Abstract: System and method for terminating instances and autoscaling instance groups of computing platforms. For example, a method includes determining whether an instance of an instance group is identified as eligible for termination. The method further includes, in response to determining that the instance of the instance group is identified as eligible for termination, terminating the eligible instance. The terminating the eligible instance includes, in response to a runtime of the eligible instance being equal to or larger than a predetermined maximum lifetime, terminating the eligible instance.

Abstract: Embodiments of the present disclosure relate to user interfaces and systems that may enable dynamic and interactive access of, investigation of, and analysis of data objects stored in one or more databases. The data objects may be accessed from the one or more databases, and presented in multiple related portions of a display. In particular, the system provides a time-based visualization of data objects (and/or properties associated with the data objects) to a user such that the user may, for example, determine connections between various data objects, observe flows of information among data objects, and/or investigate related data objects.

Abstract: System and method for terminating instances and autoscaling instance groups of computing platforms. For example, a method includes determining whether an instance of an instance group is identified as eligible for termination. The method further includes, in response to determining that the instance of the instance group is identified as eligible for termination, terminating the eligible instance. The terminating the eligible instance includes, in response to a runtime of the eligible instance being equal to or larger than a predetermined maximum lifetime, terminating the eligible instance.

Abstract: Disclosed are data gathering and analysis systems, methods, and computer-readable storage media to facilitate an investigation process. The method includes accessing a data object representing an investigative issue as part of initiating an investigative session. The method further includes causing presentation, on a display of a device, of a user interface configured to receive user search queries and present search results for each received search query. The method further includes tracking user activity including one or more user actions performed during the investigative session. The method further includes creating a record of the user activity, and linking the record of the user activity with the data object representing the investigative issue.

Abstract: Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, and provide results of the automated analysis in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a compact, human-readable analysis of the data clusters. The human-readable analyses (also referred to herein as “summaries” or “conclusions”) of the data clusters may be organized into an interactive user interface so as to enable an analyst to quickly navigate among information associated with various data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation. Embodiments of the present disclosure also relate to automated scoring of the clustered data structures.

Abstract: Systems are provided for managing defect data objects. A system stores a plurality of defect data objects that have been input to the system, and generates an issue item including one or more defect data objects that are selected from the stored defect data objects based on user input. The system determines similarity between the one or more defect data objects in the issue item and one or more of the stored defect data objects that are out of the issue item, based on comparison of one or more parameter values. The system determines one or more candidate defect data objects to be included in the issue item from the one or more of the stored defect data objects that are out of the issue item based on the similarity, and includes one or more of the determined candidate defect data objects in the issue item based on user input.

Abstract: Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, automatically tag and group those clustered data structures, and provide results of the automated analysis and grouping in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a tiled display of the groups of related data clusters such that the analyst may quickly and efficiently evaluate the groups of data clusters. In particular, the groups of data clusters may be dynamically re-grouped and/or filtered in an interactive user interface so as to enable an analyst to quickly navigate among information associated with various groups of data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation.

Abstract: Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, and provide results of the automated analysis in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a compact, human-readable analysis of the data clusters. The human-readable analyses (also referred to herein as “summaries” or “conclusions”) of the data clusters may be organized into an interactive user interface so as to enable an analyst to quickly navigate among information associated with various data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation. Embodiments of the present disclosure also relate to automated scoring of the clustered data structures.

Abstract: The subject invention pertains to the detection and differentiation of genetic variations by nucleic acid amplification. The invention provides methods of detecting one or more genetic variations in a nucleic acid that are in close proximity simultaneously. The invention further provides primer and probe oligonucleotides and methods of using said primers and probes in assays to detect genetic variants of concern of SARS-CoV-2. The methods of the invention detect genetic variants of other pathogens, including influenza, or genetic variants involved in inheritable diseases or cancer.

Abstract: Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, and provide results of the automated analysis in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a compact, human-readable analysis of the data clusters. The human-readable analyses (also referred to herein as “summaries” or “conclusions”) of the data clusters may be organized into an interactive user interface so as to enable an analyst to quickly navigate among information associated with various data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation. Embodiments of the present disclosure also relate to automated scoring of the clustered data structures.

