Guided regularized random forest feature selection for smartphone based human activity recognition.

Human activity recognition (HAR) is an eminent area of research due to its extensive scope of applications in remote health monitoring, sports, smart home, and many more. Smartphone-based HAR systems use high-dimensional sensor data to infer human physical activities. Researchers continuously endeavor to select pertinent and non-redundant features without compromising the classification accuracy.

Mathematical modelling for decision making of lockdown during COVID-19.

Due to the recent worldwide outbreak of COVID-19, there has been an enormous change in our lifestyle and it has a severe impact in different fields like finance, education, business, travel, tourism, economy, etc., in all the affected countries. In this scenario, people must be careful and cautious about the symptoms and should act accordingly.

On Development of MySignals based prototype for application in health vitals monitoring.

India's health infrastructure is under pressure since the daily COVID-19 cases have crossed the milestone of 4 Lakhs cases per day which surpass the previous years' peak. Patients with mild symptoms have been advised for home treatment since most of the hospitals are running out of bed. In this situation delivering healthcare to people has become revolutionizing due to the rapid advancement of embedded systems, communication, and informatics technologies.

Feature fusion using deep learning for smartphone based human activity recognition.

Identification of human physical activities is an active research area since long due to its application in personalized health and fitness monitoring. The performance accuracy of human activity recognition (HAR) models mainly depend on the features which are extracted from domain knowledge. The features are the input of the classification algorithm to efficiently identify human physical activities.

A Working Prototype Using DS18B20 Temperature Sensor and Arduino for Health Monitoring.

Due to the successful emergence of internet of things, sensor-based real-time health monitoring is getting popularized. A usable health-monitoring system is required for prolonged monitoring of the patient with reduced cost. This paper describes a working prototype system for real-time health-monitoring system using DS18B20 temperature sensor, Arduino Nano with micro-controller ATmega328 where Zigbee module is used for wireless communication.

Lactam nonanic acid, a new substance from Cleome viscosa with allelopathic and antimicrobial properties.

Cleome viscosa L. (Capparidaceae) is well known for its medicinal properties. Lactam nonanoic acid (LNA) [2-amino-9-(4-oxoazetidin-2-yl)-nonanoic acid; C12H22N2O3, mol.

Eco-friendly synthesis and study of new plant growth promoters: 3,3'-Diindolylmethane and its derivatives.

3,3'-Diindolylmethane (DIM) derivatives 3a-k, prepared in one-pot from indoles 1a-k and hexamethylenetetramine (2) using ionic liquid [Bmim]BF(4) as eco-friendly recyclable solvent as well as catalyst, showed good plant growth promoting activity on Oryza sativa. Among the DIM derivatives synthesized 3c shows potent auxin like growth promoting activity.