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Search results for: MAGNETIC SIGNATURES, MEASUREMENT DEPTH, MODELING, NEURAL NETWORKS
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Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublicationIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...
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Modelowanie przepływu pary przez okołodźwiękowe wieńce turbinowe z użyciem sztucznych sieci neuronoych
PublicationNiniejszy artykuł stanowi opis modelu przepływu pary przez okołodźwiękowe stopnie turbinowe, stworzonego w oparciu o sztuczne sieci neuronowe (SSN). Przedstawiony model neuronowy pozwala na wyznaczenie rozkładu wybranych parametrów w analizowanym przekroju kanału przepływowego turbiny dla rozpatrywanego zakresu wartości ciśnienia wlotowego.
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Computational intelligence methods in production management
PublicationThis chapter presents a survey of selected computational intelligence methods used in production management. This group of methods includes, among others, approaches based on the artificial neural networks, the evolutionary algorithms, the fuzzy logic systems and the particle swarm optimization mechanisms. From the abovementioned methods particularly noteworthy are the evolutionary and the particle swarm algorithms, which are successfully...
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Data fusion of sparse, heterogeneous, and mobile sensor devices using adaptive distance attention
PublicationIn environmental science, where information from sensor devices are sparse, data fusion for mapping purposes is often based on geostatistical approaches. We propose a methodology called adaptive distance attention that enables us to fuse sparse, heterogeneous, and mobile sensor devices and predict values at locations with no previous measurement. The approach allows for automatically weighting the measurements according to a priori...
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Optymalizacja treningu i wnioskowania sieci neuronowych
PublicationSieci neuronowe są jedną z najpopularniejszych i najszybciej rozwijających się dziedzin sztucznej inteligencji. Ich praktyczne wykorzystanie umożliwiło szersze użycie komputerów w wielu obszarach komunikacji, przemysłu i transportu. Dowody tego są widoczne w elektronice użytkowej, medycynie, a nawet w zastosowaniach militarnych. Wykorzystanie sztucznej inteligencji w wielu przypadkach wymaga jednak znacznej mocy obliczeniowej,...
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Stress anisotropy characterisation with the help of Barkhausen effect detector with adjustable magnetic field direction
PublicationIn the paper we describe a novel apparatus for the measurement of the Barkhausen noise (BN) angular dependence, which in turn may be indicative of the stress induced anisotropy of magnetic properties. Such dependence can be further used for the stress distribution evaluation. The change of magnetization direction in the material is obtained by varying the magnetic flux density in two perpendicular yokes of the apparatus. We present...
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Three-dimensional mapping for data collected using variable stereo baseline
PublicationThe paper describes a system of 3D mapping of data collected with due regard for variable baseline. This solution constitute an extension to a VisRobot sub-system developed as a subsystem, necessary for implementing the generic idea of using mobile robots to explore an indoor static environment. This subsystem is to acquire stereo images, calculate the depth in the images and construct the sought 3D map. Stereo images are obtained...
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Analysis of Methods for Determining Shallow Waterbody Depths Based on Images Taken by Unmanned Aerial Vehicles
PublicationHydrographic surveys enable the acquisition and processing of bathymetric data, which after being plotted onto nautical charts, can help to ensure safety of navigation, monitor changes in the coastal zone, and assess hydro-engineering structure conditions. This study involves the measurement of waterbody depth, identification of the seabed shape and geomorphology, the coastline course, and the location of underwater obstacles....
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Accurate Modeling of Frequency Selective Surfaces Using Fully-Connected Regression Model with Automated Architecture Determination and Parameter Selection Based on Bayesian Optimization
PublicationSurrogate modeling has become an important tool in the design of high-frequency structures. Although full-wave electromagnetic (EM) simulation tools provide an accurate account for the circuit characteristics and performance, they entail considerable computational expenditures. Replacing EM analysis by fast surrogates provides a way to accelerate the design procedures. Unfortunately, modeling of microwave passives is a challenging...
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Training of Deep Learning Models Using Synthetic Datasets
PublicationIn order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...
