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Wyniki wyszukiwania dla: SELF-SUPERVISED LEARNING
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Employees’ self-expansion as a mediator between perceived work conditions and work engagement and productive behaviors
PublikacjaThere 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...
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Unusual dynamics and nonlinear thermal self-focusing of initially focused magnetoacoustic beams in a plasma
PublikacjaUnusual 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...
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Measurement of the Development of a Learning IT Organization Supported by a Model of Knowledge Acquisition and Processing
PublikacjaThe 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...
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NON-STATIONARY THERMAL SELF-ACTION OF ACOUSTIC BEAMS CONTAINING SHOCK FRONTS IN THERMOCONDUCTING FLUID
PublikacjaNon-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...
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Towards Scalable Simulation of Federated Learning
PublikacjaFederated 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...
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Organizational Wisdom: The Impact of Organizational Learning on the Absorptive Capacity of an Enterprise
PublikacjaPurpose: 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...
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Self-healing mechanism of metallopolymers investigated by QM/MM simulations and Raman spectroscopy
PublikacjaThe 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,...
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Self-standing Nanoarchitectures
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Self-standing Nanoarchitectures
PublikacjaDespite 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...
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A Highly Scalable, Modular Architecture for Computer Aided Assessment e-Learning Systems
PublikacjaIn 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...
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E-Learning Service Management System For Migration Towards Future Internet Architectures
PublikacjaAs 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...
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Continuous learning as a method of raising qualifications – the perspective of workers, employers and training organizations
PublikacjaContinuous 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...
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New trifunctional acrylic water-based paint with self-cleaning, biocidal and magnetic properties
PublikacjaIn 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...
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Self-Organizing Map representation for clustering Wikipedia search results
PublikacjaThe 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...
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Self–Organizing Map representation for clustering Wikipedia search results
PublikacjaThe 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...
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Self-refraction of acoustic pulses with shock fronts in some nonequilibrium media
PublikacjaThe 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...
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Divide and not forget: Ensemble of selectively trained experts in Continual Learning
PublikacjaClass-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,...
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Multimedia industrial and medical applications supported by machine learning
PublikacjaThis 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...
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Virtual spring damper method for nonholonomic robotic swarm self-organization and leader following
PublikacjaIn 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...
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Machine learning applied to acoustic-based road traffic monitoring
PublikacjaThe 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...
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Machine learning applied to acoustic-based road traffic monitoring
PublikacjaThe 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...
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Self-compacting grout to produce two-stage concrete
PublikacjaTraditional 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...
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Analysing the Residential Market Using Self-Organizing Map
PublikacjaAlthough 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...
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Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning
PublikacjaIn 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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Discovering Rule-Based Learning Systems for the Purpose of Music Analysis
PublikacjaMusic 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...
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Self-Concept Clarity and Religious Orientations: Prediction of Purpose in Life and Self-Esteem
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Evaluating the risk of endometriosis based on patients’ self-assessment questionnaires
PublikacjaBackground 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...
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Harmony Search to Self-Configuration of Fault-Tolerant Grids for Big Data
PublikacjaIn 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...
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Self-advocacy of a person with a disability in the dual role of paid worker and volunteer: Theoretical considerations and a case study
PublikacjaThe 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...
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Self-assembled concentric stripes of diamond particles by a pinning-depinning mechanism
PublikacjaWe 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...
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Self-Testing of Analog Parts Terminated by ADCs Based on Multiple Sampling of Time Responses
PublikacjaA 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...
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Topological degree for equivariant gradient perturbations of an unbounded self-adjoint operator in Hilbert space
PublikacjaWe 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.
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Compact Substrate-Integrated Hexagonal Cavity-Backed Self-Hexaplexing Antenna for Sub-6 GHz Applications
PublikacjaA 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...
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Computational Simulation of the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublikacjaThis chapter investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organisational culture results in better mistake management and thus better organisational learning, (2) Effective organisational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader’s behavior must align for the best learning...
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Self-compacting grout to produce two-stage concrete
PublikacjaTraditional concrete (TC) is primarily composed...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublikacjaThe 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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Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning
PublikacjaFollowing the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides...
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An integrated e-learning services management system providing HD videoconferencing and CAA services
PublikacjaIn this paper we present a novel e-learning services management system, designed to provide highly modifiable platform for various e-learning tools, able to fulfill its function in any network connectivity conditions (including no connectivity scenario). The system can scale from very simple setup (adequate for servicing a single exercise) to a large, distributed solution fit to support an enterprise. Strictly modular architecture...
