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    Wyświetlanie 1-15 z 15
    Tytuł:
    Application of stereology for assessment of two-phase flow structures
    Autorzy:
    Masiukiewicz, M.
    Ulbrich, R.
    Zając, D.
    Powiązania:
    https://bibliotekanauki.pl/articles/175510.pdf
    Data publikacji:
    2013
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    stereological analysis
    two-phase flow pattern
    pattern recognition
    Opis:
    This paper describes a method for two-phase flow structures evaluation of gas-liquid mixture based on theoretical assumptions for the stereology in materials science. This assessment is based on the analysis of digital images, obtained with a high-speed camera. The bright field technique was used for process visualization. The images obtained during the visualisation were, in fact, projections of the structures. For the given recording conditions, the stereological analysis applied was based on the linear method and on the method of random and directed secants. The new methods of determining important parameters of two-phase flow were proposed on the basis of collected data. The parameters are as follows: the volume fraction, the interfacial area, the number of objects in one of the phases of the mixture and two other structural parameters of the selected two-phase fluid obtained from the analysis of the two-dimensional image (average length of chords for projected objects, average free distance for convex shapes from the projection).
    Źródło:
    Transactions of the Institute of Fluid-Flow Machinery; 2013, 125; 39-54
    0079-3205
    Pojawia się w:
    Transactions of the Institute of Fluid-Flow Machinery
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Automatic detection and counting of platelets in microscopic image
    Autorzy:
    Burduk, R.
    Krawczyk, B.
    Powiązania:
    https://bibliotekanauki.pl/articles/333065.pdf
    Data publikacji:
    2010
    Wydawca:
    Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
    Tematy:
    rozpoznawanie wzorców
    nauczanie maszynowe
    analiza obrazu
    pattern recognition
    bioinformatic
    machine learning
    image analysis
    platelet
    Opis:
    In this paper we present a machine learning-based approach for detecting platelet cells in microscopic smear images. Counting how many platelets appeared in each smear image is one of the basic tasks done in many laboratories. In many cases this is still done by a human — laboratory technician. Due to very small size and often great quantity of those cells, precise estimating of the number of platelets is not a trivial task. As in all man-dependent problems the whole process is very sensitive to errors, time-consuming and its accuracy is limited by human perception. We propose alternative, fully automatic solution that is free of those drawbacks. Our idea is based on the combination of techniques driven from two fields of modern computer science: the image analysis and pattern recognition ⁄ machine learning. It not only reduces the error rate, but, what is more important, also decreases the time needed for each smear image analysis. The obtained results are very satisfying and our solution is more precise than estimation based on human perception. This will improve the quality of laboratory work and allow to save time that can be spent on other important tasks.
    Źródło:
    Journal of Medical Informatics & Technologies; 2010, 16; 173-178
    1642-6037
    Pojawia się w:
    Journal of Medical Informatics & Technologies
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Classification of vehicles in motion based on ground vibration
    Autorzy:
    Bartmański, C.
    Powiązania:
    https://bibliotekanauki.pl/articles/114089.pdf
    Data publikacji:
    2015
    Wydawca:
    Stowarzyszenie Inżynierów i Techników Mechaników Polskich
    Tematy:
    vibroacoustics
    digital signal processing
    wavelet analysis
    pattern recognition
    Opis:
    The paper presents a method of measuring the structure of traffic, based on the ground vibration generated by moving vehicles. The measuring system, which uses the presented method, works according to a classical model of pattern recognition process. The method of extracting features based on the wavelet transform was developed. The choice of the classifier’s algorithm was made experimentally. The algorithms were tested using signal recordings performed in typical road conditions.
