Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for optimizing a process of polishing semiconductor wafers. In one aspect, the method comprises repeatedly performing the following: i) selecting a configuration of input settings for polishing a semiconductor wafer, based on a causal model that measures current causal relationships between input settings and a quality of semiconductor wafers; ii) receiving a measure of the quality of the semiconductor wafer polished with the configuration of input settings; and iii) adjusting, based on the measure of the quality of the semiconductor wafer polished with the configuration of input settings, the causal model.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for optimizing parameters of one or more proportional-integral-derivative (PID) controllers. In one aspect, the method comprises repeatedly performing the following: i) selecting a configuration of respective PID parameters for each of the plurality of PID controllers, based on a causal model that measures causal relationships between PID parameters and a measure of success in controlling the system; ii) determining the measure of success of the configuration of respective PID parameters for the plurality of PID controllers in controlling the system; and iii) adjusting, based on the measure of success of the configuration of respective PID parameters for the plurality of PID controllers in controlling the system, the causal model.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining causal models for controlling environments. One of the methods includes repeatedly selecting, by a control system for the environment, control settings for the environment based on internal parameters of the control system, wherein: at least some of the control settings for the environment are selected based on a causal model, and the internal parameters include a first set of internal parameters that define a number of previously received performance metric values that are used to generate the causal model for a particular controllable element; obtaining, for each selected control setting, a performance metric value; determining that generating the causal model for the particular controllable element would result in higher system performance; and adjusting, based on the determining, the first set of internal parameters.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for optimizing a manufacturing process. In one aspect, the method comprises repeatedly performing the following: i) selecting a configuration of control settings for a manufacturing process, based on a causal model that measures causal relationships between control settings and a measure of a success of the manufacturing process; ii) determining the measure of the success of the manufacturing process using the configuration of control settings; and iii) adjusting, based on the measure of the success of the manufacturing process using the configuration of control settings, the causal model.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining causal models for controlling environments. One of the methods includes repeatedly selecting control settings for the environment based on (i) a causal model that identifies causal relationships between possible settings for controllable elements in the environment and environment responses that reflect a performance of the control system in controlling the environment and (ii) current values of a set of internal parameters; and during the repeatedly selecting: monitoring environment responses to the selected control settings; determining, based on the environment responses, an indication that one or more properties of the environment have changed; and in response, modifying the current values of one or more of the internal parameters.

Abstract: Example techniques of this disclosure are directed determining one or more values that represent a monitoring attribute for one or more body-worn tracking devices (BWTDs). In some instances, the techniques include determining a compliance metric that represents a level of compliance for at least one offender. That is, the compliance metric may be a quantitative value that represents whether a user wearing BWTD is complying with established rules or desired behaviors.

Abstract: Method for active battery management to optimize battery performance. The method includes providing signal injections for charging and discharging of a battery. The signal injections include various charging and discharging profiles, rates, and endpoints. Response signals corresponding with the signal injections are received, and a utility of those signals is measured. Based upon the utility of the response signals, data relating to charging and discharging of the battery is modified to optimize battery performance and to determine when to discharge the battery into a power grid in order to return power to the grid in exchange for an economic benefit such as a payment or rebate from a utility company.

Abstract: Systems and methods for detecting/identifying novel material samples are provided. A test sample image is processed with a trained transformation function to obtain a transformed matrix. A measure of similarity of the test image based on the transformed matrix is compared to a threshold to determine whether the test sample is novel to a batch of material samples that are provided to train the transformation function.

Abstract: In an example, a system comprises at least one body-worn tracking device (BWTD) configured to transmit location data that indicates a location of the BWTD and a computing system configured to communicate with the at least one BWTD. The computing system is configured to receive the location data from the at least one BWTD, determine, based on a set of weighted filters associated with at least one monitoring attribute, at least one gradient value corresponding to the location data, where the at least one gradient value represents a level of the at least one monitoring attribute, and perform at least one operation based on the at least one gradient value.

Abstract: Example techniques of this disclosure are directed determining one or more values that represent a monitoring attribute for one or more body-worn tracking devices (BWTDs). In some instances, the techniques include determining a compliance metric that represents a level of compliance for at least one offender. That is, the compliance metric may be a quantitative value that represents whether a user wearing BWTD is complying with established rules or desired behaviors.

Abstract: In an example, a system comprises at least one body-worn tracking device (BWTD) configured to transmit location data that indicates a location of the BWTD and a computing system configured to communicate with the at least one BWTD. The computing system is configured to receive the location data from the at least one BWTD, determine, based on a set of weighted filters associated with at least one monitoring attribute, at least one gradient value corresponding to the location data, where the at least one gradient value represents a level of the at least one monitoring attribute, and perform at least one operation based on the at least one gradient value.

Abstract: Example techniques of this disclosure are directed determining one or more values that represent a monitoring attribute for one or more body-worn tracking devices (BWTDs). In some instances, the techniques include determining a compliance metric that represents a level of compliance for at least one offender. That is, the compliance metric may be a quantitative value that represents whether a user wearing BWTD is complying with established rules or desired behaviors.

Abstract: Technologies are generally provided to enable the peak-to-average power ratio (PAPR) in OFDM communication systems to be adjusted to a particular level. In some examples, an N-symbol transmission vector may be partitioned into k equal partitions, a Fast Fourier Transform (FFT) may be performed on each partition, and an interleaving union of FFT results may be generated. The results of the interleaving union may be used for transmission after mapping them to the M subcarriers and performing an M-point IFFT. On the receiver side, FFT may be performed on M subcarriers, where each of L end user devices may be assigned N subcarriers out of M=N*L available subcarriers. The N subcarriers of the FFT results may be de-mapped and subjected to an interleaving partition. Subsequently, an Inverse FFT (IFFT) may be performed on each partition and results of the IFFT operation employed for symbol detection.

Abstract: Technologies are generally provided to enable the peak-to-average power ratio (PAPR) in OFDM communication systems to be adjusted to a particular level. In some examples, an N-symbol transmission vector may be partitioned into k equal partitions, a Fast Fourier Transform (FFT) may be performed on each partition, and an interleaving union of FFT results may be generated. The results of the interleaving union may be used for transmission after mapping them to the M subcarriers and performing an M-point IFFT. On the receiver side, FFT may be performed on M subcarriers, where each of L end user devices may be assigned N subcarriers out of M=N*L available subcarriers. The N subcarriers of the FFT results may be de-mapped and subjected to an interleaving partition. Subsequently, an Inverse FFT (IFFT) may be performed on each partition and results of the IFFT operation employed for symbol detection.