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Search results for: LEAK DETECTION AND IDENTIFICATION

  • Cascade Object Detection and Remote Sensing Object Detection Method Based on Trainable Activation Function

    Publication
    • S. N. Shivappriya
    • M. J. P. Priyadarsini
    • A. Stateczny
    • C. Puttamadappa
    • B. D. Parameshachari

    - Remote Sensing - Year 2021

    Object 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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  • Identification of hydroacoustic wave sources of ship in motion

    Publication

    - Polish Maritime Research - Year 2010

    This 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

    Publication

    Modern 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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  • TOXIC GASES IDENTIFICATION USING SINGLE ELECTROCATALYTIC SENSOR RESPONSES AND ARTIFICIAL NEURAL NETWORK

    The 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...

  • Detection of damages in a rivetted plate

    Publication

    The 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...

  • Distributed Framework for Visual Event Detection in Parking Lot Area

    The 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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  • Sensorless Disturbance Detection for Five Phase Induction Motor with Third Harmonic Injection

    The 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...

  • Robust identification of quadrocopter model for control purposes

    Publication

    The 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

    The 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...

  • Transient detection for speech coding applications

    Signal 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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  • Algorithms of chemicals detection using raman spectra

    Raman 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

    Publication

    Solution 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...

  • Identification of regions of interest in video for a traffic monitoring system

    Publication

    - Year 2008

    A 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.

    Publication

    - Studia Geotechnica et Mechanica - Year 2003

    The 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...

  • Generalized Savitzky–Golay filters for identification of nonstationary systems

    Publication

    The 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

    Publication

    - Year 2011

    The 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

    The 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

    Publication

    The 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

    Publication

    - MECHATRONICS - Year 2016

    The 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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  • On the lower smoothing bound in identification of time-varying systems

    Publication

    - AUTOMATICA - Year 2008

    In 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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  • On ''cheap smoothing'' opportunities in identification of time-varying systems

    Publication

    - AUTOMATICA - Year 2008

    In 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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  • Visual Features for Endoscopic Bleeding Detection

    Aims: 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

    Publication

    Camera 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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  • Automatic audio-visual threat detection

    Publication

    - Year 2010

    The 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...

  • Rapid Assays for Specific Detection of Fungi of Scopulariopsis and Microascus Genera and Scopulariopsis brevicaulis Species

    Publication

    Purpose 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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  • Building Knowledge for the Purpose of Lip Speech Identification

    Consecutive 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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  • Direct detection of quantum entanglement

    Publication

    - PHYSICAL REVIEW LETTERS - Year 2002

    Basing 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.

  • A new assay for the simultaneous identification and differentiation of Klebsiella oxytoca strains.

    Publication

    - APPLIED MICROBIOLOGY AND BIOTECHNOLOGY - Year 2016

    Klebsiella 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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  • A Triplet-Learnt Coarse-to-Fine Reranking for Vehicle Re-identification

    Publication

    - Year 2020

    Vehicle 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...

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  • Exploring Neural Networks for Musical Instrument Identification in Polyphonic Audio

    Publication

    - IEEE INTELLIGENT SYSTEMS - Year 2024

    The 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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  • Identification of defected sensors in an array of amperometric gas sensors

    Purpose Amperometric gas sensors are commonly used in air quality monitoring in long-term measurements. Baseline shift of sensor responses and power failure may occur over time, which is an obstacle for reliable operation of the entire system. The purpose of this study is to check the possibility of using PCA method to detect defected samples, identify faulty sensor and correct the responses of the sensor identified as faulty. Design/methodology/approach In...

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  • Comparison of edge detection algorithms for electric wire recognition

    Publication

    Edge 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

    Publication

    - TRAC-TRENDS IN ANALYTICAL CHEMISTRY - Year 2024

    In 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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  • Identification of Bodner-Partom model parameters for technical fabrics

    Publication

    The thorough analysis of modeling technical fabrics behavior with the viscoplastic Bodner-Partom constitutive law is presented. The study has been focused on differences between the warp and weft direction of the material. To obtain the model’s parameters only the uniaxial tensile laboratory tests with three different, but constant strain rates are required. The parameters have been found for polyester fibers PVC coated fabrics:...

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  • Chemical identification of rubber fender sample and hardness and density measurements

    Publication

    - Year 2015

    Scope of testing: Chemical identification of rubber fender sample and hardness and density measurements. - Raport z badań zleconych - Numer umowy: 031178

  • Rating by detection: an artifact detection protocol for rating EEG quality with average event duration

    Publication
    • D. Węsierski
    • M. R. Rufuie
    • O. Milczarek
    • W. Ziembla
    • P. Ogniewski
    • A. Kołodziejak
    • P. Niedbalski

    - Journal of Neural Engineering - Year 2023

    Quantitative 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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  • On noncausal weighted least squares identification of nonstationary stochastic systems

    Publication

    - AUTOMATICA - Year 2011

    In 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 (windowed) 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...

