5078035
Order-Based Decision Rules Acquisition in Continuous-Valued Decision Information Systems
In a continuous-valued information system, attribute values of objects represent not only the relative distances, but also the ordinal relation of objects. By considering the relative distances of objects, some discretization approaches and other approaches were proposed in previous literature, to discuss the attribute reduces of the system. This paper considers ordinal relations of objects, and utilizes dominance relation rough set model to discuss decision rules acquisition problems. Firstly, concepts of order-based decision rules and generalized order-based decision rules are introduced. Then the concept of optimal order-based decision rule is defined. In order to compute optimal order-based decision rules, the concept of reduct of the object is proposed. Lastly, discernibility functions of objects are constructed, and used to compute optimal order-based decision rules by Boolean reasoning techniques.
452800
Rough Derivatives in Rough Function Model and Their Application
On the theory and application of rough derivatives in rough function model, the notion of generalized rough functions is defined to improve the definition of higher order rough derivatives Pawlak proposed, and analyze the functional features of roughly derived functions and higher order roughly derived functions. The rough extremum definition of discrete functions is given, Fermat theorem and Rolle theorem of roughly smooth discrete functions are proposed and proved, which complete and perfect the theoretical foundation of rough derivatives application in rough function model. The concepts that are rough monotone and rough convexity of discrete functions are defined. By comparing with the derivative application of real continuous function, a series of theorems are put forward which are the relation theorem of rough derivatives and rough monotone, the two sufficient conditions of rough extrema, the two relation theorems of rough derivatives and rough convexity. Moreover, some new results are achieved such as the sufficient condition of rough smoothing of discrete functions, etc.
13203624
A distributed object tracing system
Trace-based analysis has always been used to guide and motivate more effective hardware and software design. Existing traces available, however, are unsuitable for studying object-based storage system, a very active area of current storage research, because they are collected from the traditional file systems and don't contain information about object. Thus, a kind of distributed object tracing system is presented in this paper which built on the object-based Lustre file system. The tracing system regards object as capturing unit which we also call it object-trace. Objects information is synchronously captured from three software subsystems of Lustre cluster file system, and eventually integrated into one entire trace for every request of each user. To improve I/O performance and efficiency, we employ a ring of buffers to store trace data which finally is written out to a trace file by an output driver. In particular, we use some database tables to save the final incorporated traces for convenient post-analysis. A prototype of object tracing system is designed and implemented on Linux
117805231
Hierarchical methods for three-dimensional surface reconstruction
Surface reconstruction from raw data such as volume data, implicit functions, and scattered data in three-dimensional space is very useful in medical imaging, scientific visualization, and geometric modeling. In this study, several surface reconstruction techniques are investigated. A new surface reconstruction technique and several interpolation schemes are introduced for processing the volume data. A new hierarchical scheme for extracting three-dimensional surfaces from volume data is presented. The hierarchical scheme is used to visualize different levels of surface detail allowing a user to explore different features of the surface at different scales. Estimated surface curvature is used as a smoothness condition, and the distance measurement between different levels of surfaces constructed is used as a stopping criterion. The volume pyramid used by the hierarchical scheme was built and tested by two different data structures: an octree and wavelet transforms. The hierarchical method using three-dimensional wavelet transforms is also useful in multiresolution surface analysis. An adaptive hierarchical method using an octree is implemented to increase the accuracy of the surface by adaptively subdividing regions of high curvature using an appropriate interpolation scheme without substantially increasing the number of polygons.
16300996
Research on Optimization Algorithm for Attribute Reduction of Decision System
Attribute reduction is one of the central issue in the theoretical research of rough set, aiming at the NP-hard problem of acquiring minimal reduction and all reduction, an optimization algorithm is proposed to construct reduction tree based on discernibility matrix for acquiring attribute reduction. The discernibility set is acquired by improving discernibility matrix first, then the core and reduction candidate information are obtained, finally the minimal reduction and all reduction are sought fast and effectively by considering attribute frequency as heuristic information, and time cost of the algorithm is analyzed. The time complexity of the algorithm is lower than other presented algorithms.
2407307
Dynamictrust: the trust development in peer-to-peer environments
In peer-to-peer (P2P) environments, trust is a very important issue when transactions/interactions occur between peers. In general, the trust evaluation on transactions/interactions relies on the recommendations from other peers, which may be inaccurate. This paper presents Dynamictrust, a P2P trust evaluation system. It is based on our peer trust evaluation model, which measures the credibility of peers' recommendations, and thus filters noise in responses and obtains more accurate and objective trust values
495169
EachWiki: Suggest to Be an Easy-To-Edit Wiki Interface for Everyone
In this paper, we present EachWiki, an extension of Semantic Media Wiki characterized by an intelligent suggestion mechanism. It aims to facilitate the wiki authoring by recommending the following elements: links, categories, and properties. We exploit the semantics of Wikipedia data and leverage the collective wisdom of web users to provide high quality annotation suggestions. The proposed mechanism not only improves the usability of Semantic MediaWiki but also speeds up its converging use of terminology. The suggestions are applied to relieve the burden of wiki authoring and attract more inexperienced contributors, thus making Semantic MediaWiki even better Semantic Web proto types and data source.