Abstract: The invention relates to a computer-implemented system and method for providing data science as a service (DSaaS) using a real time data prediction contest. Participants in the real time data prediction contest are permitted to execute and submit algorithms, utilize third party data sources, and utilize sub-contests to generate data predictions for the data prediction contest. The participants in the data prediction contest may be humans or software robots. A category of sponsor confidential information related to the data prediction is defined and maintained as confidential by the sponsor, while various methods are implemented to obtain relevant algorithms and data for the data prediction. The sponsor receives data predictions from the participants on a real time or near real time basis, calculates a score for the data predictions, and compensates participants according to their score.

Abstract: The invention relates to a computer-implemented system and method for providing data science as a service (DSaaS) using a real time data prediction contest. The method may comprise the steps of presenting a consumer interface via a network that allows a data consumer to identify a subject data source having data fields that can be predicted; and presenting a participant interface via the network that allows a participant to select a competition in which to participate and provides a web services interface enabling the participant to provide web services that can be called by the web services interface. The web services provide a prediction of the at least one data field, and the web services are permitted to utilize external data sources in generating the prediction. The prediction can then be transmitted via the network to the consumer.

Abstract: A method is performed by a plurality of networked party computing systems configured to perform secure multi-party computations, each computer system having at least one processor and a memory. The method can include creating a secret shared matrix based on secret data of each of the plurality of party computing systems, wherein the secret shared matrix includes a plurality of time-shifted sequences of data from each of an independent time series of data and a dependent time series of data; computing, based on the secret shared matrix and in a secure multi-party computation, a secret shared model for predicting the dependent time series of data based on the independent time series of data; and using the secret shared model to determine a statistic for one of the plurality of time-shifted sequences of data from the independent time series as a predictor of the dependent time series of data.

Abstract: The invention relates to a computer-implemented system and method for providing data science as a service (DSaaS) using a real time data prediction contest. Participants in the real time data prediction contest are permitted to execute and submit algorithms, utilize third party data sources, and utilize sub-contests to generate data predictions for the data prediction contest. The participants in the data prediction contest may be humans or software robots. A category of sponsor confidential information related to the data prediction is defined and maintained as confidential by the sponsor, while various methods are implemented to obtain relevant algorithms and data for the data prediction. The sponsor receives data predictions from the participants on a real time or near real time basis, calculates a score for the data predictions, and compensates participants according to their score.

Abstract: The invention relates to a computer-implemented system and method for providing data science as a service (DSaaS) using a real time data prediction contest. The method may comprise the steps of presenting a consumer interface via a network that allows a data consumer to identify a subject data source having data fields that can be predicted; and presenting a participant interface via the network that allows a participant to select a competition in which to participate and provides a web services interface enabling the participant to provide web services that can be called by the web services interface. The web services provide a prediction of the at least one data field, and the web services are permitted to utilize external data sources in generating the prediction. The prediction can then be transmitted via the network to the consumer.

Abstract: Methods, systems, and apparatus, including computer program products, for providing a liquidity based metric and/or index for low liquidity securities. In an aspect, actions can include receiving transaction data including data relating to one or more transactions of a first security, obtaining, using a data processing apparatus, one or more reference values, in which each reference value is contemporaneous with a corresponding transaction of the first security, generating, using the data processing apparatus, a transaction liquidity factor for each reference value-transaction pair, and combining the transaction liquidity factors into an asset liquidity factor for the first security.

Abstract: A machine-implemented method includes: obtaining transaction data relating to one or more financial assets, the transaction data including the identity of the one or more financial assets, corresponding valuation data for the one or more financial assets, and corresponding volume data for the one or more financial assets; receiving, at the data processing apparatus, a request to display information relating to a first financial asset from the one or more financial assets; generating, in response to receiving the request, output data for display at a user terminal, in which the output data includes a user interface that displays at least a portion of the transaction data relating to the first financial asset and market projection information relating to the first financial asset, in which the market projection information is substantially contemporaneous with the portion of transaction data; and transmitting the output data to the user terminal.

Abstract: A method for calculating pricing information for a financial instrument consisting of a plurality of underlying financial instruments that includes the steps of: calculating a default time vector for a plurality of default scenarios wherein each default time vector includes a measure of a likelihood of default for each of the plurality of underlying financial instruments; calculating one or more cash flows for a subset of the default scenarios thereby forming a training set; training a neural network with the training set; and using the neural network to estimate one or more cash flows for a remaining number of the plurality of default scenarios.

