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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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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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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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ANALYTICAL AND QUANTITATIVE CYTOLOGY AND HISTOLOGY
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Raw data of AuAg nanoalloy plasmon resonances used for machine learning method
Open Research DataRaw data used for machine learning process. UV-vis measurements of AuAg alloyed nanostructures created from thin films. Plasmonic band position dependence on fabrication parameters. Small presentation reviewing achieved structures and their properties.
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Koncepcja zastosowania systemów agentowych do oceny technologii informatycznych
PublicationW pracy przedstawiono koncepcję wykorzystania systemów agentowych do oceny technologii informatycznych. Praca zawiera opis koncepcji oraz przedstawia możliwości wykorzystania narzędzi informatycznych mogących znaleźć zastosowanie do implementacji i weryfikacji proponowanego rozwiązania. Praca jest częścią wspólnych badań nad tworzeniem rozwiązań do oceny technologii informatycznych, które obejmują wykorzystanie ocen eksperckich...
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Combinatorial Pattern Matching
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S-Modules - An Approach to Capture Semantics fo Modularized DL Knowledge Bases
PublicationModularity of ontologies has been recently recognized as a key requirement for collaborative ontology engineering and distributed ontology reuse. Partitioning of an ontology into modules naturally gives rise to development of module processing methods. In this paper we describe an algebra of ontology modules developed during our work on a Knowledge Base Management System called RKaSeA. The idea differs from other algebras in the...
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Concept of the agent system for the information technology evaluation
PublicationIn this paper the concept of the agent system for the information technology evaluation has been presented. This article includes the concept description and shows abilities of using software tools which can be applicable to implementation and verification of proposed solution. The article is the part of common researches over creation solutions for information technology evaluation which range over using expert's evaluation and...
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Marek Kubale prof. dr hab. inż.
PeopleDetails 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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Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publication(1) About 15-20% of couples struggle with the problem of infertility. 30 to 40% of these cases are caused by abnormalities in the structure and motility of sperm. Sometimes the only possibility for such people is to use the procedure of artificial insemination. CASA systems are used to increase the efficiency of this procedure by selecting the appropriate sperm cell. (2) This paper presents an approach to the sperm classification...
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A FPTAS for minimizing total completion time in a single machine time-dependent scheduling problem
PublicationIn 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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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
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Hardware accelerated implementation of wavelet transform for machine vision in road traffic monitoring system
PublicationW 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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A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine
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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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Neural Networks, Support Vector Machine and Genetic Algorithms for Autonomous Underwater Robot Support
PublicationIn 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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3D Machine Vision System for Inspection of Contact Strips in Railway Vehicle Current Collectors
PublicationConstruction 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
PublicationIn 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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SIMULATION AND EXPERIMENTAL RESEARCH OF CLAW POLE MACHINE WITH A HYBRID EXCITATION AND LAMINATED ROTOR CORE
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Optimal selection of the sawdust separation device for a narrow-kerf sawing machine PRW15-M
PublicationW 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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Comparative studies of manufacturing strategies within multi-machine production systems using simulation
PublicationZaprezentowano 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
PublicationCelem 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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Machine-learning methods for estimating compressive strength of high-performance alkali-activated concrete
PublicationHigh-performance alkali-activated concrete (HP-AAC) is acknowledged as a cementless and environmentally friendly material. It has recently received a substantial amount of interest not only due to the potential it has for being used instead of ordinary concrete but also owing to the concerns associated with climate change, sustainability, reduction of CO2 emissions, and energy consumption. The characteristics and amounts of the...
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Game theory-based virtual machine migration for energy sustainability in cloud data centers
PublicationAs the demand for cloud computing services increases, optimizing resource allocation and energy consumption has become a key factor in achieving sustainability in cloud environments. This paper presents a novel approach to address these challenges through an optimized virtual machine (VM) migration strategy that employs a game-theoretic approach based on particle swarm optimization (PSO) (PSO-GTA). The proposed approach leverages...
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DETECTION OF BREATHING AND HEART RATE USING AN ECG SIGNAL MEASURED WHILE BATHING IN THE BATHTUB
PublicationNowadays a new area of interest is gaining importance - it is home biomedical examination. Intelligent home can be supported by set of devices for habitants observation. It can be particularly useful for elders or person with some health risks but living alone. One of critical locations within the house is bathroom. One of utilities in the bathroom is a bathtub which is sometimes preferred over shower. There are reports of problems...
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Multi-criteria Differential Evolution for Optimization of Virtual Machine Resources in Smart City Cloud
PublicationIn a smart city, artificial intelligence tools support citizens and urban services. From the user point of view, smart applications should bring computing to the edge of the cloud, closer to citizens with short latency. However, from the cloud designer point of view, the trade-off between cost, energy and time criteria requires the Pareto solutions. Therefore, the proposed multi-criteria differential evolution can optimize virtual...
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Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublicationSince high-quality real data acquired from selected road sections are not always available, a traffic control solution can use data from software traffic simulators working offline. The results show that in contrast to microscopic traffic simulation, the algorithms employing neural networks can work in real-time, so they can be used, among others, to determine the speed displayed on variable message road signs. This paper describes...
