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Search results for: learning about natural phenomena
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A framework to analyse the probability of accidental hull girder failure considering advanced corrosion degradation for risk-based ship design
PublicationShip’s hull girder failure could result from maritime accident that can cause human life loss, environmental disaster, and major economic impacts. In risk-based ship design paradigm, accounting for rare phenomena (e.g. ship-ship collision or grounding) is important to provide safe and durable structure. In-service corrosion-induced hull degradation should be considered at the design stage, as it can significantly affect structural...
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Relationship between Chemical Structure and Biological Activity Evaluated In Vitro for Six Anthocyanidins Most Commonly Occurring in Edible Plants
PublicationNumerous studies have provided evidence that diets rich in anthocyanins show a broad spectrum of health benefits. Anthocyanins in nature are usually found in the form of glycosides. Their aglycone forms are called anthocyanidins. The chemical structure of anthocyanins is based on the flavylium cation, but they differ in the position and number of substituents. However, the bioactives and foods that contain them are frequently treated...
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Electro-optical transducer based on indium-tin-oxide-coated optical fiber for analysis of ionized media
PublicationThe paper introduces a concept of an optical fiber based electro-optical transducer for monitoring of ionized media, such as low-temperature plasma. It utilizes optical fiber with a section of a core coated with tailored indium tin oxide (ITO) thin film and thus combines the optical phenomena of lossy-mode resonance (LMR) with the electrostatic probe. ITO is an optically transparent and electrically conductive material and if its...
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Simplified Numerical Model for Transient Flow of Slurries at Low Concentration
PublicationRapid transients are particularly dangerous in industrial hydro-transport systems, where solid-liquid mixtures are transported via long pressure pipelines. A mathematical description of such flow is difficult due to the complexity of phenomena and difficulties in determining parameters. The main aim of the study was to examine the influence of the simplified mixture density and wave celerity description on satisfactory reproduction...
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THE 3D MODEL OF WATER SUPPLY NETWORK WITH APPLICATION OF THE ELEVATION DATA
Publication3D visualization is a key element of research and analysis and as the source used by experts in various fields e.g.: experts from water and sewage systems. The aim of this study was to visualize in three-dimensional space model of water supply network with relief. The path of technological development of GESUT data (Geodezyjna Ewidencja Sieci Uzbrojenia Terenu – geodetic records of public utilities) for water supply and measurement...
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Pathological and physiological high-frequency oscillations in focal human epilepsy
PublicationHigh-frequency oscillations (HFO; gamma: 40-100 Hz, ripples: 100-200 Hz, and fast ripples: 250-500 Hz) have been widely studied in health and disease. These phenomena may serve as biomarkers for epileptic brain; however, a means of differentiating between pathological and normal physiological HFO is essential. We categorized task-induced physiological HFO during periods of HFO induced by a visual or motor task by measuring frequency,...
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Hydraulic analysis of causes of washout of Gdynia-Orłowo seashore during the flood in the Kacza river estuary
PublicationIn July 2016 in the Three-city agglomeration a rainfall episode of over a day duration and 150 mm summary rainfall height, occurred. This situation, extreme as for Polish conditions, caused significant freshets in rivers and streams running into Gdansk Bay, the Baltic Sea, and serving as collectors of rainfall waters for the sea-coast towns. In many areas of the Three-city flood phenomena and overflows took place. The flood also...
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Porous structures in aspects of transpirating cooling of oxycombustion chamber walls
PublicationA wet oxycombustion chamber, which must be effectively cooled due to high temperature evolved during the oxy-combustion process, by using the phenomena of Reynolds thermal transpiration and Navier slip velocity. Closures needed to execute mass flow rate in a microchannel, which should be treated as a single porous structure in the walls of the combustion chamber, have been obtained by applying a local 3D approach. The Navier-Stokes...
