LC International Journal of STEM (ISSN: 2708-7123)
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Build A Secure Healthcare System Based On the Metadata of Patient Information
Get PDFBuilding a secure healthcare system based on metadata involves several key steps to ensure that patient information remains confidential and secure. Metadata refers to information about data, such as the time and date of creation, author, and location, rather than the content of the data itself. In this paper, there are many steps that considered when building a secure healthcare system based on metadata: we begin with defining metadata standards: Establishing metadata standards for healthcare data can help ensure consistency and interoperability across different systems. This can include standards for data elements, data formats, and data models. Implement access controls: Access controls should be implemented to restrict access to sensitive patient data. Role-based access control can be used to limit access to specific data based on job responsibilities. Use encryption: Encryption can be used to protect patient data from unauthorized access. Data encryption should be implemented at rest and in transit to protect data at all times. Secure storage: Patient data should be stored securely, including backups and archives. Secure storage can help prevent data loss and unauthorized access. We obtain a perfect time for processing compare with other resources and perfect time for check the metadata and hyperlink of patient's information
Empirical Evaluation of Pre-Trained Deep Learning Networks for Pneumonia Detection
Get PDFPneumonia is a significant global health issue, characterized by a substantial mortality risk, impacting a vast number of individuals on a global scale. The quick and precise identification of pneumonia is crucial for the optimal treatment and management of this condition. This research work aims to answer the pressing need for precise diagnostic methods by using two advanced deep learning models, namely VGG19 and ResNet50, for the purpose of pneumonia detection in chest X-ray pictures. Furthermore, the present area of research is on the use of deep learning methodologies in the domain of medical image analysis, namely in the identification of pneumonia cases via the examination of chest X-ray images. The study challenge pertains to the pressing need for accurate and automated pneumonia diagnosis to assist healthcare professionals in making timely and educated judgements. The VGG19 and ResNet50 models were trained and assessed using the comprehensive RSNA Pneumonia dataset. In order to enhance their performance in the classification of chest X-ray pictures as either normal or pneumonia-affected, the models underwent rigorous training and meticulous fine-tuning. Based on the results obtained from our investigation, it was seen that the VGG19 model exhibited a notable accuracy rate of 93\%, surpassing the ResNet50 model's accuracy of 84\%. Furthermore, it is worth noting that both models demonstrated a notable level of precision, recall, and f1-scores in the identification of normal and pneumonia patients. This indicates their potential for accurately classifying such instances. Furthermore, our research findings indicate that deep learning models, namely VGG19, have a high level of efficacy in reliably detecting pneumonia via the analysis of chest X-ray pictures. These models has the capacity to function as helpful tools for expediting and ensuring the precise identification of pneumonia by healthcare practitioners
Deep Fake Detection in Social Media Forensic Taxonomy, Challenges, Future Directions
Get PDFWith the rapid growth of smartphone technology, it is now commonplace to upload & download videos as part of digital social networking. More incidents are being recorded on video than ever before, so the information on them is more valuable than ever. In this paper, we give a full review of how to get information from video content & find fakes. In this context, we look at different modern methods for detecting video fakes, computer vision & (ML) methods like (DL). We also discuss recurring resource, legal, also technical issues, as well as the challenging of applying Deep learning for the task, such as the theory underpinning DL, CV, restricted, datasets, real-time processing, ML, employed with IoT-based devices. This survey also lists common video forensics analysis & investigation products. In this survey we examine video content information extraction & counterfeit detection in detail, which, as far as we know, has not been done before
Controlling of Power and Performing Operations in Home Automation Devices
Get PDFDifferent electrical devices can be automatically controlled by moving into ON and OFF state by programming the devices using google assistant and IOT. Different Components of the system use different transmission modes that are implemented through communicate user control of devices through the NodeMCU to the actual appliance The main control system implements wireless technology to allow remote access from Smart Phone. The case like Industries where several Number of devices are in ON state for long time even after the industrial task is completed which consume IoT of power. An alternate solution is Monitoring some devices OFF state and some into ON state so that the industries can perform the task by effective utilization of power. IOT is an important technology which helps to communicate one device to another device. In this paper we controlling the devices based on the LDR
Design and Implementation of a Holistic and Robust Wi-Fi Authentication and Authorization Framework for Secure Wireless Networks
Get PDFWireless networks have become a significant portion of existing systems of communication, giving suitable and elastic connectivity. Wi-Fi networks have evolved to be everywhere in our day-to-day lives, and with this growing service, the security dangers associated with wireless networks have also expanded. Our work suggests a holistic and robust Wi-Fi authentication and authorization framework for safe networks. The suggested framework includes three main components ( authentication, authorization, and encryption). The authentication utilizes a secure password-based authentication protocol to authenticate users and devices on the wireless network. The authorization utilizes network segmentation and access control to limit unauthorized access and mitigate attacks. Eventually, the encryption utilizes the Advanced Encryption Standard (AES) algorithm to guarantee confidentiality in addition to the integrity of wireless communications. Evaluate the efficacy of the suggested framework based on the executed experiments utilizing the OMNeT++ simulator. The outcomes demonstrate that the framework provides robust security against a variety of attacks, such as eavesdropping, man-in-the-middle attacks, and denial-of-service attacks. Also, the suggested work was discovered to have minimal influence on network performance, with only a slight increase in latency and a modest decrease in throughput
A Comprehensive Review of D2D Communication in 5G and B5G Networks
