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Process of Medical Dataset Construction for Machine Learning-Multifield Study and Guidelines
PublicationThe acquisition of high-quality data and annotations is essential for the training of efficient machine learning algorithms, while being an expensive and time-consuming process. Although the process of data processing and training and testing of machine learning models is well studied and considered in the literature, the actual procedures of obtaining data and their annotations in collaboration with physicians are in most cases...
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Using deep learning to increase accuracy of gaze controlled prosthetic arm
PublicationThis paper presents how neural networks can be utilized to improve the accuracy of reach and grab functionality of hybrid prosthetic arm with eye tracing interface. The LSTM based Autoencoder was introduced to overcome the problem of lack of accuracy of the gaze tracking modality in this hybrid interface. The gaze based interaction strongly depends on the eye tracking hardware. In this paper it was presented how the overall the...
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Exploring DAD and ADD Methods for Dealing with Urban Heat Island Effect
PublicationThe Urban Heat Island (UHI) effect in the context of climate change and temperature fluctuations is an increasing challenge for contemporary cities. Numerous activities focus on mitigation and adaptation to the UHI effect using both appropriately selected design strategies and technological solutions. However, not all of these technologies support the postulates of ecological and low-carbon cities. Their design, implementation,...
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Can the Pandemic Be a Catalyst of Spatial Changes Leading Towards the Smart City?
PublicationThe worldwide spread of Covid‐19 infections has had a pervasive influence on cities and the lives of their residents. The current crisis has highlighted many urban problems, including those related to the functionality of urban structures, which directly affect the quality of life. Concurrently, the notion of “smart cities” is becoming a dominant trend in the discourse on urban development. At the intersection of these two phenomena,...
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TensorHive: Management of Exclusive GPU Access for Distributed Machine Learning Workloads
PublicationTensorHive is a tool for organizing work of research and engineering teams that use servers with GPUs for machine learning workloads. In a comprehensive web interface, it supports reservation of GPUs for exclusive usage, hardware monitoring, as well as configuring, executing and queuing distributed computational jobs. Focusing on easy installation and simple configuration, the tool automatically detects the available computing...
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Distance learning trends: introducing new solutions to data analysis courses
PublicationNowadays data analysis of any kind becomes a piece of art. The same happens with the teaching processes of statistics, econometrics and other related courses. This is not only because we are facing (and are forced to) teach online or in a hybrid mode. Students expect to see not only the theoretical part of the study and solve some practical examples together with the instructor. They are waiting to see a variety of tools, tutorials,...
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Effect of convection and microwave heating on the retention of bioactive components in human milk
PublicationBioactive substances are very important components of human milk (HM), especially for premature newborns. The effects of convection (CH) and microwave heating (MWH) at 62.5 and 66 °C, on the level of selected bioactive components of HM: lysozyme (LZ), lactoferrin (LF), secretory immunoglobulin A (sIgA), basal lipase (BL), cytokine TGF-2, vitamin C and total antioxidant capacity (TAC) was compared. Regardless of the used heating methods...
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DEEP LEARNING BASED ON X-RAY IMAGING IMPROVES COXARTHROSIS DETECTION
PublicationObjective: The purpose of the study was to create an Artificial Neural Network (ANN) based on X-ray images of the pelvis, as an additional tool to automate and improve the diagnosis of coxarthrosis. The research is focused on joint space narrowing, which is a radiological symptom showing the thinning of the articular cartilage layer, which is translucent to X-rays. It is the first and the most important of the radiological signs...
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Modeling lignin extraction with ionic liquids using machine learning approach
PublicationLignin, next to cellulose, is the second most common natural biopolymer on Earth, containing a third of the organic carbon in the biosphere. For many years, lignin was perceived as waste when obtaining cellulose and hemicellulose and used as a biofuel for the production of bioenergy. However, recently, lignin has been considered a renewable raw material for the production of chemicals and materials to replace petrochemical resources....
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Smart Asset Management for District Heating Systems in the Baltic Sea Region.
PublicationThe purpose of this review is to provide insight and a comparison of the current status of district heating (DH) systems for selected Baltic Sea countries (Denmark, Germany, Finland, Latvia, Lithuania, Poland, and Sweden), especially from viewpoints of application and solutions of novel smart asset management (SAM) approaches. Furthermore, this paper considers European projects ongoing from 2016, involving participants from the...
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Smart platforms for collaborative urban design and peer-to-peer sharing of resources
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Model-Based Adaptive Machine Learning Approach in Concrete Mix Design
PublicationConcrete mix design is one of the most critical issues in concrete technology. This process aims to create a concrete mix which helps deliver concrete with desired features and quality. Contemporary requirements for concrete concern not only its structural properties, but also increasingly its production process and environmental friendliness, forcing concrete producers to use both chemically and technologically complex concrete...
