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Wyniki wyszukiwania dla: BLENDED E-LEARNING
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New Directions for Teaching and Learning
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Journal of College Reading and Learning
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International Journal of Learning and Change
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Second Language Learning and Teaching
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Advances in Learning and Behavioral Disabilities
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Malaysian Journal of Learning & Instruction
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International Journal of Technologies in Learning
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Journal of Motor Learning and Development
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CONTINUUM Lifelong Learning in Neurology
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Journal of Formative Design in Learning
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Scholarship of Teaching and Learning in Psychology
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JOURNAL OF MACHINE LEARNING RESEARCH
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Journal of Applied Learning and Teaching
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Critical Studies in Teaching and Learning
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Higher Learning Research Communications
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Canadian Journal of Learning and Technology
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Machine Learning and Knowledge Extraction
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Machine Learning-Science and Technology
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JOURNAL OF COMPUTER ASSISTED 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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Investigating the disease- modifying properties of sclerotiorin in Alzheimer's therapy using acetylcholinesterase inhibition
PublikacjaAlzheimer's disease (AD) is a progressive neurodegenerative disorder caused due to the damage and loss of neurons in specific brain regions. It is the most common form of dementia observed in older people. The symptoms start with memory loss and gradually cause the inability to speak and do day-to-day activities. The cost of caring for those affected individuals is huge and is probably beyond most developing countries capability....
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Computational analysis of an infinite magneto-thermoelastic solid periodically dispersed with varying heat flow based on non-local Moore–Gibson–Thompson approach
PublikacjaIn this investigation, a computational analysis is conducted to study a magneto-thermoelastic problem for an isotropic perfectly conducting half-space medium. The medium is subjected to a periodic heat flow in the presence of a continuous longitude magnetic field. Based on Moore–Gibson–Thompson equation, a new generalized model has been investigated to address the considered problem. The introduced model can be formulated by combining...
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Robust-adaptive dynamic programming-based time-delay control of autonomous ships under stochastic disturbances using an actor-critic learning algorithm
PublikacjaThis paper proposes a hybrid robust-adaptive learning-based control scheme based on Approximate Dynamic Programming (ADP) for the tracking control of autonomous ship maneuvering. We adopt a Time-Delay Control (TDC) approach, which is known as a simple, practical, model free and roughly robust strategy, combined with an Actor-Critic Approximate Dynamic Programming (ACADP) algorithm as an adaptive part in the proposed hybrid control...
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Structural Factors Affecting Cytotoxic Activity of (E)-1-(Benzo[d ][1,3]oxathiol-6-yl)-3-phenylprop-2-en-1-one Derivatives
PublikacjaDerivatives of (E)-1-(5-alkoxybenzo[d][1,3]oxathiol-6-yl)-3-phenylprop-2-en-1-one (1) demonstrated exceptionally high in vitro cytotoxic activity, with IC50 values of the most active derivatives in the nanomolar range. To identify structural fragments necessary for the activity, several analogs deprived of selected fragments were prepared, and their cytotoxic activity was tested. It was found that the activity depends on combined effects...
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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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Emilia Miszewska dr inż.
OsobyEmilia Miszewska urodziła się w 1986 roku w Gdańsku. Ukończyła Szkołę Podstawową nr 17 w Gdańsku z klasami sportowymi o profilu pływanie oraz Liceum Sportowe nr 11 im. Janusza Kusocińskiego w Gdańsku. W 2005 roku rozpoczęła jednolite studia magisterskie na Wydziale Inżynierii Lądowej i Środowiska, które ukończyła w roku 2011, broniąc pracę dyplomową pt. „Analiza i opracowanie wytycznych zabezpieczenia pożarowego oraz planu...
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Avaliação das propriedades de impulso e freqüência em sistemas de aterramento
PublikacjaBezpieczne uziemienia projektowane dla celów ochrony odgromowej powinny odprowadzać prądy wyładowań atmosferycznych przy możliwie niewielkim spadku napięcia. Dla oceny ich skuteczności należy brać pod uwagę nie tylko ich rezystancję, lecz przede wszystkim impedancję. W pracy porównano wyniki symulacji komputerowych i pomiarów na obiektach rzeczywistych impedancji uziemień mierzonych przy wymuszeniach udarowych oraz wysokoczęstotliwościowych.
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Mesh-based internet on the Baltic sea for improving e-navigation services. A case study
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Gdansk 2020, Grunwaldzka (E) street - video data - pedestrian, bicycles, vehicles
Dane BadawczeGdansk 2020, Grunwaldzka (E) street - video data - pedestrian, bicycles, vehicles
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Szymon Zaporowski mgr inż.
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Simulation Method for Scheduling Linear Construction Projects Using the Learning– Forgetting Effect
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
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Machine learning techniques combined with dose profiles indicate radiation response biomarkers
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Multivariate Features Extraction and Effective Decision Making Using Machine Learning Approaches
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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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Effects of mutual learning in physical education to improve health indicators of Ukrainian students
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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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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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Machine Learning and data mining tools applied for databases of low number of records
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Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
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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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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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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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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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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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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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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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