Abstract: Methods and systems for generating a neural network (NN)-based climate forecasting model are disclosed. The methods and systems perform steps of selecting a global climate simulation dataset from a plurality of simulation datasets each generated from a global climate simulation model; training the NN-based climate forecasting model on the selected global climate simulation dataset; and validating the NN-based climate forecasting model using observational historical climate data. Embodiments of the present invention enable accurate climate forecasting without the need to run new dynamical global climate simulations on supercomputers. Also disclosed are benefits of the new methods, and alternative embodiments of implementation.

Abstract: Methods and systems for training a neural network (NN)-based climate forecasting model on a pre-processed multi-model ensemble of global climate simulation data from a plurality of global climate simulation models (GCMs), are disclosed. The methods and systems perform steps of determining a common spatial scale and a common temporal scale for the multi-model ensemble of global climate simulation data; spatially re-gridding the multi-model ensemble to the common spatial scale; temporally homogenizing the multi-model ensemble to the common temporal scale; augmenting the spatially re-gridded, temporally homogenized multi-model ensemble with synthetic simulation data generated from the spatially re-gridded, temporally homogenized multi-model ensemble; and training the NN-based climate forecasting model using the spatially re-gridded, temporally homogenized, and augmented multi-model ensemble of global climate simulation data.

Abstract: Hybrid bonded die stacks, related apparatuses, systems, and methods of fabrication are disclosed. One or both of an integrated circuit (IC) die hybrid bonding region and a base substrate hybrid bonding region are surrounded by a protective layer and hydrophobic structures on the protective layer. The protective layer is formed prior to pre-bond processing to protect the hybrid bonding region during plasma activation, clean test, high temperature processing, or the like. Immediately prior to bonding, the hydrophobic structures are selectively applied to the protective layer. The hybrid bonding regions are brought together with a liquid droplet therebetween, and capillary forces cause the IC die to self-align. A hybrid bond is formed by evaporating the droplet and a subsequent anneal. The hydrophobic structures contain the liquid droplet for alignment during bonding.

Abstract: Methods and systems for generating a neural network (NN)-based climate forecasting model are disclosed. The methods and systems perform steps of selecting a global climate simulation dataset from a plurality of simulation datasets each generated from a global climate simulation model; training the NN-based climate forecasting model on the selected global climate simulation dataset; and validating the NN-based climate forecasting model using observational historical climate data. Embodiments of the present invention enable accurate climate forecasting without the need to run new dynamical global climate simulations on supercomputers. Also disclosed are benefits of the new methods, and alternative embodiments of implementation.

Abstract: A method of controlling signal transmission in a building control system including measuring a number of signal values associated with an environmental variable using a sensor of a wireless device, dynamically determining, by the wireless device, a noise threshold based on the number of signal values, combining a first signal value and a second signal value of the number of signal values using a mathematical relationship to determine a result associated with the first signal value and the second signal value, and periodically transmitting the first signal value from the wireless measurement device to a controller in response to the result exceeding the noise threshold.

Abstract: Methods and systems for generating a multi-model ensemble of global climate simulation data from a plurality of pre-existing global climate simulation model (GCM) datasets, are disclosed. The methods and systems perform steps of computing a GCM dataset validation measure based on at least one sample statistic for at least one climate variable from the pre-existing GCM dataset; selecting a validated subset of the plurality of pre-existing GCM datasets; selecting a subset of GCM datasets; generating candidate ensembles of GCM datasets; computing an ensemble forecast skill score for each candidate ensemble based on a model analog; generating the multi-model ensemble of GCM datasets by selecting a candidate ensemble with a best ensemble forecast skill score; and training the NN-based climate forecasting model using the multi-model ensemble of GCM datasets. Embodiments of the present invention enable accurate climate forecasting without the need to run new dynamical global climate simulations on supercomputers.

Abstract: Methods and systems for generating a multi-model ensemble of global climate simulation data from a plurality of pre-existing global climate simulation model (GCM) datasets, are disclosed. The methods and systems perform steps of computing a GCM dataset validation measure based on at least one sample statistic for at least one climate variable from the pre-existing GCM dataset; selecting a validated subset of the plurality of pre-existing GCM datasets; selecting a subset of GCM datasets; generating one or more candidate ensembles of GCM datasets; computing an ensemble forecast skill score for each candidate ensemble of GCM datasets; generating the multi-model ensemble of GCM datasets by selecting a candidate ensemble of GCM datasets with a best ensemble forecast skill score; and training the NN-based climate forecasting model using the multi-model ensemble of GCM datasets.

Abstract: In aspects, methods and apparatus are provided for the generation of haptic command signals to cause haptic effect outputs at one or more haptic output devices. The haptic command signals may be generated based on haptic media, supplementary media, and/or haptic device capability. Generating the haptic command signals may include creation or modification of haptic effects, distribution of haptic effects, and/or warping of haptic signals. The methods and apparatus may operate according to combinations of developer provided rules and system enabled inferences. Numerous other aspects are provided.

Abstract: In aspects, methods and apparatus are provided for the generation of haptic command signals to cause haptic effect outputs at one or more haptic output devices. The haptic command signals may be generated based on haptic media, supplementary media, and/or haptic device capability. Generating the haptic command signals may include creation or modification of haptic effects, distribution of haptic effects, and/or warping of haptic signals. The methods and apparatus may operate according to combinations of developer provided rules and system enabled inferences. Numerous other aspects are provided.

