Abstract: System and method for predicting and scoring a data model are provided. The system includes a memory configured to receive a plurality of data sets. The system also includes a processing subsystem operatively coupled to the memory and configured to select one or more variables based on a plurality of parameters, to apply feature engineering and transformation on one or more variables to extract a plurality of features from the plurality of data sets, to build new data model based on the plurality of features, to evaluate a classification technique to select a right machine learning model based on a plurality of elements, to predict a newly built data model based on an evaluated classification technique and score the predicted data model. The system further includes a display model operatively coupled to the processing subsystem and configured to present the predicted and scored data model in one or more forms.

Abstract: A biosensor component is provided that provides enhanced characteristics for use in biosensors, such as blood glucose sensors. The biosensor component comprises a substrate and a conductive layer coated on the substrate. The conductive layer includes nickel, chromium, and iron, such that a combined weight percent of the nickel and chromium in the conductive layer is in the range of 80 to less than 95 weight percent, and the weight percent of iron in the conductive layer is greater than 5 weight percent and less than 12 weight percent.

Abstract: Segments of a network having connectivity issues are detected in a network environment that may include one or more cloud computing platforms. A mutual information algorithm is used to determine relevance of network element factors, a subset of factors are selected based on relevance, and clustered according to values for the subset of factors, and quality of the clusters evaluated. Various thresholds for selecting the subset of factors may be used to determine which provides improved cluster quality. An approach for performing root cause analysis of events in a network environment selects bad events for logging alerts based on whether a factor is found to distinguish bad events according to a mutual information algorithm. Events for alerts maybe aggregated based on temporal proximity or similarity. Visualization may be performed using Sankey diagrams with each column representing a factor.

Abstract: A system and method for data analysis and presentation of data are provided. The system for data analysis and presentation of data includes a memory configured to receive a plurality of data sets. The system also includes a processing subsystem operatively coupled to the memory and configured to determine a plurality of properties of the plurality of data sets, to analyse a categorical variable of the plurality of data sets based on the plurality of properties of the plurality of the plurality of data sets, to identify one or more custom rules based on an analysed categorical variable, to interpret the identified one or more custom rules, to identify a graph based on one or more custom rules, to identify one or more textual insights based on one or more custom rules and the identified graph, to present the identified graph and one or more textual insights.

Abstract: An architecture for dynamically selecting and routing traffic from Internet of things (IoT) devices and sensors to the nearest or most proximate IoT hub device. A method can comprise receiving a connection request from a user device; retrieving address data representing a network device of a group of network devices; and sending the address data to the user device.

Abstract: An architecture for dynamically selecting and routing traffic from Internet of things (IoT) devices and sensors to the nearest or most proximate IoT hub device. A method can comprise receiving a connection request from a user device; retrieving address data representing a network device of a group of network devices; and sending the address data to the user device.

Abstract: System and method to build and score predictive model for numerical attributes are provided. The system includes a memory and a processing subsystem. The processing subsystem is configured to select one or more numerical variables from the plurality of data sets based on a plurality of parameters, to apply feature engineering and transformation on the one or more numerical variables, to perform time series forecasting on the one or more numerical variables based on the plurality of features extracted, to evaluate and select appropriate prediction technique based a regression technique based on a plurality of elements, to build a prediction model, to score the built prediction model based on the performed time series forecasting and an evaluated regression technique and to predict the built prediction model based on an obtained score. Further, the system uses the plurality of parameters and the prediction method to score and predict the prediction model.

Abstract: Systems and methods for generating synthetic data using federated, collaborative, privacy preserving learning models are disclosed. In one embodiment, a method for generating synthetic data from real data for use in a federated learning network may include: (1) conducting, by a backend for a first institution of a plurality of institutions in a federated learning network, a transaction comprising transaction data; (2) generating, by the backend for the first institution, local synthetic data for the transaction data using a local synthetic data generating model; (3) sharing, by the backend for the first institution, the local synthetic data with a plurality of backends for other institutions; (4) receiving, by the backend for the first institution, global synthetic data from the plurality of backends for the other institutions; and (5) training, by the backend for the first institution, a local machine learning model with the global synthetic data.

Abstract: A biosensor component that provides enhanced characteristics for use in biosensors, such as blood glucose sensors. The biosensor component comprises a substrate, and a composite layer deposited on the substrate. The composite layer includes a conductive metal component and a resistive material component, where the conductive metal component comprises one or more non-noble metals, and where the resistive material component in the composite layer is present in an amount greater than 20 atomic percent.

