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Wyniki wyszukiwania dla: MACHINE LEARNING, 3D-PRINTED FIBER REINFORCED CONCRETE, MODEL INTERPRETABILITY, COMPRESSIVE STRENGTH
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Designing acoustic scattering elements using machine learning methods
PublikacjaIn the process of the design and correction of room acoustic properties, it is often necessary to select the appropriate type of acoustic treatment devices and make decisions regarding their size, geometry, and location of the devices inside the room under the treatment process. The goal of this doctoral dissertation is to develop and validate a mathematical model that allows predicting the effects of the application of the scattering...
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Detection of debonding in reinforced concrete beams using ultrasonic transmission tomography and hybrid ray tracing technique
PublikacjaThis paper concerns inspection of reinforced concrete elements, with particular emphasis on assessing the quality of the adhesive connection between steel and concrete. A novel theoretical model was developed to determine the paths of transmitted, refracted and reflected elastic waves as well as a creeping wave propagated along the inclusion surface. Imaging the internal structure of tested beams was based on wave propagation measurements...
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Prediction of cast-in-place concrete strength of the extradosed bridge deck based on temperature monitoring and numerical simulations
PublikacjaThe work is devoted to the implementation of a monitoring system for high performance concrete embedded in the span of an extradosed bridge deck using a modified maturity method augmented by numerical simulations conducted by the authors’ FEM code. The paper presents all research stages of bridge construction and considers the conclusions drawn from the results of laboratory tests, field measurements, and numerical calculations....
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Ultrasound monitoring for evaluation of damage in reinforced concrete
PublikacjaThe paper deals with automated monitoring of damage evolution in concrete elements subjected to three-point bending tests. The monitoring is based on the nonlinear interactions of traveling ultrasonic waves with micro-crack zones inside the concrete specimens and surface-breaking cracks. The developed procedure assumes semi-continuous ultrasonic testing during the element full loading cycle and generation of the power spectral...
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RMS-based damage detection in reinforced concrete beams: numerical simulations
PublikacjaImage-based damage detection methods using guided waves are well known and widely applied approaches in structural diagnostics. They are usually utilized in detection of surface damages or defects of plate-like structures. The article presents results of the study of applicability of imaging wave-based methods in detection in miniscule internal damage in the form of debonding. The investigations were carried out on numerical models...
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Shear resistance of low height precast concrete lintels
PublikacjaThe scope of the paper is to investigate analytically and determine experimentally the shear resistance of low height reinforced precast concrete lintels. The chosen procedures included in national and international standards applied for the design of structural concrete elements to an estimation of shear behaviour of reinforced concrete elements are described. The characteristic and designed shear strength of precast concrete...
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The influence of reinforcement on load carrying capacity and cracking of the reinforced concrete deep beam joint
PublikacjaThe paper presents the results of experimental research of the spatial reinforced concrete deep beam systems orthogonally reinforced and with additional inclined bars. Joint of the deep beams in this research was composed of the longitudinal deep beam with a cantilever suspended at the transversal deep beam. The cantilever deep beam was loaded throughout the depth and the transversal deep beam was loaded at the mid-span by longitudinal...
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A Machine Learning Approach for Estimating Overtime Allocation in Software Development Projects
PublikacjaOvertime planning in software projects has traditionally been approached with search-based multi-objective optimization algorithms. However, the explicit solutions produced by these algorithms often lack applicability and acceptance in the software industry due to their disregard for project managers' intuitive knowledge. This study presents a machine learning model that learns the preferred overtime allocation patterns from solutions...
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Low-cost 3D Printed Circularly Polarized Lens Antenna for 5.9 GHz V2X Applications
PublikacjaThis paper presents design and realization of a circularly polarized antenna consisting of a linearly polarized patch antenna and a 3D printed lens, at the same time performing the functions of wave collimator and a polarizer. The antenna is dedicated for 802.11p systems, as a part of road infrastructure, with operation bandwidth 5.85 - 5.925 GHz. Its realised gain and axial ratio at center frequency 5.9 GHz are 14.3 dBi and 2.17...
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Textile reinforced concrete members subjected to tension, bending, and in-plane loads: Experimental study and numerical analyses
PublikacjaTextile reinforced concrete has raised increasing research interest during the last years, mainly due to its potential to be used for freeform shell structures involving complex load situations. Yet, most experimental work has focused on test setups with primarily uniaxial loading. In the current work, such setups are complemented with a novel test setup of deep beams, including in-plane bending and shear. Further, nonlinear finite...
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Debonding Size Estimation in Reinforced Concrete Beams Using Guided Wave-Based Method
PublikacjaThe following paper presents the results of the theoretical and experimental analysis of the influence of debonding size on guided wave propagation in reinforced concrete beams. The main aim of the paper is a development of a novel, baseline-free method for determining the total area of debonding between steel rebar embedded in a concrete cover on the basis of the average wave velocity or the time of flight. The correctness of...
