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Wyniki wyszukiwania dla: e-learing
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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublikacjaThis 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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THE SYNCHROSQUEEZING METHOD IN BEARING ESTIMATION OF STATIONARY SIGNALS FOR PASSIVE SONAR WITH TOWED ARRAY
PublikacjaIn 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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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublikacjaThis 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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Enhancing diaphragmatic defect repair and regeneration: How biomaterials leading the way to progress?
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Running characteristics of aerodynamic bearing with self-lifting capability at low rotational speed
PublikacjaAn 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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Analysis of sloping brace stiffness influence on stability and load bearing capacity of a truss
PublikacjaThe 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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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublikacjaIn 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
PublikacjaHuman-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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The effects of relational and psychological capital on work engagement: the mediation of learning goal orientation
PublikacjaPurpose – 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
PublikacjaWe 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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Field Tests on Hydrodynamic and Hybrid Operation of a Bidirectional Thrust Bearing of a Pump-Turbine
PublikacjaIn 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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Fuzzy reasoning system design and assessment of load-bearing endoprostheses and their fabrication processes
PublikacjaZaproponowano 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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A comparative performance assessment of a hydrodynamic journal bearing lubricated with oil and magnetorheological fluid
PublikacjaThis 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
PublikacjaPlasmonic 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
PublikacjaOrganizations 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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Supervised-learning-based development of multi-bit RCS-reduced coding metasurfaces
PublikacjaCoding 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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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublikacjaIn 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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Improving the accuracy of bearing in active sonar with cylindrical array using spectrum estimation.
PublikacjaThe 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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DESIGN AND THEORETICAL ANALYSIS OF A PROTOTYPE TILTING-PAD RADIAL BEARING WITH ADJUSTABLE CLEARANCE
PublikacjaThe 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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Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning
PublikacjaFollowing 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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Visual Content Learning in a Cognitive Vision Platform for Hazard Control (CVP-HC)
PublikacjaThis 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
PublikacjaTraffic-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
PublikacjaThis 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
PublikacjaThe 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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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublikacjaThe 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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Effect of manufacturing errors of the pad sliding surface on the performance of the hydrodynamic thrust bearing
PublikacjaIn 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
PublikacjaThe 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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The influence of time of hearing aid use on auditory perception in various acoustic situations
PublikacjaThe assessment of sound perception in hearing aids, especially in the context of benefits that a prosthesis can bring, is a complex issue. The objective parameters of the hearing aids can easily be determined. These parameters, however, do not always have a direct and decisive influence on the subjective assessment of quality of the patient’s hearing while using a hearing aid. The paper presents the development of a method for...
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Ecological bearing systems for water turbines – research and development at Gdansk University of Technology
PublikacjaIncreasing requirements for environmental protection make it necessary to introduce new materials and designs. Hydroelectric power plants operating in direct contact with water reservoirs and rivers are potentially endangering water cleanliness, hence they should also be modernized in the way minimizing the environmental hazards. A lot of progress in this field has been achieved in last decades, but still there is much work to...
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New Generation of Water lubricated Foil bearing - Numerical Models and Experimental Verification
PublikacjaIn 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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Comparison of Deep Neural Network Learning Algorithms for Mars Terrain Image Segmentation
PublikacjaThis paper is dedicated to the topic of terrain recognition on Mars using advanced techniques based on the convolutional neural networks (CNN). The work on the project was conducted based on the set of 18K images collected by the Curiosity, Opportunity and Spirit rovers. The data were later processed by the model operating in a Python environment, utilizing Keras and Tensorflow repositories. The model benefits from the pretrained...
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Automated hearing loss type classification based on pure tone audiometry data
PublikacjaHearing problems are commonly diagnosed with the use of tonal audiometry, which measures a patient’s hearing threshold in both air and bone conduction at various frequencies. Results of audiometry tests, usually represented graphically in the form of an audiogram, need to be interpreted by a professional audiologist in order to determine the exact type of hearing loss and administer proper treatment. However, the small number of...
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Deep learning-enabled integration of renewable energy sources through photovoltaics in buildings
PublikacjaInstalling photovoltaic (PV) systems in buildings is one of the most effective strategies for achieving sustainable energy goals and reducing carbon emissions. However, the requirement for efficient energy management, the fluctuating energy demands, and the intermittent nature of solar power are a few of the obstacles to the seamless integration of PV systems into buildings. These complexities surpass the capabilities of rule-based...
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Advancing Solar Energy: Machine Learning Approaches for Predicting Photovoltaic Power Output
PublikacjaThis research is primarily concentrated on predicting the output of photovoitaic power, an essential field in the study of renewable energy. The paper comprehensively reviews various forecasting methodologies, transitioning from conventional physical and statistical methods to advanced machine learning (ML) techniques. A significant shift has been observed from traditional point forecasting to machine learning-based forecasting...
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Application of the Flipped Learning Methodology at a Business Process Modelling Course – A Case Study
PublikacjaFlipped learning has been known for a long time, but its modern use dates back to 2012, with the publication of Bergmann and Saams. In the last decade, it has become an increasingly popular learning method. Every year, the number of publications on implementing flipped learning experiments is growing, just as the amount of research on the effectiveness of this educational method. The aim of the article is to analyze the possibilities...
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Autonomous Perception and Grasp Generation Based on Multiple 3D Sensors and Deep Learning
PublikacjaGrasping 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
PublikacjaAlthough 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
PublikacjaEEG-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 for the management of biochar yield and properties of biomass sources for sustainable energy
PublikacjaBiochar 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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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublikacjaThe 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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Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits
PublikacjaThe 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
PublikacjaIn 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
PublikacjaNeurodivergent 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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Combining MUSHRA Test and Fuzzy Logic in the Evaluation of Benefits of Using Hearing Prostheses
PublikacjaAssessing 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
PublikacjaThis 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
PublikacjaIn 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
PublikacjaTo 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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Predicting emotion from color present in images and video excerpts by machine learning
PublikacjaThis 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
PublikacjaVisibility 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
PublikacjaIn 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....