Abstract: A method of determining if a commit is problematic includes determining a complexity of the commit; determining an author of the commit; determining an experience of the author; determining a component affected by the commit; and assigning a risk value to the commit based on the complexity, the author, the experience of the author and the component affected.

Abstract: A method for testing commits from a third-party product into a dependent product includes receiving a first commit from a third-party product; waiting for additional commits from the third-party product; receiving a second commit from the third-party product; testing the first and second commit using a pre-trained learning model; determining if the first commit is problematic, and if the first commit is problematic, sending the first commit for review before implementation; and determining if the second commit is problematic, and if the second commit is problematic, sending the second commit for review before implementation. Accumulating the first and second commits for testing at once reduces system resources.

Abstract: A method for creating a learning model that evaluates risks of applying commits in a third-party product to a dependent product is disclosed. The method includes collecting data on past commits; training the learning model using the collected data; and using the learning model to determine if future commits are problematic.

Abstract: A method for alerting a community to potential problematic commits includes receiving a commit submitted by an author in a project; testing the commit using a pre-trained learning model; and determining if the commit is problematic, and if the commit is problematic, sending a report in the project outlining the level of risk of implementing the commit and a reason for the level or risk. Users of the project will be alerted to potential risk of particular commits.

Abstract: A computer implemented method of training a user to perform a task includes receiving task data from a user device; identifying a task associated with the task data; querying a knowledgebase for data associated with the task; generating an AR pattern for training the user to perform the task; and transmitting the AR pattern to the user device. An augmented reality training system includes a computer device connected to a user device having a video camera. The computer device receives the video data from the video camera and identifies a task from the digital video data. A knowledgebase is connected to the computer device. The knowledgebase contains resources related to the task. The system identifies a task to be performed, queries the knowledgebase for resources and creates an augmented reality pattern with an avatar from the resources for training a user.

Abstract: An artificially intelligent method includes the steps of monitoring, by a processor, information sources to identify primary semantic information; capturing, by the processor, the primary semantic information; reformatting, by the processor, the primary semantic information according to a predetermined format; analyzing, by the processor, the primary semantic information to establish secondary semantic information; and establishing, by the processor, ontologies from the primary, secondary, and additional secondary semantic information.

Abstract: A method of creating a trained database from a document corpus includes creating a tailored neural network for the document corpus by using sentences to create word-level association and sentence-level association; and applying action-trigger phrase sets, created front the document corpus independent of creating the tailored neural network, to the tailored neural network to create a trained database; wherein processing a query through the trained database, rather than the document corpus, increases the speed of processing the query and increases the accuracy of the result.

Abstract: An approach to information retrieval is contemplated for facilitating semantic search and response over a large domain of technical documents is disclosed. First, the grammar and morphology of the statements and instructions expressed in the technical documents is used to filter training data to extract the text that is most information-rich, that is the text that contains domain-specific jargon, in context. This training data is then vectorized and fed as input to an SBERT neural network model that learns an embedding of related words and terms in the text, i.e. the relationship between a given set of words contained in a user's query and the instructions from the technical documentation text most likely to assist in the user's operations. There are two parsing tasks. The first is to select a minimal sample of sentences from the document corpus that capture the domain-specific terminology (jargon). The result is set of sentences used to train BERT and SBERT.

Abstract: A method of parsing implicit tables within a document includes parsing, by a processor, a document to determine a pattern for a set of text that sets apart the information contained therein from the rest of the text; determining, by the processor, from the pattern of spacing, a first descriptive phrase and a second descriptive phrase; and assigning, by the processor, the first descriptive phrase as an action and the second descriptive phrase as a trigger.

Abstract: A computing system architecture includes a service server and a first validator. The first validator is communicable to the service server. A validation request is sent from the service server to the first validator for validating a transaction. The validation request including a first facial image of a party of the transaction. The validator performs a facial recognition using the first facial image of the party for validating the transaction.

