Abstract: An application automatically composed using natural language processing. A natural language input comprising one or more application requirements is received via an interface. The natural language input is parsed to extract one or more chunks, each chunk representing one of the application requirements, and at least one of the chunks representing at least one of one or more main functionalities described by the application requirements. A coarse architecture logically arranging the main functionalities to satisfy the application requirements is inferred according to the chunks. Existing assets corresponding to the chunks are identified, each asset associated with at least one of the main functionalities. The identified assets are assembled according to the coarse architecture. The assembled assets are deployed as an application.

Abstract: Embodiments for recommending predictive modeling methods and features by a processor. One or more extracted methods and features of one or more predictive models are received according to selected criteria from both a structured database and from one or more data sources from a remote database. One or more extracted predictive model methods and features may be recommended according to the selected criteria.

Abstract: A method is provided for determining at least one candidate reactant. One embodiment of this method includes the following steps: forming by a computer processor a graph of known reactants and known products, the graph comprising links between the known reactants and their known products, receiving by a computer processor the target compound, determining by a computer processor whether the graph includes the target compound and adding the target compound to the graph if the target compound was not previously included, forming by a computer processor a matrix representing at least a portion of the known reactants, a portion of the known products and the target compound, providing a matrix value of the graph by a computer processor for one or more candidate reactants and determining by a computer processor at least one link in the graph between the target compound and the candidate reactant based on matrix values.

Abstract: An application automatically composed using natural language processing. A natural language input comprising one or more application requirements is received via an interface. The natural language input is parsed to extract one or more chunks, each chunk representing one of the application requirements, and at least one of the chunks representing at least one of one or more main functionalities described by the application requirements. A coarse architecture logically arranging the main functionalities to satisfy the application requirements is inferred according to the chunks. Existing assets corresponding to the chunks are identified, each asset associated with at least one of the main functionalities. The identified assets are assembled according to the coarse architecture. The assembled assets are deployed as an application.

Abstract: An application automatically composed using natural language processing. A natural language input comprising one or more application requirements is received via an interface. The natural language input is parsed to extract one or more chunks, each chunk representing one of the application requirements, and at least one of the chunks representing at least one of one or more main functionalities described by the application requirements. A coarse architecture logically arranging the main functionalities to satisfy the application requirements is inferred according to the chunks. Existing assets corresponding to the chunks are identified, each asset associated with at least one of the main functionalities. The identified assets are assembled according to the coarse architecture. The assembled assets are deployed as an application.

Abstract: An application automatically composed using natural language processing. A natural language input comprising one or more application requirements is received via an interface. The natural language input is parsed to extract one or more chunks, each chunk representing one of the application requirements, and at least one of the chunks representing at least one of one or more main functionalities described by the application requirements. A coarse architecture logically arranging the main functionalities to satisfy the application requirements is inferred according to the chunks. Existing assets corresponding to the chunks are identified, each asset associated with at least one of the main functionalities. The identified assets are assembled according to the coarse architecture. The assembled assets are deployed as an application.

Abstract: In an approach for adaptive sampling of smart meter data, a computer retrieves one or more balancing constraints associated with one or more smart meter sensors. The computer retrieves meter sensor data from the one or more smart meter sensors according to the one or more balancing constraints. The computer determines a subsample of the meter sensor data based, at least in part, on one or more similar consumption patterns of meter sensor data, and then transmits the subsample of the meter sensor data to an optimization engine for use in solving an optimization problem.

Abstract: Embodiments for recommending predictive modeling methods and features by a processor. One or more extracted methods and features of one or more predictive models are received according to selected criteria from both a structured database and from one or more data sources from a remote database. One or more extracted predictive model methods and features may be recommended according to the selected criteria.

Abstract: In an approach for adaptive sampling of smart meter data, a computer retrieves one or more balancing constraints associated with one or more smart meter sensors. The computer retrieves meter sensor data from the one or more smart meter sensors according to the one or more balancing constraints. The computer determines a subsample of the meter sensor data, and then transmits the subsample of the meter sensor data to an optimization engine for use in solving an optimization problem.

