Social Friend Recommendation Based on Multiple Network Correlation

© 2015 IEEE. Friend recommendation is an important recommender application in social media. Major social websites such as Twitter and Facebook are all capable of recommending friends to individuals. However, most of these websites use simple friend recommendation algorithms such as similarity, popularity, or 'friend's friends are friends,' which are intuitive but consider few of the characteristics of the social network. In this paper we investigate the structure of social networks and develop an algorithm for network correlation-based social friend recommendation (NC-based SFR). To accomplish this goal, we correlate different 'social role' networks, find their relationships and make friend recommendations. NC-based SFR is characterized by two key components: 1) related networks are aligned by selecting important features from each network, and 2) the network structure should be maximally preserved before and after network alignment. After important feature selection has been made, we recommend friends based on these features. We conduct experiments on the Flickr network, which contains more than ten thousand nodes and over 30 thousand tags covering half a million photos, to show that the proposed algorithm recommends friends more precisely than reference methods

Two-Stage Friend Recommendation Based on Network Alignment and Series Expansion of Probabilistic Topic Model

© 2017 IEEE. Precise friend recommendation is an important problem in social media. Although most social websites provide some kinds of auto friend searching functions, their accuracies are not satisfactory. In this paper, we propose a more precise auto friend recommendation method with two stages. In the first stage, by utilizing the information of the relationship between texts and users, as well as the friendship information between users, we align different social networks and choose some "possible friends." In the second stage, with the relationship between image features and users, we build a topic model to further refine the recommendation results. Because some traditional methods, such as variational inference and Gibbs sampling, have their limitations in dealing with our problem, we develop a novel method to find out the solution of the topic model based on series expansion. We conduct experiments on the Flickr dataset to show that the proposed algorithm recommends friends more precisely and faster than traditional methods

Determination of AGC capacity requirement and regulation strategies considering penalties of tie-line power flow deviations

2003-2004 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

In silico Assessment of Drug-like Properties of Alkaloids from Areca catechu L Nut

Purpose: To investigate in silico the drug-like properties of alkaloids (arecoline, arecaidine, guvacine, guvacoline, isoguvacine, arecolidine and homoarecoline) obtained from the fruits of Areca catechu L (areca nut).Methods: All chemical structures were re-drawn using Chemdraw Ultra 11.0. Furthermore, software including Bio-Loom for Windows - version 1.5, Molinspiration Property Calculator and ACD/I-LAB service were used to predict the drug-like properties of the alkaloids, including relative molecular mass (MW), partition coefficient log P (cLog P), number of hydrogen bond donors (HBD), number of hydrogen bond acceptors (HBA), topological polar surface area (TPSA), number of rotatable bonds (NROTB), pKa, and aqueous solubility at a given pH (LogS). In addition, Lipinski’s rule was used to evaluate druglike properties.Results: From our research, MWs of the seven compounds were all < 500. HBD and cLog P values of the seven compounds were all < 5, and HBA values were all < 10. In addition, TPSA value of each compound was < 60 Å2, and NROTB value was < 10. Besides, pKa values of the seven alkaloids were > 7.5; furthermore, they possess good solubility at pH 1.0, 5.0, and 7.0.Conclusion: All the seven alkaloids possess good drug-like properties, and demonstrated good oral absorption and bioavailability. The results also suggest that these compounds can be further developed into new oral drugs for treating certain diseases.Keywords: Areca catechu L, Areca nut, Drug-like properties, Alkaloids, Arecoline, Arecaidine, Guvacine, Guvacoline, Isoguvacine, Arecolidine, Homoarecoline, In silic

Studies on critical issues related to operating reserves in deregulated electricity market environment

2002-2003 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Malondialdehyde level and some enzymatic activities in subclinical mastitis milk

The purpose of this study was to evaluate the changes occurring in milk malondialdehyde (MDA) level and some enzymatic activities as a result of subclinical mastitis (SCM) in dairy cows. A total of 124 milk samples were collected from 124 lactating cows from the same herd in the period between the 2nd week after calving and the 10th week postpartum. They were classified by bacterial culture and the California mastitis test (CMT) as positive were deemed to have glands with SCM, and the periodic incidence rate of SCM was 26.6%. The most common bacterial isolates from SCM cases were Staphylococcus aureus (47%) and coagulase negative Staphylococci (CNS) (27%). The mean level of MDA and activities of lactate dehydrogenase (LDH) and alkaline phosphatase (ALP) were significantly higher in SCM milk than in normal milk, while the mean activity of glutathione peroxidase (GPx) was significantly lower in SCM milk than in normal milk. There were no differences in the activities of superoxide dismutase (SOD) and aspartate aminotransferase (AST) between normal milk and SCM milk. Therefore, the measurement of milk MDA level and GPx, LDH and ALP activities, appears to be a suitable diagnostic method for identifying SCM in dairy cows.Key words: Subclinical mastitis, mastitis diagnostic, etiology, malonaldehyde (MDA), enzym

Use of facile mechanochemical method to functionalize carbon nanofibers with nanostructured polyaniline and their electrochemical capacitance

A facile approach to functionalize carbon nanofibers [CNFs] with nanostructured polyaniline was developed via in situ mechanochemical polymerization of polyaniline in the presence of chemically treated CNFs. The nanostructured polyaniline grafting on the CNF was mainly in a form of branched nanofibers as well as rough nanolayers. The good dispersibility and processability of the hybrid nanocomposite could be attributed to its overall nanostructure which enhanced its accessibility to the electrolyte. The mechanochemical oxidation polymerization was believed to be related to the strong Lewis acid characteristic of FeCl3 and the Lewis base characteristic of aniline. The growth mechanism of the hierarchical structured nanofibers was also discussed. After functionalization with the nanostructured polyaniline, the hybrid polyaniline/CNF composite showed an enhanced specific capacitance, which might be related to its hierarchical nanostructure and the interaction between the aromatic polyaniline molecules and the CNFs

Control and Characterization of Individual Grains and Grain Boundaries in Graphene Grown by Chemical Vapor Deposition

The strong interest in graphene has motivated the scalable production of high quality graphene and graphene devices. Since large-scale graphene films synthesized to date are typically polycrystalline, it is important to characterize and control grain boundaries, generally believed to degrade graphene quality. Here we study single-crystal graphene grains synthesized by ambient CVD on polycrystalline Cu, and show how individual boundaries between coalescing grains affect graphene's electronic properties. The graphene grains show no definite epitaxial relationship with the Cu substrate, and can cross Cu grain boundaries. The edges of these grains are found to be predominantly parallel to zigzag directions. We show that grain boundaries give a significant Raman "D" peak, impede electrical transport, and induce prominent weak localization indicative of intervalley scattering in graphene. Finally, we demonstrate an approach using pre-patterned growth seeds to control graphene nucleation, opening a route towards scalable fabrication of single-crystal graphene devices without grain boundaries.Comment: New version with additional data. Accepted by Nature Material

Search for K_S K_L in psi'' decays

K_S K_L from psi'' decays is searched for using the psi'' data collected by BESII at BEPC, the upper limit of the branching fraction is determined to be B(psi''--> K_S K_L) < 2.1\times 10^{-4} at 90% C. L. The measurement is compared with the prediction of the S- and D-wave mixing model of the charmonia, based on the measurements of the branching fractions of J/psi-->K_S K_L and psi'-->K_S K_L.Comment: 5 pages, 1 figur

Survey on operating reserve procurement and pricing in deregulated electricity market environment

2003-2004 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe