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Technique for reducing erosion in large-scale circulating fluidized bed units
PublicationThis paper presents a methodology, implemented for a real industrial-scale circulating fluidized bed boiler, to mitigate the risk of heating surfaces exposed to an intensive particle erosion process. For this purpose, a machine learning algorithm was developed to support the boiler reliability management process. Having a tool that can help mitigate the risk of uncontrolled power unit failure without expensive and technically complex...
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Exploring Cause-and-Effect Relationships Between Public Company Press Releases and Their Stock Prices
PublicationThe aim of the work is to design and implement a method of exploring the cause-and-effect relationships between company announcements and the stock prices on NASDAQ stock exchange, followed by a brief discussion. For this purpose, it was necessary to download the stock quotes of selected companies from the NASDAQ market from public web sources. Additionally, media messages related to selected companies had to be downloaded, and...
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Comparing the Effectiveness of ANNs and SVMs in Forecasting the Impact of Traffic-Induced Vibrations on Building
PublicationTraffic - induced vibrations may cause damage to structural elements and may even lead to structural collapse. The aim of the article is to compare the effectiveness of algorithms in forecasting the impact of vibrations on buildings using the Machine Learning (ML) methods. The paper presents two alternative approaches by using Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs). Factors that may affect traffic-induced...
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INFLUENCE OF DATA NORMALIZATION ON THE EFFECTIVENESS OF NEURAL NETWORKS APPLIED TO CLASSIFICATION OF PAVEMENT CONDITIONS – CASE STUDY
PublicationIn recent years automatic classification employing machine learning seems to be in high demand for tele-informatic-based solutions. An example of such solutions are intelligent transportation systems (ITS), in which various factors are taken into account. The subject of the study presented is the impact of data pre-processing and normalization on the accuracy and training effectiveness of artificial neural networks in the case...
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A tool for integrating Web Site services over User Interface
PublicationCompanies and organizations are building information systems by integrating previously independent applications, together with new developments. This integration process has to deal with existing applications, which can only be used through their specific interfaces, and often cannot be modified. Integration of web applications running remotely and controlled by separate organizations becomes even more complicated, as their user...
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Histogram of Gradients with Cell Average Intensity for Human Detection
PublicationThe modification of the descriptor in human detector using Histogram of Oriented Gradients and support vector machine is presented. The proposed modification requires inserting the average cell intensitiesresulting with the increase of the length of the descriptor from 3780 to 4200 values, but it is easy to compute and instantly gives 14-26% of miss rate improvement at 10^-4 False Positives Per Window (FPPW). The modification...
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Problems of analytical determination of journal bearing bush fatigue strength estimates
PublicationProblems connected with determination of stress distribution in sliding layer of thinwalled bearing bushes, investigated in bearing fatigue test rigs, have been presented. Using an example of plain bearings tested in the fatigue machine SMOK (built at the Gdask University of Technology) problems with obtaining a convergence of iterative procedure for determining the fatigue strength estimators of bearing alloy surface layer are...
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Accurate modeling of quasi-resonant inverter fed IM drive
PublicationIn this paper wide-band modeling methodology of a parallel quasi-resonant dc link inverter (PQRDCLI) fed induction machine (IM) is presented. The modeling objective is early-design stage prediction of conductive electromagnetic interference (EMI) emissions of the considered converter fed IM drive system. Operation principles of the selected topology of PQRDCLI feeding IM drive are given. Modeling of the converter drive system is...
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Detection, classification and localization of acoustic events in the presence of background noise for acoustic surveillance of hazardous situations
PublicationEvaluation of sound event detection, classification and localization of hazardous acoustic events in the presence of background noise of different types and changing intensities is presented. The methods for discerning between the events being in focus and the acoustic background are introduced. The classifier, based on a Support Vector Machine algorithm, is described. The set of features and samples used for the training of the...
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Method of selecting the LS-SVM algorithm parameters in gas detection process
PublicationIn this paper we showed the method of resistive gas sensors data processing. The UV irradiation and temperature modulation was applied to improve gas sensors’ selectivity and sensitivity. Noise voltage across the sensor’s terminals (proportional to its resistance fluctuations) was recorded to estimate power spectral density. This function was an input data vector for LS-SVM (least squares – support vector machine) algorithm, which...
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Experience-Oriented Knowledge Management for Internet of Things
PublicationIn this paper, we propose a novel approach for knowledge management in Internet of Things. By utilizing Decisional DNA and deep learning technologies, our approach enables Internet of Things of experiential knowledge discovery, representation, reuse, and sharing among each other. Rather than using traditional machine learning and knowledge discovery methods, this approach focuses on capturing domain’s decisional events via Decisional...
