Novo método iterativo de localização da câmera baseado no conceito de resection-intersection

A Odometria Visual é o processo de estimar o movimento de um ente a partir de duas ou mais imagens fornecidas por uma ou mais câmeras. É uma técnica de grande importância na visão computacional, com aplicações em diversas áreas tais como assistência ao motorista e navegação de veículos autônomos, sistemas de realidade aumentada, veículos autônomos não-tripulados (VANTs) e até mesmo na exploração interplanetária. Os mé- todos mais comuns de Odometria Visual utilizam câmeras com visão estéreo, através das quais é possível calcular diretamente as informações de profundidade de detalhes de uma cena, o que permite estimar as posições sucessivas das câmeras. A Odometria Visual Monocular estima o deslocamento de um objeto com base nas imagens fornecidas por uma única câmera, o que oferece vantagens construtivas e operacionais embora exija processamento mais complexo. Os sistemas de Odometria Visual Monocular do tipo esparsos estimam a pose da câmera a partir de singularidades detectadas nas imagens, o que reduz significativamente o poder de processamento necessário, sendo assim ideal para aplica- ções de tempo real. Nessa óptica, este trabalho apresenta um novo sistema de Odometria Visual Monocular esparsa para tempo real, validado em veículo instrumentado. O novo sistema é baseado no conceito de Resection-Intersection, combinado com um novo teste de convergência, e um método de refinamento iterativo para minimizar os erros de reproje- ção. O sistema foi projetado para ser capaz de utilizar diferentes algoritmos de otimização não linear, tais como Gauss-Newton, Levenberg-Marquardt, Davidon-Fletcher-Powell ou Broyden–Fletcher–Goldfarb–Shannon. Utilizando o benchmark KITTI, o sistema proposto obteve um erro de translação em relação à distância média percorrida de 0, 86% e erro médio de rotação em relação à distância média percorrida de 0.0024◦/m. O sistema foi desenvolvido em Python em uma única thread, foi embarcado em uma placa Raspberry Pi 4B e obteve um tempo médio de processamento de 775ms por imagem para os onze primeiros cenários do benchmark. O desempenho obtido neste trabalho supera os resultados de outros sistemas de Odometria Visual Monocular baseados no conceito de ResectionIntersection até o momento submetidos na classificação do benchmark KITTI.Visual Odometry is the process of estimating the movement of an entity from two or more images provided by one or more cameras. It is a technique ofmain concern in computer vision, with applications in several areas such as driver assistance and autonomous vehicle navigation, augmented reality systems, Unmanned Aerial Vehicle (UAV) and even in interplanetary exploration. Most common methods of Visual Odometry use stereo cameras, through which it is possible to directly calculate the depth information of details of a scene, which allows to estimate the successive positions of the cameras. Monocular Visual Odometry estimates the displacement of an object based on images provided by a single camera, which offers constructive and operational advantages although it requires more complex processing. Sparse-type Monocular Visual Odometry systems estimate the camera pose from singularities detected in the images, which significantly reduces the processing power required, thus making it ideal for real-time applications. In this perspective, this work presents a new Sparse Monocular visual Odometry system for real-time, validated on a instrumented vehicle. The new system is based on the Resection-Intersection concept, combined with an expanded convergence test, and an iterative refinement method to minimize reprojection errors. It was designed to be able to use different non-linear optimization algorithms, such as Gauss-Newton, Levenberg-Marquardt, Davidon-FletcherPowell or Broyden–Fletcher–Goldfarb–Shannon. Using the benchmark KITTI, the proposed system obtained a translation error in relation to the average distance traveled of 0.86% and an average rotation error in relation to the average distance covered of 0.0024◦/m. The system was developed in Python on a single thread, was embedded on a Raspberry Pi 4B board and an average processing time of 775ms per image for the first eleven scenarios of the benchmark. The results obtained in this work surpass the results obtained by other visual odometry systems based on the concept of Resection-Intersection so far submitted to the KITTI benchmark ranking

