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This paper concerns the optimization and coordination of the conventional FACTS (Flexible AC Transmission Systems) damping controllers in multimachine power system. Firstly, the parameters of FACTS controller are optimized. Then, a hybrid fuzzy logic controller for the coordination of FACTS controllers is presented. This coordination method is well suitable(More)
BACKGROUND Methyl bromide is being phased out for use on stored commodities, as it is listed as an ozone-depleting substance, and phosphine is the fumigant widely used on grains. However, phosphine resistance occurs worldwide, and phosphine fumigation requires a long exposure period and temperatures of >15 °C. There is an urgent requirement for the(More)
Gene selection based on microarray data, is highly important for classifying tumors accurately. Existing gene selection schemes are mainly based on ranking statistics. From manifold learning standpoint, local geometrical structure is more essential to characterize features compared with global information. In this study, we propose a supervised gene(More)
Identifying the microRNA-disease relationship is vital for investigating the pathogenesis of various diseases. However, experimental verification of disease-related microRNAs remains considerable challenge to many researchers, particularly for the fact that numerous new microRNAs are discovered every year. As such, development of computational methods for(More)
Identifying protein complexes in protein-protein interaction (PPI) networks is a fundamental problem in computational biology. High-throughput experimental techniques have generated large, experimentally detected PPI datasets. These interactions represent a rich source of data that can be used to detect protein complexes; however, such interactions contain(More)
Currently, there are lots of methods to select informative SNPs for haplotype reconstruction. However, there are still some challenges that render them ineffective for large data sets. First, some traditional methods belong to wrappers which are of high computational complexity. Second, some methods ignore linkage disequilibrium that it is hard to interpret(More)
Time-course gene expression datasets, which record continuous biological processes of genes, have recently been used to predict gene function. However, only few positive genes can be obtained from annotation databases, such as gene ontology (GO). To obtain more useful information and effectively predict gene function, gene annotations are clustered together(More)
Current research community on data streams mining focuses on mining balanced data streams. However, the skewed class distribution appears in many data streams applications. In this paper, we introduce the method of discovering concept drifting on skewed data streams and propose an algorithm for classifying skewed data streams based on reusing data, RDFCSDS(More)
Current research on data stream classification mainly focuses on supervised learning, in which a fully labeled data stream is needed for training. However, fully labeled data streams are expensive to obtain, which makes the supervised learning approach difficult to be applied to real-life applications. In this paper, we consider the problem of one-class(More)
INTRODUCTION MicroRNAs (miRNAs) has emerged as important factors in osteogenesis and chondrogenesis. This study aimed to determine whether miR-221 is involved in the regulation of osteoporosis and its underlying mechanism. METHODS Total RNA was extracted from fresh femoral neck trabecular bone from women undergoing hip replacement due to either(More)