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Search results for: E-LEARING
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Fuzzy reasoning system design and assessment of load-bearing endoprostheses and their fabrication processes
PublicationZaproponowano piec zastosowan podejscia rozumowania rozmytego do rozwiazania problemów w dziedzinie biomechanikioraz inzynierii biomateriałów. Obejmuja one: (A) oszacowanie maksymalnych naprezen kontaktowych działajacych naendoproteze, (B) zaprojektowanie procesu spiekania dla otrzymania porowatego implantu, (C) opracowanie planu utleniania wcelu otrzymania struktury nanorurkowej na stopach Ti, (D) oraz (E) zaprojektowanie osadzania...
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Improving the accuracy of bearing in active sonar with cylindrical array using spectrum estimation.
PublicationThe articles presents a method for improving the accuracy of bearing in multibeam sonar with a cylindrical array. Based on a known spatial spectrum estimation technique, the method has been successfully used in linear array systems. Its accuracy of bearing is satisfactory and ensures a relatively low computational effort. The article discusses certain simplifications and assumptions to adapt the spatial spectrum estimation technique...
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AUTOMATIC LEARNING OF STRATEGY AND RULES IN CARD GAMES USING IMAGE FROM CAMERA
PublicationBelow work tries to answer a question: if it is possible to replace real human with computer system in social games. As a subject for experiments, card games were chosen, because they require a lot of player interaction (playing and taking cards), while their rules are easy to present in form of clear list of statements. Such a system, should allow real players to play without constant worrying about guiding or helping computer...
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New Generation of Water lubricated Foil bearing - Numerical Models and Experimental Verification
PublicationIn the paper a new idea of foil water lubricated bearing and methodology of hydrodynamic characteristics calculations is presented. To assesses the theoretical characteristics of these bearings two different computer models were built. First is structural model coupled with fluid model. It takes into account: fluid flow in the deformed fluid gap, specific design of bearing support and friction in bearing support. The second is...
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Running characteristics of aerodynamic bearing with self-lifting capability at low rotational speed
PublicationAn aerodynamic journal bearing that is capable of self-generating squeeze-film pressure is presented and its dynamic characteristics investigated numerically and experimentally. A numerical method based on a time marching static model was applied to assess the orbit trajectory path of the rotor upon a perturbation. Experimental results were obtained to validate the effect of the self- generated squeeze-film pressure on the stability...
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Field Tests on Hydrodynamic and Hybrid Operation of a Bidirectional Thrust Bearing of a Pump-Turbine
PublicationIn vertical shaft pump turbines operating in pumped storage power plants an important role is played by a thrust bearing. Due to the bidirectional character of operation, thrust bearing tilting pads have to be supported symmetrically, which is known to be unfavourable from the point of view of their performance. Large thrust bearings have to be carefully designed so as to minimise excessive thermo-elastic pad deformations. The...
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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublicationThis paper analyzes functions and structures of the memory that is an indispensable part of an Intelligent System of Decision-making (ISD), developed as a universal engine for autonomous robotics. A simplified way of processing and coding information in human cognitive processes is modelled and adopted for the use in autonomous systems. Based on such a knowledge structure, an artificial model of reality representation and a model...
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublicationIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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THE SYNCHROSQUEEZING METHOD IN BEARING ESTIMATION OF STATIONARY SIGNALS FOR PASSIVE SONAR WITH TOWED ARRAY
PublicationIn this paper, a novel method of bearing estimation in a passive sonar system with a towed array is introduced. The classical approach of bearing estimation based on the spatial spectrum [1] is extended by using the synchrosqeezing method that is a part of the reassignment method introduced by Kodera et al. [2]. Using this method leads to a precise bearing estimation. The proposed method requires a relatively small amount of computation,...
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Analysis of sloping brace stiffness influence on stability and load bearing capacity of a truss
PublicationThe paper is focused on the numerical study of stability and load bearing capacity of a truss with side elastic braces. The structure is made in reality. The rotational and sliding brace stiffnesses were taken into account. Linear buckling analysis and non-linear static analysis with geometric and material nonlinearity were performed for the beam and shell model of the truss with respect to the angle of sloping braces. As a result...
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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublicationThis paper analyzes functions and structures of the memory that is an indispensable part of an Intelligent System of Decision-making (ISD), developed as a universal engine for autonomous robotics. A simplified way of processing and coding information in human cognitive processes is modelled and adopted for the use in autonomous systems. Based on such a knowledge structure, an artificial model of reality representation and a model...
