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Search results for: FIBER-REINFORCED CONCRETE BEAM, CHAINED MACHINE LEARNING MODEL, DUCTILITY INDEX, BENDING LOAD CAPACITY, ARTIFICIAL NEURAL NETWORKS
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Prediction of the Biogenic Amines Index of Poultry Meat Using an Electronic Nose
PublicationThe biogenic amines index of fresh chicken meat samples during refrigerated storage was predicted based on the headspace analysis using an electronic nose equipped with an array of electrochemical sensors. The reference biogenic amines index values were obtained using dispersive liquid–liquid microextraction–gas chromatography–mass spectrometry. A prototype electronic nose with modular construction and a dedicated sample chamber...
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Neural networks in the diagnostics of induction motor rotor cages.
PublicationW środowisku Lab VIEW została stworzona aplikacja służąca do pomiaru, prezentacji i zapisu przebiegów widma prądu stojana z uwzględnieniem potrzeb pomiarowych występujących podczas badania wirników silników indukcyjnych przy użyciu sieci neuronowych. Utworzona na bazie zbioru uczącego sieć Kohonena z powodzeniem rozwiązała stawiany przed nią problem klasyfikacji widm prądu stojana, a co za tym idzie również diagnozy stanu...
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Applications of neural networks and perceptual masking to audio restoration
PublicationOmówiono zastosowania algorytmów uczących się w dziedzinie rekonstruowania nagrań fonicznych. Szczególną uwagę zwrócono na zastosowanie sztucznych sieci neuronowych do usuwania zakłócających impulsów. Ponadto opisano zastosowanie inteligentnego algorytmu decyzyjnego do sterowania maskowaniem perceptualnym w celu redukowania szumu.
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Application of neural networks for turbine rotor trajectory investigation.
PublicationW pracy przedstawiono rezultaty badań sieci neuronowych przewidujących trajektorię wirnika turbinowego uzyskanych ze stanowiska turbiny modelowej. Badania wykazały, iż sieci neuronowe wydają się być z powodzeniem zastosowane do przewidywania trajektorii ruchu wirnika turbiny. Najważniejszym zadaniem wydaje się poprawne określenie wektorów sygnałów wejściowych oraz wyjściowych jak również prawidłowe stworzenie sieci neuronowej....
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Problems in toxicity analysis - application of fuzzy neural networks
PublicationPraca dotyczy zastosowania sztucznych sieci neuronowych do przygotowywania danych do szacowania toksyczności (wody powierzchniowe). Przygotowanie to polega na sztucznym zagęszczaniu zbioru danych, które następnie mogą być wykorzystane do szacowania/modelowania wartości toksyczności na ich podstawie.
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On some problems in determining tensile parameters of concrete model from size effect tests
PublicationThe paper presents results of numerical simulations of size effect phenomenon in concrete specimens. The behaviour of in-plane geometrically similar notched and unnotched beams under three-point bending is investigated. In total 18 beams are analysed. Concrete beams of four different sizes and five different notch to depth ratios are simulated. Two methods are applied to describe cracks. First, an elasto-plastic constitutive law...
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Experimental method to evaluate the load-carrying capacity of double corrugated sheet profiles
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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublicationThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...
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System Loss Model for Body-to-Body Networks in Indoor and Outdoor Environments
PublicationA system loss model for body-to-body networks in indoor and outdoor environments is proposed in this paper, based on measurements taken at 2.45 GHz. The influence of the type of environment, antenna visibility and user mobility on model parameters has been investigated. A significant impact of mutual antennas’ placement and their visibility is shown. The proposed model fits well to empirical data, with the average root mean square...
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Size effect in concrete under splitting tension
PublicationThe size effect is a fundamental phenomenon in concrete materials. It denotes that both the nominal structural strength and material ductility always decrease with increasing element size under tension. In the paper splitting tensile tests on cylindrical concrete specimens with the different diameter were carried out. Two types of the loading strip (plywood board and steel cylinder) were used. The concrete strength and ductility...
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Experimental measurements of artificial hip joint surfaces and applications for the preassure and capacity distributions
PublicationZe względu na wzrastającą potrzebę wszczepiania człowiekowi endoprotez stawu biodrowego, niniejsza praca przedstawia badania geometrycznej struktury ich powierzchni, które mają znaczący wpływ na proces smarowania, eksploatacji oraz funkcjonowanie narządów ruchu.
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ANALYSIS OF IMPACT of SHIP model parameters on changes of control quality index in ship dynamic positioning system
PublicationIn this work there is presented an analysis of impact of ship model parameters on changes of control quality index in a ship dynamic positioning system designed with the use of a backstepping adaptive controller. Assessment of the impact of ship model parameters was performed on the basis of Pareto-Lorentz curves and ABC method in order to determine sets of the parameters which have either crucial, moderate or low impact on objective...
