Search
Filters
total: 2270
filtered: 1723
-
Catalog
- Publications 1723 available results
- Journals 192 available results
- Conferences 28 available results
- Publishing Houses 1 available results
- People 95 available results
- Projects 8 available results
- e-Learning Courses 67 available results
- Events 9 available results
- Open Research Data 147 available results
Chosen catalog filters
displaying 1000 best results Help
Search results for: SELF-SUPERVISED LEARNING
-
Employees’ self-expansion as a mediator between perceived work conditions and work engagement and productive behaviors
PublicationThere has been increasing scientific interest in the relationships between self-perception and group identity development processes as well as the behavioural implications of these processes in organizational contexts. Recently, the concept of workplace self-expansion has been introduced to work and organizational psychology. That is, the self-expanding characteristics of work and the workplace have been related to job satisfaction...
-
Self-Perceived Personal Brand Equity of Knowledge Workers by Gender in Light of Knowledge-Driven Organizational Culture: Evidence From Poland and the United States
PublicationThis study contributes to the limited literature on the personal branding of knowledge workers by revealing that a culture that incorporates knowledge, learning, and collaboration supports (explicit and tacit) knowledge sharing among employees and that sharing matters for knowledge workers’ self-perceived personal brand equity. Analysis of 2,168 cases from the United States and Poland using structural equation modeling (SEM) showed...
-
Unusual dynamics and nonlinear thermal self-focusing of initially focused magnetoacoustic beams in a plasma
PublicationUnusual thermal self-focusing of two-dimensional beams in plasma which axis is parallel to the equilibrium straight magnetic field is considered. The equi- librium parameters of plasma determine scenario of a beam divergence (usual or unusual) which is stronger as compared with a flow without magnetic field. Nonlinear thermal self-action of a magnetosonic beam behaves differently in the ordinary and unusual cases. Damping of wave...
-
Process of Medical Dataset Construction for Machine Learning-Multifield Study and Guidelines
PublicationThe acquisition of high-quality data and annotations is essential for the training of efficient machine learning algorithms, while being an expensive and time-consuming process. Although the process of data processing and training and testing of machine learning models is well studied and considered in the literature, the actual procedures of obtaining data and their annotations in collaboration with physicians are in most cases...
-
Data augmentation for improving deep learning in image classification problem
PublicationThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
-
NON-STATIONARY THERMAL SELF-ACTION OF ACOUSTIC BEAMS CONTAINING SHOCK FRONTS IN THERMOCONDUCTING FLUID
PublicationNon-stationary thermal self-action of a periodic or impulse acoustic beam containing shock fronts in a thermoconducting Newtonian fluid is studied. Self-focusing of a saw-tooth periodic and impulse sound is considered, as well as that of a solitary shock wave which propagates with the linear sound speed. The governing equations of the beam radius are derived. Numerical simulations reveal that the thermal conductivity weakens the...
-
Internet photogrammetry as a tool for e-learning
PublicationAlong with Internet development, there were interactive applications which allow for remote sensing and photogrammetric analysis. An example of an application that can provide Earth images and make it possible to measure distances in these images is Google Earth. The authors, who have experience from 2001-2015 argue that it is possible and it is important to create more advanced photogrammetric network applications. In this there...
-
Convolutional Neural Networks for C. Elegans Muscle Age Classification Using Only Self-Learned Features
PublicationNematodes Caenorhabditis elegans (C. elegans) have been used as model organisms in a wide variety of biological studies, especially those intended to obtain a better understanding of aging and age-associated diseases. This paper focuses on automating the analysis of C. elegans imagery to classify the muscle age of nematodes based on the known and well established IICBU dataset. Unlike many modern classification methods, the proposed...
-
Data Domain Adaptation in Federated Learning in the Breast Mammography Image Classification Problem
PublicationWe are increasingly striving to introduce modern artificial intelligence techniques in medicine and elevate medical care, catering to both patients and specialists. An essential aspect that warrants concurrent development is the protection of personal data, especially with technology's advancement, along with addressing data disparities to ensure model efficacy. This study assesses various domain adaptation techniques and federated...
-
Innovative e-learning approach in teaching based on case studies - Innocase project
PublicationThe article presents the application of innovative e-learning approach for the creation of case study content. Case study methodology is becoming more and more widely applied in modern education, especially in business and management field. Although case study methodology is quite well recognized and used in education, there are still few examples of developing e-learning content on the basis of case studies. This task is to be...
-
Explainable machine learning for diffraction patterns
PublicationSerial crystallography experiments at X-ray free-electron laser facilities produce massive amounts of data but only a fraction of these data are useful for downstream analysis. Thus, it is essential to differentiate between acceptable and unacceptable data, generally known as ‘hit’ and ‘miss’, respectively. Image classification methods from artificial intelligence, or more specifically convolutional neural networks (CNNs), classify...
