Filtry
wszystkich: 989
wybranych: 821
-
Katalog
Filtry wybranego katalogu
Wyniki wyszukiwania dla: INTELLIGENT SIGNAL PROCESSING, MACHINE LEARNING, DATASETS
-
Research and applications of active bearings: A state-of-the-art review
PublikacjaControllable/active bearings are mainly associated with active magnetic bearings (AMBs), whereas active bearing control is also found in many types of bearings, e.g. fluid, gas and hybrid bearings. The article presents a review of the literature describing the structure and results of studies of active bearings. Active control brings a number of benefits resulting in the fact that their use as a support for rotors becomes increasingly...
-
Monitoring the curing process of epoxy adhesive using ultrasound and Lamb wave dispersion curves
PublikacjaMonitoring the stiffness of adhesives is a crucial issue when considering the durability andstrength of adhesive joints. While there are many studies conducted on specimens madeonly from adhesive, the problem of curing of an adhesive film in real joints is moderatelyconsidered. This paper presents the monitoring of stiffening of epoxy adhesive using ultra-sound. Ultrasonic pulse velocity method was firstly applied for monitoring...
-
On DoA estimation for rotating arrays using stochastic maximum likelihood approach
PublikacjaThe flexibility needed to construct DoA estimators that can be used with rotating arrays subject to rapid variations of the signal frequency is offered by the stochastic maximum likelihood approach. Using a combination of analytic methods and Monte Carlo simulations, we show that for low and moderate source correlations the stochastic maximum likelihood estimator that assumes noncorrelated sources has accuracy comparable to the...
-
An adaptive-noise Augmented Kalman Filter approach for input-state estimation in structural dynamics
PublikacjaThe establishment of a Digital Twin of an operating engineered system can increase the potency of Structural Health Monitoring (SHM) tools, which are then bestowed with enhanced predictive capabilities. This is particularly relevant for wind energy infrastructures, where the definition of remaining useful life is a main driver for assessing the efficacy of these systems. In order to ensure a proper representation of the physical...
-
A Control Theoretical Approach to Spectral Factorization is Unstable
PublikacjaLocal stability analysis of a recently proposed recursive feedback-based approach to spectral factorization is performed. The method is found not to give stability guarantees. Interestingly enough, its global behavior often allows one to obtain reasonable approximations of spectral factorizations if a suitable stopping criterion is employed.
-
Corrosion damage identification based on the symmetry of propagating wavefield measured by a circular array of piezoelectric transducers: Theoretical, experimental and numerical studies
PublikacjaThe article investigates the results obtained from numerical simulations and experimental tests concerning the propagation of guided waves in corroded steel plates. Developing innovative methodologies for assessing corrosion-induced degradation is crucial for accurately diagnosing offshore and ship structures exposed to harsh environmental conditions. The main aim of the research is to analyze how surface irregularities affect...
-
On optimal tracking of rapidly varying telecommunication channels
PublikacjaWhen parameters of mobile telecommunication channels change rapidly, classical adaptive filters, such as exponentially weighted least squares algorithms or gradient algorithms, fail to estimate them with sufficient accuracy. In cases like this, one can use identification methods based on explicit models of parameter changes such as the method of basis functions (BF). When prior knowledge about parameter changes is available the...
-
Transfer learning in imagined speech EEG-based BCIs
PublikacjaThe Brain–Computer Interfaces (BCI) based on electroencephalograms (EEG) are systems which aim is to provide a communication channel to any person with a computer, initially it was proposed to aid people with disabilities, but actually wider applications have been proposed. These devices allow to send messages or to control devices using the brain signals. There are different neuro-paradigms which evoke brain signals of interest...
-
Predicting the seismic collapse capacity of adjacent SMRFs retrofitted with fluid viscous dampers in pounding condition
PublikacjaSevere damages of adjacent structures due to structural pounding during earthquakes have emphasized the need to use some seismic retrofit strategy to enhance the structural performance. The purpose of this paper is to study the influence of using linear and nonlinear Fluid Viscous Dampers (FVDs) on the seismic collapse capacities of adjacent structures prone to pounding and proposing modification factors to modify the median...