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Modeling of Wireless Traffic Load in Next Generation Wireless Networks
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Load introduction to composite columns revisited—Significance of force allocation and shear connection stiffness
PublicationThe AISC 360-16 Specification recommends that the design shear force between parts of a composite column in the load introduction area shall be calculated based on the force allocation at ultimate limit state. Applicability of this straightforward method to the load levels that usually arise in slender composite columns is questionable, as this capacity-based force allocation is only true when the axial force is equal to the plastic...
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Displacement piles - classification and methods for the calculation of bearing capacity.
PublicationDisplacement piles belong to a group of technologies whose main idea is to install or make a pile without extracting ground material. According to definition, contained in PN-EN:1997-1:2008, displacement piles should be considered as driven, pressed in using vibrators and made with the use of spread augers. The classification of piles used so far with regard to the technology of execution is modified. An additional element is the...
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Determination of the rigidity and deformation energy of the technological machine load-carrying systems
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Simplified approach to assess the dynamic response of a container ship subjected to bow slamming load
PublicationSimplified approach to assess the dynamic response of a container ship subjected to the bow slamming load, resulting in a transient vibratory response, typically called a 'whip-ping', is presented. The accurate numerical modelling is very complex and involves cou-pling of the hydrodynamic and structural solution at every time step, leading to huge com-putational and workload cost. Thus, the one-way coupling methodology is adopted,...
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Artificial-Neural-Network-Based Sensorless Nonlinear Control of Induction Motors
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Ultracapacitor modeling and control with discrete fractional order artificial neural network
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On thermal and Flow Expert Systems Based on Artificial Neural Network (ANN)
PublicationZaprezentowano możliwość realizacji jednego z zadań systemów eksperckich, polegającego na określaniu rozmiaru eksploatacyjnej degradacji parametrów geometrycznych układów łopatkowych turbin. Dyskusję przeprowadzono w oparciu o zastosowanie wybranego typu sztucznej sieci neuronowej (SSN). Badano jakość i dokładność polegającą na dobrej identyfikacji rozmiaru degradacji przez tę wybraną SSN wykrywającą rozmiar degradacji geometrycznej....
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Artificial Neural Network-Based Sensorless Nonlinear Control Of Induction Motors
PublicationW niniejszym artykule przedstawiono strukturę sztucznej sieci neuronowej służącej do korygowania działania układu estymacji prędkości kątowej wirnika. Odtworzona prędkość kątowa wirnika zostały wykorzystane w bezczujnikowym układzie sterowania silnikiem indukcyjnym pracującym w zamkniętej pętli sprzężenia prędkościowego.Przedstawiono wyniki badań eksperymentalnych z silnikiem o mocy 1,1kW.
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System Loss Model for Body Area Networks in Room Scenarios
PublicationThis paper presents an analysis of system loss in Body Area Networks for room scenarios, based on a wideband measurement campaign at 5.8 GHz. The measurements were performed with a fixed antenna transmitting vertically and horizontally polarised signals, while the user wears dualpolarised antennas. The average system losses in co- and crosspolarised channels are 41.4 and 42.6 dB for vertically polarised transmitted signals and...
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LOS and NLOS identification in real indoor environment using deep learning approach
PublicationVisibility conditions between antennas, i.e. Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) can be crucial in the context of indoor localization, for which detecting the NLOS condition and further correcting constant position estimation errors or allocating resources can reduce the negative influence of multipath propagation on wireless communication and positioning. In this paper a deep learning (DL) model to classify LOS/NLOS...
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Machine-Learning-Powered EM-Based Framework for Efficient and Reliable Design of Low Scattering Metasurfaces
PublicationPopularity of metasurfaces has been continuously growing due to their attractive properties including the ability to effectively manipulate electromagnetic (EM) waves. Metasurfaces comprise optimized geometries of unit cells arranged as a periodic lattice to obtain a desired EM response. One of their emerging application areas is the stealth technology, in particular, realization of radar cross section (RCS) reduction. Despite...
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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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Numerical investigations on early indicators of fracture in concrete at meso-scale.
PublicationFracture is a major reason of the global failure of concretes. The understanding of fracture is important to ensure the safety of structures and to optimize the material behaviour. In particular an early prediction possibility of fracture in concretes is of major importance. In this paper, concrete fracture under bending was numerically analysed using the Discrete Element Method (DEM). The real mesoscopic structure of a concrete...
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Creating a radiological database for automatic liver segmentation using artificial intelligence.
