Abstract: Apparatuses, methods, and systems for generating simulations of physical variables of a physical system are disclosed. A method includes fusing, by the one or more computing devices, the observation data and the numeric simulation data, including training a spatial-temporal emulator model for a physical numerical model using the observation data, the numeric simulation data, and the domain interpretable data.

Abstract: Apparatuses, methods, and systems for generating gridded predictions of a probability of wildfire spread for geographies are disclosed. One method includes sensing observational climate and earth surface data, obtaining historical data on wildfire spread events, obtaining gridded climate data, creating a set of input features, creating a gridded wildfire data set, training a model that learns one or more probabilistic mapping function emulators between the set of input features and the gridded wildfire data set, which predicts a first probability of wildfire occurrence and a rate and extent of wildfire spread within a geographical region and at a specified period of time, and generating gridded wildfire prediction data including a second probability of wildfire occurrence and spread within the geographical region, using the model and a new set of input features over the geographical region but for a different time period.

Abstract: A computer system receives customer records listing customer attributes and an adoption status of the customer, such as whether the customer has enrolled in a particular energy efficiency program. An initial set of patterns are identified among the customer records, such as according to a decision tree. The initial set is pruned to obtain a set of patterns that meet minimum support and effectiveness and maximum overlap requirements. The patterns are assigned to segments according to an optimization algorithm that seeks to maximize the minimum effectiveness of each segment, where the effectiveness indicates a number of customers matching the pattern of each segment that have positive adoption status. The optimization algorithm may be a bisection algorithm that evaluates a linear-fractional integer program (LFIP-F) to iteratively approach an optimal distribution of patterns.

Abstract: A computer system receives customer records listing customer attributes and an adoption status of the customer, such as whether the customer has enrolled in a particular energy efficiency program. An initial set of patterns are identified among the customer records, such as according to a decision tree. The initial set is pruned to obtain a set of patterns that meet minimum support and effectiveness and maximum overlap requirements. The patterns are assigned to segments according to an optimization algorithm that seeks to maximize the minimum effectiveness of each segment, where the effectiveness indicates a number of customers matching the pattern of each segment that have positive adoption status. The optimization algorithm may be a bisection algorithm that evaluates a linear-fractional integer program (LFIP-F) to iteratively approach an optimal distribution of patterns.

Abstract: Apparatuses, methods, and systems for generating simulations of physical variables of a physical system are disclosed. A method includes fusing, by the one or more computing devices, the observation data and the numeric simulation data, including training a spatial-temporal emulator model for a physical numerical model using the observation data, the numeric simulation data, and the domain interpretable data.

Abstract: There is disclosed a system and method for transferring waste heat from integrated circuits. In an embodiment, the system comprises: a self-contained enclosure having integrated circuits therein, the self-contained enclosure further including: a first fluid circuit configured for removing waste heat from the integrated circuits; an inlet for connection from an external water tank and an outlet for connection to the external water tank, that when connected with the external water tank forms a second fluid circuit; a heat exchanger operatively connected to the first fluid circuit and the second fluid circuit, and configured to transfer thermal energy therebetween; and a control for regulating a temperature gradient and a flow rate in each of the first and second fluid circuits, such that both a desired integrated circuit operating temperature and a desired water tank temperature is achieved.

Abstract: Apparatuses, methods, and systems for increasing a spatial resolution of gridded spatial-temporal data on weather and climate-related physical variables are disclosed.

Abstract: Apparatuses, methods, and systems for generating simulations of physical variables of a physical system are disclosed. A method includes fusing observation data and numeric simulation data. The fusing includes preprocessing the observational data and the numeric simulation data to remove inconsistencies of the observational data and the numeric simulation data, processing the preprocessed observational data and the numeric simulation data to extract interpretable structures and patterns within that data using ground truth and labeled information to create domain interpretable data, normalizing the preprocessed observation data, the numeric simulation data, and the domain interpretable data layers.

Abstract: There is disclosed a system and method for transferring waste heat from integrated circuits. In an embodiment, the system comprises: a self-contained enclosure having integrated circuits therein, the self-contained enclosure further including: a first fluid circuit configured for removing waste heat from the integrated circuits; an inlet for connection from an external water tank and an outlet for connection to the external water tank, that when connected with the external water tank forms a second fluid circuit; a heat exchanger operatively connected to the first fluid circuit and the second fluid circuit, and configured to transfer thermal energy therebetween; and a control for regulating a temperature gradient and a flow rate in each of the first and second fluid circuits, such that both a desired integrated circuit operating temperature and a desired water tank temperature is achieved.

Abstract: A computer system receives customer records listing customer attributes and an adoption status of the customer, such as whether the customer has enrolled in a particular energy efficiency program. An initial set of patterns are identified among the customer records, such as according to a decision tree. The initial set is pruned to obtain a set of patterns that meet minimum support and effectiveness and maximum overlap requirements. The patterns are assigned to segments according to an optimization algorithm that seeks to maximize the minimum effectiveness of each segment, where the effectiveness indicates a number of customers matching the pattern of each segment that have positive adoption status. The optimization algorithm may be a bisection algorithm that evaluates a linear-fractional integer program (LFIP-F) to iteratively approach an optimal distribution of patterns.

