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Undulating Seal Whiskers Evolved Optimal Wavelength-to-Diameter Ratio for Efficient Reduction in Vortex-Induced Vibrations (Adv. Sci. 2/2024)

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ADVANCED SCIENCE 2024年第2期11卷 e2304304页

作者： Kamat, Amar M. Zheng, Xingwen Bos, Julian Cao, Ming Triantafyllou, Michael S. Kottapalli, Ajay Giri Prakash Bioinspired MEMS and Biomedical Devices Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen Groningen The Netherlands Discrete Technology and Production Automation Group Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen Groningen The Netherlands Department of Mechanical Engineering Massachusetts Institute of Technology (MIT) Cambridge MA USA MIT Sea Grant College Program Massachusetts Institute of Technology (MIT) Cambridge MA USA Bioinspired MEMS and Biomedical Devices Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen Groningen The Netherlands MIT Sea Grant College Program Massachusetts Institute of Technology (MIT) Cambridge MA USA

Seals are well-known for their remarkable hydrodynamic trail-following capabilities made possible by undulating flow-sensing whiskers that enable the seals to detect fish swimming as far as 180 m away. In this work, the form-function relationship in the undulating whiskers of two different phocid seal species, viz. harbor and gray seals, is studied. The geometry and material properties of excised harbor and grey seal whiskers are systematically characterized using blue light 3D scanning, optical and scanning electron microscopy, and nanoindentation. The effect of the undulating geometry on the whiskers’ vibration in uniform water flow is studied using both experimental (piezoelectric MEMS and 3D-printed piezoresistive sensors developed in-house) and numerical (finite element method) techniques. The results indicate that the dimensionless ratio of undulation wavelength to mean whisker diameter (λ/Dm) in phocid seals may have evolved to be in the optimal range of 4.4–4.6, enabling an order-of-magnitude reduction in vortex-induced vibrations (compared to a similarly-shaped circular cylinder) and, consequently, an enhanced flow sensing capability with minimal self-induced noise. The results highlight the importance of the dimensionless λ/Dm ratio in the biomimetic design of seal whisker-inspired vibration-resistant structures, such as marine risers and wake detection sensors for submarines.

关键词： 3D printing biological fluid dynamics biomimetics microelectromechanical systems (MEMS) seal whiskers vortex-induced vibrations

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Electrospun bundled carbon nanofibers for skin-inspired tactile sensing,proprioception and gesture tracking applications

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npj Flexible Electronics 2021年第1期5卷 242-255页

作者： Debarun Sengupta Joshua Romano Ajay Giri Prakash Kottapalli Department of Advanced Production Engineering(APE) Engineering and Technology Institute Groningen(ENTEG)University of GroningenGroningen 9747 AGThe Netherlands MIT Sea Grant College Program Massachusetts Institute of Technology(MIT)77 Massachusetts AvenueNW98-151CambridgeMA 02139USA

In this work,we report a class of wearable,stitchable,and sensitive carbon nanofiber(CNF)-polydimethylsiloxane(PDMS)composite-based piezoresistive sensors realized by carbonizing electrospun polyacrylonitrile(PAN)nanofibers and subsequently embedding in PDMS elastomeric thin ***-mechanical tactile sensing characterization of the resulting piezoresistive strain sensors revealed a linear response with an average force sensitivity of~1.82 kN−1 for normal forces up to 20 *** real-time functionality of the CNF-PDMS composite sensors in wearable body sensor networks and advanced bionic skin applications was demonstrated through human motion and gesture monitoring experiments.A skin-inspired artificial soft sensor capable of demonstrating proprioceptive and tactile sensory perception utilizing CNF bundles has been ***,a 16-point pressure-sensitive flexible sensor array mimicking slow adapting low threshold mechanoreceptors of glabrous skin was *** devices in tandem with neuromorphic circuits can potentially recreate the sense of touch in robotic arms and restore somatosensory perception in amputees.