PublicationImaging in medicine is an irreplaceable stage in the diagnosis and treatment of cancer. The subsequent therapeutic effect depends on the quality of the imaging tests performed. In recent years we have been observing the evolution of 2D to 3D imaging for many medical fields, including oncological surgery. The aim of the study is to present a method of selection of radiological imaging tests for learning neural networks.
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Evolving gene regulatory networks controlling foraging strategies of prey and predators in an artificial ecosystem
PublicationCo-evolution of predators and prey is an example of an evolutionary arms race, leading in nature to selective pressures in positive feedback. We introduce here an artificial life ecosystem in which such positive feedback can emerge. This ecosystem consists of a 2-dimensional liquid environment and animats controlled by evolving artificial gene regulatory networks encoded in linear genomes. The genes in the genome encode chemical...
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Reduced model of gyroscopic system
PublicationThe paper presents the method of model reduction for the system with gyroscopic interactions. Two methods were used to obtain the approximate discrete models of the continuous structure: the modal decomposition method and the rigid finite element method. The first approach is used for this part of a system for which it is easy to formulate orthogonality conditions, meanwhile the second one is used for other part. The method enables...
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Neural reliability model of diesel engines
PublicationW artykule przedstawiono wyniki weryfikacji hipotezy zakładającej celowość zastosowania modelu niezawodnościowego silnika tłokowego z zapłonem samoczynnym w postaci sztucznej sieci neuronowej. Weryfikację przeprowadzono w oparciu o wyniki badań eksploatacyjnych.
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Chemical and Mechanical Properties of 70-Year-Old Concrete
PublicationThe aim of this research is to determine the durability and strength of concrete continuous footing based on the chosen mechanical, physical, and chemical properties of the concrete. The presented investigations constitute some opinions from experts on the bearing capacity of concrete continuous footing and the possibilities of carrying additional loads and extended working life. The cylindrical specimens were taken from continuous...
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Machinability investigation in electric discharge machining of carbon fiber reinforced composites for aerospace applications
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An Improved Convolutional Neural Network for Steganalysis in the Scenario of Reuse of the Stego-Key
PublicationThe topic of this paper is the use of deep learning techniques, more specifically convolutional neural networks, for steganalysis of digital images. The steganalysis scenario of the repeated use of the stego-key is considered. Firstly, a study of the influence of the depth and width of the convolution layers on the effectiveness of classification was conducted. Next, a study on the influence of depth and width of fully connected...
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Artificial Intelligence Aided Architectural Design
PublicationTools and methods used by architects always had an impact on the way building were designed. With the change in design methods and new approaches towards creation process, they became more than ever before crucial elements of the creation process. The automation of architects work has started with computational functions that were introduced to traditional computer-aided design tools. Nowadays architects tend to use specified tools...
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Flexible Knowledge–Vision–Integration Platform for Personal Protective Equipment Detection and Classification Using Hierarchical Convolutional Neural Networks and Active Leaning
PublicationThis work is part of an effort to develop of a Knowledge-Vision Integration Platform for Hazard Control (KVIP-HC) in industrial workplaces, adaptable to a wide range of industrial environments. The paper focuses on hazards resulted from the non-use of personal protective equipment (PPE). The objective is to test the capability of the platform to adapt to different industrial environments by simulating the process of randomly selecting...
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An influence of the ship's block coefficient implementation on the evaluation of it's hull girder bending
PublicationAn influence of the three different ways of implementation ship's block coefficient δ (three geometrical models) on the stresses due to wave bending moment have been investigated. Two models have been applied and compared: beam one (description of the shape usingparameters) and FEM shell model (direct representation of the shape). The outcomes have been compared to Polish Register of Shipping (PRS) rules. The results show that...
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Experimental and numerical investigations of size effects in reinforced concrete beams with steel or basalt bars.
PublicationW artykule przedstawiono wyniki obliczeń efektów skali w belkach betonowych zbrojonych prętami stalowymi i bazaltowymi podczas zginania. Zastosowano model sprężysto-plastyczny z nielokalnym osłabieniem. Rozkład wytrzymałości na rozciąganie był stochastyczny – przestrzennie skorelowany. Belki były geometrycznie podobne. Wyniki porównano z modelem efektu skali Bazanta
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Towards neural knowledge DNA
PublicationIn this paper, we propose the Neural Knowledge DNA, a framework that tailors the ideas underlying the success of neural networks to the scope of knowledge representation. Knowledge representation is a fundamental field that dedicates to representing information about the world in a form that computer systems can utilize to solve complex tasks. The proposed Neural Knowledge DNA is designed to support discovering, storing, reusing,...
