Search
Filters
total: 9335
filtered: 6760
-
Catalog
Chosen catalog filters
displaying 1000 best results Help
Search results for: TIME SERIES CLASSIFICATIONLEARNING SYSTEMSCAPSULE NETWORKSDATA MININGMULTI-HEAD CONVOLUTIONAL NEURAL NETWORKSSIGNAL PROCESSING
-
VALIDATION OF A THREE-DIMENSIONAL HEAD PHANTOM FOR IMAGING DATA
Publication -
Methodology for Processing of 3D Multibeam Sonar Big Data for Comparative Navigation
PublicationAutonomous navigation is an important task for unmanned vehicles operating both on the surface and underwater. A sophisticated solution for autonomous non-global navigational satellite system navigation is comparative (terrain reference) navigation. We present a method for fast processing of 3D multibeam sonar data to make depth area comparable with depth areas from bathymetric electronic navigational charts as source maps during...
-
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...
-
Thermal Image Processing for Respiratory Estimation from Cubical Data with Expandable Depth
PublicationAs healthcare costs continue to rise, finding affordable and non-invasive ways to monitor vital signs is increasingly important. One of the key metrics for assessing overall health and identifying potential issues early on is respiratory rate (RR). Most of the existing methods require multiple steps that consist of image and signal processing. This might be difficult to deploy on edge devices that often do not have specialized...
-
The OptD-multi method in LiDAR processing
PublicationNew and constantly developing technology for acquiring spatial data, such as LiDAR (light detection and ranging), is a source for large volume of data. However, such amount of data is not always needed for developing the most popular LiDAR products: digital terrain model (DTM) or digital surface model. Therefore, in many cases, the number of contained points are reduced in the pre-processing stage. The degree of reduction is determined...
-
Imidazolium ionic liquids in mineral processing
PublicationImidazoliowe ciecze jonowe (ILs) stanowią nową klasę związków o szerokich możliwościach przemysłowego zastosowania. Z przeglądu dostępnej literatury wynika, że ILs mogłyby zostać wykorzystane do odzysku i oczyszczania metali ze środowiska wodnego oraz rud w procesach ługowania, ekstarkcji rozpuszczalnikowej oraz w procesach elektrochemicznych. Pochodne imidazoliowe mogą być wykorzystywane zarówno jako rozpuszczalniki jak i aktywne...
-
Temporal Changes in Complexity of Cardiovascular Regulation during Head-Up Tilt Test by Entropic Measures of Fluctuations of Heart Period Intervals and Systolic Blood Pressure
PublicationTemporal changes in complexity of cardiovascular regulation during head-up tilt test by entropic measures of fluctuations of heart period intervals and systolic blood pressure
-
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...
-
A Bayesian regularization-backpropagation neural network model for peeling computations
PublicationA Bayesian regularization-backpropagation neural network (BRBPNN) model is employed to predict some aspects of the gecko spatula peeling, viz. the variation of the maximum normal and tangential pull-off forces and the resultant force angle at detachment with the peeling angle. K-fold cross validation is used to improve the effectiveness of the model. The input data is taken from finite element (FE) peeling results. The neural network...
-
Time-scale modification of speech signals for supporting hearing impaired schoolchildren
PublicationA study of time scale modification algorithmsapplied to hearing impaired schoolchildren supporting ispresented. Variety of algorithms are considered, namely:overlap and add, two variations of synchronized overlapand add, and the phase vocoder. Their effectiveness as wellas real-time processing capabilities are examined.
-
Total Completion Time Minimization for Scheduling with Incompatibility Cliques
PublicationThis 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...
-
Neural Network-Based Sequential Global Sensitivity Analysis Algorithm
PublicationPerforming global sensitivity analysis (GSA) can be challenging due to the combined effect of the high computational cost, but it is also essential for engineering decision making. To reduce this cost, surrogate modeling such as neural networks (NNs) are used to replace the expensive simulation model in the GSA process, which introduces the additional challenge of finding the minimum number of training data samples required to...
-
Relativistic hydrodynamics on graphics processing units
Publication -
Probe signal processing for channel estimation in underwater acoustic communication system
PublicationUnderwater acoustic communication channels are characterized by a large variety of propagation conditions. Designing a reliable communication system requires knowledge of the transmission parameters of the channel, namely multipath delay spread, Doppler spread, coherence time, and coherence bandwidth. However, the possibilities of its estimation in a realtime underwater communication system are limited, mainly due to the computational...
-
Metamaterial-Based Series-Fed Antenna with High Gain and Wideband Performance for Millimeter Wave Spectrum Applications
PublicationThis paper presents a high-gain, wideband series-fed antenna designed for 5G millimeter-wave (MMW) applications. The structure employs a substrate-integrated waveguide (SIW)-based power splitter and metamaterials (MMs). The power divider functions effectively at 27.5 GHz, exhibiting an impedance bandwidth from 26.9–28.6 GHz. The series-fed dipole is assembled on the SIW-based power splitter, incorporating four dipoles with varying...