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Decisional DNA Based Conceptual Framework for Smart Manufacturing
PublicationThis paper presents the conceptual framework for systematic knowledge representation, storage and reuse of manufacturing information in a production scenario. This knowledge structure is designed for three levels in a manufacturing set up viz. first at the engineering objects level, second at process and finally at factory level. Virtual engineering object (VEO) deals with knowledge at the individual object/component/machine level...
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Monitoring the BTEX Volatiles during 3D Printing with Acrylonitrile Butadiene Styrene (ABS) Using Electronic Nose and Proton Transfer Reaction Mass Spectrometry
PublicationWe describe a concept study in which the changes of concentration of benzene, toluene, ethylbenzene, and xylene (BTEX) compounds and styrene within a 3D printer enclosure during printing with different acrylonitrile butadiene styrene (ABS) filaments were monitored in real-time using a proton transfer reaction mass spectrometer and an electronic nose. The quantitative data on the concentration of the BTEX compounds, in particular...
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Lamb wave-based monitoring of shear failure of an adhesive lap joint
PublicationThe paper presents a study on the elastic wave propagation in adhesive joints of steel plates subjected to tensile loading. A single lap joint was chosen for analysis because of its simplicity and plurality of applications. Experimental investigations consisted of the uniaxial extension of prepared specimens. Force and displacement values were recorded by a testing machine. Simultaneously, guided Lamb waves were excited and signals...
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Listening to Live Music: Life beyond Music Recommendation Systems
PublicationThis paper presents first a short review on music recommendation systems based on social collaborative filtering. A dictionary of terms related to music recommendation systems, such as music information retrieval (MIR), Query-by-Example (QBE), Query-by-Category (QBC), music content, music annotating, music tagging, bridging the semantic gap in music domain, etc. is introduced. Bases of music recommender systems are shortly presented,...
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A Wind Energy Conversion System Based on a Generator with Modulated Magnetic Flux
PublicationIn this work, the concept of an energy conversion system for wind turbines based on the modified permanent magnet synchronous generator (PMSG) is presented. In the generator, a pair of three-phase windings is used, one of which is connected in a “star” and the second in a “delta” configuration. At the outputs of both windings, two six-pulse uncontrolled (diode) rectifiers are included. These rectifiers are mutually coupled by a...
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Comparative Study of Integer and Non-Integer Order Models of Synchronous Generator
PublicationThis article presents a comparison between integer and non-integer order modelling of a synchronous generator, in the frequency domain as well as in the time domain. The classical integer order model was compared to one containing half -order systems. The half-order systems are represented in a Park d-q axis equivalent circuit as impedances modelled by half-order transmittances. Using a direct method based on the approximation...
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Models of Brushless Synchronous Generator for Studying Autonomous Electrical Power System
PublicationThis is a PhD dissertation. The work presented in this monograph was carried out at the Department of Power Electronics and Electrical Machines, Faculty of Electrical and Control Engineering at the Gdansk University of Technology. Developed during the research models of brushless synchronous generator ware verified using FEM based simulations and measurements conducted on the prototype generator. The main focus of the research...
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Wykorzystanie algorytmów ewolucyjnych do doboru wzmocnień rozszerzonego obserwatora prędkości maszyny indukcyjnej
PublicationW pracy opisano sposób doboru wzmocnień rozszerzonego obserwatora prędkości maszyny indukcyjnej przy wykorzystaniu algorytmów ewolucyjnych. Zaproponowano funkcję celu opartą na rozkładzie biegunów obserwatora. Ze względu na wpływ prędkości maszyny na dynamikę obserwatora zaproponowano dobór wzmocnień obserwatora dla różnych przedziałów prędkości. Dla poszczególnych przedziałów zaprezentowano wyniki doboru wzmocnień w postaci tabel...
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Diagnostyka łożysk silnika indukcyjnego na podstawie prądu zasilającego przy użyciu sztucznych sieci neuronowych
PublicationW artykule zawarto wyniki badań dotyczące diagnostyki łożysk silnika indukcyjnego na podstawie pomiarów prądu zasilającego z wykorzystaniem sztucznych sieci neuronowych. Zaprezentowano wyniki uczenia sieci oraz rezultaty testów przeprowadzonych na danych spoza zbioru uczącego. Badania wykonane zostały na obiektach z celowo wprowadzonymi uszkodzeniami łożysk. Przedstawiona nowa koncepcja zakłada użycie zestawu sieci neuronowych...
