Systems and methods for performing a consumer advertising transaction at a retail device are disclosed. According to one system and method, an identifier associated with the retail device is provided to a personal communication device. An application-specific user interface specific to the retail device is associated based on the identifier. A selection is received for the consumer advertising transaction made by a consumer interacting with the application-specific user interface executing on the personal communication device. The consumer advertising transaction is performed based on the received selection for the consumer advertising transaction made by the consumer interacting with the application-specific user interface.
Systems and methods for performing a consumer advertising transaction at a retail device are disclosed. According to one system and method, an identifier associated with the retail device is provided to a personal communication device. An application-specific user interface specific to the retail device is associated based on the identifier. A selection is received for the consumer advertising transaction made by a consumer interacting with the application-specific user interface executing on the personal communication device. The consumer advertising transaction is performed based on the received selection for the consumer advertising transaction made by the consumer interacting with the application-specific user interface.
Systems and methods for performing a consumer purchase transaction at a retail device are disclosed. According to one system and method, an identifier associated with the retail device is provided to a personal communication device. An application-specific user interface is associated with the retail device based on the identifier. A selection is received for the consumer purchase transaction made by a consumer interacting with the application-specific user interface executing on the personal communication device. The consumer purchase transaction is performed based on the received selection for the consumer purchase transaction made by the consumer interacting with the application-specific user interface.
The invention relates to an electromyographic signalgait recognition method for optimizing a support vector machine based on a genetic algorithm. According to the electromyographic signalgait recognition method, the penalty parameter and the kernel function parameter of the support vector machine are optimized with the genetic algorithm, the performance of the support vector machine is accordingly optimized, and the efficiency and the accuracy of the support vector machine for recognizing lower limb movement gaits based on electromyographic signals are improved. The electromyographic signalgait recognition method includes the steps of firstly, carrying out de-noising processing on the collected lower limb electromyographic signals with a wavelet modulus maximum de-noising method; secondly, extracting the time domain characteristics of the de-noised electromyographic signals to form characteristic samples; thirdly, optimizing parameters of the support vector machine with the genetic algorithm to obtain a set of optimal parameters with the minimum errors, and constructing a classifier through the parameters; finally, inputting a characteristic sample set into the optimized classifier for gait recognition. The electromyographic signal gait recognition method is easy to operate, rapid in calculation and high in recognition rate, and has the application value and the broad prospects in the human bodylower limb gait recognition field.
A method, apparatus and program product include an Automatic TestingSystem for creating a test framework for testing operating system components. The Automatic TestingSystem resides on a server and includes a master driver which assists in creating test cases and scenarios. The Automatic TestingSystem issues commands to distribute execution to one or more remote client machines in a cluster through, for instance, an external remote shell program. Results of the command are retrieved, as though it was invoked on the machine directly. The logic and parameters needed to run the test scenarios are stored in a database accessible on the web, and test results are compiled and stored in the database to be sent to any designated test customer.
The invention relates to computers, more particularly to a method and apparatus for entering a password to gain access to computer databases. The object of the invention is to provide efficient protection of the user's password from reproduction by an unauthorized person, to substantially increase the number of possible combinations and to create passwords that are maximum easy for the users to memorize. An embodiment of the invention comprises entering parameters of a password entry dynamic image to a computer; displaying to the user the dynamic image with the selected parameters; pointing at least one predetermined object of the dynamic image that has taken a user-predetermined position in space and / or state in time. Another embodiment comprises setting a predetermined access code in the form of a rhythmic pattern; preliminary entering said rhythmic pattern via a user's entry device to a computer to store and use the rhythmic pattern in subsequent password entries; when entering the password, entering said rhythmic pattern via a set of contact means of the user's entry device.
