Abstract: Systems, methods, and apparatuses are described for determining compliance with a plurality of restrictions associated with one or more devices in an organization. First text indicating restrictions may be received, and second text indicating a current configuration of one or more devices may be received. Both sets of text may be processed by, e.g., removing a portion of the text based on a predetermined list of terms and simplifying the text using a lemmatization algorithm. A first vector and second vector may be generated based on the processed sets of text, and each vector may be weighted based on an inverse frequency of words in their respective text. Each vector may be normalized based on semantic analysis. The two vectors may be compared. Based on the comparison, third text corresponding to a portion of the second vector may be generated and transmitted to a third computing device.

Abstract: Various embodiments include methods and systems having detection apparatus operable to cancel or reduce leakage signal originating from a source signal being generated and transmitted from a transmitter. A leakage cancellation signal can be generated digitally, converted to an analog signal, and then subtracted in the analog domain from a received signal to provide a leakage-reduced signal for use in detection and analysis of objects. A digital cancellation signal may be generated by generating a cancellation signal in the frequency domain and converting it to the time domain. Optionally, an estimate of a residual leakage signal can be generated and applied to reduce residual leakage remaining in the leakage-reduced signal. Additional apparatus, systems, and methods can be implemented in a variety of applications.

Abstract: Systems, methods, and apparatuses are described for determining compliance with a plurality of restrictions associated with one or more devices in an organization. First text indicating restrictions may be received, and second text indicating a current configuration of one or more devices may be received. Both sets of text may be processed by, e.g., removing a portion of the text based on a predetermined list of terms and simplifying the text using a lemmatization algorithm. A first vector and second vector may be generated based on the processed sets of text, and each vector may be weighted based on an inverse frequency of words in their respective text. Each vector may be normalized based on semantic analysis. The two vectors may be compared. Based on the comparison, third text corresponding to a portion of the second vector may be generated and transmitted to a third computing device.

Abstract: Systems, methods, and apparatuses are described for determining compliance with a plurality of restrictions associated with one or more devices in an organization. First text indicating restrictions may be received, and second text indicating a current configuration of one or more devices may be received. Both sets of text may be processed by, e.g., removing a portion of the text based on a predetermined list of terms and simplifying the text using a lemmatization algorithm. A first vector and second vector may be generated based on the processed sets of text, and each vector may be weighted based on an inverse frequency of words in their respective text. Each vector may be normalized based on semantic analysis. The two vectors may be compared. Based on the comparison, third text corresponding to a portion of the second vector may be generated and transmitted to a third computing device.

Abstract: Methods and systems are described herein for merging datasets from multiple content domains for training a prediction model to predict a solution for a request related to a specific content domain. A dataset for a content domain may include requests and solutions organized as groups. For example, a dataset for a first content domain may include a first group having (a) a first set of requests (e.g., questions or queries) related to a first topic, and (h) a solution (e.g., an answer) associated with the first set of requests. The datasets of different content domains are analyzed based on context-based vector representations of the requests or solutions to determine the groups that are similar and merge those similar groups into a single merged group. A prediction model is trained with the merged groups for obtaining a prediction of a solution to any given request.

Abstract: Systems, methods, and apparatuses are described for determining compliance with a plurality of restrictions associated with one or more devices in an organization. First text indicating restrictions may be received, and second text indicating a current configuration of one or more devices may be received. Both sets of text may be processed by, e.g., removing a portion of the text based on a predetermined list of terms and simplifying the text using a lemmatization algorithm. A first vector and second vector may be generated based on the processed sets of text, and each vector may be weighted based on an inverse frequency of words in their respective text. Each vector may be normalized based on semantic analysis. The two vectors may be compared. Based on the comparison, third text corresponding to a portion of the second vector may be generated and transmitted to a third computing device.