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Wyniki wyszukiwania dla: BLENDED E-LEARNING
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Love your mistakes!—they help you adapt to change. How do knowledge, collaboration and learning cultures foster organizational intelligence?
PublikacjaPurpose: 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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Technology-Enhanced Environmental Learning: Co-design of Educational Mobile Application Case
PublikacjaThe process of co-creating an educational mobile application to support environmentally friendly behavior is presented in this paper. The research material consisted of quantitative data collected on the application during the first testing phase by early adopters. The results suggest that the most frequently used features of the app were related to transport and educational activities. While women tended to split their time between...
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Rigorous numerics for critical orbits in the quadratic family
PublikacjaWe develop algorithms and techniques to compute rigorous bounds for finite pieces of orbits of the critical points, for intervals of parameter values, in the quadratic family of one-dimensional maps fa(x)=a−x2. We illustrate the effectiveness of our approach by constructing a dynamically defined partition P of the parameter interval Ω=[1.4,2] into almost 4 million subintervals, for each of which we compute to high precision the...
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The effects of relational and psychological capital on work engagement: the mediation of learning goal orientation
PublikacjaPurpose – This paper proposes a research model in which learning goal orientation (LGO) mediates the impacts of relational capital and psychological capital (PsyCap) on work engagement. Design/methodology/approach – Data obtained from 475 managers and employees in the manufacturing and service industries in Poland were utilized to assess the linkages given above. Common method variance was controlled by the unmeasured latent method...
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Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublikacjaCatheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified...
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Optimizing Medical Personnel Speech Recognition Models Using Speech Synthesis and Reinforcement Learning
PublikacjaText-to-Speech synthesis (TTS) can be used to generate training data for building Automatic Speech Recognition models (ASR). Access to medical speech data is because it is sensitive data that is difficult to obtain for privacy reasons; TTS can help expand the data set. Speech can be synthesized by mimicking different accents, dialects, and speaking styles that may occur in a medical language. Reinforcement Learning (RL), in the...
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Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
PublikacjaBreast cancer is the most frequent female cancer, with a considerable disease burden and high mortality. Early diagnosis with screening mammography might be facilitated by automated systems supported by deep learning artificial intelligence. We propose a model based on a weakly supervised Clustering-constrained Attention Multiple Instance Learning (CLAM) classifier able to train under data scarcity effectively. We used a private...
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Koło naukowe CJO - Tech-Enhanced English Learning (TEEL)
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Assessment Of the Relevance of Best Practices in The Development of Medical R&D Projects Based on Machine Learning
PublikacjaMachine learning has emerged as a fundamental tool for numerous endeavors within health informatics, bioinformatics, and medicine. However, novices among biomedical researchers and IT developers frequently lack the requisite experience to effectively execute a machine learning project, thereby increasing the likelihood of adopting erroneous practices that may result in common pitfalls or overly optimistic predictions. The paper...
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Automated detection of pronunciation errors in non-native English speech employing deep learning
PublikacjaDespite significant advances in recent years, the existing Computer-Assisted Pronunciation Training (CAPT) methods detect pronunciation errors with a relatively low accuracy (precision of 60% at 40%-80% recall). This Ph.D. work proposes novel deep learning methods for detecting pronunciation errors in non-native (L2) English speech, outperforming the state-of-the-art method in AUC metric (Area under the Curve) by 41%, i.e., from...
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An Adaptive Network Model for a Double Bias Perspective on Learning from Mistakes within Organizations
PublikacjaAlthough making mistakes is a crucial part of learning, it is still often being avoided in companies as it is considered as a shameful incident. This goes hand in hand with a mindset of a boss who dominantly believes that mistakes usually have negative consequences and therefore avoids them by only accepting simple tasks. Thus, there is no mechanism to learn from mistakes. Employees working for and being influenced by such a boss...
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Comprehensive determination of flavouring additives and nicotine in e-cigarette refill solutions. Part II: Gas-chromatography–mass spectrometry analysis
PublikacjaFlavouring compounds are an essential part of e-liquid products for cigarettes. In general, they are regarded as safe for ingestion, but they may have unrecognized risks when they are inhaled. In some cases, manufactures do not currently abide by the Tobacco Products Directive (2014/40/EU) and do not declare the detailed contents of e-liquids on their labels. To help evaluate the health impact of flavouring substances, there is...
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Incorporating Iris, Fingerprint and Face Biometric for Fraud Prevention in e-Passports Using Fuzzy Vault
PublikacjaA unified frame work which provides a higher security level to e-passports is proposed. This framework integrates face, iris and fingerprint images. It involves three layers of security: the first layer maps a biometric image to another biometric image which is called biostego image. Three mapping schemes are proposed: the first scheme maps single biometric image to single biostego image, the second scheme maps dual biometric images...
