Abstract: Disclosed are systems, methods, and apparatus of an automated and self-service kiosk that allows customers to select inventory items available from the kiosk and walk or move away with selected inventory item(s) without having to process payment, identify the inventory item(s), or provide any other form of checkout. After a customer has picked one or more items and departed the kiosk, the picked items are determined and the customer charged for the items. For example, one or more of detected weight changes measured at the kiosk and/or images generated at the kiosk may be used to identify items picked by the customer from the kiosk.

Abstract: Disclosed are systems, methods, and apparatus of an automated and self-service kiosk that allows customers to select inventory items available from the kiosk and walk or move away with selected inventory item(s) without having to process payment, identify the inventory item(s), or provide any other form of checkout. After a customer has picked one or more items and departed the kiosk, the picked items are determined and the customer charged for the items. For example, one or more of detected weight changes measured at the kiosk and/or images generated at the kiosk may be used to identify items picked by the customer from the kiosk.

Abstract: Devices and methods are provided for using virtual fulfillment center locations to facilitate delivery of items. A device may receive a virtual location associated with transportation of an item to a first location. The device may determine a geographic zone associated with the virtual location. The device may determine a first delivery time associated with delivering the item from the first location, and determine a second delivery time associated with delivering the item from the virtual location. The device may receive a purchase request for the item, from a second device, wherein the purchase request is associated with delivery to a second location. The device may determine an estimated delivery date to the delivery location based on the first delivery time or the second delivery time. The device may send, to the second device, an indication of the estimated delivery date.

Abstract: Certain aspects of the present disclosure provide techniques for detecting and preventing web service usage anomalies. Embodiments include forecasting, based on a model, a number of resource instances for one or more web services for a time period. Embodiments include receiving, after the time period has elapsed, a detected number of resource instances for the one or more web services for the time period. Embodiments include comparing the detected number of resource instances to the forecasted number of resource instances. Embodiments include determining, based on the comparing, a usage anomaly. Embodiments include determining an impact of the usage anomaly. Embodiments include outputting an indication of the usage anomaly and the impact of the usage anomaly.

Abstract: Systems and methods of the present disclosure may read source data corresponding to a source variable and apply a transformation to the source variable to generate an output variable. Accordingly, one such method comprises receiving a request to access an output variable by applying one or more data transformations to input data; before applying an actual data transformation to the input data, identifying that a match exists with a database of prior data transformations that have been applied to source variables to generate derived variables; identifying that a source variable in the matching one or more data transformations is flagged as sensitive data; and processing the request to access the output variable subject to an access restriction in response to the identification of the source variable that is flagged as sensitive data.

Abstract: Systems and methods of the present disclosure may read source data corresponding to a source variable and apply a transformation to the source variable to generate an output variable. Accordingly, one such method comprises receiving a request to generate an output variable by applying one or more data transformations to a source variable; before applying an actual data transformation to the source variable, checking a database of prior data transformations that have been applied to source variables to generate existing output variables for a match with the requested one or more data transformations to the source variable; determining that a match exists in the database, wherein the match is associated with an existing output variable; and/or responding to the request by providing the existing output variable associated with the match that exists in the database of prior data transformations.

Abstract: Disclosed is a process for producing terephthalic acid. The process includes contacting p-xylene with a gaseous stream containing oxygen (O2) in presence of a homogeneous catalyst solution, at a reaction temperature of 180° C. to 195° C. to oxidize at least a portion of the p-xylene and form a product stream containing terephthalic acid, said homogeneous catalyst solution contains 350 ppm to 450 ppm cobalt (Co), 170 ppm to 270 ppm manganese (Mn), and 410 ppm to 510 ppm bromine (Br), wherein a Br/(Co+Mn) wt. % ratio is 0.5:1 to 1:1, and a Co to Mn wt. % ratio is 1.5:1 to 2:1.

Abstract: The method includes receiving historical data from a first data source; analyzing the historical data for a desired characteristic; determining a representative value for the desired characteristic of the historical data; determining a first data expectation for the historical data based on the representative value; transmitting the first data expectation to a first data recipient; receiving first incoming data from the first data source; analyzing the desired characteristic of the first incoming data; determining a first incoming data value for the desired characteristic for the first incoming data; comparing the first incoming data value and the representative value; determining a first difference between the first incoming data value and the representative value; and/or comparing the first difference to a difference threshold which indicates whether a difference between an incoming data value and the representative value is significant.

Abstract: Disclosed are systems, methods, and apparatus of an automated and self-service kiosk that allows customers to select inventory items available from the kiosk and walk or move away with selected inventory item(s) without having to process payment, identify the inventory item(s), or provide any other form of checkout. After a customer has picked one or more items and departed the kiosk, the picked items are determined and the customer charged for the items. For example, one or more of detected weight changes measured at the kiosk and/or images generated at the kiosk may be used to identify items picked by the customer from the kiosk.

Abstract: Systems and methods for controlling traffic flow for software experimentation are disclosed. An example method includes receiving a first traffic from a first plurality of users to receive an existing feature or a new feature, determining, from the first traffic, a first portion of the first plurality of users to receive the existing feature (with the first portion bounded by a first lower threshold and/or a first upper threshold) and a second portion of the first plurality of users to receive a new feature (with the second portion bounded by a second lower threshold and/or a second upper threshold). The method also includes providing the existing feature to the first portion, providing the new feature to the second portion, receiving feedback from the first plurality of users, and adjusting the first portion and/or the second portion based on the feedback and based on the bounds.

