Abstract: An imaging device is provided that may be used for visually inspecting structures. In one embodiment, the imaging device includes an image capture device; and a rail system having a stationary component connected to the image capture device and a sliding component for movement along a horizontal axis. The system can further include a jig structure engaged to the sliding component of the rail system. The jig structure may include a first mount location for engagement to a first type connector and a second mount location for engagement to a second type connector. The jig structure is engaged to the sliding component to position the housing so that the first and second mount locations are in line and parallel to a direction of travel along the horizontal axis including a point at which the first and second mount locations pass through the imaging location.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a machine learning model to generate embeddings of inputs to the machine learning model, the machine learning model having an encoder that generates the embeddings from the inputs and a decoder that generates outputs from the generated embeddings, wherein the embedding is partitioned into a sequence of embedding partitions that each includes one or more dimensions of the embedding, the operations comprising: for a first embedding partition in the sequence of embedding partitions: performing initial training to train the encoder and a decoder replica corresponding to the first embedding partition; for each particular embedding partition that is after the first embedding partition in the sequence of embedding partitions: performing incremental training to train the encoder and a decoder replica corresponding to the particular partition.

Abstract: A computer-implemented method includes accessing data from distinct data domains corresponding to different data sources, and determining a core dimension of the accessed data common to first and second distinct data domains. The method further includes generating a data set from the data sources using a columnar data generation engine, and deriving, from the data set via stateless processing, a first guided page including actionable elements depicting data derived from the first distinct data domain. The method further includes responsive to a user interaction with one of the actionable elements, providing, dependent on the common core dimension, direct navigation from the first to the second distinct data domain, and predicting, from the data set based on machine learning and prior to the user interaction, a second guided page that depicts data derived from the second distinct data domain and is presented responsive to the direct navigation.

Abstract: Assisted analytics, facilitates responding to a user selection of a measure that is calculated from a data set that is characterized by a plurality of dimensions of data, populating, with a processor a set of dimensions of the data with dimensions that contribute at least one data value to the user selected measure by calculating, for each dimension of the data in the set of dimensions of data a measure outlier threshold for a set of timeframe-specific values of the measure. This outlier threshold is applied, for each dimension of the data in the set of dimensions of data to calculate a dimension-specific outlier factor by aggregating timeframe-specific outlier weights for each timeframe in which a timeframe-specific value in the set of timeframe-specific values exceeds the measure outlier threshold. The results of this aggregation can be displayed in a ranked list of dimensions based on the dimension-specific outlier factor.

Abstract: A method of securing a computer resource against unauthorized access includes sending, by a processing device, a challenge data structure to a user computer system, obtaining a user response representing at least one user-selected image from the plurality of images, and providing access to the computer resource for the user computer system based on whether the at least one user-selected image is consistent with the one or more correct images. The challenge data structure defines a challenge to be presented to a user of the user computer system. The challenge involves selecting one or more correct images that conform to one or more aspects of a challenge key from a plurality of images based on a relative orientation with respect to one another of elements within the plurality of images.

Abstract: In embodiments, an authentication server interfaces between a user device with a self-signed certificate and a verifying computer that accepts a user name and password. The user device generates a self-signed certificate signed by a private key on the user device. The self-signed certificate is transmitted to a verifying party computer over a network. The verifying party stores the self-signed certificate with user identification data. The user migrates trust to another device by providing the root certificate and intermediate certificate as a certificate chain to a second device, which then adds a new intermediate certificate to create a longer certificate chain with the same root certificate. In subsequent communications, the verifying party receives a certificate chain including the self-signed certificate from the second user device, and matches that with the user identification data stored in a database.

Abstract: A snow and ice removal device may include one or more, heating elements. A control unit may be configured to control the heating element to produce heat. A power source may be in electrical communication with the control unit and the heating element. Heat may be applied to the roof surface by the heating element to loosen and/or melt accumulated ice or snow from the roof surface of the vehicle.

Abstract: A method of providing a frame-based mel spectral representation of speech includes receiving a text utterance having at least one word and selecting a mel spectral embedding for the text utterance. Each word has at least one syllable and each syllable has at least one phoneme. For each phoneme, the method further includes using the selected mel spectral embedding to: (i) predict a duration of the corresponding phoneme based on corresponding linguistic features associated with the word that includes the corresponding phoneme and corresponding linguistic features associated with the syllable that includes the corresponding phoneme; and (ii) generate a plurality of fixed-length predicted mel-frequency spectrogram frames based on the predicted duration for the corresponding phoneme. Each fixed-length predicted mel-frequency spectrogram frame represents mel-spectral information of the corresponding phoneme.

Abstract: In embodiments, an authentication server interfaces between a user device with a self-signed certificate and a verifying computer that accepts a user name and password. The user device generates a self-signed certificate signed by a private key on the user device. The self-signed certificate is transmitted to a verifying party computer over a network. The verifying party stores the self-signed certificate with user identification data, including at least one of a user name, user address, user email, user phone number, user tax ID, user social security number and user financial account number. In subsequent communications, the verifying party receives a certificate chain including the self-signed certificate, and matches that with the user identification data stored in a database.

Abstract: The disclosure provides methods and systems for analyzing genotype data. In some embodiments, a computer-implemented method comprises receiving data relating to one or more phenotypes of a subject or family members thereof, and ranking genes based on their association score with one or more phenotypes. Next, an output of the data is generated, the output comprising a comparison of the data based on the association score. The comparison can be in at least one of numeric and graphic form.

