Abstract: A method includes obtaining operating data associated with operation of a cross-directional industrial process controlled by at least one model-based process controller. The method also includes, during a training period, performing closed-loop model identification with a first portion of the operating data to identify multiple sets of first spatial and temporal models. The method further includes identifying clusters associated with parameter values of the first spatial and temporal models. The method also includes, during a testing period, performing closed-loop model identification with a second portion of the operating data to identify second spatial and temporal models. The method further includes determining whether at least one parameter value of at least one of the second spatial and temporal models falls outside at least one of the clusters.

Abstract: A renewable power plant configured to deliver electrical power to an electrical grid in accordance with a reference is disclosed. The renewable power plant comprises at least one energy generating system of a first type, at least one energy generating system of a second type, and a control system including a central power plant controller (CPPC) which generates setpoints for controlling the energy generating systems in accordance with the reference. The energy generating systems provide feedback signals to the CPPC. The control system is configured to generate a modified feedback signal based on the feedback signal received from the energy generating systems of the second type, and using a model representing operational behavior of the energy generating systems of the second type. The CPPC is configured to apply the modified feedback signal to a feedback control loop for controlling the energy generating systems.

Abstract: Techniques for detecting physical conditions at a physical premises from collection of sensor information from plural sensors execute one or more unsupervised learning models to continually analyze the collected sensor information to produce operational states of sensor information, produce sequences of state transitions, detect during the continual analysis of sensor data that one or more of the sequences of state transitions is a drift sequence, correlate determined drift state sequence to a stored determined condition at the premises, and generate an alert based on the determined condition. Various uses are described for these techniques.

Abstract: A data-based nuclear power plant design basis management system and a method therefor are disclosed. According to an embodiment of the present invention, the data-based nuclear power plant design basis management system comprises a database for storing: information on a plurality of design basis for defining a design basis document for configuration management in a nuclear power plant; information on a category, corresponding to each of the design basis, among a plurality of categories; and an associative relationship between the plurality of design basis, wherein the plurality of categories includes design requirements (REQ), at least one design basis specification (DBS) for satisfying the REQ, and the like.

Abstract: A determination apparatus extracts a plurality of specific events that have values greater than an event determination threshold from among a plurality of events that have occurred in chronological order. The determination apparatus generates a feature amount related to adjacent occurrence intervals of the plurality of specific events, using the plurality of specific events. The determination apparatus generates array data corresponding to the plurality of events using points each having components of the event determination threshold and the feature amount, while changing the event determination threshold. The determination apparatus determines a type of the plurality of events using the array data.

Abstract: In an exemplary embodiment, software made in accordance with the present invention displays a marketplace interface, which displays at least a portion of a CAD model and a set of marketplace tool selectors to a user such that the user can manipulate the tool selectors to interact with an electronic marketplace. The marketplace interface may include a spectrum interface designed and configured to allow the user to selectively augment the marketplace interface with additional functionality. Various corresponding and related systems, methods, and software are described.

Abstract: An extremum seeking controller includes a processing circuit configured to modulate a manipulated variable provided as an input to a plant using an extremum-seeking control technique to drive a gradient of an objective function with respect to the manipulated variable toward an extremum. The objective function includes a performance variable characterizing a performance of the plant responsive to the manipulated variable. The objective function also includes a saturation adjustment term that becomes active as the plant approaches a saturation point and remains active as the plant operates within a saturated region past the saturation point. The saturation adjustment term causes the processing circuit to adjust the manipulated variable toward a value of the manipulated variable that returns the plant from the saturated region to a non-saturated region.

Abstract: Systems, methods, techniques and apparatuses of power network control are disclosed. One exemplary embodiment is a power network comprising a plurality of zones each including a plurality of measurement devices structured to measure electrical characteristics of the corresponding zone, a zone controller structured to receive measurements from the plurality of measurement devices, a distributed energy resource (DER), and a load. Each zone controller is structured to receive a set of local measurements from the plurality of measurement devices of the corresponding zone, calculate a sensitivity matrix using the received set of local measurements, determine whether a voltage violation has occurred in the corresponding zone, determine a DER set point using the received set of local measurements in response to determining the voltage violation has occurred in the corresponding zone, and transmit the DER set point to the DER.

Abstract: According to an aspect, there is provided method for commissioning a drive. First, a local network is established between a wireless computing device, one or more wireless sensor devices and a drive. Each wireless sensor device is configured to measure one or more physical quantities associated with an industrial system controlled by the drive. The wireless computing device configures wirelessly the drive and the one or more wireless sensor devices for performing measurements. In response to receiving one or more measured values from the one or more wireless sensor devices, the wireless computing device displays the information on the one or more measured values on a display for providing guidance for a user of the wireless computing device for adjusting drive parameters of the drive.

