Filtry
wszystkich: 13627
wybranych: 11128
-
Katalog
- Publikacje 11128 wyników po odfiltrowaniu
- Czasopisma 337 wyników po odfiltrowaniu
- Konferencje 151 wyników po odfiltrowaniu
- Osoby 279 wyników po odfiltrowaniu
- Wynalazki 1 wyników po odfiltrowaniu
- Projekty 29 wyników po odfiltrowaniu
- Laboratoria 1 wyników po odfiltrowaniu
- Aparatura Badawcza 12 wyników po odfiltrowaniu
- Kursy Online 234 wyników po odfiltrowaniu
- Wydarzenia 11 wyników po odfiltrowaniu
- Dane Badawcze 1444 wyników po odfiltrowaniu
Filtry wybranego katalogu
wyświetlamy 1000 najlepszych wyników Pomoc
Wyniki wyszukiwania dla: FIBER-REINFORCED CONCRETE BEAM, CHAINED MACHINE LEARNING MODEL, DUCTILITY INDEX, BENDING LOAD CAPACITY, ARTIFICIAL NEURAL NETWORKS
-
Innovative Cold-formed GEB Section under Bending
PublikacjaThis paper is concerned with the numerical bending capacity study of the innovative cold-formed GEB sections. Both linear buckling analysis and non-linear static analysis incorporating geometric and material nonlinearity were carried out employing a shell structural model. The magnitudes of buckling load and limit load with respect to GEB section depth and thickness were obtained. The opened cold-formed section was tested assuming...
-
Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublikacjaIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
-
Machine learning approach to packaging compatibility testing in the new product development process
PublikacjaThe paper compares the effectiveness of selected machine learning methods as modelling tools supporting the selection of a packaging type in new product development process. The main goal of the developed model is to reduce the risk of failure in compatibility tests which are preformed to ensure safety, durability, and efficacy of the finished product for the entire period of its shelf life and consumer use. This kind of testing...
-
Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks
PublikacjaThe 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...
-
Noise profiling for speech enhancement employing machine learning models
PublikacjaThis paper aims to propose a noise profiling method that can be performed in near real-time based on machine learning (ML). To address challenges related to noise profiling effectively, we start with a critical review of the literature background. Then, we outline the experiment performed consisting of two parts. The first part concerns the noise recognition model built upon several baseline classifiers and noise signal features...
-
A study on fibre-reinforced concrete elements properties based on the case of habitat modules in the underwater sills
PublikacjaHydrotechnical constructions are mostly objects functioning in extreme conditions and requiring a custom-made construction project. In the case of using prefabricated elements, it is required to develop production, transport, assembly, conservation and repair technology. Concerning the problem of concrete cracks, modern repair systems allow positive effects to be achieved in many cases of concrete elements repair. In this work...
-
Stochastic model of the load spectrum for main engines of sea-going ships
PublikacjaW artykule przedstawiono możliwość zastosowania procesów semimarkowskich do probabilistycznego opisu widma obciążeń silników o zapłonie samoczynnym, zastosowanych do napędu statków - czyli silników głównych. W rozważaniach uwzględnione zostały charakterystyki zewnętrzne mocy tego rodzaju silników. Umożliwiły one sformułowanie czteroelementowego zbioru stanów procesu obciążeń tego rodzaju silników. Do opisu rzeczywistego procesu...
-
Automatic Breath Analysis System Using Convolutional Neural Networks
PublikacjaDiseases related to the human respiratory system have always been a burden for the entire society. The situation has become particularly difficult now after the outbreak of the COVID-19 pandemic. Even now, however, it is not uncommon for people to consult their doctor too late, after the disease has developed. To protect patients from severe disease, it is recommended that any symptoms disturbing the respiratory system be detected...
-
Automatic Breath Analysis System Using Convolutional Neural Networks
PublikacjaDiseases related to the human respiratory system have always been a burden for the entire society. The situation has become particularly difficult now after the outbreak of the COVID-19 pandemic. Even now, however, it is common for people to consult their doctor too late, after the disease has developed. To protect patients from severe disease, it is recommended that any symptoms disturbing the respiratory system be detected as...
-
Architectural Modifications to Enhance Steganalysis with Convolutional Neural Networks
PublikacjaThis paper investigates the impact of various modifications introduced to current state-of-the-art Convolutional Neural Network (CNN) architectures specifically designed for the steganalysis of digital images. Usage of deep learning methods has consistently demonstrated improved results in this field over the past few years, primarily due to the development of newer architectures with higher classification accuracy compared to...
-
Downlink Capacity-Coverage Trade-off Estimation Based on Measurement of WCDMA/FDD Interface Load
PublikacjaThe method of capacity-coverage trade-off determination by using of universal load characteristics and normalized coverage curves for the WCDMA/FDD radio interface has been presented. The practical applications of discussed method for UMTS radio network planning process and network exploitation has been mentioned.