Get PDFThe evolution of Device-to-device (D2D) communication represents a significant breakthrough within the realm of mobile technology, particularly in the context of 5G and beyond 5G (B5G) networks. This innovation streamlines the process of data transfer between devices that are in close physical proximity to each other. D2D communication capitalizes on the capabilities of nearby devices to communicate directly with one another, thereby optimizing the efficient utilization of available network resources, reducing latency, enhancing data transmission speed, and increasing the overall network capacity. In essence, it empowers more effective and rapid data sharing among neighboring devices, which is especially advantageous within the advanced landscape of mobile networks such as 5G and B5G. The development of D2D communication is largely driven by mobile operators who gather and leverage short-range communications data to propel this technology forward. This data is vital for maintaining proximity-based services and enhancing network performance. The primary objective of this research is to provide a comprehensive overview of recent progress in different aspects of D2D communication, including the discovery process, mode selection methods, interference management, power allocation, and how D2D is employed in 5G technologies. Furthermore, the study also underscores the unresolved issues and identifies the challenges associated with D2D communication, shedding light on areas that need further exploration and developmen
An Efficient Exponential Estimator of Population Mean in the Presence of Median of the Study Variable
Get PDFSurvey sampling practitioners have been working on efficiency improvement and bias reduction in finite population parameter estimation. We proposed an exponential estimator of population mean in the presence of median of study variable. The bias and mean square error of the proposed estimator were obtained using Taylor series method. The relative performance of the proposed estimators with respect to conventional and some existing estimators were assessed using three (3) natural dataset information. The novel median based estimator perform better than the conventional, usual mean, ratio, regression and other existing estimators considered in the study have been established. The empirical results shown that the proposed estimator is more efficient than the conventional and some existing estimators considered in the study
Enhancing Security and Energy Efficiency in Wireless Sensor Network Routing with IOT Challenges: A Thorough Review
Get PDFWireless sensor networks (WSNs) have emerged as a crucial component in the field of networking due to their cost-effectiveness, efficiency, and compact size, making them invaluable for various applications. However, as the reliance on WSN-dependent applications continues to grow, these networks grapple with inherent limitations such as memory and computational constraints. Therefore, effective solutions require immediate attention, especially in the age of the Internet of Things (IoT), which largely relies on the effectiveness of WSNs. This study undertakes a comprehensive review of research conducted between 2018 and 2020, categorizing it into six main domains: 1) Providing an overview of WSN applications, management, and security considerations. 2) Focusing on routing and energy-saving techniques. 3) Reviewing the development of methods for information gathering, emphasizing data integrity and privacy. 4) Emphasizing connectivity and positioning techniques. 5) Examining studies that explore the integration of IoT technology into WSNs with an eye on secure data transmission. 6) Highlighting research efforts aimed at energy efficiency. The study addresses the motivation behind employing WSN applications in IoT technologies, as well as the challenges, obstructions, and solutions related to their application and development. It underscores that energy consumption remains a paramount issue in WSNs, with untapped potential for improving energy efficiency while ensuring robust security. Furthermore, it identifies existing approaches' weaknesses, rendering them inadequate for achieving energy-efficient routing in secure WSNs. This review sheds light on the critical challenges and opportunities in the field, contributing to a deeper understanding of WSNs and their role in secure IoT applications
The Dawn of Digital Payments: Revolutionizing India's Financial Landscape
Get PDFThe study investigates how India's digital payments revolution has altered the financial landscape. India has recently seen a huge movement towards digital payments as a result of the quick development of technology and the widespread usage of cell phones. This transformation has significantly changed the financial landscape of the country along with how people interact. Demonetization, a government program that was put into effect in 2016, made a substantial contribution to the growth of electronic payments. People and businesses started looking for other payment options as a result of the abrupt withdrawal of high-value currency notes, which increased the volume of digital transactions. People are finding it easier and easier to access digital payment systems as a result of the widespread use of smartphones and the affordability of internet access. With the rise in popularity of mobile payment apps like Paytm, PhonePe, and Google Pay, India's financial landscape has changed. Financial inclusion enabled by the digital revolution has allowed millions of unbanked and underbanked individuals to access formal financial services through digital payments. With just a smartphone and a bank account, people can easily send money, pay bills, and shop online. This change has promoted economic openness in the country and empowered small businesses
Vision-Based Monocular SLAM in Micro Aerial Vehicle
Get PDFMicro Aerial Vehicles (MAVs) are popular for their efficiency, agility, and lightweights. They can navigate in dynamic environments that cannot be accessed by humans or traditional aircraft. These MAVs rely on GPS and it will be difficult for GPS-denied areas where it is obstructed by buildings and other obstacles. Simultaneous Localization and Mapping (SLAM) in an unknown environment can solve the aforementioned problems faced by flying robots. A rotation and scale invariant visual-based solution, oriented fast and rotated brief (ORB-SLAM) is one of the best solutions for localization and mapping using monocular vision.
In this paper, an ORB-SLAM3 has been used to carry out the research on localizing micro-aerial vehicle Tello and mapping an unknown environment. The effectiveness of ORB-SLAM3 was tested in a variety of indoor environments. An integrated adaptive controller was used for an autonomous flight that used the 3D map, produced by ORB-SLAM3 and our proposed novel technique for robust initialization of the SLAM system during flight. The results show that ORB-SLAM3 can provide accurate localization and mapping for flying robots, even in challenging scenarios with fast motion, large camera movements, and dynamic environments. Furthermore, our results show that the proposed system is capable of navigating and mapping challenging indoor situations