The proposed paper presents the DC/AC microgrid modeling using the Energy storage units and photovoltaic (PV) panels. The modal consists of a two stage power conversion. The power is supplied to the both DC and AC loads by this PV solar panels. The suitable way to explore the PV generation model is by using manufacturer datasheet. A bidirectional converter is connected to the battery storage system and dc bus. To keep the bus voltage stable, the storage system absorbs the excess power whenever generation is more and delivers power to the load when generation is less. This system eliminates hazards of islanding by supply the local loads continuously incase of grid discontinuity. This paper emphasizes on control and stability of dc bus voltage and energy management scheme. Matlab/Simulink is used for integration of system modeling and efficiency of the system is verified by simulation.
Face Recognition is important Biometric credentials for identification or verification of a person. In this paper, we propose a novel technique of generating compressed unique features of face images which helps in improving matching speed of recognition. The training face database samples are applied to 2D-DWT to obtain LL band features. The LL band features are subjected to normalization to scale the magnitude values in the range 0 to 1. The output of normalization is further convolved with the original face sample to obtain unique features. The convolved output is subjected to Gaussian filter to obtain smoothened image features. Further, The feature vector of several image samples of single person are compressed to convert into single vector to database feature vectors are created by compressing feature vectors of single person face samples in to single column unique vectors which helps in scaling down of feature vectors and improve matching speed. The test samples are subjected to same process to generate unique compressed test feature vectors and are compared with database vectors using Euclidean distance. The results are tabulated for different set of face databases and also compared with existing techniques to validate the performance of proposed method.
The article reports on a development of RP-HPLC method for the quantitative determination of Levetiracetam in tablet dosage forms. The chromatographic separations were performed using Phenomenex_ C18 (250 mm x 4.6 mm i.d, 5 μm particle size) column at 40 ºC temperatures. The optimum mobile phase consisted of methanol, water and acetonitrile in the ratio of 30:10:60. Auto sampler 20 μl was used and kept at 15 ºC temperature. Analysis was done with flow rate of 1.0 ml/min at 212 nm (_ max of Levetiracetam) wavelength by using photodiode array (PDA) detector. The drug was analyzed for acid, alkaline, oxidative, hydrolytic, photolytic and thermal degradation studies. The standard calibration curve was plotted for the drug and results showed that the drug was linear (r2 = 0.999) in the concentration range between 0.01 – 1.5 μg/ml. The results of stress testing undertaken according to the International Conference on Harmonization (ICH) guidelines reveal that the selected method is selective and stability-indicating for determination of levitiracetam in pharmaceutical formualtion.
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