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Metoda diagnostyki cieplno-przepływowej turbin parowych wykorzystująca elementy algorytmów genetycznych
PublikacjaRozprawa doktorska poświęcona jest opisowi budowania metody diagnostyki cieplno-przepływowej z wykorzystaniem elementów algorytmów genetycznych. Do tworzenia założeń i algorytmów metody posłużono się przykładem funkcjonowania bloku elektrowni kondensacyjnej ze szczególnym uwzględnieniem układu łopatkowego turbiny parowej. Celem pracy jest zbudowanie metody diagnostyki cieplno-przepływowej. Zadaniem metody jest przeprowadzenie procesu...
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CANCER DETECTION AND PREVENTION
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Biomolecular Detection and Quantification
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Journal of Forensic Identification
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MODELING IDENTIFICATION AND CONTROL
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PCR test for Microsporum canis identification
PublikacjaMicrosporum canis, for which the natural hosts are cats and dogs, is the most prevalent zoophilic agent causing tinea capitis and tinea corporis in humans. We present here a diagnostic PCR test for M. canis, since its detection and species identification is relevant to the choice of treatment and to the understanding of a probable source of infection. An M. canis-specific PCR was evaluated using 130 clinical isolates of dermatophytes...
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Molecular detection of Candida krusei
PublikacjaThe species identification of fungi belonging to genus Candida is an important issue as this genus becomes the emerging problem of nosocomial infections. As Candida krusei presents intrinsicresistance to the fluconazole that is the drug of the first choice in case of invasive candidiasis the PCR identifying the DNA of C. krusei was elaborated. The analytical sensitivity of the assay on spiked blood samples was estimated at 3-5...
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System identification 2021/22 - project
Kursy Online -
System identification 2022/23 - project
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Towards Robust Identification of Nonstationary Systems
PublikacjaThe 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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Radiation Detection Technology and Methods
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Open-Set Speaker Identification Using Closed-Set Pretrained Embeddings
PublikacjaThe 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
PublikacjaThe 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
PublikacjaThe 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
PublikacjaIn 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
PublikacjaDamage 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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Cascade Object Detection and Remote Sensing Object Detection Method Based on Trainable Activation Function
PublikacjaObject 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
PublikacjaThe 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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Detection of Toxoplasma gondii oocysts in environmental samples
PublikacjaToxoplasma 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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Identification of models and signals robust to occasional outliers
PublikacjaIn 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,...