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Search results for: DARA-DRIVEN MODELING , SURROGATE MODELING , PERFORMANCE-DRIVEN SURROGATES , NESTED KRIGING , DEEP REGRESSION MODEL
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Experimental and Theoretical Insights into the Intermolecular Interactions in Saturated Systems of Dapsone in Conventional and Deep Eutectic Solvents
PublicationSolubility is not only a crucial physicochemical property for laboratory practice but also provides valuable insight into the mechanism of saturated system organization, as a measure of the interplay between various intermolecular interactions. The importance of these data cannot be overstated, particularly when dealing with active pharmaceutical ingredients (APIs), such as dapsone. It is a commonly used anti-inflammatory and...
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Towards a precise model of DSM economics
PublicationRozdział podejmuje zagadnienia związane z opłacalnością zastosowania metod dziedzinowych (ang. Domain-Specific Modeling). Omówiono cechy charakterystyczne metod dziedzinowych i powiązanej z nimi technologii. Przedstawiono model kosztów pokrywający koszty początkowe, koszty utrzymania oraz koszty i zyski powiązane z fazą wytwarzania z zastosowaniem automatyzacji. Zaprezentowano model referencyjny kosztów przy tradycyjnym wytwarzaniu...
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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublicationComplexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...
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The impact of precipitation and external carbon source addition on biological nutrient removal in activated sludge systems – experimental investigation and mathematical modeling
PublicationThe aim of this study was to determine the effects of chemical precipitation and addition of external carbonsources on the denitrification capability and enhanced biological phosphorus removal (EBPR) interactions atthe ‘Wschod’ WWTP (600,000 PE) in Gdansk (northern Poland). For this purpose, different kinds of batch experimentswere carried out with the settled wastewater (without pretreatment and after coagulation-flocculation)and...
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Experimental investigations and damage growth modeling of EN‐AW 2024 aluminum alloy under LCF loading accounting creep pre‐deformation
PublicationThis article presents the results of experimental tests of creep rupture and of low-cycle fatigue (LCF) of EN-AW 2024 aluminum alloy devoid of damage and having preliminary damage. The preliminary damage was dealt in the process of creep at elevated temperature 100C, 200C, and 300C until achievement of two different strain values at each temperature. Samples with preliminary damage were subjected to fatigue tests at room temperature....
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Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublicationThis paper focuses on convolution neural network quantization problem. The quantization has a distinct stage of data conversion from floating-point into integer-point numbers. In general, the process of quantization is associated with the reduction of the matrix dimension via limited precision of the numbers. However, the training and inference stages of deep learning neural network are limited by the space of the memory and a...
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Modeling the Effect of External Carbon Source Addition under Different Electron Acceptor Conditions in Biological Nutrient Removal Activated Sludge Systems
Publicationhe aim of this study was to expand the International Water Association Activated Sludge Model No. 2d (ASM2d) to predict the aerobic/anoxic behavior of polyphosphate accumulating organisms (PAOs) and “ordinary” heterotrophs in the presence of different external carbon sources and electron acceptors. The following new aspects were considered: (1) a new type of the readily biodegradable substrate, not available for the anaerobic activity...
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Modeling of wind wave induced sediment transport in the coastal zone of polish marine areas (Southern Baltic)
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Modeling of the M X-ray line structures for tungsten and L X-ray line structures for molybdenum
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The comparison of semiempirical and ab initio molecular modeling methods in activity and property evaluation of selected antimicrobial sulfonamides
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Usability of accident and incident reports for evidence-based risk modeling – A case study on ship grounding reports
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Structure–activity relationships study on biological activity of peptides as dipeptidyl peptidase IV inhibitors by chemometric modeling
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<title>TESLA cavity modeling and digital implementation with FPGA technology solution for control system development</title>
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How the “Liquid Drop” Approach Could Be Efficiently Applied for Quantitative Structure–Property Relationship Modeling of Nanofluids
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Fuzzy soft modeling of environmental data. A study of the impact of a Phosphatic Fertilizer Plant on the adjacent environment in Gdańsk
PublicationAnaliza podobieństwa obejmuje nie tylko zastosowanie logiki rozmytej, ale również wiele innych podejść matematycznych. Opracowano wiele algorytmów, których celem jest wyodrębnienie wyraźnych skupień (hard clusters) z danego zbioru danych. Prawdopodobnie najczęściej stosowanymi algorytmami są tzw. algorytmy c-średnie (c-means algorithms). Twarde c-średnie (hard c-means) służy do ostrej klasyfikacji, podczas której obiekt jest przypisany...
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Modeling and optimization of chemical-treated torrefaction of wheat straw to improve energy density by response surface methodology
PublicationToday, torrefaction is important technique for extending the potential of biomass for improvement of energy density. The independent variables investigated for torrefaction study were temperature, retention time, acid concentration, and particle size. The experiment was designed by central composite design (CCD) method using design expert (version 11). The three dependent variables were higher heating value (HHV), energy enhancement...
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Ontological Modeling for Contextual Data Describing Signals Obtained from Electrodermal Activity for Emotion Recognition and Analysis
PublicationMost of the research in the field of emotion recognition is based on datasets that contain data obtained during affective computing experiments. However, each dataset is described by different metadata, stored in various structures and formats. This research can be counted among those whose aim is to provide a structural and semantic pattern for affective computing datasets, which is an important step to solve the problem of data...
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Green`s function methods for Mathematical modeling of unidirectional diffusion process in isothermal metals bonding process
PublicationPodano wykorzystanie funkcji Greena w rozwiązaniu matematycznego modelu dyfuzji jednowymiarowej podczas izotermicznego łączenia metali.
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FE-modeling of shear resistance degradation in granular materials during cyclic shearing under CNS condition
PublicationW artykule przedstawiono wyniki numerycznej analizy degradacji wytrzymałości na ścinanie w materiałach granulowanych podczas cyklicznego ścinania z warunkiem stałej sztywności normalnej. Obliczenia wykonano przy zastosowaniu metody elementów skończonych i mikropolarnego modelu hipoplastycznego.
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Dynamic model of nuclear power plant turbine
PublicationThe paper presents the dynamic multivariable model of Nuclear Power Plant steam turbine. Nature of the processes occurring in a steam turbine causes a task of modeling it very difficult, especially when this model is intended to be used for on-line optimal process control (model based) over wide range of operating conditions caused by changing power demand. Particular property of developed model is that it enables calculations...
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Experimental investigations and prediction of WEDMed surface of nitinol SMA using SinGAN and DenseNet deep learning model
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Deep slot effect in the squirrel-cage induction motors with scalar (V/F) control
PublicationQualitative characteristics of the electrical drive considerably depend on identification accuracy of math model parameters. In particular, it is depend on detection accuracy of stator active resistance r1 that is used in calculation of flux linkages, rotary speed in sensorless control systems. Paper provides analysis of influence of stator deep slot effect to stator active resistance value
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Modeling nitrous oxide production by a denitrifying-enhancedbiologically phosphorus removing (EBPR) activated sludge in thepresence of different carbon sources and electron acceptors
PublicationIn this study, the IWA Activated Sludge Model No. 2d (ASM2d) was expanded to identify the most important mechanisms leading to the anoxic nitrous oxide (N2O) production in the combined nitrogen (N) and phosphorus (P) removal activated sludge systems. The new model adopted a three-stage denitrification concept and was evaluated against the measured data from one/two-phase batch experiments carried out with activated sludge withdrawn...
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Team Roles and Team Performance in Small Virtual Software Teams
PublicationThe article presents the results of research on the composition of team roles conducted in 24 student software teams. An adaptation of M. Belbin’s model by B. Kożusznik was used. The model of team balance according to Belbin and Haaf is presented and correlations between team balance and team performance are analysed. Team performance is measured at three levels: result, satisfaction and team climate. The selected constellation...
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How to model ROC curves - a credit scoring perspective
PublicationROC curves, which derive from signal detection theory, are widely used to assess binary classifiers in various domains. The AUROC (area under the ROC curve) ratio or its transformations (the Gini coefficient) belong to the most widely used synthetic measures of the separation power of classification models, such as medical diagnostic tests or credit scoring. Frequently a need arises to model an ROC curve. In the biostatistical...
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Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks
PublicationThe increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated...
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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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A unified coarse-grained model of biological macromolecules based on mean-field multipole–multipole interactions
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Koncepcja i modelowanie wysokoobrotowego napędu elektrycznego turbosprężarki. Zastosowanie w ogniwach paliwowych pojazdów samochodowych
PublicationAbstract: Electrical vehicles powered by hydrogen fuel cells become a potential alternative to conventional vehicles. The polymer electrolyte membrane (PEM) are typical fuel cells used in fuel cell vehicle (FCV). The global efficiency of a PEM fuel cell stack is greatly impacted by the use of a motorized compressor for the air supply system. The motor-compressor set-up may consume up to 19 % of the energy supplied by the PEM fuel...
