Abstract: An abnormal-sound detection device has an imaging unit, an operation range identification unit, a sound collection unit, an abnormal-sound detection unit, an abnormal-sound generation position identification unit, and an abnormal-sound source determination unit. The operation range identification unit identifies and stores the operation range of a diagnosis object on the basis of the image captured by an imaging unit. The abnormal-sound detection unit detects abnormalities in sounds included in the sounds collected by the sound collection unit, the sounds arriving from the diagnosis object. When an abnormality in a sound is detected by the abnormal-sound detection unit, the abnormal-sound generation position identification unit identifies the position at which the abnormality of the sound was generated.

Abstract: The embodiment of the present disclosure provides a method and an Internet of Things (IoT) system for safety management of a smart gas underground gas pipeline network. The method is implemented by a smart gas safety management platform and includes: obtaining basic monitoring information of at least one pipeline network partition collected by distributed monitoring components arranged at a plurality of monitoring points; determining at least one key monitoring point and monitoring content of the at least one key monitoring point; determining an inspection plan and a performance allocation plan for the smart gas safety management platform; adjusting the preset monitoring frequency of the distributed monitoring components located at different key monitoring points and at areas surrounding the different key monitoring points; and generating an alarm message to be sent to a user terminal based on an inspection result of the inspection robot.

Abstract: The present disclosure discloses a method for automatically identifying south troughs by improved Laplace and relates to the technical field of meteorology. The method includes the following steps: acquiring grid data of a geopotential height field; calculating a gradient field of the geopotential height field in an x direction; searching for a turning point where a gradient value turned from being negative to being positive, and cleaning the gradient field; calculating a divergence of the x direction to obtain an improved Laplacian numerical value L?; performing 0,1 binarization processing on the L? to obtain a black-and-white image and a plurality of targets of potential troughs, merging the black-and-white image and the plurality of targets of the potential troughs by expansion, recovering original scale through erosion, and selecting an effective target through an angle of direction of a contour and an axial ratio.

Abstract: A touch detecting apparatus includes an electrostatic sensor provided on an object; and a processor configured to detect whether a hand touches the object based on a capacitance measured by the electrostatic sensor. The processor is configured to, in response to the capacitance being greater than or equal to a first touch threshold, detect that the hand touches the object, and, for a second predetermined time from when a change amount of the capacitance during a first predetermined time becomes greater than or equal to a noise threshold, continue a state where a correction value has been added to the first touch threshold.

Abstract: A method for correlating data comprises acquiring a first sequence signal and a second sequence signal, wherein the first sequence signal comprises at least a first data point including a first set of components and the second sequence signal comprises at least a second data point including a second set of components; acquiring a first set of user picks and a second set of user picks, wherein the first and the second sets of user picks each contain a respective first and second correspondence between a component in the first set of components and a component in the second set of components; combining the first and second sets of user picks with the first and second sequence signals to create a first hyper-complex signal and a second hyper-complex signal; and performing signal alignment on the first and second hyper-complex signals.

Abstract: A chemical sensing system is described. The chemical sensing system can include a plurality of sensors arranged on at least one substrate. The sensors may have differing sensitivities to sense different analytes, and may each be configured to output a signal in response to sensing one or more of the different analytes. The chemical sensing system can further include a computer processor programmed to receive the signals output from the plurality of sensors. The computer processor may be further programmed to determine a concentration of analytes in the sample based, at least in part, on the received signals and a model relating the signals or information derived from the signals to an output representation having bases corresponding to analytes.

Abstract: The systems and methods of the invention pertain to analyzing steam generator tube data for the detection of wear. Further, the invention is capable of performing a comparison of current tube signal data to baseline or historic tube signal data, e.g., from previous and/or the first, in-service inspection of the steam generator. The systems and methods are automated and can generate results to show potential tube-to-tube contact wear areas as well as the progression of tube-to-tube gap reduction within a steam generator tube bundle. In certain embodiments, the invention is capable of comparing current and historical eddy current data to determine the difference that may be related to degradation or other interested phenomena, and of processing and trending historical comparison results to establish normal variance and detect abnormal variances.