-
Regularized Local Basis Function Approach to Identification of Nonstationary Processes
PublikacjaThe problem of identification of nonstationary stochastic processes (systems or signals) is considered and a new class of identification algorithms, combining the basis functions approach with local estimation technique, is described. Unlike the classical basis function estimation schemes, the proposed regularized local basis function estimators are not used to obtain interval approximations of the parameter trajectory, but provide...
-
Comments on “Closed Form Variable Fractional Time Delay Using FFT”
PublikacjaIn this letter drawbacks of the aforementioned paper are pointed out. The proposed approach is improved with minor modifications of the discrete frequency response. This allows for design of fractional delay filters which are close to optimal and can be efficiently implemented in the frequency domain using the sliding DFT based structure. Alternatively, the derived equivalent closed form formulae for offset windows can be used...
-
Dynamic mass measurement in checkweighers using a discrete time-variant low-pass filter
PublikacjaConveyor belt type checkweighers are complex mechanical systems consisting of a weighing sensor (strain gauge load cell, electrodynamically compensated load cell), packages (of different shapes, made of different materials) and a transport system (motors, gears, rollers). Disturbances generated by the vibrating parts of such a system are reflected in the signal power spectra in a form of strong spectral peaks, located usually in...
-
Variable Fractional Delay Filter Design Using a Symmetric Window
PublikacjaIn this paper a numerically efficient method for designing a nearly optimal variable fractional delay (VFD) filter based on a simple and well-known window method is presented. In the proposed method a single window extracted from the optimal filter with fixed fractional delay (FD) is divided into even and odd part. Subsequently, the odd part is discarded and symmetric even part of the extracted window is used to design a family...
-
Systemidentificationbasedapproachtodynamicweighing revisited
PublikacjaDynamicweighing,i.e.,weighingofobjectsinmotion,withoutstoppingthemonthe weighing platform,allowsonetoincreasetherateofoperationofautomaticweighing systems, usedinindustrialproductionprocesses,withoutcompromisingtheiraccuracy. Sincetheclassicalidentification-basedapproachtodynamicweighing,basedonthe second-ordermass–spring–dampermodeloftheweighingsystem,doesnotyieldsa- tisfactoryresultswhenappliedtoconveyorbelttypecheckweighers,severalextensionsof thistechniqueareexamined.Experimentsconfirmthatwhenappropriatelymodifiedthe identification-basedapproachbecomesareliabletoolfordynamicmassmeasurementin checkweighers.
-
Smooth least absolute deviation estimators for outlier-proof identification
PublikacjaThe paper proposes to identify the parameters of linear dynamic models based on the original implementation of least absolute deviation estimators. It is known that the object estimation procedures synthesized in the sense of the least sum of absolute prediction errors are particularly resistant to occasional outliers and gaps in the analyzed system data series, while the classical least squares procedure unfortunately becomes...
-
Fast recursive basis function estimators for identification of time-varying processes
PublikacjaW pracy wprowadzono nową kategorię filtrów adaptacyjnych opartych na metodzie funkcji bazowych i wykorzystujących koncepcję postfiltracji. Proponowane algorytmy pozwalają połączyć niską złożoność obliczeniową i dobre właściwości śledzące.
-
Synthesis and biological evaluation of 2,7-Dihydro-3H-dibenzo[de,h]cinnoli- ne-3,7-done derivatives a novel group of anticancer agents active on a multidrug resistance cell line.
PublikacjaZsyntezowano serię pochodnych pirydazonu z jednym lub dwoma łańcuchami bocznymi w różnych pozycjach chromoforu tetracyklicznego. Związki wykazały aktywność cytoksyczną na mysią białaczkę L1210 i ludzką k562 oraz na linii komórkowej oporności krzyżowej MDR (k562/DX). Dwa najbardziej aktywne związki przetestowano in vivo na mysiej białaczce P388. Wykazały one aktywność przeciwnowotworową porównywalną z aktywnością Mitoxantronu.
-
Fast algorithms for identyfication of periodiccaly varying systems.
PublikacjaPraca dotyczy identyfikacji obiektów o parametrach zmieniających się w sposób okresowy. Zaproponowane algorytmy śledzenia parametrów cechują się niską złożonością obliczeniową, typową dla podejścia gradientowego a zarazem wysoką jakością śledzenia typową dla złożonych algorytmów opartych na metodzie funkcji bazowych.
