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Search results for: PEEK BEARING
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Fusion-based Representation Learning Model for Multimode User-generated Social Network Content
PublicationAs mobile networks and APPs are developed, user-generated content (UGC), which includes multi-source heterogeneous data like user reviews, tags, scores, images, and videos, has become an essential basis for improving the quality of personalized services. Due to the multi-source heterogeneous nature of the data, big data fusion offers both promise and drawbacks. With the rise of mobile networks and applications, UGC, which includes...
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Fast Machine-Learning-Enabled Size Reduction of Microwave Components Using Response Features
PublicationAchieving compact size has emerged as a key consideration in modern microwave design. While structural miniaturization can be accomplished through judicious circuit architecture selection, precise parameter tuning is equally vital to minimize physical dimensions while meeting stringent performance requirements for electrical characteristics. Due to the intricate nature of compact structures, global optimization is recommended,...
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Machine-learning methods for estimating compressive strength of high-performance alkali-activated concrete
PublicationHigh-performance alkali-activated concrete (HP-AAC) is acknowledged as a cementless and environmentally friendly material. It has recently received a substantial amount of interest not only due to the potential it has for being used instead of ordinary concrete but also owing to the concerns associated with climate change, sustainability, reduction of CO2 emissions, and energy consumption. The characteristics and amounts of the...
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Tacit Knowledge Sharing and Value Creation in the Network Economy: Socially Driven Evolution of Business
PublicationKey factors which affect competitive advantage in the network economy are innovation, relationships, cooperation, and knowledge. Sharing knowledge is not easy. Companies find it problematic. Presented studies show that the essence of the value creation today is not in sharing explicit but rather tacit knowledge, which is a source of creativity and innovation. Delivering value through knowledge does not only require efficient Transactive...
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Tacit Knowledge Sharing and Project Performance. Does the Knowledge Workers' Personal Branding Matter?
PublicationTacit knowledge sharing is the real challenge for knowledge management today. Network economy has completely changed the role of knowledge workers who now become independent tacit knowledge producers. Bearing this fact in mind, the author studied how tacit knowledge sharing affects the process of building a personal brand and project performance. For this purpose, the authors conducted a study among Polish professionals with different...
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Deep learning techniques for biometric security: A systematic review of presentation attack detection systems
PublicationBiometric technology, including finger vein, fingerprint, iris, and face recognition, is widely used to enhance security in various devices. In the past decade, significant progress has been made in improving biometric sys- tems, thanks to advancements in deep convolutional neural networks (DCNN) and computer vision (CV), along with large-scale training datasets. However, these systems have become targets of various attacks, with...
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Optimizing Medical Personnel Speech Recognition Models Using Speech Synthesis and Reinforcement Learning
PublicationText-to-Speech synthesis (TTS) can be used to generate training data for building Automatic Speech Recognition models (ASR). Access to medical speech data is because it is sensitive data that is difficult to obtain for privacy reasons; TTS can help expand the data set. Speech can be synthesized by mimicking different accents, dialects, and speaking styles that may occur in a medical language. Reinforcement Learning (RL), in the...
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An Adaptive Network Model for a Double Bias Perspective on Learning from Mistakes within Organizations
PublicationAlthough making mistakes is a crucial part of learning, it is still often being avoided in companies as it is considered as a shameful incident. This goes hand in hand with a mindset of a boss who dominantly believes that mistakes usually have negative consequences and therefore avoids them by only accepting simple tasks. Thus, there is no mechanism to learn from mistakes. Employees working for and being influenced by such a boss...
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A machine learning approach to classifying New York Heart Association (NYHA) heart failure
PublicationAccording to the European Society of Cardiology, globally the number of patients with heart failure nearly doubled from 33.5 million in 1990 to 64.3 million in 2017, and is further projected to increase dramatically in this decade, still remaining a leading cause of morbidity and mortality. One of the most frequently applied heart failure classification systems that physicians use is the New York Heart Association (NYHA) Functional...
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
PublicationCirculating tumor cells (CTCs) are tumor cells that separate from the solid tumor and enter the bloodstream, which can cause metastasis. Detection and enumeration of CTCs show promising potential as a predictor for prognosis in cancer patients. Furthermore, single-cells sequencing is a technique that provides genetic information from individual cells and allows to classify them precisely and reliably. Sequencing data typically...
