Abstract: A system is provided for computing and tracking resource state changes using a multichain distributed register technology. In particular, the system may comprise an index distributed register that may be stored across a plurality of distributed register nodes. The index distributed register may comprise one or more resource-specific data records that may in turn make up a resource-specific distributed register originating from the index distributed register. The resource-specific distributed register may comprise an initial data record that defines the attributes of the resource, and one or more subsequent data records that may be linked with the initial data record to reflect changes in the state of the resource to be tracked. Based on the data within each of the resource-specific distributed register, the system may compute resource analysis scores and/or trigger real-time user alerts.

Abstract: The present disclosure details systems, computer program products, and methods for machine engine analysis of network interaction data to identify conflicts. This involves the activation of an intelligence engine that connects to a backend data engine to access a database of conflict of interest (COI) datasets. The intelligence engine analyzes incoming applicant data and the COI datasets to identify potential conflicts. The identified conflicts are validated using stochastic metrics via a rules engine. A quantifiable probability metric is calculated, representing the probability of conflict from both organizational and individual perspectives. Based on the potential conflict of interest, a recommendation is generated that aligns with the calculated probability. The system then provides recommendations via API or on a user interface that is communicatively coupled to the processor.

Abstract: Big data searches, statistical computation and artificial intelligence is leveraged to determine the likelihood that a user will renounce an object post-resource event. Specifically, the present invention relies on object-identifying data and user data to key a plurality of data mining searches of big data sources. In response to extracting responsive data from the big data sources, the present invention implements statistical computing to determine a go/no-go indicator that indicates either that (i) the user is unlikely to renounce (i.e., abandon, fail to use and/or return) the object post-resource event, or (ii) the user is likely to renounce (i.e., abandon, fail to use and/or return) the object post-resource event. Artificial Intelligence (AI) is used to analyze previous likelihood of renunciation determinations to determine a confidence level which is used in the statistical computation of the go/no-go indicator.

Abstract: A system is provided for an artificial intelligence-based engine for generating recommendations for resource allocation. In particular, the system may comprise an artificial intelligence module configured to access one or more data sources containing resource data associated with one or more users. Based on the resource data, the system may identify a group of analogous users with respect to a specific user. The system may then generate one or more recommendations for a resource allocation associated with the user. The one or more recommendations may then be presented on a graphical interface of a user device associated with the user. In this way, the system may provide an AI-driven method for efficient allocation of resources.

Abstract: Big data searches, statistical computation and artificial intelligence is leveraged to determine the likelihood that a user will renounce an object post-resource event. Specifically, the present invention relies on object-identifying data and user data to key a plurality of data mining searches of big data sources. In response to extracting responsive data from the big data sources, the present invention implements statistical computing to determine a go/no-go indicator that indicates either that (i) the user is unlikely to renounce (i.e., abandon, fail to use and/or return) the object post-resource event, or (ii) the user is likely to renounce (i.e., abandon, fail to use and/or return) the object post-resource event. Artificial Intelligence (AI) is used to analyze previous likelihood of renunciation determinations to determine a confidence level which is used in the statistical computation of the go/no-go indicator.

Abstract: Big data searches, statistical computation and artificial intelligence are leveraged to determine the likelihood that a user will renounce a facility or service post-acceptance. Specifically, the present invention relies on facility/service data and/or user data to key a plurality of data mining searches of big data sources. In response to extracted responsive data from the big data sources, the present invention implements statistical computing along with machine learning/Artificial Intelligence techniques to determine a go/no-go indicator that indicates either (i) the user is unlikely to renounce (i.e., abandon, fail to use and/or return) the facility or service post-acceptance/acquisition, or (ii) the user is likely to renounce the facility/service.

Abstract: A method and apparatus for generating frames for communicating over a network are provided. The method includes: receiving input signals and signal information comprising at least one from among new signal information, existing data dictionary information, and topology information, determining frame packing rules based on the received signal information, and generating frames of output data based on the determined frame packing rules. The method may be used to package vehicle controller area network messages for transmission over other networks.

Abstract: A method of automatically administering servers is disclosed. The method includes automatically transmitting commands to at least one of the servers. Administrator level access is non-invasively obtained on the at least one of the servers utilizing the automatically transmitted commands. The at least one of the servers is administered using the administrator level access and the automatically transmitted commands.

