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DNAffinity: a machine-learning approach to predict DNA binding affinities of transcription factors
PublikacjaWe 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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Przetwarzanie emocjonalne i scenariusze jego zastosowania w edukacji i e-edukacji
PublikacjaW pracy zbadano możliwości i celowość zastosowania mechanizmów i narzędzi przetwarzania emocjonalnego w e-edukacji. Wyróżniono i opisano szereg scenariuszy użycia technik afektywnych, zarówno w zastosowaniu komputerów do wspomagania tradycyjnych procesów edukacyjnych, jak i do nauczania za pośrednictwem środków elektronicznych. Jedne z najciekawszych zastosowań dotyczą poszukiwania optymalnej afektywnej przestrzeni uczenia się,...
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Intra-subject class-incremental deep learning approach for EEG-based imagined speech recognition
PublikacjaBrain–computer interfaces (BCIs) aim to decode brain signals and transform them into commands for device operation. The present study aimed to decode the brain activity during imagined speech. The BCI must identify imagined words within a given vocabulary and thus perform the requested action. A possible scenario when using this approach is the gradual addition of new words to the vocabulary using incremental learning methods....
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Love your mistakes!—they help you adapt to change. How do knowledge, collaboration and learning cultures foster organizational intelligence?
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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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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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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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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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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Giovanni Antonio Dosio a Napoli e un sepolcro per Stanislao Rescius, umanista e diplomatico polacco.
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Flow boiling of R1233zd(E) in a 3 mm vertical tube at moderate and high reduced pressures
PublikacjaThe results of flow boiling of R1233zd(E) in a 3 mm vertical stainless steel tube are presented at moderate and high saturation temperatures. Integral flow characteristics in the form of pressure drop and heat transfer coefficient are discussed for saturation temperatures ranging from 115 to 145 °C (corresponding reduced pressures from 0.2 to 0.7), mass velocity of 800 kg/m2s and heat flux of 20 kW/m2. All of the obtained heat...
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The DraC usher in Dr fimbriae biogenesis of uropathogenic E. coli Dr+ strains
PublikacjaBiogeneza fimbrii Dr kodowanych przez operon dra uropatogennych szczepów Escherichia coli (infekcje górnych dróg moczowych) odbywa się na bazie zakonserwowanego systemu sekrecji typu chaperone-usher. Funkcjonowanie powyższego systemu sekrecji opiera się na dwóch komponentach białkowych, periplazmatycznym chaperonie DraB i zewnątrzbłonowym kanale DraC. Białko DraB kontroluje proces składania podjednostek fimbrialnych DraE, natomiast...
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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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E-technologie w edukacji i terapii dzieci z autyzmem w Polsce
PublikacjaArtykuł dotyczy możliwości wsparcia technologiami informacyjnymi edukacji i terapii dzieci z za - burzeniami rozwoju ze spektrum autyzmu. Szczególna uwaga zostanie poświęcona aplikacjom przeznaczonym na urządzenia mobilne (tablety). Artykuł podsumowuje przesłanki zastosowania tabletów w pracy z dziećmi auty - stycznymi oraz pokazuje kategorie aplikacji, jakie mogą wspierać terapię i edukację dzieci. Zostały przedstawione wyniki...
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Evaluation of flavour profiles in e-cigarette refill solutions using gas chromatography–tandem mass spectrometry
PublikacjaMany flavour compounds that are present in e-liquids for e-cigarettes are responsible for specific tastes and smoking sensations for users. Data concerning content and specific types of flavours is often limited and unknown to users. The aim of the research was to define and compare flavour profiles of e-liquids with the same group taste from different manufacturers. Gas chromatography coupled with tandem mass spectrometry (GC–MS/MS)...
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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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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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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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Recent advancements in molecularly imprinted polymers for the removal of heavy metal ions and dyes
PublikacjaContamination set off by highly toxic metal ions and dyes is a big threat to the environment and living beings. Various industries like metal plating, mining, pesticides, battery manufacturing, and dyeing release metal ions and toxic dyes directly into the water. It is necessary to remove these toxic substances from the environment. Molecular imprinting technology (MIT) got a lot of attention in the last two decades because of...
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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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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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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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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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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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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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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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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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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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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...