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- Publikacje 1491 wyników po odfiltrowaniu
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Wyniki wyszukiwania dla: e. coli, machine learning, optical method, spectroscopy, urine, urospesis
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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublikacjaTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
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Anita Maria Dąbrowicz-Tlałka dr
OsobyUzyskała, z wynikiem bardzo dobrym, tytuł magistra na kierunku matematyka na Wydziale Matematyki Uniwersytetu Gdańskiego. Praca magisterska pt. „Zbiory swojskie i dzikie w R3” była z dziedziny topologia geometryczna. Równolegle ukończyła na Uniwersytecie Gdańskim „Podyplomowe Studium Podstaw Informatyki”. W 2001 roku uzyskała na Politechnice Poznańskiej tytuł doktora nauk matematycznych. Praca doktorska pt. „Iteracje monotoniczne...
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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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PERFORMANCE COMPARISON OF MACHINE LEARNING ALGORITHMS FOR PREDICTIVE MAINTENANCE
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Machine Learning for Sensorless Temperature Estimation of a BLDC Motor
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Stacking-Based Integrated Machine Learning with Data Reduction
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Data Reduction Algorithm for Machine Learning and Data Mining
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Machine Learning Modelling and Feature Engineering in Seismology Experiment
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Machine learning applied to bi-heterocyclic drugs recognition
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Personal bankruptcy prediction using machine learning techniques
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Machine learning system for estimating the rhythmic salience of sounds.
PublikacjaW artykule przedstawiono badania dotyczące wyszukiwania danych rytmicznych w muzyce. W pracy przedstawiono postać funkcji rankingujacej poszczególnych dźwięków frazy muzycznej. Opracowano metodę tworzenia wszystkich możliwych hierarchicznych struktur rytmicznych, zwanych hipotezami rytmicznymi. Otrzymane hipotezy są następnie porządkowane w kolejności malejącej wartości funkcji rankingującej, aby ustalić, która ze znalezionych...
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INVESTIGATION OF THE LOMBARD EFFECT BASED ON A MACHINE LEARNING APPROACH
PublikacjaThe Lombard effect is an involuntary increase in the speaker’s pitch, intensity, and duration in the presence of noise. It makes it possible to communicate in noisy environments more effectively. This study aims to investigate an efficient method for detecting the Lombard effect in uttered speech. The influence of interfering noise, room type, and the gender of the person on the detection process is examined. First, acoustic parameters...
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The use of machine learning for face regions detection in thermograms
PublikacjaThe aim of this study is to analyse the methods of detecting characteristic points of the face in thermographic images. As part of the implementation an extensive analysis of scientific publications covering similar issues both for the analysis of images made in visible light and thermographic images was carried out. On the basis of this analysis, 3 models were selected and then they were implemented and tested on the basis of...
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MACHINE LEARNING SYSTEM FOR AUTOMATED BLOOD SMEAR ANALYSIS
PublikacjaIn this paper the authors propose a decision support system for automatic blood smear analysis based on microscopic images. The images are pre-processed in order to remove irrelevant elements and to enhance the most important ones - the healthy blood cells (erythrocytes) and the pathologic (echinocytes). The separated blood cells are analyzed in terms of their most important features by the eigenfaces method. The features are the...
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MACHINE LEARNING–BASED ANALYSIS OF ENGLISH LATERAL ALLOPHONES
PublikacjaAutomatic classification methods, such as artificial neural networks (ANNs), the k-nearest neighbor (kNN) and selforganizing maps (SOMs), are applied to allophone analysis based on recorded speech. A list of 650 words was created for that purpose, containing positionally and/or contextually conditioned allophones. For each word, a group of 16 native and non-native speakers were audio-video recorded, from which seven native speakers’...
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Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study
PublikacjaThis study explores the edaravone solubility space encompassing both neat and binary dissolution media. Efforts were made to reveal the inherent concentration limits of common pure and mixed solvents. For this purpose, the published solubility data of the title drug were scrupulously inspected and cured, which made the dataset consistent and coherent. However, the lack of some important types of solvents in the collection called...
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E-learning w małych i średnich przedsiębiorstwach
PublikacjaW rozdziale przedstawiono podstawowych zagadnienia e-learningu w małych i średnich przedsiębiorstwach oraz przykłady realizowanych projektów.
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E-learning course "International comparative studies on SMEs"
PublikacjaProjekt Leonardo da Vinci "International comparative studies and course development on SMEs" został zainspirowany poprzednim projektem LdV "A European Diploma in SME Management". Bazując na poprzednich doświadczeniach projektowych zaproponowano opracowanie struktur dla opisania narodowych systemów małych i średnich przedsiębiorstw (ang. SME Small Media Enterprises) przy wykorzystaniu dostępnych krajowych danych. Udowodniono, że...
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Olgun Aydin dr
OsobyOlgun Aydin finished his PhD by publishing a thesis about Deep Neural Networks. He works as a Principal Machine Learning Engineer in Nike, and works as Assistant Professor in Gdansk University of Technology in Poland. Dr. Aydin is part of editorial board of "Journal of Artificial Intelligence and Data Science" Dr. Aydin served as Vice-Chairman of Why R? Foundation and is member of Polish Artificial Intelligence Society. Olgun is...
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From Data to Decision: Interpretable Machine Learning for Predicting Flood Susceptibility in Gdańsk, Poland
PublikacjaFlood susceptibility prediction is complex due to the multifaceted interactions among hydrological, meteorological, and urbanisation factors, further exacerbated by climate change. This study addresses these complexities by investigating flood susceptibility in rapidly urbanising regions prone to extreme weather events, focusing on Gdańsk, Poland. Three popular ML techniques, Support Vector Machine (SVM), Random Forest (RF), and...
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Predicting seismic response of SMRFs founded on different soil types using machine learning techniques
PublikacjaPredicting the Maximum Interstory Drift Ratio (M-IDR) of Steel Moment-Resisting Frames (SMRFs) is a useful tool for designers to approximately evaluate the vulnerability of SMRFs. This study aims to explore supervised Machine Learning (ML) algorithms to build a surrogate prediction model for SMRFs to reduce the need for complex modeling. For this purpose, twenty well-known ML algorithms implemented in Python software are trained...
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Novel approach to modeling spectral-domain optical coherence tomography with Monte Carlo method
PublikacjaNumerical modeling Optical Coherence Tomography (OCT) systems is needed for optical setup optimization, development of new signal processing methods and assessment of impact of different physical phenomena inside the sample on OCT signal. The Monte Carlo method has been often used for modeling Optical Coherence Tomography, as it is a well established tool for simulating light propagation in scattering media. However, in this method...
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Systemy z Uczeniem Maszynowym / Systems with Machine Learning 2022/2023
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublikacjaDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublikacjaDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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Diagnostics of cvd process by means of optical emission spectroscopy.
PublikacjaZastosowano optyczną spektroskopię emisyjną do badania w trybie in-situ dysocjacji cząsteczek oraz wzbudzenia i jonizacji atomów wodoru podczas procesu syntezy cienkich warstw diamentowych metodą chemicznego osadzania z par gazowych wspomaganego plazmą mikrofalową (mPACVD). Zbudowano tor światłodowy, umożliwiający sprzężenie komory CVD z systemem spektroskopowym i wykonywanie pomiarów bezinwazyjnych. Wykonano pomiary spektralne...
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Machine-Learning-Powered EM-Based Framework for Efficient and Reliable Design of Low Scattering Metasurfaces
PublikacjaPopularity of metasurfaces has been continuously growing due to their attractive properties including the ability to effectively manipulate electromagnetic (EM) waves. Metasurfaces comprise optimized geometries of unit cells arranged as a periodic lattice to obtain a desired EM response. One of their emerging application areas is the stealth technology, in particular, realization of radar cross section (RCS) reduction. Despite...
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Lead-free bismuth-based perovskites coupled with g–C3N4: A machine learning based novel approach for visible light induced degradation of pollutants
PublikacjaThe use of metal halide perovskites in photocatalytic processes has been attempted because of their unique optical properties. In this work, for the first time, Pb-free Bi-based perovskites of the Cs3Bi2X9 type (X = Cl, Br, I, Cl/Br, Cl/I, Br/I) were synthesized and subjected to comprehensive morphological, structural, and surface analyses, and photocatalytic properties in the phenol degradation reaction were examined. Furthermore,...
