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Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance
PublikacjaIdentification 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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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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Predicting seismic response of SMRFs founded on different soil types using machine learning techniques
PublikacjaPredicting 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
PublikacjaBiomass 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
PublikacjaTransformative 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
PublikacjaAccurate 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
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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Adaptive Dynamical Systems Modelling of Transformational Organizational Change with Focus on Organizational Culture and Organizational Learning
PublikacjaTransformative 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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Implementing SP4CE Learning Rooms concept and AUTODESK online certification in the preparation of a new generation of engineers.
PublikacjaIn academia, educators do not always cope with rapidly changing technologies. Yet keeping up with new trends is essential to graduates’ success in a competitive job market. In the article, the author will answer the question of how Autodesk University Open Educational Resources and Certiport exams including GMetrix can enhance students’ academic progress and prepare them for future career. The concept of co-operation between Authorized...
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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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The influence of strain on the Verwey transition as a function of dopant concentration: towards a geobarometer for magnetite-bearing rocks
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Diversity of Students’ Unethical Behaviors in Online Learning Amid COVID-19 Pandemic: An Exploratory Analysis
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Deep learning based segmentation using full wavefield processing for delamination identification: A comparative study
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Vibration-Based Diagnostics of Radial Clearances and Bolts Loosening in the Bearing Supports of the Heavy-Duty Gearboxes
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Perception of Pathologists in Poland of Artificial Intelligence and Machine Learning in Medical Diagnosis—A Cross-Sectional Study
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Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study
PublikacjaThis 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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Solubility of dapsone in deep eutectic solvents: Experimental analysis, molecular insights and machine learning predictions
PublikacjaBackground. 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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Novel PCSE-based approach of inclined structures geometry analysis on the example of the Leaning Tower of Pisa
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System oceny efektywności użytkowania aparatów słuchowych (Hearing aid use effectiveness evaluation system)
PublikacjaCelem rozprawy jest opracowanie metody oceny efektywności protezowania słuchu przy użyciu aparatów słuchowych, która pozwoli w łatwy sposób poddawać ocenie korzyść z użytkowania protez słuchowych w najbardziej typowych sytuacjach akustycznych. Przedstawiono genezę podjętych badań i na tej podstawie zaproponowano cele i tezy rozprawy doktorskiej. W pracy w pierwszej kolejności zawarto przegląd dotyczący rodzajów ubytku słuchu...
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“Fearing your own queer self”: Depictions of Diasporic Queer Experience in Grace Lau’s Poetry
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SELECTING A REPRESENTATIVE DATA SET OF THE REQUIRED SIZE USING THE AGENT-BASED POPULATION LEARNING ALGORITHM
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Influence of hydrostatic pump operation period on performance of a thrust bearing of a 125 MW pump-turbine
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Evaluation of water turbine hydrodynamic thrust bearing performance on the basis of thermoelastohydrodynamic calculations and operational data
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Guest editorial: learning, scheduling, resource optimization, and evolution in smart artificial systems: challenges and support
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Fully Separated Flow Control Using DBD Plasma Actuators Located at the Leading Edge of an Airfoil
PublikacjaIn 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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A ROLE PLAYING GAME NAME GENERATOR LEARNING ITS CREATIVITY FROM ARKADIA MUD PLAYERS
PublikacjaThe 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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Study of the Influence of Heat Convection Coefficient on Predicted Performance of a Large Tilting-Pad Thrust Bearing
PublikacjaPart of the heat generated by the shearing of the lubricating film during operation of a hydrodynamic bearing is transferred to the bearing components. In the case of the pad, which is usually fully submerged in the lubricating oil, heat is further transferred at the pad free walls to the oil by convection. This mechanism causes a thermal gradient in a pad and, consequently, its thermal deflection. In large hydrodynamic thrust...
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Assessment of possible application of water lubricated sintered brass slide bearing for marine propeller shaft
PublikacjaW artykule przedstawiono wyniki badań eksperymentalnych smarowanego wodą łożyska poprzecznego z panwią wykonaną ze spieku brązu.Przedstawiono wyniki pomiarów rozkładu ciśnienia w filmie smarnym, trajektorie osi wału oraz oporów ruchu.Przeprowadzono ocenę przydatności tego typu łożyska do łożyskowania okrętowych wałów śrubowych.
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Comparison of induction motor bearing diagnostic test results through vibration and stator current measurement
PublikacjaThe paper discusses results of tests performed by authors, related to the angine bearings diagnostic using vibration and stator current measurements. The paper contains the description of an automatic measurement system, developed for measurement of those harmonics and processing that to obtain bearing diagnostic information. System was tested on objects with intentionally made defects in bearings, results of this test was also...
