Programa de Pós-Graduação em Engenharia Elétrica - PPGEE/ITEC
URI Permanente desta comunidadehttps://repositorio.ufpa.br/handle/2011/2314
O Programa de Pós-Graduação em Engenharia Elétrica (PPGEE) do Instituto de Tecnologia (ITEC) da Universidade Federal do Pará (UFPA) foi o primeiro e é considerado o melhor programa de pós-graduação em Engenharia Elétrica da Região Amazônica. As atividades acadêmicas regulares dos cursos de mestrado e doutorado são desenvolvidas principalmente nas Faculdades de Engenharia Elétrica e Engenharia de Computação, supervisionadas pela Coordenação do Programa de Pós-Graduação em Engenharia Elétrica (CPPGEE).
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Item Acesso aberto (Open Access) Análise de canal para frequência de 3,5 GHz em aeroporto(Universidade Federal do Pará, 2022-01-28) MACEDO, Alex Sanches; BARROS, Fabrício José Brito; http://lattes.cnpq.br/9758585938727609; http://lattes.cnpq.br/9758585938727609With the constant evolution of technology and communication systems, the increase in data exchange, speed and reliability regarding access to the mobile network has reinforced. Several causes such as spectral deficiency, difficulties in signal coverage, problems with antennas and radio link, are obstacles to be worked on and improved in order to provide services with higher quality within a mobile communication network infrastructure. To meet the vertiginous increase in the consumption of users and equipment connected to the mobile network, several works and researches are being proposed and developed. In Brazil, the arrival of fifth generation technology (5G) is expected from 2021, which will use the frequency band of 3.5 GHz. 5G promises fast connectivity with more users covering services and applications that demand high data rates over a wide coverage area. In particular, on this frequency that represents a sub-6 GHz band to be used for 5G in Brazil. As for the behavior of the channel, the characterization of this channel is of important relevance. Thus, in this dissertation, the study on channel analysis for the frequency of 3.5 GHz in a large indoor environment was motivated, this scenario is in a lobby of the International Airport Val de Cans, in Belém do Pará. measurements were performed for Line-Of-Sight (LOS) and through channel probing the dispersion parameters of the small-scale channel are extracted. These parameters are the average RMS delay and average RMS spread, the channel coherence band and the power profile and delays were also verified. Understanding large-scale signal propagation is important for designing mobile radio systems. The signal was also investigated through the Floating-Intercept (FI), Close-In (CI) models and their variations are applied and analyzed to evaluate the path loss for co-polarization (V-V and H-H) and cross-polarization (V-H and H-V ). It can be inferred that the methodology applied on a large scale proved to be adequate with the data and, when compared to other types of environments and other frequencies found in the literature.Item Acesso aberto (Open Access) Uma Análise do uso de informacões multiescala no mapeamento da PSNR para pontuacão perceptual(Universidade Federal do Pará, 2019-11-18) GONÇALVES, Luan Assis; ZAMPOLO, Ronaldo de Freitas; http://lattes.cnpq.br/9088524620828017; BARROS, Fabrício José Brito; http://lattes.cnpq.br/9758585938727609The prediction of visual quality is crucial in image and video systems. For this task, image quality metrics based on the mean squared error prevail in the field, due to their mathematical straightforwardness, even though they do not correlate well with the visual human perception. Latest achievements in the area support that the use of convolutional neural networks (CNN) to assess perceptual visual quality is a clear trend. Results in other applications, like blur detection and de-raining, indicate the combination of information from different scales improves the CNN performance. However, to the best of our knowledge, the best way to embody multi-scale information in visual quality characterization is still an open issue. Thus, in this work, we investigate the influence of using multi-scale information to predict the perceptual image quality. Specifically, we propose a single-stream dense network that estimates a spatially-varying parameter of a logistic function used to map values of a objective visual quality metric to subjective visual quality scores through the reference image. The proposed method achieved a reduction of 36.37% and 69.45% for the number of parameters and floating-point operations per second, respectively, and its performance is compared with a competing state-of-the-art approach by using a public image database.Item Acesso aberto (Open Access) Aplicação de redes neurais artificiais para predição de RSSI e SNR em ambiente de bosque amazônico(Universidade Federal do Pará, 2024-06-11) BARBOSA, Brenda Silvana de Souza; ARAÚJO, Jasmine Priscyla Leite