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Search results for: SELF-SUPERVISED LEARNING
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Viruses, cancer and non-self recognition
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Nascent entrepreneurship and the role of self-efficacy
PublicationCelem artykułu jest opisanie roli, jaką w tworzeniu nowej firmy pełni poczucie własnej skuteczności. W pierwszej części artykułu opisane są źródła poczucia samoskuteczności oraz jego następstwa w oparciu o teorię Bandury. W drugiej części artykułu opisane jest rozróżnienie pomiędzy ogólnym poczuciem samoskuteczności a poczuciem samoskuteczności w kontekście przedsiębiorczości (ESE). Autorzy przedstawiają teoretyczne i metodologiczne...
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Self-tuning adaptive frequency tracker
PublicationAn automatic gain tuning algorithm is proposed for a recently introduced adaptive notch filter. Theoretical analysis and simulations show that, under Gaussian random-walk type assumptions, the proposed extension is capable of adjusting adaptation gains of the filter so as to minimize the mean-squared frequency tracking error without prior knowledge of the true frequency trajectory. A simplified one degree of freedom version of...
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Self-defence work of wooden construction
PublicationTrwałość konstrukcji drewnianych, prawidłowo zaprojektowanych i wykonanych zależy przede wszystkim od sposobu ich użytkowania. Brak okresowych remontów może doprowadzić do zniszczenia struktury drewna na skutek korozji biologicznej. Konsekwencją tego są nadmierne przemieszczenia konstrukcji lub utrata jej stateczności a więc zagrożenia awaryjne.
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DNAffinity: a machine-learning approach to predict DNA binding affinities of transcription factors
PublicationWe present a physics-based machine learning approach to predict in vitro transcription factor binding affinities from structural and mechanical DNA properties directly derived from atomistic molecular dynamics simulations. The method is able to predict affinities obtained with techniques as different as uPBM, gcPBM and HT-SELEX with an excellent performance, much better than existing algorithms. Due to its nature, the method can...
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Intra-subject class-incremental deep learning approach for EEG-based imagined speech recognition
PublicationBrain–computer interfaces (BCIs) aim to decode brain signals and transform them into commands for device operation. The present study aimed to decode the brain activity during imagined speech. The BCI must identify imagined words within a given vocabulary and thus perform the requested action. A possible scenario when using this approach is the gradual addition of new words to the vocabulary using incremental learning methods....
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Love your mistakes!—they help you adapt to change. How do knowledge, collaboration and learning cultures foster organizational intelligence?
PublicationPurpose: The study aims to determine how the acceptance of mistakes is related to adaptability to change in a broad organizational context. Therefore it explores how knowledge, collaboration, and learning culture (including “acceptance of mistakes”) might help organizations overcome their resistance to change. Methodology: The study uses two sample groups: students aged 18–24 (330 cases) and employees aged >24 (326 cases) who work...
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Diffusible hydrogen management in underwater wet self-shielded flux cored arc welding
PublicationThis article reports the effect of underwater wet welding parameters and conditions on the diffusible hydrogen content in deposited metal for welding with a self-shielded flux cored wire. The diffusible hydrogen content in deposited metal was determined using the glycerin method according to the Plackett-Burman design determining the significance of the effect of the stick out length, welding current, arc voltage, travel speed...
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Two‐functional μBIST for Testing and Self‐Diagnosis of Analog Circuits in Electronic Embedded Systems
PublicationThe paper concerns the testing of analog circuits and blocks in mixed‐signal Electronic Embedded Systems (EESs), using the Built‐in Self‐Test (BIST) technique. An integrated, two‐functional, embedded microtester (μBIST) based on reuse of signal blocks already present in an EES, such as microprocessors, memories, ADCs, DACs, is presented. The novelty of the μBIST solution is its extended functionality. It can perform 2 testing functions:...
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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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Learning & Memory
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Adult Learning
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Open Learning
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For the Learning of Mathematics
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Teaching & Learning
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Vocations and Learning
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LEARNing Landscapes
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Action Learning
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Support for Learning
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E-Learning
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Ubiquitous Learning
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Learning Disabilities
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Online Learning
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LEARNING & MEMORY
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MACHINE LEARNING
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LEARNING & BEHAVIOR
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LANGUAGE LEARNING
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Learning and Instruction
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MANAGEMENT LEARNING
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LEARNING AND MOTIVATION
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Metacognition and Learning
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Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublicationCatheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified...
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Optimizing Medical Personnel Speech Recognition Models Using Speech Synthesis and Reinforcement Learning
PublicationText-to-Speech synthesis (TTS) can be used to generate training data for building Automatic Speech Recognition models (ASR). Access to medical speech data is because it is sensitive data that is difficult to obtain for privacy reasons; TTS can help expand the data set. Speech can be synthesized by mimicking different accents, dialects, and speaking styles that may occur in a medical language. Reinforcement Learning (RL), in the...
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Testing Students’ Entrepreneurial Self-Efficacy as an Early Predictor of Entrepreneurial Activities. Evidence From the SEAS Project
PublicationOver the last forty years, since Bandura (1977) introduced the concept of self-efficacy, there have been a constantly growing number of research publications using this concept. Its early development resulted in the creation of a new construct of entrepreneurial self-efficacy (ESE) proposed for the first time by (Chen et al. 1998). Since then, many different groups of research concerning ESE have emerged - one of them is the study...