Abstract: System and method to analyze and predict impact of textual data are provided. The system also includes a processing subsystem configured to select textual data from a plurality of data sets stored in a memory, to extract data from external sources using crawling, to identify at least one context of the textual data using one or more identification methods. The processing subsystem includes an NLP module configured to match the textual data with NLP frameworks using a mapping method based on a plurality of parameters, to apply feature engineering and transformation on the textual data to extract a plurality of features from the plurality of data sets and to analyze matched textual data of the textual using at least one analysis method. The processing subsystem also includes a predictive module configured to predict one or more future values of the analyzed textual data using the one or more predictive methods.

Abstract: Edge clusters execute in a plurality of regional clouds of a cloud computing platforms, which may include cloud POPs. Edge clusters may be programmed to control access to applications executing in the cloud computing platform. Edge clusters and an intelligent routing module route traffic to applications executing in the cloud computing platform. Cost and latency may be managed by the intelligent routing module by routing requests over the Internet or a cloud backbone network and using or bypassing cloud POPs. The placement of edge clusters may be selected according to measured or estimated latency. Latency may be estimated using speed test servers and the locations of speed test servers may be verified.

Abstract: An aggregated BIER networking system includes first and second aggregated BFER devices that are each directly connected to first and second receiver devices. The first aggregated BFER device receives a request from the first receiver device for multicast data packets generated by a source device and transmits the request to a BFIR device. The first aggregated BFER device also receives an identification from the second aggregated BFER device of the second receiver device that has requested multicast data packets generated by the source device. The first aggregated BFER device advertises a virtual BFER device that appears to be directly connected to each of the first and second aggregated BFER devices, and each of the first and second receiver devices. The first aggregated BFER device then receives a multicast data packet identifying the virtual BFER device, and forwards the multicast data packet to each of the first and second receiver devices.

Abstract: Edge clusters execute in a plurality of regional clouds of a cloud computing platforms, which may include cloud POPs. Edge clusters may be programmed to control access to applications executing in the cloud computing platform. Edge clusters and an intelligent routing module route traffic to applications executing in the cloud computing platform. Cost and latency may be managed by the intelligent routing module by routing requests over the Internet or a cloud backbone network and using or bypassing cloud POPs. The placement of edge clusters may be selected according to measured or estimated latency. Latency may be estimated using speed test servers and the locations of speed test servers may be verified.

Abstract: An aggregated switch PBR system includes aggregated switches coupled together by an ICL and to a first core switch by a first LAG. A first aggregated switch includes a first link in the first LAG, and a second link to a second core switch. The first aggregated switch provides a first PBR entry in its PBR table that redirects packets initially provided for forwarding via the second link to the second core switch such that those packets are forwarded via the first link to the first core switch. When the first link becomes unavailable, the first aggregated switch provides a second PBR entry in its PBR table that redirects the packets initially provided for forwarding via the second link to the second core switch such that those packets are forwarded via the ICL to the second aggregated switch for transmission via the first LAG to the first core switch.

Abstract: Edge clusters execute in a plurality of regional clouds of a cloud computing platforms, which may include cloud POPs. Edge clusters may be programmed to control access to applications executing in the cloud computing platform. Edge clusters and an intelligent routing module route traffic to applications executing in the cloud computing platform. Cost and latency may be managed by the intelligent routing module by routing requests over the Internet or a cloud backbone network and using or bypassing cloud POPs. The placement of edge clusters may be selected according to measured or estimated latency. Latency may be estimated using speed test servers and the locations of speed test servers may be verified.

Abstract: An architecture for dynamically selecting and routing traffic from Internet of things (IoT) devices and sensors to the nearest or most proximate IoT hub device. A method can comprise receiving a connection request from a user device; retrieving address data representing a network device of a group of network devices; and sending the address data to the user device.

Abstract: A networking aggregation link provisioning system includes a second aggregated networking device that is configured to provide a second portion of a link aggregation to a connected device, and a first aggregated networking device that is configured to provide a first portion of the link aggregation to the connected device. The first aggregated networking device establishes an inter-aggregated-networking-device link with the second aggregated networking device and, in response, synchronizes first aggregated networking device process(es) running in the first aggregated networking device with respective corresponding second aggregated networking device process(es) running in the second aggregated networking device.

Abstract: An aggregated BIER networking system includes first and second aggregated BFER devices that are each directly connected to first and second receiver devices. The first aggregated BFER device receives a request from the first receiver device for multicast data packets generated by a source device and transmits the request to a BFIR device. The first aggregated BFER device also receives an identification from the second aggregated BFER device of the second receiver device that has requested multicast data packets generated by the source device. The first aggregated BFER device advertises a virtual BFER device that appears to be directly connected to each of the first and second aggregated BFER devices, and each of the first and second receiver devices. The first aggregated BFER device then receives a multicast data packet identifying the virtual BFER device, and forwards the multicast data packet to each of the first and second receiver devices.