Abstract: Three artificial intelligence (AI) linguistic processing architectures are proposed for early detection of Alzheimer's Disease based entirely on a patient's language abilities. Three C-Attention network architectures are presented: one that uses only PoS features, one that uses only the latent features (e.g., language embeddings) and a unified architecture, which uses both features. (FIG. 3).

Abstract: Various embodiments of systems, architecture, and/or methods are described for negotiating accesses to wireless spectrum of heterogeneous networks (e.g., Wifi, cellular 3G, cellular LTE, cellular 5G etc.) among multiple users, service providers, and services. As such, a software defined architecture is disclosed. In some embodiments, the disclosed software defined architecture can include establishing a (dedicated) logical control path from a central controller remotely located from an end device of a user. Such a logical control path is agnostic to the type and/or number of underlying wireless networks and is supplemental to conventionally known data paths, i.e., paths for exchanging data.

Abstract: Various embodiments of systems, architecture, and/or methods are described for negotiating accesses to wireless spectrum of heterogeneous networks (e.g., Wifi, cellular 3G, cellular LTE, cellular 5G etc.) among multiple users, service providers, and services. As such, a software defined architecture is disclosed. In some embodiments, the disclosed software defined architecture can include establishing a (dedicated) logical control path from a central controller remotely located from an end device of a user. Such a logical control path is agnostic to the type and/or number of underlying wireless networks and is supplemental to conventionally known data paths, i.e., paths for exchanging data.

Abstract: An apparatus and method for determining whether text is deceptive has a computer programmed with software that automatically analyzes text in digital form by at least one of statistical analysis of psycho-linguistic cues, IP geo-location, gender analysis, authorship analysis, and analysis to detect coded/camouflaged messages. The computer has truth data against which the text message can be compared and a graphical user interface. The computer may be connectable to the Internet and may obtain the text automatically. Speech-to-text software may be used to convert verbal messages to text for analysis. The system may be made available on a webpage, web service, on a computer or by a wireless device. The text may be emails, website content, tweets. In one embodiment, the system detects coded messages.

Abstract: An apparatus and method for determining whether a text is deceptive may comprise analyzing a body of textual content known to be one of text containing true content and text containing deceptive content; identifying psycho-linguistic cues that are indicative of a text being deceptive; statistically analyzing, via a computing device, a given text based upon the psycho-linguistic cues to determine if the text is deceptive. The apparatus and method may further comprise weighting the psycho-linguistic cues and statistically analyzing based on the weighted psycho-linguistic cues. The statistically analyzing step may be performed using one of a cue matching analysis, a weighted cue matching analysis, a Markov chain analysis, and a sequential probability ratio testing binary hypothesis analysis. The psycho-linguistic cues may be separated into categories, including increasing trend cues and decreasing trend cues and analyzed according to presence in a category from within the categories.

Abstract: A steganographic message/advertisement embedding method is presented that can be used for contextual and targeted advertising supporting unobtrusive and on-demand message/advertisement delivery. The present invention presents over two client devices, the method includes receiving, on a first client device, a primary multimedia presentation with a plurality of steganographic codes embedded therein; whereby the steganographic code is not perceivable during a rendering of the multimedia presentation and the steganographic code is associated with at least one secondary multimedia presentation. Next; the primary multimedia presentation is rendered on the first client device. The first client device receives a user selection to select at least one of the steganographic codes.

Abstract: An apparatus and method for determining whether text is deceptive has a computer programmed with software that automatically analyzes text in digital form by at least one of statistical analysis of psycho-linguistic cues, IP geo-location, gender analysis, authorship analysis, and analysis to detect coded/camouflaged messages. The computer has truth data against which the text message can be compared and a graphical user interface. The computer may be connectable to the Internet and may obtain the text automatically. Speech-to-text software may be used to convert verbal messages to text for analysis. The system may be made available on a webpage, web service, on a computer or by a wireless device. The text may be emails, website content, tweets. In one embodiment, the system detects coded messages (FIG. 19).

Abstract: An apparatus and method for determining whether a text is deceptive may comprise analyzing a body of textual content known to be one of text containing true content and text containing deceptive content; identifying psycho-linguistic cues that are indicative of a text being deceptive; statistically analyzing, via a computing device, a given text based upon the psycho-linguistic cues to determine if the text is deceptive. The apparatus and method may further comprise weighting the psycho-linguistic cues and statistically analyzing based on the weighted psycho-linguistic cues. The statistically analyzing step may be performed using one of a cue matching analysis, a weighted cue matching analysis, a Markov chain analysis, and a sequential probability ratio testing binary hypothesis analysis. The psycho-linguistic cues may be separated into categories, including increasing trend cues and decreasing trend cues and analyzed according to presence in a category from within the categories.

Abstract: A method and apparatus for automatically identifying harmful electronic messages, such as those presented in emails, on Craigslist or on Twitter, Facebook and other social media websites, features methodology for discriminating unwanted garbage communications (spam) and unwanted deceptive messages (scam) from wanted, truthful communications based upon patterns discernable from samples of each type of electronic communication. Methods are proposed that enable discrimination of wanted from unwanted communications in short electronic messages, such as on Twitter and for multilingual application.

Abstract: A steganographic message/advertisement embedding method is presented that can be used for contextual and targeted advertising supporting unobtrusive and on-demand message/advertisement delivery. The present invention presents over two client devices, the method includes receiving, on a first client device, a primary multimedia presentation with a plurality of steganographic codes embedded therein; whereby the steganographic code is not perceivable during a rendering of the multimedia presentation and the steganographic code is associated with at least one secondary multimedia presentation. Next; the primary multimedia presentation is rendered on the first client device. The first client device receives a user selection to select at least one of the steganographic codes.

Abstract: A product and process for extracting hidden data from a stego-image that has been subjected to scaling attacks are disclosed. The hidden data extraction method of the present invention retains the one-to-one mapping of the stego-image blocks to the corresponding blocks in the scaled image. When the stego-image is scaled down, the block size for extracting the hidden data is reduced proportionally. When the stego-image is scaled up, the block size for extracting the hidden data is increased proportionally. The total overall number of blocks of pixels to be examined is kept constant between the scaled image and the stego-image. The hidden data extraction method can be combined with any existing block-DCT based data hiding method to provide an overall method for dealing with scaling attacks. Both the extraction method and the combined method can be implemented in software and stored within a machine-readable medium.