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Search results for: facial recognition, drowsiness, real-time monitoring, machine learning, neural networks, driver, fatigue
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Service time distribution influence on end-to-end call setup delay calculation in networks with Session Initiation Protocol
PublicationThe most important GoS parameter for networks with SIP protocol is end-to-end call setup delay. So far there were no coherent models allowing calculation of these parameters for networks with SIP protocol. Few models were developed but they are insufficient. In the paper we propose model which allows end-to-end call setup delay calculation for networks with SIP protocol. The model is using chain of M/G/1/K models and is applicable...
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Neural Network Application for Recognition of Geometry Degradation of Power Cycle Components
PublicationPrzedyskutowano problem rozpoznawania degradacji geometrycznej. Skuteczne zastosowanie wybranego typu sieci neuronowej (SSN) jest prezentowane w referacie. SSN wykrywająca typy degradacji geometrycznej wykazała wysoką jakość. Pokazano pewną możliwość ekstrapolacji takich SSN. Pokazano możliwość wykrywania typów degradacji geometrycznej nawet w przypadku pozyskiwania niepełnych danych pomiarowych.
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Piotr Rajchowski dr inż.
PeoplePiotr Rajchowski (Member, IEEE) was born in Poland, in 1989. He received the E.Eng., M.Sc., and Ph.D. degrees in radio communication from the Gdańsk University of Technology (Gdańsk Tech), Poland, in 2012, 2013, and 2017, respectively. Since 2013, he has been working at the Department of Radiocommunication Systems and Networks, Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, as a IT...
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Optimization-based stacked machine-learning method for seismic probability and risk assessment of reinforced concrete shear walls
PublicationEfficient seismic risk assessment aids decision-makers in formulating citywide risk mitigation plans, providing insights into building performance and retrofitting costs. The complexity of modeling, analysis, and post-processing of the results makes it hard to fast-track the seismic probabilities, and there is a need to optimize the computational time. This research addresses seismic probability and risk assessment of reinforced...
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Emotions Embodied in the SVC of an Autonomous Driver System
PublicationA concept of embodied intelligence (EI) is considered. None of such implementations can be fully identified with artificial intelligence. Projects that dare to approach AI and EI should be based on both the AI concepts (symbolic and sub-symbolic), in solving real problems of perception and decision-making. Therefore, the EI, in this paper, is understood as a methodology that uses all available resources and algorithms from the...
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Systematic Literature Review for Emotion Recognition from EEG Signals
PublicationResearchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...
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Systematic Literature Review for Emotion Recognition from EEG Signals
PublicationResearchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...
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Prediction of fracture toughness in fibre-reinforced concrete, mortar, and rocks using various Machine learning techniques
PublicationMachine Learning (ML) method is widely used in engineering applications such as fracture mechanics. In this study, twenty different ML algorithms were employed and compared for the prediction of the fracture toughness and fracture load in modes I, II, and mixed-mode (I-II) of various materials, including fibre-reinforced concrete, cement mortar, sandstone, white travertine, marble, and granite. A set of 401 specimens of “Brazilian...
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DETERMINATION OF VERTICAL DISPLACEMENTS IN RELATIVE MONITORING NETWORKS
PublicationThe problem of determining displacements of objects is an important and current issue, in particular in terms of operational safety. This is a requirement that covers geodetic, periodic control measurements in order to determine horizontal and vertical displacements. The paper is focused on the analysis of vertical displacements. Geodetic measurements and their interpretation allow to reduce the risk of possible structural catastrophes....
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System do diagnostyki dermatofitowych zakażeń powierzchniowych oparty na technice Real-Time PCR
PublicationDermatofity należą do blisko spokrewnionej grupy grzybów, które wykazują wysokie powinowactwo do skeratynizowanych tkanek. Cecha ta czyni je odpowiedzialnymi za powierzchniowe grzybice skóry, paznokci oraz włosów. Szacuje się, iż nawet do 20% ludzi na całym świecie dotkniętych jest infekcjami powodowanymi przez dermatofity. Ich leczenie wymaga długotrwałego zastosowania leków przeciwgrzybiczych. W celu dobrania odpowiedniego leczenia...