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublicationMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
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Enhancing seismic performance of buckling-restrained brace frames equipped with innovative bracing systems
PublicationNowadays, to improve the performance of conventional bracing systems, in which, buckling in the pressure loads is the main disadvantage, the buckling-restrained brace (BRB) is introduced as a solution. In this study, the performance of the BRB system was improved with innovative lateral-resisting systems of double-stage yield buckling-restrained brace (DYB), and a combination of DYB improved with shape memory alloy (SMA) materials...
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Automated detection of pronunciation errors in non-native English speech employing deep learning
PublicationDespite significant advances in recent years, the existing Computer-Assisted Pronunciation Training (CAPT) methods detect pronunciation errors with a relatively low accuracy (precision of 60% at 40%-80% recall). This Ph.D. work proposes novel deep learning methods for detecting pronunciation errors in non-native (L2) English speech, outperforming the state-of-the-art method in AUC metric (Area under the Curve) by 41%, i.e., from...
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Consideration of Pseudo Strain Energy in Determination of Fatigue Life and Microdamage Healing of Asphalt Mastics
PublicationRest periods between cyclic loads can lead to recovery of damage and extension of fatigue life. This phenomenon is referred to as healing. Healing is clearly observed in bituminous materials, such as asphalt mastics, which belong to the components of asphalt mixtures. Due to the nature of road pavement traffic loading, which is characterized by series of intermittent pulses with rest periods, consideration of healing is necessary...
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Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublicationCatheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified...
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Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublicationIn this work, a computationally efficient method based on data driven surrogate models is pro-posed for the design optimization procedure of a Frequency Selective Surface (FSS)-based filtering antenna (Filtenna). A Filtenna acts as a as module that simultaneously pre-filters unwanted sig-nals, and enhances the desired signals at the operating frequency. However, due to a typically large number of design variables of FSS unit elements,...
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Coda wave interferometry in monitoring the fracture process of concrete beams under bending test
PublicationEarly detection of damage is necessary for the safe and reliable use of civil engineering structures made of concrete. Recently, the identification of micro-cracks in concrete has become an area of growing interest, especially using wave-based techniques. In this paper, a non-destructive testing approach for the characterization of the fracture process was presented. Experimental tests were made on concrete beams subjected to mechanical...
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Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublicationSince high-quality real data acquired from selected road sections are not always available, a traffic control solution can use data from software traffic simulators working offline. The results show that in contrast to microscopic traffic simulation, the algorithms employing neural networks can work in real-time, so they can be used, among others, to determine the speed displayed on variable message road signs. This paper describes...
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Nonadditivity of quantum and classical capacities for entanglement breaking multiple-access channels and the butterfly network
PublicationWe analyze quantum network primitives which are entanglement breaking. We show superadditivity of quantum and classical capacity regions for quantum multiple-access channels and the quantum butterfly network. Since the effects are especially visible at high noise they suggest that quantum information effects may be particularly helpful in the case of the networks with occasional high noise rates. The present effects provide a qualitative...
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Semantic technologies based method of collection, processing and sharing information along food chain
PublicationIn the paper the method of collecting, processing and sharing information along food chain is presented. Innovative features of that method result from advantages of data engineering based on semantic technologies. The source to build ontology are standards and regulations related to food production, and data collected in databases owned by food chain participants. It allows food chain information resources can be represented in...
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Development of potential candidate reference materials for drugs in bottom sediment, cod and herring tissues
PublicationRegular use of a reference material and participation in a proficiency testing program can improve the reliability of analytical data. This paper presents the preparation of candidate reference materials for the drugs metoprolol, propranolol, carbamazepine, naproxen, and acenocoumarol in freshwater bottom sediment and cod and herring tissues. These reference materials are not available commercially. Drugs (between 7 ng/g and 32...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublicationMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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Wireless Link Selection Methods for Maritime Communication Access Networks—A Deep Learning Approach
PublicationIn recent years, we have been witnessing a growing interest in the subject of communication at sea. One of the promising solutions to enable widespread access to data transmission capabilities in coastal waters is the possibility of employing an on-shore wireless access infrastructure. However, such an infrastructure is a heterogeneous one, managed by many independent operators and utilizing a number of different communication...
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Effect of bending-torsion on fracture and fatigue life for 18Ni300 steel specimens produced by SLM
PublicationIn this study, different fracture surfaces caused by fatigue failure were generated from 18Ni300 steel produced by selective laser melting (SLM). Hollow round bars with a transverse hole were tested under bending-torsion to investigate the crack initiation mechanisms and fatigue life. Next, the post-failure fracture surfaces were examined by optical profilometer and scanning electron microscope. The focus is placed on the relationship...
