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Publicações - engenharias

A methodology to assess energy efficiency of conventional lathes DA COSTA, DALBERTO DIAS; GUSSOLI, MAURICIO; Pablo Deivid Valle; REBEYKA, CLAUDIMIR JOSÉ Energy Efficiency, v. 15, n. 1, p. 7-19, 2022 DOI Home page Palavra-chave: energy efficiency; Energy consumption; machining; Conventional lathes Áreas do conhecimento: Engenharias; SIMULAÇÃO E INTEGRAÇÃO DE PROCESSOS resumo ... Conventional machine tools are still widely used for a large group of small machining companies, mainly in countries with emerging economies. There is a wide variety of high-efficiency electric motors for machine tools in machining; however, most conventional machine tools are driven by three-phase squirrel-cage induction motors (SCIM). This type of machines in small companies deserves a systematic study on energy efficiency. Therefore, the main purpose of this work is to propose a methodology to assess the energy efficiency of conventional lathes with three-phase squirrel-cage induction motors. A case study was conducted with the proposed methodology that demonstrated that the energy efficiency can be depicted by constructing characteristic curves for each machine tool. The control of depth of cut (ap) is a sufficient condition for the construction of the characteristic curves of a conventional lathe. As a result, it was concluded that at the shop floor environment, the final user could install a digital wattmeter to read the electric power and analyze, from the characteristic curves, whether the machining operation is running on an efficient mode. The machine tool manufacturer can also incorporate a wattmeter into conventional lathes with squirrel-cage induction motors to measure and report the efficiency status during the machining operation.
Backwashable dynamic membrane made of anchored CNT on SiC microfiltration membranes applied to oil in water emulsion filtration Alexandre Poli; SFEIR, R.; Alexandre Ferreira Santos; Jacob, M.; P.BALDONY-ANDREY; BATIOT-DUPEYRAT, C.; TEYCHENE, Benoit SEPARATION AND PURIFICATION TECHNOLOGY, v. 278, p. 119566 2022 DOI Home page Palavra-chave: Petróleo; Emulsão; nanotubos de carbono Áreas do conhecimento: Engenharias; Operações Industriais e Equipamentos para Engenharia Química; Engenharias; Engenharia Química; Processos Industriais de Engenharia Química; Processos Biotecnológicos; Engenharias; Engenharia Química; Tecnologia Química; Petróleo e Petroquímica resumo ...
Bactericide and antimicrobial effects of ethanolic extracts of propolis and geopropolis of stingless bees natives from the state of Parana in multi-resistant microorganisms Lucy Schellin; Silvia Haluch; Sandro Froehner Brazilian Journal of Development, v. 8, n. 1, p. 2894-2917, 2022 DOI Palavra-chave: bee glu; sustainability; controle da poluição Áreas do conhecimento: Engenharias; Engenharia Sanitária; Saneamento Ambiental; Qualidade do Ar, das Águas e do Solo resumo ... (pt) The value of ecosystem concerning for the maintenance of riparian forests for the protection of water bodies can be essential to the preservation of natural resources, fauna and flora, and all of them inter-connected. Native stingless bees are fundamental pollinating agents for food production, besides the production of propolis and geopropolis, being each of these products, with local characteristics, depending on the vegetation available. The preservation of riparian forests enhances the insertion of meliponaries in communities bordering superficial water bodies and emphasizes the socio-environmental importance because this activity can be an extra source of income for small rural producers. In this work, the antimicrobial and antibacterial potential of propolis from stingless bees, native from the State of Paraná - Brazil, was examined, whose products can be extremely important considering its socio-economic and environmental view. Ethanolic extracts of propolis and geopropolis of native bees were tested according the antimicrobial and bactericidal capacity. The test was conducted with ethanolic extract of Africanized bees, in order to use it as control. The ethanolic extract of propolis and geopropolis of tested species showed to be effective as bactericide for the strains of bacteria Pseudomonas aeruginosa (gram-positive) and Klebsiella planticola , Escherichia coli , Raoutella planticola (gram-negative). In addition, it was observed that fungi can be inertized in honey by reducing the moisture content and the chemical defense barrier due to the substances present in the propolis and geopropolis against microorganisms. Inside the hives bees use propolis/geopropolis as sanitizer, to promote the fixation of microorganisms. In addition to pollination, the hives have an important function as controlling pests and pathogens.