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublicationDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublicationDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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Systemy z Uczeniem Maszynowym / Systems with Machine Learning 2022/2023
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Consideration of Pseudo Strain Energy in Determination of Fatigue Life and Microdamage Healing of Asphalt Mastics
PublicationRest periods between cyclic loads can lead to recovery of damage and extension of fatigue life. This phenomenon is referred to as healing. Healing is clearly observed in bituminous materials, such as asphalt mastics, which belong to the components of asphalt mixtures. Due to the nature of road pavement traffic loading, which is characterized by series of intermittent pulses with rest periods, consideration of healing is necessary...
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Using On-line Measurement by Electronic Nose and Computer Simulations for Real-time Control at WWTP
PublicationContinuous investigation of wastewater quality can be carried out by a device called an e-nose. One important feature of the proposed real-time control system for WWTP is that using on-line measurements by e-nose together (Figure 1) with technological sets picked on this basis by means of computer models, it is possible to change treatment process parameters, depending on the current quality of wastewater. It can be used for the...
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Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble
PublicationThis paper proposes a novel approach for intelligent fault diagnosis for stroke Diesel marine engines, which are commonly used in on-road and marine transportation. The safety and reliability of a ship's work rely strongly on the performance of such an engine; therefore, early detection of any type of failure that affects the engine is of crucial importance. Automatic diagnostic systems are of special importance because they can...
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Digital measurements in monitoring of position and velocity of machine subassambly
PublicationReferat dotyczy zastosowania enkoderów z sygnałem wyjściowym kwadraturowym współdziałających z odpowiednim systemem DAQ do monitorowania przebiegu ruchu podzespołów maszyn technologicznych. Przedyskutowano podstawowe zasady konstrukcji układów do cyfrowych pomiarów prędkości i przemieszczeń.Porównano wady, zalety i ograniczenia rozdzielczości pomiaru prędkości dwoma znanymi sposobami. Omówiono własne rozwiązania zastosowane w układach...
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Monitoring of the circular saw vibrations with machine vision system.
PublicationPraca przedstawia metodologię wyznaczania drgań obracających się pił tarczowych z wykorzystaniem technik wizyjnych. Na podstawie otrzymanych wyników można wyznaczyc prędkości krytyczne piły oraz podac obszary prędkości zalecanych (najmniejsze wartości drgań poprzecznych piły).
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Machine-Learning-Powered EM-Based Framework for Efficient and Reliable Design of Low Scattering Metasurfaces
PublicationPopularity of metasurfaces has been continuously growing due to their attractive properties including the ability to effectively manipulate electromagnetic (EM) waves. Metasurfaces comprise optimized geometries of unit cells arranged as a periodic lattice to obtain a desired EM response. One of their emerging application areas is the stealth technology, in particular, realization of radar cross section (RCS) reduction. Despite...
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublicationMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
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An Improved Convolutional Neural Network for Steganalysis in the Scenario of Reuse of the Stego-Key
PublicationThe topic of this paper is the use of deep learning techniques, more specifically convolutional neural networks, for steganalysis of digital images. The steganalysis scenario of the repeated use of the stego-key is considered. Firstly, a study of the influence of the depth and width of the convolution layers on the effectiveness of classification was conducted. Next, a study on the influence of depth and width of fully connected...
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Neural network breast cancer relapse time prognosis
PublicationPrzedstawiono architekturę i wyniki testowania sztucznej sieci neuronowej w prognozowaniu czasu nawrotu choroby u kobiet chorych na raka piersi. Sieć neuronowa uczona była na danych zgromadzonych przez 20 lat. Dane opisują grupę 439 pacjentów za pomocą 40 parametrów. Spośród tych parametrów wybrano 6 najistotniejszych: liczbę przerzutowych węzłów chłonnych, wielkość guza, wiek, skalę według Blooma oraz stan receptorów estrogenowych...
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Thermal Images Analysis Methods using Deep Learning Techniques for the Needs of Remote Medical Diagnostics
PublicationRemote medical diagnostic solutions have recently gained more importance due to global demographic shifts and play a key role in evaluation of health status during epidemic. Contactless estimation of vital signs with image processing techniques is especially important since it allows for obtaining health status without the use of additional sensors. Thermography enables us to reveal additional details, imperceptible in images acquired...
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Long-distance quantum communication over noisy networks without long-time quantum memory
PublicationThe problem of sharing entanglement over large distances is crucial for implementations of quantum cryptography. A possible scheme for long-distance entanglement sharing and quantum communication exploits networks whose nodes share Einstein-Podolsky-Rosen (EPR) pairs. In Perseguers et al. [Phys. Rev. A 78, 062324 (2008)] the authors put forward an important isomorphism between storing quantum information in a dimension D and transmission...
