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Wyniki wyszukiwania dla: INTELLIGENT SIGNAL PROCESSING, MACHINE LEARNING, DATASETS
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Anna Czaja mgr inż.
OsobyPo ukończeniu studiów magisterskich na kierunku Informatyka (Politechnika Gdańska, Wydział Elektroniki, Telekomunikacji i Informatyki) przez szereg lat pracowała jako programista. Obecnie zatrudniona na stanowisku asystenta w Katedrze Zastosowań Informatyki w Zarządzaniu (Politechnika Gdańska, Wydział Zarządzania i Ekonomii). Uczestniczka studiów doktoranckich III stopnia na wydziale Zarządzania i Ekonomii na Politechnice Gdańskiej....
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Detection and Mitigation of GPS Spoofing Based on Antenna Array Processing
PublikacjaIn this article authors present an application of spatial processing methods for GPS spoofing detection and mitigation. In the first part of this article, a spoofing detection method, based on phase delay measurements, is proposed. Accuracy and precision of phase delay estimation is assessed for various qualities of received signal. Spoofing detection thresholds are determined. Efficiency of this method is evaluated in terms of...
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MICROSEISMIC EVENT DETECTION USING DIFFERENT ALGORITHMS ON REAL DATA FROM PATCH ARRAY GEOPHONE GRID FROM EASTERN POMERANIA FRACTURING JOB
PublikacjaThe microseismic monitoring is a method of monitoring of fracture propagation during hydraulic fracturing process. Hydraulic fracturing is a method of reservoir stimulation used especially for unconventional gas recovery. A matrix of several thousand geophones is placed on the surface of earth to record every little tremor of ground induced by fracturing process. Afterwards, the signal is analysed and the place of tremor occurrence...
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A Simplistic Downlink Channel Estimation Method for NB-IoT
PublikacjaThis paper presents a downlink channel estimation method intended for a Narrowband Internet of Things (NB-IoT) access link. Due to its low computational complexity, this method is well suited for energy-efficient IoT devices, still providing acceptable reception quality in terms of signal-to-noise (SNR) performance. This paper describes the physical layer of NB-IoT within the scope of channel estimation, and also reviews existing...
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Decisional DNA for modeling and reuse of experiential clinical assessments in breast cancer diagnosis and treatment
PublikacjaClinical Decision Support Systems (CDSS) are active knowledge resources that use patient data to generate case specific advice. The fast pace of change of clinical knowledge imposes to CDSS the continuous update of the domain knowledge and decision criteria. Traditional approaches require costly tedious manual maintenance of the CDSS knowledge bases and repositories. Often, such an effort cannot be assumed by medical teams, hence...
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Examining Influence of Distance to Microphone on Accuracy of Speech Recognition
PublikacjaThe problem of controlling a machine by the distant-talking speaker without a necessity of handheld or body-worn equipment usage is considered. A laboratory setup is introduced for examination of performance of the developed automatic speech recognition system fed by direct and by distant speech acquired by microphones placed at three different distances from the speaker (0.5 m to 1.5 m). For feature extraction from the voice signal...
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Experimental and Theoretical Screening for Green Solvents Improving Sulfamethizole Solubility
PublikacjaSolubility enhancement of poorly soluble active pharmaceutical ingredients is of crucial importance for drug development and processing. Extensive experimental screening is limited due to the vast number of potential solvent combinations. Hence, theoretical models can offer valuable hints for guiding experiments aimed at providing solubility data. In this paper, we explore the possibility of applying quantum-chemistry-derived...
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Experience-Oriented Intelligence for Internet of Things
PublikacjaThe Internet of Things (IoT) has gained significant attention from industry as well as academia during the past decade. The main reason behind this interest is the capabilities of the IoT for seamlessly integrating classical networks and networked objects, and hence allows people to create an intelligent environment based on this powerful integration. However, how to extract useful information from data produced by IoT and facilitate...
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Microgrinding with single-disk lapping kinematics.
PublikacjaGrinding operations are carried out with a variety of tool-workpiece configurations. The selection of a grinding process for a particular application depends on part shape, part size, ease of fixture, requirements concerning the acceptable shape errors. It is evident that lapping is very effective in eliminating the waviness while surface grinding is not. Dual disk machines for the double face grinding with planetary kinematics...
