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Machine-Learning-Powered EM-Based Framework for Efficient and Reliable Design of Low Scattering Metasurfaces
PublikacjaPopularity 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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Decisional DNA (DDNA) Based Machine Monitoring and Total Productive Maintenance in Industry 4.0 Framework
PublikacjaThe entire manufacturing spectrum is transforming with the advent of Industry 4.0. The features of Set of Experience Knowledge Structure (SOEKS) and Decisional DNA (DDNA) were utilized for developing Virtual Engineering Objects (VEO), Virtual Engineering Process (VEP) and Virtual Engineering Factory (VEF), which in turn facilitate the creation of smart factories. In this study, DDNA based Machine Monitoring for Total Maintenance...
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Computational Complexity and Its Influence on Predictive Capabilities of Machine Learning Models for Concrete Mix Design
PublikacjaThe design of concrete mixtures is crucial in concrete technology, aiming to produce concrete that meets specific quality and performance criteria. Modern standards require not only strength but also eco-friendliness and production efficiency. Based on the Three Equation Method, conventional mix design methods involve analytical and laboratory procedures but are insufficient for contemporary concrete technology, leading to overengineering...
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Analysis of surface roughness of chemically impregnated Scots pine processed using frame-sawing machine
PublikacjaThe objective of this work was to evaluate the effect of the impregnation process of pine wood (Pinus sylvestris L.) on roughness parameters of the surface processed on a frame sawing. The samples weredried and impregnated using a commercial procedure by a local company. The touch method withthe use of measuring stylus (pin) was employed to determine of surface roughness of the samplesconsidering parameters, namely, arithmetical...
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A novel hybrid adaptive framework for support vector machine-based reliability analysis: A comparative study
PublikacjaThis study presents an innovative hybrid Adaptive Support Vector Machine - Monte Carlo Simulation (ASVM-MCS) framework for reliability analysis in complex engineering structures. These structures often involve highly nonlinear implicit functions, making traditional gradient-based first or second order reliability algorithms and Monte Carlo Simulation (MCS) time-consuming. The application of surrogate models has proven effective...
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Machine-Learning Methods for Estimating Performance of Structural Concrete Members Reinforced with Fiber-Reinforced Polymers
PublikacjaIn recent years, fiber-reinforced polymers (FRP) in reinforced concrete (RC) members have gained significant attention due to their exceptional properties, including lightweight construction, high specific strength, and stiffness. These attributes have found application in structures, infrastructures, wind power equipment, and various advanced civil products. However, the production process and the extensive testing required for...
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Optical method supported by machine learning for urinary tract infection detection and urosepsis risk assessment
PublikacjaThe study presents an optical method supported by machine learning for discriminating urinary tract infections from an infection capable of causing urosepsis. The method comprises spectra of spectroscopy measurement of artificial urine samples with bacteria from solid cultures of clinical E. coli strains. To provide a reliable classification of results assistance of 27 algorithms was tested. We proved that is possible to obtain...
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Speed estimation of a car at impact with a W-beam guardrail using numerical simulations and machine learning
PublikacjaThis paper aimed at developing a new method of estimating the impact speed of a passenger car at the moment of a crash into a W-beam road safety barrier. The determination of such a speed based on the accident outcomes is demanding, because often there is no access to full accident data. However, accurate determination of the impact speed is one of the key elements in the reconstruction of road accidents. A machine learning algorithm...
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The forecasted values of cutting power for sawing on band sawing machines for Polish Scots pine wood (Pinus sylvestris L.) in a function of its provenance.
PublikacjaIn this paper the predicted values of cutting power for band sawing machine (EB 1800, f. EWD), which is used in the Polish sawmills, were showed. The values of cutting power were forecasted for Scots pine (Pinus sylvestris L.) wood of five provenances from Poland. These values were determined using an innovative method of predicting the cutting power, which takes into account of elements of fracture mechanics. The resulting predictions...
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Prediction of Overall In Vitro Microsomal Stability of Drug Candidates Based on Molecular Modeling and Support Vector Machines. Case Study of Novel Arylpiperazines Derivatives
PublikacjaOther than efficacy of interaction with the molecular target, metabolic stability is the primary factor responsible for the failure or success of a compound in the drug development pipeline. The ideal drug candidate should be stable enough to reach its therapeutic site of action. Despite many recent excellent achievements in the field of computational methods supporting drug metabolism studies, a well-recognized procedure to model...
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Laser induced elastooptics in novel Bi2O3, and Pr2O3 doped tellurite rich glasses
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Novel porous carbon/clay nanocomposites derived from kaolinite/resorcinol-formaldehyde polymer blends: synthesis, structure and sorption properties
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High pressure luminescence and time resolved spectra of La2Be2O5:Pr3+
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High pressure and time resolved luminescence spectra of Gd3Ga5O12:Pr3+ crystal
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Theoretical and experimental research of heat and mass transfer in adsorption process in dac systems
PublikacjaPrzedstawiono badania wymiany ciepła i masy w stałych adsorpcyjnych elementach wykonanych na bazie silikażelu. Zaprezentowano również informacje dotyczące osuszania w systemach klimatyzacyjnych. Na zkończenie pokazano wyniki numerycznej symulacji i skojarzonej wymiany ciepła i masy w chłodzonym osuszaczu.
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Photophysics and Halide Quenching of Soret-excited ZnTPPS4- in Aqueous Media
PublikacjaSteady state S2-S0 and S1-S0 absorption and emission spectra and picosecond S2 decay and S1 fluorescence rise times have been measured for the model porphyrin ZnTPPS4− in water and in aqueous iodide solutions of constant ionic strength. The dynamics of S1 quenching by iodide are well-modeled by a Stern-Volmer mechanism yielding kQ = 1.75 × 109 M−1 s−1. The S2 state is quenched on a ps time scale by a static electron-transfer mechanism...
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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublikacjaAtmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...
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Stability analysis of nanobeams in hygrothermal environment based on a nonlocal strain gradient Timoshenko beam model under nonlinear thermal field
PublikacjaThis article is dedicated to analyzing the buckling behavior of nanobeam subjected to hygrothermal environments based on the principle of the Timoshenko beam theory. The hygroscopic environment has been considered as a linear stress field model, while the thermal environment is assumed to be a nonlinear stress field based on the Murnaghan model. The size-dependent effect of the nanobeam is captured by the nonlocal strain gradient...
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Galerkin formulations with Greville quadrature rules for isogeometric shell analysis: Higher order elements and locking
PublikacjaWe propose new Greville quadrature schemes that asymptotically require only four in-plane points for Reissner-Mindlin (RM) shell elements and nine in-plane points for Kirchhoff-Love (KL) shell elements in B-spline and NURBS-based isogeometric shell analysis, independent of the polynomial degree of the elements. For polynomial degrees 5 and 6, the approach delivers high accuracy, low computational cost, and alleviates membrane and...
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Galerkin formulations of isogeometric shell analysis: Alleviating locking with Greville quadratures and higher-order elements
PublikacjaWe propose new quadrature schemes that asymptotically require only four in-plane points for Reissner–Mindlin shell elements and nine in-plane points for Kirchhoff–Love shell elements in B-spline and NURBS-based isogeometric shell analysis, independent of the polynomial degree p of the elements. The quadrature points are Greville abscissae associated with pth-order B-spline basis functions whose continuities depend on the specific...
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Efficient and robust quadratures for isogeometric analysis: Reduced Gauss and Gauss–Greville rules
PublikacjaThis work proposes two efficient quadrature rules, reduced Gauss quadrature and Gauss–Greville quadrature, for isogeometric analysis. The rules are constructed to exactly integrate one-dimensional B-spline basis functions of degree p, and continuity class C^{p−k}, where k is the highest order of derivatives appearing in the Galerkin formulation of the problem under consideration. This is the same idea we utilized in Zou et al....
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Blue-dye intraoperative sentinel lymph node mapping in early non-small cell lung cancer
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Orientational Order and Dynamics of Nematic Multipodes Based on Carbosilazane Cores Using Optical and Dielectric Spectroscopy
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Metoda wektorowa pomiaru impedancji pętli zwarciowej w obecności załóceń. Autoreferat rozprawy doktorskiej.**2002, 16 s. 11 rys. bibliogr. 12 poz. ma szyn.
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Cadmium, arsenic, selenium and iron– Implications for tumor progression in breast cancer
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Binder availability and blending efficiency of reclaimed asphalt: A state-of-the-art review
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Measuring moisture damage of hot-mix asphalt (HMA) by digital imaging-assisted modified boiling test (ASTM D3625): Recent advancements and further investigation
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Threshold photoelectron studies of isoxazole over the energy range 9.9-30 eV
PublikacjaThe threshold photoelectron spectrum of the isoxazole molecule, C3H3NO has been measured over the photon energy range 9.9-30 eV with the use of synchrotron radiation. In the 9.9-10.8 eV range, corresponding to photoionization from the highest occupied molecular orbital 3a"(π3), seven well resolved vibrational series have been observed and their modes are tentatively assigned. A strong adiabatic ionization, with an energy of 11.132...
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Experimental and Numerical Investigation of Tensile and Flexural Behavior of Nanoclay Wood-Plastic Composite
PublikacjaIn this study, the effect of wood powder and nanoclay particle content on composites’ mechanical behavior made with polyethylene matrix has been investigated. The wood flour as a reinforcer made of wood powder was at levels of 30, 40, and 50 wt.%, and additional reinforcement with nanoclay at 0, 1, 3, and 5 wt.%. Furthermore, to make a composite matrix, high-density polyethylene was used at levels of 70, 60, and 50% by weight....
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Influence of geometry of iron poles on the cogging torque of a field control axial flux permanent magnet machine
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Universal Predictors of Dental Students’ Attitudes towards COVID-19 Vaccination: Machine Learning-Based Approach
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Detection of Cystic Fibrosis Symptoms Based on X-Ray Images Using Machine Learning- Pilot Study
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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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Control of induction machine supplied by a current source inverter using the multi-scalar transformation and backstepping approach
PublikacjaThe paper describes the voltage control technique of squire-cage induction machines supplied by a current source inverter. The control system is based on new transformation of the electric drive system (machine and inverter) state variables to the multi-scalar variables form. The backstepping approach is used to obtain the feedback control law. The control system contains the structure of the observer...
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Control Strategy of a Five-Phase Induction Machine Supplied by the Current Source Inverter With the Third Harmonic Injection
PublikacjaIn the five-phase induction machine (IM), it is possible to better use the electromagnetic circuit than in the three-phase IM. This requires the use of an adequate converter system which will be supplied by an induction machine. The electric drive system described, in this article, includes the five-phase induction machine supplied by the current source inverter (CSI). The proposed novelty—not presented previously—is the control...
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Prediction of fracture toughness in fibre-reinforced concrete, mortar, and rocks using various Machine learning techniques
PublikacjaMachine Learning (ML) method is widely used in engineering applications such as fracture mechanics. In this study, twenty different ML algorithms were employed and compared for the prediction of the fracture toughness and fracture load in modes I, II, and mixed-mode (I-II) of various materials, including fibre-reinforced concrete, cement mortar, sandstone, white travertine, marble, and granite. A set of 401 specimens of “Brazilian...
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Chip suction system in circular sawing machine: empirical research and computational fluid dynamics numerical simulations
PublikacjaThe experimental analysis of the wood chip removing system during its redesigning in the existing sliding table circular saw and computational fluid dynamic (CFD) numerical simulations of the air flow process is presented in the paper. The attention was focused on the extraction hood and the bottom shelter of the actual existing system. The main aim was to perform experimental research on the pressure distribution inside the...
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Prediction of Wastewater Quality at a Wastewater Treatment Plant Inlet Using a System Based on Machine Learning Methods
PublikacjaOne of the important factors determining the biochemical processes in bioreactors is the quality of the wastewater inflow to the wastewater treatment plant (WWTP). Information on the quality of wastewater, sufficiently in advance, makes it possible to properly select bioreactor settings to obtain optimal process conditions. This paper presents the use of classification models to predict the variability of wastewater quality at...
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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublikacjaOne of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the ability to anticipate their flexural response. With a comprehensive grid search, several stacked models (i.e., chained, parallel) consisting of various machine learning (ML) algorithms and artificial neural networks (ANNs) were developed to predict the flexural response of SFRC beams. The flexural performance of SFRC beams under bending was...
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Cost-Efficient Measurement Platform and Machine-Learning-Based Sensor Calibration for Precise NO2 Pollution Monitoring
PublikacjaAir quality significantly impacts human health, the environment, and the economy. Precise real-time monitoring of air pollution is crucial for managing associated risks and developing appropriate short- and long-term measures. Nitrogen dioxide (NO2) stands as a common pollutant, with elevated levels posing risks to the human respiratory tract, exacerbating respiratory infections and asthma, and potentially leading to chronic lung...
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Ecology In Tribology: Selected Problems of Eliminating Natural Oil-Based Lubricants from Machine Friction Couples
PublikacjaThe elimination of mineral oil-based lubricants from machines has multiple beneficial effects on the natural environment. Firstly – these lubricants are a direct threat to the environment in the event of leaks; secondly – their elimination reduces the demand for crude oil from which they are obtained. In addition, in many cases, e.g. when replacing traditional lubricants with water, friction losses in the bearings can also be reduced...
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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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Application of fiber optic sensors using Machine Learning algorithms for temperature measurement of lithium-ion batteries
PublikacjaOptical fiber sensorsusing low-coherence interferometry require processing ofthe output spectrum or interferogramto quickly and accurately determine the instantaneous value of the measured quantity, such as temperature.Methods based on machine learning are a good candidate for this application. The application of four such methods in an optical fiber temperature sensoris demonstrated.Using aZnO-coated...
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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-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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Development of an emulation platform for synchronous machine power generation system using a nonlinear functional level model
PublikacjaThe article presents the Power Hardware in the Loop (PHIL) approach for an autonomous power system analysis based on the synchronous generator model incorporating magnetic saturation effects. The model was prepared in the MATLAB/Simulink environment and then compiled into the C language for the PHIL platform implementation. The 150 kVA bidirectional DC/AC commercial-grade converter was used to emulate the synchronous generator....
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Modélisation d'ordre non entier des machines synchrones. Modèle fréquentiel non linéaire, identification des paramètres, calcul de la réponse temporelle.
PublikacjaDans les réseaux d'énergie électrique contemporains, on assiste à une diversification considérable des différentes sources d'énergie. L'énergie produite est transformée par une grande quantité de dispositifs électriques pour être finalement acheminée à diverses installations électriques. Il devient donc primordial d'améliorer les modèles des différents composants électriques afin de pouvoir prévoir les interactions entre eux et...
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Limiting distribution of the three-state semi-Markov model of technical state transitions of ship power plant machines and its applicability in operational decision-making.
PublikacjaThe article presents the three-state semi-Markov model of the process {W(t): t 0} of state transitions of a ship power plant machine, with the following interpretation of these states: s1 – state of full serviceability, s2 – state of partial serviceability, and s3 – state of unserviceability. These states are precisely defined for the ship main engine (ME). A hypothesis is proposed which explains the possibility of application...
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Structural Investigations and Determination of Current and Voltage Characteristics in Htsc 2G SF12050 Tapes
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Mechanical and Corrosion Properties of Magnesium-Bioceramic Nanocomposites
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