A novel method for detecting optimal location and parameters of power system stabilizer (PSS) based on intelligent techniques

ABSTRACT: This paper presents a new technique to design a Power System Stabilizer (PSS) in multi-machine power system. The method is based on the Particle Swarm Optimization (PSO) algorithm for tuning PSS parameters including lead-lag compensator time constants as well as the controller gain. For evaluating the particles evolution throughout the searching process, an eigenvalue-based multi-objective function is used. The DIgSILENT is used as tool for modelling test system and programming PSO algorithm. Then by using a fuzzy approach implemented in Matlab/fuzzy toolbox the optimal number and location for PSSs specified. Two-area (four-machine 11bus) Power system is considered as the case study in this paper. Simulation results for various operating conditions prove the capability of the proposed algorithm in damping improvement of power system

New generalized fuzzy metrics and fixed point theorem in fuzzy metric space

In this paper, in fuzzy metric spaces (in the sense of Kramosil and Michalek (Kibernetika 11:336-344, 1957)) we introduce the concept of a generalized fuzzy metric which is the extension of a fuzzy metric. First, inspired by the ideas of Grabiec (Fuzzy Sets Syst. 125:385-389, 1989), we define a new G-contraction of Banach type with respect to this generalized fuzzy metric, which is a generalization of the contraction of Banach type (introduced by M Grabiec). Next, inspired by the ideas of Gregori and Sapena (Fuzzy Sets Syst. 125:245-252, 2002), we define a new GV-contraction of Banach type with respect to this generalized fuzzy metric, which is a generalization of the contraction of Banach type (introduced by V Gregori and A Sapena). Moreover, we provide the condition guaranteeing the existence of a fixed point for these single-valued contractions. Next, we show that the generalized pseudodistance J:X×X→[0,∞) (introduced by Włodarczyk and Plebaniak (Appl. Math. Lett. 24:325-328, 2011)) may generate some generalized fuzzy metric NJ on X. The paper includes also the comparison of our results with those existing in the literature

Genomic landscape of patients with FLT3-mutated acute myeloid leukemia (AML) treated within the CALGB 10603/RATIFY trial

The aim of this study was to characterize the mutational landscape of patients with FLT3-mutated acute myeloid leukemia (AML) treated within the randomized CALGB 10603/RATIFY trial evaluating intensive chemotherapy plus the multi-kinase inhibitor midostaurin versus placebo. We performed sequencing of 262 genes in 475 patients: mutations occurring concurrently with the FLT3-mutation were most frequent in NPM1 (61%), DNMT3A (39%), WT1 (21%), TET2 (12%), NRAS (11%), RUNX1 (11%), PTPN11 (10%), and ASXL1 (8%) genes. To assess effects of clinical and genetic features and their possible interactions, we fitted random survival forests and interpreted the resulting variable importance. Highest prognostic impact was found for WT1 and NPM1 mutations, followed by white blood cell count, FLT3 mutation type (internal tandem duplications vs. tyrosine kinase domain mutations), treatment (midostaurin vs. placebo), ASXL1 mutation, and ECOG performance status. When evaluating two-fold variable combinations the most striking effects were found for WT1:NPM1 (with NPM1 mutation abrogating the negative effect of WT1 mutation), and for WT1:treatment (with midostaurin exerting a beneficial effect in WT1-mutated AML). This targeted gene sequencing study provides important, novel insights into the genomic background of FLT3-mutated AML including the prognostic impact of co-mutations, specific gene-gene interactions, and possible treatment effects of midostaurin