Abstract: A bare metal server, or other computing device, may be represented as a JSON file (extending the concept to infrastructure as code) containing hardware, firmware and software versions with links to a kickstarter file depending on the needs of an application, SKU type or some other criteria. Rather than a management node in an L2 network which has a DHCP server to IP lease and facilitate OS installation, a workflow then generates a bootstrap kernel which initializes the bare metal server with an IP address, VLAN, and network gateway which is used to reach out to the network to download and install a kernel, upgrade firmware for various hardware components like BIOS, BMC, NIC, RAID, SSD, NVME, FPGA, etc. The bootstrap kernel may further configure RAID and JBOD, flash custom images on hardware components and may further instruct the server to incrementally download and install an operating system.

Abstract: There is provided a method of and apparatus for streaming data. Data segments containing audio and/or video data content are received over a network. The data segments are stored in a buffer. It is determined that the network has capacity to provide the content in the data segments at a higher quality than is currently stored in the buffer prior to playout of the data segments. A higher quality version of content of one or more data segments in the buffer that have the latest relative playout time are requested in preference to requesting a higher quality version of content of data segments that have earlier relative playout times.

Abstract: A computing system is configured to analyze both measurement data and indicator data as big data aggregated in measurement database and indicator database by deep learning for each lot of a part or for each lot of a finished product and a part pre-associated with each other, and also for each consolidation target between bases subordinate to the same start point corresponding to identification information that specifies a business user of the computing system. Analysis target layers by the deep learning are a three-layer serial hierarchical structure containing a production condition layer and an environment condition layer as a start point for analysis of a part layer, or a four-layer serial hierarchical structure containing a part layer, a production condition layer, and an environment condition layer as a start point for analysis of a finished product layer.

Abstract: Methods and systems for monitoring a premises are described. A computing device may receive data from a premises management system. The computing device determines one or more actions to perform by analyzing the data. The computing device may determine to output, via a user interface, an indication associated with the data. A user may request video associated with the data.

Abstract: Systems and methods of network telemetry caching and distribution are provided. The system can receive network telemetry data and store it as a plurality of data nodes. The system can maintain a node pointer map and a node pointer queue. If the system receives an update to a data node having a corresponding node pointer not already present in the node pointer map, the system can add the node pointer to the node pointer queue and to the node pointer map with a count of zero. If the node pointer is already present in the node pointer map, the system can increment the node count for the node pointer in the node pointer map and not add the node pointer to the node pointer queue. The system can transmit data values and node counts to the client device for each node pointer in the node pointer queue.

Abstract: Aspects of the present disclosure relate to automatic monitor position adjustment. An indication that an application is being launched is received. A preferred monitor position for the application is determined by referencing a data store mapping preferred monitor positions to respective metadata attributes, where the preferred monitor position for the application is determined based on the preferred monitor position being mapped to a first metadata attribute associated with the application within the data store. An actuator associated with the monitor is then instructed to adjust the position of the monitor to the preferred monitor position.

Abstract: The disclosure provides an approach for compliance management in a network. Embodiments include receiving, by a manager, a system health plugin. Embodiments include determining a configuration change for a network. Embodiments include receiving data indicating a current security posture of the network. Embodiments include determining an impact to the security posture of the network based on the configuration change. Embodiments include generating a notification relating to the impact to the security posture of the network. Embodiments include receiving a decision relating to the configuration change in response to the notification. Embodiments include performing an action based on the decision.

Abstract: Network slicing can provide logical network partitioning. This introduces a high degree of flexibility to support devices with different requirements in terms of quality of service, as well as to optimize the network usage. However, each one of these networks can be used for distinct business purposes. Thus, individual slice surveillance statistics, including failure messages, can be utilized to alert other slices that share the same infrastructure. Thus, an early recovery action can be prompted based on a single slice's anomalies being shared with other slices.

Abstract: Acquiring labeled data can be a significant bottleneck in the development of machine learning models that are accurate and efficient enough to enable safety-critical applications, such as automated driving. The process of labeling of driving logs can be automated. Unlabeled real-world driving logs, which include data captured by one or more vehicle sensors, can be automatically labeled to generate one or more labeled real-world driving logs. The automatic labeling can include analysis-by-synthesis on the unlabeled real-world driving logs to generate simulated driving logs, which can include reconstructed driving scenes or portions thereof. The automatic labeling can further include simulation-to-real automatic labeling on the simulated driving logs and the unlabeled real-world driving logs to generate one or more labeled real-world driving logs. The automatically labeled real-world driving logs can be stored in one or more data stores for subsequent training, validation, evaluation, and/or model management.

