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A possible solution for noise attenuation material for urban buses: The downtown São Paulo case study

Noise and Vibration Worldwide 2025年第3期56卷 137-147页

作者： Monteiro, Elvis C Avila, Antonio F Division Stellantis Betim Brazil Mechanical Engineering Graduate Studies Program Universidade Federal de Minas Gerais Belo Horizonte Brazil Department of Mechanical Engineering and Mechanical Engineering Graduate Studies Program Universidade Federal de Minas Gerais Belo Horizonte Brazil

Urban buses, particularly in large cities, are exposed to significant noise pollution. This paper presents a new family of materials at the micro/nano level designed for urban noise attenuation, specifically for application in urban buses. Melamine foam is combined in series with nanomembranes, creating a composite material that functions as a Helmholtz resonator. As sound waves pass over the nanomembranes, they are disturbed, and the sound resonates within the melamine foam. This interaction reduces the energy of the sound waves and enhances the noise absorption coefficient. In ten cases studied, the average sound absorption coefficient was approximately 89%, with peak frequencies ranging from 2400 Hz to 4300 Hz. The average thickness of the nanomembranes was around 5.0 µm, while the melamine foam had a thickness of 13 mm. The mean noise reduction achieved was about 11 dB, which depends on factors such as the morphology, thickness, and pore size of the nanomembranes. A case study conducted in downtown São Paulo demonstrated that applying these materials to urban buses can significantly reduce interior noise levels. Finally, the proposed system is fully scalable and adaptable for various applications where acoustic insulation is required. © The Author(s) 2025.

关键词： Noise pollution

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Rheological and stability analysis of cement pastes incorporating silica-based wastes

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Particuology 2024年第6期89卷 144-152页

作者： Julia da Rosa Martins Janaíde Cavalcante Rocha Dachamir Hotza Luciano Senff Graduate Program in Materials Science and Engineering(PPGMAT) Federal University of Santa Catarina(UFSC)Florianópolis88040-900SCBrazil Graduate Program in Civil Engineering(PPGEC) Federal University of Santa Catarina(UFSC)Florianópolis88040-900SCBrazil Graduate Program in Chemical Engineering(POSENQ) Federal University of Santa Catarina(UFSC)Florianópolis88040-900SCBrazil Department of Mobility Engineering Federal University of Santa Catarina(UFSC)Joinville89219-600SCBrazil

This study investigates the influence of waste characteristics,especially zeta potential,on the properties of cement pastes and *** focus is to evaluate the impact of the zeta potential of cement particles and waste materials on the sedimentation speed,rheology,and hardening time of stabilized cement *** Cement II F 40,retarder additive,silica,and fly ash were used in the *** pastes were prepared,and during the stabilization period,their rheological properties and pH were *** zeta potential and sedimentation speed of the cement and waste particles were measured at the pH that the pastes presented during the entire stabilization *** the stabilization period,the pastes were subjected to the hardening time *** zeta potential analyses revealed diverse values for the different powder types,with the cement particles exhibiting a zeta potential of−3.0 mV,the silica particles exhibiting−10.5 mV,and the fly ash particles exhibiting−20.3 *** influence of the high zeta potential modulus was observed on the sedimentation speed,with the solution containing fly ash exhibiting a speed of 40.01μm/s,whereas the solution containing only cement exhibited a speed of 99.38μm/*** the pastes,the results indicate that the presence of fly ash particles with a significantly negative zeta potential led to a 16%reduction in hardening time compared to particles with a lower modulus of zeta *** tests showed that the inclusion of fly ash particles prevented the formation of *** the zeta potential influenced agglomerate formation and hardening time,it was found to have no effect on yield stress or viscosity.

关键词： Wastes Zeta potential Setting time Rheometry

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Measuring Public Wi-Fi Security Awareness via Captive Portal Connections Using a Microcontroller

Measuring Public Wi-Fi Security Awareness via Captive Portal...

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2024 Workshop on Communication Networks and Power Systems, WCNPS 2024

作者： Mariano, Hyago Santana Cafe, Daniel Chaves Professional Graduate Program in Electrical Engineering-PPEE Department of Electrical Engineering Brazil

ISBN: (纸本)9798331507152

This article proposes the implementation of a captive portal system on a microcontroller to assess users' maturity regarding the safe use of public Wi-Fi networks. The use of public Wi-Fi networks has become increasingly common in places like cafes, airports, shopping centers, and hotels. However, many users are unaware of the risks associated with using these unsecured networks, such as personal information theft, privacy invasion, and cyberattacks. This study aims to utilize a microcontroller to generate a signal mimicking a known public network, where, upon user login, an educational authentication portal will be displayed. This portal will not only provide information about security risks but also evaluate the users' maturity level in adopting safe practices on public Wi-Fi networks, offering guidelines on how to protect their data and devices. © 2024 IEEE.

