A New Method of Information Decision-making Based on D-S Evidence Theory

D-S evidence theory is a method broadly applied in fusion for decision-making. However, this theory has some shortcomings in the formula of evidence combination with the exception that evidence of fully conflict can not be combined, then the probability validity is difficult to determine and sometimes the composed evidence is different from people's subjective judgments or some other issues. These confine the application of evidence to some extent. Some of them have the dubious credibility which affects the fusion result when Multi evidence are combined together. In order to expand the application of the formula of this theory and enhance the reliability of the fusion results, a new combination formula is introduced in this paper, which is also compared with other formulas in other literatures and finally the improved reliability of this combination formula is verified. At last, through data-mining of the decision-making information on a number of isolated points, a new method using combined evidence to make decisions is described. It's proven from the experimental results that the new combination method not only works well and effectively in the evidence of a high level of conflict but also is applicable to fusion for decision-making

In-Plane Deformation Mechanics for Highly Stretchable Electronics

Scissoring in thick bars suppresses buckling behavior in serpentine traces that have thicknesses greater than their widths, as detailed in a systematic set of analytical and experimental studies. Scissoring in thick copper traces enables elastic stretchability as large as approximate to 350%, corresponding to a sixfold improvement over previously reported values for thin geometries (approximate to 60%).</p

Dry deposition of polycyclic aromatic hydrocarbons and its influence on surface soil contamination in Tianjin, China

ISCLT3 dispersion model was applied to calculate the flux of dry deposition of polycyclic aromatic hydrocarbons (PAHs) in Tianjin, China based on a high resolution emission inventory. Field observations of dry deposition at 22 sampling sites were used for model validation. The mean deposition flux densities (and standard deviation) of 15 PAHs were 4.62 +/- 2.99 mu g m(-2) d(-1) and 2.75 +/- 1.78 mg m(-2) d(-1) in the heating and the non-heating seasons, respectively, with a time-weighted annual mean of 3.37 +/- 1.81 mu g m(-2) d(-1) (based on the durations of the heating and non-heating seasons). High fluxes occurred in the urbanized areas as well as near two coke and gasification facilities. It was revealed that PAH concentrations in surface soil were correlated significantly with both dry deposition and soil organic matter content. Accordingly, a linear regression model was developed for predicting surface soil PAH concentration based on deposition flux density and soil organic matter content.National Basic Research Program [2007CB407303]; National Science Foundation of China [40730737, 140710019001

NC unit trapped by fullerenes: a density functional theory study on Sc3NC@C-2n (2n=68, 78 and 80)

Endohedral metallofullerenes (EMFs) with a trapped cluster size larger than four are rather scarce. Inspired by a recent experimental observation, we explored the possibility of encapsulating an unusual Sc3NC unit in three representative fullerene cages, namely, C-68, C-78 and C-80, by means of density functional computations. The geometries, electronic and electrochemical redox properties of the corresponding EMFs, Sc3NC@C-2n (2n = 68, 78 and 80), were investigated. These novel EMFs all have very favorable binding energies, implying a considerable possibility for experimental realization. The recently observed m/z = 1121 peak in the mass spectroscopy was characterized as Sc3NC@C-80. Notably the lowest-energy isomer of Sc3NC@C-78 has a non-IPR C-78 outer cage, the possibility to accommodate five atoms inside a fullerene as small as C-68 is also intriguing. Moreover, the intracluster and metal-cage covalent interactions were revealed by a quantum theory of atoms in molecules study. Infrared absorption spectra and C-13 nuclear magnetic resonance spectra were also computed to assist future experimental characterization.NSFC [20773018, 20873067, 20673088, 20425312, 20721001, 20423002]; 973 Program [2007CB815307]; NSF, USA [CHE-0716718]; Institute for Functional Nanomaterials (NSF) [0701525]; US Environmental Protection Agency (EPA) [RD-83385601

GiveALink: Mining a Semantic Network of Bookmarks for Web Search and Recommendation

GiveALink is a public site where users donate their bookmarks to the Web community. Bookmarks are analyzed to build a new generation of Web mining techniques and new ways to search, recommend, surf, personalize and visualize the Web. We present a semantic similarity measure for URLs that takes advantage both of the hierarchical structure of the bookmark files of individual users, and of collaborative filtering across users. We analyze the social bookmark network induced by the similarity measure. A search and recommendation system is built from a number of ranking algorithms based on prestige, generality, and novelty measures extracted from the similarity data

Method for improving classification performance of neural network based on fuzzy input and network inversion

In order to effectively improve the classification performance of neural network, first architecture of fuzzy neural network with fuzzy input was proposed. Next a cost function of fuzzy outputs and non-fuzzy targets was defined. Then a learning algorithm from the cost function for adjusting weights was derived. And then the fuzzy neural network was inversed and fuzzified inversion algorithm was proposed. Finally, computer simulations on real-world pattern classification problems examine the effectives of the proposed approach. The experiment results show that the proposed approach has the merits of high learning efficiency, high classification accuracy and high generalization capability

Keyword spotting system based on biomimetic pattern recognition

The mandarin keyword spotting system was investigated, and a new approach was proposed based on the principle of homology continuity and point location analysis in high-dimensional space geometry theory which are both parts of biomimetic pattern recognition theory. This approach constructed a hyper-polyhedron with sample points in the training set and calculated the distance between each test point and the hyper-polyhedron. The classification resulted from the value of those distances. The approach was tested by a speech database which was created by ourselves. The performance was compared with the classic HMM approach and the results show that the new approach is much better than HMM approach when the training data is not sufficient