Abstract: Systems and methods may be provided to execute online tests of a valve in a digital valve positioner. The digital valve positioner may receive a request to execute a test of the valve, which specifies a test start point, and queue the request for execution. The digital valve positioner may subsequently receive a new setpoint for the valve. The digital valve positioner may further reposition the valve according to the new setpoint. The digital valve positioner may further, while the valve is being repositioned, compare the test start point to a current position of the valve, and in response to determining that the current position of the valve has reached the test start point, collect sensor data indicative of the operation of the valve, to generate results of the test.

Abstract: In some embodiments, a system includes an uphole processor and a tool drill string having a downhole device including a downhole processor. The uphole processor may include a memory storing instructions, the uphole processor may be communicatively coupled to the downhole processor, and the uphole processor may be configured to execute the instructions to determine a configuration setting of the system, determine whether the configuration setting indicates a trigger event has occurred, and responsive to determining the trigger event has occurred, transmit a downlink message to the downhole processor to modify an aspect of the downhole device.

Abstract: Methods and systems are provided for utilization of vehicle speed and barometric pressure sensors. In one example, a method may include measuring a change in a barometric pressure resulting from a measured change in a vehicle speed, modeling the change in the barometric pressure based on a change in a ram-air pressure resulting from the change in the vehicle speed, and indicating a degraded barometric pressure measurement when a difference between the measured and the modeled change in the barometric pressure is greater than a threshold pressure difference.

Abstract: Performing in-vehicle network diagnostics is provided. A cloud system receives wiring diagnostic data from a vehicle. The wiring diagnostic data includes information with respect to electrical operation of a plurality of segments of wiring of the vehicle. A machine-learning model of the cloud system is utilized to analyze the wiring diagnostic data. Responsive to the machine-learning model identifying an issue with the electrical operation based on the wiring diagnostic data, a response is sent from the cloud system to the vehicle, the response including one or more corrective actions to be performed by the vehicle to address the issue.

Abstract: A candidate extraction apparatus, a candidate extraction method, and a candidate extraction program extract appropriate candidates for an input into a processing module. The processing module is associated with first metadata indicating a condition of the input data. A plurality of devices are each associated with second metadata indicating an attribute of the input data output from the device. The candidate extraction apparatus includes a first obtaining unit, a second obtaining unit, and an extraction unit. The first obtaining unit obtains the first metadata. The second obtaining unit obtains the second metadata associated with each of the plurality of devices. The extraction unit extracts the candidates greater in number than at least one input port from the plurality of devices based on the first metadata and the second metadata.

Abstract: In some examples, a device can control an HVAC system within a building. The device includes a memory configured to store an actual configuration of the HVAC system and processing circuitry operably coupled to the memory. The processing circuitry is configured to determine which field wires connect a terminal to the HVAC system. The processing circuitry is further configured to determine an actual configuration of the HVAC system based on which field wires connect the terminal to the HVAC system and determine a geographic location of the HVAC controller or of the device. The processing circuitry is configured to determine that the actual configuration includes an irregularity based on the determined geographic location and generate an output in response to determining that the actual configuration includes an irregularity.

Abstract: An HVAC system includes a suction-side sensor, a liquid-side sensor, an outdoor temperature sensor, and a controller. The controller determines that initial criteria are satisfied for initiating validation of the suction-side sensor and the liquid-side sensor. After determining that the initial criteria are satisfied, a suction-side property value, liquid-side property value, and outdoor temperature value are received. The controller determines whether a first validation criteria and a second validation criteria are satisfied. If both the first validation criteria and the second validation criteria are satisfied, the suction-side sensor, the liquid-side sensor, and the outdoor temperature sensor are determined to be functioning properly. Otherwise, the controller determines which one or more of the sensors are malfunctioning.

Abstract: An ink impact point correction apparatus for automatically measuring and correcting an impact point of ink using a pattern on a substrate, on which a coordinate system is displayed, and a substrate treating system including the same are provided. The ink impact point correction apparatus includes a recognition unit for acquiring information on the impact point of ink at a plurality of points located on a substrate; and a correction unit for correcting a position of an ink discharge point on the substrate based on the information on the impact point, wherein a coordinate pattern in the form of a coordinate system is formed at the plurality of points.