-
MACHINE LEARNING APPLICATIONS IN RECOGNIZING HUMAN EMOTIONS BASED ON THE EEG
PublicationThis study examined the machine learning-based approach allowing the recognition of human emotional states with the use of EEG signals. After a short introduction to the fundamentals of electroencephalography and neural oscillations, the two-dimensional valence-arousal Russell’s model of emotion was described. Next, we present the assumptions of the performed EEG experiment. Detail aspects of the data sanitization including preprocessing,...
-
Solubility of dapsone in deep eutectic solvents: Experimental analysis, molecular insights and machine learning predictions
PublicationBackground. Dapsone (DAP) is an anti-inflammatory and antimicrobial active pharmaceutical ingredient used to treat, e.g., AIDS-related diseases. However, low solubility is a feature hampering its efficient use. Objectives. First, deep eutectic solvents...
-
Self-healing mechanism of metallopolymers investigated by QM/MM simulations and Raman spectroscopy
PublicationThe thermally induced self-healing mechanisms in metallopolymers based on bisterpyridine complexes of iron(II) sulfate and cadmium(II) bromide, respectively, were studied by means of combined quantum mechanical/molecular mechanical (QM/MM) simulations and Raman spectroscopy. Two possible healing schemes, one based on a decomplexation of the cross-linking complexes and a second one relying on the dissociation of ionic clusters,...
-
Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech
PublicationWe present a novel deep learning model for the detection and reconstruction of dysarthric speech. We train the model with a multi-task learning technique to jointly solve dysarthria detection and speech reconstruction tasks. The model key feature is a low-dimensional latent space that is meant to encode the properties of dysarthric speech. It is commonly believed that neural networks are black boxes that solve problems but do not...
-
Self-standing Nanoarchitectures
Publication -
Self-standing Nanoarchitectures
PublicationDespite there are structures invisible for the human eye, they mastered the world of advanced electronic devices, sensors, novel cosmetics or drugs. When the dimensions of the materials go down to the nanometres scale, their properties change dramatically comparing to the observable objects. Because of their tiny size, they gained the name of nanomaterials but simultaneously their importance has significantly grown up. Nanomaterials...
-
New trifunctional acrylic water-based paint with self-cleaning, biocidal and magnetic properties
PublicationIn the present study, we report the synthesis and application of ZnFe2O4/SiO2-TiO2 nanocomposites with nonstoichiometric content of Fe to Zn used for the first time for the preparation of new generation trifunctional paints with self-cleaning, biocidal and magnetic properties. Currently, there are no compositions on the market for obtaining protective coatings in the form of paint, which simultaneously exhibit biocidal, magnetic...
-
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...
-
Measurement of the Development of a Learning IT Organization Supported by a Model of Knowledge Acquisition and Processing
PublicationThe paper presents a model of knowledge acquisition and processing for the development of learning organizations. The theory of a learning organization provides neither metrics nor tools to measure its development The authors' studies in this field are based on their experience gathered after projects realized in real IT organizations. The authors have described the construction of the model and the methods of its verification...
-
Self-Organizing Map representation for clustering Wikipedia search results
PublicationThe article presents an approach to automated organization of textual data. The experiments have been performed on selected sub-set of Wikipedia. The Vector Space Model representation based on terms has been used to build groups of similar articles extracted from Kohonen Self-Organizing Maps with DBSCAN clustering. To warrant efficiency of the data processing, we performed linear dimensionality reduction of raw data using Principal...
-
Self–Organizing Map representation for clustering Wikipedia search results
PublicationThe article presents an approach to automated organization of textual data. The experiments have been performed on selected sub-set of Wikipedia. The Vector Space Model representation based on terms has been used to build groups of similar articles extracted from Kohonen Self-Organizing Maps with DBSCAN clustering. To warrant efficiency of the data processing, we performed linear dimensionality reduction of raw data using Principal...
-
Self-refraction of acoustic pulses with shock fronts in some nonequilibrium media
PublicationThe nonlinear self-refraction of acoustic pulsed beams, which include shock fronts, is studied. The medium of sound propagation is a gas where thermodynamically nonequilibrium processes take place, such as exothermic chemical reaction or excitation of vibrational degrees of a molecule’s freedom. Comparative analysis of the features of sound propagation over gases where pure nonlinear attenuation of the shock wave occurs, and gases...
-
Towards Scalable Simulation of Federated Learning
PublicationFederated learning (FL) allows to train models on decentralized data while maintaining data privacy, which unlocks the availability of large and diverse datasets for many practical applications. The ongoing development of aggregation algorithms, distribution architectures and software implementations aims for enabling federated setups employing thousands of distributed devices, selected from millions. Since the availability of...