The invention relates to an electromyographic signalgait recognition method based on particle swarm optimization and a support vector machine. A particle swarm optimizationalgorithm is utilized to optimize a penalty parameter and a kernel function parameter of the support vector machine so that the performance of the support vector machine can be optimized, and effective recognition and classification are achieved. Firstly, wavelet modulus maximum denoising is carried out on collected lower limb electromyographic signals; secondly, time domainfeature extraction is conducted on the electromyographic signals after denoising is carried out to obtain feature samples; thirdly, parameter optimization is carried out on the support vector machine by means of the particle swarm optimizationalgorithm to obtain a set of optimal parameters with minimal errors, and a classifier is constructed; at last, a feature sample set of the electromyographic signals is input to the classifier, and then classification and recognition are conducted on gait states. According to the method, both accuracy and adaptivity of classification are taken into consideration, the computational process is simple and efficient, and the method has broad application prospects in the field of lower limb motion state recognition.
The present invention discloses a method, a system and an equipment for removing the Media Access Control address, which belong to the communication field. The method comprises: when the notice received by an NPE equipment does not carry a particular identifier, the B-MAC address table corresponding to the VPLS is removed, and the notice is transmitted; when the notice carries a particular identifier, the notice is transmitted; when the notice received by a UPE equipment does not carry a particular identifier, the B-MAC address table corresponding to the VPLS is removed; and when the notice carries a particular identifier, the B-MAC address table corresponding to the particular identifier in a C-MAC address table is removed. The system comprises a network provider edge equipment and a user side provider edge equipment. By adding the particular identifier in the notice removing the MAC address, the present invention avoids the needless MAC address learning of the NPE equipment and the UPE equipment, and reduces the impact to the network equipment.
Systems and methods for performing a consumer advertising transaction at a retail device are disclosed. According to one system and method, an identifier associated with the retail device is provided to a personal communication device. An application-specific user interface specific to the retail device is associated based on the identifier. A selection is received for the consumer advertising transaction made by a consumer interacting with the application-specific user interface executing on the personal communication device. The consumer advertising transaction is performed based on the received selection for the consumer advertising transaction made by the consumer interacting with the application-specific user interface.
The invention provides a message sending method and network equipment. In the application, a first network device of a cross-device link aggregation group is connected with a user side device througha first port, and is connected with a second network device of the cross-device link aggregation group through a second port. The first network device configures a first preset ARP table entry for theuser side equipment when both the first port and the second port do not have a fault.; when the first port breaks down, the message of which the destination is the user side equipment can be forwarded to the second network equipment directly by utilizing the second port and the first preset ARP table item; and then the second network device forwards the message to the user side device, and the first network device does not need to wait for learning the ARP table item of the user side device, so that the data packet loss time and quantity when the first port fails are effectively reduced.
The invention discloses a method for avoiding interference of medium access control address list on access device, comprising that an exchange chip in data plane closes the MAC address study at network port, a MAC address study module exchanges the MAC address study function of the exchange chip, the MAC address study module and a MAC address legality check module filter illegal MAC address study to build a legal MAC address list, a control plane sets studied a new legal MAC address list into the exchange chip, and starts an aging process, when aged, deletes the MAC address of the exchange chip. Since the exchange chip uses static MAC address, the invention converts the dangerous MAC address study function of exchange chip into safe MAC address study of control plane, to avoid MAC address list interference caused by source MAC attack.
A control apparatus for a power train including a continuously variable transmission and a clutch arranged in series with the continuously variable transmission is provided in which an engaging pressure of the clutch is first reduced until a slip occurs, and is then increased after detection of the slip so as to re-engage the clutch, and an engaging pressure of the clutch to be established is calculated by giving an excess pressure to the engaging pressure at which the clutch is re-engaged, such that an excess amount of the transmitted torque of the clutch is set smaller than that of the continuously variable transmission. The control apparatus is adapted to determine a learned value as a correction value of the engaging pressure that is set in advance in accordance with an input torque applied to the clutch, based on the engaging pressure calculated by giving the excess pressure to the engaging pressure at which the clutch is re-engaged.
The invention discloses a power electronic circuit fault diagnosis method based on an optimized deep belief network. The method comprises the following steps: (1) using an RT-LAB semi-physical simulation platform to set a fault expierment, and acquiring direct current side bus output voltage signals under different fault modes to serve as original fault characteristic quantities; (2) extracting anintrinsic mode function component and an envelope spectrum thereof of the output voltagesignal by utilizing empirical mode decomposition, calculating a plurality of statistical characteristics, andconstructing an original fault characteristic set; (3) removing redundancy and interference features in the original fault feature set based on a feature selection method of an extreme learning machine, and performing normalization processing to serve as a fault sensitive feature set; (4) dividing the fault sensitive feature set into a training sample and a test sample, and preliminarily determining the structure of the deep belief network; (5) adopting a doodle search algorithm to optimize the deep belief network, and setting the number of hidden neurons of the network; And (5) obtaining a fault diagnosis result. According to the invention, the fault feature data size and the fault identification accuracy are improved.
The invention relates to a test apparatus and method for uncorrelated sound vibration load combination application and uncorrelated multisource frequency domain load identification, and three methods for performing uncorrelated multisource frequency domain load identification in a complicated sound vibration simulation environment by utilizing the apparatus. The three methods are a general-reversion-of-least-square method, an improved regularization method and a multi-input multi-output support vector regression method respectively. The three methods are all capable of identifying the values of a plurality of uncorrelated frequency domain load sources at the same time according to vibration responses of a plurality of test points. The general-reversion-of-least-square method does not need to measure a phase of a transfer function; each frequency corresponding to the improved regularization method has an optimal regularization parameter; and the multi-input multi-output support vector regression method is capable of effectively avoiding the over-learning phenomenon.
The invention relates to a small samplerelay protection reliability parameter estimation method based on a SVM (Support Vector Machine). The method comprises the following steps: 1, using an empirical formula to calculate the empirical reliability of an original failure sample and performing linear processing; 2, using a SVM algorithm to perform regression of failure data and performing prediction to generate a new enlarged sample; 3, performing linear fitting of the original failure data to obtain a parameter estimation value as a new iteration initial value; and 4, performing least square fitting of the enlarged new sample to obtain a final reliability parameter estimation result. Compared with the prior art, the method provided by the invention can effectively solve problems that priori knowledge and statistical samples are extremely in shortage as the operation time of an intelligent transformerstation is short, and is beneficial for objective analysis and evaluation of reliability of a protection system.
The invention provides a real-time detection method for a single-stage multi-scale specific target based on an effective receptive field. The method comprises the following steps: firstly, extractinga corresponding feature layer from a multi-scale architecture of an SSD, and selecting a scale according to a pixel range covered by a receptive field; secondly, an anchor structure in a traditional method is removed, fewer feature layers are adopted, and classification and regression are directly carried out on corresponding receptive field frames of the feature map by utilizing the characteristics of a natural receptive field; Finally, an RF (receptive field) sampling frame ash placement learning strategy is adopted, and redundant parameters are prevented from being learned. According to themethod, the complexity of a traditional algorithm based on an anchor sampling frame is greatly reduced, the detection efficiency is improved, the real-time effect can be achieved, and the method hasvery high use value under the application background with very large data volume.
A control system for a continuously variable transmission of a vehicle, in which a clamping pressure of rotary members to clamp a transmission member is learned and set in every operating state of a prime mover connected to an input side of the continuously variable transmission having those rotary members and transmission member. The control system comprises: an operating state changing mechanism for an operating state of the prime mover in response to a satisfaction of learning execution condition of the clamping pressure; a torque change suppressing mechanism for suppressing a change in a torque resulting from the change in the operating state of the prime mover; and a clamping pressure learning device for learning the clamping pressure in the operating state of the prime mover after the change, while the operating state of the prime mover is being changed and the change in the torque resulting from the change in the operating state of the prime mover is being suppressed by the torque change suppressing means.
