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Search results for: E-LEARING
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Multivariate Features Extraction and Effective Decision Making Using Machine Learning Approaches
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The noise-induced harmful effect assessment based on the properties of the human hearing system
PublicationA new way of assessment of noise-induced harmful effects on human hearing system is presented in the paper. The method takes into consideration properties of the human hearing system. The pro-posed method determines the cumulative impact on hearing system produced by the excessive noise. Based on the predicted effects of the noise exposure, the new types of noise indicators were developed. The evaluation of these indicators was...
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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublicationIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
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Influence of Thermal Imagery Resolution on Accuracy of Deep Learning based Face Recognition
PublicationHuman-system interactions frequently require a retrieval of the key context information about the user and the environment. Image processing techniques have been widely applied in this area, providing details about recognized objects, people and actions. Considering remote diagnostics solutions, e.g. non-contact vital signs estimation and smart home monitoring systems that utilize person’s identity, security is a very important factor....
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Effect of manufacturing errors of the pad sliding surface on the performance of the hydrodynamic thrust bearing
PublicationIn the present study, investigation of the effect of manufacturing errors on the performance of large tilting pad thrust bearings has been performed, following a CFD-based Thermohydrodynamic analysis of a single pad. A 3D model has been generated, including the pad, the lubricant film and the corresponding part of the collar. The pad has been assumed to be deformed about the pivot point, due to thrust loading. Manufacturing errors...
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Iron(III)-selective materials based on a catechol-bearing amide for optical sensing
PublicationThe synthesis and ion-binding properties of a new amide L derived from 3,4-dihydroxybenzoic acid are described. Due to the presence of a catechol unit, the compound interacts selectively with iron(III) in organic solvent (dimethyl sulfoxide, DMSO) to produce a color change from pale yellow to green. The incorporation of the ligand L into polymeric matrices or its encapsulation into surfactant-based spheres enables analyte detection...
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Visual Content Learning in a Cognitive Vision Platform for Hazard Control (CVP-HC)
PublicationThis 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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A Proposed Machine Learning Model for Forecasting Impact of Traffic-Induced Vibrations on Buildings
PublicationTraffic-induced vibrations may cause various damages to buildings located near the road, including cracking of plaster, cracks in load-bearing elements or even collapse of the whole structure. Measurements of vibrations of real buildings are costly and laborious. Therefore the aim of the research is to propose the original numerical algorithm which allows us to predict, with high probability, the nega-tive dynamic impact of traffic-induced...
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Combined thrust radial bearing of a submarine main shaft – Design and analysis of failure
PublicationThis paper presents an analysis of the combined thrust radial bearing of a submarine propulsion shaft. The lubrication system of the bearing is based on a fixed ring. The efficiency of the lubrication system depends on the shaft speed and temperature, which affects oil viscosity. In turn, the thrust bearing load also depends on the rotational speed of the shaft, because as the speed increases, the drag of the ship increases simultaneously,...
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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublicationThe aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was...
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Autonomous Perception and Grasp Generation Based on Multiple 3D Sensors and Deep Learning
PublicationGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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On the use of leading safety indicators in maritime and their feasibility for Maritime Autonomous Surface Ships
PublicationAlthough the safety of prospective Maritime Autonomous Surface Ships will largely depend on their ability to detect potential hazards and react to them, the contemporary scientific literature lacks the analysis of how to achieve this. This could be achieved through an application of leading safety indicators. The aim of the performed study was to identify the research directions of leading safety indicators in three safety-critical...
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Pursuing the Deep-Learning-Based Classification of Exposed and Imagined Colors from EEG
PublicationEEG-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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Machine learning approach to packaging compatibility testing in the new product development process
PublicationThe paper compares the effectiveness of selected machine learning methods as modelling tools supporting the selection of a packaging type in new product development process. The main goal of the developed model is to reduce the risk of failure in compatibility tests which are preformed to ensure safety, durability, and efficacy of the finished product for the entire period of its shelf life and consumer use. This kind of testing...