关键词： Wi-Fi

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Soil Water Content Estimation over Plantation Area Using FMCW Radar

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Progress In Electromagnetics Research B 2023年 101卷 155-173页

作者： Ridhia, Fildha Pramudita, Aloysius Adya Suratman, Fiky Y. Graduate Program of Electrical Engineering Department Telkom University Indonesia Telecommunication Engineering Department Telkom University Indonesia Electrical Engineering Department Telkom University Indonesia

In plantation areas, soil conditions affect the crop's quality. One of the crucial elements in the soil for plant survival is soil water content (SWC). Radar system has advantages that can be implemented for measuring SWC in plantation areas. A radar system operates by utilizing electromagnetic waves to obtain the dielectric characteristics of the soil. However, the presence of tea plants has become an obstacle to the radar wave propagation toward the soil layer. Re ected signal, which is in uenced by the presence of vegetation, makes the estimation of SWC inaccurate. Consequently, the estimation of SWC needs to consider the vegetation's effect. This study uses an FMCW radar system, which operates at a frequency of 24 GHz. A layer medium propagation model is proposed in this study to prove the relationship between the re ected signal and the SWC. The re ection coefficient extracted from the radar signal is used to estimate the SWC. The vegetation propagation constant was obtained from the average field measurement results. The gravimetric method is used to validate the SWC estimation in vegetation's presence using the radar system. The results of the field experiments showed that the proposed method succeeded in estimating the SWC by considering the presence of vegetation with an average error of 3.57%. The proposed method has the potential to be applied to plantation areas. © 2023, Progress In Electromagnetics Research B. All Rights Reserved.

关键词： Vegetation

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Understanding the interplay of sludge characteristics and dewatering in water treatment plants: a review

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Environmental Technology Reviews 2024年第1期13卷 794-813页

作者： Paffrath, Silvia F. Carissimi, Elvis Schner, Jéssica C. N. Ferrari, Keila F. H. Etchepare, Ramiro G. Graduate Program in Water Resources and Environmental Engineering Federal University of Paraná Curitiba Brazil Department of Sanitary and Environmental Engineering Federal University of Santa Maria Santa Maria Brazil Graduate Program in Civil Engineering Federal University of Santa Maria Santa Maria Brazil Department of Hydraulics Sanitation Federal University of Paraná Curitiba Brazil

In the realm of water supply and the management of residues arising from water treatment plants (WTP), an essential challenge lies in understanding and characterising sludge, and assessing whether these characteristics impact sludge dewatering, an essential step to reduce the management costs of these wastes. This review focuses specifically on the characterisation of sludge properties relevant to dewatering performance, addressing an underexplored aspect within recent literature on water treatment plant sludge (WTS). Unlike prior studies, which predominantly focus on sludge reuse after dewatering, this review systematically examines the direct correlations and interdependencies between sludge characteristics and dewatering outcomes, addressing gaps in literature. A bibliometric analysis of global WTS research revealed an annual average of fewer than 14 publications since 1957. Keywords related to sludge characteristics are notably scarce in connection with ‘dewatering’, highlighting a specific gap that this review aims to address. This review categorises sludge characteristics into ‘micro-properties’ and ‘macro-properties’, providing detailed descriptions of each. The latter primarily influence dewatering and are generally unmeasured in WTPs due to the inherent difficulties in their determination. However, it’s possible to derive macro-properties from micro-properties, establishing their relationship and subsequently selecting an appropriate dewatering technique. Main findings underscore direct proportionality between: viscosity (micro) and capillary suction time–CST (macro), solid concentration–SC (micro) and CST;and inverse proportionality between: SC and specific resistance to filtration–SRF (macro). These findings contribute a refined understanding of parameters affecting sludge dewatering processes, supporting further research focused on enhancing efficiency in WTS management. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Dewatering

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Hyperparameter optimization for cardiovascular disease data-driven prognostic system

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Visual Computing for Industry,Biomedicine,and Art 2023年第1期6卷 218-244页

