183 results about "Behavioral modeling" patented technology

A behavioral modeling technique that captures driver delay. The output characteristics of a typical driver are represented by two basic element types: switching and non-switching. Switching elements are functions of both time-varying and non-time-varying parameters, and non-switching elements are functions of non-time-varying parameters only. The outputs of these elements are characterized and tabulated by applying a DC voltage on the output of the driver and measuring the current through each element. The time-varying switching element are represent by time-controlled resistors. The invention provides a methodology to account for variations in input transition rate, supply voltage(s) or temperature.

The present invention described secures a computer account against unauthorized access caused as a result of identity-theft, and insider-espionage using artificial intelligence and behavioral modeling methods. The present invention has the ability to detect intruders or impersonators by observing “suspicious” activity under a computer account. When it sees such suspicious behavior, it uses artificial intelligence to authenticate the suspect by interrogation. The present invention asks the suspect questions that only the legitimate computer account owner can verify correctly. If the suspect fails the interrogation, that proves that he/she is an impersonator and therefore further access to the computer account is denied immediately. On the other hand if the suspect passes, access to the computer account is restored. The present invention uses a Programmable Artificial Intelligence Engine (PAIE) to interact with computer users in human natural language. The PAIE can also be programmed to suit other applications where natural language interaction with humans is helpful.

The invention relates to the field of a social network and is applied to a network system with social elements. The invention discloses a method and a system for calculating user influence in a social network, and in the method, the behaviors of users are analyzed so that a model of the behavior of influence spread among users is established and the mold is used for identifying the most influential people in the social network. The system records user access logs in real time. The method comprises the following steps that: (1) an influence behavior extracting module filters the interactive behaviors in the logs; (2) an influence spread calculating module determines the influence of the current behavior spread according to the type and the actor of the behavior and the emotion tendentiousness analysis of the relative content; (3) an influence updating module mergers the data generated through the increment; (4) a user ranking module incrementally calculates the most influential people; and (5) a service module appoints a target user range and sequences the target users according to the influence. The method and the system can dynamically reflect the change condition of the user influence according to the interactive behaviors of the users in the social network.

Methods for calibrating a photolithographic system are disclosed. A cold lens contour for a reticle design and at least one hot lens contour for the reticle design are generated from which a process window is defined. Aberrations induced by a lens manipulator are characterized in a manipulator model and the process window is optimized using the manipulator model. Aberrations are characterized by identifying variations in critical dimensions caused by lens manipulation for a plurality of manipulator settings and by modeling behavior of the manipulator as a relationship between manipulator settings and aberrations. The process window may be optimized by minimizing a cost function for a set of critical locations.

A communications controller is provided for empowering the user of a communications device, such as a telephone or other device, to assume control over incoming communications. This communications controller is based on artificial intelligence and behavior modeling techniques. Each communication is identified by unique identification information associated with an incoming communication. The user selects one of a plurality of different priority rating levels for a particular communication. The user also selects or infers block time intervals for each priority to indicate times during which incoming communication is not desired. Dynamic communications control is achieved by also determining the mood of the user or mode of the device. Undesirable communications will be “blocked”. For example, when that particular caller places a call to the user, the user's communication controller determines the caller's identification information and recalls the priority and corresponding blocking time interval for that particular caller. The user's mood or the mode of the communications device is determined. The call is accordingly passed to the communication device or blocked.

A method and a system for contextually managing and executing a change in security behavior of a target user are provided. The system extracts multiple context attributes including activity telemetry, skill, etc., from multiple external applications. The system dynamically generates one or more security behavioral models for each user based on behavior modeling criteria. The system dynamically generates a security behavior score for each user by scoring a selection of the context attributes from their security behavioral models. The system dynamically generates targeted, contextual control elements specific to a target user identified from among the users using the security behavioral models, the security behavior score, and one or more context libraries. The system dynamically renders one or more of the targeted, contextual control elements on a user device of the target user through one or more delivery channels for executing a change in the security behavior of the target user.

A method and system for detecting anomalies in an aeroengine. The method and system define a behavior model of a controller of the aeroengine using a time regression modeling the behavior of the controller as a function of a data set relating to the controller and including measurements of past behaviors and command and state measurements of the controller; continuously recalculate the behavior model for each new data set; and monitor statistical variation of the behavior model to detect a behavior anomaly of the controller representing an operating anomaly of the engine.

Disclosed is a system for detecting security threats in a local network. A security analytics system collects data about entities in the local network. The raw data can be filtered to extract data fields from the raw data that are relevant to detecting security threats in the local network. The filtered data can be converted into structured data that formats the information in the filtered data. The structured data may be formatted based on a set of schema, and can be used to generate a set of features. The security analytics system can use the generated features to build machine-learned models of the behavior of entities in the local network. The security analytics system can use the machine-learned models to generate threat scores representing the likelihood a security threat is present. The security analytics system can provide an indication of the security threat to a user.

The invention relates to a human body behavioral modeling identification method based on a priori knowledge cluster in a computer system. The method comprises the steps of human body behavioral modeling processing and human body behavioral identification processing. By the adoption of human body behavioral modeling identification method based on the priori knowledge cluster in the computer system, a constructed modeling system has a self-learning capacity and can continuously perfect a classifier along with the classification of observed samples. In cluster distribution obtained in the process of human body behavioral modeling, if outliers exist, the outliers serve as an abnormal behavioral model. When the system is designed, precaution is given as required, the method has great realistic meanings, important influence of priori knowledge on a human body behavioral identification result is considered, an improved cluster method is adopted to model and identify the human body, and foundation can be laid for identifying abnormal behaviors. The method is simple and efficient, can accurately identify different behavioral modes, and has good expandability. Working performance is reliable and stable, and the application range is wide.

The invention discloses a human body posture behavior intelligent analysis and recognition method. The method comprises the following steps: collecting sample video data; extracting all joint points of each human body in each frame of image in the sample video, and connecting all joint points of each human body in a segmented and partial manner; connecting the same joint point of each human body in two adjacent frames of images to form a space-time diagram of each human body skeleton framework; classifying the behaviors by adopting a SoftMax classifier, and dividing behavior feature categories; performing deep learning according to the divided behavior feature categories, and training a behavior analysis model; collecting a human body posture behavior video to be analyzed, extracting a space-time diagram of each human body skeleton framework in the video, inputting the space-time diagrams into the behavior analysis model, and analyzing the behavior category of each human body in the video by the behavior analysis module. Human body posture behaviors are analyzed and recognized through feature extraction, behavior modeling and behavior classification, and the accuracy is high.

The invention provides a method of processing a wafer using Ion Energy (IE)-related multilayer process sequences and Ion Energy Controlled Multi-Input/Multi-Output (IEC-MIMO) models and libraries that can include one or more measurement procedures, one or more IEC-etch sequences, and one or more Ion Energy Optimized (IEO) etch procedures. The IEC-MIMO process control uses dynamically interacting behavioral modeling between multiple layers and/or multiple IEC etch sequences. The multiple layers and/or the multiple IEC etch sequence can be associated with the creation of lines, trenches, vias, spacers, contacts, and gate structures that can be created using IEO etch procedures.

The invention provides a method of processing a wafer using multilayer processing sequences and Multi-Layer/Multi-Input/Multi-Output (MLMIMO) models and libraries that can include one or more measurement procedures, one or more Poly-Etch (P-E) sequences, and one or more metal-gate etch sequences. The MLMIMO process control uses dynamically interacting behavioral modeling between multiple layers and/or multiple process steps. The multiple layers and/or the multiple process steps can be associated with the creation of lines, trenches, vias, spacers, contacts, and gate structures that can be created using isotropic and/or anisotropic etch processes.

