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Research on a permanent magnet assisted synchronous reluctance machine with hybrid excitation
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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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Calculation of self and mutual inductances of the switched reluctance machine mathematical model.
PublicationA mathematical model of the switched reluctance machine (SRM) in a drive system obtained using Lagrange's energy method and a method of calculation of self and mutual inductances of the SRM are presented in the paper. The self and mutual inductances are elements of Lagrange's function in generalised coordinates and have been calculated using the finite element method (FEM). Selected calculation results for the particular machine...
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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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Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools
PublicationA high monetary value of the construction projects is one of the reasons of frequent disputes between a general contractor (GC) and a client. A construction site is a unique, one-time, and single-product factory with many parties involved and dependent on each other. The organizational dependencies and their complexity make any fault or mistake propagate and influence the final result (delays, cost overruns). The constant will...
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Process of Medical Dataset Construction for Machine Learning-Multifield Study and Guidelines
PublicationThe acquisition of high-quality data and annotations is essential for the training of efficient machine learning algorithms, while being an expensive and time-consuming process. Although the process of data processing and training and testing of machine learning models is well studied and considered in the literature, the actual procedures of obtaining data and their annotations in collaboration with physicians are in most cases...
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TensorHive: Management of Exclusive GPU Access for Distributed Machine Learning Workloads
PublicationTensorHive is a tool for organizing work of research and engineering teams that use servers with GPUs for machine learning workloads. In a comprehensive web interface, it supports reservation of GPUs for exclusive usage, hardware monitoring, as well as configuring, executing and queuing distributed computational jobs. Focusing on easy installation and simple configuration, the tool automatically detects the available computing...
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Rotor-Flux Vector based Observer of Interior Permanent Synchronous Machine
PublicationThe sensorless control system of the interior permanent magnet machine is considered in this paper. The control system is based on classical linear controllers. In the machine, there occurs non-sinusoidal distribution of rotor flux together with the slot harmonics, which are treated as the control system disturbances. In this case, the classical observer structure in the (d-q) is unstable for the low range of rotor speed resulting...
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Control system based on the modified multiscalar model for the double fed machine
PublicationPrzedstawiono 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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Simulation of influence of the air gap asymmetryon voltage waveforms of a synchronous machine
PublicationResults of simulation of a synchronous generator with the air gap asymmetry characterised by eccentricity are presented in the paper. The Lagrange's energy method has been used in derivation of the model equations. Analysis of influence of the air gap asymmetry on characteristics of self and mutual inductances of windings, as well as analysis of induced voltage waveforms as a function of the air gap asymmetry have been performed....
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Testing motional accuracy of a manufacturing machine - a task imposed on modern maintenance
PublicationArtykuł 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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High gain/bandwidth off‑chip antenna loaded with metamaterial unit‑cell impedance matching circuit for sub‑terahertz near‑field electronic systems
PublicationAn innovative off-chip antenna (OCA) is presented that exhibits high gain and efficiency performance at the terahertz (THz) band and has a wide operational bandwidth. The proposed OCA is implemented on stacked silicon layers and consists of an open circuit meandering line. It is shown that by loading the antenna with an array of subwavelength circular dielectric slots and terminating it with a metamaterial unit cell, its impedance...
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Patch size setup and performance/cost trade-offs in multi-objective antenna optimization using domain patching technique
PublicationA numerical study concerning multi-objective optimization of antenna structures using sequential domain patching (SDP) technique has been presented. We investigate the effect of various setups of the patch size on the operation of the SDP algorithm and possible trade-offs concerning the quality of the Pareto set found by SDP and the computational cost of the optimization process. Our considerations are illustrated using a UWB monopole...
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Multi-objective design optimization of antenna structures using sequential domain patching with automated patch size deter-mination
PublicationIn this paper, a simple yet efficient and reliable technique for fully automated multi-objective design optimization of antenna structures using sequential domain patching (SDP) is discussed. The optimization procedure according to SDP is a two-step process: (i) obtaining the initial set of Pareto-optimal designs representing the best possible trade-offs between considered conflicting objectives, and (ii) Pareto set refinement...
