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Search results for: LEAK DETECTION AND IDENTIFICATION
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System identification 2021/22 - project
e-Learning Courses -
System identification 2022/23 - project
e-Learning Courses -
Radiation Detection Technology and Methods
Journals -
Towards Robust Identification of Nonstationary Systems
PublicationThe article proposes a fast, two-stage method for the identification of nonstationary systems. The method uses iterative reweighting to robustify the identification process against the outliers in the measurement noise and against the numerical errors that may occur at the first stage of identification. We also propose an adaptive algorithm to optimize the values of the hyperparameters that are crucial for this new method.
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Open-Set Speaker Identification Using Closed-Set Pretrained Embeddings
PublicationThe paper proposes an approach for extending deep neural networks-based solutions to closed-set speaker identification toward the open-set problem. The idea is built on the characteristics of deep neural networks trained for the classification tasks, where there is a layer consisting of a set of deep features extracted from the analyzed inputs. By extracting this vector and performing anomaly detection against the set of known...
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Camera Orientation-Independent Parking Events Detection
PublicationThe paper describes the method for detecting precise position and time of vehicles parking in a parking lot. This task is trivial in case of favorable camera orientation but gets much more complex when an angle between the camera viewing axis and the ground is small. The method utilizes background subtraction and object tracking algorithms for detecting moving objects in a video stream. Objects are classified into vehicles and...
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Faults and Fault Detection Methods in Electric Drives
PublicationThe chapter presents a review of faults and fault detection methods in electric drives. Typical faults are presented that arises for the induction motor, which is valued in the industry for its robust construction and cost-effective production. Moreover, a summary is presented of detectable faults in conjunction with the required physical information that allow a detection of specific faults. In order to address faults of a complete...
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On noncausal identification of nonstationary stochastic systems
PublicationIn this paper we consider the problem of noncausal identification of nonstationary,linear stochastic systems, i.e., identification based on prerecorded input/output data. We show how several competing weighted least squares parameter smoothers, differing in memory settings, can be combined together to yield a better and more reliable smoothing algorithm. The resulting parallel estimation scheme automatically adjusts its smoothing...
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Influence of statistical errors on damage detection based on structuralflexibility and mode shape curvature
PublicationDamage detection procedures based on measured natural frequencies and building structure mode shapes are discussed in this paper. Modal curvature and structural flexibility approaches are tested. Attention is paid to the modal identification errors that influence damage detection. This problem is studied using a computer simulation of a simple supported beam. For practical cases, the peak picking methodand its statistical errors...
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Analityka surfaktantów w próbkach środowiskowych
PublicationSurfaktanty stanowią grupę związków charakteryzujących się specyficznymi właściwościami fizykochemicznymi (m.in. amfifilowa budowa, zdolność rozpuszczania się w cieczach o różnej polarności, zdolność do tworzenia micelli) i z tego względu są one wykorzystywane w wielu sferach działalności człowieka. Związki powierzchniowo-czynne ulegają różnorodnym przemianom fizykochemicznym, co umożliwia ich migrację między różnymi elementami...
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Detection of Toxoplasma gondii oocysts in environmental samples
PublicationToxoplasma gondii is an obligate intracellular parasite that has capacity to infect warm-blooded animals. Human toxoplasmosis is usually asymptomatic, whereas severe complications may occur in immunocompromised patients (e.g. AIDS) or in case of congenitalinfection. One of the sources of acquiring human toxoplasmosis is ingestion of T. gondii oocysts. It is known that newly infected cats can shed millions of oocysts into the environment,...
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Cascade Object Detection and Remote Sensing Object Detection Method Based on Trainable Activation Function
PublicationObject detection is an important process in surveillance system to locate objects and it is considered as major application in computer vision. The Convolution Neural Network (CNN) based models have been developed by many researchers for object detection to achieve higher performance. However, existing models have some limitations such as overfitting problem and lower efficiency in small object detection. Object detection in remote...
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Modal parameters identification with Particle Swarm Optimization
PublicationThe paper presents method of the modal parameters identification based on the Particle Swarm Optimization (PSO) algorithm [1]. The basic PSO algorithm is modified in order to achieve fast convergence and low estimation error of identified parameters values. The procedure of identification as well as algorithm modifications are presented and some simple examples for the SISO systems are provided. Results are compared with the results...
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Identification of models and signals robust to occasional outliers
PublicationIn this paper estimation algorithms derived in the sense of the least sum of absolute errors are considered for the purpose of identification of models and signals. In particular, off-line and approximate on-line estimation schemes discussed in the work are aimed at both assessing the coefficients of discrete-time stationary models and tracking the evolution of time-variant characteristics of monitored signals. What is interesting,...