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Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks
PublicationAge prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age verification purposes. Research on these issues is usually carried out using high-resolution X-ray scans of parts of the body, such as images of the hands or images of the chest. In this...
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MP3vec: A Reusable Machine-Constructed Feature Representation for Protein Sequences
Publication—Machine Learning (ML) methods have been used with varying degrees of success on protein prediction tasks, with two inherent limitations. First, prediction performance often depends upon the features extracted from the proteins. Second, experimental data may be insufficient to construct reliable ML models. Here we introduce MP3vec, a transferable representation for protein sequences that is designed to be used specifically for sequence-to-sequence...
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Computer Networks EN 2022
e-Learning CoursesThe student becomes familiar with the network layered logical architectures, classifies the basic problems of network communication and identifies and analyzes selected protocols and mechanisms of LAN and WAN (IP) networks.
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Computer Networks EN 2023
e-Learning CoursesThe student becomes familiar with the network layered logical architectures, classifies the basic problems of network communication and identifies and analyzes selected protocols and mechanisms of LAN and WAN (IP) networks.
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Real-Time Monnitoring of Vegetable Oils' Thermal Degradation Using Proton Transfer Reaction Mass Spectrometry
PublicationThe volatile aldehydes, which are generated during frying, can be harmful to human health, therefore the concentration of these compounds in frying fumes should be monitored. In addition, aldehydes are markers of oils’ quality, and so it is possible to determine shelf-life or suitability for frying of these oils. Commonly, in order to determine aldehydes concentration gas chromatography is performed, however it does not allow for...
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Mining inconsistent emotion recognition results with the multidimensional model
PublicationThe paper deals with the challenge of inconsistency in multichannel emotion recognition. The focus of the paper is to explore factors that might influence the inconsistency. The paper reports an experiment that used multi-camera facial expression analysis with multiple recognition systems. The data were analyzed using a multidimensional approach and data mining techniques. The study allowed us to explore camera location, occlusions...
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Towards neural knowledge DNA
PublicationIn this paper, we propose the Neural Knowledge DNA, a framework that tailors the ideas underlying the success of neural networks to the scope of knowledge representation. Knowledge representation is a fundamental field that dedicates to representing information about the world in a form that computer systems can utilize to solve complex tasks. The proposed Neural Knowledge DNA is designed to support discovering, storing, reusing,...
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OBTAINING FLUID FLOW PATTERN FOR TURBINE STAGE WITH NEURAL MODEL.
PublicationIn the paper possibility of applying neural model to obtaining patterns of proper operation for fluid flow in turbine stage for fluid-flow diagnostics is discussed. Main differences between Computational Fluid Dynamics (CFD) solvers and neural model is given, also limitations and advantages of both are considered. Time of calculations of both methods was given, also possibilities of shortening that time with preserving the accuracy...
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Application of Artificial Neural Networks in Investigations of Steam Turbine Cascades
PublicationZaprezentowano wyniki badań numerycznych zastosowania sieci neuronowych przy obliczeniach przepływów w palisadach turbin parowych. Na podstawie uzyskanych wyników wykazano, że sieci neuronowe mogą być używane do szacowania przestrzennego rozkładu parametrów przepływu, takich jak entalpia, entropia, ciśnienie czy prędkość czynnika w kanale przepływowym. Omówiono również zastosowania tego typu metod przy projektowaniu palisad, stopni...
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Forecasting of currency exchange rates using artificial neural networks
PublicationW rozdziale tym autor przedstawił wyniki swoich badań nad wykorzystaniem sztucznych sieci neuronowych do prognozowania kursu walut (na przykładzie pary walutowej PLN-USD).Głównym celem badań było porównanie skuteczności przewidywania kursu złotówki w latach 1997 - 2005 przy pomocy różnych rodzajów sieci neuronowych.
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Using neural networks to examine trending keywords in Inventory Control
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Neural networks based NARX models in nonlinear adaptive control
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Prediction of antimicrobial activity of imidazole derivatives by artificial neural networks
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Application of neural networks for description of pressure distribution in slide bearing.