Abstract: A method and a system of predicting an electric system load based on wavelet noise reduction and empirical mode decomposition-autoregressive integrated moving average (EMD-ARIMA) are provided. The method and the system belong to a field of electric system load prediction. The method includes the following steps. Raw load data of an electric system is obtained first. Next, noise reduction processing is performed on the load data through wavelet analysis. The noise-reduced load data is further processed through an EMD method to obtain different load components. Finally, ARIMA models corresponding to the different load components are built. Further, the ARIMA models are optimized through an Akaike information criterion (AIC) and a Bayesian information criterion (BIC). The load components obtained through predicting the different ARIMA models are reconstructed to obtain a final prediction result, and accuracy of load prediction is therefore effectively improved.

Abstract: An example screening system includes a plurality of detectors about a screening area. Each detector includes a sensor configured to detect information from one or more objects moving along a path from an entrance to an exit of the screening area. The plurality of detectors include a first detector configured to detect information from a first location of the path, and a second detector configured to detect information from a second location of the path. The second detector is configured to adapt its functionality based on a finding of the first detector for a given one of the one or more objects.

Abstract: A high-temperature disaster forecast method based on a directed graph neural network is provided, and the method includes the following steps: S1, performing standardization processing on meteorological elements respectively to scale the meteorological elements into a same value range; S2, taking the meteorological elements as nodes in the graph, and describing relationships among the nodes by an adjacency matrix of graph; then learning node information by a stepwise learning strategy and continuously updating a state of the adjacency matrix; S3, training the directed graph neural network model after determining a loss function, obtaining a model satisfying requirements by adjusting a learning rate, an optimizer and regularization parameters as a forecast model, and saving the forecast model; and S4, inputting historical multivariable time series into the forecast model, changing an output stride according to demands, and thereby obtaining high-temperature disaster forecast for a future period of time.

Abstract: The present invention relates to a method for determining a seeding effect area and a non-seeding effect area in accordance with a wind system according to the present invention can use numerical simulation data, radar precipitation data, and ground precipitation data to systematically specify the steps of determining the seeding effect area and the non-seeding effect area in accordance with the wind system. Moreover, the method according to the present invention can easily divide the seeding effect area and the non-seeding effect area according to the physical properties of clouds and quantitatively verify the effectiveness of artificial precipitation experiments conducted by purpose in the future.

Abstract: This disclosure relates to the fields of applied meteorology, in particular to a visualization analysis method of the tropical cyclone forecast verification index data, which comprises the following steps: acquiring tropical cyclone data; obtaining a track forecast verification index and an intensity forecast verification index of the tropical cyclone with the tropical cyclone data; obtaining a visible view of the tropical cyclone track forecast error and a visible view of the tropical cyclone intensity forecast error according to the track forecast verification index and the intensity forecast verification index, and in combination with the geographic information of the tropical cyclone; obtaining a first error and a second error according to the track forecast verification index, and obtaining a joint distribution map of the first error and the second error by using the first error and the second error; obtaining a composite box-shaped histogram through the intensity forecast verification index.

Abstract: An abnormality diagnostic device for a feed axis mechanism diagnoses an abnormality occurrence and an abnormal portion of the feed axis mechanism. The feed axis mechanism transmits a rotation of a motor to a ball screw coupled by a coupling to rotate the ball screw. The abnormality diagnostic device includes a resonance frequency measuring unit and a diagnosis unit. The resonance frequency measuring unit measures a resonance frequency at a plurality of stroke positions within a stroke range of the feed axis mechanism. The diagnosis unit identifies the abnormal portion based on a relationship between the stroke positions and change amounts relative to a standard value of the measured respective resonance frequencies.

