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Wyniki wyszukiwania dla: blended e-learning
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Koncepcja zapewnienia interoperacyjności w rozproszonych systemach uczelnianychW : Perspektywy Rozwoju e-Uczelni w Kontekście Globalnej Informatyzacji; - e-uczelnia, konferencja krajowa; 14-15 maja 2009, Gdańsk. - [skrypt prezentacji]
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UV-Vis-Induced Degradation of Phenol over Magnetic Photocatalysts Modified with Pt, Pd, Cu and Au Nanoparticles
PublikacjaThe combination of TiO2 photocatalyst and magnetic oxide nanoparticles enhances the separation and recoverable properties of nanosized TiO2 photocatalyst. Metal-modified (Me = Pd, Au, Pt, Cu) TiO2/SiO2@Fe3O4 nanocomposites were prepared by an ultrasonic-assisted sol-gel method. All prepared samples were characterized by X-ray powder diffraction (XRD) analysis, Brunauer-Emmett-Teller (BET) method, X-ray photoelectron spectroscopy...
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Copper(I) halide cluster-based coordination polymers modulated by chiral ditopic dithiodianthranilide ligands: synthesis, crystal structure and photoluminescence
PublikacjaReaction of copper(I) halides with chiral dithiodianthranilidesmdtaandbdtaafforded polymeric complexeswhere polynuclear CuX clusters were linked together by ditopic bridging ligands into 1D chains or 2D layerstructures. In the case of racemic ligands double stranded chain polymers were formed where the Cu4X4(X = I or Br) cores are connected by enantiomeric pairs of the ditopic ligands. In contrast, a homochiralmdtaligand created...
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Amygdalin: Toxicity, Anticancer Activity and Analytical Procedures for Its Determination in Plant Seeds
PublikacjaAmygdalin (D-Mandelonitrile 6-O--D-glucosido--D-glucoside) is a natural cyanogenic glycoside occurring in the seeds of some edible plants, such as bitter almonds and peaches. It is a medically interesting but controversial compound as it has anticancer activity on one hand and can be toxic via enzymatic degradation and production of hydrogen cyanide on the other hand. Despite numerous contributions on cancer cell lines, the clinical...
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A palatal prosthesis from archaeological research in the St Francis of Assisi church in Cracow (Poland)
PublikacjaThe hard palate is a septum that not only prevents food from entering between the oral and nasal cavity, but also plays an important role during breathing or speech. The presence of cavities within it negatively affects the comfort of life of people with this type of impairment. Hence, in the literature one can find examples of the use of hard palate prostheses to restore the separation between the nasal and oral cavity. During...
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Low-Cost and Highly-Accurate Behavioral Modeling of Antenna Structures by Means of Knowledge-Based Domain-Constrained Deep Learning Surrogates
PublikacjaThe awareness and practical benefits of behavioral modeling methods have been steadily growing in the antenna engineering community over the last decade or so. Undoubtedly, the most important advantage thereof is a possibility of a dramatic reduction of computational expenses associated with computer-aided design procedures, especially those relying on full-wave electromagnetic (EM) simulations. In particular, the employment of...
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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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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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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublikacjaIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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Machine Learning and data mining tools applied for databases of low number of records
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DALSA: Domain Adaptation for Supervised Learning From Sparsely Annotated MR Images
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Improved estimation of dynamic modulus for hot mix asphalt using deep learning
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Machine learning techniques combined with dose profiles indicate radiation response biomarkers
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Simulation Method for Scheduling Linear Construction Projects Using the Learning– Forgetting Effect
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Learning Feedforward Control Using Multiagent Control Approach for Motion Control Systems
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Learning from Imbalanced Data Streams Based on Over-Sampling and Instance Selection
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Effects of mutual learning in physical education to improve health indicators of Ukrainian students
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Nondestructive Chicken Egg Fertility Detection Using CNN-Transfer Learning Algorithms
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Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
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Development and Optimization of Deep Learning Systems for MRI Analysis in Alzheimer's Disease Monitoring
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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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Influence of Thermal Imagery Resolution on Accuracy of Deep Learning based Face Recognition
PublikacjaHuman-system interactions frequently require a retrieval of the key context information about the user and the environment. Image processing techniques have been widely applied in this area, providing details about recognized objects, people and actions. Considering remote diagnostics solutions, e.g. non-contact vital signs estimation and smart home monitoring systems that utilize person’s identity, security is a very important factor....
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Autonomous Perception and Grasp Generation Based on Multiple 3D Sensors and Deep Learning
PublikacjaGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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Comparison of Deep Neural Network Learning Algorithms for Mars Terrain Image Segmentation
PublikacjaThis paper is dedicated to the topic of terrain recognition on Mars using advanced techniques based on the convolutional neural networks (CNN). The work on the project was conducted based on the set of 18K images collected by the Curiosity, Opportunity and Spirit rovers. The data were later processed by the model operating in a Python environment, utilizing Keras and Tensorflow repositories. The model benefits from the pretrained...
