Abstract: The present invention relates to a process for the preparation of blue-fluorescence emitting carbon dots (CDTs) from sub-bituminous tertiary high sulfur Indian coals. More particularly, the present invention relates to the production of characteristics carbon dots from low-quality Indian coals by an ultrasonic-assisted wet-chemical method. Also, the present invention provides a simple and environmentally benign method for fabrication of characteristics and size-controlled carbon dots.

Abstract: Generally described, systems and methods are provided for detecting the impact of network failures. The system collects performance information from a plurality of nodes and links in a network, aggregates the collected performance information across paths in the network, processes the aggregated performance information for detecting failures on the paths, adjusts the set of performance information by removing the performance information for any nodes considered to be associated with performance information that is statistically different from performance information from other nodes at a given location or extrapolates the collected information to other paths, and determines the impact to customers of the network failures detected using the adjusted set of performance information.

Abstract: The present invention relates to a process for the preparation of blue-fluorescence emitting carbon dots (CDTs) from sub-bituminous tertiary high sulfur Indian coals. More particularly, the present invention relates to the production of characteristics carbon dots from low-quality Indian coals by an ultrasonic-assisted wet-chemical method. Also, the present invention provides a simple and environmentally benign method for fabrication of characteristics and size-controlled carbon dots.

Abstract: Disclosed are various embodiments for analyzing media performance as a basis for production of new media. A computing device identifies a plurality of attributes correlated with performance of a media file. The computing device then selects a plurality of media files for testing, wherein individual ones of the plurality of media files have at least one of the plurality of attributes. The computing device sends at least one of the plurality of media files to a client device. Subsequently, the computing device calculates a rating for the at least one of the plurality of media files based at least in part on a response on feedback data received from the client device.

Abstract: A network analysis module may obtain information including but not limited to network traffic and topology information for a network environment including multiple separate networks and physical connections between the networks. The module generates a network topology model including but not limited to extreme-case failure or break information according to the network topology information, and applies the historical network traffic information to the network topology model to predict future expected normal traffic load and extreme-case traffic load for each route over the physical connections between the networks. Output may include one or more reports for each route, each report indicating the historical and predicted traffic levels for both normal and extreme-case scenarios of a respective route.

Abstract: Generally described, systems and methods are provided for detecting the impact of network failures. The system collects performance information from a plurality of nodes and links in a network, aggregates the collected performance information across paths in the network, processes the aggregated performance information for detecting failures on the paths, adjusts the set of performance information by removing the performance information for any nodes considered to be associated with performance information that is statistically different from performance information from other nodes at a given location or extrapolates the collected information to other paths, and determines the impact to customers of the network failures detected using the adjusted set of performance information.

Abstract: Generally described, systems and methods are provided for detecting the impact of network failures. The system collects performance information from a plurality of nodes and links in a network, aggregates the collected performance information across paths in the network, processes the aggregated performance information for detecting failures on the paths, adjusts the set of performance information by removing the performance information for any nodes considered to be associated with performance information that is statistically different from performance information from other nodes at a given location or extrapolates the collected information to other paths, and determines the impact to customers of the network failures detected using the adjusted set of performance information.

Abstract: Disclosed are various embodiments that provide a mixture model approach to network forecasting. Network traffic models are generated for multiple host types. Weights are determined for the network traffic models. A network forecast is generated based at least in part on a hardware footprint forecast and on the network traffic models as weighted by the determined weights.

Abstract: Disclosed are various embodiments that provide a mixture model approach to network forecasting. Network traffic models are generated for multiple host types. Weights are determined for the network traffic models. A network forecast is generated based at least in part on a hardware footprint forecast and on the network traffic models as weighted by the determined weights.

Abstract: Generally described, systems and methods are provided for detecting locations of failures of network paths. The system collects information from a plurality of nodes and links in a network, aggregates the collected performance information across paths in the network, processes the aggregated performance information for detecting failures on the paths, and determines at least one location for network failures. In some aspects, processing the aggregated information may include determining the performance information on each of the nodes and links in the network. The performance information on each of the nodes and links may be determined by application and optimization of an objective function.

Abstract: Generally described, systems and methods are provided for detecting locations of failures of network paths. The system collects information from a plurality of nodes and links in a network, aggregates the collected performance information across paths in the network, processes the aggregated performance information for detecting failures on the paths, and determines at least one location for network failures. In some aspects, processing the aggregated information may include determining the performance information on each of the nodes and links in the network. The performance information on each of the nodes and links may be determined by application and optimization of an objective function.

Abstract: A network analysis module may obtain information including but not limited to network traffic and topology information for a network environment including multiple separate networks and physical connections between the networks. The module generates a network topology model including but not limited to extreme-case failure or break information according to the network topology information, and applies the historical network traffic information to the network topology model to predict future expected normal traffic load and extreme-case traffic load for each route over the physical connections between the networks. Output may include one or more reports for each route, each report indicating the historical and predicted traffic levels for both normal and extreme-case scenarios of a respective route.

Abstract: A network analysis module may obtain information including but not limited to network traffic and topology information for a network environment including multiple separate networks and physical connections between the networks. The module generates a network topology model including but not limited to extreme-case failure or break information according to the network topology information, and applies the historical network traffic information to the network topology model to predict future expected normal traffic load and extreme-case traffic load for each route over the physical connections between the networks. Output may include one or more reports for each route, each report indicating the historical and predicted traffic levels for both normal and extreme-case scenarios of a respective route.