-
An Analysis of Neural Word Representations for Wikipedia Articles Classification
PublicationOne of the current popular methods of generating word representations is an approach based on the analysis of large document collections with neural networks. It creates so-called word-embeddings that attempt to learn relationships between words and encode this information in the form of a low-dimensional vector. The goal of this paper is to examine the differences between the most popular embedding models and the typical bag-of-words...
-
Analog CMOS processor for early vision processing with highly reduced power consumption
PublicationA new approach to an analog ultra-low power visionchip design is presented. The prototype chip performs low-levelconvolutional image processing algorithms in real time. Thecircuit is implemented in 0.35 μm CMOS technology, contains64 x 64 SIMD matrix with embedded analogue processors APE(Analogue Processing Element). The photo-sensitive-matrix is of2.2 μm x 2.2 μm size, giving the density of 877 processors permm2. The matrix dissipates...
-
Processing data on sea bottom structure obtained by means of the parametric sounding
PublicationThe aim of the paper is to analyze data obtain during sounding of the Gdansk Bay by means of the parametric sonar. The accuracy of the sea bottom structure investigation needs the correct configuration of research equipment and the proper calibration of peripheral devices (GPS, heading sensor, motion sensor MRU-Z and navigation units) which provide necessary data to bathymetrical measurement system enabling its work with whole...
-
Processing data on sea bottom structure obtained by means of the parametric sounding
PublicationThe aim of the paper is to analyze data obtained during sounding the Gdansk Bay sea bed by means of the parametric echo-sounder. The accuracy of the sea bottom structure investigation needs correct configuration of research equipment and proper calibration of peripheral devices (GPS, heading sensor, MRU-Z motion sensor and navigation instruments which provide necessary data to bathymetrical measurement system, enabling its work...
-
High frequency oscillations are associated with cognitive processing in human recognition memory
PublicationHigh frequency oscillations are associated with normal brain function, but also increasingly recognized as potential biomarkers of the epileptogenic brain. Their role in human cognition has been predominantly studied in classical gamma frequencies (30-100 Hz), which reflect neuronal network coordination involved in attention, learning and memory. Invasive brain recordings in animals and humans demonstrate that physiological oscillations...
-
Mutually polarizable QM/MM model with in situ optimized localized basis functions
PublicationWe extend our recently developed quantum-mechanical/molecular mechanics (QM/MM) approach [Dziedzic et al., J. Chem. Phys. 145, 124106 (2016)] to enable in situ optimization of the localized orbitals. The quantum subsystem is described with ONETEP linear-scaling density functional theory and the classical subsystem – with the AMOEBA polarizable force field. The two subsystems interact via multipolar electrostatics and are fully...
-
Emerging Processes for Sustainable Processing of Food Ingredients and Products
PublicationIn recent decades, traditional food processing processes, such as homogenization, pasteurization, canning, drying, and smoking, among others, have been successfully applied to obtain, to some extent, acceptable food items. However, with the increasing food demand, as a consequence of the growing population worldwide, new, tunable, and enriched food products are demanded, requiring the implementation of emerging technologies in...
-
Assessment of Therapeutic Progress After Acquired Brain Injury Employing Electroencephalography and Autoencoder Neural Networks
PublicationA method developed for parametrization of EEG signals gathered from participants with acquired brain injuries is shown. Signals were recorded during therapeutic session consisting of a series of computer assisted exercises. Data acquisition was performed in a neurorehabilitation center located in Poland. The presented method may be used for comparing the performance of subjects with acquired brain injuries (ABI) who are involved...
-
Adaptive identification of sparse underwater acoustic channels with a mix of static and time-varying parameters
PublicationWe consider identification of sparse linear systems with a mix of static and time-varying parameters. Such systems are typical in underwater acoustics (UWA), for instance, in applications requiring identi- fication of the acoustic channel, such as UWA communications, navigation and continuous-wave sonar. The recently proposed fast local basis function (fLBF) algorithm provides high performance when identi- fying time-varying systems....
-
Novel Fault Identification for Electromechanical Systems via Spectral Technique and Electrical Data Processing
PublicationIt is proposed, developed, investigated, and validated by experiments and modelling for the first time in worldwide terms new data processing technologies, higher order spectral multiple correlation technologies for fault identification for electromechanical systems via electrical data processing. Investigation of the higher order spectral triple correlation technology via modelling has shown that the proposed data processing technology...