The invention provides a method and a device for path maximum transmission unit (PMTU) learning. In a transmission control protocol (TCP) connection establishment process, forwarding equipment modifies a value of a maximum segment size (MSS) option in a Syn message, so that the value of the MSS option in the Syn message finally can be modified into the minimum of maximum transmission unit (MTU) values of all forwarding equipment in a transmission path; moreover, a final value of the MSS option in the Syn message is also carried by a Syn+Ack message and an Ack message, so that communication equipment can learn a PMTU by utilizing the value of the MSS option in the TCP connection establishment process, and is not required to learn the PMTU hop by hop in a communication process after the establishment of TCP connection; and therefore, PMTU learning speed can be increased, and a network bandwidth occupied by the PMTU learning can be saved. A change in the MTU value of the forwarding equipment also can be adapted by modifying a value of an MSS option in the Syn+Ack message by the forwarding equipment.
Links are managed and units of information are linked based on a list having identifiers placed in a hierarchical order relative to other identifiers, the identifiers for identifying the units of information. Lists are stored and examined to determine the hierarchical order of the identifiers relative to the other identifiers, and a unit of information is linked to at least one other unit of information based on a relative hierarchical order between an identifier identifying the unit of information and another identifier identifying at least one other unit of information.
The invention discloses a method for predicting the residual life of complex equipment based on a double-layer long-short-term memory network. The method includes by adopting a depth learn algorithm,preprocessing the historical data of complex equipment, and building a two-tier long-term and short-term (LSTM) network, wherein the number of LSTM cells in a two-layer long-short-term (LSTM) networkis determined by a continuous time period. The current data are preprocessed and transferred to the trained two-layer LSTM network, and the output of the two-layer LSTM network is set as the predictedvalue of the residual life of complex equipment. The residual life prediction model of the complex equipment based on the double-layer LSTM provided by the invention can improve the prediction accuracy of the residual life of the complex equipment. Complex equipment can thus be maintained in a timely and effective manner, while reducing the occurrence of accidents. It is of great significance toensure the safety of complex equipment operation and reduce unnecessary maintenance at the same time.
The invention relates to a pedestrian's abnormal behavior detection method comprising the steps as follows: estimating the pedestrian density in a video frame, and classifying the video frame as a high- and medium-density scene or a low-density scene according to the obtained pedestrian density; if the video scene is a high- and medium-density scene, grouping-tracking the pedestrians in the video frame and detecting whether there is an abnormal behavior using a group tracking method based on group structure dynamic evolution; and if the video scene is a low-density scene, tracking a target pedestrian in the video frame and detecting whether there is an abnormal behavior using a trajectory segment correlation method. The method is simple and convenient, avoids a complex model learning process, is of strong adaptability, and enables the monitoring staff to find the cause of a security problem more efficiently and saves manpower.
The control system comprises: an operating state changing mechanism for an operating state of the prime mover in response to a satisfaction of learning execution condition of the clamping pressure; a torque change suppressing mechanism for suppressing a change in a torque resulting from the change in the operating state of the prime mover; and a clamping pressure learning device for learning the clamping pressure in the operating state of the prime mover after the change, while the operating state of the prime mover is being changed and the change in the torque resulting from the change in the operating state of the prime mover is being suppressed by the torque change suppressing mechanism.
The invention provides a combined filling system for measured wind speed loss values of multiple neighboring wind motors in a wind field. The combined filling system comprises a wind speed data similarity determination unit, a model parameter identification unit, a wavelet neural network submodel filling unit and a combined filling unit. The combined filling system for the measured wind speed loss values of multiple neighboring wind motors in the wind field is used for overcoming the technical defects of an existing method in filling of lost measured wind speed values when the measured wind speeds of multiple neighboring wind motors in the wind field have loss values simultaneously; the similarity of the wind speed data is analyzed by use of three methods, namely a dynamic time alignment method, a correlation coefficient method and a spatial neighbor method, in a two-dimensional time domain; the measurement wind speeds of a plurality of wind motors most similar to the wind motor having the lost measured wind speed in wind speed evolution near a loss sampling point are extracted, and a wavelet neural network is established for each measured wind speed to perform lost wind speed filling; the system is adaptive to the wind speed data of different wind field by use of adjustable parameters; a combined filling method based on entropy weight is adopted, and finally, a filling system for the measured wind speed loss values of multiple neighboring wind motors in the wind field is put forward.