802 results about "Machine models" patented technology

A system and method in accordance with the present invention determines in real-time the portions of a set of characters from a data or character stream which satisfies one or more predetermined regular expressions. A Real-time Deterministic Finite state Automaton (RDFA) ensures that the set of characters is processed at high speeds with relatively small memory requirements. An optimized state machine models the regular expression(s) and state related alphabet lookup and next state tables are generated. Characters from the data stream are processed in parallel using the alphabet lookup and next state tables, to determine whether to transition to a next state or a terminal state, until the regular expression is satisfied or processing is terminated. Additional means may be implemented to determine a next action from satisfaction of the regular expression.

Symmetrical / asymmetrical bidirectional S-shaped I-V characteristics with trigger voltages ranging from 10 V to over 40 V and relatively high holding current are obtained for advanced sub-micron silicided CMOS (Complementary Metal Oxide Semiconductor) / BiCMOS (Bipolar CMOS) technologies by custom implementation of P1-N2-P2-N1 / / N1-P3-N3-P1 lateral structures with embedded ballast resistance 58, 58A, 56, 56A and periphery guard-ring isolation 88-86. The bidirectional protection devices render a high level of electrostatic discharge (ESD) immunity for advanced CMOS / BiCMOS processes with no latchup problems. Novel design-adapted multifinger 354 / interdigitated 336 layout schemes of the ESD protection cells allow for scaling-up the ESD performance of the protection structure and custom integration, while the I-V characteristics 480 are adjustable to the operating conditions of the integrated circuit (IC). The ESD protection cells are tested using the TLP (Transmission Line Pulse) technique, and ESD standards including HBM (Human Body Model), MM (Machine Model), and IEC (International Electrotechnical Commission) IEC 1000-4-2 standard for ESD immunity. ESD protection performance is demonstrated also at high temperature (140° C.). The unique high ratio of dual-polarity ESD protection level per unit area, allows for integration of fast-response and compact protection cells optimized for the current tendency of the semiconductor industry toward low cost and high density-oriented IC design. Symmetric / asymmetric dual polarity ESD protection performance is demonstrated for over 15 kV HBM, 2 kV MM, and 16.5 kV IEC for sub-micron technology.

During a targeting technique, a machine model is generated based on content-interaction data that specifies interactions of users of a social network, with categorical content corresponding to predefined interest segments. The content-interaction data may include viewing of the categorical content and sharing of the categorical content with other users of the social network. This machine-learning model is then used to calculate scores for the users based on the attributes in their profiles that indicate probabilities of their interest in additional categorical content. Moreover, based on the calculated scores, a subset of the users is associated with an interest segment. For example, the users may be ranked based on their calculated scores, and the subset may be those users having scores exceeding a threshold or a predefined value. Furthermore, advertisements may be targeted to the users in the subset based on the association with the interest segment.

In a storage target device controller capable of managing multiple command contexts, methods and associated apparatus are provided for automatically managing the plurality of contexts using a state machine model. The state machine model is operable on a target device controller having an active context register set for processing of the presently active transfer on the host channel and an inactive context register set for storing an inactive context. The active context register set and inactive context register set are rapidly and automatically swapped by operation of the state machine model to resume or start processing of an inactive context. Additional inactive contexts are stored in a buffer memory associated with the target device controller. The inactive context register set is automatically stored into a selected one of the additional inactive contexts or loaded from a selected one of the additional inactive contexts by operation of the state machine model of the present invention. The state machine model performs appropriate swap, load, and store operations for contexts in accordance with priorities to improve performance of the target device. The highest priority is an auto-write context corresponding to a write command for which data will be imminently received on the host channel. The next priority is the disk context so as to provide sufficient host channel activity to maintain continuous disk channel operation. The last priority is any other context corresponding to any other command which is neither an auto-write context or the present disk context.

Systems, devices, and methods that implement state machine models in wearable electronic devices are described. A wearable electronic device stores processor-executable gesture identification instructions that, when executed by an on-board processor, enable the wearable electronic device to identify one or more gesture(s) performed by a user. The wearable electronic device also stores processor-executable state determination instructions that, when executed by the processor, cause the wearable electronic device to enter into and transition between various operational states depending on signals detected by on-board sensors. The state machine models described herein enable the wearable electronic devices to identify and automatically recover from operational errors, malfunctions, or crashes with minimal intervention from the user.