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Continuous learning as a method of raising qualifications – the perspective of workers, employers and training organizations
PublicationContinuous learning is discussed in strategic documents of Poland and the European Union. In Poland, the idea of continuous learning is not very popular. However, in the context of strong competition in the labour market and the progressive globalization processes, the skills issue takes on new meaning — both for employees and employers. In order to adapt skills to labour market needs it is necessary to conduct adequate studies...
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DESIGN AND THEORETICAL ANALYSIS OF A PROTOTYPE TILTING-PAD RADIAL BEARING WITH ADJUSTABLE CLEARANCE
PublicationThe article introduces a design and analysis results of a prototype ORC (organic Rankine cycle) turbo generator rotor assembly of 300kW power, supported by tilting-pad bearings of original design. The calculations were performed for a prototype turbo generator rotor. The shaft of this machine is supported with two radial bearings, lubricated with an unusual lubricant – a low-boiling-point agent. The main objective of the presented...
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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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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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Water-lubricated stern tube bearing - experimental and theoretical investigations of thermal effects
PublicationThe paper presents research results of thermal phenomena accompanying operation of a water-lubricated stern tube bearing with axial grooves. Experimental tests revealed, that intensity of forced axial flow has strong influence on bush temperature. Numerical simulations focused on investigation of the thermal phenomena under operation of water-lubricated journal bearing showed, that restricted axial flow promotes backflow of the...
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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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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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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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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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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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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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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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Combining visual and acoustic modalities to ease speech recognition by hearing impaired people
PublicationArtykuł prezentuje system, którego celem działania jest ułatwienie procesu treningu poprawnej wymowy dla osób z poważnymi wadami słuchu. W analizie mowy wykorzystane zostały parametry akutyczne i wizualne. Do wyznaczenia parametrów wizualnych na podstawie kształtu i ruchu ust zostały wykorzystane modele Active Shape Models. Parametry akustyczne bazują na współczynnikach melcepstralnych. Do klasyfikacji wypowiadanych głosek została...
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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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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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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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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.
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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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Polski rynek leasingu - stan i perspektywy
PublicationArtykuł podejmuje tematykę funkcjonowania leasingu w warunkach polskiej gospodarki. Charakterystyce poddano umowy leasingowe. Określono korzyści oraz wady wynikające z ich zawierania. W dalszej części pracy zbadano jak kształtuje się wartościowo wolumen podpisywanych umów leasingowych w Polsce od początku roku 2001 do trzeciego kwartału 2009. Wyznaczono również udział rynku leasingowego w finansowaniu inwestycji ogółem w kraju....
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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 (IPHC).
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Utulization of biomass for heating purposes in pomeranian region
PublicationW publikacji przedstawiono analizę potencjału użycia odnawialnych źródeł energii do produkcji ciepła w regionie pomorskim. Każde miasto regionu zostało oszacowane pod względem potencjału użycia odnawialnych źródeł energii. Dwa obszary miejskie cechują się tym, że mają potencjał pokrycia swojego zapotrzebowania na ciepło tylko ze słomy, czyli możemy rozpatrywać produkcję ciepła z kotłów opalanych słomą jako 100% potencjalne zapotrzebowanie...
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Research on Linear Actuators for Active Foil Bearings
PublicationActive foil bearings are a kind of gas foil bearing. They contain actuators which allow for modification of the bearing sleeve size and the shape of the lubrication gap. Rotor vibrations can be actively controlled by these changes. It is possible, among other things, to reduce the starting torque, control the vibration amplitude at different speeds and improve operational safety. Prototypes of active foil bearings are being developed...
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Organizational IT Competency, Knowledge Workers and Knowledge Sharing
PublicationIT competency plays a vital role in knowledge management processes. Information technology affects an organization’s ability to store and recall knowledge that has been made explicit through codification, including different forms such as written documents, reports, presentations, patents, formulas, etc. This study aims to measure the influence of a company’s IT competency dimensions such as IT-knowledge,...
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Sustainable Knowledge Sharing Model for IT Agile Projects
PublicationIn order to overcome work environment challenges and remain competitive in the market, organisations must adapt. An organisation's competitiveness can be improved through knowledge sharing; however, improvement without responsibility can have a negative impact on the sociotechnical environment which people cannot fully comprehend. According to researchers, business involvement in sustainable development goals remains minimal [51]....