Abstract: A monitoring system for data collection related to a production line of an industrial environment includes a data storage structured to store a plurality of data collection templates, each of the plurality of data collection templates comprising a data collection routine; a data collector structured to interpret a plurality of detection values that correspond to a plurality of input channels, wherein the plurality of detection values are obtained according to a data collection routine corresponding to a selected one of the plurality of data collection templates; wherein the data storage is further structured to store at least a portion of the plurality of detection values; a data analysis circuit structured to interpret at least a subset of the detection values to determine a state value corresponding to one of a process or a component of the production line; and an expert system circuit structured to perform a data collection modification by performing one of: adjusting the data collection routine correspond

Abstract: A method for operating an automation system comprising at least one field device associated to a local control device is provided. The method comprises: controlling an operation of the field device based on control data generated by the local control device; receiving monitoring data describing the controlled operation of the field device from the field device; modifying configuration data of the local control device based on the monitoring data; generating upload data comprising information about the modification of the configuration data and/or about changes in the operation of the field device resulting from the modification of the configuration data; in the local control device and/or in a central control device, deleting, encrypting and/or masking specified information from the upload data to generate modified upload data; and providing the modified upload data for use by another local control device.

Abstract: Provided are energy device control systems for distributed grid subsystem that control a first power demand of a plurality of appliances. The control system comprises a graphical user interface configured to accept a user input indicative of a first demand and dynamic allocation flexibility associated with the a respective energy device; a communication interface configured to aggregate dynamic allocation values from a plurality of system nodes including at least the user input indicative of a first demand and the dynamic allocation flexibility; and at least one processor programmed to: generate a learning model for evaluating dynamic future allocation with future energy execution prediction, wherein the dynamic future allocation includes at least energy operational information based on a categorization of energy usage at a plurality of respective energy devices; and trigger energy generation on the energy grid at respective generator nodes according to the learning model and dynamic projections.

Abstract: An information processing device includes: a memory; and a processor configured to: hold each of values of state variables included in an evaluation function representing energy; calculate the change value of the energy for each of state transitions, when a state transition occurs due to a change of any of the values of the state variables; control a temperature value representing temperature; select any of the state transitions, based on priority information set based on state transition information updated last time with respect to identification information for identifying each state transition, and transition acceptance information indicating transition acceptance determined based on the change value, and a generated thermal noise; and output a lowest energy state which is the values of the state variables when the energy to be updated based on the selected state transition becomes a lowest value.

Abstract: An apparatus, methods and systems for data collection in an industrial environment are disclosed. A monitoring system can include a data collector coupled to a plurality of analog sensors to collect data, a data storage structured to store a plurality of data collection management plans comprising template data collection routines for collection of data, a data acquisition circuit structured to interpret a plurality of detection values from the collected data, and a data analysis circuit structured to analyze the collected data and select one of the plurality of data collection management plans, wherein the selected one of the plurality of data collection management plans is selected is at least in part based on a data analysis of received data from the plurality of analog sensors.

Abstract: An error compensation system for a numerical control (NC) machine tool based on iterative learning control, including a trajectory generating module, a down-sampling module, a position controller, a first holder, a velocity-loop iterative learning controller, a velocity controller, a second holder and a control plant. The trajectory generating module is configured to generate a desired trajectory command including a first sampling command. The first sampling command is transmitted to the down-sampling module and the velocity-loop iterative learning controller. The first sampling command is down-sampled through the down-sampling module to obtain a second sampling command. The velocity-loop iterative learning controller is configured to receive the first sampling command, and obtain a first sampling error compensation sequence according to a first sampling error sequence and a first sampling error compensation sequence of a previous iteration machining process stored therein.

Abstract: A method and a control device for the throughput-optimized production of printed circuit boards on a pick-and-place line is provided. Further provided is a method for the throughput-optimized production of printed circuit boards on a pick-and-place line, wherein: the printed circuit boards are divided into groups known as clusters; each cluster is produced using one set-up; the set-up is realized by changing tables that can be attached to the pick-and-place line, each changing table having at least one feed device for keeping ready stocks of components; a quantity of changing tables needed for each set-up is referred to as a changing table set and an empty changing table set includes changing tables having feed devices that are empty.