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Nowotwory Journal of Oncology
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Oncology in Clinical Practice
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Metody formułowania ontologicznych zapytań
PublicationArtykuł dotyczy problemu wydobywania danych wyrażonych w postaci ontologii opisanej językiem Web Ontology Language. Dane takie mogą być wydobywane przy użyciu ontologicznych zapytań. Artykuł przedstawia rodzaje języków umożliwiających formułowanie tego rodzaju zapytań. Ontologiczne zapytania mogą być formułowane przez użytkowników podobnie jak zapytania w wyszukiwarkach internetowych tworzone w celu znajdowania stron internetowych....
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American Society of Clinical Oncology educational book / ASCO. American Society of Clinical Oncology. Meeting
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RSS-Based DoA Estimation for ESPAR Antennas Using Support Vector Machine
PublicationIn this letter, it is shown how direction-of-arrival (DoA) estimation for electronically steerable parasitic array radiator (ESPAR) antennas, which are designed to be integrated within wireless sensor network nodes, can be improved by applying support vector classification approach to received signal strength (RSS) values recorded at an antenna's output port. The proposed method relies on ESPAR antenna's radiation patterns measured...
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Application of sliding switching functions in backstepping based speed observer of induction machine
PublicationThe paper presents an analysis of the speed observer which is based on the backstepping and sliding mode approach. The speed observer structure is based on the extended mathematical model of an induction machine. The observer structure is based on the measured phase stator currents and transformed to ( αβ ) coordinate system. The stator voltage vector components are treated as known values. Additionally, such an observer structure...
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The methodology for determining of the value of cutting power for cross cutting on optimizing sawing machine
PublicationIn the article the methodology of forecasting the energy effects of the cross-cutting process using the classical method, which takes into account the specific cutting resistance, is presented. The values of cutting power for the cross-cutting process of two types of wood (softwood and hardwood) were forecasted for the optimizing sawing machine with using presented methodology. The cross-cutting process with high values of feed...
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<title>Management system of ELHEP cluster machine for FEL photonics design</title>
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Multivariate Features Extraction and Effective Decision Making Using Machine Learning Approaches
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Machine learning techniques combined with dose profiles indicate radiation response biomarkers
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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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Evaluation of Machine Learning Methods for the Experimental Classification and Clustering of Higher Education Institutions
PublicationHigher education institutions have a big impact on the future of skills supplied on the labour market. It means that depending on the changes in labour market, higher education institutions are making changes to fields of study or adding new ones to fulfil the demand on labour market. The significant changes on labour market caused by digital transformation, resulted in new jobs and new skills. Because of the necessity of computer...
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The application of a photopolymer material for the manufacture of machine elements using rapid prototyping techniques
PublicationThe paper discusses the application of polymer resin for 3D printing. The first section focuses on rapid prototyping technique and properties of the photopolymer, used as input material in the manufacture of machine components. Second part of the article was devoted to exemplary 3-D-printed elements for incorporation in machines. The article also contains detailed description of problems encountered in implementation of the selected...
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Dynamic variables limitation for backstepping control of induction machine and voltage source converter
PublicationDynamic variables limitation for backstepping control of induction machine and voltage source converter The paper presents the method of control of an induction squirrel-cage machine supplied by a voltage source converter. The presented idea is based on an innovative method of the voltage source converter control, consisting in direct joining of the motor control system with the voltage source rectifier control system. The combined...
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Improving operating efficiency of a gas turboset via cooperation with an absorption refrigerating machine
PublicationThe 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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Sensorless Multiscalar Control of Five-Phase Induction Machine with Inverter Output Filter
PublicationThe 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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Application of Support Vector Machine for Determination of Impact of Traffic-Induced Vibrations on Buildings
PublicationThe aim of the article is to present an algorithm of Support Vector Machine created to forecast the impact of traffic-induced vibrations on residential buildings. The method is designed to classify the object into one of two classes. The classification into the first class means that there is no impact of vibrations on the building, while classification to the second class indicates the possible influence and suggests the execution...