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WEB-CAM AS A MEANS OF INFORMATION ABOUT EMOTIONAL ATTEMPT OF STUDENTS IN THE PROCESS OF DISTANT LEARNING
PublikacjaNew methods in education become more popular nowadays. Distant learning is a good example when teacher and student meet in virtual environment. Because interaction in this virtual world might be complicated it seems necessary to assure as much methods of conforming that student is still engaged in the process of learning as it is possible. We would like to present assumption that by means of web-cam we will be able to track facial...
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A Self-Adaptive Complex Root Tracing Algorithm for the Analysis of Propagation and Radiation Problem
PublikacjaAn 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...
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A Compact Self-Hexaplexing Antenna Implemented on Substrate-Integrated Rectangular Cavity for Hexa-Band Applications
PublikacjaThis 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...
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Deep learning for ultra-fast and high precision screening of energy materials
PublikacjaSemiconductor materials for energy storage are the core and foundation of modern information society and play important roles in photovoltaic system, integrated circuit, spacecraft technology, lighting applications, and other fields. Unfortunately, due to the long experiment period and high calculation cost, the high-precision band gap (the basic characteristic parameter) of semiconductor is difficult to obtain, which hinders the...
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Wisdom from Experience Paradox: Organizational Learning, Mistakes, Hierarchy and Maturity Issues
PublikacjaOrganizations often perceive mistakes as negligence and low-performance indicators, yet they can be a precious learning resource. However, organizations cannot learn from mistakes if they have not accepted them. This study aimed to explore how organizational hierarchy and maturity levels influence the relationship between mistakes acceptance and the ability to change. A sample composed of 380 Polish employees working in knowledge-driven...
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Deep learning techniques for biometric security: A systematic review of presentation attack detection systems
PublikacjaBiometric technology, including finger vein, fingerprint, iris, and face recognition, is widely used to enhance security in various devices. In the past decade, significant progress has been made in improving biometric sys- tems, thanks to advancements in deep convolutional neural networks (DCNN) and computer vision (CV), along with large-scale training datasets. However, these systems have become targets of various attacks, with...
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Exact resultant equilibrium conditions in the non-linear theory of branching and self-intersecting shells
PublikacjaWe formulate the exact, resultant equilibrium conditions for the non-linear theory of branching and self-intersecting shells. The conditions are derived by performing direct through-the-thickness integration in the global equilibrium conditions of continuum mechanics. At each regular internal and boundary point of the base surface our exact, local equilibrium equations and dynamic boundary conditions are equivalent, as expected,...
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Predictions of cervical cancer identification by photonic method combined with machine learning
PublikacjaCervical 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...
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Some fundamental aspects of self-levitating sliding contact bearings and their practical implementations
PublikacjaIn this study, fundamental aspects and mechanisms of acoustic levitation together with governing equations are presented first. Then, the acoustic levitation phenomenon is considered as a new way to design air suspension systems capable of self-levitation. A particular emphasis is laid on journal bearings and their specific geometrical configuration. A practical feasibility of using acoustic levitation to separate contacting surfaces...
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Recent Advances in Polymer Nanocomposites: Unveiling the Frontier of Shape Memory and Self-Healing Properties—A Comprehensive Review
PublikacjaShape memory and self-healing polymer nanocomposites have attracted considerable attention due to their modifiable properties and promising applications. The incorporation of nanomaterials (polypyrrole, carboxyl methyl cellulose, carbon nanotubes, titania nanotubes, graphene, graphene oxide, mesoporous silica) into these polymers has significantly enhanced their performance, opening up new avenues for diverse applications. The...
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THE ONLINE APPLICATION AND E-LEARNING IN THE COMPETENCE-BASED MANAGEMENT IN PUBLIC ADMINISTRATION ORGANIZATIONS
PublikacjaThe integration of effective management of work-related processes and utilization of human resources potential leads to the development of organization. The purpose of this paper was to examine how the principles of competences-based management can be introduced to enhance organization’s effectiveness in human resources management. A model of assessment and development of competences-based management, embracing an online application...
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Concrete mix design using machine learning
PublikacjaDesigning a concrete mix is a process of synthesizing many components, it is not a simple process and requires extensive technical knowledge. The design process itself focuses on obtaining the required strength of concrete. Very often designing a concrete mix takes into account the need to maintain the proper water-demand and frost-resistance features. The parameters that influence the concrete class most significantly are the...
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Highly-Miniaturized Self-Quadruplexing Antenna Based on Substrate-Integrated Rectangular Cavity
PublikacjaThis paper introduces a novel self-quadruplexing antenna (SQA) architecture using a substrate-integrated rectangular cavity (SIRC) for compact size, wide-frequency re-designability, and high isolation responses. The proposed SQA is developed by engraving two U-shaped slots (USSs) on the top conductor of the SIRC. The USSs are excited by employing four microstrip feedlines to achieve self-quadruplexing antenna characteristics. The...