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Computer vision techniques applied for reconstruction of seafloor 3D images from side scan and synthetic aperture sonars data
PublikacjaThe Side Scan Sonar and Synthetic Aperture Sonar are well known echo signal processing technologies that produce 2D images of the seafloor. Both systems combines a number of acoustic pings to form a high resolution image of seafloor. It was shown in numerous papers that 2D images acquired by such systems can be transformed into 3D models of seafloor surface by algorithmic approach using intensity information, contained in a grayscaled...
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LOW COST MEASUREMENT MODULE FOR MATRIX OF AMPEROMETRIC GAS SENSOR
PublikacjaThis paper describes an amperometric sensor module for gas concentration measurement. A module can be used for many types of electrochemical gas sensors without major hardware changes. Device is based on AVR ATmega8 microcontroller. As signal processing circuit a specialized integrated circuit LMP9l000 configurable via I2C interface is used. The concept of a measuring system composed of several modules dedicated for a gas sensors...
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A Biofeedback System that Uses the Game to Study Electrical Muscle Activity
PublikacjaThe aim of this project was to design a system that will allow performing repetitive muscle exercises using a biofeedback device. It is supposed to enhance the motivation and attractiveness of the performed tasks thanks to an interactive game developed for mobile devices with the Android operating system. The built-in calibration mechanisms enable the users to play a game that is independent of their abilities which evens out the...
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Pomiar odpowiedzi impulsowej kanału radiowego na obszarze morskim i przybrzeżnym
PublikacjaW artykule zaprezentowano wyniki pomiarów odpowiedzi impulsowej kanału radiowego na obszarze morskim i przybrzeżnym. Pomiary przeprowadzono na częstotliwości 1457 MHz a sygnałem sondującym był sygnał o paśmie 10 MHz z modulacją BPSK i pseudoprzypadkową zawartością binarną. Odbierane sygnały były rejestrowane przez dwie stacje ruchome, zainstalowane w samolocie i na łodzi patrolowej. Podczas późniejszej obróbki danych zastosowano...
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Buzz-based honeybee colony fingerprint
PublikacjaNon-intrusive remote monitoring has its applications in a variety of areas. For industrial surveillance case, devices are capable of detecting anomalies that may threaten machine operation. Similarly, agricultural monitoring devices are used to supervise livestock or provide higher yields. Modern IoT devices are often coupled with Machine Learning models, which provide valuable insights into device operation. However, the data...
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Examining Classifiers Applied to Static Hand Gesture Recognition in Novel Sound Mixing System
PublikacjaThe main objective of the chapter is to present the methodology and results of examining various classifiers (Nearest Neighbor-like algorithm with non-nested generalization (NNge), Naive Bayes, C4.5 (J48), Random Tree, Random Forests, Artificial Neural Networks (Multilayer Perceptron), Support Vector Machine (SVM) used for static gesture recognition. A problem of effective gesture recognition is outlined in the context of the system...
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A new optimal algorithm for a time-dependent scheduling problem
PublikacjaIn this article a single machine time-dependent scheduling problem with total completion time criterion is considered. There are n given jobs j_1, ..., j_n and the processing time pi of the i-th job is given by p_i = 1 + b_is_i, where si is the starting time of the i-th job, i = 1, ..., n. If all jobs have different and non-zero deterioration rates and bi > bj => bi >= (b_min+1)/(b_min) b_j + 1/b_min, where b_min = min{b_i}, then...
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Acoustic radar employing particle velocity sensors
PublikacjaA concept, practical realization and applications of a passive acoustic radar to automatic localization, tracking of sound sources were presented in the paper. The device consist of the new kind of multichannel miniature sound intensity sensors and a group of digital signal processing algorithms. Contrary to active radars, it does not emit the scanning beam but after receiving surroundings sounds it provide information about the...
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Novel approach to modeling spectral-domain optical coherence tomography with Monte Carlo method
PublikacjaNumerical modeling Optical Coherence Tomography (OCT) systems is needed for optical setup optimization, development of new signal processing methods and assessment of impact of different physical phenomena inside the sample on OCT signal. The Monte Carlo method has been often used for modeling Optical Coherence Tomography, as it is a well established tool for simulating light propagation in scattering media. However, in this method...
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Improving automatic surveillance by sound analysis
PublikacjaAn automatic surveillance system, based on event detection in the video image can be improved by implementing algorithms for audio analysis. Dangerous or illegal actions are often connected with distinctive sound events like screams or sudden bursts of energy. A method for detection and classification of alarming sound events is presented. Detection is based on the observation of sudden changes in sound level in distinctive sub-bands...
