SFLA based PI parameter optimization for optimal controlling of a Buck converter's voltage

2017 International Artificial Intelligence and Data Processing Symposium (IDAP) -- SEP 16-17, 2017 -- Malatya, TURKEY -- IEEE Turkey Sect, Anatolian SciIn this work, it is aimed to control the output of Buck Converter which steps down a DC voltage level. Discrete Time PI Algorithm is chosen as control algorithm. The controller parameters of K-p and K-i is calculated by means of the optimization process to increase the efficiency of power transmission of Buck Converter instead of classical methods like Pole Placement Method. It is chosen Shuffled Frog Leaping Algorithm (SFLA) which is an iterative algorithm as optimization algorithm. The results obtained from simultaneous executions of control process is discussed by simulating in Matlab-Simulink.WOS:0004268687000722-s2.0-8503989657

Independent effect of fatigue on health-related quality of life in patients with idiopathic Parkinson's disease

albay, vasfiye burcu/0000-0003-0428-981XWOS: 000365711100009PubMed: 26198763Nonmotor symptoms (NMS) of idiopathic Parkinson's disease (IPD), specifically fatigue, depression and sleep disturbances, are important contributors for worse quality of life and poor patient outcomes. the aim of this research is to determine the relationship between fatigue and other NMS and the independent effect of fatigue on health-related quality of life (HRQoL) in patients with IPD. 86 IPD patients and 85 healthy individuals were included in our study. Participants were evaluated by their answers to the Beck Depression Inventory, Fatigue Severity Scale, Epworth Sleepiness Scale and Parkinson's Disease Questionnaire-39. Hoehn-Yahr stage, disease duration, medications and demographical characteristics were also noted. ROC analysis was used to determine the cutoff point for HRQoL. Nonparametric Spearman correlation analysis was used for determining the relationship between variables. Independent factors which affect HRQoL were detected by multiple forward stepwise logistic regression analysis. NMS were associated with each other and with HRQoL when they act concomitantly (p 0.05). the stage of IPD and levodopa-entacapone treatment had independent effects on HRQoL too (p < 0.05). Fatigue was found as the most important factor which affects HRQoL among all investigated NMS. So, it is important to ask about fatigue in routine controls of IPD patients and try to treat it for improving life quality