Abstract: An apparatus, methods and systems for network-sensitive data collection related to a process in an industrial environment are disclosed. The system can include a data collector communicatively coupled to a plurality of input channels and to a network infrastructure, each of the plurality of input channels communicatively coupled to at least one sensor of the industrial environment, a data storage circuit structured to store a plurality of collector routes and wherein the data collector receives collected data from the plurality of input channels utilizing a collector route, a data analysis circuit structured to determine a data collection quality parameter and interpret the collected data to determine a state value of the industrial environment and an analysis response circuit structured to adjust the selected one of the plurality of collector routes in response to one of the data collection quality parameter or the state value of the industrial environment.

Abstract: A disturbance source positioning method for positioning disturbance sources in a system including a plurality of nodes is provided. The method includes the following steps: grouping the plurality of nodes into a plurality of node groups based on an oscillation feature; establishing an in-group causality of the plurality of node groups based on a successive order of a coherent oscillation component; selecting at least one candidate group from the plurality of node groups based on the in-group causality; and positioning at least one disturbance source node in each candidate group.

Abstract: Transportation systems have artificial intelligence including neural networks for recognition and classification of objects and behavior including natural language processing and computer vision systems. The transportation systems involve sets of complex chemical processes, mechanical systems, and interactions with behaviors of operators. System-level interactions and behaviors are classified, predicted and optimized using neural networks and other artificial intelligence systems through selective deployment, as well as hybrids and combinations of the artificial intelligence systems, neural networks, expert systems, cognitive systems, genetic algorithms and deep learning.

Abstract: A system displays simulation data on a canvas. Software instructions stored on a memory device and executable by a processor display a first set of simulation data on a canvas, the first set of simulation data corresponding to a first zoom level of the canvas. Instructions adjust the canvas from the first zoom level to a second zoom level. Instructions display a second set of simulation data on the canvas, said displayed second set of simulation data corresponding to the second zoom level of the canvas.

Abstract: Systems and methods for providing data exploration techniques are provided. For instance, user inputs specifying one or more data parameters can be received. One or more data sets can be obtained from a data source based at least in part on the data parameters. The data can be grouped into one or more groupings based at least in part on the data parameters. Each data grouping can have a plurality of subsets. A distribution of data can be determined for each data subset. A plurality of data representations can be generated based at least in part on the data parameters and the distributions of data. The distributions of data for each data subset can then be compared. One or more suggested applications or at least one data subset can be determined based at least in part on the comparison.

Abstract: There is a need for more effective and efficient data modeling and/or data visualization solutions. This need can be addressed by, for example, solutions for performing data modeling and/or data visualization in an effective and efficient manner. In one example, solutions for generating a data model with dynamic relational awareness are disclosed. In another example, solutions for processing data retrieval queries using data models with dynamic relational awareness are disclosed. In yet another example, solutions for generating data visualizations using data models with dynamic relational awareness are disclosed. In a further example, solutions for integrating external data objects into data models with dynamic relational awareness are disclosed.

Abstract: Methods and systems of identifying a time reduction in a manufacturing time associated with a plurality of products. One system includes an electronic processor configured to receive training data. The electronic processor is also configured to determine a first set of testing parameters from the plurality of testing parameters to remove for the assembly line based on the training data and determine a second set of testing parameters to keep by removing the first set of testing parameters from the plurality of testing parameters. The electronic processor is also configured to determine a predictive model to replace the first set of testing parameters based on the training data associated with the second set of testing parameters, and automatically update a testing process for the assembly line to turn off the first set of testing parameters and use the predictive model in place of the first set of testing parameters.

Abstract: A load-energy efficiency evaluation and monitoring method includes an actual part processing number and a theoretical part processing number of the numerical control machine tool within an evaluation period are obtained to calculate a loading performance of the numerical control machine tool. A waste time value and a standby power value of the numerical control machine tool are obtained to calculate a waste energy value of the numerical control machine tool. A single-part actual processing energy consumption is obtained and used, together with a single-part ideal processing energy consumption, to calculate the load-energy efficiency of the numerical control machine tool. A relationship model between the load-energy efficiency and the loading performance of the numerical control machine tool is built based on the obtained model of the load-energy efficiency of the numerical control machine tool and the obtained model of the loading performance of the numerical control machine tool.

