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Search results for: MAGNETIC SIGNATURES, MEASUREMENT DEPTH, MODELING, NEURAL NETWORKS
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GNSS INVENTORY OF HISTORIC NARROW-GAUGE RAILWAY LINE IN KOSZALIN UNDER EXTREMELY UNFAVORABLE MEASUREMENTS CONDITIONS FROM THE POINT OF VIEW OF SATELLITE SIGNALS AVAILABILITY
PublicationA team of academic researchers from the Gdańsk University of Technology, Gdynia Maritime University and the Polish Naval Academy have been working since 2009 on the methodology of using active GNSS geodetic networks for geodetic inventory of railways and on adapting this measurement technique for designing geometric layouts of railway and tram lines. Over the years, the team tested a variety of configurations of receivers and settings...
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Dynamic unattended measurement based routing algorithm for diffServ architecture
PublicationDynamic routing is very important in terms of assuring QoS in today's packet networks especially for streaming and elastic services. Existing solutions dedicated to dynamic routing are often too complicated and seem to be not usable in real time traffic scenarios where transferred traffic may vary significantly. This was the main reason for research and new routing mechanism proposal which should apply to today's packet networks....
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Paradoxes in the engineering change management process
PublicationPurpose: The main purpose of this paper is to conceptualize and operationalize paradoxes that are significant in the engineering change management (ECM) process. The following research question was stated: What are the paradoxes that influence the ECM process, and how can they be measured? Design/methodology/approach: The study is divided into two parts: conceptualization and operationalization. Conceptualization involved a literature...
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MACHINE LEARNING APPLICATIONS IN RECOGNIZING HUMAN EMOTIONS BASED ON THE EEG
PublicationThis study examined the machine learning-based approach allowing the recognition of human emotional states with the use of EEG signals. After a short introduction to the fundamentals of electroencephalography and neural oscillations, the two-dimensional valence-arousal Russell’s model of emotion was described. Next, we present the assumptions of the performed EEG experiment. Detail aspects of the data sanitization including preprocessing,...
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Updating the Coupling Algorithm between HYDRUS and MODFLOW in the HYDRUS Package for MODFLOW
PublicationThe HYDRUS-based flow package for MODFLOW (the HPM or the HYDRUS package) is an existing unsaturated zone flow package for MODFLOW. In MODFLOW with the HPM, the groundwater modeling domain is discretized into regular grids that can be combined into multiple zones based on similarities in soil hydrology, topographical characteristics, and the depth to the groundwater. Each of these zones is assigned one unsaturated soil profile...
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Method for determining of shallow water depths based on data recorded by UAV/USV vehicles and processed using the SVR algorithm
PublicationBathymetric measurements in waters shallower than 1 m are necessary to monitor seafloor relief changes in the coastal zone. This is especially important for ensuring the safety of navigation, navigation efficiency, as well as during the design and monitoring of hydrotechnical structures. Therefore, the aim of this article is to present a method for determining of shallow water depths based on data recorded by Unmanned Aerial Vehicle...
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The voltage on bus bars of the main switchboard of the car carrier electrical power system at sea trials during a sea voyage
Open Research DataThe dataset is part of the research results on the quality of supply voltage on bus bars of the main switchboard of the ship's electrical power system in different states of ship exploitation. The attached dataset contains the measurement results conducted onboard the car carrier at sea trials. The data were recorded during a sea voyage, under normal...
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The effect of social media communication on consumer perceptions of brands
PublicationResearchers and brand managers have limited understanding of the effects social media communication has on how consumers perceive brands. We investigated 504 Facebook users in order to observe the impact of firm-created and user-generated (UG) social media communication on brand equity (BE), brand attitude (BA) and purchase intention (PI) by using a standardized online survey throughout Poland. To test the conceptual model, we...
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A probabilistic-driven framework for enhanced corrosion estimation of ship structural components
PublicationThe work proposes a probabilistic-driven framework for enhanced corrosion estimation of ship structural components using Bayesian inference and limited measurement data. The new approach for modelling measurement uncertainty is proposed based on the results of previous corrosion tests that incorporate the non-uniform character of the corroded surface of structural components. The proposed framework's basic features are outlined,...