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Combining MUSHRA Test and Fuzzy Logic in the Evaluation of Benefits of Using Hearing Prostheses
PublicationAssessing the effectiveness of hearing aid fittings based on the benefits they provide is crucial but intricate. While objective metrics of hearing aids like gain, frequency response, and distortion are measurable, they do not directly indicate user benefits. Hearing aid performance assessment encompasses various aspects, such as compensating for hearing loss and user satisfaction. The authors suggest enhancing the widely used...
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Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublicationThis 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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Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning
PublicationIn 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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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublicationTo this day, driver fatigue remains one of the most significant causes of road accidents. In this paper, a novel way of detecting and monitoring a driver’s physical state has been proposed. The goal of the system was to make use of multimodal imaging from RGB and thermal cameras working simultaneously to monitor the driver’s current condition. A custom dataset was created consisting of thermal and RGB video samples. Acquired data...
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The effects of relational and psychological capital on work engagement: the mediation of learning goal orientation
PublicationPurpose – 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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DNAffinity: a machine-learning approach to predict DNA binding affinities of transcription factors
PublicationWe present a physics-based machine learning approach to predict in vitro transcription factor binding affinities from structural and mechanical DNA properties directly derived from atomistic molecular dynamics simulations. The method is able to predict affinities obtained with techniques as different as uPBM, gcPBM and HT-SELEX with an excellent performance, much better than existing algorithms. Due to its nature, the method can...
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Predicting emotion from color present in images and video excerpts by machine learning
PublicationThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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LOS and NLOS identification in real indoor environment using deep learning approach
PublicationVisibility conditions between antennas, i.e. Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) can be crucial in the context of indoor localization, for which detecting the NLOS condition and further correcting constant position estimation errors or allocating resources can reduce the negative influence of multipath propagation on wireless communication and positioning. In this paper a deep learning (DL) model to classify LOS/NLOS...
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Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning
PublicationIn this paper, the data, information, knowledge, and wisdom (DIKW) pyramid is revisited in the context of deep learning applied to machine learningbased audio signal processing. A discussion on the DIKW schema is carried out, resulting in a proposal that may supplement the original concept. Parallels between DIWK pertaining to audio processing are presented based on examples of the case studies performed by the author and her collaborators....
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Detection of People Swimming in Water Reservoirs with the Use of Multimodal Imaging and Machine Learning
PublicationEvery year in many countries, there are fatal unintentional drownings in different water reservoirs like swimming pools, lakes, seas, or oceans. The existing threats of this type require creating a method that could automatically supervise such places to increase the safety of bathers. This work aimed to create methods and prototype solutions for detecting people bathing in water reservoirs using a multimodal imaging system and...
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Technology-Enhanced Environmental Learning: Co-design of Educational Mobile Application Case
PublicationThe 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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Detecting type of hearing loss with different AI classification methods: a performance review
PublicationHearing is one of the most crucial senses for all humans. It allows people to hear and connect with the environment, the people they can meet and the knowledge they need to live their lives to the fullest. Hearing loss can have a detrimental impact on a person's quality of life in a variety of ways, ranging from fewer educational and job opportunities due to impaired communication to social withdrawal in severe situations. Early...
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Supervised-learning-based development of multi-bit RCS-reduced coding metasurfaces
PublicationCoding metasurfaces have been introduced as efficient tools allowing meticulous control over the electromagnetic (EM) scattering. One of their relevant application areas is radar cross section (RCS) reduction, which principally relies on the diffusion of impinging EM waves. Despite its significance, careful control of the scattering properties poses a serious challenge at the level of practical realization. This article is concerned...
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Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning
PublicationFollowing the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides...