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Methods of Artificial Intelligence for Prediction and Prevention Crisis Situations in Banking Systems
PublicationIn 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.
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BADANIE WPŁYWU INDUKCJI REMANENCJI NA STAN PRZEJŚCIOWY JEDNOFAZOWEGO UKŁADU TRANSFORMATOROWEGO
PublicationW referacie przedstawiono wyniki badań eksperymentalnych i symulacyjnych wpływu indukcji remanencji w rdzeniu transformatora jednofazowego na jego stan przejściowy przy jego pracy jałowej. Badany obiekt jest układem transformatorowym o dwóch uzwojeniach nawiniętych na zwijanym z blachy anizotropowej rdzeniu w kształcie toroidu. Doświadczenia eksperymentalne polegały na rozładowywaniu kondensatora przez uzwojenie strony pierwotnej...
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Inspection of Gas Pipelines Using Magnetic Flux Leakage Technology
PublicationMagnetic non-destructive testing methods can be classified into the earliest methods developed for assessment of steel constructions. One of them is the magnetic flux leakage technology. A measurement of the magnetic flux leakage is quite commonly used for examination of large objects such as tanks and pipelines. Construction of a magnetic flux leakage tool is relatively simple, but a quantitative analysis of recorded data is a...
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Path Loss Analysis for the IoT Applications in the Urban and Indoor Environments
PublicationThe Internet of Things (IoT) networks concept implies their presence in a various and untypical locations, usually with a disturbed radio signals propagation. In the presented paper an investigation of an additional path loss observed in an underground environment was described. The proposed measurement locations correspond to the operation areas of rapidly growing narrowband IoT (NBIoT) networks, the ones using the Long Term Evolution...
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Fake VIP Attacks and Their Mitigation via Double-Blind Reputation
PublicationIn a generic setting subsuming communication networks, resource sharing systems, and multi-agent communities, a client generates objects of various classes carrying class-dependent signatures, to which a server assigns class-dependent service quality. A Fake VIP attack consists in false declaration of a high class, with an awareness that detection of object signature at the server side is costly and so invoked reluctantly. We show...
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Path Loss Modelling for Location Service Applications
PublicationThe aim of this paper is the path loss modeling for the radiolocation services in radiocommunication networks, particularly in cellular networks. The main results of the measurements obtained in the physical layer of the UMTS are introduced. A new method for the utilization of the multipath propagation phenomenon to improve the estimation of the distance between the mobile station (MS) and the base station (BS) is outlined. This...
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Experience-Based Cognition for Driving Behavioral Fingerprint Extraction
PublicationABSTRACT With the rapid progress of information technologies, cars have been made increasingly intelligent. This allows cars to act as cognitive agents, i.e., to acquire knowledge and understanding of the driving habits and behavioral characteristics of drivers (i.e., driving behavioral fingerprint) through experience. Such knowledge can be then reused to facilitate the interaction between a car and its driver, and to develop better and...
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Ferromagnetic nanoparticles imaging by means of Magnetic Force Microscopy
Open Research DataFerromagnetic nanoparticles can be used as building blocks for advanced thin film magnets, and can also be used in data storage and biomedical technologies. Nano-crystalline ferrites with the chemical formula NixZn (1 - x) Fe2O4, where x = 0, 0.2, 0.4, 0.6, 0.8, 1.0 show anti-corrosion properties and suppress electromagnetic interference, in the case...
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Projektowanie i eksploatacja dróg szynowych z wykorzystaniem mobilnych pomiarów satelitarnych
PublicationNiniejsza monografia zawiera szczegółowy opis aktywnych sieci geodezyjnych GNSS oraz modelowania dokładności określania pozycji w pomiarach satelitarnych. Omówiono również opracowaną technikę mobilnych pomiarów satelitarnych toru kolejowego oraz aplikacje związane z jej zastosowaniem w projektowaniu i eksploatacji dróg szynowych. Autorzy zawarli w pracy wyniki swoich badań, wykonywanych na przestrzeni lat 2009–2015. Badania przeprowadzono...
