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Search results for: NATURAL SWEETENERS
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Accidental wow evaluation based on sinusoidal modeling and neural nets prediction
PublicationReferat przedstawia opis algorytmu do określenia charakterystyki zniekształcenia kołysania dźwięku. Prezentowane podejście wykorzystuje sinusoidalną analizę dźwięku bazującą zarówno na amplitudowym jak i fazowym widmie sygnału fonicznego. Trajektorie poszczególnych składowych tonalnych, obrazujące zniekształcenie kołysania, określane są na podstawie analizy ich chwilowych amplitud, częstotliwości i faz. Dodatkowo referat przedstawia...
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Artificial Neural Networks for Prediction of Antibacterial Activity in Series of Imidazole Derivatives
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Multisensor Tracking of Marine Targets - Decentralized Fusion of Kalman and Neural Filters
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Use of Neural Networks in Diagnostics of Rolling-Element Bearing of the Induction Motor
PublicationBearing defect is statistically the most frequent cause of an induction motor fault. The research described in the paper utilized the phenomenon of the current change in the induction motor with bearing defect. Methods based on the analysis of the supplying current are particularly useful when it is impossible to install diagnostic devices directly on the motor. The presented method of rolling-element bearing diagnostics used indirect...
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ReFlexeNN - the Wearable EMG Interface with Neural Network Based Gesture Classification
PublicationThe electromyographic activity of muscles was measured using a wireless biofeedback device. The aim of the study was to examine the possibility of creating an automatic muscle tension classifier. Several measurement series were conducted and the participant performed simple physical exercises - forcing the muscle to increase its activity accordingly to the selected scale. A small wireless device was attached to the electrodes placed...
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Toward Intelligent Vehicle Intrusion Detection Using the Neural Knowledge DNA
PublicationIn this paper, we propose a novel intrusion detection approach using past driving experience and the neural knowledge DNA for in-vehicle information system security. The neural knowledge DNA is a novel knowledge representation method designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing systems. We examine our approach for classifying malicious vehicle control commands...
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Neural Networks in the Diagnostics Process of Low-Power Solar Plant Devices
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From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublicationRecently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...
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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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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublicationIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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Deep neural networks approach to skin lesions classification — A comparative analysis
PublicationThe 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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Adjusted SpikeProp algorithm for recurrent spiking neural networks with LIF neurons
PublicationA problem related to the development of a supervised learning method for recurrent spiking neural networks is addressed in the paper. The widely used Leaky-Integrate-and-Fire model has been adopted as a spike neuron model. The proposed method is based on a known SpikeProp algorithm. In detail, the developed method enables gradient descent learning of recurrent or multi-layer feedforward spiking neural networks. The research included...
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Efficient uncertainty quantification using sequential sampling-based neural networks
PublicationUncertainty quantification (UQ) of an engineered system involves the identification of uncertainties, modeling of the uncertainties, and the forward propagation of the uncertainties through a system analysis model. In this work, a novel surrogate-based forward propagation algorithm for UQ is proposed. The proposed algorithm is a new and unique extension of the recent efficient global optimization using neural network (NN)-based...
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Constrained aerodynamic shape optimization using neural networks and sequential sampling
PublicationAerodynamic shape optimization (ASO) involves computational fluid dynamics (CFD)-based search for an optimal aerodynamic shape such as airfoils and wings. Gradient-based optimization (GBO) with adjoints can be used efficiently to solve ASO problems with many design variables, but problems with many constraints can still be challenging. The recently created efficient global optimization algorithm with neural network (NN)-based prediction...
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From Scores to Predictions in Multi-Label Classification: Neural Thresholding Strategies
PublicationIn this paper, we propose a novel approach for obtaining predictions from per-class scores to improve the accuracy of multi-label classification systems. In a multi-label classification task, the expected output is a set of predicted labels per each testing sample. Typically, these predictions are calculated by implicit or explicit thresholding of per-class real-valued scores: classes with scores exceeding a given threshold value...
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Comparison of the Ability of Neural Network Model and Humans to Detect a Cloned Voice
PublicationThe vulnerability of the speaker identity verification system to attacks using voice cloning was examined. The research project assumed creating a model for verifying the speaker’s identity based on voice biometrics and then testing its resistance to potential attacks using voice cloning. The Deep Speaker Neural Speaker Embedding System was trained, and the Real-Time Voice Cloning system was employed based on the SV2TTS, Tacotron,...
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Evaluation of Facial Pulse Signals Using Deep Neural Net Models
PublicationThe reliable measurement of the pulse rate using remote photoplethysmography (PPG) is very important for many medical applications. In this paper we present how deep neural networks (DNNs) models can be used in the problem of PPG signal classification and pulse rate estimation. In particular, we show that the DNN-based classification results correspond to parameters describing the PPG signals (e.g. peak energy in the frequency...