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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublikacjaOne of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the ability to anticipate their flexural response. With a comprehensive grid search, several stacked models (i.e., chained, parallel) consisting of various machine learning (ML) algorithms and artificial neural networks (ANNs) were developed to predict the flexural response of SFRC beams. The flexural performance of SFRC beams under bending was...
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Cost-Efficient Measurement Platform and Machine-Learning-Based Sensor Calibration for Precise NO2 Pollution Monitoring
PublikacjaAir quality significantly impacts human health, the environment, and the economy. Precise real-time monitoring of air pollution is crucial for managing associated risks and developing appropriate short- and long-term measures. Nitrogen dioxide (NO2) stands as a common pollutant, with elevated levels posing risks to the human respiratory tract, exacerbating respiratory infections and asthma, and potentially leading to chronic lung...
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Optical flow method for measuring deformation of soil specimen subjected to torsional shearing
PublikacjaIn this study optical flow method was used for soil small deformation measurement in laboratory tests. The main objective was to observe how the deformation distributes along the whole height of cylindrical soil specimen subjected to torsional shearing (TS test). The experiments were conducted on dry non-cohesive soil specimens under two values of isotropic pressure. Specimens were loaded with low-amplitude cyclic torque to analyze...
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Extracellular secretion of Pseudoalteromonas sp. cold-adapted esterase in Escherichia coli in the presence of Pseudoalteromonas sp. components of ABC transport system
PublikacjaEnzymy lipolityczne, głównie lipazy i esterazy, stanowią cenną grupę biokatalizatorów wykorzystywanych w przemyśle. Coraz większe zainteresowanie tą klasą enzymów sprawiło, że poszukuje się alternatywnych źródeł ich pozyskiwania. W celu zbadania wpływu białek transportu ABC Pseudoalteromonas sp. 643A na ekspresję genu, sekrecję i aktywność esterazy EstA z tego mikroorganizmu w systemie ekspresyjnym E. coli skonstruowano układ do...
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Optical Emission Spectroscopy of Microwave (915 MHz) Plasma in Atmospheric Pressure Nitrogen with Addition of Ethanol Vapour
PublikacjaIn this paper results of optical emission spectroscopic study of microwave 915 MHz plasma in atmospheric pressure nitrogen with an addition of ethanol vapour are presented. The plasma was generated in waveguide- -supplied cylinder-type nozzleless microwave plasma source. The aim of research was to determine the rotational Trot and vibrational Tvib temperatures of CN and C2. A method called bubbling was employed to introduce alcohol (ethanol)...
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A rapid and sensitive method for the quantitative analysis of ibuprofen and its metabolites in equine urine samples by gas chromatography-tandem mass spectrometry
PublikacjaIbuprofen is widely used in human and veterinary medicine for the treatment of chronic pain as well as rheumatic and musculoskeletal disorders. However, t he anal- gesic and anti-inflammatory properties of Ibuprofen have contributed to frequent drug abuse in equestr ian s ports. A sensitive and rapid gas chromatography with tandem mass spectrometry based method with a simple liquid-liquid extraction and deriva- tization requiring...
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Playback detection using machine learning with spectrogram features approach
PublikacjaThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublikacjaBiomass management in terms of energy consumption optimization has become a recent challenge for developed countries. Nevertheless, the multiplicity of materials and operating parameters controlling energy consumption in wastewater treatment plants necessitates the need for sophisticated well-organized disciplines in order to minimize energy consumption and dissipation. Sewage sludge (SS) disposal management is the key stage of...
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Structure and optical parameters of Eu doped tellurium oxide thin films prepared by reactive magnetron sputtering method
PublikacjaIn this work the structural properties and photoluminescence of tellurium dioxide thin films doped by europium were described. Thin films were deposited by magnetron sputtering method and simultaneously heated at 200 °C. Presence of Eu ions and their valence states was confirmed by X-ray photoemission spectroscopy measurements. The structure of the films as well as the influence of europium dopant on crystalline structure of the...
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Exploration of the Solubility Hyperspace of Selected Active Pharmaceutical Ingredients in Choline- and Betaine-Based Deep Eutectic Solvents: Machine Learning Modeling and Experimental Validation
PublikacjaDeep eutectic solvents (DESs) are popular green media used for various industrial, pharmaceutical, and biomedical applications. However, the possible compositions of eutectic systems are so numerous that it is impossible to study all of them experimentally. To remedy this limitation, the solubility landscape of selected active pharmaceutical ingredients (APIs) in choline chloride- and betaine-based deep eutectic solvents was...
