-In transformer fault diagnosis, dissolved gas analysis (DGA) is been widely employed for a long period and numerous methods have been innovated to interpret its results. Still in some cases it fails to identify the corresponding faults. Due to the limitation of training data and non-linearity, the estimation of key-gas ratio in the transformer oil becomes more complicated. This paper presents Intuitionistic Fuzzy expert System (IFS) to diagnose several faults in a transformer. This revised approach is well suitable to diagnosis the transformer faults and the corresponding action to be taken. The proposed method is applied to an independent data of different power transformers and various case studies of historic trends of transformer units. It has been proved to be a very advantageous tool for transformer diagnosis and upkeep planning. This method has been successfully used to identify the type of fault developing within a transformer even if there is conflict in the results of AI technique applied to DGA data.
Prevention of healthcare-associated infections: protecting patients, saving livesSir,Healthcare-Associated Infections (HAIs) are those infections which the patients acquire during the course of receiving treatment and are not present or incubating at the time of admission. It also includes infections which appear after discharge and occupational infections among healthcare staff. 1 These infections are mostly caused by viral, bacterial or fungal pathogens and the most common types of HAIs include: blood stream infections, pneumonias (e.g. ventilator-associated pneumonia), urinary tract infections and surgical site infections.
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