Abstract: Examples of a record generation system are provided. The system may receive a record generation requirement from a user. The system may obtain record data, a plurality of user documents, and identify a record corpus from the record data. The system may sort the record data into a plurality of data domains. The system may determine at least one record mapping context including a record value from the plurality of user documents. The system may determine a selection rule from the plurality of data domains for each of the record mapping context. The system may create a record index corresponding to the plurality of user documents. The system may create a record generation model corresponding to the record generation requirement based on the record index. The system may generate a record generation result corresponding to the record generation requirement comprising the relevant record generation model.

Abstract: A system includes a security controller located within a central-zone in communication with a provisioned agent operating on an edge-zone device. The security controller may implement controller-blind security control on the edge-zone device by making security authorization determinations using a secure-operation confidence analysis performed by the provisioned agent. The provisioned agent, operating within the edge-zone, may have access to un-sanitized data, which may be unavailable to the security controller in the central-zone. The provisioned agent may access condition-descriptors via a secure-operation confidence assignment matrix. Using the condition-descriptors, the provisioned agent determine feedback, which may include a secure-operation confidence coefficient, based on the un-sanitized data to which the security controller is blind.

Abstract: A digital content management system for using an enterprise resource planning (ERP) system converted from a legacy ERP using a shell conversion technique is provided. The system may include a final-converted ERP that communicates with one or more servers and one or more data stores in a network.

Abstract: Implementations are directed to receiving delivery order data for delivery of the tangible asset, the delivery order data including a unique identifier associated with a mobile device of a recipient, receiving evidence data from the mobile device of the recipient, providing an order record stored in a distributed ledger system, the order record including at least a portion of the delivery order data, and the evidence data, determining that the tangible asset is to be handed over to the recipient, and in response: collecting delivery evidence data, providing the delivery evidence data for comparison to the evidence data, and receiving a validation result based on the comparison, and selectively indicating that the tangible asset has been handed over to the recipient at least partially based on the validation result, and updating the order record stored in the distributed ledger system.

Abstract: A device may receive issue resolution information, associated with a cognitive model, including an item of issue resolution information that describes an issue and a resolution to the issue. The device may assign the item of issue resolution information to a domain hierarchy, where the assigning is associated with a first user. The device may generate a question and an answer corresponding to the item of issue resolution information, where the generating of the question and the answer is associated with a second user. The device may approve the question and the answer, where the approving is associated with a third user. The device may generate a question/answer (QA) pair for the question and the answer. The device may create a data corpus including the QA pair, and provide the data corpus to cause the cognitive model to be trained based on the data corpus.

Abstract: An intelligent return path data (iRPD) system enables transmission of return path data via a communication network for a television connected to a non-hybrid set top box (STB). The iRPD system is configured to receive the key codes of the keys pressed on a remote control device along with the date time stamps and the location information. The iRPD system analyzes the keypress data along with the date time stamps to recognize the channels accessed in programming operations and the non-programming control operations executed by a viewer operating the remote control device. The viewer's behavior pattern is thus recorded and analyzed to identify the viewer. Upon identifying the viewer, various functions such as collecting the viewership statistics, implementing metered usage billing or ecommerce activities are enabled.

Abstract: A system and method for transforming unstructured text into structured form is disclosed. The system and method include converting an input word sequence (e.g., sentence) into tagged output which can be then easily be converted into a structured format. The system may include a bidirectional recurrent neural network that can generate multiple labels of individual words or phrases. In some embodiments, a customized learning loss equation involving set similarity is used to generate the multiple labels.

Abstract: A network communication stack running on relational processing circuitry performs control and maintenance actions on records from a database server managed by repository control circuitry. The database interaction layer of the communication stack accesses the records on the database server. The database interaction layer passes the accessed records to the data processing layer for parsing and storage as tabular entries. An operator may perform manipulations on the tabular entries using a command interface generated by the command layer of the communication stack using locally-defined interface parameters that are independent of characteristics of the database server. The data processing layer recompiles manipulated entries into an altered record. The database interaction layer sends the altered record back to the database server.

Abstract: The present disclosure relates to systems, methods, and computer readable medium for automatically managing API documentation and code generation. The disclosure provides an IDE plug-in that may import a machine readable reference documentation file from a documentation database, and create automatically generated code from the machine readable reference documentation file. Generally, the IDE plug-in may then allow a developer to validate their project back against the machine readable reference documentation file to ensure that all expected code is present in the project. This may allow the developer to ensure that the project properly meets the functional objectives intended for the API, before their implementation is deployed.

Abstract: A system maintains a knowledge layout to support the analysis of active events and determination of epicenter and aftershock nodes via an event reach stack. At an input layer of the event reach stack, the system may receive active event data. At a semantic layer, the system may parse the active event data to determine event phrases. Based on the event phrases, the system may identify epicenter nodes directly affected by the active event. At an analytic model layer, the system may successively determine aftershock nodes by traversing the knowledge layout outward from the epicenter nodes. The system then directs the response to the active event to the aftershock and epicenter nodes, via action at a focus response layer of the event reach stack.