关键词： prop gesture artificial

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Using a spiral fin to replace a wavy fin in the condenser of an air conditioner

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International Journal of Thermofluids 2024年 21卷

作者： Chimres, Nares Kaew-on, Jatuporn Surapapwong, Thanis Chittiphalungsri, Thunyawat Wongwises, Somchai Mechanical Engineering Program Faculty of Engineering Thaksin University Phatthalung93210 Thailand PTT Exploration and Production Public Company Limited Bangkok Chatuchak10900 Thailand Co. Ltd. Nonthaburi Muang11000 Thailand Department of Mechanical Engineering Faculty of Engineering King Mongkut's University of Technology Thonburi Bangkok Bangmod10140 Thailand Pathum Thani12120 Thailand

An experimental and numerical investigation of an L-footed spiral fin's thermal performance for replacement of wavy fins used in condensers is presented. This condenser is used for air conditioners with a capacity of 2.64 kW–3.52 kW (9000–12,000 BTU/hr). Eight spiral fins with various fin pitches and fin diameters are studied. Each spiral fin is designed to have an area that is equal to that of a baseline wavy fin. The investigation found that the heat transfer coefficient and pressure drop obtained with the wavy fin are greater than those obtained with a spiral fin. Moreover, the spiral fin gives a performance index or "goodness factor" that is about 0.2–11.9 % greater than that of a wavy fin. © 2023 The Author(s)

关键词： Heat transfer coefficients

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Analysis of the Brazilian Climate Data Influence on Soybean Pricing by Using Long Short-Term Memory Models

SSRN

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SSRN 2024年

作者： Oliva, Jefferson Tales Martelli, Otávio Pigozzo de Castro Barbosa, Marco Antônio Dal Molin, Viviane Casanova, Dalcimar Teixeira, Marcelo Graduate Program in Electrical and Computer Engineering Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil Department of Academic Informatics Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil Graduate Program in Production and Systems Engineering Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil

This work uses machine learning to verify whether the Brazilian climate influences international soybean price prediction. For this, climatic data, dollar quotes, inflation, and annual soybean production were collected from different data sources. Then, the collected data were pre-processed and grouped by Brazilian state. Afterward, data from the five most productive Brazilian states are chosen, such as Mato Grosso (MT), Mato Grosso do Sul (MS), Goiás (GO), Paraná (PR), and Rio Grande do Sul (RS). Afterward, predictive models are built using the long short-term memory (LSTM) method, which is applied in each chosen state dataset considering two different settings: with and without climatic data. Thus, two models were built for each Brazilian state, totaling ten predictors. In the experimental evaluation, when trained with climatic data, the PR model achieved the lowest values of root mean squared error (RMSE) and mean absolute error (MAE). Regarding predictors trained without climate data, the RS and PR obtained the lowest values of RMSE and MAE, respectively. After conducting statistical hypothesis tests, no significant difference was found among models, stating, with 95% certainty, that, in this study, the Brazilian climatic data did not influence the model performance for predicting soybean prices. On the other hand, one of the main contributions of work is conducting an unprecedented study about soybean price prediction using Brazilian climatic data. © 2024, The Authors. All rights reserved.

关键词： Long short-term memory

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Soybean Price Prediction by Using Lstm Models Based on Brazilian Climatic Data

SSRN

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SSRN 2024年

作者： Oliva, Jefferson Tales Martelli, Otávio Pigozzo de Castro Barbosa, Marco Antônio Molin, Viviane Dal Casanova, Dalcimar Teixeira, Marcelo Graduate Program in Electrical Engineering Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil Department of Academic Informatics Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil Graduate Program in Production and Systems Engineering Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil

关键词： Long short-term memory

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A Multi-Criteria Approach to Assess Interconnections Among the Environmental, Economic, and Social Dimensions of Circular Economy