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Evaluation of structural change during fast transformation process of cross-linked NR into liquid NR by light pyrolysis
PublicationThe presence of cross-linked networks in rubber creates a tremendous problem for recycling and reusing of waste rubber. Fast transformation of cross-linked natural rubber (NR) into liquid natural rubber was carried out by light pyrolysis in temperature range from 240 to 300 °C in variable time (in range: 1–30 min). The transformation efficiency was evaluated by measuring the sol fraction and the cross-link density of the gel fraction....
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Improvement of speech intelligibility in the presence of noise interference using the Lombard effect and an automatic noise interference profiling based on deep learning
PublicationThe Lombard effect is a phenomenon that results in speech intelligibility improvement when applied to noise. There are many distinctive features of Lombard speech that were recalled in this dissertation. This work proposes the creation of a system capable of improving speech quality and intelligibility in real-time measured by objective metrics and subjective tests. This system consists of three main components: speech type detection,...
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Wireless Link Selection Methods for Maritime Communication Access Networks—A Deep Learning Approach
PublicationIn recent years, we have been witnessing a growing interest in the subject of communication at sea. One of the promising solutions to enable widespread access to data transmission capabilities in coastal waters is the possibility of employing an on-shore wireless access infrastructure. However, such an infrastructure is a heterogeneous one, managed by many independent operators and utilizing a number of different communication...
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Deep learning in the fog
PublicationIn the era of a ubiquitous Internet of Things and fast artificial intelligence advance, especially thanks to deep learning networks and hardware acceleration, we face rapid growth of highly decentralized and intelligent solutions that offer functionality of data processing closer to the end user. Internet of Things usually produces a huge amount of data that to be effectively analyzed, especially with neural networks, demands high...
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The Indication Methods and Techniques of Urban Light Pollution
PublicationThe goal of this study is to review and categorize approaches and methods of facing urban light pollution. Probing various references and documents, the current practice focus on extracting and reviewing different types of urban light pollution detection, survey, and measurement to define a taxonomy of methods by instant comparison. The means of measurement and detecting this pollution include 14 most cited techniques that have...
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Improving performance of large thrust bearings through modeling and experimentation
PublicationLarge thrust bearings are highly loaded machine elements and their failures cause serious losses. Start ups and stoppages of the bearing under load are specially critical regimes of operation. Load carrying capacity depends on the profile of the oil gap. In transient states this profile is also changing. In the design of large thrust bearings minimizing thermo-elastic deformations is an important goal, which can be accomplished...
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Asynchronous time difference of arrival (ATDOA) method
PublicationA new method for a location service in the asynchronous wireless sensor networks is outlined. This method, which is called asynchronous time difference of arrival (ATDOA), enables calculation of the position of a mobile node without knowledge of relative time differences (RTDs) between measuring sensors. The ATDOA method is based on the measurement of time difference of arrival between the node and the same sensor at the discrete...
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Superconductivity on a Bi Square Net in LiBi
PublicationWe present the crystallographic analysis, superconducting characterization and theoretical modeling of LiBi, that contains the lightest and the heaviest nonradioactive metal. The compound crystallizes in a tetragonal (CuAu-type) crystal structure with Bi square nets separated by Li planes (parameters a = 3.3636(1)Å and c = 4.2459(2) Å, c/a = 1.26). Superconducting state was studied in detail by magnetic susceptibility and heat...
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Optical Sensor Based Gestures Inference Using Recurrent Neural Network in Mobile Conditions
PublicationIn this paper the implementation of recurrent neural network models for hand gesture recognition on edge devices was performed. The models were trained with 27 hand gestures recorded with the use of a linear optical sensor consisting of 8 photodiodes and 4 LEDs. Different models, trained off-line, were tested in terms of different network topologies (different number of neurons and layers) and different effective sampling frequency...
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RNDM 2016 Workshop and 2nd Meeting of COST CA15127-RECODIS: Highlights from the Resilience Week in Halmstad, Sweden
PublicationLeading network resilience researchers took part in the Resilience Week on Sept. 12-15, 2016 at Halmstad University, SE by Prof. Magnus Jonsson from the Centre for Research on Embedded Systems (CERES), Halmstad University, SE, and Prof. Jacek Rak from Gdansk University of Technology, PL. It included two major events: - The 2nd Meeting of COST CA15127–RECODIS Action (Resilient Communication Services Protecting End-user Applications...