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Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublikacjaIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...
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Predicting emotion from color present in images and video excerpts by machine learning
PublikacjaThis 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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Deep learning based thermal image segmentation for laboratory animals tracking
PublikacjaAutomated systems for behaviour classification of laboratory animals are an attractive alternative to manual scoring. However, the proper animals separation and tracking, especially when they are in close contact, is the bottleneck of the behaviour analysis systems. In this paper, we propose a method for the segmentation of thermal images of laboratory rats that are in close contact during social behaviour tests. For this, we are...
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Supporting First Year Students Through Blended-Learning - Planning Effective Courses and Learner Support
PublikacjaHigher education has been actively encouraged to find more effective and flaxible delivery models to provide all students with access to good quality learning experiences. This paper describes students opinion about using e-learning techniques and their participation in courses provided in different ways as additional help and expectations of first year students.
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Model-Based Adaptive Machine Learning Approach in Concrete Mix Design
PublikacjaConcrete mix design is one of the most critical issues in concrete technology. This process aims to create a concrete mix which helps deliver concrete with desired features and quality. Contemporary requirements for concrete concern not only its structural properties, but also increasingly its production process and environmental friendliness, forcing concrete producers to use both chemically and technologically complex concrete...
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Open source solution LMS for supporting e-learning/blended learning engineers
PublikacjaW artykule zaprezentowano darmowe systemy zarządzania kształceniem na odległość wspomagające e-learningowe/mieszane nauczanie inżynierów. Pierwszy system TeleCAD został opracowany w ramach projektu Leonardo da Vinci (1998-2001). System TeleCAD był propozycją w projekcie V Ramowy CURE (2003-2006). W roku 2003 dzięki projektowi Leonardo da Vinci EMDEL (2001-2005) Centrum Edukacji Niestacjonarnej Politechniki Gdańskiej wybrało system...
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Self-organization in artificial environment.
PublikacjaPrzedstawiono rezultaty eksperymentów symulacyjnych procesów samoorganizacji zachodzących w środowisku programowym modelowania indywiduowego systemów fizycznych. Środowisko to ukierunkowane jest na modelowanie systemów składających się z wielkiej liczby poruszajacych się i oddziałujących na siebie jednostek.
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Influence of Self-Similar Traffic Type on Performance of QoS Routing Algorithms
PublikacjaProviding a Quality of Services (QoS) into current telecommunication networks based on packet technology is a big challenge nowadays. Network operators have to support a number of new services like voice or video which generate new type of traffic. This traffic serviced with QoS in consequence requires access to appropriate network resources. Additionally, new traffic type is mixed with older one, like best-effort. Analysis of...
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International Journal of Psychoanalytic Self Psychology
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Science of Diabetes Self-Management and Care
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Journal of Self-Governance and Management Economics
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LOS and NLOS identification in real indoor environment using deep learning approach
PublikacjaVisibility 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...
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An idea of an approach to self-testing of mixed signal systems based on a quadratic function stimulation
PublikacjaA new approach to self-testing of the analog parts of mixed-signal electronic systems controlled by microcontrollers equipped with an ADC and a DAC is presented. It is based on a BIST and a new fault diagnosis method. A novelty is the use of the DAC as a component of the BIST, allowing to generate a stimulating signal with a quadratic function shape. It contributes to a better extraction of information about the state of the circuit...
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Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools
PublikacjaA high monetary value of the construction projects is one of the reasons of frequent disputes between a general contractor (GC) and a client. A construction site is a unique, one-time, and single-product factory with many parties involved and dependent on each other. The organizational dependencies and their complexity make any fault or mistake propagate and influence the final result (delays, cost overruns). The constant will...
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Reinforcement Learning Algorithm and FDTD-based Simulation Applied to Schroeder Diffuser Design Optimization
PublikacjaThe aim of this paper is to propose a novel approach to the algorithmic design of Schroeder acoustic diffusers employing a deep learning optimization algorithm and a fitness function based on a computer simulation of the propagation of acoustic waves. The deep learning method employed for the research is a deep policy gradient algorithm. It is used as a tool for carrying out a sequential optimization process the goal of which is...
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Detecting Lombard Speech Using Deep Learning Approach
PublikacjaRobust Lombard speech-in-noise detecting is challenging. This study proposes a strategy to detect Lombard speech using a machine learning approach for applications such as public address systems that work in near real time. The paper starts with the background concerning the Lombard effect. Then, assumptions of the work performed for Lombard speech detection are outlined. The framework proposed combines convolutional neural networks...
