Abstract: A computer-implemented method, system, and/or computer program product generates and utilizes synthetic context-based objects. One or more processors define a context object, where the context object provides a context that identifies a specific subject-matter, from multiple subject-matters, of a non-contextual data object. The processor(s) associate the non-contextual data object with the context object to define a synthetic context-based object and the synthetic context-based object with at least one specific data store. A request is received from a requester for data from said at least one specific data store that is associated with the synthetic context-based object, where said at least one specific data store is within a database of multiple data stores. Data is returned to the requester from said at least one specific data store that is associated with the synthetic context-based object.

Abstract: A sensor system comprises: an energy storage device electrically coupled to an intermittent energy release device that causes the energy storage device to release stored energy intermittently; a sensor electrically coupled to the energy storage device, where the sensor detects physical events occurring at a physical device and is intermittently powered by electrical energy received from the energy storage device; a synaptic neural network core electrically coupled to the sensor, where the synaptic neural network core converts sensor readings into an object that describes the physical events occurring at the physical device; a transponder electrically coupled to the synaptic neural network core; and a storage buffer within the transponder, where the storage buffer stores the object for transmission from the transponder to a monitoring system, where the intermittent energy release device provides power to the sensor in response to the transponder transmitting the object to the monitoring system.

Abstract: A system is provided for inferring sensor topology in a structure. The system includes a receiver, a server communicatively coupled to the receiver and a sensor topology engine communicatively coupled to the receiver and the server. The receiver is configured to receive identification information that sensors have been and deployed throughout the structure to sense a presence of an operator and to receive sensor readings from the sensors and couple the sensor readings to the sensor topology engine. The sensor topology engine is further configured analyze the identification information and the sensor readings to infer zones of the multiple spaces in which the presence of the operator is sensed by at least one of the sensors, borders of each of the zones, and dead zones adjacent to one or more of the zones in which the presence of the operator is not sensed and build a topological graph.

Abstract: A scoped search engine is disclosed. The scoped search engine includes a memory unit storing reference data records. The scoped search engine also includes a data comparison unit that searches the reference data records using different searches. The scoped search engine further includes a match analysis unit that combines result data from the different searches and determines a scope for a subsequent search based on the combined result data.

Abstract: A method, computer program product and system for generating and maintaining synthetic context events. The steps include searching a data structure of synthetic context-based objects and associated data for a pattern of context exhibited at a first specified frequency within a first specified time period; combining the synthetic context-based objects and associated data exhibiting the pattern of context exhibited at the first specified frequency within the first specified time period into a synthetic context event; and optimizing and maintaining the synthetic context event by searching the data structure for additional synthetic context-based objects and associated data exhibiting a same pattern of context at a second specified time period different than the first specified time period and adding the additional synthetic context-based objects and associated data to the synthetic context event.

Abstract: A computer-implemented method, system, and/or computer program product generates and utilizes synthetic context-based objects. One or more processors define a context object, where the context object provides a context that identifies a specific subject-matter, from multiple subject-matters, of a non-contextual data object. The processor(s) associate the non-contextual data object with the context object to define a synthetic context-based object and the synthetic context-based object with at least one specific data store. A request is received from a requester for data from said at least one specific data store that is associated with the synthetic context-based object, where said at least one specific data store is within a database of multiple data stores. Data is returned to the requester from said at least one specific data store that is associated with the synthetic context-based object.

Abstract: A processor-implemented method, system, and/or computer program product generates and utilizes synthetic context-based objects. A non-contextual data object is associated with a context object, which comports with a predetermined set of constraints, to define a synthetic context-based object, where the non-contextual data object ambiguously relates to multiple subject-matters, and where the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object. The synthetic context-based object is then associated with at least one specific data store, which includes data that is associated with data contained in the non-contextual data object and the context object. A request for a data store that is associated with the synthetic context-based object results in the return of at least one data store that is associated with the synthetic context-based object.