Abstract: A method includes receiving an input text utterance to be synthesized into expressive speech having an intended prosody and a target voice and generating, using a first text-to-speech (TTS) model, an intermediate synthesized speech representation for the input text utterance. The intermediate synthesized speech representation possesses the intended prosody. The method also includes providing the intermediate synthesized speech representation to a second TTS model that includes an encoder portion and a decoder portion. The encoder portion is configured to encode the intermediate synthesized speech representation into an utterance embedding that specifies the intended prosody. The decoder portion is configured to process the input text utterance and the utterance embedding to generate an output audio signal of expressive speech that has the intended prosody specified by the utterance embedding and speaker characteristics of the target voice.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a machine learning model to generate embeddings of inputs to the machine learning model, the machine learning model having an encoder that generates the embeddings from the inputs and a decoder that generates outputs from the generated embeddings, wherein the embedding is partitioned into a sequence of embedding partitions that each includes one or more dimensions of the embedding, the operations comprising: for a first embedding partition in the sequence of embedding partitions: performing initial training to train the encoder and a decoder replica corresponding to the first embedding partition; for each particular embedding partition that is after the first embedding partition in the sequence of embedding partitions: performing incremental training to train the encoder and a decoder replica corresponding to the particular partition.

Abstract: A method includes obtaining training data including a plurality of training audio signals and corresponding transcripts. Each training audio signal is spoken by a target speaker in a first accent/dialect. For each training audio signal of the training data, the method includes generating a training synthesized speech representation spoken by the target speaker in a second accent/dialect different than the first accent/dialect and training a text-to-speech (TTS) system based on the corresponding transcript and the training synthesized speech representation. The method also includes receiving an input text utterance to be synthesized into speech in the second accent/dialect. The method also includes obtaining conditioning inputs that include a speaker embedding and an accent/dialect identifier that identifies the second accent/dialect.

Abstract: Consumer needs for life insurance benefits change over time, yet traditional individual insurance policies have a fixed death benefit. Embodiments disclosed herein are directed to a system and method for administering life insurance policies with death benefits that are automatically, periodically adjusted, without requiring new underwriting, based on third-party data linked to the insured's specific life insurance need. Embodiments disclosed herein facilitate the alignment of life insurance benefits with an individual's need as those needs change over time regardless of their changing health status, ensuring coverage when the need increases while saving money on unnecessary premiums when the need is declining.

Abstract: A ground reaction force plate apparatus and measuring system are provided. The apparatus includes a plate for receiving a force to be measured as applied by a subject to the plate and a plurality of load cells in an arrangement supporting the plate, each load cell being a single-axis sensor with the axis provided at an angle to a plane of the plate and oriented towards a centre of the plate. The load cells are configured to measure data relating to a force vector at the angled single-axis sensor when the subject applies a force to the plate. A data collection controller is provided for logging time series measurements of the load cells over a time in which the subject applies a force to the plate. The system applies machine learning processing to output the load cell measurements as a three-dimensional ground reaction force on the plate by a subject.

Abstract: A method includes receiving an input text utterance to be synthesized into expressive speech having an intended prosody and a target voice and generating, using a first text-to-speech (TTS) model, an intermediate synthesized speech representation tor the input text utterance. The intermediate synthesized speech representation possesses the intended prosody. The method also includes providing the intermediate synthesized speech representation to a second TTS model that includes an encoder portion and a decoder portion. The encoder portion is configured to encode the intermediate synthesized speech representation into an utterance embedding that specifies the intended prosody. The decoder portion is configured to process the input text utterance and the utterance embedding to generate an output audio signal of expressive speech that has the intended prosody specified by the utterance embedding and speaker characteristics of the target voice.

Abstract: A computer-implemented method includes accessing data from distinct data domains corresponding to different data sources, and determining a core dimension of the accessed data common to first and second distinct data domains. The method further includes generating a data set from the data sources using a columnar data generation engine, and deriving, from the data set via stateless processing, a first guided page including actionable elements depicting data derived from the first distinct data domain. The method further includes responsive to a user interaction with one of the actionable elements, providing, dependent on the common core dimension, direct navigation from the first to the second distinct data domain, and predicting, from the data set based on machine learning and prior to the user interaction, a second guided page that depicts data derived from the second distinct data domain and is presented responsive to the direct navigation.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a machine learning model to generate embeddings of inputs to the machine learning model, the machine learning model having an encoder that generates the embeddings from the inputs and a decoder that generates outputs from the generated embeddings, wherein the embedding is partitioned into a sequence of embedding partitions that each includes one or more dimensions of the embedding, the operations comprising: for a first embedding partition in the sequence of embedding partitions: performing initial training to train the encoder and a decoder replica corresponding to the first embedding partition; for each particular embedding partition that is after the first embedding partition in the sequence of embedding partitions: performing incremental training to train the encoder and a decoder replica corresponding to the particular partition.

Abstract: Methods for electrochemically oxidizing organic compounds in aqueous solution. The methods include contacting an aqueous solution comprising organic compounds with a first anode and electrochemically oxidizing at least a portion of the organic compounds to provide a first aqueous solution comprising oxidation products; and contacting the first aqueous solution comprising oxidation products with a first cathode and electrochemically reducing at least a portion of the oxidation products to provide a first aqueous solution comprising reduced products and residual oxidizable organic compounds.

Abstract: A computer-implemented method includes generating, via a multi-user business collaboration platform, at least one guided navigation page based at least in part on data used to measure a goal associated with a workflow of a business. The method further includes facilitating direct navigation among a plurality of data domains in response to a user selection of one of a plurality of displayable actionable elements each associated with at least one core dimension of information predetermined to be pertinent to the continuation of the workflow of the business. The method further includes applying goal attainment algorithms to at least a portion of the data and recommending a candidate collaboration project in a user interface of the multi-user business collaboration platform. The candidate collaboration project includes team members selected from a list of team members associated with the workflow for the business.