Abstract: A method for health assessment of a system including a transport apparatus including registering predetermined operating data embodying at least one dynamic performance variable output by the transport apparatus, determining a base value (CpkBase) characterized by a probability density function of each of the dynamic performance variable output, resolving from the transport apparatus in situ process motion commands of the apparatus controller and defining another predetermined motion set of the transport apparatus, registering predetermined operating data embodying the at least one dynamic performance variable output by the transport apparatus and determining with the processor another value (CpkOther) characterized by the probability density function of each of the dynamic performance variable output by the transport apparatus, and comparing the other value and the base value (CpkBase) for each of the dynamic performance variable output by the transport apparatus respectively corresponding to the predetermin

Abstract: An abnormality diagnosis method for diagnosing an abnormality in equipment includes acquiring multivariate time-series data for a plurality of measurement items from the equipment, diagnosing an abnormality in operational state of the equipment based on the multivariate time-series data, and diagnosing a cause of the abnormality. The diagnosing a cause of the abnormality includes extracting a feature of a first section before the occurrence of the abnormality from the multivariate time-series data of the first section, extracting a feature of a second section after the occurrence of the abnormality from the multivariate time-series data of the second section, obtaining an amount of change in feature from a difference between the feature of the first section and the feature of the second section, and diagnosing a measurement item that is the cause of the abnormality based on the amounts of change in features of the plurality of measurement items.

Abstract: Systems, devices, and methods for testing medical devices comprising: a test device configured for testing a medical device; and a user computing device in communication with the test device, where the user computing device comprises a processor having addressable memory, where the processor is configured to: receive an ID of the medical device to be tested; select a profile associated with the received ID of the medical device; select a preset associated with the selected profile; initiate testing of the medical device by the test device; receive one or more parameter values from based on test information results from the test device; determine a test result based on pass criteria from a comparison of the received one or more parameter values to the one or more simulation parameter values of the preset.

Abstract: An information processing device includes a controller configured to acquire a record of a predetermined action for maintaining a commercial value of a first vehicle by a first user who rents the first vehicle from a first service that is a vehicle rental service, and provide an incentive to the first user when the record of the predetermined action is at a level equal to or higher than a predetermined reference.

Abstract: A driving method and a display device are disclosed. The driving method drives the display panel according to a common voltage look-up table, and the common voltage look-up table is generated by a method including: driving a preset area for display with a preset area gray-scale value; shooting the preset area and obtaining a brightness and a flicker value corresponding to the preset area; adjusting the common voltage value multiple times, and recording the common voltage value when the corresponding flicker value is the minimum as the optimal common voltage value; adjusting the preset area gray-scale value multiple times, and recording a plurality of optimal common voltage values corresponding to the adjusted preset area gray-scale values; and generating the common voltage look-up table according to the multiple preset area gray-scale values and the corresponding optimal common voltage values.

Abstract: A non-transitory memory component including software that, upon execution by a processor, perform operations to classify an activity performed by a user. First, the software receives activity data pertaining to an activity being performed by a user. The activity data may include one or more parameters associated with the activity including steps and time. Thereafter, a step rate is calculated based on the activity data, an activity is determined based on the calculated step rate, and an effort is determined in terms of cardiovascular intensity based, at least in part, on the calculated step rate. An appropriate effort threshold of determined cardiovascular intensity is identified based on oxygen uptake threshold. After, an activity type is classified using the effort and the activity.

Abstract: A predicting device, including a processor configured to: acquire displacement data that expresses a time series of displacements at respective points in time that are input to a vibration proofing member, and velocity data that expresses a time series of velocities at respective points in time that are input to the vibration proofing member; generate first load data of the vibration proofing member by inputting the acquired displacement data and velocity data into a model that is for inferring, from the displacement data and the velocity data, load data; generate second load data of the vibration proofing member by inputting the acquired displacement data and velocity data into a regression trained model that is for inferring, from the displacement data and the velocity data, load data; and infer load data relating to the vibration proofing member by adding together the generated first load data and the generated second load data.

Abstract: An information processing apparatus includes: a reception module configured to receive selection of an output signal corresponding to a root cause from a group including a plurality of output signals, the plurality of output signals being obtained from a plurality of devices to be managed and being obtained in a predetermined period; a replacement module configured to replace a selection result received by the reception module with a combination of the selection results in two output signals, the selection result being corresponding to the group, the two output signals being selected from the plurality of output signals; and a model generation module configured to generate a ranking model of the plurality of output signals based on the selection results after the replacement.