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Faults and Fault Detection Methods in Electric Drives
PublikacjaThe chapter presents a review of faults and fault detection methods in electric drives. Typical faults are presented that arises for the induction motor, which is valued in the industry for its robust construction and cost-effective production. Moreover, a summary is presented of detectable faults in conjunction with the required physical information that allow a detection of specific faults. In order to address faults of a complete...
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RSS-Based DoA Estimation for ESPAR Antennas Using Support Vector Machine
PublikacjaIn this letter, it is shown how direction-of-arrival (DoA) estimation for electronically steerable parasitic array radiator (ESPAR) antennas, which are designed to be integrated within wireless sensor network nodes, can be improved by applying support vector classification approach to received signal strength (RSS) values recorded at an antenna's output port. The proposed method relies on ESPAR antenna's radiation patterns measured...
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Data-driven, probabilistic model for attainable speed for ships approaching Gdańsk harbour
PublikacjaThe 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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Supply current signal and artificial neural networks in the induction motor bearings diagnostics
PublikacjaThis paper contains research results of the diagnostics of induction motor bearings based on measurement of the supply current with usage of artificial neural networks. Bearing failure amount is greater than 40% of all engine failures, which makes their damage-free operation crucial. Tests were performed on motors with intentionally made bearings defects. Chapter 2 introduces the concept of artificial neural networks. It presents...
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Asynchronous distributed state estimation based on a continuous-time stochastic model
PublikacjaW artykule rozważa się ogólny problem estymacji stanu w asynchronicznych rozłożonych systemach (ADE) opartych na wielu czujnikach. W takich systemach stan obiektu jest oceniany przez grupę lokalnych estymatorów, z których każdy oparty zwykle na filtrze Kalmana, dokonuje fuzji danych zebranych poprzez jego lokalne czujniki oraz danych uzyskanych od innych (zdalnych) procesorów, w celu wyznaczenia możliwie najlepszych estymat. Przeprowadzając...
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Pre-arrangement of solvability, complexity, stability and quality of GPC systems
PublikacjaPraca dotyczy podstawowych problemów strojenia algorytmów dyskretnoczasowego uogólnienia sterowania predykcyjnego (GPC). Optymalne sterowanie predykcyjne, w sensie pewnego kwadratowego funkcjonału kosztów, wyznacza się rozwiązując odpowiednie liniowe zadanie. W pracy podano warunki, przy których macierz tego zadania jest macierzą o pełnym kolumnowym rzędzie - co gwarantuje istnienie optymalnego sterownika. W następnej kolejności...
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Hybrid SONIC: joint feedforward–feedback narrowband interference canceler
PublikacjaSONIC (self-optimizing narrowband interference canceler) is an acronym of a recently proposed active noise control algorithm with interesting adaptivity and robustness properties. SONIC is a purely feedback controller, capable of rejecting nonstationary sinusoidal disturbances (with time-varying amplitude and/or frequency) in the presence of plant (secondary path) uncertainty. We show that although SONIC can work reliably without...
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PROPRIETARY SOFTWARE IN TECHNICAL HIGHER EDUCATION
PublikacjaThe authors present a relatively easy way to extend the quality of education in professional studies (engineering) on major “Geodesy and Cartography”. They indicate the possibility to deepen students’ knowledge by using in the educational process proprietary software enriching education. The authors use their own experiences, results of the cooperation with employers, as well as the effects of scientific research to introduce into...
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PROPRIETARY SOFTWARE IN TECHNICAL HIGHER EDUCATION
PublikacjaThe authors present a relatively easy way to extend the quality of education in professional studies (engineering) on major “Geodesy and Cartography”. They indicate the possibility to deepen students’ knowledge by using in the educational process proprietary software enriching education. The authors use their own experiences, results of the cooperation with employers, as well as the effects of scientific research to introduce...
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Analysis-by-synthesis paradigm evolved into a new concept
PublikacjaThis work aims at showing how the well-known analysis-by-synthesis paradigm has recently been evolved into a new concept. However, in contrast to the original idea stating that the created sound should not fail to pass the foolproof synthesis test, the recent development is a consequence of the need to create new data. Deep learning models are greedy algorithms requiring a vast amount of data that, in addition, should be correctly...
