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STUDY OF ROTATIONAL BAND STRUCTURE OF EVEN-EVEN 132;134SM NUCLEI
ARUN GUPTA,SURBHI GUPTA,SIMI GUPTA,SURAM SINGH,ARUN BHARTI 장전수학회 2021 Proceedings of the Jangjeon mathematical society Vol.24 No.4
The study of neutron-decient nuclei in the A130 mass region has been an interesting subject in nuclear structure physics as this region is considered to be transitional region. In the present work, the positive parity rotational band structure of even-even 132,134Sm up to the high spin states has been studied in a microscopic frame work of calculations known as Projected Shell Model (PSM). Yrast spectra for 132,134Sm have been obtained from the PSM calculations and has been found to be in good agreement with the available experimental data. Besides this, the present calculations have also reported the occurrence of back bending at the same spins at which experimental data shows in both the nuclei.
An Optimised Fuzzy Approach to Remove Mixed Noise from Images
Sweety Deswal,Surbhi Singhania,Shailender Gupta,Pranjal Garg 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.4
Mixed noises can be defined as a combination of different types of noises acting on a single carrier. There has been a mention of various mechanisms used to restore images corrupted with mixed noise in the past. This paper proposes a simple method based on fuzzy set theory and Bilateral Filter to remove mixed noises and compares it with previously mentioned techniques such as: Vector Median Filter(VMF), Vector Direction Filter (VDF), Fuzzy Peer Group Averaging (FPGA), Fuzzy Vector Median Filter (FVMF), Bilateral Filter (BF), Adaptive Bilateral Filter (ABF), Switching Bilateral Filter (SBF), Joint Bilateral Filter (JBF), and Trilateral Filter (TF) on the basis of performance metrics such as Peak Signal to Noise Ratio (PSNR), Mean Absolute Error (MAE), Mean Square Error (MSE) and Normalised Colour Difference (NCD). For the purpose of a detailed analysis, the performance of each method is evaluated by varying the image size and the noise density by implementing them in MATLAB-09. The mixed noise used in this paper is a combination of three noise i.e. poisson, impulse and Gaussian noise. The simulation and result shows that the proposed method provides better PSNR and hence better image quality than almost all the methods mentioned above.