6,799 research outputs found
Restaurant customers\u27 revisit intention and negative word-of-mouth behavior
The purpose of this study is threefold. First, this study intends to determine the factors which affect whether or not customers complain to management when they had problems at a casual table service restaurant. Second, this study seeks to determine the factors which affect the likelihood of returning to the restaurant for customers who complained to management about their problems. Third, this study examines the factors which affect the extent of negative word-of-mouth engaged by customers who complained to management; This study confirms the importance of complaint management in restaurant business. It further suggests how restaurant managers utilize their resources to resolve customers\u27 problems and thereby enhancing customer satisfaction. Thus, management may build a long-term relationship with customers and retain loyal customers
Macroscopic Quantum Tunneling Effect of Z2 Topological Order
In this paper, macroscopic quantum tunneling (MQT) effect of Z2 topological
order in the Wen-Plaquette model is studied. This kind of MQT is characterized
by quantum tunneling processes of different virtual quasi-particles moving
around a torus. By a high-order degenerate perturbation approach, the effective
pseudo-spin models of the degenerate ground states are obtained. From these
models, we get the energy splitting of the ground states, of which the results
are consistent with those from exact diagonalization methodComment: 25 pages, 14 figures, 4 table
Cross-Lingual Cross-Platform Rumor Verification Pivoting on Multimedia Content
With the increasing popularity of smart devices, rumors with multimedia
content become more and more common on social networks. The multimedia
information usually makes rumors look more convincing. Therefore, finding an
automatic approach to verify rumors with multimedia content is a pressing task.
Previous rumor verification research only utilizes multimedia as input
features. We propose not to use the multimedia content but to find external
information in other news platforms pivoting on it. We introduce a new features
set, cross-lingual cross-platform features that leverage the semantic
similarity between the rumors and the external information. When implemented,
machine learning methods utilizing such features achieved the state-of-the-art
rumor verification results
A Bayesian measurement error model for two-channel cell-based RNAi data with replicates
RNA interference (RNAi) is an endogenous cellular process in which small
double-stranded RNAs lead to the destruction of mRNAs with complementary
nucleoside sequence. With the production of RNAi libraries, large-scale RNAi
screening in human cells can be conducted to identify unknown genes involved in
a biological pathway. One challenge researchers face is how to deal with the
multiple testing issue and the related false positive rate (FDR) and false
negative rate (FNR). This paper proposes a Bayesian hierarchical measurement
error model for the analysis of data from a two-channel RNAi high-throughput
experiment with replicates, in which both the activity of a particular
biological pathway and cell viability are monitored and the goal is to identify
short hair-pin RNAs (shRNAs) that affect the pathway activity without affecting
cell activity. Simulation studies demonstrate the flexibility and robustness of
the Bayesian method and the benefits of having replicates in the experiment.
This method is illustrated through analyzing the data from a RNAi
high-throughput screening that searches for cellular factors affecting HCV
replication without affecting cell viability; comparisons of the results from
this HCV study and some of those reported in the literature are included.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS496 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
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