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Search results for: CRANK BEARING
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Accuracy Investigations of Turbine Blading Neural Models Applied to Thermal and Flow Diagnostics
PublicationPossibility of replacing computional fluid dynamics simulations by a neural model for fluid flow and thermal diagnostics of steam turbines is investigated. Results of calculations of velocity magnitude of steam for 3D model of the stator of steam turbine is presented.
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Optical flow method for measuring deformation of soil specimen subjected to torsional shearing
PublicationIn this study optical flow method was used for soil small deformation measurement in laboratory tests. The main objective was to observe how the deformation distributes along the whole height of cylindrical soil specimen subjected to torsional shearing (TS test). The experiments were conducted on dry non-cohesive soil specimens under two values of isotropic pressure. Specimens were loaded with low-amplitude cyclic torque to analyze...
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Effect of surface on the flexomagnetic response of ferroic composite nanostructures; nonlinear bending analysis
PublicationOur analysis incorporates the geometrically nonlinear bending of the Euler-Bernoulli ferromagnetic nanobeam accounting for a size-dependent model through assuming surface effects. In the framework of the flexomagnetic phenomenon, the large deflections are investigated referring to von-Kármán nonlinearity. Employing the nonlocal effects of stress coupled to the gradient of strain generates a scale-dependent Hookean stress-strain...
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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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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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On Nonlinear Bending Study of a Piezo-Flexomagnetic Nanobeam Based on an Analytical-Numerical Solution
PublicationAmong various magneto-elastic phenomena, flexomagnetic (FM) coupling can be defined as a dependence between strain gradient and magnetic polarization and, contrariwise, elastic strain and magnetic field gradient. This feature is a higher-order one than piezomagnetic, which is the magnetic response to strain. At the nanoscale, where large strain gradients are expected, the FM effect is significant and could be even dominant. In...
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On Effective Bending Stiffness of a Laminate Nanoplate Considering Steigmann–Ogden Surface Elasticity
PublicationAs at the nanoscale the surface-to-volume ratio may be comparable with any characteristic length, while the material properties may essentially depend on surface/interface energy properties. In order to get effective material properties at the nanoscale, one can use various generalized models of continuum. In particular, within the framework of continuum mechanics, the surface elasticity is applied to the modelling of surface-related...
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Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits
PublicationThe Contextual Multi-Armed Bandits (CMAB) framework is pivotal for learning to make decisions. However, due to challenges in deploying online algorithms, there is a shift towards offline policy learning, which relies on pre-existing datasets. This study examines the relationship between the quality of these datasets and the performance of offline policy learning algorithms, specifically, Neural Greedy and NeuraLCB. Our results...
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Looking through the past: better knowledge retention for generative replay in continual learning
PublicationIn this work, we improve the generative replay in a continual learning setting to perform well on challenging scenarios. Because of the growing complexity of continual learning tasks, it is becoming more popular, to apply the generative replay technique in the feature space instead of image space. Nevertheless, such an approach does not come without limitations. In particular, we notice the degradation of the continually trained...
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Leading with Understanding: Cultivating Positive Relationships between Neurotypical Leaders and Neurodivergent Employees
PublicationNeurodivergent employees have atypical needs that require distinctive leadership approaches. In this study, the specific nature of a relationship between neurodivergent employees and their neurotypical leaders is explored through the lens of the Leader-Member-Exchange (LMX) theory. This two-phased qualitative study builds on 12 semi-structured interviews with neurodivergent employees and an unstructured focus group with 15 individuals...
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BACTERIAL INACTIVATION VIA LASER-DRIVEN GOLD NANOPARTICLE HEATING: SIMULATION AND ANALYSIS
PublicationThis study utilizes CFD technique to simulate the inactivation of E. coli bacteria within a microfluidic chamber, employing gold nanoparticles irradiated by a laser beam. Employing a single-phase model, the presence of bacteria is considered by treating thermal properties in the governing equations as effective, combining those of water and bacteria using established correlations from scientific literature. The conversion of light...
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Gender as a Moderator of the Double Bias of Mistakes – Knowledge Culture and Knowledge Sharing Effects
PublicationThere is no learning without mistakes. The essence of the double bias of mistakes is the contradiction between an often-declared positive attitude towards learning from mistakes, and negative experiences when mistakes occur. Financial and personal consequences, shame, and blame force desperate employees to hide their mistakes. These adverse outcomes are doubled in organizations by the common belief that managers never make mistakes,...
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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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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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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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Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublicationBiochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts,...
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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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Heating caused by a non periodic ultrasound. Theory and calculations on pulse and stationary sources.
PublicationPrzedstawiono teorię ewolucji ogrzewania na skutek przejścia fali akustycznej każdego typu. Przedyskutowano obliczenia na podstawie nowych wzorów dla fali impulsowej i uderzeniowej. Wzory zgadzają się z klasycznymi w wypadku fal okresowych.
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublicationThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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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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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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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublicationComplexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...
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SIMULATIONS OF FRACTURE IN CONCRETE BEAMS UNDER BENDING USING A CONTINUUM AND DISCRETE APPROACH
PublicationThe paper describes two-dimensional meso-scale results of fracture in notched concrete beams under bending. Concrete was modelled as a random heterogeneous 4-phase material composed of aggregate particles, cement matrix, interfacial transitional zones and air voids. Within continuum mechanics, the simulations were carried out with the finite element method based on a isotropic damage constitutive model enhanced by a characteristic...
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Fracture surface formation of notched 2017A-T4 aluminium alloy under bending fatigue
PublicationThe effect of cyclic loading on facture surface topology in notched components made by aluminium alloys is not completely clear. Fractogra-phy and fracture mechanics can help to understand this interdependency. This paper aims to study the distribution of the fracture surface roughness of notched 2017A-T4 aluminium alloy after bending fatigue using an optical focus-variation surface measurement technique by applying the fracture...
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In Reference to The Challenges of Pharmacotherapy of SARS-CoV-2 Infection in Patients With Sudden Sensorineural Hearing Loss Due to COVID-19
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STUDY IN MECHANICAL FAULT ELEMENT THERMOGRAPHY THROUGH THE MACHINE: The case of deep groove ball bearings of a career without screen.
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Comparison of endotracheal intubation performed with 3 devices by paramedics wearing chemical, biological, radiological, and nuclear personal protective equipment
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Modelling of network schedule including priority of selected technical resources
PublicationThe paper presents a method of network planning CPM – Critical Path Method. The author compares models of optimal solutions to design deadlines for individual works, taking various leading technical resources such as is labor and a tower crane into account.
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The reality of the ''Lower'' and the ''Higher'' man within the human being: towards the new type of philosophical anthropology of infrastructures of the personal human being
PublicationW artykule, pt. " The Reality of the "Lower" and the "Higher" Man within the Human Being: Towards the New Type of Philosophical Anthropology of Infrastructures of the Personal Human Being" ("Realność "niższego" i "wyższego" człowieka w obrębie ludzkiego bytu. Ku nowemu typowi antropologii filozoficznej infrastruktur osobowego bytu ludzkiego") usiłowałem pokazać, że realność "niższego" i "wyższego" człowieka w obrębie...
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An electric ring thruster as auxiliary manoeuvring propulsion system for watercraft - construction analysis
PublicationThe reported project aimed at examining properties and purposefulness of use of modern electromagneticbearings for a screw propeller in a prototype version of a synchronous ring motor with rare earths magnets.Bearings of this type generate electromagnetic forces which keep the rotor in a state of levitation. Therotating machine with magnetic bearings can work in any environment which reveals diamagnetic properties(air, vacuum,...
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STABILITY ANALYSIS OF A TRUSS WITH SLOPING ELASTIC BRACES
PublicationSteel trusses have a much greater strength and stiffness in their plane than out of their plane, and therefore should be braced against lateral deflection and twisting. Such elements like purlins apart from bearing vertical load are part of bracing that stabilize roof trusses against distortional buckling. The stability of trusses with elastic bracing was investigated in an experimental research. Braces situated at some angle measured...