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Energy Consumption Modeling in SPMD and DAC Applications
PublicationIn this chapter, we show a study of energy consumption during execution of SPMD and DAC application – the same applications which time of execution we modeled in the previous two chapters. We measured an average power usage at a single node of the GALERA+ cluster during application execution and then we modeled the total energy consumption by the application. Next we simulated the applications using MERPSYS and we compared the...
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Short and Long Term Measurements in Assessment of FRP Composite Footbridge Behavior
PublicationThe paper presents application of different sensors for the purpose of short and long term measurements, as well as a structural health monitoring (SHM) system to assess the behavior of a novel fiber reinforced plastics (FRP) composite footbridge. The aim is to present a thorough and concise description of these sensors networks and results gathered with their aid during in situ measurement of strains, displacements, and vibrations,...
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Mutual Coupling Reduction in Antenna Arrays Using Artificial Intelligence Approach and Inverse Neural Network Surrogates
PublicationThis paper presents a novel approach to reduce undesirable coupling in antenna arrays using custom-designed resonators and inverse surrogate modeling. To illustrate the concept, two stand-ard patch antenna cells with 0.07λ edge-to-edge distance are designed and fabricated to operate at 2.45 GHz. A stepped-impedance resonator is applied between the antennas to suppress their mutual coupling. For the first time, the optimum values...
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Simulation model for evaluation of QoS routing algorithm in large packet networks
PublicationThe variety of traffic transferred via current telecommunication networks includes also voice, which should meet quality requirements. One of mechanisms, which can support QoS in current packet networks, is routing. There exist many routing proposals which should introduce the QoS into the network but practically they don't. Following paper presents the realization of simulation model for evaluation of a new routing algorithm DUMBRA...
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Results of nanoindentation test to calculate residual stress in an eyelet of undercarriage drag strut after laser treatment
Open Research DataIn order to determine the residual stress in the laser-processed an eyelet of undercarriage drag strut, a nanoindentation test was performed before and after stress relief annealing. For this purpose, after the hardness test, the sample was subjected to stress relief annealing at 270 °C for 2 hours. Annealing was performed in a vacuum furnace. Hardness...
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Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech
PublicationWe present a novel deep learning model for the detection and reconstruction of dysarthric speech. We train the model with a multi-task learning technique to jointly solve dysarthria detection and speech reconstruction tasks. The model key feature is a low-dimensional latent space that is meant to encode the properties of dysarthric speech. It is commonly believed that neural networks are black boxes that solve problems but do not...
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Comparison of Deep Neural Network Learning Algorithms for Mars Terrain Image Segmentation
PublicationThis 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...
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Fragmentation of Hydrographic Big Data Into Subsets During Reduction Process
PublicationThe article presented problems of fragmentation of hydrographic big data into smaller subsets during reduction process. Data reduction is a processing of reduce the value of the data set, in order to make them easier and more effective for the goals of the analysis. The main aim of authors is to create new reduction method. The article presented the first stage of this method – fragmentation of bathymetric data into subsets. It...
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Crystal growth and properties of a binary intermetallic ZrBi2 compound
PublicationSingle crystals of ZrBi2 were grown by a self-flux method. The material adopts TiAs2 structure type with lattice parameters: a = 10.233(4) Å, b = 15.581(2) Å, c = 3.994(5) Å. Crystals of ZrBi2 were studied by means of magnetic susceptiblity, specific heat and resistivity measurements. The compound reveals a metallic-like behavior (RRR = 30). The Sommerfeld coefficient equals γ = 1.59(16) mJ mol-1 K-2 and Debye temperature ΘD =...
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Reduction of the Velocity Impact on the Magnetic Flux Leakage Signal
PublicationThe velocity effect on the magnetic flux leakage (MFL) signal was investigated in this paper. Experiments were performed for velocity of the MFL tool within the range of 0–2 m/s. The velocity was not constant during each measurement to imitate real operational conditions of the MFL tool. Two components of the leakage were measured, i.e. the tangential to the motion direction (x) and the normal to the investigated surface (z). In...
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Fault detection in measuring systems of power plants
PublicationThis paper describes possibility of forming diagnostic relations based on application of the artifical neural networks (ANNs), intended for the identifying of degradation of measuring instruments used in developed power systems. As an example a steam turbine high-power plant was used. And, simulative calculations were applied to forming diagnostic neural relations. Both degradation of the measuring instruments and simultaneously...
