Abstract: Aspects of the present disclosure relate to a machine determining a quality ranking of a subject. The machine accesses a current input representing answers to a plurality of questions about the subject, each answer representing a ranking of a quality of the subject at a specified time, where the subject has a geographic location. The machine determines, based on the current input, an overall ranking of the quality of the subject. The machine determines, based on the current input and based on one or more of input received about the subject at a time different from the specified time and input about other subjects proximate to the geographic location, a future ranking of the quality of the subject. The machine transmits a graphical output corresponding to the overall ranking and the determined future ranking of the quality of the subject.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for a checkout system executable code monitoring, and user account compromise determination system. The system monitors executable code initiating and executing on checkout systems, including determining hashes of the executable code. The system determines whether the executable code is malicious based on the hash, and associated information of the executable code. Additionally, the system monitors user access to checkout systems, and determines user accounts associated with being compromised. User interfaces are generated describing checkout systems associated with a risk of being compromised, and are configured for user interaction, which cause generation of updated user interfaces and access to electronic data stores to determine information relevant to the user interaction.

Abstract: Embodiments of the present disclosure relate to a data analysis system that may receive data comprising a plurality of raw data items from one or more data sources, such as a monitoring agent located in a monitored network. The received data may be scored using one or more scoring rules and/or algorithms, with raw data items satisfying a score threshold designated as “data item leads.” Raw data items associated with a data item lead may be searched and displayed to the user via an interactive user interface. The data analysis system may be used to execute searches and additional enrichments against the received raw data items. The data analysis system may group received raw data items based upon shared attribute values. The data analysis system may be used to categorize received data and construct timelines, histograms, and/or other visualizations based upon the various attributes of the raw data items.

Abstract: Automated defect sourcing systems identify root-causes of yield excursions due to contamination, process faults, equipment failure and/or handling. They perform this function in timely manner and provide accurate and timely feedback to address and contain the sources of yield excursion. A signature repository stores known wafer surface manufacturing defect types as set of rules. The signature of a manufacturing defect pattern is associated with the equipment or process that causes the defects, and is used to source the manufacturing defects and to provide process control for changing and/or stopping yield excursion during fabrication. A defect signature rule-based engine matches wafer defects against the signature repository during wafer fabrication. Once the defect signature is detected during fabrication, handling and/or disposing the root-cause of the corresponding defect is facilitated using messages according to an event handling database.