Biosorption investigation of Cu(II) ions from aqueous solutions using sericin?alginate particles: Kinetic, equilibrium, and thermodynamic Giovana Gonçalves Dusi; GEOVANA SILVA MARQUES; Marina Lourenço Kienteca; Marcelino Luiz Gimenes; Myriam Lorena Melgarejo Navarro Cerutti; da Silva, Vítor R. SUSTAINABLE CHEMISTRY AND PHARMACY, v. 25, p. 100601 2022 DOI Home page Palavra-chave: biosorption; Cu(ii) ions; Silk sericin; Sodium alginate Áreas do conhecimento: Engenharias; Operações Industriais e Equipamentos para Engenharia Química; Operações de Separação e Mistura; Engenharias; Engenharia Química; Tecnologia Química; Água resumo ... In this study, sericin–alginate particles are produced for use as a biosorbent to remove Cu(II) ions from an aqueous solution in a batch biosorption s…
Blending colored and depth CNN pipelines in an ensemble learning classification approach for warehouse application using synthetic and real data Paulo Henrique Martinez Piratelo; Gideon Villar Leandro; Rodrigo Negri de Azeredo; Eduardo Massashi Yamao; José Francisco Bianchi Filho; Gabriel Maidl; Felipe Silveira Marques Lisboa; Laercio Pereira de Jesus; Renato de Arruda Penteado Neto; LEANDRO DOS SANTOS COELHO Machines, v. 10, n. 1, p. 1-26, 2022 DOI Home page Palavra-chave: aprendizado profundo; processamento de imagens resumo ... Electric companies face flow control and inventory obstacles such as reliability, outlays, and time-consuming tasks. Convolutional Neural Networks (CNNs) combined with computational vision approaches can process image classification in warehouse management applications to tackle this problem. This study uses synthetic and real images applied to CNNs to deal with classification of inventory items. The results are compared to seek the neural networks that better suit this application. The methodology consists of fine-tuning several CNNs on Red–Green–Blue (RBG) and Red–Green–Blue-Depth (RGB-D) synthetic and real datasets, using the best architecture of each domain in a blended ensemble approach. The proposed blended ensemble approach was not yet explored in such an application, using RGB and RGB-D data, from synthetic and real domains. The use of a synthetic dataset improved accuracy, precision, recall and f1-score in comparison with models trained only on the real domain. Moreover, the use of a blend of DenseNet and Resnet pipelines for colored and depth images proved to outperform accuracy, precision and f1-score performance indicators over single CNNs, achieving an accuracy measurement of 95.23%. The classification task is a real logistics engineering problem handled by computer vision and artificial intelligence, making full use of RGB and RGB-D images of synthetic and real domains, applied in an approach of blended CNN pipelines.