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Process of Medical Dataset Construction for Machine Learning-Multifield Study and Guidelines
PublikacjaThe acquisition of high-quality data and annotations is essential for the training of efficient machine learning algorithms, while being an expensive and time-consuming process. Although the process of data processing and training and testing of machine learning models is well studied and considered in the literature, the actual procedures of obtaining data and their annotations in collaboration with physicians are in most cases...
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Modes of Failure Analysis in Reinforced Concrete Beam Using Laser Scanning and Synchro-Photogrammetry
PublikacjaThe following paper reveal the limitations and possibilities of terrestrial laser scanning technology adaptation in diagnostics of reinforced concrete beams. In this paper, authors present potential spectrum of TLS use in modes of failure analysis of R-C beams and determines under which conditions the laser technologies might be applied. Research was carried out at the Regional Laboratory of Structural Engineering at Gdansk University...
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2D Mathematical Model of the Commutator Sliding Contact of an Electrical Machine
PublikacjaW artykule przedstawiono model matematyczny 2D komutatorowego zestyku ślizgowego z wieloma stopniami swobody. W modelu uwzględniono zmienne wymuszenia działające na szczotkę. Wymuszenia te są wynikiem falistości wirującego komutatora. Szczotka została zamodelowana jako system wielu mas, elementów sprężystych i tłumików rozłożonych w kierunku stycznym i promieniowym. Zamodelowano wszystkie oddziaływania lepkosprężyste pomiędzy komutatorem...
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Predicting Compressive Strength of Cement-Stabilized Rammed Earth Based on SEM Images Using Computer Vision and Deep Learning
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Compressive Strength and Leaching Behavior of Mortars with Biomass Ash
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Influence of effective width of flange on calculation and reinforcement dimensioning of beam of reinforced concrete frame
PublikacjaThe paper analyses the influence of modelling the cross-section of a beam in two-storey reinforced concrete frame of industrial warehouse with dimensions: 18.0 m × 32.0 m using bar elements on the results of bending moments, the value of elastic deflection and the dimensioning of reinforcement due to bending. Six options were considered: a beam as a rectangular section and five T-beam variants with different definitions of effective...
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A 3D lattice model to describe fracture process in fibrous concrete
PublikacjaArtykuł omawia wyniki modelowania procesu zarysowania w elementach betonowych zawierające stalowe włókna przy zastosowaniu dyskretnego modelu kratownicowego. Beton był modelowany na poziomie mezoskali z uwzględnieniem 5 faz: kruszywa, zaczynu cementowego, włókien i obu stref kontaktu. Obliczenia trójwymiarowe wykonano dla jednoosiowego rozciągania.
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Antenna Optimization Using Machine Learning with Reduced-Dimensionality Surrogates
PublikacjaIn modern times, antenna design has become more demanding than ever. The escalating requirements for performance and functionality drive the development of intricately structured antennas, where parameters must be meticulously adjusted to achieve peak performance. Often, global adjustments to geometry are necessary for optimal results. However, direct manipulation of antenna responses evaluated with full-wave electromagnetic (EM)...
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Advancing Solar Energy: Machine Learning Approaches for Predicting Photovoltaic Power Output
PublikacjaThis research is primarily concentrated on predicting the output of photovoitaic power, an essential field in the study of renewable energy. The paper comprehensively reviews various forecasting methodologies, transitioning from conventional physical and statistical methods to advanced machine learning (ML) techniques. A significant shift has been observed from traditional point forecasting to machine learning-based forecasting...
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Restoration and preservation of the reinforced concrete poles of fence at the former Auschwitz concentration and extermination camp
PublikacjaThe objective of this study was to assess the present state of the reinforced concrete poles of fence at the former Auschwitz I and Auschwitz II-Birkenau concentration and extermination camp. The poles were subjected to renovation about 10 years ago. After this time some deficiencies of applied renovation method were noticed. Cracks appeared between fresh and original part of concrete cover. Analysis of the reasons of these failures...
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Restoration and preservation of the reinforced concrete poles of fence at the former Auschwitz concentration and extermination camp
PublikacjaThe objective of this study was to assess the present state of the reinforced concrete poles of fence at the former Auschwitz I and Auschwitz II-Birkenau concentration and extermination camp. The poles were subjected to renovation about 10 years ago. After this time some deficiencies of applied renovation method were noticed. Cracks appeared between fresh and original part of concrete cover. Analysis of the reasons of these failures...
