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Search results for: AXIAL-FLUX MACHINE
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Robust flux observer system with sliding mode and fuzzy logic control of Induction Motors
PublicationW pracy przedstawiono implementację nowego obserwatora strumienia wirnika silnika indukcyjnego zastosowanego w układzie sterowania polowo zorientowanego ze sterowaniem ślizgowym. Proponowany system jest niewrażliwy na zmiany rezystancji stojana silnika w wyniku zastosowania korekcyjnego sprzężenia zwrotnego. Przedstawiono porównanie układów z oraz bez zastosowania sterowania ślizgowego. Zamieszczono wyniki badań symulacyjnych...
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Kinetic flux vector splitting scheme for solving non-reactive multi-component flows
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Obliczanie indukcyjnych układów grzejnych z wykorzystaniem interfejsu API komercyjnego pakietu Flux
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Technology of laser deposition of narrow bead overlays using solid and flux-cored wires
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Machine learning approach to packaging compatibility testing in the new product development process
PublicationThe paper compares the effectiveness of selected machine learning methods as modelling tools supporting the selection of a packaging type in new product development process. The main goal of the developed model is to reduce the risk of failure in compatibility tests which are preformed to ensure safety, durability, and efficacy of the finished product for the entire period of its shelf life and consumer use. This kind of testing...
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Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method
PublicationPlasmonic nanostructures based on AuAg nanoalloys were fabricated by thermal annealing of metallic films in an argon atmosphere. The nanoalloys were chosen because they can extend the wavelength range in which plasmon resonance occurs and thus allow the design of plasmonic platforms with the desired parameters. The influence of initial fabrication parameters and experimental conditions on the formation of nanostructures was investigated....
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Polymeric Bearings as a new base isolation system suitable for mitigating machine-induced vibrations
PublicationThe present paper summarizes the preliminary results of the experimental shaking table investigation conducted in order to verify the effectiveness of a new base isolation system consisting of Polymeric Bearings in reducing strong horizontal machine-induced vibrations. Polymeric Bearing considered in the present study is a prototype base isolation system, which was constructed with the use of a specially prepared flexible polymer...
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Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers
PublicationThis chapter presents the application of new information technology in education for the training of air traffic controllers (ATCs). Machine learning, multi-criteria decision analysis, and text analysis as the methods of artificial intelligence for ATCs training have been described. The authors have made an analysis of the International Civil Aviation Organization documents for modern principles of ATCs education. The prototype...
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Detection of People Swimming in Water Reservoirs with the Use of Multimodal Imaging and Machine Learning
PublicationEvery year in many countries, there are fatal unintentional drownings in different water reservoirs like swimming pools, lakes, seas, or oceans. The existing threats of this type require creating a method that could automatically supervise such places to increase the safety of bathers. This work aimed to create methods and prototype solutions for detecting people bathing in water reservoirs using a multimodal imaging system and...
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Computational Complexity and Its Influence on Predictive Capabilities of Machine Learning Models for Concrete Mix Design
PublicationThe 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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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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A machine learning approach to classifying New York Heart Association (NYHA) heart failure
PublicationAccording to the European Society of Cardiology, globally the number of patients with heart failure nearly doubled from 33.5 million in 1990 to 64.3 million in 2017, and is further projected to increase dramatically in this decade, still remaining a leading cause of morbidity and mortality. One of the most frequently applied heart failure classification systems that physicians use is the New York Heart Association (NYHA) Functional...
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Solubility of dapsone in deep eutectic solvents: Experimental analysis, molecular insights and machine learning predictions
PublicationBackground. Dapsone (DAP) is an anti-inflammatory and antimicrobial active pharmaceutical ingredient used to treat, e.g., AIDS-related diseases. However, low solubility is a feature hampering its efficient use. Objectives. First, deep eutectic solvents...
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Speed observer of induction machine based on backstepping and sliding mode for low‐speed operation
PublicationThis paper presents a speed observer design based on backstepping and slidingmode approaches. The inputs to the observer are the stator current and thevoltage vector components. This observer structure is extended to the integra-tors. The observer stabilizing functions contain the appropriate sliding surfaceswhich result from the Lyapunov function. The rotor angular speed is obtainedfrom the non‐adaptive formula with a sliding...
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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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Is it too late now to say we’re sorry? Examining anxiety contagion and crisis communication strategies using machine learning
PublicationIn this paper, we explore the role of perceived emotions and crisis communication strategies via organizational computer-mediated communication in predicting public anxiety, the default crisis emotion. We use a machine-learning approach to detect and predict anxiety scores in organizational crisis announcements on social media and the public’s responses to these posts. We also control for emotional and language tones in organizational...