Abstract: A system for determining a vulnerability of source code includes a processor; and non-transitory computer readable media that includes instruction code that causes the processor to receive source code and a selection of one or more code analyzers for detecting vulnerability issues in the source code. The processor executes the one or more code analyzer to generate initial vulnerability data. The initial vulnerability data specifies one or more vulnerable code sections in the source code. The processor communicates the initial vulnerability data to a vulnerability analyzing engine. The vulnerability analyzing engine is configured to identify one or more code sections of the one or more code sections of the initial vulnerability data that correspond to false positives.

Abstract: A distributed data storage layer supports biometric identification systems. The biometric identity system includes hardware and software improvements for capturing, retrieving, and verifying identity based on securely stored biometric data in the distributed data storage layer. As a result, the biometric identity system provides increased individual security and reliable identification.

Abstract: A cyber range system provides a cyber warfare training platform that integrates participation of technical (such as cyber defense personnel) and non-technical participants (such as executives or managers of an organization) within a simulation run, simulates missing participants with cross-contextual AI bots, and trains the bots in a simulated target network may be provided. The system may discover and simulate an organization's computer network so that personnel may be trained on a simulation that mimics their own network. The system may generate role bots that may each simulate a role of a participant. Each of these role bots may be computationally trained over the course of multiple simulation runs based on assessments of a training team that may moderate the simulation runs. Updated versions of the role bots may be stored in a data store for execution in the simulation run or future simulation runs.

Abstract: A device may receive, from an augmented reality device, speech data identifying augmented reality interactions with an augmented reality robot. The device may receive, from a camera, video data identifying movements of a real robot based on the augmented reality interactions with the augmented reality robot. The device may process the speech data to obtain first action data identifying first actions that the real robot is to perform. The device may process the video data to obtain second action data identifying second actions that the real robot is to perform. The device may process the first action data and the second action data to generate pseudocode. The device may transform the pseudocode into code. The device may cause the real robot to execute the code, wherein executing the code causes the real robot to perform the first actions and the second actions.

Abstract: A method for controlling access to one or more of a plurality of target systems includes receiving profile data that defines one or more features associated with a plurality of individuals with one or more entitlements of those individuals. Each entitlement is indicative of target system access. The method further includes generating a model that relates the one or more features and the one or more entitlements of the plurality of individuals. Profile data that defines one or more features associated with a target individual is received from a first user management system. A listing that includes one or more entitlements associated with the target individual, and confidence values associated with the one or more entitlements is generated based on the profile data and the model. Each confidence value is indicative of whether the target individual should be granted a corresponding entitlement.

Abstract: A method for validating information includes accessing validation rules from a validation rule store and transferring a plurality of received data files and the validation rules to a validation storage space. The method also includes selecting each of the one or more data files defined in the validation configuration file. Each data file includes a plurality of records, each record having values associated with a plurality of attributes. For each data file, the method includes applying the plurality of validation rules to determine valid and invalid content within the data file; and generating a report that specifies the invalid content of each data file.

Abstract: The network simulation platform may determine a plurality of potential links to connect a plurality of target nodes to an existing fiberoptic infrastructure. The network simulation platform may determine a set of potential links, of the plurality of potential links, based on one or more criteria. The network simulation platform may determine, based on the set of potential links, an initial fiberoptic network simulation that includes one or more links. The network simulation platform may determine, for each link of the one or more links, a respective weighted highway score associated with the link and may determine, based on the initial fiberoptic network simulation and the respective weighted highway scores associated with the one or more links of the initial fiberoptic network simulation, a final fiberoptic network simulation. The network simulation platform may cause, based on the final fiberoptic network simulation, one or more actions to be performed.

Abstract: Aspects of the present disclosure provide systems, methods, and computer-readable storage media that leverage artificial intelligence and machine learning to screen candidate pharmaceutical molecules or compounds for pharmaceutical uses (e.g., treating diseases or conditions). The screening may be based on structural similarity between the candidate pharmaceutical molecules and various pharmaceutical targets (e.g., proteins, nucleic acids, etc.). In aspects, one or more machine learning (ML) models may be trained to assign a candidate pharmaceutical molecule to one of multiple clusters based on chemical/physical properties of the candidate pharmaceutical molecule and chemical/physical properties of pharmaceutical targets associated with the clusters. The pharmaceutical targets associated with the cluster may be scored based on comparisons between the candidate pharmaceutical molecule and the pharmaceutical target, and a subset of the pharmaceutical targets may be identified based on the scores.

Abstract: The global proliferation of high speed communication networks has created unprecedented opportunities for geographically distributed resource interaction. A data structure synthesizer provides crowd source project management features, crowd source resource sentiment analysis features, and crowd source resource configuration features.

Abstract: A device receives virtual network function (VNF) data identifying a VNF to be implemented in a network and configures the VNF data with hardware and software requirements for deploying the VNF in a non-production environment, wherein configuring the VNF data with the hardware and software requirements generates a configured VNF. The device deploys the configured VNF in the non-production environment and performs one or more tests on the configured VNF deployed in the non-production environment. The device receives one or more test results based on performing the one or more tests on the configured VNF, and updates the configured VNF, based on the one or more test results, to generate an updated VNF. The device causes the updated VNF to be deployed in the network.