-
Global Optimization for Recovery of Clipped Signals Corrupted With Poisson-Gaussian Noise
PublikacjaWe study a variational formulation for reconstructing nonlinearly distorted signals corrupted with a Poisson-Gaussian noise. In this situation, the data fidelity term consists of a sum of a weighted least squares term and a logarithmic one. Both of them are precomposed by a nonlinearity, modelling a clipping effect, which is assumed to be rational. A regularization term, being a piecewise rational approximation of the ℓ0 function...
-
Computer-assisted pronunciation training—Speech synthesis is almost all you need
PublikacjaThe research community has long studied computer-assisted pronunciation training (CAPT) methods in non-native speech. Researchers focused on studying various model architectures, such as Bayesian networks and deep learning methods, as well as on the analysis of different representations of the speech signal. Despite significant progress in recent years, existing CAPT methods are not able to detect pronunciation errors with high...
-
Inspection of Gas Pipelines Using Magnetic Flux Leakage Technology
PublikacjaMagnetic non-destructive testing methods can be classified into the earliest methods developed for assessment of steel constructions. One of them is the magnetic flux leakage technology. A measurement of the magnetic flux leakage is quite commonly used for examination of large objects such as tanks and pipelines. Construction of a magnetic flux leakage tool is relatively simple, but a quantitative analysis of recorded data is a...
-
English Language Learning Employing Developments in Multimedia IS
PublikacjaIn the realm of the development of information systems related to education, integrating multimedia technologies offers novel ways to enhance foreign language learning. This study investigates audio-video processing methods that leverage real-time speech rate adjustment and dynamic captioning to support English language acquisition. Through a mixed-methods analysis involving participants from a language school, we explore the impact...
-
MP3vec: A Reusable Machine-Constructed Feature Representation for Protein Sequences
Publikacja—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...
-
Introduction to the ONDM 2022 special issue
PublikacjaThis JOCN special issue contains extended versions of selected papers presented at the 26th International Conference on Optical Network Design and Modeling (ONDM 2022), which took place 16–19 May 2022 at Warsaw University of Technology, Warsaw, Poland. The topics covered by the papers represent trends in optical networking research: application of machine learning to network management, cross-layer network performance optimization,...
-
Waveform design for fast clutter cancellation in noise radars
PublikacjaCanceling clutter is an important, but computation-ally intensive part of signal processing in noise radars. It is shown that considerable improvements can be made to a simple least squares canceler if minor constraints are imposed onto noise waveform. The proposed scheme is potentially capable of canceling clutter in real-time, even for high sampling rates.
-
University Students’ Research on Artificial Intelligence and Knowledge Management. A Review and Report of Multi-case Studies
PublikacjaLeading technologies are very attractive for students preparing their theses as the completion of their studies. Such an orientation of students connected with professional experiences seems to be a crucial motivator in the research in the management and business areas where these technologies condition the development of professional activities. The goal of the paper is the analysis of students’ thesis topics defended in the last...
-
Research and Analysis of Accuracy of Location Estimation in Inertial Navigation System
PublikacjaIn the article the research and analysis of digital signal processing and its influence on accuracy of location estimation in developed inertial navigation system was presented. The purpose of the system is to localize moving people in indoor environment. During research a measuring unit for recording selected movement parameters was made. In the article were also described author’s inertial navigation algorithms.
-
Affective Learning Manifesto – 10 Years Later
PublikacjaIn 2004 a group of affective computing researchers proclaimed a manifesto of affective learning that outlined the prospects and white spots of research at that time. Ten years passed by and affective computing developed many methods and tools for tracking human emotional states as well as models for affective systems construction. There are multiple examples of affective methods applications in Intelligent Tutoring Systems (ITS)....
-
Vertical vibration reduction and audible sound analysis in surface grinding with electroplated tools
PublikacjaOne of the first approaches to the development of a grinding process monitoring system based on audible sound sensors is presented in the paper. Electroplated diamond tools (abrasive D64 and D107) were used in a modified single-disc lapping machine configuration for flat grinding of ceramics (Al2O3). The main aim of the machine modification was to reduce the vertical vibration in order to decrease the tool wear and to increase...
