34 results about "Training study" patented technology

The invention provides a knowledge map optimal path inquiry method based on depth reinforcement learning, includes two modules, module 1 and module 2, the first module is an offline training module ofthe knowledge map optimal path model, the second module is the on-line application module of the knowledge map optimal path model, the knowledge map optimal path model offline training module is provided with a depth reinforcement learning component, to present the entity carries on the depth intensification training study, so that that next entity is obtain, as the following entity repeats the train learning of the current entity, so that the optimal path model is obtained.The invention adds the generalization ability of the model and improves the calculation accuracy. The logic structure ofthe invention is clear and the calculation mode is flexible. Especially, the reinforcement learning and the depth learning can be distributed and the operation efficiency is improved.

The invention discloses a depth study-based network risk early warning method. The method comprises the following steps of: A1. collecting cyberspace asset risk sample data of a full network segment, and storing the cyberspace asset risk sample data in a database; A2. extracting data from the database, and performing convolutional neural network distributed training study, so as to form an initial risk prediction model; and A3. inputting production data into the risk prediction model, evaluating a risk value of the production data, if the risk value reaches an early warning threshold, alarming. Through adoption of the method and device, security risk evaluation and early warning are performed on multiple target networks or targets without obvious vulnerability, and the security state of one network can be evaluated overall; the response speed is improved, and the risk points can be found rapidly; and the maintenance cost is lowered, and the manpower is saved.

The invention provides a system for special dictation training study related to numbers in a foreign language. The system comprises an obtaining unit capable of obtaining dictation materials, a judging unit conducting judgment according to the dictation material, an initializing unit conducting initialization, a setting unit setting difficulty levels and a storage unit for storing a dictation question bank. The obtaining unit, the judging unit, the initializing unit and the setting unit are connected in sequence. The storage unit is connected with the judging unit. According to the system and method for special dictation training study related to the numbers in the foreign language and based on the current capacity levels of response to the dictation numbers in the foreign language of a learner training is automatically and gradually enhanced from easy dictations to difficult dictations and training is intensified in a concentrated mode.

The invention discloses a gesture recognition system and a gesture recognition method. The gesture recognition system at least comprises an intelligent mobile terminal which is provided with accelerated speed, direction and magnetic field sensors, and used to record sensor data of user gestures and extract features, and recognizes the user gestures according to the features by using a training model obtained in training of a model training platform, and further comprises the model training platform which is used to mark and perform normalization processing on the gesture features of the various user gestures, collected by the intelligent mobile terminal, perform feature training study and obtain the training model. The gesture recognition system and the gesture recognition method can input information through gesture information so as to complete corresponding tasks under the circumstance that a user can not or does not want to input the information through a touch screen or a keyboard, and enables a smart phone user to complete the corresponding tasks by simply waving a hand.

This invention relates to mobile terminal orientation and its programming service method, firstly roughly orientating, which is to orientate the honeycomb net position or the small zone, secondly exactly orientating, which is the manual assistant one key orientation or the small zone exactly orientation or the slightly orientation; wherein the slightly orientation includes the character distilling, comparatively identifying, exactly orientation and training studying; the slightly net is the blue tooth slightly net, the mobile terminal adds the slightly net to obtain the information such as the orientation; service condition, service and the service parameter, wherein the service condition is composed of the special position, time and service; and this invention satisfies the service requirement of the different orientation precision and the mobile communication requirement of the different occasion.

The invention provides an automatic waste empty house site information extraction method based on a remote-sensing image. According to the method, the high-resolution remote sensing image is partitioned through vector cadastre data constraint, a method that the contextual feature of a multi-dimensional space structure serves as the recognition feature of a waste empty house site, and a method that classified recognition conducted through a classifier is adopted, the recognition accuracy of the waste empty house site is effectively improved, and automated extraction of the waste empty house site is achieved. The method mainly includes the steps that (1) the high-resolution remote sensing image and the vector cadastre data of the region to be extracted of the waste empty house site are obtained, the high-resolution remote sensing image is partitioned through the vector cadastre data constraint, and a house site object is extracted; (2) the house site object serves as the father object, partition is conducted continuously, and internal sub objects of the house site and related house and courtyard features of the waste empty house site are extracted to form a multi-dimensional feature space; (3) samples and the classifier are selected to conduct training study of the classifier; (4) by the adoption of the method of classified recognition conducted through the classifier is adopted, a waste empty house site plaque is recognized, and the recognition result is output.

The invention provides a VANETs vehicle accident risk prediction model based on AdaBoost-SO (trichotomy Adaboost with SMOTE and One-Hot encoding) and using an SMOTE algorithm and a one-bit effective coding three-point adaptive lifting algorithm. The model can provide the theoretical basis for an ITS (International Traffic System) and driving safety assistance. According to the invention, firstly aresearch data set is filled, samples in the data set are balanced through an SMOTE algorithm, a few types of oversampling are synthesized, and each sample feature is subjected to One-Hot coding, andthen the trachomy Adaboost-SO algorithm is used for train and research the data set to obtain a system model, and finally the traffic data is imported through the VANETs to obtain the probability of vehicle accidents.