-
Music Data Processing and Mining in Large Databases for Active Media
PublicationThe aim of this paper was to investigate the problem of music data processing and mining in large databases. Tests were performed on a large data-base that included approximately 30000 audio files divided into 11 classes cor-responding to music genres with different cardinalities. Every audio file was de-scribed by a 173-element feature vector. To reduce the dimensionality of data the Principal Component Analysis (PCA) with variable...
-
A non-uniform real-time speech time-scale stretching method
PublicationAn algorithm for non-uniform real-time speech stretching is presented. It provides a combination of typical SOLA algorithm (Synchronous Overlap and Add ) with the vowels, consonants and silence detectors. Based on the information about the content and the estimated value of the rate of speech (ROS), the algorithm adapts the scaling factor value. The ability of real-time speech stretching and the resultant quality of voice were...
-
Structure-Property Relationship and Multiple Processing Studies of Novel Bio-Based Thermoplastic Polyurethane Elastomers
PublicationCurrently, the growing demand for polymeric materials has led to an increased need to develop effective recycling methods. This study focuses on the multiple processing of bio-based thermoplastic polyurethane elastomers (bio-TPUs) as a sustainable approach for polymeric waste management through mechanical recycling. The main objective is to investigate the influence of two reprocessing cycles on selected properties of bio-TPUs....
-
Quantum entanglement in time
PublicationIn this paper we present a concept of quantum entanglement in time in a context of entangled consistent histories. These considerations are supported by presentation of necessary tools closely related to those acting on a space of spatial multipartite quantum states. We show that in similarity to monogamy of quantum entanglement in space, quantum entanglement in time is also endowed with this property for a particular history....
-
Usage of Two-Center Basis Function Neural Classifiers in Compact Smart Resistive Sensors
PublicationA new solution of the smart resistance sensorwith the Two-Center Basis Function (TCBF) neuralclassifier, for which the resistance sensor is a component ofan anti-aliasing filter of an ADC is proposed. Thetemperature measurement procedure is based on excitationof the filter by square impulses, sampling time response ofthe filter and processing measured voltage values by theTCBF classifier. All steps of the measurement procedure...
-
Characteristics of an image sensor with early-vision processing fabricated in standard 0.35 µm CMOS technology
PublicationThe article presents measurement results of prototype integrated circuits for acquisition and processing of images in real time. In order to verify a new concept of circuit solutions of analogue image processors, experimental integrated circuits were fabricated. The integrated circuits, designed in a standard 0.35 µm CMOS technology, contain the image sensor and analogue processors that perform low-level convolution-based image...
-
Software Modeling from the Perspective of Intuitive Information Processing
PublicationThere is psychological evidence that humans process information not only consciously but also intuitively. Intuitive information processing is present also during the activities related to software modeling. The goal of this paper is to analyze software modeling from the perspective of theories which describe intuitive (nonconscious, implicit) information processing. The paper includes presentation of relevant psychological theories,...
-
Outlier detection method by using deep neural networks
PublicationDetecting outliers in the data set is quite important for building effective predictive models. Consistent prediction can not be made through models created with data sets containing outliers, or robust models can not be created. In such cases, it may be possible to exclude observations that are determined to be outlier from the data set, or to assign less weight to these points of observation than to other points of observation....
-
A Selection of Starting Points for Iterative Position Estimation Algorithms Using Feedforward Neural Networks
PublicationThis article proposes the use of a feedforward neural network (FNN) to select the starting point for the first iteration in well-known iterative location estimation algorithms, with the research objective of finding the minimum size of a neural network that allows iterative position estimation algorithms to converge in an example positioning network. The selected algorithms for iterative position estimation, the structure of the...
-
Automatic singing quality recognition employing artificial neural networks
PublicationCelem artykułu jest udowodnienie możliwości automatycznej oceny jakości technicznej głosów śpiewaczych. Pokrótce zaprezentowano w nim stworzoną bazę danych głosów śpiewaczych oraz zaimplementowane parametry. Przy pomocy sztucznych sieci neuronowych zaprojektowano system decyzyjny, który oceniono w pięciostopniowej skali jakość techniczną głosu. Przy pomocy metod statystycznych udowodniono, że wyniki generowane przez ten system...
-
an intelligent image processing sensor - the algorithm and the hardware implementation
PublicationW artykule przedstawiono algorytm przeznaczony do rozpoznawania obiektów ruchomych w obrazie do celu analizy ruchu pojazdów. Algorytm został zrealizowany w układzie FPGA.Ang.: This paper describes the idea and theimplementation of the robust algorithm dedicated toextraction of moving vehicles from real-time cameraimages for the evaluation of traffic parameters, suchas the number of vehicles, their direction of movementand their...
-
Artificial Neural Networks as an architectural design tool- generating new detail forms based on the Roman Corinthian order capital
PublicationThe following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital....
-
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...