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Caring for Children with Dravet Syndrome: Exploring the Daily Challenges of Family Caregivers
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Caring for Children with Dravet Syndrome: Exploring the Daily Challenges of Family Caregivers
PublicationWhile Polish studies focus on the symptoms, causes and treatment of people suffering from Dravet syndrome (DS), much less is known about the situation of the family caregivers of DS children. This study was designed to explore the experiences, daily challenges and needs related to caring for DS children. An anonymous self-administered online questionnaire was developed. Thesurvey was completed by 75 family caregivers affiliated...
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The accuracy assessment of determining the axis of railway track basing on the satellite surveying
PublicationW 2009 roku na Politechnice Gdańskiej rozpoczęto badania nad wykorzystaniem serwisu pomiarów fazowych NAVGEO aktywnej sieci geodezyjnej ASG-EUPOS dla przeprowadzania ciągłych pomiarów przebiegu trasu kolejowej. Celem kontynuowanych badań jest próba oceny możliwości zastosowania pomiarów fazowych GNSS, realizowanych przez kilka odbiorników, dla projektowania oraz inwentaryzacji toru kolejowego. Do oceny dokładności określenia osi...
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Investigations on fracture in reinforced concrete beams in 3-point bending using continuous micro-CT scanning
PublicationThis study explores a fracture process in rectangular reinforced concrete (RC) beams subjected to quasi-static three-point bending. RC beams were short and long with included longitudinal reinforcement in the form of a steel or basalt bar. The ratio of the shear span to the effective depth was 1.5 and 0.75. The focus was on the load–deflection diagram and crack formation. Three-dimensional (3D) analyses of the size and distribution...
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EXPERIMENTAL STUDY OF DIFFERENT SUPPLY DESIGNS IN HYDRODYNAMIC THRUST BEARINGS = Badania doświadczalne różnych sposobów smarowania wzdłużnych łożysk ślizgowych
PublicationHydrodynamiczne łożyska wzdłużne charakteryzują się znacznymi stratami tarcia, które przyczyniają się do wzrostu temperatury łożyska i obniżenia jego nośności. Obecnie olej smarujący jest zazwyczaj chłodzony w zewnętrznych układach chłodzenia. Po schłodzeniu olej jest dostarczany z powrotem do korpusu łożyska, z reguły do przestrzeni między klockami łożyska. Skuteczność dostarczania schłodzonego oleju w pobliże wlotu do szczeliny...
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First tests of water lubricated propeller shaft bearings = Wstępne badania zespołu smarowanych wodą łożysk okrętowego wału śrubowego
PublicationW pierwszej części referatu zaprezentowano nowe stanowsko badawcze przy pomocy którego można badać smarowane wodą łożyska wału śrubowego. W drugiej części pracy przedstawiono uzyskane wyniki pomiarów oporów ruchu i trajektorii osi wału.
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
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Population dynamics of Baltic herring since the Viking Age revealed by ancient DNA and genomics
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Experimental Evaluation of the Agent-Based Population Learning Algorithm for the Cluster-Based Instance Selection
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Surface topography analysis based on fatigue fractures obtained with bending of the 2017A-T4 alloy
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Do new EU members have any chance of earning as much as Westerns do?
PublicationThis article examines the wage dispersion in the European Union in the last ten years (1996-2006). The research is motivated by the fact that New Members States (NMS) expected that wage convergence would occurred after their accession to the EU. At the same time Old Member States (OMS) have been increasingly concerned with the possibility that the EU enlargement could influence their local labor markets and wages through new channels...
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Exploring the meaning of night shift placement in nursing education: A European multicentre qualitative study
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Deep learning model for automated assessment of lexical stress of non-native english speakers
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A Reaction of Thioamides with Zinc Ammoniates Leading to Simple Amidines. Discovery of a New Zwitterionic Monomethylamidine
PublicationThe reaction of thioamides with the R1R2N-ZnCl ammoniates leads to N-mono-, N,N'-di-, N,N-disubstituted, and unsubstituted amidines with high concns. of amines in abs. ethanol. The efficient direct formation of the N,N'-dimethylamidine can be explained by a greater reactivity of methylamine compared with dimethylamine. Discovery of a new zwitterion (induced by a carbonyl oxygen) suggests that the stabilization in the thymine...