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Quantum-correlation breaking channels, broadcasting scenarios, and finite Markov chains
PublicationOne of the classical results concerning quantum channels is the characterization of entanglementbreakingchannels [M. Horodecki et al., Rev. Math. Phys 15, 629 (2003)]. We address the questionwhether there exists a similar characterization on the level of quantum correlations which may gobeyond entanglement. The answer is fully affirmative in the case of breaking quantum correlationsdown to the, so called, QC (Quantum-Classical)...
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Modal analysis of temporary steel grandstand equipped with different bracing systems
PublicationThe aim of this paper is to present the results of numerical analysis focused on temporary steel scaffolding grandstand. The investigation has been devoted to modal analysis where modes of free vibrations and corresponding natural frequencies have been estimated and compared. The structure was equipped with different types of stiffener members. One on them is a typical tubular stiffener, while the second one is spe-cially designed...
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Relationships between Trust and Collaborative Culture in The Context of Tacit Knowledge Sharing
PublicationThe literature review presents a lot of theoretical and empirical evidence that Trust affects Collaborative Culture. The opposite also proves to be true: Collaborative Culture influences Trust. The main hypothesis presented in this paper says that both these factors are strongly correlated and modify each other. This study examines the mutual relationship of the said variables in the context of Tacit Knowledge Sharing based on...
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Smart heating system for home extending utilization of renewable energy sources
PublicationIn the paper a modern approach to smart home heating is presented. Proposed solution utilizes at least two low-polluting energy source technologies. The main idea is to connect well known ecological energy sources in a way that they can support each other and minimize risks of failure when using single system or even both of them but managed in separate way. Considered energy technologies, used separatelly, have disadvan-tages,...
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Analysis of 2D Feature Spaces for Deep Learning-based Speech Recognition
Publicationconvolutional neural network (CNN) which is a class of deep, feed-forward artificial neural network. We decided to analyze audio signal feature maps, namely spectrograms, linear and Mel-scale cepstrograms, and chromagrams. The choice was made upon the fact that CNN performs well in 2D data-oriented processing contexts. Feature maps were employed in the Lithuanian word recognition task. The spectral analysis led to the highest word...
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Knowledge Sharing and Organizational Culture Dimensions: Does Job Satisfaction Matter?
PublicationThe aim of this study is to examine how job satisfaction influences the relationship between company performance, knowledge sharing, and organizational culture, perceived through the prism of Hofstede’s cultural dimensions, controlled by company size and staff position. A survey of 910 Polish employees (mainly knowledge workers) with different roles and experiences across different industries was conducted. The data were analyzed...
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Real and Virtual Instruments in Machine Learning – Training and Comparison of Classification Results
PublicationThe continuous growth of the computing power of processors, as well as the fact that computational clusters can be created from combined machines, allows for increasing the complexity of algorithms that can be trained. The process, however, requires expanding the basis of the training sets. One of the main obstacles in music classification is the lack of high-quality, real-life recording database for every instrument with a variety...
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Optimization of using recuperative braking energy on a double-track railway line
PublicationIn the introduction, possible ways of reusing energy from recuperation are presented. Next, the paper investigates the possibility of using regenerative braking in the range allowed by the detailed timetable by adopting the method of transferring the recovered electric energy directly to the catenary and immediate use of this energy by another train at the same power section. In the main part of the work, it is shown, that the...
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Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublicationThis paper focuses on convolution neural network quantization problem. The quantization has a distinct stage of data conversion from floating-point into integer-point numbers. In general, the process of quantization is associated with the reduction of the matrix dimension via limited precision of the numbers. However, the training and inference stages of deep learning neural network are limited by the space of the memory and a...
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Effect of elliptical defect orientation on the durability of specimens subjected to cyclic bending
PublicationThis work presents the effect of elliptical defects orientation on the durability of specimens made of C45 steel. Three kinds of specimens with elliptical defects in the form of a one-sided notch oriented at different angles 45, 60, and 90 degrees were subjected to cyclic bending (R=-1). The stress state analysis was performed using local and non-local methods to determine an equivalent amplitude of stress, and then the results...
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Predictions of cervical cancer identification by photonic method combined with machine learning
PublicationCervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors...
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Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools
PublicationA high monetary value of the construction projects is one of the reasons of frequent disputes between a general contractor (GC) and a client. A construction site is a unique, one-time, and single-product factory with many parties involved and dependent on each other. The organizational dependencies and their complexity make any fault or mistake propagate and influence the final result (delays, cost overruns). The constant will...
