Impact of Income Level of an Individual on his BMI and Performance Analysis using Various Machine Learning Approaches on ATUS Survey 2014–16

Author(s):  
Neha Singh ◽  
Sinu Mathew ◽  
Neha Kunte
Author(s):  
Rajasekaran Thangaraj ◽  
Sivaramakrishnan Rajendar ◽  
Vidhya Kandasamy

Healthcare motoring has become a popular research in recent years. The evolution of electronic devices brings out numerous wearable devices that can be used for a variety of healthcare motoring systems. These devices measure the patient's health parameters and send them for further processing, where the acquired data is analyzed. The analysis provides the patients or their relatives with the medical support required or predictions based on the acquired data. Cloud computing, deep learning, and machine learning technologies play a prominent role in processing and analyzing the data respectively. This chapter aims to provide a detailed study of IoT-based healthcare systems, a variety of sensors used to measure parameters of health, and various deep learning and machine learning approaches introduced for the diagnosis of different diseases. The chapter also highlights the challenges, open issues, and performance considerations for future IoT-based healthcare research.


2021 ◽  
Vol 11 (10) ◽  
pp. 568
Author(s):  
Milena P. Ilić ◽  
Dan Păun ◽  
Nevenka Popović Šević ◽  
Aleksandra Hadžić ◽  
Anca Jianu

Higher education in the Republic of Serbia needs to be reformed. This paper presents a performance analysis of the changes that the authors assume are mandatory, presenting the research problem this article addresses. Cabinet research, performed by analyzing the theoretical building blocks of available knowledge and experience, is underway. Articles and studies from various publications, such as academic journals and institutes, were used as sources. In addition, academic articles and papers and studies about artificial intelligence, machine learning, and extended reality were also consulted. The authors consider that these technologies could be of great assistance in developing a new higher education strategy. Further, this research is exploratory given that information from the 100 Serbian students from selected higher education institutions was used to better understand if these technologies are welcomed by students. Based on SmartPls software, the research analysis proved that artificial intelligence (AI) and machine learning (ML) are appropriate technologies implemented in higher education institutions (HEI) to develop skills among students, a collaborative learning environment, and an accessible research environment. Additionally, extended reality (XR) facilitates increased motivation, engagement, and learning-by-doing activities between students, offering a realistic environment for learning.


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