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Examination of advanced isotropic constitutive laws under complex stress states in plain and reinforced concrete specimens
PublikacjaThe performance of advanced isotropic constitutive laws under complex stress states in plain and reinforced concrete specimens is investigated. Three different formulations are chosen: original Mazars model, Mazars mi model and model proposed by Pereira and coworkers. The degradation of the material in all formulations is described via a single variable, but a strain/stress state is taken into account via quite sophisticated relationships....
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Baseline-free debonding detection in reinforced concrete structures by elastic wave propagation
PublikacjaThe article presents the results of the numerical and experimental analysis concerning wave propagation in reinforced concrete (RC) beams with various extent of debonding between the steel rod and concrete cover. The main aim of the paper was to consider the unsolved research gaps, which considerably limit the application of wave-based methods in practice. The propagation of the flexural wave modes excited and registered on the...
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Thermal-Humidity Parameters of 3D Printed Wall
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Isothermal Calorimetry and Compressive Strength Tests of Mortar Specimens for Determination of Apparent Activation Energy
PublikacjaThe hydration process of cementitious materials involves a thermally activated reaction that depends on the composition of the mixture and the curing temperature. The main parameter affecting the temperature variation of cast-in-place concrete is the apparent activation energy, which can be used for the efficient prediction of the temperature evolution and maturity index of hardening concrete. This paper discusses two methods to...
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Model-free and Model-based Reinforcement Learning, the Intersection of Learning and Planning
PublikacjaMy doctoral dissertation is intended as the compound of four publications considering: structure and randomness in planning and reinforcement learning, continuous control with ensemble deep deterministic policy gradients, toddler-inspired active representation learning, and large-scale deep reinforcement learning costs.
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Numerical modeling of GPR field in damage detection of a reinforced concrete footbridge
PublikacjaThe paper presents a study on the use of the ground penetrating radar (GPR) method in diagnostics of a footbridge. It contains experimental investigations and numerical analyses of the electromagnetic field propagation using the finite difference time domain method (FDTD). The object of research was a reinforced concrete footbridge over a railway line. The calculations of the GPR field propagation were performed on a selected cross-section...
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Robust and Efficient Machine Learning Algorithms for Visual Recognition
PublikacjaIn visual recognition, the task is to identify and localize all objects of interest in the input image. With the ubiquitous presence of visual data in modern days, the role of object recognition algorithms is becoming more significant than ever and ranges from autonomous driving to computer-aided diagnosis in medicine. Current models for visual recognition are dominated by models based on Convolutional Neural Networks (CNNs), which...
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Parametrical 3D model of an asynchronous motor - AutoCAD application.
PublikacjaA computer program for automatic drawing of 3D models of squirrel-cage induction motors is presented in this paper. The created model of a machine is of parametrical nature, which means that the user defines geometry of particular elements (shaft, stator core, bearing, windings etc.) on the basis dimensions and some other parameters e.g. type of bearing, kind of winding, number of slots. This program is useful for 3D modelling...
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Multimedia industrial and medical applications supported by machine learning
PublikacjaThis article outlines a keynote paper presented at the Intelligent DecisionTechnologies conference providing a part of the KES Multi-theme Conference “Smart Digital Futures” organized in Rome on June 14–16, 2023. It briefly discusses projects related to traffic control using developed intelligent traffic signs and diagnosing the health of wind turbine mechanisms and multimodal biometric authentication for banking branches to provide...
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A novel heterogeneous model of concrete for numerical modelling of ground penetrating radar
PublikacjaThe ground penetrating radar (GPR) method has increasingly been applied in the non-destructive testing of reinforced concrete structures. The most common approach to the modelling of radar waves is to consider concrete as a homogeneous material. This paper proposes a novel, heterogeneous, numerical model of concrete for exhaustive interpretation of GPR data. An algorithm for determining the substitute values of the material constants...
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Machine learning applied to acoustic-based road traffic monitoring
PublikacjaThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
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Machine learning applied to acoustic-based road traffic monitoring
PublikacjaThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
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The New 3D Printed Left Atrial Appendage Closure with a Novel Holdfast Device: A Pre-Clinical Feasibility Animal Study
PublikacjaMany patients undergoing cardiac surgery have risk factors for both atrial fibrillation and stroke. The left atrial appendage (LAA) is the primary site for thrombi formation. Therefore LAA occlusion devices should be tested for their ability to reduce future cerebral ischemic events in patients with high-risk of haemorrhage. The aim of this study was to evaluate the safety and feasibility of a novel left atrial appendage exclusion...
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Flexural behaviour of concrete slabs reinforced with FRP bars in experiments and according to aci ACI 440.1R guide
PublikacjaThe paper presents research conducted on two concrete slabs reinforced with the carbon composite bars and two other concrete slabs reinforced with basalt composite bars. The carbon bars were plain, while the basalt ones were ribbed. The slabs were experimentally investigated in the flexural state of effort with the concentrated forces applied. The results are compared with the analytical solution proposed in the guide ACI 440.1R-06...
