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wyświetlamy 1000 najlepszych wyników Pomoc
Wyniki wyszukiwania dla: MACHINE LEARNING, 3D-PRINTED FIBER REINFORCED CONCRETE, MODEL INTERPRETABILITY, COMPRESSIVE STRENGTH
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Raman studies of 3D printed CB-PLA samples after microwave treatment
Dane BadawczeThis dataset contains Raman spectroscopy analyses of microwave-activated carbon-black doped polylactic acid 3D printed electrodes.
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
PublikacjaWetlands provide vital ecological and socioeconomic services but face escalating pressures worldwide. This study undertakes an integrated spatiotemporal assessment of the multifaceted vulnerabilities shaping Khinjhir Lake, an ecologically significant wetland ecosystem in Pakistan, using advanced geospatial and machine learning techniques. Multi-temporal optical remote sensing data from 2000 to 2020 was analyzed through spectral...
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Moisture Influence on Compressive Strength of Calcium Silicate Masonry Units–Experimental Assessment and Normative Calculations
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Damage detection in 3D printed plates using ultrasonic wave propagation supported with weighted root mean square calculation and wavefield curvature imaging
Publikacja3D printing (additive manufacturing, AM) is a promising approach to producing light and strong structures with many successful applications, e.g., in dentistry and orthopaedics. Many types of filaments differing in mechanical properties can be used to produce 3D printed structures, including polymers, metals or ceramics. Due to the simplicity of the manufacturing process, biodegradable polymers are widely used, e.g., polylactide (polylactide...
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Evaluation of pounding effects between reinforced concrete frames subjected to far-field earthquakes in terms of damage index
PublikacjaIn this paper, three different damage indexes were used to detect nonlinear damages in two adjacent Reinforced Concrete (RC) structures considering pounding effects. 2-, 4- and 8-story benchmark RC Moment Resisting Frames (MRFs) were selected for this purpose with 60%, 75%, and 100% of minimum separation distance and also without any in-between separation gap. These structures were analyzed using the incremental dynamic analysis...
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Autonomous Perception and Grasp Generation Based on Multiple 3D Sensors and Deep Learning
PublikacjaGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublikacjaMaximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit...
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Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning
PublikacjaMethods Results Discussion References Abbreviations Copyright Abstract Background: The spread of false medical information on the web is rapidly accelerating. Establishing the credibility of web-based medical information has become a pressing necessity. Machine learning offers a solution that, when properly deployed, can be an effective tool in fighting medical misinformation on the web. Objective: The aim of this study is to...
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Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study
PublikacjaThis study explores the edaravone solubility space encompassing both neat and binary dissolution media. Efforts were made to reveal the inherent concentration limits of common pure and mixed solvents. For this purpose, the published solubility data of the title drug were scrupulously inspected and cured, which made the dataset consistent and coherent. However, the lack of some important types of solvents in the collection called...
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Mechanical properties of two-stage concrete modified by silica fume
PublikacjaAbstract. Two-stage concretes, despite the fact that they have proven themselves in various types of construction, have not been studied to the same extent as traditional heavy concretes. Therefore, the article developed the composition of frame concrete with various additives in the composition of the cement-sand mortar. A comparison of the mechanical characteristics of the developed compositions with the addition of silica fume...
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Ultrasonic wave propagation and digital image correlation measurements of polyolefin fibre-reinforced concrete beams under 3-point bending (beam B-002)
Dane BadawczeThe DataSet contains the results of the mechanical behaviour of a concrete beam under a 3-point bending test. The beams had dimensions 15 x 15 x 70 cm3. The beam B-Con was made of concrete without fibres (as the reference beam), while beams B-002, B-004, and B-006 were manufactured from the concrete mix containing 2 kg/m3, 4 kg/m3 and 6 kg/m3 of fibres,...