Abstract: A connector detecting device for a connector includes a test vehicle, including a plurality of detecting points, to assemble with the connector; and a function module, formed an electrical connection with the test vehicle, configured to determine a conduction status between the connector and the test vehicle according to a loop of the plurality of detecting points and the connector.

Abstract: A method includes receiving initial sensor data and additional sensor data; and generating combined sensor data. A computing device for includes one or more processors; and one or more memories coupled to the one or more processors, the one or more memories including non-transitory computer executable instructions stored therein that, when executed by the one or more processors, cause the one or more processors to: receive initial sensor data and additional sensor data; and generate combined sensor data. A computer readable storage medium includes non-transitory computer readable instructions stored thereon for generating data regarding a vehicle crash, wherein the instructions when executed on one or more processors cause the one or more processors to: receive initial sensor data and additional sensor data; and generate combined sensor data.

Abstract: Various systems and methods for implementing a software defined industrial system are described herein. For example, an orchestrated system of distributed nodes may run an application, including modules implemented on the distributed nodes. In response to a node failing, a module may be redeployed to a replacement node. In an example, self-descriptive control applications and software modules are provided in the context of orchestratable distributed systems. The self-descriptive control applications may be executed by an orchestrator or like control device and use a module manifest to generate a control system application. For example, an edge control node of the industrial system may include a system on a chip including a microcontroller (MCU) to convert IO data. The system on a chip includes a central processing unit (CPU) in an initial inactive state, which may be changed to an activated state in response an activation signal.

Abstract: An audio and vibration based power distribution equipment condition monitoring system and method is provided. The system includes an intelligent audio analytic (IAA) device and a sensing assembly. The IAA device has computer executable instructions such as an audio data processing algorithms configured to identify and predict impending anomalies associated with one or more power distribution equipment using one or more neural networks.

Abstract: An apparatus and method for determining a recommended cyber-attack risk remediation action are provided. The apparatus includes a processor and a memory communicatively coupled to the at least a processor. The memory contains instructions configuring the at least a processor to receive a cyber profile associated with a digital environment. The processor is further configured to receive a risk profile associated with the cyber profile and determine at least one recommended risk remediation action based on the risk profile. In addition, the processor is configured to generating a user interface data structure configured to display the determined at least one recommended risk remediation action.

Abstract: An apparatus comprising: an obtaining unit configured to obtain target data as a result of discrimination of each portion of input data performed by a discriminator having learned in advance by using existing labeled data; a setting unit configured to set each portion of the target data, which is effective for additional learning of the discriminator, as local data; a determining unit configured to determine not less than one partial region of the target data, which accepts labeling by a user, based on a distribution of the set local data in the target data; and a display control unit configured to cause a display unit to display the determined not less than one partial region.

Abstract: The Coriolis mass flowmeter includes a measuring tube, an exciter mechanism, a sensor arrangement, and an electronic transmitter circuit including measuring and control electronics and drive electronics connected to the measuring and control electronics. The drive electronics are adapted, in a first operating mode, to generate an electrical driver signal that supplies electrical power to the exciter mechanism such that the measuring tube executes forced oscillations having an excitation frequency and, in a second operating mode, to cease generating the electrical driver signal. The transmitter circuit is adapted to switch the drive electronics from the first operating mode to the second operating mode such that the measuring tube executes free, damped oscillations in the second operating mode, and the measuring and control electronics are adapted to, based on a phase difference between oscillation measuring signals from the sensor arrangement, to generate measured values representing the mass flow rate.

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 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: An image processing control device includes: a memory; and a processor coupled to the memory and configured to: determine, on a basis of a processing rate of an image processing program to be deployed, a type of transfer data extracted from video at a time of transferring the video to be processed by the image processing program to be deployed to be a moving image or a still image; and select, on a basis of the type of the transfer data, a deployment destination information processing device to which the image processing program to be deployed is deployed from among a plurality of information processing devices.

Abstract: A method of estimating future aging of a transformer includes generating probabilistic models of factors that affect effective aging of the transformer, generating probabilistic profiles of the factors that affect effective aging of the transformer based on the probabilistic models, generating expected hot spot profiles from the probabilistic profiles, simulating a plurality of aging scenarios of the transformer based on the expected hot spot profiles and ambient temperature profiles, and estimating future aging of the transformer from the plurality of aging scenarios.

Abstract: Circuit board inspection by receiving a near infrared (NIR) image of at least a portion of a circuit board, analyzing the NIR image using a machine learning model, and detecting anomalous circuit board portions according to the analysis.