    Źródło:
    Measurement Automation Monitoring; 2015, 61, 3; 72-75
    2450-2855
    Pojawia się w:
    Measurement Automation Monitoring
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Closest paths in graph drawings under an elastic metric
    Autorzy:
    Baran, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/330666.pdf
    Data publikacji:
    2018
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    elastic shape analysis
    pattern recognition
    superpixel segmentation
    analiza kształtu
    rozpoznawanie wzorca
    segmentacja obrazu
    superpiksel
    Opis:
    This work extends the dynamic programming approach to calculation of an elastic metric between two curves to finding paths in pairs of graph drawings that are closest under this metric. The new algorithm effectively solves this problem when all paths between two given nodes in one of these graphs have the same length. It is then applied to the problem of pattern recognition constrained by a superpixel segmentation. Segmentations of test images, obtained without statistical modeling given two shape endpoints, have good accuracy.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2018, 28, 2; 387-397
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Could k-NN classifier be Useful in tree leaves recognition?
    Autorzy:
    Horaisová, K.
    Powiązania:
    https://bibliotekanauki.pl/articles/229900.pdf
    Data publikacji:
    2014
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    binary image
    Fourier transform
    affine invariance
    harmonic analysis
    pattern recognition
    k-NN classifier
    Opis:
    This paper presents a method for affine invariant recognition of two-dimensional binary objects based on 2D Fourier power spectrum. Such function is translation invariant and their moments of second order enable construction of affine invariant spectrum except of the rotation effect. Harmonic analysis of samples on circular paths generates Fourier coefficients whose absolute values are affine invariant descriptors. Affine invariancy is approximately saved also for large digital binary images as demonstrated in the experimental part. The proposed method is tested on artificial data set first and consequently on a large set of 2D binary digital images of tree leaves. High dimensionality of feature vectors is reduced via the kernel PCA technique with Gaussian kernel and the k-NN classifier is used for image classification. The results are summarized as k-NN classifier sensitivity after dimensionality reduction. The resulting descriptors after dimensionality reduction are able to distinguish real contours of tree leaves with acceptable classification error. The general methodology is directly applicable to any set of large binary images. All calculations were performed in the MATLAB environment.
    Źródło:
    Archives of Control Sciences; 2014, 24, 2; 177-192
    1230-2384
    Pojawia się w:
    Archives of Control Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Detection of human eye components on the basis of multispectral imaging
    Autorzy:
    Michalak, M.
    Nurzyńska, K.
    Świtoński, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/333415.pdf
    Data publikacji:
    2012
    Wydawca:
    Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
    Tematy:
    rozpoznawanie wzorców
    analiza wielospektralna
    przetwarzanie obrazów
    segmentacja obrazu
    pattern recognition
    multispectral analysis
    image processing
    image segmentation
    Opis:
    In this paper the methods for selecting of the most important parts of the human eyes are described. On the basis of the real 21 channel multispectral images the model of finding the lens and the spot are defined. These methods are based on the most popular algorithms of image processing. The approach to veins detection is still undefined but in the article the most important channels are pointed out and the channel difference between eyelash and the veins is also mentioned.
    Źródło:
    Journal of Medical Informatics & Technologies; 2012, 19; 41-47
    1642-6037
    Pojawia się w:
    Journal of Medical Informatics & Technologies
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Don’t fight the tape! Technical Analysis Momentum and Contrarian Signals as Common Cognitive Biases
    Autorzy:
    Zielonka, Piotr
    Białaszek, Wojciech
    Biedrzycki, Paweł
    Dzik, Bartłomiej
    Powiązania:
    https://bibliotekanauki.pl/articles/1933544.pdf
    Data publikacji:
    2020-02
    Wydawca:
    Akademia Leona Koźmińskiego w Warszawie
    Tematy:
    technical analysis
    pattern recognition
    cognitive biases
    momentum
    contrarian
    Opis:
    Purpose: Stock market participants use technical analysis to seek trends in stock price charts despite its doubtful efficiency. We tested whether technical analysis signals represent typical and common cognitive biases associated with the continuation or reversal of the trend. Methodology: We compared investors’ opinions about the predictive power of technical analysis signals grouped into five conditions: real technical analysis signals associated with trend continuation (real momentum signals) or trend reversal (real contrarian signals), fake momentum or fake contrarian signals, and fluctuation signals. Findings: Investors assigned larger predictive power to real and fake signals associated with trend continuation than to signals associated with trend reversal. Fake signals, which represented cognitive biases, elicited similar predictions about trend continuation or reversal to real technical analysis signals. Originality: Market players assess momentum signals to have greater predictive power than contrarian signals and neutral signals to have the least predictive power. These results are independent of whether technical analysis signals were well-known to investors or made up by experimenters. The hardwired propensity of our brains to detect patterns combined with the non-natural environment of the stock market creates the illusion of expertise that is not easy to dispel.
