Earticle

Face recognition (FR) system can automatically identify or check face image from a digital camera or image generation equipment, in order to do this, to extract facial features from images obtained, and compared with face data in the database. At present, almost all of the FR face barriers associated with facial Angle, including the lack of light and the low resolution, these problems has greatly reduce the recognition rate. In order to solve this problem, this paper proposes a face recognition framework based on the sub pattern under the condition of illumination change, first of all, the framework using minimize the total variation image of discrete cosine transform (DTV) and the Gabor filter, and combined the sub-mode analysis (SMP) and distinguish the accumulative feature transformation (DAFT), can effectively solve the face recognition problem of light conditions big change, secondly by extracting the texture characteristics of local model is not sensitive to illumination changes, using Distance transformation measures (Distance Conversion Metrics, DCM) and k-means (K-Mean) algorithm, the recognition rate of face recognition is improved effectively. The effectiveness of the method verified respectively on the two face library: ATR - Jaffe and Yale, the experimental results show that compared with other state-of-the-art methods, the proposed method in dealing with the face recognition problem under the condition of the unrestricting obtained better recognition effect.

In recent times, development of nanofluid insulation for power transformers is a hot research topic. Many researchers reported the enhancement in dielectric characteristics of nano modified mineral oils. Considering the drawbacks of petroleum based mineral oil, it is necessary to understand the dielectric characteristics of nanofluids developed with natural ester based oils. Palm oil has better insulation characteristics comparable to mineral oil. However very few research reports is available in the area of nanofluids based on palm oil. Partial discharge (PD) is one of the major sources of insulation performance degradation of transformer oil. It is essential to understand the partial discharge(PD) characteristics by collecting huge data base of PD performance of nano modified palm oil which will increase its confidence level for power transformer application. Knowing these facts, in the present work, certain laboratory experiments have been performed on PD characteristics of nano $SiO_2$ modified palm oil at different electrode configurations. Influence of concentration of nano filler material on the PD characteristics is also studied. Partial discharge inception voltage, Phase resolved partial discharge (PRPD) pattern, PD signal time-frequency domain characteristics, PD signal equivalent timelength-bandwidth mapping, Weibull distribution statistical parameters of PRPD pattern, skewness, repetition rate and phase angle variations are evaluated at different test conditions. From the results of the experiments conducted, we came to understand that PD performance of palm oil is considerably enhanced with the addition of $nano-SiO_2$ filler at 0.01%wt and 0.05%wt concentration. Significant reduction in PD inception voltage, repetition rate, Weibull shape parameter and PD magnitude are noticed with addition of $SiO_2$ nanofillers in palm oil. These results will be useful for recommending nano modified palm oil for power transformer applications.