Abstract: An embodiment of the present invention monitors a process across a plurality of systems associated with a supply chain. A context is determined for an order, where at least one of the features of the context includes information from a networked sensing device. One or more first machine learning models identify a plurality of orders of an order history having features corresponding to the order. A second machine learning model is trained with the identified plurality of orders to predict the monitoring interval for the order. The second machine learning model predicts the monitoring interval for the order based on the context of the order. The monitoring interval for the order is dynamically adjusted based on the predicted monitoring interval, and the order is monitored through an order fulfillment process across the plurality of systems associated with the supply chain in accordance with the adjusted monitoring interval.

Abstract: A diagnostic system for an inverter module includes a motor control module configured to determine operating characteristics of the inverter module. The operating characteristics include of at least one of a voltage, a current, and a switching frequency associated with operation of the inverter module. A diagnostic module is configured to receive the operating characteristics of the inverter module, estimate at least one junction temperature of a component of the inverter module based on the operating characteristics, calculate a health indicator of the inverter module based on the estimated junction temperature, and selectively output an alert based on the calculated health indicator.

Abstract: An automatic robot control system and methods relating thereto are described. These systems include components such as a touch screen panel (“TSP”) robot controller for controlling a TSP robot, a camera robot controller for controlling a camera robot and an audio robot controller for controlling an audio robot. The TSP robot operates inside a TSP testing subsystem, the camera robot operates inside a camera testing subsystem, and the audio robot operates inside an audio testing subsystem. Inside the audio testing subsystem, an audio signals measurement system, using a bi-directional coupling, controls the operation of the audio robot controller. In this control scheme, a test application controller is designed to control the different types of subsystem robots. Methods relating to TSP, camera, and audio robots, and their controllers, taken individually or in combination, for automatic testing of device functionalities are also described.

Abstract: A valve maintenance assistance device includes: a valve ID storing portion configured to store IDs of an ON-OFF valve which may be a candidate for maintenance; an opening acquiring portion configured to acquire opening measurement data from an opening sensor provided on the ON-OFF valve; a pressure acquiring portion configured to acquire pressure measurement data on operating device air supplied to an operating device of the ON-OFF valve; a storing portion configured to store the opening measurement data and the pressure measurement data; and a diagnosis index calculating portion configured to calculate a dead zone time from when an operating device air pressure is changed until an opening degree of the ON-OFF valve is changed as a diagnosis index based on the pressure measurement data and the opening measurement data; and a diagnosis index presenting portion configured to present a numerical value of the diagnosis index calculated by the diagnosis index calculating portion.

Abstract: The present disclosure generally pertains to systems and methods for verifying operation and configuration of a lighting network. In some embodiments, a site controller is configured to receive sensor data from a plurality of sensors and to transmit commands to nodes of a lighting network for controlling light sources based on the sensor data. The site controller is also configured to store a site plan including a listing of the nodes and, for each of the nodes, indicating a number of sensors to be coupled to the respective node. The site controller is further configured to detect the sensors coupled to the nodes based on the sensor data and to compare the detected sensors to the site plan for determining whether the detect sensors is consistent with the site plan. If not, the site controller is configured to provide an alert.

Abstract: A failure diagnosis system includes a sensor that is provided in a diagnosis target device and detects diagnosis target information of the diagnosis target device, an abnormality determination unit that determines whether or not an abnormality occurs in the diagnosis target device based on the diagnosis target information detected by the sensor, a storage unit that stores a site of the diagnosis target device where the abnormality determination is possible and a sensor installation location where a sensor needs to be installed for the abnormality determination of the site, a designation reception unit that receives designation of a site where the abnormality determination is performed, and a presentation unit that executes predetermined presentation processing. The presentation processing by the presentation unit includes processing of presenting the sensor installation location where the sensor needs to be installed to perform the abnormality determination of the designated site.

Abstract: In one aspect, a device agnostic system for providing a fully connected worker risk assessment is disclosed. The system includes an interface and data model for capturing and interpreting one or more variables associated with a worker's body motion and non-body motion related data. The system further includes a processor for aggregating, assessing, and interpreting the one or more input variables to perform a fully connected worker risk assessment based on not only the worker's movement, but also non-movement related data. The processor further provides an output based on the processed one or more input variables to provide a fully connected risk assessment and solutions relating to the same.