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Distance learning trends: introducing new solutions to data analysis courses
PublikacjaNowadays 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,...
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Self-Association of Amphotericin B: Spontaneous Formation of Molecular Structures Responsible for the Toxic Side Effects of the Antibiotic
PublikacjaAmphotericin B (AmB) is a lifesaving antibiotic used to treat deep-seated mycotic infections. Both the pharmaceutical activity and highly toxic side effects of the drug rely on its interaction with biomembranes, which is governed by the molecular organization of AmB. In the present work we present detailed analysis of self-assembly of AmB molecules in different environments, interesting from the physiological standpoint, based...
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User -friendly E-learning Platform: a Case Study of a Design Thinking Approach Use
PublikacjaE-learning systems are very popular means to support the teaching process today. These systems are mainly used by universities as well as by commercial training centres. We analysed several popular e-learning platforms used in Polish universities and find them very unfriendly for the users. For this reason, the authors began the work on the creation of a new system that would be not only useful, but also usable for students, teachers...
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Self-Organization in Multi-Agent Systems Based on Examples of Modeling Economic Relationships between Agents
PublikacjaThe goal of the research was to observe and analyze self-organization patterns in Multi-Agent Systems (MAS) by modeling basic economic relationships between agents forming a closed loop of relations necessary for their survival. The paper describes a worked-out MAS including an example of a production cycle and used economic rules. A special focus is put on behavior rules and decision systems of an individual agent such as: product...
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Training of Deep Learning Models Using Synthetic Datasets
PublikacjaIn order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...
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Ireneusz Czarnowski Prof.
OsobyIRENEUSZ CZARNOWSKI is a graduate of the Faculty of Electrical Engineering at Gdynia Maritime University. He gained a doctoral degree in the field of computer science at Poznan University of Technology and a postdoctoral degree in the field of computer science at Wroclaw University of Science and Technology. Since 1998 is associated with Gdynia Maritime University, currently is a professor of computer science in the Department...
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A Proposed Machine Learning Model for Forecasting Impact of Traffic-Induced Vibrations on Buildings
PublikacjaTraffic-induced vibrations may cause various damages to buildings located near the road, including cracking of plaster, cracks in load-bearing elements or even collapse of the whole structure. Measurements of vibrations of real buildings are costly and laborious. Therefore the aim of the research is to propose the original numerical algorithm which allows us to predict, with high probability, the nega-tive dynamic impact of traffic-induced...
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Looking through the past: better knowledge retention for generative replay in continual learning
PublikacjaIn 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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Application of TMS320c67xx signal processors for SONIC-self-optimizing narrowband interference canceler
PublikacjaThe paper presents a laboratory system for testing active control algorithms of acoustics noise in ducts. An applied algorithm - self-optimizing narrowband interference canceller (SONIC), allows one to remove narrowband disturbances of constant or slowly time-varying frequencies. Example experimental results of using the laboratory system for supression of sinusoidal disturbance are described. An electronic part of the system was...
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Is participation in music festivals a self-expansion opportunity? Identity, self-perception, and the importance of music’s functions
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Robust and Efficient Machine Learning Algorithms for Visual Recognition
PublikacjaIn visual recognition, the task is to identify and localize all objects of interest in the input image. With the ubiquitous presence of visual data in modern days, the role of object recognition algorithms is becoming more significant than ever and ranges from autonomous driving to computer-aided diagnosis in medicine. Current models for visual recognition are dominated by models based on Convolutional Neural Networks (CNNs), which...
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Estimation of the minimal number of periodic points for smooth self-maps of odd dimensional real projective spaces
PublikacjaLet f be a smooth self-map of a closed connected manifold of dimension m⩾3. The authors introduced in [G. Graff, J. Jezierski, Minimizing the number of periodic points for smooth maps. Non-simply connected case, Topology Appl. 158 (3) (2011) 276-290] the topological invariant NJD_r[f], where r is a fixed natural number, which is equal to the minimal number of r-periodic points in the smooth homotopy class of f. In this paper smooth...
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Minimization of the number of periodic points for smooth self-maps of closed simply-connected 4-manifolds
PublikacjaLet M be a smooth closed simply-connected 4-dimensional manifold, f be a smooth self-map of M with fast grow of Lefschetz numbers and r be a product of different primes. The authors calculate the invariant equal to the minimal number of r-periodic points in the smooth homotopy class of f.
