Abstract: Software performance evaluation and support is achieved proactively in a cloud architecture by collecting Key Performance Indicators (KPIs) of software performance across multiple tenants. Such software performance KPIs can include but are not limited to data volumes, backend calculation runtimes, and front end request runtimes. Influencing factors of a software performance model (e.g., model complexity, calculation complexity; application complexity) may be gathered. The collected data is referenced as a training corpus to create an Artificial Intelligence (AI) revealing correlation between model characteristic(s) and software performance. The AI is applied in the form of predictive analytics and/or Robotic Process Automation (RPA) to proactively identify software performance challenges and issue alerts. Embodiments may define lower thresholds and/or performance degradations that result in alert triggering.

Abstract: Various embodiments include a computer-aided method for state estimation of a power network using an artificial neural network with one or more inputs technically associated with the power network. The method may include calculating a state estimation using captured temporal measurement signals of the power network as inputs for the neural network. At least an amplitude of a harmonic of one of the measurement signals is used as an input for the neural network.

Abstract: A method for determining the set of focal laws of a plurality of focal points located in a test object includes the steps of providing a bidimensional array of transducer elements in a coupling medium and defining at least a scan line by a set of focal points. For each scan line, the method comprises performing the sub-steps of choosing a two preliminary focal points, calculating a first auxiliary time-of-flight corresponding to the time-of-flight of a wave emitted from the corresponding transducer element and received in the first preliminary focal point, and a second auxiliary time-of-flight corresponding to the time-of-flight of a wave emitted from the same transducer and received in the second preliminary focal point.

Abstract: A method for determining a regulation range of pumping power of a three-machine pumped storage unit is provided. The method includes: obtaining a first parameter set of pumping measurement parameters for characterizing the three-machine pumped storage unit and determining a pumping process efficiency; determining a first relational expression based on the pumping process efficiency and a design efficiency of a pumped storage power station and establishing a second relational expression; and determining a third relational expression based on power absorbed by a power grid and the second relational expression and determining a fourth relational expression, where the fourth relational expression reflects the regulation range of the pumping power of the three-machine pumped storage unit. The method for determining the regulation range of the pumping power of the three-machine pumped storage unit is proposed according to unit characteristics and operating economy of the power station.

Abstract: A method of determining application-specific plausibilities of measured values of measurands measured by measurement devices in a specific application is disclosed, comprising the steps of: recording data including items of diagnostic information for the measurement devices and variable values of specified variables including each measurand; for each measurand determining a total plausibility of the current measured values of the measurand based on plausibility values determined based on plausibility criteria including a diagnostic criterium and an application-specific threshold criterium and based on reliability values indicative of a statistical reliability of current measured value(s) of the measurand; and providing the total plausibilities and/or a total plausibility index determined based on the total plausibilities.

Abstract: A method for fusing environment-related parameters includes providing at least one environment-related parameter of a first sensor system; providing at least one environment-related parameter of a second sensor system; providing at least one respective boundary condition that existed when the respective at least one environment-related parameter of the respective sensor system was determined; assigning the at least one respective boundary condition to the respective at least one environment-related parameter of the respective sensor system; providing an evaluation scheme which assigns weighting factors to the respective environment-related parameter of the respective sensor system depending on the respective boundary conditions; and fusing, with a fusion device, the at least one environment-related parameter of the first sensor system with the at least one environment-related parameter of the second sensor system according to the assigned weighting factors to determine the representation of the environment of

Abstract: A method includes obtaining a pre-trained machine learning model and a training embedding snapshot from a remote system, and obtaining one or more input data samples captured by a user device. The method includes, for each particular input data sample of the one or more input data samples, processing, using an on-device machine learning model corresponding to the pre-trained machine learning model, the particular input data sample to generate a corresponding on-device embedding and one or more corresponding predicted outputs, and generating, using the training embedding snapshot and the corresponding on-device embedding, corresponding performance data. The method includes aggregating the corresponding performance data for the one or more input data samples to determine one or more performance metrics for the on-device machine learning model, and transmitting the one or more performance metrics to the remote system.

Abstract: A dynamic characteristic-reflected shoreline evaluation system and a method thereof are proposed. The system may include a data collection processor configured to collect various types of information for shoreline evaluation with respect to an evaluation target region. The system may also include a shoreline evaluation processor configured to determine a shoreline rank by reflecting static characteristics and dynamic characteristics of the evaluation target region on a basis of data collected through the data collection unit. The system may further include an output processor configured to output the various types of information comprising an evaluation result of the shoreline evaluation unit and an overall process and result of the system. The system may further include a communication processor configured to transmit and receive various types of data through wired or wireless communication with an external device. The system may include a controller configured to control an overall operation of the system.

Abstract: The technology disclosed relates to a method for inducing an agent-under-test (AUT) to disclose respective outputs in response to processing a target input probe. An agent sampling logic is configured to analyze respective outputs to determine whether the outputs represent a sample for the target input probe and to also determine a confidence level of the respective outputs being the sample for the target input probe.

Abstract: The technologies discussed herein relate to methods, systems, media, etc., for automatically triggering a user device action based on utilizing one or more ethanol sensor devices. In embodiments, an ethanol sensor device can detect ethanol vapor concentrations and determine whether the concentration is above a threshold. In embodiments, the ethanol sensor device can transmit the detected concentrations to one or more servers, which can cause the user device to initiate an action based on a concentration level that is above the threshold. For example, the server can provide one or more ride hailing services, such that the server initiates the user device action that includes providing, for display on a user interface of the user device, one or more selectable ride hailing transportation options from a location corresponding to the user device. In some embodiments, the server provides services corresponding to physical or mental health.