de; http://lattes.cnpq.br/4001747699670004; https://orcid.org/0000-0003-3514-0401; BARROS, Fabrício José Brito; http://lattes.cnpq.br/9758585938727609The presence of green areas in urbanized cities is crucial to reduce the negative impacts of urbanization. However, these areas can influence the signal quality of IoT devices that use wireless communication, such as LoRa technology. Vegetation attenuates electromagnetic waves, interfering with data transmission between IoT devices, resulting in the need for signal propagation modeling that considers the effect of vegetation on its propagation. In this context, this research was conducted at the Federal University of Pará, using measurements in a wooded environment composed of the Pau-Mulato species, typical of the Amazon. Two propagation models based on machine learning, GRNN and MLPNN, were developed to consider the effect of Amazonian trees on propagation, analyzing different factors such as the height of the transmitter relative to the trunk, the beginning of the foliage, and the middle of the tree canopy, as well as the LoRa spreading factor (SF) 12 and the copolarization of the transmitter and receiver antennas. The best models were the machine learning ones, GRNN and MLPNN, which demonstrated greater accuracy, achieving root mean square error (RMSE) values of 3.86 dB and 3.8614 dB, and standard deviation (SD) of 3.8558 dB and 3.8564 dB, respectively. On the other hand, compared to classical models in the literature, the best-performing model was the Floating Intercept (FI) model, with RMSE and SD errors around 7.74 dB and 7.77 dB, respectively, while the FITU-R model had the highest RMSE and SD errors, around 26.40 dB and 9.65 dB, respectively, for all heights and polarizations. Furthermore, the importance of this study lies in its potential to boost wireless communications in wooded environments, as it was observed that even at short distances at heights of 12 m and 18 m, the SNR (Signal-to-Noise Ratio) had lower values due to the influence of the foliage, but it was still possible to send and receive data. Finally, it was shown that vertical polarization achieved the best results for the Amazon forest environment.Item Acesso aberto (Open Access) Detecção e rastreamento de componentes de vagões ferroviários utilizando redes neurais convolucionais e restricões geométricas(Universidade Federal do Pará, 2020-04-27) GONÇALVES, Camilo Lélis Assis; BARROS, Fabrício José Brito; http://lattes.cnpq.br/9758585938727609A inspeção de componentes de trem que podem causar descarrilamento possui um papel importante na manutenção ferroviária. A fim de aumentar a produtividade e a segurança, empresas prestadoras de serviços procuram por soluções de inspeção automáticas e confiáveis. Apesar da inspeção automática baseada em visão computacional ser um conceito consolidado, tais aplicações desafiam a comunidade de desenvolvimento em razão de fatores ambientais e logísticos a serem considerados. Este trabalho propõe uma técnica de detecção e estimativa das posições das regiões de dreno presentes em vagões de trem. Nosso detector/rastreador consiste em uma rede neural convolucional e um conjunto de restrições geométricas, que levam em conta a trajetória ideal dos componentes de interesse dos vagões e as distâncias entre eles. Detalhamos os procedimentos de treinamento e validação, juntamente com as métricas utilizadas para aferir a performance do sistema proposto. Os resultados apresentados são comparados com outras duas técnicas, e exibem um bom custo‑benefício entre confiança e complexidade computacional para a detecção dos componentes de interesse.Item Acesso aberto (Open Access) Estimação de descarga de dispositivo IoT usando deep learning com otimização NSGA-II(Universidade Federal do Pará, 2024-02-28) MACEDO, Wilson Antonio Cosmo; BARROS, Fabrício José Brito; http://lattes.cnpq.br/9758585938727609The increasing adoption of IoT (Internet of Things) network applications highlights the need to optimize energy management in these systems, because energy efficiency is crucial for the adaptability of IoT implementations. This study analyzes the discharge curves of a rechargeable battery in an IoT network context utilizing LoRa (Long Range) communication and various sensors, with the objective of generating multiple discharge curves to estimate the battery behavior in this scenario. These curves were used to train a Multilayer Artificial Neural Network (ANN), implementing Deep Learning techniques, where the ANN architecture was outlined using the NSGA-II (Non-dominated Sorting Genetic Algorithm II) Multi-objective Optimization algorithm. This resulted in models capable of estimating the battery discharge time by analyzing a segment of the discharge process observed by the model with a mean squared error of approximately two minutes for the most efficient model found. This result represents a very positive margin, considering that the duration of the discharge tests extends to approximately seventy-one hours and the data collection sampling rate