Abstract: An industrial plant machine learning system includes a machine learning model, providing machine learning data, an industrial plant providing plant data and an abstraction layer, connecting the machine learning model and the industrial plant, wherein the abstraction layer is configured to provide standardized communication between the machine learning model and the industrial plant, using a machine learning markup language.

Abstract: The present disclosure includes a heating, ventilation, and/or air-conditioning (HVAC) control system with a controller and a device communicatively coupled to the controller. The device is configured to implement an engagement protocol, wherein to grant the controller write access to protected registers of the device the engagement protocol functions to require: receiving a reset command at a reset register of the device; receiving a passcode at a passcode register of the device; matching the passcode received at the passcode register to an authentication passcode; and receiving or matching the passcode within a timeframe defined by a timer.

Abstract: A work type identification apparatus (2000) acquires, for a target region (12) of a target object (10) on which a wiping work is to be performed, a 5 temperature data sequence (40) indicating a time variation of a temperature of the target region (12). The work type identification apparatus (2000) determines a type of wiping work performed on the target region (12) based on the time variation of the temperature of the target region (12) indicated by the temperature data sequence (40).

Abstract: An information processing device includes a memory, and a processor configured to execute a process. The process includes acquiring a first controller model, the first controller model including information indicating a control condition based on a measurement value, and information indicating a control action defining an action of a control target when the control condition is satisfied; and outputting a second controller model, the second controller model being capable of tolerating a measurement value including a measurement error, wherein the second controller model includes information indicating a control condition based on the information indicating the control condition included in the first controller model, and information indicating a control action based on the information indicating the control condition and the information indicating the control action included in the first controller model.

Abstract: A program fragmentation unit (131) divides a target program into fragments according to groups of processing. A fragment group extraction unit (132) extracts, from among sets of fragments, each set in which instruction groups match between fragments, as a fragment group. A functionalization candidate extraction unit (136) extracts, from among sets of fragment groups, a set in which instruction groups match between fragment groups, usage patterns of a variable group match between the fragment groups, and types of variables match between the fragment groups, as a functionalization candidate. An output unit (140) outputs information on the functionalization candidate.

Abstract: A location tracking system includes a plurality of markers disposed on a fixture in an area having an absolute coordinate in the factory, an image collecting device fixedly attached to a tracking target for management, configured to recognize an absolute location of a reference marker detected by a visual odometry (VO) method in an image captured by a camera, and estimate a relative location based on the absolute location of the reference marker; and a server configured to track a location of the target based on the relative location received through a wireless communication from the image collecting device.

Abstract: Implementations are described herein for providing a GUI that is designed to visualize how aliases are assigned and/or distributed in a process automation facility. In various implementations, alias registration data associated with distributed control nodes (DCNs) of a process automation facility may be retrieved. The alias registration data may include mappings between connection strings of input/output (I/O) channels made accessible by the DCNs and aliases registered to the I/O channels. A graphical user interface (GUI) may be rendered with graphical elements that visualize at least some of the DCNs and at least some of the mappings between the connection strings and the aliases. The mappings may be analyzed to detect irregularities among the registered aliases. One or more of the graphical elements of the GUI that correspond to the one or more detected irregularities among the registered aliases may be visually emphasized.

Abstract: A system for autonomously generating an implementing a machine executable file is disclosed herein. The system can include a node and an artificial intelligence generated machine executable (“AGMX”) platform communicatively coupled to the node. The AGMX platform can include a control circuit and a memory to store an artificial intelligence model that, when executed by the control circuit, causes the AGMX platform to receive a user input including an objective, generate an instruction for the node to execute based on the objective, determine a management authority protocol to be assigned to the node, wherein the management authority protocol defines an ability of the node to deviate from the instruction, generate an AGMX file including the instruction and the management authority protocol, wherein the AGMX file is to be executed by the node, and transmit the AGMX file to the node for execution by the node.

Abstract: An agricultural implement includes a plurality of ground-engaging tools configured to modify a surface configuration of an agricultural field and a hydraulically-controlled subsystem configured to modify an operating angle of the plurality of ground-engaging tools. The agricultural implement also includes a sensor coupled to the hydraulically-controlled subsystem configured to generate sensor signals indicative of a current operating angle of the plurality of ground-engaging tools. The agricultural implement also includes an implement control system configured to receive the sensor signals from the sensor to determine the current operating angle of the plurality of ground-engaging tools, and, upon determining the current operating angle is to be changed to a new operating angle, generate control signals for the hydraulically-controlled subsystem to modify the operating angle of the plurality of ground-engaging tools from the current operating angle to the new operating angle.

Abstract: A system can comprise a processor and a memory that can store executable instructions that, when executed by the processor, facilitate performance of operations comprising generating data comprising a power source identifier to be transmitted as a data transmission; and transmitting, to a power consumer, the data transmission via a power connection from a power source. The data transmission can comprise other information related to the power source. The operations can further comprise receiving one or more consumption data transmissions from one or more power consumers, wherein the one or more power consumers are associated with the power source and comprise the power consumer, and wherein at least one of the one or more consumption data transmissions comprises a consumption indicator associated with the power consumer.

