Prasanta K. Panigrahi

Siddharth Patwardhan, Utso Majumder, Aditya Das Sarma et al.

The percolation threshold is an important measure to determine the inherent rigidity of large networks. Predictors of the percolation threshold for large networks are computationally intense to run, hence it is a necessity to develop predictors of the percolation threshold of networks, that do not rely on numerical simulations. We demonstrate the efficacy of five machine learning-based regression techniques for the accurate prediction of the percolation threshold. The dataset generated to train the machine learning models contains a total of 777 real and synthetic networks. It consists of 5 statistical and structural properties of networks as features and the numerically computed percolation threshold as the output attribute. We establish that the machine learning models outperform three existing empirical estimators of bond percolation threshold, and extend this experiment to predict site and explosive percolation. Further, we compared the performance of our models in predicting the percolation threshold using RMSE values. The gradient boosting regressor, multilayer perceptron and random forests regression models achieve the least RMSE values among considered models.

Prasanta K. Panigrahi

We study the thermal quantum correlations in tripartite atomic system under the existence of Herring-Flicker (HF) coupling among the atoms. We explore two topologically distinct configurations of three coupled two-level atoms, viz., loop and line, differing in their coupling pattern. Further, the systems having asymmetric arrangement of atoms are quantum mechanically correlated more strongly than systems having symmetric arrangements. The variable nature of HF coupling leads to the increase of both concurrence and discord from zero to a saturation value from where they decrease to zero as a function of inter-atomic distance. Further separation leads to both the quantities attaining another saturation value. This controlled correlations play an important role in the design of quantum data buses that can transfer quantum states to establish quantum communication. The systems coupled via HF coupling will be efficient for this task as they are maximally entangled in parametrically controlled manner. Thus, these systems will be propitious for various quantum protocols such as secure communication, quantum cryptography, quantum key distribution etc.

Subhayan Roy Moulick, Prasanta K. Panigrahi

We propose the idea of a Quantum Cheque Scheme, a cryptographic protocol in which any legitimate client of a trusted bank can issue a cheque, that cannot be counterfeited or altered in anyway, and can be verified by a bank or any of its branches. We formally define a Quantum Cheque and present the first Unconditionally Secure Quantum Cheque Scheme and show it to be secure against any no-signaling adversary. The proposed Quantum Cheque Scheme can been perceived as the quantum analog of Electronic Data Interchange, as an alternate for current e-Payment Gateways.

Sabyasachi Mukhopadhyay, Soham Mandal, Sawon Pratiher et al.

Our proposed hyper kurtosis based histogram equalized DIC images enhances the contrast by preserving the brightness. The evolution and development of precancerous activity among tissues are studied through S-transform (ST). The significant variations of amplitude spectra can be observed due to increased medium roughness from normal tissue were observed in time-frequency domain. The randomness and inhomogeneity of the tissue structures among human normal and different grades of DIC tissues is recognized by ST based timefrequency analysis. This study offers a simpler and better way to recognize the substantial changes among different stages of DIC tissues, which are reflected by spatial information containing within the inhomogeneity structures of different types of tissue.

Sabyasachi Mukhopadhyay, Soham Mandal, Sawon Pratiher et al.

In this paper, a comparative study between proposed hyper kurtosis based modified duo-histogram equalization (HKMDHE) algorithm and contrast limited adaptive histogram enhancement (CLAHE) has been presented for the implementation of contrast enhancement and brightness preservation of low contrast human brain CT scan images. In HKMDHE algorithm, contrast enhancement is done on the hyper-kurtosis based application. The results are very promising of proposed HKMDHE technique with improved PSNR values and lesser AMMBE values than CLAHE technique.

Sabyasachi Mukhopadhyay, Soham Mandal, Nandan K Das et al.

CT scan images of human brain of a particular patient in different cross sections are taken, on which wavelet transform and multi-fractal analysis are applied. The vertical and horizontal unfolding of images are done before analyzing these images. A systematic investigation of de-noised CT scan images of human brain in different cross-sections are carried out through wavelet normalized energy and wavelet semi-log plots, which clearly points out the mismatch between results of vertical and horizontal unfolding. The mismatch of results confirms the heterogeneity in spatial domain. Using the multi-fractal de-trended fluctuation analysis (MFDFA), the mismatch between the values of Hurst exponent and width of singularity spectrum by vertical and horizontal unfolding confirms the same.

Subhayan Roy Moulick, Siddharth Arora, Chirag Jain et al.

A semi-blind watermarking scheme is presented based on Singular Value Decomposition (SVD), which makes essential use of the fact that, the SVD subspace preserves significant amount of information of an image and is a one way decomposition. The principal components are used, along with the corresponding singular vectors of the watermark image to watermark the target image. For further security, the semi-blind scheme is extended to an invisible hash based watermarking scheme. The hash based scheme commits a watermark with a key such that, it is incoherent with the actual watermark, and can only be extracted using the key. Its security is analyzed in the random oracle model and shown to be unforgeable, invisible and satisfying the property of non-repudiation.

Sabyasachi Mukhopadhyay, Debadatta Dash, Swapnil Barmase et al.

Both of Wavelet and Fast Fourier Transform are strong signal processing tools in the field of Data Analysis. In this paper fast fourier transform (FFT) and Wavelet Transform are employed to observe some important features of Solar image (December, 2004). We have tried to find out the periodicity and coherence of different sections of the solar image. We plotted the distribution of energy in solar surface by analyzing the solar image with scalograms and 3D-coefficient plots.