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Wyniki wyszukiwania dla: pm synchronous machine
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Optimization of chip removing system operation in circular sawing machine
PublikacjaThe paper presents the optimization of the wood chips removing system in the sliding table saw. Chips are generated during the cutting of the material. The attention was focused on the upper casing of mentioned system. The methodical experimental studies of the pressure distribution inside the casing during the wood chip removing operation for the selected rotational speed of saw blade with a diameter of 300 mm and 450 mm were...
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Playback detection using machine learning with spectrogram features approach
PublikacjaThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
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The methodology of design of satellite working mechanism of positive displacement machine
PublikacjaIn this paper is described a methodology of design of satellite mechanism consisting of two noncircular gears (externally toothed rotor and internally toothed curvature) and circular gears (satellites). In the presented methodology is assumed that the rotor pitch line is known, and the curvature pitch line is necessary to designate. The presented methodology applies to mechanisms for which the number of the curvature humps is at...
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LOW PLACTICITY BURNISHING PROCESSES. Fundaments, tools and machine tools
PublikacjaW obszernej monografii (530 stron) autor przedstawił w sposób kompleksowy zagadnienia związane z wykończeniową metodą obróbki części maszyn przez powierzchniową obróbkę plastyczną-nagniataniem. Jest to pierwsza książka w języku angielskim poświęcona tej bezwiórowej i ekologicznej metodzie obróbki. W wielu przypadkach w technologii różnorodnych części maszyn i innych urządzeń, nagniatanie może zastąpić operację szlifowania. Ma to...
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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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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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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublikacjaBiomass management in terms of energy consumption optimization has become a recent challenge for developed countries. Nevertheless, the multiplicity of materials and operating parameters controlling energy consumption in wastewater treatment plants necessitates the need for sophisticated well-organized disciplines in order to minimize energy consumption and dissipation. Sewage sludge (SS) disposal management is the key stage of...
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublikacjaDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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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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The chemistry, properties and performance of flame-retardant rubber composites: Collecting, analyzing, categorizing, machine learning modeling, and visualizing
PublikacjaRubbers combine the flexibility with mechanical strength, supporting myriad applications, but suffer from inherent flammability. Formulation and production of flame-retardant rubber composites (FRRCs) have intensively been practiced over years, but not comprehensively reviewed. This necessity has outlined collecting, analyzing, screening, classifying, and interpreting the literature with the aim of classifying the FRRCs. We quantified...
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Failure analysis of a high-speed induction machine driven by a SiC-inverter and operating on a common shaft with a high-speed generator
PublikacjaDue to ongoing research work, a prototype test rig for testing high-speed motors/generators has been developed. Its design is quite unique as the two high- speed machines share a single shaft with no support bearings between them. A very high maximum operating speed, up to 80,000 rpm, was required. Because of the need to minimise vibration during operation at very high rotational speeds, rolling bearings were used. To eliminate...
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Thermal analysis and experimental verification of permanent magnet synchronous motor by combining lumped-parameter thermal networks with analytical method
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Optimization-based stacked machine-learning method for seismic probability and risk assessment of reinforced concrete shear walls
PublikacjaEfficient seismic risk assessment aids decision-makers in formulating citywide risk mitigation plans, providing insights into building performance and retrofitting costs. The complexity of modeling, analysis, and post-processing of the results makes it hard to fast-track the seismic probabilities, and there is a need to optimize the computational time. This research addresses seismic probability and risk assessment of reinforced...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublikacjaWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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The effect of full-cell impregnation of pine wood (Pinus Sylvestris L.) on the fine dust content during sawing on a frame sawing machine
PublikacjaIn this paper the results of the analysis of the effect of the impregnation treatment of pine wood on the granularity of sawdust from the sawing process on the frame sawing machine PRW 15M are presented. Granulometric analyses of chips from impregnated and unimpregnated pine wood implies that the impregnation of pine wood does not affect the size and structure of the sawdust produced. A major ≈ 95% share of the formed chips is...
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Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
PublikacjaControlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient’s genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched...
