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Decisional-DNA-Based Digital Twin Implementation Architecture for Virtual Engineering Objects
PublikacjaDigital twin (DT) is an enabling technology that integrates cyber and physical spaces. It is well-fitted for manufacturing setup since it can support digitalized assets and data analytics for product and process control. Conventional manufacturing setups are still widely used all around the world for the fabrication of large-scale production. This article proposes a general DT implementation architecture for engineering objects/artifacts...
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Coastal Cliffs Monitoring and Prediction of Displacements Using Terrestial Laser Scanning
PublikacjaCoastal cliffs are very sensitive to degradation caused by erosion and abrasion. Thus, it is very important to monitor susceptibility of the cliffs in terms of slope angles and ground fall resulting from vertical morphology of the cliffs. The results could be used for example to establish the boundaries of the safe investments zone or retreat infrastructure buildings in case of real threat such as degradation of the objects of...
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Electromagnetic interference frequencies prediction model of flyback converter for snubber design
PublikacjaSnubber design for flyback converters usually requires experimental prototype measurements or simulation based on accurate and complex models. In this study simplified circuit modelling of a flyback converter has been described to dimension snubbers in early stage of design process. Simulation based prediction of the transistor and diode ringing frequencies has been validated by measurements in a prototype setup. In that way obtained...
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Improving Effectiveness of SVM Classifier for Large Scale Data
PublikacjaThe paper presents our approach to SVM implementation in parallel environment. We describe how classification learning and prediction phases were pararellised. We also propose a method for limiting the number of necessary computations during classifier construction. Our method, named one-vs-near, is an extension of typical one-vs-all approach that is used for binary classifiers to work with multiclass problems. We perform experiments...
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Observing its long-term effects on a short-term, multi-day evaluation of the effectiveness of hearing aid use
PublikacjaThe main objective of the research study was to develop a method for evaluating the effectiveness of hearing protection with hearing aids tailored to the needs and prevailing conditions in the acoustic environments where the elderly most often reside. The method was also intended to estimate the benefits of hearing aids and allow prediction of such an effect based on a short-term trial. It is noteworthy that a short-term evaluation...
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FFT analysis of temperature modulated semiconductor gas sensor response for the prediction of ammonia concentration under humidity interference
PublikacjaThe increasing environmental contamination forces the need to design reliable devices for detecting of the volatile compounds present in the air. For this purpose semiconductor gas sensors, which have been widely used for years, are often utilized. Although they have many advantages such as low price and quite long life time, they still lack of long term stability and selectivity. Namely, environmental conditions have significant...
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Electrochemical simulation of metabolism for antitumor-active imidazoacridinone C-1311 and in silico prediction of drug metabolic reactions
PublikacjaThe metabolism of antitumor-active 5-diethylaminoethylamino-8-hydroxyimidazoacridinone (C-1311) has been investigated widely over the last decade but some aspects of molecular mechanisms of its metabolic transformation are still not explained. In the current work, we have reported a direct and rapid analytical tool for better prediction of C-1311 metabolism which is based on electrochemistry (EC) coupled on-line with electrospray...
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Concrete mix design using machine learning
PublikacjaDesigning a concrete mix is a process of synthesizing many components, it is not a simple process and requires extensive technical knowledge. The design process itself focuses on obtaining the required strength of concrete. Very often designing a concrete mix takes into account the need to maintain the proper water-demand and frost-resistance features. The parameters that influence the concrete class most significantly are the...
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Proceedings of the fib Symposium 2019: Concrete - Innovations in Materials, Design and Structures 2019
PublikacjaDesigning a concrete mix is a process of synthesizing many components, it is not a simple process and requires extensive technical knowledge. The design process itself focuses on obtaining the required strength of concrete. Very often designing a concrete mix takes into account the need to maintain the proper water-demand and frost-resistance features. The parameters that influence the concrete class most significantly are the...
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Fast and reliable knowledge-based design closure of antennas by means of iterative prediction-correction scheme
PublikacjaA novel framework for expedited antenna optimization with an iterative prediction-correction scheme is proposed. The methodology is comprehensively validated using three real-world antenna structures: narrow-band, dual-band and wideband, optimized under various design scenarios. The keystone of the proposed approach is to reuse designs pre-optimized for various sets of performance specifications and to encode them into metamodels...
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Combination of instrumental and qualitative descriptive analysis for evaluation of selected tonic waters quality features
PublikacjaThe combination of sensory and instrumental analysis was applied for quality assurance of selected tonic waters. The Quantitative Descriptive Analysis (QDA) in terms of fourteen sensory attributes (aroma, astringency, bite, burn, numbing, tongue heaviness, carbonation, mouth coating, sweet taste, sour taste, bitter taste, sweet aftertaste, sour aftertaste, bitter aftertaste) of selected tonic waters was performed by sensory experts....
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Localization of impulsive disturbances in archive audio signals using predictive matched filtering
PublikacjaThe problem of elimination of impulsive disturbances from archive audio signals is considered and its new solution, called predictive matched filtering, is proposed. The new approach is based on the observation that a large percentage of noise pulses corrupting archive audio recordings have highly repetitive shapes that match several typical “patterns”, called click templates. To localize noise pulses, click templates can be correlated...
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AN INNOVATIVE APPROACH TO PREDICTION ENERGETIC EFFECTS OF WOOD CUTTING PROCESS WITH CIRCULAR-SAW BLADES
PublikacjaIn the classical approach, energetic effects (cutting forces and cutting power) of wood sawing process are generally calculated on the basis of the specific cutting resistance, which is in the case of wood cutting the function of more or less important factors. The aim of the paper is to present a new calculating model using the application of modern fracture mechanics and to compare cutting parameters of native beech, Bendywood...
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A city and a wind farm. Landscape perspective
PublikacjaThe aim of the paper is to present the problems of the location of the wind farms in close neighbourhood to the historical cities, and the ways to minimize the potential landscape threats. The production of clean energy is obligatory in EU. In spite of how positive to the environment the wind energy production is, it may cause negative effects. The results of landscape studies of two towns in Poland prove that the location of such...
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Akaike's final prediction error criterion revisited
PublikacjaWhen local identification of a nonstationary ARX system is carried out, two important decisions must be taken. First, one should decide upon the number of estimated parameters, i.e., on the model order. Second, one should choose the appropriate estimation bandwidth, related to the (effective) number of input-output data samples that will be used for identification/ tracking purposes. Failure to make the right decisions results...
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MESOSCALE FUNCTIONS OF GPS SLANT DELAY
PublikacjaThe paper presents a computer module for GPS slant delay determination using data from COAMPS (Coupled Ocean/Atmosphere Mesoscale Prediction System) mesoscale non-hydrostatic model of the atmosphere which is run on IA64 Feniks computer cluster in the Department of Civil Engineering and Geodesy of the Military University of Technology. The slant delay is the result of integrating the ray (eikonal) equation for the spatial function...
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Robustness Analysis of a Distributed MPC Control System of a Turbo-Generator Set of a Nuclear Plant – Disturbance Issues
PublikacjaTypically, there are two main control loops with PI controllers operating at each turbo-generator set. In this paper, a distributed model predictive controller with local quadratic model predictive controllers for the turbine generator is proposed instead of a set of classical PI controllers. The local quadratic predictive controllers utilize step-response models for the controlled system components. The parameters of these models...
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Safety assurance strategies for autonomous vehicles
PublikacjaAssuring safety of autonomous vehicles requires that the vehicle control system can perceive the situation in the environment and react to actions of other entities. One approach to vehicle safety assurance is based on the assumption that hazardous sequences of events should be identified during hazard analysis and then some means of hazard avoidance and mitigation, like barriers, should be designed and implemented. Another approach...
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Developing Prognostic Models of Organization Evolution
PublikacjaThe work focuses on the problem of measuring evolution of IT organizations. Changes in business influence functioning of the IT organization. IT departments or companies must ensure that the needs of their parent company/customers will be met. Therefore they must constantly evolve. Following question can be raised: is it possible to support process of changes the IT organization to run it smoother, faster, easier but with reduced...
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Ultrawideband transmission in physical channels: a broadband interference view
PublikacjaThe superposition of multipath components (MPC) of an emitted wave, formed by reflections from limiting surfaces and obstacles in the propagation area, strongly affects communication signals. In the case of modern wideband systems, the effect should be seen as a broadband counterpart of classical interference which is the cause of fading in narrowband systems. This paper shows that in wideband communications, the time- and frequency-domain...
