A system detects a user's mood and in response establishes computer settings including computer game settings, recommends social network interactions, advises other users, alters task scheduling, and in general enhances collective group mood, collective productivity, social interaction, and engagement.

A method for exchange of equipment performance data includes the steps of: obtaining performance data of a communicatively-insulated device; converting the performance data into a scannable code; capturing an image of the scannable code; decoding the scannable code using a communicatively-enabled device to extract an address string encoded in the scannable code, the address string comprising an address of a remote server and the performance data; initiating, by the communicatively-enabled device, a communications link with the remote server using the address string thereby to provide the performance data to the remote server; performing, by the remote server, analytics on the performance data; and sending historic device performance data and/or analytical results to a remote computing device and/or sending a link to the historic device performance data and/or analytical results to the remote computing device; wherein the communicatively-insulated device is packaging equipment and wherein obtaining the performance data comprises: running a calibration phantom through the packaging equipment; scanning the calibration phantom with a calibration unit; and using the calibration unit to generate a system status report identifying one or more operational parameters of the packaging equipment.

The present disclosure relates to a non-transitory computer-readable recording medium storing an analysis program that causes a computer to execute a process. The process includes sampling an instruction address of one of instructions included in a program during execution of the program, identifying a first function that includes the sampled instruction address in an address range, rewriting mark information associated with the identified first function, identifying first information corresponding to the instruction address of the first function among a plurality of first information based on the rewritten mark information, identifying second information corresponding to the instruction address of the first function among a plurality of second information based on the rewritten mark information, storing the first information and the second information in a memory, and analyzing performance of the program based on the first information and the second information stored in the memory.

Methods, systems, and non-transitory computer readable medium are described for sensor metrology data integration. A method includes receiving sets of sensor data and sets of metrology data. Each set of sensor data includes corresponding sensor values associated with producing corresponding product by manufacturing equipment and a corresponding sensor data identifier. Each set of metrology data includes corresponding metrology values associated with the corresponding product manufactured by the manufacturing equipment and a corresponding metrology data identifier. The method further includes determining common portions between each corresponding sensor data identifier and each corresponding metrology data identifier. The method further includes, for each of the sensor-metrology matches, generating a corresponding set of aggregated sensor-metrology data and storing the sets of aggregated sensor-metrology data to train a machine learning model. The trained machine learning model is capable of generating one or more outputs for performing a corrective action associated with the manufacturing equipment.

One embodiment provides a computer implemented method of estimating replication completion time. The method includes creating a historical dataset of prior replication data; determining a set of replication parameters to consider; inputting the historical dataset and the set of replication parameters to a replication completion time estimator module; generating a replication completion time prediction based on the historical dataset and the set of replication parameters; and generating a confidence prediction corresponding to the replication completion time prediction.

Disclosed are systems, computer-readable media and methods for monitoring performance data across microservices. One example method includes establishing a service policy configured on a centralized switch controller, applying the service profile to a virtual interface associated with a microservice, mapping a microservice name for the microservice to an IP address and a port number, tracking a protocol flow for the microservice, wherein the protocol flow is associated with a virtual switch, to yield data, aggregating the data to yield aggregated data and presenting the aggregated data on a user interface.

A technique for tracking web browsing activity of a client device that includes storing, in a memory, a client profile having a client identifier associated therewith, providing a client device with a cache file having the client identifier embedded therein, receiving from the client device an identification of a client action and the client identifier, and updating the client profile to include the identification of the client action.

Embodiments disclosed herein provide for monitoring performance of a processing device to manage non-precise events. A processing device includes a performance counter to track a non-precise event and to increment upon occurrence of the non-precise event, wherein the non-precise event comprises a first type of performance event that is not linked to an instruction in an instruction trace. The processing device also includes a first handler circuit to generate and store a first record, the first record comprising architectural metadata defining a state of the processing device at a time of generation of the first record, wherein the first handler circuit to generate records corresponding to precise events. The processing device further includes a second handler circuit communicably coupled to the first handler circuit, the second handler circuit to cause the first handler circuit to generate a second record for the non-precise event upon overflow of the performance counter.

One example of a system includes a plurality of clients, a master chunk coordinator, and a plurality of chunk servers. Each client submits requests to access chunks of objects. The master chunk coordinator maintains chunk information for each object. Each chunk server includes a chunk monitor to monitor client requests, maintain chunk statistics for each chunk based on the monitoring, and transmit the chunk statistics for each chunk to the master chunk coordinator. The master chunk coordinator instructs the chunk servers to re-chunk objects, replicate chunks, migrate chunks, and resize chunks based on the chunk statistics to meet specified parameters.

A processor includes an instruction pipeline and control circuitry. The instruction pipeline is configured to process instructions of program code. The control circuitry is configured to monitor the processed instructions at run-time, to construct an invocation data structure comprising multiple entries, wherein each entry (i) specifies an initial instruction that is a target of a branch instruction, (ii) specifies a portion of the program code that follows one or more possible flow-control traces beginning from the initial instruction, and (iii) specifies, for each possible flow-control trace specified in the entry, a next entry that is to be processed following processing of that possible flow-control trace, and to configure the instruction pipeline to process segments of the program code, by continually traversing the entries of the invocation data structure.