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Selection of form factors of machine carrying systems in reliance on the process duty
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Features of Machine Cyclogram Optimization with the Account of Interaction of Mechanism Links with Stops
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Determination of the rigidity and deformation energy of the technological machine load-carrying systems
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Control system based on the modified multiscalar model for the double fed machine
PublikacjaPrzedstawiono układ sterowania maszyną asynchroniczą dwustronnie zasilaną wykorzystujący zmodyfikowany model multisaklarny. Wprowadzone nielinowe sprzężenia pozwalają na podział systemu na dwa niezależne podukłady. Pododuje to brak zauważalnych sprzężeń przy regulacji mocy czynnej i biernej regulowanej przez kontrolery PI. W układzie wyeliminowano konieczność stosowania kaskadowego połączenia regulatorów. Przedstawiono wyniki symulacji.
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Testing motional accuracy of a manufacturing machine - a task imposed on modern maintenance
PublikacjaArtykuł dotyczy zagadnień utrzymania ruchu maszyn w powiązaniu z problemami parametryzacji zautomatyzowanych napędów. Przedstawiono krótki przegląd i kierunki rozwoju wspomagania komputerowego w ramach zakładowych systemów utrzymania ruchu. Zwrócono uwagę na pomijanie w popularnie publikowanych graficznych modelach systemów informatycznych CIM, ich podsystemów dedykowanych dla wspomagania utrzymania ruchu maszyn, podczas gdy takie...
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Efficient sampling of high-energy states by machine learning force fields
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Modular machine learning system for training object detection algorithms on a supercomputer
PublikacjaW pracy zaprezentowano architekturę systemu służącego do tworzenia algorytmów wykorzystujących metodę AdaBoost i służących do wykrywania obiektów (np. twarzy) na obrazach. System został podzielony na wyspecjalizowane moduły w celu umożliwienia łatwej rozbudowy i efektywnego zrównoleglenia implementacji przeznaczonej dla superkomputera. Na przykład, system może być rozszerzony o nowe cechy i algorytmy ich ekstrakcji bez konieczności...
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Molecular Diffusion Simulation on ARUZ – Massively-parallel FPGA-based Machine
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Stacking and rotation-based technique for machine learning classification with data reduction
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POPULATION-BASED MULTI-AGENT APPROACH TO SOLVING MACHINE LEARNING PROBLEMS
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The use of tamping machine for diagnosising the longitudinal forces in rails of CWR track
PublikacjaW pracy przedstawiono przebieg prowadzonych od kilkunastu lat w Politechnice Gdańskiej badań nad wyznaczaniem sił podłużnych w szynach toru bezstykowego. Opisano skonstruowaną aparaturę pomiarową. Badania eksperymentalne polegały na podnoszeniu, a następnie poprzecznym nasuwaniu rusztu torowego za pomocą podbijarki. Rejestrowano przy tym wartości przemieszczeń toru oraz odkształcenia siłowników hydraulicznych. W rezultacie ostatnich...
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Tests on lateral resistance in railway track during operation of tamping machine
PublikacjaArtykuł prezentuje koncepcję prowadzenia badań oporów poprzecznych w trakcie procesu regulacji geometrycznej toru kolejowego za pomocą podbijarki. Jest to zatem kontynuacja badań nad zastosowaniem podbijarki torowej w diagnostyce toru bezstykowego; wcześniej zajmowano się kwestią określania sił podłużnych w szynach. Przedstawiono sposób wyznaczania oporów poprzecznych polegający na ciągłej rejestracji przemieszczenia oraz siły...
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Experimental examination and modification of chip suction system in circular sawing machine
PublikacjaThe article presents the results of experimental examination of the wood chip suction system in the existing sliding table saw before and after its modifi cation. The studies focused on the extraction hood of the mentioned system. The methodical experimental research of the pressure distribution inside the hood during wood chip removal for the selected rotational speed of saw blades of 3500 and 6000 min-1 with a diameter of 300...
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Evaluation of aspiration problems in L2 English pronunciation employing machine learning
PublikacjaThe approach proposed in this study includes methods specifically dedicated to the detection of allophonic variation in English. This study aims to find an efficient method for automatic evaluation of aspiration in the case of Polish second-language (L2) English speakers’ pronunciation when whole words are analyzed instead of particular allophones extracted from words. Sample words including aspirated and unaspirated allophones...