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Influence of frame sawing machine´s kinematics on saw blade tooth wear.
PublicationW pracy przedstawiono wpływ kinematyki pilarki ramowej na zużycie ostrzy piłtrakowych.
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Sensorless control of five-phase induction machine supplied by the VSI with output filter
PublicationIn this paper, a novel sensorless control structure based on multi-scalar variables is proposed. The tatic feedback control law is obtained by using the multi-scalar variables transformation, where the multi-scalar variables approach allows a full linearization of the nonlinear system. The control system could be described as “optimized” because of the minimized number of controllers. Furthermore, control system is divided into...
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Advancing Solar Energy: Machine Learning Approaches for Predicting Photovoltaic Power Output
PublicationThis research is primarily concentrated on predicting the output of photovoitaic power, an essential field in the study of renewable energy. The paper comprehensively reviews various forecasting methodologies, transitioning from conventional physical and statistical methods to advanced machine learning (ML) techniques. A significant shift has been observed from traditional point forecasting to machine learning-based forecasting...
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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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Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublicationThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublicationTo 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 for the management of biochar yield and properties of biomass sources for sustainable energy
PublicationBiochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts,...
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DNAffinity: a machine-learning approach to predict DNA binding affinities of transcription factors
PublicationWe present a physics-based machine learning approach to predict in vitro transcription factor binding affinities from structural and mechanical DNA properties directly derived from atomistic molecular dynamics simulations. The method is able to predict affinities obtained with techniques as different as uPBM, gcPBM and HT-SELEX with an excellent performance, much better than existing algorithms. Due to its nature, the method can...
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Slowly-closing valve behaviour during steam machine accelerated start-up
PublicationThe paper discusses the state of stress in a slowly-closing valve during accelerated start-up of a steam turbine. The valve is one of the first components affected by high temperature gradients and is a key element on which the power, efficiency and safety of the steam system depend. The authors calibrated the valve model based on experimental data and then performed extended Thermal-FSI analyses relative to experiment. The issue...
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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublicationThe 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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A Proposed Machine Learning Model for Forecasting Impact of Traffic-Induced Vibrations on Buildings
PublicationTraffic-induced vibrations may cause various damages to buildings located near the road, including cracking of plaster, cracks in load-bearing elements or even collapse of the whole structure. Measurements of vibrations of real buildings are costly and laborious. Therefore the aim of the research is to propose the original numerical algorithm which allows us to predict, with high probability, the nega-tive dynamic impact of traffic-induced...
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Genetic Algorithm Approach for Gains Selection of Induction Machine Extended Speed Observer
PublicationThe subject of this paper is gains selection of an extended induction machine speed observer. A high number of gains makes manual gains selection difficult and due to nonlinear equations of the observer, well-known methods of gains selection for linear systems cannot be applied. A method based on genetic algorithms has been proposed instead. Such an approach requires multiple fitness function calls; therefore, using a quality index...
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Nonadaptive estimation of the rotor speed in an adaptive full order observer of induction machine
PublicationThe article proposes a new method of reproducing the angular speed of the rotor of a cage induction machine designed for speed observers based on the adaptive method. In the proposed solution, the value of the angular speed of the rotor is not determined by the classical law of adaptation using the integrator only by an algebraic relationship. Theoretical considerations were confirmed by simulation and experimental tests.
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Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
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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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Machine-aided detection of SARS-CoV-2 from complete blood count
PublicationThe current gold standard for SARS-CoV-2 detection methods lacks the functionality to perform population screening. Complete blood count (CBC) tests are a cost-effective way to reach a wide range of people – e.g. according to the data of the Central Statistical Office of Poland from 2016, there are 3,000 blood diagnostic laboratories in Poland, and 46% of Polish people have at least one CBC test per year. In our work, we show...
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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...