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Catalog Publications
Year 2023
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Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning
PublicationIn this paper, the data, information, knowledge, and wisdom (DIKW) pyramid is revisited in the context of deep learning applied to machine learningbased audio signal processing. A discussion on the DIKW schema is carried out, resulting in a proposal that may supplement the original concept. Parallels between DIWK pertaining to audio processing are presented based on examples of the case studies performed by the author and her collaborators....
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DATA INTEROPERABILITY AND THE OPEN DATA ECOSYSTEM: ROLES AND RESEARCH AREAS
PublicationSustainability and value-creation are considered important parameters to measure the success of an open data system. Unfortunately, existing open data systems are not meeting their promises to achieve a sustainable and value-based open data system. Van Loenen et al. (2021) proposed a sustainable and value-creating open data ecosystem. According to their study, the open data ecosystem needs to be user-driven, inclusive, circular,...
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Data-driven, probabilistic model for attainable speed for ships approaching Gdańsk harbour
PublicationThe growing demand for maritime transportation leads to increased traffic in ports. From this arises the need to observe the consequences of the specific speed ships reach when approaching seaports. However, usually the analyzed cases refer only to the statistical evaluation of the studied phenomenon or to the empirical modelling, ignoring the mutual influence of variables such as ship type, length or weather conditions. In this...
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Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublicationIn this work, a computationally efficient method based on data driven surrogate models is pro-posed for the design optimization procedure of a Frequency Selective Surface (FSS)-based filtering antenna (Filtenna). A Filtenna acts as a as module that simultaneously pre-filters unwanted sig-nals, and enhances the desired signals at the operating frequency. However, due to a typically large number of design variables of FSS unit elements,...
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Dataset Related Experimental Investigation of Chess Position Evaluation Using a Deep Neural Network
PublicationThe idea of training Articial Neural Networks to evaluate chess positions has been widely explored in the last ten years. In this paper we investigated dataset impact on chess position evaluation. We created two datasets with over 1.6 million unique chess positions each. In one of those we also included randomly generated positions resulting from consideration of potentially unpredictable chess moves. Each position was evaluated...
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Debonding of coin-shaped osseointegrated implants: Coupling of experimental and numerical approaches
PublicationWhile cementless implants are now widely used clinically, implant debonding still occur and is difficult to anticipate. Assessing the biomechanical strength of the bone–implant interface can help improving the understanding of osseointegration phenomena and thus preventing surgical failures. A dedicated and standardized implant model was considered. The samples were tested using a mode III cleavage device to assess the mechanical...
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Decomposition of the induced magnetism degaussing problem for fast determination of currents in demagnetization coils wrapped outside an object under arbitrary external field conditions
PublicationSafe passage of ships in the presence of sea mines can be ensured by limiting or reducing the ship’s magnetic footprint. For vessels with plastic hulls, the main component that requires magnetic damping is the engine. Demagnetization of such an object can be achieved by wrapping it with coils and setting the direct current appropriately. For each specific geographic location, the currents in the coils can be determined iteratively...
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Deep Eutectic Solvent Stir Bar Sorptive Extraction: A Rapid Microextraction Technique for the Determination of Vitamin D3 by Spectrophotometry
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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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Deep eutectic solvents in analytical sample preconcentration Part B: Solid-phase (micro)extraction
PublicationOne of the key challenges of modern analytical chemistry is the monitoring of trace amounts of contaminants using sensitive and selective instrumental techniques. Due to the variety and complexity of some samples, it is often necessary to properly prepare a sample and to perform a preconcentration of trace amounts of analytes. In line with the principles of Green Analytical Chemistry (GAC), it is important for an analytical procedure...
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Deep Eutectic Solvents: Properties and Applications in CO2 Separation
PublicationNowadays, many researchers are focused on finding a solution to the problem of global warming. Carbon dioxide is considered to be responsible for the “greenhouse” effect. The largest global emission of industrial CO2 comes from fossil fuel combustion, which makes power plants the perfect point source targets for immediate CO2 emission reductions. A state-of-the-art method for capturing carbon dioxide is chemical absorption using...
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Deep learning approach for delamination identification using animation of Lamb waves
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Deep learning super-resolution for the reconstruction of full wavefield of Lamb waves
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Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublicationAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
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Deformation of an elastic second gradient spherical body under equatorial line density of dead forces
PublicationWe consider deformations of an elastic body having initially a spherical shape. Assumed deformation energy depends on the first and second gradient of displacements. We apply an equatorial line density of dead loads, that are forces per unit line length directed in radial direction and applied along the equator of the sphere. We restrict ourselves our analysis to the case of linearized second strain gradient isotropic elasticity...
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Degradation of bisphenol S – a contaminant of emerging concern - by synergistic ozone and percarbonate based AOP
PublicationDegradation of bisphenol S was studied using ozone activated by sodium percarbonate and the effectiveness of optimized process was compared with the peroxone process. The influence of several factors including sodium percarbonate concentration, ozone dose, pH, and water matrix were investigated. A synergetic coefficient of 3.84 was achieved for the combination of sodium percarbonate and ozone, confirming the effectiveness of this...
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Degradation of cefadroxil drug by newly designed solar light responsive alcoholic template-based lanthanum ferrite nanoparticles
PublicationIn this work, lanthanum ferrite nanoparticles were synthesized via a simple co-precipitation method. Two different templates, namely sorbitol and mannitol, were used in this synthesis to tune the optical, structural, morphological, and photocatalytic properties of lanthanum ferrite. The synthesized lanthanum ferrite-sorbitol (LFOCo-So) and lanthanum ferrite-mannitol (LFOCo-Mo) were investigated through Ultraviolet–Visible (UV–Vis),...
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Degradation of Rhodamine dyes by Advanced Oxidation Processes (AOPs) – Focus on cavitation and photocatalysis - A critical review
PublicationThis review evaluates selected advanced oxidation processes (AOPs) - cavitation and photocatalysis - successfully used for wastewater treatment towards degradation of Rhodamine (Rh) dyes. Reactor configuration and impact of process parameters and oxidants addition (hydrogen peroxide, ozone, persulfates) on degradation effectiveness along with degradation mechanisms are discussed. Best technologies provide 100% degradation within...
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Dehydrogenation in electron-induced dissociative ionization of pyridine molecule
PublicationThe electron-impact dissociative ionization of pyridine has been investigated using mass spectrometry. Thirty-two well-resolved mass peaks have been identified in the cation mass spectra and assigned to the most likely ionic molecular fragments. The new sixteen ionic fragments' appearance energies have been determined, and sixteen others remeasured. The total cross-section for electron-impact ionization of pyridine has been measured...
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Dekodowanie kodów iterowanych z użyciem sieci neuronowej
PublicationNadmiarowe kody iterowane są jedną z prostych metod pozyskiwania długich kodów korekcyjnych zapewniających dużą ochronę przed błędami. Jednocześnie, chociaż ich podstawowy iteracyjny dekoder jest prosty koncepcyjnie oraz łatwy w implementacji, to nie jest on rozwiązaniem optymalnym. Poszukując alternatywnych rozwiązań zaproponowano, przedstawioną w pracy, strukturę dekodera tego typu kodów wspomaganą przez sieci neuronowe. Zaproponowane...