Abstract: Embodiments of the present disclosure relate to user interfaces and systems that may enable dynamic and interactive access of, investigation of, and analysis of data objects stored in one or more databases. The data objects may be accessed from the one or more databases, and presented in multiple related portions of a display. In particular, the system provides a time-based visualization of data objects (and/or properties associated with the data objects) to a user such that the user may, for example, determine connections between various data objects, observe flows of information among data objects, and/or investigate related data objects.

Abstract: Systems are provided for managing defect data objects. A system stores a plurality of defect data objects that have been input to the system, and generates an issue item including one or more defect data objects that are selected from the stored defect data objects based on user input. The system determines similarity between the one or more defect data objects in the issue item and one or more of the stored defect data objects that are out of the issue item, based on comparison of one or more parameter values. The system determines one or more candidate defect data objects to be included in the issue item from the one or more of the stored defect data objects that are out of the issue item based on the similarity, and includes one or more of the determined candidate defect data objects in the issue item based on user input.

Abstract: System and method for terminating instances and autoscaling instance groups of computing platforms. For example, a method includes determining whether an instance of an instance group is identified as eligible for termination. The method further includes, in response to determining that the instance of the instance group is identified as eligible for termination, terminating the eligible instance. The terminating the eligible instance includes, in response to a runtime of the eligible instance being equal to or larger than a predetermined maximum lifetime, terminating the eligible instance.

Abstract: Embodiments of the present disclosure relate to user interfaces and systems that may enable dynamic and interactive access of, investigation of, and analysis of data objects stored in one or more databases. The data objects may be accessed from the one or more databases, and presented in multiple related portions of a display. In particular, the system provides a time-based visualization of data objects (and/or properties associated with the data objects) to a user such that the user may, for example, determine connections between various data objects, observe flows of information among data objects, and/or investigate related data objects.

Abstract: System and method for terminating instances and autoscaling instance groups of computing platforms. For example, a method includes determining whether an instance of an instance group is identified as eligible for termination. The method further includes, in response to determining that the instance of the instance group is identified as eligible for termination, terminating the eligible instance. The terminating the eligible instance includes, in response to a runtime of the eligible instance being equal to or larger than a predetermined maximum lifetime, terminating the eligible instance.

Abstract: Systems are provided for managing defect data objects. A system stores a plurality of defect data objects that have been input to the system, and generates an issue item including one or more defect data objects that are selected from the stored defect data objects based on user input. The system determines similarity between the one or more defect data objects in the issue item and one or more of the stored defect data objects that are out of the issue item, based on comparison of one or more parameter values. The system determines one or more candidate defect data objects to be included in the issue item from the one or more of the stored defect data objects that are out of the issue item based on the similarity, and includes one or more of the determined candidate defect data objects in the issue item based on user input.

Abstract: Disclosed are data gathering and analysis systems, methods, and computer-readable storage media to facilitate an investigation process. The method includes accessing a data object representing an investigative issue as part of initiating an investigative session. The method further includes causing presentation, on a display of a device, of a user interface configured to receive user search queries and present search results for each received search query. The method further includes tracking user activity including one or more user actions performed during the investigative session. The method further includes creating a record of the user activity, and linking the record of the user activity with the data object representing the investigative issue.

Abstract: Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, automatically tag and group those clustered data structures, and provide results of the automated analysis and grouping in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a tiled display of the groups of related data clusters such that the analyst may quickly and efficiently evaluate the groups of data clusters. In particular, the groups of data clusters may be dynamically re-grouped and/or filtered in an interactive user interface so as to enable an analyst to quickly navigate among information associated with various groups of data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation.

Abstract: Disclosed are data gathering and analysis systems, methods, and computer-readable storage media to facilitate an investigation process. The method includes accessing a data object representing an investigative issue as part of initiating an investigative session. The method further includes causing presentation, on a display of a device, of a user interface configured to receive user search queries and present search results for each received search query. The method further includes tracking user activity including one or more user actions performed during the investigative session. The method further includes creating a record of the user activity, and linking the record of the user activity with the data object representing the investigative issue.

Abstract: Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, automatically tag and group those clustered data structures, and provide results of the automated analysis and grouping in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a tiled display of the groups of related data clusters such that the analyst may quickly and efficiently evaluate the groups of data clusters. In particular, the groups of data clusters may be dynamically re-grouped and/or filtered in an interactive user interface so as to enable an analyst to quickly navigate among information associated with various groups of data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation.