an enterprise resource planning (erp) software is needed for industries and companies that want to develop in future. many of the manufactures and companies have a problem with erp software selection. an inappropriate selection process can affect both the implementation and the performance of the company significantly. although several models are proposed to solve this problem many of them did n...

In this research, the demand function of drinkable  water in Qazvin Province was estimated using dynamic and static methods. The required data were collected from the data of the provinces of Qazvin in the time period (1996-2016) and collected by referring to the statistical system of Statistics Center of Iran and the provincial planning and budget organization of Qazvin Province. The explanato...

Attribute grammars are a powerful specification paradigm for many language processing tasks, particularly semantic analysis of programming languages. Recent attribute grammar systems use dynamic scheduling algorithms to evaluate attributes by need. In this paper, we show how to remove the need for a generator, by embedding a dynamic approach in a modern, object-oriented programming language to ...

As the product of combining Internet Things (IoT), cloud computing, and traditional healthcare, Intelligent IoT Healthcare (IIoTH) brings us a lot convenience, meanwhile security privacy issues have attracted great attention. Dynamic searchable symmetric encryption (DSSE) technique can make user search dynamic healthcare information from IIoTH system under condition that is protected. In this a...

the partial differential equations for water flow and solute transport in a two-dimensional saturated domain are rendered discrete using the finite difference technique; the resulting system of algebraic equations is solved using a dynamic programming (dp) method. the advantage of the dp algorithm is that the problem is converted from solving an algebraic system of order nc(nl-1) nc(nl-1) into...

In this paper, we study probabilistic and rough set approaches to missing attribute values. Probabilistic approaches are based on imputation, a missing attribute value is replaced either by the most probable known attribute value or by the most probable attribute value restricted to a concept. In this paper, in a rough set approach to missing attribute values we consider two interpretations of ...

We introduce a new combinatorial dimension that gives a good approximation of the number of queries needed to learn in the exact learning model, no matter what set of queries is used. This new dimension generalizes previous dimensions providing upper and lower bounds for all sorts of queries, and not for just example-based queries as in previous works. Our new approach gives also simpler proofs...

As big data often contains a significant amount of uncertain, unstructured, and imprecise that are structurally complex incomplete, traditional attribute reduction methods less effective when applied to large-scale incomplete information systems extract knowledge. Multigranular computing provides powerful tool for use in analysis conducted at different levels granularity. In this article, we pr...