Search

Using Hybrid optimization algorithms for nonlinear systems analysis is a novel approach. It is a powerful technique that uses the exploitation ability of one algorithm and the exploration ability of another algorithm, to find the best solution. Literature survey reveals that hybrid algorithms not only show quality response but also give faster convergence of error for nonlinear systems. In this paper, hybrid optimization techniques based proportional integral derivative (PID) controller is used for benchmark problems: Continuous stirred tank reactor (CSTR), Inverted pendulum and blood glucose system. Two recent hybrid algorithms: Particle swarm optimization‐Gravitational search algorithm (PSO‐GSA) and Particle swarm optimization‐Grey wolf algorithm (PSO‐GWO) are implemented to control the temperature and concentration of CSTR, pendulum angle of inverted pendulum, glucose concentration and insulin level of blood glucose system. In PID and PSOGWO algorithms, the exploration abilities of GSA and GWO combined with the exploitation ability of PSO have been used. The performance of these algorithms is then compared with individual PSO, GSA, and GWO algorithms proving their superiority. Stability is ensured using the Lyapunov approach while the robustness of the systems is checked using the parameter perturbation technique. Simulation results show substantial improvement in the performance of these systems by using these meta‐heuristic hybrid optimization techniques. A comparative analysis of these algorithms has also been done. [ABSTRACT FROM AUTHOR]

Identification and controlling of non‐linear and complex dynamical systems have been a major concern and a serious topic of study in the field of adaptive control systems. Various techniques based on artificial intelligence have been used for this purpose. For modelling and control of plants, it is essential to optimize the values of the parameters associated with the respective technique. Searching the right or optimum value of the associated parameters is known as optimization. The intelligent water drop (IWD) algorithm is an optimization algorithm derived from the natural intelligence of water drop, which always chooses the shortest possible path while travelling from rivers and lakes towards oceans and seas. This paper introduces a new way of visualizing and understanding the IWD algorithm and presents its respective application in the field of modelling and controlling of non‐linear dynamic systems with the help of illustrative examples. Fuzzy type‐1 and recurrent fuzzy systems have been optimized using this algorithm. Its learning ability is compared with that of the grasshopper algorithm, a particle swarm optimization (PSO) based algorithm and the gradient descent method. The examples show the superiority of the IWD algorithm over the other optimization techniques. [ABSTRACT FROM AUTHOR]

Introduction Stenotrophomonas maltophilia is an emerging environmental, gram-negative, multidrug-resistant organism, associated with risk factors such as prolonged hospitalization, invasive procedures, admission to the intensive care unit, mechanical ventilation, use of indwelling catheters, administration of immunosuppressants or corticosteroids, human immunodeficiency virus infection, underlying malignancy, and organ transplantation. The organism, despite being of low invasiveness in immune-competent individuals, is difficult to treat because of intrinsic resistance to several antimicrobial agents. Materials and Methods This study focuses on commonly encountered resistance from among the isolates over a duration of 7 years from 2012 to 2018, analyzed retrospectively. Identification and susceptibility testing were performed using Vitek 2 (BioMérieux, Marcy-l'Etoile, France). Results Bloodstream infections were found to be most common (52.02%), followed by respiratory infections (35.83%). The median age of the patients was 36 years, and male to female ratio was 143:27. The median duration of hospital stay was 18 days, and mortality was seen in 18.82% of patients. Susceptibility to cotrimoxazole and levofloxacin was seen in 97.1% of isolates (168 out of 173) and 90.1% of isolates (156 out of 173), respectively. Conclusion Despite being effective in a majority of S. maltophilia isolates, both cotrimoxazole and levofloxacin have their shortcomings. Cotrimoxazole is bacteriostatic and can cause bone marrow suppression and resistance to levofloxacin sometimes develops during therapy. Thus, the therapy should be decided considering the characteristics of both of these drugs. [ABSTRACT FROM AUTHOR]