The Internet of Things (IoT) has great importance in the medical industry. The creation of intelligent sensors, intelligent machines, and superior algorithms for lightweight communication made it feasible to connect medical equipment in order to monitor biomedical signals and also to detect illnesses in patients without human intervention. This new IoT and medical equipment connection is called IoMT. This IoMT model is most adapted to this pandemic since every human being has to be interconnected and monitored via a larger communication network. Hence, this article provides an overview of remote healthcare systems, monitoring ingestible sensors, mobile health, smart hospitals, and improved chronic disease management focused on t

     In this study, dark and various light qualities (white, red, green, and blue) were applied to evaluate their effects on growth characteristics, chemical content, and callus characteristics of Rosa damascene Mill. and Rosa hybirda L.

   Explant (single-node and shoot tips) cultured on MS media supplemented with sucrose, agar, and plant growth regulators ( Kin 0.5 mg/l and IBA 1 mg/l for whole plant formation experiment or 1 mg/l kin with 0.5 mg/l IBA for callus experiment), incubated in a growth chamber.

   The results of the whole plant formation experiment showed variation in growth characteristics in two types of Rosa, Green and white light caused the height ratio of shoot growth compared wi

Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa