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Search results for: ACTIVE%20LEARNING
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Modeling of Ozonation of Reactive Black 5 Through a Kinetic Approach
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Cadmium inhibitory action leads to changes in structure of ferredoxin:NADP+ oxidoreductase
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C-reactive Protein as a Diagnostic and Prognostic Factor of Endometrial Cancer
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C-reactive protein as a diagnostic and prognostic factor of endometrial cancer
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Determination of Effects and Mechanisms of Action of Bacterial Amyloids on Antibiotic Resistance
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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...
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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...
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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...
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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.
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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....
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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.
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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...
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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.
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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...
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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.
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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...
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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...
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Piotr Jaskuła dr hab. inż.
PeopleI am a Faculty member (Associate Professor, Highway and Transportation Research Department) at the Faculty of Civil and Environmental Engineering, Gdansk University of Technology, Poland).My main research interests include: pavement structures, interlayer bonding, pavement materials, recycling of road pavements, asphalt mixtures, bitumens, construction and maintenance of pavement structures.My lectures at the University include:...
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Janusz Cieśliński prof. dr hab. inż.
PeopleHe was born on April 15, 1954 in Slupsk. He graduated from the Faculty of Mechanical Engineering at Gdańsk University of Technology (1978). In 1986 he received the title of Doctor, in 1997 he obtained the title of Ph.D. with habilitation, and in 2006 he received the title of Professor. He worked as head of department and vice-dean for Education at the Faculty of Mechanical Engineering for two terms (2002-2008). His research interests...
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AMERICAN INDIAN AND ALASKA NATIVE MENTAL HEALTH RESEARCH
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Progress in Community Health Partnerships-Research Education and Action
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Contribution of UDP-glucuronosyltransferases (UGTs) in metabolism of acridinone antitumor agents, C-1311, C-1305, and their less active structural analogues, C-1330 and C-1299
PublicationCelem prowadzonych badań było określenie roli UDP-glukuronylotransferaz, uważanych za najważniejsze enzymy detoksykujące, w metabolizmie pochodnych imidazo- i triazoloakrydonu. Wykazano, że najbardziej aktywne przeciwnowotworowo związki z obu grup, tj. C-1311 i C-1305 są transformowane do O-glukuronidów, w przeciwieństwie do ich metoksylowych analogów, odpowiednio związku C-1330 i C-1299. Analiza składu mieszanin reakcyjnych zawierających...
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A New Expression System Based on Psychrotolerant Debaryomyces macquariensis Yeast and Its Application to the Production of Cold-Active β-D-Galactosidase from Paracoccus sp. 32d
PublicationYeasts provide attractive host/vector systems for heterologous gene expression. The currently used yeast-based expression platforms include mesophilic and thermotolerant species. A eukaryotic expression system working at low temperatures could be particularly useful for the production of thermolabile proteins and proteins that tend to form insoluble aggregates. For this purpose, an expression system based on an Antarctic psychrotolerant...
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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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Evaluation of Machine Learning Methods for the Experimental Classification and Clustering of Higher Education Institutions
PublicationHigher education institutions have a big impact on the future of skills supplied on the labour market. It means that depending on the changes in labour market, higher education institutions are making changes to fields of study or adding new ones to fulfil the demand on labour market. The significant changes on labour market caused by digital transformation, resulted in new jobs and new skills. Because of the necessity of computer...
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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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Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
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Deep learning-enabled integration of renewable energy sources through photovoltaics in buildings
PublicationInstalling photovoltaic (PV) systems in buildings is one of the most effective strategies for achieving sustainable energy goals and reducing carbon emissions. However, the requirement for efficient energy management, the fluctuating energy demands, and the intermittent nature of solar power are a few of the obstacles to the seamless integration of PV systems into buildings. These complexities surpass the capabilities of rule-based...
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Comparison of Deep Neural Network Learning Algorithms for Mars Terrain Image Segmentation
PublicationThis 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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Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning
PublicationIn this work, we investigate exemplar-free class incremental learning (CIL) with knowledge distillation (KD) as a regularization strategy, aiming to prevent forgetting. KDbased methods are successfully used in CIL, but they often struggle to regularize the model without access to exemplars of the training data from previous tasks. Our analysis reveals that this issue originates from substantial representation shifts in the teacher...
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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...
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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...
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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...
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Advancing Solar Energy: Machine Learning Approaches for Predicting Photovoltaic Power Output
PublicationThis research is primarily concentrated on predicting the output of photovoitaic power, an essential field in the study of renewable energy. The paper comprehensively reviews various forecasting methodologies, transitioning from conventional physical and statistical methods to advanced machine learning (ML) techniques. A significant shift has been observed from traditional point forecasting to machine learning-based forecasting...
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Application of the Flipped Learning Methodology at a Business Process Modelling Course – A Case Study
PublicationFlipped learning has been known for a long time, but its modern use dates back to 2012, with the publication of Bergmann and Saams. In the last decade, it has become an increasingly popular learning method. Every year, the number of publications on implementing flipped learning experiments is growing, just as the amount of research on the effectiveness of this educational method. The aim of the article is to analyze the possibilities...
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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...
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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....
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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...
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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...
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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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Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublicationBiochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts,...
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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...
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Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method
PublicationPlasmonic nanostructures based on AuAg nanoalloys were fabricated by thermal annealing of metallic films in an argon atmosphere. The nanoalloys were chosen because they can extend the wavelength range in which plasmon resonance occurs and thus allow the design of plasmonic platforms with the desired parameters. The influence of initial fabrication parameters and experimental conditions on the formation of nanostructures was investigated....