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Numerical investigations of size effects in notched and un-notched concrete beams under bending
PublicationW artykule przedstawiono wyniki numerycznej analizy efektów skali (efektu deterministycznego i stochastycznego) w belkach betonowych z nacięciem i bez nacięcia poddanych zginaniu z uwzględnieniem lokalizacji odkształceń. Obliczenia wykonano przy zastosowaniu metody elementów skończonych i sprężysto-plastycznego modelu z nielokalnym osłabieniem. Pokazano wpływ wielkości belek betonowych na ich nośność oraz rozkład lokalizacji odkształceń.
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Experimental investigations of damage evolution in concrete during bending by continuous micro-CT scanning
PublicationThe paper describes experimental investigation results of fracture in notched concrete beams under quasi-static three-point bending. To visualize 3D fracture in concrete under bending, an extended X-ray micro-computed tomography system was used, i.e. the tomography system SkyScan 1173 was connected to the loading machine ISTRON 5569. This combined system enabled to shot images of deforming concrete beams during a continuous deformation...
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Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publication(1) About 15-20% of couples struggle with the problem of infertility. 30 to 40% of these cases are caused by abnormalities in the structure and motility of sperm. Sometimes the only possibility for such people is to use the procedure of artificial insemination. CASA systems are used to increase the efficiency of this procedure by selecting the appropriate sperm cell. (2) This paper presents an approach to the sperm classification...
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Impact of Work on the Well-Being of Police Officers and Firefighters
PublicationWork is one of the most important spheres of human functioning and has a significant impact on individual overall well-being. The purpose of this study is to assess the positive and negative impact of the work of police officers and firefighters on their well-being in different spheres of life. In particular, the study examines the relationship between the type of occupation and the elements that generate a feeling of well-being,...
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Plant-based nutrition supplementation on the well-being of servicemen
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AMO perspectives on the well-being of neurodivergent human capital
PublicationExisting management research and management practices frequently overlook the relationship between the above-average human capital of highly functioning neurodivergent employees, their subjective well-being in the workplace and performance outcomes. This paper calls for greater attention to the hidden human capital associated with neurodiversity by mainstreaming implementation of neurodiversity-friendly policies and practices. Drawing...
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Analiza możliwości wpływania na pracę promieniowego uszczelnienia ślizgowego poprzez deformowanie jego panwi = Analysis of possibility of influence on the radial sliding seals operating by deformation of the bearing sleeve
PublicationW referacie przedstawiono zasadę działania promieniowych uszczelnień ślizgowych oraz ukazano istotny wpływ podstawowych parametrów konstrukcyjnych na skuteczność i jakość ich pracy. Uszczelnienia te stosowane są w instalacjach okrętowych śrub nastawnych, w turbinach wodnych typu Kaplana i maszynach górniczych do drążenia tuneli. Umożliwiają one wprowadzenie oleju pod ciśnieniem do wnętrza obracającego się wału. Zapewnienie stabilnej...
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Brain perfusion imaging with the use of parametric modelling basing on DSC-MRI data
PublicationW pracy do estymacji parametrów perfuzji mózgu: przepływu krwi mózgowej (cerebral blood flow, CBF), objętości krwi mózgowej (cerebral blood volume, CBV) oraz średniego czasu przejścia (mean transit time, MTT) wykorzystano pomiary DSC-MRI (Dynamic Susceptibility Contrast Magnetic Resonance Imaging). W modelowaniu danych MRI zastoswoano model trzykompartmentowy. Przedstawiono i porównano dwa podejścia do identyfikacji modelu różniące...
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Caring Ability and Professional Values of Polish Nursing Students—A Cross-Sectional Study
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Driving force of acoustic streaming caused by aperiodic sound beamin unbounded volumes
PublicationRównanie dynamiczne kierujące lokalnej w czasie siłą radiacyjną ruchu wirowego wyprowadzono. Stwierdzono, iż zawiera ona trzy części: jedna stanowi wzór klasyczny, druga daje zero po uśrednieniu względem okresu fali akustycznej, lecz różni się od zera dla nieokresowego dźwięku. Trzecia składowa związana jest z małymi dyfrakcyjnymi efektami, zachodzącymi podczas propagacji wiązki. Przejście do wzoru klasycznego w przypadku źródła...