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  • Toward Robust Pedestrian Detection With Data Augmentation

    Publication

    In this article, the problem of creating a safe pedestrian detection model that can operate in the real world is tackled. While recent advances have led to significantly improved detection accuracy on various benchmarks, existing deep learning models are vulnerable to invisible to the human eye changes in the input image which raises concerns about its safety. A popular and simple technique for improving robustness is using data...

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  • Regularized Local Basis Function Approach to Identification of Nonstationary Processes

    The 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...

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  • PCR detection of Scopulariopsis brevicaulis

    Scopulariopsis brevicaulis is known as a most common etiological factor of the mould toenail infections. There are also reports indicating that S. brevicaulis could cause organ and disseminated infections. Nowadays microscopic observations from the direct sample and culture are crucial for the appropriate recognition of the infection. In this paper is presented a PCR-based method for S. brevicaulis detection. The specificity of...

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  • A New Method of Noncausal Identification of Time-varying Systems

    The paper shows that the problem of noncausal identification of a time-varying FIR (finite impulse response) sys- tem can be reformulated, and solved, as a problem of smoothing of the preestimated parameter trajectories. Characteristics of the smoothing filter should be chosen so as to provide the best trade- off between the bias and variance of the resulting estimates. It is shown that optimization of the smoothing operation can...

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  • A framework for automatic detection of abandoned luggage in airport terminal

    Publication

    A framework for automatic detection of events in a video stream transmitted from a monitoring system is presented. The framework is based on the widely used background subtraction and object tracking algorithms. The authors elaborated an algorithm for detection of left and removed objects based on mor-phological processing and edge detection. The event detection algorithm collects and analyzes data of all the moving objects in...

  • A new look at the statistical identification of nonstationary systems

    Publication

    The paper presents a new, two-stage approach to identification of linear time-varying stochastic systems, based on the concepts of preestimation and postfiltering. The proposed preestimated parameter trajectories are unbiased but have large variability. Hence, to obtain reliable estimates of system parameters, the preestimated trajectories must be further filtered (postfiltered). It is shown how one can design and optimize such...

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  • Face detection algorithms evaluation for the bank client verification

    Publication

    Results of investigation of face detection algorithms in the video sequences are presented in the paper. The recordings were made with a miniature industrial USB camera in real conditions met in three bank operating rooms. The aim of the experiments was to check the practical usability of the face detection method in the biometric bank client verification system. The main assumption was to provide as much as possible user interaction...

  • Metals and metal-binding ligands in wine: Analytical challenges in identification.

    Background Due to important role of metals in the vinification process as well as their impact on the human health, their content in this alcoholic beverage has been extensively studied by many researchers. It is already known that speciation of metals determines their toxicity and bioavailability as well as influences their activity. Understanding the chemistry and knowing the structures of metal complexes could have relevant...

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  • Direct spectrum detection based on Bayesian approach

    The paper investigates the Bayesian framework's performance for a direct detection of spectrum parameters from the compressive measurements. The reconstruction signal stage is eliminated in by the Bayesian Compressive Sensing algorithm, which causes that the computational complexity and processing time are extremely reduced. The computational efficiency of the presented procedure is significantly...

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  • Automatic Incident Detection at Intersections with Use of Telematics

    While there are many examples of Intelligent Transport System deployments in Poland, more attention should be paid to traffic incident management and detection on dual-carriageways and urban street networks. One of the aims of CIVITAS DYN@MO, a European Union funded project, is to use TRISTAR (an Urban Transport Management System) detection modules to detect incidents at junctions equipped with traffic signals. First part of paper...

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  • Efficient algorithm for blinking LED detection dedicated to embedded systems equipped with high performance cameras

    Publication

    This paper presents the concept and implementation of an efficient algorithm for detection of blinking LED or similar signal sources. Algorithm is designed for embedded devices equipped with high performance cameras being a part of an indoor positioning embedded system. An algorithm to be implemented in such a system should be efficient in terms of computational power what is hard to be achieved when large amount of data from camera...

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  • Detection of impulsive disturbances in archive audio signals

    Publication

    In this paper the problem of detection of impulsive disturbances in archive audio signals is considered. It is shown that semi-causal/noncausal solutions based on joint evaluation of signal prediction errors and leave-one-out signal interpolation errors, allow one to noticeably improve detection results compared to the prediction-only based solutions. The proposed approaches are evaluated on a set of clean audio signals contaminated...

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  • Loop-mediated isothermal amplification (LAMP) as a diagnostic tool in detection of infectious diseases

    Publication

    Loop-mediated isothermal amplification (LAMP) is a gene amplification method which amplifies DNA with high specificity and efficiency under isothermal conditions. Because of its rapidity and simplicity, it is a valuable diagnostic tool in the early detection and identification of infectious diseases. LAMP method is based on the use of a set of four to six specially designed primers spanning six to eight distinct sequences on the...

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