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Mrówczan sodu z nowym pakietem inhibitorów korozji jako ekologiczny środek do odladzania infrastruktury lotniczej.
PublicationPrzedstawiono wyniki badań korozji kadmowej powłoki na stali oraz korozji po zanurzeniu stopów metali w mrówczanie sodu z nowym pakietem inhibitorów korozji, zawierającym synergiczną kompozycję poliasparaginianu sodu oraz imidazolu. Ponadto wyznaczono zdolność penetracji lodu przez badany układ. Właściwo- ści opracowanej kompozycji odladzającej porównano z właściwościami środków dostępnych na rynku. Uzyskane wyniki wskazują, że otrzymany...
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Expedited Optimization of Passive Microwave Devices Using Gradient Search and Principal Directions
PublicationOver the recent years, utilization of numerical optimization techniques has become ubiquitous in the design of high-frequency systems, including microwave passive components. The primary reason is that the circuits become increasingly complex to meet ever growing performance demands concerning their electrical performance, additional functionalities, as well as miniaturization. Nonetheless, as reliable evaluation of microwave device...
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Tolerance Optimization of Antenna Structures by Means of Response Feature Surrogates
PublicationFabrication tolerances and other types of uncertainties, e.g., the lack of precise knowledge of material parameters, have detrimental effects on electrical and field performance of antenna systems. In the case of input characteristics these are particularly noticeable for narrow- and multi-band antennas where deviations of geometry parameters from their nominal values lead to frequency shifts of the operating frequency bands. Improving...
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The possibility of estimating the height of the ionospheric inhomogeneities based on TEC variations maps obtained from dense GPS network
PublicationA state of the ionosphere can be effectively studied using electromagnetic signals received from global navigation satellite systems (GNSS). Utilization of the dual frequency observations allows estimating values of the total electron content (TEC). They can be used for a number of scientific studies such as detection and monitoring of traveling ionospheric disturbances or plasma bubbles. Moreover, maps of TEC variations allow...
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Odwieczny model dziejów Rosji
PublicationThe article discusses a dual model of the history of Russia presented in the speeches ofPolish Romantics included in the Russian studies texts of the following epochs and inthe works of Russian authors, e.g. Yuri Lotman and Boris Uspensky. The author provesthat the Gnostic-Manichaean influence on the religiousness of Russians is the sourceof their accumulation of rebellion against the world and the human...
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Metamaterial-Based Series-Fed Antenna with High Gain and Wideband Performance for Millimeter Wave Spectrum Applications
PublicationThis paper presents a high-gain, wideband series-fed antenna designed for 5G millimeter-wave (MMW) applications. The structure employs a substrate-integrated waveguide (SIW)-based power splitter and metamaterials (MMs). The power divider functions effectively at 27.5 GHz, exhibiting an impedance bandwidth from 26.9–28.6 GHz. The series-fed dipole is assembled on the SIW-based power splitter, incorporating four dipoles with varying...
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Nanodiamonds Doped with Manganese for Applications in Magnetic Resonance Imaging
PublicationNanodiamonds (NDs) are emerging with great potential in biomedical applications like biomarking through fluorescence and magnetic resonance imaging (MRI), targeted drug delivery, and cancer therapy. The magnetic and optical properties of NDs could be tuned by selective doping. Therefore, we report multifunctional manganese-incorporated NDs (Mn-NDs) fabricated by Mn ion implantation. The fluorescent properties of Mn-NDs were tuned...
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High-performance activation of ozone by sonocavitation for BTEX degradation in water
PublicationThis work presents a novel advanced oxidation process (AOP) for degradation of emerging organic pollutants – benzene, toluene, ethylbenzene and xylenes (BTEXs) in water. A comparative study was performed for sonocavitation assisted ozonation under 40–120 kHz and 80–200 kHz dual frequency ultrasounds (DFUS). Based on the obtained results, the combination of 40–120 kHz i.e., low-frequency US (LFDUS) with O3 exhibited excellent oxidation...
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Greedy Multipoint Model-Order Reduction Technique for Fast Computation of Scattering Parameters of Electromagnetic Systems
PublicationThis paper attempts to develop a new automated multipoint model-order reduction (MOR) technique, based on matching moments of the system input–output function, which would be suited for fast and accurate computation of scattering parameters for electromagnetic (EM) systems over a wide frequency band. To this end, two questions are addressed. Firstly, the cost of the wideband reduced model generation is optimized by automating a...