作者： Jayson Saputra Cindy Lawrencya Jecky Mitra Saini Suharjito Suharjito Industrial Engineering Department BINUS Graduate Program-Master of Industrial EngineeringBina Nusantara UniversityJakarta 11480Indonesia

Prediction and diagnosis of cardiovascular diseases(CVDs)based,among other things,on medical examinations and patient symptoms are the biggest challenges in *** 17.9 million people die from CVDs annually,accounting for 31%of all deaths *** a timely prognosis and thorough consideration of the patient’s medical history and lifestyle,it is possible to predict CVDs and take preventive measures to eliminate or control this life-threatening *** this study,we used various patient datasets from a major hospital in the United States as prognostic factors for *** data was obtained by monitoring a total of 918 patients whose criteria for adults were 28-77 years *** this study,we present a data mining modeling approach to analyze the performance,classification accuracy and number of clusters on Cardiovascular Disease Prognostic datasets in unsupervised machine learning(ML)using the Orange data mining *** techniques are then used to classify the model parameters,such as k-nearest neighbors,support vector machine,random forest,artificial neural network(ANN),naïve bayes,logistic regression,stochastic gradient descent(SGD),and *** determine the number of clusters,various unsupervised ML clustering methods were used,such as k-means,hierarchical,and density-based spatial clustering of applications with noise *** results showed that the best model performance analysis and classification accuracy were SGD and ANN,both of which had a high score of 0.900 on Cardiovascular Disease Prognostic *** on the results of most clustering methods,such as k-means and hierarchical clustering,Cardiovascular Disease Prognostic datasets can be divided into two *** prognostic accuracy of CVD depends on the accuracy of the proposed model in determining the diagnostic *** more accurate the model,the better it can predict which patients are at risk for CVD.

关键词： Cardiovascular disease Data-driven analytics Data mining Hyperparameter optimization Orange data mining software Prognostic system Unsupervised machine learning

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Optimization of machine learning models for predicting the compressive strength of fiber-reinforced self-compacting concrete

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Frontiers of Structural and Civil engineering 2023年第2期17卷 284-305页

作者： Hai-Van Thi MAI May Huu NGUYEN Son Hoang TRINH Hai-Bang LY Civil Engineering Department University of Transport TechnologyHanoi 100000Vietnam Civil and Environmental Engineering Program Graduate School of Advanced Science and EngineeringHiroshima UniversityHiroshima 739-8527Japan

Fiber-reinforced self-compacting concrete(FRSCC)is a typical construction material,and its compressive strength(CS)is a critical mechanical property that must be adequately *** the machine learning(ML)approach to estimating the CS of FRSCC,the current research gaps include the limitations of samples in databases,the applicability constraints of models owing to limited mixture components,and the possibility of applying recently proposed *** study developed different ML models for predicting the CS of FRSCC to address these *** neural network,random forest,and categorical gradient boosting(CatBoost)models were optimized to derive the best predictive model with the aid of a 10-fold cross-validation technique.A database of 381 samples was created,representing the most significant FRSCC dataset compared with previous studies,and it was used for model *** findings indicated that CatBoost outperformed the other two models with excellent predictive abilities(root mean square error of 2.639 MPa,mean absolute error of 1.669 MPa,and coefficient of determination of 0.986 for the test dataset).Finally,a sensitivity analysis using a partial dependence plot was conducted to obtain a thorough understanding of the effect of each input variable on the predicted CS of *** results showed that the cement content,testing age,and superplasticizer content are the most critical factors affecting the CS.

关键词： compressive strength self-compacting concrete artificial neural network decision tree CatBoost

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Polygalacturonase-inhibiting proteins as an exogenously applied natural solution for prevention of postharvest fungal infections

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Synthetic and Systems Biotechnology 2024年第3期9卷 481-493页

作者： Tiffany Chiu Yanran Li Graduate Program in Genetics Genomicsand Bioinformatics1140 Batchelor HallUniversity of California RiversideCalifornia92521USA Program of Chemical Engineering Department of NanoengineeringUniversity of CaliforniaSan DiegoCA92521USA

