Abstract: A method for accelerating data transfer over a network between a first computer and a second computer includes establishing a plurality of connections for transferring data. The plurality of connections may be established between the first computer and the second computer and may be defined as a virtual circuit. The method may also include de-multiplexing the data into a plurality of data packets and assigning sequence numbers to each of the data packets. The method may further include transmitting the plurality of data packets through the virtual circuit in an order corresponding to the assigned sequence numbers, and receiving the plurality of data packets regardless of the assigned sequence number. The method may still further include sequencing the plurality of data packets into an order corresponding to the assigned sequence number and multiplexing the plurality of data packets.

Abstract: A computer-based platform is provided for integrating data from multiple systems including (but not limited to) point of sale (POS) terminals, video systems, electronic article surveillance (EAS) systems, automatic teller machines (ATMs), gas pumps, alarm systems, radio frequency identification (RFID) detection systems, etc. The subject computer-based platform is configured to gather and correlate data (e.g., transactional data and/or video data), package such data into multiple discrete system “events”, and to provide various features for proactively identifying selected events as “exceptions”. Additional aspects of the computer-based platform may be utilized to provide signaled identification to a user of identified exceptions and other integrated system data. Still further aspects of the platform can be used to group these new events to create larger groupings of multiple transactions, events, data, exceptions, and/or research.

Abstract: A lure depth analyzer includes a digital processor, a lure analyzer data structure, a user interface having a display and user inputs to input and display variables relating to fishing lures. The database relates specific lures to running depth, length of line, and other variables such as line type, speed, and addition weights added to the line. The angler is interactively led through the user interface to provide known information and angler selections. The display returns information necessary for the angler to cast or troll a lure at a particular depth.

Abstract: A method and system for monitoring point of sale exceptions includes the ability to proactively and automatically analyze POS transactional data for certain patterns or occurrences that typically indicate specific behavior at or near a POS terminal in connection with a sales related operation, retrieve time-correlated video segments of a specified length of time from a camera source associated with the POS terminal used to execute aforementioned transaction, and present the video and transaction data together without obstruction on the same user display for contemporaneous review.

Abstract: A computer-based platform is provided for integrating data from multiple systems including (but not limited to) point of sale (POS) terminals, video systems, electronic article surveillance (EAS) systems, automatic teller machines (ATMs), gas pumps, alarm systems, radio frequency identification (RFID) detection systems, etc. The subject computer-based platform is configured to gather and correlate data (e.g., transactional data and/or video data), package such data into multiple discrete system “events”, and to provide various features for proactively identifying selected events as “exceptions”. Additional aspects of the computer-based platform may be utilized to provide signaled identification to a user of identified exceptions and other integrated system data. Still further aspects of the platform can be used to group these new events to create larger groupings of multiple transactions, events, data, exceptions, and/or research.

Abstract: A method and system for monitoring point of sale exceptions includes the ability to proactively and automatically analyze POS transactional data for certain patterns or occurrences that typically indicate specific behavior at or near a POS terminal in connection with a sales related operation, retrieve time-correlated video segments of a specified length of time from a camera source associated with the POS terminal used to execute aforementioned transaction, and present the video and transaction data together without obstruction on the same user display for contemporaneous review.