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Embodying Intelligence in Autonomous Systems with the Use of Cognitive Psychology and Motivation Theories
PublicationThe article discusses, on a certain level of abstraction and generalization, a coherent anthropological approach to the issue of controlling autonomous robots or agents. A contemporary idea can be based on appropriate modeling of the human mind using the available psychological knowledge. One of the main reasons for developing such projects is the lack of available and effective top-down approaches resulting from the known research...
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Embodying Intelligence in Autonomous and Robotic Systems with the Use of Cognitive Psychology and Motivation Theories
PublicationThe article discusses, on a certain level of abstraction and generalization, a coherent anthropological approach to the issue of controlling autonomous robots or agents. A contemporary idea can be based on appropriate modeling of the human mind using the available psychological knowledge. One of the main reasons for developing such projects is the lack of available and effective top-down approaches resulting from the known research...
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A GPU Solver for Sparse Generalized Eigenvalue Problems with Symmetric Complex-Valued Matrices Obtained Using Higher-Order FEM
PublicationThe paper discusses a fast implementation of the stabilized locally optimal block preconditioned conjugate gradient (sLOBPCG) method, using a hierarchical multilevel preconditioner to solve nonHermitian sparse generalized eigenvalue problems with large symmetric complex-valued matrices obtained using the higher-order finite-element method (FEM), applied to the analysis of a microwave resonator. The resonant frequencies of the low-order...
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Reliable data-driven modeling of high-frequency structures by means of nested kriging with enhanced design of experiments
PublicationData-driven (or approximation) surrogate models have been gaining popularity in many areas of engineering and science, including high-frequency electronics. They are attractive as a way of alleviating the difficulties pertinent to high computational cost of evaluating full-wave electromagnetic (EM) simulation models of microwave, antenna, and integrated photonic components and devices. Carrying out design tasks that involve massive...
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Cost‐efficient performance‐driven modelling of multi‐band antennas by variable‐fidelity electromagnetic simulations and customized space mapping
PublicationElectromagnetic (EM) simulations have become an indispensable tool in the design of contemporary antennas. EM‐driven tasks, for example, parametric optimization, entail considerable computational efforts, which may be reduced by employing surrogate models. Yet, data‐driven modelling of antenna characteristics is largely hindered by the curse of dimensionality. This may be addressed using the recently reported domain‐confinement...
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Structure and the space vector modulation for a medium-voltage power-electronic-transformer based on two seven-level cascade H-bridge inverters
PublicationThis study presents the structure and the space vector pulse-width modulation (SVPWM) for power electronic transformer (PET) based on two seven-level cascade H-bridge (CHB) inverters. The DC links of CHB inverters are coupled with nine dual-active bridge (DAB) converters with medium-frequency transformers. The DC-link voltages are equalised with two methods – through the control of DAB voltages...
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Swapping Space for Time: An Alternative to Time-Domain Interferometry
PublicationYoung's double-slit experiment [1] requires two waves produced simultaneously at two different points in space. In quantum mechanics the waves correspond to a single quantum object, even as complex as a big molecule. An interference is present as long as one cannot tell for sure which slit is chosen by the object. The more we know about the path, the worse the interference. In the paper we show that quantum mechanics allows for...
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Cost-Efficient Surrogate Modeling of High-Frequency Structures Using Nested Kriging with Automated Adjustment of Model Domain Lateral Dimensions
PublicationSurrogate models are becoming popular tools of choice in mitigating issues related to the excessive cost of electromagnetic (EM)-driven design of high-frequency structures. Among available techniques, approximation modeling is by far the most popular due to its versatility. In particular, the surrogates are exclusively based on the sampled simulation data with no need to involve engineering insight or problem-specific knowledge....
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Deep convolutional neural network for predicting kidney tumour malignancy
PublicationPurpose: According to the statistics, up to 15-20% of removed solid kidney tumors turn out to be benign in postoperative histopathological examination, despite having been identified as malignant by a radiologist. The aim of the research was to limit the number of unnecessary nephrectomies of benign tumors. Methods or Background: We propose a machine-aided diagnostic system for kidney...
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Experimental and Theoretical Insights into the Intermolecular Interactions in Saturated Systems of Dapsone in Conventional and Deep Eutectic Solvents
PublicationSolubility is not only a crucial physicochemical property for laboratory practice but also provides valuable insight into the mechanism of saturated system organization, as a measure of the interplay between various intermolecular interactions. The importance of these data cannot be overstated, particularly when dealing with active pharmaceutical ingredients (APIs), such as dapsone. It is a commonly used anti-inflammatory and...
