Research
Machine Learning Algorithm for Development of Enhanced Support Vector Machine Technique to Predict Stress
Stress is a common risk factor for many diseases. A correct and efficient prediction model is required to predict stress levels for targeted prevention and intervention in the personal healthcare domain. Before preventing the event of stress-related diseases, stress should be detected and managed early. However, surveys are used to evaluate an individual's stress condition with ease of measurement and requiring little time. However, anything that puts high demands on a person makes it stressful. This includes positive events such as getting married, buying a house, going to college, or receiving a promotion. Of course, not all stress is caused by external factors. Stress can also be internal or self-generated, when a person worries excessively about something that may or may not happen, or have irrational, pessimistic thoughts about life. This article aims to develop a predictive model to find the interruption of stress using an efficient way. One of the successive machine learning algorithm is SVM. This paper proposed to enhance the parameters of SVM which is used to improve the efficiency for predicting stress. This article proposed an Enhanced Support Vector Machine classifier to predict Stress. The stress dataset is downloaded from the Kaggle repository with 951 instances and 21 attributes.
Adaptive Multicast Multimedia Transmission Routing Protocol System (ACMMR) for Congestion Control and Load Balancing Techniques in Mobile Adhoc Networks
A MANET is a probable solution for this need to quickly establish interactions in a mobile and transient environment. Proposed congestion controlled adaptive multicasting routing protocol to achieve load balancing and avoid congestion in MANETs. The existing algorithm for finding multicasting routes computes fail-safe multiple paths, which provide all the intermediate nodes on the primary path with multiple routes to target node. Routing may let a congestion happen, which is detected by congestion control, but dealing with congestion in this reactive manner results in longer delay and redundant packet loss and requires significant overhead if a new route is needed. Transmission of real-time video typically has bandwidth, delay, and loss requirements. Video transmission over wireless network poses many challenges. To overcome these challenges, extensive research has been conducted in the various areas of video application.
