arXiv subjects
Publications and source records attributed to Prabhjot Singh.
This study is about the Iterated Function System (IFS) of similarities on $\mathbb R$ that satisfies Weak Separation property (WSP). We explore if this implies Finite type property. We look into the most simple case with condition that closed interval [0,1] is an attractor of the IFS. The necessity of this condition is not strict but still unknown.
NOvA is a two detector, long baseline neutrino oscillation experiment designed to study $ν_{e}$ ($\barν_{e}$) appearance and $ν_μ$ ($\barν_μ$) disappearance in a $ν_μ$ ($\barν_μ$) beam produced at Fermilab. The near detector (ND) is located 100 meters underground at a distance of 1 km from the target whereas the far detector (FD) is located on the surface, 810 km away from the beam source in Ash River, MN. The ND is used to measure the beam before oscillations and the FD measures the oscillated spectrum. The ND and the FD are functionally identical detectors and the ND spectra are extrapolated to the FD to predict the signal and background spectra expected in the FD. The extrapolation and data fitting techniques developed for these analyses within NOvA are presented.
We build an example of a system $\mathcal{S}$ of similarities in $\mathbb{R}^2$ whose attractor is a plane dendrite $K\supset [0,1]$ which satisfies one point intersection property, while the post-critical set of the system $\mathcal{S}$ is a countable set whose natural projection to $K$ is dense in the middle-third Cantor set.
This paper exemplifies the implementation of an efficient Information Retrieval (IR) System to compute the similarity between a dataset and a query using Fuzzy Logic. TREC dataset has been used for the same purpose. The dataset is parsed to generate keywords index which is used for the similarity comparison with the user query. Each query is assigned a score value based on its fuzzy similarity with the index keywords. The relevant documents are retrieved based on the score value. The performance and accuracy of the proposed fuzzy similarity model is compared with Cosine similarity model using Precision-Recall curves. The results prove the dominance of Fuzzy Similarity based IR system.