Abstract: The concept involves efficiently using machine learning to quickly identify possible fraudulent applications in small business loan and credit applications by automatically flagging applications that meet certain criteria. In one preferred implementation, the tool compares a business description to a selected NAICS code in a loan application to assess the potential for fraud. Specifically, an algorithm can match the leftmost two digits of the selected code with the description of the category from an applicant. An engine calculates a probability of a fraud score based on the matching attached to the application. Because the tool detects fraud proactively rather than reactively, it substantially reduces computational costs and resources and reduces the biases associated with highly intensive manual work.

Abstract: Embodiments of the disclosure extract annotations from web pages. The annotations are combined with search results and/or advertisements to allow the user to better understand the content of the search result or advertisement landing web page. A visual snapshot of the web page is taken. Visual processing extracts information from the visual representation. The HTML, for the web page is also analyzed and various pieces of information extracted. The information from the visual processing is combined with the information extracted from the HTML. The combined information is evaluated and information for the annotations are selected. The annotations are then combined with the search results and/or advertisements.

Abstract: A method for providing authentication using an image sensor of an electronic device including: receiving, by the electronic device, a plurality of frames from the image sensor of the electronic device, wherein each frame includes a plurality of Optical Black (OB) pixels; determining, by the electronic device, a set of optimal OB pixels from the plurality of frames; and generating, by the electronic device, a unique key based on the set of optimal OB pixels for the authentication.

Abstract: Server hardware failure is predicted, with a probability estimate, of a possible future server failure along with an estimated cause of the future server failure. Based on the prediction, the particular server can be evaluated and if the risk is confirmed, load balancing can be performed to move a load (e.g., virtual machines (VMs)) off of the at-risk server onto low-risk servers. High availability of deployed load (e.g., VMs) is then achieved. A flow of big data may be on the order of 1,000,000 parameters per minute. A scalable tree-based AI inference engine processes the flow. One or more leading indicators are identified (including server parameters and statistic types) which reliably predict hardware failure. This allows a telco operator to monitor cloud-based VMs and perform a hot-swap on virtual machines if needed by shifting virtual machines VMs from the at-risk server to low-risk servers. Servers having a health score indicating high risk are indicated on a visual display called a heat map.

Abstract: Computer technology for selecting content and/or ordering content from a full version of a product specification to make a customized version of the product specification for a requester that has requested a product specification. This customization of the product specification is based at least in part on “context information,” which means any information relevant to the requester's expected use of the product specification except for information that the requester put into the request (for example, if the request includes a search query, that search query would not qualify as “context information”).

Abstract: The present disclosure provides a system for real-time health monitoring of one or more users. The system includes a computing device associated with a facility, a plurality of cameras, an AI edge device, and a communication network. Moreover, the system includes a server, a database, and a notification interface. The AI edge device monitors the health of one or more users in real-time. The AI edge device monitors the health of the one or more users by processing a video feed captured by the plurality of cameras. Further, the AI edge device notifies the health-related issues in real-time using the notification interface to a first set of users.

Abstract: Techniques for utilizing model and hyperparameter optimization for multi-objective machine learning are disclosed. In one example, a method comprises the following steps. One of a plurality of hyperparameter optimization operations and a plurality of model parameter optimization operations are performed to generate a first solution set. The other of the plurality of hyperparameter optimization operations and the plurality of model parameter optimization operations are performed to generate a second solution set. At least a portion of the first solution set and at least a portion of the second solution set are combined to generate a third solution set.

Abstract: The present disclosure relates to immunogenic compositions comprising tetanus, diphtheria, and acellular pertussis (Tdap) antigens, and a toll-like receptor 9 (TLR9) agonist, such as oligonucleotide comprising an unmethylated cytidine-phospho-guanosine (CpG) motif. The immunogenic compositions may further comprise an aluminum salt adjuvant to which the Tdap antigens are adsorbed. The immunogenic compositions are suitable for active booster immunization against tetanus, diphtheria, and pertussis in an individual in need thereof.

Abstract: Various examples are directed to systems and methods for visualizing computerized model decisions. A model system may access result data that comprises event results for a plurality of events and event feature data describing sets of event features. A first event result for a first event of the plurality of events is generated using the computerized model and a first set of event features from the event feature data. The model system may access importance score data comprising importance scores for at least a portion of the first set of event features, wherein a first event feature is assigned a first importance score and a second event feature is assigned a second importance score indicating a greater importance than the first importance score. The model system may also generate a user interface for display to a human user. The user interface may comprise a background area; a first visual indicator positioned on the background area and corresponding to the first event feature.

Abstract: Embodiments determine mismatches in evaluations. Embodiments receive a first evaluation of an employee from a supervisor of the employee, the first evaluation including supervisor comment ratings and supervisor numerical ratings, each of the supervisor comment ratings and supervisor numerical ratings corresponding to an evaluation category. Embodiments receive a second evaluation of the employee from the employee, the second evaluation including employee comment ratings and employee numerical ratings, each of the employee comment ratings and employee numerical ratings corresponding to the evaluation category. Embodiments determine first sentiment polarity scores of the supervisor comment ratings and second sentiment polarity scores of the employee comment ratings.

