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Search results for: NATURAL PIGMENTS
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Processing of musical data employing rough sets and artificial neural networks
PublicationArtykuł opisuje założenia systemu automatycznej identyfikacji muzyki i dźwięków muzycznych. Dokonano przeglądu standardu MPEG-7, ze szczególnym naciskiem na parametry opisowe dźwięku. Przedyskutowano problemy analizy danych audio, związane z zastosowaniami wykorzystującymi MPEG-7. W oparciu o eksperymenty przedstawiono efektywność deskryptorów niskiego poziomu w automatycznym rozpoznawaniu dźwięków instrumentów muzycznych. Przedyskutowano...
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Artificial Neural Network-Based Sensorless Nonlinear Control Of Induction Motors
PublicationW niniejszym artykule przedstawiono strukturę sztucznej sieci neuronowej służącej do korygowania działania układu estymacji prędkości kątowej wirnika. Odtworzona prędkość kątowa wirnika zostały wykorzystane w bezczujnikowym układzie sterowania silnikiem indukcyjnym pracującym w zamkniętej pętli sprzężenia prędkościowego.Przedstawiono wyniki badań eksperymentalnych z silnikiem o mocy 1,1kW.
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Estimation of musical sound separation algorithm effectiveness employing neural networks.
PublicationŚlepa separacja dźwięków sygnałów muzycznych zawartych w zmiksowanym materiale jest trudnym zadaniem. Jest to spowodowane tym, że dźwięki znajdujące się w relacjach harmonicznych mogą zawierać kolidujące składowe sinusoidalne (składowe harmoniczne). Ewaluacja wyników separacji jest również problematyczna, gdyż analiza błędu energetycznego często nie odzwierciedla subiektywnej jakości odseparowanych sygnałów. W tej publikacji zostały...
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A neural network based system for soft fault diagnosis in electronic circuits
PublicationW artykule przedstawiono system do diagnostyki uszkodzeń parametrycznych w układach elektronicznych. W systemie zaimplementowano słownikową metodę lokalizacji uszkodzeń, bazującą na pomiarach w dziedzinie częstotliwości przeprowadzanych za pomocą analizatora transmitancji HP4192A. Rozważono główne etapy projektowania systemu: definiowanie modelu uszkodzeń, wybór optymalnych częstotliwosci pomiarowych, ekstrakcję cech diagnostycznych,...
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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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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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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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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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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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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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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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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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Thermoplastic polyurethanes derived from petrochemical or renewable resources: A comprehensive review
PublicationThermoplastic polyurethanes (TPUs) materials are obtained by the reaction of polyol (ether-, ester-, and carbonate-based diols with average molecular weight in the range from 1,000 to 3,000 g/mol) with aliphatic or aromatic diisocyanates. Synthesized materials consist of the hard and soft segments which are separated in different level. All mechanical and thermal properties of TPUs depend on the chemical structure of used monomers,...
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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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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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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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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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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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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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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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Optimum Geometry and Stress Control of Deformed Double Layer Dome for Gravity and Lateral Loads
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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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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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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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Wybrane wiadomości z etnobotaniki i etnofarmacji. Karty z dziejów lecznictwa naturalnego [Selected issues from ethnobotany and ethno-pharmacy. Pages from the history of natural medicine]
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A multi-analytical approach to the characterization of natural organic dyestuffs and inorganic substrates present in the 19th-century artistic oil paints manufactured by a French art materials supplier Richard Aines
PublicationThis paper presents a comprehensive analysis of artistic paints produced in the 19th century by a French art materials supplier Richard Ain`es. Improved mild extraction with hydrofluoric acid enabled the observation of intact organic dyes. Reversed-phase liquid chromatography with diode-array and mass spectrometry detection was utilised for the identification of 35 dyes present in yellow and red paint samples, and in selected plant...
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Distinct hippocampal-prefrontal neural assemblies coordinate memory encoding, maintenance, and recall
PublicationShort-term memory enables incorporation of recent experience into subsequent decision-making. This processing recruits both the prefrontal cortex and hippocampus, where neurons encode task cues, rules, and outcomes. However, precisely which information is carried when, and by which neurons, remains unclear. Using population decoding of activity in rat medial prefrontal cortex (mPFC) and dorsal hippocampal CA1, we confirm that mPFC...
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System for monitoring road slippery based on CCTV cameras and convolutional neural networks
PublicationThe slipperiness of the surface is essential for road safety. The growing number of CCTV cameras opens the possibility of using them to automatically detect the slippery surface and inform road users about it. This paper presents a system of developed intelligent road signs, including a detector based on convolutional neural networks (CNNs) and the transferlearning method employed to the processing of images acquired with video...
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Highlighting interlanguage phoneme differences based on similarity matrices and convolutional neural network
PublicationThe goal of this research is to find a way of highlighting the acoustic differences between consonant phonemes of the Polish and Lithuanian languages. For this purpose, similarity matrices are employed based on speech acoustic parameters combined with a convolutional neural network (CNN). In the first experiment, we compare the effectiveness of the similarity matrices applied to discerning acoustic differences between consonant...
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PTD4 Peptide Increases Neural Viability in an In Vitro Model of Acute Ischemic Stroke
PublicationIschemic stroke is a disturbance in cerebral blood flow caused by brain tissue ischemia and hypoxia. We optimized a multifactorial in vitro model of acute ischemic stroke using rat primary neural cultures. This model was exploited to investigate the pro-viable activity of cell-penetrating peptides: arginine-rich Tat(49–57)-NH2 (R49KKRRQRRR57-amide) and its less basic analogue, PTD4 (Y47ARAAARQARA57-amide). Our model included glucose...
