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Wyszukujesz frazę "degradation indicator" wg kryterium: Temat

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    Wyświetlanie 1-3 z 3
    Tytuł:
    Sulphur and heavy metals content in the soil of meadow ecosystems adjoining the metallurgic plant Huta Katowice as an indicator of environment degradation
    Autorzy:
    Kimsa, T
    Pawelko, K.
    Ciepal, R.
    Palowski, B.
    Sliwinska-Wyrzychowska, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/1450127.pdf
    Data publikacji:
    2001
    Wydawca:
    Polska Akademia Nauk. Instytut Agrofizyki PAN
    Tematy:
    sulphur
    degradation indicator
    soil
    soil property
    environment degradation
    Upper Silesian Industrial Area
    degraded ecosystem
    anthropogenic ecosystem
    meadow ecosystem
    heavy metal
    Opis:
    The content of Cu, Pb, Zn, Fe, Cd and S in the upper soil layer of meadow ecosystems surrounding the steelworks "Huta Katowice" was investigated. Sampling plots were located at a different distance and direction from the plant, but in a similar type of meadow community and soil. Spatial and seasonal variability of the investigated elements content was found. Such results indicate that the investigated area was polluted both by that steelworks and by the industrial plants situated in the Industrial Region of Upper Silesia.
    Źródło:
    Acta Agrophysica; 2001, 51; 101-111
    1234-4125
    Pojawia się w:
    Acta Agrophysica
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Environmental effects of using large rivers for irrigation in the Kazakhstan – Syr Darya case study
    Autorzy:
    Mustafayev, Zhumakhan
    Mosiej, Józef
    Abdyvalieva, Karlygas S.
    Kozykeeva, Alija
    Powiązania:
    https://bibliotekanauki.pl/articles/1844408.pdf
    Data publikacji:
    2020
    Wydawca:
    Instytut Technologiczno-Przyrodniczy
    Tematy:
    diversity index
    irrigation
    soil degradation
    Syr Darya River
    environmental risk indicator
    Opis:
    The issues discussed in the paper concern the assessment of changes in quantitative and qualitative indicators of water resources in the climatic conditions of the southern part of Kazakhstan. For this purpose, many years of systematic field observations and other continuous data obtained from the functioning measurement and observation stations operating within the Aral-Syrdarya Basin Inspection were used. On the basis of the obtained data, indicators were determined that characterize the quantity and quality of water supplied to the soil in the irrigation process, as well as the quantity and quality of water flowing out of the drainage systems, together with an evaluation of the effectiveness of irrigation and drainage systems. Soil salinity was assessed in five irrigated massifs with a total area of 332.55 thous. ha. For the same irrigated massifs, the annual amounts of water taken for irrigation, the amount of outflowing water and the assessment of the mineralization level were determined. Based on the developed results of field observations characterizing the hydrological and environmental situation of the lower section of the Syr Darya River in 1960–2015, the negative reaction coefficients were calculated for the local population, soil and vegetation for five of the irrigated massifs of the Kyzylorda region. The ecological situation of the habitat of soil and plants in the lower reaches of the Syr Darya River in all irrigation areas deteriorates on a time scale, since as a result of the reclamation of agricultural lands, intensive secondary soil salinization occurs and the formation of infiltration runoff with high mineralization, contributing to the violation of the harmonization of the relationship between nature and man.
    Źródło:
    Journal of Water and Land Development; 2020, 47; 125-134
    1429-7426
    2083-4535
    Pojawia się w:
    Journal of Water and Land Development
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Degradation assessment of bearing based on machine learning classification matrix
    Autorzy:
    Kumar, Satish
    Kumar, Paras
    Kumar, Girish
    Powiązania:
    https://bibliotekanauki.pl/articles/1841739.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
    Tematy:
    degradation state
    health condition indicator
    machine learning
    diagnostic model
    prognostic model
    Opis:
    In the broad framework of degradation assessment of bearing, the final objectives of bearing condition monitoring is to evaluate different degradation states and to estimate the quantitative analysis of degree of performance degradation. Machine learning classification matrices have been used to train models based on health data and real time feedback. Diagnostic and prognostic models based on data driven perspective have been used in the prior research work to improve the bearing degradation assessment. Industry 4.0 has required the research in advanced diagnostic and prognostic algorithm to enhance the accuracy of models. A classification model which is based on machine learning classification matrix to assess the degradation of bearing is proposed to improve the accuracy of classification model. Review work demonstrates the comparisons among the available state-of-the-art methods. In the end, unexplored research technical challenges and niches of opportunity for future researchers are discussed.
    Źródło:
    Eksploatacja i Niezawodność; 2021, 23, 2; 395-404
    1507-2711
    Pojawia się w:
    Eksploatacja i Niezawodność
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

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