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The features of steel surface hardening with high energy heating by high frequency currents and shower cooling
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Numerical Modeling of Steel Surface Hardening in the Process of High Energy Heating by High Frequency Currents
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Solubility of dapsone in deep eutectic solvents: Experimental analysis, molecular insights and machine learning predictions
PublicationBackground. Dapsone (DAP) is an anti-inflammatory and antimicrobial active pharmaceutical ingredient used to treat, e.g., AIDS-related diseases. However, low solubility is a feature hampering its efficient use. Objectives. First, deep eutectic solvents...
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KABA Subject Heading Language as the Main Resource Subject Organization Tool in a Semantic Knowledge Base
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Novel PCSE-based approach of inclined structures geometry analysis on the example of the Leaning Tower of Pisa
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Technical Aspects and Energy Effects of Waste Heat Recovery from District Heating Boiler Slag
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Serial depletion of Baltic herring since the Viking Age revealed by ancient DNA and population genomics
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SELECTING A REPRESENTATIVE DATA SET OF THE REQUIRED SIZE USING THE AGENT-BASED POPULATION LEARNING ALGORITHM
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Diversity of Students’ Unethical Behaviors in Online Learning Amid COVID-19 Pandemic: An Exploratory Analysis
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Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study
PublicationThis study explores the edaravone solubility space encompassing both neat and binary dissolution media. Efforts were made to reveal the inherent concentration limits of common pure and mixed solvents. For this purpose, the published solubility data of the title drug were scrupulously inspected and cured, which made the dataset consistent and coherent. However, the lack of some important types of solvents in the collection called...
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Errorless Learning as a method of neuropsychological rehabilitation of individuals suffering from dementia in the course of Alzheimer’s disease
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Fractional-Order PID Controller (FOPID)-Based Iterative Learning Control for a Nonlinear Boiler System
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Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance
PublicationIdentification of active electrodes that record task-relevant neurophysiological activity is needed for clinical and industrial applications as well as for investigating brain functions. We developed an unsupervised, fully automated approach to classify active electrodes showing event-related intracranial EEG (iEEG) responses from 115 patients performing a free recall verbal memory task. Our approach employed new interpretable...
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Size effect in concrete beams under bending – influence of the boundary layer and the numerical description of cracks
PublicationIn the paper the size effect phenomenon in concrete is analysed. The results of numerical simulations of using FEM on geometrically similar un-notched and notched concrete beams under bending are presented. Concrete beams of four different sizes and five different notch heights under three-point bending test were simulated. In total 18 beams were analysed. Two approaches were used to describe cracks in concrete. First, eXtended...
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Project-Based Learning as a Method for Interdisciplinary Adaptation to Climate Change—Reda Valley Case Study
PublicationThe challenges of the global labour market require university authorities to extend traditional forms of education into more innovative and effective solutions. Project-based learning (PjBL) is one of highly effective methods for acquiring knowledge and teaching “soft” skills to future employees. This article describes an experimental use of PjBL at a university with a long history of teaching based on traditional methods—the Gdansk...
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Impact performance of novel multi-layered prepacked aggregate fibrous composites under compression and bending
PublicationMulti-layered Prepacked aggregate fibrous composite (MLPAFC) is a new type of concrete, which is prepared in two subsequent stages of aggregate-fibre skeleton prepacking and cementitious grouting. In this study, ten MLPAFC mixtures were prepared in three subsequent layers incorporating different contents of four different types of steel fibres. Long and short hooked-end and crimped steel fibers were adopted with 3.0 and 1.5% dosages...
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Old-timer Vehicle - Braking Efficiency Measurement at Vehicle Inspection Stations and Roadworthiness Validity Certificate.
PublicationObtaining the Roadworthiness Validity Certificate for an old-timer vehicle involves an appropriate test performance, namely, "Old-timer Vehicle Technical Specification Compliance Test". It seems obvious that this kind of test should include a considerable checklist, however, the current legal regulations connected with this test are not specific enough. One of the certificates issued on this test results is "Old-timer Vehicle Technical...
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Guest editorial: learning, scheduling, resource optimization, and evolution in smart artificial systems: challenges and support
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Supporting First Year Students Through Blended-Learning - Planning Effective Courses and Learner Support
PublicationHigher 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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Post-failure fracture surface analysis of notched steel specimens after bending-torsion fatigue
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Prediction of the structures of proteins with the UNRES force field, including dynamic formation and breaking of disulfide bonds
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Shot peening intensity effect on bending fatigue strength of S235, S355 and P460 structural steels
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Comparison of classical Winter's bracing requirements of compressedtruss chord with stability analysis of 3D truss-model
PublicationMost code requirements concerning bracing are based on principles developed by Winter. The present research is devoted tostudy a lateral buckling of truss with linear elastic side supports. The classical Winter's model of truss chord in the case ofout of the truss plane buckling is compared with nonlinear analysis of 3D truss model. Full bracing condition, that permitsthe truss chord to support load level corresponding to an unbraced...
