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3rd International Conference on Data Mining

作者： Curotto, CL Ebecken, NFF CESEC UFPR Civil Engineering Graduate Program Brazil COPPE UFRJ Civil Engineering Graduate Program Brazil

ISBN: (纸本)1853129259

The OLE DB for DM (Microsoft's object-based technology for sharing information and services across process and machine boundaries focused on database mining applications) specification provides an industry standard for implementation of data mining algorithms aggregated with Microsoft SQL Server 2000. The Simple Naive Bayes classifier is,, implemented using the OLE DB for DM Resource Kit. Numeric input attributes, multiple prediction trees and incremental classification are considered. All necessary steps to implement this algorithm are explained and discussed. Some results are shown to illustrate the capabilities of the implementation.

关键词： Data mining

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Development of ceramic membranes from sugarcane bagasse ash for microfiltration of biodiesel production effluents

Open Ceramics

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Open Ceramics 2025年 22卷

作者： Pin, Clarissa Ferreira Brandler, Danieli Flores, Gabriela Cristina Perusin Kubiaki Levandoski, William Mateus Bruschi, Giovani Jordi Pelissaro, Deise Trevizan Dervanoski, Adriana Korf, Eduardo Pavan Pasquali, Gean Delise Leal Graduate Program in Enviromental Science and Technology Federal University of Fronteira Sul Erechim/RS 99700-970 Brazil Departament of Civil Engineering Integrated Regional University of Alto Uruguai and Missões – Erechim/RS 99709-910 Brazil Departament of Environmental and Sanitary Engineering Federal University of Fronteira Sul Erechim/RS 99700-970 Brazil

Ceramic membranes have emerged as a promising solution for microfiltration processes, offering advantages such as cost-effectiveness, environmental benefits, and the utilization of abundant raw materials derived from agro-industrial solid waste. This study investigates the fabrication and performance of ceramic membranes composed of kaolin the varying proportions of sugarcane bagasse ash (SCBA - 40 wt % and 60 wt %), with focus on efficiency in treating biodiesel wastewater. The membranes were characterized (porosity, average pore diameter, and mechanical strength). The membrane containing 40 wt % SCBA - employed without any pre-treatment- exhibited the best overall performance, achieving porosity of 38.5 %, an pore diameter of 0.9 µm, and mechanical strength of 27 MPa, indicating a favorable balance between permeability and structural integrity. The best-performing membrane achieved removal efficiencies of color 83 % and turbidity 67 %. Microstructural analysis revealed a network of interconnected mesopores, which are particularly effective for the retention of colloidal and suspended contaminants. © 2025 The Authors

关键词： Agro-industrial solid waste Industrial effluent Membrane filtration

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CAD and CAE Integration Through Scientific Visualization Techniques for Illumination Design

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Tsinghua Science and Technology 2008年第S1期13卷 26-33页

作者： Tiago Martinuzzi Buriol Sergio Scheer Graduate Program in Numerical Methods for Engineering Civil Engineering Research Center Federal University of Parana

Engineers tend to use different software to perform tasks such as geometry modeling, database management, numerical analysis, and visualization. This may cause decrease of productivity and loss of information during the conversion process between different data file formats. This paper presents a computer aided design (CAD) and computer aided engineering (CAE) system integration using scientific visualization tools and techniques. It deals with the development of a 3D CAD add-in for lighting analysis which uses the CAD model as 3D interface for creating a lighting scheme, processing, and visualizing 2D or 3D illuminance fields. Visualization features as color and contour mapping were developed using the visualization toolkit (VTK) toolkit. The application integrates all functionalities of the 3D CAD with tools for light sources database management, pre-processing, processing, and post-processing of illuminance fields in a single environment. This approach increases productivity and eliminates the need for different software.

关键词： illumination design scalar fields post-processing 3D computer aided design (CAD) visualization toolkit (VTK) systems integration

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Application of machine learning technique for predicting and evaluating chloride ingress in concrete

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Frontiers of Structural and civil engineering 2022年第9期16卷 1153-1169页

作者： Van Quan TRAN Van Loi GIAP Dinh Phien VU Riya Catherine GEORGE Lanh Si HO Department of Civil Engineering University of Transport TechnologyHanoi 100000Vietnam Civil and Environmental Engineering Program Graduate School of Advanced Science and EngineeringHiroshima UniversityHiroshima 739-8527Japan

