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Search results for: DEDICATED MACHINES
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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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Integrating Experience-Based Knowledge Representation and Machine Learning for Efficient Virtual Engineering Object Performance
PublicationMachine learning and Artificial Intelligence have grown significant attention from industry and academia during the past decade. The key reason behind interest is such technologies capabilities to revolutionize human life since they seamlessly integrate classical networks, networked objects and people to create more efficient environments. In this paper, the Knowledge Representation technique of Set of Experience...
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Decisional DNA (DDNA) Based Machine Monitoring and Total Productive Maintenance in Industry 4.0 Framework
PublicationThe 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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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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A novel hybrid adaptive framework for support vector machine-based reliability analysis: A comparative study
PublicationThis 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
PublicationIn 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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Generative Process Planning with Reasoning based on Geometrical Product Specification
PublicationThe focus of this paper is on computer aided process planning for parts manufacture in systems of definite process capabilities, involving the use of multi-axis machining centers for parts shaping and grinding machines for finishing. It presents in particular a decision making scheme for setup determination as a part of generative process planning. The planning procedurę consists of two stages. The first stage is associated with...
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In silico studies and β-cyclodextrin mediated neutral synthesis of 4-oxo-4,5,6,7-tetrahydroindoles of potential biological interest
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Magnesiate-Utilized/Benzyne-Mediated Approach to Indenopyridones from 2-Pyridones: An Attempt To Synthesize the Indenopyridine Core of Haouamine
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Correction to “Emerging Anticancer Activity of Candidal Glucosamine-6-Phosphate Synthase Inhibitors upon Nanoparticle-Mediated Delivery”
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The Effects of Acute and Chronic Haloperidol Treatment on Dopamine Release Mediated by the Medial Forebrain Bundle in the Striatum and Nucleus Accumbens
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ClpP/ClpX-mediated degradation of the bacteriophage λ O protein and regulation of λ phage and λ plasmid replication
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Comparison of siRNA-mediated silencing of glycosaminoglycan synthesis genes and enzyme replacement therapy for mucopolysaccharidosis in cell culture studies.
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Diphosphination of CO2 and CS2 mediated by frustrated Lewis pairs - catalytic route to phosphanyl derivatives of formic and dithioformic acid
PublicationThe first example of CO2 diphosphination is described. Reactions of unsymmetrical diphosphanes with CE2 (E = O, S) catalyzed by BPh3 insert a CE2 molecule into the P-P bond with formation of the products of the general formula R2P-E-C(=E)-PR2. The obtained CO2 adducts arise from synergistic interaction of diphosphane and borane with CO2 molecule.
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A method of Functional Test interval selection with regards to Machinery and Economical aspects
PublicationThis paper discusses the problem of choosing the optimal frequency of functional test, including the reliability calculations and production efficiency, but also the effect of company risk management. The proof test as a part of the functional test interval is well described for the process industry. Unfortunately, this situation is not the case for the machinery safety functions with low demand mode. Afterwards, it is presented...
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Effect of the Relative Position of the Face Milling Tool towards the Workpiece on Machined Surface Roughness and Milling Dynamics
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Analysis of specific cutting resistance while cutting frozen pine blocks with narrow-kerf stellite tipped saws on frame sawing machines.
PublicationPrzedstawiono wyniki analizy oporów skrawania drewna zmrożonego podczas przecierania pryzm sosnowych na pilarce ramowej za pomocą cienkich pił. Badania prowadzono dla temperatur drewna -5 st. C, -20 st. C oraz dla porównania w temperaturze +18 st. C. Wilgotność drewna wynosiła 30%. Zaobserwowano znaczacy wzrost oporów skrawania wraz ze spadkiem jego temperatury.
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Hydrostatic drives as safe and energy saving machines. The drive investigation method compatible diagram of power increase opposite to the direction of power flow
PublicationProjektanci i producenci napędu hydrostatycznego nie dysponują możliwością dokładnego określania jego sprawności energetycznej zmieniającej się szeroko w polu pracy napędzanego urządzenia a więc w pełnym zakresie zmiany prędkości i obciążenia silnika hydraulicznego oraz lepkości zastosowanego czynnika roboczego. Dotyczy to zarówno określania strat i sprawności maszyn wyporowych (pompy i silnika hydraulicznego) zastosowanych w układzie...
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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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Detection of Cystic Fibrosis Symptoms Based on X-Ray Images Using Machine Learning- Pilot Study
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Application of fiber optic sensors using Machine Learning algorithms for temperature measurement of lithium-ion batteries
PublicationOptical 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
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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Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublicationMaximizing 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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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublicationAtmospheric 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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Development of an emulation platform for synchronous machine power generation system using a nonlinear functional level model
PublicationThe 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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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublicationOne 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
PublicationAir 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
PublicationThe 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
PublicationThis 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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Control of induction machine supplied by a current source inverter using the multi-scalar transformation and backstepping approach
PublicationThe 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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Prediction of Wastewater Quality at a Wastewater Treatment Plant Inlet Using a System Based on Machine Learning Methods
PublicationOne 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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Chip suction system in circular sawing machine: empirical research and computational fluid dynamics numerical simulations
PublicationThe 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 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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Control Strategy of a Five-Phase Induction Machine Supplied by the Current Source Inverter With the Third Harmonic Injection
PublicationIn 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
PublicationMachine 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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Universal Predictors of Dental Students’ Attitudes towards COVID-19 Vaccination: Machine Learning-Based Approach
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Quantitative Soil Characterization for Biochar–Cd Adsorption: Machine Learning Prediction Models for Cd Transformation and Immobilization
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Detection of specific UL49 sequences of Marek's disease virus CVI988/Rispens strain using loop-mediated isothermal amplification
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Stromal-Epithelial Cross-Talk in the Intestinal Stem Cell Niche is Mediated by a Regulatory Network that Involves TGF-Beta and CTGF
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Microemulsion-Mediated Synthesis and Properties of Uniform Ln:CaWO4(Ln = Eu, Dy) Nanophosphors with Multicolor Luminescence for Optical and CT Imaging
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Potassium trimethylsilanolate-mediated conversion of dialkyl phosphonates to their anhydrous potassium monoalkyl phosphonates under mild, non-aqueous conditions
PublicationPrzedstawiona została metoda syntezy bezwodnych soli potasowych fosfonianów monoalkilu z odpowiednich fosfonianów dialkilu w reakcji z trimetylosilanolanem potasu w bezwodnym eterze i chlorku metylenu. Metoda ta może być również stosowana dla makrocyklicznych kaliks[4]arenów z wbudowanymi grupami fosfonowymi na górnej obręczy; preferowanym rozpuszczalnikiem jest w tym przypadku bezwodny THF. Zaletą opisanej metody są łagodne warunki...
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Towards plant-mediated chemistry – Au nanoparticles obtained using aqueous extract of Rosa damascena and their biological activity in vitro
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New Tetragonal ReGa5(M) (M = Sn, Pb, Bi) Single Crystals Grown from Delicate Electrons Changing
PublicationSingle crystals of the new Ga-rich phases ReGa~5(Sn), ReGa~5(Pb) and ReGa~5(Bi) were successfully obtained from the flux method. The new tetragonal phases crystallize in the space group P4/mnc (No. 128) with vertex-sharing capped Re2@Ga14 oblong chains. Vacancies were discovered on the Ga4 and Ga5 sites, which can be understood as the direct inclusion of elemental Sn, Pb and Bi into the structure. Heat capacity measurements were...
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A pilot study with flow mediated skin fluorescence: A novel device to assess microvascular endothelial function in coronary artery disease
PublicationBackground: Endothelial dysfunction is one of the earliest vascular manifestations in the pathogenesis of cardiovascular disease. Noninvasive, simple and inexpensive methods of endothelial function assessment are therefore needed. Methods: Microvascular endothelial function was assessed in coronary artery disease (CAD) patients by flow mediated skin fluorescence (FMSF), based on measurements of NADH fluorescence intensity during...
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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
PublicationOther 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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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.
PublicationIn 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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The Perception and Attitudes toward COVID-19 Vaccines: A Cross-Sectional Study in Poland
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Selected problems of planning machinery and devices location in a ship´s engine room.
PublicationPrzedstawiono podstawowe zasady rozplanowania maszyn i urządzeń w przedziale maszynowym na statku. Podano warunki i kryteria wpływające na proces projektowania rozmieszczenia maszyn i urządzeń w siłowni. Przedstawiono główne warunki i zasady dotyczące rozplanowania głównego układu napędowego, elektrowni, kotłowni pomocniczych oraz innych instalacji siłownianych.
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Cost minimization of locating construction machinery park with the use of simulation and optimization algorithms
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HCI-Based Wireless System for Measuring the Concentration of Mining Machinery and Equipment Operators
PublicationMaintaining stable and reliable working conditions is a matter of vital importance for various companies, especially those involving heavy machinery. Due to human exhaustion, as well as unpredicted hazards and dangerous situations, the personnel has to take actions and wisely plan each move. This paper presents a human–computer interaction (HCI)-based system that uses a concentration level measurement function to increase the safety...