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Efficiency of Biomass Energy used for Heating Purposes in a Residential Building in Comparison with other Energy Sources
PublicationThis paper discusses the results of analyses investigating the energy efficiency of biomass in comparison with other popular energy carriers used for heating, ventilation and water heating in residential buildings. The compared energy sources were lignite, natural gas, heating oil and electricity produced by conventional and integrated power generation plants. The most efficient variant relying on biomass and the least efficient...
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Transcriptional profile of in vitro expanded human epidermal progenitor cells for the treatment of non-healing wounds
PublicationBackground Epidermal progenitor cells (EPCs) have been under extensive investigation due to their increasing potential of application in medicine and biotechnology. Cultured human EPCs are used in the treatment of chronic wounds and have recently became a target for gene therapy and toxicological studies. One of the challenges in EPCs culture is to provide a high number of undifferentiated, progenitor cells displaying high viability...
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Three-point bending test of sandwich beams supporting the GFRP footbridge design process - validation
PublicationSome selected aspects concerning material and construction design issues for pedestrian footbridge made of GFRP composite materials are elaborated in this paper. The analysis is focused on validation tests, which are particularly important because of the advanced technology and materials that are used for this innovative bridge. The considered footbridge is a sandwich-type shell structure comprising of PET foam core and outer skins...
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When Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharing
PublicationABSTRACT In this article, we introduce a novel concept combining neural network technology and Decisional DNA for knowledge representation and sharing. Instead of using traditional machine learning and knowledge discovery methods, this approach explores the way of knowledge extraction through deep learning processes based on a domain’s past decisional events captured by Decisional DNA. We compare our approach with kNN (k-nearest...
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Bacterial cellulose in the field of wound healing and regenerative medicine of skin: recent trends and future prospectives
PublicationIn this overview, we focused on the bacterial cellulose (BC) applications, described in recently published scientific papers, in the field of skin regenerative medicine and wound care industry. Bacterial cellulose was proven to be biocompatible with living tissues. Moreover, its mechanical properties and porous structure are considered to be suitable for biomedical applications. It is due to the fact that porous structure of bacterial...
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A ROLE PLAYING GAME NAME GENERATOR LEARNING ITS CREATIVITY FROM ARKADIA MUD PLAYERS
PublicationThe paper proposes an approach to creative generation of new names for the purposes of Role Playing Games in fantasy realms. The generator based on an existing database of na mes is able to propose a set of new names with regard to demanded attributes, such as: length of the name, sex and race of the character, a given p hrase as the origin for the generated name as well as subjective evaluations from former users. The software...
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Neural network simulator's application to reference performance determination of turbine blading in the heat-flow diagnostics.
PublicationIn the paper, the possibility of application of artificial neural networks to perform the fluid flow calculations through both damaged and undamaged turbine blading was investigated. Preliminary results are presented and show the potentiality of further development of the method for the purpose of heat-flow diagnostics.
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Fully Separated Flow Control Using DBD Plasma Actuators Located at the Leading Edge of an Airfoil
PublicationIn the framework of the PLASMAERO European project, experiments were conducted to investigate the authority of surface DBD plasma actuators to alter a fully separated flow around an airfoil in order to improve its aerodynamic performances in its natural stall regime. In this paper, unsteady excitation control is more specifically investigated. The key control parameter studied here is the burst frequency which periodically imposes...
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Orientation-aware ship detection via a rotation feature decoupling supported deep learning approach
PublicationShip imaging position plays an important role in visual navigation, and thus significant focuses have been paid to accurately extract ship imaging positions in maritime videos. Previous studies are mainly conducted in the horizontal ship detection manner from maritime image sequences. This can lead to unsatisfied ship detection performance due to that some background pixels maybe wrongly identified as ship contours. To address...
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Development and evaluation of RADA-PDGF2 self-assembling peptide hydrogel for enhanced skin wound healing
PublicationBackground: Wound healing complications affect numerous patients each year, creating significant economic and medical challenges. Currently, available methods are not fully effective in the treatment of chronic or complicated wounds; thus, new methods are constantly sought. Our previous studies showed that a peptide designated as PDGF2 derived from PDGF-BB could be a promising drug candidate for wound treatment and that RADA16-I...
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Unsupervised Learning for Biomechanical Data Using Self-organising Maps, an Approach for Temporomandibular Joint Analysis
PublicationWe proposed to apply a specific machine learning technique called Self-Organising Maps (SOM) to identify similarities in the performance of muscles around human temporomandibular joint (TMJ). The performance was assessed by measuring muscle activation with the use of surface electromyography (sEMG). SOM algorithm used in the study was able to find clusters of data in sEMG test results. The SOM analysis was based on processed sEMG...
