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Search results for: MAGNETIC SIGNATURES, MEASUREMENT DEPTH, MODELING, NEURAL NETWORKS
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Speaker Recognition Using Convolutional Neural Network with Minimal Training Data for Smart Home Solutions
PublicationWith the technology advancements in smart home sector, voice control and automation are key components that can make a real difference in people's lives. The voice recognition technology market continues to involve rapidly as almost all smart home devices are providing speaker recognition capability today. However, most of them provide cloud-based solutions or use very deep Neural Networks for speaker recognition task, which are...
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Emotion Recognition from Physiological Channels Using Graph Neural Network
PublicationIn recent years, a number of new research papers have emerged on the application of neural networks in affective computing. One of the newest trends observed is the utilization of graph neural networks (GNNs) to recognize emotions. The study presented in the paper follows this trend. Within the work, GraphSleepNet (a GNN for classifying the stages of sleep) was adjusted for emotion recognition and validated for this purpose. The...
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Reliability data safety instrumented systems SIS from the functional safety analysis example critical instalation
Open Research DataThe dataset represents the results of an example of functional safety analysis systems is presented below. It is based on a control system, which consists of some basic components like sensors, programmable logic controllers and valves. It is a part of petrochemical critical installations. The communication between sensor logic controllers and actuators...
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Design of Microstrip UWB Balun Using Quasi-TEM Approach Aided by the Artificial Neural Network
PublicationThe 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....
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Olgun Aydin Dr
PeopleOlgun Aydin finished his PhD by publishing a thesis about Deep Neural Networks. He works as a Senior Data Scientist in PwC Poland, gives lectures in Gdansk University of Technology in Poland and member of WhyR? Foundation. Olgun is a very big fan of R and author of the book called “R Web Scraping Quick Start Guide” , two video courses are called “Deep Dive into Statistical Modelling using R” and “Applied Machine Learning and Deep...
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Control of the cultivation of cartilages for using in the biobearings.
PublicationBiotribologiczne charakterystyki biołożysk są zależne od procesu hodowli żywej tkanki chrząstki w bioreaktorze. Z kolei proces ten, jest wielowymiarowym procesem dynamicznym sterowanym za pomocą odpowiedniego układu automatycznej regulacji. Praca przedstawia prawo i algorytm sterowania takiego procesu. W tym celu zastosowano sztuczne sieci neuronowe (Artificial Neural Networks - ANN) i zaprezentowano wyniki obliczeń.
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Optical Coherence Tomography for nanoparticles quantitative characterization
PublicationThe unique features of nanocomposite materials depend on the type and size of nanoparticles, as well as their placement in the composite matrices. Therefore the nanocomposites manufacturing process requires inline control over certain parameters of nanoparticles such as dispersion and concentration. Keeping track of nanoparticles parameters inside a matrix is currently a difficult task due to lack of a fast, reliable and cost effective...
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DIAGNOSIS OF MALIGNANT MELANOMA BY NEURAL NETWORK ENSEMBLE-BASED SYSTEM UTILISING HAND-CRAFTED SKIN LESION FEATURES
PublicationMalignant melanomas are the most deadly type of skin cancer but detected early have high chances for successful treatment. In the last twenty years, the interest of automated melanoma recognition detection and classification dynamically increased partially because of public datasets appearing with dermatoscopic images of skin lesions. Automated computer-aided skin cancer detection in dermatoscopic images is a very challenging task...
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Spatiotemporal Assessment of Satellite Image Time Series for Land Cover Classification Using Deep Learning Techniques: A Case Study of Reunion Island, France
PublicationCurrent Earth observation systems generate massive amounts of satellite image time series to keep track of geographical areas over time to monitor and identify environmental and climate change. Efficiently analyzing such data remains an unresolved issue in remote sensing. In classifying land cover, utilizing SITS rather than one image might benefit differentiating across classes because of their varied temporal patterns. The aim...
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Fiber-optic Fabry-Pérot sensors – modeling versus measurements results
PublicationThis paper describes how parameters of investigated substances and the fiber-optic Fabry-Pérot sensing interferometer affect the spectrum of the optical radiation at the output of the sensor. First, the modeling of the operation of the sensing interferometer was conducted. Most important parameters and effects that were taken into account are: dependences of the refractive indices of the core and the cladding, as well the mode...
