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Search results for: learning about natural phenomena
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Hydrogen Embrittlement and Oxide Layer E ect in the Cathodically Charged Zircaloy-2
PublicationThe present paper is aimed at determining the less investigated effects of hydrogen uptake on the microstructure and the mechanical behavior of the oxidized Zircaloy-2 alloy. The specimens were oxidized and charged with hydrogen. The different oxidation temperatures and cathodic current densities were applied. The scanning electron microscopy, X-ray electron diffraction spectroscopy, hydrogen absorption assessment, tensile, and...
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Simulation of fluid structure interaction in a novel design of high pressure axial piston hydraulic pump
PublicationA novel type of an axial, piston-driven high pressure hydraulic pump with variable capacity marks a significant improvement in the area of the hydraulic machinery design. Total discharge from hydrostatic forces eliminates a need for a servomechanism, thus simplifying operation, reducing weight and introducing the possibility of the pump displacement control by computer. PWK-type pumps, invented in the Gdansk University of Technology,...
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Physics augmented classification of fNIRS signals
PublicationBackground. Predictive classification favours performance over semantics. In traditional predictive classification pipelines, feature engineering is often oblivious to the underlying phenomena. Hypothesis. In applied domains such as functional Near Infrared Spectroscopy (fNIRS), the exploitation of physical knowledge may improve the discriminative quality of our observation set. Aims. Give exemplary evidence that intervening the...
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Material characterisation of biaxial glass-fibre non-crimp fabrics as a function of ply orientation, stitch pattern, stitch length and stitch tension
PublicationDue to their high density-specific stiffnesses and strength, fibre reinforced plastic (FRP) composites are particularly interesting for mobility and transport applications. Warp-knitted non-crimp fabrics (NCF) are one possible way to produce such FRP composites. They are advantageous because of their low production costs and the ability to tailor the properties of the textile to the reinforcement and drape requirements of the application....
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Joint experimental and theoretical study on low-energy elastic electron scattering by gaseous alkynes: Differential cross sections, shape resonances, and methylation effects
PublicationA detailed comparison of experimental and theoretical elastic cross sections for low-energy electron scattering by ethyne, taken earlier in our group by Gauf et al. [Phys. Rev. A 87, 012710 (2013)], and some of its methylated derivatives, propyne, and the isomers 1-butyne and 2-butyne, taken here, are presented. The present differential cross sections were measured at incident electron energies ranging from 1 eV to 30 eV and...
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Size effect at aggregate level in microCT scans and DEM simulation – Splitting tensile test of concrete
PublicationThe paper describes an experimental and numerical study of size effect on concrete cylindrical specimens in splitting tensile test. Own experimental campaign was performed on specimens with 5 various diameters from D = 74, 105, 150, 192 and 250 mm with hardboard loading strips (distributed load according to standard methods) scaled proportionally to the specimen diameter. The crack opening-control system was applied to obtain the...
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Photophysical processes in the selected white organic light-emitting diodes
PublicationThe first part discusses history of organic emitters, the scope of the work, phenomena in molecular systems, types of architectures in OLEDs, types of OLEDs emitting white light with examples from the literaturę and a description of the parameters chcracterizing LEDs. The second part describes materials, production of the samples, the measurement systems and results. In chapter 8.1 the results for the OLEDs based on emission from...
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Selected problems of decision making modelling in power engineering
PublicationThe paper presents the selected problems of decision making modelling in power engineering specially investment risk evaluation methods. The proposed model can be used in the range programming the development and investing process in power engineering. Decision making problems in power engineering and the evaluation of investment effectiveness in particular are closely related to modelling which relatively accurately reflects...
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Using UAV Photogrammetry to Analyse Changes in the Coastal Zone Based on the Sopot Tombolo (Salient) Measurement Project
PublicationThe main factors influencing the shape of the beach, shoreline and seabed include undulation, wind and coastal currents. These phenomena cause continuous and multidimensional changes in the shape of the seabed and the Earth’s surface, and when they occur in an area of intense human activity, they should be constantly monitored. In 2018 and 2019, several measurement campaigns took place in the littoral zone in Sopot, related to...
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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublicationThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
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Big Data from Sensor Network via Internet of Things to Edge Deep Learning for Smart City
PublicationData from a physical world is sampled by sensor networks, and then streams of Big Data are sent to cloud hosts to support decision making by deep learning software. In a smart city, some tasks may be assigned to smart devices of the Internet of Things for performing edge computing. Besides, a part of workload of calculations can be transferred to the cloud hosts. This paper proposes benchmarks for division tasks between an edge...
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Natural/bio-based sorbents as greener extractive materials for endocrine disrupting compounds in samples of different matrix composition
PublicationEndocrine-disrupting compounds (EDCs) are a group of chemicals that interfere with the endocrine system, leading to adverse effects on human health and the environment. Increasing concerns over the EDCs presence in various environmental compartments has driven the search for greener extraction materials. Recently, the use of polymers of natural origin (biopolymers) has been demonstrated to be an effective and promising research...
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Natural language dictionaries implemented as finite automata
PublicationRozdział przedstawia wykorzystanie automatów skończonych jako słowników języka naturalnego. Podane są podstawy teoretyczne. Omówione są zastosowania: realizacja doskonałej funkcji mieszającej, analizy i syntezy morfologicznej, poprawiania pisowni i dopisywania znaków diakrytycznych, wydobywanie informacji. Podano algorytmy tworzenia automatów oraz omówiono sposoby reprezentacji automatów z uwzględnieniem kompresji.
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Natural Hydroxyapatite as a by-product of industrial biomass gasification
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Degradation of modified TPS in natural and industrial compost
PublicationThe aim of the study was to determine in the pilot studies the degree of decomposition of modified by us thermoplasic starch (potato starch).Commercial and new obtained by us foils were tested in an open roofing at normal weather conditions. The most visible changes were observed in TPS modified by epoxidized soybean oil and arabic gum contrary to commercial foils where there was no mass change observed.
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Ecology and Conservation of Steppes and Semi-Natural Grasslands
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Inhibition of cancer antioxidant defense by natural compounds
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The Role of the Natural Antioxidant Mechanism in Sperm Cells
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Natural Antioxidants as Multifunctional Additives for Polymeric Materials
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Hydrogels Based on Natural Polymers for Cardiac Applications
PublicationIn this work agar- and borax-based hydrogels with and without the addition of poly(vinyl alcohol) (PVA) at different concentrations were synthesized. Hydrogels were modified by the same amount of acetylsalicylic acid (ASA) which exhibits antithrombotic properties. The effect of modification by ASA on the properties of hydrogels was analyzed.
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Thermal degradation kinetics of poly(propylene succinate) prepared with the use of natural origin monomers
PublicationLinear biobased polyester polyols were prepared with the use of succinic acid and 1,3-pro- panediol (both with natural origin). Tetraisopropyl orthotitanate (TPT) was used as a catalyst. In order to determine the effect of various synthesis temperature conditions on the thermal degradation kinet- ics, nine sequences of temperature conditions were used during two-step polycondensation reaction. Thermogravimetric analysis was conducted...
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Latest Insights on Novel Deep Eutectic Solvents (DES) for Sustainable Extraction of Phenolic Compounds from Natural Sources
PublicationPhenolic compounds have long been of great importance in the pharmaceutical, food, and cosmetic industries. Unfortunately, conventional extraction procedures have a high cost and are time consuming, and the solvents used can represent a safety risk for operators, consumers, and the environment. Deep eutectic solvents (DESs) are green alternatives for extraction processes, given their low or non-toxicity, biodegradability, and reusability....
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Real and Virtual Instruments in Machine Learning – Training and Comparison of Classification Results
PublicationThe continuous growth of the computing power of processors, as well as the fact that computational clusters can be created from combined machines, allows for increasing the complexity of algorithms that can be trained. The process, however, requires expanding the basis of the training sets. One of the main obstacles in music classification is the lack of high-quality, real-life recording database for every instrument with a variety...
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Characteristics of microstructural phenomena occurring on the surface of protective gloves by the action of mechanical and chemical factors
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Case studies of resonance phenomena in high voltage overhead power lines with shunt reactors
PublicationMisguided design of the towers of power transmission lines can lead to serious problems such as voltage asymmetry, overvoltages, electric arc extinction difficulties or resonance – in case of double circuit line with shunt reactors. The paper points out those threats on example of 400 kV double circuit overhead transmission line with shunt reactors.
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Artificial Neural Network in Forecasting the Churn Phenomena Among Costumers of IT and Power Supply Services
PublicationThis paper presents an attempt to use an artificial neural network to investigate the churn phenomenon among the customers of a telecommunications operator. An attempt was made to create a data model based on the customer lifetime value (CLV) rather than on activity alone. A multilayered artificial neural network was used for the experiments. The results yielded a 99% successful identification rate for customers in no danger of...
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Metal dusting phenomena of 501 AISI furnace tubes in refinery fractional distillation unit
PublicationThe purpose of this investigation was to conduct the failure analysis of 501 AISI furnace tubes places before distillation column in fractional distillation unit. The investigated furnace tubes were planned to work for ten years however after just two years of exploitation <30% of the material left. The observed corrosion process had the intense and complex character. The well-adhered shiny black deposits and deep, round pits were...
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Regulatory B Cells Involvement in Autoimmune Phenomena Occurring in Pediatric Graves’ Disease Patients
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Surface phenomena in discotic liquid crystals investigated using polarized FTIR transmission spectroscopy
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Parallel simulations of electrophysiological phenomena in myocardium on large 32 and 64-bit Linux clusters.
PublicationW pracy podjęto badania i przeprowadzono symulacje zjawisk elektrofizjologicznych w mięśniu sercowym z wykorzystaniem wytworzonego w tym celu oprogramowania równoległego opartego na MPI. Zaimplementowano i zbadano ulepszenia kodu prowadzące do uzyskania dobrej skalowalności oraz przeprowadzono testy wydajności na najnowszych 32 i 64-bitowych klastrach linuksowych. Praca stanowi próbę równoległej implementacji znanego podejścia...
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Polyurethanes modified with natural polymers for medical application. Part II. Polyurethane/gelatin, polyurethane/starch, polyurethane/cellulose
PublicationThis paper is a literature overview of biomedical PUR modifications with natural polymers such as starch, cellulose and gelatin. Properties like biodegradability and biocompatibility of modified PUR cause that these materials may be used as wound dressings, tissue scaffolds, tissue implants and also vascular grafts.
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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublicationIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
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LDNet: A Robust Hybrid Approach for Lie Detection Using Deep Learning Techniques
PublicationDeception detection is regarded as a concern for everyone in their daily lives and affects social interactions. The human face is a rich source of data that offers trustworthy markers of deception. The deception or lie detection systems are non-intrusive, cost-effective, and mobile by identifying facial expressions. Over the last decade, numerous studies have been conducted on deception detection using several advanced techniques....
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile...
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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublicationLiquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile strengths...
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DNAffinity: a machine-learning approach to predict DNA binding affinities of transcription factors
PublicationWe present a physics-based machine learning approach to predict in vitro transcription factor binding affinities from structural and mechanical DNA properties directly derived from atomistic molecular dynamics simulations. The method is able to predict affinities obtained with techniques as different as uPBM, gcPBM and HT-SELEX with an excellent performance, much better than existing algorithms. Due to its nature, the method can...
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Projektowanie zajęć prowadzonych na odległość (10h e-learning)
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Koło naukowe CJO - Tech-Enhanced English Learning (TEEL)
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Intra-subject class-incremental deep learning approach for EEG-based imagined speech recognition
PublicationBrain–computer interfaces (BCIs) aim to decode brain signals and transform them into commands for device operation. The present study aimed to decode the brain activity during imagined speech. The BCI must identify imagined words within a given vocabulary and thus perform the requested action. A possible scenario when using this approach is the gradual addition of new words to the vocabulary using incremental learning methods....
