul Joseph Frangi, Alejandro F. Buyx, Alena Emelie, Anais Lara, Andrea Porras, Antonio R. Chan, An-Wen Navarro, Arcadi Glocker, Ben Botwe, Benard O. Khanal, Bishesh Beger, Brigit Wu, Carol C. Cintas, Celia Langlotz, Curtis P. Rueckert, Daniel Mzurikwao, Deogratias Fotiadis, Dimitrios I. Zhussupov, Doszhan Ferrante, Enzo Meijering, Erik Weicken, Eva González, Fabio A. Asselbergs, Folkert W. Prior, Fred Krestin, Gabriel P. Collins, Gary S. Tegenaw, Geletaw S. Kaissis, Georgios Misuraca, Gianluca Tsakou, Gianna Dwivedi, Girish Kondylakis, Haridimos Jayakody, Harsha Woodruf, Henry C. Mayer, Horst Joachim Aerts, Hugo JWL Walsh, Ian Chouvarda, Ioanna Buvat, Irène Tributsch, Isabell Rekik, Islem Duncan, James Kalpathy-Cramer, Jayashree Zahir, Jihad Park, Jinah Mongan, John Gichoya, Judy W. Schnabel, Julia A. Kushibar, Kaisar Riklund, Katrine Mori, Kensaku Marias, Kostas Amugongo, Lameck M. Fromont, Lauren A. Maier-Hein, Lena Alberich, Leonor Cerdá Rittner, Leticia Phiri, Lighton Marrakchi-Kacem, Linda Donoso-Bach, Lluís Martí-Bonmatí, Luis Cardoso, M. Jorge Bobowicz, Maciej Shabani, Mahsa Tsiknakis, Manolis Zuluaga, Maria A. Bielikova, Maria Fritzsche, Marie-Christine Camacho, Marina Linguraru, Marius George Wenzel, Markus De Bruijne, Marleen Tolsgaard, Martin G. Ghassemi, Marzyeh Ashrafuzzaman, Md Goisauf, Melanie Yaqub, Mohammad Abadía, Mónica Cano Mahmoud, Mukhtar M.E. Elattar, Mustafa Rieke, Nicola Papanikolaou, Nikolaos Lazrak, Noussair Díaz, Oliver Salvado, Olivier Pujol, Oriol Sall, Ousmane Guevara, Pamela Gordebeke, Peter Lambin, Philippe Brown, Pieta Abolmaesumi, Purang Dou, Qi Lu, Qinghua Osuala, Richard Nakasi, Rose Zhou, S. Kevin Napel, Sandy Colantonio, Sara Albarqouni, Shadi Joshi, Smriti Carter, Stacy Klein, Stefan Petersen, Steffen E. Aussó, Susanna Awate, Suyash Raviv, Tammy Riklin Cook, Tessa Mutsvangwa, Tinashe E.M. Rogers, Wendy A. Niessen, Wiro J. Puig-Bosch, Xènia Zeng, Yi Mohammed, Yunusa G. Aquino, Yves Saint James Salahuddin, Zohaib Starmans, Martijn P.A. Department de Matemàtiques i Informàtica Universitat de Barcelona Barcelona Spain Barcelona Spain DTU Compute Technical University of Denmark Kgs Lyngby Denmark Department of Mathematics and Computer Science Faculty of Science and Technology Milton Margai Technical University Freetown Sierra Leone Center for Computational Imaging & Simulation Technologies in Biomedicine Schools of Computing and Medicine University of Leeds Leeds United Kingdom Cardiovascular Science and Electronic Engineering Departments KU Leuven Leuven Belgium Institute of History and Ethics in Medicine Technical University of Munich Munich Germany Faculty of Engineering of Systems Informatics and Sciences of Computing Galileo University Guatemala City Guatemala Department of Biostatistics and Informatics Colorado School of Public Health University of Colorado Anschutz Medical Campus AuroraCO United States Department of Medicine Women’s College Research Institute University of Toronto Toronto Canada Universitat Pompeu Fabra BarcelonaBeta Brain Research Center Barcelona Spain Department of Computing Imperial College London London United Kingdom School of Biomedical & Allied Health Sciences University of Ghana Accra Ghana Department of Midwifery & Radiography School of Health & Psychological Sciences City University of London United Kingdom Kathmandu Nepal European Heart Network Brussels Belgium Department of Thoracic Imaging University of Texas MD Anderson Cancer Center Houston United States IBM Research Africa Nairobi Kenya Departments of Radiology Medicine and Biomedical Data Science Stanford University School of Medicine Stanford United States Institute for AI and Informatics in Medicine Klinikum rechts der Isar Technical University Munich Munich Germany Department of Computing Imperial College London London United Kingdom Muhimbili University of Health and Allied Sciences Dar es Salaam Tanzania United Republic of Ioannina Greece Almaty AI Lab Almaty Kazakhstan

Background: Despite major advances in artificial intelligence (AI) research for healthcare, the deployment and adoption of AI technologies remain limited in clinical practice. In recent years, concerns have been raised about the clinical, technical, ethical and legal risks associated with healthcare AI. To increase adoption in the real world, it is essential that AI technologies are trusted and accepted by patients, clinicians, health organisations and authorities. This paper describes the FUTURE-AI framework as the first international consensus guideline for trustworthy AI in healthcare. Methods: The FUTURE-AI consortium was founded in 2021 and now comprises 117 interdisciplinary experts from 50 countries representing all continents, including AI scientists, clinical researchers, biomedical ethicists, and social scientists. Over a two-year period, the consortium established guiding principles and best practices for trustworthy and deployable AI through an iterative process comprising an in-depth literature review, a modified Delphi survey, and online consensus meetings. Findings: The FUTURE-AI framework was established based on six guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 30 best practices were defined, addressing technical, clinical, socio-ethical and legal dimensions of trustworthy AI. The recommendations cover the entire lifecycle of healthcare AI, from design, development and validation to regulation, deployment, and monitoring. Interpretation: FUTURE-AI is a structured, risk-informed framework which provides guidance for constructing healthcare AI tools that will be trusted, deployed and adopted in real-world clinical practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of healthcare AI. Copyright © 2023, The Authors. All rights

关键词： Clinical research

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Concerns and limitations in agile software development: A survey with Paraguayan companies

arXiv

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arXiv 2017年

作者： Salinas, Myrian R. N. Neto, Adolfo Gustavo Serra Seca Emer, Maria Claudia F. P. Postgraduate Program in Applied Computing Academic Department of Informatics Federal University of Technology Parana Brazil

This year, the Agile Manifesto completes seventeen years and, throughout the world, companies and researchers seek to understand their adoption stage, as well as the benefits, barriers, and limitations of agile methods. Although we have some studies and questionnaire data at the global level, we know little about how the Paraguayan software community is adopting agile methods. The present work conducted a research to set up the current stage of adoption, initial concerns and barriers of implementation of agile methods in software development companies in Paraguay. An online survey was sent to representatives of 53 Paraguayan companies. Of these, 9 (17%) companies responded. The concern about adopting more agile methods (44.44% of respondents) was the lack of reliability in product quality if developed using agile methods. The main barrier was the lack of experience (66.66%) of the companies. Copyright © 2017, The Authors. All rights reserved.

关键词： Surveys

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