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Search results for: LEASING PRACOWNICZY
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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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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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Modern remote sensing and the challenges facing education systems in terms of its teaching
PublicationCurrently the fastest growing area of geodesy is undoubtedly remote sensing. The importance that it has recently conducted on the effectiveness of worldwide research determines its huge success. Examination of the specific characteristics of objects without direct contact with them is a key feature has opened the way to the new very interesting areas of contemporary research. In this light, it seems reasonable to say that there...
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THE ONLINE APPLICATION AND E-LEARNING IN THE COMPETENCE-BASED MANAGEMENT IN PUBLIC ADMINISTRATION ORGANIZATIONS
PublicationThe integration of effective management of work-related processes and utilization of human resources potential leads to the development of organization. The purpose of this paper was to examine how the principles of competences-based management can be introduced to enhance organization’s effectiveness in human resources management. A model of assessment and development of competences-based management, embracing an online application...
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Common-Mode Voltage and Bearing Currents in PWM Inverters: Causes, Effects and Prevention
PublicationIn modern induction motor drives an increase of transistors' switching frequency and a decrease of switching times are the sources of some serious problems. The high dv/dt and the common mode voltage generated by the inverter PWM control results in the appearances of bearing currents, shaft voltages, motor terminal overvoltages, the decrease of motor efficiency, and electromagnetic interference. The aspects of common mode (CM)...
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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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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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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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UV-Light-Induced Fluctuation Enhanced Sensing by WO3-Based Gas Sensors
PublicationWO3-based gas sensors were investigated under UV-light irradiation and at different working temperatures with the object of achieving superior sensitivity and selectivity. Resistance fluctuations in the WO3 layer were studied together with dc resistance measurements. The data were taken in synthetic air, ethanol, nitrogen dioxide, and mixtures of these gases. We conclude that UV irradiation can easily be applied to enhance the...
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Fluctuation-enhanced and conductometric gas sensing with nanocrystalline NiO thin films: A comparison
PublicationNanocrystalline thin films of NiO were prepared by advanced reactive gas deposition, and their responses to formaldehyde, ethanol and methane gases were studied via fluctuation-enhanced and conductometric methods Thin films with thicknesses in the 200–1700-nm range were investigated in as-deposited form and after annealing at 400 and 500 °C. Morphological and structural analyses showed porous deposits with NiO nanocrystals having...
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Nickel Oxide Thin Film Sensor for Fluctuation-Enhanced Gas Sensing of Formaldehyde
PublicationNanocrystalline nickel-oxide-based thin films were prepared by advanced reactive gas deposition, and the response of these films to formaldehyde was studied by fluctuationenhanced sensing. Morphological and structural analyses showed porous deposits of nickel oxide particles with face-centered cubic structure. Resistance fluctuations were measured upon exposure to ethanol, formaldehyde and methane at 200 °C. Power density spectra...
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Prototype of an opto-capacitive probe for non-invasive sensing cerebrospinal fluid circulation
PublicationIn brain studies, the function of the cerebrospinal fluid (CSF) awakes growing interest, particularly related to studies of the glymphatic system in the brain, which is connected with the complex system of lymphatic vessels responsible for cleaning the tissues. The CSF is a clear, colourless liquid including water (H2O) approximately with a concentration of 99 %. In addition, it contains electrolytes, amino acids, glucose, and...
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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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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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One-step recovery of REE oxalates in electro-leaching of spent NdFeB magnets
PublicationRecovery of rare-earth elements (REEs) from spent NdFeB magnets is receiving great attention because of high amount of neodymium and potential risk of environmental pollution. In this study, a novel environment-friendly hydrometallurgical route is proposed for efficient recovery of REEs during electrochemical leaching with sulfuric and oxalic acids. With proper adjustment of the electrolyte composition and operating conditions,...
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Phytoremediation—From Environment Cleaning to Energy Generation—Current Status and Future Perspectives
Publication:Phytoremediationis a technology based on the use of green plants to remove, relocate, deactivate, or destroy harmful environmental pollutants such as heavy metals, radionuclides, hydrocarbons, and pharmaceuticals. Under the general term of phytoremediation, several processes with distinctively different mechanisms of action are hidden. In this paper, the most popular modes of phytoremediation are described and discussed. A broad...
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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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Extended Newmark method to assess stability of slope under bidirectional seismic loading
PublicationThe paper concerns the dynamic behavior of a simple slope model subjected to simultaneous horizontal and vertical excitations. The proposed method is based on Newmark’s sliding block concept, however, four new features are introduced. The most important assumption is that the normal component of dynamic excitations affects the resisting force both before and after the initiation of the relative slope motion, making it time-dependent....
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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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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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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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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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Nitrogen dioxide gas-sensing detection with GO modified CuO thin films
PublicationGas sensors have been continuously developed over the last few decades for several applications including air quality monitoring, automotive industry and recently for medical use. Gas sensors are usually based on metal oxides (MOXs), such as SnO2, TiO2, ZnO, WO3, CuO. Recently, new materials such as graphene oxide and heterostructures of graphene oxide and metal oxides are utilized for gassensing applications.
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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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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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Recurrent potential pulse technique for improvement of glucose sensing ability of 3D polypyrrole
PublicationIn this work, a new approach for using a 3D polypyrrole (PPy) conducting polymer as a sensing material for glucose detection is proposed. Polypyrrole is electrochemically polymerized on a platinum screen-printed electrode in an aqueous solution of lithium perchlorate and pyrrole. PPy exhibits a high electroactive surface area and high electrochemical stability, which results in it having excellent electrocatalytic properties. The...
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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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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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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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Enhanced gas sensing by graphene-silicon Schottky diodes under UV irradiation
PublicationThe effect of ultraviolet (UV) or blue irradiation on graphene/n-doped silicon Schottky junctions toward gas sensing was investigated. Schottky diodes were subjected to oxidizing nitrogen dioxide (NO2, 1–3 ppm) and reducing tetrahydrofuran (THF, 50–200 ppm), showing significantly different responses observed on the currentvoltage (I-V) characteristics, especially under UV light (275 nm). NO2 affected the resistive part of the forward region...
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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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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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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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Impact of temperature on optical sensing in biology based on investigation of SARS‐CoV ‐2
PublicationIn this paper, we present an investigation of the influence of the temperature on the sensing of biological samples. We used biofunctionalized microsphere-based fiber-optic sensor to detect immunoglobulin G attached to the sensor head at temperatures relevant in biological research: 5°C, 25°C, and 55°C. The construction of the sensor allowed us to perform measurements in the small amount of solution. The results of our experiment...
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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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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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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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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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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...