Abstract: Disclosed are techniques and apparatuses that are configured to receive an indication that a web browsing session executing on an enterprise server needs additional information based on a request for additional information being sent to a client device. The request may include an identifier of the web browsing session and an identifier of an enterprise server that initiated the web browsing session. A globally unique identifier related to the web browsing session and an identifier of the enterprise server is stored in a common data store. The web browsing session may be paused when the web browsing session requests additional information from a client device. The client device may respond with the additional information. The system may provide the identifier of the enterprise server to a load balancing component so the identified web browsing session executing on the enterprise server may continue to be used.

Abstract: Techniques for synthetic data generation in computer-based reasoning systems are discussed and include receiving a request for generation of synthetic data based on a set of training data cases. One or more focal training data cases are determined. For undetermined features (either all of them or those that are not subject to conditions), a value for the feature is determined based on the focal cases. In some embodiments, the generated synthetic data may be checked for similarity against the training data, and if similarity conditions are met, it may be modified (e.g., resampled), removed, and/or replaced.

Abstract: A system and method for deploying software is disclosed. The system includes an architecture for deploying simulation software as a service. The architecture includes a client layer. The client layer includes an edge device, a resource manager, an update framework, a firewall, and a key management system. The architecture further includes a control layer communicatively coupled to the client layer, wherein a portion of the control layer is configured within a server. The control layer includes an application programming interface, one or more containers, wherein at least one of the one or more containers is a simulation processing container. The control layer further includes an orchestration node, a continuous integration tool, one or more processors, and a content delivery network module. The architecture further includes a data layer communicatively coupled to the one or more containers.

Abstract: A method including receiving, from a user device, a user request to access data associated with a web page; generating, by a processor, a first transaction identification; collecting transaction information, the transaction information comprising server-side metrics; integrating, by the processor, the first transaction identification with the transaction information; transmitting, by the processor, the first transaction identification to the user device; receiving, from the user device, client-side data associated with a second transaction identification; integrating, by the processor, the server-side metrics and the client-side data; and analyzing, by the processor, the integrated server-side metrics and the client-side data.

Abstract: Mobility service providers and others can use cloud platforms to meet customer demand. Due to changing demand or changing technology numerous issues arise. For example, server utilization within the cloud platform can become less efficient over time. As another example, virtual machines and virtual network functions processed by the cloud platform typically need to be extensively tested and certified, which can be expensive. Moreover, intra-platform communication can play a significant role in the costs to operate a cloud platform. Techniques detailed herein can address many of these issues, e.g., by providing mechanisms for increasing host or server utilization in response to changing demand, introducing a container technique for virtual machines to mitigate testing costs, and modeling bandwidth resources.

Abstract: Techniques for synthetic data generation in computer-based reasoning systems are discussed and include receiving a request for generation of synthetic training data based on a set of training data cases. One or more focal training data cases are determined. For undetermined features (either all of them or those that are not subject to conditions), a value for the feature is determined based on the focal cases. In some embodiments, validity of the generated value may be checked based on feature information. In some embodiments, generated synthetic data may be checked against all or a portion of the training data to ensure that it is not overly similar.

Abstract: In one embodiment, an illustrative method herein comprises: receiving, at a device, a plurality of captured end-user navigation sessions for a monitored application; generating, by the device, a mapping of end-user workflows for the monitored application based on an aggregation of the plurality of captured end-user navigation sessions; determining, by the device, one or more particular end-user workflows from the mapping of end-user workflows for synthetic testing; generating, by the device, one or more synthetic scripts that traverse the one or more particular end-user workflows respectively; and sharing, by the device, the one or more synthetic scripts with a synthetic monitoring system to cause the synthetic monitoring system to synthetically test the monitored application using the one or more synthetic scripts to traverse the one or more particular end-user workflows.

Abstract: One embodiment is directed to a system for enabling two or more users to interact within a virtual world comprising virtual world data, comprising a computer network comprising one or more computing devices, the one or more computing devices comprising memory, processing circuitry, and software stored at least in part in the memory and executable by the processing circuitry to process at least a portion of the virtual world data; wherein at least a first portion of the virtual world data originates from a first user virtual world local to a first user, and wherein the computer network is operable to transmit the first portion to a user device for presentation to a second user, such that the second user may experience the first portion from the location of the second user, such that aspects of the first user virtual world are effectively passed to the second user.

Abstract: A method of controlling use of network-connectable devices is provided. First network requests from a first user device executing a first operating system are monitored, and applications operating in the foreground on the first user device during the first network requests are monitored. A model is trained based on the first network requests and based on the applications respectively operating in the foreground on the first user device during the first network requests. Second network requests from a second user device executing a second operating system are monitored, and the model is applied to the second network requests from the second user device to determine a particular application operating in the foreground on the second user device. A function of the second user device is restricted based on the determining of the particular application operating in the foreground on the second user device.