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Deep learning for ultra-fast and high precision screening of energy materials
PublicationSemiconductor materials for energy storage are the core and foundation of modern information society and play important roles in photovoltaic system, integrated circuit, spacecraft technology, lighting applications, and other fields. Unfortunately, due to the long experiment period and high calculation cost, the high-precision band gap (the basic characteristic parameter) of semiconductor is difficult to obtain, which hinders the...
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Evaluation of aspiration problems in L2 English pronunciation employing machine learning
PublicationThe approach proposed in this study includes methods specifically dedicated to the detection of allophonic variation in English. This study aims to find an efficient method for automatic evaluation of aspiration in the case of Polish second-language (L2) English speakers’ pronunciation when whole words are analyzed instead of particular allophones extracted from words. Sample words including aspirated and unaspirated allophones...
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Determination of the Bending Properties of Wire Rope Used in Cable Barrier Systems
PublicationThis paper presents research on the bending properties of 3 × 7 19-mm wire rope commonly used in road cable barriers. A total of 19 experimental tests were conducted. In addition, two nonlinear 3D numerical models of the wire rope using beam and solid finite elements were developed. Based on these models, four numerical simulations were carried out. The numerical results were validated against the experimental ones and a very good...
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Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks
PublicationThe increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated...
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A Note on Knowledge Management Education: Towards Implementing Active Learning Methods
PublicationKnowledge Management as an area of education is still a big challenge for teachers and practitioners. Nevertheless, there are several useful teaching methods in active education, especially oriented towards courses where innovation and delivering dynamic knowledge are critical. The goal of the paper is to present and discuss criteria relevant in the selection of active educational methods supporting knowledge management courses....
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Deep learning based thermal image segmentation for laboratory animals tracking
PublicationAutomated systems for behaviour classification of laboratory animals are an attractive alternative to manual scoring. However, the proper animals separation and tracking, especially when they are in close contact, is the bottleneck of the behaviour analysis systems. In this paper, we propose a method for the segmentation of thermal images of laboratory rats that are in close contact during social behaviour tests. For this, we are...
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Multi-scale modelling of concrete beams subjected to three-point bending
PublicationW artykule przedstawiono wyniki numeryczne MES dwuskalowego modelowania belek betonowych z nacięciem na poziomie skali makro i mezo. Obliczenia wykonano przy wykorzystaniu modelu degradacji sztywności z nielokalnym osłabieniem. Beton został opisany na poziomie skali mezo jako stochastyczny materiał 3-składnikowy złożony z kruszywa, zaczynu cementowego oraz stref kontaktu. Natomiast na poziomie skali makro został opisany jako materiał...
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Nanosecond pulsed electric fields (nsPEFs) impact and enhanced Photofrin II® delivery in photodynamic reaction in cancer and normal cells
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Transmembrane Transport and Anticancer Activity of Strontium Ranelate Delivered with Nanosecond Pulsed Electric Fields (nsPEFs) into Human Cells in Vitro
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Geometrically nonlinear FEM analysis of FGM shells based on neutral physical surface approach in 6-parameter shell theory
PublicationThe paper presents the formulation of the elastic constitutive law for functionally graded materials (FGM) on the grounds of nonlinear 6-parameter shell theory with the 6th parameter being the drilling degree of freedom. The material law is derived by through-the-thickness integration of the Cosserat plane stress equations. The constitutive equations are formulated with respect to the neutral physical surface. The influence of...
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Inhomogeneity of low-noise wearing courses evaluated by tire/road noise measurements using the close-proximity method
PublicationPerforming numerous analyses of tire/road noise measurements on low-noise pavements during the last several years, the authors observed significant inhomogeneity of the wearing course in numerous cases, while similar problems were almost non-existent when dense pavements were measured. Three main causes of low-noise pavement inhomogeneity can be defined. The first one is imperfections in the technology used for asphalt mix production...
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On the effectiveness of Ni alloy-bronze composite lattice structures used in slide bearings operated under heavy loads
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Observing its long-term effects on a short-term, multi-day evaluation of the effectiveness of hearing aid use
PublicationThe main objective of the research study was to develop a method for evaluating the effectiveness of hearing protection with hearing aids tailored to the needs and prevailing conditions in the acoustic environments where the elderly most often reside. The method was also intended to estimate the benefits of hearing aids and allow prediction of such an effect based on a short-term trial. It is noteworthy that a short-term evaluation...
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INFLUENCE OF SOLID PARTICLE CONTAMINATION ON THE WEAR PROCESS IN WATER LUBRICATED MARINE STRUT BEARINGS WITH NBR AND PTFE BUSHES
PublicationThis paper reports on a study of the influence of solid particle contamination on the wear process in water-lubricated slide bearings (steel-acrylonitrile-butadiene rubber (NBR) and steel- polytetrafluoroethylene (PTFE)). To compare the wear of the shaft journal and bushes (NBR and PTFE) when lubricated with fresh water and contaminated water, an experiment was carried out to identify key factors that influence the state of wear...