Abstract: A method of automatically administering servers is disclosed. The method includes automatically transmitting commands to at least one of the servers. Administrator level access is non-invasively obtained on the at least one of the servers utilizing the automatically transmitted commands. The at least one of the servers is administered using the administrator level access and the automatically transmitted commands.

Abstract: According to one embodiment of the invention, method of automatically administering a plurality of servers includes automatically transmitting commands to at least one of the plurality of servers. Administrator level access is non-invasively obtained on the at least one of the plurality of the servers utilizing the automatically transmitted commands. The at least one of the plurality of the servers is administered using the administrator level access and the automatically transmitted commands.

Abstract: A system and method for compartmentalizing memory sections in a controller to allow compartments to be individually reprogrammed without affecting files in other compartments. The method includes defining a main memory in the controller that stores a plurality of different types of content files that each include lines of code, where the main memory includes compartments having memory slots for lines of code that have been programmed and empty memory slots where lines of codes can be written into. The main memory is initially programmed to store desired content files in the memory compartments. Subsequently, if it is determined that code stored in the main memory needs to be reprogrammed, the reprogramming is performed to flash only the memory compartments that include the code that needs to be reprogrammed and those memory compartments that include code that is linked to the code that needs to be reprogrammed.

Abstract: A method and apparatus for providing a Medicare Part D Pharmacy Benefits Calculator. A computer user inputs data for prescriptions to be purchased by a prospective insured for a plan period. The prescription data includes a quantity, a days supply, and a number of fills. The data for each prescription the user enters is used to calculate anticipated out-of-pocket costs for the prescriptions for one or more pharmacy benefits plans available to the prospective insured. The cost data is presented to the user in a way that illustrates how out-of-pocket costs will vary over the course of a plan period. The user may view costs for alternative drugs and alternatives sources of drugs. The user may vary and expand the presentation of the cost data to better understand the available plan benefits. The invention helps prospective insureds decide among alternative Medicare Part D pharmacy benefits plans offered by one or more insurance companies.

Abstract: A method and apparatus for providing a Medicare Part D Pharmacy Benefits Calculator. A computer user inputs data for prescriptions to be purchased by a prospective insured for a plan period. The prescription data includes a quantity, a days supply, and a number of fills. The data for each prescription the user enters is used to calculate anticipated out-of-pocket costs for the prescriptions for one or more pharmacy benefits plans available to the prospective insured. The cost data is presented to the user in a way that illustrates how out-of-pocket costs will vary over the course of a plan period. The user may view costs for alternative drugs and alternatives sources of drugs. The user may vary and expand the presentation of the cost data to better understand the available plan benefits. The invention helps prospective insureds decide among alternative Medicare Part D pharmacy benefits plans offered by one or more insurance companies.

Abstract: A method and apparatus for providing a Medicare Part D Pharmacy Benefits Calculator. A user inputs data for prescriptions to be purchased by a prospective insured for a plan period. The prescription data includes a quantity, a days supply, and a number of fills. The data for each prescription the user enters is used to calculate anticipated out-of-pocket costs for the prescriptions for one or more pharmacy benefits plans available to the prospective insured. The cost data is presented to the user in a way that illustrates how out-of-pocket costs will vary over the course of a plan period. The user may view costs for alternative drugs and alternatives sources of drugs. The user may vary and expand the presentation of the cost data to better understand the available plan benefits. The invention helps prospective insureds decide among alternative Medicare Part D pharmacy benefits plans offered by one or more insurance companies.

Abstract: A non-carbon black pigment blend is mixed with a coating layer of an optical fiber to provide a black appearing colored optical fiber. The pigment blend does not absorb UV light and is formed by blending three primary colors including red, blue and yellow. The combination of these three primary colors creates a black appearing colored secondary coating. The proportions of the primary colors are controlled to provide the desired shade of black with, in general, no one coloration of pigment exceeding 45% by weight of the total pigment added to the secondary coating. The pigment blend may further include white pigment to provide a slate tone black appearing color. The proportion of white pigment, in general, not exceeding 10 percent by weight of the total pigment added to the secondary coating. The pigment is mixed as a concentrate which is added to a secondary coating layer for application to the optical fiber.