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Spectral criterion of infinite fatigue life of machinery parts under multi-axial random loading
PublicationPrzedstawiono kryterium nieograniczonej trwałości zmęczeniowej metalowych elementów poddanych wieloosiowym losowym drganiom. W celu jego wyznaczenia zastosowano hipotezę energii odkształcenia postaciowego i równanie Goodmana/Soderberga. Traktując gęstości widmowe mocy składowych naprężenia jako znane, kryterium to sformułowano w dziedzinie częstości. W przykładzie obliczeniowym rozpatrzono okresowy w sensie średniokwadratowym stan...
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Research of new two-speed planet type gear hydraulic motors with axial clearance compensation.
PublicationOpisano sposoby realizacji napędu dwubiegowego na przykładzie silnika satelitowego HS 3,2 [dm3/obr.] oraz przedstawiono zalety i przykłady zastosowań napędów wielobiegowych. Zaprezentowano porównanie metody analitycznej oraz eksperymentalnej wyznaczania nierównomierności chłonności hydraulicznego silnika satelitowego w celu zweryfikowania własności eksploatacyjnych silnika dwubiegowego HS 3,2/0,8 [dm3/obr] wyprodukowanego przez...
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Experimental research of circular saw blade tooth axial run-out influence on cutting effects
PublicationW pracy przedstawiono metodę pomiaru i wyniki badań doświadczalnych wpływu bicia osiowego ostrzy piły tarczowej na efekty przecinania
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Experimental Studies of Concrete-Filled Composite Tubes under Axial Short- and Long-Term Loads
PublicationThe paper presents experimental studies on axially compressed columns made of concrete-filled glass fiber reinforced polymer (GFRP) tubes. The infill concrete was C30/37 according to Eurocode 2. The investigated composite pipes were characterized by different angles of fiber winding in relation to the longitudinal axis of the element: 20, 55 and 85 degrees. Columns of two lengths, 0.4 m and 2.0 m, were studied. The internal diameter...
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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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Machine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects
PublicationMachine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects Hammed A. Mojeed & Rafal Szlapczynski Conference paper First Online: 14 September 2023 161 Accesses Part of the Lecture Notes in Computer Science book series (LNAI,volume 14125) Abstract Software development project requires proper planning to mitigate risk and...
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How Integration of a Brain-Machine Interface and Obstacle Detection System Can Improve Wheelchair Control via Movement Image
PublicationThis study presents a human-computer interaction combined with a brain-machine interface (BMI) and obstacle detection system for remote control of a wheeled robot through movement imagery, providing a potential solution for individuals facing challenges with conventional vehicle operation. The primary focus of this work is the classification of surface EEG signals related to mental activity when envisioning movement and deep relaxation...
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Dynamics of the circular sawing machine spindle system
PublicationW pracy przedstawiono wyniki badań wpływu prędkości obrotowej na dynamikę układu wrzecionowego pilarki tarczowej. Czynnikami badanymi były bicie osiowe i promieniowe wrzeciona, które mierzono za pomocą czujników wiroprądowych na kierunku działania przekładni pasowej, a także na kierunku do niego prostopadłym. Przeprowadzone badania eksperymentalne wykazały, że wartość prędkości obrotowej wrzeciona oraz sposób przekazywania mocy...
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Frequency characteristics of induction machine speed observers
PublicationWłaściwości napędu bezczujnikowego z silnikiem indukcyjnym zależą od struktury obserwatora prędkości. System ten wymaga starannej analizy w przypadku uszkodzenia maszyny, której celem jest odpowiedź na pytania: jak układ regulacji pracuje przy niesymetrii maszyny spowodowanej np. uszkodzeniem klatki wirnika oraz jak obserwator odtwarza pulsacje prędkości spowodowane niesymetrią maszyny. W artykule przedstawiono charakterystyki...
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Research on Innovative Hybrid Excited Synchronous Machine
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Bearing testing machine with rotating load vector.
PublicationW pracy przedstawiono koncepcję konstrukcyjną i prototyp stanowiska badawczego z wirująca reakcją łożyskową przeznaczonego do testowania wytrzymałości zmęczeniowej warstw ślizgowych w łożyskach poprzecznych. Konstrukcja i przeznaczenie maszyny zbudowanej w laboratorium tribologicznym Politechniki Gdańskiej jest zgodna z zaleceniami normy ISO 7905. Przeanalizowano zalety i wady maszyny badawczej o takim wzorcu obciążenia testującego.
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Dynamics of the total system of the circular sawing machine
PublicationW pracy przedstwaiono przyczyny i efekty zmiany położenia ostrzy piły tarczowej. Opisana metoda pomiaru zachowania dynamicznego piły pozwala uzytkownikowi okreslic przyczyny drgań. Ponadto, może wskazać drogi efektywnej ich minimalizacji.