Abstract: Apparatuses, methods, and systems for generating simulations of physical variables of a physical system are disclosed. A method includes fusing observation data and numeric simulation data. The fusing includes preprocessing the observational data and the numeric simulation data to remove inconsistencies of the observational data and the numeric simulation data, processing the preprocessed observational data and the numeric simulation data to extract interpretable structures and patterns within that data using ground truth and labeled information to create domain interpretable data, normalizing the preprocessed observation data, the numeric simulation data, and the domain interpretable data layers.

Abstract: Apparatuses, methods, and systems for generating simulations of physical variables of a physical system are disclosed. A method includes fusing observation data and numeric simulation data. The fusing includes preprocessing the observational data and the numeric simulation data to remove inconsistencies of the observational data and the numeric simulation data, processing the preprocessed observational data and the numeric simulation data to extract interpretable structures and patterns within that data using ground truth and labeled information to create domain interpretable data, normalizing the preprocessed observation data, the numeric simulation data, and the domain interpretable data layers.

Abstract: Apparatuses, methods, and systems for generating gridded predictions of a probability of wildfire spread for geographies are disclosed. One method includes sensing observational climate and earth surface data, obtaining historical data on wildfire spread events, obtaining gridded climate data, creating a set of input features, creating a gridded wildfire data set, training a model that learns one or more probabilistic mapping function emulators between the set of input features and the gridded wildfire data set, which predicts a first probability of wildfire occurrence and a rate and extent of wildfire spread within a geographical region and at a specified period of time, and generating gridded wildfire prediction data including a second probability of wildfire occurrence and spread within the geographical region, using the model and a new set of input features over the geographical region but for a different time period.

Abstract: Apparatuses, methods, and systems for increasing a spatial resolution of gridded spatial-temporal data on weather and climate-related physical variables are disclosed.

Abstract: A computer system receives customer records listing customer attributes and an adoption status of the customer, such as whether the customer has enrolled in a particular energy efficiency program. An initial set of patterns are identified among the customer records, such as according to a decision tree. The initial set is pruned to obtain a set of patterns that meet minimum support and effectiveness and maximum overlap requirements. The patterns are assigned to segments according to an optimization algorithm that seeks to maximize the minimum effectiveness of each segment, where the effectiveness indicates a number of customers matching the pattern of each segment that have positive adoption status. The optimization algorithm may be a bisection algorithm that evaluates a linear-fractional integer program (LFIP-F) to iteratively approach an optimal distribution of patterns.

Abstract: Apparatuses, methods, and systems for generating simulations of physical variables of a physical system are disclosed. A method includes fusing observation data and numeric simulation data. The fusing includes preprocessing the observational data and the numeric simulation data to remove inconsistencies of the observational data and the numeric simulation data, processing the preprocessed observational data and the numeric simulation data to extract interpretable structures and patterns within that data using ground truth and labeled information to create domain interpretable data, normalizing the preprocessed observation data, the numeric simulation data, and the domain interpretable data layers.

Abstract: A computer system receives customer records listing customer attributes and an adoption status of the customer, such as whether the customer has enrolled in a particular energy efficiency program. An initial set of patterns are identified among the customer records, such as according to a decision tree. The initial set is pruned to obtain a set of patterns that meet minimum support and effectiveness and maximum overlap requirements. The patterns are assigned to segments according to an optimization algorithm that seeks to maximize the minimum effectiveness of each segment, where the effectiveness indicates a number of customers matching the pattern of each segment that have positive adoption status. The optimization algorithm may be a bisection algorithm that evaluates a linear-fractional integer program (LFIP-F) to iteratively approach an optimal distribution of patterns.

Abstract: An apparatus for a transportable toy system is provided. A transportable toy system comprising a toy body, a cavity within the toy body, and a sensor package within the cavity of the toy body. The sensor package comprises one or more processors, a plurality of electronic digital sensors coupled to the one or more processors, a wireless networking transceiver coupled to the one or more processors, and non-transitory computer-readable storage medium coupled to the one or more processors and storing one or more sequences of instructions. The sensor package is removable from the cavity of the toy and if removed utility of the toy is maintained. The sensors in the sensor package may be an accelerometer, an altimeter, a gyroscope, and/or other sensors. The instructions stored on the non-transitory computer-readable storage medium cause the one or more processors to detect a set of changes, based on readings from the sensors, to the toy in response to a change in position of the toy.

Abstract: A methodology is provided for informing targeted Demand-Response (DR) and marketing programs that focus on the temperature-sensitive part of residential electricity demand. The methodology uses energy consumption readings collected from “smart” electricity meters, as well as hourly temperature readings. Individual consumption is decomposed into a thermal-sensitive part and a base load (non thermally-sensitive), a model of temperature response that is based on thermal regimes, i.e., unobserved decisions of customers to use their heating or cooling appliances. This model is used to extract useful benchmarks that compose a thermal profiles of individual customers, i.e., terse characterizations of the statistics of these customers' temperature-sensitive consumption. This knowledge may, in turn, inform the DR program by allowing scarce operational and marketing budgets to be spent on customers whose influencing will yield highest energy reductions at the right time.