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Wyświetlanie 1-2 z 2
Tytuł:
Invasive vs. Non-Invasive Methods in Estimating Slope Stability, with Application in the Copou Area, Iaşi, Romania
Autorzy:
Pascariu, F.
Negru, C.
Şaramet, M.
Chelariu, C.
Powiązania:
https://bibliotekanauki.pl/articles/1401973.pdf
Data publikacji:
2015-08
Wydawca:
Polska Akademia Nauk. Instytut Fizyki PAN
Tematy:
91.30.pd
91.62.Ty
92.40.Ha
Opis:
Slope stability analysis represents nowadays a constant pursuit, being applied in various domains, such as geological and geomorphological studies, civil engineering or urban expansion. In this paper, two different methods were employed in order to establish the stability of the Copou Hill, Iaşi, Romania, and the results were compared. The first, non-invasive, method involves obtaining a landslide risk map by identifying the factors that induce the slope failure and overlaying the obtained maps. The second one, invasive, implies computing a safety factor using the infinite slope method, employing well data from this area and ranging the thickness of the water column. This comparison was made in order to improve the non-invasive method, so as to apply it in areas where there is no geological information. The resulting landslide risk map shows values of the average coefficient Kₘ ranging between 0.21 and 0.63, implying a medium to high failure probability for the studied slope. On the other hand, the infinite slope method indicates a safety factor with values between 0.91 and 1.49, at a complete flooding of the land-sliding lithological column, with a single exception with much lower value. These values are below the admissible factor, suggesting failure with a medium to high probability. Comparing these two methods, significant similarities between the landslide risk map results and the computed safety factors can be observed. For further testing of the first method, similar studies should also be made in other areas.
Źródło:
Acta Physica Polonica A; 2015, 128, 2B; B-193-B-196
0587-4246
1898-794X
Pojawia się w:
Acta Physica Polonica A
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A hybrid scheduler for many task computing in big data systems
Autorzy:
Vasiliu, L.
Pop, F.
Negru, C.
Mocanu, M.
Cristea, V.
Kolodziej, J.
Powiązania:
https://bibliotekanauki.pl/articles/907647.pdf
Data publikacji:
2017
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
many task computing
scheduling heuristics
QoS
big data system
simulation
obliczenia wielofunkcyjne
szeregowanie zadań
duży zbiór danych
Opis:
With the rapid evolution of the distributed computing world in the last few years, the amount of data created and processed has fast increased to petabytes or even exabytes scale. Such huge data sets need data-intensive computing applications and impose performance requirements to the infrastructures that support them, such as high scalability, storage, fault tolerance but also efficient scheduling algorithms. This paper focuses on providing a hybrid scheduling algorithm for many task computing that addresses big data environments with few penalties, taking into consideration the deadlines and satisfying a data dependent task model. The hybrid solution consists of several heuristics and algorithms (min-min, min-max and earliest deadline first) combined in order to provide a scheduling algorithm that matches our problem. The experimental results are conducted by simulation and prove that the proposed hybrid algorithm behaves very well in terms of meeting deadlines.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2017, 27, 2; 385-399
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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