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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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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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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.
PublicationW pracy przedstawiono wpływ kinematyki pilarki ramowej na zużycie ostrzy piłtrakowych.
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Analytical model of torsional vibrations of typical sawing machine main drive system
PublicationPrzedstawiono 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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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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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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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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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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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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Mapping of the Covid-19 Vaccine Uptake Determinants From Mining Twitter Data
PublicationOpinion polls on vaccine uptake clearly show that Covid-19 vaccine hesitancy is increasing worldwide. Thus, reaching herd immunity not only depends on the efficacy of the vaccine itself, but also on overcoming this hesitancy of uptake in the population. In this study, we revealed the determinants regarding vaccination directly from people’s opinions on Twitter, based on the framework of the 6As taxonomy. Covid-19 vaccine acceptance...
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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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Predicting emotion from color present in images and video excerpts by machine learning
PublicationThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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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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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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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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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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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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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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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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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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Proposal of New Starch-Blends Composition Quickly Degradable in Marine Environment
PublicationThe aim of this paper was to obtain a quickly degradable in seawater polymer blend as an alternative proposal for classical polymer packaging. For preliminary studies: poly(lactic acid) (PLA), starch, calcium carbonate (CaCO3), gelatin and glycerol were chosen. PLA was pointed out due to its biodegradability and comparable properties to polyethylene or polypropylene. Whereas starch was chosen as abundant, renewable and cheap polymer...
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Mercury concentrations in marine biota with special focus on grey and ringed seals
PublicationMarine organisms are exposed and sensitive to effects of environmental contamination by heavy metals including different forms of mercury. Baltic seals as the top predators of the marine ecosystem are even more endangered due to (considerable) longevity as well as a long biological half-time of toxin elimination. The concentrations of mercury in seals from the Baltic is poorly known, thus the aim of this work is to determine and...
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Multisensor Tracking of Marine Targets - Decentralized Fusion of Kalman and Neural Filters
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Calcite Nanotuned Chitinous Skeletons of Giant Ianthella basta Marine Demosponge
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Multibeam Sonar Characterisation of Seafloor in the Context of Visualisation and Dissemination of Marine Data
PublicationThe paper presents the seafloor characterisation method based on multibeam sonar data. it relies on using three types of multibeam seafloor sensing data: 1) the grey-level sonar images (echograms) of seabed, 2) the 3D model of the seabed surface which consists of high resolution bathymetric data, 3) the set of time domain bottom echo envelopes received in the consecutive sonar beams. The classification is performed by utilisation...
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Diagnosing marine turbine engines through energy characteristics of their flow section
PublicationThe aim of the performed research was to develop of diagnostic method of the flow section of a marine turbine combustion engine based on the level of delamination of its energy characteristics. The here adopted diagnostic model provides for a formulation of the evaluation of the technical conditions based on the measurements of the parameters of the thermodynamic medium in the characteristic control cross-sections of the engine...
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Identification of diagnostic parameter sensitivity during dynamic processes of a marine engine
PublicationChanging some parameters of the engine structure alters the emission of harmful components in the exhaust gas. This applies in particular to the damage of charge exchange system as well as fuel system and engine supercharger. These changes are much greater during the dynamic states and their accompanying transitional processes. The different sensitivity of diagnostic parameters to the same force, coming from the engine structure, but...
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Speciation of trace element compounds in samples of biota from marine ecosystems
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3D visualisation and monitoring of marine pollutant aggregations in Web-based GIS
PublicationPrzedstawiony internetowy GIS służy do integracji, przetwarzania i wizualizacji pochodzących z wielu źródeł danych o różnych komponentach środowiska morskiego, w tym o zanieczyszczeniach. Jako przykład przedstawiono wyniki trójwymiarowego modelowania rozprzestrzeniania się wylewu olejowego w morzu.
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Using Rule-Based System for Monitoring Marine Navigation Data Processing
PublicationProcessing marine navigational data requires sophisticated software solutions. Typically, specialized tools called processors are analyzing raw data from different sensors. It becomes important to create the monitoring software that is able to validate and verify processing components integrated into the final system. Drools®business rule management platform provides a core business rules engine, web authoring and rules management...
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Implementing Simulationx in the Modelling of Marine Shafting Steady State Torsional Vibrations
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Distribution of the International Marine Traffic Air Pollutant Emissions in the Port of Split
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Speciation of heavy metal compounds in samples of biota from marine ecosystems
PublicationIt has become increasingly evident that the toxicity, mobility, bioavailability and bioaccumulation of metals are dependent on the particular physico-chemical form in which the element occurs in the environment. Special attention is paid to metals, which are essential for the proper functioning of organisms if present in appropriate amounts but are toxic if in excess (i.e. Se, Cr, Zn), and also to non-essential elements (i.e. Hg,...
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Integration of Geographic Information Systems for Monitoring and Dissemination of Marine Environment Data
PublicationZastosowanie Systemów Informacji Przestrzennej (GIS) do celu monitorowania i wizualizacji różnych procesów środowiska morskiego jest dziedziną badaną od końca XX wieku. W ostatnich latach rozwój szerokopasmowego dostępu do Internetu oraz dostępność klastrów obliczeniowych pozwalają na wykonywanie czasochłonnych i wymagających operacji, takich jak analizy przestrzenne, w sposób zdalny. Jakkolwiek do tej pory sieciowe Systemy Informacji...
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Analytical methods and problems related to the determination of organotin compounds in marine sediments
PublicationProcedury analityczne oznaczania zwiazków cynoorganicznych w osadach morskich skladają się z wilu operacji i czynnosci (pobieranie próbek, wstępne przygotowanie, transport, oznaczenia końcowe). Zazwyczaj procedury te charakteryzują się dużą praco- i czasochłonnością. W pracy omówiono podstawowe źródła błędów zwiazane z w/wym etapami postepowania analitycznego oraz przedstawiono sposoby im zapobiegania.
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Possibilities of heat transfer augmentation in heat exchangers with minichannels for marine applications
PublicationIn the paper, new trends in development of microchannel heat exchangers are presented. The exchangers developed in this way can be applied in marine applications. Main attention was focused on heat exchangers design with reduced size of passages namely based on microchannels. In our opinion future development of high power heat exchangers will be based on networks micro heat exchangers.
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Hydrodynamic Loads on Marine Propellers Subject to Ventilation and Out of Water Condition
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Hydrodynamic Loads on Marine Propellers Subject to Ventilation and Out of Water Condition
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Detection of corrosion process in marine environment by means of acoustic emission technique
PublicationW pracy przedstawiono możliwość detekcji procesu korozyjnego nieniszczącą metodą emisji akustycznej konstrukcji metalowych pracujących w środowisku wody morskiej. Pewną alternatywą wobec technik elektrochemicznych w monitorowaniu korozji zaproponowano nieniszczącą technikę emisji akustycznej. Emisja akustyczna znana jako zjawisko fizyczne i technika pomiarowa znalazły zastosowanie w detekcji korozji obiektów morskich. W związku...
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The reuse of brine to enhance the ripening of marine and freshwater fish resistant to marinating
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On the Use of Selected 4th Generation Nuclear Reactors in Marine Power Plants
PublicationThis article provides a review of the possibility of using different types of reactors to power ships. The analyses were carried out for three different large vessels: a container ship, a liquid gas carrier and a bulk carrier. A novelty of this work is the analysis of the proposal to adapt marine power plants to ecological requirements in shipping by replacing the conventional propulsion system based on internal combustion engines...
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Operation evaluation method for marine turbine combustion engines in terms of energetics
PublicationAn evaluation proposal (quantitative determination) of an y combustion turbine engine operation has been presented , wherein the impact energy occurs at a given time due to Energy conversion. The fact has been taken into account that in this type of internal combustion engines the energy conversion occurs first in the combustion chambers and in the spaces between the blade of the turbine engine. It was assumed that in the combustion...
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Thermohydraulic and thermoeconomic performance of a marine heat exchanger on a naval surface ship
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International Journal of Machine Learning and Cybernetics
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