Abstract: A system and method for monitoring pH of an intraoral device involves receiving the oral pH data from at least one pH sensor embedded within the intraoral device. The oral pH data is then correlated with one or more user related data to classify the oral pH data into one or more pre-defined categories indicative of a health condition. Further, the machine learning module generates feedback and/or recommendations for the user based on the classification of the oral pH data into one or more pre-defined categories. The oral pH data and/or feedback and/or recommendations are then communicated to the user and/or external device.

Abstract: An intraoral monitoring device includes a flexible substrate, a plurality of sensors, a rechargeable battery, a device module and a communication module. The plurality of sensors senses a plurality of health parameters from an associated user, in real time, to generate a plurality of sensed signals. The device module includes a memory, a controller and a segregation module. The memory stores various health parameters and their respective ranges, various health reports of the user, and basic details of all users. A controller is configured to generate sensed data and the segregation module is configured to segregate the data corresponding to the plurality of health parameters associated with the users. A communication module is configured to enable data communication to and from the intraoral device.

Abstract: An intraoral monitoring device includes a plurality of sensors integrated on a flexible substrate. The plurality of sensors includes first and second photoplethysmography (PPG) sensors. The first PPG sensor is coupled along an anterior portion of the flexible substrate and adapted to be located intraorally along a first anatomical location defined along a mid-line of a maxilla, facing the labial mucosa, directly at a septal branch of a superior labial artery in a front lip to consistently provide a plurality of first PPG signal, relating to a plurality of cardiorespiratory parameters. Further, the second PPG sensor is coupled to a rear portion of the flexible substrate, adapted to be located intraorally along a second anatomical location defined along the interior part of an oral cavity facing outward toward the labial mucosa to consistently provide a plurality of second PPG signals, relating to a plurality of muscular parameters.

Abstract: A system, method, and computer program product are provided for providing proactive customer care for issues associated with billing or ordering processes. In use, a likelihood that a customer is going to call a call center to address at least one issue associated with at least one of an ordering process or a billing process is predicted. Additionally, it is determined whether the customer is likely to call the call center based on the predicted likelihood that the customer is going to call the call center. Further, the customer is proactively notified before the customer contacts the call center, if it is determined that the customer is likely to call the call center.

Abstract: An event processing system, method, and computer program product are provided. A plurality of records are stored, including a plurality of events of different event types for a plurality of customers. In use, an indication is received in connection with one or more aspects associated with one or more of the events for one or more of the customers. Based on such indication, one or more subsets of the events of one or more of the records are identified. In some optional embodiments, such one or more event subsets are then processed to reduce noise therein, resulting in fewer events in the one or more event subsets. To this end, a result of the processing may be displayed in a variety of ways for a variety of purposes.

Abstract: A system, method, and computer program product are provided for identifying significant records (e.g. journeys, etc.). In use, a plurality of records including a plurality of events are stored. Further, an indication is received regarding at least one subset of the records. Thereafter, at least a portion of the events of the at least one subset of the records are processed to generate mean information such that the records of the at least one subset may be compared, utilizing the mean information. This may be accomplished while avoiding, at least in part, a covariance calculation, or in such a manner that the comparison is independent of such covariance calculation. A result of the comparison may be displayed.

Abstract: A system, method, and computer program product are provided for identifying significant attributes of records (e.g. journeys, etc.). A plurality of records are stored, including a plurality of events with a plurality of attributes. Further, the attributes of the events are processed, utilizing machine learning. To this end, at least one of the attributes are identified as being significant, based on the processing. Such identified at least one attribute may then be displayed, etc.

Abstract: An event-based system, method, and computer program product are provided for intervening in connection with a network service. A plurality of measurements are identified that correspond to at least one aspect of a network service. Such measurements are processed and it is determined whether a criterion has been met, based on the processing. One or more events are identified based on the determination whether the criterion has been met. Further, the one or more events are aggregated, and at least one record is produced, based on the aggregation. To this end, an intervention is carried out in connection with the network service, based on the at least one record.

Abstract: A system, method, and computer program product are provided for identification of common root causes with sequential patterns. In use, a plurality of customer event sequences are identified. Additionally, the plurality of customer event sequences are grouped into a hierarchical framework of patterns. Further, a root-cause analysis (RCA) is performed for the customer event sequences utilizing the hierarchical framework of patterns.

Abstract: A system, method, and computer program product are provided for detecting and measuring changes in network behavior of communication networks utilizing real-time clustering algorithms. In use, network traffic associated with at least one communication network is received. Additionally, the network traffic is characterized and classified based on similarities in the network traffic utilizing one or more real-time clustering algorithms. Further, changes in network behavior of the at least one communication network are detected and measured utilizing information associated with the classified network traffic.

Abstract: A system, method, and computer program product are provided for identification of common root causes with sequential patterns. In use, a plurality of customer event sequences are identified. Additionally, the plurality of customer event sequences are grouped into a hierarchical framework of patterns. Further, a root-cause analysis (RCA) is performed for the customer event sequences utilizing the hierarchical framework of patterns.

Abstract: Articles such as compact discs are traded among a plurality of members who are registered in a common community. Each member has an account including a trading credit balance and a mailing address. A user interface is provided that allows a member to enter articles that the member owns and is willing to trade and articles that the member wants to own. The user interface also receives article trading instruction messages. An administration computer hosts the plurality of members and facilitates article trades among the members. The administration computer identifies matches between owned and wanted articles. For each identified match, an article trading instruction message is sent to the article owner requesting that the article owner mail the owned article to the mailing address of the member who wants to own the article.