Filters
total: 4842
filtered: 3509
-
Catalog
- Publications 3509 available results
- Journals 220 available results
- Conferences 29 available results
- People 118 available results
- Projects 12 available results
- Research Equipment 1 available results
- e-Learning Courses 93 available results
- Events 12 available results
- Open Research Data 848 available results
Chosen catalog filters
displaying 1000 best results Help
Search results for: ACTIVE%20LEARNING
-
TensorHive: Management of Exclusive GPU Access for Distributed Machine Learning Workloads
PublicationTensorHive is a tool for organizing work of research and engineering teams that use servers with GPUs for machine learning workloads. In a comprehensive web interface, it supports reservation of GPUs for exclusive usage, hardware monitoring, as well as configuring, executing and queuing distributed computational jobs. Focusing on easy installation and simple configuration, the tool automatically detects the available computing...
-
Distance learning trends: introducing new solutions to data analysis courses
PublicationNowadays data analysis of any kind becomes a piece of art. The same happens with the teaching processes of statistics, econometrics and other related courses. This is not only because we are facing (and are forced to) teach online or in a hybrid mode. Students expect to see not only the theoretical part of the study and solve some practical examples together with the instructor. They are waiting to see a variety of tools, tutorials,...
-
Predictions of cervical cancer identification by photonic method combined with machine learning
PublicationCervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors...
-
Deep learning approach on surface EEG based Brain Computer Interface
PublicationIn this work we analysed the application of con-volutional neural networks in motor imagery classification for the Brain Computer Interface (BCI) purposes. To increase the accuracy of classification we proposed the solution that combines the Common Spatial Pattern (CSP) with convolutional network (ConvNet). The electroencephalography (EEG) is one of the modalities we try to use for controlling the prosthetic arm. Therefor in this...
-
Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublicationThis paper focuses on convolution neural network quantization problem. The quantization has a distinct stage of data conversion from floating-point into integer-point numbers. In general, the process of quantization is associated with the reduction of the matrix dimension via limited precision of the numbers. However, the training and inference stages of deep learning neural network are limited by the space of the memory and a...
-
UK travel agents’ evaluation of eLearning courses offered by destinations: an exploratory study.
PublicationThis study aims to develop an understanding of the use of e-learning courses created for travel agents by Destination Management Organizations (DMOs). It explores agents’ perceptions of such courses. The research examines the views of 304 UK-based travel agents using online survey and investigates whether age, sex, type of agency, work experience, and educational level have influence on e-learning uptake. The satisfaction of travel...
-
Symulacja pracy przesuwnika fazowego w sieci elektroenergetycznej przy połączeniu transformatora szeregowego w gwiazdę
PublicationPoniższy artykuł prezentuje sposób regulacji mocy czynnej i biernej za pomocą przesuwnika fazowego, którego uzwojenie transformatora dodawczego (szeregowego) jest połączone w gwiazdę. W artykule pokazano regulację mocy czynnej i biernej na przykładzie wybranego systemu elektroenergetycznego. Omawiany przesuwnik fazowy reguluje jednocześnie przepływem mocy czynnej i biernej w danym systemie elektroenergetycznym.
-
Immediate and late benefits of treating very elderly people with hypertension: results from active treatment extension to Hypertension in the Very Elderly randomised controlled trial
Publication -
Extracellular matrix metalloproteinase inducer (EMMPRIN) expression correlates positively with active angiogenesis and negatively with basic fibroblast growth factor expression in epithelial ovarian cancer
Publication -
N,N’-Bis(salicylidene)ethylenediamine (Salen) as an Active Compound for the Recovery of Ni(II), Cu(II), and Zn(II) Ions from Aqueous Solutions
Publication -
Porous carbon derived from rice husks as sustainable bioresources: insights into the role of micro-/mesoporous hierarchy in hosting active species for lithium–sulphur batteries
PublicationThe exploration of natural resources as sustainable precursors affords a family of green materials. Exploring highly abundant and available biowaste precursors remaining from food processing throughout a scalable and cost-effective material synthesis path is highly important especially for new materials discovery in emerging energy storage technologies such as lithium–sulphur (Li–S) batteries. Herein, we have produced a series...
-
Aspects of Tests and Assessment of Filtering Materials Used for Respiratory Protection Against Bioaerosols. Part I: Type of Active Substance, Contact Time, Microorganism Species
Publication -
C-reactive Protein as a Diagnostic and Prognostic Factor of Endometrial Cancer
Publication -
C-reactive protein as a diagnostic and prognostic factor of endometrial cancer
Publication -
Induction of the Stringent Response Underlies the Antimicrobial Action of Aliphatic Isothiocyanates
Publication -
High accuracy and octave error immune pitch detection algorithms.