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Ultrasonic wave propagation and digital image correlation measurements of polyolefin fibre-reinforced concrete beams under 3-point bending (beam B-Con)
Dane BadawczeThe DataSet contains the results of the mechanical behaviour of a concrete beam under a 3-point bending test. The beams had dimensions 15 x 15 x 70 cm3. The beam B-Con was made of concrete without fibres (as the reference beam), while beams B-002, B-004, and B-006 were manufactured from the concrete mix containing 2 kg/m3, 4 kg/m3 and 6 kg/m3 of fibres,...
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Ultrasonic wave propagation and digital image correlation measurements of polyolefin fibre-reinforced concrete beams under 3-point bending (beam B-004)
Dane BadawczeThe DataSet contains the results of the mechanical behaviour of a concrete beam under a 3-point bending test. The beams had dimensions 15 x 15 x 70 cm3. The beam B-Con was made of concrete without fibres (as the reference beam), while beams B-002, B-004, and B-006 were manufactured from the concrete mix containing 2 kg/m3, 4 kg/m3 and 6 kg/m3 of fibres,...
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Ultrasonic wave propagation and digital image correlation measurements of polyolefin fibre-reinforced concrete beams under 3-point bending (beam B-006)
Dane BadawczeThe DataSet contains the results of the mechanical behaviour of a concrete beam under a 3-point bending test. The beams had dimensions 15 x 15 x 70 cm3. The beam B-Con was made of concrete without fibres (as the reference beam), while beams B-002, B-004, and B-006 were manufactured from the concrete mix containing 2 kg/m3, 4 kg/m3 and 6 kg/m3 of fibres,...
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THE 3D MODEL OF WATER SUPPLY NETWORK WITH APPLICATION OF THE ELEVATION DATA
Publikacja3D visualization is a key element of research and analysis and as the source used by experts in various fields e.g.: experts from water and sewage systems. The aim of this study was to visualize in three-dimensional space model of water supply network with relief. The path of technological development of GESUT data (Geodezyjna Ewidencja Sieci Uzbrojenia Terenu – geodetic records of public utilities) for water supply and measurement...
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An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublikacjaThis study presents an advanced algorithm for selecting machine learning (ML) models for nitrous oxide (N2O) emission prediction in wastewater treatment plants (WWTPs) employing the activated sludge process. The examined ML models comprised multivariate adaptive regression spline (MARS), support vector machines (SVM), and extreme gradient boosting (XGboost). The study explores the concept that involves new criteria to select the...
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Experimental Studies of Concrete-Filled Composite Tubes under Axial Short- and Long-Term Loads
PublikacjaThe paper presents experimental studies on axially compressed columns made of concrete-filled glass fiber reinforced polymer (GFRP) tubes. The infill concrete was C30/37 according to Eurocode 2. The investigated composite pipes were characterized by different angles of fiber winding in relation to the longitudinal axis of the element: 20, 55 and 85 degrees. Columns of two lengths, 0.4 m and 2.0 m, were studied. The internal diameter...
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Deep Learning Basics 2023/24
Kursy OnlineA course about the basics of deep learning intended for students of Computer Science. It includes an introduction to supervised machine learning, the architecture of basic artificial neural networks and their training algorithms, as well as more advanced architectures (convolutional networks, recurrent networks, transformers) and regularization and optimization techniques.
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Discrete element method modelling of elastic wave propagation in a meso-scale model of concrete
PublikacjaThis paper deals with the accurate modelling of ultrasonic wave propagation in concrete at the mesoscopic level. This was achieved through the development of a discrete element method (DEM) model capable of simulating elastic wave signals comparable to those measured experimentally. The main objective of the work was to propose a novel methodology for constructing a meso-scale model of concrete dedicated to the analysis of elastic...