-
Energy-Efficient Self-Supervised Technique to Identify Abnormal User Over 5G Network for E-Commerce
PublikacjaWithin the realm of e-commerce networks, it is frequently observed that certain users exhibit behavior patterns that differ substantially from the normative behaviors exhibited by the majority of users. The identification of these atypical individuals and the understanding of their behavioral patterns are of significant practical significance in maintaining order on e-commerce platforms. One such method for accomplishing this...
-
Energy-Efficient Self-Supervised Technique to Identify Abnormal User Over 5G Network for E-Commerce
PublikacjaWithin the realm of e-commerce networks, it is frequently observed that certain users exhibit behavior patterns that differ substantially from the normative behaviors exhibited by the majority of users. The identification of these atypical individuals and the understanding of their behavioral patterns are of significant practical significance in maintaining order on e-commerce platforms. One such method for accomplishing this objective...
-
Deep learning techniques for biometric security: A systematic review of presentation attack detection systems
PublikacjaBiometric technology, including finger vein, fingerprint, iris, and face recognition, is widely used to enhance security in various devices. In the past decade, significant progress has been made in improving biometric sys- tems, thanks to advancements in deep convolutional neural networks (DCNN) and computer vision (CV), along with large-scale training datasets. However, these systems have become targets of various attacks, with...
-
Intelligent Autonomous Robot Supporting Small Pets in Domestic Environment
PublikacjaIn this contribution, we present preliminary results of the student project aimed at the development of an intelligent autonomous robot supporting small pets in a domestic environment. The main task of this robot is to protect a freely moving small pets against accidental stepping on them by home residents. For this purpose, we have developed the mobile robot which follows a pet and makes an alarm signal when a human is approaching....
-
A FPTAS for minimizing total completion time in a single machine time-dependent scheduling problem
PublikacjaIn this paper a single machine time-dependent scheduling problem with total completion time criterion is considered. There are given n jobs J1,…,Jn and the processing time pi of the ith job is given by pi=a+bisi, where si is the starting time of the ith job (i=1,…,n),bi is its deterioration rate and a is the common base processing time. If all jobs have deterioration rates different and not smaller than a certain constant u>0,...
-
Rough Set Based Modeling and Visualization of the Acoustic Field Around the Human Head
PublikacjaThe presented research aims at modeling acoustical wave propagation phenomena by applying rough set theory in a novel manner. In a typical listening environment sound intensity is determined by numerous factors: a distance from a sound source, signal levels and frequencies, obstacles’ locations and sizes. Contrarily, a free-field is characterized by direct, unimpeded propagation of the acoustical waves. The proposed approach is...
-
Radar Signal Parameters Estimation Using Phase Accelerogram in the Time-Frequency Domain
PublikacjaRadar signal parameter estimation, in the context of the reconstruction of the received signal in a passive radar utilizing other radars as a source of illumination, is one of the fundamental steps in the signal processing chain in such a device. The task is also a crucial one in electronic reconnaissance systems, e.g. ELINT (Electronic Intelligence) systems. In order to obtain accurate results it is important to measure, estimate...
-
Wavelet-based denoising method for real phonocardiography signal recorded by mobile devices in noisy environment
PublikacjaThe main obstacle in development of intelligent autodiagnosis medical systems based on the analysis of phonocardiography (PCG) signals is noise. The noise can be caused by digestive and respiration sounds, movements or even signals from the surrounding environment and it is characterized by wide frequency and intensity spectrum. This spectrum overlaps the heart tones spectrum, which makes the problem of PCG signal filtrating complex....
-
From the multiple frequency tracker to the multiple frequency smoother
PublikacjaThe problem of extraction/elimination of nonstationary sinusoidalsignals from noisy measurements is considered. This problem is usually solved using adaptive notch filtering (ANF)algorithms. It is shown that the accuracy of frequency estimates can be significantly increased if the results obtained from ANF are backward-time filtered by an appropriately designed lowpass filter. The resulting adaptive notch smoothing (ANS)algorithm...
-
How to Design Affect-aware Educational Systems – the AFFINT Process Approach
PublikacjaComputer systems, that support learning processes, can adapt to the needs and states of a learner. The adaptation might directly address the knowledge deficits and most tutoring systems apply an adaptable learning path of that kind. Apart from a preliminary knowledge state, there are more factors, that influence education effectiveness and among those there are fluctuating emotional states. The tutoring systems may recognize or...