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Modeling of multi-cavity Fabry-Perot optical fiber sensors
PublikacjaReflectance characteristics of a two-cavity extrinsic Fabry-Perot optical fiber sensor were investigated using computer modeling. Calculations were performed using a plane wave-based approach, selected for clarity of results. Based on the modeling results, it can be concluded that the two-cavity Fabry-Perot interferometer can be used to measure two different quantities, such as refractive index and temperature, independently. It...
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Automatic Correction of Non-Anechoic Antenna Measurements Using Complex Morlet Wavelets
PublikacjaReal-world performance of antennas is normally tested in anechoic chambers (ACs). Alternatively, experimental validation can be performed in non-anechoic environments and refined in the course of post-processing. Unfortunately, the existing methods are difficult to setup and prone to failure. In this letter, a wavelet-based framework for correction of non-anechoic antenna measurements has been proposed. The method involves automatic...
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Special Issue: “Non-Destructive Testing of Structures”
PublikacjaThe Special Issue “Non-Destructive Testing of Structures” has been proposed to present recent developments in the field of diagnostics of structural materials and components in civil and mechanical engineering. The papers highlighted in this editorial concern various aspects of non-invasive diagnostics, including such topics as condition assessments of civil and mechanical structures and connections of structural elements, the...
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Application of Multiplicative Drift Correction and Component Correction methods on simulated gas sensor array responses
PublikacjaSensor response drift is one of the most challenging problems in gas-analyzing systems. Such systems, commonly called electronic noses, are expected to be reliable and reproducible in the long term. Due to the drift phenomena, electronic noses usability is limited to the relatively short period of time, and frequent recalibrations of device are required. Because it is very hard to fabricate sensors without drift, this phenomenon...
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Comparing the Effectiveness of ANNs and SVMs in Forecasting the Impact of Traffic-Induced Vibrations on Building
PublikacjaTraffic - induced vibrations may cause damage to structural elements and may even lead to structural collapse. The aim of the article is to compare the effectiveness of algorithms in forecasting the impact of vibrations on buildings using the Machine Learning (ML) methods. The paper presents two alternative approaches by using Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs). Factors that may affect traffic-induced...
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Listening to Live Music: Life beyond Music Recommendation Systems
PublikacjaThis paper presents first a short review on music recommendation systems based on social collaborative filtering. A dictionary of terms related to music recommendation systems, such as music information retrieval (MIR), Query-by-Example (QBE), Query-by-Category (QBC), music content, music annotating, music tagging, bridging the semantic gap in music domain, etc. is introduced. Bases of music recommender systems are shortly presented,...
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Exploring Cause-and-Effect Relationships Between Public Company Press Releases and Their Stock Prices
PublikacjaThe aim of the work is to design and implement a method of exploring the cause-and-effect relationships between company announcements and the stock prices on NASDAQ stock exchange, followed by a brief discussion. For this purpose, it was necessary to download the stock quotes of selected companies from the NASDAQ market from public web sources. Additionally, media messages related to selected companies had to be downloaded, and...
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Monitoring the BTEX Volatiles during 3D Printing with Acrylonitrile Butadiene Styrene (ABS) Using Electronic Nose and Proton Transfer Reaction Mass Spectrometry
PublikacjaWe describe a concept study in which the changes of concentration of benzene, toluene, ethylbenzene, and xylene (BTEX) compounds and styrene within a 3D printer enclosure during printing with different acrylonitrile butadiene styrene (ABS) filaments were monitored in real-time using a proton transfer reaction mass spectrometer and an electronic nose. The quantitative data on the concentration of the BTEX compounds, in particular...
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Technique for reducing erosion in large-scale circulating fluidized bed units
PublikacjaThis paper presents a methodology, implemented for a real industrial-scale circulating fluidized bed boiler, to mitigate the risk of heating surfaces exposed to an intensive particle erosion process. For this purpose, a machine learning algorithm was developed to support the boiler reliability management process. Having a tool that can help mitigate the risk of uncontrolled power unit failure without expensive and technically complex...
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Multiple Cues-Based Robust Visual Object Tracking Method
PublikacjaVisual object tracking is still considered a challenging task in computer vision research society. The object of interest undergoes significant appearance changes because of illumination variation, deformation, motion blur, background clutter, and occlusion. Kernelized correlation filter- (KCF) based tracking schemes have shown good performance in recent years. The accuracy and robustness of these trackers can be further enhanced...
