Abstract: An improved empirical formula-based estimation techniques based on correcting situational bias includes generating a map associated with situational bias in one or more empirical formulas. The map corresponds to trajectories of outputs for the one or more empirical formulas, where each trajectory of the trajectories is based on a change to an influencer variable of the one or more empirical formulas. The influencer variable is associated with data that is stable during the change to the influencer variable. The improved empirical formula-based estimation technique further includes identifying a convergence in the trajectories of the outputs for the one or more empirical formulas, where the convergence is based on adaptable boundary conditions and indicative of a compensation for the situational bias in the one or more empirical formulas, and outputting an inference based on the convergence in the trajectories of the outputs for the one or more empirical formulas.

Abstract: Methods and systems for performing pest infestation forewarning are described. In one embodiment, intuition based forewarning method includes collecting and storing core data and surroundings data, wherein the core data includes parameters describing a system and ring data includes parameters describing surroundings of grain storage container-based (e.g., silo-based) environments. The collected core data and ring data are analyzed to determine one or more changing situations of the storage container-based (e.g., silo-based) environments. A system forewarning is generated based on the changing situations that are observed.

Abstract: Methods and systems correlating hypotheses outcomes using relevance scoring for intuition based forewarning are disclosed. For one example, an intuition based forewarning method includes collecting and storing core data and surroundings data, wherein the core data includes parameters describing a system and ring data includes parameters describing surroundings of the system. The collected core data and ring data are analyzed to determine one or more changing situations of the system. A relevance score is provided for each determined changing situation of the system based on the analyzed core data and ring data. Each determined situation is correlated with one or more hypotheses outcomes representing a future system state based on the relevance score. The hypotheses may be modified using, for example, auto-hypothesis generation. A system forewarning is generated based on the correlated hypotheses outcomes which can be observed by one or more users.

Abstract: Methods and systems for performing pest infestation forewarning are described. In one embodiment, intuition based forewarning method includes collecting and storing core data and surroundings data, wherein the core data includes parameters describing a system and ring data includes parameters describing surroundings of grain storage container-based (e.g., silo-based) environments. The collected core data and ring data are analyzed to determine one or more changing situations of the storage container-based (e.g., silo-based) environments. A system forewarning is generated based on the changing situations that are observed.

Abstract: Methods and systems correlating hypotheses outcomes using relevance scoring for intuition based forewarning are disclosed. For one example, an intuition based forewarning method includes collecting and storing core data and surroundings data, wherein the core data includes parameters describing a system and ring data includes parameters describing surroundings of the system. The collected core data and ring data are analyzed to determine one or more changing situations of the system. A relevance score is provided for each determined changing situation of the system based on the analyzed core data and ring data. Each determined situation is correlated with one or more hypotheses outcomes representing a future system state based on the relevance score. A system forewarning is generated based on the correlated hypotheses outcomes which can be observed by one or more users.

Abstract: In accordance with disclosed embodiments, there are provided systems, methods, and apparatuses for implementing video shooting guns and personal safety management applications.

Abstract: In accordance with disclosed embodiments, there are provided systems, methods, and apparatuses for implementing video shooting guns and personal safety management applications.

Abstract: In accordance with disclosed embodiments, there are provided systems, methods, and apparatuses for implementing video shooting guns and personal safety management applications.

Abstract: An apparatus and a method are disclosed herein for improving predictive and preventive analytics, event tracking and processing of large combinations of data. In one embodiment, a method comprising, receiving a first data set, the first data set including data from a plurality of sources; applying a first rule set to the first subset; responsive to detecting an emergency as a result of the application of the first rule set, generating an emergency notification; generating an intuition by (a) applying a second rule set to a second subset of the first data set, the second rule set selected from one or more rule sets based on the emergency notification, and (b) selecting a course of action based on a result of the application of the second predefined rule set; and providing the course of action to a user is disclosed.

Abstract: Methods and systems correlating hypotheses outcomes using relevance scoring for intuition based forewarning are disclosed. For one example, an intuition based forewarning method includes collecting and storing core data and surroundings data, wherein the core data includes parameters describing a system and ring data includes parameters describing surroundings of the system. The collected core data and ring data are analyzed to determine one or more changing situations of the system. A relevance score is provided for each determined changing situation of the system based on the analyzed core data and ring data. Each determined situation is correlated with one or more hypotheses outcomes representing a future system state based on the relevance score. A system forewarning is generated based on the correlated hypotheses outcomes which can be observed by one or more users.

