Object Classification Using Substance Based Neural Network

Object recognition has shown tremendous increase in the field of image analysis. The required set of image objects is identified and retrieved on the basis of object recognition. In this paper, we propose a novel classification technique called substance based image classification (SIC) using a wavelet neural network. The foremost task of SIC is to remove the surrounding regions from an image to reduce the misclassified portion and to effectively reflect the shape of an object. At first, the image to be extracted is performed with SIC system through the segmentation of the image. Next, in order to attain more accurate information, with the extracted set of regions, the wavelet transform is applied for extracting the configured set of features. Finally, using the neural network classifier model, misclassification over the given natural images and further background images are removed from the given natural image using the LSEG segmentation. Moreover, to increase the accuracy of object classification, SIC system involves the removal of the regions in the surrounding image. Performance evaluation reveals that the proposed SIC system reduces the occurrence of misclassification and reflects the exact shape of an object to approximately 10–15%

Improved Fractional Order VSS Inc-Cond MPPT Algorithm for Photovoltaic Scheme

Nowadays a hot topic among the research community is the harnessing energy from the free sunlight which is abundant and pollution-free. The availability of cheap solar photovoltaic (PV) modules has to harvest solar energy with better efficiency. The nature of solar modules is nonlinear and therefore the proper impedance matching is essential. The proper impedance matching ensures the extraction of the maximum power from solar PV module. Maximum power point tracking (MPPT) algorithm is acting as a significant part in solar power generating system because it varies in the output power from a PV generating set for various climatic conditions. This paper suggested a new improved work for MPPT of PV energy system by using the optimized novel improved fractional order variable step size (FOVSS) incremental conductance (Inc-Cond) algorithm. The new proposed controller combines the merits of both improved fractional order (FO) and variable step size (VSS) Inc-Cond which is well suitable for design control and execution. The suggested controller results in attaining the desired transient reaction under changing operating points. MATLAB simulation effort shows MPPT controller and a DC to DC Luo converter feeding a battery load is achieved. The laboratory experimental results demonstrate that the new proposed MPPT controller in the photovoltaic generating system is valid

Synthesis, magnetic and optical properties of core/shell Co1-xZnxFe2O4/SiO2 nanoparticles

The optical properties of multi-functionalized cobalt ferrite (CoFe2O4), cobalt zinc ferrite (Co0.5Zn0.5Fe2O4), and zinc ferrite (ZnFe2O4) nanoparticles have been enhanced by coating them with silica shell using a modified Stöber method. The ferrites nanoparticles were prepared by a modified citrate gel technique. These core/shell ferrites nanoparticles have been fired at temperatures: 400°C, 600°C and 800°C, respectively, for 2 h. The composition, phase, and morphology of the prepared core/shell ferrites nanoparticles were determined by X-ray diffraction and transmission electron microscopy, respectively. The diffuse reflectance and magnetic properties of the core/shell ferrites nanoparticles at room temperature were investigated using UV/VIS double-beam spectrophotometer and vibrating sample magnetometer, respectively. It was found that, by increasing the firing temperature from 400°C to 800°C, the average crystallite size of the core/shell ferrites nanoparticles increases. The cobalt ferrite nanoparticles fired at temperature 800°C; show the highest saturation magnetization while the zinc ferrite nanoparticles coated with silica shell shows the highest diffuse reflectance. On the other hand, core/shell zinc ferrite/silica nanoparticles fired at 400°C show a ferromagnetic behavior and high diffuse reflectance when compared with all the uncoated or coated ferrites nanoparticles. These characteristics of core/shell zinc ferrite/silica nanostructures make them promising candidates for magneto-optical nanodevice applications

Analysis of Fuzzy-Logic MPPT controller for Photovotlaic Application

In this study nonlinearity of solar temparute and irradiation leads to variable of photovoltaic power output and reduces in efficiency. A technique based on simulation study is developed to increase the power output of the soalr panels using the combination of photovoltaic system with fuzzy logic control maximum power point tracking algorithm. The MPPT system increase the panel output power under various circumfreences. In this work, to enhance the power abstraction  in a controlled manner an intelligent algorithm named as P&O set of rules is introduced, which is commonly stated as maximum power point tracking approach. The exclusive approaches i.e unit power approach and feeder-flow approaches are being penetrated into the cross-breed system. In turn, determines the reference parameters effectively. The conversion of DC output is taken over by the DC-DC buck–boost converter and implemented through the MATLAB/ SIMULINK tool to enable accuracy and excellent tracking performance at various climatic conditions.  The above projected Flexi operated mode conditions go well in exacting the maximum power, greater efficiency by reducing the number of modes with improved stability and performance the system