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The Neural Knowledge DNA Based Smart Internet of Things
PublicationABSTRACT The Internet of Things (IoT) has gained significant attention from industry as well as academia during the past decade. Smartness, however, remains a substantial challenge for IoT applications. Recent advances in networked sensor technologies, computing, and machine learning have made it possible for building new smart IoT applications. In this paper, we propose a novel approach: the Neural Knowledge DNA based Smart Internet...
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BEHAVIOR OF REINFORCED CONCRETE BEAMS CONTAINING LIGHTWEIGHT AGGREGATE IN THE TENSILE ZONE
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Experimental investigations of size effect in reinforced concrete beams failing by shear
PublicationW artykule omówiono wyniki doświadczalne efektu skali w zbrojonych betonowych belkach niszczących się przez ścinanie. Doświadczenia wykonano dla belek o różnych wymiarach ze zbrojeniem stalowym i bazaltowym. Podczas doświadczeń pomierzono siłę oraz szerokości lokalizacji i rys. Wyniki porównano z modelem skali wg Bazanta.
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Numerical analysis of behaviour of reinforced concrete elements under eccentric compression
PublicationPrzedstawiono wyniki modelowania nośności elementów żelbetowych stosując metodę elementów skończonych. Do opisu betonu zastosowano sprężysto-plastyczne prawo materiałowe wg Druckera-Pragera. Do modelowania stali zbrojeniowej zastosowano sprężysto-plastyczne prawo materiałowe według von Misesa. Obliczenia wykonano dla ścian żelbetowych.
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A general theory for anisotropic Kirchhoff–Love shells with in-plane bending of embedded fibers
PublicationThis work presents a generalized Kirchhoff–Love shell theory that can explicitly capture fiber-induced anisotropy not only in stretching and out-of-plane bending, but also in in-plane bending. This setup is particularly suitable for heterogeneous and fibrous materials such as textiles, biomaterials, composites and pantographic structures. The presented theory is a direct extension of classical Kirchhoff–Love shell theory to incorporate...
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Cleaner energy for sustainable future using hybrid photovoltaics-thermoelectric generators system under non-static conditions using machine learning based control technique
PublicationIn addition to the load demand, the temperature difference between the hot and cold sides of the thermoelectric generator (TEG) module determines the output power for thermoelectric generator systems. Maximum power point tracking (MPPT) control is needed to track the optimal global power point as operating conditions change. The growing use of electricity and the decline in the use of fossil fuels have sparked interest in photovoltaic-TEG...
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PTD4 Peptide Increases Neural Viability in an In Vitro Model of Acute Ischemic Stroke
PublicationIschemic stroke is a disturbance in cerebral blood flow caused by brain tissue ischemia and hypoxia. We optimized a multifactorial in vitro model of acute ischemic stroke using rat primary neural cultures. This model was exploited to investigate the pro-viable activity of cell-penetrating peptides: arginine-rich Tat(49–57)-NH2 (R49KKRRQRRR57-amide) and its less basic analogue, PTD4 (Y47ARAAARQARA57-amide). Our model included glucose...
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A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine
PublicationRNA protein interactions (RPI) play a pivotal role in the regulation of various biological processes. Experimental validation of RPI has been time-consuming, paving the way for computational prediction methods. The major limiting factor of these methods has been the accuracy and confidence of the predictions, and our in-house experiments show that they fail to accurately predict RPI involving short RNA sequences such as TERRA RNA....
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Test-supported numerical analysis for evaluation of the load capacity of thin-walled corrugated profiles
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GPU Power Capping for Energy-Performance Trade-Offs in Training of Deep Convolutional Neural Networks for Image Recognition
PublicationIn the paper we present performance-energy trade-off investigation of training Deep Convolutional Neural Networks for image recognition. Several representative and widely adopted network models, such as Alexnet, VGG-19, Inception V3, Inception V4, Resnet50 and Resnet152 were tested using systems with Nvidia Quadro RTX 6000 as well as Nvidia V100 GPUs. Using GPU power capping we found other than default configurations minimizing...
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Advanced current regulated PWM inverter with simplified load model.
PublicationW artykule przedstawionio nowy regulator prądu stojana silnika asynchronicznego zasilanego z falownika napięcia. Regulator wykorzystuje obliczenia siły elektromotorycznej silnika. Rozważonio wpływ zmian parametrów silnika na działanie regulatora. Wykorzystano uproszczony model silnika bez uwzględnienienia rezystancji stojana. Zastosowano stałą częstotliwość próbkowania prądu. Układ zrealizowania w programie symulacyjnym oraz na...
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Neural networks based NARX models in nonlinear adaptive control
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