Polygalacturonase inhibiting proteins(PGIPs)are plant proteins involved in the inhibition of polygalacturonases(PGs),cell-wall degrading enzymes often secreted by phytopathogenic ***,we confirmed that PGIP2 from Phaseolus vulgaris(PvPGIP2)can inhibit the growth of Aspergillus niger and Botrytis cinerea on agar *** this study,we further validated the feasibility of using PGIP as an environmental and ecological friendly agent to prevent fungal infection *** found that application of either purified PGIP(full length PvPGIP2 or truncated tPvPGIP2_5-8),or PGIP-secreting Saccharomyces cerevisiae strains can effectively inhibit fungal growth and necrotic lesions on tobacco *** also examined the effective amount and thermostability of PGIP when applied on plants.A concentration of 0.75 mg/mL or higher can significantly reduce the area of *** *** activity of full-length PvPGIPs is not affected after incubation at various temperatures ranging from􀀀20 to 42◦C for 24 h,while truncated tPvPGIP2_5-8 lost some efficacy after incubation at 42◦***,we have also examined the efficacy of PGIP on tomato *** the purified PvPGIP2 proteins were applied to tomato fruit inoculated with *** at a concentration of roughly 1.0 mg/mL,disease inci-dence and area of disease had reduced by more than half compared to the controls without PGIP *** study explores the potential of PGIPs as exogenously applied,eco-friendly fungal control agents on fruit and vegetables post-harvest.

关键词： PGIP Antifungal agent Pest control Postharvest treatment

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Learning feature alignment and dual correlation for few‐shot image classification

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CAAI Transactions on Intelligence Technology 2024年第2期9卷 303-318页

作者： Xilang Huang Seon Han Choi Department of Electronic and Electrical Engineering Ewha Womans UniversitySeoulSouth Korea Graduate Program in Smart Factory Ewha Womans UniversitySeoulSouth Korea

Few‐shot image classification is the task of classifying novel classes using extremely limited labelled *** perform classification using the limited samples,one solution is to learn the feature alignment(FA)information between the labelled and unlabelled sample *** FA methods use the feature mean as the class prototype and calculate the correlation between prototype and unlabelled features to learn an alignment ***,mean prototypes tend to degenerate informative features because spatial features at the same position may not be equally important for the final classification,leading to inaccurate correlation ***,the authors propose an effective intraclass FA strategy that aggregates semantically similar spatial features from an adaptive reference prototype in low‐dimensional feature space to obtain an informative prototype feature map for precise correlation ***,a dual correlation module to learn the hard and soft correlations was developed by the *** module combines the correlation information between the prototype and unlabelled features in both the original and learnable feature spaces,aiming to produce a comprehensive cross‐correlation between the prototypes and unlabelled *** both FA and cross‐attention modules,our model can maintain informative class features and capture important shared features for *** results on three few‐shot classification benchmarks show that the proposed method outperformed related methods and resulted in a 3%performance boost in the 1‐shot setting by inserting the proposed module into the related methods.

关键词： image classification machine learning metric learning

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Negative Stiffness Mechanism on An Asymmetric Wave Energy Converter by Using A Weakly Nonlinear Potential Model

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China Ocean engineering 2024年第4期38卷 689-700页

作者： Sunny Kumar POGULURI Dongeun KIM Yoon Hyeok BAE Department of Ocean Engineering IIT MadrasChennaiIndia Multidisciplinary Graduate School Program for Wind Energy Jeju National UniversityJejuRepublic of Korea Mechanical and System Design Engineering Hongik UniversitySeoulRepublic of Korea

Salter's duck,an asymmetrical wave energy converter(WEC)device,showed high efficiency in extracting energy from 2D regular waves in the past;yet,challenges remain for fluctuating wave *** can potentially be addressed by adopting a negative stiffness mechanism(NSM)in WEC devices to enhance system efficiency,even in highly nonlinear and steep 3D waves.A weakly nonlinear model was developed which incorporated a nonlinear restoring moment and NSM into the linear formulations and was applied to an asymmetric WEC using a time domain potential flow *** model was initially validated by comparing it with published experimental and numerical computational fluid dynamics *** current results were in good agreement with the published *** was found that the energy extraction increased in the range of 6%to 17%during the evaluation of the effectiveness of the NSM in regular *** irregular wave conditions,specifically at the design wave conditions for the selected test site,the energy extraction increased by 2.4%,with annual energy production increments of approximately *** findings highlight the potential of NSM in enhancing the performance of asymmetric WEC devices,indicating more efficient energy extraction under various wave conditions.

关键词： asymmetric wave energy converter negative stiffness mechanism weakly nonlinear potential flow power

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