Abstract: Techniques and systems for detecting leakage of computing resources in cloud computing architectures are described. In some implementations, first data may be obtained that indicates usage of a computing resource, such as non-volatile memory, volatile memory, processor cycles, or network resources, by a group of computing devices included in a cloud computing architecture. The first data may be used to determine reference data that may include a distribution of values of usage of the computing resource by the group of computing devices. Second data may also be collected that indicates usage of the computing resource by the group of computing devices during a subsequent time frame. The second data may be evaluated against the reference data to determine whether one or more conditions indicating a leak of the computing resource are satisfied.

Abstract: A transformer area identification method includes: performing data acquisition on all sub-meters and a master meter in an identification domain to obtain a steady-state load, and generating a steady-state load jump curve; and performing load jump feature matching between steady-state load jump curves of all the sub-meters and a steady-state load jump curve of the master meter, and obtaining attribution of the sub-meters with a load jump according to matching results. A method for constructing transformer area line topology is further provided. A load jump identification technique is utilized to acquire a load value of each node in a transformer area power supply network, so as to form a load jump curve for each node. By performing load jump feature matching between load jump curves of all sub-meters and a load jump curve of a master meter, a mounting relationship of a corresponding electric meter is determined.

Abstract: A method for distributed electrical power determination of at least one consumer connected to a voltage source via a voltage path, where a voltage measurement device determines a supply voltage of the voltage source at a voltage measurement point and at least one current measurement device determines a consumer current of the consumer at a current measurement point. The method comprises recording measured values of the supply voltage to determine a voltage curve of the supply voltage, recording measured values of the consumer current to determine a current curve of the consumer current, analyzing the measured values of the supply voltage and/or the measured values of the consumer current with an analysis function to determine voltage characteristics of the voltage curve and/or current characteristics of the current curve, and determining at least one power value taking into account the voltage and/or current characteristics.

Abstract: An embodiment of the present application relates to the field of radar technology, and discloses a method and a device for adjusting parameters of LiDAR, and a LiDAR. The method includes: acquiring 3D environment information around the LiDAR; identifying a scenario type where the LiDAR is positioned and a drivable area based on the 3D environment information; determining a parameter adjusting strategy of the LiDAR based on the scenario type and the drivable area; and adjusting current operating parameters of the LiDAR based on the parameter adjusting strategy.

Abstract: A civil engineering machine has a machine control unit configured to determine data which defines the position and/or orientation of a reference point on the civil engineering machine in relation to a reference system independent of the position and orientation of the civil engineering machine. A geometrical shape to be produced on the ground is preset in either a machine control unit or a field rover control unit. The field rover is used to determine a position of at least one identifiable point of the preset geometrical shape in the independent reference system. Curve data defining a desired curve in the independent reference system, corresponding to the preset shape, is determined at least partially on the basis of the position of the at least one identifiable point of the preset geometrical shape in the independent reference system.

Abstract: Embodiments herein describe coupling traditional fan and shaper control along with aggregated knowledge of the temperature history of a hardware device to optimally manage the temperature of the hardware device to preserve its expected life while also providing the lower power, best performing solution possible. In one embodiment, a cooling application manages the expected life by trading off performance and power versus temperature to achieve a desired (or accepted) lifetime. In one embodiment, the cooling application calculates a historical temperature value for the hardware device which is then used to determine the expected life of the hardware device.

Abstract: First data indicating a position of a first end surface of a first sheet material and second data indicating a position of a second end surface of a second sheet material are acquired from an inspection machine, and information indicating that a winding body has a defect and a cause of the defect is any of a plurality of winding cores is output to a display for maintenance in a case where continuous positions of the first end surface indicated by the first data and continuous positions of the second end surface indicated by the second data are tilted with respect to reference lines.

Abstract: The present disclosure relates to the technical field of aquafarm monitoring, and in particular to a method, system and apparatus for intelligently monitoring an aquafarm with multi-dimensional panoramic perception. The method includes: analyzing preprocessed multi-dimensional panoramic perception information with time series analysis to obtain a linear fitting model; constructing a water quality forecasting-alarming model according to the linear fitting model; inputting fused data to a convolutional neural network (CNN) for training to obtain an electrical device fault diagnosis model; and monitoring an aquafarm with the water quality forecasting-alarming model and the electrical device fault diagnosis model.

Abstract: An electronic device, while displaying application content for a first application on a touchscreen display, detects an input comprising one or more touches on a region of the touchscreen display that includes the application content of the first application. In response to detecting the input comprising the one or more touches, the electronic device, in accordance with a determination that the one or more touches correspond to a system gesture for switching applications, replaces display of the first application with a second application without delivering information corresponding to the one or more touches to the first application; and in accordance with a determination that the touches do not correspond to a system gesture, delivers the information corresponding to the one or more touches to the first application.

Abstract: A system for determining a health condition and an anomaly of a field equipment 104 is provided. The system includes sensors 106A-N which sense information associated with the equipment 104, a field device 110 which receives the sensor data from sensors 106A-N, a camera unit 108 that captures visual data of the equipment 104 and a server 112. The server 112 includes a database 114 that stores the sensor data and the visual data. The server 112 further includes a fault detection module 202 that processes the sensor data to determine a fault or the health condition of the equipment 104, an image processing module 204 that is trained to detect the irregularities/anomaly in the equipment 104 by processing the visual data, and a report generation module 206 that generates an automated health report 212 based on the detected anomaly and the health condition of the equipment 104.

