Performance enhancement of stepped basin solar still based on OSELM with traversal tree for higher energy adaptive control

A basin solar still precision design is regularly not reachable. To solve this issue, the basin area is coated with a nanolayer which allows to stimulate and control the multifaceted of the fast evaporations of physiognomies. The use of adaptive neural network-based approaches leads to better design cause permits detecting the conjunction, gigantic period feed, lower performances parameters which can be detrimental to system production. Further, an online Sequential Extreme Learning Machine (OSELM) system can be used to obtain the latest solar still based on adaptive control. Here, the solar still has been created at physical scale activity for haste of energy absorption. The performance of solar still is defined by the uniform occurrence with time series of dynamics transfer from basin liner to saline water. The feasibility scheme to authenticate was studied by applying calculation to the extensive heat transfer process. The furious SiO2/TiO2 nanoparticles used for the stepped basin solar still (SBSS) efficiency shows an increase of performances by 37.69% and 49.21%, respectively using 20% and 30% of SiO2/TiO2 coating. It is comparable higher when equated against an SBSS coating either SiO2 or TiO2, and/or no nanoparticles coatings. The binary search tree enabled to find the optimal cost for the solar still investigated and obtaining a superior design with higher performances

Better analysis of greedy binary search tree on decomposable sequences

In their seminal paper [Sleator and Tarjan, J.ACM, 1985], the authors conjectured that the splay tree is dynamically optimal binary search tree (BST). In spite of decades of intensive research, the problem remains open. Perhaps a more basic question, which has also attracted much attention, is if there exists any dynamically optimal BST algorithm. One such candidate is GREEDY which is a simple and intuitive BST algorithm [Lucas, Rutgers Tech. Report, 1988; Munro, ESA, 2000; Demaine, Harmon, Iacono, Kane and Patrascu, SODA, 2009]. [Demaine et al., SODA, 2009] showed a novel connection between a geometric problem. Since dynamic optimality conjecture in its most general form remains elusive despite much effort, researchers have studied this problem on special sequences. Recently, [Chalermsook, Goswami, Kozma, Mehlhorn and Saranurak, FOCS, 2015] studied a type of sequences known as k-{\em decomposable sequences} in this context, where k parametrizes easiness of the sequence. Using tools from forbidden submatrix theory, they showed that GREEDY takes n2O(k2) time on this sequence and explicitly raised the question of improving this bound. In this paper, we show that GREEDY takes O(nlogk) time on k-decomposable sequences. In contrast to the previous approach, ours is based on first principles. One of the main ingredients of our result is a new construction of a lower bound certificate on the performance of any algorithm. This certificate is constructed using the execution of GREEDY, and is more nuanced and possibly more flexible than the previous independent set certificate of Demaine et al. This result, which is applicable to all sequences, may be of independent interest and may lead to further progress in analyzing GREEDY on k-decomposable as well as general sequences.by Navin Goyal and Manoj Gupt