Abstract: A multi-layered fire-resistant roofing underlayment is disclosed. The roofing underlayment has a core of aluminum foil. On each side of the aluminum foil is a layer of nonwoven material. A lamination coating is between the aluminum foil layer and the layers of nonwoven material. At the bottom of the roofing underlayment is a backside coating layer. The roofing underlayment may be utilized in bats or rolls.

Abstract: The system comprises approving a credit application during a single http session, transmitting an encoded secure token to a web-client participating in the http session, receiving from the mobile communications device the secure token, and transmitting the transaction account data to the mobile communications device, in response to the receiving the secure token. The system may further comprise the mobile communications device decoding the secure token.

Abstract: Methods, apparatus, systems and articles of manufacture to determine and apply polarity-based error correction code are disclosed. In some examples, the methods and apparatus create an array by setting a first set of bit locations of a code word to have a first value and setting a second set of bit locations of the code word to have a second value different from the first value. In some examples, when the array satisfies a parity check, the methods and apparatus determine that bit locations having the first value from the array form a polarity-based error correction code.

Abstract: Techniques are described herein that are capable of performing quality-based action(s) regarding engineer-generated documentation associated with code and/or an API. Features are extracted from data associated with the engineer-generated documentation, which includes engineer-generated document(s). Weights are assigned to the features. The quality-based action(s) are performed. The quality-based action(s) include generating quality score(s) for the engineer-generated document(s) and/or providing a recommendation to revise a subset of the engineer-generated document(s). Each quality score is based at least in part on the weights assigned to the features that correspond to the respective engineer-generated document. The recommendation recommends performance of an operation to increase the quality of each engineer-generated document in the subset based at least in part on the weights assigned to the features that correspond to the subset.

Abstract: An apparatus comprising: a radiation receiving apparatus provided with an opening operable to receive radiation from a radiation source through the opening; wherein the radiation receiving apparatus comprises a deflection apparatus arranged to change a trajectory of a particle through the opening arriving at the radiation receiving apparatus.

Abstract: Electrochemical cells and methods for their production are provided. In particular, multi-well assay plates including multi-electrode wells are provided. The multi-electrode wells contain multiple electrodes that are electrically isolated from one another, permitting the various electrodes of the various wells to be addressed in any suitable combination.

Abstract: Server hardware failure is predicted, with a probability estimate, of a possible future server failure along with an estimated cause of the future server failure. Based on the prediction, the particular server can be evaluated and if the risk is confirmed, load balancing can be performed to move a load (e.g., virtual machines (VMs)) off of the at-risk server onto low-risk servers. High availability of deployed load (e.g., VMs) is then achieved. A flow of big data may be on the order of 1,000,000 parameters per minute. A scalable tree-based AI inference engine processes the flow. One or more leading indicators are identified (including server parameters and statistic types) which reliably predict hardware failure. This allows a telco operator to monitor cloud-based VMs and perform a hot-swap on virtual machines if needed by shifting virtual machines VMs from the at-risk server to low-risk servers. Servers having a health score indicating high risk are indicated on a visual display called a heat map.

Abstract: A system and method is provided to selectively process and store tables of a relational database by calculating an overall data sensitivity score for each table based on predefined attribute rules; performing column-wise splitting of at least one of the tables into a first table and a second table based on the overall data sensitivity score of each table, thereby generating a total number of relational database tables; storing a first subset of the total number of relational database tables in a private cloud storage database in a distributed storage environment based on the overall data sensitivity scores of each of the total number of relational database tables; and storing a second subset of the total number of relational database tables in a public cloud storage database of the distributed storage environment based on the overall data sensitivity scores of each of the total number of relational database tables.

Abstract: Server hardware failure is predicted, with a probability estimate, of a possible future server failure along with an estimated cause of the future server failure. Based on the prediction, the particular server can be evaluated and if the risk is confirmed, load balancing can be performed to move a load (e.g., virtual machines (VMs)) off of the at-risk server onto low-risk servers. High availability of deployed load (e.g., VMs) is then achieved. A flow of big data may be on the order of 1,000,000 parameters per minute. A scalable tree-based AI inference engine processes the flow. One or more leading indicators are identified (including server parameters and statistic types) which reliably predict hardware failure. This allows a telco operator to monitor cloud-based VMs and perform a hot-swap on virtual machines if needed by shifting virtual machines VMs from the at-risk server to low-risk servers. Servers having a health score indicating high risk are indicated on a visual display called a heat map.

Abstract: A computer system maintains structure data indicating geometrical constraints for each structure category of a plurality of structure categories. The computer system generates a virtual 3D representation of a structure based on a set of images depicting the structure. For each image in the set of images, one or more landmarks are identified. Based on the landmarks, a candidate structure category is selected. The virtual 3D representation is generated based on the geometrical constraints of the candidate structure category and the landmarks identified in the set of images.