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- Publikacje 1435 wyników po odfiltrowaniu
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Wyniki wyszukiwania dla: E. COLI, MACHINE LEARNING, OPTICAL METHOD, SPECTROSCOPY, URINE, UROSPESIS
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Estimation of optical parameters of highly scattering materials by time-of-flight spectroscopy.
PublikacjaPrzedstawiono metody wyznaczania podstawowych parametrów materiałów silnie rozpraszających światło na podstawie pomierzonego rozkładu czasu przelotu krótkich impulsów laserowych. W algorytmie wykorzystano metodę Monte Carlo i metodę dyfuzji do opisu propagacji światła. Oszacowano dokładność oszacowywania tych parametrów.
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Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublikacjaPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...
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Rediscovering Automatic Detection of Stuttering and Its Subclasses through Machine Learning—The Impact of Changing Deep Model Architecture and Amount of Data in the Training Set
PublikacjaThis work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary patient diagnosis, and enabling communication with the previously mentioned voice assistants. The first part of this work provides an overview of examples of classical and deep learning...
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Machine learning-based prediction of seismic limit-state capacity of steel moment-resisting frames considering soil-structure interaction
PublikacjaRegarding the unpredictable and complex nature of seismic excitations, there is a need for vulnerability assessment of newly constructed or existing structures. Predicting the seismic limit-state capacity of steel Moment-Resisting Frames (MRFs) can help designers to have a preliminary estimation and improve their views about the seismic performance of the designed structure. This study improved data-driven decision techniques in...
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Projektowanie zajęć prowadzonych na odległość (10h e-learning)
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THE EFFECT OF WOOD DRYING METHOD ON THE GRANULARITY OF SAWDUST OBTAINED DURING THE SAWING PROCESS USING THE FRAME SAWING MACHINE
PublikacjaThe experimental results of the study focused on the effect of drying processes of warm air drying at the temperature of 6580°C and warm air-steam mixture drying at the temperature of 105°C of pine and beech wood to the size of sawdust grains created by cutting using RPW 15M frame saw is presented in the paper. Particle size analysis of dry sawdust was performed using two methods - screening method and optical method based on...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublikacjaWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
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Machine learning techniques combined with dose profiles indicate radiation response biomarkers
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Machine Learning and data mining tools applied for databases of low number of records
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Multivariate Features Extraction and Effective Decision Making Using Machine Learning Approaches
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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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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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Solubility Characteristics of Acetaminophen and Phenacetin in Binary Mixtures of Aqueous Organic Solvents: Experimental and Deep Machine Learning Screening of Green Dissolution Media
PublikacjaThe solubility of active pharmaceutical ingredients is a mandatory physicochemical characteristic in pharmaceutical practice. However, the number of potential solvents and their mixtures prevents direct measurements of all possible combinations for finding environmentally friendly, operational and cost-effective solubilizers. That is why support from theoretical screening seems to be valuable. Here, a collection of acetaminophen...
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Integrating Statistical and Machine‐Learning Approach for Meta‐Analysis of Bisphenol A‐Exposure Datasets Reveals Effects on Mouse Gene Expression within Pathways of Apoptosis and Cell Survival
PublikacjaBisphenols are important environmental pollutants that are extensively studied due to different detrimental effects, while the molecular mechanisms behind these effects are less well understood. Like other environmental pollutants, bisphenols are being tested in various experimental models, creating large expression datasets found in open access storage. The meta‐analysis of such datasets is, however, very complicated for various...
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Expedited Machine-Learning-Based Global Design Optimization of Antenna Systems Using Response Features and Multi-Fidelity EM Analysis
PublikacjaThe design of antenna systems poses a significant challenge due to stringent per-formance requirements dictated by contemporary applications and the high com-putational costs associated with models, particularly full-wave electromagnetic (EM) analysis. Presently, EM simulation plays a crucial role in all design phases, encompassing topology development, parametric studies, and the final adjustment of antenna dimensions. The latter...
