This paper presents a method of medicine composition concentration analysis based on least square support vector machines (LS-SVMs) and examines the importance of the hyperparameter choice in improvement of algorithm ...
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It obviously gets limited advantage in massive storage system that all the management works are done by the servers, such as file server and metadata server of traditional storage area network (SAN). Moreover, storage...
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It obviously gets limited advantage in massive storage system that all the management works are done by the servers, such as file server and metadata server of traditional storage area network (SAN). Moreover, storage device with deficient intelligence leads to lack of supporting local policy and does not scale well in performance and functionality when the number of storage device is added. At the same time, servers, e.g. metadata servers, are easy turned into bottlenecks when load balancing policies only depend on servers to scheme. This paper studied object storage system (OSS) which is a novel solution for massive storage. And the whole object storage system is divided into some domains. Each domain has its own metadata server, object storage controllers and clients (or application servers). Load balancing policies, involved three facets: metadata server (based on globe), object storage controller (based on local) and object, are presented.
Spatial data mining is the process of discovering interesting and previously unknown, but potentially useful patterns from large spatial databases. Extracting interesting and useful patterns from spatial datasets is m...
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Spatial data mining is the process of discovering interesting and previously unknown, but potentially useful patterns from large spatial databases. Extracting interesting and useful patterns from spatial datasets is more difficult than extracting patterns from traditional numeric and categorical data due to the complexity of spatial data types, spatial relationships, and spatial autocorrelation. In this paper, we provide a new visual hierarchical clustering based on graph-partitioning algorithm called VSG-CLUST, which groups and visualizes cluster hierarchies consisting of both non-spatial and spatial attributes. Our method is fundamentally different from conventional clustering algorithms, that usually do not take into account the spatial structure, which refers to the distance between patterns, topology, density, and other spatial distribution characteristics, and lack efficient level-of-detail strategy for visualization. In contrast, VSG-CLUST is able to recognize spatial patterns that involve neighbors. With the help of tree graph our method converts a multidimensional spatial clustering problem to a graph partitioning (tree partitioning) problem. We provide a theoretical basis for the approach and demonstrate the capability of the graph for maintaining the spatial structure. VSG-CLUST is implemented in a fully open and interactive manner, and it supports various visualization techniques including data mining algorithm visualization. A Web-based working demo with Fujian province environmental monitoring data is presented to illustrate the usability and effectiveness of VSG-CLUST and the proposed scheme.
Most of traditional load balancing strategies are based on servers or applications architecture. Storage subsystem, as the back tier, provides file or block interface to server or application tier, is often ignored wh...
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ISBN:
(纸本)076952432X
Most of traditional load balancing strategies are based on servers or applications architecture. Storage subsystem, as the back tier, provides file or block interface to server or application tier, is often ignored when the bottleneck of service is studied. Our load balancing strategy is based on storage object, which provides object interface for the up tier. We concentrate on storage objects with massive dynamic processing. The characteristics of storage object in object storage system (OSS) enable us to apply our load balancing strategy at the back end of servers or applications in order to deal with bottlenecks at the storage tier in data-intensive applications
An amount of data-intensive applications pay more attention to the performance of storage system. Prefetching is an efficient approach to improve the I/O performance. The present algorithms of prefetching have some li...
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An amount of data-intensive applications pay more attention to the performance of storage system. Prefetching is an efficient approach to improve the I/O performance. The present algorithms of prefetching have some limitations and cannot suit for some kinds of access patterns. Intelligent prefetching strategy can recognize the current access pattern by analyzing the access trace independently. Prefetching based on the pattern recognized is more effective than blindly prefetching. Using this algorithm in a VI-based data grid prototype system (VI-DGPS), the storage nodes is divided into groups by the relation of the data, only one node judges the pattern and all other nodes just receive the pattern info in a group. All nodes in a group prefetch synchronously based on the access pattern to reduce the request response time. Test result shows that the strategy has a good performance in our system.
In UML, a modeling language popularly used to describe models at different abstraction levels, sequence diagram and statechart are both used to represent systems' behavior models. A consistency problem may arise d...
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In UML, a modeling language popularly used to describe models at different abstraction levels, sequence diagram and statechart are both used to represent systems' behavior models. A consistency problem may arise due to the fact that sequence diagram represent interactive behavior of all objects, whereas statechart represent the complete behavior of one specific object. This paper proposes an approach checking the consistency between sequence diagrams and state diagrams. In our approach, statechart is formalized using finite state processes and sequence diagram is represented using messages trace. An existing tool LTSA is used to support our method.
In this article, we investigate the problem of preparing qualitative spatial relations before implementing spatial data mining by checking consistency in a constraint network, which includes topological and cardinal d...
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In this article, we investigate the problem of preparing qualitative spatial relations before implementing spatial data mining by checking consistency in a constraint network, which includes topological and cardinal directional relations between pairs of spatial objects. We aim to explore potential spatial relations and possible inconsistency among the data of relationships for enforcing the correctness of spatial data mining. This task is carried out through qualitative spatial reasoning method, specifically consistency checking. We try to lay the theoretical foundation for this kind of problem. Instead of using conventional composition tables, we investigate the interactions between topological and cardinal directional relations with the aid of rules. These rules are shown to be sound, i.e. the deductions are logically correct. Based on these rules, an improved constraint propagation algorithm is introduced to enforce the path consistency. An example is presented to show the utility of these rules.
In this paper, a relatively flexible filter called extended bilateral filter is proposed, by which some particular filters can be designed via selecting an appropriate pixel of interest (POI) and defining a kernel for...
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In this paper, a relatively flexible filter called extended bilateral filter is proposed, by which some particular filters can be designed via selecting an appropriate pixel of interest (POI) and defining a kernel for the filter according to some specified requirements. Based on the filter, a fluorescein-angiogram-oriented filter, high-intensity preserving (HIP) filter is introduced to solve the problems of high-intensity preservation when denoising. The results of the experiments show that the HIP filter has the ability of noise suppression, and the ability of high-intensity preservation, which can keep the intensities of bright pixels from degrading via distributing the weights adaptively according to the location and the intensity of each pixel.
In workflow systems or other applications, users need more semantic information. Ontologies and semantic Web are important technologies for managing semantic information. Our work is focused on semantic spatial inform...
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In workflow systems or other applications, users need more semantic information. Ontologies and semantic Web are important technologies for managing semantic information. Our work is focused on semantic spatial information in distributed workflow. The spatial relations was described by Description Logic, the ontologies was then constructed using the RDF Schemas and OWL Capabilities. These theories and methods are enclosed in a middleware, and the middleware was embedded in workflow system of the government in Jilin Province.
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