Abstract: The invention relates to a cleaning robot and a material identification method thereof, which is suitable for cleaning robots. The cleaning robot is pre-set with a threshold comparison table and comprises a plurality of comparison thresholds, wherein each comparison threshold defines an interval of accumulated energy information accumulated by the moving plane of different materials within a predetermined period of time. The cleaning robot generates accumulated energy information during the movement, so that the cleaning robot can find the comparison threshold corresponding to the accumulated energy information from the threshold comparison table, and then determines the material of the moving plane contacted by the cleaning robot.

Abstract: A control method for a human-computer interaction device, a human-computer interaction device, and a human-computer interaction system are described. The control method includes: capturing first voice information of a first object; identifying a second object related to the first voice information; acquiring first information related to the second object; and presenting the first information.

Abstract: Certain aspects of the present disclosure provide a method, including determining a plurality of constraints for a system in a first format wherein at least one constraint of the plurality of constraints comprises a discrete constraint associated with a discrete variable; converting the plurality of constraints in the first format into a set of formatted constraints in a second format; determining a near feasible solution that satisfies a first subset of formatted constraints of the set of formatted constraints; determining an optimal solution by performing an optimization technique on the near feasible solution based on the first subset of formatted constraints; converting the optimal solution of the first subset of formatted constraints into an optimal solution of the plurality of constraints in the first format; and implementing the optimal solution within the system.

Abstract: A server assembly service determines configurations for custom assembled servers based on time-series utilization metadata for servers executing workloads similar to workloads that are to be executed on the custom assembled servers. The server assembly service determines trends in the time-series utilization metadata and compares the identified trends to associations between workload utilization trends and application classes to determine one or more application classes for applications executing the workloads. The service uses the determined application classes to select server configurations for custom servers that are to be assembled to execute workloads similar to the workloads related to the server utilization metadata. In some embodiments, the service selects custom server configurations without access to applications or application data for workloads of concern.

Abstract: A method and an apparatus for reducing an effect of local process variations of a digital circuit on a hardware performance monitor includes measuring a set of performance values (c1, c2 . . . cn) of the digital circuit by n identical hardware performance monitors, where n is a natural number greater than 1, determining an average value cmean of the measured performance values (c1, c2 . . . cn), as an approximation of an ideal performance value c0, selecting one performance value cj of the set of performance values (c1, c2 . . . cn) by a controller, comparing the performance value cj with a reference value cref by a controller the controller, resulting in a deviation value ?c, and controlling an actuator by using the deviation ?c for regulating the local global process variations to the approximation cmean of the ideal performance value c0.

Abstract: An apparatus, methods and systems for monitoring network-sensitive data collection related to an industrial production process are disclosed. The system may include a data collector communicatively coupled to a plurality of input channels and to a network infrastructure, a data storage circuit structured to store a plurality of collector routes wherein the data collector receives collected data utilizing a selected collector route, a data analysis circuit structured to determine a data collection quality parameter and a state value of the industrial production process, a pattern recognition circuit structured to determine an identified pattern in response to at least a portion of the collected data and at least one of the state value or the data collection quality parameter, and an analysis response circuit structured to adjust one of the collector routes or the industrial production process in response to the identified pattern.

Abstract: A numerical control device for a machine tool, the machine tool including: a reference shaft that moves a tool or a workpiece; and a superimposition shaft that moves a tool or the workpiece. The numerical control device superimposes the movement amount of the reference shaft on the movement amount of the superimposition shaft. The numerical control device including a control computation unit that, in response to a superimposition control command, changes at least one of a first vibration rate, a second vibration rate, and a main shaft rotation speed on a basis of a first vibration command, a second vibration command and a main shaft rotation speed command such that the first vibration rate stays constant and the second vibration rate stays constant. The first vibration rate is a number of times that of the reference shaft vibrates per rotation of a main shaft.

Abstract: A system, method and apparatus for data collection related to a chemical production process are described. A system may include a data acquisition circuit structured to interpret a plurality of detection values, each of the plurality of detection values corresponding to input received from a detection package, the detection package including at least one of a plurality of input sensors coupled to at least one of a plurality of components of the process, a data analysis circuit structured to analyze a subset of the plurality of detection values to determine at least one of a sensor state, a process state, and a component state, wherein the data analysis circuit includes a pattern recognition circuit, and an analysis response circuit structured to perform an action in response to the at least one of the sensor state, the process state, and the component state.

Abstract: A method and controller system are described for automatically tuning a controller of a drilling rig. The controller system includes a controller that determines a moving average of measured values, determines a moving standard deviation of the measured values, defines an outer zone of measured values with the determined moving average and the determined moving standard deviation, defines an inner zone of measured values with the determined moving average and the determined moving standard deviation, monitors the measured values for the occurrence of statistical events with respect to the outer zone and inner zone. Based on the detected statistical event, the controller adjusts the gain of the controller the based on the statistical event being associated with the outer zone or inner zone.

