96 results about "Alphanumeric" patented technology

The systems and methods disclosed herein obtain a set of alphanumeric characters defining constraints for agents and the agents' operational data. Each agent uses an output from a first set of artificial intelligence (AI) models and predefined objectives to autonomously generate proposed actions for execution on software application(s). For each agent, a second set of AI models evaluates the agent by identifying gaps in the proposed actions by comparing them with the expected actions. Using a third set of AI models and the identified gaps, the systems modify the proposed actions by adding, altering, or removing actions from the proposed actions.

The systems and methods disclosed herein receives, from a computing device, operational data indicating software or hardware assets used on informational assets, and obtains set of alphanumeric characters defining operative boundaries for expected system assets, which include a set of common attributes. Using the set of attributes, a first set of AI models determines observed system assets from the operational data, each with specific features. A second set of AI models associates each information asset with the corresponding observed system assets. For each observed system asset, a third set of AI models identifies criteria within the alphanumeric characters, compares the criteria with the asset's features to identify gaps, and generates actions to ensure the observed system asset meets the identified criteria.

The systems and methods disclosed herein receive an output generation request from that includes input for generating an output using a language model. The input includes a set of alphanumeric characters associated with operative standards for a first set of actions. The system divides the set of alphanumeric characters into text subsets. For each text subset, a vector representation is determined. Prompts are created for each vector representation including the set of alphanumeric characters, query contexts, keywords, and / or the text subset. Each vector representation's prompt is input into the language model, which generates a second set of actions of related actions, where subsequently generated actions are based on prior generated actions. The system aggregates the second set of actions into a third set of actions and displays a graphical layout. The graphical layout displays a representation of the set of alphanumeric characters and the corresponding actions.

The systems and methods disclosed herein obtain a set of alphanumeric characters defining constraints for agents and the agents' operational data. Each agent uses an output from a first set of artificial intelligence (AI) models and predefined objectives to autonomously generate proposed actions for execution on software application(s). For each agent, a second set of AI models evaluates the agent by identifying gaps in the proposed actions by comparing them with the expected actions. Using a third set of AI models and the identified gaps, the systems modify the proposed actions by adding, altering, or removing actions from the proposed actions.

The systems and methods disclosed herein receive alphanumeric characters defining operative boundaries for expected model use cases, along with operational data. The expected model use cases share common attributes, which are used by a first AI model to construct observed model use cases from the operational data. Each observed model use case includes features such as a text-based description, expected input and output,? AI model(s) generating the expected output from the input, and / or data supporting the AI models. For each observed model use case, a second AI model maps the alphanumeric characters and features to a risk category, selecting from multiple risk categories based on the level of risk associated with the features. The system identifies criteria for the observed model use case within the alphanumeric characters and generates gaps by comparing the criteria with the features of the observed model use case.

Systems and methods are disclosed comprising techniques for record-to-event conversion, such as retrieving at least one alphanumeric record associated with a monitored digital communication transmitted among two or more users, generating a time-enumerated data structure that stores an event entry set for the monitored digital communication, selectively identifying at least one discrete event for the monitored digital communication, generating one or more relevance scores for the at least one discrete event, identifying at least one valid discrete event from the at least one discrete event, generating an event attribute set for the at least one valid discrete event, updating the normalized event attribute set for a new event entry within the event entry set of the time-enumerated data structure, and transmitting the updated time-enumerated data structure within an elapsed duration after retrieving the at least one alphanumeric record.

The systems and methods disclosed herein receive an output generation request from that includes input for generating an output using a language model. The input includes a set of alphanumeric characters associated with operative standards for a first set of actions. The system divides the set of alphanumeric characters into text subsets. For each text subset, a vector representation is determined. Prompts are created for each vector representation including the set of alphanumeric characters, query contexts, keywords, and / or the text subset. Each vector representation's prompt is input into the language model, which generates a second set of actions of related actions, where subsequently generated actions are based on prior generated actions. The system aggregates the second set of actions into a third set of actions and displays a graphical layout. The graphical layout displays a representation of the set of alphanumeric characters and the corresponding actions.

The technology evaluates the compliance of an AI application with predefined vector constraints. The technology employs multiple specialized models trained to identify specific types of non-compliance with the vector constraints within AI-generated responses. One or more models evaluate the existence of certain patterns within responses generated by an AI model by analyzing the representation of the attributes within the responses. Additionally, one or more models can identify vector representations of alphanumeric characters in the AI model's response by assessing the alphanumeric character's proximate locations, frequency, and / or associations with other alphanumeric characters. Moreover, one or more models can determine indicators of vector alignment between the vector representations of the AI model's response and the vector representations of the predetermined characters by measuring differences in the direction or magnitude of the vector representations.