Abstract: A method for load balancing in a multi-core processor of an electronic device, the method including dividing, by the electronic device, a first task and at least one second task into a plurality of task-jobs, determining, by the electronic device, at least one core configuration for each of the plurality of task-jobs, scheduling, by the electronic device, each of the plurality of task-jobs on at least one core of the multi-core processor based on the at least one core configuration to generate an execution schedule, and executing, by the multi-core processor, the plurality of task-jobs according to the execution schedule.

Abstract: This disclosure provides systems, methods and apparatuses for detecting anomalous activity in an electronic system. In some implementations, a system generates a set of model parameters based on a number (n) of historical datapoints in a dataset, where each datapoint represents activity detected in the electronic system over a respective period of time. The system receives a first new data point for the data set and generates a first test parameter based on a value of the first new datapoint and an average and a measure of spread of the n historical datapoints. The system further compares the first test parameter to the set of model parameters and determines whether the first new datapoint represents an anomaly based at least in part on the comparison.

Abstract: A system may retrieve a pattern from a pattern database with the pattern identifying a type of sensitive data. The system may also retrieve data identified by a variable from a big data management system. The system may then match the data to the pattern to detect the type of sensitive data in the data. An output may be generated in response to the data matching the pattern. A variable access permission may be retrieved for the variable from a permissions repository, a sensitive data permission may be retrieved for the type of sensitive data from the permissions repository, and the variable access permission may be compared to the sensitive data permission to detect a discrepancy.

Abstract: This disclosure provides systems, methods and apparatuses for detecting anomalous activity in an electronic system. In some implementations, a system generates a set of model parameters based on a number (n) of historical datapoints in a dataset, where each datapoint represents activity detected in the electronic system over a respective period of time. The system receives a first new data point for the data set and generates a first test parameter based on a value of the first new datapoint and an average and a measure of spread of the n historical datapoints. The system further compares the first test parameter to the set of model parameters and determines whether the first new datapoint represents an anomaly based at least in part on the comparison.

Abstract: Systems, methods, and computer-readable media are disclosed for systems and methods for anonymization of user data for privacy across distributed computing systems. Example methods may include determining, by a first computer system, a request for content to present at a user device, wherein the request for content is associated with a user account, determining a first search query associated with the user account, and determining a first keyword associated with the first search query. Some methods may include generating a first hash value for the first keyword, sending the first hash value to a second computer system for identification of first content for presentation at the user device, and causing the second computer system to send the first content to the user device for presentation, wherein the first computer system does not receive the first content.

Abstract: The systems are generally configured to provide rewards. The systems are capable of syncing transaction accounts with one or more reward programs and one or more channels. Moreover, the systems are capable dynamically provisioning rewards in one or more subsets to a rewards program to distribute high, medium and low value rewards to a reward program throughout the duration of the program.

Abstract: A system may read source data corresponding to a source variable and apply a transformation to the source variable to generate an output variable. The transformation may include logic, and the output variable may be configured for ingestion into a big data storage format. The system may record lineage data of the output variable that comprises the transformation and/or the source variable. The system may also receive a request to generate a requested output variable. The requested output variable may be generated from a second transformation that is the same as the first transformation. The system may thus match the first transformation to the second transformation using the lineage data. In response to matching the first transformation to the second transformation, the system may deny the request. The original output variable may be returned in response to the matching the first transformation to the second transformation.

Abstract: A system for applying access permissions to read requests may write a file to a storage media. The file may contain data, an embedded flag, and an embedded verification datum of the embedded flag. The embedded flag may indicate an access permissions requisite for file access. The system may also receive a request to access the file from a user and retrieve an access permission for the user. The system may also compare the embedded flag to the access permission for the user to determine the user has permission to access the file. A verification datum may be calculated, and the calculated verification datum may be compared to the embedded verification datum to determine the embedded flag has not changed.

Abstract: Certain aspects of the present disclosure provide techniques for detecting and preventing web service usage anomalies. Embodiments include forecasting, based on a model, a number of resource instances for one or more web services for a time period. Embodiments include receiving, after the time period has elapsed, a detected number of resource instances for the one or more web services for the time period. Embodiments include comparing the detected number of resource instances to the forecasted number of resource instances. Embodiments include determining, based on the comparing, a usage anomaly. Embodiments include determining an impact of the usage anomaly. Embodiments include outputting an indication of the usage anomaly and the impact of the usage anomaly.

Abstract: A system may store a plurality of first records comprising a first variable in a first data storage format. The system may also store a plurality of second records comprising a second variable in a second data storage format. The first data storage format may have a different data structure than the second data storage format. The system may then generate a catalog including a first location of the first variable and a second location of the second variable. The first location identifies the first data storage format, which is where the first variable is stored. The second location identifies the second data storage format, which is where the second variable is stored. The system may then receive a request to access at least one of the first variable or the second variable and access the first variable and/or the second variable in response to the request.