Symmetrical / asymmetrical bidirectional S-shaped I-V characteristics with trigger voltages ranging from 10 V to over 40 V and relatively high holding current are obtained for advanced sub-micron silicided CMOS (Complementary Metal Oxide Semiconductor) / BiCMOS (Bipolar CMOS) technologies by custom implementation of P1-N2-P2-N1 / / N1-P3-N3-P1 lateral structures with embedded ballast resistance 58, 58A, 56, 56A and periphery guard-ring isolation 88-86. The bidirectional protection devices render a high level of electrostatic discharge (ESD) immunity for advanced CMOS / BiCMOS processes with no latchup problems. Novel design-adapted multifinger 354 / interdigitated 336 layout schemes of the ESD protection cells allow for scaling-up the ESD performance of the protection structure and custom integration, while the I-V characteristics 480 are adjustable to the operating conditions of the integrated circuit (IC). The ESD protection cells are tested using the TLP (Transmission Line Pulse) technique, and ESD standards including HBM (Human Body Model), MM (Machine Model), and IEC (International Electrotechnical Commission) IEC 1000-4-2 standard for ESD immunity. ESD protection performance is demonstrated also at high temperature (140° C.). The unique high ratio of dual-polarity ESD protection level per unit area, allows for integration of fast-response and compact protection cells optimized for the current tendency of the semiconductor industry toward low cost and high density-oriented IC design. Symmetric / asymmetric dual polarity ESD protection performance is demonstrated for over 15 kV HBM, 2 kV MM, and 16.5 kV IEC for sub-micron technology.

The present invention discloses a driving behavior decision system of an automatic driving public traffic vehicle. The system comprises an external environment perception module, an information fusion processing module, a driving scene determination module and a driving behavior decision module. The external environment perception module comprises a vision sensor, a laser radar, a millimeter wave radar, a GPS location module and a high-precision map. The driving behavior decision module employs a limitation state machine model, and the driving behavior decision module employs a driving behavior determination decision model based on an ID3 decision tree; and the information fusion processing module performs fusion processing of the environment information sent by an external environment perception module and sends the information after fusion processing to the driving scene determination module and the driving behavior decision module. The driving behavior decision system of the automatic driving public traffic vehicle can improve the driving safety of the automatic driving public traffic vehicle and effectively reduce the probability of traffic accidents.

The invention discloses a dynamic confirming method for performance index value normal fluctuating range, comprising following steps: obtaining a historical value of the network performance index, and dynamically obtaining the latest historical sample data; processing pre-treatment to obtain a normal sample data; processing phase space re-construction to obtain a training sample data; processing training modeling to take residual error white noise as condition of selecting the optimal supporting vector machine model; using the optimal supporting vector machine model to predict the data on the to-be predicted time point, and calculating the confidence interval of the predicted value to obtain the performance index value normal fluctuating range; detecting whether the optimal supporting vector machine model is suitable for the next prediction of the to-be predicted time point; if the model is not suitable, processing re-training. The invention also discloses a device for the dynamic confirmation performance index value normal fluctuating range. The invention significantly enhances the precision of the performance dynamic early warning, and reduces wrong report and missing report of the performance warning.

The invention discloses a video recommendation method. The method comprises the steps that user information data, video information data and behavior information data generated when a user watches videos are collected; a factorization machine model is established according to the collected data, and a reinforcement learning network model is trained; historical behavior information data up to the video currently watched by the user is acquired, and a recommended video of the user is obtained based on the factorization machine model and the trained reinforcement learning network model according to the historical behavior information data; and actual feedback information of the user on the recommended video is recorded, and the factorization machine model and the trained reinforcement learning network model are optimized according to the actual feedback information. The invention furthermore discloses a video recommendation system. Through the video recommendation method and system, video recommendation accuracy and speed can be effectively improved.

