Abstract: Systems, computer-implemented methods, and computer program products to facilitate automated model pipeline generation with entity monitoring, interaction, and/or intervention are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise an interaction backend handler component that provides a recommended input action corresponding to a model pipeline candidate being evaluated in an automated model pipeline generation process. The computer executable components can further comprise a visualization render component that renders an input visualization corresponding to the model pipeline candidate based on the recommended input action.

Abstract: Techniques facilitating automatic feature extraction from a relational database are provided. In an embodiment, a method can include generating an entity graph based on a relational database, wherein the entity graph comprises a first node associated with a first table in the relational database and a second node associated with a second table in the relational database. In another embodiment, the method can include joining the first table and the second table based on an edge between the first table and the second table defined by the entity graph, wherein a resulting joined table is connected by a column of data. In another embodiment, the method can include extracting a feature from the column of data using a data mining algorithm selected from a set of data mining algorithms based on a type of data in the column of data.

Abstract: Systems, computer-implemented methods, and computer program products to facilitate visualization of a model selection process are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise an interaction backend handler component that obtains one or more assessment metrics of a model pipeline candidate. The computer executable components can further comprise a visualization render component that renders a progress visualization of the model pipeline candidate based on the one or more assessment metrics.

Abstract: Techniques regarding one or more automated machine learning processes that analyze time series data are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a time series analysis component that selects a machine learning pipeline for meta transfer learning on time series data by sequentially allocating subsets of training data from the time series data amongst a plurality of machine learning pipeline candidates.

Abstract: The invention relates to heterocyclic compounds of the formula (I), in which all of the variables are as defined in the specification; capable of modulating the activity of CFTR. The invention further provides a method for manufacturing compounds of the invention, and its therapeutic uses. The invention further provides methods to their preparation, to their medical use, in particular to their use in the treatment and management of diseases or disorders including Cystic fibrosis and related disorders.

Abstract: Techniques facilitating automatic feature extraction from a relational database are provided. In an embodiment, a method can include generating an entity graph based on a relational database, wherein the entity graph comprises a first node associated with a first table in the relational database and a second node associated with a second table in the relational database. In another embodiment, the method can include joining the first table and the second table based on an edge between the first table and the second table defined by the entity graph, wherein a resulting joined table is connected by a column of data. In another embodiment, the method can include extracting a feature from the column of data using a data mining algorithm selected from a set of data mining algorithms based on a type of data in the column of data.

Abstract: Techniques facilitating iterative widening search for designing chemical compounds are provided. A computer-implemented method can comprise receiving, by a system operatively coupled to a processor, an indication of a constrained structure portion of a chemical compound and a first unconstrained structure portion of the chemical compound. The method can also comprise determining, by the system, a second unconstrained structure portion for the chemical compound based on a determination that the second unconstrained structure portion satisfies a defined condition related to a difference between the first unconstrained structure portion and the second unconstrained structure portion.

Abstract: Various implementations of the present disclosure relate to text to visualization In a method, information items are extracted from a natural language sentence. Visual elements associated with the information items are determined. A visual representation of the natural language sentence based on the visual elements is determined, the visual representation indicating information expressed by the natural language sentence.

Abstract: Systems, computer-implemented methods, and computer program products to facilitate automated generation of a machine learning pipeline based on a pipeline grammar are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a pipeline structure generator component that generates a machine learning pipeline structure based on a pipeline grammar. The computer executable components can further comprise a pipeline optimizer component that selects one or more machine learning modules that achieve a defined objective to instantiate a machine learning pipeline based on the machine learning pipeline structure.

Abstract: A system and method for reaction rules database correction. The method includes receiving a user-input correction to a first reaction rule in a reaction rules database, and locating a second reaction rule in the reaction rules database that is similar to the first reaction rule. The method also includes calculating a correctness score for the second reaction rule, and determining that the correctness score for the second reaction rule is below a threshold correctness score. Additionally, the method includes presenting, in response to the determining that the correctness score for the second reaction rule is below the threshold correctness score, the second reaction rule to a user, receiving a user-input correction to the second reaction rule, and updating the reaction rules database to include the user-input correction to the second reaction rule.