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Surface EMG-based signal acquisition for decoding hand movements
Open Research DataBiosignal processing plays a crucial role in modern hand prosthetics. The challenge is to restore functionality of a lost limb based on the signals acquired from the surface of the stump. The number of sensors (emg channels) used for signal acquisition influence the quality of a prosthetic hand. Modern algorithms (including neural networks) can significantly...
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Adaptive CAD-Model Construction Schemes
PublicationTwo advanced surrogate model construction techniques are discussed in this paper. The models employ radial basis function (RBF)interpolation scheme or artificial neural networks (ANN) with a new training algorithm. Adaptive sampling technique is applied withrespect to all variables. Histograms showing the quality of the models are presented. While the quality of RBF models is satisfactory, theperformance of the ANN models obtained...
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Distributed protection against non-cooperative node behavior in multi-hop wireless networks
PublicationAn important security problem in today's distributed data networks is the prevention of non-cooperative behavior i.e., attacks consisting in the modification of standard node operation to gain unfair advantage over other system nodes. Such a behavior is currently feasible in many types of computer networks whose communication protocols are designed to maximize the network performance assuming full node cooperation. Moreover, it...
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Comparison of the Ability of Neural Network Model and Humans to Detect a Cloned Voice
PublicationThe vulnerability of the speaker identity verification system to attacks using voice cloning was examined. The research project assumed creating a model for verifying the speaker’s identity based on voice biometrics and then testing its resistance to potential attacks using voice cloning. The Deep Speaker Neural Speaker Embedding System was trained, and the Real-Time Voice Cloning system was employed based on the SV2TTS, Tacotron,...
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Machine Learning in Multi-Agent Systems using Associative Arrays
PublicationIn this paper, a new machine learning algorithm for multi-agent systems is introduced. The algorithm is based on associative arrays, thus it becomes less complex and more efficient substitute of artificial neural networks and Bayesian networks, which is confirmed by performance measurements. Implementation of machine learning algorithm in multi-agent system for aided design of selected control systems allowed to improve the performance...
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Expert systems in assessing the construction process safety taking account of the risk of disturbances
PublicationThe objective of the paper is to present the issue of safety manage-ment during the construction process. Threats in the form of disturb-ances may occur in the preparatory phase, during the execution of the construction project and also during its operational use. The arti-cle presents the concept of applying the methodology based, among others, on Learning Bayesian Networks, Artificial Neural Networks and Support Vector Machine,...
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Diagnostyka łożysk silnika indukcyjnego na podstawie prądu zasilającego przy użyciu sztucznych sieci neuronowych
PublicationW artykule zawarto wyniki badań dotyczące diagnostyki łożysk silnika indukcyjnego na podstawie pomiarów prądu zasilającego z wykorzystaniem sztucznych sieci neuronowych. Zaprezentowano wyniki uczenia sieci oraz rezultaty testów przeprowadzonych na danych spoza zbioru uczącego. Badania wykonane zostały na obiektach z celowo wprowadzonymi uszkodzeniami łożysk. Przedstawiona nowa koncepcja zakłada użycie zestawu sieci neuronowych...
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Ligand-Modified Boron-Doped Diamond Surface: DFT Insights into the Electronic Properties of Biofunctionalization
PublicationWith the increasing power of computation systems, theoretical calculations provide a means for quick determination of material properties, laying out a research plan, and lowering material development costs. One of the most common is Density Functional Theory (DFT), which allows us to simulate the structure of chemical molecules or crystals and their interaction. In developing a new generation of biosensors, understanding the nature...
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CeIr3: superconductivity in a phase based on tetragonally close packed clusters
PublicationWe present the crystallographic analysis, superconducting and spectroscopic characterization, and theoretical modeling of CeIr3. Lattice parameters a = 5.2945(1) Å and c = 26.219(1) Å are found for the R-3m symmetry crystal structure, which are close to the literature values. CeIr3 is a moderate type-II superconductor (κ GL = 17, λ e–p = 0.65) below 2.5 K. Ce ions exhibit a strongly intermediate valence character as evidenced by...
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Numerical analysis of open channel steady gradually varied flow using the simplified saint-venant equations
PublicationFor one-dimensional open-channel flow modeling, the energy equation is usually used. There exist numerous approaches using the energy equation for open-channel flow computations, which resulted in the development of several very efficient methods for solving this problem applied to channel networks. However, the dynamic equation can be used for this purpose as well. This paper introduces a method for solving a system of non-linear...