The invention provides an aquaculture dissolved oxygen concentration online forecasting method and an aquaculture dissolved oxygen concentration online forecasting system. The method comprises the following steps of: acquiring water quality index and related meteorological factor data in a scheduled time period to establish an original data set; performing data standardized pre-processing on the original data set by using a normalization method to acquire a training sample data set of a least square support vector regression (LSSVR) machine model; training the LSSVR machine model by using the training sample data set, and optimizing the parameters of the LSSVR machine model to acquire an optimal LSSVR machine model; and acquiring water quality index and related meteorological factor data of an aquaculture ecological environment on line in real time, and inputting the acquired water quality index and related meteorological factor data to the optimal LSSVR machine model to acquire a dissolved oxygen concentration forecasting value. By using the method and the system, accurate and efficient forecasting of the aquaculture dissolved oxygen concentration is realized.

In order to improve a simulation system for representing actions of machining units of a machine tool, in particular actions in the machining of a workpiece, in accordance with a CNC machining program complex by means of at least one first visualization unit in the form of actions of virtual machining units of a virtual machine tool, comprising an action control, which has at least one first data processing unit, which establishes control commands for actions of the virtual machining units by a control program processing CNC blocks of the CNC machining program complex, and a visualization control, which has at least one second data processing unit, which represents actions of the virtual machining units on the first visualization unit by a visualization program on the basis of configuration data of a stored machine model and the control commands determined by the action control, in such a way that it can be operated more easily, it is proposed that the simulation system comprises an operating control with a third data processing unit, which operates the action control by an operating program, and that the operating program has a program management function, which transfers at least program parts of the CNC machining program complex in a workpiece-related manner from said CNC machining program complex stored in a memory of the third data processing unit to the action control for executing said program complex.

A work state virtual simulation system for an electric haulage shearer based on different geological conditions belongs to automatic control and system simulation of shearers. The work state virtual simulation system comprises devices and a method, wherein the devices consist of a shearer work condition remote monitoring platform, a database, a remote controller, a visual basic system, an industrial Ethernet, a local controller and a machine-mounted detection control system. The method comprises the following steps of: acquiring shearer work condition parameters for the machine-mounted detection control system; carrying out data analysis on the shearer work condition parameters; finally, transmitting the shearer work condition parameters to the shearer monitoring platform for detecting and achieving through the local controller and the industrial Ethernet; on the basis of accessing an achieving database in real time, drawing fully mechanized coal faces under different geological conditions by applying a virtual real technology; and driving a shearer virtual sample machine to realize real reappearance of the work state of the shearer. A shearer virtual sample machine model is driven by using real-time work condition parameters provided by the machine-mounted detection control system, so that a shearer virtual simulation system has the field feeling entering the fully mechanized coal faces and favorable interaction.

The invention discloses a pressure testing method, device and system for intelligent terminal software. The pressure testing method comprises the following steps: receiving the intelligent terminal software, a testing script thereof and a testing machine model list; selecting an intelligent terminal of a corresponding testing machine model being connected on the cloud; sending the intelligent terminal software and the testing script thereof to the selected intelligent terminal; conducting testing control on the selected intelligent terminal. The testing control comprises the following steps: installing and operating the intelligent terminal software; repeatedly playing back the testing script aiming at the intelligent terminal software to realize the pressure test on the basis of the specified frequency. By the adoption of the pressure testing method, device and system, the amount of intelligent machine models covered by the pressure test can be increased, and the testing speed and the testing efficiency are improved.

The invention relates to a pollution flashover index forecasting method for a regional power grid, belonging to the technical field of transmission and distribution monitoring. The method of the invention comprises the following steps: (1) forecasting the current value of the equivalent salt deposit density in real time by an insulator surface equivalent salt deposit density forecasting model; (2) forecasting pollution flashover critical voltage by an insulator pollution flashover critical voltage forecasting model; (3) forecasting the insulator pollution flashover index of the power grid by a pollution flashover graded forecasting and prewarning model; and (4) judging the state. The invention has the advantages of providing a multivariable equivalent salt deposit density time sequence forecasting model based on phase space reconstruction, solving by a supporting vector machine model, solving the forecasting problem under the conditions of small sample of equivalent salt deposit density data and noise, and improving the forecasting prediction.

