Abstract: The present invention relates to a method for controlling a building automation system comprising the steps of measuring at least two indoor environmental quality parameter values, calculating for the measured indoor environmental quality parameter values a dimensionless indoor environmental quality index from the respective measured indoor environmental quality parameter value, calculating a control index as a weighted sum of the indoor environmental quality indices, and defining a predetermined upper threshold index and starting a control procedure when the control index is below the predetermined upper threshold index, or defining a predetermined lower threshold index and starting the control procedure when the control index is above the predetermined lower threshold index, wherein the control procedure includes controlling the BAS such that at least one, multiple or all indoor environmental quality indices are each within a respective first predetermined range.

Abstract: Centralized data set management techniques are implemented for data sets for machine learning applications. New data sets may be created from a search of managed data set labels. Data objects of the managed data sets that are found in the search are then used to generate a new data set. The new data set is then made available for machine learning applications to use.

Abstract: A computer system and associated processes are disclosed for grouping similar real estate properties into contiguous neighborhoods, and for generating neighborhood-specific models capable of estimating property values within their respective neighborhoods. A clustering component uses various sources of property-level data to group properties based on measures of property similarity. For example, the clustering component may measure property similarity based on how frequently specific properties are designated as comparable in appraisal reports. A model generator uses a machine learning process to determine, for specific neighborhoods, correlations between property attributes and values, and uses these correlations to generate the neighborhood specific models.

Abstract: Embodiments control and optimize batch processes. An embodiment obtains and standardizes historical operating data from a plurality of batch production runs of an industrial process. For each batch production run, the standardized operating data corresponding to the batch is partitioned into one or more stages and one or more signature for each stage is determined using the partitioned standardized data. Each determined signature is associated with a class label based upon whether output of a batch run corresponding to the signature conforms or does not conform with operational standards. A model is trained, with at least a subset of the signatures as inputs and associated class labels as outputs, to predict, based on operating data from a real-world batch process, whether output of the process will conform or not conform with the operational standards. Online predictions can be automatically or manually applied to control and optimize a batch production run.

Abstract: A tightening apparatus and a control method for the tightening apparatus are provided. The tightening apparatus includes a mounting main body and a plurality of tightening mechanisms provided on the mounting main body. Each of the tightening mechanisms includes: a tightening actuation module, configured to tighten a fastener into a mounting hole along an axis in a first direction; a visual positioning module, configured to collect image information of the fastener located in the mounting hole, determine positioning information of the fastener based on the image information, and determine second-direction position compensation information and third-direction position compensation information of the tightening actuation module based on the positioning information; a second-direction driving mechanism, configured to drive the tightening actuation module to move in a second direction based; and a third-direction driving mechanism, configured to drive the tightening actuation module to move in a third direction.

Abstract: The present invention is a wind farm control method implementing an acquisition (ACQ) of a wind speed and direction distribution, an acquisition of the wind speed and direction in real time (Vac), a wind farm model (MOD F) and a load model (MOD C) for each wind turbine. Finally, an optimization step (OPT) allows target operating points to be determined for each turbine. The optimization step implements optimization of an expected value of the energy generated for the entire wind speed and a direction distribution according to an expected value of the load of each turbine for the entire wind speed and direction distribution. The target operating points (target yaw angles for example) are then applied to the turbines of the wind farm (CON).

Abstract: Spectral data associated with one or more regions of a surface of a substrate is identified. The substrate has been processed according to one or more first operations of a process recipe that is unknown to a system controller for the manufacturing system. The spectral data is provided as input to a machine learning model that is trained to predict, based on given spectral data, a respective process recipe associated with the substrate and one or more operations of the respective process recipe that have already been performed. A determination is made, based on one or more outputs of the machine learning model, that the substrate is associated with the process recipe and that one or more second operations are yet to be performed. The substrate is caused to be processed according to the one or more second operations of the process recipe.

Abstract: Systems and methods for data Process an optimized analytics environment are disclosed. The system may enable users to create data processing requests, interact with various data sources and datasets, and generate data processing outputs. The system may receive a data processing request from an audio-enabled input source or a UI-based input source. The system may determine whether the data processing request at least partially matches a stored data processing request. The system may receive a data processing request selection comprising the data processing request or the stored data processing request. The system may execute the data processing request selection on a data source.

Abstract: A tertiary frequency modulation method for a power system, AGC based on power plant input performs active power regulation for tertiary frequency modulation in different modes in power plants in case of secondary frequency modulation failure of the power system and unidirectional deviation of grid frequency from rated frequency for a period: perform tertiary frequency modulation based on the reserved capacity of the secondary frequency modulation or the regulation amount of primary frequency modulation or random parameters. The invention relates to tertiary frequency modulation whose action sequence is later than that of the primary frequency modulation and the secondary frequency modulation to realize astatic frequency regulation.

Abstract: A device and method operated thereby may control a hydraulic pump to pump a hydraulic fluid into a chamber of a piston coupled to a fifth wheel of the tractor to raise the fifth wheel. The device, and method operated thereby, may sense, at intervals as the fifth wheel rises, a pressure value of the hydraulic fluid in the chamber. The device, and method operated thereby, may process the pressure values to determine when the landing gear is lifted off the ground.