Automatic assessment of honey bee cells using deep learning

Temporal assessment of honey bee colony strength is required for different applications in many research projects, which often involves counting the number of comb cells with brood and food reserves multiple times a year. There are thousands of cells in each comb, which makes manual counting a time-consuming, tedious and thereby an error-prone task. Therefore, the automation of this task using modern imaging processing techniques represents a major advance. Herein, we developed a software capable of (i) detecting each cell from comb images, (ii) classifying its content and (iii) display the results to the researcher in a simple way. The cells’ contents typically display a high variation of patterns which make their classification by software a challenging endeavour. To address this challenge, we used Deep Neural Networks (DNNs). DNNs are known for achieving the state of art in many fields of study including image classification, because they can learn features that best describe the content being classified by themselves. Our DNN model was trained with over 70,000 manually labelled cell images whose cells were separated into seven classes. Our contribution is an end-to-end software capable of doing automatic background removal, cell detection, and classification of cell content based on an input comb image. With this software, colony assessment achieves an average accuracy of 94% across the seven classes in our dataset, representing a substantial progress regarding the approximation methods (e.g. Lieberfeld) currently used by honey bee researchers and previous techniques based on machine learning that used handmade features like colour and texture.A análise temporal sobre a qualidade e força de colônias de abelha melífera (Apis mellifera L.) é necessária em muitos projetos de pesquisa. Ela pode ser realizada contando alvéolos com alimento (pólen e néctar) e criação. É comum que ela seja feita diversas vezes ao ano. A grande quantidade de alvéolos em cada favo torna a tarefa demorada e tediosa ao pesquisador. Assim, frequentemente essa contagem é feita forma aproximada usando métodos como o de Lieberfeld. Automatizar este processo usando técnicas modernas de processamento de imagem representa um grande avanço, pois resultados mais precisos e padronizados poderão ser obtidos em menos tempo. O objetivo deste trabalho é construir de um software capaz de detectar, classificar e contar alvéolos a partir de uma imagem. Após, ele deverá apresentar os dados de forma simplificada ao usuário. Para tratar da alta variação de padrões como textura, cor e iluminação presente nas alvéolos, usaremos Deep Neural Network (DNN), que são modelos computacionais conhecidos por terem alcançado o estado da arte em várias tarefas relacionadas a processamento de sinais e imagens. Para o treinamento desses modelos utilizamos mais de 70.000 alvéolos anotadas por um apicultor experiente, separadas em sete classes. Entre nossas contribuições estão métodos de préprocessamento que garantem uma alta taxa de detecção de alvéolos, aliados a modelos de segmentação baseados em DNNs que asseguram uma baixa taxa de falsos positivos. Com nossos classificadores conseguimos uma acurácia média de 94% em nosso dataset e obtivemos resultados superiores a outros métodos baseados em contagens aproximadas e técnicas de análise por imagem que não utilizam DNNs.This research was conducted in the framework of the project BEEHOPE, funded through the 2013-2014 BiodivERsA/FACCE-JPI Joint call for research proposals, with the national founders FCT(Portugal), CNRS(France), and MEC(Spain)

Thermal conductivity of calcium silicate boards at high temperatures: an experimental approach

Thermal conductivity analysis of fire insulation materials is of great importance for determining the critical temperature of structures. The magnitude of this thermal property has a significant influence on the analysis of temperature distribution and heat flow which depends essentially on the thermal properties of the protection material. Knowing accurate information about the effects of high temperatures on thermal conductivity is an important prerequisite for a performance based design of fire safety in buildings. Therefore, an investigation of two different calcium silicate boards has been performed to demonstrate how the thermal conductivity is affected when exposed to high temperatures. A set of experimental tests is presented. They were conducted in different techniques such as: the transient plane source (TPS) and the guarded hot plate (GHP).info:eu-repo/semantics/publishedVersio

