Vision-Based Building Seismic Displacement Measurement by Stratification of Projective Rectification Using Lines

We propose a new flexible technique for accurate vision-based seismic displacement measurement of building structures via a single non-stationary camera with any perspective view. No a priori information about the camera’s parameters or only partial knowledge of the internal camera parameters is required, and geometric constraints in the world coordinate system are employed for projective rectification in this research. Whereas most projective rectifications are conducted by specifying the positions of four or more fixed reference points, our method adopts a stratified approach to partially determine the projective transformation from line-based geometric relationships on the world plane. Since line features are natural and plentiful in a man-made architectural building environment, robust estimation techniques for automatic projective/affine distortion removal can be applied in a more practical way. Both simulations and real-recorded data were used to verify the effectiveness and robustness of the proposed method. We hope that the proposed method could advance the consumer-grade camera system for vision-based structural measurement one more step, from laboratory environments to real-world structural health monitoring systems

Prediction of Commuter’s Daily Time Allocation

This paper presents a model system to predict the time allocation in commuters’ daily activity-travel pattern. The departure time and the arrival time are estimated with Ordered Probit model and Support Vector Regression is introduced for travel time and activity duration prediction. Applied in a real-world time allocation prediction experiment, the model system shows a satisfactory level of prediction accuracy. This study provides useful insights into commuters’ activity-travel time allocation decision by identifying the important influences, and the results are readily applied to a wide range of transportation practice, such as travel information system, by providing reliable forecast for variations in travel demand over time. By introducing the Support Vector Regression, it also makes a methodological contribution in enhancing prediction accuracy of travel time and activity duration prediction

Postoperative steroids after Kasai portoenterostomy for biliary atresia: A meta-analysis

AbstractAim: The aim of this systematic review and meta-analysis was to determine if adjunct steroids affect jaundice-free, cholangitis, and survival rates after Kasai portoenterostomy. Methods: The literature was searched using the following terms: biliary atresia, portoenterostomy, steroids, glucocorticoids, dexamethasone, prednisolone, and hydrocortisone. The primary outcome was the jaundice-free rate. Secondary outcomes were cholangitis and survival rates. Results: Ten studies were included in the systematic review and 8 in the meta-analyses. Steroid treatment regimens were inconsistent between studies. The pooled odds ratio (OR) for the jaundice-free rate did not significantly favor steroid over non-steroid treatment (1.95; 95% confidence interval [CI]: 0.91–4.11; P = 0.087), nor did the pooled OR for the cholangitis rate (0.75; 95% CI: 0.48–1.17; P = 0.202). Overall survival ranged from 58 to 95% in the steroid group and from 36 to 96% in the control group. Native liver survival ranged from 30 to 56% in the steroid group and from 31 to 48% in the control group. The survival data were not suitable for meta-analysis. Conclusions: Although these results imply that adjunct steroids after Kasai portoenterostomy for BA may not improve jaundice-free or cholangitis rates, the quality of available evidence is limited and therefore not definitive. Additional high quality studies are needed

Investing with Fast Thinking

Using data from a major online peer-to-peer lending market, we document that investors follow a simple rule of thumb under time pressure: they rush to invest in loans with high interest rates without sufficiently examining credit ratings, which are freely available on the trading interface. Our experiments show that making credit rating information more salient “nudges” investors into better decisions. Firsthand experience matters for learning for non-informational reasons: An investor responds differently when observing a default of her own loan, relative to observing a default of another investor’s loan