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佳木斯造纸厂从芬兰奥斯龙公司引进了一套新型、高效、低碱流失的压力过滤、洗涤苛化系统。本文就如何延长该系统主体元件──滤套的使用寿命这一技术问题,进行系统的阐述。 相似文献
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主要介绍了自动化部近几年来在科技创新和管理方面的工作经验,如围绕莱钢生产建设全力推进技术创新;以“数字莱钢”建设为目标,加快推进莱钢信息化建设,所有这些都为莱钢提供了强有力的自动化信息化技术支撑。 相似文献
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Intensity modulated radiation therapy (IMRT) is one of the most effective modalities for modern cancer treatment. The key to successful IMRT treatment hinges on the delivery of a two-dimensional discrete radiation intensity matrix using a device called a multileaf collimator (MLC). Mathematically, the delivery of an intensity matrix using an MLC can be viewed as the problem of representing a non-negative integral matrix (i.e., the intensity matrix) by a linear combination of certain special non-negative integral matrices called segments, where each such segment corresponds to one of the allowed states of the MLC. The problem of representing the intensity matrix with the minimum number of segments is known to be NP-complete. In this paper, we present two approximation algorithms for this matrix representation problem. To the best of our knowledge, these are the first algorithms to achieve non-trivial performance guarantees for multi-row intensity matrices. 相似文献
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Luan Yu Shi Yuhang Wu Wanyin Liu Zhiyao Chang Hai Cheng Jun 《Knowledge and Information Systems》2021,63(10):2791-2814
Knowledge and Information Systems - In the past decade, human activity recognition (HAR) has grown in popularity due to its applications in security and entertainment. As recent years have... 相似文献
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Large-scale data-intensive cloud computing with the MapReduce framework is becoming pervasive for the core business of many
academic, government, and industrial organizations. Hadoop, a state-of-the-art open source project, is by far the most successful
realization of MapReduce framework. While MapReduce is easy- to-use, efficient and reliable for data-intensive computations,
the excessive configuration parameters in Hadoop impose unexpected challenges on running various workloads with a Hadoop cluster
effectively. Consequently, developers who have less experience with the Hadoop configuration system may devote a significant
effort to write an application with poor performance, either because they have no idea how these configurations would influence
the performance, or because they are not even aware that these configurations exist. There is a pressing need for comprehensive
analysis and performance modeling to ease MapReduce application development and guide performance optimization under different
Hadoop configurations. In this paper, we propose a statistical analysis approach to identify the relationships among workload
characteristics, Hadoop configurations and workload performance. We apply principal component analysis and cluster analysis
to 45 different metrics, which derive relationships between workload characteristics and corresponding performance under different
Hadoop configurations. Regression models are also constructed that attempt to predict the performance of various workloads
under different Hadoop configurations. Several non-intuitive relationships between workload characteristics and performance
are revealed through our analysis and the experimental results demonstrate that our regression models accurately predict the
performance of MapReduce workloads under different Hadoop configurations. 相似文献