The invention provides a generic access network-based tele-medicine system which comprises a medicine terminal, a user self-service portal and a machine-to-machine (M2M) service management platform; wherein the medical terminal is used for collecting physical index data of a user and transmitting the collected physical index data to the M2M service management platform; the user self-service portal is used for determining the machine model of the medicine terminal according to selection of the user, and sending a registration request carrying the machine model of the medicine terminal to the M2M service management platform, as well as receiving and storing diagnosis result data from the M2M service management platform, and showing the diagnosis result data to the user according to the request of the user; and the M2M service management platform is used for scheduling information of a corresponding adaptive template according to the machine model of the medicine terminal in registration information of the user, storing and displaying the analyzed physical index data and transmitting the diagnosis result data to the user self-service portal.

The invention discloses a regularization state machine model design method with a stateful protocol. The regularization state machine model design method is used for improving a traditional fuzz test aiming at a stateful network protocol, enables a test case generated by the traditional fuzz test to be targeted but not indigested, has a wide cover range and is efficient. The regularization state machine model design method comprises the steps of step 1, obtaining the protocol specifications of a to-be-tested network protocol, and obtaining the protocol rules and a preliminary protocol state machine model through format analysis on the to-be-tested network protocol; step 2, generating a regularization state machine model for simplifying state space according to the preliminary protocol state machine model and the information of the state rules; step 3, generating a state generating tree combined with a state and the rules according to the protocol rules and the regularization state machine model, simplifying the relation between the state and a message through the state generating tree, and eliminating insignificant combinations; step 4, generating a preliminary test case; step 5, carrying out regular variation on the preliminary test case, and obtaining a final test case set.

The invention discloses a radar radiation source identification method based on phase noise unintentional modulation characteristic, relates to an identification method of a radar radiation source, and aims to solve the problem that the identification rate of an existing radiation source identification method based on phase noise is not high. The method disclosed by the invention comprises the following steps of analyzing the structure of a phase-lock frequency synthesizer in a radar transmitter system; building a model of phase noise generated by the phase-lock frequency synthesizer; calculating a bispectrum diagonal slice characteristic and a bispectrum non-diagonal slice characteristic; forming a characteristic matrix Y by using a bispectrum diagonal slice characteristic matrix A1 and a bispectrum non-diagonal slice characteristic matrix B1; performing PCA (Principal Component Analysis) dimensional reduction and building a type-known transmitter vector machine model; identifying a transmission signal of a type-unknown transmitter by utilizing the built vector machine model so as to realize the identification of a radar radiation source. The method disclosed by the invention is applicable to the identification of the radar radiation source.

The invention relates to the air-conditioner production field, in particular to the frequency conversion air conditioning outdoor device testing system in the production process. The frequency conversion air conditioning outdoor device testing system of the invention integrates a variety of outdoor device communication protocols, and a variety of machine models, a variety of testing models, a variety of detection methods testing procedures, and by the machine model setting, it can achieve the detection to a variety of air-conditioning outdoor machines, making the testing system more common; according to the detection mode setting, it can use multiple detection models to detect the tested outdoor machine, making the testing system detection functions better; according to the detection method setting, it can use a variety of detection means to detect, making the testing system more flexible during detection; the frequency conversion air conditioning outdoor device testing system of the invention can also real-time display the return signal of the measured outdoor machine, making detection results more intuitive, and more understanding.

The invention provides a photovoltaic-power-station low-voltage penetrating performance evaluation method based on an inverter model test. The method includes the following steps: step1: carrying out a low-voltage penetrating model test on a photovoltaic inverter single-machine model; performing fault simulation on a grid-connection photovoltaic inverter model according to test parameters of the model test and verifying the low-voltage penetrating performance of the photovoltaic inverter single-machine model; step2: constructing a photovoltaic power station model; step3: performing steady-state power flow calculation on the photovoltaic power station model and analyzing the steady-state performance of the photovoltaic power station model; step4: according to a low-voltage penetrating performance standard of the photovoltaic power station, verifying the low-voltage penetrating performance of the photovoltaic power station model. Compared with the prior art, the photovoltaic-power-station low-voltage penetrating performance evaluation method based on the inverter model test is capable of meeting evaluation demands of power grids on low-voltage penetrating technical requirements of a large-size photovoltaic power station under conditions that a low-voltage penetrating test on the whole of a photovoltaic power station cannot be carried out and a test on a photovoltaic power generation unit cannot be carried out effectively.