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Calibration of precipitation estimation algorithm with particular emphasis on the Pomeranian region using high performance computing
PublikacjaFast and accurate precipitation estimation is an important element of remote atmosphere monitoring, as it allows, for example, to correct short-term weather forecasts and the prediction of several types of meteorological threats. The paper presents methodology for calibrating precipitation estimation algorithm based on MSG SEVIRI sensor data, and Optimal Cloud Analysis product available via EumetCast transmission. Calibration is...
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Influence of pitting corrosion on fatigue and corrosion fatigue of ship and offshore structures. Part II: Load - pit crack interaction
PublikacjaIn the paper has been discussed influence of stresses on general corrosion rate and corrosion pit nucleation and growth rate, whose presence has been questioned by some authors but accepted by most of them. Influence of pit walls roughness on fatigue life of a plate suffering pit corrosion and presence of so called "non damaging" pits which never lead to initiation of fatigue crack, has been presented. Possibility of prediction...
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Two Stage SVM and kNN Text Documents Classifier
PublikacjaThe paper presents an approach to the large scale text documents classification problem in parallel environments. A two stage classifier is proposed, based on a combination of k-nearest neighbors and support vector machines classification methods. The details of the classifier and the parallelisation of classification, learning and prediction phases are described. The classifier makes use of our method named one-vs-near. It is...
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Ionosphere variability I: Advances in observational, monitoring and detection capabilities
PublikacjaThe paper aims to review recent advances regarding the observational and monitoring capabilities of the ionization conditions in the Earth's upper atmosphere. The analysis spans both ground and space-based experiments, seeking for new installations and/or missions, new or upgraded instrumentation and/or observational network establishments as means for advancing current understanding and prediction ability of the ionosphere variability....
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Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublikacjaSince 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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Natural ventilation performance of family building in cold climate during windy days
PublikacjaAdequately designed natural ventilation is the cheapest and easiest way to effectively remove indoor pollutants and keep the fresh air inside a building. A prediction of performance and effectiveness of ventilation in order to determine the design of a ventilation system can provide real and long term cost savings. The paper presents results of performance (air change rate ACH) and effectiveness (CO2 concentration in the breathing...
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Outlier detection method by using deep neural networks
PublikacjaDetecting outliers in the data set is quite important for building effective predictive models. Consistent prediction can not be made through models created with data sets containing outliers, or robust models can not be created. In such cases, it may be possible to exclude observations that are determined to be outlier from the data set, or to assign less weight to these points of observation than to other points of observation....
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An adaptive-noise Augmented Kalman Filter approach for input-state estimation in structural dynamics
PublikacjaThe establishment of a Digital Twin of an operating engineered system can increase the potency of Structural Health Monitoring (SHM) tools, which are then bestowed with enhanced predictive capabilities. This is particularly relevant for wind energy infrastructures, where the definition of remaining useful life is a main driver for assessing the efficacy of these systems. In order to ensure a proper representation of the physical...
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Accuracy of Pretreatment Ultrasonography Assessment of Intra-Abdominal Spread in Epithelial Ovarian Cancer: A Prospective Study
PublikacjaThe aim of this study was to test the accuracy of ultrasonography performed by gynecological oncologists for the preoperative assessment of epithelial ovarian cancer (EOC) spread in the pelvis and abdominal cavity. A prospective, observational cohort study was performed at a single tertiary cancer care unit. Patients with suspected EOC were recruited and underwent comprehensive transvaginal and abdominal ultrasonography performed...
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Investigation of the road noise source employing an automatic noise monitoring station
PublikacjaThe paper presents a pilot investigation of noise source models in two selected localizations in the context of future dynamic noise map creation. The experiments were carried out using the automatic noise monitoring station engineered at the Multimedia Systems Departmentof the Gda´nsk University of Technology. The results of the noise measurements employing monitoring stations and its comparison to the reference values are depicted....