Abstract: A processor-implemented method, system, and/or computer program product measures and displays facets in context-based conformed dimensional data gravity wells. Conformed dimensional objects and synthetic context-based objects are parsed into n-tuples. A virtual mass of each parsed object is calculated, in order to define a shape of multiple context-based conformed dimensional data gravity wells that are created when data objects that are pulled into each of the context-based conformed dimensional data gravity well frameworks on a context-based conformed dimensional gravity wells membrane. Data from the multiple context-based conformed dimensional data gravity wells then populates nodes in a data model. A displayed appearance of the particular context-based conformed dimensional data gravity well is dynamically adjusted according to how many parsed synthetic context-based objects are pulled into the particular context-based conformed dimensional data gravity well.

Abstract: A sensor system comprises: an energy storage device electrically coupled to an intermittent energy release device that causes the energy storage device to release stored energy intermittently; a sensor electrically coupled to the energy storage device, where the sensor detects physical events occurring at a physical device and is intermittently powered by electrical energy received from the energy storage device; a synaptic neural network core electrically coupled to the sensor, where the synaptic neural network core converts sensor readings into an object that describes the physical events occurring at the physical device; a transponder electrically coupled to the synaptic neural network core; and a storage buffer within the transponder, where the storage buffer stores the object for transmission from the transponder to a monitoring system, where the intermittent energy release device provides power to the sensor in response to the transponder transmitting the object to the monitoring system.

Abstract: A processor-implemented method, system, and/or computer program product mitigate subjectively disturbing content. A context-based data gravity wells membrane supports one or more gravity wells, which hold subjectively disturbing synthetic context-based objects made up of a non-contextual data object, a first context object, and a second context object. The first context object defines the non-contextual data object, and the second context object describes how subjectively disturbing content generated by combining the non-contextual data object and the first context object is according to predefined parameters described by the second context object. New content is passed across the context-based data gravity wells membrane.

Abstract: A sensor system comprises: an energy storage device; an intermittent energy release device electrically coupled to the energy storage device, wherein the intermittent energy release device causes the energy storage device to release stored energy intermittently; a sensor electrically coupled to the energy storage device; a register electrically coupled to the sensor, wherein the register stores readings from the sensor; a synaptic neural network core electrically coupled to the sensor, wherein the synaptic neural network core converts the readings from the sensor into a synthetic context-based object that is derived from the readings and a context object; a transponder electrically coupled to the synaptic neural network core; and a storage buffer within the transponder, wherein the storage buffer stores the synthetic context-based object for transmission by the transponder to a monitoring system.

Abstract: A computer system securely accesses a specific data store. A non-contextual data object is associated with a context object to define a first synthetic context-based object. The non-contextual data object ambiguously describes multiple types of persons, and the context object provides a circumstantial context that identifies a specific type of person from the multiple types of persons. The first synthetic context-based object is associated with at least one specific data store in a data structure. A string of binary data that describes a requester of data, including a time window for receipt and security level of the requester, is received by the computer system for generating a new synthetic context-based object. If there is a match between the new synthetic context-based object, the first synthetic context-based object, and the security level of the requester, then the data is returned to the requester by the computer system.

Abstract: A method, system, and/or computer program product stores and retrieves payload data using a ternary content addressed memory (TCAM) hybrid memory. TCAM data is transmitted to a context masking device. The TCAM data identifies a type of payload data, and the context masking device masks the TCAM data with a context mask to create a masked TCAM data. One or more processors append the masked TCAM to payload data to create multiple stored units of TCAM-identified payload data in a location addressable store (LAS). The processor(s) receive a request for data. The request includes a masked request TCAM data that identifies a content and context of requested data. An exclusive OR (XOR) chip identifies relevant payload data within the LAS that are within a predefined Hamming distance of the masked request TCAM data. The processor(s) return the relevant payload data within the LAS to the requester.

