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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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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.
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Optical time of flight spectroscopy for highly scattering materials measurements.
PublikacjaW artykule omówiono możliwości wykorzystania optycznej spektroskopii czasu przelotu w wyznaczaniu podstawowych parametrów optycznych materiałów silnie rozpraszających światło. Wykorzystano tu metodę Monte Carlo i metodę dyfuzji.
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Test of the antimicrobial properties against E. coli of the innovative CS-2b 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 b preservative in the solution of model fluids.During the test, the infected product is inoculated (on chromogenic Coliform Agar) at specified intervals (0 min. [cs2b 0] and after 1 day-24 h of incubation [cs2b...
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Optical-Spectrometry-Based Method for Immunosuppressant Medicine Level Detection in Aqueous Solutions
PublikacjaIn this paper, an investigation into detecting immunosuppressive medicine in aqueous solutions using a spectrometry-based technique is described. Using optical transmissive spectrometry, absorbance measurements in the spectra range from 250 nm to 1000 nm were carried out for different cyclosporine A (CsA) concentrations in aqueous solutions. The experiment was conducted for samples both with and without interferent substances—glucose...
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Stacking and rotation-based technique for machine learning classification with data reduction
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POPULATION-BASED MULTI-AGENT APPROACH TO SOLVING MACHINE LEARNING PROBLEMS
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Efficient sampling of high-energy states by machine learning force fields
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Modular machine learning system for training object detection algorithms on a supercomputer
PublikacjaW pracy zaprezentowano architekturę systemu służącego do tworzenia algorytmów wykorzystujących metodę AdaBoost i służących do wykrywania obiektów (np. twarzy) na obrazach. System został podzielony na wyspecjalizowane moduły w celu umożliwienia łatwej rozbudowy i efektywnego zrównoleglenia implementacji przeznaczonej dla superkomputera. Na przykład, system może być rozszerzony o nowe cechy i algorytmy ich ekstrakcji bez konieczności...
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Evaluation of aspiration problems in L2 English pronunciation employing machine learning
PublikacjaThe approach proposed in this study includes methods specifically dedicated to the detection of allophonic variation in English. This study aims to find an efficient method for automatic evaluation of aspiration in the case of Polish second-language (L2) English speakers’ pronunciation when whole words are analyzed instead of particular allophones extracted from words. Sample words including aspirated and unaspirated allophones...
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E-learning - prawdziwa czy fikcyjna koncepcja edukacyjnego rozwoju uczelni
PublikacjaNie można zaprzeczyć, że wykorzystanie narzędzi multimedialnych oraz Internetu pozwala na dodanie istotnych, z punku widzenia dydaktyki, komponentów edukacyjnych tworzących kompetencje i umiejętności zawodowe, a także te czysto akademickie. Trzeba rozważyć, czy wszystkie strony procesu dydaktycznego na uczelni są przygotowane do e−learningu. Oczywistym wymogiem jest posiadanie odpowiedniej bazy sprzętowej i przygotowanej kadry...
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Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning
PublikacjaTheophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally...
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Distribution of relaxation times as a method of separation and identification of complex processes measured by impedance spectroscopy
PublikacjaImpedance spectroscopy is one of the most commonly performed measurements to characterize electronic and electrochemical systems. Impedance spectra have limited resolution and many different processes may overlap what could be the reason of obstructions in its proper later analysis. Up to date, there are three approaches to solve this problem: examining impedance spectra itself, fitting spectra with equivalent circuits, and calculating...
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Tuning Ferulic Acid Solubility in Choline-Chloride- and Betaine-Based Deep Eutectic Solvents: Experimental Determination and Machine Learning Modeling
PublikacjaDeep eutectic solvents (DES) represent a promising class of green solvents, offering particular utility in the extraction and development of new formulations of natural compounds such as ferulic acid (FA). The experimental phase of the study undertook a systematic investigation of the solubility of FA in DES, comprising choline chloride or betaine as hydrogen bond acceptors and six different polyols as hydrogen bond donors....
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Projektowanie zajęć prowadzonych na odległość (10h e-learning)
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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublikacjaThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...
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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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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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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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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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Precise Identification of Different Cervical Intraepithelial Neoplasia (CIN) Stages, Using Biomedical Engineering Combined with Data Mining and Machine Learning
PublikacjaCervical cancer (CC) is one of the most common female cancers worldwide. It remains a significant global health challenge, particularly affecting women in diverse regions. The pivotal role of human papillomavirus (HPV) infection in cervical carcinogenesis underscores the critical importance of diagnostic strategies targeting both HPV infection and cervical...
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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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Multivariate Features Extraction and Effective Decision Making Using Machine Learning Approaches
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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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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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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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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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Data-driven Models for Predicting Compressive Strength of 3D-printed Fiber-Reinforced Concrete using Interpretable Machine Learning Algorithms
Publikacja3D printing technology is growing swiftly in the construction sector due to its numerous benefits, such as intricate designs, quicker construction, waste reduction, environmental friendliness, cost savings, and enhanced safety. Nevertheless, optimizing the concrete mix for 3D printing is a challenging task due to the numerous factors involved, requiring extensive experimentation. Therefore, this study used three machine learning...
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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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High-Performance Machine-Learning-Based Calibration of Low-Cost Nitrogen Dioxide Sensor Using Environmental Parameter Differentials and Global Data Scaling
PublikacjaAccurate tracking of harmful gas concentrations is essential to swiftly and effectively execute measures that mitigate the risks linked to air pollution, specifically in reducing its impact on living conditions, the environment, and the economy. One such prevalent pollutant in urban settings is nitrogen dioxide (NO2), generated from the combustion of fossil fuels in car engines, commercial manufacturing, and food processing. Its...
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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 goes global: Cross-sectional return predictability in international stock markets
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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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Edyta Gołąb-Andrzejak dr hab.
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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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New Manufacturing Method Of Sensor Oriented Optical Fibers
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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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Photoacoustic and optical absorption spectroscopy studies of luminescentCr3+andCr4+centers in yttrium aluminum garnet
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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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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...