A computer project management system and method for the creation of an electronic control unit software is provided. The system has a software architecture tool configured to design a graphical model of an electronic control unit for a motor vehicle. A behavior model tool converts the graphical model into a computer readable production code. A software container has a file generated based on the electronic control unit. A container manager compares the software container with a prior software container during the importation or exportation of the software container to or from the software architecture tool or the behavior model tool, and a comparison list is generated indicating whether interface modifications for the electronic control unit were made. The comparison list is then displayed to a user on a display screen.

The invention discloses a multi-agent-based virtual miner safety behavior modeling and emergency simulation system. The system is characterized by comprising a monitoring layer, an analysis layer, a simulation layer, a decision enforcement layer and a database layer, wherein a communication agent is responsible for communication between every two layers; the monitoring layer consists of various detection agents; the analysis layer consists of a database management module; the simulation layer comprises an ordinary simulation module, a self-defined simulation module and an agent generation module; the decision enforcement layer comprises a commanding module, an enforcement module and an evaluation module; the database layer comprises an integrated database, a model base and a knowledge base. According to the system, an evolution trend during the occurrence of various disasters in a mine and evacuation behaviors of underground miners under a real condition can be simulated in a simulation environment, the system can be extended according to different environments of different mines in a self-defined way, a guiding basis is provided for the underground emergency evacuation of the mines in the real condition, and the safety production efficiency and the scientific management level of a mine environment are greatly improved.

A mobile terminal for providing life observations by monitoring data being transmitted to/from the terminal. A mobile terminal proxy works in conjunction with a data collection engine and platform connection settings to detect at least on data object type and forward information relating to the data type to the data collection engine. Various observation logic and triggering rules may be implemented for the data collection. A server arrangement may further utilize context and behavior modeling using observations from plural mobile terminals and guiding the mobile terminals for future observations.

A hardware design emulation system that includes one or more emulators and one or more associated run-time assist units (RTAUs). The emulator logic is a combination of user model logic, reflecting the hardware design, and non-user model logic. A handshaking controller produces a domain step signal and a model step signal. The domain step signal indicates that the emulator is entering a state for executing the next step of the logic with which it is programmed, be it user model logic or non-user model logic. The model step signal indicates that the emulator is entering a state for advancing the user model defined by the user model logic. This dual handshaking protocol enhances versatility by enabling a wide variety of RTAUs to be used, particularly in combination with one another. Also, a RTAU can, in accordance with its programming, "skip steps" (either model steps or domain steps) to enhance efficiency if there is a known relationship between cycles of the emulator logic and cycles of the user model. In addition, system stoppage logic efficiently alerts other RTAUs when one RTAU has caused the emulation to stop. Furthermore, the emulation system can be scaled to accommodate a greater number of RTAUs by cascading the master panels to which they are connected.

The invention discloses a following behavioral modeling method which takes into account lane-changing of a front vehicle. The method comprises the steps that S1 the lane-changing trajectory data of a lane-changing vehicle, the rear vehicle of the lane-changing vehicle and the front vehicle of the lane-changing vehicle are acquired when the vehicle changes the lane and drives off the lane; S2 the acceleration state change of the lane-changing vehicle during the lane-changing process is determined; S3 whether the lane-change vehicle drives off the current lane or not, if so, the second front vehicle of the current lane is used as the tracking target, otherwise the front vehicle of the current lane and the lane-changing vehicle which drives off are used as following targets; S4 modeling basic parameters based on a genetic algorithm are calibrated; S5 a driver competition coefficient is identified; and S6 the following acceleration of the current vehicle at a next moment is output. According to the invention, based on a classic following behavioral model FVDM model, a pitch gain factor is introduced to reflect the enlargement of the rear vehicle to the front driving space when the front vehicle in the current late is laterally deviated, so as to reasonably reflect the influence of the lane-changing behavior of the front vehicle to the following behavior of the rear vehicle; and the adaptability of the following behavioral modeling method is effectively improved.