Abstract: A method includes generating style values and experiential language tags (ELTs) for a plurality of books based on retrieved book content and reader reviews, respectively. The method further includes generating an ELT prediction model based on the style values and the ELTs. The ELT prediction model is configured to receive a set of style values for a new book and output a set of predicted ELTs for the new book, the set of predicted ELTs indicating predicted reader experiences with the new book. The method further includes receiving user-submitted book content from a remote user device, determining style values for the user-submitted book content, and determining a list of predicted ELTs for the user-submitted book content using the style values for the user-submitted book content and the ELT prediction model. Additionally, the method includes transmitting, to the user device, the list of predicted ELTs for the user-submitted book content.

Abstract: A method includes generating style values and experiential language tags (ELTs) for a plurality of books based on retrieved book content and reader reviews, respectively. The method further includes generating an ELT prediction model based on the style values and the ELTs. The ELT prediction model is configured to receive a set of style values for a new book and output a set of predicted ELTs for the new book, the set of predicted ELTs indicating predicted reader experiences with the new book. The method further includes receiving user-submitted book content from a remote user device, determining style values for the user-submitted book content, and determining a list of predicted ELTs for the user-submitted book content using the style values for the user-submitted book content and the ELT prediction model. Additionally, the method includes transmitting, to the user device, the list of predicted ELTs for the user-submitted book content.

Abstract: A method includes generating style values and experiential language tags (ELTs) for a plurality of books based on retrieved book content and reader reviews, respectively. The method further includes generating an ELT prediction model based on the style values and the ELTs. The ELT prediction model is configured to receive a set of style values for a new book and output a set of predicted ELTs for the new book, the set of predicted ELTs indicating predicted reader experiences with the new book. The method further includes receiving user-submitted book content from a remote user device, determining style values for the user-submitted book content, and determining a list of predicted ELTs for the user-submitted book content using the style values for the user-submitted book content and the ELT prediction model. Additionally, the method includes transmitting, to the user device, the list of predicted ELTs for the user-submitted book content.

Abstract: A method includes generating style values and experiential language tags (ELTs) for a plurality of books based on retrieved book content and reader reviews, respectively. The method further includes generating an ELT prediction model based on the style values and the ELTs. The ELT prediction model is configured to receive a set of style values for a new book and output a set of predicted ELTs for the new book, the set of predicted ELTs indicating predicted reader experiences with the new book. The method further includes receiving user-submitted book content from a remote user device, determining style values for the user-submitted book content, and determining a list of predicted ELTs for the user-submitted book content using the style values for the user-submitted book content and the ELT prediction model. Additionally, the method includes transmitting, to the user device, the list of predicted ELTs for the user-submitted book content.

Abstract: The technology described in this document is embodied in a method that includes processing data in a dataset that represents time-varying information about at least one pulse pressure wave propagating through blood in a subject acquired at a location of the subject. The method also includes determining whether one or more segments of the dataset were captured from a subject other than an expected subject by analyzing morphological features of the segments.

Abstract: The technology described in this document is embodied in a method that includes processing data in a first dataset that represents time-varying information about at least one pulse pressure wave propagating through blood in a subject acquired at a location of the subject. The method also includes providing information related to the data to a remote device.

Abstract: In certain embodiments, an apparatus comprises an input and one or more processors. The input receives known locations of wireless mobile nodes over a wireless link. The one or more processors determine geometric features associated with the locations, and calculate an apparatus location of the apparatus from the known locations and the geometric features.

Abstract: The technology described in this document is embodied in a method that includes processing data in a first dataset that represents time-varying information about at least one pulse pressure wave propagating through blood in a subject acquired at a location of the subject. The data is acquired while the subject is in a situation associated with risk indicated by the data.

Abstract: The technology described in this document is embodied in a method that includes processing data in a first dataset that represents time-varying information about at least one pulse pressure wave propagating through blood in a subject acquired at a location of the subject. The method also includes providing information related to the data to a remote device.

Abstract: The technology described in this document is embodied in a method that includes processing data in a dataset that represents time-varying information about at least one pulse pressure wave propagating through blood in a subject acquired at a location of the subject. The method also includes determining whether one or more segments of the dataset were captured from a subject other than an expected subject by analyzing morphological features of the segments.

Abstract: The technology described in this document is embodied in a method that includes processing data in a first dataset that represents time-varying information about at least one pulse pressure wave propagating through blood in a subject acquired at a location of the subject. The method also includes providing, based on the data, information about a medication regimen of the subject.

Abstract: The technology described in this document is embodied in a method that includes deriving a metric associated with a state of a subject, the state of the subject being one or more members selected from the group consisting of health, sleep, fitness, and stress. Deriving the metric is based on data in a first dataset that represents time-varying information about at least one pulse pressure wave propagating through blood in the subject acquired at a location of the subject.

Abstract: In certain embodiments, a first network device stores a security key associated with a second network device. The first network device computes access information according to the security key and a time value. The access information may be a network address or a port/socket. The first network device sends a packet to the second network device using the access information. The first network device then computes next access information according to the security key and a next time value and sends a packet to the second network device using the next access information.

Abstract: In certain embodiments, an apparatus comprises an input and one or more processors. The input receives known locations of wireless mobile nodes over a wireless link. The one or more processors determine geometric features associated with the locations, and calculate an apparatus location of the apparatus from the known locations and the geometric features.

Abstract: In certain embodiments, a first network device stores a security key associated with a second network device. The first network device computes access information according to the security key and a time value. The access information may be a network address or a port/socket. The first network device sends a packet to the second network device using the access information. The first network device then computes next access information according to the security key and a next time value and sends a packet to the second network device using the next access information.