WHOOPH: whale optimization-based optimal placement of hub node within a WBAN

Abstract Biosensor nodes of a wireless body area network (WBAN) transmit physiological parameter data to a central hub node, spending a substantial portion of their energy. Therefore, it is crucial to determine an optimal location for hub placement to minimize node energy consumption in data transmission. Existing methods determine the optimal hub location by sequentially placing the hub at multiple random locations within the WBAN. Performance measures like link reliability or overall node energy consumption in data transmission are estimated for each hub location. The best-performing location is finally selected for hub placement. Such methods are time-consuming. Moreover, the involvement of other nodes in the process of hub placement results in an undesirable loss of network energy. This paper shows the whale optimization algorithm (WOA)-based hub placement scheme. This scheme directly gives the best location for the hub in the least amount of time and with the least amount of help from other nodes. The presented scheme incorporates a population of candidate solutions called "whale search agents". These agents carry out the iterative steps of encircling the prey (identifying the best candidate solution), bubble-net feeding (exploitation phase), and random prey search (exploration phase). The WOA-based model eventually converges into an optimized solution that determines the optimal location for hub placement. The resultant hub location minimizes the overall amount of energy consumed by the WBAN nodes for data transmission, which ultimately results in an elongated lifespan of WBAN operation. The results show that the proposed WOA-based hub placement scheme outperforms various state-of-the-art related WBAN protocols by achieving a network lifetime of 8937 data transmission rounds with 93.8% network throughput and 9.74 ms network latency

Characterization of bioactive and fruit quality compounds of promising mango genotypes grown in Himalayan plain region

Twenty mango genotypes grown in the plains of the Himalayas were characterized by their physical, physiological, biochemical, mineral and organoleptic attributes: fruit firmness, weight, peel thickness, shape, dry seed weight, respiration rate, weight loss, and shelf life. Biochemical attributes such as soluble solids, total carotenoids, total phenolic content, antioxidant activity, titratable acidity, ascorbic acid and total sugars were also determined. In addition, mineral content and fruit-softening enzymes were measured, and an organoleptic evaluation was performed. Polygalactouronase (PG), pectin methylesterase (PME) and lipoxygenase (LOX) were measured from the pulp adjacent to the peel. Similarly, biochemical attributes and mineral content were evaluated using fruit pulp, while organoleptic evaluation included fruit pulp characters and the fruit’s external appearance. The results of the study showed that the ‘Malda’ genotype exhibited the highest total phenolic content (560.60 µg/100 g), total antioxidant (5.79 µmol TE/g), and titratable acidity (0.37%) among the tested genotypes. ‘Amrapali’ had the highest soluble solid content (25.20 °B), ‘Jawahar’ had the highest ascorbic acid content (44.20 mg/100 g pulp), ‘Mallika’ had the highest total flavonoid content (700.00 µg/g) and ‘Amrapali’ had the highest total carotenoid content (9.10 mg/100 g). Moreover, the genotypes ‘Malda’, ‘Safed Malda’and ‘Suvarnarekha’ had a shelf life of 4–5 days longer than other tested genotypes. The genotypes with high biochemical attributes have practical utility for researchers for quality improvement programmes and processing industries as functional ingredients in industrial products. This study provides valuable information on the nutritional and functional properties of different mango genotypes, which can aid in developing improved varieties with enhanced health benefits and greater practical utility for processing industries