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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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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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Genetic programming for attribute construction in data mining

Genetic programming for attribute construction in data minin...

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6th European Conference on Genetic programming, EuroGP 2003

作者： Otero, Fernando E. B. Silva, Monique M. S. Freitas, Alex A. Nievola, Julio C. Postgraduate Program in Applied Computer Science Rua Imaculada Conceicao 1155 CuritibaPR80215-901 Brazil Computing Laboratory University of Kent Canterbury KentCT2 7NF United Kingdom

ISBN: (纸本)354000971X

For a given data set, its set of attributes defines its data space representation. The quality of a data space representation is one of the most important factors influencing the performance of a data mining algorithm. The attributes defining the data space can be inadequate, making it difficult to discover high-quality knowledge. In order to solve this problem, this paper proposes a Genetic programming algorithm developed for attribute construction. This algorithm constructs new attributes out of the original attributes of the data set, performing an important preprocessing step for the subsequent application of a data mining algorithm. © 2003, Springer-Verlag Berlin Heidelberg, All rights Reserved.

关键词： Genetic programming

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Feature selection and image classification using rough sets theory

Feature selection and image classification using rough sets ...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Alex Sandro Aguiar Pessoa Stephan Stephany Leila Maria Garcia Fonseca Postgraduate Program in Applied Computing National Institute for Space Research Brazil Computing and Applied Mathematics Laboratory National Institute for Space Research Brazil Image Processing Division National Institute for Space Research Brazil

Current generation of satellite imaging sensors include multispectral or even hyperspectral devices. The resulting multiple images that are acquired require new processing and analysis techniques. Image classification processing demands can be very high requiring feature/attribute selection in order to employ a minimum number of bands while keeping good classification accuracy. This work shows the use of the Rough Sets theory for multi-band image classification. This theory has a good and simple mathematical formalism and does not requires further informations such as the pertinence degree or the probability distribution in the classification process. The case study was performed with a 7-band Landsat 5 image showing the suitability of the feature selection approach and its potential to be employed in multi or hyperspectral image classification.

关键词： Decision support systems

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UHF signal measurements and prediction using propagation models

UHF signal measurements and prediction using propagation mod...

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SBMO/IEEE MTT-S International Conference on Microwave and Optoelectronics (IMOC)

作者： Karine S. Almeida Rafael T. Santos Edgar Silva Cássio C. Cardoso Ivonete M. L. Oliveira FAPESB Postgraduate Program in Applied Computing (PGCA) State University of Feira de Santana (UEFS) Feira de Santana BA Brazil

This paper presents a radio propagation measurement campaign of the received power in a campus scenario at State University of Feira de Santana (UEFS) and Imigrantes Highway. Comparisons and an analysis between the obtained values during the measurements at UEFS and the following propagation models: Free Space, Two-Ray, Log-Distance and Two-Ray without approximations are presented. The measurements taken at Imigrantes Highway are also compared to Two-Ray model without approximations.

关键词： Receivers Mathematical model Transmitting antennas Antenna measurements Predictive models Road transportation

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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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A parallel implementation of the LTSn method for a radiative transfer problem

A parallel implementation of the LTSn method for a radiative...

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International Symposium on Computer Architecture and High Performance computing (SBAC-PAD)

作者： R.P. Souto H.F. de Campos Velho S. Stephany A.J. Preto C.F. Segatto M.T. Vilhena Postgraduate Program Applied Computing (CAP/INPE) Sao Paulo Brazil PPGMAp PROMEC UFRGS Universidade Federal do Rio Grande do Sul Porto Alegre Rio Grande do Sul Brazil

A radiative transfer solver that implements the LTSn method was optimized and parallelized using the MPI message passing communication library. Timing and profiling information was obtained for the sequential code in order to identify performance bottlenecks. Performance tests were executed in a distributed memory parallel machine, a multicomputer based on IA-32 architecture. The radiative transfer equation was solved for a cloud test case to evaluate the parallel performance of the LTSn method. The LTSn code includes spatial discretization of the domain and Fourier decomposition of the radiances leading to independent azimuthal modes. This yields an independent radiative transfer equation for each mode that can be executed by a different processor in a parallel implementation. Speed-up results show that the parallel implementation is suitable for the used architecture.

关键词： Concurrent computing Message passing Testing Computer architecture Libraries Timing Parallel machines Laplace equations Matrix decomposition Communication standards

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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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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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