Development of 2D casting process CAD system based on PDF/image files

A casting process CAD is put forward to design and draw casting process. The 2D casting process CAD, most of the current systems are developed based on one certain version of the AutoCAD system. However the application of these 2D casting process CAD systems in foundry enterprises are restricted because they have several deficiencies, such as being overly dependent on the AutoCAD system, and some part files based on PDF format can not be opened directly. To overcome these deficiencies, for the first time an innovative 2D casting process CAD system based on PDF and image format file has been proposed, which breaks through the traditional research and application notion of the 2D casting process CAD system based on AutoCAD. Several key technologies of this system such as coordinate transformation, CAD interactive drawing, file storage, PDF and image format files display, and image recognition technologies were described in detail. A practical 2D CAD casting process system named HZCAD2D（PDF） was developed, which is capable of designing and drawing the casting process on the part drawing based on the PDF format directly, without spending time on drawing the part produced by AutoCAD system. Final y, taking two actual castings as examples, the casting processes were drawn using this system, demonstrating that this system can significantly shorten the cycle of casting process designing.

FARMER:A novel approach to file access correlation mining and evaluation reference model

File semantic has proven effective in optimizing large scale distributed file system.As a consequence of the elaborate and rich I/O interfaces between upper layer applications and file systems,file system can provide useful and insightful information about semantic.Hence,file semantic mining has become an increasingly important practice in both engineering and research community.Unfortunately,it is a challenge to exploit file semantic knowledge because a variety of factors coulda ffect this information exploration process.Even worse,the challenges are exacerbated due to the intricate interdependency between these factors,and make it difficult to fully exploit the potentially important correlation among various semantic knowledges.This article proposes a file access correlation miming and evaluation reference（FARMER） model,where file is treated as a multivariate vector space,and each item within the vector corresponds a separate factor of the given file.The selection of factor depends on the application,examples of factors are file path,creator and executing program.If one particular factor occurs in both files,its value is non-zero.It is clear that the extent of inter-file relationships can be measured based on the likeness of their factor values in the semantic vectors.Benefit from this model,FARMER represents files as structured vectors of identifiers,and basic vector operations can be leveraged to quantify file correlation between two file vectors.FARMER model leverages linear regression model to estimate the strength of the relationship between file correlation and a set of influencing factors so that the ＂bad knowledge＂ can be filtered out.To demonstrate the ability of new FARMER model,FARMER is incorporated into a real large-scale object-based storage system as a case study to dynamically infer file correlations.In addition FARMER-enabled optimize service for metadata prefetching algorithm and object data layout algorithm is implemented.Experimental results show that is FARMER-enabled prefetching algorithm is shown to reduce the metadata operations latency by approximately 30%-40% when compared to a state-of-the-art metadata prefetching algorithm and a commonly used replacement policy.