Search results for: INTELLIGENT SIGNAL PROCESSING, MACHINE LEARNING, DATASETS - Bridge of Knowledge

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Search results for: INTELLIGENT SIGNAL PROCESSING, MACHINE LEARNING, DATASETS

Search results for: INTELLIGENT SIGNAL PROCESSING, MACHINE LEARNING, DATASETS

  • Classification of Sea Going Vessels Properties Using SAR Satellite Images

    Publication

    The aim of the project was to analyze the possibility of using machine learning and computer vision to identify (indicate the location) of all sea-going vessels located in the selected area of the open sea and to classify the main attributes of the vessel. The key elements of the project were to download data from the Sentinel-1 satellite [1], download data on the sea vessels [2], then automatically tag data and develop a detection...

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  • Pipelined Two-Operand Modular Adders

    Publication

    Pipelined two-operand modular adder (TOMA) is one of basic components used in digital signal processing (DSP) systems that use the residue number system (RNS). Such modular adders are used in binary/residue and residue/binary converters, residue multipliers and scalers as well as within residue processing channels. The structure of pipelined TOMAs is usually obtained by inserting an appropriate number of pipeline register layers within...

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  • Open smart glasses development platform for AAL applications

    Publication

    - Year 2017

    This paper describes an open platform for multi sensory electronic glasses that supports new and enhanced methods for intelligent interaction with patients, with smart objects, or to be used as new data input modalities like proximity sensor or smart textile interfaces. All the activities have been developed, investigated and evaluated within EU CHIST-ERA eGlasses project...

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  • Decisional DNA for modeling and reuse of experiential clinical assessments in breast cancer diagnosis and treatment

    Publication
    • E. Sanchez
    • W. Peng
    • C. Toro
    • C. Sanin
    • M. Grana
    • E. Szczerbicki
    • E. Carrasco
    • F. Guijarro
    • L. Brualla

    - NEUROCOMPUTING - Year 2014

    Clinical 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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  • Novel 5.1 Downmix Algorithm with Improved Dialogue Intelligibility

    Publication

    A new algorithm for 5.1 to stereo downmix is introduced, which addresses the problem of dialogue intelligibility. The algorithm utilizes proposed signal processing algorithms to enhance the intelligibility of movie dialogues, especially in difficult listening conditions or in compromised speaker setup. To account for the latter, a playback configuration utilizing a portable device, i.e. an ultrabook, is examined. The experiments...

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  • Remote Health Monitoring of Wind Turbines Employing Vibroacoustic Transducers and Autoencoders

    Publication

    Implementation of remote monitoring technology for real wind turbine structures designed to detect potential sources of failure is described. An innovative multi-axis contactless acoustic sensor measuring acoustic intensity as well as previously known accelerometers were used for this purpose. Signal processing methods were proposed, including feature extraction and data analysis. Two strategies were examined: Mel Frequency Cepstral...

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  • Experimental and Theoretical Screening for Green Solvents Improving Sulfamethizole Solubility

    Publication

    - Materials - Year 2021

    Solubility 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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  • Examining Influence of Distance to Microphone on Accuracy of Speech Recognition

    Publication

    The 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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  • Further Developments of the Online Sound Restoration System for Digital Library Applications

    Publication

    New signal processing algorithms were introduced to the online service for audio restoration available at the web address: www.youarchive.net. Missing or distorted audio samples are estimated using a specific implementation of the Jannsen interpolation method. The algorithm is based on the autoregressive model (AR) combined with the iterative complementation of signal samples. Since the interpolation algorithm is computationally...

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  • Karol Dziedziul dr hab.

  • Experience-Oriented Intelligence for Internet of Things

    Publication

    - CYBERNETICS AND SYSTEMS - Year 2017

    The 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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  • Detection and Mitigation of GPS Spoofing Based on Antenna Array Processing

    In 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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  • A Simplistic Downlink Channel Estimation Method for NB-IoT

    Publication

    This 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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  • MICROSEISMIC EVENT DETECTION USING DIFFERENT ALGORITHMS ON REAL DATA FROM PATCH ARRAY GEOPHONE GRID FROM EASTERN POMERANIA FRACTURING JOB

    The 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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  • Buzz-based honeybee colony fingerprint

    Non-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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  • Microgrinding with single-disk lapping kinematics.

    Publication

    - Year 2015

    Grinding 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...

