The Classical statistical inference for integer valued time-series has primarily been restricted to the integer valued autoregressive (INAR) process. Markov chain Monte Carlo (MCMC) methods have been shown to be a useful tool in many branches of statistics and is particularly well suited to integer valued time-series where statistical inference is greatly assisted by data augmentation. Thus in ...

the selection of best information system (is) project from many competing proposals is a critical business activity which is very helpful to all organizations. while previous is project selection methods are useful but have restricted application because they handle only cases with precise data. indeed, these methods are based on precise data with less emphasis on imprecise data. this paper pro...

A tone mapping operation (TMO) for HDR images with fixed-point arithmetic is proposed. A TMO generates a low dynamic range (LDR) image from a high dynamic range (HDR) image by compressing its dynamic range. Since HDR images are generally expressed in a floating-point data format, a TMO also deals with floating-point data even though resulting LDR images have integer data. As a result, conventio...

It is known that the integer partitions may be encoded as either ascending or descending compositions for the purposes of systematic generation. In this paper we give an efficient data structure for storing all ascending compositions of a positive integer. Using this structure, we improved the fastest known algorithm for generating integer partitions.

Mixed Integer Optimization has been a topic of active research in past decades. It has been used to solve Statistical problems of classification and regression involving massive data. However, there is an inherent degree of vagueness present in huge real life data. This impreciseness is handled by Fuzzy Sets. In this Paper, Fuzzy Mixed Integer Optimization Method (FMIOM) is used to find solutio...

Association rule mining is basically used to generate association rules on a real life datasets. A well-known algorithm called apriori is used to generate the frequent pattern itemsets for a given transaction. Since real life dataset consist of nominal, continuous, integer attribute fields, to convert it into binary format some type of pre-processing has to be done on the dataset. In this paper...