PublicationBadano rozkład ciśnienia hydrodynamicznego w łożysku ślizgowym dla wybranych wariantów łożyska. Wykazano, że zastosowanie sieci neuronowych umożliwia opis rozkładu ciśnienia hydrodynamicznego z uwzględnieniem zmian geometrycznych (bezwymiarowa długość - L) i mechanicznych (mimośrodowość względem H) łożyska.
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Identification of slide bearing main parameters using neural networks.
PublicationWykazano, że sieci neuronowe jak najbardziej nadają się do identyfikacji głównych parametrów geometrycznych i ruchowych hydrodynamicznych łożysk ślizgowych.
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Estimation the rhythmic salience of sound with association rules and neural networks
PublicationW referacie przedstawiono eksperymenty mające na celu automatyczne wyszukiwanie wartości rytmicznych we frazie muzycznej. W tym celu wykorzystano metody data mining i sztuczne sieci neuronowe.
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Exploration of the Solubility Hyperspace of Selected Active Pharmaceutical Ingredients in Choline- and Betaine-Based Deep Eutectic Solvents: Machine Learning Modeling and Experimental Validation
PublicationDeep eutectic solvents (DESs) are popular green media used for various industrial, pharmaceutical, and biomedical applications. However, the possible compositions of eutectic systems are so numerous that it is impossible to study all of them experimentally. To remedy this limitation, the solubility landscape of selected active pharmaceutical ingredients (APIs) in choline chloride- and betaine-based deep eutectic solvents was...
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Lead-free bismuth-based perovskites coupled with g–C3N4: A machine learning based novel approach for visible light induced degradation of pollutants
PublicationThe use of metal halide perovskites in photocatalytic processes has been attempted because of their unique optical properties. In this work, for the first time, Pb-free Bi-based perovskites of the Cs3Bi2X9 type (X = Cl, Br, I, Cl/Br, Cl/I, Br/I) were synthesized and subjected to comprehensive morphological, structural, and surface analyses, and photocatalytic properties in the phenol degradation reaction were examined. Furthermore,...
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Real-Time Volatilomics: A Novel Approach for Analyzing Biological Samples
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Concept of web service for real-time satellite imagery dissemination
PublicationW artykule zaproponowano system upowszechniania obrazów satelitarnych w czasie niemal rzeczywistym realizujący ideę oprogramowania jako usługi. System jest złożony z 4 logicznych modułów - modułu akwizycji danych, zarządzania, serwera Web oraz klienta. Protokół zapytań WCS jest wykorzystywany jako interfejs pomiędzy większością modułów. System tworzony jest z myślą o udostępnianiu danych dla zdalnych użytkowników w formie usługi...
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Hardware Implementation of Real Time Cavity Parameters Identification System
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Real-Time Multimedia Stream data Processing in a Supercomputer Environment
PublicationRozdział opisuje doświadczenia uzyskane przez autorów podczas pracy w projekcie MAYDAY EURO 2012. Przedstawiono główny cel projektu - stworzenie systemu umożliwiającego rozwijanie i równolegle wykonywanie usług multimedialnych w środowisku klastra obliczeniowego dużej mocy. opisano tematykę przetwarzania dużej liczby strumieni multimedialnych na komputerach dużej mocy. Następnie zaprezentowano możliwości platformy KASKADA: tworzenie...
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Real-Time Aerial Mapping by Image Features Extraction and Matching
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Semantic Integration of Heterogeneous Recognition Systems
PublicationComputer perception of real-life situations is performed using a variety of recognition techniques, including video-based computer vision, biometric systems, RFID devices and others. The proliferation of recognition modules enables development of complex systems by integration of existing components, analogously to the Service Oriented Architecture technology. In the paper, we propose a method that enables integration of information...
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Load path sensitivity and multiaxial fatigue life prediction of metals under non-proportional loadings
PublicationEngineering components often operate under complex loadings, in which the variable amplitude multiaxial stresses are raised by geometric discontinuities including holes, grooves, fillets and shoulders, etc. Besides, the non-proportional loading will lead to the rotation of maximum principal stress/strain and additional fatigue damage of structural elements in service. Consequently, the multiaxial and non-proportional loading have...
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An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublicationThis study presents an advanced algorithm for selecting machine learning (ML) models for nitrous oxide (N2O) emission prediction in wastewater treatment plants (WWTPs) employing the activated sludge process. The examined ML models comprised multivariate adaptive regression spline (MARS), support vector machines (SVM), and extreme gradient boosting (XGboost). The study explores the concept that involves new criteria to select the...