Convolutional neural networks for time series classification

Time series classification is an important task in time series data mining, and has attracted great interests and tremendous efforts during last decades. However, it remains a challenging problem due to the nature of time series data: high dimensionality, large in data size and updating continuously. The deep learning techniques are explored to improve the performance of traditional feature-based approaches. Specifically, a novel convolutional neural network (CNN) framework is proposed for time series classification. Different from other feature-based classification approaches, CNN can discover and extract the suitable internal structure to generate deep features of the input time series automatically by using convolution and pooling operations. Two groups of experiments are conducted on simulated data sets and eight groups of experiments are conducted on real-world data sets from different application domains. The final experimental results show that the proposed method outperforms state-of-the-art methods for time series classification in terms of the classification accuracy and noise tolerance. © 1990-2011 Beijing Institute of Aerospace Information.

象牙海岸Issia地区铌钽砂矿的研究(英文)

在西非的象牙海岸Issia地区分布着许多铌钽矿床,包括原生矿和砂矿。原生矿产在分带很好的伟晶岩中。这个地区发育着许多花岗岩和花岗伟晶岩。伟晶岩可分为:(1)分异不好的伟晶岩,无矿化;(2)含Be伟晶岩,分带较好,见绿柱石;(3)含Be-Nb-Ta的伟晶岩,分带很好,是矿体;(4)Be-Nb-Ta-Li伟晶岩,分带很好,是矿体。除了10多个原生矿外,还有许多砂矿。砂矿有两种类型:一种近原生矿的坡积砂矿,另一种是经河流冲刷搬运后的冲积砂矿。我们选择了Etienne-Meguhe砂矿作为近原生矿的坡积砂矿的代表,Bemadi矿作为河流冲积型的砂矿的代表,对这两种类型的砂矿的风化、搬运、沉积机理进行了比较研究。研究发现不同的搬运距离和搬运模式对铌钽砂矿的主要矿物——铌钽铁矿的化学性质没有什么影响,而其物理形态则发生了变化。坡积型砂矿的铌钽铁矿常与石英、长石等矿物连生,其颗粒大小与原生的Nb-Ta伟晶岩中的铌钽铁矿一致;经河流冲积而形成的砂矿中,铌钽铁矿颗粒变小、轮廓变得圆滑,几乎无连生矿物,但矿体集中,常在河流的冲积扇中分布,易开采。

Infrared modeling and imaging simulation of midcourse ballistic targets based on strap-down platform

An infrared （IR） imaging simulation framework based on the strap-down platform is proposed for midcourse ballistic targets. It overcomes the shortcoming of the existing algorithms, which cannot simulate IR imaging from the entire midcourse process. The proposed framework includes three steps, target characteristic modeling, motion modeling, and imaging modeling. In imaging modeling, the staring focal plane is taken into account due to its wide employment. In order to obtain IR images of high fidelity, especially that the fluctuation of the target signal-to-noise ratio （SNR） is reasonably similar to the actual one, this paper proposes an improved IR imaging simulation method. The proposed method considers two critical factors of the pixel plane, occupy-empty ratio and defect elements, which affect the imaging of targets markedly but are neglected in previous work. Finally, the IR image sequence of high fidelity is obtained. And the correlative parameters of simulation can be set according to the given scene. Thus the generated images can satisfy the needs of algorithms validation for tracking and recognition.

Micro-motion dynamics analysis of ballistic targets based on infrared detection

The dynamic characteristics related to micro-motions, such as mechanical vibration or rotation, play an essential role in classifying and recognizing ballistic targets in the midcourse, and recent researches explore ways of extracting the micro-motion features from radar signals of ballistic targets. In this paper, we focus on how to investigate the micro-motion dynamic characteristics of the ballistic targets from the signals based on infrared (IR) detection, which is mainly achieved by analyzing the periodic fluctuation characteristics of the target IR irradiance intensity signatures. Simulation experiments demonstrate that the periodic characteristics of IR signatures can be used to distinguish different micro motion types and estimate related parameters. Consequently, this is possible to determine the micro-motion dynamics of ballistic targets based on IR detection.

Reversal of CQ11, a chloroquine derivative, on multidrug resistance in doxorubicin-resistant breast cancer cell line MCF/DOX

Objective： To investigate the reversal effect of CQ11, a chloroquine derivative, on multidrug resistance （MDR） in doxorubicin （DOX）-resistant human breast carcinoma cell line MCF/DOX. Methods： Cells of a human breast cancer cell line, MCF, and its DOX-resistant variant, MCF/DOX, were cultivated with DOX and/or CQ11. The cytotoxicity of drugs in vitro was assayed by MTT method. The accumulation of DOX in these cells was detected by fluorescence spectrophotometer. Results： MCF/DOX cells were 119 times more resistant to DOX in comparison with M CF cells. After simultaneous treatment with CQ 11 at the concentrations of 1.0, 2.5 and 5.0 μmol/L, the IC50 of DOX for MCF/DOX cells decreased from 3.1 ±0.47 μmot/L to 0.58 ± 0.032, 0.19 ± 0.012 and 0.081 ± 0.015 μmol/L, respectively, thus, increasing the DOX sensitivity by 5.3-fold （P 〈 0.01）, 16- fold （P 〈 0.01） and 38-fold （P 〈 0.01）, respectively. In the accumulation assay of DOX, simultaneous incubation of MCF/DOX cells with CQ11 significantly increased the DOX accumulation in MCF/DOX cells. No such results were found in parental MCF cells. Conclusion： CQ11 had strong MDR reversal effect by enhancing intracellular DOX accumulation in MCF/DOX cells, indicating that CQ11 may be a promising MDR chemosensitivity.