-
Use of Neural Networks in Diagnostics of Rolling-Element Bearing of the Induction Motor
PublikacjaBearing defect is statistically the most frequent cause of an induction motor fault. The research described in the paper utilized the phenomenon of the current change in the induction motor with bearing defect. Methods based on the analysis of the supplying current are particularly useful when it is impossible to install diagnostic devices directly on the motor. The presented method of rolling-element bearing diagnostics used indirect...
-
Crack monitoring in concrete beams under bending using ultrasonic waves and coda wave interferometry: the effect of excitation frequency on coda
PublikacjaConcrete is one of the most widely used construction materials in the world. In recent years, various non-destructive testing (NDT) and structural health monitoring (SHM) techniques have been investigated to improve the safety and control of the current condition of concrete structures. This study focuses on micro-crack monitoring in concrete beams. The experimental analysis was carried out on concrete elements subjected to three-point...
-
Convolutional Neural Networks for C. Elegans Muscle Age Classification Using Only Self-Learned Features
PublikacjaNematodes Caenorhabditis elegans (C. elegans) have been used as model organisms in a wide variety of biological studies, especially those intended to obtain a better understanding of aging and age-associated diseases. This paper focuses on automating the analysis of C. elegans imagery to classify the muscle age of nematodes based on the known and well established IICBU dataset. Unlike many modern classification methods, the proposed...
-
Influence of artificial thermal ageing on polyester-reinforced and polyvinyl chloride coated AF9032 technical fabric
PublikacjaThe presented work deals with the thermal ageing evaluation for polyester-reinforced and polyvinyl chloride coated fabrics. The architectural fabric AF9032 was exposed to artificial thermal ageing by subjecting the material samples to temperature levels of 80℃ and 90℃ for up to 12 weeks. The mechanical properties of the aged fabric have been separately described by the identified linear piecewise model (with assumption of the elastic...
-
Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublikacjaBiochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts,...
-
The vibration-based assessment of the influence of elevated temperature on the condition of concrete beams with pultruded GFRP reinforcement
PublikacjaConcrete beams reinforced with glass fiber reinforced polymer (GFRP) bars subjected to elevated temperature have been experimentally studied. The influence of high temperatures on GFRP-reinforced concrete beams condition has been check both, destructively and nondestructively. The nondestructive tests foresaw vibration-based tests to obtain the natural frequency values after exposure to varying temperatures. The vibration-based...
-
Machine Learning Algorithm-Based Tool and Digital Framework for Substituting Daylight Simulations In Early- Stage Architectural Design Evaluation
PublikacjaThe aim of this paper is to examine the new method of obtaining the simulation-based results using backpropagation of errors artificial neural networks. The primary motivation to conduct the research was to determine an alternative, more efficient and less timeconsuming method which would serve to achieve the results of daylight simulations. Three daylight metrics: Daylight Factor, Daylight Autonomy and Daylight Glare Probability have...
-
Mechanical properties of sisal fiber-reinforced soybean oil-based polyurethane biocomposites
PublikacjaIn this paper the results of the mechanical properties of polyurethane biocomposites reinforced with short sisal fibers are presented. The fillers were added in different amount: 5, 10 and 15% by mass. Tensile test, hardness, abrasion resistance, elasticity were determined according to the standards.
-
Comparison of Deep Neural Network Learning Algorithms for Mars Terrain Image Segmentation
PublikacjaThis paper is dedicated to the topic of terrain recognition on Mars using advanced techniques based on the convolutional neural networks (CNN). The work on the project was conducted based on the set of 18K images collected by the Curiosity, Opportunity and Spirit rovers. The data were later processed by the model operating in a Python environment, utilizing Keras and Tensorflow repositories. The model benefits from the pretrained...
-
Diagnosis of damages in family buildings using neural networks
PublikacjaThe article concerns a problem of damages in family buildings, which result from traffic-induced vibrations. These vibrations arise from various causes and their size is influenced by many factors. The most important is the type of a road, type and weight of vehicles that run on the road, type and condition of the road surface, the distance from the house to the source of vibrations and many others which should be taken into account....
-
Comparison of selected clustering algorithms of raw data obtained by interferometric methods using artificial neural networks
Publikacja -
Blood Pressure Estimation Based on Blood Flow, ECG and Respiratory Signals Using Recurrent Neural Networks
PublikacjaThe estimation of systolic and diastolic blood pressure using artificial neural network is considered in the paper. The blood pressure values are estimated using pulse arrival time, and additionally RR intervals of ECG signal together with respiration signal. A single layer recurrent neural network with hyperbolic tangent activation function was used. The average blood pressure estimation error for the data obtained from 21 subjects...