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Love your mistakes!—they help you adapt to change. How do knowledge, collaboration and learning cultures foster organizational intelligence?
PublicationPurpose: The study aims to determine how the acceptance of mistakes is related to adaptability to change in a broad organizational context. Therefore it explores how knowledge, collaboration, and learning culture (including “acceptance of mistakes”) might help organizations overcome their resistance to change. Methodology: The study uses two sample groups: students aged 18–24 (330 cases) and employees aged >24 (326 cases) who work...
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Technology-Enhanced Environmental Learning: Co-design of Educational Mobile Application Case
PublicationThe process of co-creating an educational mobile application to support environmentally friendly behavior is presented in this paper. The research material consisted of quantitative data collected on the application during the first testing phase by early adopters. The results suggest that the most frequently used features of the app were related to transport and educational activities. While women tended to split their time between...
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The effects of relational and psychological capital on work engagement: the mediation of learning goal orientation
PublicationPurpose – This paper proposes a research model in which learning goal orientation (LGO) mediates the impacts of relational capital and psychological capital (PsyCap) on work engagement. Design/methodology/approach – Data obtained from 475 managers and employees in the manufacturing and service industries in Poland were utilized to assess the linkages given above. Common method variance was controlled by the unmeasured latent method...
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Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublicationCatheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified...
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Optimizing Medical Personnel Speech Recognition Models Using Speech Synthesis and Reinforcement Learning
PublicationText-to-Speech synthesis (TTS) can be used to generate training data for building Automatic Speech Recognition models (ASR). Access to medical speech data is because it is sensitive data that is difficult to obtain for privacy reasons; TTS can help expand the data set. Speech can be synthesized by mimicking different accents, dialects, and speaking styles that may occur in a medical language. Reinforcement Learning (RL), in the...
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Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
PublicationBreast cancer is the most frequent female cancer, with a considerable disease burden and high mortality. Early diagnosis with screening mammography might be facilitated by automated systems supported by deep learning artificial intelligence. We propose a model based on a weakly supervised Clustering-constrained Attention Multiple Instance Learning (CLAM) classifier able to train under data scarcity effectively. We used a private...
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Expert system against machine learning approaches as a virtual sensor for ventricular arrhythmia risk level estimation
PublicationRecent advancements in machine learning have opened new avenues for preventing fatal ventricular arrhythmia by accurately measuring and analyzing QT intervals. This paper presents virtual sensor based on an expert system designed to prevent the risk of fatal ventricular arrhythmias associated with QT-prolonging treatments. The expert system categorizes patients into three risk levels based on their electrocardiogram-derived QT...
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Assessment Of the Relevance of Best Practices in The Development of Medical R&D Projects Based on Machine Learning
PublicationMachine learning has emerged as a fundamental tool for numerous endeavors within health informatics, bioinformatics, and medicine. However, novices among biomedical researchers and IT developers frequently lack the requisite experience to effectively execute a machine learning project, thereby increasing the likelihood of adopting erroneous practices that may result in common pitfalls or overly optimistic predictions. The paper...
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Cellulose Nanofibers Isolated from the Cuscuta Reflexa Plant as a Green Reinforcement of Natural Rubber
PublicationIn the present work, we used the steam explosion method for the isolation of cellulose nanofiber (CNF) from Cuscuta reflexa, a parasitic plant commonly seen in Kerala and we evaluated its reinforcing efficiency in natural rubber (NR). Fourier Transform Infrared Spectroscopy (FTIR), X-Ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), and Thermogravimetric analysis (TGA) techniques...
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Automated detection of pronunciation errors in non-native English speech employing deep learning
PublicationDespite significant advances in recent years, the existing Computer-Assisted Pronunciation Training (CAPT) methods detect pronunciation errors with a relatively low accuracy (precision of 60% at 40%-80% recall). This Ph.D. work proposes novel deep learning methods for detecting pronunciation errors in non-native (L2) English speech, outperforming the state-of-the-art method in AUC metric (Area under the Curve) by 41%, i.e., from...