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MnxCo3-xO4 spinel oxides as efficient oxygen evolution reaction catalysts in alkaline media
PublicationThe design of efficient electrocatalysts for oxygen evolution reaction (OER) is an essential task in developing sustainable water splitting technology for the production of hydrogen. In this work, manganese cobalt spinel oxides with a general formula of MnxCo3-xO4 (x=0, 0.5, 1, 1.5, 2) were synthesised via a soft chemistry method. Non-equilibrium mixed powder compositions were produced, resulting in high electrocatalytic activity....
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Expedited Gradient-Based Design Closure of Antennas Using Variable-Resolution Simulations and Sparse Sensitivity Updates
PublicationNumerical optimization has been playing an increasingly important role in the design of contemporary antenna systems. Due to the shortage of design-ready theoretical models, optimization is mainly based on electromagnetic (EM) analysis, which tends to be costly. Numerous techniques have evolved to abate this cost, including surrogate-assisted frameworks for global optimization, or sparse sensitivity updates for speeding up local...
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A general isogeometric finite element formulation for rotation‐free shells with in‐plane bending of embedded fibers
PublicationThis article presents a general, nonlinear isogeometric finite element formulation for rotation-free shells with embedded fibers that captures anisotropy in stretching, shearing, twisting, and bending - both in-plane and out-of-plane. These capabilities allow for the simulation of large sheets of heterogeneous and fibrous materials either with or without matrix, such as textiles, composites, and pantographic structures. The work...
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Limitation of Floating-Point Precision for Resource Constrained Neural Network Training
PublicationInsufficient availability of computational power and runtime memory is a major concern when it comes to experiments in the field of artificial intelligence. One of the promising solutions for this problem is an optimization of internal neural network’s calculations and its parameters’ representation. This work focuses on the mentioned issue by the application of neural network training with limited precision. Based on this research,...
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Rapid Surrogate-Aided Multi-Criterial Optimization of Compact Microwave Passives Employing Machine Learning and ANNs
PublicationThis article introduces an innovative method for achieving low-cost and reliable multi-objective optimization (MO) of microwave passive circuits. The technique capitalizes on the attributes of surrogate models, specifically artificial neural networks (ANNs), and multi-resolution electromagnetic (EM) analysis. We integrate the search process into a machine learning (ML) framework, where each iteration produces multiple infill points...
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Acceleration of Electromagnetic Simulations on Reconfigurable FPGA Card
PublicationIn this contribution, the hardware acceleration of electromagnetic simulations on the reconfigurable field-programmable-gate-array (FPGA) card is presented. In the developed implementation of scientific computations, the matrix-assembly phase of the method of moments (MoM) is accelerated on the Xilinx Alveo U200 card. The computational method involves discretization of the frequency-domain mixed potential integral equation using...
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ESTIMATING AVERSION TO RANK INEQUALITY UNDERLYING SELECTED ITALIAN INDICES OF INCOME INEQUALITY
PublicationIn this paper, we estimate aversion to rank inequality (ATRI) underlying selected Italian income inequality indices, I, notably the Pietra index, the Bonferroni index and the “new” Zenga index. We measure ATRI by the parameter v of the generalised Gini index G(v). ATRI is distinct from aversion to income inequality, as measured by parameter ε of Atkinson’s index A(ε). We propose eliciting v from the equation I = GE(v). As, in general,...
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Day-ahead Solar Power Forecasting Using LightGBM and Self-Attention Based Encoder-Decoder Networks
PublicationThe burgeoning trend of integrating renewable energy harvesters into the grid introduces critical issues for its reliability and stability. These issues arise from the stochastic and intermittent nature of renewable energy sources. Data-driven forecasting tools are indispensable in mitigating these challenges with their rugged performance. However, tools relying solely on data-driven methods often underperform when an adequate...
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Tworzenie miejskości po 1990r., Geneza niemieckiej urbanistyki współczesnych założeń mieszkaniowych
PublicationArtykuł jest przyczyną do przypomnienia genezy współczesnej formy niemieckich miejskich struktur mieszkaniowych w kontekście zmian rozumienia ich wymiaru miejskości. Niemiecka myśl urbanistyczna łączy w sobie dwie wyraziste tradycje dwudziestego wieku - Gründerzeit i KlassischeModerne. Pozostaje jednak silnie otwarta na innowację generowaną nie tylko dzięki postępowi technicznemu, ale przede wszystkim poprzez planowanie interdyscyplinarne...