The invention relates to a distortion correction method for a large-field-of-view display device, and belongs to the technical field of intelligent information image processing. The method comprises: establishing an artificial neural network with a dual-layer implicit structure and solving a weight and a threshold of each layer of the artificial neural network with the dual-layer implicit structure by utilizing a particle swarm algorithm; taking a value corresponding to a global extreme value as the weight and the threshold of the neural network and substituting the value into the established artificial neural network to perform training study to form an image distortion correction model; and finally inputting distortion image data into the distortion correction model to perform correction to obtain a corrected image. According to the method, the weight and the threshold of the artificial neural network are trained by adopting the particle swarm algorithm to overcome the shortcomings of local minimum, low convergence speed and the like of a conventional artificial neural network; and the method is easy to implement, good in data processing capability, high in correction precision and suitable for distortion correction of the large-field-of-view display device.

The invention discloses an MALDI-TOF-MS-based dead slaughtered meat identification method. The method comprises the following steps: preparing a sample set, wherein the sample set comprises a training sample set, a testing sample set and a to-be-measured sample set; measuring the sample sets by using the MALDI-TOF-MS to obtain a corresponding mass spectrum; establishing a neural work classifier based on the mass spectrum of the training sample set and the testing sample set; classifying the samples in the to-be-measured sample set by applying the neural network classifier to obtain the identification result. The invention also discloses an MALDI-TOF-MS-based dead slaughtered meat identification system. The metabolomic and proteomic difference of dead slaughtered meat and living slaughtered meat is found in the molecular level by virtue of the mass spectrometer, interference of environmental factors and sample factors is reduced maximally through training study and testing of the neutral network classifier, the detection process has high stability, sensitivity and accuracy, the detection result has high reproducibility, and the MALDI-TOF-MS based dead slaughtered meat identification method and the MALDI-TOF-MS based dead slaughtered meat identification system are a scientific, accurate and efficient dead slaughtered meat identification method as well as a scientific, accurate and efficient dead slaughtered meat identification system.

The invention relates to an electronic mobile training and test system of hygienic knowledge for public service staff. The electronic mobile training and test system of the hygienic knowledge for the public service staff comprises a main test room system and a mobile test system. The main test room system comprises a main server, a first network exchanger and a touch type computer or a desktop computer. The mobile test room system comprises a subordinate server, a second network exchanger and a tablet personal computer. After the mobile test system is applied, a test can be organized by only one person. Testing on main test room and mobile test rooms can be started simultaneously and do not interfere. All test data are automatically collected, organized and undergo statistical analysis. Working efficiency is improved and office resources are saved. Knowledge training study materials for the public service staff can be installed on the electronic mobile training and test system in advance. The mobile test rooms can be converted into mobile classrooms as required at any time and at any places so that the employed staff can be conveniently trained.

The system includes a processor configured for receiving biomedical documents including an identifier of the target and/or of the disease; specifying an offset time the offset time indicating a time interval ahead of the performing of the prediction; specifying a time window ending at the begin of the offset time; extracting a plurality of features selectively from the ones of the received documents published during the time window; providing a classifier having been trained on training features extracted from biomedical training documents published within a training time window ending at the begin of the offset time ahead of a moment the outcome of one or more training studies on training target-disease-pairs was disclosed; executing the classifier, thereby providing the extracted features as input; and outputting a classification result indicating whether the drug directed at the target can be used to treat the disease.

The invention discloses a multi-functional rehabilitation training device for rats with brain injury, and relates to the technical field of medical simulation experiments. The main points of the technical scheme are that the multi-functional rehabilitation training device comprises a main box body and a main controller; the main box body is internally provided with an annular plane runway, an annular three-dimensional runway and a static training room which are coaxially arranged from outside to inside; a plurality of dynamic training rooms which are uniformly distributed along the circumferential direction are communicated between the annular plane runway and the annular three-dimensional runway, and a dark light training pipeline is arranged between the static training room and the annular plane runway; and the training path is from the annular plane runway, the dynamic training rooms, the annular three-dimensional runway, the static training room, the dark light training pipeline to the annular plane runway in sequence. Diversified training conditions meeting actual conditions are provided for rat brain injury rehabilitation training, and basic data are provided for brain injury rehabilitation training research after data in the training process are collected.

The invention belongs to the field of daily living articles, and provides a study chair which comprises a chair face, a supporting part, two pairs of chair legs for supporting the chair face, a study desktop and a containing part. The supporting part is perpendicular to the chair face and arranged above one lateral side of the chair face. The containing part is formed among the two pairs of chair legs, and comprises supporting rods connected with the chair legs, and a plurality of connecting rods arranged between the supporting rods. The study desktop is arranged on one side of the chair face and higher than the chair face. By adding the study desktop and the containing part to an ordinary chair, the training study chair is formed; the study desktop and a drawer box can be used for writing and stationery containing, the containing part can be used for containing backpacks and other personal belongings, and the study chair is simple in structure, high in practicability, firm, attractive and durable.

The invention discloses a user event relevance calculation method based on content environment enhancement. The method comprises the following steps: lowering the dimensions of archives of a user and social events by using a topic model, and converting the archives into topic distribution; calculating user preference features of the user archives and the social event archives; extracting online and offline social influence features based on a collaborative filtering method by taking the user preference features as probabilities of the fact that the user participates in corresponding events; acquiring local interested topic distribution according to events in a city where the user is located, and comparing the local interested topic distribution with the events to obtain local popularity features; acquiring user event relevance through a training study sequencing model. According to the method, content environment relevant information in an event social network is fully mined to extract the features of user preferences, social influences and local popularity for calculation, and a plurality of features are combined, so that the accuracy of a final result is increased, and the technical problem concerned with recommendation specific to the type of novel objects such as social events in a personalized recommending system is solved.