Abstract: A method includes receiving samples of one or more monitored variables relating to building equipment, updating a statistical metric of the samples, determining whether the building equipment is operating in a steady state or operating in a transient state using the statistical metric of the samples, and adjusting an operation that uses the samples as an input based on whether the building equipment is operating in the steady state or operating in the transient state.

Abstract: A method and apparatus for determining a pressure in an annulus between an inner casing and an outer casing. An acoustic transducer is disposed within the casing at a selected depth within the inner casing and is configured to generate an acoustic pulse and receive a reflection of the acoustic pulse from the inner casing. A time of flight is measured of the acoustic pulse to the inner surface of the inner casing. An inner diameter of the inner casing is determined from the time of flight. The pressure in the annulus is determined from the inner diameter. A processor can be used to measure time and determine inner diameter and annulus pressure.

Abstract: A method of controlling signal transmission in a building control system including measuring a number of signal values associated with an environmental variable using a sensor of a wireless device, dynamically determining, by the wireless device, a noise threshold based on the number of signal values, combining a first signal value and a second signal value of the number of signal values using a mathematical relationship to determine a result associated with the first signal value and the second signal value, and periodically transmitting the first signal value from the wireless measurement device to a controller in response to the result exceeding the noise threshold.

Abstract: A method for performing extremum-seeking control of a plant includes determining multiple values of a correlation coefficient that relates a control input provided as an input to the plant to a performance variable that characterizes a performance of the plant in response to the control input. The performance variable includes a noise-free portion and an amount of noise. The method includes determining an adjusted correlation coefficient by scaling a first value of the correlation coefficient selected from the multiple values relative to a second value of the correlation coefficient selected from the multiple values. The adjusted correlation coefficient relates the noise-free portion of the performance variable to the control input. The method includes using the adjusted correlation coefficient to modulate the control input provided as an input to the plant.

Abstract: A temperature control system. The control system includes a flow sensor configured to monitor water flow through a valve, an actuator coupled to the valve, and a first controller configured to establish a setpoint for a second controller. The second controller monitors fluid flow through the valve and combines a weighted first command from the first controller and a weighted second command from the second controller to generate a control signal, wherein combining the weighted first command and the weighted second command is based on the reliability of the flow sensor. The second controller further controls the actuator based on the control signal.

Abstract: Methods and systems for training a neural network (NN)-based climate forecasting model on a pre-processed multi-model ensemble of global climate simulation data from a plurality of global climate simulation models (GCMs), are disclosed. The methods and systems perform steps of determining a common spatial scale and a common temporal scale for the multi-model ensemble of global climate simulation data; spatially re-gridding the multi-model ensemble to the common spatial scale; temporally homogenizing the multi-model ensemble to the common temporal scale; augmenting the spatially re-gridded, temporally homogenized multi-model ensemble with synthetic simulation data generated from the spatially re-gridded, temporally homogenized multi-model ensemble; and training the NN-based climate forecasting model using the spatially re-gridded, temporally homogenized, and augmented multi-model ensemble of global climate simulation data.

Abstract: A method of controlling signal transmission in a building control system including measuring a number of signal values associated with an environmental variable using a sensor of a wireless device, dynamically determining, by the wireless device, a noise threshold based on the number of signal values, combining a first signal value and a second signal value of the number of signal values using a mathematical relationship to determine a result associated with the first signal value and the second signal value, and periodically transmitting the first signal value from the wireless measurement device to a controller in response to the result exceeding the noise threshold.

Abstract: Embodiments of the present invention use radar technology to detect features or conditions in a well. A radar unit having an electronics subsystem and an antenna subsystem is positioned downhole in the well. The radar unit is coupled receive power from and communicate with to a surface system. The electronics subsystem generates RF signals which are provided to the antenna subsystem, generating radar wavefronts that are propagated toward areas of interest (e.g., farther downhole). The radar wavefronts may be electronically or mechanically steered in the desired direction. The antenna subsystem receives radar signals that are reflected back to the unit by features or conditions in the well. The received reflected signals are converted to electronic signals that are interpreted by the electronics subsystem of the radar unit or by the surface system to identify the features or conditions that caused the reflections.

Abstract: Methods and systems for training a neural network (NN)-based climate forecasting model on a pre-processed multi-model ensemble of global climate simulation data from a plurality of global climate simulation models (GCMs), are disclosed. The methods and systems perform steps of determining a common spatial scale and a common temporal scale for the multi-model ensemble of global climate simulation data; spatially re-gridding the multi-model ensemble to the common spatial scale; temporally homogenizing the multi-model ensemble to the common temporal scale; augmenting the spatially re-gridded, temporally homogenized multi-model ensemble with synthetic simulation data generated from the spatially re-gridded, temporally homogenized multi-model ensemble; and training the NN-based climate forecasting model using the spatially re-gridded, temporally homogenized, and augmented multi-model ensemble of global climate simulation data.

Abstract: A self-perturbing extremum-seeking controller for a plant that includes at least a static portion includes a processing circuit. The processing circuit is configured to obtain a value of a performance variable characterizing a performance of the plant. The processing circuit is configured to determine a sign of a gradient of the performance variable with respect to an input to the static portion of the plant. The processing circuit is configured to adjust a control input for the plant using the sign of the gradient, and provide the control input to the plant to affect the performance variable.

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.