An appliance management system includes a plurality of appliances connected to a network and a portable terminal. Each of the appliances includes a sensor configured to detect an abnormality of the appliance, and a first near field wireless communication module configured to broadcast an identifier of the appliance when the sensor detects the abnormality. The portable terminal includes a second near field wireless communication module and a controller. The controller is configured to control the second near field wireless communication module to transmit an access request to an abnormal appliance upon the second near field wireless communication module receiving an identifier of the abnormal appliance. The terminal controller is also configured to control a display to display an abnormality screen including the identifier of the abnormal appliance upon the second near field wireless communication module receiving abnormality information from the abnormal appliance.

A system includes a cluster of nodes, memory, and a processor, where the cluster includes an application programming interface (API) server and one or more components. The processor is configured to initialize an interface to the API server, where the interface is operable to send status information from the one or more components within the cluster via a single output stream. The API server is configured to modify the single output stream of the API server to output status information associated with a first component of the one or more components within the cluster. The status information is aggregated and it is determined whether the cluster is at a failure point. In response to determining that the cluster is at a failure point, an execution signal is set to false, where the execution signal is accessible to an automation tool in communication the cluster.

An apparatus for computing functions using polynomial-based approximation, comprising one or more processing circuitries configured for computing a polynomial-based approximant approximating a function by executing one or more iterations. Each iteration comprising computing the polynomial-based approximant using scaled fixed-point unit(s) according to a constructed set of coefficients, minimizing an approximation error of the computed polynomial-based approximant compared to the function while complying with one or more constraints selected from a group comprising at least: an accuracy, a compute graph size, a computation complexity, and a hardware utilization of the processing circuitry(s), adjusting one or more of the coefficients in case the approximation error is incompliant with the constraint(s) and initiating another iteration. The polynomial-based approximant and its adjusted set of coefficients for which the computed polynomial-based approximant complies with the constraint(s) may be output to one or more processing circuitries configured to approximate the function by computing the polynomial-based approximant.

Systems, apparatuses, and methods related to using memory device sensors are described. Some memory system or device types include sensors embedded in their circuitry. For instance, another device can be coupled to a memory device with an embedded sensor. The memory device can transmit a signal representing sensor data generated by the embedded sensor using a sensor output coupled to the other device. A controller coupled to a memory device may determine one or more threshold values of a sensor or sensors embedded in a memory device. The memory device may transmit an indication responsive to one or more sensors detecting a value greater or less than a threshold and may transmit the indication to another device.

The invention relates to a system for generating synthetic digital data, comprising: a receiver configured to receive at least one measured signal, in particular an RF signal or a sensor signal, a converter configured to convert the at least one measured signal to a digital dataset representing signal characteristics of the at least one measured signal, at least one trainable neural network encoder, wherein, during a training routine, the neural network encoder is configured to receive the digital dataset and to generate a compressed representation of the digital dataset, a processing unit configured to analyze the compressed representation and to detect a correlation between the digital dataset and the compressed representation, wherein the processing unit is configured to generate decoder input data based on the detected correlation, and a trained neural network decoder which is configured to receive the decoder input data and to generate synthetic digital data representing signal characteristics of the at least one measured signal based on the decoder input data.

A system and method for generating analytics based on interactions through digital channels. The method includes determining a plurality of interaction sensor signals based on interactions with an electronic form (e-form); clustering at least one set of similar interaction sensor signals of the determined plurality of interaction sensor signals, wherein each set of similar interaction sensor signals includes signals determined based on interactions with the same portion of the e-form; and generating at least one analytic based on each clustered set of interaction sensor signals.

A solution is disclosed for computer hardware replacement using performance analytics that selects replacement computer hardware based on actual user needs and enterprise priorities. Key performance data is collected and compared with various baselines, thereby identifying hardware that is performing below acceptable levels. Enterprise data and collected data are received from an instrumented operating system on a computing device. The collected data includes boot performance, application performance, and hardware performance. Based at least on the collected data, a usability score is determined by performing a weighted calculation on the collected data. Based at least on the usability score and the enterprise data, it is determined whether a score improvement is required. Based at least on the enterprise data, a score improvement selection is determined. The score improvement selection is reported based at least on determining that a score improvement is required.

A system including a bus, a processor coupled to the bus, a non-volatile memory coupled to the bus, circuitry for providing a detected condition, and a secure controller. The secure controller is coupled to the circuitry for providing a detected condition and to selectively enable communication of information between the non-volatile memory and the bus in response to the detected condition.

An automated improving of quality of service of a data center. Transients of a power grid fed to a power supply unit are monitored by a probe. Information on transients is provided across an interface to a server of the data center. Based on characteristics of the transients, a reliability of the data center is subjected to automated updating. A request for migration of workload requiring a higher reliability than the updated reliability can be sent to a central management. When the central management has identified another data center that can meet the required reliability, the central management migrates or relocates the workload to the another data center.

A flow metering system includes a flow meter coupled to a plurality of sensors and configured to measure volume of fluid flowing through the flow meter. The system also includes a metrology computer coupled to the flow meter and the sensors. The metrology computer is configured to receive live values from a plurality of sensors during a first time period, train an artificial intelligence engine based on the live values received during the first time period, and detect a sensor failure based on a deviation between a live value from the sensor and a predicted value for the sensor. The predicted value is based on live values from other of the plurality of sensors and the artificial intelligence engine.