Abstract: Provided is a prediction system for calculating a prediction value related to a prediction target to which prediction in an arbitrary period is adapted. The prediction system includes a storage device which records a plurality of data used to calculate the prediction value and a control device which includes a predetermined operation model and applies the plurality of data to the operation model to calculate the prediction value. The control device changes the operation model, on the basis of information of respective temporal attributes of the plurality of data.

Abstract: A prediction of an electric power consumption and/or a generation of at least one of a load and a source coupled to an electric power grid is generated responsive to a forecast of an event. A desired state of an asset on the grid is identified responsive to the prediction. A functional representation of a control scheme for the asset is identified based on a sensitivity of the control parameter to a variance in operation of the electric power grid with respect to the prediction.

Abstract: A shuttle for logistics includes a vehicle body, a supercapacitor, a straight wheel, a straight motor, a transverse wheel, a transverse motor, a synchronous belt, a position sensor, a charging contact, a lifting motor, a lifting frame, a second synchronous belt, an encoder, a PLC controller, a lifting cam, a lifting position sensor, a telescopic fork, a finger, a telescopic fork position sensor, a telescopic fork motor, an antenna, and a controller. A bottom of the vehicle body is provided with the straight wheel and the transverse wheel, and a level of the straight wheel is lower than that of the transverse wheel. The straight motor and the transverse motor are arranged on the vehicle body, respectively. The straight motor is linked to the straight wheel, and the transverse motor is linked to the transverse wheel. The supercapacitor is arranged on the vehicle body.

Abstract: A system for developing a simulation of a process. In one aspect, a system creates a first model within the simulation. The first model represents a part of the process and comprises a first port to which other models may be connected. The system also creates a second model within the simulation. The second model represents another part of the process and comprises a second port to which other models may be connected. The system then connects the first port and the second port together. Upon connection, the system allocates a memory location as a connection variable that represents a type of information transfer between the first and second ports. A first port variable, which represents a value transferrable through the first port, is set to reference the value at the allocated memory location. Similarly, a second port variable, which represents a value transferrable through the second port, is also set to reference the value at the allocated memory location.

Abstract: Sensor data is detected from at least one sensor selected and installed for detecting operating conditions of at least one equipment. The sensor data includes an operating condition of at least one equipment. The sensor is selected dependent on indications of a user restriction and a predictive model. A sensor data signal is generated dependent on the sensor data. The sensor data signal is transmitted to a network device for collecting the sensor data and transforming the collected sensor data into a formatted transmission signal having a format for transmission over a network to a network server. The network server receives the formatted transmission signal for performing on-demand service of at least one of analysis, reporting and visualization dependent on the operating condition.

Abstract: To control a technical system having multiple system components, multiple functional modules access a common data model. The functional modules in this case include an interface module, a simulation module and an output module. The data model includes data components associated with the system components and simulation model data for a simulation model of the technical system. The functional modules are actuated by a flow controller, wherein the flow controller and a respective functional module have functional-module-specific selection data transmitted between them that the respective functional module takes as a basis for accessing model data of the data model. The interface module continually captures operating data of the technical system and stores them in the data model by means of selection-data-specific access.

Abstract: Machine learning techniques provide predictions of computer system load and cooling requirements, allowing cooling systems to anticipate, prepare for, and ameliorate, those requirements. Techniques provide confirmation or denial that the computer and cooling systems are operating as expected, allowing those systems to determine if any parts are failing. Techniques provide information regarding likely effect due to proposed changes. Techniques provide probabilistic predictions, well in advance, of whether parts will fail or degrade. Techniques provide probabilistic predictions whether parts will fail or degrade, responsive to degrees of redundancy, set points for of cooling, or set points when cooling starts or ends.

Abstract: A system for performing industrial tasks includes a robot and a computing device. The robot includes one or more sensors that collect data corresponding to the robot and an environment surrounding the robot. The computing device includes a user interface, a processor, and a memory. The memory includes instructions that, when executed by the processor, cause the processor to receive the collected data from the robot, generate a virtual recreation of the robot and the environment surrounding the robot, receive inputs from a human operator controlling the robot to demonstrate an industrial task. The system is configured to learn how to perform the industrial task based on the human operator's demonstration of the task, and perform, via the robot, the industrial task autonomously or semi-autonomously.