The systems and methods disclosed herein obtain a set of alphanumeric characters defining constraints for agents and the agents' operational data. Each agent uses an output from a first set of artificial intelligence (AI) models and predefined objectives to autonomously generate proposed actions for execution on software application(s). For each agent, a second set of AI models evaluates the agent by identifying gaps in the proposed actions by comparing them with the expected actions. Using a third set of AI models and the identified gaps, the systems modify the proposed actions by adding, altering, or removing actions from the proposed actions.

The systems and methods disclosed herein receive an output generation request from that includes input for generating an output using a language model. The input includes a set of alphanumeric characters associated with operative standards for a first set of actions. The system divides the set of alphanumeric characters into text subsets. For each text subset, a vector representation is determined. Prompts are created for each vector representation including the set of alphanumeric characters, query contexts, keywords, and / or the text subset. Each vector representation's prompt is input into the language model, which generates a second set of actions of related actions, where subsequently generated actions are based on prior generated actions. The system aggregates the second set of actions into a third set of actions and displays a graphical layout. The graphical layout displays a representation of the set of alphanumeric characters and the corresponding actions.

The systems and methods disclosed herein receive alphanumeric characters defining operative boundaries for expected model use cases, along with operational data. The expected model use cases share common attributes, which are used by a first AI model to construct observed model use cases from the operational data. Each observed model use case includes features such as a text-based description, expected input and output,? AI model(s) generating the expected output from the input, and / or data supporting the AI models. For each observed model use case, a second AI model maps the alphanumeric characters and features to a risk category, selecting from multiple risk categories based on the level of risk associated with the features. The system identifies criteria for the observed model use case within the alphanumeric characters and generates gaps by comparing the criteria with the features of the observed model use case.

Training images mimicking handwritten text including one or more non-alphanumeric characters are used at least for training an optical character recognition (OCR) machine learning model. The train images are generated as follows. A character sequence format and the non-alphanumeric characters are specified. Character sequences in the specified character sequence format with the specified non-alphanumeric characters are generated using a regular expression pattern for the specified character sequence format. Synthetic handwritten images are generated for each character sequence. A handwritten text image-generating machine learning model for generating the training images is trained using at least the generated synthetic handwritten images. The training images mimicking the handwritten text including the non-alphanumeric characters are generated using the trained handwritten text image-generating machine learning model.

The invention relates to the technical field of big data, in particular to a calling voice recognition output system and method based on multi-mode and data fusion. The method comprises the following steps: acquiring voice data, analyzing a voice instruction, searching full-field ADSB information, performing number matching, outputting a matching result, and generating standardized radio voice data; a bilingual system automatic switching algorithm is realized; various standard compatible processing of alphanumeric pronunciation is realized; two calling fuzzy matching functions, a front and back nasal interference processing algorithm and a weight processing method in the mode are realized; identifying a calling number by adopting a multi-source auxiliary means; according to the airline Chinese abbreviation, aircraft number calling identification is carried out; the system comprises an audio processing module, a multi-source auxiliary module, an instruction control and processing module and a number matching module. The voice instruction is analyzed, the whole ADSB information is searched, and a multi-source auxiliary means is adopted to recognize the call number, so that the recognition performance in a complex environment is improved, and the real-time requirement is met.

Systems and methods are disclosed comprising techniques for record-to-event conversion, such as retrieving at least one alphanumeric record associated with a monitored digital communication transmitted among two or more users, generating a time-enumerated data structure that stores an event entry set for the monitored digital communication, selectively identifying at least one discrete event for the monitored digital communication, generating one or more relevance scores for the at least one discrete event, identifying at least one valid discrete event from the at least one discrete event, generating an event attribute set for the at least one valid discrete event, updating the normalized event attribute set for a new event entry within the event entry set of the time-enumerated data structure, and transmitting the updated time-enumerated data structure within an elapsed duration after retrieving the at least one alphanumeric record.

Described herein are various embodiments for customized device pairing based on device features. An embodiment operates by receiving, from a first device, a message indicating motion sensing capability of the first device available for pairing the first device with a second device, wherein the first device does not include an alphanumeric keypad. A sequence of actions to be performed on the first device is generated. The sequence of actions is provided for display. An indicia indicating a set of one or more actions performed on the first device is received. It is determined that the set of one or more actions of the indicia corresponds to the sequence of actions provided for display, and the first device is paired with a second device.