Abstract: A method, system, and/or computer program product stores and retrieves payload data using a ternary content addressed memory (TCAM) hybrid memory. TCAM data is transmitted to a context masking device. The TCAM data identifies a type of payload data, and the context masking device masks the TCAM data with a context mask to create a masked TCAM data. One or more processors append the masked TCAM to payload data to create multiple stored units of TCAM-identified payload data in a location addressable store (LAS). The processor(s) receive a request for data. The request includes a masked request TCAM data that identifies a content and context of requested data. An exclusive OR (XOR) chip identifies relevant payload data within the LAS that are within a predefined Hamming distance of the masked request TCAM data. The processor(s) return the relevant payload data within the LAS to the requester.

Abstract: A processor-implemented method, system, and/or computer program product derives and utilizes a context object to generate a synthetic context-based object. A context object for a non-contextual data object is derived by contextually searching a document that contains multiple instances of the non-contextual data object. The non-contextual data object is associated with the derived context object to define a synthetic context-based object, where the non-contextual data object ambiguously relates to multiple subject-matters, and where the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object. The synthetic context-based object is then associated with a data store in a data structure that contains heterogeneous data stores that hold data of different formats.

Abstract: A processor-implemented method, system, and/or computer program product generates and utilizes synthetic context-based objects. A non-contextual data object is associated with a context object to define a synthetic context-based object, where the non-contextual data object ambiguously relates to multiple subject-matters, and where the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object. The synthetic context-based object is then associated with at least one specific data store, which includes data that is associated with data contained in the non-contextual data object and the context object. A request for a data store that is associated with the synthetic context-based object results in the return of at least one data store that is associated with the synthetic context-based object.

Abstract: A processor-implemented method, system, and/or computer program product derives and utilizes a context object to generate a synthetic context-based object. A context object for a non-contextual data object is derived by contextually searching a document, which contains multiple instances of the non-contextual data object, according to a profile of a particular user. The non-contextual data object is associated with the derived context object to define a synthetic context-based object, where the non-contextual data object ambiguously relates to multiple subject-matters, and where the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object. The synthetic context-based object is then associated with a data store in a data structure that contains heterogeneous data stores having different formats.

Abstract: A computer system securely accesses a specific data store. A non-contextual data object is associated with a context object to define a first synthetic context-based object. The non-contextual data object ambiguously describes multiple types of persons, and the context object provides a circumstantial context that identifies a specific type of person from the multiple types of persons. The first synthetic context-based object is associated with at least one specific data store in a data structure. A string of binary data that describes a requester of data, including a time window for receipt and security level of the requester, is received by the computer system for generating a new synthetic context-based object. If there is a match between the new synthetic context-based object, the first synthetic context-based object, and the security level of the requester, then the data is returned to the requester by the computer system.

Abstract: A processor-implemented method, system, and/or computer program product securely accesses a specific data store. A non-contextual data object is associated with a context object to define a first synthetic context-based object. The non-contextual data object ambiguously describes multiple types of persons, and the context object provides a circumstantial context that identifies a specific type of person from the multiple types of persons. The first synthetic context-based object is associated with at least one specific data store in a data structure. A string of binary data that describes a requester of data, including a time window for receipt and security level of the requester, is received by a security module for generating a new synthetic context-based object. If there is a match between the new synthetic context-based object, the first synthetic context-based object, and the security level of the requester, then the data is returned to the requester.

Abstract: A processor-implemented method, system, and/or computer program product measures and displays facets in context-based conformed dimensional data gravity wells. Conformed dimensional objects and synthetic context-based objects are parsed into n-tuples. A virtual mass of each parsed object is calculated, in order to define a shape of multiple context-based conformed dimensional data gravity wells that are created when data objects that are pulled into each of the context-based conformed dimensional data gravity well frameworks on a context-based conformed dimensional gravity wells membrane. Data from the multiple context-based conformed dimensional data gravity wells then populates nodes in a data model. A displayed appearance of the particular context-based conformed dimensional data gravity well is dynamically adjusted according to how many parsed synthetic context-based objects are pulled into the particular context-based conformed dimensional data gravity well.