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Determination of API content in a pilot-scale blending by near-infrared spectroscopy as a first step method to process line implementation
PublikacjaNear infrared (NIR) spectroscopy was used for estimation of powder blend homogeneity and manufacturing control of a medicinal product powder mixture containing active pharmaceutical ingredient (API). Aiming at initiating a Process Analytical Technology (PAT) activity, the first step was a stationary mode atline evaluation. In this, the content of pharmaceutical active compound in the powder mixtures intended to the direct tabletting...
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A high-accuracy method of computation of x-ray waves propagation through an optical system consisting of many lenses
PublikacjaThe propagation of X-ray waves through an optical system consisting of many X-ray refractive lenses is considered. Two differential equations are contemplated for solving the problem for electromagnetic wave propagation: first – an equation for the electric field, second – an equation derived for a complex phase of an electric field. Both equations are solved by the use of a finite-difference method. The simulation error is estimated...
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Project-Based Learning as a Method for Interdisciplinary Adaptation to Climate Change—Reda Valley Case Study
PublikacjaThe challenges of the global labour market require university authorities to extend traditional forms of education into more innovative and effective solutions. Project-based learning (PjBL) is one of highly effective methods for acquiring knowledge and teaching “soft” skills to future employees. This article describes an experimental use of PjBL at a university with a long history of teaching based on traditional methods—the Gdansk...
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
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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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Advances in Architectures, Big Data, and Machine Learning Techniques for Complex Internet of Things Systems
PublikacjaTe 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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Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publikacja(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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E-LEARNING NA POLITECHNICE GDAŃSKIEJ - HISTORIA ROZWOJU W LATACH 1995-2020
PublikacjaInternet oraz kształcenie oparte na wykorzystaniu e-technologii stały się nieodłącznym elementem edukacji. Artykuł przedstawia zarys historii rozwoju e-learningu na Politechnice Gdańskiej, przykładowe rozwiązania technologiczne, elementy tworzenia struktur organizacyjnych oraz związanych z legislacją, a także wybrane projekty wykorzystujące szeroko pojęte e-technologie w edukacji akademickiej realizowanej na Uczelni
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Edyta Gołąb-Andrzejak dr hab.
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Thickness monitoring of thin lamellae by optical measurement method
PublikacjaDo dnia dziesiejszego do pomiaru grubosci tarcicy używa się głównie suwmiarek. Celem projektu było opracowanie skanera, nie wymagajacego wysokich nakładów finansowych, do pomiarów grubości lameli po operacji rozpiłowywania drewna. Opracowany system jest zdolny do wykrywania elementów odbiegajacych od okreslonych tolerancji wymiarowych. zastosowano metodę pomiaru typu sandwich wykorzystująca 4 głowice laserowe. Wyazano, że przy...
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New Manufacturing Method Of Sensor Oriented Optical Fibers
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Photoacoustic and optical absorption spectroscopy studies of luminescentCr3+andCr4+centers in yttrium aluminum garnet
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Employing a biofeedback method based on hemispheric synchronization in effective learning
PublikacjaIn this paper an approach to build a brain computer-based hemispheric synchronization system is presented. The concept utilizes the wireless EEG signal registration and acquisition as well as advanced pre-processing methods. The influence of various filtration techniques of EOG artifacts on brain state recognition is examined. The emphasis is put on brain state recognition using band pass filtration for separation of individual...
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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublikacjaThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
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Perception of Pathologists in Poland of Artificial Intelligence and Machine Learning in Medical Diagnosis—A Cross-Sectional Study
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Letter to the Editor: Complete resonance assignments of the 'donor-strand' AfaD: The afimbrial invasin from Diffusely Adherent E. coli.
PublikacjaUstalono strukturę NMR rekombiantowego białka AfaD-dsc. Uzyskane wyniki są podstawą do badań rentgenograficznych struktury białek AfaD/DraD.
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E-Beam Irradiation and Ozonation as an Alternative to the Sulphuric Method of Wine Preservation
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Electronic Journal of e-Learning
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E-Learning and Digital Media
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Optical method for verification of homogeneity of phantoms for calibration of magnetic resonance
PublikacjaThe primary purpose of this study was to develop a laboratory photonic set-up for characterisation of homogeneity of gel phantoms for calibration of magnetic resonance. In this system, optical coherence tomography allows the detection of micro- and macroscopic heterogeneities of a structure. The set-up was used to perform measurements of agar and agar-carrageenan gels, which are the basis for more complex phantoms for magnetic...
