In data grid, using reservation is accepted to provide scheduling and service quality. Users need to have an access to the stored data in geographical environment, which can be solved by using replication, and an action taken to reach certainty. As a result, users are directed toward the nearest version to access information. The most important point is to know in which sites and distributed sy...

Data Grid provides sharing services for very large data around the world. Data replication is one of the most effective approaches to reduce access latency and response time. In addition to the benefits, replication has costs such as storage and bandwidth consumption, especially when storage space is low and limited. Therefore,  the data replacement should be done wisely. In this p...

Large-scale data management is a critical problem in a distributed system such as cloud,P2P system, World Wide Web (WWW), and Data Grid. One of the effective solutions is data replicationtechnique, which efficiently reduces the cost of communication and improves the data reliability andresponse time. Various replication methods can be proposed depending on when, where, and howreplicas are gener...

Data Envelopment Analysis (DEA) is a mathematical programming technique for evaluatingthe relative efficiency of a set of Decision Making Units (DMUs) and can also be utilized forsetting target. Target setting is one of the important subjects since according to its resultsefficiency can be increased. An important issue to be currently discussed, is to set targetwhile considering share data. The...

the present study is an attempt toward evaluating the performance of portfolios using mean-variance-skewness model with negative data. mean-variance non-linear framework and mean-variance-skewness non- linear framework had been proposed based on data envelopment analysis, which the variance of the assets had been used as an input to the dea and expected return and skewness were the output. conv...

background policy makers need models to be able to detect groups at high risk of hiv infection. incomplete records and dirty data are frequently seen in national data sets. presence of missing data challenges the practice of model development. several studies suggested that performance of imputation methods is acceptable when missing rate is moderate. one of the issues which was of less concern...