896 resultados para localizzazione, location-aware, posizionamento indoor


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Natl Chiao Tung Univ, Dept Comp Sci

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It is found that the nitro substituent of some aromatic bifunctional compounds shows unusual reactivity towards protonation. In the chemical ionization mass spectra of nitrobenzoic acids and their esters and amides, and of nitrophenols and their ethers, protonations on the carboxyl, ester, amide, hydroxyl or alkoxyl groups are highly suppressed by that on the nitro group. As a result, fragmentations based on protonation on these groups unexpectedly become negligible. Ortho effects were observed for all the ortho isomers where the initial protonation on the nitro group is followed by an intramolecular proton transfer reaction, which leads to the expected 'normal' fragmentations. Protonation on the nitro substituent is much more favourable in energy than on any of the other substituents. The interaction of the two substituents through the conjugating benzene ring is found to be responsible for this 'unfair' competitive protonation. The electron-attracting nitro group strongly destabilizes the MH+ ions formed through protonation on the other substituent; although the COR (R = OH, OMe, OEt, NH2) groups are also electron-withdrawing, their effects are weaker than that of NO2; thus protonation on the latter group produces more-stable MH+ ions. On the other hand, an electron-releasing group OR (R = H, Me, Et) stabilizes the nitro-protonated species; the stronger the electron-donating effect of this group the more stable the nitro-protonated ions.

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The goal of this work is to navigate through an office environmentsusing only visual information gathered from four cameras placed onboard a mobile robot. The method is insensitive to physical changes within the room it is inspecting, such as moving objects. Forward and rotational motion vision are used to find doors and rooms, and these can be used to build topological maps. The map is built without the use of odometry or trajectory integration. The long term goal of the project described here is for the robot to build simple maps of its environment and to localize itself within this framework.

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The purpose of this paper is to make an example which, first, illustrates Starret’s Spatial Imposibility Theorem, when agents have free mobility; and second, allowes us to get a competitive equilibrium with transportation when agents move only if there is a noticeable difference in utilities that justifies the change of location.

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We investigate adaptive buffer management techniques for approximate evaluation of sliding window joins over multiple data streams. In many applications, data stream processing systems have limited memory or have to deal with very high speed data streams. In both cases, computing the exact results of joins between these streams may not be feasible, mainly because the buffers used to compute the joins contain much smaller number of tuples than the tuples contained in the sliding windows. Therefore, a stream buffer management policy is needed in that case. We show that the buffer replacement policy is an important determinant of the quality of the produced results. To that end, we propose GreedyDual-Join (GDJ) an adaptive and locality-aware buffering technique for managing these buffers. GDJ exploits the temporal correlations (at both long and short time scales), which we found to be prevalent in many real data streams. We note that our algorithm is readily applicable to multiple data streams and multiple joins and requires almost no additional system resources. We report results of an experimental study using both synthetic and real-world data sets. Our results demonstrate the superiority and flexibility of our approach when contrasted to other recently proposed techniques.