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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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Modelling of FloodWave Propagation with Wet-dry Front by One-dimensional Diffusive Wave Equation
PublicationA full dynamic model in the form of the shallow water equations (SWE) is often useful for reproducing the unsteady flow in open channels, as well as over a floodplain. However, most of the numerical algorithms applied to the solution of the SWE fail when flood wave propagation over an initially dry area is simulated. The main problems are related to the very small or negative values of water depths occurring in the vicinity of...
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Particle shape dependence in 2D granular media
PublicationParticle shape is a key to the space-filling and strength properties of granular matter. We consider a shape parameter eta describing the degree of distortion from a perfectly spherical shape. Encompassing most specific shape characteristics such as elongation, angularity and non-convexity, eta is a low-order but generic parameter that we used in a numerical benchmark test for a systematic investigation of shape dependence in sheared...
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Power System Dynamics. Stability and Control. 3rd edition
PublicationComprehensive, state-of-the-art review of information on the electric power system dynamics and stability. It places the emphasis first on understanding the underlying physical principles before proceeding to more complex models and algorithms. The book explores the influence of classical sources of energy, wind farms and virtual power plants, power plants inertia and control strategy on power system stability. The book cover...
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Expedited optimization of antenna input characteristics with adaptive Broyden updates
PublicationSimulation-driven adjustment of geometry and/or material parameters is a necessary step in the design of contemporary antenna structures. Due to their topological complexity, other means, such as supervised parameter sweeping, does not usually lead to satisfactory results. On the other hand, rigorous numerical optimization is computationally expensive due to a high cost of underlying full-wave electromagnetic (EM) analyses, otherwise...
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A new anisotropic bending model for nonlinear shells: Comparison with existing models and isogeometric finite element implementation
PublicationA new nonlinear hyperelastic bending model for shells formulated directly in surface form is presented, and compared to four existing prominent bending models. Through an essential set of elementary nonlinear bending test cases, the membrane and bending stresses of each model are examined analytically. Only the proposed bending model passes all the test cases, while the other bending models either fail or only pass the test cases for...
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W-dominance: Tradeoff-inspired dominance relation for preference-based evolutionary multi-objective optimization
PublicationThe paper presents a method of incorporating decision maker preferences into multi-objective meta-heuristics. It is based on tradeoffcoefficients and extends their applicability from bi-objective to multi-objective. The method assumes that a decision maker specifies a priori each objective’s importance as a weight interval. Based on this, w-dominance relation is introduced, which extends Pareto dominance. By replacing reference...
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A new multi-process collaborative architecture for time series classification
PublicationTime series classification (TSC) is the problem of categorizing time series data by using machine learning techniques. Its applications vary from cybersecurity and health care to remote sensing and human activity recognition. In this paper, we propose a novel multi-process collaborative architecture for TSC. The propositioned method amalgamates multi-head convolutional neural networks and capsule mechanism. In addition to the discovery...
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From Darcy to Turbulent Flow: Investigating Flow Characteristics and Regime Transitions in Porous Media
PublicationThis research addresses the flow characteristics within a porous medium composed of a monolayer of closely packed spheres, spanning from viscous-dominated to turbulent flow regimes. In the first part of this paper, the turbulent flow characteristics at a 30 MPa pressure drop within the domain are presented. The results are averaged across different cross-sections between the inlet and outlet. In the second part of the study, simulations...
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How can HSR promote inter-city collaborative innovation across regional borders?
PublicationMany studies have shown that high-speed rail (HSR) can reshape the spatial pattern of economic geography. However, there needs to be more logical argumentation and rigorous empirical design on the paths and mechanisms involved. This paper considers the impact of the border effect on HSR links and innovation clusters from the perspective of inter-regional collaborative innovation. It provides a logical and compact theoretical...
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Reliable Microwave Modeling By Means of Variable-Fidelity Response Features
PublicationIn this work, methodologies for low-cost and reliable microwave modeling are presented using variable-fidelity response features. The two key components of our approach are: (i) a realization of the modeling process at the level of suitably selected feature points of the responses (e.g., S-parameters vs. frequency) of the structure at hand, and (ii) the exploitation of variable-fidelity EM simulation data, also for the response...
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Deep eutectic solvents – Ideal solution for clean air or hidden danger?
PublicationThe industrial sector is one of the fastest-growing sources of greenhouse gases, due to its excessive energy consumption to meet the rapidly growing demand for energy-intensive products. The use of deep eutectic solvents (DESs) has been studied extensively in order to cope with these harmful gases, but their usage can be an issue in respect to ecological reasons. Do deep eutectic solvents harm the atmosphere? Yes, these solvents...
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Analiza skuteczności wybranych strategii kontrariańskich na warszawskiej GPW w latach 2014–2018
PublicationCapital multiplication is the main goal of investors and for many years they have been looking for methods and strategies that would enable them to achieve it to the greatest possible extent. Due to the fact that the expectations and characteristics of investors, including those concerning the investment period, are diverse, multiple strategies have emerged. One of such strategies, mainly long-term in nature, is the so-called...
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Computationally-efficient design optimisation of antennas by accelerated gradient search with sensitivity and design change monitoring
PublicationElectromagnetic (EM) simulation tools are of primary importance in the design of contemporary antennas. The necessity of accurate performance evaluation of complex structures is a reason why the final tuning of antenna dimensions, aimed at improvement of electrical and field characteristics, needs to be based on EM analysis. Design automation is highly desirable and can be achieved by coupling EM solvers with numerical optimisation...
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Client-side versus server-side geographic data processing performance comparison: Data and code
PublicationThe data and code presented in this article are related to the research article entitled “Analysis of Server-side and Client-side Web-GIS data processing methods on the example of JTS and JSTS using open data from OSM and Geoportal” (Kulawiak et al., 2019). The provided 12 datasets include multi-point and multi-polygon data of different scales and volumes, representing real-world geographic features. The datasets cover the area...
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Seismic damage diagnosis in adjacent steel and RC MRFs considering pounding effects through improved wavelet-based damage-sensitive feature
PublicationThis paper aims to propose complex Morlet (cmorfb-fc) wavelet-based refined damage-sensitive feature (rDSF) as a new and more precise damage indicator to diagnose seismic damages in adjacent steel and Reinforced Concrete (RC) Moment Resisting Frames (MRFs) assuming pounding conditions using acceleration responses. The considered structures include 6- and 9-story steel and 4- and 8-story RC benchmark MRFs that are assumed to have...
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Creating new voices using normalizing flows
PublicationCreating realistic and natural-sounding synthetic speech remains a big challenge for voice identities unseen during training. As there is growing interest in synthesizing voices of new speakers, here we investigate the ability of normalizing flows in text-to-speech (TTS) and voice conversion (VC) modes to extrapolate from speakers observed during training to create unseen speaker identities. Firstly, we create an approach for TTS...
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Trust and Distrust in e-Democracy
PublicationIn the digital government research literature, the concept of trust is typically used as a precondition for the adoption of digital technology in the public sector or an outcome of a roadmap leading up to such adoption. The concept plays a central role in many decisions linked to the planning, adoption and management of the public sector technology. In contrast, the concept of distrust is almost neglected in such literature but,...
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Fast EM-Driven Parameter Tuning of Microwave Circuits with Sparse Sensitivity Updates via Principal Directions
PublicationNumerical optimization has become more important than ever in the design of microwave components and systems, primarily as a consequence of increasing performance demands and growing complexity of the circuits. As the parameter tuning is more and more often executed using full-wave electromagnetic (EM) models, the CPU cost of the overall process tends to be excessive even for local optimization. Some ways of alleviating these issues...
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A Surrogate-Assisted Measurement Correction Method for Accurate and Low-Cost Monitoring of Particulate Matter Pollutants
PublicationAir pollution involves multiple health and economic challenges. Its accurate and low-cost monitoring is important for developing services dedicated to reduce the exposure of living beings to the pollution. Particulate matter (PM) measurement sensors belong to the key components that support operation of these systems. In this work, a modular, mobile Internet of Things sensor for PM measurements has been proposed. Due to a limited...