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Economical methods for measuring road surface roughness
PublicationTwo low-cost methods of estimating the road surface condition are presented in the paper, the first one based on the use of accelerometers and the other on the analysis of images acquired from cameras installed in a vehicle. In the first method, miniature positioning and accelerometer sensors are used for evaluation of the road surface roughness. The device designed for installation in vehicles is composed of a GPS receiver and...
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Determination of magnetisation conditions in a Double-Core Barkhausen Noise measurement set-up
PublicationThe magnetic Barkhausen effect is useful forassessing 1D and 2D stress states of ferromagnetic steelobjects. However, its extension to technically importantmaterials, such as duplex anisotropic steels, remains challenging. The determination of magnetisation inside the studied object and the electromagnet for various geometries, materials and magnetisation angles is a key issue.Three-dimensional, dynamic finite element analysis...
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A coarse‐grained approach to NMR ‐data‐assisted modeling of protein structures
PublicationThe ESCASA algorithm for analytical estimation of proton positions from coarse-grained geometry developed in our recent work has been implemented in modeling protein structures with the highly coarse-grained UNRES model of polypeptide chains (two sites per residue) and nuclear magnetic resonance (NMR) data. A penalty function with the shape of intersecting gorges was applied to treat ambiguous distance restraints, which automatically...
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Application of method of differential magnetometric system for detection of sunken objects
PublicationThis paper presents a magnetometric system with scalar sensors mounted on two independent platforms, which is used to detect sunken shipwrecks. Increasing the distance between the sensors allows for more precise measurement of the difference in the magnetic induction module than in the case of sensors mounted e.g. on the aeroplane’s wings. This type of system makes it possible to enlarge detection range of the sunken wrecks.
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Sztuczne sieci neuronowe oraz metoda wektorów wspierających w bankowych systemach informatycznych
PublicationW artykule zaprezentowano wybrane metod sztucznej inteligencji do zwiększania efektywności bankowych systemów informatycznych. Wykorzystanie metody wektorów wspierających czy sztucznych sieci neuronowych w połączeniu z nowoczesną technologią mikroprocesorową umożliwia znaczący wzrost konkurencyjności banku poprzez dodanie nowych funkcjonalności. W rezultacie możliwe jest także złagodzenie skutków kryzysu finansowego.
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A Method for Optimising the Blade Profile in Kaplan Turbine
PublicationThis paper introduces a method of blade profile optimisation for Kaplan-type turbines, based on modelling the interaction between rotor and stator blades. Rotor and stator blade geometry is described mathematically by means of a midline curve and thickness distribution. Genetic algorithms are then used to find a global optimum that minimises the loss coefficient. This allows for variety of possible blade shapes and configurations....
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Knowledge representation of motor activity of patients with Parkinson’s disease
PublicationAn approach to the knowledge representation extraction from biomedical signals analysis concerning motor activity of Parkinson disease patients is proposed in this paper. This is done utilizing accelerometers attached to their body as well as exploiting video image of their hand movements. Experiments are carried out employing artificial neural networks and support vector machine to the recognition of characteristic motor activity...
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Selection of Features for Multimodal Vocalic Segments Classification
PublicationEnglish speech recognition experiments are presented employing both: audio signal and Facial Motion Capture (FMC) recordings. The principal aim of the study was to evaluate the influence of feature vector dimension reduction for the accuracy of vocalic segments classification employing neural networks. Several parameter reduction strategies were adopted, namely: Extremely Randomized Trees, Principal Component Analysis and Recursive...
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublicationIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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AUTOMATED NEGOTIATIONS OVER COLLABORATION PROTOCOL AGREEMENTS
PublicationThe dissertation focuses on the augmentation of proactive document - agents with built-in intelligence to recognize execution context provided by devices visited during a business process, and to reach collaboration agreement despite conflicting requirements. The proposed solution, based on intelligent bargaining using neural networks to improve simple multi-issue negotiation between the document and thedevice, requires practically...
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Application of wavelength division multiplexing in sensor networks
PublicationOver the past few years the need to acquire data on various parameters from a number of sensors grew. The need that led to the development of a network of sensors which enables simultaneous control and measurement in a wide range of applications. The aim of this article is to discuss a possibility of connecting a variety of sensors in a network that would utilize WDM technology. Wavelength Division Multiplexing is commonly used...