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Optical emission spectroscopy of plasma generated by a waveguide-supplied microwave plasma source operated at 915MHz
PublikacjaIn this paper we present the results of an optical emission spectroscopic study of an atmospheric pressure microwave (915 MHz) nitrogen and nitrogen with carbon dioxide (1%) plasma at high working gas flow rate. This study was aimed at determining rotational Trot and vibrational Tvib temperatures of N+2 ions and N2, CN molecules. The plasma was generated in a waveguide-supplied cavity-resonant type microwave plasma source. All...
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An Analysis of Low Frequency Discharge in a CH3SiCl3-Ar-H2 Mixture by Optical Emission Spectroscopy and Actinometry
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Orientational Order and Dynamics of Nematic Multipodes Based on Carbosilazane Cores Using Optical and Dielectric Spectroscopy
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Quantitative Soil Characterization for Biochar–Cd Adsorption: Machine Learning Prediction Models for Cd Transformation and Immobilization
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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublikacjaAtmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...
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Detection of Cystic Fibrosis Symptoms Based on X-Ray Images Using Machine Learning- Pilot Study
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Universal Predictors of Dental Students’ Attitudes towards COVID-19 Vaccination: Machine Learning-Based Approach
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Prediction of Wastewater Quality at a Wastewater Treatment Plant Inlet Using a System Based on Machine Learning Methods
PublikacjaOne of the important factors determining the biochemical processes in bioreactors is the quality of the wastewater inflow to the wastewater treatment plant (WWTP). Information on the quality of wastewater, sufficiently in advance, makes it possible to properly select bioreactor settings to obtain optimal process conditions. This paper presents the use of classification models to predict the variability of wastewater quality at...
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Beata Krawczyk dr hab.
Osobydr hab. Beata Krawczyk, prof. uczelni Stopnie naukowe, wykształcenie, kwalifikacje Beata Krawczyk uzyskała tytuł magistra biologii na Wydziale Biologii (wówczas: Wydział Biologii i Nauk o Ziemi), Uniwersytetu Gdańskiego w 1986 roku, a doktorat z biologii molekularnej na Wydziale Biologii (wówczas: Wydział Biologii, Geografii i Oceanologii) Uniwersytetu Gdańskiego w 1996 roku. Stopień doktora habilitowanego w zakresie nauk biologicznych...
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NLITED - New Level of Integrated Techniques for Daylighting Education: Preliminary Data on the Use of an E-learning Platform
PublikacjaProject NLITED – New Level of Integrated Techniques for Daylighting Education - is an educational project for students and professionals. The project's objective is to create and develop an online eLearning platform with 32 eModules dedicated to daylight knowledge. The project also offers e-learners two summer school training where the theory is put into practice. The platform was launched on January 31, 2022. The paper...
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Method using square-pulse excitation for high-impedance spectroscopy of anticorrosion coatings
PublikacjaArtykuł prezentuje metodę spektroskopii impedancyjnej przeznaczonej do diagnostyki powłok antykorozyjnych na obiektach bezpośrednio w terenie. Aby skrócić czas uzyskania widma impedancji (w zakresie od 1 mHz do 1 MHz) do kilku minut, wykorzystano sygnały harmoniczne do pomiaru widma powyżej 10 Hz a impuls prostokątny w dolnym zakresie częstotliwości. Do wyznaczania widma użyto algorytmów DSP odpowiednich do sygnału pobudzenia....
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Cleaner energy for sustainable future using hybrid photovoltaics-thermoelectric generators system under non-static conditions using machine learning based control technique
PublikacjaIn addition to the load demand, the temperature difference between the hot and cold sides of the thermoelectric generator (TEG) module determines the output power for thermoelectric generator systems. Maximum power point tracking (MPPT) control is needed to track the optimal global power point as operating conditions change. The growing use of electricity and the decline in the use of fossil fuels have sparked interest in photovoltaic-TEG...