Sentence examples for Future scored from inspiring English sources

WWF was praised for its breadth of resources and strong brand value, while Forum for the Future scored highly on consulting prowess and alignment with business interests.

David Villa and Neymar, Barcelona's past and future, scored a goal each as the Spanish Super Copa first leg finished 1-1 athehe Vicente Calderón.

Since the start of the year, the United Nations has been wooed by its onetime detractors in the Bush administration to re-enter Iraq and chart the country's political future, scored a breakthrough in the decades-long struggle to reunite the feuding Turkish and Greek Cypriots, and acted with unaccustomed swiftness to authorize deployment of a multinational force to Haiti.

Restore Our Future scored support from at least two other notable media executives.

"Wearing the number nine shirt for Dundee United had been my career high and I would love to be back at Tannadice in the future scoring goals for the club I have supported all my life," said Moore.

In San Diego, for example, prior scores account for roughly 25 percent of the variation in future scores.

But New York is an outlier: Prior scores predict less than 2 percent of the variation in future scores.

Judging by a recent region-wide flurry of arrests, trials and harsh sentences slapped on dissidents, future scores may well be worse.

Grades are based on a point system: in New York, 0 to 13 points yields an A, 14 to 27 points a B, and 28 or more points a C. In other jurisdictions, numerical scores substantively predict future scores.

Instead of the derivation of the scores, this back-end system proposes a stacking of past and future scores with the present score to model the dynamic behavior in a different way. Figure 3 shows this combination process where several score frames from the past and several score frames from the future are stacked with the present frame.

This problem is essentially a time-series forecasting issue [9], because one can regard the popularity score of each topic (e.g., the number of publications related to a specific topic) across different years as a time series data, and further predict the topic's unseen future score by using time-series forecasting.