Abstract: In one aspect, fuel inventory data characterizing a level of fuel stored at a fuel storage facility can be received from a sensor in operable communication with the fuel storage facility. Flow meter data characterizing an amount of fuel dispensed from the fuel storage facility by a fuel dispenser nozzle can be received from a flow meter in fluid communication with the fuel dispenser nozzle and the fuel storage facility. Fuel transaction data characterizing the dispensing of fuel by the fuel dispenser nozzle and the dispensing of the fuel by one or more additional fuel dispenser nozzles in fluid communication with the fuel storage facility can be received. An estimate of meter drift characterizing a change in calibration of the flow meter can be determined based on the fuel inventory data, the flow meter data, and the fuel transaction data. The estimate of meter drift can be provided.

Abstract: Data characterizing a fuel storage facility can be received from one or more of a plurality of sensors disposed in the fuel storage facility. A fuel leak prediction for the fuel storage facility can be determined by a server, based on the received data, and further based on at least one predictive model that predicts whether a fuel leak exists in the fuel storage facility. The fuel leak prediction can be provided by the server. Related apparatus, systems, methods, techniques, and articles are also described.

Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for an end-to-end wireless sensor hub include: configuring a sensor hubs in an order using a sequence established by 5 a time of addition to a network. The sensor hubs is grouped into one or more groups. Sensor data captured by the one or more groups is obtained according to a current group number, wherein the sensor data is obtained from each group of the one or more groups according to a predetermined schedule.

Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for glare mitigation techniques include: obtaining images containing a representation of a mark, the images comprising multiple poses of the mark and generating a single image from the images that contain a representation of the mark with reduced glare when compared to the images comprising multiple poses of the mark. The single image is provided for processing of the representation of the mark to identify information associated with the mark.

Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for generating synthetic images, include: obtaining a captured image of a symbol that encodes data; producing a synthetic image from the captured image using a trained machine learning model, wherein the trained machine learning model has been trained using first images and second images of examples of symbols, wherein the second images have a second image quality that is different than a first image quality of first images, and wherein parameters of the machine learning model have been adjusted responsive to image features to tradeoff content loss versus style loss using measurements of information content correlation between third images produced during training and each of the first images and the second images, the measurements being from a comparison metric; and providing the synthetic image for use by a program configured to identify information in images of symbols.

Abstract: Methods, devices, apparatus, systems and computer-readable storage media for assessing damages on vehicles are provided. In one aspect, a method includes: accessing an image of a vehicle showing shapes each indicating at least one damage area on the vehicle; providing the image as input to a first model to identify the shapes in the image and obtaining shape data describing a position of each shape identified in the image; providing the image as input to a second model to identify one or more panels of the vehicle and obtaining panel data describing a position of each panel identified in the image; automatically correlating the one or more shapes and the one or more panels based on the shape data and the panel data to determine a number of shapes present on each panel; and generating a damage assessment report describing the number of shapes present on each panel.

Abstract: Among other things, the techniques described herein include a method for receiving a plurality of images of one or more containers while the one or more containers are being emptied, the plurality of images comprising a training set of images and a validation set of images; labeling each image of the plurality of images as including either an overfilled container or a not-overfilled container; processing each image of the plurality of images to reduce bias of a machine learning model; training, and based on the labeling, the machine learning model using the plurality of images; and optimizing the machine learning model by performing learning against the validation set, the optimized machine learning model being used to generate a prediction for a new image of a container, the prediction indicating whether the container in the new image was overfilled prior to the new container being emptied.

Abstract: Systems and methods for detecting hail damage on a vehicle are described including, receiving an image of at least a section of a vehicle. Detecting a plurality of hail damage including, detecting a plurality of damaged areas distributed over the entire section of the vehicle, and differentiating the plurality of damaged areas from one or more areas of noise, processing the received image to classify one or more sections of the vehicle as one or more panels of the vehicle bodywork, and using the detected areas of damage, the classification of the seriousness of the damage and the classification of one or more panels to compute a panel damage density estimate.

Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for photocopy or counterfeit detection include: obtaining images with a representation of a same mark and predicting an authenticity of the representation of the same mark in each image to obtain an authenticity prediction corresponding to each image of the set of images. The authenticity predictions are consolidated to determine an ensemble prediction of authenticity associated with the same mark.

Abstract: In one aspect, data characterizing a fuel storage facility can be received from a sensor in operable communication with the fuel storage facility. An estimate of meter drift of a flow meter of a fuel dispenser in fluid communication with the fuel storage facility can be determined based on the received data. The estimate of meter drift can be determined based on at least one predictive model that predicts whether a calibration parameter characterizing a calibration of the flow meter has deviated from a predetermined flow meter calibration parameter. The estimate of meter drift can be provided.