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Three dimensional simulations of FRC beams and panels with explicit definition of fibres-concrete interaction
PublicationHigh performance concrete (HPC) is a quite novel material which has been rapidly developed in the last few decades. It exhibits superior mechanical properties and durability comparing to normal concrete. HPC can achieve also superior tensile performance if strong fibres (steel or carbon) are implemented in the matrix. Thus, there exist the unabated interest in studying how the addition of different types of fibres modifies the...
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublicationDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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USING ARTIFICIAL NEURAL NETWORKS FOR PREDICTING SHIP FUEL CONSUMPTION
PublicationIn marine vessel operations, fuel costs are major operating costs which affect the overall profitability of the maritime transport industry. The effective enhancement of using ship fuel will increase ship operation efficiency. Since ship fuel consumption depends on different factors, such as weather, cruising condition, cargo load, and engine condition, it is difficult to assess the fuel consumption pattern for various types...
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Nieliniowa statyka 6-parametrowych powłok sprężysto plastycznych. Efektywne obliczenia MES
PublicationGłównym zagadnieniem omawianym w monografii jest sformułowanie sprężysto-plastycznego prawa konstytutywnego w nieliniowej 6-parametrowej teorii powłok. Wyróżnikiem tej teorii jest występujący w niej w naturalny sposób tzw. stopień 6 swobody, czyli owinięcie (drilling rotation). Podstawowe założenie pracy to przyjęcie płaskiego stanu naprężenia uogólnionego na ośrodek typu Cosseratów. Takie podejście stanowi oryginalny aspekt opracowania....
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Trust and Distrust in e-Democracy
PublicationIn the digital government research literature, the concept of trust is typically used as a precondition for the adoption of digital technology in the public sector or an outcome of a roadmap leading up to such adoption. The concept plays a central role in many decisions linked to the planning, adoption and management of the public sector technology. In contrast, the concept of...
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Relationship between wages, labour productivity and unemployment rate in new EU member countries
PublicationThe main aim of this article is to find out the extent to which relative labour productivity and relative unemployment rate changes determine relative wage changes. We use average annual macro-data for the period 2002-2013 for Poland and other 5 new EU members: Estonia, Hungary, Slovak, Czech Republic and Slovenia. Using Poland as benchmark, rst we examine the correlation between wage, productivity and unemployment rate changes...
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublicationIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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Improving Accuracy of Contactless Respiratory Rate Estimation by Enhancing Thermal Sequences with Deep Neural Networks
PublicationEstimation of vital signs using image processing techniques have already been proved to have a potential for supporting remote medical diagnostics and replacing traditional measurements that usually require special hardware and electrodes placed on a body. In this paper, we further extend studies on contactless Respiratory Rate (RR) estimation from extremely low resolution thermal imagery by enhancing acquired sequences using Deep...
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Identification of Parameters Influencing the Accuracy of the Solution of the Nonlinear Muskingum Equation
PublicationTwo nonlinear versions of the Muskingum equation are considered. The difference between both equations relates to the exponent parameter. In the first version, commonly used in hydrology, this parameter is considered as free, while in the second version, it takes a value resulting from the kinematic wave theory. Consequently, the first version of the equation is dimensionally inconsistent, whereas the proposed second one is consistent. It...
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Reduced-cost electromagnetic-driven optimisation of antenna structures by means of trust-region gradient-search with sparse Jacobian updates
PublicationNumerical optimisation plays more and more important role in the antenna design. Because of lack of design-ready theoretical models, electromagnetic (EM)-simulation-driven adjustment of geometry parameters is a necessary step of the design process. At the same time, traditional parameter sweeping cannot handle complex topologies and large number of design variables. On the other hand, high computational cost of the conventional...
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Filter-Hilbert Method for Automatic Correction of Non-Anechoic Antenna Measurements with Embedded Self-Calibration Mechanism
PublicationOne of the most important steps in the process of antenna development involves measurements of its prototype. Far-field performance of radiators is normally characterized in strictly controlled environments such as anechoic chambers which can ensure certification-grade accuracy. Unfortunately, they are also characterized by high construction costs which might not be justified for low-budget research and/or teaching-related activities....
