FAW Group

About: FAW Group is a based out in . It is known for research contribution in the topics: Electric vehicle & Finite element method. The organization has 294 authors who have published 243 publications receiving 1496 citations. The organization is also known as: FAW.

Customizing RST for the Automatic Production of Technical Manuals

Abstract: Rhetorical Structure Theory (RST) has emerged as a promising candidate for text representation in NLG. We investigated the applicability of RST in the automatic production of multilingual technical manuals. Starting from a domain knowledge base, we construct an RST-tree for a particular manual section, which is then converted to a set of sentence plans. These plans serve as input to sentence generators that produce the final text. In this paper, we report first on a number of open questions regarding general aspects of RST. Arguing that the original set of RST relations is not specific enough for practical generation purposes, we suggest a number of new relations that we found useful in our domain. After briefly examining the stage of RST tree construction, we then outline a procedure for converting RST trees to a sequence of sentence plans.

Self-assembled large-area Co(OH)2 nanosheets/ionic liquid modified graphene heterostructures toward enhanced energy storage

Abstract: Large-area Co(OH)2 nanosheets have been successfully coated with ionic liquid modified graphenevia a general strategy. The advantageous combination of graphene and the 2D structure of the Co(OH)2 nanosheets endows the obtained heterostructures with a remarkable lithium-storage performance, including high reversible capacity and superior cyclic and rate performance.

Characteristics of cobalt-based alloy coating on tool steel prepared by powder feeding laser cladding

Abstract: Co-based alloy coating was deposited on tool steel by powder feeding laser cladding. Sections of such coatings were examined to reveal their microstructures and phases using scanning electron microscope (SEM) and X-ray diffractometer (XRD). The results showed that the prime phase ( γ -Co dendrite) and other phases, including Cr 23 C 6 , Co 7 W 6 , and CrNi existed in the coatings. Some different solidification morphologies, such as planar (at the interface), cellular and dendrite formed, varying from the interface to the surface. Fine microstructures of γ -Co dendrite and lamellar eutectic in dendritical regions strengthened the coatings. Besides, the effects of aged treatment on the microstructure and microhardness of the surface coating were studied. Aged treatment led to the precipitations of some carbide particles (Cr 7 C 3 and Co 3 C) and boride particles (Co 4 B) from the cladded coating, causing an increase in microhardness in the laser-cladded coating.

Deep Background Modeling Using Fully Convolutional Network

Abstract: Background modeling plays an important role for video surveillance, object tracking, and object counting. In this paper, we propose a novel deep background modeling approach utilizing fully convolutional network. In the network block constructing the deep background model, three atrous convolution branches with different dilate are used to extract spatial information from different neighborhoods of pixels, which breaks the limitation that extracting spatial information of the pixel from fixed pixel neighborhood. Furthermore, we sample multiple frames from original sequential images with increasing interval, in order to capture more temporal information and reduce the computation. Compared with classical background modeling approaches, our approach outperforms the state-of-art approaches both in indoor and outdoor scenes.

Research on Markov property analysis of driving cycles and its application

Abstract: The Markov property of driving cycles was discussed by making a thorough description of their essential characteristics. The Markov chain, a useful tool for designing and expressing driving cycles, has been increasingly used in the field of driving cycles in recent years. Although the Markov property of driving cycles left unproved, some researchers have taken it for granted that it is appropriate to design driving cycle with Markov chain. In our research, the vehicle dynamics model and the car-following model were used to establish the two-dimensional Markov state transition model. On the other hand, the driving data from the city of Changchun were collected to analyze how states (in Markov theory) correlation changes with the increase of time intervals. After the Markov property had been proven, the theory of ergodicity was applied to reveal the relationship between velocity-acceleration joint probability distribution (VA Probability) and state transition matrix. Finally, the application of Markov property was also discussed briefly. This research will lay a theoretical foundation for designing driving cycles and ECO driving (Economical and Ecological).