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Automated detection of pronunciation errors in non-native English speech employing deep learning
PublicationDespite significant advances in recent years, the existing Computer-Assisted Pronunciation Training (CAPT) methods detect pronunciation errors with a relatively low accuracy (precision of 60% at 40%-80% recall). This Ph.D. work proposes novel deep learning methods for detecting pronunciation errors in non-native (L2) English speech, outperforming the state-of-the-art method in AUC metric (Area under the Curve) by 41%, i.e., from...
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Minimal number of periodic points of smooth boundary-preserving self-maps of simply-connected manifolds
PublicationLet M be a smooth compact and simply-connected manifold with simply-connected boundary ∂M, r be a fixed odd natural number. We consider f, a C1 self-map of M, preserving ∂M . Under the assumption that the dimension of M is at least 4, we define an invariant Dr(f;M,∂M) that is equal to the minimal number of r-periodic points for all maps preserving ∂M and C1-homotopic to f. As an application, we give necessary and sufficient...
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Methodology for assessing end-user requirements in the Ella4Life project: elders’ perspectives about self-monitoring
PublicationThe purpose of this paper is to explore elders’ perspectives about self-monitoring and using specially developed sensor technology for measuring health indicators. The qualitative research method is focus-groups with guidelines that were designed for understanding elder’s requirements about monitoring health indicators. We present them two devices: the first sensor is a device for monitoring of cardiac action potential fixed into...
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The awareness of the profession and the self-reflection of the primary, secondary and upper secondary school teachers on their own practice in the light of empirical studies
PublicationThe article presents the issue of awareness of the profession and the self-reflection of the primary, secondary and upper secondary school teachers’ on their own practice. The text refers to data based on empirical studies.
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Self-Adaptive Mesh Generator for Global Complex Roots and Poles Finding Algorithm
PublicationIn any global method of searching for roots and poles, increasing the number of samples increases the chances of finding them precisely in a given area. However, the global complex roots and poles finding algorithm (GRPF) (as one of the few) has direct control over the accuracy of the results. In addition, this algorithm has a simple condition for finding all roots and poles in a given area: it only requires a sufficiently dense...
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An experimental study of self-sensing concrete enhanced with multi-wall carbon nanotubes in wedge splitting test and DIC
PublicationConcrete is the worldwide most utilized construction material because of its very good performance, forming ability, long-term durability, and low costs. Concrete is a brittle material prone to cracking. Extensive cracking may impact durability and performance over time considerably. The addition of a small amount of carbon nanotubes (CNT) increases the concrete’s overall electrical conductivity, enabling internal structure...
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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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Projektowanie zajęć prowadzonych na odległość (10h e-learning)
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublicationWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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Frequency of use, moral incongruence, and religiosity and their relationships with self-perceived addiction to pornography, internet use, social networking and online gaming
PublicationBackground and Aims Moral incongruence involves disapproval of a behaviour in which people engage despite their moral beliefs. Although considerable research has been conducted on how moral incongruence relates to pornography use, potential roles for moral incongruence in other putative behavioural addictions have not been investigated. The aim of this study was to investigate the role of moral incongruence in self‐perceived...
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Reducing the number of periodic points in the smooth homotopy class of a self-map of a simply-connected manifold with periodic sequence of Lefschetz numbers
PublicationLet f be a smooth self-map of an m-dimensional (m >3) closed connected and simply-connected manifold such that the sequence of the Lefschetz num- bers of its iterations is periodic. For a fixed natural r we wish to minimize, in the smooth homotopy class, the number of periodic points with periods less than or equal to r. The resulting number is given by a topological invariant J[f] which is defned in combinatorial terms and is...
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Modeling lignin extraction with ionic liquids using machine learning approach
PublicationLignin, next to cellulose, is the second most common natural biopolymer on Earth, containing a third of the organic carbon in the biosphere. For many years, lignin was perceived as waste when obtaining cellulose and hemicellulose and used as a biofuel for the production of bioenergy. However, recently, lignin has been considered a renewable raw material for the production of chemicals and materials to replace petrochemical resources....
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Optical method supported by machine learning for dynamics of C‐reactive protein concentrations changes detection in biological matrix samples
PublicationIn this article we present the novel spectroscopy method supported with machine learning for real-time detection of infectious agents in wastewater. In the case of infectious diseases, wastewater monitoring can be used to detect the presence of inflammation biomarkers, such as the proposed C-reactive protein, for monitoring inflammatory conditions and mass screening during epidemics for early detection in communities of concern,...
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Diagnosis of Damage in a Steel Tank with Self-Supported Roof through Numerical Analysis
PublicationThe safety of civil engineering structures is one of the most important issues of building industry. That is why the assessment of the damage-involved structural response has recently become of major concern to engineers. Among a number of different approaches to diagnosis of damage, the method of measuring the changes in natural frequencies is considered to be one of the most effective indicators of global damage. From the practical...
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Structural Adaptive, Self-Separating Material for Removing Ibuprofen from Waters and Sewage
Publication-cyclodextrin nanosponge (CDM) was used for the adsorption of ibuprofen (IBU) from water and sewage. The obtained material was characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), Brunauer–Emmett–Teller (BET), Barrett– Joyner–Halenda (BJH), Harkins and Jura t-Plot, zeta potential, thermogravimetric analysis (TGA), differential scanning calorimetry (DSC) and elementary analysis (EA)....
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Pursuing the Deep-Learning-Based Classification of Exposed and Imagined Colors from EEG
PublicationEEG-based brain-computer interfaces are systems aiming to integrate disabled people into their environments. Nevertheless, their control could not be intuitive or depend on an active external stimulator to generate the responses for interacting with it. Targeting the second issue, a novel paradigm is explored in this paper, which depends on a passive stimulus by measuring the EEG responses of a subject to the primary colors (red,...