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Deep neural networks approach to skin lesions classification — A comparative analysis
PublikacjaThe paper presents the results of research on the use of Deep Neural Networks (DNN) for automatic classification of the skin lesions. The authors have focused on the most effective kind of DNNs for image processing, namely Convolutional Neural Networks (CNN). In particular, three kinds of CNN were analyzed: VGG19, Residual Networks (ResNet) and the hybrid of VGG19 CNN with the Support Vector Machine (SVM). The research was carried...
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Autoencoder application for anomaly detection in power consumption of lighting systems
PublikacjaDetecting energy consumption anomalies is a popular topic of industrial research, but there is a noticeable lack of research reported in the literature on energy consumption anomalies for road lighting systems. However, there is a need for such research because the lighting system, a key element of the Smart City concept, creates new monitoring opportunities and challenges. This paper examines algorithms based on the deep learning...
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Total Completion Time Minimization for Scheduling with Incompatibility Cliques
PublikacjaThis paper considers parallel machine scheduling with incompatibilities between jobs. The jobs form a graph equivalent to a collection of disjoint cliques. No two jobs in a clique are allowed to be assigned to the same machine. Scheduling with incompatibilities between jobs represents a well-established line of research in scheduling theory and the case of disjoint cliques has received increasing attention in recent...
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Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublikacjaAccurate 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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Projektowanie filtrów IIR przy zastosowaniu algorytmu ewolucyjnego
PublikacjaW pracy zaprezentowano metodę projektowania filtrów cyfrowych IIR (InfiniteImpulse Response) przy wykorzystaniu algorytmu ewolucyjnego w dwóch wariantach. W pierwszym projektowane są filtry w taki sposób, aby ich charakterystyki amplitudowe spełniały postawione założenia. W drugim wariancie przedstawiono możliwość polepszenia charakterystyk fazowych filtrów IIR. Otrzymane rezultaty są porównane z wynikami otrzymanymi podczas projektowania...
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Video Analytics-Based Algorithm for Monitoring Egress from Buildings
PublikacjaA concept and practical implementation of the algorithm for detecting of potentially dangerous situations of crowding in passages is presented. An example of such situation is a crush which may be caused by obstructed pedestrian pathway. Surveillance video camera signal analysis performed on line is employed in order to detect hold-ups near bottlenecks like doorways or staircases. The details of implemented algorithm which uses...
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SYNTHESIZING MEDICAL TERMS – QUALITY AND NATURALNESS OF THE DEEP TEXT-TO-SPEECH ALGORITHM
PublikacjaThe main purpose of this study is to develop a deep text-to-speech (TTS) algorithm designated for an embedded system device. First, a critical literature review of state-of-the-art speech synthesis deep models is provided. The algorithm implementation covers both hardware and algorithmic solutions. The algorithm is designed for use with the Raspberry Pi 4 board. 80 synthesized sentences were prepared based on medical and everyday...
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Detection, classification and localization of acoustic events in the presence of background noise for acoustic surveillance of hazardous situations
PublikacjaEvaluation of sound event detection, classification and localization of hazardous acoustic events in the presence of background noise of different types and changing intensities is presented. The methods for discerning between the events being in focus and the acoustic background are introduced. The classifier, based on a Support Vector Machine algorithm, is described. The set of features and samples used for the training of the...
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Experimental and Theoretical Insights into the Intermolecular Interactions in Saturated Systems of Dapsone in Conventional and Deep Eutectic Solvents
PublikacjaSolubility 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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Optical Coherence Tomography for nanoparticles quantitative characterization
PublikacjaThe unique features of nanocomposite materials depend on the type and size of nanoparticles, as well as their placement in the composite matrices. Therefore the nanocomposites manufacturing process requires inline control over certain parameters of nanoparticles such as dispersion and concentration. Keeping track of nanoparticles parameters inside a matrix is currently a difficult task due to lack of a fast, reliable and cost effective...
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RMS-based damage identification in adhesive joint between concrete beam and steel plate using ultrasonic guided waves
PublikacjaAdhesive joints have numerous applications in many branches of industry, such as civil engineering, automotive, aerospace and shipbuilding. As with most structural elements, adhesive joints can experience any damage mechanism, which induces the need for diagnostic testing. Ultrasonic waves are widely used for non-destructive inspection of many structures and their elements, including adhesive joints. Guided wave propagation method...