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Analysis of pavement structure sensitivity to passage of oversized heavy duty vehicle in terms of bearing capacity
PublikacjaOversized heavy duty vehicles occur in traffic very rarely but they reach extremely high weights, even up to 800 tonne. The detrimental impact of these vehicles on pavement structure is much higher than in case of commercial vehicles that comprise typical traffic, thus it is necessary to assess the sensitivity of pavement structure to passage of oversized vehicles. The paper presents results of sample calculations of load equivalency factor...
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High-precision bearing estimation for active sonar with cylindrical array performed by interpolated array transformation
PublikacjaThe article presents a method for improving the accuracy of bearing in multibeam sonar with a cylindrical array. The antenna’s non-linear shape and the resulting non-uniform sampling of the signal in space, mean that known methods of high-resolution spectral analysis cannot be used. In order to apply an algorithm from this group, a linear virtual antenna must be produced. The paper presents a technique of mapping a cylindrical...
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Iterative learning approach to active noise control of highly autocorrelated signals with applications to machinery noise
PublikacjaThis 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
PublikacjaPopularity 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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Project-Based Learning as a Method for Interdisciplinary Adaptation to Climate Change—Reda Valley Case Study
PublikacjaThe 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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Thermal Images Analysis Methods using Deep Learning Techniques for the Needs of Remote Medical Diagnostics
PublikacjaRemote 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
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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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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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...
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Computational Complexity and Its Influence on Predictive Capabilities of Machine Learning Models for Concrete Mix Design
PublikacjaThe design of concrete mixtures is crucial in concrete technology, aiming to produce concrete that meets specific quality and performance criteria. Modern standards require not only strength but also eco-friendliness and production efficiency. Based on the Three Equation Method, conventional mix design methods involve analytical and laboratory procedures but are insufficient for contemporary concrete technology, leading to overengineering...
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Orientation-aware ship detection via a rotation feature decoupling supported deep learning approach
PublikacjaShip 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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Unsupervised Learning for Biomechanical Data Using Self-organising Maps, an Approach for Temporomandibular Joint Analysis
PublikacjaWe 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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Evaluation of water turbine hydrodynamic thrust bearing performance on the basis of thermoelastohydrodynamic calculations and operational data.
PublikacjaW pracy przedstawiono analizę konstrukcji łożyska wzdłużnego turbiny wodnej. Łożysko zostało skonstruowane około 50 lat temu, a jego konstrukcja przewiduje kompensację termicznych odkształceń klocków. W analizie uwzględniono odkształcenia łożyska i wymianę ciepła w filmie smarowym i klockach łożyskowych. Poza obecną konstrukcją łożyska przeprowadzono również studium wpływu podstawowych parametrów konstrukcyjnych: grubości klocka...
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Influence of hydrostatic pump operation period on performance of a thrust bearing of a 125 MW pump-turbine.
PublikacjaW pracy przedstawiono wyniki badań eksploatacyjnych łożysk wzdłużnych pompoturbin 125 MW elektrowni szczytowo pompowej (esp) Żar. W celu oceny warunków pracy łożysk wyposażono je w segmenty pomiarowe umożliwiające pomiary temperatury i położenia segmentu. W pracy omówiono konstrukcję i wyposażenie segmentu badawczego, metodykę wyznaczania charakterystycznych wielkości. Omówiono także wyniki badań wpływu czasu pracy pompy hydrostatycznego...
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Justifying the prolongation of the service life of the bearing structure of a tank car when using Y25 bogies
PublikacjaThis paper substantiates the use of Y25 bogies under tank cars in order to prolong their service life. The reported study has been carried out for a tank car with rated parameters, as well as the actual ones, registered during full-scale research. Mathematical modeling was performed to determine the basic indicators of the tank car dynamics. The differential equations of motion were solved by a Runge-Kutta method using the Mathcad...
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Machine-Learning Methods for Estimating Performance of Structural Concrete Members Reinforced with Fiber-Reinforced Polymers
PublikacjaIn recent years, fiber-reinforced polymers (FRP) in reinforced concrete (RC) members have gained significant attention due to their exceptional properties, including lightweight construction, high specific strength, and stiffness. These attributes have found application in structures, infrastructures, wind power equipment, and various advanced civil products. However, the production process and the extensive testing required for...
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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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Path integrals formulations leading to propagator evaluation for coupled linear physics in large geometric models
PublikacjaReformulating 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....
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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...