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Contactless Hearing Aid for Infants Employing Signal Processing Algorithms. [Bezkontaktowy aparat słuchowy dla niemowląt wykorzystujący algorytmy przetwarzania sygnału]
PublicationZaprojektowany bezkontaktowy aparat słuchowy umiejscawiany jest w łóżeczku niemowlęcia. Aparat składający się z matrycy 4 mikrofonów oraz prototypowej karty z procesorem DSP pracuje w polu swobodnym. Przetworzony sygnał mowy emitowany jest z wykorzystaniem miniaturowych głośników. Opracowane algorytmy pozwalają na elminację akustycznych sprzężeń zwrotnych, które mogą wystepować ze względu na niewielką odległość mikrofonów od głośników...
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Powłoki fluoropolimerowe oraz przeciwzatarciowe w łożyskach foliowych smarowanych wodą = Fluoropolymer and anti-friction coatings for water-lubricated foil bearings
PublicationW artykule przedstawiono krótką charakterystykę oraz wyniki badań tribologicznych wybranych powłok fluoropolimerowych oraz przeciwzatarciowych. Badania zużycia powłok przeprowadzono pod kątem zastosowania w oryginalnym łożysku foliowym smarowanym wodą. Na podstawie analizy wyników wyłoniono trzy powłoki do potencjalnego zastosowania w łożyskach foliowych smarowanych wodą.
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Analiza przepływu oleju przez rowek smarowy wzdłużnego łożyska ślizgowego = Analysis of the lubricant flow through the hydrodynamic thrust bearings groove
PublicationSmarowanie zanurzeniowe jest tradycyjnym sposobem smarowania wzdłużnych łożysk ślizgowych. Jednak rozwiązanie to wykazuje umiarkowaną skuteczność w zapewnieniu optymalnie niskich temperatur w filmie smarowym a ponadto jest przyczyną strat mocy związanych z mieszaniem oleju w obudowie łożyska, co jest szczególnie widoczne w łożyskach szybkoobrotowych. Wymagania stawiane nowym konstrukcjom łożysk ślizgowych to zwiększanie nośności...
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Wykorzystanie modelu silnika indukcyjnego klatkowego do prądowej diagnostyki jego łożysk. Application of induction machine model for current diagnostics of bearings
PublicationW pracy podano widmo prądu stojana dla silnika normalnego oraz wprawianego w drgania o nastawianej częstotliwości. Drgania korpusu wirnika skutkują uginaniem się wirnika, co symuluje bicie wirnika od uszkodzenia łożysk. Podano też model matematyczny silnika, dopuszczający niecentryczność wirnika. Podano widmo prądu stojana przy pracy z wibracjami wirnika odwzorowującymi w pewnym przybliżeniu wibracje od uszkodzonych łożysk.
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Comparative wear test of journal sliding bearings with sintered bronze and Babbitt alloy bushes lubricated by environmentally acceptable/adapted lubricants (EAL)
PublicationA growing awareness of the negative effects of mineral oils on the natural environment has resulted in the introduction of new regulations related to environmental protection. One of these regulations requires the use of environmentally acceptable/adapted lubricants (EAL) to lubricate marine main shaft bearings, in place of the mineral lubricating oils that have been used for decades. Classification Societies, which supervise...
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Post-failure fracture surface analysis of notched steel specimens after bending-torsion fatigue
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Prediction of the structures of proteins with the UNRES force field, including dynamic formation and breaking of disulfide bonds
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Shot peening intensity effect on bending fatigue strength of S235, S355 and P460 structural steels
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Diversity of Students’ Unethical Behaviors in Online Learning Amid COVID-19 Pandemic: An Exploratory Analysis
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The features of steel surface hardening with high energy heating by high frequency currents and shower cooling
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Numerical Modeling of Steel Surface Hardening in the Process of High Energy Heating by High Frequency Currents
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Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study
PublicationThis study explores the edaravone solubility space encompassing both neat and binary dissolution media. Efforts were made to reveal the inherent concentration limits of common pure and mixed solvents. For this purpose, the published solubility data of the title drug were scrupulously inspected and cured, which made the dataset consistent and coherent. However, the lack of some important types of solvents in the collection called...
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Errorless Learning as a method of neuropsychological rehabilitation of individuals suffering from dementia in the course of Alzheimer’s disease
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Fractional-Order PID Controller (FOPID)-Based Iterative Learning Control for a Nonlinear Boiler System
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Deep learning based segmentation using full wavefield processing for delamination identification: A comparative study
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Perception of Pathologists in Poland of Artificial Intelligence and Machine Learning in Medical Diagnosis—A Cross-Sectional Study
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