Abstract: An example method is described for monitoring a network. The method includes detecting that a network attribute has been updated at a network device. The method further includes selecting, based in part on the updated network attribute, a set of network functionality tests from a group of network functionality tests. The method further includes executing the set of network functionality tests. The method further includes receiving information describing functionality of the network during the set of network functionality tests at the network device. The method further includes determining results of the set of network functionality tests based on the information describing functionality of the network. The method further includes calculating a network functionality score based, in part, on the results of the set of network functionality tests.

Abstract: A system or method executing an intelligent face framing management system comprising a processor to execute code instructions of a multimedia multi-user collaboration application to join a videoconference session, a display screen, a speaker, a video camera, and a microphone where the video camera captures a videoframe of a user and the processor to input videoframe data, including the detected user's image, into a trained neural network to determine image features for the intelligent face framing management system to generate optimized face framing adjustments center or normalize the user's image in the captured videoframes or intelligently select an alternate camera and prepare those videoframes for transmission.

Abstract: A system for using artificial intelligence to analyze user activity data, the system comprising a computing device configured to receive from a user, at least a biological extraction and at least a user activity datum, determine a current user location, generate a diagnostic output as a function of the biological extraction, wherein the diagnostic output comprises a condition of the user, retrieve, from a fingerprint database, at least a datum of user fingerprint data, identify a plurality of compatible elements at the current user location as a function of the condition of the user, select at least a compatible element as a function of the fingerprint data, and present, via a graphical user interface, the at least a compatible element to a user device.

Abstract: Systems and methods for detection and cleanup of unused microservices. An example method comprises: identifying, by a processing device, a microservice in a running state; identifying a network proxy associated with the microservice; monitoring traffic between the network proxy and the network; determining that the network proxy has no traffic with the network during a window, wherein the window is a predetermined period of time or a predetermined amount of data that is sent to or from the network; and deleting the microservice and the network proxy.

Abstract: A communication device includes a first communication circuit configured to receive, from a user terminal, a notification signal including at least identification information and request information representing a transmission request to provide transmission data including at least biomedical information, a second communication circuit configured to receive the transmission data from the user terminal, and a controller.

Abstract: Systems and methods are disclosed for cross-device task registration and resumption. In one implementation, a task can be received from a task registration service of a first device associated with a user. Such a task can include an application identifier that identifies an application that executes on the device. A notification that the user has accessed a second device can be received. In response to the notification, the task can be provided to a task resumption service of the second device.

Abstract: A machine-to-machine (M2M) node is configured to provide a communication management function to facilitate communication between a first service layer in a first network and a second service layer in a second network. The M2M node is configured to store a plurality of attributes for use by the communication management function and to receive via the first network, a first message from a first application in the first service layer. The M2M node is configured to determine, based on at least a first attribute identifying an expiration time after which the communication management function does not facilitate communication, that the communication management function is available to process the first message. The M2M node is configured to determine, based on at least a second attribute defining an access control list identifying applications in the first service layer, that the communication management function is available to process the first message.

Abstract: One example method includes configuring an input device based in part on a type of network with which the input device is expected to be used, configuring an output device based in part on a type of network with which the output device is expected to be used, registering the input device and the output device with an orchestrator, downloading a service needed to process a data stream generated by the input device, configuring an execution pipeline, and the execution pipeline includes the service, receiving the data stream from the input device and processing the data stream with the execution pipeline, and transmitting information relating to the processed data stream to the output device.

Abstract: A system, method, and apparatus for detecting errors in an artificial intelligence engine. The method includes processing a medical image of a patient at an artificial intelligence engine, and producing a first test result at the artificial intelligence engine based on the medical image. The method also includes detecting an error in the first test result using a server emulator, and producing a second test result that corrects the error in the first test result. In addition, the method includes transmitting the second test result from the artificial intelligence engine to a picture archiving and communication systems server.

Abstract: Methods, systems, and computer-readable storage media for determining a sub-set of services, each service in the sub-set of services being in an overload status and having a SSF associated therewith, providing statistics associated with each service in the sub-set of services and relating service call statistics to each API group of a set of API groups, determining a set of sessions based on the service call statistics, each session in the set of sessions associated with at least one service in the sub-set of services having a service call statistic that exceeds a threshold service call statistic, defining an execution group and a waiting group, determining that a session is in the waiting group, and in response, blocking a request of the session from being processed by a service in the sub-set of services, and providing a wait indication to a user associated with the session.

Abstract: Systems and methods for optical device configuration. The methods comprise: receiving, by a mobile device, network configuration data for an electronic device that is at least partially out of reach to individuals without use of a climbable object, has an optical input device, and needs to have a network connection established; outputting from the mobile device a first visible sequence representing an activation code; receiving the activation code at the electronic device via the optical input device; performing operations by the electronic device to transition an operational mode to a configuration mode in response to the activation code; outputting from the mobile device a second visible sequence representing network configuration data for the electronic device; receiving the network configuration data at the electronic device via the optical input device; and modifying, by the electronic device, network settings in accordance with the network configuration data.