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublikacjaDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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New Method of Non-Linear Electrochemical Impedance Spectroscopy with an Amplitude-Modulated Perturbation Signal
PublikacjaThe paper presents a new method of non-linear electrochemical impedance spectroscopy (NLEIS), which allows fast and nondestructive evaluation of the corrosion rate and determination of the Tafel coefficients values for a corrosion system under investigation. This method employs amplitude modulation of the ac perturbation signal. The study demonstrated that it was possible to obtain impedance characteristic as a function of the...
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Didaktische simulationsmodelle fur E-learning in der IK-ausbildung.
PublikacjaPrzedstawiono dydaktyczne modele symulacyjne wykorzystywane w zdalnym kształceniu z zakresu informatyki i technik komunikacyjnych. Pokazano na przykładach zbudowanych symulatorów, w jaki sposób zrealizować lub dostosować modele symulacyjne do zdalnego nauczania. Opisano doświadczenia autorów w wykorzystaniu modeli symulacyjnych w zdalnym nauczaniu.
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Dissolution of Nb-doped hydroxyapatite prepared via low-temperature mechanochemical method: Spectroscopy studies
PublikacjaCalcium phosphate glass ceramics with nominal hydroxyapatite stoichiometry doped with niobium were synthesized using simple as well as low-temperature mechanochemical method and then in the form of compressed pellet were submitted to the static dissolution process in distilled water for one month. The results of structural analysis, performed mainly on the base of spectroscopic methods such as: infrared absorption spectroscopy,...
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Machine learning-based prediction of residual drift and seismic risk assessment of steel moment-resisting frames considering soil-structure interaction
PublikacjaNowadays, due to improvements in seismic codes and computational devices, retrofitting buildings is an important topic, in which, permanent deformation of buildings, known as Residual Interstory Drift Ratio (RIDR), plays a crucial role. To provide an accurate yet reliable prediction model, 32 improved Machine Learning (ML) algorithms were considered using the Python software to investigate the best method for estimating Maximum...
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Szymon Zaporowski mgr inż.
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International Journal of Machine Learning and Cybernetics
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International Journal of Machine Learning and Computing
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The chemistry, properties and performance of flame-retardant rubber composites: Collecting, analyzing, categorizing, machine learning modeling, and visualizing
PublikacjaRubbers combine the flexibility with mechanical strength, supporting myriad applications, but suffer from inherent flammability. Formulation and production of flame-retardant rubber composites (FRRCs) have intensively been practiced over years, but not comprehensively reviewed. This necessity has outlined collecting, analyzing, screening, classifying, and interpreting the literature with the aim of classifying the FRRCs. We quantified...
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A facile method for Tauc exponent and corresponding electronic transitions determination in semiconductors directly from UV–Vis spectroscopy data
PublikacjaIn this work, a facile method allowing for estimation of the exponent in the Tauc equation directly from the UV–vis spectra is presented. It is based on the Taylor expansion of the logarithmic version of the Tauc equation. The Tauc exponent is calculated from the tangent slope of the absorption data. Knowledge of this coefficient provides information about the optical transition types and is used as an input for the calculations...
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Test of the antimicrobial properties against E. coli of the innovative CS-2a preservative.
Dane BadawczeThe dataset contains the results of a single series of determinations of the antimicrobial properties against E. coli of the innovative CS-2 a preservative in the solution of model fluids.During the test, the infected product is inoculated (on chromogenic Coliform Agar) at specified intervals (0 min. [cs2a 0] and after 1 day-24 h of incubation [cs2a...
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Applying of the optical time-of-flight spectroscopy for the paper and pulp characterization
PublikacjaW pracy przedstawiono korzyści wykorzystania optycznej spektroskopii czasu przelotu w badaniach papieru i miazgi drzewnej. Przedmiotem badań były różne gatunki papieru oraz miazgi drzewnej (bez obróbki cieplnej, po obróbce cieplnej lub po obróbce chemicznej). W pomiarach wykorzystano półprzewodnikowe lasery impulsowe oraz w charakterze fotoodbiorników kamerę smugową lub licznik fotonów.