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DO WE NEED NAVIER NUMBER? – FURTHER REMARKS AND COMPARISON WITH ANOTHER DIMENSIONLESS NUMBERS
PublikacjaThis paper presents a role of the Navier number (Na-dimensionless slip-length) in universal modelling of flow reported in micro- and nano-channels like: capillary biological flows, fuel cell systems, micro-electro-mechanical systems and nano-electro-mechanical systems. Similar to another bulk-like and surface-like dimensionless numbers, the Na number should be treated as a ratio of internal viscous to external viscous momentum...
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COMPARISON OF TWO MODELS OF CONDENSATION
PublikacjaIn the low-pressure part of steam turbine, the state path usually crosses the saturation line in penultimate stages. At least last two stages of this part of turbines operate in two –phase region. The liquid phase in this region in mainly created in the process of homogeneous and heterogeneous condensation. Several observations confirm however, that condensation often occurs earlier than it is predicted by theory i.e. before the...
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Decisional DNA and Optimization Problem
PublikacjaMany researchers have proved that Decisional DNA (DDNA) and Set of Experience Knowledge Structure (SOEKS or SOE) is a technology capable of gathering information and converting it into knowledge to help decision-makers to make precise decisions in many ways. These techniques have a feature to combine with different tools, such as data mining techniques and web crawlers, helping organization collect information from different sources...
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Sparse autoregressive modeling
PublikacjaIn the paper the comparison of the popular pitch determination (PD) algorithms for thepurpose of elimination of clicks from archive audio signals using sparse autoregressive (SAR)modeling is presented. The SAR signal representation has been widely used in code-excitedlinear prediction (CELP) systems. The appropriate construction of the SAR model is requiredto guarantee model stability. For this reason the signal representation...
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Identification of nonstationary multivariate autoregressive processes– Comparison of competitive and collaborative strategies for joint selection of estimation bandwidth and model order
PublikacjaThe problem of identification of multivariate autoregressive processes (systems or signals) with unknown and possibly time-varying model order and time-varying rate of parameter variation is considered and solved using parallel estimation approach. Under this approach, several local estimation algorithms, with different order and bandwidth settings, are run simultaneously and compared based on their predictive performance. First,...
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Estimation and Prediction of Vertical Deformations of Random Surfaces, Applying the Total Least Squares Collocation Method
PublikacjaThis paper proposes a method for determining the vertical deformations treated as random fields. It is assumed that the monitored surfaces are subject not only to deterministic deformations, but also to random fluctuations. Furthermore, the existence of random noise coming from surface’s vibrations is also assumed. Such noise disturbs the deformation’s functional models. Surface monitoring with the use of the geodetic levelling...
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Estimation of Housing Demand with Adaptive Neuro-Fuzzy Inference Systems (ANFIS)
PublikacjaIt has always been important to anticipate the demand for a product. To determine the demand for any product, the parameters such as the economic situation and the demands of the rival products are used generally. Especially in the housing sector, which is the locomotive sector for emerging countries, it is critical to anticipate housing demand and its relationship with economic variables. Because of that, economists, real estate...
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Dynamic Bankruptcy Prediction Models for European Enterprises
PublikacjaThis manuscript is devoted to the issue of forecasting corporate bankruptcy. Determining a firm’s bankruptcy risk is one of the most interesting topics for investors and decision-makers. The aim of the paper is to develop and to evaluate dynamic bankruptcy prediction models for European enterprises. To conduct this objective, four forecasting models are developed with the use of four different methods—fuzzy sets, recurrent and...
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Modeling the Structure, Dynamics, and Transformations of Proteins with the UNRES Force Field
PublikacjaThe physics-based united-residue (UNRES) model of proteins ( www.unres.pl ) has been designed to carry out large-scale simulations of protein folding. The force field has been derived and parameterized based on the principles of statistical-mechanics, which makes it independent of structural databases and applicable to treat nonstandard situations such as, proteins that contain D-amino-acid residues. Powered by Langevin dynamics...
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INFLUENCE OF THE HULL SHAPE ON THE ENERGY DEMAND OF A SMALL INLAND VESSEL WITH HYBRID PROPULSION
PublikacjaRecently, there has been a significant development of ecological propulsion systems, which is in line with the general trend of environmentally friendly “green shipping”. The main aim is to build a safe, low-energy passenger ship with a highly efficient, emission-free propulsion system. This can be achieved in a variety of ways. The article presents the main problems encountered by designers and constructors already at the stage...