    Źródło:
    Central European Management Journal; 2020, 28(2); 98-110
    2658-0845
    2658-2430
    Pojawia się w:
    Central European Management Journal
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Estimation of significance of AlkB and AlkA proteins in DNA repair in Escherichia coli model
    Autorzy:
    Sokołowska, B.
    Maciejewska, A. M.
    Jóźwik, A.
    Kuśmierek, J. T.
    Powiązania:
    https://bibliotekanauki.pl/articles/333316.pdf
    Data publikacji:
    2011
    Wydawca:
    Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
    Tematy:
    rozpoznawanie obrazów
    klasyfikator najbliższych sąsiadów
    analiza cech pracy odbiornika
    naprawa DNA
    adaptacyjna odpowiedź
    powstawanie mutacji
    bakterie e.coli
    pattern recognition
    fuzzy k-NN classifier
    ROC analysis
    DNA repair
    adaptive response
    mutagenesis
    AlkB dioxygenase
    AlkA glycosylase
    E.coli
    Opis:
    The paper concerns estimation of significance of differences of mutagenesis level between the wild-type strain (wt) and its derivatives which differ in DNA repair ability, namely alkA and alkB strain, devoided AlkA glycosylase and AlkB dioxygenase activity, respectively. The strains were analyzed for their ability to repair 1,N6-ethenoadenine (εA) - chloroacetaldehyde adduct to DNA. The analysis was done using classical statistical and pattern recognition methods. The obtained results confirmed that AlkB dioxygenase plays the most important role in εA repair in E. coli in the experimental modeling.
    Źródło:
    Journal of Medical Informatics & Technologies; 2011, 17; 321-326
    1642-6037
    Pojawia się w:
    Journal of Medical Informatics & Technologies
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Hidden Context Influence on Pattern Recognition
    Autorzy:
    Kulikowski, J. L.
    Powiązania:
    https://bibliotekanauki.pl/articles/307822.pdf
    Data publikacji:
    2013
    Wydawca:
    Instytut Łączności - Państwowy Instytut Badawczy
    Tematy:
    decision making
    hidden information
    intuition
    pattern recognition
    scene analysis
    Opis:
    The influence of hidden additional information concerning the circumstances of input data acquisition on the quality of decisions based on the data is considered. An analogue to the intuition influencing natural decision making is indicated. The problem of contextual information in decision making based on Bayes rule, on reference data sets in various applications as well as of scene analysis by numerous examples is illustrated.
    Źródło:
    Journal of Telecommunications and Information Technology; 2013, 1; 72-78
    1509-4553
    1899-8852
    Pojawia się w:
    Journal of Telecommunications and Information Technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    IMAGE PATTERN ANALYSIS WITH IMAGE POTENTIAL TRANSFORM
    Autorzy:
    Oleg, Butusov
    Dikusar, Vasily
    Powiązania:
    https://bibliotekanauki.pl/articles/452838.pdf
    Data publikacji:
    2018
    Wydawca:
    Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Katedra Ekonometrii i Statystyki
    Tematy:
    binary image transform
    distance and potential transform
    statistical indices
    geometric signatures
    pattern analysis
    pattern recognition
    Opis:
    Pattern analysis with image transform based on potential calculation was considered. Initial gray-scale image is sliced into equidistant levels and resulting binary image was prepared by joining of some levels to one binary image. Binary image was transformed under assumption that white pixels in it may be considered as electric charges or spins. Using this assumption Ising model and Coulomb model interaction between white pixels was used for image potential transform. The transform was calculated using moving window. The resulting gray-scale image was again transformed to binary image using the thresholding on 0.5 level. Further binary images were analyzed using statistical indices (average, standard deviation, skewness, kurtosis) and geometric signatures: area, eccentricity, Euler number, orientation and perimeter. It was found that the most suitable geometric signature for pattern configuration analysis of Ising potential transform (IPT) and Coulomb potential transform (CPT) is area value. Similarly the most suitable statistics is distance statistics between white pixels.