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Neural Oscillation During Mental Imagery in Sport: An Olympic Sailor Case Study
PublicationThe purpose of the current study was to examine the cortical correlates of imagery depending on instructional modality (guided vs. self-produced) using various sports-related scripts. According to the expert-performance approach, we took an idiosyncratic perspective analyzing the mental imagery of an experienced two-time Olympic athlete to verify whether different instructional modalities of imagery (i.e., guided vs. self-produced)...
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Development of a tropical disease diagnosis system using artificial neural network and GIS
PublicationExpert systems for diagnosis of tropical diseases have been developed and implemented for over a decade with varying degrees of success. While the recent introduction of artificial neural networks has helped to improve the diagnosis accuracy of such systems, this aspect is still negatively affected by the number of supported diseases. A large number of supported diseases usually corresponds to a high number of overlapping symptoms,...
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Heavy duty vehicle fuel consumption modelling using artificial neural networks
PublicationIn this paper an artificial neural network (ANN) approach to modelling fuel consumption of heavy duty vehicles is presented. The proposed method uses easy accessible data collected via CAN bus of the truck. As a benchmark a conventional method, which is based on polynomial regression model, is used. The fuel consumption is measured in two different tests, performed by using a unique test bench to apply the load to the engine. Firstly,...
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Physics-guided neural networks (PGNNs) to solve differential equations for spatial analysis
PublicationNumerous examples of physically unjustified neural networks, despite satisfactory performance, generate contradictions with logic and lead to many inaccuracies in the final applications. One of the methods to justify the typical black-box model already at the training stage and lead to many inaccuracies in the final applications. One of the methods to justify the typical black-box model already at the training stage involves extending...
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Neural modelling of dynamic systems with time delays based on an adjusted NEAT algorithm
PublicationA problem related to the development of an algorithm designed to find an architecture of artificial neural network used for black-box modelling of dynamic systems with time delays has been addressed in this paper. The proposed algorithm is based on a well-known NeuroEvolution of Augmenting Topologies (NEAT) algorithm. The NEAT algorithm has been adjusted by allowing additional connections within an artificial neural network and...
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Can architecture be 11-dimensional? The nature of space in the architecture of the digital world era
PublicationThis research aims to explore the development of architectural theories about ‘architectural dimensions’ and look at architecture as a multidimensional space. It is important to understand that with today's development of virtual reality technology and through the combination of theories of physics and architecture, a new possibility of creating space has emerged. The arguments are made through inductive reasoning and grounded...
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Diagnosing wind turbine condition employing a neural network to the analysis of vibroacoustic signals
PublicationIt is important from the economic point of view to detect damage early in the wind turbines before failures occur. For this purpose, a monitoring device was built that analyzes both acoustic signals acquired from the built-in non-contact acoustic intensity probe, as well as from the accelerometers, mounted on the internal devices in the nacelle. The signals collected in this way are used for long-term training of the autoencoder...
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Benchmarking Deep Neural Network Training Using Multi- and Many-Core Processors
PublicationIn the paper we provide thorough benchmarking of deep neural network (DNN) training on modern multi- and many-core Intel processors in order to assess performance differences for various deep learning as well as parallel computing parameters. We present performance of DNN training for Alexnet, Googlenet, Googlenet_v2 as well as Resnet_50 for various engines used by the deep learning framework, for various batch sizes. Furthermore,...
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Supply current signal and artificial neural networks in the induction motor bearings diagnostics
PublicationThis 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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Self-organizing Artificial Neural Networks into Hydrographic Big Data Reduction Process
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Artificial Neural Networks in Classification of Steel Grades Based on Non-Destructive Tests
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Designing the Composition of Cement Stabilized Rammed Earth Using Artificial Neural Networks
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The Influence of Input Data Standardization Method on Prediction Accuracy of Artificial Neural Networks
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Towards bees detection on images: study of different color models for neural networks
PublicationThis paper presents an approach to bee detection in videostreams using a neural network classifier. We describe the motivationfor our research and the methodology of data acquisition. The maincontribution to this work is a comparison of different color models usedas an input format for a feedforward convolutional architecture appliedto bee detection. The detection process has is based on a neural...
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Application 2D Descriptors and Artificial Neural Networks for Beta-Glucosidase Inhibitors Screening
PublicationBeta-glucosidase inhibitors play important medical and biological roles. In this study, simple two-variable artificial neural network (ANN) classification models were developed for beta-glucosidase inhibitors screening. All bioassay data were obtained from the ChEMBL database. The classifiers were generated using 2D molecular descriptors and the data miner tool available in the STATISTICA package (STATISTICA Automated Neural...
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In Search of Panacea—Review of Recent Studies Concerning Nature-Derived Anticancer Agents
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Accuracy Investigations of Turbine Blading Neural Models Applied to Thermal and Flow Diagnostics
PublicationPossibility of replacing computional fluid dynamics simulations by a neural model for fluid flow and thermal diagnostics of steam turbines is investigated. Results of calculations of velocity magnitude of steam for 3D model of the stator of steam turbine is presented.
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Leveraging Training Strategies of Artificial Neural Network for Classification of Multiday Electromyography Signals
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