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Low-Loss 3D-Printed Waveguide Filters Based on Deformed Dual-Mode Cavity Resonators
PublikacjaThis paper introduces a new type of waveguide filter with smooth profile, based on specially designed dual-mode (DM) cavity resonators. The DM cavity design is achieved by applying a shape deformation scheme. The coupling between the two orthogonal cavity modes is implemented by breaking the symmetry of the structure, thus eliminating the need for additional coupling elements. The modes operating in the cavity are carefully analyzed...
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Analyzing the relationship between sound, color, and emotion based on subjective and machine-learning approaches
PublikacjaThe aim of the research is to analyze the relationship between sound, color, and emotion. For this purpose, a survey application was prepared, enabling the assignment of a color to a given speaker’s/singer’s voice recordings. Subjective tests were then conducted, enabling the respondents to assign colors to voice/singing samples. In addition, a database of voice/singing recordings of people speaking in a natural way and with expressed...
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FE investigations of the effect of fluctuating local tensile strength on coupled energetic-statistical size effect in concrete beams
PublikacjaThe effect of fluctuating local tensile strength on a coupled energetic-statistical size effect in plain concrete beams under bending was numerically investigated. First, the influence of varying autocorrelation length of the random field describing a spatial variation of local tensile strength was studied. Next, the influence of the coefficient of variation of local tensile strength was analyzed. The numerical FE investigations...
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Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools
PublikacjaA high monetary value of the construction projects is one of the reasons of frequent disputes between a general contractor (GC) and a client. A construction site is a unique, one-time, and single-product factory with many parties involved and dependent on each other. The organizational dependencies and their complexity make any fault or mistake propagate and influence the final result (delays, cost overruns). The constant will...
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Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
PublikacjaExamining the game-changing possibilities of explainable machine learning techniques, this study explores the fast-growing area of biochar production prediction. The paper demonstrates how recent advances in sensitivity analysis methodology, optimization of training hyperparameters, and state-of-the-art ensemble techniques have greatly simplified and enhanced the forecasting of biochar output and composition from various biomass...
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Noise profiling for speech enhancement employing machine learning models
PublikacjaThis paper aims to propose a noise profiling method that can be performed in near real-time based on machine learning (ML). To address challenges related to noise profiling effectively, we start with a critical review of the literature background. Then, we outline the experiment performed consisting of two parts. The first part concerns the noise recognition model built upon several baseline classifiers and noise signal features...
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Predicting emotion from color present in images and video excerpts by machine learning
PublikacjaThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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Integration of thermographic data with the 3D object model
PublikacjaThe aim of the paper is to present new method for merging the 3D model data of the measured object with thermograms. Our technique is based on the combination of visual 3D imaging technique and thermal imaging technique, which maps the 2D thermograms on to 3D anatomical mesh model. The combination of these imaging modalities allows the generation of combined 3D and thermal data from which thermal signatures can be verified and...
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Potential of Reusing 3D Printed Concrete (3DPC) Fine Recycled Aggregates as a Strategy towards Decreasing Cement Content in 3DPC
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Shear fracture of longitudinally reinforced concrete beams under bending using Digital Image Correlation and FE simulations with concrete micro-structure based on X-ray micro-computed tomography images
PublikacjaThe paper presents experimental and numerical investigations of the shear fracture in rectangular concrete beams longitudinally reinforced with steel or basalt bar under quasi-static three point bending. Shear fracture process zone formation and development on the surface of beams was investigated by Digital Image Correlation (DIC) whereas thorough analyses of 3D material micro-structure, air voids, width and curvature of shear...
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Predictions of cervical cancer identification by photonic method combined with machine learning
PublikacjaCervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors...
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Characterization of Corrosion-Induced Fracture in Reinforced Concrete Beams Using Electrical Potential, Ultrasound and Low-Frequency Vibration
PublikacjaThe paper deals with the non-destructive experimental testing of the reinforced concrete beams under progressive corrosion. A series of experiments using electrical potential, ultrasound and low-frequency vibrations techniques are reported. Electrical potential and natural frequencies were used to characterise and monitor the corrosion process at its initial state. The P-wave velocity measurements were proved to be effective in...
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Thermo-mechanic tests using 3d printed elements
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From Data to Decision: Interpretable Machine Learning for Predicting Flood Susceptibility in Gdańsk, Poland
PublikacjaFlood susceptibility prediction is complex due to the multifaceted interactions among hydrological, meteorological, and urbanisation factors, further exacerbated by climate change. This study addresses these complexities by investigating flood susceptibility in rapidly urbanising regions prone to extreme weather events, focusing on Gdańsk, Poland. Three popular ML techniques, Support Vector Machine (SVM), Random Forest (RF), and...