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Identification of models and signals robust to occasional outliers
PublicationIn this paper estimation algorithms derived in the sense of the least sum of absolute errors are considered for the purpose of identification of models and signals. In particular, off-line and approximate on-line estimation schemes discussed in the work are aimed at both assessing the coefficients of discrete-time stationary models and tracking the evolution of time-variant characteristics of monitored signals. What is interesting,...
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Variable-structure algorithm for identification of quasi-periodically varying systems
PublicationThe paper presents a variable-structure version of a generalized notchfiltering (GANF) algorithm. Generalized notch filters are used for identification of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. The proposed algorithm is a cascade of two GANF filters: a multiple-frequency "precise" filter bank, used for precise system tracking, and a...
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Identification of hydroacoustic wave sources of ship in motion
PublicationThis paper deals with results of identification tests of acoustic field spectrum of underwater noise generated by ship in motion. The field is connected with acoustic activity of ship mechanisms and devices in operation. Vibration energy generated by the mechanisms and devices is transferred through ship structural elements to surrounding water where it propagates in the form of acoustic waves of a broad band of frequencies. In...
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Spectral Methods for Modelling of Wave Propagation in Structures in Terms of Damage Detection—A Review
PublicationModern methods of detection and identification of structural damage direct the activities of scientific groups towards the improvement of diagnostic methods using for example the phenomenon of mechanical wave propagation. Damage detection methods that use mechanical wave propagation in structural components are extremely effective. Many different numerical approaches are used to model this phenomenon, but, due to their universal...
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Detection of damages in a rivetted plate
PublicationThe paper presents the results of damage detection in a riveted aluminium plate. The detection method has been based on Lamb wave propagation. The plate has been analysed numerically and experimentally. Numerical calculations have been carried out by the use of the time-domain spectral finite element method, while for the experimental analysis laser scanning Doppler vibrometry (LSDV) has been utilised. The panel has been excited...
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Distributed Framework for Visual Event Detection in Parking Lot Area
PublicationThe paper presents the framework for automatic detection of various events occurring in a parking lot basing on multiple camera video analysis. The framework is massively distributed, both in the logical and physical sense. It consists of several entities called node stations that use XMPP protocol for internal communication and SRTP protocol with Jingle extension for video streaming. Recognized events include detecting parking...
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A study of nighttime vehicle detection algorithms
Open Research DataThis dataset is from my master's thesis "A study of nighttime vehicle detection algorithms". It contains both raw data and preprocessed dataset ready to use. In the pictures below you can see how images were annotated.
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TOXIC GASES IDENTIFICATION USING SINGLE ELECTROCATALYTIC SENSOR RESPONSES AND ARTIFICIAL NEURAL NETWORK
PublicationThe need for precise detection of toxic gases drives development of new gas sensors structures and methods of processing the output signals from the sensors. In literature, artificial neural networks are considered as one of the most effective tool for the analysis of gas sensors or sensors arrays responses. In this paper a method of toxic gas components identification using a electrocatalytic gas sensor as a detector and an artificial...
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Sensorless Disturbance Detection for Five Phase Induction Motor with Third Harmonic Injection
PublicationThe paper presents a sensorless disturbance detection procedure that was done on a five phase induction motor with third harmonic injection. A test bench was developed where a three phase machine serves as disturbance generator of different frequencies. The control of the machines is based on multi scalar variables that ensures an independent control of the motor EMF and the rotor flux. For disturbance identification a speed observer...
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Transient detection for speech coding applications
PublicationSignal quality in speech codecs may be improved by selecting transients from speech signal and encoding them using a suitable method. This paper presents an algorithm for transient detection in speech signal. This algorithm operates in several frequency bands. Transient detection functions are calculated from energy measured in short frames of the signal. The final selection of transient frames is based on results of detection...
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Robust identification of quadrocopter model for control purposes
PublicationThe paper addresses a problem of quadrotor unmanned aerial vehicle (so-called X4-flyer or quadrocopter) utility model identification for control design purposes. To that goal the quadrotor model is assumed to be composed of two abstracted subsystems, namely a rigid body (plant) and four motors equipped with blades (actuators). The model of the former is acquired based on a well-established dynamic equations of motion while the...
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Identification of Optocoupler Devices with RTS Noise
PublicationThe results of noise measurements in low frequency range for CNY 17 type optocouplers are presented. The research were carried out on devices with different values of Current Transfer Ratio (CTR). The methods for identification of Random Telegraph Signal (RTS) in noise signal of optocouplers were proposed. It was found that the Noise Scattering Pattern method (NSP method) enables to identify RTS noise as non-Gaussian component...