-
Organizational Wisdom: The Impact of Organizational Learning on the Absorptive Capacity of an Enterprise
PublicationPurpose: In this article, we analyze the concept of organizational wisdom, indicating its key elements and verifieng the relationships between them. Design/Methodology/Approach: The study was conducted at Vive Textile Recycling Sp. z o.o in Poland. Empirical data was collected from 138 managers using the PAPI technique. Structural equation modelling (SEM) was performed to test the research hypotheses. Additionally, the significance...
-
Virtual spring damper method for nonholonomic robotic swarm self-organization and leader following
PublicationIn this paper, we demonstrate a method for self-organization and leader following of nonholonomic robotic swarm based on spring damper mesh. By self-organization of swarm robots we mean the emergence of order in a swarm as the result of interactions among the single robots. In other words the self-organization of swarm robots mimics some natural behavior of social animals like ants among others. The dynamics of two-wheel robot...
-
Analysing the Residential Market Using Self-Organizing Map
PublicationAlthough the residential property market has strong connections with various sectors, such as construction, logistics, and investment, it works through different dynamics than other markets; thus, it can be analysed from various perspectives. Researchers and investors are mostly interested in price trends, the impact of external factors on residential property prices, and price prediction. When analysing price trends, it is beneficial...
-
Self-compacting grout to produce two-stage concrete
PublicationTraditional concrete (TC) is primarily composed of a mixture of cement, fine and coarse aggregates, and water. TC is made by mixing together all the components before placing them. Using non-traditional concrete (two-stage concrete) to solve and to eliminate the problem of the aggregate segregation which appears in TC and in the self-compacting concrete. Two-stage concrete (TSC) consists of two main components, namely the grout...
-
A Highly Scalable, Modular Architecture for Computer Aided Assessment e-Learning Systems
PublicationIn this chapter, the authors propose a novel e-learning system, dedicated strictly to knowledge assessment tasks. In its functioning it utilizes web-based technologies, but its design differs radically from currently popular e-learning solutions which rely mostly on thin-client architecture. The authors' research proved that such architecture, while well suited for didactic content distribution systems is ill-suited for knowledge...
-
E-Learning Service Management System For Migration Towards Future Internet Architectures
PublicationAs access to knowledge and continuous learning are among the most valuable assets in modern, technological society, it is hardly surprising that e-learning solutions can be counted amongst the most important groups of services being deployed in modern network systems. Based on analysis of their current state-of-the-art, we decided to concentrate our research and development work on designing and implementing a management system...
-
Self-Concept Clarity and Religious Orientations: Prediction of Purpose in Life and Self-Esteem
Publication -
Continuous learning as a method of raising qualifications – the perspective of workers, employers and training organizations
PublicationContinuous learning is discussed in strategic documents of Poland and the European Union. In Poland, the idea of continuous learning is not very popular. However, in the context of strong competition in the labour market and the progressive globalization processes, the skills issue takes on new meaning — both for employees and employers. In order to adapt skills to labour market needs it is necessary to conduct adequate studies...
-
Psychophysiological strategies for enhancing performance through imagery – skin conductance level analysis in guided vs. self-produced imagery
PublicationAthletes need to achieve their optimal level of arousal for peak performance. Visualization or mental rehearsal (i.e., Imagery) often helps to obtain an appropriate level of activation, which can be detected by monitoring Skin Conductance Level (SCL). However, different types of imagery could elicit different amount of physiological arousal. Therefore, this study aims: (1) to investigate differences in SCL associated with two instructional...
-
Harmony Search to Self-Configuration of Fault-Tolerant Grids for Big Data
PublicationIn this paper, harmony search algorithms have been proposed to self-configuration of fault-tolerant grids for big data processing. Some tasks related to big data processing have been considered. Moreover, two criteria have been applied to evaluate quality of grids. The first criterion is a probability that all tasks meet their deadlines and the second one is grid reliability. Furthermore, some intelligent agents based on harmony...
-
Evaluating the risk of endometriosis based on patients’ self-assessment questionnaires
PublicationBackground Endometriosis is a condition that significantly affects the quality of life of about 10 % of reproductive-aged women. It is characterized by the presence of tissue similar to the uterine lining (endometrium) outside the uterus, which can lead lead scarring, adhesions, pain, and fertility issues. While numerous factors associated with endometriosis are documented, a wide range of symptoms may still be undiscovered. Methods In...
-
Divide and not forget: Ensemble of selectively trained experts in Continual Learning
PublicationClass-incremental learning is becoming more popular as it helps models widen their applicability while not forgetting what they already know. A trend in this area is to use a mixture-of-expert technique, where different models work together to solve the task. However, the experts are usually trained all at once using whole task data, which makes them all prone to forgetting and increasing computational burden. To address this limitation,...
