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Search results for: CRANK BEARING
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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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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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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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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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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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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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Open source learning management systems at civil engineering and environmental department: TeleCAD and Moodle.
PublicationW rozdziale zaprezentowano dwa systemy zarządzania kształceniem, służące do przygotowania i prowadzenia e-kursów. Pierwszy z nich TeleCAD został opracowany w ramach projektu Leonardo da Vinci (1998-2001). Ostanie użycie systemu miało miejsce w roku akademickim 2003/2004 i był on wykorzystany w projekcie CURE (V Program Ramowy, 2003-2006). W roku 2003 dzięki wsparciu projektu Leonardo da Vinci EMDEL (2001-2005) Centrum Edukacji...
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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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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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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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Plant-based nutrition supplementation on the well-being of servicemen
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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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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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Caring Ability and Professional Values of Polish Nursing Students—A Cross-Sectional Study
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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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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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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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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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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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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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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublicationThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
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Transcriptional profile of in vitro expanded human epidermal progenitor cells for the treatment of non-healing wounds
PublicationBackground Epidermal progenitor cells (EPCs) have been under extensive investigation due to their increasing potential of application in medicine and biotechnology. Cultured human EPCs are used in the treatment of chronic wounds and have recently became a target for gene therapy and toxicological studies. One of the challenges in EPCs culture is to provide a high number of undifferentiated, progenitor cells displaying high viability...
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Size effect in concrete beams under bending – influence of the boundary layer and the numerical description of cracks
PublicationIn the paper the size effect phenomenon in concrete is analysed. The results of numerical simulations of using FEM on geometrically similar un-notched and notched concrete beams under bending are presented. Concrete beams of four different sizes and five different notch heights under three-point bending test were simulated. In total 18 beams were analysed. Two approaches were used to describe cracks in concrete. First, eXtended...
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Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance
PublicationIdentification of active electrodes that record task-relevant neurophysiological activity is needed for clinical and industrial applications as well as for investigating brain functions. We developed an unsupervised, fully automated approach to classify active electrodes showing event-related intracranial EEG (iEEG) responses from 115 patients performing a free recall verbal memory task. Our approach employed new interpretable...
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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublicationTo improve the user's localization estimation in indoor and outdoor environment a novel radiolocalization system using deep learning dedicated to work both in indoor and outdoor environment is proposed. It is based on the radio signatures using radio signals of opportunity from LTE an WiFi networks. The measurements of channel state estimators from LTE network and from WiFi network are taken by using the developed application....
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Predicting seismic response of SMRFs founded on different soil types using machine learning techniques
PublicationPredicting the Maximum Interstory Drift Ratio (M-IDR) of Steel Moment-Resisting Frames (SMRFs) is a useful tool for designers to approximately evaluate the vulnerability of SMRFs. This study aims to explore supervised Machine Learning (ML) algorithms to build a surrogate prediction model for SMRFs to reduce the need for complex modeling. For this purpose, twenty well-known ML algorithms implemented in Python software are trained...
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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublicationBiomass management in terms of energy consumption optimization has become a recent challenge for developed countries. Nevertheless, the multiplicity of materials and operating parameters controlling energy consumption in wastewater treatment plants necessitates the need for sophisticated well-organized disciplines in order to minimize energy consumption and dissipation. Sewage sludge (SS) disposal management is the key stage of...
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Adaptive Dynamical Systems Modelling of Transformational Organizational Change: with Focus on Organizational Culture and Organizational Learning
PublicationTransformative Organizational Change becomes more and more significant both practically and academically, especially in the context of organizational culture and learning. However computational modeling and a formalization of organizational change and learning processes are still largely unexplored. This paper aims to provide an adaptive network model of transformative organizational change and translate a selection of organizational...
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Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublicationAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
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Intra-subject class-incremental deep learning approach for EEG-based imagined speech recognition
PublicationBrain–computer interfaces (BCIs) aim to decode brain signals and transform them into commands for device operation. The present study aimed to decode the brain activity during imagined speech. The BCI must identify imagined words within a given vocabulary and thus perform the requested action. A possible scenario when using this approach is the gradual addition of new words to the vocabulary using incremental learning methods....
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Adaptive Dynamical Systems Modelling of Transformational Organizational Change with Focus on Organizational Culture and Organizational Learning
PublicationTransformative Organizational Change becomes more and more significant both practically and academically, especially in the context of organizational culture and learning. However computational modeling and a formalization of organizational change and learning processes are still largely unexplored. This paper aims to provide an adaptive network model of transformative organizational change and translate a selection of organizational...
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Implementing SP4CE Learning Rooms concept and AUTODESK online certification in the preparation of a new generation of engineers.
PublicationIn academia, educators do not always cope with rapidly changing technologies. Yet keeping up with new trends is essential to graduates’ success in a competitive job market. In the article, the author will answer the question of how Autodesk University Open Educational Resources and Certiport exams including GMetrix can enhance students’ academic progress and prepare them for future career. The concept of co-operation between Authorized...
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Supporting First Year Students Through Blended-Learning - Planning Effective Courses and Learner Support
PublicationHigher education has been actively encouraged to find more effective and flaxible delivery models to provide all students with access to good quality learning experiences. This paper describes students opinion about using e-learning techniques and their participation in courses provided in different ways as additional help and expectations of first year students.
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Comparison of classical Winter's bracing requirements of compressedtruss chord with stability analysis of 3D truss-model
PublicationMost code requirements concerning bracing are based on principles developed by Winter. The present research is devoted tostudy a lateral buckling of truss with linear elastic side supports. The classical Winter's model of truss chord in the case ofout of the truss plane buckling is compared with nonlinear analysis of 3D truss model. Full bracing condition, that permitsthe truss chord to support load level corresponding to an unbraced...
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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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Diversity of Students’ Unethical Behaviors in Online Learning Amid COVID-19 Pandemic: An Exploratory Analysis
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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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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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Post-failure fracture surface analysis of notched steel specimens after bending-torsion fatigue
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