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A comparative performance assessment of a hydrodynamic journal bearing lubricated with oil and magnetorheological fluid
PublicationThis work presents the investigation results of a journal bearing lubricated with magnetorheological fluid that is activated by a local constant magnetic field to vary both the local flow resistance and pressure. The bearing performance is assessed via Finite Element Modelling (FEM) and results are corroborated by experiments. The FEM model uses the Bingham model to describe the fluid film. A dedicated test rig is used to assess...
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Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method
PublicationPlasmonic nanostructures based on AuAg nanoalloys were fabricated by thermal annealing of metallic films in an argon atmosphere. The nanoalloys were chosen because they can extend the wavelength range in which plasmon resonance occurs and thus allow the design of plasmonic platforms with the desired parameters. The influence of initial fabrication parameters and experimental conditions on the formation of nanostructures was investigated....
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Wisdom from Experience Paradox: Organizational Learning, Mistakes, Hierarchy and Maturity Issues
PublicationOrganizations often perceive mistakes as negligence and low-performance indicators, yet they can be a precious learning resource. However, organizations cannot learn from mistakes if they have not accepted them. This study aimed to explore how organizational hierarchy and maturity levels influence the relationship between mistakes acceptance and the ability to change. A sample composed of 380 Polish employees working in knowledge-driven...
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Modeling of bearing capacity of footings on sand within stochastic micro-polar hypoplasticity.
PublicationAnalizowano numerycznie efekt wstępnego rozkładu wskaźnika porowatości na wytrzymałość i strefy ścinania w problemach fundamentów na piasku w skali modelowej. Obliczenia wykonano przy zastosowaniu stochastycznej metody elementów skończonych i mikropolarnego modelu hipoplastycznego. Wskaźnik porowatości miał formę skorelowanych pól stochastycznych. Dodatkowo obliczono efekt skali dla 3 różnych szerokości fundamentów.
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Membrane cleaning and pretreatments in membrane distillation – a review
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The Resistance of Polyethersulfone Membranes on the Alkaline Cleaning Solutions
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Heating of fuse - elements in transient and steady - state
PublicationPrzedstawiono wyniki obliczeń numerycznych nagrzewania topików bezpieczników w stanach nieustalonych i ustalonych i wykonanych w pakiecie FLUX 2D. W obliczeniach uwzględniono nagrzewania całej wkładki bezpiecznikowej. Do analizy wybrano temperaturę w przewężeniu topika. W wyniku przeprowadzonych badań stwierdzono, że przy obliczaniu parametrów przedłukowych należy uwzględniać przewodzenie ciepła w topiku oraz brać pod uwagę zmienną...
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Places of worship, spiritual healing and urban regeneration
PublicationMany researchers demonstrated that it is possible to help people achieve mental and physical regeneration with proper architecture, urban and landscape planning. The term therapeutic landscapes could also be applied to places of worship, where people gather for spiritual healing and renewal. Public space that they offer is inclusively open to all. Addition- ally, they serve to reinvigorate the places where they are located. Shrines...
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Measurement accuracy of the system to control the microwave heating.
PublicationPrzedstawiono skrótowo zasadę pracy i konstrukcję systemu do badań naukowych procesów grzania mikrofalowego. Wyprowadzono wyrażenie opisujące wartość średniokwadratową błędu pomiaru energii mikrofalowej i przeanalizowano składowe błędu pomiaru powodowane przez rzeczywiście występujące w układzie pomiarowym parametry techniczne jego części mikrofalowej.
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Modelling of acoustic backscattering by southern Baltic herring
PublicationAssessment of Baltic herring abundance can be carried out using acoustic techniques. Analysis of the relationship between the Baltic herring individual target strength, TS, and the total fish length, L, important for the acoustic assessment, showed the relationship to be dependent on the location of the study area. This finding motivated a detailed analysis of the relationship for the herring occurring in the southern Baltic...
