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Search results for: marine%20bearings
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The Setting Time of Polyether Impression Materials after Contact with Conventional and Experimental Gingival Margin Displacement Agents
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Time for a paradigm shift in shared decision-making in trauma and emergency surgery? Results from an international survey
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A decision-making system supporting selection of commanded outputs for a ship's propulsion system with a controllable pitch propeller
PublicationThe ship's operators have to make decisions regarding the values of commanded outputs (commanded engine speed and pitch ratio) which ensure maximum vessel speed and minimum fuel consumption. Obviously, the presented decision problems are opposed. Therefore, there is a need for a compromise solution that enables more flexible vessel voyage planning. This paper deals with development of a computer-aided system supporting selection...
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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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Quantitative Soil Characterization for Biochar–Cd Adsorption: Machine Learning Prediction Models for Cd Transformation and Immobilization
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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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Assessing groundwater vulnerability to pollution in the Puck region (denudation moraine upland) using vertical seepage method
PublicationDegradation of groundwater quality can cause a serious water supply and environmental problems. The identify of potential groundwater pollution can be determined by assessment of groundwater vulnerability method. The assessment of groundwater vulnerability to pollution was based on estimation of migration time of potential conservative contamination through the vadose zone. Area of investigation is a type of denudation moraine...
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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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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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Design of new cholinesterase inhibitors based on phosphorus analogs of tacrine as potential anti-Alzheimer’s disease agents
PublicationBased on the analysis of the determined free binding energy (using the AutoDock Vina 1.1.2 docking program), the most potent cholinesterase inhibitors were selected. Moreover, studies of 3D visualization of the results of molecular modeling led to the identification of potential sites for the interaction of new potential inhibitors with amino acid residues building active sites of investigated cholinesterases.
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Active Learning on Ensemble Machine-Learning Model to Retrofit Buildings Under Seismic Mainshock-Aftershock Sequence
PublicationThis research presents an efficient computational method for retrofitting of buildings by employing an active learning-based ensemble machine learning (AL-Ensemble ML) approach developed in OpenSees, Python and MATLAB. The results of the study shows that the AL-Ensemble ML model provides the most accurate estimations of interstory drift (ID) and residual interstory drift (RID) for steel structures using a dataset of 2-, to 9-story...
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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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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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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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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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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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Verification of Satellite Railway Track Position Measurements Making Use of Standard Co-Ordinate Determination Techniques
PublicationThe article presents the results of satellite railway track position measurements performed by a multidisciplinary research team, the members of which represented Gdansk University of Technology and Gdynia Maritime University. Measuring methods are described which were used for reconstructing the railway track axis position and diagnosing railway track geometry deformations. As well as that, the description of the novel method...
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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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Rapid Surrogate-Aided Multi-Criterial Optimization of Compact Microwave Passives Employing Machine Learning and ANNs
PublicationThis article introduces an innovative method for achieving low-cost and reliable multi-objective optimization (MO) of microwave passive circuits. The technique capitalizes on the attributes of surrogate models, specifically artificial neural networks (ANNs), and multi-resolution electromagnetic (EM) analysis. We integrate the search process into a machine learning (ML) framework, where each iteration produces multiple infill points...
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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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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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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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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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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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Lower Rim Substituted p-tert-Butyl-Calix[4]arene. Part 15. Pb(II)-Ion-Selective Electrodes Based on p-tert-Butyl-calix[4]arene Thioamides.
PublicationTetra podstawione tioamidowe pochodne para-tert-butylokaliks[4]arenu (1-5) zostały zastosowane jako jonofory w membranowych elektrodach jonoselektywnych (EJS) selektywne na kationy Pb(II). Wyznaczono współczynniki selektywności. Czwartorzędowe kaliks[4]aren-tioamidy (1,2) wykazują nadzwyczaj dobrą selektywność na kationy Pb(II) w porównaniu z kaliks[4]aren-amidami. Membrany z tymi ligandami wykazują dużą trwałość, a charakterystyki...
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Lower rim substituted p-tert-butyl-calix[4]arene. Part 17. Synthesis, extractive and ionophoric properties of p-tert-butylcalix[4]arene appended with hydroxamic acid moieties
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Lower rim substituted p-tert-butyl-calix[4]arene. Part 16. Synthesis of 25,26,27,28-tetrakis(piperidinylthiocarbonylmethylene)-p-tert-butylcalix[4]arene and its interaction with metal ions
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Lower rim substituted p-tert-butyl-calix[4]arene. Part 17. synthesis, extractive and ionophoric properties of p-tert-butylcalix[4]arene appended with hydroxamix acid moieties
PublicationThe synthesis and characterization of four p-tert-butylcalix[4]arene-hydroxamic acidc are reported. The dependence of the metal ion binding, assessed by liquid extraction of the metal nitrates from water into dichloromethane in individual and competitive experiments, on the ligand structure, is presented. The results showed that those ligands could be successfully used in separation process of trnasition and heavy metals often...
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Response of murine gut microbiota to a prebiotic based on oligosaccharides derived via hydrolysis of fungal α-(1→3)-d-glucan: Preclinical trial study on mice
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High resolution optical and acoustic remote sensing datasets of the Puck Lagoon
PublicationThe very shallow marine basin of Puck Lagoon in the southern Baltic Sea, on the Northern coast of Poland, hosts valuable benthic habitats and cultural heritage sites. These include, among others, protected Zostera marina meadows, one of the Baltic’s major medieval harbours, a ship graveyard, and likely other submerged features that are yet to be discovered. Prior to this project, no comprehensive high-resolution remote sensing...
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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
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Boletin de Investigaciones Marinas y Costeras
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REVMAR-Revista Ciencias Marinas y Costeras
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INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
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Journal of Ocean Engineering and Marine Energy
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JOURNAL OF EXPERIMENTAL MARINE BIOLOGY AND ECOLOGY
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Identification of Markers Associated with Yield Traits and Morphological Features in Maize (Zea mays L.)
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Amine-functionalized magnetite-silica nanoparticles as effective adsorbent for removal of uranium(VI) ions
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Aquaporin 2: Identification and analysis of expression in calves’ urine during their first month of life
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New sorbent materials for selective extraction of cocaine and benzoylecgonine from human urine samples
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Determination of cyanide ion in urine samples using ion chromatography with pulsed amperometric detection.
PublicationCyanides are widely applied in industrial activity, including gold and silver mining and the production of organic chemicals. HCN is also formed directly from fossil fuel combustion sources from gasoline and diesel vehicles. In natural environment, in plants seeds for example an apple seed, it exists as a cyanogenic glycosides. The amount of cyanide ions originating from food products is however rather small. Larger concentrations...
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Mehanika mašin, mehanizmov i materialov
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Andrzej Stateczny prof. dr hab. inż.
PeopleProf. Dr. Andrzej Stateczny is a Professor of Gdansk Technical University Poland and President of Marine Technology Ltd. His research interests are mainly centered on navigation, hydrography and geoinformatics. Current RF research activities include radar navigation, comparative navigation, hydrography, artificial intelligence methods focused on image processing and multisensory data fusion. He has been the Principal Investigator...
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Germline DNA Retention in Murine and Human Rearranged T Cell Receptor Gene Coding Joints: Alternative Recombination Signal Sequences and V(D)J Recombinase Errors
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Joanna Wolszczak-Derlacz dr hab.
PeopleI am an Associate Professor at Gdańsk University of Technology, Faculty of Management and Economics. I gained my PhD in July 2006 for which I received the Polish Prime Ministry’s Award for the outstanding doctoral thesis. Between 2007 and 2008, I was a beneficiary of the Max Weber Fellowship at the European University Institute in Florence, Italy. I conducted part of my research at the Katholieke Universiteit Leuven, Belgium...
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Annales Universitatis Mariae Curie-Skłodowska Sectio I Philosophia-Sociologia
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ANNALES UNIVERSITATIS MARIAE CURIE-SKŁODOWSKA, SECTIO DD: MEDICINA VETERINARIA
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ANNALES UNIVERSITATIS MARIAE CURIE-SKŁODOWSKA, SECTIO J: PAEDAGOGIA-PSYCHOLOGIA
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Annales Universitatis Mariae Curie-Sklodowska, sectio N – Educatio Nova
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