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Molecular Heterogeneity of Papillary Thyroid Cancer: Comparison of Primary Tumors and Synchronous Metastases in Regional Lymph Nodes by Mass Spectrometry Imaging
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Does diclofenac act like a photosynthetic herbicide on green algae? Chlamydomonas reinhardtii synchronous culture-based study with atrazine as reference
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Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning
PublikacjaTheophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally...
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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublikacjaThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...
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Machine learning-based prediction of seismic limit-state capacity of steel moment-resisting frames considering soil-structure interaction
PublikacjaRegarding the unpredictable and complex nature of seismic excitations, there is a need for vulnerability assessment of newly constructed or existing structures. Predicting the seismic limit-state capacity of steel Moment-Resisting Frames (MRFs) can help designers to have a preliminary estimation and improve their views about the seismic performance of the designed structure. This study improved data-driven decision techniques in...
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Improving operating efficiency of a gas turboset via cooperation with an absorption refrigerating machine
PublikacjaThe analysis of increase of ambient air temperature entering the compressor on reduction in power output from the turbine and increase fuel use was conduced. For medium size gas turbine operates in winter and summer conditions elementary power and economical values was calculated. Conditions of the determination of turbine inlet air cooling solution (using thermal storage for reduce equipment size) are presented
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<title>Management system of ELHEP cluster machine for FEL photonics design</title>
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Machine learning techniques combined with dose profiles indicate radiation response biomarkers
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Analytical model of torsional vibrations of typical sawing machine main drive system
PublikacjaPrzedstawiono model fizyczny i matematyczny drgań skrętnych napędu głównego typowej pilarki tarczowej. Model tworzą elementy sztywne SES połączone między sobą za pośrednictwem elementów sprężysto - tłumiących EST w układzie szeregowym. W modelu matematycznym uwzględniono: właściwości dynamiczne silnika napędowego, wymiary piły tarczowej, cechy materiału obrabianego (wymiary, rodzaj drewna, wilgotność drewna) oraz właściwości dynamiczne...
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Multivariate Features Extraction and Effective Decision Making Using Machine Learning Approaches
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Influence of frame sawing machine´s kinematics on saw blade tooth wear.
PublikacjaW pracy przedstawiono wpływ kinematyki pilarki ramowej na zużycie ostrzy piłtrakowych.
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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublikacjaTo this day, driver fatigue remains one of the most significant causes of road accidents. In this paper, a novel way of detecting and monitoring a driver’s physical state has been proposed. The goal of the system was to make use of multimodal imaging from RGB and thermal cameras working simultaneously to monitor the driver’s current condition. A custom dataset was created consisting of thermal and RGB video samples. Acquired data...
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Machine Learning and data mining tools applied for databases of low number of records
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From the Dynamic Lattice Liquid Algorithm to the Dedicated Parallel Computer – mDLL Machine
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Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
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Sensorless Multiscalar Control of Five-Phase Induction Machine with Inverter Output Filter
PublikacjaThe paper presents a complete solution for speed sensorless control system for five-phase induction motor with voltage inverter, LC filter and nonlinear control of combined fundamental and third harmonic flux distribution. The control principle, also known as multiscalar control, nonlinear control or natural variables control, is based on a use of properly selected scalar variables in control feedback to linearize controlled system....
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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublikacjaThe aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was...
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Volume optimization of high-speed surface-mounted permanent magnet synchronous motor based on sequential quadratic programming technique and analytical solution
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Machine learning-based prediction of residual drift and seismic risk assessment of steel moment-resisting frames considering soil-structure interaction
PublikacjaNowadays, due to improvements in seismic codes and computational devices, retrofitting buildings is an important topic, in which, permanent deformation of buildings, known as Residual Interstory Drift Ratio (RIDR), plays a crucial role. To provide an accurate yet reliable prediction model, 32 improved Machine Learning (ML) algorithms were considered using the Python software to investigate the best method for estimating Maximum...
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Solubility Characteristics of Acetaminophen and Phenacetin in Binary Mixtures of Aqueous Organic Solvents: Experimental and Deep Machine Learning Screening of Green Dissolution Media
PublikacjaThe solubility of active pharmaceutical ingredients is a mandatory physicochemical characteristic in pharmaceutical practice. However, the number of potential solvents and their mixtures prevents direct measurements of all possible combinations for finding environmentally friendly, operational and cost-effective solubilizers. That is why support from theoretical screening seems to be valuable. Here, a collection of acetaminophen...