-
Self-advocacy of a person with a disability in the dual role of paid worker and volunteer: Theoretical considerations and a case study
PublicationThe changing models of disability influence the way people with disabilities participate in social life, and how they can transform their life and environment. Such participation may take the form of work and volunteering, as well as participation in self-advocacy movements. This paper aims to explore how a woman with hearing impairment perceives her dual role as a regular worker and voluntary self-advocate within one organization...
-
Multimedia industrial and medical applications supported by machine learning
PublicationThis article outlines a keynote paper presented at the Intelligent DecisionTechnologies conference providing a part of the KES Multi-theme Conference “Smart Digital Futures” organized in Rome on June 14–16, 2023. It briefly discusses projects related to traffic control using developed intelligent traffic signs and diagnosing the health of wind turbine mechanisms and multimodal biometric authentication for banking branches to provide...
-
Self-assembled concentric stripes of diamond particles by a pinning-depinning mechanism
PublicationWe describe the novel mechanism of spontaneous formation of the concentric stripe patterns of microdiamonds via gradual solvent evaporation from a suspension confined in a teardrop well. The self-organized patterns exhibit a series of arcs with regular spacings varying between hundreds of micrometers and millimeters. They result from an interplay between the directional forced circulation of the solvent and a stick-slip movement...
-
Self-Testing of Analog Parts Terminated by ADCs Based on Multiple Sampling of Time Responses
PublicationA new approach for self-testing of analog parts terminated by analog-to-digital converters in mixed-signal electronic microsystems controlled by microcontrollers is presented. It is based upon a new fault diagnosis method using a transformation of the set of voltage samples of the time response of a tested analog part to a square impulse into localization curves placed in a multidimensional measurement space. The method can be used...
-
Topological degree for equivariant gradient perturbations of an unbounded self-adjoint operator in Hilbert space
PublicationWe present a version of the equivariant gradient degree defined for equivariant gradient perturbations of an equivariant unbounded self-adjoint operator with purely discrete spectrum in Hilbert space. Two possible applications are discussed.
-
Machine learning applied to acoustic-based road traffic monitoring
PublicationThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
-
Machine learning applied to acoustic-based road traffic monitoring
PublicationThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
-
Compact Substrate-Integrated Hexagonal Cavity-Backed Self-Hexaplexing Antenna for Sub-6 GHz Applications
PublicationA self-multiplexing SIW antenna based on hexagonal SIW cavity is proposed. The self-hexaplexing antenna consists of different sizes of resonating elements, which provide the hexaband operations. The antenna resonates at 5 GHz, 5.17 GHz, 5.32 GHz, 5.53 GHz, 5.62 GHz, and 5.72 GHz by employing different slot lengths between the resonating elements. The proposed antenna provides the individual tunable characteristics of the operating...
-
Survey of ICT students' views on self-assessment of professional preparation after remote study
PublicationThe contemporary post-pandemic reality is characterised by an undisputable shift toward remote education and work. The aim of this article is to identify the assessment of ICT evaluation of different forms of study, including desktop, remote and hybrid forms; to find out their preferences towards different forms of education and work, and to determine their sense of self-efficacy in terms of professional tasks undertaken after...
-
Self-compacting grout to produce two-stage concrete
PublicationTraditional concrete (TC) is primarily composed...
-
Discovering Rule-Based Learning Systems for the Purpose of Music Analysis
PublicationMusic analysis and processing aims at understanding information retrieved from music (Music Information Retrieval). For the purpose of music data mining, machine learning (ML) methods or statistical approach are employed. Their primary task is recognition of musical instrument sounds, music genre or emotion contained in music, identification of audio, assessment of audio content, etc. In terms of computational approach, music databases...
-
A Self-Adaptive Complex Root Tracing Algorithm for the Analysis of Propagation and Radiation Problem
PublicationAn improved complex root tracing algorithm for radiation and propagation issues is proposed. The approach is based on a self-adaptive discretization of Cauchy’s argument principle for a C × R space and requires a reduced number of function calls in comparison to other procedures presented in the literature. A few different examples concerning propagation and radiation problems have been considered to verify the validity and efficiency...
-
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....
-
A Compact Self-Hexaplexing Antenna Implemented on Substrate-Integrated Rectangular Cavity for Hexa-Band Applications
PublicationThis brief introduces a novel architecture of a compact self-hexaplexing antenna (SHA) implemented on a substrate-integrated rectangular cavity (SIRC) for hexa-band applications. The proposed SHA is configured by using an SIRC resonator, two Pi-shaped slots (PSSs), and six 50Ω microstrip feedlines. The PSSs are connected back-to-back and loaded on top of the SIRC resonator to produce six patch radiators (PRs). The PRs are excited...