    Źródło:
    Metody Ilościowe w Badaniach Ekonomicznych; 2018, 19, 1; 12-27
    2082-792X
    Pojawia się w:
    Metody Ilościowe w Badaniach Ekonomicznych
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Intelligent pattern recognition of SLM machine energy data
    Autorzy:
    Uhlmann, E.
    Pastl Pontes, R.
    Laghmouchi, A.
    Hohwieler, E.
    Feitscher, R.
    Powiązania:
    https://bibliotekanauki.pl/articles/99469.pdf
    Data publikacji:
    2017
    Wydawca:
    Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
    Tematy:
    pattern recognition
    data analysis
    additive manufacturing
    energy data
    Opis:
    Selective Laser Melting (SLM) is an additive manufacturing process, in which the research has been increasing over the past few years to meet customer-specific requirements. Different parameters from the process and the machine components have been monitored in order to obtain vital information such as productivity of the machine and quality of the manufactured workpiece. The monitoring of parameters related to energy is also realized, but the utilisation of such data is usually performed for determining basic information, for instance, from energy consumption. By applying machine learning algorithms on these data, it is possible to identify not only the steps of the manufacturing process, but also its behaviour patterns. Along with these algorithms, evidences regarding the conditions of components and anomalies can be detected in the acquired data. The results can be used to point out the process errors and component faults and can be adopted to analyse the energy efficiency of the SLM process by comparing energy consumption of one single layer during the manufacturing of different components. Moreover, the state of the manufacturing process and the machine can be determined automatically and applied to predict failures in order to launch appropriate counter measures.
    Źródło:
    Journal of Machine Engineering; 2017, 17, 2; 65-76
    1895-7595
    2391-8071
    Pojawia się w:
    Journal of Machine Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Local embedding and dimensionality reduction in detection of skin tumor tissue
    Autorzy:
    Michalak, M.
    Świtoński, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/333429.pdf
    Data publikacji:
    2012
    Wydawca:
    Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
    Tematy:
    rozpoznawanie wzorców
    analiza wielospektralna
    redukcja wymiarowości
    selekcja cech
    pattern recognition
    multispectral analysis
    dimensionality reduction
    feature selection
    Opis:
    This article shows the limitation of the usage of dimensionality reduction methods. For this purpose three algorithms were analyzed on the real medical data. This data are multispectral images of human skin labeled as tumor or non-tumor regions. The classification of new data required the special algorithm of new data mapping that is also described in the paper. Unfortunately, the final conclusion is that this kind of local embedding algorithms should not be recommended for this kind of analysis and prediction.
    Źródło:
    Journal of Medical Informatics & Technologies; 2012, 19; 59-65
    1642-6037
    Pojawia się w:
    Journal of Medical Informatics & Technologies
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Multi-parameter data visualization by means of principal component analysis (PCA) in qualitative evaluation of various coal types
    Autorzy:
    Niedoba, T.
