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Wyniki wyszukiwania dla: STRING MATCHING
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Optimal edge-coloring with edge rate constraints
PublikacjaWe consider the problem of covering the edges of a graph by a sequence of matchings subject to the constraint that each edge e appears in at least a given fraction r(e) of the matchings. Although it can be determined in polynomial time whether such a sequence of matchings exists or not [Grötschel et al., Combinatorica (1981), 169–197], we show that several questions about the length of the sequence are computationally intractable....
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Studii si cercetări filologice. Seria Limbi Străine Aplicate
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Machine learning techniques combined with dose profiles indicate radiation response biomarkers
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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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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
PublikacjaHigher 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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Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
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<title>Management system of ELHEP cluster machine for FEL photonics design</title>
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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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The application of a photopolymer material for the manufacture of machine elements using rapid prototyping techniques
PublikacjaThe 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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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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Multivariate Features Extraction and Effective Decision Making Using Machine Learning Approaches
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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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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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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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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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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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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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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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Dynamic variables limitation for backstepping control of induction machine and voltage source converter
PublikacjaDynamic 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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Sensorless control of five-phase induction machine supplied by the VSI with output filter
PublikacjaIn 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
PublikacjaThis 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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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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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 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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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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W stronę spersonalizowanego miasta?
PublikacjaOd czasów Platona i Witruwiusza nie ustają wysiłki na rzecz dążenia do prawdy, dobra i piękna skupione wokół miasta jako idei politycznej i przestrzeni fundamentalnie egzystencjalnej. Towarzyszy im od wieków myślenie o idealnej organizacji i kompozycji miasta, o poczuciu podmiotowości mieszkańców i użytkowników, doświadczaniu przez nich czasu i przestrzeni. Szczególnie w ostatnich dekadach, gdy już nie przestrzeń, a czas i jego...
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Knowledge Risks in the Sharing Economy
PublikacjaThis chapter presents a theoretical analysis of potential risks connected with knowledge that organizations operating in the sharing economy might potentially face. Nowadays, it can be stated that an increasing amount of individuals and organizations participate in sharing and exchanging data, information, and knowledge, as well as physical goods and services (Botsman & Rogers, 2011). The development of the sharing economy has...
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Fast bubble dynamics and sizing
PublikacjaSingle bubble sizing is usually performed by measuring the resonant bubble response using the Dual Frequency Ultrasound Method. However, in practice, the use of millisecond-duration chirp-like waves yields nonlinear distortions of the bubble oscillations. In comparison with the resonant curve obtained under harmonic excitation, it was observed that the bubble dynamic response shifted by up to 20 percent of the resonant frequency...
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MULTIMODALNE POMIARY DRGAŃ STRUNY
PublikacjaW artykule zostały przedstawione badania drgań struny zrealizowane przy użyciu szybkich kamer wizyjnych, mikrofonu oraz akcelerometru. Obiektem badań były instrumenty muzyczne. Opisano zjawiska zachodzące w instrumencie podczas tworzenia się i wydobywania z niego dźwięku. Celem pracy było zbadanie różnic w wynikach otrzymanych poprzez pomiary wykonane z użyciem zróżnicowanych reprezentacji obrazowych i sygnałowych. Zaproponowano...
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Economics of credit scoring management
PublikacjaCredit scoring models constitute an inevitable element of modern risk and profitability management in retail financial lending institutions. Quality,or separation power of a credit scoring model is usually assessed with the Gini coefficient. Generally, the higher Gini coefficient the better, as in this way a bank can increase number of good customers and/or reject more bad applicants. In...
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Mobbing ze strony współpracowników.
PublikacjaPrzesladowcą(mobberem),oprócz podmiotu zatrudniającego,moze być również inny pracownik.Jest to sytuacja,w której pojawiają sie różne relacje interpersonalne, z którch najważniejszą dotyczą:pracodawcy-mobbera,pracodawcy-mobbingowanego,mobbera-mobbingowanego.W opracowaniu opisano instytucje prawne utrudniajace lub wręcz uniemożliwiające rozwój mobbingu.Szczególną uwagę zwrócono na opisanie instytucji rozwiazania umowy o pracę(zarówno...
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Raw data of AuAg nanoalloy plasmon resonances used for machine learning method
Dane BadawczeRaw 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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Combinatorial Pattern Matching
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Zeszyty Naukowe Centrum Badań im. Edyty Stein
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Modelling the Safety Levels of ICT Equipment Exposed to Strong Electromagnetic Pulses
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Stimulation of Heavy Metal Adsorption Process by Using a Strong Magnetic Field
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Storing thermal energy from solar collectors for the needs of a detached house
PublikacjaThis work evaluates the possibility of meeting a single familu household's need for hot water and heat year round, using solar collectors as the sole energy sourse. The main flaw of energetic systems based on solar energy is that the energy supply is usually insufficient in winter, when it is most needed. This work is going to show thatm for a house surface of 150 m2 and base dimension of 10x10m, it is possible to supply sufficient...
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The shadowing chain lemma for singular Hamiltonian systems involving strong forces
PublikacjaW niniejszym artykule rozważamy autonomiczny układ Hamiltonowski na płaszczyźnie z potencjałem, który ma punkt osobliwy (studnię nieskończonej głębokości) i maksimum globalne właściwe równe zero przyjmowane w dwóch różnych punktach płaszczyzny. Przy założeniu, że w otoczeniu punktu osobliwego potencjał spełnia warunek Gordona(gradient tego potencjału w otoczeniu punktu osobliwego jest tzw. silną siłą, ang. a strong force) dowodzimy...
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On the use of enhanced strain formulation in 6-field nonlinear shell theory with asymetric strain measures
PublikacjaW pracy zbadano możliwość zastosowania techniki wzbogaconych odkształceń do usunięcia zjawiska blokady w elementach skończonych opracowanych w ramach 6-parametrowej nieliniowej teorii powłok z niesymetrycznymi miarami odkształceń membranowych. Przedstawiono i porównano 4 warianty pol wzogacających odkształcenia
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Analysis of strain localization in reinforced concrete elements with explicit second-gradient strain damage approach
PublikacjaArtykuł omawia obliczanie elementów żelbetowych przy zastosowaniu modelu zniszczeniowego z degradacją sztywności z uwzględnieniem lokalizacji odkształceń. Obliczenia wykonano dla belek żelbetowych.
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Piotr Paradowski dr
OsobyDr Piotr Paradowski's areas of expertise in quantitative social science methods include truncated and censored models, quantile regressions, survival analysis, panel data models, discrete regressions and qualitative choice models, instrumental variable estimation, and hierarchical modeling. He is also an expert in statistical matching and statistical methods to handle missing data. In addition, he conducts research on income and...
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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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Predicting Value of Binding Constants of Organic Ligands to Beta-Cyclodextrin: Application of MARSplines and Descriptors Encoded in SMILES String
PublikacjaThe quantitative structure–activity relationship (QSPR) model was formulated to quantify values of the binding constant (lnK) of a series of ligands to beta–cyclodextrin (β-CD). For this purpose, the multivariate adaptive regression splines (MARSplines) methodology was adopted with molecular descriptors derived from the simplified molecular input line entry specification (SMILES) strings. This approach allows discovery of regression...