Analysis of Chinese Citizens’ Perception and Its Differences of City Spirit: A Case Study of Hefei City

City spirit is the soul of the city. The spread of city spirit not only could establish a civilized specimen for citizens, but also create a good cultural atmosphere for the city. Hefei residents’ perception of city spirit is extensive, and most of Hefei citizens consider the expression words of city spirit are very appropriate, which is enlightened, open-minded, actual and innovate. Great majority of Hefei citizens willing to support the propaganda and promotion of the city spirit, and they think the promotion of the city spirit plays a key role in the way of city’s development. In addition,significant differences in the perception of urban spirituality emerge among residents with different economic and social characteristics. There are four aspects about how to enhance the public perception of city spirit, which including increasing dissemination channels and means,strengthening guidance according to the difference of residents, encouraging participation of community residents, and building good atmosphere depending on the city’s advantages

Field-aware Calibration: A Simple and Empirically Strong Method for Reliable Probabilistic Predictions

It is often observed that the probabilistic predictions given by a machine learning model can disagree with averaged actual outcomes on specific subsets of data, which is also known as the issue of miscalibration. It is responsible for the unreliability of practical machine learning systems. For example, in online advertising, an ad can receive a click-through rate prediction of 0.1 over some population of users where its actual click rate is 0.15. In such cases, the probabilistic predictions have to be fixed before the system can be deployed. In this paper, we first introduce a new evaluation metric named field-level calibration error that measures the bias in predictions over the sensitive input field that the decision-maker concerns. We show that existing post-hoc calibration methods have limited improvements in the new field-level metric and other non-calibration metrics such as the AUC score. To this end, we propose Neural Calibration, a simple yet powerful post-hoc calibration method that learns to calibrate by making full use of the field-aware information over the validation set. We present extensive experiments on five large-scale datasets. The results showed that Neural Calibration significantly improves against uncalibrated predictions in common metrics such as the negative log-likelihood, Brier score and AUC, as well as the proposed field-level calibration error.Comment: WWW 202

N-[11-(4-Chloro­phen­yl)-11,12-dihydro­benzo[c]phenanthridin-6-yl]benzamide

There are two independent mol­ecules in the asymmetric unit of the title compound, C30H21ClN2O, which differ slightly in the orientation of the unsubstituted phenyl ring. Inter­molecular C—H⋯π inter­actions stabilize the crystal structure. The crystal studied was found to be a racemic twin. The dihedral angles between the substituted phenyl ring and the benzo[c]phenanthridine system are 87.13 (5) and 79.25 (5)° in the two molecules