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Search results for: SELF-SUPERVISED LEARNING
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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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E-Learning and Digital Media
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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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Galvanostatic cycling with potential limitation (GCPL) of WS2/userGOx (composites of tungsten disulfide and ultrafast self-expanded and reduced graphene oxide) and ex-WS2 (exfoliated tungsten disulfide)
Open Research DataThese data contain results of galvanostatic cycling with potential limitation (GCPL) of WS2/userGOx (composites of tungsten disulfide and ultrafast self-expanded and reduced graphene oxide) and ex-WS2 (exfoliated tungsten disulfide). The data were collected for samples obtained from three ex-WS2:GO dispersions - with 1:1, 1:2, and 2:1 weight ratios.
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Robust-adaptive dynamic programming-based time-delay control of autonomous ships under stochastic disturbances using an actor-critic learning algorithm
PublicationThis 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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Low-Cost and Highly-Accurate Behavioral Modeling of Antenna Structures by Means of Knowledge-Based Domain-Constrained Deep Learning Surrogates
PublicationThe 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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Autonomous Perception and Grasp Generation Based on Multiple 3D Sensors and Deep Learning
PublicationGrasping 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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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublicationThe 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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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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Machine Learning and data mining tools applied for databases of low number of records
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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
PublicationTo 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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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
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Multivariate Features Extraction and Effective Decision Making Using Machine Learning Approaches
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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
PublicationIn 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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Influence of Thermal Imagery Resolution on Accuracy of Deep Learning based Face Recognition
PublicationHuman-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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Solubility Characteristics of Acetaminophen and Phenacetin in Binary Mixtures of Aqueous Organic Solvents: Experimental and Deep Machine Learning Screening of Green Dissolution Media
PublicationThe 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
PublicationNowadays, 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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Sense of Purpose in Life and Escape from Self as the Predictors of Quality of Life in Clinical Samples
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When Membership Gives Strength to Act: Inclusion of the Group Into the Self and Feeling of Personal Agency
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Self-assembled epitaxial BiFeO3 nanostructures as a tailored platform for vertically aligned nanocomposites development
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Conformation Properties, Chiroptical Spectra, and Molecular Self-Assembly of 2,3-Piperazinodiones and Their Dithiono Analogues
PublicationRodzina chiralnych cyklicznych oksamidów została otrzymana przez kondensację optycznie czynnych 1,2-diamin ze szczawianem dietylu. Tionowanie produktów odczynnikiem Lawessona doprowadziło do chiralnych 2,3-dipiperazynodionów. Geometrie cząsteczkowe badano z użyciem obliczeń kwantowo-mechanicznych DFT i porównano z wynikami analizy krystalograficznej. Sześcioczłonowy pierścień heterocykliczny przyjmuje konformację półkrzesłową,...
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SONIC - Self-optimizing narrowband interference canceler: comparison of two frequency tracking strategies
PublicationThis paper presents a new approach to rejection of complex-valued sinusoidal disturbances acting at the output of a discrete-time linear stable plant with unknown and possibly time-varying dynamics. It is assumed that both the instantaneous frequency of the sinusoidal disturbance and its amplitude may be slowly varying with time and that the output signal is contaminated with wideband measurement noise. The proposed disturbance...
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Capacity efficient shared protection and fast restoration scheme in self-configured optical networks
PublicationW artykule zaproponowano nową koncepcję optymalizacji rozdziału zasobów dla przeżywalnych sieci rozległych, która gwarantuje szybkie odtwarzanie usług po wystąpieniu awarii. Wykazano, iż proponowany algorytm, wykorzystujący ideę wierzchołkowego kolorowania grafów, nie powoduje wydłużania ścieżek zabezpieczających - zjawiska charakterystycznego dla powszechnie stosowanych algorytmów optymalizacji. Udowodniono, iż powyższa cecha...
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Perception of Self-Efficacy and Health-Related Behavior in Context of Taekwon-Do Sport Camps
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Subjective Preferences Towards Various Conditions of Self-Administered Questionnaires: AHP and Conjoint Analyses
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Stress and self-image in multiple sclerosis patients and selected positive aspects of struggling with the disease
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Influence of Acid-Modified Clinoptilolite on the Self-Adhesive Properties of Silicone Pressure-Sensitive Adhesives
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The Effect of Pt-type Catalysts on Self-adhesive Properties of Silicone Pressure-sensitive Adhesives
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Multi-agent systems registration and maintenance of address mapping without agent self-registation
PublicationMonitoring of dynamic multi-agent systems, here agents are allowed to appear and disappear, and can migrate between network nodes is a complex tasks. Applying the traditional monitoring methods is not effective, as little can be assumed in advance about such environments. It is necessary to track changes in addressing and availability of agents to create and maintain mapping between agents and their network addresses. The...
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Scalable Maintenance of Address Mapping and Autodetecion in Environments Where Agents are Uncapable of Self-Registration
PublicationWhen working with multi-agent systems it is often desirable to manage the agent set. The existing methods of central monitoring stems from two different fields of application. The first has its roots in in computer network monitoring, the other in mutli-agent simulation environments. Both approaches are not general enough to cater for loosely controlled environments, where the total agent population is not known and often fluctuating,...
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Some problems of self-excited vibrations of turbine rotors. Part I: The theoretical method
PublicationPrzedstawiono teoretyczną metodę określania uszczelnienia nadbandażowego lub dławicy zupełnej, które odgrywa największą rolę w generowaniu samowzbudnych drgań typu aerodynamicznego wirników turbinowych. Drgania harmoniczne układu wirnika turbiny opisane są macierzowym równaniem, a wymuszenia aerodynamiczne określane metodą współczynników wpływu.
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Design and experimental evaluation of pod propulsor models for a large self-propelled ship model.
PublicationArtykuł przedstawia serię hydrodynamicznych badań swobodnych dwóch modeli pędnika podowego. Pędniki zostały zaprojektowane i zbudowane specjalnie dla dwóch wersji dużego modelu okrętu z własnym napędem, przeznaczonego do eksperymentów manewrowych. Jedna wersja jest napędzana pojedyńczym pędnikiem, druga jest wyposażona w dwa pędniki. Oba modele podów były badane w kanale obiegowym. Celem eksperymentu były pomiary sześciu składowych...
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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
PublicationBisphenols 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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Lead-free bismuth-based perovskites coupled with g–C3N4: A machine learning based novel approach for visible light induced degradation of pollutants
PublicationThe 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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Edyta Gołąb-Andrzejak dr hab.
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The database of odd algebraic periods for quasi-unipotent self-maps of a space having the same homology group as the connected sum of g tori
Open Research DataThe dataset consists of 20 files indexed by numbers g=1,...,20. Each file provides sets of odd algebraic periods for all quasi-unipotent self-maps of a space having the same homology groups as the connected sum of g tori. Let us remark that each data set covers all algebraical restrictions that come from zeta functions for the sets of minimal Lefschetz...
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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
PublicationPlain 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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XRD (X-ray diffraction) patterns of WS2/userGOx (composites of tungsten disulfide and ultrafast self-expanded and reduced graphene oxide), ex-WS2 (exfoliated tungsten disulfide) and GO (graphene oxide)
Open Research DataThese data contain XRD (X-ray diffraction) patterns of WS2/userGOx (composites of tungsten disulfide and ultrafast self-expanded and reduced graphene oxide), ex-WS2 (exfoliated tungsten disulfide) and GO (graphene oxide). The data were collected for samples obtained from three ex-WS2:GO dispersions - with 1:1, 1:2, and 2:1 weight ratios.