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Fast Fading Influence on the Deep Learning-Based LOS and NLOS Identificationin Wireless Body Area Networks
PublicationIn the article, the fast fading influence on the proposed DL (Deep Learning) approach for LOS (Line-of-Sight) and NLOS (Non-Line-of-Sight) conditions identification in Wireless Body Area Networks is investigated. The research was conducted on the basis of the off-body communication measurements using the developed mobile measurement stand, in an indoor environment for both static and dynamic scenarios. The measurements involved...
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Feasibility Study GaN Transistors Application in the Novel Split-Coils Inductive Power Transfer System with T-Type Inverter
PublicationA promising solution for inductive power transfer and wireless charging is presented on the basis of a single-phase three-level T-type Neutral Point Clamped GaN-based inverter with two coupled transmitting coils. The article focuses on the feasibility study of GaN transistor application in the wireless power transfer system based on the T-type inverter on the primary side. An analysis of power losses in the main components of the...
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Structural, magnetic and spectral properties of tetrahedral cobalt(II) silanethiolates: a variety of structures and manifestation of field-induced slow magnetic relaxation
PublicationBlue crystals of five heteroleptic cobalt(II) silanethiolates 1–5 have been obtained by the reaction of [Co{SSi (tBuO)3}2(NH3)]2 with aminopyridines and aminomethylpyridines at an appropriate molar ratio and their structural, spectral, thermal and magnetic properties have been established and described. All complexes 1–5 contain Co(II) ions in a tetrahedral CoN2S2 environment formed by (tBuO)3SiS− residues and pyridines and present...
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Urban scene semantic segmentation using the U-Net model
PublicationVision-based semantic segmentation of complex urban street scenes is a very important function during autonomous driving (AD), which will become an important technology in industrialized countries in the near future. Today, advanced driver assistance systems (ADAS) improve traffic safety thanks to the application of solutions that enable detecting objects, recognising road signs, segmenting the road, etc. The basis for these functionalities...
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Modeling nutrient removal and energy consumption in an advanced activated sludge system under uncertainty
PublicationActivated sludge models are widely used to simulate, optimize and control performance of wastewater treatment plants (WWTP). For simulation of nutrient removal and energy consumption, kinetic parameters would need to be estimated, which requires an extensive measurement campaign. In this study, a novel methodology is proposed for modeling the performance and energy consumption of a biological nutrient removal activated sludge system...
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LDRAW based positional renders of LEGO bricks
Open Research Data243 different LEGO bricks renders of size 250x250 in 5 colors in 120 viewing angles stored as JPEG images. The renders are used to train neural networks for bricks recognition. All images were generated using L3P (http://www.hassings.dk/l3/l3p.html) and POV-Ray (http://www.povray.org/) tools and were based on the 3D models from LDraw (https://www.ldraw.org/)...
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Spatial characterization of H 2: CH 4 dissociation level in microwave ECR plasma source by fibre-optic OES
PublicationSpatially resolved optical emission spectroscopy (SR-OES) was used to investigate microwave activated H2/Ar/CH4 plasma under conditions of the electron cyclotron resonance (ECR). The chemistry and composition of the gas phase were studied using self-designed fibre-optic system with echelle type spectrometer during CVD deposition of polycrystalline diamond. One-dimensional intensity profiles of the main species were collected along...
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Application of the Optimum Dataset Method in Archeological Studies on Barrows
PublicationLight Detection and Ranging (LiDAR) became one of the technologies used in archaeological research. It allows for relatively easy detection of archaeological sites that have their own field form, e.g.: barrows, fortresses, tracts, ancient fields [1]. As a result of the scanning, the so-called point cloud is obtained, often consisting of millions of points. Such large measurement datasets are very time-consuming and labor-intensive...
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Categorization of emotions in dog behavior based on the deep neural network
PublicationThe aim of this article is to present a neural system based on stock architecture for recognizing emotional behavior in dogs. Our considerations are inspired by the original work of Franzoni et al. on recognizing dog emotions. An appropriate set of photographic data has been compiled taking into account five classes of emotional behavior in dogs of one breed, including joy, anger, licking, yawning, and sleeping. Focusing on a particular...
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A new approach to active noise and vibration control - [Part I: the known frequency case]
PublicationThis paper presents a new approach to rejection of complex-valued sinusoidal disturbances acting at the output of a discrete-time stable linear plant with unknown dynamics. It is assumed that the frequency of the sinusoidal disturbance is known, and that the output signal is contaminated with wideband measurement noise. The disturbance rejection control rule is first derived and analyzed for a nominal plant model, different from...