Abstract: According to an example implementation, a method may include transmitting, by a user device to a base station in a wireless network, a system information request for on-demand system information during a random access procedure, where the system information request is a request for one or more parameters that enable the user device to communicate in the wireless network, receiving, by the user device from the base station, an indication of a wait period in which the user device waits before obtaining the on-demand system information, waiting, by the user device, a time duration during the wait period, and monitoring, by the user device after expiration of the wait period, a system information window in which a system information message having the on-demand system information is broadcasted by the base station.

Abstract: Correlation of component information provided by diverse detection and data collection methods is used to discover additional components and identify and record relationships between these and still other components. Each detection and data collection method can be individually useful to discover components, and to provide at least some information about one or more discovered components to identify at least one relationship between the discovered components.

Abstract: An IoT system includes a computing module for controlling an integral function of the system and including an analysis unit and a machine learning unit. The analysis unit is capable of operational analysis and creating a predictive model and creating a predictive model according to the data analyzed. The machine learning unit has an algorithm function to create a corresponding learning model. An IoT module is electrically connected to the computing module to serve as an intermediate role. At least one detection unit is electrically connected to the IoT module and disposed in soil to detect data of environmental and soil conditions and sends the data detected to the computing module for subsequent analysis.

Abstract: Systems and methods include receiving data from a network that includes a plurality of network elements that operate at a plurality levels that include any of network layers and encapsulations; displaying any of the plurality of network elements as a three-dimensional icon on a network map; illustrating a plinth in the three-dimensional icon for each of the plurality of levels for each network element of the any of the plurality of network elements, wherein a plinth at each level indicates a corresponding network element participates in that level; and illustrating horizontal connectivity as links between any of the network elements via associated plinths.

Abstract: An approach is provided for accessing and managing data from multiple heterogeneous data sources, processing the data to generate processing results, and providing user access to the processing results via a portal. The portal provides unified intelligent views of the processing results across the heterogeneous data sources, providing a single source of facts and trends. Embodiments include controlling user access to the views based upon user credentials.

Abstract: The disclosure relates to methods and systems for predicting time of occurrence of future server failures using server logs and a stream of numeric time-series data occurred with a particular time window. Method performed by processor includes accessing plurality of server logs and stream of numeric time-series data, applying density and sequential machine learning model over plurality of server logs for obtaining first and second outputs, respectively, applying a stochastic recurrent neural network model over the stream of time-series data to obtain third output. The method includes aggregating first, second, and third outputs using an ensemble model, predicting likelihood of at least one future server anomaly based on the aggregating, and determining time of occurrence of the at least one future server anomaly by capturing server behavior characteristics using time-series network model. The server behavior characteristics include time-series patterns of the stream of numeric time-series data.

Abstract: A trust reality service brokering apparatus located on an edge cloud receives a context rule, analyzes event data of at least one physical entity connected to the edge cloud based on the context rule, and transmits an action command to a physical entity or virtual entity corresponding to the event when it is determined that an event has occurred according to an analysis result.

Abstract: Systems and methods are provided for receiving a first media content item associated with a first interactive object of an interactive message, receiving a second media content item associated with a second interactive object of the interactive message, generating a third media content item based on the first media content item and second media content item, wherein the third media content item comprises combined features of the first media content item and the second media content item, and causing display of the generated third media content item.

Abstract: Virtual Reality (VR) processing devices and methods are provided for transmitting user feedback information comprising at least one of user position information and user orientation information, receiving encoded audio-video (A/V) data, which is generated based on the transmitted user feedback information, separating the A/V data into video data and audio data corresponding to a portion of a next frame of a sequence of frames of the video data to be displayed, decoding the portion of a next frame of the video data and the corresponding audio data, providing the audio data for aural presentation and controlling the portion of the next frame of the video data to be displayed in synchronization with the corresponding audio data.

Abstract: A client device determines a local user gradient value based on a current user preference vector and a local item gradient value based on a current item feature vector. The client device updates a user preference vector by using the local user gradient value and updates an item feature vector by using the local item gradient value. The client device determines a neighboring client device based on a predetermined adjacency relationship. The local item gradient value is sent by the client device to the neighboring client device. The client device receives a neighboring item gradient value sent by the neighboring client device. The client device updates the item feature vector by using the neighboring item gradient value. In response to the client device determining that a predetermined iteration stop condition is satisfied, the client device outputs the user preference vector and the item feature vector.

Abstract: Disclosed herein are embodiments of systems, methods, and products comprises an analytic server, which evaluates user data for premium financing status and dynamically renders graphical user interfaces. The server trains an artificial intelligence model based on historical user data. The artificial intelligence model comprises one or more data points with each data point representing one of a plurality of attributes and applies a logistic regression algorithm to identify a weight factor for each attribute. The server uses a dynamic algorithm to generate a score by combining the plurality of attributes based on the weight factors. The server receives responses regarding the scores that indicate the premium financing status of each case. The server retrains the artificial intelligence model to identify new weight factors based on negative responses data. The server automatically displays new scores calculated based on the new weight factors.