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Computational Analysis of Transformational Organisational Change with Focus on Organisational Culture and Organisational Learning: An Adaptive Dynamical Systems Modeling Approach
PublikacjaTransformative Organisational Change becomes more and more significant both practically and academically, especially in the context of organisational culture and learning. However computational modeling and formalization of organisational change and learning processes are still largely unexplored. This chapter aims to provide an adaptive network model of transformative organisational change and translate a selection of organisational...
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New approach for e-cigarette aerosol collection by an original automatic aerosol generator utilizing melt-blown non-woven fabric
PublikacjaCurrently, there is lack of standardized conditions for the collection and analysis of e-cigarette (EC) aerosol. Considering the urgent need for the development of these guidelines, a procedure for EC aerosol analysis was developed. A novel automatic e-cigarette aerosol generator was designed. For the first time, melt-blown non-woven fabric was applied for the effective uptake of compounds released from vaporized e-liquid. The...
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Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublikacjaThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
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AUTOMATIC LEARNING OF STRATEGY AND RULES IN CARD GAMES USING IMAGE FROM CAMERA
PublikacjaBelow work tries to answer a question: if it is possible to replace real human with computer system in social games. As a subject for experiments, card games were chosen, because they require a lot of player interaction (playing and taking cards), while their rules are easy to present in form of clear list of statements. Such a system, should allow real players to play without constant worrying about guiding or helping computer...
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Blended natural and synthetic coagulants for the COD and BOD removal from surface water; optimization by response surface methodology: The case of Gibe river
PublikacjaA novel wastewater treatment method is presented in this study. It combines natural coagulants derived from watermelon seeds with the commonly used synthetic coagulant alum. This research demonstrates a remarkable synergy between these two coagulants in removing nutrients from Gibe River wastewater. Combining natural and chemical coagulants often improves water treatment by enhancing particle destabilization, accelerating floc...
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Broadband communication solutions for maritime ITSs: Wider and faster deployment of new e-navigation services
Publikacjan its initial part, the paper presents an overview of popular technologies and systems currently developed or employed in maritime communication. These solutions are used to provide both ship-to-ship and ship-to-shore communication for the purpose of supporting specific services, often dedicated to maritime safety and e-navigation. Utility of such communication systems have been thoroughly verified over the years and their strengths...
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Ewolucyjny rozwój uczelnianej infrastruktury komunikacyjno-informacyjnej na potrzeby e-uczelni
PublikacjaStosowane i proponowane rozwiązania w obszarze technologii informacyjnych stwarzają szerokie możliwości w rozwoju i wdrażaniu systemów komunikacyjno-informacyjnych wspomagających i usprawniających specyficzną działalności uczelni a szczególnie wspierających e-Uczelnię. Wymaga to jednak wprowadzenia zmian w infrastrukturze technicznej i organizacji pracy. W artykule rozpa-trzono możliwości wykorzystania uczelnianych infrastruktur...
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Visual Content Learning in a Cognitive Vision Platform for Hazard Control (CVP-HC)
PublikacjaThis work is part of an effort for the development of a Cognitive Vision Platform for Hazard Control (CVP-HC) for applications in industrial workplaces, adaptable to a wide range of environments. The paper focuses on hazards resulted from the nonuse of personal protective equipment (PPE). Given the results of previous analysis of supervised techniques for the problem of classification of a few PPE (boots, hard hats, and gloves...
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Phage therapy as a novel strategy in the treatment of urinary tract infections caused by E. coli
PublikacjaUrinary tract infections (UTIs) are regarded as one of the most common bacterial infections affecting millions of people, in all age groups, annually in the world. The major causative agent of complicated and uncomplicated UTIs are uropathogenic E. coli strains (UPECs). Huge problems with infections of this type are their chronicity and periodic recurrences. Other disadvantages that are associated with UTIs are accompanying complications...
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Przyjazne aplikacje dla dzieci z autyzmem – e-edukacja na poziomie przedszkolnym
PublikacjaArtykuł dotyczy możliwości wykorzystania aplikacji na tablety do wspomagania terapii dzieci z zaburzeniami rozwojowymi ze spektrum autyzmu. Przedstawia studium przypadku skutecznego zastosowania e-technologii w kształceniu specjalnym na poziomie przedszkolnym. Artykuł opisuje zestaw aplikacji edukacyjnych o nazwie Przyjazne Aplikacje, których celem jest wspieranie terapii dzieci z autyzmem opartej o stosowaną...
