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Hybrid excited electric machine with axial flux bridges
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Machine learning applied to bi-heterocyclic drugs recognition
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Stacking-Based Integrated Machine Learning with Data Reduction
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Geometric working volume of a satellite positive displacement machine
PublicationThis article describes a method for determining the geometric working volume of satellite positive displacement machines (pump and motor). The working mechanism of these machines is satellite mechanism consisting of two non-circular gears (rotor and curvature) and circular gears (satellites). Two variants of the satellite mechanism are presented. In the first mechanism, the rolling line of the rotor is a sinusoid "wrapped" around...
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Machine learning system for estimating the rhythmic salience of sounds.
PublicationW artykule przedstawiono badania dotyczące wyszukiwania danych rytmicznych w muzyce. W pracy przedstawiono postać funkcji rankingujacej poszczególnych dźwięków frazy muzycznej. Opracowano metodę tworzenia wszystkich możliwych hierarchicznych struktur rytmicznych, zwanych hipotezami rytmicznymi. Otrzymane hipotezy są następnie porządkowane w kolejności malejącej wartości funkcji rankingującej, aby ustalić, która ze znalezionych...
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Direct current atmospheric pressure glow discharge generated between a pin-type solid cathode and a flowing liquid anode as a new tool for silver nanoparticles production
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Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study
PublicationThis study explores the edaravone solubility space encompassing both neat and binary dissolution media. Efforts were made to reveal the inherent concentration limits of common pure and mixed solvents. For this purpose, the published solubility data of the title drug were scrupulously inspected and cured, which made the dataset consistent and coherent. However, the lack of some important types of solvents in the collection called...
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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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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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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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Predicting seismic response of SMRFs founded on different soil types using machine learning techniques
PublicationPredicting the Maximum Interstory Drift Ratio (M-IDR) of Steel Moment-Resisting Frames (SMRFs) is a useful tool for designers to approximately evaluate the vulnerability of SMRFs. This study aims to explore supervised Machine Learning (ML) algorithms to build a surrogate prediction model for SMRFs to reduce the need for complex modeling. For this purpose, twenty well-known ML algorithms implemented in Python software are trained...
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublicationDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublicationDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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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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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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Digital Interaction and Machine Intelligence. Proceedings of MIDI’2021 – 9th Machine Intelligence and Digital Interaction Conference, December 9-10, 2021, Warsaw, Poland
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The methodology of design of satellite working mechanism of positive displacement machine
PublicationIn 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
PublicationW 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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Sensorless Control of Induction Machine Supplied by Current Source Inverter
PublicationThe paper describes the voltage control technique of induction machines supplied by a current source inverter. The control system is based on proposed new multi-scalar variables, which are named “r.” The control system contains the output filter capacitor's model. In the sensorless control system the Z type backstepping speed observer was applied. The mathematical dependences are confirmed by simulation and experimental research.
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Optimization of chip removing system operation in circular sawing machine
PublicationThe 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
PublicationThis 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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Modeling of generator performance of BLDC machine using mathematica software
PublicationW artykule porównano trzy modele maszyny bezszczotkowej prądu stałego z magnesami trwałymi(BLDC) w przypadku pracy prądnicowej. Najprostszy model qd0 sprowadzono do dwóch osi prostopadłychzwiązanych z wirnikiem [3]. Zakłada on sinusoidalny rozkład pola w szczelinie. Model opisany wosiach naturalnych wyprowadzono w oparciu o formalizm Lagrnage'a [4] i moŜe uwzględniać dowolnyrozkład pola wzbudzonego przez magnesy trwałe. Model pośredni...
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The Influence of Abrasive Machine on Temperature During One Side Lapping
PublicationPrzedstawiono wyniki badań temperatury układu wykonawczego docierarki jednotarczowej. Analizowano temperaturę trzech pierścieni prowadzących separatory przy wykorzystaniu kamery termograficznej V-20 II firmy VIGO System S.A.
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An approach to machine classification based on stacked generalization and instance selection
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Hybrid-Excited Permanent Magnet-Assisted Synchronous Reluctance Machine
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Performance Evaluation of an Axial Flux Machine with a Hybrid Excitation Design
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Hybrid Excited Synchronous Machine with Wireless Supply Control System
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Clamping precision of a cilcular saw blade on a spindle of a sawing machine
PublicationW pracy przedstawiono analizę dokładności mocowania piły tarczowej na wrzecionie pilarki, w której uwzgledniono jedynie tolerancje wykonania układu wrzeciona pilarki i piły tarczowej.
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Portable computer measurement system of machine tools in wood industry
PublicationW pracy przedstawiono przenośny system diagnostyczny przeznaczony do oceny pracy obrabiarek skrawających i urządzeń przemysłu drzewnego. Ocena procesu obróbczego odbywa się na podstawie pomiaru wielkości mechanicznych, takich jak: prędkość obrotowa , przemieszczenia oraz przyspieszenia. Korzystanie z programów komputerowych, w które system jest wyposażony, pozwala użytkownikowi maszyn na przeprowadzanie szczegółowych analiz, dzięki...
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The methods of fretting wear prevention in machine elements : chapter 9
PublicationOpisano skutki procesu frettingu w elementach maszyn i warunki ich wystąpienia. Przedstawiono przegląd metod zapobiegania zużyciu frettingowemu i jego ograniczania. Opisano laboratoryjne badania zużywania frettingowego wybranych skojarzeń w warunkach umożliwiających ograniczanie zużycia.
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2D Mathematical Model of the Commutator Sliding Contact of an Electrical Machine
PublicationW 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
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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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublicationBiomass 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
PublicationDesigning 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
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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The chemistry, properties and performance of flame-retardant rubber composites: Collecting, analyzing, categorizing, machine learning modeling, and visualizing
PublicationRubbers 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
PublicationDue 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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Optimization-based stacked machine-learning method for seismic probability and risk assessment of reinforced concrete shear walls
PublicationEfficient 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
PublicationWastewater 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
PublicationIn 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
PublicationControlled 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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Efficient sampling of high-energy states by machine learning force fields
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Experimental examination and modification of chip suction system in circular sawing machine
PublicationThe 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
PublicationThe 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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Modular machine learning system for training object detection algorithms on a supercomputer
PublicationW 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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Tests on lateral resistance in railway track during operation of tamping machine
PublicationArtykuł 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...