Abstract: Systems, methods, and non-transitory computer-readable media can be configured to perform receiving a notification of a maintenance event associated with a resource. The method includes retrieving historic maintenance data in relation to the resource with which the fault is associated, the maintenance information originating from a time period preceding the time of the maintenance event. The method includes identifying at least a portion of the retrieved historic maintenance data as being indicative of the maintenance event. The method also includes causing the portion of the retrieved historic maintenance data identified as being indicative of the maintenance event to be stored as a precursor signal of the maintenance event. The method also includes causing future maintenance data received from a plurality of resources related to the resource with which the maintenance event is associated to be monitored to predict a future occurrence of the maintenance event in the plurality of resources.

Abstract: Provided an apparatus configured to calculate a periodicity of time series data, generate a plurality of subsequences, from the time series data, a length of each subsequence set to the periodicity, calculate feature values of the plurality of subsequences; categorize the plurality of subsequences, based on the feature values thereof, into one or more groups, find a periodicity of the subsequences belonging in common to one group, based on an occurrence order of the subsequences belonging in common to the one group and perform missing event detection by identifying the subsequence, occurrence of which is expected according to the periodicity of the subsequences belonging in common to the one group, but not found.

Abstract: Technology for computerized anomaly detection, where the machine logic (for example, software) utilizes a multi-layer anomaly detection method that may include three (3) layers: (a) a baseline model for each feature at a single point, (b) a dynamic time window for historical data, and/or (c) correlation analysis for different model features.

Abstract: A system and method for recognizing and forecasting anomalous sensory behavioral patterns of a machine, including: monitoring a first set of time-stamped sensory input data related to at least one machine; determining, upon analysis of the first set of time-stamped sensory input data, a first suspicious pattern of a first anomalous sensory input behavior associated with the first set of time-stamped sensory input data; comparing the first suspicious pattern to a second pattern of a second anomalous sensory input behavior that is associated with a second set of time-stamped sensory input data, wherein the second pattern previously determined to be indicative of a machine failure; and, determining if the first suspicious pattern is correlated above a predetermined threshold with the second pattern.

Abstract: A system 10 for controlling a drilling operation by a drill rig 12 includes a receiver 16 for receiving sensed data related to the drilling operation. A processor 18 is in communication with the receiver 16, the processor 18 processing the sensed data to estimate at least one geological property of interest of a zone 20 in which the drill rig 12 is active. The processor 18 is configured to operate as a decision engine 22 to optimize the drilling operation automatically by changing at least one drilling related parameter during the drilling operation based on the at least one geological property of interest.

Abstract: A system is configured to obtain a plurality of performance metrics related to performance of a software application in a current application environment and each of a plurality of model application environments. The system assigns a score to each of the performance metrics collected for the current application environment and each of the model application environments, compares the respective scores assigned to each performance metric collected for the current application environment and each of the model application environments, and detects that at least one model application environment has a higher score associated with at least one performance metric as compared to the respective score of the at least one performance metric collected for the current application environment. The system determines a recommendation to use the at least one model application environment for the software application based on the detecting.

Abstract: Monitoring a set of virtual users during performance testing and reporting virtual user operations data to ensure an ongoing and constant transactions per second load and providing test result data with evidence of constant transactions per second (TPS) during the test. Generating and executing performance tests under constant TPS includes restarting virtual users that are terminated during the performance tests.

Abstract: A system and method for automatically detecting anomalies in an industrial control system (ICS) is provided. A behavioral model is provided, the model comprising groups of learned sets of interdependent ICS signals of parameters associated with an operation of the ICS. For each of the groups, the learned sets in the respective group include at least one independent signal and one or more dependent signals that are dependent on the independent signal in accordance with a common type of dependency. Monitoring signals of given parameters are obtained, the monitoring signals corresponding to a given learned set of the learned sets in one of the groups. Upon determining a nonconformance of an observed interdependency of the monitoring signals with a predicted interdependency of the monitoring signals, the predicted interdependency being in accordance with the type of dependency associated with the given learned set, an anomaly is automatically detected.

Abstract: Described herein are systems, methods, and software to enhance the management and deployment of data processing clusters in a computing environment. In one example, a management system may monitor data processing efficiency information for a cluster and determine when the efficiency meets efficiency criteria. When the efficiency criteria are met, the management system may identify a new configuration for the cluster and initiate an operation to implement the new configuration for the cluster.

Abstract: A system and method for processing application performance using application phase differentiation and detection is disclosed. Phase detection may be accomplished in a number of different ways, including by using a deterministic algorithm that looks for changes in the computing resource utilization patterns (as detected in the performance data collected). Machine learning (ML) and neural networks (e.g. sparse auto encoder SAE) may also be used. Performance data is aggregated according to phase and stored in a database along with additional application and computing system information. This database may then be used to find similar applications for performance prediction.