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Wang J.,Capital Normal University | Zeng Y.,Beijing Computing Center
Proceedings of the 2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2012 | Year: 2012

Large size cluster management is a complex and difficult task. In this paper, we firstly discuss distributed hierarchical autonomic management mechanisms including the framework of distributed hierarchical autonomic management system and functions of each its component. And then we design and realize a high-performance cluster management system DHAView. It has autonomic management features such as global information integration, global unified monitoring and management, alarm correlation inference base on autonomic element and local event association analysis. Now this DHAView system is successfully used to manage a real large size high performance cluster. © 2012 IEEE. Source

Wang J.,Capital Normal University | Zeng Y.,Beijing Computing Center
ICSESS 2012 - Proceedings of 2012 IEEE 3rd International Conference on Software Engineering and Service Science | Year: 2012

Weighted frequent pattern mining is suggested to discover more important frequent pattern by considering different weights of each item, and closed frequent pattern mining can reduces the number of frequent patterns and keep sufficient result information. In this paper, we propose an efficient algorithm DS-CWFP to mine closed weighted frequent pattern mining over data streams. We present an efficient algorithm based on sliding window and can discover closed weighted frequent pattern from the recent data. A new efficient DS-CWFP data structure is used to dynamically maintain the information of transactions and also maintain the closed weighted frequent patterns has been found in the current sliding window. Three optimization strategies are present. The detail of the algorithm DS-CWFP is also discussed. Experimental studies are performed to evaluate the good effectiveness of DS-CWFP. © 2012 IEEE. Source

Wang J.,Capital Normal University | Zeng Y.,Beijing Computing Center
Proceedings - 2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011 | Year: 2011

By considering different weights of items, weighted frequent pattern (WFP) mining can find more important frequent patterns. However previous WFP algorithms are not suitable for continuous, unbounded and high-speed data streams mining for they need multiple database scans. In this paper, we present an efficient algorithm DSWFP, which is based on sliding window and can discover important frequent pattern from the recent data. DSWFP has three new characters, including a new refined weight definition, a new proposed data structure and two pruning strategies. Experimental studies are performed to evaluate the good effectiveness of DSWFP. © 2011 IEEE. Source

Zhao L.,Beijing Computing Center | Ren Y.,Beijing Institute of Technology | Yan B.,Beijing Institute of Technology
Proceedings - 2015 8th International Congress on Image and Signal Processing, CISP 2015 | Year: 2015

Nature language processing is an important part in data mining, which counts a lot in the internet age. Feature extraction effects the accuracy of text classification. This paper proposes a method of iterative feature space evolution to optimize the result. Adjusting the extended dictionary and the stop word list, we optimize the feature space time and again to get a better classifier model. The final result has a higher classification accuracy than the original experiment. © 2015 IEEE. Source

Liu G.-T.,CAS Institute of Botany | Liu G.-T.,University of China Academy of Science | Ma L.,CAS Institute of Botany | Ma L.,University of China Academy of Science | And 11 more authors.
BMC Plant Biology | Year: 2014

Background: High temperature is a major environmental factor limiting grape yield and affecting berry quality. Thermotolerance includes the direct response to heat stress and the ability to recover from heat stress. To better understand the mechanism of the thermotolerance of Vitis, we combined a physiological analysis with iTRAQ-based proteomics of Vitis vinifera cv Cabernet Sauvignon, subjected to 43°C for 6 h, and then followed by recovery at 25/18°C.Results: High temperature increased the concentrations of TBARS and inhibited electronic transport in photosynthesis apparatus, indicating that grape leaves were damaged by heat stress. However, these physiological changes rapidly returned to control levels during the subsequent recovery phase from heat stress. One hundred and seventy-four proteins were differentially expressed under heat stress and/or during the recovery phase, in comparison to unstressed controls, respectively. Stress and recovery conditions shared 42 proteins, while 113 and 103 proteins were respectively identified under heat stress and recovery conditions alone. Based on MapMan ontology, functional categories for these dysregulated proteins included mainly photosynthesis (about 20%), proteins (13%), and stress (8%). The subcellular localization using TargetP showed most proteins were located in the chloroplasts (34%), secretory pathways (8%) and mitochondrion (3%).Conclusion: On the basis of these findings, we proposed that some proteins related to electron transport chain of photosynthesis, antioxidant enzymes, HSPs and other stress response proteins, and glycolysis may play key roles in enhancing grapevine adaptation to and recovery capacity from heat stress. These results provide a better understanding of the proteins involved in, and mechanisms of thermotolerance in grapevines. © 2014 Liu et al.; licensee BioMed Central Ltd. Source

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