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Improving operating efficiency of a gas turboset via cooperation with an absorption refrigerating machine
PublikacjaThe analysis of increase of ambient air temperature entering the compressor on reduction in power output from the turbine and increase fuel use was conduced. For medium size gas turbine operates in winter and summer conditions elementary power and economical values was calculated. Conditions of the determination of turbine inlet air cooling solution (using thermal storage for reduce equipment size) are presented
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Sensorless Multiscalar Control of Five-Phase Induction Machine with Inverter Output Filter
PublikacjaThe paper presents a complete solution for speed sensorless control system for five-phase induction motor with voltage inverter, LC filter and nonlinear control of combined fundamental and third harmonic flux distribution. The control principle, also known as multiscalar control, nonlinear control or natural variables control, is based on a use of properly selected scalar variables in control feedback to linearize controlled system....
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Application of Support Vector Machine for Determination of Impact of Traffic-Induced Vibrations on Buildings
PublikacjaThe 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.
PublikacjaW 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
PublikacjaPrzedstawiono model fizyczny i matematyczny drgań skrętnych napędu głównego typowej pilarki tarczowej. Model tworzą elementy sztywne SES połączone między sobą za pośrednictwem elementów sprężysto - tłumiących EST w układzie szeregowym. W modelu matematycznym uwzględniono: właściwości dynamiczne silnika napędowego, wymiary piły tarczowej, cechy materiału obrabianego (wymiary, rodzaj drewna, wilgotność drewna) oraz właściwości dynamiczne...
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Detection of People Swimming in Water Reservoirs with the Use of Multimodal Imaging and Machine Learning
PublikacjaEvery 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
PublikacjaTo this day, driver fatigue remains one of the most significant causes of road accidents. In this paper, a novel way of detecting and monitoring a driver’s physical state has been proposed. The goal of the system was to make use of multimodal imaging from RGB and thermal cameras working simultaneously to monitor the driver’s current condition. A custom dataset was created consisting of thermal and RGB video samples. Acquired data...
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Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublikacjaBiochar 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
PublikacjaThis 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
PublikacjaThe 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
PublikacjaThe 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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Nonadaptive estimation of the rotor speed in an adaptive full order observer of induction machine
PublikacjaThe 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
PublikacjaThis 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
PublikacjaThe 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
PublikacjaComplexity 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
PublikacjaIn 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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SYNTHESIS OF PHOSPHORUS TACRINE ANALOGUES AS A NEW POTENTIAL ANTI-ALZHEIMER’S DISEASE AGENTS
PublikacjaA series of novel phosphorus tacrine derivatives was obtained in three steps, including synthesis of 9-chlorotacrine, connection of 9-chlorotacrine with hexamethylenediamine, 1,8-diaminooctane and 1,12-diaminododecane linkers and reaction of obtained tacrine diamine analogues with corresponding acid ester to give nine tacrine organophosphorus compounds. All of the obtained final structures were characterized by 1H NMR, 13C NMR,...
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RSS-Based DoA Estimation for ESPAR Antennas Using Support Vector Machine
PublikacjaIn 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
PublikacjaThe 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
PublikacjaWe 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
PublikacjaPlasmonic 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
PublikacjaTraffic-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
PublikacjaThe 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
PublikacjaThe aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was...
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Marek Kubale prof. dr hab. inż.
OsobyDetails concerning: Qualifications, Experiences, Editorial boards, Ph.D. theses supervised, Books, and Recent articles can be found at http://eti.pg.edu.pl/katedra-algorytmow-i-modelowania-systemow/Marek_KubaleGoogle ScholarSylwetka prof. Marka Kubalego Prof. Marek Kubale pracuje na Wydziale ETI Politechniki Gdańskiej nieprzerwanie od roku 1969. W tym czasie napisał ponad 150 prac naukowych, w tym ponad 40 z listy JCR. Ponadto...
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3D Machine Vision System for Inspection of Contact Strips in Railway Vehicle Current Collectors
PublikacjaConstruction and technical condition of current collectors is crucial to reliability and safety of railway transportation. According to the Technical Specifications for Interoperability railway vehicles in the European Union should be equipped with carbon contact strips. Excessive wear or defects of contact strips degrade the capability of undisturbed power transmission, cause faster wear of contact wire, and can even result in...
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SSFR Test of Synchronous Machine for Different Saturation Levels using Finite-Element Method
PublikacjaIn this paper the StandStill Frequency Response characteristics (SSFR) of saturated synchronous generator (SG) have been calculated using Finite Element Method (FEM) analysis. In order to validate proposed approach for unsaturated conditions FEM simulation from Flux2D software has been compared with the measurements performed on the 10 kVA, 4- poles synchronous machine ELMOR GCe64a of salient rotor construction, equipped with a...