The technology evaluates the compliance of an AI application with predefined vector constraints. The technology employs multiple specialized models trained to identify specific types of non-compliance with the vector constraints within AI-generated responses. One or more models evaluate the existence of certain patterns within responses generated by an AI model by analyzing the representation of the attributes within the responses. Additionally, one or more models can identify vector representations of alphanumeric characters in the AI model's response by assessing the alphanumeric character's proximate locations, frequency, and / or associations with other alphanumeric characters. Moreover, one or more models can determine indicators of vector alignment between the vector representations of the AI model's response and the vector representations of the predetermined characters by measuring differences in the direction or magnitude of the vector representations.

A display device includes an information display section including discrete segments configured to display an alphanumeric character; a drive circuit section configured to selectively switch on and off each of the segments; and a control section configured to control operation of the drive circuit section. The drive circuit section includes a multiple drive circuit configured to simultaneously switch on and off particular segments among the segments of the information display section which are each for a portion of a particular alphanumeric character; and a single drive circuit configured to switch a single segment among the segments of the information display section which is other than the particular segments, the control section being configured to use the multiple drive circuit and the single drive circuit in combination for the control of the operation of the drive circuit section to cause the information display section to display the particular alphanumeric character.

A data structure and associated methods for analysis of a continuous 1,197,000-letter unvocalized Hebrew string referred to as the Word of God (WOG). The data structure contains only the twenty-two classical Hebrew letters and their five final forms, with no spacing, punctuation, vowelization, or editorial symbols. Intrinsic placement of the final letters enables deterministic segmentation of the string into 305,490 lexical units and 23,206 verses without external conventions. Fixed letter-number assignments provide a numeric architecture for evaluating substrings, detecting alterations, identifying encoded mathematical correspondences, and performing pattern analysis. The system preserves full semantic range by supporting multiple morphologically valid interpretations of unvocalized Hebrew strings. Methods for segmentation, numeric evaluation, reconstruction, integrity verification, semantic analysis, and mathematical pattern detection are provided thereby providing a reproducible foundation for computational and linguistic research.

The Degree Layout Design for alphabetical, numerical, alpha-numeric and / or symbolistic pictorializing can allow multiple users or interpreters the ability to utilize or interpret the same article of manufacture, simultaneously, without requiring the users / interpreters themselves, to rotate the article of manufacture. For smartphones, and some laptops, such a feature may be called, auto-rotate, but such a feature is not specifically designed for non-software based articles of manufacture, and where it is, such a feature is limited to what I call for my invention, zero (0) degree eye-parallel versus ninety (90) degree rotation. Essentially, this form of rotation is from landscape viewing to portrait viewing, or vice versa. My Degree Layout Design for alphabetical, numerical, alpha-numeric and / or symbolistic pictorializing allows this innovative tech-savvy concept to exist as landscape to landscape, portrait to portrait, portrait to landscape, and / or landscape to portrait, with essentially no limit in degree(s), with regard to every other article of manufacture, digital and analogue, where available, and not previously assigned, without limitation.

A method for activating or deactivating at least one hardware- and / or software functionality of an automation component having an input unit and an output unit includes: generating an identification information of the automation component; providing the identification information as a first machine interpretable code on the output unit; registering the provided first code using a service device via a reaction free, unidirectional data channel; transmitting the identification information from the service device to a server; generating a first license information using the server; transmitting the first license information as an alphanumeric data sequence of predetermined character length from the server to the service device; inputting the output first license information into the automation component using the input unit; checking the plausibility of the first license information using the automation component; activating or deactivating the hardware- and / or software functionality upon successful checking of the plausibility of the first license information.

In some implementations, a device may obtain a training corpus, from a set of pre-processed log data, associated with an alphanumeric format. The device may encode the training corpus to obtain encoded data using a set of tokens. The device may calculate a sequence length based on a statistical parameter associated with the training corpus. The device may generate a set of input sequences and a set of target sequences based on the encoded data, where each input sequence and each target sequence has a length equal to the sequence length. The device may generate a training data set based on combining the set of input sequences and the set of target sequences. The device may train a deep neural network (DNN) using the training data set and based on one or more hyperparameters to obtain a set of embedding tensors associated with an embedding layer of the DNN.

A computer mediated method for effecting proactive control of computer-controlled processes and / or devices related to a vehicle. Proactive control is enabled by computer recognition of a proactive user who is drawing (writing), signing, keyboarding, or voicing characters (letters, numbers, punctuation) and meta commands (such as DONE, NEXT, CANCEL) and transmitting an encoding of the characters and meta commands to the computer program that is empowered to control the vehicle. Drawn characters may be drawn on a touch sensitive device, on a surface viewable by a camera, or in three-dimensional space unrelated to a surface. All mechanisms for delivering encoded characters and meta commands to the computer directly controlling the vehicle are subsumed by this patent. Feedback is provided by the computer directly controlling the vehicle via a display and / or speech in order to close the loop on interpretation of the character and meta commands.