Abstract: In some examples, a system includes a plurality of articles of personal protected equipment (PPE) that are each assigned to a particular worker. The system may also include a data hub that detects an input that initiates a broadcast of diagnostic self-check messages; identifies, in response to the input, each article of PPE of the plurality of articles of PPE; broadcasts, based on identifying each article of PPE, the diagnostic self-check messages to the respective articles of PPE, wherein each article of PPE receives its respective self-check message at its communication component; in response to receiving a set of diagnostic acknowledgement messages from one or more of the plurality of articles of PPE that have performed a diagnostic self-check, determines whether the set of diagnostic acknowledge messages satisfy one or more self-check criteria; and performs one or more operations based on whether the self-check criteria are satisfied.

Abstract: A device monitors, for a software-defined networking wide area network (SD-WAN) deployment, a set of virtualized network services of the SD-WAN deployment, and applies a set of diagnostic tests to evaluate the set of virtualized network services. The device detects, based on monitoring the set of virtualized network services and in connection with applying the set of diagnostic tests, an event associated with a virtualized network service. The device analyzes, using an analytics model of SD-WAN operation, the event to identify an issue associated with the virtualized network service, and determines, based on the analytics model of SD-WAN operation, a recommendation relating to remediating the issue. The device generates an abstraction layer user interface to represent the set of virtualized network services and to convey the recommendation relating to remediating the issue, and implements, after providing the abstraction layer user interface, the recommendation to remediate the issue.

Abstract: The present disclosure relates to computer-implemented methods, software, and systems for predicting failure event occurrence for a machine asset. Run-to-failure sequences of time series data that include an occurrence of a failure event for the machine asset are received. One or more candidate cut-off values are determined based on iterative evaluation of a plurality of potential cut-off points. A candidate cut-off value is identified as substantially corresponding to a local peak point for calculated distances between relative frequency distributions of positive and negative sub-sequences. A failure prediction model is iteratively trained to iteratively extract sets of relevant features to determine a prediction horizon for an occurrence of the failure event for the machine asset. A candidate cut-off value associated with a model of highest quality from a set of failure prediction models determined during the iterations is selected to determine the prediction horizon for the machine asset.

Abstract: A method of controlling cooling water treatment may involve measuring operating data of one or more downstream heat exchangers that receive cooling water from the cooling tower. For example, the inlet and outlet temperatures of both the hot and cold streams of a downstream heat exchanger may be measured. Data from the streams passing through the heat exchanger may be used to determine a heat transfer efficiency for the heat exchanger. The heat transfer efficiency can be trended over a period of time and changes in the trend detected to identify cooling waterfouling issues. Multiple potential causes of the perceived fouling issues can be evaluated to determine a predicted cause. A chemical additive selected to reduce, eliminate, or otherwise control the cooling water fouling can be controlled based on the predicted cause of the fouling.

Abstract: A continuous anomaly detection service receives data stream and performs continuous anomaly detection on the incoming data streams. This continuous anomaly detection is performed based on anomaly detection definitions, which define a signal used for anomaly detection and an anomaly detection configuration. These anomaly detection definitions can be modified, such that continuous anomaly detection continues to be performed for the data stream and the signal, based on the new anomaly detection definition.

Abstract: An electric driven hydraulic fracking system is disclosed. A pump configuration that includes the single VFD, the single shaft electric motor, and the single hydraulic pump that is mounted on the single pump trailer. A pump configuration includes a single VFD configuration, the single shaft electric motor, and the single shaft hydraulic pump mounted on the single pump trailer. The single VFD configuration converts the electric power at the power generation voltage level distributed from the power distribution trailer to a VFD voltage level and drives the single shaft electric motor to control the operation of the single shaft electric motor and the single hydraulic pump. The VFD voltage level is a voltage level that is required to drive the single shaft electric motor. The VFD configuration also controls operation of the auxiliary systems based on the electric power at the auxiliary voltage level.

Abstract: A data processing device capable of performing problem diagnosis in a production system with a plurality of robots includes: a first time series obtaining part for obtaining historical event data used for determining some historical alarm indicator in time series and storing the historical event data as first time series data; a historic alarm indicator calculation part for calculating a series of historic alarm indicators using statistic characteristics of the first time series data; a threshold definition part for defining at least one threshold value based on a statistical distribution of the historical alarm indicators; a second time series obtaining part for obtaining operational event data during operation of the robots used for determining some operational alarm indicator in time series and storing the operational event data as second time series data; and an operational alarm indicator calculation part for calculating a series of operational alarm indicators.

