Abstract: Disclosed is a system and method for converting a voluminous stream of unstructured short text messages into event-objects of specific event type that may be of potential interest to users at far away locations. The method of structuring involves detecting long tail of events in spite of their sparsity. This is followed by extracting and correlating detected short text messages that describe same event type to create structured event objects.

Abstract: Described techniques enable resource accounting and tracking in high access rate systems using low cost memories. A first set of counters is maintained in relatively lower cost memory. The first counters generally indicate the amount of resources used for each object in a set of objects, but on a potentially delayed basis. A second set of counters of smaller size is stored in a relatively higher cost memory that supports high arrival and departure rates for accurate accounting. Each second counter indicates the amount of resources assigned (or unassigned) to an object since the object's first counter was last updated, and is incremented or decremented whenever this amount changes. A background process is configured to update individual first counters from the corresponding second counters on a recurring basis. The exact times at which a given first counter is updated may vary in accordance with a variety of approaches.

Abstract: A resource management system for a network device is described. A resource management system includes a resource manager configured to generate a sequence of a plurality of access time slots for a plurality of candidate entities and to redistribute access to one or more of the plurality of access time slots in the sequence based on availability and eligibility. The resource management system also includes a resource monitor configured to detect usage of each of the access time slots by each of the plurality of candidate entities.

Abstract: The present invention relates a novel system and method for person identification and personality assessment based on electroencephalography (EEG) signal. More particularly, this invention relates to a novel method of EEG recording and processing to map the inherent and unique properties of brain in the form of highly specific brain signature to be used as means for person identification and personality assessment.

Abstract: The present invention relates a novel system and method to diagnose and predict systemic disorders including brain disorders and mental states in early stage and more accurately. More particularly, this invention relates to a novel method of EEG recording and processing through which multiple output data streams are taken together from a system like brain and the structure of their correlation matrix is studied through its eigenvector, eigendirection and eigenspaces and other signal processing techniques including compression sensing, wavelet transform, fast fourier transform etc.

Abstract: Aspects of oversubscription monitoring are described. In one embodiment, oversubscription monitoring includes accumulating an amount of data that arrives at a network component over at least one epoch of time. Further, a core processing rate at which data can be processed by the network component is calculated. Based on the amount of data and the core processing rate, it is determined whether the network component is operating in an oversubscribed region of operation. In one embodiment, when the network component is operating in the oversubscribed region of operation, certain quality of service metrics are monitored. Using the monitored metrics, a network operation display object may be generated for identifying or troubleshooting network errors during an oversubscribed region of operation of the network component.

Abstract: Disclosed are various embodiments for multi-homing in an extended bridge, including both multi-homing of port extenders and multi-homing of end stations. In various embodiments, a controlling bridge device receives a packet via an ingress virtual port and determines a destination virtual port link aggregation group based at least in part on a destination media access control (MAC) address of an end station in the packet. The controlling bridge device selects one of multiple egress virtual ports of the destination virtual port link aggregation group. The end station of the extended bridge is reachable through any of the egress virtual ports of the destination virtual port link aggregation group. The controlling bridge device forwards the packet through the selected egress virtual port, and the forwarded packet includes an identifier of a destination virtual port to which the end station is connected.

Abstract: A downhole drilling assembly includes a drill string having an inner fluid passageway. A fluid motor disposed within the drill string has a rotor operable to rotate relative to a stator in response to a circulating fluid received via the inner fluid passageway. A drive shaft and drill bit are operably associated with and operable to rotate with the rotor. A hydraulically actuated clutch disposed within the drill string has a first configuration, wherein a first clutch assembly is disengaged from a second clutch assembly such that the drive shaft and drill bit rotate relative to the drill string and, a second configuration, wherein the first clutch assembly engages the second clutch assembly responsive to hydraulic pressure generated by rotation of the drill string such that the drive shaft and drill bit rotate with the drill string.

Abstract: A well tool apparatus for damping torsional vibration of a drill string comprises stabilizing members projecting radially outwards from a housing that is, in operation, rotationally integrated in the drill string, to stabilize the drill string by engagement with a borehole wall. The stabilizing members are displaceably mounted on the housing to permit limited angular movement thereof relative to the housing about its rotational axis. The well tool apparatus includes a hydraulic damping mechanism to damp angular displacement of the stabilizing members relative to the housing, thereby damping torsional vibration of the housing and the connected drill string, in use.

Abstract: System and method for visual Bayesian data fusion are disclosed. In an example, a plurality of datasets associated with a topic are obtained from a data lake. Each of the plurality of datasets include information corresponding to various attributes of the topic. Further, the plurality of datasets are joined to obtain a joined dataset. Furthermore, distribution associated with a target attribute is predicted using Bayesian modeling by selecting a plurality of attributes (k) based on mutual information with the target attribute in the joined dataset, learning a minimum spanning tree based Bayesian structure using the selected attributes and the target attribute, learning conditional probabilistic tables at each node of the minimum spanning tree based Bayesian structure; and predicting the distribution associated with the target attribute by querying the conditional probabilistic tables, thereby facilitating visual Bayesian data fusion.

Abstract: A directional drilling steering system is configured to direct a tubular sleeve arranged at the bottom of a drill string adjacent the drill bit at a selected tilt angle with respect to the longitudinal axis of the uphole drill string and at a selected azimuth. Tilt angle can be achieved by axial movement of one or more pistons in engagement with the downhole tubular sleeve. Azimuth can be achieved by axial movement of the pistons or by rotation of the drill string. The movement of the downhole sleeve along the deviated path causes movement of the drill bit shaft and the drill bit coupled thereto.