A segmented alphanumeric includes a display panel, at least one linearly actuated platform, and display elements. Each display element passes through an orifice in the display panel to generate protruded and segmented alphanumeric characters in combination with other extended display elements. A microactuator array is displaceable by the linearly actuated platform and includes electromagnets and rotors. Each rotor is mounted for rotation in at least one direction between an active state and an inactive state by at least one associated electromagnet. Each display element is displaced through the orifice by actuation of the linearly actuated platform via a respective rotor when the respective rotor is rotated into its active state and to evade displacement by the rotor when the rotor is rotated into its inactive state.

Disclosed, in one general aspect, is a boiler controller that includes an input for receiving a boiler water level signal, a screen having a data display that displays information. The data display includes an alphanumeric status indicator area responsive to the water level signal and operative to display status information about the water level signal in alphanumeric format, and a background indicator that extends around the alphanumeric status area and is operative to display a visual treatment that communicates different boiler safety levels. Disclosed in another general aspect is a boiler controller that includes an input for receiving a boiler water level signal and a compound level indicator that includes a vertically extending level-indicating device, a baseline reference level indicator positioned along the vertically extending level level-indicating device, and a visual treatment for the vertically extending level-indicating device that communicates different boiler safety levels. Water level outputs are also disclosed.

The present invention relates to a camera system with a digital viewfinder camera which has an interface for attaching an interchangeable lens. According to the invention, the camera system comprises at least one camera sub-unit and one evaluation unit, wherein the camera sub-unit is integrated into the viewfinder camera or can be attached to the viewfinder camera, and wherein the camera sub-unit is configured to - in a first operating mode, to capture an image of at least part of the outside of an adjustable aperture ring (16) of an interchangeable lens coupled to the viewfinder camera, wherein several aperture setting values ​​in the form of alphanumeric characters or at least one characteristic are provided on the outside of the aperture ring (16), and to transmit the image of at least part of the outside of the aperture ring (16) to the evaluation unit, wherein the evaluation unit is configured to generate an electronic aperture setting signal from the received image of at least part of the outside of the aperture ring (16) using image and / or text recognition methods, and / or - in a second operating mode, to capture an image of at least part of an interchangeable lens coupled or to be coupled to the viewfinder camera and to transmit it to the evaluation unit, wherein the evaluation unit is equipped to determine at least one identifying feature characterizing the interchangeable lens from the received image of at least part of the interchangeable lens using methods of image and / or text recognition.

A method acquires a screen capture, as a pixelated image, having text content from a first display on a first display device and processes the acquired pixelated image of the first display using optical character recognition to extract one or more alphanumeric text strings from the displayed text content. The first display device transmits the one or more extracted text strings from the first display to a second display device. At least the one or more extracted text strings are rendered on the second display device.

An archery stabilizer mount is provided and can include a base that indexes an archery stabilizer in a fixed, angular orientation relative to the base, and a bracket, which attaches to an archery bow riser, where the base is selectively installable and removable from the bracket without altering the stabilizer orientation relative to the base and / or the archery bow. The base can be repeatedly removed from and installed relative to the bracket while maintaining a reference element of the archery stabilizer indexed in the fixed angular orientation relative to the base and to the bracket. The reference element can be a branding element, such as a logo, image, alphanumeric characters or other indicia.

A method of use and a fingerprint recognition for a Point of Sale (POS) terminal system; the POS terminal system may be used as a secure means to purchase items. The POS terminal system includes a database configured to store personal information associated with an individual user. The personal information may be accessed by inputting biometric data and an alphanumeric code at a POS terminal. The invention also provides a secure means of encrypting and decrypting data files with the user's fingerprint.

To enable store employees to perform routine checks to ensure that the circuit boards in gaming machines are not counterfeit, each manufacturer's unique identification information is attached to the board. However, multiple identification information display units, each bearing different information, are detachably mounted on the printed circuit board body via easily breakable wires. When the board is placed in its case, all but one identification information display unit are broken and discarded, leading to increased costs and larger board sizes. The goal is to prevent misidentification of the identification information display units, making daily checks easier, while also achieving appropriate space savings for the circuit board. [Solution] The identification information is arranged together with the manufacturer codes of multiple companies, and is composed of alphanumeric characters using the same font as the board management number, and the manufacturer codes of multiple companies are displayed separated by special characters.