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Temperature influence on tyre/road noise on poroelastic road surface based on laboratory measurements
PublicationThe temperature effect on measured tyre/road noise is very important phenomena as it may lead to significant errors in measurement results due to substantial influence of this parameter on the obtained values. It depends mainly on the particular tyre-road combination. It is different for dense and porous as well as for bituminous and cement concrete pavements. It differs also depending on tested tyre. The correction procedure for...
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Positive management of the university
PublicationPurpose: To demonstrate that contemporary universities may be improved by synthesis of strategic antinomies, i.e. seeking the possibility of combining opposite approaches to solving problems concerning university organization and management. Findings: That approach discounts the importance of building positive relationships between members of staff and undertaking activities intended to create a situation where the...
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Semantic Analysis and Text Summarization in Socio-Technical Systems
PublicationIn this chapter the authors present the results of the development the methodology for increasing the reliability of the functioning of the Socio-Technical System. The existed methods and algorithms for processing unstructured (textual) information were studied. Taking into account noted above strengths and weaknesses of Discriminant and Probabilistic approaches of Latent Semantic Relations analysis in of the summarization projection...
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DETERMINATION OF SEAKEEPING PERFORMANCE FOR A CASE STUDY VESSEL BY THE STRIP THEORY METHOD
PublicationThe increase of seakeeping performance is of particular importance for car and passenger ferries, service ships in the gas and oil extraction industry and offshore wind power farm industry, as well as for special purpose ships (including military applications). In the water areas of the Baltic Sea, North Sea, and Mediterranean Sea, which are characterised by a short and steep wave, the hull shape has a substantial impact on the...
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Numerical analysis of vacuum drying of a porous body in the integrated domain
Publicationn the present study, the vacuum drying process of an apple slice is numerically modeled based on a control volume method. Transient two-dimensional Navier– Stokes, energy, moisture, and Luikov equations are solved by numerical coding (Fortran) to simulate the simultaneous heat and mass transfer in the ambient and apple slice, respectively. The privilege of using Luikov's model is that the capillary forces are considered, and a...
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Thermo-Mechanical Simulation of Underwater Friction Stir Welding of Low Carbon Steel
PublicationThis article investigates the flow of materials and weld formation during underwater friction stir welding (UFSW) of low carbon steel. A thermo-mechanical model is used to understand the relation between frictional heat phenomena during the welding and weld properties. To better understand the effects of the water environment, the simulation and experimental results were compared with the sample prepared by the traditional friction...
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Numerical simulation of temperature distribution of heat flow on reservoir tanks connected in a series
PublicationThe flow of temperature distribution through a medium in thermodynamic studies plays an important role in understanding physical phenomena in chemical science and petroleum engineering, while temperature distribution indicates the degree of reaction that must be undergone to obtain the final product. Therefore, this paper aims to present and apply the exponential matrix algorithm (EMA), differential transformation algorithm (DTA),...
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AUTOMATED SYSTEM FOR FLUCTUATION ENHANCED GAS SENSING
PublicationResistance gas sensors exhibit random phenomena (resistance noise) which can be utilized to improve gas sensitivity and selectivity. That new emerging technique has to be investigated to recognize optimal parameters for gas detection. It means that a measurement system has to have ability of numerous parameters adjustment (e.g., sampling frequency, heater voltage, polarization current, voltage noise amplification). That fact induced...
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Blended natural and synthetic coagulants for the COD and BOD removal from surface water; optimization by response surface methodology: The case of Gibe river
PublicationA novel wastewater treatment method is presented in this study. It combines natural coagulants derived from watermelon seeds with the commonly used synthetic coagulant alum. This research demonstrates a remarkable synergy between these two coagulants in removing nutrients from Gibe River wastewater. Combining natural and chemical coagulants often improves water treatment by enhancing particle destabilization, accelerating floc...