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Performance of Noise Map Service Working in Cloud Computing Environment
PublicationIn the paper a noise map service designated for the user interested in environmental noise subject is presented. It is based on cloud computing. Noise prediction algorithm and source model, developed for creating acoustic maps, are working in cloud computing environment. In the study issues related to noise modeling of sound propagation in urban spaces are discussed with a special focus on road noise. Examples of results obtained...
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Efficient knowledge-based optimization of expensive computational models using adaptive response correction
PublicationComputer simulation has become an indispensable tool in engineering design as they allow an accurate evaluation of the system performance. This is critical in order to carry out the design process in a reliable manner without costly prototyping and physical measurements. However, high-fidelity computer simulations are computationally expensive. This turns to be a fundamental bottleneck when it comes to design automation using numerical...
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Modelowanie i symulacja zaburzeń przewodzonych z zastosowaniem programów Saber i TCad = Modeling and simulation of conducted emissions with TCad and Saber programs
PublicationPrzedstawiono symulacyjne badania porównawcze w zakresie kompatybilności elektromagnetycznej EMC modelu obwodowego przetwornicy DC-DC podwyższającej napięcie. Wskazano na specyfikę modelowania wynikającą z potrzeby przewidywania propagacji zaburzeń przewodzonych EMI w szerokim zakresie częstotliwości. Wyznaczono model układu dla symulatora Saber i porównano pomiary charakterystyki widma EMI z wynikami otrzymanymi z symulacji. Zbadano...
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Tool Wear Monitoring Using Improved Dragonfly Optimization Algorithm and Deep Belief Network
PublicationIn recent decades, tool wear monitoring has played a crucial role in the improvement of industrial production quality and efficiency. In the machining process, it is important to predict both tool cost and life, and to reduce the equipment downtime. The conventional methods need enormous quantities of human resources and expert skills to achieve precise tool wear information. To automatically identify the tool wear types, deep...
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Hydrophobic deep eutectic solvents in microextraction techniques–A review
PublicationOver the past decade, deep eutectic solvents (DES) have been widely studied and applied in sample preparation techniques. Until recently, most of the synthesized DES were hydrophilic, which prevented their use in the extraction of aqueous samples. However, after 2015 studies on the synthesis and application of hydrophobic deep eutectic solvents (HDES) has rapidly expanded. Due to unique properties of HDES i.e. density, viscosity,...
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New light on the photocatalytic performance of NH4V4O10 and its composite with rGO
PublicationSolar-driven photocatalysis has shown great potential as a sustainable wastewater treatment technology that utilizes clean solar energy for pollutant degradation. Consequently, much attention is being paid to the development of new, efficient and low-cost photocatalyst materials. In this study, we report the photocatalytic activity of NH4V4O10 (NVO) and its composite with rGO (NVO/rGO). Samples were synthesized via a facile one-pot...
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Highly Oriented Zirconium Nitride and Oxynitride Coatings Deposited via High‐Power Impulse Magnetron Sputtering: Crystal‐Facet‐Driven Corrosion Behavior in Domestic Wastewater
PublicationHerein, highly crystalline ZrxNy and ZrxNyOz coatings are achieved by the deposition via high‐power impulse magnetron sputtering. Various N2 and N2/O2 gas mixtures with argon are investigated. The chemical composition and, as a result, mechanical properties of the deposited layer can be tailored along with morphological and crystallographic structural changes. The corrosion resistance behavior is studied by potentiodynamic measurements...
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Effect of Pin Shape on Thermal History of Aluminum-Steel Friction Stir Welded Joint: Computational Fluid Dynamic Modeling and Validation
PublicationThis article studied the effects of pin angle on heat generation and temperature distribution during friction stir welding (FSW) of AA1100 aluminum alloy and St-14 low carbon steel. A validated computational fluid dynamics (CFD) model was implemented to simulate the FSW process. Scanning electron microscopy (SEM) was employed in order to investigate internal materials’ flow. Simulation results revealed that the mechanical work...