Abstract: The present disclosure relates to a control device for electrical installations, which has improved signaling capabilities in alert conditions, particularly when said control device is no more fed by a power supply and it cannot carry out its control and monitoring functionalities. In a further aspect, the present disclosure relates to a computerized signaling system for an electrical installation, characterized in that it comprises one or more control devices having the above-mentioned improved signaling capabilities and a software application stored in one or more mobile computerized devices. Said software application is configured to make each mobile computerized mobile detect the beacon data packets broadcasted by said control devices in alert conditions.

Abstract: Systems and methods for content snippet generation, storage, and suggestion can include obtaining a user input, segmenting a sub-portion of displayed content based on the user input, and generating a content snippet that includes the segmented content and source data associated with the displayed content. A generative model can be leveraged to categorize the content snippet, determine similar content, and determine when to surface the content snippet to a user.

Abstract: Disclosed is a self-learning method of a knowledge-based dialogue system. The method includes generating, by the query generating module, a natural language query by itself based on a knowledge path for a query selected from a knowledge graph, inferring, by the answer generating module, a knowledge path for an answer corresponding to a query intention of the natural language query from the knowledge graph, and generating a natural language answer by itself based on the knowledge path for an answer, comparing and evaluating, by the dialogue evaluating unit, the knowledge path for a query and the knowledge path for an answer, and learning, by the query generating module and the answer generating module, a dialogue between the query generating module and the answer generating module based on an evaluation result of the dialogue evaluating unit.

Abstract: In a wireless power transfer system configured to contactlessly transfer power from a supply device in a road to a vehicle, the vehicle includes a plurality of power receiving devices configured to receive power from the supply device, and a power transfer ECU is configured to set, based on state information from the vehicle, a power transfer pattern by which each of a plurality of segments transfers power, the power transfer pattern being set for each power transfer device. The power transfer ECU is configured to cause each of the power transfer devices to transfer power based on the power transfer pattern.

Abstract: An appliance control method and appliance control device is disclosed, the appliance control method includes: acquiring a user action of a user and predicting a plurality of action information items about future user actions of the user based on the user action, the plurality of action information items including a plurality of actions and predicted times at which the plurality of actions are predicted to be performed. The appliance control method further includes determining appliance control operations corresponding to the plurality of actions based on the plurality of actions and the predicted times and performing the appliance control operations based on the predicted times.

Abstract: A method and apparatus for detecting and prioritizing loads comprising a load analyzer configured to receive at least one load monitoring signal from at least one channel, where each channel is configured to be coupled to at least one load, and analyze at least one load signature derived from the at least one load monitoring signal to detect a load type that is connected to the at least one channel and assign an energy consumption priority to the at least one load.

Abstract: An apparatus control device includes a processor that acquires a stimulus acting on an apparatus from an outside, and sets an action time based on the acquired stimulus data, the action time being related to a behavior that a user of the apparatus habitually performs, the action time being a time at which the apparatus acts.

Abstract: A computer system for real-time coordinated operation of power distribution systems and electric vehicles identifies a set of integrated hybrid resources (IHRs), wherein each IHR within the set of IHRs comprises one or more of: energy storage (ES) systems, solar generating units, electric vehicles (EVs), and/or inflexible loads. The computer system executes, at an IHR selected from the set of IHRs, a deep deterministic policy gradient (DDPG) algorithm, the DDPG algorithm utilizing a critic deep neural network and an actor deep neural network. The critic deep neural network estimates a Q-value of an action for a given state, and the actor deep neural network estimates a best action for the given state. Based upon an output of the DDPG algorithm, the computer system generates a charging schedule for the ES systems and the EVs within the IHR.

Abstract: An actuator assembly provides redundancy to maintain operation when a driver link is inoperable due to jamming or breakage of a prime mover, gear, link, or other drivetrain component. The actuator assembly includes a first motor and a second motor that each generate rotational forces. A first driver link is coupled to the first motor and to a first output link. Similarly, a second driver link is coupled to the second motor and to the second output link. The first output link and the second output link are also coupled to a connecting link. The connecting link exhibits a displacement force to control an angle of a control surface in an aircraft, or other vehicle, or equipment. A controller changes the control mode to enable a desired output state to be achieved in a normal operation or under a fault condition when one of the driver links is non-operational.

Abstract: A three-dimensional (3D) printer system for printing structures on a property, including a 3D printing apparatus comprising an extruder configured to layer material to manufacture a structure, and a processor configured to receive a non-fungible token (NFT) that includes a blueprint for a printable structure and a numerical index. The numerical index is a number of allowed printing operations for the blueprint. The processor may also determine whether the numerical index is above zero. Additionally, the processor may, in response to determining that the numerical index is above zero, cause the 3D printing apparatus to manufacture the printable structure based on the blueprint, and subtract one from the numerical index after the 3D printing apparatus has manufactured the printable structure.