Adaptive pixel-block based background subtraction using low-rank and block-sparse matrix decomposition

Multimedia Tools and Applications - We present three stages of a novel backgrounds subtraction method in this paper: a new pixel-block based randomized arrangement is utilized to preprocess all the...     

Comprehensiveness and uniqueness of commercial databases and open access systems

Scientometrics - In this study, scholarly communication systems provided by commercial services and open access systems are examined on the basis of the comprehensiveness and uniqueness of their...     

Finding high-impact interdisciplinary users based on friend discipline distribution in academic social networking sites

Scientometrics - Specialized academic social networking sites are gaining popularity in scientific communication. A huge volume of interdisciplinary information is generated when researchers from...     

Ni-Foam Structured Ni-Phyllosilicate Ensemble as an Efficient Monolithic Catalyst for CO2 Methanation

This work proposed a new path to synthesize Ni-phyllosilicate through the reaction of nickel hydroxide and silica sol on the surface of Ni-foam to form the monolithic Ni-phyllosilicate/Ni-foam catalyst. Ni-phyllosilicate could reprint the morphology of nickel hydroxid and firmly anchor on the framework of Ni-foam, which obtained fine Ni particles of 2.8 nm after reduction in H₂ at 650 °C, resulting in high catalytic activity for CO₂ methanation. In addition, the Ni-phyllosilicate/Ni-foam catalyst showed high long-term stability in a 100 h-lifetime test owing to the combined effects of surface confinement of Ni-phyllosilicate, firm anchoring between Ni-phyllosilicate and Ni-foam, as well as the high heat transfer property of Ni-foam.

Graphical Abstract

     

Revisiting the Parallel Strategy for DOACROSS Loops

Journal of Computer Science and Technology - DOACROSS loops are significant parts in many important scientific and engineering applications, which are generally exploited pipeline/wave-front...     

Specific emitter identification for satellite communication using probabilistic neural networks

Electromagnetic signal emitted by satellite communication (satcom) transmitters are used to identify specific individual uplink satcom terminals sharing the common transponder in real environment, which is known as specific emitter identification (SEI) that allows for early indications and warning (I&W) of the targets carrying satcom furnishment and furthermore the real time electromagnetic situation awareness in military operations. In this paper, the authors are the first to propose the identification of specific transmitters of satcom by using probabilistic neural networks (PNN) to reach the goal of target recognition. We have been devoted to the examination by exploring the feasibility of utilizing the Hilbert transform to signal preprocessing, applying the discrete wavelet transform to feature extraction, and employing the PNN to perform the classification of stationary signals. There are a total of 1000 sampling time series with binary phase shift keying (BPSK) modulation originated by five types of satcom transmitters in the test. The established PNNs classifier implements the data testing and finally yields satisfactory accuracy at 8 dB(±1 dB) carrier to noise ratio, which indicates the feasibility of our method, and even the keen insight of its application in military.     

Hierarchical Attention for Part-Aware Face Detection

International Journal of Computer Vision - Expressive representations for characterizing face appearances are essential for accurate face detection. Due to different poses, scales, illumination,...     

Spreading and Curing Behaviors of a Thermosetting Droplet-Silicone on a Heated Surface

Thermosetting materials are widely used as encapsulation in the electrical packaging to protect the core electronic components from external force, moisture, dust, and other factors. However, the spreading and curing behaviors of such kind of fluid on a heated surface have been rarely explored. In this study, we experimentally and numerically investigated the spreading and curing behaviors of the silicone(OE6550 A/B, which is widely used in the light-emitting diode packaging) droplet with diameter of ～2.2 mm on a heated surface with temperature ranging from 25 ℃ to 250 ℃. For the experiments, we established a setup with high-speed camera and heating unit to capture the fast spreading process of the silicone droplet on the heated surface. For the numerical simulation, we built a viscosity model of the silicone by using the Kiuna's model and combined the viscosity model with the Volume of Fluid(VOF) model by the User Defined Function(UDF) method. The results show that the surface temperature significantly affected the spreading behaviors of the silicone droplet since it determines the temperature and viscosity distribution inside the droplet. For surface temperature varied from 25 ℃ to 250 ℃, the final contact radius changed from ～2.95 mm to ～1.78 mm and the total spreading time changed from ～511 s to ～0.15 s. By further analyzing the viscosity evolution of the droplet, we found that the decreasing of the total spreading time was caused by the decrease of the viscosity under high surface temperature at initial spreading stage, while the reduction of the final contact radius was caused by the curing of the precursor film. This study supplies a strategy to tuning the spreading and curing behavior of silicone by imposing high surface temperature, which is of great importance to the electronic packaging.     

Threshold privacy-preserving cloud auditing with multiple uploaders

International Journal of Information Security - Data integrity is a critical security issue in cloud storage. The data integrity checking schemes by a third-party auditor (TPA) have attracted a lot...