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Measurement Stand and Methodology for Research of the Off-Body and Body-to-Body Radio Channels in WBANs with Different Diversity Schemes
PublicationThe concept of an experimental test bed for system loss and channel impulse response measurements for off-body and body-to-body radio channels in wireless body area networks (WBANs) is fully described. The possible measurement scenarios that may occur in investigation of off-body and body-to-body channels are classified and described in detail. Additionally, an evaluation is provided of the standard and expanded uncertainties of...
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General concept of reduction process for big data obtained by interferometric methods
PublicationInterferometric sonar systems apply the phase content of the sonar signal to measure the angle of a wave front returned from the seafloor or from a target. It collect a big data – datasets that are so large or complex that traditional data processing application software is inadequate to deal with them. The recording a large number of data is associated with the difficulty of their efficient use. So data have to be reduced. The main...
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Propagation Path Loss Modeling in Container Terminal Environment
PublicationThis paper describes novel method of path loss modeling for radio communication channels in container port area. Multi-variate empirical model is presented, based on multidimensional regression analysis of real path loss measurements from container terminal environment. The measurement instruments used in propagation studies in port area are also described.
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Simulating Power Generation from Photovoltaics in the Polish Power System Based on Ground Meteorological Measurements—First Tests Based on Transmission System Operator Data
PublicationThe Polish power system is undergoing a slow process of transformation from coal to one that is renewables dominated. Although coal will remain a fundamental fuel in the coming years, the recent upsurge in installed capacity of photovoltaic (PV) systems should draw significant attention. Owning to the fact that the Polish Transmission System Operator recently published the PV hourly generation time series in this article, we aim...
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Problems of modelling toxic compounds emitted by a marine internal combustion engine for the evaluation of its structure parameters
PublicationThe paper presents the possibility of using an analytical study of the engine exhaust ignition to evaluate the technical condition of the selected components. Software tools available for the analysis of experimental data commonly use multiple regression model that allows the study of the effects and iterations between model input quantities and one output variable. The use of multi-equation models gives a lot of freedom in the...
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Simplified Approach for Broadband RF Testing of Low Loss Magneto-Dielectric Samples
PublicationIn this paper, an attractive measurement techniqueis proposed to retrieve the broadband permittivity and permeabil-ity of the magneto-dielectric materials. The proposed techniqueis quite novel which mitigates the major problems associatedwith the conventional broadband RF material characterizationtechniques such as numerical instability and phase uncertaintywhen the length of the sample exceeds...
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Comparison of Deep Learning Approaches in Classification of Glacial Landforms
PublicationGlacial landforms, created by the continuous movements of glaciers over millennia, are crucial topics in geomorphological research. Their systematic analysis affords invaluable insights into past climatic oscillations and augments understanding of long-term climate change dynamics. The classification of these types of terrain traditionally depends on labor-intensive manual or semi-automated methods. However, the emergence of automated...
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Wykorzystanie sztucznych sieci neuronowych do szacowania wpływu drgań na budynki jednorodzinne
PublicationW artykule przedstawiono metodę prognozowania wpływu drgań na budynki mieszkalne z wykorzystaniem sztucznych sieci neuronowych. Drgania komunikacyjne mogą doprowadzić do uszkodzenia elementów konstrukcyjnych, a nawet do awarii budynku. Najczęstszym efektem są jednak rysy, pękanie tynku i wypraw. Metody oparte na sztucznej inteligencji są przybliżone, ale stanowią wystarczająco dokładną i ekonomiczną alternatywę dla tradycyjnych...
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Bandwidth Dependence of the Propagation Channel in Circular Metallic BAN Environments
PublicationIn this paper, the bandwidth dependence of the propagation channel for Body Area Networks (BANs) in circular metallic environments is addressed and models are proposed to evaluate the appropriate short-term fading margins that should be considered as a function of the system bandwidth. The deployment of BANs in metallic indoor environments, such as ships, factories, warehouses and other similar environments, involves additional...
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Deep Video Multi-task Learning Towards Generalized Visual Scene Enhancement and Understanding
PublicationThe goal of this thesis was to develop efficient video multi-task convolutional architectures for a range of diverse vision tasks, on RGB scenes, leveraging i) task relationships and ii) motion information to improve multi-task performance. The approach we take starts from the integration of diverse tasks within video multi-task learning networks. We present the first two datasets of their kind in the existing literature, featuring...