Abstract: Systems and methods for converting live weather data to a weather index for offsetting weather risk. Weather data source systems generate one or more weather data streams that include weather forecast model and observations data. A data distribution system receives a weather index request, identifies at least one instrument and at least one location associated with the request. Weather risk indication data is extracted among the weather data streams associated with the identified location based on predefined parameters associated with the identified instrument. The extracted data is converted into a set of weather index values corresponding to the location, based on a predetermined algorithm associated with the identified instrument. A weather index presentation package is generated that includes the set of weather index values for distribution to at least one user device. The weather index presentation package being distributed is updated concurrent with changes to weather risk indication data.

Abstract: A method and system for monitoring an extraordinary rainstorm based on multi-source data is provided. The method includes: acquiring a current moment of a target region; dividing a target time period into n rain events by means of a time window; inverting precipitable water vapor within each rain event; acquiring an accumulated rainfall per m hours within each rain event; computing, according to precipitable water vapor and the accumulated rainfall per m hours within each rain event, a mutual conversion speed V between the precipitable water vapor and the accumulated rainfall; indicating, if the conversion speed is greater than or equal to 1, that a rainfall is excessive and the extraordinary rainstorm is going to occur after the current moment; and indicating, if the conversion speed is less than 1, the rainfall is insufficient and the extraordinary rainstorm is about to end.

Abstract: Apparatuses and associated methods for load bank and power generator control are described herein. In one aspect, a method for controlling a load bank can include: receiving input via a human-machine interface (HMI) corresponding to setpoints of operation for the load bank; receiving data via a power quality analyzer and corresponding to load bank operating parameters; determining, via the power quality analyzer, whether the load bank is operating according to the setpoints of operation received from the HMI; and generating a set of commands for adjusting the load bank operating parameters based on whether the load bank is operating according to the setpoints of operation.

Abstract: A weather intelligence system retrieves weather forecast data for a number of geographic regions. The weather intelligence system determines, using the weather forecast data for each of the geographic regions, a set of geographic regions predicted to experience a weather anomaly, or unusual weather condition, during a particular time interval. The weather intelligence system determines, through a machine-learning process, whether the weather forecast data indicates conditions that people would generally consider to be unusually hot or cold. The weather intelligence system can then programmatically enable a trigger to transmit a service-related offer associated with the weather anomaly to user devices located within one of the geographic regions where that weather anomaly is determined.

Abstract: A method of determining an estimated flow rate for at least one phase of a multi-phase fluid flowing from a subsea well; a subsea well; and a system for determining an estimated flow rate for at least one phase of a multi-phase fluid flowing from a subsea well are disclosed.

Abstract: Provided is an upgrade evaluation device for calculating cost in relation to the introduction effects of an upgrade menu. The present invention has: a performance data acquisition step for acquiring the performance data of an apparatus; and an effect calculation step for calculating, on the basis of the performance data, introduction effects based on a difference in performance when an improvement function for improving the performance of the apparatus is introduced and when the improvement function is not introduced; the introduction effects being calculated for each of a plurality of points in time in a prescribed period in the effect calculation step. There may also be calculated a cost exchanged between an improvement-function-supply side and the supplied side, the cost being based on the introduction effects calculated in the effect calculation step.

Abstract: The present invention belongs to the field of nowcasting early-warning technology, and discloses a thunderstorm gale early-warning method, system, equipment and terminal. The thunderstorm gale early-warning method comprises: preprocessing single radar data to identify potential thunderstorm gale areas; and in real-time service, calling the thunderstorm gale parameter model in the potential thunderstorm gale areas identified by single radar every time to perform extrapolation for 1 hour, thereby forming a thunderstorm gale early-warning product within the next hour. The thunderstorm gale early-warning method provided by the present invention makes full use of the identification technology of dual polarization radar to identify the potential of thunderstorm gale, acquires falling areas of potential thunderstorm gale within the next hour by the extrapolation technology, and has better advance and accuracy compared with the existing thunderstorm gale early-warning method.