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Fast Machine-Learning-Enabled Size Reduction of Microwave Components Using Response Features
PublikacjaAchieving compact size has emerged as a key consideration in modern microwave design. While structural miniaturization can be accomplished through judicious circuit architecture selection, precise parameter tuning is equally vital to minimize physical dimensions while meeting stringent performance requirements for electrical characteristics. Due to the intricate nature of compact structures, global optimization is recommended,...
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Modeling lignin extraction with ionic liquids using machine learning approach
PublikacjaLignin, next to cellulose, is the second most common natural biopolymer on Earth, containing a third of the organic carbon in the biosphere. For many years, lignin was perceived as waste when obtaining cellulose and hemicellulose and used as a biofuel for the production of bioenergy. However, recently, lignin has been considered a renewable raw material for the production of chemicals and materials to replace petrochemical resources....
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The supramolecular organization of self-assembling chlorosomal bacteriochlorophyll c, d, or e mimics
PublikacjaBacteriochlorophylls (BChls) c, d, and e are the main light-harvesting pigments of green photosynthetic bacteria that self-assemble into nanostructures within the chlorosomes forming the most efficient antennas of photosynthetic organisms. All previous models of the chlorosomal antennae, which are quite controversially discussed because no single crystals could be grown so far from these organelles, involve a strong hydrogen-bonding...
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Arte e Género / Sztuka i płeć
PublikacjaKatalog wystawy towarzyszącej Konferencji na temat równości płci. Malarstwo i rysunek inspirowane tematyką konferencji przentowali artyści z Portugalii, Hiszpanii i z Polski. Jacek Krenz przedstawił cykl 7 akwarel pt. ''ENCOUNTER, Painting Haiku''.
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A longitudinal study of e-commerce diversity in Europe
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Factors affecting credibility of e-shops in Poland
PublikacjaArtykuł stanowi kontynuację tematu podjętego w poprzednich pracach autora nt. czynników wpływających na wiarygodność detalicznych sklepów internetowych. Przedstawiono w nim wstępne wyniki badań dokonanych przez autora. W artykule wskazano również na związki pomiędzy modelami wiarygodności i powszechnie stosowanymi modelami jakości.
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e-JABAT – An Implementation of the Web-Based A-Team
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An evaluation of sucrose as a possible contaminant in e-liquids for electronic cigarettes by hydrophilic interaction liquid chromatography–tandem mass spectrometry
PublikacjaThe influence of sucrose combustion products on smoking and nicotine addiction is still controversial because the presence of the sucrose may be treated as a source of aldehydes and organic acids. In e-liquids used as refills for electronic cigarettes, which are made primarily of poly(propylene glycol), glycerine and ethanol, sucrose may be present at trace levels, and its impact on mainstream smoke formation, and hence on human...
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Optical method supported by machine learning for dynamics of C‐reactive protein concentrations changes detection in biological matrix samples
PublikacjaIn this article we present the novel spectroscopy method supported with machine learning for real-time detection of infectious agents in wastewater. In the case of infectious diseases, wastewater monitoring can be used to detect the presence of inflammation biomarkers, such as the proposed C-reactive protein, for monitoring inflammatory conditions and mass screening during epidemics for early detection in communities of concern,...
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CFD COUPLING OF VOF MODEL WITH ARRHENIUS EQUATION FOR ANALYSIS OF LASER-INDUCED THERMAL DEACTIVATION OF E. COLI
PublikacjaUnderstanding bacterial deactivation at the micro-scale, particularly with E. coli, is crucial for advancing microbiology and has promising applications in biomedical research. In this research contribution, we investigate the thermal inactivation of E. coli bacteria using gold nanoparticles irradiated by a green 1-W laser within a microfluidic chamber. The microfluidic device comprises a fluidic chamber filled with a thin film...
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Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning
PublikacjaIn this work, we investigate exemplar-free class incremental learning (CIL) with knowledge distillation (KD) as a regularization strategy, aiming to prevent forgetting. KDbased methods are successfully used in CIL, but they often struggle to regularize the model without access to exemplars of the training data from previous tasks. Our analysis reveals that this issue originates from substantial representation shifts in the teacher...
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Pursuing the Deep-Learning-Based Classification of Exposed and Imagined Colors from EEG
PublikacjaEEG-based brain-computer interfaces are systems aiming to integrate disabled people into their environments. Nevertheless, their control could not be intuitive or depend on an active external stimulator to generate the responses for interacting with it. Targeting the second issue, a novel paradigm is explored in this paper, which depends on a passive stimulus by measuring the EEG responses of a subject to the primary colors (red,...
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Chiral Pyrazolo[4,3-e][1,2,4]triazine Sulfonamides—Their Biological Activity, Lipophilicity, Protein Affinity, and Metabolic Transformations
PublikacjaReferring to our previous laboratory results related to the tyrosinase and urease inhibition by pyrazolo[4,3-e][1,2,4]triazine sulfonamides, we examined here in silico the mechanism of action at the molecular level of the investigated pyrazolotriazine sulfonamides by the molecular docking method. The studied compounds being evaluated for their cytotoxic effect against cancer cell lines (MCF-7, K-562) and for recombinant Abl and...
