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Search results for: MACHINE LEARNING, 3D-PRINTED FIBER REINFORCED CONCRETE, MODEL INTERPRETABILITY, COMPRESSIVE STRENGTH
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Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance
PublicationIdentification of active electrodes that record task-relevant neurophysiological activity is needed for clinical and industrial applications as well as for investigating brain functions. We developed an unsupervised, fully automated approach to classify active electrodes showing event-related intracranial EEG (iEEG) responses from 115 patients performing a free recall verbal memory task. Our approach employed new interpretable...
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CONCRETE MIX DESIGN USING ABRAMS AND BOLOMEY METHODS
PublicationOne way to reduce the consumption of cement is to optimize its use. Many known methods of concrete design, based on the Abrams law and the Bolomey method. Therefore, the authors chose those methods for analysis. The concrete composition with the assumed strength class, calculated by any method differs significantly. This applies especially to the cement content, as its content in the composition of concrete varies from 20 to 50%....
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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublicationBiomass management in terms of energy consumption optimization has become a recent challenge for developed countries. Nevertheless, the multiplicity of materials and operating parameters controlling energy consumption in wastewater treatment plants necessitates the need for sophisticated well-organized disciplines in order to minimize energy consumption and dissipation. Sewage sludge (SS) disposal management is the key stage of...
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublicationDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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Effect of free water on the quasi‑static compression behavior of partially‑saturated concrete with a fully coupled DEM/CFD approach.
PublicationThe work aims to numerically investigate the quasi-static response of partially fluid-saturated concrete under two-dimensional uniaxial compression at the mesoscale. We investigated how the impact of free pore fluid content (water and gas) affected the quasi-static strength of concrete. The totally and partially fluid-saturated concrete behavior was simulated using an improved pore-scale hydro-mechanical model based on DEM/CFD....
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Functional 3D-Printed Polymeric Materials with Metallic Reinforcement for Use in Cut-Resistant Gloves
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Self-compacting grout to produce two-stage concrete
PublicationTraditional concrete (TC) is primarily composed of a mixture of cement, fine and coarse aggregates, and water. TC is made by mixing together all the components before placing them. Using non-traditional concrete (two-stage concrete) to solve and to eliminate the problem of the aggregate segregation which appears in TC and in the self-compacting concrete. Two-stage concrete (TSC) consists of two main components, namely the grout...
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Predicting seismic response of SMRFs founded on different soil types using machine learning techniques
PublicationPredicting the Maximum Interstory Drift Ratio (M-IDR) of Steel Moment-Resisting Frames (SMRFs) is a useful tool for designers to approximately evaluate the vulnerability of SMRFs. This study aims to explore supervised Machine Learning (ML) algorithms to build a surrogate prediction model for SMRFs to reduce the need for complex modeling. For this purpose, twenty well-known ML algorithms implemented in Python software are trained...
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Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection
PublicationDue to the exponential rise of mobile technology, a slew of new mobile security concerns has surfaced recently. To address the hazards connected with malware, many approaches have been developed. Signature-based detection is the most widely used approach for detecting Android malware. This approach has the disadvantage of being unable to identify unknown malware. As a result of this issue, machine learning (ML) for detecting malware...
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Study the impact of design method preference on the usefulness of concrete and on CO2 emissions
PublicationPurpose – The research investigates the impact of concrete design methods on performance, emphasizing environmental sustainability. The study compares the modified Bolomey method and Abrams’ law in designing concretes. Significant differences in cement consumption and subsequent CO2 emissions are revealed. The research advocates for a comprehensive life cycle assessment, considering factors like compressive strength, carbonation...
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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublicationTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
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Estimation of the Ultimate Strength of FRP Strips-to-Masonry Substrates Bond
PublicationFiber-Reinforced Polymers (FRP) were developed as a new method over the past decades due to their many beneficial mechanical properties, and they are commonly applied to strengthen masonry structures. In this paper, the Artificial Neural Network (ANN), K-fold Cross-Validation (KFCV) technique, Multivariate Adaptive Regression Spline (MARS) method, and M5 Model Tree (M5MT) method were utilized to predict the ultimate strength of...