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Evaluation of Machine Learning Methods for the Experimental Classification and Clustering of Higher Education Institutions
PublikacjaHigher 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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Integrating Experience-Based Knowledge Representation and Machine Learning for Efficient Virtual Engineering Object Performance
PublikacjaMachine learning and Artificial Intelligence have grown significant attention from industry and academia during the past decade. The key reason behind interest is such technologies capabilities to revolutionize human life since they seamlessly integrate classical networks, networked objects and people to create more efficient environments. In this paper, the Knowledge Representation technique of Set of Experience...
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Microfluidically Frequency-Reconfigurable Self-Quadruplexing Antenna Based on Substrate Integrated Square-Cavity
PublikacjaIn this article, a novel concept of self-quadruplexing tunable antenna (SQTA) enabled by microfluidic channels is investigated. The operating channels are either filled with air or dielectric liquids to enable frequency tunability. The proposed SQTA is implemented on the substrate-integrated square-cavity (SISC). A swastika-shaped slot is milled on the top-surface of the SISC to create four quarter-mode resonators. The resonators...
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Self-optimizing narrowband interference canceller - can reference signal help?
PublikacjaSONIC (Self-Optimizing Narrowband Interference Canceller) is an acronym of the recently proposed active noise control algorithm with interesting adaptivity and robustness properties. SONIC is a purely feedback controller, capable of rejecting nonstationary sinusoidal disturbances (with time-varying amplitudes and/or frequencies) in the presence of plant (secondary path) uncertainties. We show that even though SONIC can work reliably...
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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublikacjaThis paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader's behavior must align for the best learning effects....
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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublikacjaThis paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader’s behavior must align for the best learning effects....
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublikacjaMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
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Optical method supported by machine learning for urinary tract infection detection and urosepsis risk assessment
PublikacjaThe study presents an optical method supported by machine learning for discriminating urinary tract infections from an infection capable of causing urosepsis. The method comprises spectra of spectroscopy measurement of artificial urine samples with bacteria from solid cultures of clinical E. coli strains. To provide a reliable classification of results assistance of 27 algorithms was tested. We proved that is possible to obtain...
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Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublikacjaBiochar 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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Thermodynamics and kinetics of amphotericin B self-association in aqueous solution characterized in molecular detail
PublikacjaAmphotericin B (AmB) is a potent but toxic drug commonly used to treat systemic mycoses. Its efficiency as a therapeutic agent depends on its ability to discriminate between mammalian and fungal cell membranes. The association of AmB monomers in an aqueous environment plays an important role in drug selectivity, as oligomers formed prior to membrane insertion – presumably dimers – are believed to act differently on fungal (ergosterol-rich)...
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Design and Analysis of Artificial Neural Network (ANN) Models for Achieving Self-Sustainability in Sanitation
PublikacjaThe present study investigates the potential of using fecal ash as an adsorbent and demonstrates a self-sustaining, optimized approach for urea recovery from wastewater streams. Fecal ash was prepared by heating synthetic feces to 500 °C and then processing it as an adsorbent for urea adsorption from synthetic urine. Since this adsorption approach based on fecal ash is a promising alternative for wastewater treatment, it increases...
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Can Evaluation Patterns Enable End Users to Evaluate the Quality of an e-learning System? An Exploratory Study.
PublikacjaThis paper presents the results of an exploratory study whose main aim is to verify if the Pattern-Based (PB) inspection technique enables end users to perform reliable evaluation of e-learning systems in real work-related settings. The study involved 13 Polish and Italian participants, who did not have an HCI background, but used e-learning platforms for didactic and/or administrative purposes. The study revealed that the participants...
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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublikacjaThis 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...
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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublikacjaThis 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...
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Strategic Flexibility as a Mediator in Relationship between Managerial Decisions and Organizational Learning: Ambidexterity Perspective
PublikacjaPurpose: The purpose of the article is to determine strategic flexibility in the relationship between managerial decisions and organizational learning. The analyses are conducted in the ambidexterity convection. Design/Methodology/Approach: The study was conducted at a textile company. The company is a leader in the textile recycling industry in Poland. Empirical data were collected using the PAPI technique. The survey questionnaire...
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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublikacjaTo improve the user's localization estimation in indoor and outdoor environment a novel radiolocalization system using deep learning dedicated to work both in indoor and outdoor environment is proposed. It is based on the radio signatures using radio signals of opportunity from LTE an WiFi networks. The measurements of channel state estimators from LTE network and from WiFi network are taken by using the developed application....
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Deep Learning Approaches in Histopathology
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e-Learning in Tourism Education
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Online Learning Based on Prototypes
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Distributed Learning with Data Reduction
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