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    Wyświetlanie 1-5 z 5
    Tytuł:
    The penetration of topically applied ointment containing hyaluronic acid in rabbit tissues
    Autorzy:
    Birkenfeld, B.
    Parafiniuk, M.
    Bielecka-Grzela, S.
    Klimowicz, A.
    Piwowarska-Bilska, H.
    Mikolajczak, R.
    Listewnik, M.H.
    Kurzejamska-Parafiniuk, M.
    Osowski, A.
    Byszewska-Szpocinska, E.
    Powiązania:
    https://bibliotekanauki.pl/articles/30258.pdf
    Data publikacji:
    2011
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Opis:
    The properties of hyaluronic acid used for treatment of acute and chronic joint disease are known for many years and this compound is widely used both in humans and animals. To obtain a therapeutic effect of a certain drug, the appropriate concentration in the target organ or tissue is important. The application of labeled compounds is one of the frequently applied techniques to estimate drug penetration into the skin and other body tissues or organs. The aim of the study was to evaluate the penetration of hyaluronic acid labeled with I-131 through the skin and its distribution within the knee joint and other internal organs in rabbits after a topical application of an ointment containing hyaluronic acid.The experiment was performed on 22 albino rabbits divided into control and examined groups. Fifteen rabbits were exposed to the multicomponent ointment containing hyaluronic acid labeled with I-131. Time of exposure was 48 hours. Hyaluronate penetrated to a high degree into the examined tissues. No significant differences in terms of leg tissue activity were observed between a leg tissue exposed to labeled ointment and that unexposed, suggesting that after topical administration, the active component of the ointment is delivered to the joint via the blood stream. Hyaluronate applied topically penetrates through the skin into the rabbit tissues and organs and into the joint fluid of both legs (exposed and not exposed). This route of administration seems to be useful for this drug delivery and allows to avoid unnecessary side effects.
    Źródło:
    Polish Journal of Veterinary Sciences; 2011, 14, 4
    1505-1773
    Pojawia się w:
    Polish Journal of Veterinary Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Ensemble of data mining methods for gene ranking
    Autorzy:
    Wiliński, A.
    Osowski, S.
    Powiązania:
    https://bibliotekanauki.pl/articles/201570.pdf
    Data publikacji:
    2012
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    gene expression array
    feature selection
    gene ranking methods
    classification
    SVM
    Opis:
    The paper presents the ensemble of data mining methods for discovering the most important genes and gene sequences generated by the gene expression arrays, responsible for the recognition of a particular type of cancer. The analyzed methods include the correlation of the feature with a class, application of the statistical hypotheses, the Fisher measure of discrimination and application of the linear Support Vector Machine for characterization of the discrimination ability of the features. In the first step of ranking we apply each method individually, choosing the genes most often selected in the cross validation of the available data set. In the next step we combine the results of different selection methods together and once again choose the genes most frequently appearing in the selected sets. On the basis of this we form the final ranking of the genes. The most important genes form the input information delivered to the Support Vector Machine (SVM) classifier, responsible for the final recognition of tumor from non-tumor data. Different forms of checking the correctness of the proposed ranking procedure have been applied. The first one is relied on mapping the distribution of selected genes on the two-coordinate system formed by two most important principal components of the PCA transformation and applying the cluster quality measures. The other one depicts the results in the graphical form by presenting the gene expressions in the form of pixel intensity for the available data. The final confirmation of the quality of the proposed ranking method are the classification results of recognition of the cancer cases from the non-cancer (normal) ones, performed using the Gaussian kernel SVM. The results of selection of the most significant genes used by the SVM for recognition of the prostate cancer cases from normal cases have confirmed a good accuracy of results. The presented methodology is of potential use for practical application in bioinformatics.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2012, 60, 3; 461-470
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Deep learning: theory and practice
    Autorzy:
    Cichocki, A.
    Poggio, T.
    Osowski, S.
    Lempitsky, V.
    Powiązania:
    https://bibliotekanauki.pl/articles/202346.pdf
    Data publikacji:
    2018
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    deep learning
    networks
    theory
    practice
    uczenie głębokie
    sieci
    teoria
    praktyka
    Opis:
    This Special Section of the Bulletin of the Polish Academy of Sciences on Technical Sciences is devoted to theoretical aspects of deep machine learning as well as practical applications in some areas of signal and image processing, particularly in bioengineering.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2018, 66, 6; 757-759
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Improving the credibility of the extracted position from a vast collection of job offers with machine learning ensemble methods
    Autorzy:
    Drozda, Paweł
    Ropiak, Krzysztof
    Nowak, Bartosz A.
    Talun, Arkadiusz
    Osowski, Maciej
    Powiązania:
    https://bibliotekanauki.pl/articles/22615539.pdf
    Data publikacji:
    2023
    Wydawca:
    Uniwersytet Warmińsko-Mazurski w Olsztynie
    Tematy:
    machine learning
    web scraping
    granularity method
    classification
    Opis:
    The main aim of this paper is to evaluate crawlers collecting the job offers from websites. In particular the research is focused on checking the effectiveness of ensemble machine learning methods for the validity of extracted position from the job ads. Moreover, in order to significantly reduce the training time of the algorithms (Random Forests and XGBoost), granularity methods were also tested to significantly reduce the input training dataset. Both methods achieved satisfactory results in accuracy and F1 measures, which exceeded 96%. In addition, granulation reduced the input dataset by more than 99%, and the results obtained were only slightly worse (accuracy between 1% and 5%, F1 between 3% and 8%). Thus, it can be concluded that the considered methods can be used in the evaluation of job web crawlers.
    Źródło:
    Technical Sciences / University of Warmia and Mazury in Olsztyn; 2023, 26(1); 125--140
    1505-4675
    2083-4527
    Pojawia się w:
    Technical Sciences / University of Warmia and Mazury in Olsztyn
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Developing automatic recognition system of drill wear in standard laminated chipboard drilling process
    Autorzy:
    Kurek, J.
    Kruk, M.
    Osowski, S.
    Hoser, P.
    Wieczorek, G.
    Jegorowa, A.
    Górski, J.
    Wilkowski, J.
    Śmietańska, K.
    Kossakowska, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/200766.pdf
    Data publikacji:
    2016
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    diagnostic expert systems
    neural networks
    wavelet packets
    wear monitoring
    diagnostyczny system ekspercki
    sieci neuronowe
    pakiety falkowe
    monitorowanie zużycia
    Opis:
    The paper presents an automatic approach to recognition of the drill condition in a standard laminated chipboard drilling process. The state of the drill is classified into two classes: “useful” (sharp enough) and “useless” (worn out). The case “useless” indicates symptoms of excessive drill wear, unsatisfactory from the point of view of furniture processing quality. On the other hand the “useful” state identifies tools which are still able to drill holes acceptable due to the required processing quality. The main problem in this task is to choose an appropriate set of diagnostic features (variables), based on which the recognition of drill state (“useful” versus “useless”) can be made. The features have been generated based on 5 registered signals: feed force, cutting torque, noise, vibration and acoustic emission. Different statistical parameters describing these signals and also their Fourier and wavelet representations have been used for defining the features. Sequential feature selection is applied to detect the most class discriminative set of features. The final step of recognition is done by using three types of classifiers, including support vector machine, ensemble of decision trees and random forest. Six standard drills of 12 mm diameter with tungsten carbide tips were used in experiments. The results have confirmed good quality of the proposed diagnostic system.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2016, 64, 3; 633-640
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-5 z 5

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