Abstract: A method is provided for clustering data elements to extract specific patterns. The method specifies some data elements with a uniform distribution as a mini-batch and performs a single-pass cluster initialization by selecting a respective data element from the mini-batch as a respective initial cluster center to obtain cluster centers for clusters. The method assigns each data element in the mini-batch to a closest cluster by calculating a distance between each of the data elements in the mini-batch and each of the clusters. The method assigns k-minimum new centers by calculating an averaged distance to each data element in a same cluster. The method repeats the specifying step and the assigning steps responsive to a dissatisfaction of loop stop criteria which is based on distances between the centers and the K-minimum new centers. The method outputs a cluster id sequence responsive to a satisfaction of the loop stop criteria.

Abstract: A learning apparatus is provided, which comprises: a learning data acquiring unit for acquiring learning data including measurement data obtained by measuring a facility and a state of the facility; a learning pre-processing unit for performing a pre-processing for reducing a drift of the measurement data in the learning data and outputting pre-processed learning data; and a learning processing unit for performing a processing for learning a model for determining the state of the facility from the pre-processed measurement data, by using the pre-processed learning data.

Abstract: Aspects of the subject disclosure may include, for example, obtaining data from a plurality of sensors at a first point in time, analyzing the data to identify a first level of alertness of a user, predicting a second level of alertness that is required by the user to operate a machine at a second point in time that is subsequent to the first point in time, comparing the first level of alertness to the second level of alertness to generate a first comparison result, identifying a first type of a first notification based on the first comparison result, identifying a third point in time to provide the first notification based on the first comparison result, wherein the third point in time is subsequent to the first point in time and prior to the second point in time, and providing the first notification at the third point in time. Other embodiments are disclosed.

Abstract: A flow rate diagnosis apparatus includes: a main line in which a tank having a volume is provided; a branch line that branches from the main line on an upstream side of the tank; a first open close valve provided in the branch line; a second open close valve provided in the main line; a dead volume defined from the diagnosis object as an upstream end and the first open close valve and the second open close valve as downstream ends; and a second pressure control mechanism that controls a fluid flowing through the main line such that the pressure of the fluid in the dead volume is maintained at a second setting pressure during an inflow mode during which the fluid is caused to flow into the tank by closing of the first open close valve and opening of the second open close valve after a preparation mode.

Abstract: According to various embodiments, an electronic device comprises: at least one communication circuit configured to provide communication with a vehicle device or an external electronic device; at least one processor electrically connected to the at least one communication circuit; and a memory electrically connected to the at least one processor, wherein, the memory, when executed, can store instructions configured such that the at least one processor acquires and stores first information related to a vehicle device when connected to the vehicle device, acquires second information related to the vehicle device when the electronic device satisfies specified conditions, determines the state of the vehicle device on the basis of the first information and the second information, and performs a designated operation on the basis of the determination. In addition, other embodiments are possible.

Abstract: Embodiments generally relate to tracking food safety in a supply chain. In some embodiments, a method includes receiving a case identifier associated with a case of food, retrieving food information concerning the food items, analyzing the food information to determine an in-use portion of a distribution path, and associating the case identifier with user identifiers associated with candidate users determined to have purchased one or more of the food items. The method further includes receiving an incident notification message including an indication of a problem with the food item associated with the case, and identifying the case identifier associated the food item associated with the food item identifier in the incident notification message, and retrieving the one or more user identifiers associated with the case identifier, and sending one or more problem notification messages to one or more client devices of one or more candidate users.

Abstract: Methods and systems are described herein for improving anomaly detection in timeseries datasets. Different machine learning models may be trained to process specific types of timeseries data efficiently and accurately. Thus, selecting a proper machine learning model for identifying anomalies in a specific set of timeseries data may greatly improve accuracy and efficiency of anomaly detection. Another way to improve anomaly detection is to process a multitude of timeseries datasets for a time period (e.g., 90 days) to detect anomalies from those timeseries datasets and then correlate those detected anomalies by generating an anomaly timeseries dataset and identifying anomalies within the anomaly timeseries dataset. Yet another way to improve anomaly detection is to divide a dataset into multiple datasets based on a type of anomaly detection requested.

Abstract: The present invention relates to a method for estimating individual phase resistance of a motor by means of an adjustable speed drive (ASD) while the motor controlled by the ASD is running and/or is at standstill. The motor is an asynchronous motor or a synchronous motor. The invention also relates to an adjustable speed drive for executing a corresponding method.