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Work parameters research of wood pellet machine
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Cluster-based instance selection for machine classification
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An Approach to Data Reduction and Integrated Machine Classification
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Precision of cutting system in circular sawing machine
PublicationW pracy przedstawiono analizę dokładności układu przecinania pilarki tarczowej, w której uwzglednoino dokładność struktury geometryczno- ruchowej przecinarki.
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Emissivity of the one-plate lapping machine tool
PublicationPrzedstawiono wyniki badań własnych emisyjności docieraka żeliwnego docierarki jednotarczowej. Omówiono konstrukcje produkowanych docierarek jednotarczowych wyposażonych w system kontroli temperatury lub chłodzenia tarczy docierającej. Podano warunki pomiarów temperatury przy użyciu kamery termowizyjnej typu V-20II firmy VIGO System S.A.
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THERMOPLASTIC POLYMER MACHINE GUARDS – EXPLOITATION SAFETY
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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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Non-linear circuit model of a single doubly-fed induction machine formulated in natural axes for drive systems simulation purposes
PublicationMathematical modelling and a circuit model formulated in natural axes of a single doubly-fed induction machine, with the account of magnetic circuit nonlinearity are presented in the paper. Derivation of the model differential equations was based on Lagrange's energy method. State functions of magnetic elements in the model are non-linear and depend on all currents flowing in the machine windings and on the angle of rotor position....
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Application of Feedback Linearization for Air Gap Flux Control of Induction Motor in the Field Weakening Region
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Evaluation of time and space distribution of magnetic flux density in a steel plate magnetized by a C-core
PublicationBadano wpływ częstości magnesowania płyty stalowej na rozkład przestrzenny indukcji magnetycznej wewnątrz tej płyty. Rozkład ten oceniano na podstawie pomiaru natężenia emisji magnetoakustycznej a także rozkładu na powierzchni płyty natężenia efektu Barkhausena. Wyniki dyskutowane są ilościowo i porównane z wynikami modelowania metodą elementów skończonych, w której uwzględniono efekt powstawania prądów wirowych.
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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublicationComplexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...
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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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Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublicationNitrous oxide (N2O) is a key parameter for evaluating the greenhouse gas emissions from wastewater treatment plants. In this study, a new method for predicting liquid N2O production during nitrification was developed based on a mechanistic model and machine learning (ML) algorithm. The mechanistic model was first used for simulation of two 15-day experimental trials in a nitrifying sequencing batch reactor. Then, model predictions...
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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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The miniaturised emission chamber system and home-made passive flux sampler studies of monoaromatic hydrocarbons emissions from selected commercially-available floor coverings
PublicationThe estimation of the emission rate of organic compounds released from various types of indoor materials can be performed using stationary environmental test chambers (ETC) classified as ex-situ methods or small-scale portable analytical devices based on the use of passive technique at the stage of analytes sampling from the gaseous phase (in-situ methods). The paper presents results of emissions of selected organic compounds from...
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Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
PublicationExamining the game-changing possibilities of explainable machine learning techniques, this study explores the fast-growing area of biochar production prediction. The paper demonstrates how recent advances in sensitivity analysis methodology, optimization of training hyperparameters, and state-of-the-art ensemble techniques have greatly simplified and enhanced the forecasting of biochar output and composition from various biomass...
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Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publication(1) About 15-20% of couples struggle with the problem of infertility. 30 to 40% of these cases are caused by abnormalities in the structure and motility of sperm. Sometimes the only possibility for such people is to use the procedure of artificial insemination. CASA systems are used to increase the efficiency of this procedure by selecting the appropriate sperm cell. (2) This paper presents an approach to the sperm classification...
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Game theory-based virtual machine migration for energy sustainability in cloud data centers
PublicationAs the demand for cloud computing services increases, optimizing resource allocation and energy consumption has become a key factor in achieving sustainability in cloud environments. This paper presents a novel approach to address these challenges through an optimized virtual machine (VM) migration strategy that employs a game-theoretic approach based on particle swarm optimization (PSO) (PSO-GTA). The proposed approach leverages...
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
PublicationCirculating tumor cells (CTCs) are tumor cells that separate from the solid tumor and enter the bloodstream, which can cause metastasis. Detection and enumeration of CTCs show promising potential as a predictor for prognosis in cancer patients. Furthermore, single-cells sequencing is a technique that provides genetic information from individual cells and allows to classify them precisely and reliably. Sequencing data typically...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublicationMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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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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Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning
PublicationMethods Results Discussion References Abbreviations Copyright Abstract Background: The spread of false medical information on the web is rapidly accelerating. Establishing the credibility of web-based medical information has become a pressing necessity. Machine learning offers a solution that, when properly deployed, can be an effective tool in fighting medical misinformation on the web. Objective: The aim of this study is to...