The use of fuzzy logic in disease diagnosis is very common and beneficial as it incorporates the knowledge and experience of physician into fuzzy sets and rules. Most of the research proposed different systems for the diabetes diagnosis. But their accuracy of prediction is not accurate. So, the proposed system presents promising approach for accurately predicting the diabetes by considering the different parameters which are helpful in the diagnosis of diabetes. The proposed fuzzy verdict mechanism takes the information collected from the patients as inputs in the form of datasets. System considers both rules and physicians knowledge to provide the prediction rate of diabetes. Evaluation shows the approach results in better accuracy as compared to other prediction approaches.

Vague sets theory separates the evidences in favour and against of an element in a set which provides better mechanism to handle impreciseness and uncertainty. This research paper aims to handle the incompleteness and impreciseness of data associated with the disk access requests. Here, we propose a new disk scheduling algorithm, Vague Disk Scheduling (VDS) Algorithm, based on vague logic. The proposed framework includes Vague-Fuzzification Technique, Priority Expression, and VDS Algorithm. The Vague-Fuzzification Technique is applied to the input data of each disk access request and generates a priority for each request in the queue. Based on the priority allotted the requests are serviced. Finally work is evaluated on different datasets and finally compared with Fuzzy Disk Scheduling (FDS) Algorithm. The results prove that VDS algorithm performs better than FDS Algorithm.