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Ever-increasing big data forces enterprises to migrate data to cloud storage systems. Data retrieval time from the cloud will directly affect the overall application performance. Meanwhile, sensitive data stored on cloud necessitates a robust security arrangement against cyberattacks. Therefore, it is imperative that both data retrieval time and data security should be taken into account simultaneously...
In sodium aluminate solution evaporation process for alumina production, the measurement data are not accurate and contain outliers, which makes it difficult to identify the dynamic and the steady-state of the process. Therefore, an adaptive polynomial sliding filter multivariate steady-state detection method based on outliers identification is presented in this paper. Firstly, based on the analysis...
Recently, technologies on reducing energy consumption of data centers have drawn considerable attentions. One constructive way is to improve energy efficiency of servers. Aiming at this goal, we propose a new energy-aware optimization model based on the combination of data placement and task scheduling in this paper. The main contributions are: (1)The impact of servers' performance on energy consumption...
This paper describe a feasible scheme of local visual navigation, local visual navigation application scenarios often some with complex background, target species more real scenario that the obstacle avoidance is particularly important. In particular the visual navigation target segmentation in the background and the foreground objects more complex scenarios important for predicting pre-step. This...
In this work, the problem of multichannel cross-spectrum density (MCSD) estimation is studied. Based on a multichannel data model, the classic periodogram based MCSD estimator and the minimum variance (MV) based MCSD estimator are tested for cross-spectrum density estimation. Our major contribution in this work is a canonical correlation analysis (CCA) based MCSD estimator, relying on the inherent...
As listed firms' financial distress is not always occasional, it is necessary to consider dynamic change of the firms' financial condition when the firms' financial distress is pre-warned. In this paper, a longitudinal data envelopment analysis is employed to consider dynamically the listed firms' financial condition, and every listed firm in various periods is viewed as various decision making unit...
In this paper, an electricity consumption prediction model is proposed and built up by the following steps: 1) characterize historical data via fuzzy clustering method; 2) reduce the characterized data based on rough set; 3) extract the correlation between the attribute equivalence and the predicted variable; 4) set up electricity consumption prediction model finally.
This work studies the performance of a data-driven reduced rank scheme for rapid timing acquisition in multiple access communications. Our results show that when only a limited amount of preamble bits are available, instead of the true second-order statistics (SOS), the reduced rank scheme provides reliable timing information. Exploiting the structure of the multiple access interference, the data...
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