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Instance segmentation of stack composed of unknown objects
PublicationThe article reviews neural network architectures designed for the segmentation task. It focuses mainly on instance segmentation of stacked objects. The main assumption is that segmentation is based on a color image with an additional depth layer. The paper also introduces the Stacked Bricks Dataset based on three cameras: RealSense L515, ZED2, and a synthetic one. Selected architectures: DeepLab, Mask RCNN, DEtection TRansformer,...
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Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublicationSince high-quality real data acquired from selected road sections are not always available, a traffic control solution can use data from software traffic simulators working offline. The results show that in contrast to microscopic traffic simulation, the algorithms employing neural networks can work in real-time, so they can be used, among others, to determine the speed displayed on variable message road signs. This paper describes...
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Erroneous Vehicle Velocity Estimation Correction Using Anisotropic Magnetoresistive (AMR) Sensors
PublicationMagnetic field sensors installed in the road infrastructure can be used for autonomous traffic flow parametrization. Although the main goal of such a measuring system is the recognition of the class of vehicle and classification, velocity is the essential parameter for further calculation and it must be estimated with high reliability. In-field test campaigns, during actual traffic conditions, showed that commonly accepted velocity...
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Multi-functional sensor based on photonic crystal fiber using plasmonic material and magnetic fluid
PublicationA unique highly sensitive photonic crystal fiber is investigated based on plasmonic material and magnetic fluid (MF) for the simultaneous measurement of temperature and magnetic field sensor. The designed sensor is explored by tracing the different parameters such as birefringence, coupling length, power spectrum, and the peak wavelength of the transmission intensity. The magnetic field and temperature computation are attained...
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A method of earth fault loop impedance measurement without unwanted tripping of RCDs
PublicationIn low-voltage networks, earth fault loop impedance (EFLI) measurement is the basis for assessing the effectiveness of automatic disconnection of supply. Such a measurement is performed during initial and periodical verification, especially in a TN low-voltage network. Nowadays, due to widespread application of residual current devices (RCDs), such test is difficult in many circuits because RCDs operate during the test. In this...
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Machine Learning Algorithm-Based Tool and Digital Framework for Substituting Daylight Simulations In Early- Stage Architectural Design Evaluation
PublicationThe 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...
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Widespread theta synchrony and high-frequency desynchronization underlies enhanced cognition
PublicationThe idea that synchronous neural activity underlies cognition has driven an extensive body of research in human and animal neuroscience. Yet, insufficient data on intracranial electrical connectivity has precluded a direct test of this hypothesis in a whole-brain setting. Through the lens of memory encoding and retrieval processes, we construct whole-brain connectivity maps of fast gamma (30-100 Hz) and slow theta (3-8 Hz) spectral...
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A Novel IoT-Perceptive Human Activity Recognition (HAR) Approach Using Multi-Head Convolutional Attention
PublicationTogether with fast advancement of the Internet of Things (IoT), smart healthcare applications and systems are equipped with increasingly more wearable sensors and mobile devices. These sensors are used not only to collect data, but also, and more importantly, to assist in daily activity tracking and analyzing of their users. Various human activity recognition (HAR) approaches are used to enhance such tracking. Most of the existing...
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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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Resource constrained neural network training
PublicationModern applications of neural-network-based AI solutions tend to move from datacenter backends to low-power edge devices. Environmental, computational, and power constraints are inevitable consequences of such a shift. Limiting the bit count of neural network parameters proved to be a valid technique for speeding up and increasing efficiency of the inference process. Hence, it is understandable that a similar approach is gaining...
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Improved Modeling of Microwave Structures Using Performance-Driven Fully-Connected Regression Surrogate
PublicationFast replacement models (or surrogates) have been widely applied in the recent years to accelerate simulation-driven design procedures in microwave engineering. The fundamental reason is a considerable—and often prohibitive—CPU cost of massive full-wave electromagnetic (EM) analyses related to solving common tasks such as parametric optimization or uncertainty quantification. The most popular class of surrogates are data-driven...
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WYKORZYSTANIE SIECI NEURONOWYCH DO SYNTEZY MOWY WYRAŻAJĄCEJ EMOCJE
PublicationW niniejszym artykule przedstawiono analizę rozwiązań do rozpoznawania emocji opartych na mowie i możliwości ich wykorzystania w syntezie mowy z emocjami, wykorzystując do tego celu sieci neuronowe. Przedstawiono aktualne rozwiązania dotyczące rozpoznawania emocji w mowie i metod syntezy mowy za pomocą sieci neuronowych. Obecnie obserwuje się znaczny wzrost zainteresowania i wykorzystania uczenia głębokiego w aplikacjach związanych...
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Impact of Climate Change on Water Sources and River‐Floodplain Mixing in the Natural Wetland Floodplain of Biebrza River
PublicationThe origins of river and floodplain waters (groundwater, rainfall, and snowmelt) and their extent during overbank flow events strongly impact ecological processes such as denitrification and vegetation development. However, the long-term sensitivity of floodplain water signatures to climate change remains elusive. We examined how the integrated hydrological model HydroGeoSphere and the Hydraulic Mixing-Cell method could help us...
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A review on application of artificial neural network (ANN) for performance and emission characteristics of diesel engine fueled with biodiesel-based fuels
PublicationBiodiesel 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...
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On a Method of Efficiency Increasing in Kaplan Turbine
PublicationThis paper presents a method of increasing efficiency in Kaplan-type turbine. The method is based on blade profile optimisation together with modelling the interaction between rotor and stator blades. Loss coefficient was chosen as the optimisation criterion, which is related directly to efficiency. Global optimum was found by means of Genetic Algorithms, and Artificial Neural Networks were utilised for approximations to reduce...
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Classifying Emotions in Film Music - A Deep Learning Approach
PublicationThe paper presents an application for automatically classifying emotions in film music. A model of emotions is proposed, which is also associated with colors. The model created has nine emotional states, to which colors are assigned according to the color theory in film. Subjective tests are carried out to check the correctness of the assumptions behind the adopted emotion model. For that purpose, a statistical analysis of the...
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Determination of Mathematical Model Parameters of a Medium Frequency Transformer
PublicationThe paper presents the results of experimental studies of the medium frequency transformer. The object of the research was a prototype of a single-phase transformer with a core made of ferrite I-core elements and windings made of Litz conductors. The research was carried out to determine the parameters of the transformer's mathematical model. The scope of the tests included determining the magnetic hysteresis loop and measuring...
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Evolving neural network as a decision support system — Controller for a game of “2048” case study
PublicationThe paper proposes an approach to designing the neuro-genetic self-learning decision support system. The system is based on neural networks being adaptively learned by evolutionary mechanism, forming an evolved neural network. Presented learning algorithm enables for a selection of the neural network structure by establishing or removing of connections between the neurons, and then for a finding the beast suited values of the network...
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Limitation of Floating-Point Precision for Resource Constrained Neural Network Training
PublicationInsufficient availability of computational power and runtime memory is a major concern when it comes to experiments in the field of artificial intelligence. One of the promising solutions for this problem is an optimization of internal neural network’s calculations and its parameters’ representation. This work focuses on the mentioned issue by the application of neural network training with limited precision. Based on this research,...
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Speech Analytics Based on Machine Learning
PublicationIn this chapter, the process of speech data preparation for machine learning is discussed in detail. Examples of speech analytics methods applied to phonemes and allophones are shown. Further, an approach to automatic phoneme recognition involving optimized parametrization and a classifier belonging to machine learning algorithms is discussed. Feature vectors are built on the basis of descriptors coming from the music information...
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Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublicationThe diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...
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Document Agents with the Intelligent Negotiations Capability
PublicationThe paper focus is on augmenting proactive document-agents with built -in intelligence to enable them to recognize execution context provided by devices visited durning the business process, and to reach collaboration agreement despite of their conflicting requirements. We propose a solution based on neural networks to improve simple multi-issue negotiation between the document and the device, practically with no excessive cost...