    Powiązania:
    https://bibliotekanauki.pl/articles/109595.pdf
    Data publikacji:
    2014
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    principal component analysis
    PCA
    multi-parameter data visualization
    coal
    identification of data
    covariance matrix
    pattern recognition
    Opis:
    Multi-parameter data visualization methods are a modern tool allowing to classify some analyzed objects. When it comes to grained materials, e.g. coal, many characteristics have an influence on the material quality. Besides the most obvious features like particle size, particle density or ash contents, coal has many other qualities which show significant differences between the studied types of material. The paper presents the possibility of applying visualization techniques for coal type identification and determination of significant differences between various types of coal. The Principal Component Analysis was applied to achieve this purpose. Three types of coal 31, 34.2 and 35 (according to Polish classification of coal types) were investigated, which were initially screened on sieves and subsequently divided into density fractions. Next, each size-density fraction was analyzed chemically to obtain other characteristics. It was pointed out that the applied methodology allowed to identify certain coal types efficiently, which makes it useful as a qualitative criterion for grained materials. However, it was impossible to provide such identification based on contrastive comparisons of all three types of coal. The presented methodology is a new way of analyzing data concerning widely understood mineral processing.
    Źródło:
    Physicochemical Problems of Mineral Processing; 2014, 50, 2; 575-589
    1643-1049
    2084-4735
    Pojawia się w:
    Physicochemical Problems of Mineral Processing
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Selection of the most important components from multispectral images for detection of tumor tissue
    Autorzy:
    Michalak, M.
    Świtoński, A.
    Stawarz, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/951663.pdf
    Data publikacji:
    2011
    Wydawca:
    Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
    Tematy:
    rozpoznawanie obrazów
    analiza wielospektralna
    obniżenie wymiarowości
    wybór funkcji
    pattern recognition
    multispectral analysis
    dimensionality reduction
    feature selection
    Opis:
    The problem raised in this article is the selection of the most important components from multispectral images for the purpose of skin tumor tissue detection. It occured that 21 channel spectrum makes it possible to separate healthy and tumor regions almost perfectly. The disadvantage of this method is the duration of single picture acquisition because this process requires to keep the device very stable. In the paper two approaches to the problem are presented: hill climbing strategy and some ranking methods.
    Źródło:
    Journal of Medical Informatics & Technologies; 2011, 17; 303-308
    1642-6037
    Pojawia się w:
    Journal of Medical Informatics & Technologies
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Wybrane parametry stereologiczne w identyfikacji struktur przepływu mieszaniny dwufazowej gaz-ciecz
    Selected stereological parameters for the identification of two-phase gas - liquid mixture flow structures
    Autorzy:
    Masiukiewicz, M.
    Ulbrich, R.
    Powiązania:
    https://bibliotekanauki.pl/articles/2072208.pdf
    Data publikacji:
    2013
    Wydawca:
    Stowarzyszenie Inżynierów i Techników Mechaników Polskich
    Tematy:
    analiza stereologiczna
    struktura przepływu dwufazowego
    identyfikacja struktury
    stereological analysis
    two-phase flow pattern
    pattern recognition
    Opis:
    Ukazano zastosowanie metody identyfikacji struktury mieszaniny wielofazowej opartej na analizie obrazu metodami stereologicznymi. Badania realizowano w kanale prostokątnym szczelinowym i czterech minikanałach dla pionowego współprądowego przepływu mieszaniny powietrzno-wodnej. Obliczono pięć parametrów stereologicznych, na podstawie których dokonano ilościowej i jakościowej oceny struktury. Informacje te umożliwiają sprawowanie kontroli nad urządzeniem, w którym taki przepływ zachodzi.
    The paper illustrates the method of multi-phase mixture structure identification based on image analysis with stereological methods. The study was conducted in a rectangular slot channel and in minichannels for vertical co- current flow of air - water mixture. The quantitative and qualitative assessment of flow structure was calculated on basis of five specific stereological parameters. These information enable the control of device in which the flow occurs.
    Źródło:
    Inżynieria i Aparatura Chemiczna; 2013, 5; 445--446
    0368-0827
    Pojawia się w:
    Inżynieria i Aparatura Chemiczna
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-15 z 15

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