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1 - E-TECH: Online education in practice for teachers. Foundations
Kursy OnlineThis module has been designed to help teachers to get the very best out of online learning education. We've created it to support many aspects of your learning online. The aim is to provide skills to create and engage with your teaching materials online. After completion the course you can download your Certifacte.
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Type III Responses to Transient Inputs in Hybrid Nonlinear Neuron Models
PublikacjaExperimental characterization of neuronal dynamics involves recording both of spontaneous activity patterns and of responses to transient and sustained inputs. While much theoretical attention has been devoted to the spontaneous activity of neurons, less is known about the dynamic mechanisms shaping their responses to transient inputs, although these bear significant physiological relevance. Here, we study responses to transient...
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Wiarygodność i zaufanie jako fundamenty budowania relacji w e-biznesie
PublikacjaInternet będący dla niektórych synonimem nowoczesności, dla innych jego użytkowników stał się codziennym narzędziem pracy, służącym do poszukiwania informacji o potencjalnych parterach biznesowych oraz komunikowania się z nimi. Z tego powodu odpowiedź na pytanie jak oceniana jest wiarygodność informacji internetowej, oraz jakim modyfikacjom podlega komunikacja zapośredniczona przez komputer (computer mediated communication) w porównaniu...
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Patomechanizm zakażeń dróg moczowych wywoływanych przez uropatogenne szczepy E. coli
PublikacjaZakażenia układu moczowego (ZUM) to jedne z najczęstszych i najbardziej powszechnych infekcji bakteryjnych, dotykających każdego roku nawet 150 milionów ludzi na świecie. Problem z tego typu infekcjami wynika z przewlekłości choroby, nawrotów i wzrastającej lekooporności powodujących je patogenów. Uropatogenne szczepy E. coli (UPEC) są głównym czynnikiem przyczynowym ZUM. Bakterie tej grupy zawierają wiele czynników adhezyjnych...
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Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublikacjaThis paper focuses on convolution neural network quantization problem. The quantization has a distinct stage of data conversion from floating-point into integer-point numbers. In general, the process of quantization is associated with the reduction of the matrix dimension via limited precision of the numbers. However, the training and inference stages of deep learning neural network are limited by the space of the memory and a...
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Improving platelet‐RNA‐based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification
PublikacjaLiquid biopsy demonstrates excellent potential in patient management by providing a minimally invasive and cost-effective approach to detecting and monitoring cancer, even at its early stages. Due to the complexity of liquid biopsy data, machine-learning techniques are increasingly gaining attention in sample analysis, especially for multidimensional data such as RNA expression profiles. Yet, there is no agreement in the community...
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Note on universal algoritms for learning theory
PublikacjaW 2001 Cucker i Smale zaproponowali nowe podejście do teorii uczenia się w oparciu o problematykę teorii aproksymacji.W 2005 i 2007 Bivev, Cohen, Dahmen, DeVore i Temlyakov opublikowali dwie prace z teorii uczenia się. W omawianej publikacji uogólniliśmy ich rezultaty jednocześnie upraszczając dowody.
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Structure and Randomness in Planning and Reinforcement Learning
PublikacjaPlanning in large state spaces inevitably needs to balance the depth and breadth of the search. It has a crucial impact on the performance of a planner and most manage this interplay implicitly. We present a novel method \textit{Shoot Tree Search (STS)}, which makes it possible to control this trade-off more explicitly. Our algorithm can be understood as an interpolation between two celebrated search mechanisms: MCTS and random...
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A consensus-based approach to the distributed learning
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An agent-based framework for distributed learning
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Prototype selection algorithms for distributed learning
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Moduł e-Doręczeń w EZD
WydarzeniaCentrum Obiegu Dokumentów zaprasza na szkolenie online z zakresu obsługi modułu e-Doręczeń w systemie EZD.
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Moduł e-Doręczeń w EZD
WydarzeniaCentrum Obiegu Dokumentów zaprasza na szkolenie online z zakresu obsługi modułu e-Doręczeń w systemie EZD.
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Speed estimation of a car at impact with a W-beam guardrail using numerical simulations and machine learning
PublikacjaThis paper aimed at developing a new method of estimating the impact speed of a passenger car at the moment of a crash into a W-beam road safety barrier. The determination of such a speed based on the accident outcomes is demanding, because often there is no access to full accident data. However, accurate determination of the impact speed is one of the key elements in the reconstruction of road accidents. A machine learning algorithm...