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Algorithms of chemicals detection using raman spectra
PublicationRaman spectrometers are devices which enable fast and non-contact identification of examined chemicals. These devices utilize the Raman phenomenon to identify unknown and often illicit chemicals (e.g. drugs, explosives)without the necessity of their preparation. Now, Raman devices can be portable and therefore can be more widely used to improve security at public places. Unfortunately, Raman spectra measurements is a challenge...
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Detection and segmentation of moving vehicles and trains using Gaussian mixtures, shadow detection and morphological processing
PublicationSolution presented in this paper combines background modelling, shadow detection and morphological and temporal processing into one system responsible for detection and segmentation of moving objects recorded with a static camera. Vehicles and trains are detected based on their pixellevel difference from the continually updated background model utilizing a Gaussian mixture calculated separately for every pixel. The shadow detection...
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Identification of regions of interest in video for a traffic monitoring system
PublicationA system for automatic event detection in the camera image is presented in this paper. A method of limiting a region of interest to relevant parts of the image using a set of processing procedures is proposed. Image processing includes object detection with shadow removal performed in the modified YCbCr color space instead of RGB. The proposed procedures help to reduce the complexity of image processing algorithm and result in...
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A procedure for elastoplastic hardening function identification.
PublicationThe inverse analysis method for identifying a nonlinear hardening function,which governs a plastic yielding of soil and rock materials in the framework of elastoplastic theory is presented. A concept of two stage finite element based on spatial discretization of computational space and hardening function space is introduced. The proposed inverse analysis can be classified as the output least squares method. The Levenberg Marquard...
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Generalized Savitzky–Golay filters for identification of nonstationary systems
PublicationThe problem of identification of nonstationary systems using noncausal estimation schemes is consid-ered and a new class of identification algorithms, combining the basis functions approach with localestimationtechnique,isdescribed.Unliketheclassicalbasisfunctionestimationschemes,theproposedlocal basis function estimators are not used to obtain interval approximations of the parametertrajectory, but provide a sequence of point...
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The fast identification of explosives, natcotics and other chemicals carried on board of ships or transported in containers
PublicationThe fast identification of explosives, narcotics and other chemicals carried on board of ships or transported in containers to the harbors is an important problem of maritime security. Raman spectroscopy is an advanced technique used in state-of-the art laboratories for fast identification of chemicals. No sample preparation is required, and identification can be carried out through transparent packing, such as plastic or glass,...
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On Noncausal Identification of Nonstationary Multivariate Autoregressive Processes
PublicationThe problem of identification of nonstationary multivariate autoregressive processes using noncausal local estimation schemes is considered and a new approach to joint selection of the model order and the estimation bandwidth is proposed. The new selection rule, based on evaluation of pseudoprediction errors, is compared with the previously proposed one, based on the modified Akaike’s final prediction error criterion.
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Local basis function estimators for identification of nonstationary systems
PublicationThe problem of identification of a nonstationary stochastic system is considered and solved using local basis function approximation of system parameter trajectories. Unlike the classical basis function approach, which yields parameter estimates in the entire analysis interval, the proposed new identification procedure is operated in a sliding window mode and provides a sequence of point (rather than interval) estimates. It is...
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Spectrum-based modal parameters identification with Particle Swarm Optimization
PublicationThe paper presents the new method of the natural frequencies and damping identification based on the Artificial Intelligence (AI) Particle Swarm Optimization (PSO) algorithm. The identification is performed in the frequency domain. The algorithm performs two PSO-based steps and introduces some modifications in order to achieve quick convergence and low estimation error of the identified parameters’ values for multi-mode systems....
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Visual Features for Endoscopic Bleeding Detection
PublicationAims: To define a set of high-level visual features of endoscopic bleeding and evaluate their capabilities for potential use in automatic bleeding detection. Study Design: Experimental study. Place and Duration of Study: Department of Computer Architecture, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, between March 2014 and May 2014. Methodology: The features have...
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Camera sabotage detection for surveillance systems
PublicationCamera dysfunction detection algorithms and their utilization in realtime video surveillance systems are described. The purpose of using the proposed analysis is explained. Regarding image tampering three algorithms for focus loss, scene obstruction and camera displacement detection are implemented and presented. Features of each module are described and certain scenarios for best performance are depicted. Implemented solutions...
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IEEE Journal of Radio Frequency Identification
Journals -
On the lower smoothing bound in identification of time-varying systems
PublicationIn certain applications of nonstationary system identification the model-based decisions can be postponed, i.e. executed with a delay. This allows one to incorporate in the identification process not only the currently available information, but also a number of ''future'' data points. The resulting estimation schemes, which involve smoothing, are not causal. Assuming that the infinite observation history is available, the paper...