-
Retrofit analysis of florida beam-and-post reinforced concreta bridge barriers
PublikacjaTematem pracy jest analiza przebiegu kolizji drogowych w przypadku najechania rozpędzonego pojazdu na betonową barierę mostową typu "Florida beam-and-post". Przedstawiono podstawy konstruowania modelu obliczeniowego do komputerowej symulacji zderzenia przy wykorzystaniu systemu LS-Dyna. Na podstawie otrzymanych wyników sformułowano zalecenia ewentualnych modyfikacji istniejących barier w celu poprawienia ich własności.
-
A Selection of Starting Points for Iterative Position Estimation Algorithms Using Feedforward Neural Networks
PublikacjaThis article proposes the use of a feedforward neural network (FNN) to select the starting point for the first iteration in well-known iterative location estimation algorithms, with the research objective of finding the minimum size of a neural network that allows iterative position estimation algorithms to converge in an example positioning network. The selected algorithms for iterative position estimation, the structure of the...
-
3D X-ray Micro-CT Analysis of Rebar Corrosion in Reinforced Concrete Subjected to a Chloride-Induced Environment
PublikacjaThe paper presents experimental investigations of the concrete cover protective ability to coun-teract rebar corrosion in reinforced concrete cubes. To study and quantify the consequences of corrosion a reinforced concrete sample was subjected to chloride-induced environment in order to get corroded and combined with un-corroded sample. Chloride-accelerated technique can in-duce a high degree of corrosion within at a controlled...
-
Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublikacjaCatheter-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...
-
Concrete-filled FRP tubular members in marine and bridge structures
PublikacjaConcrete core of the concrete-filled tubes (CFTs) with circular cross-section is in the case of an axial compression subjected to a spatial state of compressive stresses. This state leads to enhancement in the concrete strength. The enhancement is utilized in Eurocode 4 design procedures for CFSTs (i.e. CFTs with tube made of steel). The structural design of CFFTs (i.e. CFTs with tube made of Fibre Reinforced Polymer - FRP) is...
-
A review on application of artificial neural network (ANN) for performance and emission characteristics of diesel engine fueled with biodiesel-based fuels
PublikacjaBiodiesel has been emerging as a potential and promising biofuel for the strategy of reducing toxic emissions and improving engine performance. Computational methods aiming to offer numerical solutions were inevitable as a study methodology which was sometimes considered the only practical method. Artificial neural networks (ANN) were data-processing systems, which were used to tackle many issues in engineering and science, especially...
-
Static and dynamic concrete calculations: Breakable aggregates in DEM model
PublikacjaThe paper deals with the calculations of a 3-point bending beam under static and dynamic loads. The real microstructure was obtained from laboratory tests using micro-tomography images. The quasi-static results were compared directly with experimental data at both macro and micro levels. Subsequently, higher strain rates were applied to investigate dynamic effects. The study focused on the influence of dynamic loading on the macroscopic...
-
Approximation task decomposition for artificial neural network.
PublikacjaW pracy przedstawiono wpływ dekompozycji zadania na czasochłonność projektowania oraz dokładność i szybkość obliczeń sztucznej sieci neuronowej wykorzystanej do rozwiązania rzeczywistego problemu technicznego, którego matematyczny model był znany. Celem obliczeń prowadzonych przez sieć neuronową było określenie wartości współczynnika przepływu m na podstawie znajomości wartości: przewodności dźwiękowej C i średnicy przewodu d (a...
-
Mechanical and fracture properties of concrete reinforced with recycled and industrial steel fibers using Digital Image Correlation technique and X-ray micro computed tomography
PublikacjaPaper presents investigation of fracture phenomenon in plain concrete and in concrete reinforced with both recycled steel fibers (RSF) and industrial steel fibers (ISF). The wedge splitting test (WST), which enables stable crack propagation for quasi-brittle materials, was carried out on 75 75 75 mm cube samples. Initially, fracture process zone development was investigated only on the surface of samples using Digital Image Correlation...
-
Two - scale model for concrete beams subjected to three point bending - numerical analyses and experiments
PublikacjaArtykuł omawia dwu-skalowe podejście do betonu przy wykorzystaniu połączonych modeli. Metodę elementów skończonych zastosowano na poziomie makro. Na poziomie mikro zastosowano metodę elementów dyskretnych. Macierz sztywności wyznaczono na podstawie tensora naprężeń wyznaczonego w skali mikro. Wyniki numeryczne dw-skalowe porównano z wynikami dyskretnymi dla całego obszaru.
-
Design of Microstrip UWB Balun Using Quasi-TEM Approach Aided by the Artificial Neural Network
PublikacjaThe design procedure for UWB balun realized in the microstrip technology is proposed in the paper. The procedure applies Artificial Neural Network which corrects the dimensions of the approximate design found by appropriate scaling of the dimensions of the prototype. The scale coefficients for longitudinal and transverse dimensions of microstrip lines are determined from electromagnetic modeling based on transmission line equations....