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A machine learning approach to classifying New York Heart Association (NYHA) heart failure
PublicationAccording to the European Society of Cardiology, globally the number of patients with heart failure nearly doubled from 33.5 million in 1990 to 64.3 million in 2017, and is further projected to increase dramatically in this decade, still remaining a leading cause of morbidity and mortality. One of the most frequently applied heart failure classification systems that physicians use is the New York Heart Association (NYHA) Functional...
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
PublicationCirculating tumor cells (CTCs) are tumor cells that separate from the solid tumor and enter the bloodstream, which can cause metastasis. Detection and enumeration of CTCs show promising potential as a predictor for prognosis in cancer patients. Furthermore, single-cells sequencing is a technique that provides genetic information from individual cells and allows to classify them precisely and reliably. Sequencing data typically...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublicationProper 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
PublicationProper 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
PublicationMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine
PublicationRNA protein interactions (RPI) play a pivotal role in the regulation of various biological processes. Experimental validation of RPI has been time-consuming, paving the way for computational prediction methods. The major limiting factor of these methods has been the accuracy and confidence of the predictions, and our in-house experiments show that they fail to accurately predict RPI involving short RNA sequences such as TERRA RNA....
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Speed Observer Structure of Induction Machine Based on Sliding Super-Twisting and Backstepping Techniques
PublicationThis paper presents an analysis of the two speed observer structures which are based on the backstepping and sliding super twisting approach. The observer stabilizing functions result from the Lyapunov theorem. To obtain the observer tuning gains the observer structure is linearized near the equilibrium point. The rotor angular speed is obtained from non-adaptive dependence. In the sensorless control system structure the classical...
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Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers
PublicationThis chapter presents the application of new information technology in education for the training of air traffic controllers (ATCs). Machine learning, multi-criteria decision analysis, and text analysis as the methods of artificial intelligence for ATCs training have been described. The authors have made an analysis of the International Civil Aviation Organization documents for modern principles of ATCs education. The prototype...
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Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection
PublicationDue to the exponential rise of mobile technology, a slew of new mobile security concerns has surfaced recently. To address the hazards connected with malware, many approaches have been developed. Signature-based detection is the most widely used approach for detecting Android malware. This approach has the disadvantage of being unable to identify unknown malware. As a result of this issue, machine learning (ML) for detecting malware...
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Problems associated with the up of actuating system of a single-disc lapping machine for flat surfaces
PublicationPrzedstawiono wyniki badań nagrzewania się podstawowych elementów układu wykonawczego docierarki jednotarczowej o standardowej kinematyce do obróbki powierzchni płaskich. Analizowano przyrost temperatury zespołu napędowego, rolek i pierścieni prowadzących separatory oraz tarczy docierającej i obrabianych elementów. Badano nagrzewanie się układu obróbkowego podczas wyrównywania żeliwnego narzędzia i docierania powierzchni płaskich....
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Non-Adaptive Rotor Speed Estimation of Induction Machine in an Adaptive Full-Order Observer
PublicationIn the sensorless control system of an induction machine, the rotor speed value is not measured but reconstructed by an observer structure. The rotor speed value can be reconstructed by the classical adaptive law with the integrator. The second approach, which is the main contribution of this paper, is the non-adaptive structure without an integrator. The proposed method of the rotor speed reconstruction is based on an algebraic...
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Speed observer of induction machine based on backstepping and sliding mode for low‐speed operation
PublicationThis paper presents a speed observer design based on backstepping and slidingmode approaches. The inputs to the observer are the stator current and thevoltage vector components. This observer structure is extended to the integra-tors. The observer stabilizing functions contain the appropriate sliding surfaceswhich result from the Lyapunov function. The rotor angular speed is obtainedfrom the non‐adaptive formula with a sliding...
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Advances in Architectures, Big Data, and Machine Learning Techniques for Complex Internet of Things Systems
PublicationTe feld of Big Data is rapidly developing with a lot of ongoing research, which will likely continue to expand in the future. A crucial part of this is Knowledge Discovery from Data (KDD), also known as the Knowledge Discovery Process (KDP). Tis process is a very complex procedure, and for that reason it is essential to divide it into several steps (Figure 1). Some authors use fve steps to describe this procedure, whereas others...
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Techniki szybkiego prototypowania w budowie maszyn = Rapid prototyping techniques in machine building
PublicationW 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
PublicationThe 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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Load effect impact on the exploitation of concrete machine foundations used in the gas and oil industry
PublicationMachine foundations is a critical topic in the gas and oil industry, which design and exploitation require extensive technical knowledge. Machine foundations are the constructions which are intended for mounting on it a specific type of machine. The foundation has to transfer dynamic and static load from machine to the ground. The primary difference between machine foundations and building foundations is that the machine foundations...
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Polymeric Bearings as a new base isolation system suitable for mitigating machine-induced vibrations
PublicationThe present paper summarizes the preliminary results of the experimental shaking table investigation conducted in order to verify the effectiveness of a new base isolation system consisting of Polymeric Bearings in reducing strong horizontal machine-induced vibrations. Polymeric Bearing considered in the present study is a prototype base isolation system, which was constructed with the use of a specially prepared flexible polymer...
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Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublicationCatheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified...
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Turk Onkoloji Dergisi-Turkish Journal of Oncology
Journals