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From a Point Cloud to a 3D Model - an Exercise for Users of AutoCAD and Revit
PublicationThe paper presents a proposal of the topic of an exercise for students of building faculties as part of classes on 3D modelling. The task consists in creating a three-dimensional model based on the measurement obtained with the Leica P30 laser scanner. Due to the maximum number of points in the cloud in the presented programs, the output files must be properly cleared and reduced. The point cloud was pre-processed in Cyclone software....
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Simulations of spacing of localized zones in reinforced concrete beams using elasto-plasticity and damage mechanics with non-local softening
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Simulations of spacing of localized zones in reinforced concrete beams using elastic-plasticity and damage mechanics with non-local softening
PublicationArtykuł omawia obliczanie belek żelbetowych z uwzględnieniem lokalizacji odkształceń. Obliczenia wykonano przy zastosowaniu MES na bazie sprężysto-plastycznego prawa konstytutywnego i modelu zniszczeniowego uwzględniającego degradację sztywności rozszerzonego o długość charakterystyczną mikrostruktury za pomocą teorii nielokalnej.
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FE analysis of reinforced concrete corbels with enhanced continuum models
PublicationW artykule pokazano wyniki MES symulacji wsporników żelbetowych. Zachowanie wsporników modelowano przy zastosowaniu 3 różnych modeli betonu: sprężysto-plastycznego, degradacji sprężystej i rozmytych rys. Modele rozszerzono o długość mikrostruktury przy zastosowaniu teorii nielokalnej. Wyniki numeryczne porównano z doświadczeniami z literatury.
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Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
PublicationNowadays, Buckling-Restrained Brace Frames (BRBFs) have been used as lateral force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of BRBFs plays a key role in deciding to retrofit buildings after seismic excitation; however, existing formulas have limitations and cannot effectively help civil engineers, e.g., FEMA P-58, which is a conservative estimation method. Therefore, there is a need to...
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Strength parameters of polyester reinforced PVC coated fabric after short term creep loading in biaxial mode
PublicationThis study addresses the analysis of tensile strength parameters of the technical fabric VALMEX, which is composed of two orthogonal polyester thread families (named the warp and fill) and both sides PVC coated. The material was firstly subjected to 48-hour biaxial creep loading with the equal stress level in both orthogonal directions of the fabric. The stress levels were established as follows: 4.6 kN/m, 10.4 kN/m, 16.4 kN/m,...
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Machine Learning Modelling and Feature Engineering in Seismology Experiment
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Machine learning applied to bi-heterocyclic drugs recognition
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Personal bankruptcy prediction using machine learning techniques
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Stacking-Based Integrated Machine Learning with Data Reduction
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Data Reduction Algorithm for Machine Learning and Data Mining
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PERFORMANCE COMPARISON OF MACHINE LEARNING ALGORITHMS FOR PREDICTIVE MAINTENANCE
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Machine Learning for Sensorless Temperature Estimation of a BLDC Motor
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MACHINE LEARNING SYSTEM FOR AUTOMATED BLOOD SMEAR ANALYSIS
PublicationIn this paper the authors propose a decision support system for automatic blood smear analysis based on microscopic images. The images are pre-processed in order to remove irrelevant elements and to enhance the most important ones - the healthy blood cells (erythrocytes) and the pathologic (echinocytes). The separated blood cells are analyzed in terms of their most important features by the eigenfaces method. The features are the...
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INVESTIGATION OF THE LOMBARD EFFECT BASED ON A MACHINE LEARNING APPROACH
PublicationThe Lombard effect is an involuntary increase in the speaker’s pitch, intensity, and duration in the presence of noise. It makes it possible to communicate in noisy environments more effectively. This study aims to investigate an efficient method for detecting the Lombard effect in uttered speech. The influence of interfering noise, room type, and the gender of the person on the detection process is examined. First, acoustic parameters...
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MACHINE LEARNING–BASED ANALYSIS OF ENGLISH LATERAL ALLOPHONES
PublicationAutomatic classification methods, such as artificial neural networks (ANNs), the k-nearest neighbor (kNN) and selforganizing maps (SOMs), are applied to allophone analysis based on recorded speech. A list of 650 words was created for that purpose, containing positionally and/or contextually conditioned allophones. For each word, a group of 16 native and non-native speakers were audio-video recorded, from which seven native speakers’...
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Machine learning system for estimating the rhythmic salience of sounds.
PublicationW artykule przedstawiono badania dotyczące wyszukiwania danych rytmicznych w muzyce. W pracy przedstawiono postać funkcji rankingujacej poszczególnych dźwięków frazy muzycznej. Opracowano metodę tworzenia wszystkich możliwych hierarchicznych struktur rytmicznych, zwanych hipotezami rytmicznymi. Otrzymane hipotezy są następnie porządkowane w kolejności malejącej wartości funkcji rankingującej, aby ustalić, która ze znalezionych...
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Reliability model of the crankshaft-piston assembly
PublicationThe laws that govern the durability of crankshaft-piston assembly friction nodes can be proved or at least derived or justified in an intuitive way. Operation of all the friction nodes is disturbed by external factors occurring with randomly changing intensity and also appearing at random. As the crankshaft-piston assembly friction nodes have a series structure and effects of those disturbances accumulate, their fitness for use...
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The vibration-based assessment of the influence of elevated temperature on the condition of concrete beams with pultruded GFRP reinforcement
PublicationConcrete beams reinforced with glass fiber reinforced polymer (GFRP) bars subjected to elevated temperature have been experimentally studied. The influence of high temperatures on GFRP-reinforced concrete beams condition has been check both, destructively and nondestructively. The nondestructive tests foresaw vibration-based tests to obtain the natural frequency values after exposure to varying temperatures. The vibration-based...
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Experimental ultimate strength assessment of stiffened plates subjected to marine immersed corrosion
PublicationThis study experimentally analyses the impact of marine immersed corrosion degradation on the compressive strength of the stiffened plates where the lower degradation levels were considered. The corrosion degradation test was accelerated by controlling the natural corrosion environmental factors, avoiding applying an electric current. Different groups of corrosion degradation levels and initial plate thicknesses were investigated....
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Self-compacting grout to produce two-stage concrete
PublicationTraditional concrete (TC) is primarily composed...
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Experiments and calibration of a bond-slip relation and efficiency factors for textile reinforcement in concrete
PublicationTextile reinforcement yarns consist of many filaments, which can slip relative each other. At modelling of the global structural behaviour, interfilament slip in the yarns, and slip between the yarns and the concrete can be considered by efficiency factors for the stiffness and strength of the yarns, and by applying a bond-slip relation between yarns and concrete. In this work, an effective and robust method for calibration of...
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Rapid Surrogate-Aided Multi-Criterial Optimization of Compact Microwave Passives Employing Machine Learning and ANNs
PublicationThis article introduces an innovative method for achieving low-cost and reliable multi-objective optimization (MO) of microwave passive circuits. The technique capitalizes on the attributes of surrogate models, specifically artificial neural networks (ANNs), and multi-resolution electromagnetic (EM) analysis. We integrate the search process into a machine learning (ML) framework, where each iteration produces multiple infill points...
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Fracture evolution in concrete compressive fatigue experiments based on X-ray micro-CT images
PublicationArtykuł omawia ewolucje pękania w betonie podczas cyklicznego ściskania betonu. Przestrzenną ewolucję pękania zobrazowano stosując mikro-tomograf rentgenowski. Zdjęcia wykonano dla różnych cykli zmęczeniowych. Wyniki porównano z testami monotonicznymi. Jakościowa ewolucja objętości pękania ze wzrostem zmęczeniowego zniszczenia pokazała silnie nieliniowy kształt.