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The influence of phosphorus fractions in bottom sediments on phosphate removal in semi-natural systems as the 3rd stage of biological wastewater treatment
PublicationThe research was carried out in two semi-natural systems (the polishing ponds in Swarzewo and the free water surface constructed wetland in Zarnowiec) in Poland. They were built as the 3rd stage of a conventional mechanical–biological wastewater treatment plant. These systems were built to improve the quality of the effluent of treated wastewater. In the polishing ponds and FWS wetland system, suspended solids, organic matter as...
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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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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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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
PublicationCirculating tumor cells (CTCs) are tumor cells that separate from the solid tumor and enter the bloodstream, which can cause metastasis. Detection and enumeration of CTCs show promising potential as a predictor for prognosis in cancer patients. Furthermore, single-cells sequencing is a technique that provides genetic information from individual cells and allows to classify them precisely and reliably. Sequencing data typically...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublicationMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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Unsupervised Learning for Biomechanical Data Using Self-organising Maps, an Approach for Temporomandibular Joint Analysis
PublicationWe proposed to apply a specific machine learning technique called Self-Organising Maps (SOM) to identify similarities in the performance of muscles around human temporomandibular joint (TMJ). The performance was assessed by measuring muscle activation with the use of surface electromyography (sEMG). SOM algorithm used in the study was able to find clusters of data in sEMG test results. The SOM analysis was based on processed sEMG...
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Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance
PublicationIdentification of active electrodes that record task-relevant neurophysiological activity is needed for clinical and industrial applications as well as for investigating brain functions. We developed an unsupervised, fully automated approach to classify active electrodes showing event-related intracranial EEG (iEEG) responses from 115 patients performing a free recall verbal memory task. Our approach employed new interpretable...
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Learning Communities-International Journal of Learning in Social Contexts
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Multimodal learning application with interactive animated character. [Multimodalna aplikacja edukacyjna wykorzystująca interaktywną animowaną postać]
PublicationThe aim of this study is to design a computer application that may assist teachers and therapists in multimodal manner in their work with impaired or disabled children. The application can be operated in many different ways, giving to a child with special educational needs a possibility to learn and train many skills or treat speech disorders. The main stress in this research is on the creation of animated character that will serve...
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Using Isolation Forest and Alternative Data Products to Overcome Ground Truth Data Scarcity for Improved Deep Learning-based Agricultural Land Use Classification Models
PublicationHigh-quality labelled datasets represent a cornerstone in the development of deep learning models for land use classification. The high cost of data collection, the inherent errors introduced during data mapping efforts, the lack of local knowledge, and the spatial variability of the data hinder the development of accurate and spatially-transferable deep learning models in the context of agriculture. In this paper, we investigate...
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Machine-Learning Methods for Estimating Performance of Structural Concrete Members Reinforced with Fiber-Reinforced Polymers
PublicationIn recent years, fiber-reinforced polymers (FRP) in reinforced concrete (RC) members have gained significant attention due to their exceptional properties, including lightweight construction, high specific strength, and stiffness. These attributes have found application in structures, infrastructures, wind power equipment, and various advanced civil products. However, the production process and the extensive testing required for...
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Non-linear circuit model of a single doubly-fed induction machine formulated in natural axes for drive systems simulation purposes
PublicationMathematical modelling and a circuit model formulated in natural axes of a single doubly-fed induction machine, with the account of magnetic circuit nonlinearity are presented in the paper. Derivation of the model differential equations was based on Lagrange's energy method. State functions of magnetic elements in the model are non-linear and depend on all currents flowing in the machine windings and on the angle of rotor position....
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Double-diffusive natural convection energy transfer in magnetically influenced Casson fluid flow in trapezoidal enclosure with fillets
PublicationThe prime motive of this disquisition is to deal with mathematical analysis of natural convection energy transport driven by combined buoyancy effects of thermal and solutal diffusion in a trapezoidal enclosure. Casson fluid rheological constitutive model depicting attributes of viscoelastic liquids is envisioned. The influence of the inclined magnetic field governed by Lorentz field law is also considered. To raise the essence...