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Predicting seismic response of SMRFs founded on different soil types using machine learning techniques
PublicationPredicting the Maximum Interstory Drift Ratio (M-IDR) of Steel Moment-Resisting Frames (SMRFs) is a useful tool for designers to approximately evaluate the vulnerability of SMRFs. This study aims to explore supervised Machine Learning (ML) algorithms to build a surrogate prediction model for SMRFs to reduce the need for complex modeling. For this purpose, twenty well-known ML algorithms implemented in Python software are trained...
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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublicationBiomass management in terms of energy consumption optimization has become a recent challenge for developed countries. Nevertheless, the multiplicity of materials and operating parameters controlling energy consumption in wastewater treatment plants necessitates the need for sophisticated well-organized disciplines in order to minimize energy consumption and dissipation. Sewage sludge (SS) disposal management is the key stage of...
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Adaptive Dynamical Systems Modelling of Transformational Organizational Change: with Focus on Organizational Culture and Organizational Learning
PublicationTransformative Organizational Change becomes more and more significant both practically and academically, especially in the context of organizational culture and learning. However computational modeling and a formalization of organizational change and learning processes are still largely unexplored. This paper aims to provide an adaptive network model of transformative organizational change and translate a selection of organizational...
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Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublicationAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
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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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Adaptive Dynamical Systems Modelling of Transformational Organizational Change with Focus on Organizational Culture and Organizational Learning
PublicationTransformative Organizational Change becomes more and more significant both practically and academically, especially in the context of organizational culture and learning. However computational modeling and a formalization of organizational change and learning processes are still largely unexplored. This paper aims to provide an adaptive network model of transformative organizational change and translate a selection of organizational...
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Tacit knowledge acquisition & sharing, and its influence on innovations: A Polish/US cross-country study
PublicationThis study measures the relationship between tacit knowledge sharing and innovation in the Polish (n=350) and US (n=379) IT industries. Conceptually, the study identifies the potential sources of tacit knowledge development by individuals. That is, the study examines how “learning by doing” and “learning by interaction” lead to a willingness to share knowledge and, as a consequence, to support process and product/service innovation....
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Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
PublicationBreast 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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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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Thermal Images Analysis Methods using Deep Learning Techniques for the Needs of Remote Medical Diagnostics
PublicationRemote medical diagnostic solutions have recently gained more importance due to global demographic shifts and play a key role in evaluation of health status during epidemic. Contactless estimation of vital signs with image processing techniques is especially important since it allows for obtaining health status without the use of additional sensors. Thermography enables us to reveal additional details, imperceptible in images acquired...
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Integrating Experience-Based Knowledge Representation and Machine Learning for Efficient Virtual Engineering Object Performance
PublicationMachine 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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Fracture Areas Quantitative Investigating of Bending-Torsion Fatigued Low-Alloy High-Strength Steel
PublicationIn this study, the impact of pseudo-random non-proportional bending-torsion fatigue loadings proportion on the fatigue life and the fracture surface topography was analyzed. Investigation was carried out for 24 specimens made of S355J2 steel with 11 different ratios of maximum stresses λ. For these cases, after the fatigue tests, the surface topography measurements were carried out using an optical profilometer, using the focus...
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A general isogeometric finite element formulation for rotation‐free shells with in‐plane bending of embedded fibers
PublicationThis article presents a general, nonlinear isogeometric finite element formulation for rotation-free shells with embedded fibers that captures anisotropy in stretching, shearing, twisting, and bending - both in-plane and out-of-plane. These capabilities allow for the simulation of large sheets of heterogeneous and fibrous materials either with or without matrix, such as textiles, composites, and pantographic structures. The work...
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Iterative learning approach to active noise control of highly autocorrelated signals with applications to machinery noise
PublicationThis paper discusses the design and application of iterative learning control (ILC) and repetitive control (RC) for high modal density systems. Typical examples of these systems are structural and acoustical systems considered in active structural acoustic control (ASAC) and active noise control (ANC) applications. The application of traditional ILC and RC design techniques, which are based on a parametric system model, on systems...
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Machine-Learning-Powered EM-Based Framework for Efficient and Reliable Design of Low Scattering Metasurfaces
PublicationPopularity of metasurfaces has been continuously growing due to their attractive properties including the ability to effectively manipulate electromagnetic (EM) waves. Metasurfaces comprise optimized geometries of unit cells arranged as a periodic lattice to obtain a desired EM response. One of their emerging application areas is the stealth technology, in particular, realization of radar cross section (RCS) reduction. Despite...
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Path integrals formulations leading to propagator evaluation for coupled linear physics in large geometric models
PublicationReformulating linear physics using second kind Fredholm equations is very standard practice. One of the straightforward consequences is that the resulting integrals can be expanded (when the Neumann expansion converges) and probabilized, leading to path statistics and Monte Carlo estimations. An essential feature of these algorithms is that they also allow to estimate propagators for all types of sources, including initial conditions....