Blending Colored and Depth CNN Pipelines in an Ensemble Learning Classification Approach for Warehouse Application Using Synthetic and Real Data PIRATELO, PAULO HENRIQUE MARTINEZ; Gideon Villar Leandro; DE AZEREDO, RODRIGO NEGRI; YAMAO, EDUARDO MASSASHI; BIANCHI FILHO, JOSE FRANCISCO; MAIDL, GABRIEL; LISBOA, FELIPE SILVEIRA MARQUES; DE JESUS, LAERCIO PEREIRA; PENTEADO NETO, RENATO DE ARRUDA; COELHO, LEANDRO DOS SANTOS Machines, v. 10, n. 1, p. 28-54, 2022 DOI Home page Palavra-chave: convolutional neural networks; Warehouse management; Image Classification; ensemble learning; synthetic data; Depth image Áreas do conhecimento: Engenharias; Engenharia de Computação resumo ... Electric companies face flow control and inventory obstacles such as reliability, outlays, and time-consuming tasks. Convolutional Neural Networks (CNNs) combined with computational vision approaches can process image classification in warehouse management applications to tackle this problem. This study uses synthetic and real images applied to CNNs to deal with classification of inventory items. The results are compared to seek the neural networks that better suit this application. The methodology consists of fine-tuning several CNNs on Red–Green–Blue (RBG) and Red–Green–Blue-Depth (RGB-D) synthetic and real datasets, using the best architecture of each domain in a blended ensemble approach. The proposed blended ensemble approach was not yet explored in such an application, using RGB and RGB-D data, from synthetic and real domains. The use of a synthetic dataset improved accuracy, precision, recall and f1-score in comparison with models trained only on the real domain. Moreover, the use of a blend of DenseNet and Resnet pipelines for colored and depth images proved to outperform accuracy, precision and f1-score performance indicators over single CNNs, achieving an accuracy measurement of 95.23%. The classification task is a real logistics engineering problem handled by computer vision and artificial intelligence, making full use of RGB and RGB-D images of synthetic and real domains, applied in an approach of blended CNN pipelines.
Characterization of a coating for radioprotection, by X-ray diffraction, scanning electron microscopy, and dispersive energy spectroscopy Gladis Aparecida Galindo Reisemberger de Souza; RAMON SIGIFREDO CORTÉS PAREDES; Frieda Saicla Barros; Gustavo Bavaresco Sucharski; Sebastião Ribeiro Júnior; Carlos Dalmaso Neto; Larissa Ribas Santos; Watena Ferreira ŃTchalá; Felipe Bavaroski Toledo Costa CONSTRUCTION AND BUILDING MATERIALS, v. 321, n. 126326, p. 1-9, 2022 Palavra-chave: Surface materials; Characterization; X-ray diffractometry; scanning electron microscopy; Dispersive energy spectroscopy; Thermal spray/coating Áreas do conhecimento: Ciências Exatas e da Terra; Física; Física Nuclear; Engenharias; Engenharia Civil; Inovação resumo ...
Concrete surface electrical resistivity: Effects of sample size, geometry, probe spacing and SCMs CUNHA ARAÚJO, EMANOEL; MACIOSKI, GUSTAVO; Marcelo Henrique Farias de Medeiros CONSTRUCTION AND BUILDING MATERIALS, v. 324, p. 126659 2022 DOI Palavra-chave: resistividade elétrica superficial; durabilidade do concreto Áreas do conhecimento: Engenharias; Engenharia Elétrica; Telecomunicações resumo ...
Corrosion behaviour of reactive sputtering deposition niobium oxide based coating on the 2198-T851 aluminum alloy L R Freitas; R V Gelamo; Cláudia Eliana Bruno Marino; J M A Figueiredo; N B Leite; J C S Fernandes; Jeferson A Moreto SURFACE & COATINGS TECHNOLOGY, v. 434, p. 128197 2022 DOI Palavra-chave: ligas de Al; Plasma; proteção contra a corrosão Áreas do conhecimento: Engenharias; Engenharia Elétrica; Telecomunicações; Engenharias; Engenharia de Materiais e Metalúrgica; Metalurgia Física; Corrosão resumo ...
Detailing the organic matter in suspended sediments as a tool to access the impact of land occupation in water bodies: a case of Barigui Watershed (Southern Brazil) Angela Jimenez; Neto, D. M.; GALOSKI, CARLOS EDUARDO; Sandro Froehner ENVIRONMENTAL GEOCHEMISTRY AND HEALTH, v. 1, n. 1, p. 1-16, 2022 DOI Palavra-chave: biogeochemistry; Controle Ambiental; environmental impact Áreas do conhecimento: Ciências Exatas e da Terra; Geociências; Geoquímica Orgânica; Engenharias; Engenharia Sanitária; Saneamento Ambiental; Qualidade do Ar, das Águas e do Solo resumo ...

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