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Explainable AI for Inspecting Adversarial Attacks on Deep Neural Networks
PublicationDeep Neural Networks (DNN) are state of the art algorithms for image classification. Although significant achievements and perspectives, deep neural networks and accompanying learning algorithms have some important challenges to tackle. However, it appears that it is relatively easy to attack and fool with well-designed input samples called adversarial examples. Adversarial perturba-tions are unnoticeable for humans. Such attacks...
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Toward a hybrid model of ship performance in ice suitable for route planning purpose
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A model for performance assessment of damaged ships when usig the risk-based method
PublicationArtykuł prezentuje elementy badań związanych z rozwojem metody i modelu do oceny bezpieczeństwa statków i obiektów oceanotechnicznych w stanie uszkodzonym. Przedsawiono podejście do oceny bezpieczeństwa statków i obiektów oceanotechnicznych,składające się z dwóch części: oceny zachowania się obiektów oraz oceny ryzyka. Głównym problemem zaprezentowanym w arytkule jest ocena ocena zachowania się statków i obiektów oceanotechnicznych...
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Influence of external climate on natural ventilation performance in buildings
PublicationNatural ventilation is driven by either buoyancy forces or wind pressure forces or their combinations that inherit stochastic variation into ventilation rates [ CITATION Hun99 \l 1045 ]. We now that these factors have influence on air flow speed and thermal comfort inside building. This work examines the relationship between external climate and natural ventilation including thermal comfort. The work tries in the first instance...
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A Model of Thermal Energy Storage According to the Convention of Bond Graphs (BG) and State Equations (SE)
PublicationThe main advantage of the use of the Bond Graphs method and State Equations for modeling energy systems with a complex structure (marine power plants, hybrid vehicles, etc.) is the ability to model the system components of different physical nature using identical theoretical basis. The paper presents a method of modeling thermal energy storage, which is in line with basic BG theory. Critical comments have been put forward concerning...
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Ionic Liquids and Deep Eutectic Mixtures: Sustainable Solvents for Extraction Processes
PublicationIn recent years, ionic liquids and deep eutectic mixtures have demonstrated great potential in extraction processes relevant to several scientific and technological activities. This review focuses on the applicability of these sustainable solvents in a variety of extraction techniques, including but not limited to liquid- and solid-phase (micro) extraction, microwave-assisted extraction, ultrasound-assisted extraction and pressurized...
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Behawioralne modelowanie i symulacja tranzystorów IGBT w układach energoelektronicznych = Behavioural modeling and simulation of IGBT transistors in power electronics systems
PublicationW referacie przedstawiono rezultaty prac nad modelem tranzystora bipolarnego z izolowaną bramką (IGBT), przydatnym w symulacjach układów energoelektronicznych wymagających odwzorowania zarówno stanów ustalonych jak i dynamicznych przy przełączaniu. Rozważono behawioralny model IGBT o reprezentacji za pomocą równań stanu przy wykorzystaniu katalogowych charakterystyk statycznych oraz nieliniowych aproksymacji pojemności pasożytniczych....
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Application of Feed Forward Neural Networks for Modeling of Heat Transfer Coefficient During Flow Condensation for Low and High Values of Saturation Temperatur
PublicationMost of the literature models for condensation heat transfer prediction are based on specific experimental parameters and are not general in nature for applications to fluids and non-experimental thermodynamic conditions. Nearly all correlations are created to predict data in normal HVAC conditions below 40°C. High temperature heat pumps operate at much higher parameters. This paper aims to create a general model for the calculation...
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Discrete-Element bonded-particle Sea Ice model DESIgn, version 1.3a – model description and implementation
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Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning
PublicationFollowing the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides...
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A simplified behavioral MOSFET model based on parameters extraction for circuit simulations.
PublicationThe paper presents results on behavior modeling of general purpose Metal-Oxide Semiconductor Field-Effect Transistor (MOSFET) for simulation of power electronics systems requiring accuracy both in steady-state and in switching conditions. Methods of parameters extraction including nonlinearity of parasitic capacitances and steady-state characteristics are based on manufacturer data sheet and externally measurable characteristics....
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Model-free and Model-based Reinforcement Learning, the Intersection of Learning and Planning
PublicationMy doctoral dissertation is intended as the compound of four publications considering: structure and randomness in planning and reinforcement learning, continuous control with ensemble deep deterministic policy gradients, toddler-inspired active representation learning, and large-scale deep reinforcement learning costs.
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Modeling of heat and fluid flow in granular layers using high-order compact schemes and volume penalization method
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