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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublicationThis 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
PublicationMachine 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
PublicationThe 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
PublicationBiochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts,...
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The challenge of abandonment for the sustainable management of Palaearctic natural and semi-natural grasslands
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Characteristics of Superconducting State in Vanadium: the Eliashberg Equations and Semi-analytical Formulas
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Detonations in hydrogen-methane-air mixtures in semi confined flat channels
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An efficient approach to optimization of semi‐stable routing in multicommodity flow networks
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Semi-Markovian models of the process of technical state changes of technical objects.
PublicationNajistotniejszym problemem eksploatacji wszystkich obiektów technicznych (urządzeń) jest problem racjonalnego (a zwłaszcza optymalnego) decyzyjnego sterowania procesem zmian stanów technicznych tych obiektów. Sterowanie takie może być realizowane w przypadku zastosowania między innymi modelu wspomnianego procesu zmian stanów. Mając to na uwadze, w opracowaniu tym przedstawiono formalny opis procesu eksploatacji obiektów technicznych...
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Capturing semantics of semi-structured data using partial-order trees
PublicationW artykule zaprezentowano nowe podejście do problemu klasyfikacji danych semistrukturalnych. Kryteria klasyfikacji bazują na strukturze danych (zwanej typem danych) oraz na ich usytuowaniu w grafir danych (zwanym rolą danych). Zastosowano model OEM (Object Exchange Model) do reprezentacji nazy danych semistrukturalnych. Bazując na tej reprezentacji, definiuje się typy i role obiektów semistrukturalnych i organizuje się je w struktury...
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Can Evaluation Patterns Enable End Users to Evaluate the Quality of an e-learning System? An Exploratory Study.
PublicationThis 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
PublicationThis paper analyzes functions and structures of the memory that is an indispensable part of an Intelligent System of Decision-making (ISD), developed as a universal engine for autonomous robotics. A simplified way of processing and coding information in human cognitive processes is modelled and adopted for the use in autonomous systems. Based on such a knowledge structure, an artificial model of reality representation and a model...
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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublicationThis paper analyzes functions and structures of the memory that is an indispensable part of an Intelligent System of Decision-making (ISD), developed as a universal engine for autonomous robotics. A simplified way of processing and coding information in human cognitive processes is modelled and adopted for the use in autonomous systems. Based on such a knowledge structure, an artificial model of reality representation and a model...
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Strategic Flexibility as a Mediator in Relationship between Managerial Decisions and Organizational Learning: Ambidexterity Perspective
PublicationPurpose: 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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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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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublicationTo 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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Noise profiling for speech enhancement employing machine learning models
PublicationThis paper aims to propose a noise profiling method that can be performed in near real-time based on machine learning (ML). To address challenges related to noise profiling effectively, we start with a critical review of the literature background. Then, we outline the experiment performed consisting of two parts. The first part concerns the noise recognition model built upon several baseline classifiers and noise signal features...
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Remote learning among students with and without reading difficulties during the initial stages of the COVID-19 pandemic
PublicationThis article presents the results of a survey on yet under-researched aspects of remote learning and learning difficulties in higher education during the initial stage (March – June 2020) of the COVID-19 pandemic. A total of 2182 students from University of Warsaw in Poland completed a two-part questionnaire regarding academic achievements in the academic year 2019/2020, living conditions and stress related to learning and pandemic,...
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Systemy z Uczeniem Maszynowym / Systems with Machine Learning
e-Learning Courses -
Perspektywy wykorzystania technologii internetowych typu E-learning w dydaktyce szkół wyższych.
PublicationArtykuł dotyczy nauczania przez Internet na poziomie uniwersyteckim. Zaprezentowany został model wirtualnego uniwersytetu, który obejmuje materiały dydaktyczne, komunikację, egzaminy i organizację. Artykuł koncentruje się na technicznych zagadnieniach. Przeanalizowano także wpływ wykorzystania technologii E-learning na różne aspekty życia wyższej uczelni.
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Big Data from Sensor Network via Internet of Things to Edge Deep Learning for Smart City
PublicationData from a physical world is sampled by sensor networks, and then streams of Big Data are sent to cloud hosts to support decision making by deep learning software. In a smart city, some tasks may be assigned to smart devices of the Internet of Things for performing edge computing. Besides, a part of workload of calculations can be transferred to the cloud hosts. This paper proposes benchmarks for division tasks between an edge...
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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublicationThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
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Real and Virtual Instruments in Machine Learning – Training and Comparison of Classification Results
PublicationThe continuous growth of the computing power of processors, as well as the fact that computational clusters can be created from combined machines, allows for increasing the complexity of algorithms that can be trained. The process, however, requires expanding the basis of the training sets. One of the main obstacles in music classification is the lack of high-quality, real-life recording database for every instrument with a variety...
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Application of theory of semi-Markov processes to determining distribution of probabilistic process of marine accidents resulting from colission of ships
PublicationIn this paper is presented possible application of the theory of semi-Markov processes to elaborating an eight-state model of the process of occurrence of serviceability state and unserviceability states of sea-going ships making critical manoeuvres during their entering and leaving the ports. In the analysis it was taken into account that sea-going ships are in service for a very long time t (t → ∞). The model was elaborated to...
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Możliwość oszacowania niezawodności silników o zapłonie samoczynnym z zastosowaniem teorii procesów semi-Markowa oraz podejmowania decyzji eksploatacyjnych z uwzględnieniem wiarygodności diagnozy o stanie technicznym tego rodzaju silników spalinowych = Possibility of estimating the reliability of diesel engines by applying the theory of semi-Markov processes and making operational decisions by considering reliability of diagnosis on technical state of this sort of combustion engines/
PublicationThe paper presents semi-Markov models of technical state transitions for diesel engines, useful for determining reliability of the engines. A possibility of application of a three-state model with a simplified matrix function, or even a two-state model, to determine reliability of the engines, has been described herein on examples of known from literature semi-Markov models, for the case when appropriate diagnosing systems (SDG)...
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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublicationIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublicationLiquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...
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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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Amplitude-distance spectroscopy in semi-contact mode
Open Research DataSince it was invented by Binnig et al. in 1986, atomic force microscopy (AFM) plays a key role in science and technology at the nanoscale. AFM is a microscopic technique that visualizes the surface topography using the attractive and repulsive forces of interaction between several atoms (in theory) of a blade attached to the end of the probe lever and...
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Fingerprint structure studies with semi-contact AFM
Open Research DataThe work [1] presents many, sometimes even surprising examples of the use of atomic force microscopy in modern forensics. Some of them are projectile tests using the characteristic scratch patterns created by the firing pin on the primer. There are more and more suggestions in the literature for the use of atomic force microscopy in dactyloscopy [2]....
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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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Learning & Memory
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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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