Abstract: A fluid containing component is provided having a structure and a sump for storing a fluid. A gear baffle is disposed between the rotatable component and the structure. The gear baffle includes a first side end and a second side defining a gear cavity therebetween. The fluid displaced by rotation of a gear positioned within the gear baffle collects on inner surfaces of the gear baffle and is directed out of the gear baffle through at least one flow port of the baffle.

Abstract: A fluid containing component is provided having a structure and a sump for storing a fluid. A gear baffle is disposed between the rotatable component and the structure. The gear baffle includes a first side end and a second side defining a gear cavity therebetween. The fluid displaced by rotation of a gear positioned within the gear baffle collects on inner surfaces of the gear baffle and is directed out of the gear baffle through at least one flow port of the baffle.

Abstract: Embodiments generally relate to machine translation. In one embodiment, a method includes receiving a sentence of a source language. The method also includes parsing the sentence into words. The method also includes determining scores for the words, where each score is associated with features of each respective word. The method also includes reordering the words based on the scores.

Abstract: Systems, methods, and apparatuses including computer program products are provided for encoding and using a language model. In one implementation, a method is provided. The method includes generating a compact language model, including receiving a collection of n-grams, each n-gram having one or more associated parameter values, determining a fingerprint for each n-gram of the collection of n-grams, identifying locations in an array for each n-gram using a plurality of hash functions, and encoding the one or more parameter values associated with each n-gram in the identified array locations as a function of corresponding array values and the fingerprint for the n-gram.

Abstract: Systems, methods, and apparatuses including computer program products are provided for encoding and using a language model. In one implementation, a method is provided. The method includes generating a compact language model, including receiving a collection of n-grams, each n-gram having one or more associated parameter values, determining a fingerprint for each n-gram of the collection of n-grams, identifying locations in an array for each n-gram using a plurality of hash functions, and encoding the one or more parameter values associated with each n-gram in the identified array locations as a function of corresponding array values and the fingerprint for the n-gram.