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A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine
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A FPTAS for minimizing total completion time in a single machine time-dependent scheduling problem
PublikacjaIn this paper a single machine time-dependent scheduling problem with total completion time criterion is considered. There are given n jobs J1,…,Jn and the processing time pi of the ith job is given by pi=a+bisi, where si is the starting time of the ith job (i=1,…,n),bi is its deterioration rate and a is the common base processing time. If all jobs have deterioration rates different and not smaller than a certain constant u>0,...
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Neural Networks, Support Vector Machine and Genetic Algorithms for Autonomous Underwater Robot Support
PublikacjaIn this paper, artificial neural networks, a classification technique called support vector machine and meta-heuristics genetic algorithm have been considered for development in autonomous underwater robots. Artificial neural networks have been used for seabed modelling as well as support vector machine has been applied for the obstacles classification to avoid some collision problems. Moreover, genetic algorithm has been applied...
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Techniki szybkiego prototypowania w budowie maszyn = Rapid prototyping techniques in machine building
PublikacjaW artykule omówiono przygotowanie oraz wykonanie poszczególnych elementów maszyn za pomocą techniki szybkiego prototypowania. W pierwszej części przedstawiono technologię wydruku przestrzennego oraz właściwości materiału budulcowego. Druga część artykułu została poświęcona przykładowym wydrukom i ich zastosowaniom w maszynach.
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Sensorless control system of induction machine supplied by voltage source inverter with output filter
PublikacjaThe paper focuses on sensorless control of the induction machines supplied by inverter with the output filters. “The novel” idea of the speed observer which is based on the backstepping approach is shown. The standard structure of the exponential observer is extended by the integrators and additional Z vector. The simulation and experimental results validate the proposed solution.
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Machine Learning for Control Systems Security of Industrial Robots: a Post-covid-19 Overview
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Likelihood of Transformation to Green Infrastructure Using Ensemble Machine Learning Techniques in Jinan, China
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Machine Learning Methods in Damage Prediction of Masonry Development Exposed to the Industrial Environment of Mines
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Hardware accelerated implementation of wavelet transform for machine vision in road traffic monitoring system
PublikacjaW artykule został opisany system monitorowania ruchu drogowego wykorzystujący sprzętową implementację transformacji falkowej. System został zaimplementowany za pomocą procesora zrealizowanego w technologii FPGA i małej kamery z układem konwersji analogowo-cyfrowej. System wykorzystuje transformację falkową do detekcji zatorów na skrzyżowaniach. W artykule zostały przedstawione przykładowe rezultaty rozpoznawania zatorów drogowych...
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The Problems of Application of PVD/CVD Thin Hard Coatings for Heavy-Loaded Machine Components
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SIMULATION AND EXPERIMENTAL RESEARCH OF CLAW POLE MACHINE WITH A HYBRID EXCITATION AND LAMINATED ROTOR CORE
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
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Comparative studies of manufacturing strategies within multi-machine production systems using simulation
PublikacjaZaprezentowano metodykę budowy struktur przestrzennych systemów produkcji typu gniazdowego wg zasad technologii grupowej, wykorzystując zaproponowane modele i algorytmy analizy zbiorów/relacji rozmytych. Generowane, z wykorzystaniem tych algorytmów, przebiegi procesów porównywano z przebiegami procesów w strukturach przestrzennych typu hybrydowego, tj. o wspólnych zasobach. Odnosząc się do zdefiniowanego studium przypadku, wykazano...
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Quality evaluation of computer aided information retrieval from machine typed paper documents
PublikacjaCelem międzynarodowego projektu memorial jest wspomagane komputerowo rozpoznawanie maszynopisów. Referat prezentuje zagadnienie pomiaru jakości takiego procesu. Wskazano w nim potencjalne miejsca pojawiania się błędów oraz przedstawiono i sklasyfikowano odpowiednie miary.
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Optimal selection of the sawdust separation device for a narrow-kerf sawing machine PRW15-M
PublikacjaW pracy przedstawiono granulometryczną analizę rozkładu wiórów i pyłu drzewnego otrzymanego w procesie przecinania suchych pryzm sosnowych na pilarce ramowej wielopiłowej PRW15-M. Wielkości wiórów mieściły się w granicach od 84,7 μm do nawet 14 mm. Te ostatnie są elementami będącymi efektem rozszczepiania dolnej powierzchni pryzmy przez wychodzące z niej ostrza piły. Większośc wiórów z najmniejszych frakcji ma postać sześciennych...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublikacjaProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublikacjaProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublikacjaMany 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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A machine learning approach to classifying New York Heart Association (NYHA) heart failure
PublikacjaAccording 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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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
PublikacjaCirculating 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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Game theory-based virtual machine migration for energy sustainability in cloud data centers
PublikacjaAs 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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Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers
PublikacjaThis 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...