Abstract: A security system includes a camera having a field of vision. The camera sends image frames to a machine readable memory. A processor is accessible to the machine readable memory. The processor performs acts of receiving from the camera a plurality of frames; detecting an object entering the field of vision; determining whether the object is a person; tracking a moving path of the person; and performing facial recognition on the person using at least one of the plurality of frames.

Abstract: A security system includes a camera having a field of vision. The camera sends image frames to a machine readable memory. A processor is accessible to the machine readable memory. The processor performs acts of receiving from the camera a plurality of frames; detecting an object entering the field of vision; determining whether the object is a person; tracking a moving path of the person; and performing facial recognition on the person using at least one of the plurality of frames.

Abstract: A transceiver includes a computing device having shortwave TCP/IP and hotspot capabilities enabling the computing device to communicate via shortwaves with a base station connected to the Internet and to connect to user devices. An user device can use the computing device to communicate over the Internet via shortwaves on an existing Ham Radio Network. A system for establishing communications between an user device and the Internet includes a shortwave base station have TCP/IP capabilities and connected to the Internet. The system also includes an user device and a computing device having shortwave TCP/IP and hotspot capabilities enabling the computing device to communicate via shortwaves with the base station and to connect to the user device. The user device can use the computing device to communicate over the Internet via shortwaves on an existing Ham Radio Network.

Abstract: A traffic monitoring system includes a first car moving on a first path; a camera having a field of vision including at least a portion of the first path; and a computing system. The computing system receives a plurality of images from the camera. The computing system has a processor. When instructed, the processor performs circling a perimeter of the first car on each of the images with a first rectangle; composing a first set of points, each point of the first set of points representing a center of the first rectangle; finding a first centroid using the first set of points, wherein the first centroid represents the first path; and calculating a speed of the first car using the first centroid.

Abstract: A method and system for delivering announcement broadcasts. The method includes receiving an announcement broadcast from a broadcast system of a transportation station. The method also includes interpreting the received announcement broadcast using natural language processing to extract transportation information. The method also includes the received announcement broadcast and the extracted transportation information in a data storage location. The method also includes translating the stored announcement broadcast into a text message. The method also includes transmitting the text message to at least one mobile device of at least one user registered with the announcement broadcast delivery method, based on the transportation information and the user information stored in the data storage location.

Abstract: A traffic monitoring system includes a first car moving on a first path; a camera having a field of vision including at least a portion of the first path; and a computing system. The computing system receives a plurality of images from the camera. The computing system has a processor. When instructed, the processor performs circling a perimeter of the first car on each of the images with a first rectangle; composing a first set of points, each point of the first set of points representing a center of the first rectangle; finding a first centroid using the first set of points, wherein the first centroid represents the first path; and calculating a speed of the first car using the first centroid.

Abstract: A security system includes a camera having a field of vision. The camera sends image frames to a machine readable memory. A processor is accessible to the machine readable memory. The processor performs acts of receiving from the camera a plurality of frames; detecting an object entering the field of vision; determining whether the object is a person; tracking a moving path of the person; and performing facial recognition on the person using at least one of the plurality of frames.

Abstract: A computing system architecture includes a service server and a first validator. The first validator is communicable to the service server. A validation request is sent from the service server to the first validator for validating a transaction. The validation request including a first facial image of a party of the transaction. The validator performs a facial recognition comparing the first facial image with a second facial image using a facial recognition algorithm.

Abstract: A computing system architecture includes a service server and a first validator. The first validator is communicable to the service server. A validation request is sent from the service server to the first validator for validating a transaction. The validation request including a first facial image of a party of the transaction. The validator performs a facial recognition using the first facial image of the party for validating the transaction.

Abstract: A traffic monitoring system includes a first car moving on a first path; a camera having a field of vision including at least a portion of the first path; and a computing system. The computing system receives a plurality of images from the camera. The computing system has a processor. When instructed, the processor performs circling a perimeter of the first car on each of the images with a first rectangle; composing a first set of points, each point of the first set of points representing a center of the first rectangle; finding a first centroid using the first set of points, wherein the first centroid represents the first path; and calculating a speed of the first car using the first centroid.