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Introduction to the special issue on machine learning in acoustics
PublikacjaWhen we started our Call for Papers for a Special Issue on “Machine Learning in Acoustics” in the Journal of the Acoustical Society of America, our ambition was to invite papers in which machine learning was applied to all acoustics areas. They were listed, but not limited to, as follows: • Music and synthesis analysis • Music sentiment analysis • Music perception • Intelligent music recognition • Musical source separation • Singing...
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Framework for Integration Decentralized and Untrusted Multi-vendor IoMT Environments
PublikacjaLack of standardization is highly visible while we use historical data sets or compare our model with others that use IoMT devices from different vendors. The problem also concerns the trust in highly decentralized and anonymous environments where sensitive data are transferred through the Internet and then are analyzed by third-party companies. In our research we propose a standard that has been implemented in the form of framework...
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Optical method supported by machine learning for dynamics of C‐reactive protein concentrations changes detection in biological matrix samples
PublikacjaIn this article we present the novel spectroscopy method supported with machine learning for real-time detection of infectious agents in wastewater. In the case of infectious diseases, wastewater monitoring can be used to detect the presence of inflammation biomarkers, such as the proposed C-reactive protein, for monitoring inflammatory conditions and mass screening during epidemics for early detection in communities of concern,...
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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublikacjaTo this day, driver fatigue remains one of the most significant causes of road accidents. In this paper, a novel way of detecting and monitoring a driver’s physical state has been proposed. The goal of the system was to make use of multimodal imaging from RGB and thermal cameras working simultaneously to monitor the driver’s current condition. A custom dataset was created consisting of thermal and RGB video samples. Acquired data...
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Accurate modeling of quasi-resonant inverter fed IM drive
PublikacjaIn this paper wide-band modeling methodology of a parallel quasi-resonant dc link inverter (PQRDCLI) fed induction machine (IM) is presented. The modeling objective is early-design stage prediction of conductive electromagnetic interference (EMI) emissions of the considered converter fed IM drive system. Operation principles of the selected topology of PQRDCLI feeding IM drive are given. Modeling of the converter drive system is...
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Rapid multi-objective design optimisation of compact microwave couplers by means of physics-based surrogates
PublikacjaThe authors introduce a methodology for fast multi-objective design optimisation of miniaturised microwave couplers. The approach exploits the surrogate-based optimisation paradigm with an underlying low-fidelity model constructed from an equivalent circuit of the structure under consideration, corrected through implicit and frequency space mapping. A fast prediction tool obtained this way is subsequently optimised by a multi-objective...
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Application Isssues of the Semi-Markov Reliability Model
PublikacjaPredicting the reliability of marine internal combustion engines, for instance, is of particular importance, as it makes it possible to predict their future reliability states based on the information on the past states. Correct reliability prediction is a complex process which consists in processing empirical results obtained from operating practice, complemented by analytical considerations. The process of technical state changes...
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Rapid antenna design optimization using shape-preserving response prediction
PublikacjaAn approach to rapid optimization of antennas using the shape-preserving response-prediction (SPRP) technique and coarsediscretization electromagnetic (EM) simulations (as a low-fidelity model) is presented. SPRP allows us to estimate the response of the high-fidelity EM antenna model, e.g., its reflection coefficient versus frequency, using the properly selected set of so-called characteristic points of the low-fidelity model...
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Positron scattering on molecular hydrogen: Analysis of experimental and theoretical uncertainties
PublikacjaExperiments performed in recent years on positron scattering from molecular hydrogen indicated a rise of the total cross section in the limit of zero energy, but essentially disagree on the amplitude of this rise. Mitroy and collaborators [J.-Y. Zhang et al., Phys. Rev. Lett. 103, 223202 (2009)] predicted a scattering length somewhat different from values deduced experimentally. Using a Markov chain Monte Carlo modified effective...
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Advancing Solar Energy: Machine Learning Approaches for Predicting Photovoltaic Power Output
PublikacjaThis research is primarily concentrated on predicting the output of photovoitaic power, an essential field in the study of renewable energy. The paper comprehensively reviews various forecasting methodologies, transitioning from conventional physical and statistical methods to advanced machine learning (ML) techniques. A significant shift has been observed from traditional point forecasting to machine learning-based forecasting...