Conjugate Cooling of a Discrete Heater in Laminar Channel Flow

Electronic components are usually assembled on printed circuit boards cooled by forced airflow. When the spacing between the boards is small, there is no room to employ a heat sink on critical components. Under these conditions, the components? thermal control may depend on the conductive path from the heater to the board in addition to the direct convective heat transfer to the airflow.The conjugate forced convection-conduction heat transfer from a two-dimensional strip heater flush mounted to a finite thickness wall of a parallel plates channel cooled by a laminar airflow was investigated numerically. A uniform heat flux was generated along the strip heater surface. Under steady state conditions, a fraction of the heat generation was transferred by direct convection to the airflow in the channel and the remaining fraction was transferred by conduction to the channel wall. The lower surface of the channel wall was adiabatic, so that the heat conducted from the heater to the plate eventually returned to the airflow. A portion of it returned upstream of the heater, preheating the airflow before it reached the heater surface. Due to this, it was convenient to treat the direct convection from the heater surface to the airflow by the adiabatic heat transfer coefficient. The flow was developed from the channel entrance, with constant properties.The conjugate problem was solved numerically within a single solution domain comprising both the airflow region and the solid wall of the channel. The results were obtained for the channel flow Reynolds number ranging from about 600 to 1900, corresponding to average airflow velocities from 0.5 m/s to 1.5 m/s. The effects of the solid wall to air thermal conductivities ratio were investigated in the range from 10 to 80, typical of circuit board materials. The wall thickness influence was verified from 1 mm to 5 mm. The results indicated that within these ranges, the conductive substrate wall provided a substantial enhancement of the heat transfer from the heater, accomplished by an increase of its average adiabatic surface temperature.278286Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq

Improving Random Access with NOMA in mMTC XL-MIMO

The extra-large multiple-input multiple-output (XL-MIMO) architecture has been recognized as a technology for supporting the massive MTC (mMTC), providing very high-data rates in high-user density scenarios. However, the large dimension of the array increases the Rayleigh distance (dRayl), in addition to obstacles and scatters causing spatial non-stationarities and distinct visibility regions (VRs) across the XL array extension. We investigate the random access (RA) problem in crowded XL-MIMO scenarios; the proposed grant-based random access (GB-RA) protocol combining the advantage of non-orthogonal multiple access (NOMA) and strongest user collision resolutions in extra-large arrays (SUCRe-XL) named NOMA-XL can allow access of two or three colliding users in the same XL sub-array (SA) selecting the same pilot sequence. The received signal processing in a SA basis changes the dRayl, enabling the far-field planar wavefront propagation condition, while improving the system performance. The proposed NOMA-XL GB-RA protocol can reduce the number of attempts to access the mMTC network while improving the average sum rate, as the number of SA increases.Comment: 13 pages, 5 figures, 1 table, conference VTC 2023. arXiv admin note: substantial text overlap with arXiv:2303.0053

Para uma nova caixa de Pandora: esboço de um roteiro heurístico pela sociologia da música

Ainda que a música esteja presente nas obras de autores pioneiros da sociologia (Max Weber e Georg Simmel), não é possível falar em um campo devidamente consistente do fenômeno musical dentro dos estudos sociológicos, não obstante os trabalhos de alguns pesquisadores (Simon Frith, Andy Bennett, Antoine Hennion, Tia De Nora, dentre outros), impulsionados em grande parte pelo cultural turn ocorrida na sociologia em meados dos anos de 1970. Tendo em vista este panorama, o presente artigo tem como objetivo contribuir com as discussões sobre o estado da arte da sociologia da música a partir das seguintes questões: a) o equilíbrio necessário entre a abordagem estética da música e a sua devida contextualização social; b) o papel importante da música popular em especial do pop-rock na conformação das identidades/práticas de segmentos geracionais, simbólicos e culturais específicos; c) o incremento com ênfase especial para o caso português de uma sociologia cultural que tem a música enquanto tema-chave de suas preocupações; d) as contribuições específicas da sociologia para a análise dos gêneros musicais com ênfase especial para o caso do rock alternativo.Although music is present in the works of pioneering authors of sociology (Max Weber and Georg Simmel), it is not possible to speak about a properly consistent field of music within sociological studies, despite the work of some researchers (Simon Frith, Andy Bennett, Antoine Hennion, Tia De Nora, among others), driven in large part by the cultural turn taking place in sociology in the mid-1970s. In view of this panorama, this article aims to contribute to the discussions on the state of the art of the sociology of music from the following questions: a) the necessary balance between the aesthetic approach of music and its due social contextualization; b) the important role of popular music - especially pop-rock - in shaping the identities / practices of specific generational, symbolic and cultural segments; c) the increase - with special emphasis on the Portuguese case - of a cultural sociology that has music as a key theme of its concerns; d) the specific contributions of sociology to the analysis of musical genres - with special emphasis on the case of alternative rock