is one minute.Item Acesso aberto (Open Access) Uma metodologia temporal para avaliação do desempenho de códigos concatenados em sistemas OFDM para transmissão de vídeo 4K-UHD(Universidade Federal do Pará, 2024-08-16) COSTA, Thiago de Araújo; CASTRO, Bruno Souza Lyra; http://lattes.cnpq.br/1897829604434609; BARROS, Fabrício José Brito; http://lattes.cnpq.br/9758585938727609The communication channel is a critical part of the process of information degradation. In the 4K ultra-resolution video transmission domain, the communication channel is a crucial part where information degradation occurs, inevitably leading to errors during reception. To enhance the transmission process in terms of fidelity, advanced technologies such as digital video broadcasting terrestrial (DVB-T) and its evolutionary successor, digital video broadcasting terrestrial second generation (DVB-T2), are utilized to mitigate the effects of data transmission errors. In the transition, a notable change is the replacement of the concatenated channel coding pairs. Within this scenario, this research presents an innovative methodology for the temporal analysis of 4K ultraresolution video quality under the influence of additive white Gaussian noise (AWGN) and Rayleigh channels. This analytical endeavor is facilitated through the application of concatenated coding schemes, specifically, the Bose-Chaudhuri-Hocquenghem concatenated low-density parity check (BCH-LDPC) and Reed-Solomon concatenated convolutional (RS-CONV) coders. A more comprehensive understanding of video quality can be attained by considering its temporal variations, a crucial aspect of the ongoing evolution of technological paradigms. In this study, the Structural Similarity Index (SSIM) serves as the main metric for quality assessment during simulations. Furthermore, the simulated Peak Signal-to-Noise Ratio (PSNR) values validate these findings, exhibiting consistent alignment with the SSIM-based evaluations. Additionally, the performance of the BCH-LDPC significantly outperforms that of RSCONV under the 64-QAM modulation scheme, yielding superior video quality levels that approximate or surpass those achieved by RS-CONV under QPSK (Quadrature Phase Shift Keying) modulation, leading to an increase in spectral efficiency. This enhancement is evidenced by SSIM gains exceeding 78% on average. The computation of average gains between distinct technologies in video quality analysis furnishes a robust and comprehensive evaluation framework, empowering stakeholders to make informed decisions within this domain.Item Acesso aberto (Open Access) Modelagem da perda de qualidade de videos H.264 em redes sem fio considerando perdas de PSNR e de frames(Universidade Federal do Pará, 2019-08-16) CARMONA, João Victor Costa; CAVALCANTE, Gervásio Protásio dos Santos; http://lattes.cnpq.br/2265948982068382; BARROS, Fabrício José Brito; http://lattes.cnpq.br/9758585938727609Multimedia applications have been growing in recent years; new consumptions like online games, video conference, video on demand and IP telephony are some of these. However, there is a greater prominence in the search related to videos and streaming, currently in high resolutions and mostly traffic over wireless networks, mainly due to the proliferation of mobile devices and significant increase of access networks, which make it more comfortable. Providing this information is easy. Thus, as an immediate consequence of this type of flow, there is a need for investments in techniques and mechanisms that provide the end user with the desired quality and satisfaction in the face of high definition content. This work aims to perform the modeling of video quality loss by analyzing their performance in various resolutions, specifically standards in HD and UHD, at 720p, 1080p and 2160p. In this sense, applying a correlation investigation between the metrics extracted from the videos, using Pearson’s correlation coefficient, and fundamentals of the area in question. Also proposing equations for quality loss modeling, based on analysis of metrics associated with packet loss, in which at the end of the study and according to notes made throughout the text, we used for the general modeling equation, the parameters of Loss of PSNR and Loss of Total Frames. The result obtained shows maximum values of RMSE and Standard Deviation of 0.793 dB and 0.810 dB, respectively, making the developed model very good for the tested video set and its resolutions.Item Acesso aberto (Open Access) Modelo de propagação usando dois raios com modificação de fase para mobilidade aplicado a receptor LoRa sobre rio.