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SSRN 2023年

作者： Terra dos Santos, Luiz Carlos Giannetti, Biagio Fernando Agostinho, Feni Dalano Roosevelt Liu, Gengyuan de Almeida, Cecilia Maria Villas B. Post-graduation Program in Production Engineering Paulista University Brazil State Key Joint Laboratory of Environment Simulation and Pollution Control School of Environment Beijing Normal University China

The debate about the negative impacts that production and consumption cause on the environment is in vogue. Strategies that point to a sustainable, healthy, and resilient path are being sought. One of these paths is the Circular Economy, which emerges as an alternative to reduce the socio-environmental impacts caused by the linear model of production-use-disposal, presenting opportunities to generate revenue, income, and wealth with circular processes. However, despite the circular economy being considered an essential strategy to improve overall performance toward sustainability in its three dimensions, recent research has shown that the predominant focus of circular approaches is on the economic and environmental dimensions. At the same time, the social aspects are little explored. This article addresses this problem, aiming to explore the environmental, economic, and social aspects of circular economy in three economic blocs from 2000 to 2020 using the Five Sector Sustainability Model, establishing a baseline to co-create an equitable and regenerative future. The results showed that ASEAN in the year 2000 occupied the first position in the general ranking, while the European Union had the best classification in the economic sector and Mercosur was the best ranked regarding social benefits. In 2020, while the European bloc was better positioned in the general ranking, the South American bloc occupied the last post in almost all sectors. Comparatively, the highest-ranked bloc in 2020 in overall sustainability is more in line with the UN SDG due to circular actions oriented towards the three fundamental pillars of sustainability. © 2023, The Authors. All rights reserved.

关键词： Sustainable development

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A Systematic Review: Big Data Analytics and Landslides 13

A Systematic Review: Big Data Analytics and Landslides

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13th Landslides and Engineered Slopes. Experience, Theory and Practice, ISL

作者： da Silva Azevedo, Caio Correia, Thaís Passos Corsi, Alessandra Cristina de Mesquita Spinola, Mauro Quintanilha, José Alberto Postgraduate Program in Production Engineering The Polytechnic School of the University of São Paulo – PRO - EPUSP Brazil Postgraduate Program in Transportation Engineering The Polytechnic School of the University of São Paulo – PTR - EPUSP Brazil Institute for Technological Research - IPT Production Engineering Department The Polytechnic School of the University of São Paulo – PRO – EPUSP Brazil Institute of Energy and Environment of the University of São Paulo - IEEUSP Brazil

Landslides are among the natural disasters that most affect the population in Brazil and in the world, as they are responsible for numerous human, economic, social and environmental losses. High-resolution aerial and satellite imagery, that contribute to identify this type of event are valuable sources of information, even if they are not the only ones. Machine learning (ML) techniques are often adopted to identify relevant patterns, as high performance computing and data visualization are widely and successfully applied to natural disaster-related data, particularly for landslides. The greater the volume of data processed during machine learning, the better the accuracy of the results obtained. Among other reasons, Big Data (BD) has stood out for its ability to integrate and generate a large volume of data from different sources and in different formats. The use of BD concepts and techniques has become common in several areas of knowledge, in particular for the storage and analysis of data related to natural accidents and, thus, helping to improve decision making as well as prevention of disasters. With the emergence of the BD, it came the challenge of aligning decision-making processes, so that there is no shortage of information or useless data for decision makers. In the case of Brazil and considering, especially, applications to landslide data, there is a lack of articles dealing with the subject. The aim of this study is to investigate the main features used on machine learning techniques, to map the literature, thus pointing out new routes and opportunities in the field. In the systematic review, the eligibility criteria adopted are studies published in the last 4 years (from January 2015 to December 2019), in English, at national and international levels, including publications in scientific events and relevant journals, through databases such as Scopus and Web of Science. The search was performed in a structured form with the terms "Big Data*", "machine lea

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Localization of a Crack in Moving Cylindrical Ferromagnetic Rods by Measuring the Fourier Coefficients of the Leakage Magnetic Flux

Localization of a Crack in Moving Cylindrical Ferromagnetic ...