Abstract: An apparatus and a method are disclosed herein for improving predictive and preventive analytics, event tracking and processing of large combinations of data. In one embodiment, a method comprising, receiving a first data set, the first data set including data from a plurality of sources; applying a first rule set to the first subset; responsive to detecting an emergency as a result of the application of the first rule set, generating an emergency notification; generating an intuition by (a) applying a second rule set to a second subset of the first data set, the second rule set selected from one or more rule sets based on the emergency notification, and (b) selecting a course of action based on a result of the application of the second predefined rule set; and providing the course of action to a user is disclosed.

Abstract: An apparatus and a method are disclosed herein for improving predictive and preventive analytics, event tracking and processing of large combinations of data. In one embodiment, a method comprising, receiving a first data set, the first data set including data from a plurality of sources; applying a first rule set to the first subset; responsive to detecting an emergency as a result of the application of the first rule set, generating an emergency notification; generating an intuition by (a) applying a second rule set to a second subset of the first data set, the second rule set selected from one or more rule sets based on the emergency notification, and (b) selecting a course of action based on a result of the application of the second predefined rule set; and providing the course of action to a user is disclosed.

Abstract: Systems are disclosed herein for improving analytic processing and processing for handling severe outliers in a dataset that cause predictive analytic processing to fail. In one embodiment, the system comprises one or more processors, a memory communicatively coupled to the one or more processors and to store logic, the logic, upon being executed by the one or more processors, transmits instructions to filter data for only a specified one or more variables, receives a first set of specified variables corresponding to a first external database, upon receiving the first set of specified variables, accessing a second set of specified variables corresponding to a second external database, accessing a third set of specified variables corresponding to a third external database, and performing predictive analytic processing using the first set of specified variables, the second set of specified variables and the third set of specified variables to generate a first insight.

Abstract: In accordance with disclosed embodiments, there are provided systems, methods, and apparatuses for implementing a smart beacon monitoring system supported by a processor and a memory to execute such functionality.

Abstract: In accordance with disclosed embodiments, there are provided systems, methods, and apparatuses for implementing video shooting guns and personal safety management applications.

Abstract: An apparatus and a method are disclosed herein for improving predictive and preventive analytics, event tracking and processing of large combinations of data. In one embodiment, a method comprising, receiving a first data set, the first data set including data from a plurality of sources; applying a first rule set to the first subset; responsive to detecting an emergency as a result of the application of the first rule set, generating an emergency notification; generating an intuition by (a) applying a second rule set to a second subset of the first data set, the second rule set selected from one or more rule sets based on the emergency notification, and (b) selecting a course of action based on a result of the application of the second predefined rule set; and providing the course of action to a user is disclosed.

Abstract: Systems are disclosed herein for improving analytic processing and processing for handling severe outliers in a dataset that cause predictive analytic processing to fail. In one embodiment, the system comprises one or more processors, a memory communicatively coupled to the one or more processors and to store logic, the logic, upon being executed by the one or more processors, transmits instructions to filter data for only a specified one or more variables, receives a first set of specified variables corresponding to a first external database, upon receiving the first set of specified variables, accessing a second set of specified variables corresponding to a second external database, accessing a third set of specified variables corresponding to a third external database, and performing predictive analytic processing using the first set of specified variables, the second set of specified variables and the third set of specified variables to generate a first insight.

Abstract: Systems and methods are provided for management of bio-fuel production research and development, comprising (1) mapping process template layers into process segments, wherein each process template layer specifies configuration of a bio-fuel manufacturing process via process segments, and wherein each process segment specifies a stage of the bio-fuel manufacturing process via a grouping of segment modules, (2) recording specified data at each segment module, wherein the specified data includes input data, output data, and environment data, (3) configuring workflow through each process segment according to the segment modules within respective process segments, and wherein the workflow specifies the segment modules that are present and the order of the segment modules, and (4) providing the specified data to a research and development lifecycle management module for determination of results based on tracking and comparison of specified data, and wherein segment modules are modified based on the determined resul