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Automatic audio-visual threat detection
PublicationThe concept, practical realization and application of a system for detection and classification of hazardous situations based on multimodal sound and vision analysis are presented. The device consists of new kind multichannel miniature sound intensity sensors, digital Pan Tilt Zoom and fixed cameras and a bundle of signal processing algorithms. The simultaneous analysis of multimodal signals can significantly improve the accuracy...
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On ''cheap smoothing'' opportunities in identification of time-varying systems
PublicationIn certain applications of nonstationary system identification the model-based decisions can be postponed, i.e. executed with a delay. This allows one to incorporate into the identification process not only the currently available information, but also a number of ''future'' data points. The resulting estimation schemes, which involve smoothing, are not causal. Despite the possible performance improvements, the existing smoothing...
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Direct detection of quantum entanglement
PublicationBasing on positive maps separability criterion we propose the experimentally viable, direct detection of quantum entanglement. It is efficient and does not require any a priori knowledge about the state. For two qubits it provides a sharp (i.e., “if and only if”) separability test and estimation of amount of entanglement. We view this method as a new form of quantum computation, namely, as a decision problem with quantum data structure.
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Rapid Assays for Specific Detection of Fungi of Scopulariopsis and Microascus Genera and Scopulariopsis brevicaulis Species
PublicationPurpose Fungi of Scopulariopsis and Microascus genera cause a wide range of infections, with S. brevicaulis being the most prevalent aetiological agent of mould onychomycosis. Proper identification of these pathogens requires sporulating culture, which considerably delays the diagnosis. So far, sequencing of rDNA regions of clinical isolates has produced ambiguous results due to the lack of reference sequences in publicly available...
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Comparison of edge detection algorithms for electric wire recognition
PublicationEdge detection is the preliminary step in image processing for object detection and recognition procedure. It allows to remove useless information and reduce amount of data before further analysis. The paper contains the comparison of edge detection algorithms optimized for detection of horizontal edges. For comparison purposes the algorithms were implemented in the developed application dedicated to detection of electric line...
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Molecularly imprinted polymers for the detection of volatile biomarkers
PublicationIn the field of cancer detection, the development of affordable, quick, and user-friendly sensors capable of detecting various cancer biomarkers, including those for lung cancer (LC), holds utmost significance. Sensors are expected to play a crucial role in the early-stage diagnosis of various diseases. Among the range of options, sensors emerge as particularly appealing for the diagnosis of various diseases, owing to their cost-effectiveness,...
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Building Knowledge for the Purpose of Lip Speech Identification
PublicationConsecutive stages of building knowledge for automatic lip speech identification are shown in this study. The main objective is to prepare audio-visual material for phonetic analysis and transcription. First, approximately 260 sentences of natural English were prepared taking into account the frequencies of occurrence of all English phonemes. Five native speakers from different countries read the selected sentences in front of...
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Rating by detection: an artifact detection protocol for rating EEG quality with average event duration
PublicationQuantitative evaluation protocols are critical for the development of algorithms that remove artifacts from real EEG optimally. However, visually inspecting the real EEG to select the top-performing artifact removal pipeline is infeasible while hand-crafted EEG data allow assessing artifact removal configurations only in a simulated environment. This study proposes a novel, principled approach for quantitatively evaluating algorithmically...
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A new assay for the simultaneous identification and differentiation of Klebsiella oxytoca strains.
PublicationKlebsiella oxytoca is the second most frequently identified species of Klebsiella isolated from hospitalized patients. Klebsiella spp. is difficult to identify using conventional methods and is often misclassified in clinical microbiology laboratories. K. oxytoca is responsible for an increasing number of multi-resistant infections in hospitals because of insufficient detection and identification. In this study, we propose a new...
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Exploring Neural Networks for Musical Instrument Identification in Polyphonic Audio
PublicationThe purpose of this paper is to introduce neural network-based methods that surpass state-of-the-art (SOTA) models, either by training faster or having simpler architecture, while maintaining comparable effectiveness in musical instrument identification in polyphonic music. Several approaches are presented, including two authors’ proposals, i.e., spiking neural networks (SNN) and a modular deep learning model named FMCNN (Fully...
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A Triplet-Learnt Coarse-to-Fine Reranking for Vehicle Re-identification
PublicationVehicle re-identification refers to the task of matching the same query vehicle across non-overlapping cameras and diverse viewpoints. Research interest on the field emerged with intelligent transportation systems and the necessity for public security maintenance. Compared to person, vehicle re-identification is more intricate, facing the challenges of lower intra-class and higher inter-class similarities. Motivated by deep...