Abstract: This disclosure relates generally to multi-sensor visual analytics, and more particularly to method and system for multi-sensor visual analytics using machine-learning models. In one embodiment, a method for multi-sensor visual analytics includes acquiring sensor data associated with a plurality of sensors for a plurality of days of operation. A plurality of multi-dimensional histograms, having operational profiles of the plurality of sensors are computed from the sensor data. The plurality of multi-dimensional histograms are monitored, and a plurality of multi-sensor patterns are obtained from the plurality of multi-dimensional histograms. The plurality of multi-sensor patterns are indicative of one or more properties of a plurality of sensor-clusters of the plurality of sensors. One or more visual analytical tasks are performed by processing the plurality of multi-sensor patterns using at least one machine-learning model.

Abstract: Systems and methods for predictive reliability mining are provided that enable predicting of unexpected emerging failures in future without waiting for actual failures to start occurring in significant numbers. Sets of discriminative Diagnostic Trouble Codes (DTCs) from connected machines in a population are identified before failure of the associated parts. A temporal conditional dependence model based on the temporal dependence between the failure of the parts from past failure data and the identified sets of discriminative DTCs is generated. Future failures are predicted based on the generated temporal conditional dependence and root cause analysis of the predicted future failures is performed for predictive reliability mining. The probability of failure is computed based on both occurrence and non-occurrence of DTCs. The root cause analysis enables identifying a subset of the population when an early warning is generated and also when an early warning is not generated.

Abstract: This disclosure relates generally to multi-sensor data, and more particularly to summarizing multi-sensor data. In one embodiment, the method includes computing plurality of histograms from sensor data associated with a plurality of sensors. The respective histograms of each sensor are clustered into a first plurality of sensor-clusters, and a first set of rules is extracted therefrom. First set of rules defines patterns of histograms of a set of sensors occurring frequently over a time-period. Two or more sensor-clusters from amongst the first plurality of sensor-clusters are merged selectively to obtain a second plurality of sensor-clusters. Second set of rules are extracted from the second plurality of sensor-clusters, and a set of correlated sensors are identified therefrom based on the second set of rules. Third set of rules are extracted from the set of correlated sensors, the third set of rules summarizes the multi-sensor data to represent prominent co-occurring sensor behaviors.

Abstract: A system forwards congestion management messages to a source host updating the source address in the management message. The system may determine that the congestion management message was triggered responsive to an initial communication that was previously forwarded by the system. The system may use header translation within a single addressing scheme and/or may translate the congestion management message into a different type to support forwarding to the source of the initial communication. The system may use portions of the payload of the congestion management message to determine the source of the initial communication and to derive a different header for the translated congestion management message.

Abstract: Network devices facilitate flow management through packet marking. The network devices may be switches, routers, bridges, hubs, or any other network device. The packet marking may include analyzing received packets to determine when the received packets meet a marking criterion, and then applying a configurable marking function to mark the packets in a particular way. The marking capability may facilitate deadline aware end-to-end flow management, as one specific example. More generally, the marking capability may facilitate traffic management actions such as visibility actions and flow management actions.

Abstract: The present disclosure provides solutions that may enable an enterprise providing services to a number of clients to determine whether to establish a client based SSL VPN session or a clientless SSL VPN session with a client based on an information associated with the client. An intermediary establishing SSL VPN sessions between clients and servers may receive a request from a client to access a server. The intermediary may identify a session policy based on the request. The session policy may indicate whether to establish a client based SSL VPN session or clientless SSL VPN session with the server. The intermediary may determine, responsive to the policy, to establish a clientless or client based SSL VPN session between the client and the server.

Abstract: The present disclosure relates to business data processing and facilitates fusing business data spanning disparate sources for processing distributional queries for enterprise business intelligence application. Particularly, the method comprises defining a Bayesian network based on one or more attributes associated with raw data spanning a plurality of disparate sources; pre-processing the raw data based on the Bayesian network to compute conditional probabilities therein as parameters; joining the one or more attributes in the raw data using the conditional probabilities; and executing probabilistic inference from a database of the parameters by employing an SQL engine. The Bayesian Network may be validated based on estimation error computed by comparing results of processing a set of validation queries on the raw data and the Bayesian Network.

Abstract: Methods and systems for searching logical patterns in voluminous multi sensor data from the industrial internet is provided. The method retrieves instances of patterns in time-series data where patterns are specified logically, using a sequence of symbols. The logical symbols used are a subset of the qualitative abstractions specifically, the concepts of steady, increasing, decreasing. Patterns can include symbol-sequences for multiple sensors, approximate duration as well as slope values for each symbol. To facilitate efficient querying, each sensor time-series is pre-processed into a sequence of logical symbols. Each position in the resulting compressed sequence is registered across a TRIE-based index structure corresponding to the multiple logical patterns it may belong to. Logical multi-sensor patterns are efficiently retrieved and ranked using such a structure. This method of indexing and searching provides an efficient mechanism for exploratory analysis of voluminous multi-sensor data.

Abstract: A well tool apparatus for damping torsional vibration of a drill string comprises stabilizing members projecting radially outwards from a housing that is, in operation, rotationally integrated in the drill string, to stabilize the drill string by engagement with a borehole wall. The stabilizing members are displaceably mounted on the housing to permit limited angular movement thereof relative to the housing about its rotational axis. The well tool apparatus includes a hydraulic damping mechanism to damp angular displacement of the stabilizing members relative to the housing, thereby damping torsional vibration of the housing and the connected drill string, in use.