Abstract: Some implementations relate to methods, systems, and a computing device to generate predicted scores for games based on gameplay duration. In some implementations, a method includes obtaining game session data that includes a respective session duration for each game session of a plurality of game sessions, each game session associated with a respective game and a respective game player. The method further includes grouping the plurality of games game clusters based on the game session data, each game cluster including one or more of the games such that no game is in more than one cluster. The method further includes generating a predicted score for one or more of the games and identifying at least one game as a high quality game based on the predicted score. In some implementations, generating the predicted store includes determining a distance between each game and the decision boundary.

Abstract: Implementations described herein relate to methods, systems, and computer-readable media to personalize recommendations. In some implementations, a method includes computing a user-based similarity matrix and a game-based similarity matrix, obtaining a set of user scores from a first machine learning model and the user-based similarity matrix, and obtaining a set of game scores from a second machine learning model and the game-based similarity matrix. The method also includes combining the set of user scores and the set of game scores to generate a normalized set of scores, identifying a set of personalized recommendations for the user associated with a subset of the normalized set of scores, assigning a rank to each of the plurality of items, generating a list of items wherein items in the list of items are ordered based on respective ranks, and providing a user interface to the user that includes the list of items.

Abstract: Some implementations relate to methods, systems, and a computing device to generate predicted scores for games based on gameplay duration. In some implementations, a method includes obtaining game session data that includes a respective session duration for each game session of a plurality of game sessions, each game session associated with a respective game and a respective game player. The method further includes grouping the plurality of games game clusters based on the game session data, each game cluster including one or more of the games such that no game is in more than one cluster. The method further includes generating a predicted score for one or more of the games and identifying at least one game as a high quality game based on the predicted score. In some implementations, generating the predicted store includes determining a distance between each game and the decision boundary.

Abstract: This invention relates to the field of medium and nitrogen fixation technique. More specifically, the present invention relates to a method of identifying whether Azotobacter secrets ammonia using nitrogen-free solid incubation media. Each liter of nitrogen-free incubation media comprises: K2HPO4 0.5-2 g, MgSO4.7H2O 0.1-0.5 g, CaCl2.2H2O 0.05-0.15 g, glucose 7-13 g, FeSO4.7H2O 0.005-0.02 g, NaMoO4.2H2O, 0.005-0.01 g, agar 10-20 g, and distilled water to balance. The present invention provides a method to identify whether Azotobacter secrets ammonia using nitrogen-free solid incubation media, which is simple and easy to carry out, and can accurately identify whether Azotobacter secreting nitrogenous compounds to extracellular and the ability of secretion, which play an important role in the development of bio-fertilizer industry.

Abstract: A battery is charged by first charging the battery at a constant current during a first time interval, and then charging the battery at a varying current during a second time interval. The battery can be a lithium-ion battery, and the charging uses a kinetic model. The kinetic model models the battery having an indiffused well having a capacity c, and a diffused well having a capacity 1?c, and the indiffused well is filled directly by the current, and the diffused well is filled only from the indiffused well via a valve with constant inductance.

Abstract: A battery is charged by first charging the battery at a constant current during a first time interval, and then charging the battery at a varying current during a second time interval. The battery can be a lithium-ion battery, and the charging uses a kinetic model. The kinetic model models the battery having an indiffused well having a capacity c, and a difused well having a capacity 1?c, and the indiffused well is filled directly by the current, and the diffused well is filled only from the indiffused well via a valve with constant inductance.