Abstract: An optical system affixed to an electronic apparatus is provided, including a first optical module, a second optical module, and a third optical module. The first optical module is configured to adjust the moving direction of a first light from a first moving direction to a second moving direction, wherein the first moving direction is not parallel to the second moving direction. The second optical module is configured to receive the first light moving in the second moving direction. The first light reaches the third optical module via the first optical module and the second optical module in sequence. The third optical module includes a first photoelectric converter configured to transform the first light into a first image signal.

Abstract: A method, system, and computer program product for graph-based searching for one or more data streams is disclosed. A computer-implemented method comprises extracting a plurality of tuples from one or more data streams. The method further comprises generating a graph for the plurality of tuples in which a node represents a tuple of the plurality of tuples and an edge represents a correlation between the node and another node, and the edge is generated based at least partly on one or more predetermined queries for the one or more data streams. The method further comprises traversing the graph based on the one or more predetermined queries. Accordingly, embodiments of the present disclosure can improve the search speed by use of the graph-based searching for one or more data streams.

Abstract: Provided are techniques for building and fixing a dynamic application topology. Log files are received from multiple sources comprising any of services and nodes. Information is extracted from the log files. An application topology is created for a particular point in time for an application that provides hierarchical relationships of components for executing the application using the extracted information. One or more problems in the application topology are identified. A solution is applied to each of the one or more problems.

Abstract: A method, system, and computer program product for graph-based searching for one or more data streams is disclosed. A computer-implemented method comprises extracting a plurality of tuples from one or more data streams. The method further comprises generating a graph for the plurality of tuples in which a node represents a tuple of the plurality of tuples and an edge represents a correlation between the node and another node, and the edge is generated based at least partly on one or more predetermined queries for the one or more data streams. The method further comprises traversing the graph based on the one or more predetermined queries. Accordingly, embodiments of the present disclosure can improve the search speed by use of the graph-based searching for one or more data streams.

Abstract: One embodiment for determining a marketing incentive for a user of an electronic device. In one embodiment, a computer processor detects a first electronic device within a retail environment utilizing a second electronic device that also identifies information associated with the first electronic device. In one embodiment, a computer processor determines a behavior associated with the first electronic device based, at least in part, on movement of the first electronic device within the retail environment. In one embodiment, a computer processor identifies data associated with the retail environment that includes information associated with a retailer associated with the retail environment and information associated with the first electronic device. In one embodiment, a computer processor determines a first marketing incentive based, at least in part, on the determined behavior associated with the first electronic device and the identified data associated with the retail environment.

Abstract: One embodiment for determining a marketing incentive for a user of an electronic device. In one embodiment, a computer processor detects a first electronic device within a retail environment utilizing a second electronic device that also identifies information associated with the first electronic device. In one embodiment, a computer processor determines a behavior associated with the first electronic device based, at least in part, on movement of the first electronic device within the retail environment. In one embodiment, a computer processor identifies data associated with the retail environment that includes information associated with a retailer associated with the retail environment and information associated with the first electronic device. In one embodiment, a computer processor determines a first marketing incentive based, at least in part, on the determined behavior associated with the first electronic device and the identified data associated with the retail environment.

Abstract: The method includes receiving, by one or more computer processors, a request for data usage, the request for data usage being associated with a mobile device. The method further includes identifying, by one or more computer processors, a current data usage quantity, the current data usage quantity being associated with the mobile device. The method further includes determining, by one or more computer processors, whether the current data usage quantity is beyond a threshold data usage. The method further includes responsive to the data usage quantity being beyond the threshold data usage, receiving, by one or more computer processors, mobile device information associated with the mobile device. The method further includes analyzing, by one or more computer processors, the mobile device information. The method further includes determining, by one or more computer processors, access for the request based on the mobile device information and the current data usage quantity.

Abstract: A computer-implemented method includes receiving a data stream and dividing the data stream into one or more data artefacts for one or more time intervals. The computer-implemented method further includes generating one or more contexts. Each of the one or more contexts are for at least one of the one or more time intervals. The computer-implemented method further includes storing each of the one or more data artefacts in shared storage. The shared storage is accessible for each of the one or more contexts. The computer-implemented method further includes, for each context of the one or more contexts: determining a dependency for the context; monitoring the context for a completion of said dependency; and responsive to the completion, releasing the dependency. The computer-implemented further includes removing those of the one or more data artefacts that do not belong to the dependency for any of the one or more contexts.

Abstract: A method, system, and computer program product for graph-based searching for one or more data streams is disclosed. A computer-implemented method comprises extracting a plurality of tuples from one or more data streams. The method further comprises generating a graph for the plurality of tuples in which a node represents a tuple of the plurality of tuples and an edge represents a correlation between the node and another node, and the edge is generated based at least partly on one or more predetermined queries for the one or more data streams. The method further comprises traversing the graph based on the one or more predetermined queries. Accordingly, embodiments of the present disclosure can improve the search speed by use of the graph-based searching for one or more data streams.

Abstract: A computer-implemented method includes receiving a data stream and dividing the data stream into one or more data artefacts for one or more time intervals. The computer-implemented method further includes generating one or more contexts. Each of the one or more contexts are for at least one of the one or more time intervals. The computer-implemented method further includes storing each of the one or more data artefacts in shared storage. The shared storage is accessible for each of the one or more contexts. The computer-implemented method further includes, for each context of the one or more contexts: determining a dependency for the context; monitoring the context for a completion of said dependency; and responsive to the completion, releasing the dependency. The computer-implemented further includes removing those of the one or more data artefacts that do not belong to the dependency for any of the one or more contexts.

Abstract: The method include receiving, by one or more computer processors, a request for data usage, the request for data usage being associated with a mobile device. The method further includes identifying, by one or more computer processors, a current data usage quantity, the current data usage quantity being associated with the mobile device. The method further includes determining, by one or more computer processors, whether the current data usage quantity is beyond a threshold data usage. The method further includes responsive to the data usage quantity being beyond the threshold data usage, receiving, by one or more computer processors, mobile device information associated with the mobile device. The method further includes analyzing, by one or more computer processors, the mobile device information. The method further includes determining, by one or more computer processors, access for the request based on the mobile device information and the current data usage quantity.

Abstract: Provided are techniques for building and fixing a dynamic application topology. Log files are received from multiple sources comprising any of services and nodes. Information is extracted from the log files. An application topology is created for a particular point in time for an application that provides hierarchical relationships of components for executing the application using the extracted information. One or more problems in the application topology are identified. A solution is applied to each of the one or more problems.

Abstract: A method, system, and computer program product for graph-based searching for one or more data streams is disclosed. A computer-implemented method comprises extracting a plurality of tuples from one or more data streams. The method further comprises generating a graph for the plurality of tuples in which a node represents a tuple of the plurality of tuples and an edge represents a correlation between the node and another node, and the edge is generated based at least partly on one or more predetermined queries for the one or more data streams. The method further comprises traversing the graph based on the one or more predetermined queries. Accordingly, embodiments of the present disclosure can improve the search speed by use of the graph-based searching for one or more data streams.

Abstract: The method include receiving, by one or more computer processors, a request for data usage, the request for data usage being associated with a mobile device. The method further includes identifying, by one or more computer processors, a current data usage quantity, the current data usage quantity being associated with the mobile device. The method further includes determining, by one or more computer processors, whether the current data usage quantity is beyond a threshold data usage. The method further includes responsive to the data usage quantity being beyond the threshold data usage, receiving, by one or more computer processors, mobile device information associated with the mobile device. The method further includes analyzing, by one or more computer processors, the mobile device information. The method further includes determining, by one or more computer processors, access for the request based on the mobile device information and the current data usage quantity.

Abstract: The method include receiving, by one or more computer processors, a request for data usage, the request for data usage being associated with a mobile device. The method further includes identifying, by one or more computer processors, a current data usage quantity, the current data usage quantity being associated with the mobile device. The method further includes determining, by one or more computer processors, whether the current data usage quantity is beyond a threshold data usage. The method further includes responsive to the data usage quantity being beyond the threshold data usage, receiving, by one or more computer processors, mobile device information associated with the mobile device. The method further includes analyzing, by one or more computer processors, the mobile device information. The method further includes determining, by one or more computer processors, access for the request based on the mobile device information and the current data usage quantity.

Abstract: The method include receiving, by one or more computer processors, a request for data usage, the request for data usage being associated with a mobile device. The method further includes identifying, by one or more computer processors, a current data usage quantity, the current data usage quantity being associated with the mobile device. The method further includes determining, by one or more computer processors, whether the current data usage quantity is beyond a threshold data usage. The method further includes responsive to the data usage quantity being beyond the threshold data usage, receiving, by one or more computer processors, mobile device information associated with the mobile device. The method further includes analyzing, by one or more computer processors, the mobile device information. The method further includes determining, by one or more computer processors, access for the request based on the mobile device information and the current data usage quantity.

Abstract: One embodiment for determining a marketing incentive for a user of an electronic device. In one embodiment, a computer processor detects a first electronic device within a retail environment utilizing a second electronic device that also identifies information associated with the first electronic device. In one embodiment, a computer processor determines a behavior associated with the first electronic device based, at least in part, on movement of the first electronic device within the retail environment. In one embodiment, a computer processor identifies data associated with the retail environment that includes information associated with a retailer associated with the retail environment and information associated with the first electronic device. In one embodiment, a computer processor determines a first marketing incentive based, at least in part, on the determined behavior associated with the first electronic device and the identified data associated with the retail environment.

Abstract: A computer-implemented method includes receiving a data stream and dividing the data stream into one or more data artefacts for one or more time intervals. The computer-implemented method further includes generating one or more contexts. Each of the one or more contexts are for at least one of the one or more time intervals. The computer-implemented method further includes storing each of the one or more data artefacts in shared storage. The shared storage is accessible for each of the one or more contexts. The computer-implemented method further includes, for each context of the one or more contexts: determining a dependency for the context; monitoring the context for a completion of said dependency; and responsive to the completion, releasing the dependency. The computer-implemented further includes removing those of the one or more data artefacts that do not belong to the dependency for any of the one or more contexts.

Abstract: The method include receiving, by one or more computer processors, a request for data usage, the request for data usage being associated with a mobile device. The method further includes identifying, by one or more computer processors, a current data usage quantity, the current data usage quantity being associated with the mobile device. The method further includes determining, by one or more computer processors, whether the current data usage quantity is beyond a threshold data usage. The method further includes responsive to the data usage quantity being beyond the threshold data usage, receiving, by one or more computer processors, mobile device information associated with the mobile device. The method further includes analyzing, by one or more computer processors, the mobile device information. The method further includes determining, by one or more computer processors, access for the request based on the mobile device information and the current data usage quantity.

Abstract: The method include receiving, by one or more computer processors, a request for data usage, the request for data usage being associated with a mobile device. The method further includes identifying, by one or more computer processors, a current data usage quantity, the current data usage quantity being associated with the mobile device. The method further includes determining, by one or more computer processors, whether the current data usage quantity is beyond a threshold data usage. The method further includes responsive to the data usage quantity being beyond the threshold data usage, receiving, by one or more computer processors, mobile device information associated with the mobile device. The method further includes analyzing, by one or more computer processors, the mobile device information. The method further includes determining, by one or more computer processors, access for the request based on the mobile device information and the current data usage quantity.