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Search results for: DEDICATED MACHINES
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Machining process sequencing and machine assignment in generative feature-based CAPP for mill-turn parts
PublicationProcess selection and sequencing, as one of the most complex issues when evaluated from a mathematical point of view and crucial in CAPP, still attract research attention. For the current trend of intelligent manufacturing, machining features (MFs) are the information carriers for workpiece geometry and topology representation. They are basically derived from CAD models and are used by downstream engineering applications. A feature-based...
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Forecasting values of cutting power for the sawing process of impregnated pine wood on band sawing machine
PublicationW artykule przedstawiono prognozowane wartości mocy skrawania dla pilarki taśmowej (ST100R firmy STENNER), które są stosowane w polskich tartakach. Wartości mocy skrawania oszacowano dla drewna sosny zwyczajnej (Pinus sylvestris L.), które zostało poddane impregnacji. Dla porównania wyznaczono również wartości mocy skrawania dla drewna niezaimpregnowanego. Wartości te określono za pomocą innowacyjnej metody prognozowania sił skrawania,...
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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublicationThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
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Numerical analysis of chip removing system operation in circular sawing machine using CFD software
PublicationPaper presents the analysis of the results of numerical simulations of the air flow process of wood chips removing system in the circular sawing machine. The attention is focused on the upper cover and bottom shelter of the chip removing system. Within the framework of the work a systematic numerical modeling of the air flow distribution in the cover and shelter during operation of the selected rotational speed of saw blade with...
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Optical method supported by machine learning for urinary tract infection detection and urosepsis risk assessment
PublicationThe 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
PublicationThis 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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Edyta Gołąb-Andrzejak dr hab.
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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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Ireneusz Czarnowski Prof.
PeopleIRENEUSZ CZARNOWSKI is a graduate of the Faculty of Electrical Engineering at Gdynia Maritime University. He gained a doctoral degree in the field of computer science at Poznan University of Technology and a postdoctoral degree in the field of computer science at Wroclaw University of Science and Technology. Since 1998 is associated with Gdynia Maritime University, currently is a professor of computer science in the Department...
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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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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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Magnesiate-Utilized/Benzyne-Mediated Approach to Indenopyridones from 2-Pyridones: An Attempt To Synthesize the Indenopyridine Core of Haouamine
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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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Bogdan Wiszniewski prof. dr hab. inż.
PeopleBogdan Wiszniewski graduated from Gdansk University of Technology in 1977 and was awarded an MSc in computer science and engineering with honours. In 1984 and 1998, respectively, has got his PhD and DSc. In 2006 was awarded a Professor title by the President of Poland. Lectured at the universities in Canada, US and UK. Principal investigator or coordinator in many national and international R&D projects with the significant...
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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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Optimization of the femtosecond laser impulse for excitation and the spin-orbit-mediated dissociation in the NaRb molecule
Open Research DataHigh accuracy ab initio potential energy curves (1tSigma+, 2sSigma+, 1tPi), electronic transition dipole moment function (1tSigma+ - 1tPi), and spin-orbit coupling (2sSigma+ - 1tPi) have been calculated for the NaRb molecule. The time-dependent excitation and dissociation processes in the polar alkali diatomic NaRb molecule and the quantum properties...
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Non-enzymatic glutathione-mediated conjugation of unsymmetrical bisacridine C-2028 with anticancer activity
Open Research DataThe presented data complement the studies on the interplay between C-2028 (anticancer-active unsymmetrical bisacridine) and the glutathione S-transferase/glutathione (GST/GSH) system.
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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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Journal of Machinery Manufacture and Reliability
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Machines, Computations and Universality (Universal Machines and Computations)
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Sylwester Kaczmarek dr hab. inż.
PeopleSylwester Kaczmarek received his M.Sc in electronics engineering, Ph.D. and D.Sc. in switching and teletraffic science from the Gdansk University of Technology, Gdansk, Poland, in 1972, 1981 and 1994, respectively. His research interests include: IP QoS and GMPLS and SDN networks, switching, QoS routing, teletraffic, multimedia services and quality of services. Currently, his research is focused on developing and applicability...
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Machine Graphics and Vision
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Detection of Cystic Fibrosis Symptoms Based on X-Ray Images Using Machine Learning- Pilot Study
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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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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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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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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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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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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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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 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 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 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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Quantitative Soil Characterization for Biochar–Cd Adsorption: Machine Learning Prediction Models for Cd Transformation and Immobilization
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Universal Predictors of Dental Students’ Attitudes towards COVID-19 Vaccination: Machine Learning-Based Approach
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Michał Mazur dr inż.
PeopleAktualne zainteresowania inżynieria mechaniczna, robotyka, drgania mechaniczne, analiza modalna, sterowanie, systemy czasu rzeczywistego Wybrane publikacje Kaliński K., Galewski M., Mazur M., Chodnicki M, 2017, Modelling and Simulation Of A New Variable Stiffness Holder for Milling Of Flexible Details, Polish Maritime Research, vol 24, ss. 115-124 Kaliński K. J., Mazur M.: Optimal control at energy performance index of the mobile...
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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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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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