PublicationW publikacji przedstawiona została metoda poprawiająca dokładność estymacji częstotliwości podstawowej dźwięków naturalnych i syntetycznych. Opracowany algorytm wykorzystuje sztczną sieć neuronową. Dodatkowo przedstawiony został algorytm zoptymalizowany pod kątem błędów oktawowych, operujący w dziedzinie częstotliwości. Przedstawiona metoda jest bardzo skuteczna zarówno dla sygnałów harmonicznych o znaczącej energii poszczególnych...
-
Modeling of Ozonation of Reactive Black 5 Through a Kinetic Approach
Publication -
Cadmium inhibitory action leads to changes in structure of ferredoxin:NADP+ oxidoreductase
Publication -
Unveiling the Pool of Metallophores in Native Environments and Correlation with Their Potential Producers
PublicationFor many organisms, metallophores are essential biogenic ligands that ensure metal scavenging and acquisition from their environment. Their identification is challenging in highly organic matter rich environments like peatlands due to low solubilization and metal scarcity and high matrix complexity. In contrast to common approaches based on sample modification by spiking of metal isotope tags, we have developed a two-dimensional...
-
Effect of pH on the Redox and Sorption Properties of Native and Phosphorylated Starches
Publication -
Moderately Reactive Molecules Forming Stable Ionic Compounds with Superhalogens
Publication -
Different Modes of Hydrogen Peroxide Action During Seed Germination
Publication -
The Issues of Reactive Power Compensation in High-voltage Transmission Lines
PublicationThis paper discusses the selection of compensation shunt reactors for a double-circuit 400 kV transmission line using the example of the newly built Elk Bis – Alytus transmission line. The analysis takes into account various conditions of the power system. The published results relate to voltage levels in steady states and during switching processes and short circuits.
-
Prevalence Problem in the Set of Quadratic Stochastic Operators Acting on L1
PublicationThis paper is devoted to the study of the problem of prevalence in the class of quadratic stochastic operators acting on the L1 space for the uniform topology. We obtain that the set of norm quasi-mixing quadratic stochastic operators is a dense and open set in the topology induced by a very natural metric. This shows the typical long-term behaviour of iterates of quadratic stochastic operators.
-
Protection of Pedestrians as the Key Action for Implementing - Poland’s Vision Zero
PublicationWHO reports show that pedestrians account for 10 to 70% of total road crash fatalities. In Poland, pedestrians also represent a significant road safety problem. For many years, pedestrian collisions have accounted for approx. 30% of total road crashes with more than 30% of pedestrians killed. Therefore, pedestrian safety has been one of Poland’s main objectives in its road safety programs implemented over the past 20 years. The...
-
Asymptotic properties of quadratic stochastic operators acting on the L1 space
PublicationQuadratic stochastic operators can exhibit a wide variety of asymptotic behaviours and these have been introduced and studied recently in the ℓ1 space. It turns out that in principle most of the results can be carried over to the L1 space. However, due to topological properties of this space one has to restrict in some situations to kernel quadratic stochastic operators. In this article we study the uniform and strong asymptotic...
-
Carboxy derivative of dioxydiphenylpropane diglycydyl ether monomethacrylate as an addtive for composites
PublicationThe modifier of composites was used in the presence of polyetylene polyamine. Physico-mechanical properties and chemical stability of coatings thus obtained were analyzed.
-
Mispronunciation Detection in Non-Native (L2) English with Uncertainty Modeling
PublicationA common approach to the automatic detection of mispronunciation in language learning is to recognize the phonemes produced by a student and compare it to the expected pronunciation of a native speaker. This approach makes two simplifying assumptions: a) phonemes can be recognized from speech with high accuracy, b) there is a single correct way for a sentence to be pronounced. These assumptions do not always hold, which can result...
-
Mechanical properties of the human stomach under uniaxial stress action
PublicationThe aim of this study was to estimate the range of mechanical properties of the human stomach in order to use the collected data in numerical modelling of surgical stapling during resections of the stomach. The biomedical tests were conducted in a self-developed tensile test machine. Twenty-two fresh human stomach specimens were used for the experimental study of its general strength. The specimens were obtained from morbidly obese...