Abstract: A system monitoring apparatus comprising: a complementing unit that generates complemented node information by complementing, based on a complementing model trained using information collected in a testing system using a monitoring command and an agent, first node information collected in an operated system using the monitoring command; and an estimating unit that estimates the probability of a link being present between nodes by inputting the complemented node information to a link estimating model trained using the information collected in the testing system using the monitoring command and the agent.

Abstract: The present disclosure relates to a method and a system for detecting an object. A method of detecting an object, according to an embodiment of the present disclosure, includes determining whether the object in a region of interest of a (host) vehicle is in a turning state or a straight moving state, determining a location of a reference point for the object based on the determination, extracting first outline points from LiDAR points for the object, which are included in a point cloud received from a LiDAR sensor, based on the reference point, generating at least one virtual point based on a length of a line segment connecting the first outline points, and generating a bounding box of the object corresponding to a heading direction of the object based on second outline points including the first outline points and the at least one virtual point.

Abstract: Described are various embodiments of a system and method for adaptive user experience cycle profiling under anomalous environmental respiratory conditions, such as in hyperbaric or hypobaric environments. In one embodiment, the system comprises an environmental sensor operable to monitor a respiratory environment parameter representative of the anomalous environmental respiratory condition that defines the experience cycle; and a physiological sensor operable to concurrently monitor a physiological parameter representative of the user's cumulative physiological response to the anomalous environmental respiratory condition over time during the experience cycle.

Abstract: Fault diagnosis in industries typically involves identification of key variables/sensors bearing fault signature, classification of detected fault into known fault classes and detecting root causes/sources of the fault. This disclosure relates to a method and system for a deep learning based causal inference in a multivariate time series data of abnormal events and failures in industrial manufacturing processes and equipment. The system generates causal networks for non-linear and non-stationary multivariate time series data. The causal network learns for a dynamic non-stationary and nonlinear complex process or system fault using observed data without any prior process knowledge. The causal networks of faults are identified in real-time using a deep learning-based causal network learning technique.

Abstract: Disclosed is an apparatus including an input interface. The input interface is configured to obtain input sensor data. For example, the input sensor data includes light detection and ranging (LiDAR) data indicative of an environment. The apparatus includes a pre-processor communicatively coupled to the input interface. The pre-processor optionally includes a parser logic. The pre-processor includes a decoder communicatively coupled to the parser logic. The segmentation logic is configured to parse the input sensor data. The decoder is configured to decode the parsed input sensor data. The pre-processor is configured to provide the decoded input sensor data and the parsed input sensor data to a processor for fusion.

Abstract: Systems and methods are provided for utilization of optimal data access interface usage in machine learning pipelines. Examples of the systems and methods disclosed herein include identifying data access interfaces comprising at least a first data access interface for a persistent storage distributed across a plurality of storage nodes and at least a second data access interface for an in-memory object store, and receiving, from a compute node, a data operation request as part of a machine learning pipeline. Additionally, performance metrics are obtained for the plurality of access interfaces, and based on a type of data operation request, the data operation is executed using a data access interface selected from the plurality of data access interface based on the performance metrics and providing an object handle to the compute node.

Abstract: A matching method for semiconductor topography measurement and a processing device using the same are provided. The matching method includes the following steps. An original surface topography curve is obtained. The original surface topography curve is obtained by measuring along a measurement straight line path of a semiconductor device. The original surface topography curve is converted into a surface topography variation curve. A circuit layout is obtained. A plurality of conductor density variation curves are obtained along a plurality of layout straight-line paths. According to a plurality of weighted values of a plurality of topography variation observation intervals of the surface topography variation curve, a weighted correlation between the surface topography variation curve and each of the conductor density variation curves is analyzed.

Abstract: The present application discloses a blade fault diagnosis method, apparatus and system, and a storage medium, the method includes: acquiring a blade rotation audio collected by an audio collection device during operation of a wind turbine generator system; preprocessing the blade rotation audio based on a wind noise filtering algorithm to obtain a blade rotation audio filtered out of wind noise; dividing the blade rotation audio filtered out of wind noise to obtain audio segments corresponding to blades of the wind turbine generator system respectively; diagnosing, based on the audio segments, whether the blades each corresponding to one of the audio segments are faulty. The present application can diagnose whether a corresponding blade is faulty respectively according to the audio segments of different blades, which improves the accuracy of the diagnosis results.

Abstract: Methods and systems for a monitoring system for data collection in an industrial environment including a data collector communicatively coupled to a plurality of input channels connected to data collection points operationally coupled to at least one industrial component in at least one of an industrial boiler system or industrial pipeline system; a data storage structured to store a library of stored noise patterns associated with operation of the at least one industrial component; a data acquisition circuit structured to interpret a plurality of detection values from the collected data; and a data analysis circuit structured to: analyze the collected data, determine a measured noise pattern for the at least one industrial component, and compare the measured noise pattern to the library of stored noise patterns to identify a changed condition of the at least one industrial component.

Abstract: A module for a microscope includes at least one sensor and/or at least one actuator, and a control and evaluation unit. The control and evaluation unit is configured to determine current parameter values of parameters of the sensor and/or of the actuator, analyze the parameter values using a statistical model stored in the control and evaluation unit to determine an operating state value that characterizes an operating state of the module, and identify the operating state as an abnormal operating state upon determining that the operating state value satisfies a predefined condition with respect to a threshold value.