arXiv subjects
Publications and source records attributed to Monika Singh.
We prove the discrete Rubio de Francia extrapolation theorem for a pair of quasi non-increasing sequences with $\mathcal{QB}_{\beta, p}$ weight class. Also, a weight characterization of the boundedness of the generalized discrete Hardy averagin19g operator on the class of quasi non-increasing sequences from $l_w^p(\mathbb{Z}^+)$ is proved.
We define the grand amalgam Lebesgue function space $l^{q), \theta}(L^p),$ and study the fundamental structural properties of the space, including completeness. Then we define the small Lebesgue sequence space and study its function space properties. Furthermore, we prove a version of the H\"{o}lders inequality on the frame work of these spaces. Finally, we study the multiplication operator in the setting of these spaces.
We characterize the modular and norm inequalities for the Dunkl-Hausdorff operator defined on non-negative non-increasing functions in the framework of the weighted Orlicz spaces.
COVID-19 pandemic has brought unprecedented challenges to the world, and vaccination has been a key strategy to combat the disease. Since Twitter is one of the most widely used public microblogging platforms, researchers have analysed COVID-19 vaccines and vaccination Twitter discourse to explore the conversational dynamics around the topic. While contributing to the crisis informatics literature, we curate a large-scale geotagged Twitter dataset, GeoCovaxTweets Extended, and explore the discourse through multiple spatiotemporal analyses. This dataset covers a longer time span of 38 months, from the announcement of the first vaccine to the availability of booster doses. Results show that 43.4% of the collected tweets, although containing phrases and keywords related to vaccines and vaccinations, were unrelated to the COVID-19 context. In total, 23.1% of the discussions on vaccines and vaccinations were classified as Pro, 16% as Hesitant, 11.4% as Anti, and 6.1% as Informative. The trend shifted towards Pro and Informative tweets globally as vaccination programs progressed, indicating a change in the public's perception of COVID-19 vaccines and vaccination. Furthermore, we explored the discourse based on account attributes, i.e., followers counts and tweet counts. Results show a significant pattern of discourse differences. Our findings highlight the potential of harnessing a large-scale geotagged Twitter dataset to understand global public health communication and to inform targeted interventions aimed at addressing vaccine hesitancy.
We prove Rubio de Francia extrapolation results in Lebesgue and grand Lebesgue spaces for quasi monotone functions with $QB_{β,p}$ weights. The extrapolation in Lebesgue spaces with the weight class $QB_{β,\infty}$ has also been investigated. As an application, we characterize the boundedness of the Hardy averaging operator for quasi monotone functions in the grand Lebesgue spaces.
Digital forensic investigation has become more challenging due to the rapid growth in the volume of encountered data. It is difficult for an investigator to examine the entire volume of encountered data manually. Approximate Matching algorithms are being used to serve the purpose by automatically filtering correlated and relevant data that an investigator needs to examine manually. Presently there are several prominent approximate matching tools and technique those are being used to assist critical investigation process. However, to measure the guarantees of a tool, it is important to understand the exact requirement of an investigator regarding these algorithms. This paper presents the findings of a closed survey conducted among a highly experienced group of federal state and local law enforcement practitioners and researchers, aimed to understand the practitioner and researcher's opinion regarding approximate matching algorithms. The study provides the baseline attributes of approximate matching tools that a scheme should possess to meet the real requirement of an investigator.
We obtain a pointwise description of functions belonging to function spaces with the lattice property. In particular, it is valid for Banach function spaces provided that the Hardy-Littlewood maximal operator is bounded. We also study weighted grand Sobolev spaces, defined on arbitrary open sets (of finite or infinite measure), and provide pointwise description of them.
The single phase polycrystalline Ba1/4Sr3/4MnO3 layered perovskite manganite has been synthesized by combustion method having various crystallite sizes. The room temperature X-ray diffraction patterns reveal that Ba1/4Sr3/4MnO3 crystallizes into hexagonal crystal structure with space group P63/mmc as confirmed by Rietveld refinement. The scanning electron micrographs of Ba1/4Sr3/4MnO3 reveal uniform crystallite size of the samples. Effect of crystallite size on lattice strain and crystal structure has been studied using Rietveld refinement and Williamson-Hall plot, respectively. The structural lattice parameters decrease with increasing crystallite size. However, lattice strain increases with increasing crystallite-size.