-
Jaw biomechanics: Estimation of activity of muscles acting at the temporomandibular joint
PublicationThe aim of this study was to elaborate a method of estimation of activity of surface muscles acting at the temporomandibular joint of the healthy subjects by using a surface electromyography (EMG). The scope of this study involved testing chosen jaw motions (open, close, lateral deviation) and process of mastication occurring during eating food with different toughness (chewing gum, cereal and carrot) by using mixed sides, right...
-
About Unusual Diffraction and Thermal Self-Action of Magnetosonic Beam
PublicationThe dynamics of slightly diverging two-dimensional beams whose direction forms a constant angle θ with the equilibrium straight magnetic strength is considered. The approximate dispersion relations and corresponding links which specify hydrodynamic perturbations in confined beams are derived. The study is dedicated to the diffraction of a magnetosonic beam and nonlinear thermal self-action of a beam in a thermoconducting gaseous plasma....
-
Estimation of wind pressure acting on the new palm house in Gdansk
PublicationThis paper deals with the problem of numerical simulations of wind loads acting on a Palm House with complex geometry. Flow simulations with aid of computational fluid dynamics procedures have been performed to check if the pressure distributions for the structure are greater than those calculated using the standard design codes with assumption that the Palm House horizontal cross sections are described by smooth cylinders.
-
Simulation Method for Scheduling Linear Construction Projects Using the Learning– Forgetting Effect
Publication -
Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
Publication -
Machine learning techniques combined with dose profiles indicate radiation response biomarkers
Publication -
Multivariate Features Extraction and Effective Decision Making Using Machine Learning Approaches
Publication -
DALSA: Domain Adaptation for Supervised Learning From Sparsely Annotated MR Images
Publication -
Improved estimation of dynamic modulus for hot mix asphalt using deep learning
Publication -
Effects of mutual learning in physical education to improve health indicators of Ukrainian students
Publication -
Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublicationThis paper analyzes functions and structures of the memory that is an indispensable part of an Intelligent System of Decision-making (ISD), developed as a universal engine for autonomous robotics. A simplified way of processing and coding information in human cognitive processes is modelled and adopted for the use in autonomous systems. Based on such a knowledge structure, an artificial model of reality representation and a model...
-
LOS and NLOS identification in real indoor environment using deep learning approach
PublicationVisibility conditions between antennas, i.e. Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) can be crucial in the context of indoor localization, for which detecting the NLOS condition and further correcting constant position estimation errors or allocating resources can reduce the negative influence of multipath propagation on wireless communication and positioning. In this paper a deep learning (DL) model to classify LOS/NLOS...
-
Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning
PublicationIn this paper, the data, information, knowledge, and wisdom (DIKW) pyramid is revisited in the context of deep learning applied to machine learningbased audio signal processing. A discussion on the DIKW schema is carried out, resulting in a proposal that may supplement the original concept. Parallels between DIWK pertaining to audio processing are presented based on examples of the case studies performed by the author and her collaborators....
-
Detection of People Swimming in Water Reservoirs with the Use of Multimodal Imaging and Machine Learning
PublicationEvery year in many countries, there are fatal unintentional drownings in different water reservoirs like swimming pools, lakes, seas, or oceans. The existing threats of this type require creating a method that could automatically supervise such places to increase the safety of bathers. This work aimed to create methods and prototype solutions for detecting people bathing in water reservoirs using a multimodal imaging system and...
-
Technology-Enhanced Environmental Learning: Co-design of Educational Mobile Application Case
PublicationThe process of co-creating an educational mobile application to support environmentally friendly behavior is presented in this paper. The research material consisted of quantitative data collected on the application during the first testing phase by early adopters. The results suggest that the most frequently used features of the app were related to transport and educational activities. While women tended to split their time between...
-
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...
-
Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublicationThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
-
Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublicationThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
-
Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits
PublicationThe Contextual Multi-Armed Bandits (CMAB) framework is pivotal for learning to make decisions. However, due to challenges in deploying online algorithms, there is a shift towards offline policy learning, which relies on pre-existing datasets. This study examines the relationship between the quality of these datasets and the performance of offline policy learning algorithms, specifically, Neural Greedy and NeuraLCB. Our results...
-
Looking through the past: better knowledge retention for generative replay in continual learning
PublicationIn this work, we improve the generative replay in a continual learning setting to perform well on challenging scenarios. Because of the growing complexity of continual learning tasks, it is becoming more popular, to apply the generative replay technique in the feature space instead of image space. Nevertheless, such an approach does not come without limitations. In particular, we notice the degradation of the continually trained...
-
Predicting emotion from color present in images and video excerpts by machine learning
PublicationThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...