Abstract: A system for modeling a basket of securities containing a plurality of securities is provided and includes a default/recovery model database for storing default/recovery data regarding the plurality of securities. Also included is a default simulation engine for calculating a default time for at least one of the plurality of securities based on the default/recovery data. Finally, a cash flow engine is included for generating cash flows for the basket of securities based on the default times.

Abstract: A system for modeling a basket of securities containing a plurality of securities is provided and includes a default/recovery model database for storing default/recovery data regarding the plurality of securities. Also included is a default simulation engine for calculating a default time for at least one of the plurality of securities based on the default/recovery data. Finally, a cash flow engine is included for generating cash flows for the basket of securities based on the default times.

Abstract: A system for modeling a basket of securities containing a plurality of securities is provided and includes a default/recovery model database for storing default/recovery data regarding the plurality of securities. Also included is a default simulation engine for calculating a default time for at least one of the plurality of securities based on the default/recovery data. Finally, a cash flow engine is included for generating cash flows for the basket of securities based on the default times.

Abstract: A method and system for assisting a user in generating a report regarding a procedure such as a medical procedure. A first display region provides a hierarchical menu of available keywords from a knowledge base. A second display region provides a hierarchical menu of particular keywords that have been selected by the user. A third display region provides a report from a sentence that was generated by populating a sentence model based on the selected keywords. The sentence can be edited by selecting a keyword from the sentence, then selecting a replacement keyword from the first display region. A grammar engine corrects the grammar of the sentence based on user settings for the keywords.

Abstract: A method and system for capturing patient related data in an endoscopic system comprising an imaging node adapted to capture and display endoscopic images during the course of an endoscopic examination. The patient data capture system and method includes a display device that provides an interface to enable a user to enter data relating to a patient examined during the examination, including patient vital sign information at various phases of care relating to the endoscopic examination and, further including individual graphic controls for enabling entry of values relating to the patient's vitals information. The entered patients vitals information is associated with a timestamp. The patient vitals information and associated timestamps are stored in a database record associated with the patient. Further data capable of being entered into the system includes medications administered, Aldrete scores and intraprocedural assessments.

Abstract: A system and method for enabling the automatic setting of a mask for displaying live endoscopic images on a monitor device. An imaging node processor selects a pre-determined mask setting based on an automatically detected solid state imager (CCD) type when connected to the video processor, and a selected magnifying ratio. Based on this information, a mask pattern is automatically generated in a main memory. A merge function enables the mask to be displayed with cutout portions where information including, live or frozen image, thumbnail image associated with a static image capture, and patient demographic information is displayed. The user may select the frame coordinate locations corresponding to the corners of the live viewable area, captured image display and other system and demographic information to be displayed. Further, while the system is configured to include pre-defined masks, users are additionally able to create additional masks or modify the system-defined masks.

Abstract: A system designed to support and manage the workflow for all user roles pertaining to an endoscopic laboratory, from registration and scheduling of patient information through pre-procedure, procedure and post-procedure phases of an endoscopic examination, including support for the entry, by various users associated with an endoscopic laboratory, of information and data including the processing and storage of endoscopic images captured during an endoscopic exam of a patient, for association with a patient record stored in a database, and including the entry of procedure notes and generation of reports that include the stored images, all via an integrated user interface.

Abstract: A method for calculating pricing information for a financial instrument consisting of a plurality of underlying financial instruments that includes the steps of: calculating a default time vector for a plurality of default scenarios wherein each default time vector includes a measure of a likelihood of default for each of the plurality of underlying financial instruments; calculating one or more cash flows for a subset of the default scenarios thereby forming a training set; training a neural network with the training set; and using the neural network to estimate one or more cash flows for a remaining number of the plurality of default scenarios.

Abstract: A system for modeling a basket of securities containing a plurality of securities is provided and includes a default/recovery model database for storing default/recovery data regarding the plurality of securities. Also included is a default simulation engine for calculating a default time for at least one of the plurality of securities based on the default/recovery data. Finally, a cash flow engine is included for generating cash flows for the basket of securities based on the default times.