Invariant Einstein metrics on three-locally-symmetric spaces

In this paper, we classify three-locally-symmetric spaces for a connected, compact and simple Lie group. Furthermore, we give the classification of invariant Einstein metrics on these spaces

JiTS: Just-in-Time Scheduling for Real-Time Sensor Data Dissemination

We consider the problem of real-time data dissemination in wireless sensor networks, in which data are associated with deadlines and it is desired for data to reach the sink(s) by their deadlines. To this end, existing real-time data dissemination work have developed packet scheduling schemes that prioritize packets according to their deadlines. In this paper, we first demonstrate that not only the scheduling discipline but also the routing protocol has a significant impact on the success of real-time sensor data dissemination. We show that the shortest path routing using the minimum number of hops leads to considerably better performance than Geographical Forwarding, which has often been used in existing real-time data dissemination work. We also observe that packet prioritization by itself is not enough for real-time data dissemination, since many high priority packets may simultaneously contend for network resources, deteriorating the network performance. Instead, real-time packets could be judiciously delayed to avoid severe contention as long as their deadlines can be met. Based on this observation, we propose a Just-in-Time Scheduling (JiTS) algorithm for scheduling data transmissions to alleviate the shortcomings of the existing solutions. We explore several policies for non-uniformly delaying data at different intermediate nodes to account for the higher expected contention as the packet gets closer to the sink(s). By an extensive simulation study, we demonstrate that JiTS can significantly improve the deadline miss ratio and packet drop ratio compared to existing approaches in various situations. Notably, JiTS improves the performance requiring neither lower layer support nor synchronization among the sensor nodes

SODIUM - RARE-GAS VAN DER WAALS MOLECULES

The intensity of the fluorescent radiation from the red wing of the Na D-lines perturbed by rare-gas atoms has been measured as a function of temperature and rare-gas density. These observations were then combined with a quasistatic analysis to determine the potential well depths and the emission peak wavelengths for {\rm Na(3P)He}\sb2, {\rm Na(3P)Ar}\sb2, {\rm Na(3P)Kr}\sb2, and {\rm Na(3P)Ar}\sb3 molecules. The following results were obtained: for {\rm Na\sp\* He}\sb2, {\rm D = 820(110)\ cm}\sp{-1}, $\lambda = 8400$ A; for {\rm Na\sp\* Ar}\sb2, {\rm D = 1100(150)\ cm}\sp{-1}, $\lambda = 7200$ A; for {\rm Na\sp\* Kr}\sb2, {\rm D = 1355(180)\ cm}\sp{-1}, $\lambda = 7400$ A; and for {\rm Na\sp\* Ar}\sb3, {\rm D = 1595(300)\ cm}\sp{-1}, $\lambda = 8600$ A. These results are consistent with a simple model of the alkali-rare-gas molecules in which the depth of the potential energy well of a given molecule can be accurately represented as the sum of well depths of the individual alkali-rare-gas pairs

A Digital Watermarking Approach Based on DCT Domain Combining QR Code and Chaotic Theory

This paper proposes a robust watermarking approach based on Discrete Cosine Transform domain that combines Quick Response Code and chaotic system.Comment: 7 pages, 6 figure

A Method of Protein Model Classification and Retrieval Using Bag-of-Visual-Features

In this paper we propose a novel visual method for protein model classification and retrieval. Different from the conventional methods, the key idea of the proposed method is to extract image features of proteins and measure the visual similarity between proteins. Firstly, the multiview images are captured by vertices and planes of a given octahedron surrounding the protein. Secondly, the local features are extracted from each image of the different views by the SURF algorithm and are vector quantized into visual words using a visual codebook. Finally, KLD is employed to calculate the similarity distance between two feature vectors. Experimental results show that the proposed method has encouraging performances for protein retrieval and categorization as shown in the comparison with other methods