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Automatic music set organizatio based on mood of music / Automatyczna organizacja bazy muzycznej na podstawie nastroju muzyki
PublicationThis work is focused on an approach based on the emotional content of music and its automatic recognition. A vector of features describing emotional content of music was proposed. Additionally, a graphical model dedicated to the subjective evaluation of mood of music was created. A series of listening tests was carried out, and results were compared with automatic mood recognition employing SOM (Self Organizing Maps) and ANN (Artificial...
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Variable Data Structures and Customized Deep Learning Surrogates for Computationally Efficient and Reliable Characterization of Buried Objects
PublicationIn this study, in order to characterize the buried object via deep-learning-based surrogate modeling approach, 3-D full-wave electromagnetic simulations of a GPR model has been used. The task is to predict simultaneously and independent of each characteristic parameters of a buried object of several radii at different positions (depth and lateral position) in various dispersive subsurface media. This study has analyzed variable...
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Shallow Water Equations as a Mathematical Model of Whitewater Course Hydrodynamics
PublicationPredicting the positions of local hydraulic phenomena, as well as accurately esti-mating the depth and velocity of the water flow are necessary to correctly config-ure a whitewater canoeing course. Currently, a laboratory and full 3D CFD model-ing are typically used in the design process to meet these needs. The article points to another possibility which can be useful at the preliminary stage of the design. The authors show that...
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Eu2Mg3Bi4: Competing Magnetic Orders on a Buckled Honeycomb Lattice
PublicationThe honeycomb lattice and its derived variants provide information on modeling and designing quantum magnets. A novel magnetic material, Eu2Mg3Bi4, which stabilizes in a previously unknown buckled honeycomb lattice, was discovered by high-pressure and high-temperature methods. We report here on the synthesis exploration of pure single crystals, structural determination of the buckled honeycomb lattice of europium moments, and experimental observation...
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Recurrent Neural Network Based Adaptive Variable-Order Fractional PID Controller for Small Modular Reactor Thermal Power Control
PublicationThis paper presents the synthesis of an adaptive PID type controller in which the variable-order fractional operators are used. Due to the implementation difficulties of fractional order operators, both with a fixed and variable order, on digital control platforms caused by the requirement of infinite memory resources, the fractional operators that are part of the discussed controller were approximated by recurrent neural networks...
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Hysteresis modelling of a medium frequency single-phase transformer
PublicationThe article describes a feedback Preisach hysteresis model equivalent circuit implementation of a medium frequency single-phase transformer being a part of a high power and high efficiency DC-DC converter. The macroscopic models of magnetic hysteresis are introduced and the feedback Preisach model is selected for further analysis. The hysteresis model is developed for a prototype transformer and the hysteresis loops are compared...
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Towards Knowledge Sharing Oriented Adaptive Control
PublicationIn this paper, we propose a knowledge sharing oriented approach to enable a robot to reuse other robots' knowledge by adapting itself to the inverse dynamics model of the knowledge-sharing robot. The purpose of this work is to remove the heavy fine-tuning procedure required before using a new robot for a task via reusing other robots' knowledge. We use the Neural Knowledge DNA (NK-DNA) to help robots gain empirical knowledge and...
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Soft Sensor Application in Identification of the Activated Sludge Bulking Considering the Technological and Economical Aspects of Smart Systems Functioning
PublicationThe paper presented the methodology for the construction of a soft sensor used for activated sludge bulking identification. Devising such solutions fits within the current trends and development of a smart system and infrastructure within smart cities. In order to optimize the selection of the data-mining method depending on the data collected within a wastewater treatment plant (WWTP), a number of methods were considered, including:...
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Binocular Vision Impairments Therapy Supported By Contactless Eye-gaze Tracking System
PublicationBinocular vision impairments often result in partial or total loss of stereoscopic vision. The lack of binocular vision is a serious vision impairment that deserves more attention. Very important result of the binocular vision impairments is a binocular depth perception. This paper describes also a concept of a measurement and therapy system for the binocular vision impairments by using eye-gaze tracking system.