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Magnetoacoustic heating in a quasi-isentropic magnetic gas
PublicationThe nonlinear heating of a plasma which associates with the transfer of energy of magnetoacoustic waves into that of the entropy mode, is analytically studied. A plasma is uniform and motionless at equilibrium. Perturbations in a plasma are described by a system of ideal magnetohydrodynamic equations. The equilibrium straight magnetic strength and the wave vector form a constant angle which varies from 0 to π/2. There exist four...
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Molecular Biology of Meniscal Healing: A Narrative Review
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Car-sharing: The Impact on Metropolitan Spatial Structures
PublicationMany examples from the past show that new technologies designed to solve particular problems can also create side effects generating new problems. Some unforeseen or unwanted results may influence space use and spatial structures. Car-sharing is an invention to compete with car ownership. It drastically rise efficiency of car use, reducing the number of vehicles per users. Diffusion of car-sharing is going to accelerate in the...
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Security Information Sharing for the Polish Power System
PublicationThe Polish Power System is becoming increasingly more dependent on Information and Communication Technologies which results in its exposure to cyberattacks, including the evolved and highly sophisticated threats such as Advanced Persistent Threats or Distributed Denial of Service attacks. The most exposed components are SCADA systems in substations and Distributed Control Systems in power plants. When addressing this situation...
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Large Hydrodynamic Thrust Bearings and Their Application in Hydrogenerators
PublicationLarge hydrodynamic thrust bearings are the bearings which, due to hydrodynamic lubrication, allow large axial load to be transferred from a moving part (shaft) to the stationary part via a thin layer of the lubricant (usually oil), thus providing extremely low friction and practically no wear. Hydrogenerators with vertical shafts are the most important application of large thrust bearings. Main design and scientific problems of...
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Analysis of resistive and inductive heating of railway turnouts
PublicationElektryczne ogrzewanie rozjazdów kolejowych jest istotnym problemem technicznym i ekonomicznym. Z tych względów potrzebne są badania w celu optymalizacji systemu ogrzewania rozjazdów kolejowych. W artykule przedstawiono analizę porównawczą strat energii podczas ogrzewania rozjazdów kolejowych z wykorzystaniem dwóch różnych metod. Analiza ogrzewania rozjazdów przeprowadzono w programie ANSYS.(Analiza oporowego i indukcyjnego nagrzewania...
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Stability of a truss under upward wind loading
PublicationThe present paper is devoted to the numerical investigations of stability of a truss under upward wind load. The truss is braced at its the upper cord. A structural variant including lateral braces, or lateral and torsional braces is considered. The research presents the problems of linear buckling and non-linear static analysis of the truss shell and beam model with geometric and material non-linearity are presented. The initial...
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The State and Critical Assessment of the Sharing Economy in Europe
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The Sharing Economy in Europe: From Idea to Reality
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Diagnostics of induction motor bearings - possibility of measurements
PublicationIn induction motors damage in the elements of electromagnetic system, for example in the wiring of stator, rotor or in the magnetic circuit can appear as well as damage of mechanical parts (bearings, rotor, shaft). Bearing diagnostics is so important in supervision of motor condition, because extensive research shows that the bearings arethe elements most susceptible to damage. This paper presents the research which the author...
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A method for evaluating durability of porous slide bearings
PublicationThe article presents the structures of porous bearings bushes and greasy lubricants, and the similarity criterion resulting from this structures. A phisical model is proposed which describes the operation of the porous slide bearing bush taking into account, via analogy, the phenomena taking place in the grease lubricant nodes instead of those observed in the bush structures.Included are the result of experimental tests of three...
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Temperature measurements in monitoring of large thrust bearings
PublicationW pracy przedstwiono krytyczną analizę aktualnych metod diagnostyki dużych hydrodnamicznych łożysk wzdłużnych hydrozespołów elektrowni wodnych. Wykazano niedostatki i zagrożenia płynące ze stosowania diagnostyki opartej na jednopunktowym pomiarze temperatury. Zaprezentowano wstępna koncepcję nowej metody diagnostycznej opartej na odwrotnym zagadnieniu przepływu ciepła.