Accidents can have a significant impact on road safety and the efficiency of transport. With the ever-increasing number of vehicles on the road, it is crucial to quickly detect and respond to such events to decrease t...
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In this research, we propose a low-cost indoor localization technique using the CSI. By using CSI signal as input data, different locations and human activities are classified effectively using machine learning models...
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This research study introduces Alfred, a novel open-source Autonomous Mobile Robot (AMR) platform and a physical testbed that enables the integration of virtual scenarios. This system allows for the development and ev...
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Cyber-attacks are a growing threat to individuals, businesses, and governments. Data science helps improve security by analyzing network traffic and system activities. Intrusion detection systems (IDSs) are essential ...
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With the revolutionary growth of the Internet of Things (IoT) and the increasing number of chronic disease patients, a trend toward building a reliable, smart prescription system to aid healthcare has emerged. Many pa...
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In the rapidly changing field of pharmaceutical development, it is crucial to speed up clinical trials in order to introduce effective drugs in a timely manner. Conventional methods of forecasting molecular characteri...
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When people observe pictures, different pictures will generate different emotions, and the painters often convey emotional energy to the audience through the media. Through the effect of this emotional transfer, peopl...
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Medical image fusion is crucial for various applications, yet existing fusion models often encounter issues such as low quality, information loss, and insufficient contrast. This paper presents a novel approach to med...
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The demand for better health services has resulted in the advancementof remote monitoring health, i.e., virtual nursing systems, to watch and supportthe elderly with innovative concepts such as being patient-centric, ...
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The demand for better health services has resulted in the advancementof remote monitoring health, i.e., virtual nursing systems, to watch and supportthe elderly with innovative concepts such as being patient-centric, easier to use,and having smarter interactions and more accurate conclusions. While virtual nursing services attempt to provide consumers and medical practitioners with continuous medical and health monitoring services, access to allied healthcare expertssuch as nurses remains a challenge. In this research, we present Virtual NursingUsing Deep Belief Networks for Elderly People (DBN-EP), a new framework thatprovides a virtual nurse agent deployed on a senior citizen’s home, workplace, orcare centre to help manage their health condition on a continuous basis. Using thismethod, healthcare providers can assign various jobs to nurses by utilizing a general task definition mechanism, in which a task is defined as a combination ofmedical workflow, operational guidelines, and data gathered from a remotelymonitored virtual nursing system. Practitioners are in charge of DBN-EP andmake treatment decisions for patients. This allows a DBN-EP to act as a personalized full-time nurse for a client by carrying out practitioner support activitiesbased on information gathered about the client’s health. An electronic PersonalHealth Record (ePHR) system, such as a specialized web portal and mobile apps,could provide such patient information to elderly person family members and carecentres. We created a prototype system using a DBN-EP system that allows traditional client applications and healthcare provider systems to collaborate. Finally,we demonstrate how this system may benefit the elderly through a result anddebate.
Hepatitis C is the liver's festering that can lead to severe liver damage, usually caused by the hepatitis C virus. Hepatitis C has different stages. It is tough to cure in it's last stages;at the same time, i...
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