Journal Articles
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Item Minimum distance of the boundary of the set of PPT states from the maximally mixed state using the geometry of the positive semidefinite cone(Springer New York LLC barbara.b.bertram@gsk.com, 2019) Banerjee, S.; Patel, A.A.; Panigrahi, P.K.Using a geometric measure of entanglement quantification based on Euclidean distance of the Hermitian matrices (Patel and Panigrahi in Geometric measure of entanglement based on local measurement, 2016. arXiv:1608.06145), we obtain the minimum distance between the set of bipartite n-qudit density matrices with a positive partial transpose and the maximally mixed state. This minimum distance is obtained as 1dn(dn-1), which is also the minimum distance within which all quantum states are separable. An idea of the interior of the set of all positive semidefinite matrices has also been provided. A particular class of Werner states has been identified for which the PPT criterion is necessary and sufficient for separability in dimensions greater than six. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.Item Multimodal behavior analysis in computer-enabled laboratories using nonverbal cues(Springer Science and Business Media Deutschland GmbH info@springer-sbm.com, 2020) Banerjee, S.; Ashwin, T.S.; Guddeti, R.M.R.In the modern era, there is a growing need for surveillance to ensure the safety and security of the people. Real-time object detection is crucial for many applications such as traffic monitoring, security, search and rescue, vehicle counting, and classroom monitoring. Computer-enabled laboratories are generally equipped with video surveillance cameras in the smart campus. But, from the existing literature, it is observed that the use of video surveillance data obtained from smart campus for any unobtrusive behavioral analysis is seldom performed. Though there are several works on the students’ and teachers’ behavior recognition from devices such as Kinect and handy cameras, there exists no such work which extracts the video surveillance data and predicts the behavioral patterns of both the students and the teachers in real time. Hence, in this study, we unobtrusively analyze the students’ and teachers’ behavioral patterns inside a teaching laboratory (which is considered as an indoor scenario of a smart campus). Here, we propose a deep convolution network architecture to classify and recognize an object in the indoor scenario, i.e., the teaching laboratory environment of the smart campus with modified Single-Shot MultiBox Detector approach. We used six different class labels for predicting the behavioral patterns of both the students and the teachers. We created our dataset with six different class labels for training deep learning architecture. The performance evaluation demonstrates that the proposed method performs better with an accuracy of 0.765 for classification and localization. © 2020, Springer-Verlag London Ltd., part of Springer Nature.Item The γ-Valerolactone (GVL) as Innoxious Reaction Media for the Synthesis of 2-Aryl-2H-Indazoles via C-N and N-N Bond Formation under Cu(I)-Catalyzed Ligand and Base Free Conditions(Taylor and Francis Ltd., 2024) Singh, L.S.; Kant, K.; Banerjee, S.; Sengupta, R.; AlObaid, A.A.; Pal, M.; Dutta, S.; Aljaar, N.; Malakar, C.C.An efficient method for N-arylation and N-N bond formation has been developed using an innoxious reaction medium, γ-valerolactone (GVL), as both a solvent and a ligand. The strategy involves utilizing CuI as a catalyst under conditions free of external ligands and bases. Various aldehyde and amine derivatives with different functional groups were investigated, resulting in the production of 2-aryl-2H-indazole compounds with yields ranging from 75% to 93%. This study highlights the effectiveness of GVL, a solvent derived from biomass, as a reaction medium and ligand in a multicomponent reaction. © 2023 Taylor & Francis Group, LLC.