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FTIR Study and Mechanical Properties of Cellulose Fiber-Reinforced Thermoplastic Composites
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Quasi-Static and Dynamic Testing of Carbon Fiber Reinforced Magnesium Composites
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PROPERTIES OF FIBER REINFORCED CEMENT COMPOSITES WITH CENOSPHERES FROM COAL ASH
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Foundations and Trends in Machine Learning
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Machine Learning and Knowledge Extraction
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Machine Learning-Science and Technology
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Influence of the Addition of Recycled Aggregates and Polymer Fibers on the Properties of Pervious Concrete
PublikacjaThe aim of the study was to check the possibility of reusing aggregate from recycled concrete waste and rubber granules from car tires as partial substitution of natural aggregate. The main objective was to investigate the effects of recycled waste aggregate modified with polymer fibers on the compressive and flexural strength, modulus of elasticity and permeability of pervious concrete. Fibers with a multifilament structure and...
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The chemistry, properties and performance of flame-retardant rubber composites: Collecting, analyzing, categorizing, machine learning modeling, and visualizing
PublikacjaRubbers combine the flexibility with mechanical strength, supporting myriad applications, but suffer from inherent flammability. Formulation and production of flame-retardant rubber composites (FRRCs) have intensively been practiced over years, but not comprehensively reviewed. This necessity has outlined collecting, analyzing, screening, classifying, and interpreting the literature with the aim of classifying the FRRCs. We quantified...
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
PublikacjaCirculating tumor cells (CTCs) are tumor cells that separate from the solid tumor and enter the bloodstream, which can cause metastasis. Detection and enumeration of CTCs show promising potential as a predictor for prognosis in cancer patients. Furthermore, single-cells sequencing is a technique that provides genetic information from individual cells and allows to classify them precisely and reliably. Sequencing data typically...
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Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance
PublikacjaIdentification 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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SELECTED PROBLEMS OF MACHINE DYNAMICS (2024)
Kursy OnlineThe course is devoted towards lectures assocuated with the novel issues of machine and structures dynamics. The following lectures will be given during the SPMD course: - introduction to selected problems of machine dynamics, - definition of the machine and structure working environment, - internal and external loads on machines and structures, - dynamics of machines and structures, - strength of machines and structures, - special...
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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublikacjaBiomass 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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CONCRETE MIX DESIGN USING ABRAMS AND BOLOMEY METHODS
PublikacjaOne 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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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublikacjaDesigning 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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Functional 3D-Printed Polymeric Materials with Metallic Reinforcement for Use in Cut-Resistant Gloves
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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.
PublikacjaThe 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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Predicting seismic response of SMRFs founded on different soil types using machine learning techniques
PublikacjaPredicting 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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Self-compacting grout to produce two-stage concrete
PublikacjaTraditional 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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Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection
PublikacjaDue 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
PublikacjaPurpose – 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
PublikacjaTreatment 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
PublikacjaFiber-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
PublikacjaThe 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
PublikacjaArtykuł 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
PublikacjaW 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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Mechanical properties of VL E27 steel for shipbuilding – 3D model of fracture (test in +20°C)
Dane BadawczeOne of the basic divisions of steels used for ship hulls and ocean engineering structures is the division into: normal strength steels, high strength steels and extra high strength steels. The belonging to the group is determined by the mechanical properties of the steel, such as: yield point, ultimate strength and plastic elongation after fracture....
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Mechanical properties of VL E27 steel for shipbuilding – 3D model of fracture (test in 0°C)
Dane BadawczeOne of the basic divisions of steels used for ship hulls and ocean engineering structures is the division into: normal strength steels, high strength steels and extra high strength steels. The belonging to the group is determined by the mechanical properties of the steel, such as: yield point, ultimate strength and plastic elongation after fracture....
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Mechanical properties of VL E27 steel for shipbuilding – 3D model of fracture (test in -20°C)
Dane BadawczeOne of the basic divisions of steels used for ship hulls and ocean engineering structures is the division into: normal strength steels, high strength steels and extra high strength steels. The belonging to the group is determined by the mechanical properties of the steel, such as: yield point, ultimate strength and plastic elongation after fracture....
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Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
PublikacjaNowadays, 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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Machine learning system for estimating the rhythmic salience of sounds.
PublikacjaW 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...