The invention discloses a voice communication management system, comprising a communication management device, a state machine model and a state machine; the communication management device is used for storing and maintaining all current effective communication processes, receiving semantic information of a user and providing a corresponding response through the state machine; the state machine model is used for storing all information of a communication field structure, is a static description file of a communication field, and can perform state maintenance and generate a system response according to the field rule described by the state machine model in the operation process; the state machine is used for tracking the state information of the communication progress during the operation, updating the communication state when the user generates an input operation, and dynamically generating a corresponding response according to the current communication state; the particular field information that the state machine relates to is appointed by the state machine model. The voice communication management system can perform customization on a specific communication flow through embedding the JavaScript codes and can realize more flexible communication management.

The invention provides an automatic box feeding machine, which comprises a machine frame provided with a box inlet and a box outlet. The automatic box feeding machine is characterized in that the machine frame is provided with a lifting device which is connected with the box inlet; and the upper side of the lifting device is provided with a moving and rotating device, and the lower side of the moving and rotating device on one side of the lifting device is provided with a paper box aligning and stacking device which is connected with the box outlet. The automatic box feeding machine can completely achieve automatic box feeding, and overcome the defects of high labor intensity, low work efficiency, and the like, brought by feeding boxes by workers in the prior art. The automatic box feeding machine has the advantages of compact structure, reasonable layout and accurate and quick automatic box feeding, and does not occupy more production spaces. Proper automatic box feeding machine models can be selected according to different box sealing machine layouts of the prior art, so that the automatic box feeding machine also has the advantages of wide application range, convenient installation and investment conversation, and can provide guarantee for cigarette packing to achieve fully-automatic operation.

The invention discloses a parking space state judgment method of a geomagnetic vehicle detector. The method includes the following steps that: a three-axis (XYZ) magnetoresistive sensor with a temperature compensation function is adopted; when the sensor is installed, the Z axis of the sensor is perpendicular to the ground, the Y axis and X axis of the sensor point to the adjacent edges of a parking space respectively; two axial directions (i.e. horizontal axial directions) of the Y axis and X axis are set as auxiliary reference axes and are used for monitoring the dynamic perturbation value of a magnetic field; the axial direction (i.e. vertical axial direction) of the Z axis is set as a main reference axis and is used for judging the static variation amount of the magnetic field; and a horizontal surface magnetic field dynamic perturbation value monitoring and vertical axial direction magnetic field strength variation amount determination method is used in combination to judge whether the parking space is unoccupied or unoccupied. According to the method, whether vertical axial direction magnetic field strength variation amount is larger than an uplink threshold value or is smaller than a downlink threshold value is judged, and a Mealy state machine model is used to judge the current status of the parking space. With the method adopted, interference on parking space judgment of the geomagnetic vehicle detector caused by adjacent parking spaces, surrounding passing vehicles and sensor temperature drift and background magnetic field drift can be effectively inhibited, and the problem of frequently jump of the state of a parking space can be solved.

In a gear cutting simulation method and device, a gear-cutting-machine model which specifies relative positions between a blank model and a cutter model is created. A gear model is created as a result of simulation of gear cutting which is performed with the blank model and the cutter model arranged in the gear-cutting-machine model.

A system for optimizing selection of transcription engines using a combination of selected machine learning models. The system includes a plurality of preprocessors that generate a plurality of features from a media data set. The system further includes a deep learning neural network model, a gradient boosted machine model and a random forest model used in generating a ranked list of transcription engines. A transcription engine is selected from the ranked list of transcription engines to generate a transcript for the media dataset.