Abstract: In an approach for adaptive sampling of smart meter data, a computer retrieves one or more balancing constraints associated with one or more smart meter sensors. The computer retrieves meter sensor data from the one or more smart meter sensors according to the one or more balancing constraints. The computer determines a subsample of the meter sensor data based, at least in part, on one or more similar consumption patterns of meter sensor data, and then transmits the subsample of the meter sensor data to an optimization engine for use in solving an optimization problem.

Abstract: A method is provided for determining at least one candidate reactant. One embodiment of this method includes the following steps: forming by a computer processor a graph of known reactants and known products, the graph comprising links between the known reactants and their known products, receiving by a computer processor the target compound, determining by a computer processor whether the graph includes the target compound and adding the target compound to the graph if the target compound was not previously included, forming by a computer processor a matrix representing at least a portion of the known reactants, a portion of the known products and the target compound, providing a matrix value of the graph by a computer processor for one or more candidate reactants and determining by a computer processor at least one link in the graph between the target compound and the candidate reactant based on matrix values.

Abstract: Generating actionable information is provided. A plurality of different types of data corresponding to a set of customers of a service is collected via a network. A list of customers is generated from the set of customers of the service that are likely to take an action corresponding to a business goal. The list of customers is based on a linked set of labels corresponding to the business goal for a subset of customers within the set of customers of the service. The actionable information corresponding to customers within the list of customers is generated. An action step is performed based on the generated actionable information corresponding to the customers within the list of customers.

Abstract: In an approach for adaptive sampling of smart meter data, a computer retrieves one or more balancing constraints associated with one or more smart meter sensors. The computer retrieves meter sensor data from the one or more smart meter sensors according to the one or more balancing constraints. The computer determines a subsample of the meter sensor data, and then transmits the subsample of the meter sensor data to an optimization engine for use in solving an optimization problem.

Abstract: In an approach for adaptive sampling of smart meter data, a computer retrieves one or more balancing constraints associated with one or more smart meter sensors. The computer retrieves meter sensor data from the one or more smart meter sensors according to the one or more balancing constraints. The computer determines a subsample of the meter sensor data, and then transmits the subsample of the meter sensor data to an optimization engine for use in solving an optimization problem.

Abstract: In an approach for adaptive sampling of smart meter data, a computer retrieves one or more balancing constraints associated with one or more smart meter sensors. The computer retrieves meter sensor data from the one or more smart meter sensors according to the one or more balancing constraints. The computer determines a subsample of the meter sensor data, and then transmits the subsample of the meter sensor data to an optimization engine for use in solving an optimization problem.

Abstract: Laser-based material processing systems, exhaust systems, and methods for using such systems are disclosed herein. One embodiment of a laser-based material processing system can include an exhaust assembly configured to remove contaminants from a material processing area. The exhaust assembly can include a vacuum source and an exhaust plenum carried by a moveable arm of a gantry-style laser beam positioning assembly. The moveable arm can extend along a first axis and can be moveable along a second axis generally normal to the first axis. The exhaust plenum can extend lengthwise in a direction generally parallel with the first axis. The exhaust assembly can also include an intake slot extending lengthwise along the exhaust plenum across at least a portion of the material processing area. The exhaust assembly can further include one or more flexible exhaust ducts in fluid communication with the vacuum source and the exhaust plenum.

Abstract: Laser-based material processing systems, exhaust systems, and methods for using such systems are disclosed herein. One embodiment of a laser-based material processing system can include an exhaust assembly configured to remove contaminants from a material processing area. The exhaust assembly can include a vacuum source and an exhaust plenum carried by a moveable arm of a gantry-style laser beam positioning assembly. The moveable arm can extend along a first axis and can be moveable along a second axis generally normal to the first axis. The exhaust plenum can extend lengthwise in a direction generally parallel with the first axis. The exhaust assembly can also include an intake slot extending lengthwise along the exhaust plenum across at least a portion of the material processing area. The exhaust assembly can further include one or more flexible exhaust ducts in fluid communication with the vacuum source and the exhaust plenum.