Abstract: The present disclosure is directed to systems and methods for analyzing digital images to determine alphanumeric strings depicted in the digital images. An electronic device may generate a set of filtered images using a received digital image. The electronic device may also perform an optical character recognition (OCR) technique on the set of filtered images, and may filter out any of the set of filtered images according to a set of rules.

Abstract: The present disclosure is directed to systems and methods for analyzing digital images to determine alphanumeric strings depicted in the digital images. An electronic device may generate a set of filtered images using a received digital image. The electronic device may also perform an optical character recognition (OCR) technique on the set of filtered images, and may filter out any of the set of filtered images according to a set of rules. The electronic device may further identify a set of common elements representative of the alphanumeric string depicted in the digital image, and determine a machine-encoded alphanumeric string based on the set of common elements.

Abstract: A method and system for improving analysis of social media and other usage data to determine user sentiments are disclosed. Social media posts are identified as relevant to determining user sentiments regarding a service provider. Posts are analyzed by machine learning algorithms to determine user general sentiments and specific sentiments. User interaction metrics indicating user interaction with service provider web site or application may also be analyzed. Sentiment and interaction determinations may be used with other data to predict likelihood of user attrition for services of the service provider. Sentiment determinations associated with social media posts may further be used to determine priority levels for the posts, including response urgency levels. Determined priority levels may then be used to implement appropriate actions in a timely manner based upon the post urgency.

Abstract: The present disclosure is directed to systems and methods for analyzing digital images to determine alphanumeric strings depicted in the digital images. An electronic device may generate a set of filtered images using a received digital image. The electronic device may also perform an optical character recognition (OCR) technique on the set of filtered images, and may filter out any of the set of filtered images according to a set of rules.

Abstract: The present disclosure is directed to systems and methods for analyzing digital images to determine alphanumeric strings depicted in the digital images. An electronic device may generate a set of filtered images using a received digital image. The electronic device may also perform an optical character recognition (OCR) technique on the set of filtered images, and may filter out any of the set of filtered images according to a set of rules. The electronic device may further identify a set of common elements representative of the alphanumeric string depicted in the digital image, and determine a machine-encoded alphanumeric string based on the set of common elements.

Abstract: A method and system for improving analysis of social media and other usage data to determine user sentiments are disclosed. Social media posts are identified as relevant to determining user sentiments regarding a service provider. Posts are analyzed by machine learning algorithms to determine user general sentiments and specific sentiments. User interaction metrics indicating user interaction with service provider web site or application may also be analyzed. Sentiment and interaction determinations may be used with other data to predict likelihood of user attrition for services of the service provider. Sentiment determinations associated with social media posts may further be used to determine priority levels for the posts, including response urgency levels. Determined priority levels may then be used to implement appropriate actions in a timely manner based upon the post urgency.

Abstract: A method and system for improving analysis of social media and other usage data to determine user sentiments are disclosed. Social media posts are identified as relevant to determining user sentiments regarding a service provider. Posts are analyzed by machine learning algorithms to determine user general sentiments and specific sentiments. User interaction metrics indicating user interaction with service provider web site or application may also be analyzed. Sentiment and interaction determinations may be used with other data to predict likelihood of user attrition for services of the service provider. Sentiment determinations associated with social media posts may further be used to determine priority levels for the posts, including response urgency levels. Determined priority levels may then be used to implement appropriate actions in a timely manner based upon the post urgency.

Abstract: The present disclosure is directed to systems and methods for analyzing digital images to determine alphanumeric strings depicted in the digital images. An electronic device may generate a set of filtered images using a received digital image. The electronic device may also perform an optical character recognition (OCR) technique on the set of filtered images, and may filter out any of the set of filtered images according to a set of rules. The electronic device may further identify a set of common elements representative of the alphanumeric string depicted in the digital image, and determine a machine-encoded alphanumeric string based on the set of common elements.

Abstract: A method and system for improving analysis of social media and other usage data to determine user sentiments are disclosed. Social media posts are identified as relevant to determining user sentiments regarding a service provider. Posts are analyzed by machine learning algorithms to determine user general sentiments and specific sentiments. User interaction metrics indicating user interaction with service provider web site or application may also be analyzed. Sentiment and interaction determinations may be used with other data to predict likelihood of user attrition for services of the service provider. Sentiment determinations associated with social media posts may further be used to determine priority levels for the posts, including response urgency levels. Determined priority levels may then be used to implement appropriate actions in a timely manner based upon the post urgency.

Abstract: The present disclosure is directed to systems and methods for analyzing digital images to determine alphanumeric strings depicted in the digital images. An electronic device may generate a set of filtered images using a received digital image. The electronic device may also perform an optical character recognition (OCR) technique on the set of filtered images, and may filter out any of the set of filtered images according to a set of rules. The electronic device may further identify a set of common elements representative of the alphanumeric string depicted in the digital image, and determine a machine-encoded alphanumeric string based on the set of common elements.

Abstract: Disclosed is a new conductive current collector plate. The plate has alternating concentric ridges and channels on one side and a series of holes drilled perpendicular to and through the diameter of the concentric ridges. Two plates used in combination as the cathode and anode side of a typical proton exchange membrane (PEM) fuel cell distribute fuel or oxidant evenly across the membrane and does not require the use of a manifold.