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Bees Detection on Images: Study of Different Color Models for Neural Networks
PublicationThis paper presents an approach to bee detection in video streams using a neural network classifier. We describe the motivation for our research and the methodology of data acquisition. The main contribution to this work is a comparison of different color models used as an input format for a feedforward convolutional architecture applied to bee detection. The detection process has is based on a neural binary classifier that classifies...
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Working in harmony with nature. Green office buildings in a present-day city
PublicationMetropolis - as main point of people's migration, mostly because of work, have to face sustainable development as a strategy for the near future. This article describes possible ways leading to the best office building concepts in the design process. Searching for a workspace in harmony with nature is one of the aspects of a balanced development. The challenge is to create functional, compact, environmentally friendly and healthy...
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Comparative study of neural networks used in modeling and control of dynamic systems
PublicationIn this paper, a diagonal recurrent neural network that contains two recurrent weights in the hidden layer is proposed for the designing of a synchronous generator control system. To demonstrate the superiority of the proposed neural network, a comparative study of performances, with two other neural network (1_DRNN) and the proposed second-order diagonal recurrent neural network (2_DRNN). Moreover, to confirm the superiority...
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Czy można budować morskie obiekty hydrotechniczne wspólnie z naturą?
PublicationOmówiono ideę proekologicznego budowania kanału żeglugowego przez Mierzeję Wiślaną. Przeanalizowano przeobrażenia środowiska przyrodniczego mierzei oraz przedstawiono propozycje proekologicznych rozwiązań konstrukcyjno - technologicznych budowy kanału żeglugowego. Omówiono także sposoby minimalizacji i kompensacji strat środowiskowych związanych z budową kanału żeglugowego.
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Applying artificial neural networks for modelling ship speed and fuel consumption
PublicationThis paper deals with modelling ship speed and fuel consumption using artificial neural network (ANN) techniques. These tools allowed us to develop ANN models that can be used for predicting both the fuel consumption and the travel time to the destination for commanded outputs (the ship driveline shaft speed and the propeller pitch) selected by the ship operator. In these cases, due to variable environmental conditions, making...
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Emotion Recognition from Physiological Channels Using Graph Neural Network
PublicationIn recent years, a number of new research papers have emerged on the application of neural networks in affective computing. One of the newest trends observed is the utilization of graph neural networks (GNNs) to recognize emotions. The study presented in the paper follows this trend. Within the work, GraphSleepNet (a GNN for classifying the stages of sleep) was adjusted for emotion recognition and validated for this purpose. The...
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Iterative Global Sensitivity Analysis Algorithm with Neural Network Surrogate Modeling
PublicationGlobal sensitivity analysis (GSA) is a method to quantify the effect of the input parameters on outputs of physics-based systems. Performing GSA can be challenging due to the combined effect of the high computational cost of each individual physics-based model, a large number of input parameters, and the need to perform repetitive model evaluations. To reduce this cost, neural networks (NNs) are used to replace the expensive physics-based...
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Hierarchical 2-step neural-based LEGO bricks detection and labeling
PublicationLEGO bricks are extremely popular and allow the creation of almost any type of construction due to multiple shapes available. LEGO building requires however proper brick arrangement, usually done by shape. With over 3700 different LEGO parts this can be troublesome. In this paper, we propose a solution for object detection and annotation on images. The solution is designed as a part of an automated LEGO bricks arrangement. The...
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Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets
PublicationArtificial Neural Network (ANN) models, specifically Convolutional Neural Networks (CNN), were applied to extract emotions based on spectrograms and mel-spectrograms. This study uses spectrograms and mel-spectrograms to investigate which feature extraction method better represents emotions and how big the differences in efficiency are in this context. The conducted studies demonstrated that mel-spectrograms are a better-suited...
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A Comprehensive Analysis of Deep Neural-Based Cerebral Microbleeds Detection System
PublicationMachine learning-based systems are gaining interest in the field of medicine, mostly in medical imaging and diagnosis. In this paper, we address the problem of automatic cerebral microbleeds (CMB) detection in magnetic resonance images. It is challenging due to difficulty in distinguishing a true CMB from its mimics, however, if successfully solved it would streamline the radiologists work. To deal with this complex three-dimensional...
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An Automated Method for Biometric Handwritten Signature Authentication Employing Neural Networks
PublicationHandwriting biometrics applications in e-Security and e-Health are addressed in the course of the conducted research. An automated graphomotor analysis method for the dynamic electronic representation of the handwritten signature authentication was researched. The developed algorithms are based on dynamic analysis of electronically handwritten signatures employing neural networks. The signatures were acquired with the use of the...