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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublicationThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...
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Experimental and Numerical Study on Mechanical Characteristics of Aluminum/Glass Fiber Composite Laminates
PublicationThe fiber-metal composites made of aluminum sheets and glass fibers reinforced with a polyester resin as the matrix were studied. The composites were prepared by hand lay-up method. Some aspects of manufacturing affecting the composite behavior were considered. In particular, the influences of the arrangement of layers and their number on the mechanical and physical properties of composites with ten different compositions were...
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Towards development of sustainable lightweight 3D printed wall building envelopes – Experimental and numerical studies
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Susceptibility to biofilm formation on 3D-printed titanium fixation plates used in the mandible: a preliminary study
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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublicationThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
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Reduced model of gyroscopic system
PublicationThe paper presents the method of model reduction for the system with gyroscopic interactions. Two methods were used to obtain the approximate discrete models of the continuous structure: the modal decomposition method and the rigid finite element method. The first approach is used for this part of a system for which it is easy to formulate orthogonality conditions, meanwhile the second one is used for other part. The method enables...
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Feature Importance of Stabilised Rammed Earth Components Affecting the Compressive Strength Calculated with Explainable Artificial Intelligence Tools
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Three dimensional simulations of FRC beams and panels with explicit definition of fibres-concrete interaction
PublicationHigh performance concrete (HPC) is a quite novel material which has been rapidly developed in the last few decades. It exhibits superior mechanical properties and durability comparing to normal concrete. HPC can achieve also superior tensile performance if strong fibres (steel or carbon) are implemented in the matrix. Thus, there exist the unabated interest in studying how the addition of different types of fibres modifies the...
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The Influence of the Aircraft Operating Fluids on the Mechanical Parameters of the Airport Surface Concrete
PublicationThe authors of the article assessed the impact of operating fluids used to service aircraft on changing mechanical parameters of cement concrete intended for airport pavement. The research concerned concrete designed with the use of CEM I 42.5N LH NA low-alkali cement, broken granite aggregate, fine washed aggregate, and admixtures. The analysis included the assessment of changes in dierences in endurance parameters over various...
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The application of a photopolymer material for the manufacture of machine elements using rapid prototyping techniques
PublicationThe paper discusses the application of polymer resin for 3D printing. The first section focuses on rapid prototyping technique and properties of the photopolymer, used as input material in the manufacture of machine components. Second part of the article was devoted to exemplary 3-D-printed elements for incorporation in machines. The article also contains detailed description of problems encountered in implementation of the selected...
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Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning
PublicationTheophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally...
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Machine-Learning-Powered EM-Based Framework for Efficient and Reliable Design of Low Scattering Metasurfaces
PublicationPopularity of metasurfaces has been continuously growing due to their attractive properties including the ability to effectively manipulate electromagnetic (EM) waves. Metasurfaces comprise optimized geometries of unit cells arranged as a periodic lattice to obtain a desired EM response. One of their emerging application areas is the stealth technology, in particular, realization of radar cross section (RCS) reduction. Despite...
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Selected Aspects of 3D Printing for Emergency Replacement of Structural Elements
PublicationThe paper presents a synthetic characterization of modern methods of manufacturing or regenerating machine elements. Considered methods are machining and additive methods, in particular 3D printing in the FDM/FFF technique. For the study, the authors made samples of the holder bracket using selected methods. Samples made by machining operations, 3D printing with various filling were tested. The paper contains a technical and economic...
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Customization of UWB 3D-RTLS Based on the New Uncertainty Model of the AoA Ranging Technique
PublicationThe increased potential and effectiveness of Real-time Locating Systems (RTLSs) substantially influence their application spectrum. They are widely used, inter alia, in the industrial sector, healthcare, home care, and in logistic and security applications. The research aims to develop an analytical method to customize UWB-based RTLS, in order to improve their localization performance in terms of accuracy and precision. The analytical...