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Wyszukujesz frazę "Bayat, H." wg kryterium: Autor

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    Wyświetlanie 1-6 z 6
    Tytuł:
    Seed priming with selenium improves growth, water relation and antioxidant activity of pot marigold (Calendula officinalis L.) under drought conditions
    Autorzy:
    Bayat, H.
    Aminifard, M.H.
    Powiązania:
    https://bibliotekanauki.pl/articles/13082686.pdf
    Data publikacji:
    2021
    Wydawca:
    Uniwersytet Przyrodniczy w Lublinie. Wydawnictwo Uniwersytetu Przyrodniczego w Lublinie
    Źródło:
    Acta Scientiarum Polonorum. Hortorum Cultus; 2021, 20, 1; 27-36
    1644-0692
    Pojawia się w:
    Acta Scientiarum Polonorum. Hortorum Cultus
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Pedotransfer function capability to simulate behaviour of smectitic soils in estimation of various soil water retention curve models
    Zdolność funkcji pedotransferowych do symulowania zachowania gleb smektytowych w modelach krzywej retencji wodnej gleb
    Autorzy:
    Zadeh, G.E.
    Bayat, H.
    Powiązania:
    https://bibliotekanauki.pl/articles/906252.pdf
    Data publikacji:
    2012
    Wydawca:
    Uniwersytet Marii Curie-Skłodowskiej. Wydawnictwo Uniwersytetu Marii Curie-Skłodowskiej
    Opis:
    For modelling the flow transport in unsaturated conditions, we can use hydraulic properties which are expensive and time-consuming to be obtained directly because of high variability and complexity of soil systems. Few studies have been done about pedotransfer functions (PTFs) in smectitic soils. Moreover, the utility of fractal parameters in the prediction of soil water retention curve (SWRC) have not been investigated in these soils. In this study, PTFs have been made for estimating the parameters of van Genuchten (VG) and Dexter models by regression and artificial neural networks methods. Therefore, 69 soil samples were collected from Guilan Province, Iran. Fractal and non-fractal models were fitted to the particle size distribution (PSD) and micro-aggregate size distribution (ASD) and their parameters were calculated. To create PTFs, the parameters of PSD and ASD models were used as estimators. The comparison of the results of the two models of Dexter and VG shows the priority of Dexter model for the purpose of testing of smectitic soils. The results showed the superiority of Fredlund et al. PSD model parameters and fractal parameters of ASD, in the estimation of Dexter and VG SWRC models, respectively. This outcome may be related to the higher accuracy of Fredlund et al. PSD model in the description of the PSD data in the clayey soils. However, the higher number of parameters in comparison to the number of fractal model parameters may be another reason.
    Źródło:
    Polish Journal of Soil Science; 2012, 45, 2
    0079-2985
    Pojawia się w:
    Polish Journal of Soil Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Fitting soil particle-size distribution (PSD) models by PSD curve fitting software
    Autorzy:
    Rastgou, M.
    Bayat, H.
    MansoorizadehM., M.
    Powiązania:
    https://bibliotekanauki.pl/articles/971471.pdf
    Data publikacji:
    2019
    Wydawca:
    Uniwersytet Marii Curie-Skłodowskiej. Wydawnictwo Uniwersytetu Marii Curie-Skłodowskiej
    Opis:
    This paper describes a particle-size distribution (PSD) curve fitting software for analyzing the soil PSD and soil physical properties. A better characterization of soil texture can be obtained by describing the soil PSD using mathematical models. The mathematical equations of soil PSD are mainly used as a basis to estimate the soil hydraulic properties. Until now, many attempts are made to represent PSD curves using mathematical models, but selecting the best PSD model requires fitting all models to the PSD data, which would be difficult and time-consuming. So far, no specific program has been developed to fit the PSD models to the experimental data. A practical user-friendly software called "PSD Curve Fitting Software" was developed and introduced to program a simultaneous fitting of all models on soil PSD data of all samples. Some of the capabilities of this software are calculating evaluation statistics for all models and soils and their statistical properties such as average, standard deviation, minimum and maximum for all models, the amount of models’ fitting parameters and their statistical properties for all soil samples, soil water retention curve by Arya and Paris (1981) and Meskini-Vishkaee et al. (2014) methods, soil hydraulic conductivity by Arya et al. (1999) method, different textural and hydraulic properties, specific surface area, and other descriptive statistics of PSD for all soil samples. All calculated parameters are presented in an output Excel file format by the software. The software runs under Windows XP/7/8/10.
    Źródło:
    Polish Journal of Soil Science; 2019, 52, 2; 211-224
    0079-2985
    Pojawia się w:
    Polish Journal of Soil Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Prediction of CEC using fractal parameters by artificial neural networks
    Autorzy:
    Bayat, H.
    Davatgar, N.
    Jalali, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/25675.pdf
    Data publikacji:
    2014
    Wydawca:
    Polska Akademia Nauk. Instytut Agrofizyki PAN
    Tematy:
    cation exchange capacity
    prediction
    fractal structure
    fractal theory
    particle size distribution
    artificial neural network
    pedotransfer function
    Opis:
    The prediction of cation exchange capacity from readily available soil properties remains a challenge. In this study, firstly, we extended the entire particle size distribution curve from limited soil texture data and, at the second step, calculated the fractal parameters from the particle size distribution curve. Three pedotransfer functions were developed based on soil properties, parameters of particle size distribution curve model and fractal parameters of particle size distribution curve fractal model using the artificial neural networks technique. 1 662 soil samples were collected and separated into eight groups. Particle size distribution curve model parameters were estimated from limited soil texture data by the Skaggs method and fractal parameters were calculated by Bird model. Using particle size distribution curve model parameters and fractal parameters in the pedotransfer functions resulted in improvements of cation exchange capacity predictions. The pedotransfer functions that used fractal parameters as predictors performed better than the those which used particle size distribution curve model parameters. This can be related to the non-linear relationship between cation exchange capacity and fractal parameters. Partitioning the soil samples significantly increased the accuracy and reliability of the pedotransfer functions. Substantial improvement was achieved by utilising fractal parameters in the clusters.
    Źródło:
    International Agrophysics; 2014, 28, 2
    0236-8722
    Pojawia się w:
    International Agrophysics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Manual Material Handling Assessment Among Workers of Iranian Casting Workshops
    Autorzy:
    Mohammadi, H.
    Motamedzade, M.
    Faghih, M. A.
    Bayat, H.
    Mohraz, M. H.
    Musavi, S.
    Powiązania:
    https://bibliotekanauki.pl/articles/89709.pdf
    Data publikacji:
    2013
    Wydawca:
    Centralny Instytut Ochrony Pracy
    Tematy:
    musculoskeletal disorders
    manual material handling
    casting workers
    Snook tables
    warsztaty odlewnicze
    zaburzenia układu mięśniowo-szkieletowego
    magazynowanie
    pracownicy odlewni
    Opis:
    Manual material handling (MMH) tasks can be found in most workplaces and they may constitute a risk factor for work-related musculoskeletal disorders (WMSDs). This study was conducted to determine the prevalence of WMSDs and to compare MMH loads with the acceptable weight and force limits among Iranian casting workers. Data were collected from 50 workers of casting workshops who performed MMH tasks. The Nordic musculoskeletal disorders questionnaire and the Snook tables were used as tools for data collection. Hand/wrist symptoms were the most prevalent problems among the workers (84%). The results of the Snook tables showed that the loads in lifting (84%), lowering (86%), carrying (66%), pushing with initial (43%) and sustained force (59%), and pulling tasks with initial (48%) and sustained force (93%) exceeded recommended limits. WMSDs occurred in high rates among the workers and, thus, ergonomics interventions should focus on decreasing WMSDs and redesigning MMH tasks.
    Źródło:
    International Journal of Occupational Safety and Ergonomics; 2013, 19, 4; 675-681
    1080-3548
    Pojawia się w:
    International Journal of Occupational Safety and Ergonomics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Parametric estimation of water retention using mGMDH method and principal component analysis
    Autorzy:
    Neyshaburi, M.R.
    Bayat, H.
    Rastgou, M.
    Mohammadi, K.
    Gregory, A.S.
    Nariman-Zadeh, N.
    Powiązania:
    https://bibliotekanauki.pl/articles/905465.pdf
    Data publikacji:
    2016
    Wydawca:
    Uniwersytet Marii Curie-Skłodowskiej. Wydawnictwo Uniwersytetu Marii Curie-Skłodowskiej
    Opis:
    Performing a primary analysis, such as principal component analysis (PCA) may increase accuracy and reliability of developed pedotransfer functions (PTFs). This study focuses on the usefulness of the soil penetration resistance (PR) and principal components (PCs) as new inputs along with the others to develop the PTFs for estimating the soil water retention curve (SWRC) using a multi-objective group method of data handling (mGMDH). The Brooks and Corey (1964) SWRC model was used to give a description of the water retention curves and its parameters were determined from experimental SWRC data. To select eight PCs, PCA was applied to all measured or calculated variables. Penetration resistance, organic matter (OM), aggregates mean weight diameter (MWD), saturated hydraulic conductivity (Ks), macro porosity (Mp), micro porosity (Mip) and eight selected PCs were used as predictors to estimate the Brooks and Corey model parameters by mGMDH. Using PR or OM, Ks and MWD, improved the estimation of SWRC in some cases. Using the predicted PR can be useful in the estimation of SWRC. Using either the MP and Mip or the eight PCs significantly improved the PTFs accuracy and reliability. It would be very useful to apply PCA on the original variables as a primary analysis to develop parametric PTFs.
    Źródło:
    Polish Journal of Soil Science; 2016, 49, 1
    0079-2985
    Pojawia się w:
    Polish Journal of Soil Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-6 z 6

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