Publications by authors named "Himanshu Upadhyay"

Wireless Sensor Networks (WSNs) are crucial in various fields including Health Care Monitoring, Battlefield Surveillance, and Smart Agriculture. However, WSNs are susceptible to malicious attacks due to the massive quantity of sensors within them. Hence, there is a demand for a trust evaluation framework within WSNs to function as a secure system, to identify and isolate malicious or faulty sensor nodes.

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The COVID-19 pandemic has significantly affected all spheres of life, including the healthcare workforce. While the COVID-19 pandemic has started driving organizational and societal shifts, it is vital for healthcare organizations and decision-makers to analyze patterns in the changing workforce. In this study, we aim to identify patterns in healthcare job postings during the pandemic to understand which jobs and associated skills are trending after the advent of COVID-19.

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In this study, we have developed a comprehensive machine learning (ML) framework for long-term groundwater contamination monitoring as the Python package PyLEnM (Python for Long-term Environmental Monitoring). PyLEnM aims to establish the seamless data-to-ML pipeline with various utility functions, such as quality assurance and quality control (QA/QC), coincident/colocated data identification, the automated ingestion and processing of publicly available spatial data layers, and novel data summarization/visualization. The key ML innovations include (1) time series/multianalyte clustering to find the well groups that have similar groundwater dynamics and to inform spatial interpolation and well optimization, (2) the automated model selection and parameter tuning, comparing multiple regression models for spatial interpolation, (3) the proxy-based spatial interpolation method by including spatial data layers or in situ measurable variables as predictors for contaminant concentrations and groundwater levels, and (4) the new well optimization algorithm to identify the most effective subset of wells for maintaining the spatial interpolation ability for long-term monitoring.

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Background: Platelet concentrates usage in the treatment of intrabony defects has been improved due to advancement of research. Many generation of platelet concentrates were used, but research regarding advanced platelet-rich fibrin (A-PRF) regarding periodontal treatment is scanty.

Aim: The purpose of the study was to evaluate and compare PRF and A-PRF in the treatment of human periodontal infrabony defects (IBDs) both clinically and radiographically.

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Oral myiasis is a rare disease, identified primarily in non-industrialised nations. It is caused fundamentally by the attack of larvae from Dipteran flies on the human tissues. Predisposing factors for oral myiasis are extraction wounds, destitute oral cleanliness, meagreness, mouth breathing amid rest, suppurative injuries, necrotic tissues, diabetes and perivascular infections primarily within the elderly, extreme halitosis, alcohol addiction, cerebral paralysis and components that favour prolonged mouth opening.

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Objective: To assess the efficacy of Platelet Rich Fibrin (PRF) on the pain and healing of the extraction socket associated with Alveolar Osteitis (Dry Socket, AO) after removal of maxillary and mandibular molars.

Study Design: 100 adult patients with age group ranging from 18 to 40 years along with established dry socket after maxillary and mandibular molar extractions who have not received any treatment for the same were included in the study. PRF was placed in the maxillary and mandibular molar extraction sockets after adequate irrigation of the socket.

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