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Infrared techniques for natural convection investigations in channels between two vertical, parallel, isothermal and symmetrically heated plates
PublicationThe effect of the gap width between two symmetrically heated vertical, parallel, isothermal plates on intensity of natural convective heat transfer in a gas (Pr = 0.71) was experimentally studied using the balance and gradient methods. In the former method heat fluxes were determined based on measurements of the voltage and electric current supplying the heaters placed inside the walls. In the latter, heat fluxes were calculated...
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Humanities and Natural Sciences
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Machine-learning methods for estimating compressive strength of high-performance alkali-activated concrete
PublicationHigh-performance alkali-activated concrete (HP-AAC) is acknowledged as a cementless and environmentally friendly material. It has recently received a substantial amount of interest not only due to the potential it has for being used instead of ordinary concrete but also owing to the concerns associated with climate change, sustainability, reduction of CO2 emissions, and energy consumption. The characteristics and amounts of the...
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Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection
PublicationDue to the exponential rise of mobile technology, a slew of new mobile security concerns has surfaced recently. To address the hazards connected with malware, many approaches have been developed. Signature-based detection is the most widely used approach for detecting Android malware. This approach has the disadvantage of being unable to identify unknown malware. As a result of this issue, machine learning (ML) for detecting malware...
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Vivedenna dosovih vod u grunt = The rain - water management solutions basedon the seepage phenomena cz.2
PublicationWprowadzanie wód opadowych do gruntu. Rozwiązania o dużej przepustowości, do użycia w odwadnianiu dużych powierzchni.
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Volterra series usefulness in modelling of the time-domain cross-talk phenomena in coupled microstrip lines with nonlinear termination
PublicationW pracy przedyskutowano możliwość wykorzystania szeregów Volterry do analizy zjawiska przesłuchu w sprzężonych liniach mikropaskowych z nieliniowym obciążeniem. Apracowano algorytm metody, zaś uzyskane wyniki numeryczne zweryfikowano poprzez porównania z wynikami badań eksperymentalnych linii obciążonych w torze transmisyjnym diodą Schottky'ego.
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Chemometric determination of solute-affected solvent vibrational spectra as a superior way of information extraction on solute solvation phenomena
PublicationW pracy zaprezentowano dwie chemometryczne metody wyznaczania widm zaburzonych rozpuszczalnika oraz liczby cząsteczek zaburzonych, na podstawie zmierzonych serii wibracyjnych widm FT-IR roztworów substancji. Pierwsza z metod została stworzona na podstawie Namiarowej Analizy Faktorowej (ang. Target Factor Analysis). Druga z nich wykorzystuje algorytm izolacji widm czystych składników z serii widm mieszanin. Działanie obu metod zostało...
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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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Project-Based Learning as a Method for Interdisciplinary Adaptation to Climate Change—Reda Valley Case Study
PublicationThe challenges of the global labour market require university authorities to extend traditional forms of education into more innovative and effective solutions. Project-based learning (PjBL) is one of highly effective methods for acquiring knowledge and teaching “soft” skills to future employees. This article describes an experimental use of PjBL at a university with a long history of teaching based on traditional methods—the Gdansk...
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Natural fish oil improves the differentiation and maturation of oligodendrocyte precursor cells to oligodendrocytes in vitro after interaction with the blood–brain barrier
PublicationThe blood–brain barrier (BBB) tightly controls the microenvironment of the central nervous system (CNS) to allow neurons to function properly. Additionally, emerging studies point to the beneficial effect of natural oils affecting a wide variety of physiological and pathological processes in the human body. In this study, using an in vitro model of the BBB, we tested the influence of natural fish oil mixture (FOM) vs. borage oil...
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Mathematical Thinking and Learning
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Animal Learning and Behavior
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Learning Environments Research
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Development and Learning in Organizations
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Journal of Workplace Learning
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Information and Learning Science
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Learning Media and Technology
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Journal of Learning Styles
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Journal of Teaching and Learning
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Journal of Learning Design
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