Abstract: Among other things, the techniques described herein include a method for receiving a plurality of images of one or more containers while the one or more containers are being emptied, the plurality of images comprising a training set of images and a validation set of images; labeling each image of the plurality of images as including either an overfilled container or a not-overfilled container; processing each image of the plurality of images to reduce bias of a machine learning model; training, and based on the labeling, the machine learning model using the plurality of images; and optimizing the machine learning model by performing learning against the validation set, the optimized machine learning model being used to generate a prediction for a new image of a container, the prediction indicating whether the container in the new image was overfilled prior to the new container being emptied.

Abstract: Systems and methods for detecting hail damage on a vehicle are described including, receiving an image of at least a section of a vehicle. Detecting a plurality of hail damage including, detecting a plurality of damaged areas distributed over the entire section of the vehicle, and differentiating the plurality of damaged areas from one or more areas of noise, processing the received image to classify one or more sections of the vehicle as one or more panels of the vehicle bodywork, and using the detected areas of damage, the classification of the seriousness of the damage and the classification of one or more panels to compute a panel damage density estimate.

Abstract: In one aspect, data characterizing a fuel storage facility can be received from a sensor in operable communication with the fuel storage facility. An estimate of meter drift of a flow meter of a fuel dispenser in fluid communication with the fuel storage facility can be determined based on the received data. The estimate of meter drift can be determined based on at least one predictive model that predicts whether a calibration parameter characterizing a calibration of the flow meter has deviated from a predetermined flow meter calibration parameter. The estimate of meter drift can be provided.

Abstract: Among other things, techniques are described for predictive maintenance using vibration analysis of vane pumps. Sensor data is obtained and pre-processed the sensor data according to at least one feature extraction system. The features are extracted from the pre-processed sensor data and classified into at least one operating condition. A representation of the at least one operating condition is rendered at a device.

Abstract: In one aspect, fuel inventory data characterizing a level of fuel stored at a fuel storage facility can be received from a sensor in operable communication with the fuel storage facility. Flow meter data characterizing an amount of fuel dispensed from the fuel storage facility by a fuel dispenser nozzle can be received from a flow meter in fluid communication with the fuel dispenser nozzle and the fuel storage facility. Fuel transaction data characterizing the dispensing of fuel by the fuel dispenser nozzle and the dispensing of the fuel by one or more additional fuel dispenser nozzles in fluid communication with the fuel storage facility can be received. An estimate of meter drift characterizing a change in calibration of the flow meter can be determined based on the fuel inventory data, the flow meter data, and the fuel transaction data. The estimate of meter drift can be provided.

Abstract: Systems and methods for detecting hail damage on a vehicle are described including, receiving an image of at least a section of a vehicle. Detecting a plurality of hail damage including, detecting a plurality of damaged areas distributed over the entire section of the vehicle, and differentiating the plurality of damaged areas from one or more areas of noise, processing the received image to classify one or more sections of the vehicle as one or more panels of the vehicle bodywork, and using the detected areas of damage, the classification of the seriousness of the damage and the classification of one or more panels to compute a panel damage density estimate.

Abstract: In one aspect, data characterizing a fuel storage facility can be received from a sensor in operable communication with the fuel storage facility. An estimate of meter drift of a flow meter of a fuel dispenser in fluid communication with the fuel storage facility can be determined based on the received data. The estimate of meter drift can be determined based on at least one predictive model that predicts whether a calibration parameter characterizing a calibration of the flow meter has deviated from a predetermined flow meter calibration parameter. The estimate of meter drift can be provided.

Abstract: Data characterizing a fuel storage facility can be received from one or more of a plurality of sensors disposed in the fuel storage facility. A fuel leak prediction for the fuel storage facility can be determined by a server, based on the received data, and further based on at least one predictive model that predicts whether a fuel leak exists in the fuel storage facility. The fuel leak prediction can be provided by the server. Related apparatus, systems, methods, techniques, and articles are also described.

Abstract: Among other things, the techniques described herein include a method for receiving a plurality of images of one or more containers while the one or more containers are being emptied, the plurality of images comprising a training set of images and a validation set of images; labeling each image of the plurality of images as including either an overfilled container or a not-overfilled container; processing each image of the plurality of images to reduce bias of a machine learning model; training, and based on the labeling, the machine learning model using the plurality of images; and optimizing the machine learning model by performing learning against the validation set, the optimized machine learning model being used to generate a prediction for a new image of a container, the prediction indicating whether the container in the new image was overfilled prior to the new container being emptied.

Abstract: Various embodiments include gas turbine seals and methods of forming such seals for advanced gas path (AGP) heat transfer designed gas turbine engines. In some cases, a turbine includes: a first arcuate component adjacent to a second arcuate component, each arcuate component formed of a ceramic matrix composite and including a seal slot located in an end face, each seal slot having a plurality of axial surfaces and radially facing surfaces extending from opposite ends of the axial surfaces and an overhanging seal assembly disposed in the seal slot. The overhanging seal assembly including an intersegment seal including a plurality of seal segments defining two vertical seal segments and a plurality of horizontal seal segments and a first overhanging positioner shim seal and a second overhanging positioner shim seal, each including an extended portion. The overhanging seal assembly disposed in the seal slot so as to provide position constrainment of the two vertical seal segments.