-
Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
PublikacjaNowadays, Buckling-Restrained Brace Frames (BRBFs) have been used as lateral force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of BRBFs plays a key role in deciding to retrofit buildings after seismic excitation; however, existing formulas have limitations and cannot effectively help civil engineers, e.g., FEMA P-58, which is a conservative estimation method. Therefore, there is a need to...
-
Assessment Of the Relevance of Best Practices in The Development of Medical R&D Projects Based on Machine Learning
PublikacjaMachine learning has emerged as a fundamental tool for numerous endeavors within health informatics, bioinformatics, and medicine. However, novices among biomedical researchers and IT developers frequently lack the requisite experience to effectively execute a machine learning project, thereby increasing the likelihood of adopting erroneous practices that may result in common pitfalls or overly optimistic predictions. The paper...
-
Characterization of fracture process in polyolefin fibre-reinforced concrete using ultrasonic waves and digital image correlation
PublikacjaThis study explores the monitoring of the fracture process in concrete beams and aims to characterize the evolution of damage in polyolefin fibre-reinforced concrete beams by utilizing the integrated application of two measurement techniques, digital image correlation and ultrasonic testing. The interpretation of registered wave time histories data was provided by the calculation of the magnitude-phase-composite metrics. An efficient...
-
User Orientation Detection in Relation to Antenna Geometry in Ultra-Wideband Wireless Body Area Networks Using Deep Learning
PublikacjaIn this paper, the issue of detecting a user’s position in relation to the antenna geometry in ultra-wideband (UWB) off-body wireless body area network (WBAN) communication using deep learning methods is presented. To measure the impulse response of the channel, a measurement stand consisting of EVB1000 devices and DW1000 radio modules was developed and indoor static measurement scenarios were performed. It was proven that for...
-
Playback detection using machine learning with spectrogram features approach
PublikacjaThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
-
Mechanical Performance and Environmental Assessment of Sustainable Concrete Reinforced with Recycled End-of-Life Tyre Fibres
PublikacjaThe presented research’s main objective was to develop the solution to the global problem of using steel waste obtained during rubber recovery during the tire recycling. A detailed comparative analysis of mechanical and physical features of the concrete composite with the addition of recycled steel fibres (RSF) in relation to the steel fibre concrete commonly used for industrial floors was conducted. A study was carried out using...
-
Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
PublikacjaControlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient’s genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched...
-
A machine learning approach to classifying New York Heart Association (NYHA) heart failure
PublikacjaAccording 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...
-
Evaluation of Machine Learning Methods for the Experimental Classification and Clustering of Higher Education Institutions
PublikacjaHigher education institutions have a big impact on the future of skills supplied on the labour market. It means that depending on the changes in labour market, higher education institutions are making changes to fields of study or adding new ones to fulfil the demand on labour market. The significant changes on labour market caused by digital transformation, resulted in new jobs and new skills. Because of the necessity of computer...
-
Blended Learning Model for Computer Techniques for Students of Architecture
PublikacjaAbstract: The article summarizes two-year experience of implementing hybrid formula for teaching Computer Techniques at the Faculty of Architecture at the Gdansk University of Technology. Original educational e-materials, consisting of video clips, text and graphics instructions, as well as links to online resources are embedded in the university e-learning educational platform. The author discusses technical constraints associated...
-
Cost-Efficient Measurement Platform and Machine-Learning-Based Sensor Calibration for Precise NO2 Pollution Monitoring
PublikacjaAir quality significantly impacts human health, the environment, and the economy. Precise real-time monitoring of air pollution is crucial for managing associated risks and developing appropriate short- and long-term measures. Nitrogen dioxide (NO2) stands as a common pollutant, with elevated levels posing risks to the human respiratory tract, exacerbating respiratory infections and asthma, and potentially leading to chronic lung...
-
Modelling relation between oxidation resistance and tribological properties of non-toxic lubricants with the use of artificial neural networks
Publikacja -
Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublikacjaWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
-
Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublikacjaThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
-
Neural network training with limited precision and asymmetric exponent
PublikacjaAlong with an extremely increasing number of mobile devices, sensors and other smart utilities, an unprecedented growth of data can be observed in today’s world. In order to address multiple challenges facing the big data domain, machine learning techniques are often leveraged for data analysis, filtering and classification. Wide usage of artificial intelligence with large amounts of data creates growing demand not only for storage...
-
Methods of Artificial Intelligence for Prediction and Prevention Crisis Situations in Banking Systems
PublikacjaIn this paper, a support vector machine has been studied due to prediction of bank crisis. To prevent outcomes of crisis situations, artificial neural networks have been characterized as applied to stock market investments, as well as to test the credibility of the bank's customers. Finally, some numerical experiments have been presented.