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Application of the neural networks for developing new parametrization of the Tersoff potential for carbon
PublicationPenta-graphene (PG) is a 2D carbon allotrope composed of a layer of pentagons having sp2- and sp3-bonded carbon atoms. A study carried out in 2018 has shown that the parameterization of the Tersoff potential proposed in 2005 by Ehrhart and Able (T05 potential) performs better than other potentials available for carbon, being able to reproduce structural and mechanical properties of the PG. In this work, we tried to improve the...
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Face with Mask Detection in Thermal Images Using Deep Neural Networks
PublicationAs the interest in facial detection grows, especially during a pandemic, solutions are sought that will be effective and bring more benefits. This is the case with the use of thermal imaging, which is resistant to environmental factors and makes it possible, for example, to determine the temperature based on the detected face, which brings new perspectives and opportunities to use such an approach for health control purposes. The...
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Application of Artificial Neural Networks to Predict Insulation Properties of Lightweight Concrete
PublicationPredicting the properties of concrete before its design and application process allows for refining and optimizing its composition. However, the properties of lightweight concrete are much harder to predict than those of normal weight concrete, especially if the forecast concerns the insulating properties of concrete with artificial lightweight aggregate (LWA). It is possible to use porous aggregates and precisely modify the composition...
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Neural Approximators for Variable-Order Fractional Calculus Operators (VO-FC)
PublicationThe paper presents research on the approximation of variable-order fractional operators by recurrent neural networks. The research focuses on two basic variable-order fractional operators, i.e., integrator and differentiator. The study includes variations of the order of each fractional operator. The recurrent neural network architecture based on GRU (Gated Recurrent Unit) cells functioned as a neural approximation for selected...
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Modeling of Surface Roughness in Honing Processes by UsingFuzzy Artificial Neural Networks
PublicationHoning processes are abrasive machining processes which are commonly employed to improve the surface of manufactured parts such as hydraulic or combustion engine cylinders. These processes can be employed to obtain a cross-hatched pattern on the internal surfaces of cylinders. In this present study, fuzzy artificial neural networks are employed for modeling surface roughness parameters obtained in finishing honing operations. As...
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Nature Nanotechnology
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Numerical Analysis of an Impact of Planned Location of Sewage Discharge on Natura 2000 Areas – The Dead Vistula Region Case Study
PublicationThis article presents results of an analysis of impact of a designed discharge of contaminated water into the Dead Vistula (Wisła Martwa) in the region of the Isthmus (Przesmyk) with the aim of determination of a possible effect of the pollution onto protected areas of Natura 2000 (bird habitats and sites, especially the Bird Paradise – Ptasi Raj) nature reserve. The analysis was conducted on the basis of the two-dimensional modelling...
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Membrane separation processes for the extraction and purification of steviol glycosides: an overview
PublicationSteviol glycosides (SGs), as natural sweeteners from Stevia rebaudiana, are currently employed for replacing sugar and its derivatives in several food products and formulations. Such compounds play an essential role in human health. Their usage provides a positive effect on preventing diseases related to sugar consumption, including diabetes mellitus, cancer, and lipid metabolism disorders. The traditional extraction of SGs is...
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The effect of transglutaminase or 1-ethyl-3-(3-dimethyl amino propyl) carbodimide (EDC) on the properties of two-component films fromfish-skin gelatin and other natural polymers
PublicationBadania dotyczą wpływu transglutaminazy na rozpuszczalność, właściwości mechaniczne oraz przepuszczalność pary wodnej dwuskładnikowych folii z żelatyny rybnej z dodatkiem kazeiny, białek soi, białek jaja kurzego lub pektyn. Dla porównania przeprowadzono równolegle modyfikacje chemiczne przy użyciu EDC.
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Selectivity Tuning by Natural Deep Eutectic Solvents (NADESs) for Extraction of Bioactive Compounds from Cytinus hypocistis—Studies of Antioxidative, Enzyme-Inhibitive Properties and LC-MS Profiles
PublicationIn the present study, the extracts of Cytinus hypocistis (L.) L using both traditional solvents (hexane, ethyl acetate, dichloromethane, ethanol, ethanol/water, and water) and natural deep eutectic solvents (NADESs) were investigated in terms of their total polyphenolic contents and antioxidant and enzyme-inhibitive properties. The extracts were found to possess total phenolic and total flavonoid contents in the ranges of 26.47–186.13...
