Abstract: The present disclosure provides a low-temperature-resistant and corrosion-resistant cargo oil tank steel suitable for high-heat-input welding and a manufacturing method therefor. The low-temperature-resistant and corrosion-resistant cargo oil tank steel suitable for high-heat-input welding includes, by weight in percent, 0.04%-0.13% C, 0.10%-0.40% Si, 0.60%-1.30% Mn, 0.005%-0.012% P, S?0.006%, 0.01%-0.05% Al, 0.03%-0.15% Sn, 0.005%-0.020% Nb, 0.005%-0.025% Ti, 0.15%-0.40% Ni, 0.15%-0.50% Cu, 0.10%-0.25% Cr, 0.007%-0.024% Ca and the balance Fe and inevitable impurities. The corrosion-resistant steel provided by the present disclosure is mainly designed for the upper deck and inner bottom plate of a storage and transportation tank of a polar route oil tanker, and the steel has excellent low-temperature toughness and can be welded with large heat input.

Abstract: The invention discloses clock management of chips, in particular to the clock domain system of interconnected dies and its management methods. The clock domain systems of the interconnected dies, comprising: global clock domains used to manage interior networks on die of the interconnected dies, standard protocol interface clock domains used to manage standard protocol conversion modules and interface source synchronous clock domains used to manage expansion synchronization controllers across dies. The clock domain systems of the interconnected dies provided by the invention modularize complicated clock networks by isolating each module from the perspective of clocks and simultaneously initiate clock synchronization among all clock domains, which is easy for interconnected network setups.

Abstract: Rake wheels for raking apparatus for gathering crop material into a windrow are disclosed. In some embodiments, the rake wheel includes disks for securing and limiting circumferential and axial movement of the tines of the rake wheel.

Abstract: Receiving point of interest zones and alerts on user devices comprises communicating, by a user computing device to a remote computing device, a request for point of interest data corresponding to points of interest within a proximity of the user device; presenting the received point of interest data; identifying a particular point of interest; and outputting an alert regarding the particular point of interest. Receiving point of interest zones on user devices comprises communicating a request for point of interest data; receiving the point of interest data from the remote network device wherein a size of the point of interest zone is determined based on a density of points of interest in the proximity of the user, and wherein the shape of the point of interest zone is expanded in a direction of travel and contracted in the opposite direction; and presenting the received point of interest data.

Abstract: Rake wheels for a raking apparatus for gathering crop material into a windrow. The rake wheel may include a center hub and a plurality of tines that extend outward from the center hub. In some embodiments, the rake wheel includes support members such as disks for securing and limiting movement of the tines of the rake wheel.

Abstract: Receiving point of interest zones and alerts on user devices comprises communicating, by a user computing device to a remote computing device, a request for point of interest data corresponding to points of interest within a proximity of the user device; presenting the received point of interest data; identifying a particular point of interest; and outputting an alert regarding the particular point of interest. Receiving point of interest zones on user devices comprises communicating a request for point of interest data; receiving the point of interest data from the remote network device wherein a size of the point of interest zone is determined based on a density of points of interest in the proximity of the user, and wherein the shape of the point of interest zone is expanded in a direction of travel and contracted in the opposite direction; and presenting the received point of interest data.

Abstract: Aspects of the present disclosure relate to incident routing in a cloud environment. In an example, cloud provider teams utilize a scout framework to build a team-specific scout based on that team's expertise. In examples, an incident is detected and a description is sent to each team-specific scout. Each team-specific scout uses the incident description and the scout specifications provided by the team to identify, access, and process monitoring data from cloud components relevant to the incident. Each team-specific scout utilizes one or more machine learning models to evaluate the monitoring data and generate an incident-classification prediction about whether the team is responsible for resolving the incident. In examples, a scout master receives predictions from each of the team-specific scouts and compares the predictions to determine to which team an incident should be routed.

Abstract: Comparing extracted card data from a continuous scan comprises receiving, by one or more computing devices, a digital scan of a card; obtaining a plurality of images of the card from the digital scan of the physical card; performing an optical character recognition algorithm on each of the plurality of images; comparing results of the application of the optical character recognition algorithm for each of the plurality of images; determining if a configured threshold of the results for each of the plurality of images match each other; and verifying the results when the results for each of the plurality of images match each other. Threshold confidence level for the extracted card data can be employed to determine the accuracy of the extraction. Data is further extracted from blended images and three-dimensional models of the card. Embossed text and holograms in the images may be used to prevent fraud.

Abstract: Identifying the geolocation of POS terminals using non-payment events to predict when the geolocation of a computing device at a time when the device detects events corresponds to the geolocation of the terminal. The device monitors for pre-selected events and transmit data to the account system. The account system determines a frequency of the events and it reaches a pre-defined threshold, the account system identifies the location of the terminal by identifying the common geolocation of the events. The identified geolocation is saved so that when a user then enters the location and transmits event data to the account system, the system can compare the geolocation of the event data to the saved geolocation to determine whether the computing device is located at the terminal. If the computing device is located at the terminal, the account system transmits offers or other content for display and use at the identified terminal.