Abstract: A system of nodes generates machine instructions representing a tool path for a tool to manufacture an object from a workpiece material. The system includes a generator node, adapted to generate and transmit a raw pass packet. The raw pass packet includes a plurality of passes, each pass having a plurality of points, and each point detailing a location in space to be traversed by the tool to manufacture an object from the material. The system includes a filter node, that receives, modifies and transmits the raw pass packet. A processing node is adapted to receive the raw pass packet and convert it to another format. The nodes are arranged as a directed acyclic graph, each node being associated with an ordering number and each node only transmitting data to a node with a higher ordering number and only receiving data from a node with a lower ordering number.

Abstract: According to the present disclosure, a method includes, wherein a processor, acquiring an activity quantity data of an animal, calculating an exercise consumption energy quantity of the animal based on the activity quantity data, calculating an estimation consumption energy quantity of the animal based on an information of a body weight of the animal, correcting the estimated consumption energy quantity of the animal using the exercise consumption energy quantity of the animal, and outputting an information related to the corrected estimation consumption energy quantity.

Abstract: A method for automatic identification of important batch events for a batch execution alignment algorithm, including receiving historical batch data of a batch process, wherein the historical batch data comprises a plurality of batch executions, and wherein each of the plurality of batch executions comprises a plurality of batch events, indicating a specific event of the batch process, and at least one time series of a process variable, indicating a development of the process variable during the batch process; determining a distance between the at least one time series of the plurality of the batch executions for each of the plurality of batch events; and identifying at least one important batch event for a batch execution alignment algorithm with a smallest distance using the determined distances.

Abstract: A method for solving multiple OPF equations of an AC electrical power system with plural topologies and admittances is provided. The method includes determining a continuous admittance space to embed the plural topologies, determining a plurality of voltage magnitudes and a plurality of voltage phase angles of the plurality of buses by a deep neural network, and reconstructing an active power generation and a reactive power generation using power flow equations according to the plurality of voltage magnitudes, the plurality of voltage phase angles, and the load inputs. The continuous admittance space is an admittance matrix of a plurality of line admittances each having a default admittance computed using a conductance and a susceptance of the plurality of branches. The deep neural network receives the load inputs and the plurality of line admittances as inputs.

Abstract: A computer-implemented technique of determining a trajectory defined by a guide wire or other elongated member is presented. A method implementation of the technique in one variant comprises obtaining image data representative of a guide wire placed in a bone, processing the image data to determine an extension of the guide wire, and selecting a portion of the guide wire extension. The method further comprises determining, from the selected portion of the guide wire extension, trajectory data indicative of a guide wire-defined trajectory.

Abstract: The present disclosure describes computer systems and computer-implemented methods for use in an agricultural operation. Vehicle location information for at least one agricultural vehicle is received, and the vehicle location information is used to determine a vehicle path. Vehicle state information is received from the vehicle and is used to determine whether the vehicle is in a working or non-working state. The vehicle path is then rendered on a map display, with the map display visually distinguishing between sections of the vehicle path traversed while the vehicle is in the working state and sections of the vehicle path traversed while the vehicle is in the non-working state.

Abstract: A system and method for prediction of failures and optimization, that can provide solution available for unsupervised learning models based on limited data that can predict different types of failure and pre-failure instances. The solution provides improvement upon previous methods of labelling by marking certain days data ahead of failure as belonging to failure data which will result in reduction of noisy data and improves good working condition data. The present invention helps with improved data quality due to labelling as the proposed method models complex distributions of feature vectors accurately and are better at finding deviations from normal data distribution which is used for detecting failures. The novel solution help to analyse and categorise the type of failures for PC Pumps currently deployed in CBM Fields for which failure days in advance can be predicted.

Abstract: It is possible to precisely manage a task in operation by precisely inferring the task with use of a trained model that is constructed by machine learning. A task management device (3) includes: a first outputting section (312) configured to output a detection class that is inferred to appear in a task at a time point at which a captured image is obtained, the detection class being inferred by inputting the captured image to an index inference model (321); and a task inferring section (314) configured to infer, on the basis of an output result from the first outputting section, the task being carried out at the time point at which the captured image is obtained.

Abstract: A server includes a storage storing data on chargers each configured to charge or discharge electric power to or from a vehicle with an electrical storage device, and a processor configured to send a user of the vehicle a message that makes a proposal to charge or discharge the vehicle by using at least one of the chargers when the vehicle travels toward a destination. The processor is configured to acquire, for each of the chargers, power supply and demand information on power demand or supply in a power grid of a region in which the charger is installed, extract a charger installed in a region with larger power demand or supply than another region from among the chargers based on predetermined information including the power supply and demand information, and send the message that makes a proposal to charge or discharge the vehicle by using the extracted charger.

Abstract: Systems and methods for monitoring apparatus(es) and equipment using a sensor cluster are described. The systems and methods can be used to automatically repair or otherwise address actual and predicted failure modes of the apparatus(es), which include electrical systems, power systems, energy storage systems, and other systems.