-
Performance Analysis of Convolutional Neural Networks on Embedded Systems
PublikacjaMachine learning is no longer confined to cloud and high-end server systems and has been successfully deployed on devices that are part of Internet of Things. This paper presents the analysis of performance of convolutional neural networks deployed on an ARM microcontroller. Inference time is measured for different core frequencies, with and without DSP instructions and disabled access to cache. Networks use both real-valued and...
-
Data-driven models for fault detection using kernel pca:a water distribution system case study
PublikacjaKernel Principal Component Analysis (KPCA), an example of machine learning, can be considered a non-linear extension of the PCA method. While various applications of KPCA are known, this paper explores the possibility to use it for building a data-driven model of a non-linear system-the water distribution system of the Chojnice town (Poland). This model is utilised for fault detection with the emphasis on water leakage detection....
-
Categorization of Cloud Workload Types with Clustering
PublikacjaThe paper presents a new classification schema of IaaS cloud workloads types, based on the functional characteristics. We show the results of an experiment of automatic categorization performed with different benchmarks that represent particular workload types. Monitoring of resource utilization allowed us to construct workload models that can be processed with machine learning algorithms. The direct connection between the functional...
-
An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublikacjaIn this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent...
-
Evaluating Accuracy of Respiratory Rate Estimation from Super Resolved Thermal Imagery
PublikacjaNon-contact estimation of Respiratory Rate (RR) has revolutionized the process of establishing the measurement by surpassing some issues related to attaching sensors to a body, e.g. epidermal stripping, skin disruption and pain. In this study, we perform further experiments with image processing-based RR estimation by using various image enhancement algorithms. Specifically, we employ Super Resolution (SR) Deep Learning (DL) network...
-
Implementation of discrete convolution using polynomial residue representation
PublikacjaConvolution is one of the main algorithms performed in the digital signal processing. The algorithm is similar to polynomial multiplication and very intensive computationally. This paper presents a new convolution algorithm based on the Polynomial Residue Number System (PRNS). The use of the PRNS allows to decompose the computation problem and thereby reduce the number of multiplications. The algorithm has been implemented in Xilinx...
-
Fast clutter cancellation for noise radars via waveform design
PublikacjaCanceling clutter is an important, but very expensive part of signal processing in noise radars. It is shown that considerable improvements can be made to a simple least squares canceler if minor constraints are imposed onto noise waveform. Using a combination of FPGA and CPU, the proposed scheme is capable of canceling both stationary clutter and moving targets in real-time, even for high sampling rates.
-
Preferred Benchmarking Criteria for Systematic Taxonomy of Embedded Platforms (STEP) in Human System Interaction Systems
PublikacjaThe rate of progress in the field of Artificial Intelligence (AI) and Machine Learning (ML) has significantly increased over the past ten years and continues to accelerate. Since then, AI has made the leap from research case studies to real production ready applications. The significance of this growth cannot be undermined as it catalyzed the very nature of computing. Conventional platforms struggle to achieve greater performance...
-
Analysis of Vibration and Acoustic Signals for Noncontact Measurement of Engine Rotation Speed
PublikacjaThe non-contact measurement of engine speed can be realized by analyzing engine vibration frequency. However, the vibration signal is distorted by harmonics and noise in the measurement. This paper presents a novel method for the measurement of engine rotation speed by using the cross-correlation of vibration and acoustic signals. This method can enhance the same frequency components in engine vibration and acoustic signal. After...
-
An Analysis of Uncertainty and Robustness of Waterjet Machine Positioning Vision System
PublikacjaThe paper presents a new Automatic Waterjet Positioning Vision System (AWPVS) and investigates components of workpiece positioning accuracy. The main purpose of AWPVS is to precisely identify the position and rotation of a workpiece placed on a waterjet machine table. Two webcams form a basis for the system, and constitute its characteristics. The proposed algorithm comprises various image processing techniques to assure a required...
-
Detection and Direction-of-Arrival Estimation of Weak Spread Spectrum Signals Received with Antenna Array
PublikacjaThis paper presents a method for the joint detection and direction of arrival (DOA) estimation of low probability of detection (LPD) signals. The proposed approach is based on using the antenna array to receive spread-spectrum signals hidden below the noise floor. Array processing exploits the spatial correlation between phase-delayed copies of the signal and allows us to evaluate the parameter used to make the decision about the...