Abstract: Receiving point of interest zones and alerts on user devices comprises communicating, by a user computing device to a remote computing device, a request for point of interest data corresponding to points of interest within a proximity of the user device; presenting the received point of interest data; identifying a particular point of interest; and outputting an alert regarding the particular point of interest. Receiving point of interest zones on user devices comprises communicating a request for point of interest data; receiving the point of interest data from the remote network device wherein a size of the point of interest zone is determined based on a density of points of interest in the proximity of the user, and wherein the shape of the point of interest zone is expanded in a direction of travel and contracted in the opposite direction; and presenting the received point of interest data.

Abstract: Rake wheels for raking apparatus for gathering crop material into a windrow are disclosed. In some embodiments, the rake wheel includes disks for securing and limiting circumferential and axial movement of the tines of the rake wheel.

Abstract: Extracting financial card information with relaxed alignment comprises a method to receive an image of a card, determine one or more edge finder zones in locations of the image, and identify lines in the one or more edge finder zones. The method further identifies one or more quadrilaterals formed by intersections of extrapolations of the identified lines, determines an aspect ratio of the one or more quadrilateral, and compares the determined aspect ratios of the quadrilateral to an expected aspect ratio. The method then identifies a quadrilateral that matches the expected aspect ratio and performs an optical character recognition algorithm on the rectified model. A similar method is performed on multiple cards in an image. The results of the analysis of each of the cards are compared to improve accuracy of the data.

Abstract: Comparing extracted card data from a continuous scan comprises receiving, by one or more computing devices, a digital scan of a card; obtaining a plurality of images of the card from the digital scan of the physical card; performing an optical character recognition algorithm on each of the plurality of images; comparing results of the application of the optical character recognition algorithm for each of the plurality of images; determining if a configured threshold of the results for each of the plurality of images match each other; and verifying the results when the results for each of the plurality of images match each other. Threshold confidence level for the extracted card data can be employed to determine the accuracy of the extraction. Data is further extracted from blended images and three-dimensional models of the card. Embossed text and holograms in the images may be used to prevent fraud.

Abstract: Rake wheels for a raking apparatus for gathering crop material into a windrow. The rake wheel may include a center hub and a plurality of tines that extend outward from the center hub. In some embodiments, the rake wheel includes support members such as disks for securing and limiting circumferential and/or axial movement of the tines of the rake wheel.

Abstract: The present invention provides a method, apparatus, and system for voice verification, wherein the method comprises: at a network side, obtaining a user voice communication number according to a voice verification request from a user side, and determining voice verification information corresponding to the voice verification request; at the network side, initiating a call to a corresponding user according to the user voice communication number, and in the case of call through, playing the determined voice verification information to the user; at the user side, performing an automatic listening and recording operation when monitoring that the user is called, and upon termination of the call, sending recording information obtained from the recording to the network side; at the network side, determining a verification result according to the voice verification information and the recording information.

Abstract: Extracting card data comprises receiving, by one or more computing devices, a digital image of a card; perform an image recognition process on the digital representation of the card; identifying an image in the digital representation of the card; comparing the identified image to an image database comprising a plurality of images and determining that the identified image matches a stored image in the image database; determining a card type associated with the stored image and associating the card type with the card based on the determination that the identified image matches the stored image; and performing a particular optical character recognition algorithm on the digital representation of the card, the particular optical character recognition algorithm being based on the determined card type. Another example superimposes the extracted data directly above, below, or beside the corresponding section on the displayed image.

Abstract: Extracting financial card information with relaxed alignment comprises a method to receive an image of a card, determine one or more edge finder zones in locations of the image, and identify lines in the one or more edge finder zones. The method further identifies one or more quadrilaterals formed by intersections of extrapolations of the identified lines, determines an aspect ratio of the one or more quadrilateral, and compares the determined aspect ratios of the quadrilateral to an expected aspect ratio. The method then identifies a quadrilateral that matches the expected aspect ratio and performs an optical character recognition algorithm on the rectified model. A similar method is performed on multiple cards in an image. The results of the analysis of each of the cards are compared to improve accuracy of the data.

Abstract: Extracting card information comprises a server at an optical character recognition (“OCR”) system that interprets data from a card. The OCR system performs an optical character recognition algorithm an image of a card and performs a data recognition algorithm on a machine-readable code on the image of the card. The OCR system compares a series of extracted alphanumeric characters obtained via the optical character recognition process to data extracted from the machine-readable code via the data recognition process and matches the alphanumeric series of characters to a particular series of characters extracted from the machine-readable code. The OCR system determines if the alphanumeric series and the matching series of characters extracted from the machine-readable code comprise any discrepancies and corrects the alphanumeric series of characters based on the particular series of characters extracted from the machine-readable code upon a determination that a discrepancy exists.

Abstract: Extracting financial card information with relaxed alignment comprises a method to receive an image of a card, determine one or more edge finder zones in locations of the image, and identify lines in the one or more edge finder zones. The method further identifies one or more quadrilaterals formed by intersections of extrapolations of the identified lines, determines an aspect ratio of the one or more quadrilateral, and compares the determined aspect ratios of the quadrilateral to an expected aspect ratio. The method then identifies a quadrilateral that matches the expected aspect ratio and performs an optical character recognition algorithm on the rectified model. A similar method is performed on multiple cards in an image. The results of the analysis of each of the cards are compared to improve accuracy of the data.