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The Experimental Determination of Bearings Dynamic Coefficients in a Wide Range of Rotational Speeds, Taking into Account the Resonance and Hydrodynamic Instability
PublicationMethods for the experimental determination of dynamic coefficients are commonly used for the analysis of various types of bearings, including hydrodynamic, aerodynamic and foil bearings. There are currently several algorithms that allow estimating bearing dynamic coefficients. Such algorithms usually use various excitation techniques applied to rotor–bearings systems. So far only a small number of scientific publications show how...
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Ocena wybranych własności materiałowych polimerowej warstwy ślizgowej hydrodynamicznego łożyska wzdłużnego = An estimation of selected material properties of the hydrodynamic thrust bearing polymer lining
PublicationZaprezentowano metody pomiaru najważniejszych własności mechanicznych i cieplnych polimerowego pokrycia segmentowego łożyska wzdłużnego, do których zaliczyć należy moduł sprężystości wzdłużnej oraz współczynnik przewodności cieplnej materiału dodatkowym utrudnieniem planowanego zadania jest fakt, że próbka do badań dostępna będzie jedynie w formie wycinka z segmentu łożyskowego, z tego powodu nie jest możliwe zastosowanie ogólnie...
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A surface-exposed DraD protein of uropathogenic Escherichia coli bearing Dr fimbriae may be expressed and secreted independently from DraC usher and DraE adhesin
PublicationOperon dra uropatogennych szczepów Escherichia coli Dr+ odpowiedzialny jest za proces bakteryjnej adhezji i inwazji. Operon dra kodujący fimbrie Dr zawiera sześć otwartych ramek odczytu - draA, draB, draC, draD, draP oraz draE. Fimbrie Dr zlokalizowane na powierzchni komórki bakteryjnej, zbudowane są z podjednostek białka DraE. Niewiele wiadomo na temat powierzchniowej ekspresji białka DraD oraz jego roli w procesie biogenezy fimbrii...
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Analiza nośności zabytkowych fundamentów w kontekście jakości użytych zapraw Analysis of the Load-Bearing Capacity of Historical Foundations in the Context of the Quality of Mortar Used
PublicationStructures of historical buildings usually have the form of masonry elements. The weakest component of such elements is mortar, especially in stone foundations, which were often used in the with a focus on the modeling of mortar as a joint connecting stones in a characteristic medieval foundation. Different types of mortar: cement, cement-lime, lime and gypsum mortars, were examined. A numerical analysis was carried out on the...
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Caring for patients with Huntington disease – A survey of caregivers’ experiences and views
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Scene Segmentation Basing on Color and Depth Images for Kinect Sensor
PublicationIn this paper we propose a method for segmenting single images from Kinect sensor by considering both color and depth information. The algorithm is based on a series of edge detection procedures designed for particular features of the scene objects. RGB and HSV color planes are separately analyzed in the first step with Canny edge detector, resulting in overall color edges mask. In depth images both clear boundaries and smooth...
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Respiratory system modelling and simulation basing on the forced oscilation technique
PublicationConventional methods of testing lung functioning demand a specific respiratory action of the patient. In contrast, the forced oscillation technique (fot) provides measurements obtained with a minimal cooperation of the subject. The aim of this study is to verify the usefulness of the forced oscillation technique modelling in respiratory system diagnosing. in order to do it two models of fot measurements have been considered: the...
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Model of speed-varing rotor for mechatronic systems analysis and design
PublicationW artykule przedstawiono sposób modelowania złożonych układów mechatronicznych w oparciu o metodę grafów wiązań. Celem zilustrowania metody posłużono się przykładem liczbowym, w którym rozważano wirnik obracający się ze zmienną prędkością kątową. Prezentowana metodyka doskonale nadaje się do modelowania układów o zróżnicowanej naturze fizycznej. Otrzymany model ma charakter obiektu o pewnej liczbie wejść i wyjść, który można w...
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Building federation of digital libraries basing on concept of atomic services
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From evil demiurge to caring hero: Images of geneticists in the movies
PublicationAlthough images of science and scientists depicted in popular culture have been criticized as an exaggeration and fear mongering, the cinema is an important resource that influences individuals’ beliefs about science. Because popular depictions of science play a crucial role in constructing the public’s ‘scientific imaginary’ they constitute an inherent dimension of the social understanding of science and are as important for...
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From evil demiurge to caring hero: images of geneticists in the movies
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Parental experiences and needs of caring for a child with 22q11.2 deletion syndrome
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