Indian Statistical Institute

About: Indian Statistical Institute is a education organization based out in Kolkata, India. It is known for research contribution in the topics: Population & Cluster analysis. The organization has 3475 authors who have published 14247 publications receiving 243080 citations. The organization is also known as: ISI & ISI Calcutta.

Cryptanalysis of LFSR-Encrypted Codes with Unknown Combining Function

Abstract: This paper proposes an approach for the cryptanalysis of stream ciphers where the encryption is performed by multiple linear feedback shift registers (LFSR) combined by a nonlinear function The attack assumes no knowledge of either the LFSR initial conditions or the combining function Thus, the actual architecture of the encryption system can be arbitrary The attack is also generalized for the situation when the combining function is correlation immune of any particular order This is in direct contrast with the existing methods which depend heavily not only on the correlation between the output of a particular LFSR and the ciphertext but also on the actual configuration of the encryption system used Thus, the proposed method is the first ciphertext only attack in the true sense of the phrase The paper also gives theoretical estimates of the cipherlengths involved in the determination of the initial conditions as well as estimation of the combining function

COVID-19 Face Mask Recognition with Advanced Face Cut Algorithm for Human Safety Measures

Abstract: In the last year, the outbreak of COVID-19 has deployed computer vision and machine learning algorithms in various fields to enhance human life interactions. COVID-19 is a highly contaminated disease that affects mainly the respiratory organs of the human body. We must wear a mask in this situation as the virus can be contaminated through the air and a non-masked person can be affected. Our proposal deploys a computer vision and deep learning framework to recognize face masks from images or videos. We have implemented a Boundary dependent face cut recognition algorithm that can cut the face from the image using 27 landmarks and then the preprocessed image can further be sent to the deep learning ResNetSO model. The experimental result shows a significant advancement of 3.4 percent compared to the YOLOV3 mask recognition architecture in just 10 epochs.

Jackknife Empirical Likelihood-based inference for S-Gini indices

Abstract: The widely used income inequality measure, Gini index, is extended to form a family of income inequality measures known as Single-Series Gini (S-Gini) indies. In this study, we develop empirical li...

Euler characteristic and quadrilaterals of normal surfaces

Abstract: Let $M$ be a compact 3-manifold with a triangulation $\tau$. We give an inequality relating the Euler characteristic of a surface $F$ normally embedded in $M$ with the number of normal quadrilaterals in $F$. This gives a relation between a topological invariant of the surface and a quantity derived from its combinatorial description. Secondly, we obtain an inequality relating the number of normal triangles and normal quadrilaterals of $F$, that depends on the maximum number of tetrahedrons that share a vertex in $\tau$.

Characteristics of particle production in high energy nuclear collisions: A model-based analysis

Abstract: The present work pertains to the production of some very important negatively charged secondaries in lead-lead and gold-gold collision at AGS, SPS and RHIC energies. We would like to examine here the role of the particular version of Sequential Chain Model (SCM), which was applied widely in the past in analysing data on various high-energy hadronic collisions, in explaining now the latest findings on the features of particle production in the relativistic nucleus-nucleus collisions. The agreement between the model of our choice and the measured data is found to be modestly satisfactory in cases of the most prominent and abundantly produced varieties of the secondaries in the above-stated two nuclear collisions.