Other

Pearson Education, Inc.

Gm Global Technolgoy Operations, Inc.

Atlantic Richfield Company

North American Philips Corporation

Cps Technology Holdings LLC

Clarios Germany Gmbh & Co. Kg

William M Murray

Scott Hellman

Alok Baikadi

David Strong

Sean York

Tim Stewart

Lee Becker

Peter Foltz

Kyle D Habermehl

Mark Rosenstein

Jill Budden

Stephen Hopkins

Andrew Gorman

Jason Daniel Fuhr

Phillip F McCauley

Jeffrey L Troxel

Thomas H Wilson

Andrew P Voss

Luis Manuel Oros

Ruediger Jaeppelt

Ronald A Lee

Mohammad Mujahid

Harry H Haft

Ruthjean Stager

Robert T Niemczyk

Samuel Downs

Disclosed is a non-lead conductive cap for a battery terminal and battery. The battery may comprise a battery housing and a positive and negative terminal, the positive and negative terminal being accessible through the battery housing; wherein the positive and negative terminal further comprise an electrically conductive cap mounted on both the positive and negative terminal, wherein the electrically conductive cap does not comprise lead.

Cap for battery terminal

Systems and methods for automated custom training of a scoring model are disclosed herein. The method include: receiving a plurality of responses received from a plurality of students in response to providing of a prompt; identifying an evaluation model relevant to the provided prompt, which evaluation model can be a machine learning model trained to output a score relevant to at least portions of a response; generating a training indicator that provides a graphical depiction of the degree to which the identified evaluation model is trained; determining a training status of the model; receiving at least one evaluation input when the model is identified as insufficiently trained; updating training of the evaluation model based on the at least one received evaluation input; and controlling the training indicator to reflect the degree to which the evaluation model is trained subsequent to the updating of the training of the evaluation model.

Systems and methods for interface-based automated custom authored prompt evaluation

Systems and methods for interface-based machine learning model output customization

Systems and methods for content aggregation creation are disclosed herein. The system can include memory having a content database and an aggregation database. The system can include a user device having a first network interface and a first I/O subsystem. The system can include a server that can: provide content to the user device via a first electrical signal; receive a selection of a portion of the provided content from the user device via a second electrical signal; automatically extract sentences from the selected portion of the provided content via a natural language processor; automatically generate a parse tree for one of the automatically extracted sentences; identify noun phrases from the part of speech tags within the parse tree; place content associated with one of the noun phrase in a content aggregation; and output the content aggregation to the user device.

System and method for automatic content aggregation generation

Systems and methods for automated evaluation model customization

Systems and methods for automated machine learning model training for a custom authored prompt

Systems and methods for automated sequencing database generation are disclosed herein. The system can include memory that can include a content library database; a graph database; and a model database. The system can include a user device and at least one server. The at least one server can: receive a content aggregation from the content library database; identify content components of the content aggregation based on a natural language processing analysis of at least a portion of the content aggregation; identify explicit sequencing of the content components; generate an intermediate content graph based on the explicit sequencing of the content components; generate a final content graph from the intermediate content graph based on implicit sequencing of the content components; and store the final content graph within the graph database.

System and method for automated hybrid sequencing database generation

System and method for automatic content aggregation evaluation

System and method for automated sequencing database generation

System and method for sequencing database-based content recommendation

System and method for automatic content aggregation database evaluation

A method for automatically initiating the flow of fluid in a pipe that may be blocked by frozen fluid in a portion of the pipe includes urging the flow of fluid through the pipe and energizing a heater disposed in and extending the pipe portion if no flow is detected in the pipe.

Method for initiating flow of fluid blocked by frozen fluid

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Enola, PA, United States of America

William M Murray