The degradation of concrete structure in the marine environment is often related to chloride-induced corrosion of reinforcement ***,the chloride concentration in concrete is a vital parameter for estimating the corrosion level of reinforcement *** research aims at predicting the chloride content in concrete using three hybrid models of gradient boosting(GB),artificial neural network(ANN),and random forest(RF)in combination with particle swarm optimization(PSO).The input variables for modeling include exposure condition,water/binder ratio(W/B),cement content,silica fume,time exposure,and depth of *** results indicate that three models performed well with high accuracy of prediction(R2⩾0.90).Among three hybrid models,the model using GB_PSO achieved the highest prediction accuracy(R2=0.9551,RMSE=0.0327,and MAE=0.0181).Based on the results of sensitivity analysis using SHapley Additive exPlanation(SHAP)and partial dependence plots 1D(PDP-1D),it was found that the exposure condition and depth of measurement were the two most vital variables affecting the prediction of chloride *** the number of different exposure conditions is larger than two,the exposure significantly impacted the chloride content of concrete because the chloride ion ingress is affected by both chemical and physical *** study provides an insight into the evaluation and prediction of the chloride content of concrete in the marine environment.

关键词： gradient boosting random forest chloride content concrete sensitivity analysis

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Nitrite impairs bioreactor performance due to decreased replication of Candidatus Brocadia sapporoensis by unbalanced energy allocation

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Water Research 2025年 283卷 123806页

作者： Qiao, Xuejiao Zhang, Liyu Qiu, Zhiguang Wu, Yang Deng, Chunfang Geng, Yanni Zhang, Yichi Yan, Yan Li, Bing Zhang, Lijuan Zhuang, Wei-Qin Yu, Ke Eco-environment and Resource Efficiency Research Laboratory School of Environment and Energy Peking University Shenzhen Graduate School Guangdong Shenzhen518055 China -Preferred Program Peking University Shenzhen518055 China State Key Laboratory of Isotope Geochemistry CAS Center for Excellence in Deep Earth Science Guangzhou Institute of Geochemistry Chinese Academy of Sciences Guangdong Guangzhou510000 China Shenzhen Engineering Research Laboratory for Sludge and Food Waste Treatment and Resource Recovery Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen518055 China Department of Civil and Environmental Engineering The University of Auckland Auckland New Zealand

The effects of nitrite on anammox activities have been extensively studied. However, the molecular mechanisms of specific microorganisms responding to nitrite in anammox systems remain unexplored. This study investigates how excessive nitrite affects the core metabolisms of AnAOB and symbiotic bacteria, further elucidating the mechanisms by which it regulates microbial growth and nitrogen removal performance. Specifically, the nitrogen removal process in a continuous-flow anammox membrane bioreactor collapsed when the nitrite concentration reached 243 mg N/L. Integrated meta-omics analyses demonstrated that excessive nitrite disrupted the energy metabolism of Ca. Brocadia sapporoensis (AMXB1), reducing the energy available for developing tolerance. Subsequently, it disrupted cell replication by impairing the biosynthesis process of AMXB1, particularly DNA replication and the formation of vital cell structures such as the cell membrane and cell wall, as well as the cellular protection system, leading to the collapse of the anammox system. Additionally, the cross-feeding of amino acids and cofactors between AMXB1 and symbiotic bacteria plays an important role in the recovery of nitrogen removal performance of anammox consortia after nitrite inhibition. The findings provide a novel strategy and direction for improving the tolerance and resilience of anammox consortia in engineered ecosystems. © 2025

关键词： Listeria

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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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A hybrid machine learning model to estimate self-compacting concrete compressive strength

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Frontiers of Structural and civil engineering 2022年第8期16卷 990-1002页

作者： Hai-Bang LY Thuy-Anh NGUYEN Binh Thai PHAM May Huu NGUYEN Civil Engineering Department University of Transport TechnologyHanoi 100000Vietnam Civil and Environmental Engineering Program Graduate School of Advanced Science and EngineeringHiroshima UniversityHiroshima 739-8527Japan

This study examined the feasibility of using the grey wolf optimizer(GWO)and artificial neural network(ANN)to predict the compressive strength(CS)of self-compacting concrete(SCC).The ANN-GWO model was created using 115 samples from different sources,taking into account nine key SCC *** validation of the proposed model was evaluated via six indices,including correlation coefficient(R),mean squared error,mean absolute error(MAE),IA,Slope,and mean absolute percentage *** addition,the importance of the parameters affecting the CS of SCC was investigated utilizing partial dependence *** results proved that the proposed ANN-GWO algorithm is a reliable predictor for SCC’s *** that,an examination of the parameters impacting the CS of SCC was provided.

关键词： artificial neural network grey wolf optimize algorithm compressive strength self-compacting concrete

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Electrocoagulation+biochar hybrid process for the treatment of printing industry wastewater

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Journal of Water Process engineering 2025年 73卷

作者： Koslowski, Luciano André Deitos Cristofolini, Milena Pauli, Camila Schwarz Lach, Carlos Eduardo Paulino, Alexandre Tadeu Santa Catarina State University-UDESC Graduate Program in Applied Chemistry College of Technological Science - CCT Santa Catarina Joinville Brazil Santa Catarina State University-UDESC College CEAVI Department of Sanitary Engineering Santa Catarina Ibirama Brazil Santa Catarina State University-UDESC College CEAVI Department of Civil Engineering Santa Catarina Ibirama Brazil

This study investigates the use of a hybrid process for the treatment of printing ink wastewater employing conventional electrocoagulation with aluminum electrodes combined with a biochar filtration column. Strategies were employed to determine the most appropriate variables for greater operational efficiency: electric current intensity (1, 2, and 3 A), electrolysis time (20, 30, and 40 min), and electrode spacing (6, 8, and 10 cm), assessing the color removal, turbidity, pH, chemical oxygen demand, and the formation of residual aluminum. The electrocoagulation+biochar hybrid process was then implemented using the biochar column and the effects of the two processes were compared. An effluent with a greater degree of polish was achieved when employing the electrocoagulation+biochar hybrid process. The results revealed a reduction in COD from 775 mg/L to 377 mg/L via conventional electrocoagulation and 212 mg/L employing the hybrid process. Removal efficiency was 51.35 % with conventional electrocoagulation and 72.64 % with the electrocoagulation+biochar hybrid process. The hybrid process also led to the removal of dissolved aluminum after the electrocoagulation process, with a concentration of <0.10 mg/L, whereas the concentration of dissolved aluminum after conventional electrocoagulation was 0.518 mg/L, with an aluminum removal rate of up to 96.77 % employing the hybrid process. The electrocoagulation+biochar hybrid process treatment process is a promising approach for the treatment of printing industry wastewater and could also be applied in studies involving the treatment of wastewater containing organic pollutants, heavy metals, and persistent organic compounds. © 2025 Elsevier Ltd

关键词： Biochar adsorption Electrocoagulation Residual aluminum Taguchi method Wastewater treatment

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Recovery of tire rubber waste after UV treatment as a recycled aggregate in cementitious composites

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Materials Today: Proceedings 2022年 58卷 1476-1479页

作者： Celestino, Roberta Aboelkheir, Mostafa Galal Sao Judas Tadeu University Civil Engineering Graduate Program Sao Paulo Brazil

Rubber is an extremely important source of raw material for the world industry, being used for various purposes. This diversification of applications is due to the vulcanization process that rubber undergoes to acquire an increase in its mechanical properties. A large amount of tire rubber is incorrectly discarded due to a lack of recycling alternatives, thus increasing the risk to the environment and public health around the world. One of the alternatives for valuing rubber is its use in civil construction by inserting it in cement matrices. If the crushed rubber is treated by physicochemical methods before mixing in with cement, possible improvements in the mechanical, thermal and acoustic properties of the cementitious mixture can be achieved. This work has as main objective to prepare a coating mortar through volumetric replacements of 5, 10, 15 and 20% of the fine aggregate by crushed tire rubber and treated by ultraviolet irradiation. Rubber samples were submitted at different times of exposure to UV irradiation for 12 h. After treating the rubber samples, the compressive strength, flexure strength and dynamic elasticity modulus of the rubber-modified mortar were characterized. From the findings, it was observed that the greater the addition of rubber to the mixture, the lower its dynamic modulus and mechanical strengths, as well. The specimens with 20% of substitution registered the lowest modulus value, which indicates that the material produced from this composite has greater deformability compared to other mixtures. Analysing the mechanical tests, it was observed that with the addition of rubber to the mixture there was a decrease in compressive strength. This is due to the fact that rubber is hydrophobic, making it difficult for water to migrate into the mixture, and consequently, decreasing the resistance of the mixture. In addition to the ductile nature of rubber itself, which behaves as a void within the mixture and does not help in load transition fro

关键词： Rubber

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STRUCTURAL ASSESSMENT OF COMPOSITE HIGHWAY BRIDGES CONSIDERING VEHICLE-BRIDGE DYNAMIC INTERACTION

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ce/papers 2024年第1-2期7卷 165-174页

作者： da Silva, Ana Célia Soares Alencar, Guilherme Santana da Silva, José Guilherme Santos Civil Engineering Post-graduate Program [PGECIV/UERJ Brazil Brazil Brazil

Over time, as the bridge deck pavement deterioration process increases, the calculated vertical translational displacements and stresses are higher. In this context, the chances of mechanical failure occurrence increase and may cause limitation in the service life of steel and composite (steel-concrete) bridges. Thus, the current work presents a methodology for fatigue analysis developed by the authors through the years. The methodology is devoted specifically for the assessment of composite bridges employing the hot-spot local S-N approach and a coupled vehicle-pavement-bridge system considering progressive pavement deterioration with stochastically generated roughness profiles. © 2024 Ernst & Sohn GmbH.

关键词： Deterioration

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