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Alimuddin

Publications and source records attributed to Alimuddin.

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Modeling Data Containing Outliers using ARIMA Additive Outlier (ARIMA-AO)

The aim this study is discussed on the detection and correction of data containing the additive outlier (AO) on the model ARIMA (p, d, q). The process of detection and correction of data using an iterative procedure popularized by Box, Jenkins, and Reinsel (1994). By using this method we obtained an ARIMA models were fit to the data containing AO, this model is added to the original model of ARIMA coefficients obtained from the iteration process using regression methods. This shows that there is an improvement of forecasting error rate data.

stat.ME

Electronic structure and magnetic properties of Ni0.2Cd0.3Fe2.5-xAlxO4 (x = 0.0 - 0.4) ferrite nanoparticles

Structural, magnetic and electronic structural properties of Ni0.2Cd0.3Fe2.5-xAlxO4 ferrites nanoparticles have been studied x-ray diffraction (XRD), transmission electron microscopy (TEM), dc magnetization, and near edge x-ray absorption fine structure spectroscopy (NEXAFS) measurements. Nanoparticles of Ni0.2Cd0.3Fe2.5-xAlxO4 (x = 0.0 - 0.4) ferrite were synthesized using sol-gel method. The XRD and TEM measurements show that all samples have single phase nature with cubic structure and have nanocrystalline behavior. From the XRD and TEM analysis, it is observed that particle size increases with Al doping. DC magnetization measurements infer that magnetic moment decreases whereas blocking temperature increases with increase in Al doping. It is observed that the magnetic moment decreases with Al doping which may be due to the dilution of the sublattice by the doping of Al ions. The NEXAFS measurements performed at room temperature indicates that Fe exist in mixed valence state.

cond-mat.mtrl-sci