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Magnetic Conference - Short Papers (INTERMAG Short Papers), IEEE International

作者： Kanta Shiku Masafumi Kuromizu Yuji Gotoh Takaaki Nara Graduate School of Information Science and Technology The University of Tokyo bunkyo-ku Japan Division of Materials Science and Production Engineering Graduate School of Engineering Oita University Oita Japan Intelligent Mechanical Systems Program Faculty of Science and Technology Oita University Oita Japan

ISBN: (数字)9798350362213

ISBN: (纸本)9798350362220

Electromagnetic nondestructive inspection for high-speed moving ferromagnetic materials is necessary for manufacturing efficiency. In this paper, we present a novel leakage magnetic flux (LMF) method to estimate the crack position in a moving cylindrical ferromagnetic rod. The method directly measures the first-order Fourier coefficients of the LMF moving with the crack by using only two coils with DC excitation. The location of a crack is estimated by the proposed method, as demonstrated for an S45C cylindrical rod.

关键词： Location awareness Coils Magnetic flux Inspection Ferromagnetic materials Manufacturing Electromagnetics

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Application of Paraconsistent Annotated Evidential Logic Eτ for a Terrestrial Mobile Robot to Avoid Obstacles

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Procedia Computer Science 2021年 192卷 1821-1830页

作者： Flavio Amadeu Bernardini Marcia Terra da Silva Jair Minoro Abe Graduate Program in Production Engineering - Paulista University. Rua Dr. Bacelar 1212

One of the significant challenges in contemporary robotics concerns navigation systems and autonomous robots’ location, being the detection and avoidance of obstacles an essential part of this system. This article proposed Paraconsistent Annotated Evidential Logic Eτ in the control algorithm for a terrestrial robot, and thus contribute with navigation systems, to avoid possible collisions with obstacles. A prototype terrestrial robot was then built with ultrasonic sensors for obstacle detection and a servomotor in steering control. Several performance tests were performed. It was noticed that by shortening the perception distances of the sensors, the performance of the robot’s displacement proved to be satisfactory.

关键词： Paraconsistent annotated logic Servomotor Terrestrial mobile robot Robotics

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An app to assist farmers in the identification of diseases and pests of coffee leaves using deep learning

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Information Processing in Agriculture 2022年第1期9卷 38-47页

作者： Jose G.M.Esgario Pedro B.C.de Castro Lucas M.Tassis Renato A.Krohling LABCIN-Nature Inspired Computing Federal University of Espirito SantoAv.Fernando Ferrari514CEP 29075-910 VitoriaEspırito SantoESBrazil LABCIN-Nature Inspired Computing and PPGI-Graduate Program in Computer Scienceand Production Engineering DepartmentFederal University of Espirito SantoAv.Fernando Ferrari514CEP 29075-910 VitoriaEspırito SantoESBrazil

In recent years,deep learning methods have been introduced for segmentation and classi-fication of leaf lesions caused by pests and *** the commonly used approaches,convolutional neural networks have provided results with high *** purpose of this work is to present an effective and practical system capable of seg-menting and classifying different types of leaf lesions and estimating the severity of stress caused by biotic agents in coffee leaves using convolutional neural *** proposed approach consists of two stages:a semantic segmentation stage with severity calculation and a symptom lesion classification *** stage was tested separately,highlighting the positive and negative points of each *** obtained very good results for the severity estimation,suggesting that the model can estimate severity values very close to the real *** the biotic stress classification,the accuracy rates were greater than 97%.Due to the promising results obtained,an App for Android platform was developed and imple-mented,consisting of semantic segmentation and severity calculation,as well as symptom classification to assist both specialists and farmers to identify and quantify biotic stresses using images of coffee leaves acquired by smartphone.

关键词： Convolutional neural networks Semantic segmentation Coffee leaf Pests and diseases App.development

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