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Periodic and chaotic dynamics in a map‐based neuron model
PublicationMap-based neuron models are an important tool in modeling neural dynamics and sometimes can be considered as an alternative to usually computationally costlier models based on continuous or hybrid dynamical systems. However, due to their discrete nature, rigorous mathematical analysis might be challenging. We study a discrete model of neuronal dynamics introduced by Chialvo in 1995. In particular, we show that its reduced one-dimensional...
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Controlled grafting of vinylic monomers on polyolefins: a robust mathematical modeling approach
PublicationExperimental and mathematical modeling analyses were used for controlling melt free-radical grafting of vinylic monomers on polyolefins and, thereby, reducing the disturbance of undesired cross-linking of polyolefins. Response surface, desirability function, and artificial intelligence methodologies were blended to modeling/optimization of grafting reaction in terms of vinylic monomer content, peroxide initiator concentration,...
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The low-frequency magnetic field emissions on-board of the vessel
Open Research DataThe data represents measurement results performed on board of the vessel. The acquired time-waveforms, corresponding to the instantaneous values of the magnetic field (MF) induction were acquired near the cable supplying the bow thruster motor. Data recording of the magnetic field density (MFD) emissions was carried out with a/d converters of the data...
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Introduction to the ONDM 2022 special issue
PublicationThis JOCN special issue contains extended versions of selected papers presented at the 26th International Conference on Optical Network Design and Modeling (ONDM 2022), which took place 16–19 May 2022 at Warsaw University of Technology, Warsaw, Poland. The topics covered by the papers represent trends in optical networking research: application of machine learning to network management, cross-layer network performance optimization,...
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Minimizing Distribution and Data Loading Overheads in Parallel Training of DNN Acoustic Models with Frequent Parameter Averaging
PublicationIn the paper we investigate the performance of parallel deep neural network training with parameter averaging for acoustic modeling in Kaldi, a popular automatic speech recognition toolkit. We describe experiments based on training a recurrent neural network with 4 layers of 800 LSTM hidden states on a 100-hour corpora of annotated Polish speech data. We propose a MPI-based modification of the training program which minimizes the...
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OPTICAL STRAIN MEASUREMENT OF CONCRETE VERSUS MANUAL EXTENSOMETER MEASUREMENT BASED ON THE TEST RC DEEP BEAM IN A COMPLEX STATE OF STRESS
PublicationThe purpose of this study is to compare the strain measurement techniques of concrete in R-C element subjected to the monotonic load up to the failure. In the analysis manual extensometer methods of measurements and the optical system ARAMIS for non-contact three-dimensional measurements of deformation was used. The test sample was a cantilever deep beam loaded throughout the depth which was a part of the reinforced concrete deep...
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Metody sztucznej inteligencji do wspomagania bankowych systemów informatycznych
PublicationW pracy opisano zastosowania nowoczesnych metod sztucznej inteligencji do wspomagania bankowych systemów informatycznych. Wykorzystanie w systemach informatycznych algorytmów ewolucyjnych, harmonicznych, czy sztucznych sieci neuronowych w połączeniu z nowoczesną technologią mikroprocesorową umożliwiają zasadniczy wzrost konkurencyjności banku. Dlatego w pracy omówiono wybrane zastosowania bankowe ze szczególnym uwzględnieniem zbliżeniowych...
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Trust-Based Model for the Assessment of the Uncertainty of Measurements in Hybrid IoT Networks
PublicationThe aim of this paper is to introduce a NUT model (NUT: network-uncertainty-trust) that aids the decrease of the uncertainty of measurements in autonomous hybrid Internet of Things sensor networks. The problem of uncertainty in such networks is a consequence of various operating conditions and varied quality of measurement nodes, making statistical approach less successful. This paper presents a model for decreasing the uncertainty...
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A Novel Method for the Deblurring of Photogrammetric Images Using Conditional Generative Adversarial Networks
PublicationThe visual data acquisition from small unmanned aerial vehicles (UAVs) may encounter a situation in which blur appears on the images. Image blurring caused by camera motion during exposure significantly impacts the images interpretation quality and consequently the quality of photogrammetric products. On blurred images, it is difficult to visually locate ground control points, and the number of identified feature points decreases...