Abstract: A well pumping apparatus including a discharge head (110), a drive string rod (130) in fluid communication with an inner cavity (142) of a production tubing (140), a pre-lubrication port (160) at the discharge head, and lubrication cups (134) installed along the drive string rod adjacent to sets of bearings (150) distributed along the drive string rod.

Abstract: In an embodiment, a method, and corresponding system and non-transitory computer readable medium storing instructions configured to cause a processor to execute steps are configured to introduce an auxiliary transformation to a digital media, resulting in a transformed digital media by generating the auxiliary transformation with a transform function. The method is further configured to evaluate the transformed digital media to generate a metric estimating a human response to the transformed digital media altered by the introduced auxiliary transformation. The method is further configured to train a neural network to remove the auxiliary transformation from any digital media by learning a desired transformation function from the transformed digital media and the metric associated with the transformed digital media.

Abstract: The present approach similarly combines task and motion planning, but does so without symbolic representations and begins with simpler tasks than other models in such domains can handle. Unlike prior approaches, the present approach does so in continuous action and state spaces which require many precise steps in the configuration space to execute what otherwise is a single output token such as “pick up” for discrete problems.

Abstract: In an embodiment, a method includes presenting, on a display, sample text in a given language to a user. The method further includes recording eye fixation times for each word of the sample text for the user and recording saccade times between each pair of fixations of the sample text. The method further includes comparing features of the gaze pattern of the user to features of a gaze pattern of a plurality of training readers. Each training reader (e.g., training user) has a known native language. The method further generates a probability of at least one an estimated native language of the user based on the results of the comparison.

Abstract: In an embodiment, Applicant's method can automatically determine proficiency in a given language by tracking a user's gaze during reading a sample text. The language proficiency test includes reading sentences in a language (e.g., a language to the user's native language). The user's, or learner's, gaze is recorded using an eye-tracking camera while they read the sample text. Applicant's method and corresponding system predicts the language proficiency of the learner based on their gaze patterns. Applicant's method and corresponding system can also predict performance on specific standardized language proficiency tests such as Michigan EPT (Michigan English Proficiency Test), TOEIC® (Test of English for International Communication®), and TOEFL® (Test of English as a Foreign Language®).

Abstract: In an embodiment, a method, and corresponding system and non-transitory computer readable medium storing instructions configured to cause a processor to execute steps are configured to introduce an auxiliary transformation to a digital media, resulting in a transformed digital media by generating the auxiliary transformation with a transform function. The method is further configured to evaluate the transformed digital media to generate a metric estimating a human response to the transformed digital media altered by the introduced auxiliary transformation. The method is further configured to train a neural network to remove the auxiliary transformation from any digital media by learning a desired transformation function from the transformed digital media and the metric associated with the transformed digital media.

Abstract: In an embodiment, a method includes presenting, on a display, sample text in a given language to a user. The method further includes recording eye fixation times for each word of the sample text for the user and recording saccade times between each pair of fixations of the sample text. The method further includes comparing features of the gaze pattern of the user to features of a gaze pattern of a plurality of training readers. Each training reader (e.g., training user) has a known native language. The method further generates a probability of at least one an estimated native language of the user based on the results of the comparison.

Abstract: In an embodiment, Applicant's method can automatically determine proficiency in a given language by tracking a user's gaze during reading a sample text. The language proficiency test includes reading sentences in a language (e.g., a language to the user's native language). The user's, or learner's, gaze is recorded using an eye-tracking camera while they read the sample text. Applicant's method and corresponding system predicts the language proficiency of the learner based on their gaze patterns. Applicant's method and corresponding system can also predict performance on specific standardized language proficiency tests such as Michigan EPT (Michigan English Proficiency Test), TOEIC® (Test of English for International Communication®), and TOEFL® (Test of English as a Foreign Language®).

Abstract: A method and apparatus for computer retrieval of database material which may be text, computer programs, graphics, audio, object classes, action specifications or other material which may be machine stored. Annotations are provided for at least selected database subdivisions, preferably with natural language questions, assertions or noun phrases or some combination/collection thereof. However, the annotations may also initially be generated in a structured form. Annotations are, if required, converted to a structured form and are stored in that form along with connections to corresponding subdivisions. Searching for relevant subdivisions involves entering a query in natural language or structured form, converting natural language queries to structured form, matching the structured form query against stored annotations and retrieving database subdivisions connected to matched annotations.

Abstract: A method and apparatus for computer text retrieval which involves annotating at least selected text subdivisions, preferably with natural language questions, assertions or noun phrases. However, the annotations may also initially be generated in a structured form. Annotations are, if required, converted to a structured form and are stored in that form. Searching for relevant text subdivisions involves entering a query in natural language or structured form, converting natural language queries to structured form, matching the structured form query against stored annotations and retrieving text subdivisions connected to matched annotations. The annotation process may be aided by utilizing various techniques for automatically or semiautomatically generating the annotations.