(Universidade Federal do Pará, 2024-09-19) RIBEIRO, Lucian Morais; BARROS, Fabrício José Brito; http://lattes.cnpq.br/9758585938727609As predicted by experts, there has been exponential growth in the number of IoT devices used by the general population. Among these devices, one of the most notable groups is the Long Range (LoRa) devices. The most relevant feature of LoRa technology is its low energy consumption, while simultaneously providing a wide coverage area. If applied in the Amazon region – a densely forested, humid area with populations far from urban centers and with very little infrastructure – this technology could offer a new range of services to the region’s inhabitants, including services involving communication on the move. Starting from the principle that the most well-known propagation models are not adjusted to the specificities of the Amazon region, nor do they consider the phase variations caused by receiver movement – which makes radio links difficult to predict – we aim to present solutions to this problem through this work, which presents adjustments to the Two-Ray propagation loss model to accommodate LoRa communications over the Amazon rivers when the receiving devices are in motion. The proposed model is compared to the standard Two-Ray Model, which serves as the baseline, and achieves better results. Additionally, the study evaluates the impact of tides on the propagation loss of LoRa signals in river environments.Item Acesso aberto (Open Access) Proposição de hardwaree software para transmissão de dados via LoRa e GSM: Estudo decaso no smart campus da UFPA(Universidade Federal do Pará, 2023-03-16) CARVALHO, Joel Alison Ribeiro; BARROS, Fabrício José Brito; http://lattes.cnpq.br/9758585938727609Society has been undergoing major transformations in the industry 5.0 era, with greater interac tion between man and machine in addition to increased connectivity. These factors have provided the growth of the internet of things, especially in cities, where Smart Cities and Smart Campus. In this sense, hardware development enables greater control over the integration of devices, as it meets the needs of the project in addition to to make the project scalable by adding new sensors as the project progresses develops. For this, in this work are developed hardware and software for transmission of data via LoRa and GSM to a middleware platform, and to validate this proposal data transmissions were carried out, considering the applications of the smart campus of UFPA: Circular Bus, Intercity Bus, Photovoltaic System and Battery System. You results showed that all equipment communicated with Dojot, as all Variables of interest for each application could be observed on the server.Item Acesso aberto (Open Access) Síntese de superfícies seletivas de frequência multicamadas via otimização bioinspirada(Universidade Federal do Pará, 2019-08-23) LIMA, Wirlan Gomes; ALCÂNTARA NETO, Miércio Cardoso de; http://lattes.cnpq.br/0549389076806391; BARROS, Fabrício José Brito; http://lattes.cnpq.br/9758585938727609The analysis of electromagnetic devices via computer software usually demands high computational cost and high processing time. In certain situations, to meet certain design objectives, finding the optimal structural parameters can take days or even weeks when done by trial and error when seeking accurate answers in highly complex structures. In this scenario, bioinspired computation (BIC) tools are strong allies in saving time, computational cost and, consequently, money. To enhance the power and efficiency of these tools, hybrid methods have been developed in which neural networks work in conjunction with optimization algorithms to obtain even more satisfactory and accurate results. In this context, this work presents the use of two multiobjective bioinspired hybrid optimization models for the design and synthesis of multilayer frequency selective surfaces (FSS). Initially, an electromagnetic investigation of the unit cell of the patch-like structures that will compose the multilayer FSS is made, which are a triangular loop and a solid diamond printed on fiberglass substrate (FR-4). The computer simulations were performed with the aid of CSTR○ Micro Wave Studio software, whose finite integrals (FIT) numerical technique is used. Three filters with distinctive characteristics that cover the C, X and Ku bands are designed. The synthesis process consists of tuning the objectives of the structures inserted in the cost function of the optimization algorithms. The modeling of the structures is performed by a general regression neural network (GRNN) and the optimization process is performed by the algorithms. The computational simulations for calculating the electromagnetic (EM) data of the multilayer FSS were performed using the CSTR○ software. The optimized values returned by the hybrid models were also simulated using Ansoft 𝐷𝑒𝑠𝑖𝑔𝑛𝑒𝑟𝑇𝑀 HFSS software to evaluate the previously obtained results. Good agreement between the simulated results was observed, showing a reduction in the processing time of the structures, besides showing that the GRNN-AG Multi model stood out in relation to the GRNN-MOCS, presenting errors in relation to the design objectives for the simulations. in CSTR○ of 0.44%, 0.254% and 0.387% for filters 1, 2 and 3, respectively, which is the most efficient hybrid model for multi-layer FSS optimization.