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Empirical analysis of tree-based classification models for customer churn prediction
PublicationCustomer churn is a vital and reoccurring problem facing most business industries, particularly the telecommunications industry. Considering the fierce competition among telecommunications firms and the high expenses of attracting and gaining new subscribers, keeping existing loyal subscribers becomes crucial. Early prediction of disgruntled subscribers can assist telecommunications firms in identifying the reasons for churn and...
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Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents
PublicationThe construction industry suffers from workplace accidents, including injuries and fatalities, which represent a significant economic and social burden for employers, workers, and society as a whole.The existing research on construction accidents heavily relies on expert evaluations,which often suffer from issues such as low efficiency, insufficient intelligence, and subjectivity.However, expert opinions provided in construction...
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Sampling-based novel heterogeneous multi-layer stacking ensemble method for telecom customer churn prediction
PublicationIn recent times, customer churn has become one of the most significant issues in business-oriented sectors with telecommunication being no exception. Maintaining current customers is particularly valuable due to the high degree of rivalry among telecommunication companies and the costs of acquiring new ones. The early prediction of churned customers may help telecommunication companies to identify the causes of churn and design...
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Opracowanie ekspertyzy dotyczącej przyczyn pękania łopatek wirnika SP turbiny PG1 typu 13UP55
PublicationZakres badań i analiz dotyczył ustalenia przyczyn pękania elementów łopatek wirnika SPA5 turbiny TG1 typu 13UP55 obejmował: 1. wykonanie badań składu chemicznego stali, z której wykonano łopatki dostarczone przez Zleceniodawcę dwoma metodami, 2. badania mikroobszarów zniszczenia łopatek na mikroskopie elektronowym skaningowym z mikroanalizatorem EDS, 3. badania metalograficzne makroskopowe i mikroskopowe fragmentów...
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Motion Trajectory Prediction in Warehouse Management Systems: A Systematic Literature Review
PublicationBackground: In the context of Warehouse Management Systems, knowledge related to motion trajectory prediction methods utilizing machine learning techniques seems to be scattered and fragmented. Objective: This study seeks to fill this research gap by using a systematic literature review approach. Methods: Based on the data collected from Google Scholar, a systematic literature review was performed, covering the period from 2016...
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Threat intelligence platform for the energy sector
PublicationIn recent years, critical infrastructures and power systems in particular have been subjected to sophisticated cyberthreats, including targeted attacks and advanced persistent threats. A promising response to this challenging situation is building up enhanced threat intelligence that interlinks information sharing and fine-grained situation awareness. In this paper a framework which integrates all levels of threat intelligence...
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THE ROLE OF INFERENCE IN MOBILE MEDICAL APPLICATION DESIGN
PublicationIn the early 21st century, artificial intelligence began to be used to process medical information. However, before this happened, predictive models used in healthcare could only consider a limited number of variables, and only in properly structured and organised medical data. Today, advanced tools based on machine learning techniques - which, using artificial neural networks, can explore extremely complex relationships - and...
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Methodology for determination of the selected mechanical properties of wood based on cutting tests
PublicationFrom kiln-dried spruce wood (with steam) as well as in natural conditions were randomly selected 8 samples. After determining the average dimensions, moisture content and density of the samples they have been cut on the frame sawing machine PRW15M for measurement of cutting power. Based on those results from a linear rela-tionship of cutting power versus feed per toot mechanical properties of wood such as facture toughness and...
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Multiscalar Control Based Airgap Flux Optimization of Induction Motor for Loss Minimization
PublicationBased on the induction motor model, considering the core loss resistance that accounts for magnetic characteristic saturation, a speed control approach is devised with an adaptive full-order (AFO) speed observer. The induction motor model analysis is done sincerely in a stationary reference frame. The control approach incorporates a flux reference generator designed to meet optimal operational circumstances and a nonlinear speed...
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Buried Object Characterization Using Ground Penetrating Radar Assisted by Data-Driven Surrogate-Models
PublicationThis work addresses artificial-intelligence-based buried object characterization using 3-D full-wave electromagnetic simulations of a ground penetrating radar (GPR). The task is to characterize cylindrical shape, perfectly electric conductor (PEC) object buried in various dispersive soil media, and in different positions. The main contributions of this work are (i) development of a fast and accurate data driven surrogate modeling...
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HCI-Based Wireless System for Measuring the Concentration of Mining Machinery and Equipment Operators
PublicationMaintaining stable and reliable working conditions is a matter of vital importance for various companies, especially those involving heavy machinery. Due to human exhaustion, as well as unpredicted hazards and dangerous situations, the personnel has to take actions and wisely plan each move. This paper presents a human–computer interaction (HCI)-based system that uses a concentration level measurement function to increase the safety...