The present invention extends to methods, systems, and computer program products for managing software lifecycle. Based on declarative models and knowledge of their interpretation, embodiments of the present invention facilitate lifecycle management for model-based software applications. Lifecycle models, such as, for example, lifecycle state machine models are stored in a shared repository such that executive services can determine how software application lifecycles are to be managed and transitioned. Software lifecycle activities can verify that a transition is possible and identify any errors preventing a lifecycle transition. Model-based error handling and error recovery mechanisms can be used to correct any identified errors.

Embodiments of the present invention provide an improvement to conventional machine model training techniques by providing an innovative system, method and computer program product for the generation of synthetic data using an iterative process that incorporates multiple machine learning models and neural network approaches. A collaborative system for receiving data and continuously analyzing the data to determine emerging patterns is provided. The proposed invention involves generating synthetic data clusters to be stored and used for retraining the main model as well as other models. In addition, the invention includes using one or more (subset) of the synthetic data clusters to train or retrain machine learning models, developing and training machine learning models that are trained with emerging synthetic data clusters, and ensembling machine learning models trained with emerging synthetic data clusters.

The invention provides a method for monitoring the state of a gearbox of a wind power generation set. The method includes the following steps of: collecting historical data of a wind power generation set SCADA system, screening out the active power, wind speed, cabin temperature, principle shaft rotation speed and gearbox oil temperature of the set under the healthy operation condition, and establishing a standard expert database; optimizing the penalty coefficient and the nuclear parameter of a least squares support vector regression machine by using a gravitational search algorithm, and establishing a gearbox oil temperature mapping model under the healthy operation condition by taking the active power, wind speed, cabin temperature, principle shaft rotation speed in the expert database as inputs and the gearbox oil temperature as an output and based on the optimized vector machine model; monitoring the gearbox of the wind power generation set in real time by using the mapping model, inputting the actually measured values of the active power, wind speed, cabin temperature and principle shaft rotation speed to obtain the predicted value of the gearbox oil temperature, defining the quotient of the predicted value of the oil temperature and the actually measured value as a judging index, and judging that a failure occurs in the gearbox of the wind power generation set and giving an alarm, if the statistical property of the judging index is abnormal. The method can be widely applied to early warning of the gearbox of the wind power generation set.

The invention discloses a support vector machine (SVM) based prediction method for the degradation tendency of super-capacitor capacitance value. The prediction method utilizes the regression function of the support vector machine to predict the degradation tendency of the super capacitor capacitance value and comprises: 1) pre-processing the input value and the output value; 2) carrying out trainings to the training set data for a regression estimation function; 3) using the particle swarm optimization algorithm to automatically optimize the relevant parameters of the support vector machine; 4) according to the optimization result, configuring the corresponding parameter values of the support vector machine; substituting the training set data into a correlation vector machine model to obtain a regression prediction model for the degradation tendency of the capacitance value; and 5) substituting the training set data into the regression prediction model to obtain the degradation tendency of the capacitance value. According to the invention, it is possible to conduct online prediction to the degradation tendency of the capacitance value. Through the introduction of a particle swarm optimization algorithm to modify the parameter optimization method, the prediction efficiency and accuracy of the algorithm are increased so that it can be applied in a larger scope.

The invention provides a universal chip for a consumable container, which comprises a memory unit, a control unit, an interface unit, a data acquisition unit and a state machine model selection unit, wherein the memory unit is used for storing information related to the consumable container, including parameter information and metrical information; the control unit is used for controlling the information access in the memory unit; the interface unit is used for providing an interface or a protocol for communication; the data acquisition unit is used for acquiring identification information of imaging equipment; and the state machine model selection unit is used for determining the model of the imaging equipment corresponding to the universal chip currently according to the identification information and a data operation state in which the universal chip is. The invention further provides a communication method of the universal chip, the consumable container with the universal chip and the imaging equipment. By adopting the universal chip, the communication method of the universal chip, the consumable container and the imaging equipment disclosed by the invention, the problem of failed matching between the universal chip and a printer resulted from cross of key authentication information is avoided; furthermore, the universal chip has individual service life.