  • Data-driven, probabilistic model for attainable speed for ships approaching Gdańsk harbour

    Publication

    The 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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  • A new optimal algorithm for a time-dependent scheduling problem

    In 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...

  • Examining Classifiers Applied to Static Hand Gesture Recognition in Novel Sound Mixing System

    The 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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  • Anna Czaja mgr inż.

    People

    After completing Master's studies in Computer Science (Gdansk University of Technology, Faculty of Electronics, Telecommunications and Informatics), she worked as a programmer for several years. Currently employed as an assistant at the Department of Applied Informatics in Management (Gdańsk University of Technology, Faculty of Management and Economics). Participant in third degree doctoral studies at the Faculty of Management...

  • Pomiar odpowiedzi impulsowej kanału radiowego na obszarze morskim i przybrzeżnym

    W 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...

  • Computer vision techniques applied for reconstruction of seafloor 3D images from side scan and synthetic aperture sonars data

    Publication

    The 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...

  • RSS-Based DoA Estimation for ESPAR Antennas Using Support Vector Machine

    In 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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  • LOW COST MEASUREMENT MODULE FOR MATRIX OF AMPEROMETRIC GAS SENSOR

    This 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

    Publication

    The 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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  • Improving automatic surveillance by sound analysis

    Publication

    An 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...

  • Faults and Fault Detection Methods in Electric Drives

    Publication

    The 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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  • Supply current signal and artificial neural networks in the induction motor bearings diagnostics

    Publication

    This 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...

  • Acoustic radar employing particle velocity sensors

    Publication

    - Year 2010

    A 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...

  • Novel approach to modeling spectral-domain optical coherence tomography with Monte Carlo method

    Numerical 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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  • Listening to Live Music: Life beyond Music Recommendation Systems

    Publication

    - Year 2018

    This 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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  • Comparing the Effectiveness of ANNs and SVMs in Forecasting the Impact of Traffic-Induced Vibrations on Building

    Traffic - 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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  • Technique for reducing erosion in large-scale circulating fluidized bed units

    Publication
    • J. Grochowalski
    • A. Widuch
    • S. Sładek
    • B. Melka
    • M. L. Nowak
    • A. Klimanek
    • M. Andrzejczyk
    • M. Klajny
    • L. Czarnowska
    • B. Hernik... and 3 others

    - POWDER TECHNOLOGY - Year 2023

    This 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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  • Monitoring the BTEX Volatiles during 3D Printing with Acrylonitrile Butadiene Styrene (ABS) Using Electronic Nose and Proton Transfer Reaction Mass Spectrometry

    We 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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  • PROPRIETARY SOFTWARE IN TECHNICAL HIGHER EDUCATION

    The 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

    The 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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  • Multiple Cues-Based Robust Visual Object Tracking Method

    Publication
    • B. Khan
    • A. Jalil
    • A. Ali
    • K. Alkhaledi
    • K. Mehmood
    • K. M. Cheema
    • M. Murad
    • H. Tariq
    • A. M. El-Sherbeeny

    - Electronics - Year 2022

    Visual 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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  • Asynchronous distributed state estimation based on a continuous-time stochastic model

    W 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

    Praca 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...

  • Hybrid SONIC: joint feedforward–feedback narrowband interference canceler

    SONIC (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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  • Analysis-by-synthesis paradigm evolved into a new concept

    This 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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  • Deep neural networks approach to skin lesions classification — A comparative analysis

    The 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

    Publication

    - IEEE Access - Year 2023

    Detecting 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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  • Modeling of multi-cavity Fabry-Perot optical fiber sensors

    Publication

    - Year 2015

    Reflectance 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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  • Application of Multiplicative Drift Correction and Component Correction methods on simulated gas sensor array responses

    Publication

    Sensor 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...

  • Special Issue: “Non-Destructive Testing of Structures”

    Publication

    - Materials - Year 2020

    The 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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  • Total Completion Time Minimization for Scheduling with Incompatibility Cliques

    Publication

    - Year 2021

    This 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

    Publication

    - Scientific Reports - Year 2023

    Accurate 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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  • Experimental and Theoretical Insights into the Intermolecular Interactions in Saturated Systems of Dapsone in Conventional and Deep Eutectic Solvents

    Publication

    - MOLECULES - Year 2024

    Solubility 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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  • Detection, classification and localization of acoustic events in the presence of background noise for acoustic surveillance of hazardous situations

    Evaluation 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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