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Quasi-one-dimensional exchange interactions and short-range magnetic correlations in CuTeO4
PublicationCuTeO4 has been proposed as a crystallographically distinct, yet electronic structure analog, of the superconducting cuprates. Here, we present a detailed characterization of the physical properties of CuTeO4 to address this proposal. Fitting of magnetic susceptibility data indicates unexpected quasi-one-dimensional, antiferromagnetic correlations at high temperature, with a nearest-neighbor Heisenberg exchange of 1=164(5) K....
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Application of Barkhausen effect in the impact assessment of welding to internal stress distribution in steel
PublicationThe paper presents identification method of internal stresses in plane steel elements in the chase of deliverance and welding assembly. The assessment was made by means of a non-destructive experimental method based on measurements incorporating local external magnetic field and the measurement of induced voltage, including Barkhausen noise. This method allows a degradation assessment due to internal and external actions, causing...
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Application of Barkhausen effect in the impact assessment of welding to internal stress distribution in steel
PublicationThe paper presents identification method of internal stresses in plane steel elements in the chase of deliverance and welding assembly. The assessment was made by means of a non-destructive experimental method based on measurements incorporating local external magnetic field and the measurement of induced voltage, including Barkhausen noise. This method allows a degradation assessment due to internal and external actions, causing...
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Characterization of Defects Inside the Cable Dielectric With Partial Discharge Modeling
PublicationThe continuous monitoring of power system devices is an important step toward keeping such capital assets safe. Partial discharge (PD)-based measurement tools provide a reliable and accurate condition assessment of power system insulations. It is very common that voids or cavities exist in every solid dielectric insulation medium. In this article, different voids are modeled and analyzed using an advanced finite element (FE)-based...
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Enhancing Resilience of FSO Networks to Adverse Weather Conditions
PublicationOptical wireless networks realized by means of gigabit optical wireless communication (OWC) systems are becoming, in a variety of applications, an important alternative, or a complementary solution, to their fiber-based counterparts. However, performance of the OWC systems can be considerably degraded in periods of unfavorable weather conditions, such as heavy fog, which temporarily reduce the effective capacity of the network....
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Indoor accelerated controlled corrosion degradation test of small- and large-scale specimens
PublicationThe work presented here is a part of a long-term project analysing the structural behaviour of ageing marine structures. An accelerated corrosion degradation set-up was developed to reproduce corroded marine structural specimens of different degrees of degradation, controlling various natural factors, i.e., temperature, oxygen content, salinity, and flow velocity. The nine stiffened plates of 1.2 m length and 30 small scale specimens...
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Modelling of wastewater treatment plant for monitoring and control purposes by state - space wavelet networks
PublicationMost of industrial processes are nonlinear, not stationary, and dynamical with at least few different time scales in their internal dynamics and hardly measured states. A biological wastewater treatment plant falls into this category. The paper considers modelling such processes for monitorning and control purposes by using State - Space Wavelet Neural Networks (SSWN). The modelling method is illustrated based on bioreactors of...
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Explainable machine learning for diffraction patterns
PublicationSerial crystallography experiments at X-ray free-electron laser facilities produce massive amounts of data but only a fraction of these data are useful for downstream analysis. Thus, it is essential to differentiate between acceptable and unacceptable data, generally known as ‘hit’ and ‘miss’, respectively. Image classification methods from artificial intelligence, or more specifically convolutional neural networks (CNNs), classify...
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Possibilities of radioisotope measuring in control of an unstable solid particles hydrotransport
PublicationThe paper presents γ-radiation proposal to control a multiphase flow, independently from circumstances. So this method may be applied even in compound industrial or environmental processes. Moreover in many cases, it is the only method for applications for dense mixture containing coarse angular grains. The constructed equipment allows continuous measurement of density as well as solid phase for both concentration and average velocity....
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An Analysis of Neural Word Representations for Wikipedia Articles Classification
PublicationOne of the current popular methods of generating word representations is an approach based on the analysis of large document collections with neural networks. It creates so-called word-embeddings that attempt to learn relationships between words and encode this information in the form of a low-dimensional vector. The goal of this paper is to examine the differences between the most popular embedding models and the typical bag-of-words...