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Wyszukujesz frazę "Ahmed, S." wg kryterium: Autor


Wyświetlanie 1-2 z 2
Tytuł:
Impact of wood-derived biochar on the hydraulic characteristics of compacted soils: Its influence on simulated farmland carbon sequestration
Autorzy:
Ahmed, A.
Kurian, J.
Satyanarayana, S.
Raghavan, V.
Powiązania:
https://bibliotekanauki.pl/articles/2083067.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Instytut Agrofizyki PAN
Tematy:
soil biochar mixture
water retention
pore-size
distribution
hydraulic conductivity
carbon sequestration
Opis:
The addition of biochar is often proposed to increase agricultural soil quality and crop yield, while at the same time sequestering carbon from the atmosphere to help mitigate global climate change. In this research, the pore-size distribution, and saturated hydraulic conductivity of sandy loam and clay loam soils amended with varying dosages (0-10% dry basis) and two different particle sizes (0.5-420 μm (PS1) or 421-841 μm (PS2)) of wood-derived biochar were investigated under compacted conditions (5, 10, or 15 standard Proctor rammer blows (5B, 10B, or 15B, respectively)). In the 5B compacted SL (SL-5B) soil, the volume of the soil fissures and transmission pores decreased, while the volume of the storage pores (SP) increased with increasing wood-derived biochar dosage. 23.1±0.9% of the volume of the 5B compacted clay loam (CL-5B) are storage pores, this value increased to 27.4±2.0% upon amendment with 10% PS1. The saturated hydraulic conductivity of the sandy loam-5B soil amended with 10% PS1 decreased from 6.8±0.3 to 0.80±0.03 mm h-1. The sandy loam farmland C emissions decreased by 0.071 tC ha-1 y-1, whereas CL farmland C emissions decreased by 0.091 tC ha-1 y-1.
Źródło:
International Agrophysics; 2021, 35, 2; 167-177
0236-8722
Pojawia się w:
International Agrophysics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Sequential Pattern Discovery Algorithm for Malaysia Rainfall Prediction
Autorzy:
Ahmed, A.
Bakar, A.
Hamdan, A.
Syed Abdullah, S.
Jaafar, O.
Powiązania:
https://bibliotekanauki.pl/articles/1402374.pdf
Data publikacji:
2015-08
Wydawca:
Polska Akademia Nauk. Instytut Fizyki PAN
Tematy:
92.40.Zg
92.60.Wc
Opis:
This study proposes a sequential pattern mining algorithm to discover sequential patterns of Malaysia rainfall data for prediction. The apriori based algorithm is employed to find the sequential patterns from the time series data. The frequent episodes of rainfall sequences are discovered and classified by the expert into four main events namely, No rain, Light, Moderate and heavy. The sequential rules of ten rainfall stations from the duration of 33 years are analysed. The proposed algorithm is able to generate higher confidence and support of frequent and sequential patterns. Generally, the proposed study has shown its potential in producing methods that manage to preserve important knowledge and thus reduce information loss in weather prediction problem.
Źródło:
Acta Physica Polonica A; 2015, 128, 2B; B-324-B-326
0587-4246
1898-794X
Pojawia się w:
Acta Physica Polonica A
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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