Elumalaivasan Poongavanam^1,*, Padmanathan Kasinathan², Kulothungan Kanagasabai³

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 249-265, 2023, DOI:10.32604/iasc.2023.030101

Abstract The nation deserves to learn what India’s future energy demand will be in order to plan and implement an energy policy. This energy demand will have to be fulfilled by an adequate mix of existing energy sources, considering the constraints imposed by future economic and social changes in the direction of a more sustainable world. Forecasting energy demand, on the other hand, is a tricky task because it is influenced by numerous micro-variables. As a result, an macro model with only a few factors that may be predicted globally, rather than a detailed analysis for each of these variables, is… More >

Xin Chang^1,2,#,*, Jin Wang^2,#, Caifang Ni¹

Oncologie, Vol.23, No.1, pp. 119-130, 2021, DOI:10.32604/oncologie.2021.014152

Abstract Objective: This research was designed to observe the value of miR-1271 and GPC3 in evaluating the prognosis of liver cancer (LC) patients after liver transarterial chemoembolization (TACE). Methods: A total of 80 patients diagnosed as LC in our hospital from January 2018 to April 2019 were included in the LC group (LCG), and then assigned into a survival group (SG) and a death group (DG) based on prognosis. Seventy healthy subjects undergoing physical examination simultaneously were included in the normal group (NG). miR-1271 and GPC3 in serum of two groups of subjects were tested via qRT-PCR. ROC curve was drawn.… More >

Chen Shen^1,*, Youping Chen¹, Bing Chen¹, Jingming Xie¹

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 379-397, 2019, DOI:10.32604/cmc.2019.04883

Abstract Continuous material processing operations like printing and textiles manufacturing are conducted under highly variable conditions due to changes in the environment and/or in the materials being processed. As such, the processing parameters require robust real-time adjustment appropriate to the conditions of a nonlinear system. This paper addresses this issue by presenting a hybrid feedforward-feedback nonlinear model predictive controller for continuous material processing operations. The adaptive feedback control strategy of the controller augments the standard feedforward control to ensure improved robustness and compensation for environmental disturbances and/or parameter uncertainties. Thus, the controller can reduce the need for manual adjustments. The controller… More >