Abstract: A heuristic engine includes capabilities to collect an unstructured data set and a current business context. Providing a heuristic algorithm, executing within the engine, with the data set and the context may allow determination of predicted future contexts and subsequent actions that refine and improve the quality of service provided to a customer. Such heuristic algorithms may learn from past data transactions and appropriate correlations with events and available data.

Abstract: In a computer-implemented method of facilitating detection of document-related fraud, fraudulent document detection rules may be generated or updated by training a machine learning program using image data corresponding to physical documents, and fraud determinations corresponding to the documents. The documents and fraudulent document detection rules may correspond to a first type of document. Image data corresponding to an image of one of the physical documents may be received, where the physical document corresponds to the first type of document. By applying the fraudulent document detection rules to the image data, it may be determined that the physical document is, or may be, fraudulent. An indication of whether the physical document is, or may be, fraudulent may be displayed to one or more people via one or more respective computing device user interfaces.

Abstract: A system and computer-implemented method for approving a dynamic mortgage application. In one aspect, the method may include determining a customer is approved for a mortgage and determining a real estate property is mortgage ready, including calculating an appraisal value for the real estate property based upon the information about the real property retrieved from a computer file or memory location/address (such as by using a machine learning or artificial intelligence algorithm). The method may still further include comparing the calculated amount the customer is approved for a mortgage loan with the calculated appraisal value of the real estate property; and approving the mortgage application of the customer for the real estate property when the calculated amount the customer is approved for the mortgage loan meets, or exceeds, the calculated appraisal value of the real estate property.

Abstract: A method of reducing a future amount of electronic fraud alerts includes receiving data detailing a financial transaction, inputting the data into a rules-based engine that generates an electronic fraud alert, transmitting the alert to a mobile device of a customer, and receiving from the mobile device customer feedback indicating that the alert was a false positive or otherwise erroneous. The method also includes inputting the data detailing the financial transaction into a machine learning program trained to (i) determine a reason why the false positive was generated, and (ii) then modify the rules-based engine to account for the reason why the false positive was generated, and to no longer generate electronic fraud alerts based upon (a) fact patterns similar to fact patterns of the financial transaction, or (b) data similar to the data detailing the financial transaction, to facilitate reducing an amount of future false positive fraud alerts.

Abstract: A computer-implemented method of continuously updating information about a customer approved for a mortgage, the customer associated with a customer identification number. In one aspect, the method may include monitoring information accessed from a blockchain corresponding to the customer identification number, the information used to determine the customer is approved for a mortgage. In addition, the method may further include receiving new information about the customer, the new information used to determine the customer is approved for a mortgage. Further, the method may include updating a block of the blockchain to include the new information and recalculating the amount in which the customer is approved for a mortgage based upon the new information received.

Abstract: Embodiments of the present invention provides a system and method of hoodie assembly. The assembly includes a sweater having a hood member, a releasable visor coupled to the hood member and configured to extend outward from the hood member, an attachment portion in communication with a back edge of the visor, and an attachment member coupled to the attachment portion and the hood member.

Abstract: In a method of preventing fraudulent online financial transactions, a request to authorize an online, financial transaction may be received, where the transaction is associated with a debit or credit card account. A computing device at which information associated with the debit or credit card account was entered for the transaction may be identified, and a first geographic location at which the computing device resides may be determined. Based upon geolocation data indicating one or more geographic locations of the authorized cardholder, it may be determined that the authorized cardholder was at a second geographic location at a time of the transaction. If the second geographic location does not correspond to the first geographic location, the financial transaction may be prevented from being executed.

Abstract: A video collection system comprising a body-wearable video camera, a camera dock, and a video collection manager. The camera dock is configured to interface with the body-wearable video camera having a camera-memory element. The camera dock includes a dock-memory element configured to receive and store video data from the camera-memory element. The video collection manager is communicatively coupled with the camera dock. The camera dock sends at least a portion of the video data to the video collection manager.

Abstract: A method of reducing a future amount of electronic fraud alerts includes receiving data detailing a financial transaction, inputting the data into a rules-based engine that generates an electronic fraud alert, transmitting the alert to a mobile device of a customer, and receiving from the mobile device customer feedback indicating that the alert was a false positive or otherwise erroneous. The method also includes inputting the data detailing the financial transaction into a machine learning program trained to (i) determine a reason why the false positive was generated, and (ii) then modify the rules-based engine to account for the reason why the false positive was generated, and to no longer generate electronic fraud alerts based upon (a) fact patterns similar to fact patterns of the financial transaction, or (b) data similar to the data detailing the financial transaction, to facilitate reducing an amount of future false positive fraud alerts.

