Abstract: Systems and methods for pre-processing data to facilitate efficient and accurate machine learning are provided. The data may include market data. The pre-processing may include partitioning the data into windows, assigning categories to windows, and generating a series of vectors. The series of vectors then being input into a computer system that executes a machine learning algorithm to efficiently train a neural network used to identify structure or patterns therein.

Abstract: The disclosed embodiments relate to a system/process which can be used to provide redundancy and error/failure recovery to a System of Record (SOR), such as an electronic financial transaction processing system or sub-system thereof, which processes transactions received from one or more sources and generates results/outputs based thereon for communication to one or more recipients/destinations/consumers. The disclosed embodiments minimize, if not eliminate, both the amount of data, i.e., the number of transactions, which can be lost during a failure and the performance impact on the SOR. Generally, the disclosed embodiments are implemented so as to receive/intercept each incoming transaction communicated to the primary instance prior to receipt thereby and intercept or otherwise regulate the communication of the outputs of the primary instance, generated based on the primary instance's processing of the incoming transactions, to the destinations/recipients/consumers thereof.

Abstract: Systems and methods are provided to identify abnormal transaction activity by a participant that is inconsistent with current conditions. Historical participant and external data are identified. A recurrent neural network identifies patterns in the historical participant and external data. A new transaction by the participant is received. The new transaction is compared using the patterns to the historical participant and external data. An abnormality score is generated. An alert is generated if the abnormality score exceeds a threshold.

Abstract: Systems and methods for pre-processing data to facilitate efficient and accurate machine learning are provided. The data may include market data. The pre-processing may include partitioning the data into windows assigning categories to windows generate a series of vectors. The series of vectors then being input into a computer system that executes a machine learning algorithm to efficiently train a neural network used to identify structure or patterns therein.

Abstract: Battery thermal barrier foam systems are provided for use within traction battery packs. Exemplary battery thermal barrier foam systems may include one or more foam blocks arranged to fill void spaces within a battery array of a traction battery pack. Each foam block may include a high temperature material system capable of mitigating cell-to-cell and/or array-to-array thermal propagation, increasing thermal insulation between battery cells, absorbing heat, etc.

Abstract: Systems and methods are provided to identify abnormal transaction activity by a participant that is inconsistent with current conditions. Historical participant and external data are identified. A recurrent neural network identifies patterns in the historical participant and external data. A new transaction by the participant is received. The new transaction is compared using the patterns to the historical participant and external data. An abnormality score is generated. An alert is generated if the abnormality score exceeds a threshold.

Abstract: Systems and methods for pre-processing data to facilitate efficient and accurate machine learning are provided. The data may include market data. The pre-processing may include partitioning the data into windows assigning categories to windows generate a series of vectors. The series of vectors then being input into a computer system that executes a machine learning algorithm to efficiently train a neural network used to identify structure or patterns therein.

Abstract: The invention is directed to pharmaceutical compositions comprising dextromethorphan and methods of use thereof. Formulations of the present invention include dextromethorphan or a pharmaceutically acceptable salt thereof in a sustained release formulation comprising a controlled release agent. Formulations of the present invention include a core tablet, optionally an active coating and, optionally a film coating. The pharmaceutical compositions may be used as an antitussive, and the invention further relates to the treatment of cough in a patient in need thereof.

Abstract: Systems and methods for pre-processing data to facilitate efficient and accurate machine learning are provided. The data may include market data. The pre-processing may include partitioning the data into windows assigning categories to windows generate a series of vectors. The series of vectors then being input into a computer system that executes a machine learning algorithm to efficiently train a neural network used to identify structure or patterns therein.

Abstract: Systems and methods are provided to identify abnormal transaction activity by a participant that is inconsistent with current conditions. Historical participant and external data are identified. A recurrent neural network identifies patterns in the historical participant and external data. A new transaction by the participant is received. The new transaction is compared using the patterns to the historical participant and external data. An abnormality score is generated. An alert is generated if the abnormality score exceeds a threshold.

Abstract: Systems and methods are provided to identify abnormal transaction activity by a participant that is inconsistent with current conditions. Historical participant and external data is identified. A recurrent neural network identifies patterns in the historical participant and external data. A new transaction by the participant is received. The new transaction is compared using the patterns to the historical participant and external data. An abnormality score is generated. An alert is generated if the abnormality score exceeds a threshold.

Abstract: Systems and methods are provided for message transmission timing optimization. The system receives a large market disrupting transaction and provides a transaction placement strategy that splits up the transaction to maximizes favorable execution value and minimizes time required to execute the entire transaction.

Abstract: Systems and methods are provided for message transmission timing optimization. The system receives a large market disrupting transaction and provides a transaction placement strategy that splits up the transaction to maximizes favorable execution value and minimizes time required to execute the entire transaction.

Abstract: The invention is directed to pharmaceutical compositions comprising dextromethorphan and methods of use thereof. Formulations of the present invention include dextromethorphan or a pharmaceutically acceptable salt thereof in a sustained release formulation comprising a controlled release agent. Formulations of the present invention include a core tablet, optionally an active coating and, optionally a film coating. The pharmaceutical compositions may be used as an antitussive, and the invention further relates to the treatment of cough in a patient in need thereof.

Abstract: A method and apparatus for publishing market data for a financial instrument utilizes existing network layer acknowledgement feature to publish market data for the financial instrument to a client device at rates in which the client device is able to process the data. The publishing rate is dynamic, as opposed to being fixed, and is able to adjust “on-the-fly” so as to prevent message queue stagnation.

Abstract: A method and apparatus for publishing market data for a financial instrument utilizes existing network layer acknowledgement feature to publish market data for the financial instrument to a client device at rates in which the client device is able to process the data. The publishing rate is dynamic, as opposed to being fixed, and is able to adjust “on-the-fly” so as to prevent message queue stagnation.

Abstract: Systems and methods are provided for message transmission timing optimization. The system receives a large market disrupting transaction and provides a transaction placement strategy that splits up the transaction to maximizes favorable execution value and minimizes time required to execute the entire transaction.

Abstract: A method and apparatus for publishing market data for a financial instrument utilizes existing network layer acknowledgement feature to publish market data for the financial instrument to a client device at rates in which the client device is able to process the data. The publishing rate is dynamic, as opposed to being fixed, and is able to adjust “on-the-fly” so as to prevent message queue stagnation.

Abstract: Systems and methods are provided to identify abnormal transaction activity by a participant that is inconsistent with current conditions. Historical participant and external data is identified. A recurrent neural network identifies patterns in the historical participant and external data. A new transaction by the participant is received. The new transaction is compared using the patterns to the historical participant and external data. An abnormality score is generated. An alert is generated if the abnormality score exceeds a threshold.

Abstract: A method and apparatus for publishing market data for a financial instrument utilizes existing network layer acknowledgement feature to publish market data for the financial instrument to a client device at rates in which the client device is able to process the data. The publishing rate is dynamic, as opposed to being fixed, and is able to adjust “on-the-fly” so as to prevent message queue stagnation.