-
Smart Approach for Glioma Segmentation in Magnetic Resonance Imaging using Modified Convolutional Network Architecture (U-NET)
PublicationSegmentation of a brain tumor from magnetic resonance multimodal images is a challenging task in the field of medical imaging. The vast diversity in potential target regions, appearance and multifarious intensity threshold levels of various tumor types are few of the major factors that affect segmentation results. An accurate diagnosis and its treatment demand strict delineation of the tumor affected tissues. Herein, we focus on...
-
Radar and Sonar Imaging and Processing (2nd Edition)
PublicationThe 14 papers (from 29 submitted) published in the Special Issue “Radar and Sonar Imaging Processing (2nd Edition)” highlight a variety of topics related to remote sensing with radar and sonar sensors. The sequence of articles included in the SI deal with a broad profile of aspects of the use of radar and sonar images in line with the latest scientific trends, in which the latest developments in science, including artificial intelligence,...
-
Extracellular miRNAs as Biomarkers of Head and Neck Cancer Progression and Metastasis
Publication -
Measurements of head surfaces of endoprostheses = Pomiary powierzchni głów endoprotez
PublicationW niniejszej pracy rozpatrywane są połowicze i całkowite endoprotezy. Rezultaty badań koncentrują się na wynikach pomiarów chropowatości powierzchni głów połowiczych i całkowitych endoprotez stawu biodrowego. Pomiary dokonane zostały dla połowiczych endoprotez z głową przyspawaną do trzpienia oraz endoprotez Frankobala z dwuczęściową głową osadzoną na sworzniu. Pomiary powierzchni dla próbek powierzchni głowy, całkowitej i połowiczej...
-
Tests of soil-geotextile systems in changeable hydraulic head conditions.
PublicationArtykuł zawiera opis stanowiska badawczego i przeprowadzonych badań filtracji w układzie grunt-geowłóknina w kierunku normalnym do płaszczyzny geosyntetyku.
-
APPLICATION OF STATISTICAL FEATURES AND MULTILAYER NEURAL NETWORK TO AUTOMATIC DIAGNOSIS OF ARRHYTHMIA BY ECG SIGNALS
PublicationAbnormal electrical activity of heart can produce a cardiac arrhythmia. The electrocardiogram (ECG) is a non-invasive technique which is used as a diagnostic tool for cardiac diseases. Non-stationarity and irregu- larity of heartbeat signal imposes many difficulties to clinicians (e.g., in the case of myocardial infarction arrhythmia). Fortunately, signal processing algorithms can expose hidden information within ECG signal contaminated...
-
Performance analysis of power swing blocking feature in ABB 670 series impedance relays
PublicationThis paper presents test results of a distance protection’s PSD power swing detection feature in ABB 670 series relays. A RED670 relay was tested, which is part of the hydroelectric set protection in Żarnowiec Pumped Storage Plant. The power swing blocking feature’s performance was analysed on the basis of the results of object tests made with an Omicron digital tester. Also presented are simulation results that illustrate the...
-
An automatic selection of optimal recurrent neural network architecture for processes dynamics modelling purposes
PublicationA problem related to the development of algorithms designed to find the structure of artificial neural network used for behavioural (black-box) modelling of selected dynamic processes has been addressed in this paper. The research has included four original proposals of algorithms dedicated to neural network architecture search. Algorithms have been based on well-known optimisation techniques such as evolutionary algorithms and...
-
Categorization of emotions in dog behavior based on the deep neural network
PublicationThe aim of this article is to present a neural system based on stock architecture for recognizing emotional behavior in dogs. Our considerations are inspired by the original work of Franzoni et al. on recognizing dog emotions. An appropriate set of photographic data has been compiled taking into account five classes of emotional behavior in dogs of one breed, including joy, anger, licking, yawning, and sleeping. Focusing on a particular...
-
Linear Time-Varying Dynamic-Algebraic Equations of Index One on Time Scales
PublicationIn this paper, we introduce a class of linear time-varying dynamic-algebraic equations (LTVDAE) of tractability index one on ar- bitrary time scales. We propose a procedure for the decoupling of the considered class LTVDAE. Explicit formulae are written down both for transfer operator and the obtained decoupled system. A projector ap- proach is used to prove the main statement of the paper and sufficient conditions of decoupling...
-
Designing of an effective structure of system for the maintenance of a technical object with the using information from an artificial neural network
Publication -
Evolving neural network as a decision support system — Controller for a game of “2048” case study
PublicationThe paper proposes an approach to designing the neuro-genetic self-learning decision support system. The system is based on neural networks being adaptively learned by evolutionary mechanism, forming an evolved neural network. Presented learning algorithm enables for a selection of the neural network structure by establishing or removing of connections between the neurons, and then for a finding the beast suited values of the network...