Abstract: Various embodiments manage energy generation in a power generation and distribution system. In one embodiment, a set of residual load data is obtained for a given period of time measured at one or more nodes within a power generation and distribution system. The set of residual load data encodes a set of power flow signals. The set of residual load data is analyzed. An amount of power contributed to the set of residual load data by at least one energy generator class is determined based on the analysis of the set of residual load data.

Abstract: Disclosed are a hole connecting layer manufacturing method, a circuit board manufacturing method and a circuit board. The hole connecting layer manufacturing method comprises: adhering a first insulating dielectric layer, used for laminating and filling, to a daughter board; laminating and solidifying the first insulating dielectric layer on the daughter board; adhering a second insulating dielectric layer, used for laminating and filling, to the first insulating dielectric layer which has been laminated and solidified; manufacturing a first receiving hole on the first insulating dielectric layer and a second receiving hole on the second insulating dielectric layer, wherein the first receiving hole and the second receiving hole are provided vertically opposite to each other; filling both the first receiving hole and the second receiving hole with a conductive medium to complete manufacturing of the hole connecting layer.

Abstract: Embodiments for using an intelligent transaction optimization assistant by a processor. One or more actions to enhance a transaction experience of one or more users may be provided according to one or more selected constraints learned via a machine learning operation from previous transaction experiences, user behavior relating to the one or more previous transaction experiences, transaction experiences shared amongst entities associated with a social network, or a combination thereof.

Abstract: The invention relates to heterocyclic compounds of the formula (I) in which all of the variables are as defined in the specification; capable of modulating the activity of CFTR. The invention further provides a method for manufacturing compounds of the invention, and its therapeutic uses. The invention further provides methods to their preparation, to their medical use, in particular to their use in the treatment and management of diseases or disorders including Cystic fibrosis and related disorders.

Abstract: Techniques facilitating automatic feature extraction from a relational database are provided. In an embodiment, a method can include generating an entity graph based on a relational database, wherein the entity graph comprises a first node associated with a first table in the relational database and a second node associated with a second table in the relational database. In another embodiment, the method can include joining the first table and the second table based on an edge between the first table and the second table defined by the entity graph, wherein a resulting joined table is connected by a column of data. In another embodiment, the method can include extracting a feature from the column of data using a data mining algorithm selected from a set of data mining algorithms based on a type of data in the column of data.

Abstract: Embodiments describe an approach for coordinating the travel of multiple vehicles traveling to a target destination, the embodiments describe generating a travel group, receiving travel group parameters from travel group members, synced GPS applications, and a weather application, generating a course of travel for the travel group members to reach a destination, and tracking each travel group member according to locations identified by the synced GPS applications. Additionally, embodiments describe determining that a subgroup of the travel group is no longer traveling within a pre-determined range of other travel group members; calculating an optimized course of travel for the subgroup to reunite with the other travel group members, adjusting the course of travel to include the optimized course of action for the subgroup, and causing each GPS application to direct the subgroup to travel according to the optimized course of travel.

Abstract: Various embodiments manage energy generation in a power generation and distribution system. In one embodiment, a set of residual load data is obtained for a given period of time measured at one or more nodes within a power generation and distribution system. The set of residual load data encodes a set of power flow signals. The set of residual load data is analyzed. An amount of power contributed to the set of residual load data by at least one energy generator class is determined based on the analysis of the set of residual load data.

Abstract: Embodiments for implementing intelligent automation of opportunity transaction workflows by a processor. One or more tasks identified in an existing transaction opportunity workflow suitable for automation may be automated in a current transaction opportunity workflow. The automated tasks may be scheduled and executed in the current transaction opportunity workflow. The automated tasks in the current transaction opportunity workflow may be monitored.

Abstract: Embodiments for providing data content consumption support by a processor. Data from one or more data sources may be captured and received by one or more data capturing devices while a user is consuming the data on the one or more data sources. A domain knowledge may be automatically updated with the data. A response may be provided to one or more queries based upon information accessed from the knowledge domain.

Abstract: Various embodiments are provided for intelligent selection of time series models by one or more processors in a computing system. Time series data may be received from a user, one or more computing devices, sensors, or a combination thereof. One or more optimal time series models may be selected upon using and/or evaluating one or more recurrent neural networks models that are trained or pre-trained using simulated time series data or historical time series data, or a combination thereof for one or more predictive analytical tasks relating to the received time series data.