Abstract: A pump includes a signal processor that receives signaling containing information about a low level of a liquid sensed in an appliance reservoir to be supplied to an appliance that uses the liquid to dispense a flavored beverage, and also about when the appliance reservoir is refilled based upon an indication that forms part of an appliance reservoir refill level calibration procedure programmed by an appliance user; and determines corresponding signaling containing information about automatically refilling the liquid in the appliance reservoir, based upon the signaling received.

Abstract: A method of detecting whether electronic fraud alerts are false positives includes receiving data detailing a financial transaction, inputting the data into a rules-based engine that determines whether to generate an electronic fraud alert for the financial transaction based upon the data, and, when an electronic fraud alert is generated, inputting the data into a machine learning program trained to identify one or more facts indicated by the data. The method may also include determining whether the identified facts can be verified by customer data and, in response to determining that the facts can be verified, retrieving or receiving first customer data. The method may further include verifying that the electronic fraud alert is not a false positive based upon analysis of the first customer data, and transmitting the verified electronic fraud alert to a mobile device of the customer to alert the customer to fraudulent activity.

Abstract: A heuristic money laundering detection engine includes capabilities to collect an unstructured data set, such as a transaction record, and detect indications of money laundering activity. By detecting money laundering activity and feeding back indications of money laundering transactions, the heuristic algorithm may continue to learn and improve detection accuracy. Such indications may include correlations to sets of transaction activity among a number of financial accounts and past indications of money laundering activity. Indications of money laundering may allow generation of audit reports for reporting to regulatory authorities.

Abstract: A method of using browsing activity to identify fraudulent online or virtual applications includes receiving a virtual application over one or more radio frequency links, determining an applicant name on the virtual application, determining an IP address of a source computer from which the virtual application originated, determining an online browsing or search history associated with the IP address, determining whether the online browsing or search history indicates recent Internet searches for the applicant name, and, in response to determining that the online browsing or search history does indicate recent Internet searches for the applicant name, flagging the virtual application as fraudulent and generating an electronic alert indicating that the virtual application is fraudulent to facilitate identifying fraudulent virtual applications for goods or services.

Abstract: A heuristic engine includes capabilities to collect an unstructured data set and detect instances of transaction fraud in a financial account. By providing a heuristic algorithm with unstructured transaction sets and indications of particular instances of transactions that correlate with past fraudulent activity allows prevention of future occurrences of fraud. Such heuristic algorithms may learn from past indications of fraudulent activity and improve accuracy of detection of future fraud detections.

Abstract: A heuristic engine includes capabilities to collect an unstructured data set, including document image data and correlate the image data with known valid data to detect document fraud. Notifications of fraud detection may include particular signature images, or characteristics of a document image. By feeding back indications of document fraud with correlations to past instances of fraud into the heuristic algorithm, the algorithm may learn and improve in fraud detection accuracy.

Abstract: A plant growing system includes an outer shell, the outer shell being biodegradable, a rooting material, the rooting material comprising external ribbing, the external ribbing forming gaps between the outer shell and the rooting material when the rooting material is inserted in the outer shell, and one or more of a fertilizer, a nutrient, or a seed. The outer shell and the rooting material form a water reservoir, the water reservoir in communication with the gaps and, prior to the plant growing system being watered, comprising the fertilizer or nutrient.

Abstract: A heuristic engine includes capabilities to collect an unstructured data set and a current business context to calculate a credit worthiness score. Providing a heuristic algorithm, executing within the engine, with the data set and the context may allow determination of predicted future contexts and recommend subsequent actions, such as assessing a credit risk of a customer transaction and reducing the risk of customer transactions by processing the available data. Such heuristic algorithms may learn from past data transactions and appropriate correlations with events and available data.

Abstract: Systems and methods for controlling the motion of an autonomous are provided. In one example embodiment, a method includes obtaining, by one or more computing devices on-board an autonomous vehicle, state data descriptive of a current state of an object that is proximate to the autonomous vehicle. The method includes determining, by the one or more computing devices, one or more features associated with the object based at least in part on the state data. The method includes determining, by the one or more computing devise, a vehicle action for the autonomous vehicle based at least in part on a machine-learned model and the one or more features associated with the object. The vehicle action includes stopping a motion of the autonomous vehicle or moving the autonomous vehicle past the object.

Abstract: A portable electronic device holder, separate from an aircraft tray table, has a spring biased lower retention portion with lower retention plates for securing a lower edge of a portable electronic device. The lower retention plate acts in concert with either one or more ridges molded into or affixed to a recess in a seat back panel, or with a spring biased, extendable upper retention portion with an upper retention plate to hold the portable electronic device in place.

Abstract: A heuristic cross-selling recommendation engine includes capabilities to collect an unstructured data set and a current business context to suggest marketing actions. By providing a heuristic algorithm and executing the algorithm within the engine with the data set allows determination of predicted future contexts and optimal marketing actions. Such heuristic algorithms may learn from past marketing transactions and appropriate correlations with events and available data.