Chitin-derived dual O-and N-doped carbon nanofibrous microspheres are reported to promote oxidative double carbonylation of alkanes with amines. Bulk chemicals such as alkanes and CO can be easily transformed to various valueadded alkyl a-ketoamides. Notably, the porous carbon nanofibrous microspheres with large surface area could supply potential adhesion sites for amines, which inhibited the oxidative decomposition of amines to promote this transformation.
Having a universal, fair, democratic and practical higher education system plays a particularly important role in the future development of the country. However, the higher education system in various countries is uneven. It is of great significance to establish a general evaluation system for the development of global education. In this paper, 23 indicators are preliminarily selected from the education data of Universitas 21 and Global Statistical Yearbook. After the gray correlation analysis, 12 indicators were selected. On the one hand, principal component analysis is used to reduce the dimension of these 12 indicators in 50 countries, and the first four principal components with cumulative contribution rate of 99% are finally selected as the input parameters of BP neural network. On the other hand, 12 indicators are divided into four aspects as the standard of scheme decision-making. Finally, a higher education quality evaluation and decision-making model based on BP neural network and analytic hierarchy process are established. Then eight countries are selected to use the model to evaluate their current higher education quality. Based on the input and evaluation results of the four aspects of higher education in various countries, the analytic hierarchy process is used to make program decision, and several improvement suggestions are put forward for the current education policies of various countries.
The present of smart mobile devices have provided unprecedented flexibility to humankind, with which people are able to access kinds of system resource through internet everywhere, including confidential data, nevertheless. While the traditional computing environment is always considered to be static and security-guarded, the context of mobile computing is much more variable, complex, and risk-hidden. To provide appropriate protection on mobile devices, we proposed a context-aware model combined with crowd-sensing paradigm to achieve fine-grained measurement of user's current context. Corresponding to the context-aware model, we categorize the context by kinds of attributes and proposed Attributetree based Context-Aware Access Control model to protect user's privacy and confidential information. The experimental result indicates that our proposed model is fine-grained, efficient and flexible to apply to different mobile platforms.
This article proposes a semantic grid mapping method for domestic robot navigation. Occupancy grid maps are sufficient for mobile robots to complete point-to-point navigation tasks in 2-D small-scale environments. However, when used in the real domestic scene, grid maps are lack of semantic information for end users to specify navigation tasks conveniently. Semantic grid maps, enhancing the occupancy grid map with the semantics of objects and rooms, endowing the robots with the capacity of robust navigation skills and human-friendly operation modes, are thus proposed to overcome this limitation. In our method, an object semantic grid map is built with low-cost sonar and binocular stereovision sensors by correctly fusing the occupancy grid map and object point clouds. Topological spaces of each object are defined to make robots autonomously select navigation destinations. Based on the domestic common sense of the relationship between rooms and objects, topological segmentation is used to get room semantics. Our method is evaluated in a real homelike environment, and the results show that the generated map is at a satisfactory precision and feasible for a domestic mobile robot to complete navigation tasks commanded in natural language with a high success rate.
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