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Optimum Geometry and Stress Control of Deformed Double Layer Dome for Gravity and Lateral Loads
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Study of free convective boundary layer of isothermal lateral surface of axisymmetrical horizontal body
PublicationPrzedstawiono rozwiązanie równań Naviera-Stokesa i Fouriera-Kirchhoffa we współrzędnych tau i sigma. Pierwsza jest styczną a druga normalną do konwekcyjnych linii prądu, wzdłuż jakich porusza się ogrzany od powierzchni płyn. Wynik w postaci równania na grubość warstwy przyściennej zweryfikowano dla granicznych przypadków ciała obrotowego o poziomej osi symetrii (stożka poziomego i kołowej pionowej płyty).
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Musical instrument sound separation methods supported by artificial nueural network decision system
PublicationRozprawa doktorska (27 czerwica 2006).Celem prowadzonych prac badawczych było opracowanie algorytmów separacji dźwięków instrumentów muzycznych. Dodatkowo dobrano zestaw parametrów tak aby możliwe było wytrenowanie sztucznej sieci neuronowej w celu automatycznego rozpoznawania odseparowanych sygnałów. Zaproponowano również aby algorytm decyzyjny odpowiedzialny za klasyfikacje dźwięków pełnił funkcję automatycznej metody oceny algorytmów...
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Initial value problems for neutral fractional differential equations involving a Riemann-Liouville derivative
PublicationBadano równania neutralne typu ułamkowego z odchylonym argumentem. Podano warunki dostateczne na istnienie jednego rozwiązania.
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Multilevel inverter neutral-point voltage sensor diagnostic based on the Extended Kalman Filter
PublicationA new algorithm for neutral point voltage imbalance estimation in DC link of the three-level (3L) neutral point clamped (NPC) voltage source inverter (VSI) is proposed. Application of the proposed algorithm does not require any additional sensors. The unbalanced voltage calculation is based on the information derived from the inverter output measured currents and from the knowledge of the load model parameters. In order to estimate...
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Behaviour of asphalt concrete in cyclic and static compression creep test with and without lateral confinement
PublicationArtykuł przedstawia wpływ metodyki badań na określanie parametrów betonu asfaltowego. Wykazano, że badania pełzania bez skrępowania bocznego w większym stopniu uwypuklają wpływ asfaltu na parametry badanego betonu asfaltowego natomiast w badaniach ze skrępowaniem bocznym, zarówno rola asfaltu jak i szkieletu mineralnego jest uwzględniana przy ocenie parametrów betonu asfaltowego. Ponadto wykazano, że lepszymi miarami do oceny betonu...
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Cyclic analysis of thermal impedance of a passive layer of aluminium in a neutral borate buffer solution
PublicationW pracy przedstawiono wyniki badań warstwy pasywnej tworzącej się na stopie 1050 A w warunkach zmieniającej się temperatury. Zmiany realizowano w sposób cykliczny zwiększając a następnie zmniejszając temperaturę. W czasie zmian temperatury prowadzono badania metodę dynamicznej elektrochemicznej spektroskopii impedancyjnej. Stwierdzono największe zmiany parametrów elektrycznego schematu zastępczego w czasie pierwszego cyklu zmian....
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Synthesis, structure and magnetic properties of neutral Ni(II) tri-tert-butoxysilanethiolate cluster
PublicationNowy klaster niklu(II) [Ni6(μ-O)6{SSi(tBuO)3}6(H2O)6(NH3)4] został otrzymany w reakcji NiCl2·6H2O z tri-tert-butoksysilanotiolu i amoniakiem w roztworze wodnym. Pomiary właściwości magnetycznych badanego związku pokazują obecność silnych antyferromagnetycznych oddziaływań pomiędzy centrami metalicznymi.
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Działania firm w organizacji EURO 2012 w rejonie Gdańska a środowisko naturalne
PublicationW pracy przedstawiono analizę wpływu działalności przedsiębiorców w przygotowaniach do turnieju finałowego mistrzostw Europy w roku 2012 w Gdańsku. Omówiono aktualny stan gospodarki wodno-ściekowej oraz gospodarki odpadami w rejonie Trójmiasta i stwierdzono brak zagrożeń dla środowiska naturalnego związanych z działalnością firm przed i w trakcie Euro 2012. Przedstawiono również zagadnienia związane z klimatem Gdańska i określono...
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Spatial expansion of the symmetrical objects point clouds to the lateral surface of the cylinder – Mathematical model
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Indoor Air Quality and Thermal Comfort in Naturally Ventilated Low-Energy Residential Houses
PublicationRozdział omawia jakość powietrza i termiczny komfort w naturalnie wentylowanych energooszczędnych budynkach mieszkalnych. Obliczenia wykonano metoda elementów skończonych dla wentylacji naturalnej. Uwzględniono 2 różne położenia wlotów powietrza oraz system grzewczy kaloryferowy i podłogowy. Wyniki MES porównano z doświadczeniami.
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Jerzy Kowalski dr hab. inż.
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