Abstract: The present invention provides a system for data mapping and storing in digital three-dimensional oscilloscope, wherein the fixed coefficients, which are calculated according the parameters and settings of a digital oscilloscope, are stored into a fixed coefficient memory CO RAM, the fixed coefficients are outputted to N fractional operation units through N?1 D flip-flop delay units to multiply with the acquired data x(n) and then be accumulated, thus N fractional calculus results are obtained. In this way, N fractional calculus results can be obtained by performing L/N fractional calculus operations. N fractional calculus results are sent to a signal processing and display module, in which they are converted into a display data through a drawing thread, and the display data are sent to LCD for displaying, thus the fractional calculus operation and display of a input signal in a digital oscilloscope is realized.

Abstract: Systems and methods for providing auto-completion options to input characters are presented. In response to receiving input characters, a plurality of items of content (that are non-textual items of content) of a corpus of content are identified. These items of content are clustered into n clusters of content according to similarities among the items of content. From the items of content of each cluster, a descriptive title is determined for the cluster. This descriptive title is an auto-completion option for the cluster. The descriptive titles/auto-completion options are provided in response to receiving the input characters.

Abstract: Systems of the present disclosure generate database queries for financial information requested in a natural-language form. A natural-language processing (NLP) financial aggregator receives a request for financial information and extracts NLP features of the request, including keywords. The NLP financial aggregator determines a type of the request based on the features and creates a query in a database-query language for the financial information based on the type and on the features. The NLP financial aggregator submits the query to a database where the financial information is stored. The software then receives the financial information from the database and sends the information to the user.

Abstract: Systems of the present disclosure generate database queries for financial information requested in a natural-language form. A natural-language processing (NLP) financial aggregator receives a request for financial information and extracts NLP features of the request, including keywords. The NLP financial aggregator determines a type of the request based on the features and creates a query in a database-query language for the financial information based on the type and on the features. The NLP financial aggregator submits the query to a database where the financial information is stored. The software then receives the financial information from the database and sends the information to the user.

Abstract: Systems of the present disclosure generate database queries for financial information requested in a natural-language form. A natural-language processing (NLP) financial aggregator receives a request for financial information and extracts NLP features of the request, including keywords. The NLP financial aggregator determines a type of the request based on the features and creates a query in a database-query language for the financial information based on the type and on the features. The NLP financial aggregator submits the query to a database where the financial information is stored. The software then receives the financial information from the database and sends the information to the user.

Abstract: Systems and methods for providing auto-completion options to input characters are presented. In response to receiving input characters, a plurality of items of content (that are non-textual items of content) of a corpus of content are identified. These items of content are clustered into n clusters of content according to similarities among the items of content. From the items of content of each cluster, a descriptive title is determined for the cluster. This descriptive title is an auto-completion option for the cluster. The descriptive titles/auto-completion options are provided in response to receiving the input characters.

Abstract: Systems and methods for providing auto-completion options to input characters are presented. In response to receiving input characters, a plurality of items of content (that are non-textual items of content) of a corpus of content are identified. These items of content are clustered into n clusters of content according to similarities among the items of content. From the items of content of each cluster, a descriptive title is determined for the cluster. This descriptive title is an auto-completion option for the cluster. The descriptive titles/auto-completion options are provided in response to receiving the input characters.

Abstract: The invention relates to a method for identifying a life event affecting a user. The method includes obtaining a classification model. The classification model models how financial data of a user relates to life events. Also, the method includes gathering the financial data of the user. The financial data of the user matches at least a subset of the classification model. In addition, the method includes identifying a life event affecting the user by applying the classification model to the financial data of the user. Still yet, the method includes customizing a user interface of an application that is utilized by the user. The customization is based on the identified life event.