The aim of this work is to prepare ternary blended PVA-Urea hydrogels containing Ormocarpum cochinchinense, Cinnamomum zeylanicum and antibiotic cephalexin by freezing-thawing method in order to assess the wound healing qualities. In addition to being a synthetic polymer, polyvinyl alcohol (PVA) is a recyclable and biocompatible artificial polymer blend that has attracted a lot of interest in biological applications. The freezingthawing process with PVA-Urea blend is used to make hydrogel film. Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), Scanning electron microscopy (SEM), swelling investigations were carried out for the composite membranes. Biological studies involving antibacterial, antifungal, cytotoxicity and wound healing activities were also carried out for the composite membranes. The composite membrane developed has a lot of potential for wound dressing and other applications.
In recent days, the Internet of Things (IoT) plays a significant role and increasing in rapid usage in various applications. As IoT is being developed for cyber-physical systems in the specific domain of e-health care, military, etc. Based on real-time applications, security plays a vital role in certain activities in educational institutions. In the institutions, there are multiple videos are collected and stored in the data repositories. Those datasets are developed specifically for certain activities and no other datasets are developed for academic activities. As there is a large number of videos and images are collected and considered, advanced technologies like, deep learning and IoT are used to perform certain tasks. In this paper, a Auto Deep learning-based Automated Identification Framework (DLAIF) is proposed to consider and reconsider the activities based on image pre-processing, model can be trained through the proposed GMM model and then predication to make an effective surveillance process based on HMM. This proposed process makes to recognize the activities through EM and log Likelihood for cyber-physical systems. In the performance analysis, the proposed model efficiency can be determined through Accuracy detection, False Positive rate and F1 Score requirement. Then calculating the accuracy is more effective for the proposed model compared to other existing models such as BWMP and LATTE.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.