Abstract: Real-time dynamic process modeling in an online model-based process control computing environment. A solver system utilizes an oracle to implement adaptive algorithms for a mixed integer nonlinear programming (MINLP) solver and a nonlinear programming (NLP) solver.

Abstract: A method includes identifying one or more proxy limit variables to be used to define an operating envelope associated with an industrial process controller. The industrial process controller is associated with a number of process variables including the proxy limit variable(s). The method also includes maximizing and minimizing at least one of the proxy limit variable(s). The method further includes presenting maximum and minimum values of the at least one of the proxy limit variable(s) as the operating envelope in a graphical user interface to at least one user. A single proxy limit variable could be used, and maximum and minimum values of the single proxy limit variable can be presented in a one-dimensional representation of the operating envelope. Multiple proxy limit variables could also be used, and maximum and minimum values of the proxy limit variables can be presented in a multi-dimensional representation of the operating envelope.

Abstract: Techniques for streaming big data in a process plant are disclosed. Generally, these techniques facilitate storage or communication of process control data, including alarms, parameters, events, and the like, in near real-time. Receivers of big data, such as big data historians or devices requesting specific data, are configured via an initial set of metadata, and thereafter receive updated metadata upon requesting it from the transmitting device, such as when the receiving device encounters an identifier in the data, which identifier was not defined in the metadata previously received.

Abstract: A computer-implemented method includes dividing a textual representation of a media content into a plurality of portions separated at temporal boundaries of the media content and performing an analysis of each portion of the plurality of portions of the textual representation of the media content to determine a characteristic associated with each respective portion of the textual representation of the media content, generating a multi-dimensional model assigning each determined characteristic to each associated respective portion of the plurality of portions of the textual representation of the media content, the multi-dimensional model identifying each determined characteristic and the temporal boundaries to enable control of an environmental control device to modify an environment proximate to a user based on the multi-dimensional model, and transmitting the multi-dimensional model to a user equipment configured to control the environmental control device to modify the environment proximate to the user base

Abstract: Bits for acknowledgement (ACK) and/or negative acknowledgement (NAK) may be allocated based on whether a special subframe configuration in a TDD configuration permits downlink transmission. For carrier aggregation, ACK/NAK bits may be allocated only to special subframes in component carriers (CCs) which permit downlink transmission. Also, for example, ACK/NAK bits may be allocated to all CC special subframes if a single CC is configured to allow downlink transmission on one of its special subframes. ACK/NAK bits may also be allocated to all special subframes.

Abstract: A control circuit includes: a controller; a controlled system; and a filter for smoothing a return signal. The controller acts on the controlled system vis-à-vis a control signal and the return signal acts on the controller. The controller and the filter are simultaneously adjustable by an adjustment. In an embodiment, the adjustment is made on the basis of a method that includes: measuring or estimating an output signal as a measurement or estimate; transferring, using the measurement or estimate, the output signal into the return signal; determining a power density spectrum of the return signal; and limiting a control signal of the controller such that a power of the control signal does not exceed a predefined limiting value.

Abstract: A method for operating and observing a technical plant to be controlled, wherein block symbols for plant schematics can be generated which are structured, personalized, and assembled dynamically at runtime which, for example, enable an efficiently guided and assisted handling of alarm messages by an operator, where the dynamically updated display of alarm-producing process objects based on an equipment hierarchy enables an evaluation of items causing floods of alarms.

Abstract: Embodiments of the invention relate to implementing a probabilistic graphical model (PGM) using magnetic tunnel junctions (MTJs). One embodiment comprises a memory array of magnetic tunnel junctions and a driver unit for programming the memory array to represent a probabilistic graphical model. The magnetic tunnel junctions are organized into multiple subsets of magnetic tunnel junctions. The driver unit selectively applies an electrical pulse to a subset of magnetic tunnel junctions to program information representing a probabilistic belief state in said subset of magnetic tunnel junctions.

Abstract: Systems and methods are disclosed for monitoring models monitoring Internet-connected devices. Systems and methods include receiving, from an Internet-connected devices monitoring system, training data, the Internet-connected devices monitoring system being configured to predict future maintenance needs and/or failures of at least one Internet-connected device. Systems and methods further include receiving, from the Internet-connected devices monitoring system, production data associated with the at least one Internet-connected device, and determining that a data distance metric between the training data and the production data exceeds a first predetermined risk threshold. Systems and methods further include determining a risk level to be associated with the Internet-connected devices monitoring model based on the determination that the data distance metric exceeds the first predetermined risk threshold.