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Reduction of exceeding the guaranteed service time for external trucks at the DCT Gdańsk container terminal using a six sigma framework
PublicationPurpose The purpose of this research was to investigate ways to reduce the average amount of exceeded guaranteed service time for external trucks at Deepwater Container Terminal Gdańsk Sp z o.o. (DCT Gdańsk) via dosing the gate activities, in particular IN-Gate entry process of trucks carrying import/export/transit containers. Design/methodology/approach A Six Sigma methodology with the DMAIC methods along with the SIPOC chart,...
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Neural Architecture Search for Skin Lesion Classification
PublicationDeep neural networks have achieved great success in many domains. However, successful deployment of such systems is determined by proper manual selection of the neural architecture. This is a tedious and time-consuming process that requires expert knowledge. Different tasks need very different architectures to obtain satisfactory results. The group of methods called the neural architecture search (NAS) helps to find effective architecture...
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Deep learning-based waste detection in natural and urban environments
PublicationWaste pollution is one of the most significant environmental issues in the modern world. The importance of recycling is well known, both for economic and ecological reasons, and the industry demands high efficiency. Current studies towards automatic waste detection are hardly comparable due to the lack of benchmarks and widely accepted standards regarding the used metrics and data. Those problems are addressed in this article by...
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Reliable computationally-efficient behavioral modeling of microwave passives using deep learning surrogates in confined domains
PublicationThe importance of surrogate modeling techniques has been steadily growing over the recent years in high-frequency electronics, including microwave engineering. Fast metamodels are employed to speedup design processes, especially those conducted at the level of full-wave electromagnetic (EM) simulations. The surrogates enable massive system evaluations at nearly EM accuracy and negligible costs, which is invaluable in parameter...
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Fully Automated AI-powered Contactless Cough Detection based on Pixel Value Dynamics Occurring within Facial Regions
PublicationIncreased interest in non-contact evaluation of the health state has led to higher expectations for delivering automated and reliable solutions that can be conveniently used during daily activities. Although some solutions for cough detection exist, they suffer from a series of limitations. Some of them rely on gesture or body pose recognition, which might not be possible in cases of occlusions, closer camera distances or impediments...
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Non-ergodic fragmentation upon collision-induced activation of cysteine–water cluster cations
PublicationCysteine–water cluster cations Cys(H2O)3,6 + and Cys(H2O)3,6H+ are assembled in He droplets and probed by tandem mass spectrometry with collision-induced activation. Benchmark experimental data for this biologically important system are complemented with theory to elucidate the details of the collisioninduced activation process. Experimental energy thresholds for successive release of water are compared to water dissociation energies...
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Optimizing Control of Wastewater Treatment Plant With Reinforcement Learning: Technical Evaluation of Twin-Delayed Deep Deterministic Policy Gradient Agent
PublicationControl of the wastewater treatment processes presents significant challenges due to the fluctuating nature of inflow and wastewater composition, alongside the system’s non-linear dynamics. Traditional control methods struggle to adapt to these variations, leading to an economically suboptimal operation of the process and a violation of norms imposed on the quality of wastewater discharged to the catchment area. This study proposes...
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Evaluation of ChatGPT Applicability to Learning Quantum Physics
PublicationChatGPT is an application that uses a large language model. Its purpose is to generate answers to various questions as well as provide information, help solve problems and participate in conversations on a wide range of topics. This application is also widely used by students for the purposes of learning or cheating (e.g., writing essays or programming codes). Therefore, in this contribution, we evaluate the ability of ChatGPT...
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Real-time simulation in non real-time environment
PublicationSimulation in real-time is a very useful tool because of didactical and practical benefits. Very important benefit of real-time simulation is a fact that operator’s decision can be taken into account in the same time scale as the real system would work. This enables construction of simulators, and opportunity to test control algorithms in Hardware in The Loop scheme using target industrial equipment. Professional real-time environments...
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A Low-Cost System for Far-Field Non-Anechoic Measurements of Antenna Performance Figures
PublicationPrototype measurements are the key step in the development of antenna structures. Typically, their far-field characteristics are validated in expensive, dedicated facilities such as open range sites, or anechoic chambers. Despite being necessary for obtaining high-precision data (e.g., for device qualification), the use of costly infrastructure might not be fully justified when the main goal of measurements includes demonstration...