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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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IM - e-test 2018/19
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Szablon e-Kursu dla KIDiT
Kursy OnlineNazwa kursu (2020/2021), kurs przeznaczony dla: Nazwa i kod przedmiotu: Nazwa przedmiotu zgodna z moja PG (np. PG_00044591) Kierunek studiów: Transport Poziom kształcenia: I stopnia - inżynierskie Rok akademicki realizacji przedmiotu: 2020/2021 Forma studiów: stacjonarne Rok studiów: 2 Semestr: 4 (letni)
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Energetyka - e-test 2018/19
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Wychowanie fizyczne II (E:40015C0)
Kursy OnlineKierunek: Automatyka, cybernetyka i robotyka (WETI), I stopnia - inżynierskie, stacjonarne, 2019/2020 - zimowy (obecnie sem. 3)
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Seminarium Dyplomowe [E][2021/2022]
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Energetyka - e-test 2019/20
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Practice e-test 2019/2020
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2023/2024_Digital Business (E:40535W0)
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SEMINARIUM DYPLOMOWE [E][2020/21]
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2024/2025_Digital Business (E:40535W0)
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Logika (E I STAC 2024)
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Czy e-demokracja i rozwiązania znane ze świata biznesu są właściwymi kierunkami zmian politycznych w Polsce?
PublikacjaCEL NAUKOWY: Celem artykułu jest przedstawienie wybranych problemów systemu demokratycznego w Polsce oraz zaproponowanie kierunków rozwoju, poprawiających jego działanie. PROBLEM i METODY BADAWCZE: Problem badawczy dotyczył sprawdzenia czy wdrożenie założeń nowoczesnych koncepcji organizacyjnych i rozwiązań teleinformatycznych może przyczynić się do sprawniejszego sprawowania demokratycznej władzy, a także podwyższenia...
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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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Małgorzata Gawrycka dr hab.
OsobyMałgorzata Gawrycka, absolwentka Wydziału Zarządzania Uniwersytetu Gdańskiego, doktor habilitowana nauk ekonomicznych. W latach 2012-2020 prodziekan ds. dydaktyki Wydziału Zarządzania i Ekonomii Politechniki Gdańskiej. Obecnie dziekan Wydziału. Zainteresowania naukowe koncentrują się na zagadnieniach związanych z polityka makroekonomiczną państwa. W szczególności problematyka sytuacji na runku pracy, zmian demograficznych, kwalifikacji...
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Sub-national structures matter when evaluating physical activity promotion: Lessons from Germany
PublikacjaBackground Public policies are increasingly acknowledged as important part of promoting physical activity (PA). However, especially in states with sub-national administrative structures such as Germany, national and sub-national approaches differ considerably. In Germany, sport for all (SfA) promotion is mostly organized at sub-national level, which is usually not covered in national evaluations. Knowledge of these structures helps...
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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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The effect of nitrogen on the structure and thermal properties of beryllium-containing Na-(Li)-Si-O-N glasses
PublikacjaTwo oxynitride glass series with the composition of 35Na2O-5BeO-(60-x)SiO2-xSi3N4 and 9Li2O- 27Na2O-5BeO-(59-x)SiO2-xSi3N4, were prepared. The glasses' topography and structure were studied by Scanning Electron Microscopy and Raman spectroscopy. The composition was analyzed by Inductively Coupled Plasma Optical Emission Spectrometer, SEM-EDS and nitrogen and oxygen elemental analyzer. Na-(Li)-Be-silicate glasses were found to contain...
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Potential Skyrmion Host Fe(IO3)3: Connecting Stereoactive Lone-Pair Electron Effects to the Dzyaloshinskii-Moriya Interaction
PublikacjaMagnetic skyrmions, which are topologically distinct magnetic spin textures, are gaining increased attention for their unique physical properties and potential applications in spintronic devices. Here we present a design strategy for skyrmion host candidates based on combinations of magnetic spin, asymmetric building units having stereoactive lone-pair electrons, and polar lattice symmetry. To demonstrate the viability of the proposed...
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“Piglia il bastone e battila molto bene… allora battila, non con animo irato, ma per zelo e carità dell’anima sua.” La violenza domestica secondo alcune testimonianze medievali
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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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Mehmet E. Uz PhD.
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Rozpoznanie ról użytkowników usługi e-mail z wykorzystaniem metody opartej na ontologii
PublikacjaSieci społeczne jako struktury ukazujące społeczne powiązania pomiędzy osobami lub całymi organizacjami poddawane są często analizie w celu rozpoznania ról, jakie pełnią poszczególni aktorzy w danej sieci. Taka klasyfikacja ról odgrywanych przez aktorów może dostarczać wielu cennych informacji o danej sieci, gdyż daje nam całościowy obraz danej sieci pozwalając na zrozumienie, w jaki sposób sieć jest zorganizowana, i w jaki sposób...
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Apolipoprotein E ( ApoE ) polymorphism is related to differences in potential fertility in women: a case of antagonistic pleiotropy?
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