17 results about "Behavioral testing" patented technology

The invention, which relates to the technical field of education recommendation, discloses a student portrait-driven education agent recommendation system based on a cognitive diagnosis map, comprising a time-frequency decomposition processing module, a weight rhythm matching module, a time sequence coupling damping module, a dynamic difference readjustment module and a time-frequency domain self-balancing control module. And the time-frequency decomposition processing module is used for establishing a time-frequency decomposition processing layer based on drifting characteristics of student portrait parameters in a time dimension, and performing energy distribution analysis on multi-source dynamic data streams from learning behaviors, test performance and emotion feedback according to time slices. Through time-frequency decomposition and non-resonance rhythm matching, dynamic coordination of weight adjustment and student portrait drifting is realized, characteristic fluctuation amplification is prevented, and the stability of a learning path is guaranteed; and a dynamic closed loop is formed through time sequence coupling damping and time-frequency domain self-balancing control, stable convergence of cognitive features is realized, and the accuracy and continuity of educational agent recommendation are improved.

The invention discloses a multi-modal perception humanoid robot behavior test method and related equipment, and the method comprises the steps: obtaining multi-modal perception data and current joint state data, splicing the multi-modal data and the current joint state data, and determining a current state vector; performing action sampling according to the current state vector and the trained processing model to obtain a plurality of sampling actions; calculating according to the plurality of sampling actions, the current state vector and a preset operation model, and determining a plurality of candidate action states from the sampling actions; performing identification calculation on the candidate action state according to a preset neural network model to obtain a total identification score, and determining a target action state according to the total identification score; and simulating and evaluating the humanoid robot according to the preset scene test case and the target action state, and generating a corresponding test report. According to the embodiment of the invention, the action adaptability and the scene adaptability can be improved. The method can be widely applied to the technical field of humanoid robots.

The utility model discloses a multifunctional device for insect breeding and behavior testing. Relates to the technical field of insect breeding equipment. A gauze partition plate is arranged in the rearing cage; a liquid feeding device, a water feeding device, a solid feeding device, an adult oviposition container and a larva feeding box are placed in the feeding chamber; a pupation box is arranged in the pupation eclosion chamber; a foam layer floats on the surface of the liquid foodstuff and is lined with filter paper; a plurality of water feeding assemblies are arranged in the water feeder, and each water feeding assembly comprises moisturizing filter paper and a fiber cotton swab; the multiple water feeding assemblies abut against one another to fully seal the bottle opening of the water feeder. The device mainly solves the bottleneck problem of drowning of the adult fruit flies, provides a suitable oviposition container for an adult oviposition selection test, can well realize breeding, continuous breeding and adult trend and oviposition behavior selection research of the adult fruit flies, avoids a large amount of death of the tested adult fruit flies, saves manpower, material resources and financial resources, and improves the test efficiency of the adult fruit flies. And the artificial feeding reproduction and test efficiency is greatly improved.

The embodiment of the application provides a kind of child behavior abnormality evaluation method and system, in the case where the child to be measured is located at least one test scene shown in test room, the behavior test data of the child to be measured collected by the data acquisition equipment arranged in test room is acquired;The behavior test data of the child to be measured is analyzed and processed, and the behavior characteristics of the child to be measured are determined;According to behavior characteristics, the probability that the child to be measured exists behavior abnormality is evaluated.The test scene corresponds to the abnormal behavior type to be evaluated of the child to be measured, and the abnormal behavior type includes at least one performance behavior corresponding to autism spectrum disorder.That is, the behavior test data of the child to be measured in real scene is collected by data acquisition equipment, to record the real action and behavior of the child to be measured comprehensively and accurately.In this way, the possibility of abnormal behavior of the child to be measured can be evaluated by analyzing behavior test data, which shortens the test time and improves the evaluation efficiency of abnormal behavior.

The invention discloses a tree shrew visual association memory evaluation method based on an 8-shaped maze, and the method comprises the following steps: preparing before an experiment, including animal screening and environment setting; performing rule training, enabling the tree shrew to learn to associate the colors of the prompt board in the selection area with channel arm selection, including familiarity environment, door pushing training, shaping training and free selection test, and opening and closing the corresponding channel arm according to the colors of the prompt board in the shaping training; formal testing is carried out, shaping training is carried out twice every day, then free selection testing is carried out according to a 1-3 random mode, and the error rate is recorded; and performing modeling evaluation, namely evaluating whether a stable memory model is established or not based on an error rate of a formal test, and entering the formal test when the prompt board continuously appears for 1-3 times according to the same color and the conversion rate is 50-65% and the error rate is lower than 20% in the free selection test. According to the tree shrew visual association memory evaluation method provided by the invention, scientificity and statistical efficacy of behavior testing are ensured, and learning deviation caused by a fixed mode in a traditional method is overcome.

The present disclosure provides an abnormal behavior test method, an abnormal behavior test device, an electronic device, a non-transitory computer-readable storage medium, and a computer program product. The abnormal behavior test method comprises: acquiring a set of behaviors to be tested pertaining to a same session within a preset time window; adding a label to each behavior in the set of behaviors to be tested, and obtaining a label feature of the set of behaviors to be tested on the basis of the labels of all of the behaviors in the set of behaviors to be tested; on the basis of a preset embedded feature extraction model, mapping the label feature of the set of behaviors to be tested into an embedded feature; on the basis of the embedded feature of the set of behaviors to be tested and an embedded feature of a historical set of behaviors obtained in advance, determining whether the set of behaviors to be tested is abnormal.

The application discloses a behavior test method and related equipment of a multi-modal perception humanoid robot, and the method comprises the following steps: acquiring multi-modal perception data and current joint state data, splicing the multi-modal data and the current joint state data to determine a current state vector; sampling actions according to the current state vector and a trained processing model to obtain a plurality of sampling actions; calculating according to the plurality of sampling actions, the current state vector and a preset running model to determine a plurality of candidate action states from the sampling actions; performing discriminant calculation on the candidate action states according to a preset neural network model to obtain a total discriminant score, and determining a target action state according to the total discriminant score; simulating and evaluating the humanoid robot according to a preset scene test case and the target action state to generate a corresponding test report. The embodiment of the application can improve the action adaptability and scene adaptability. The application can be widely applied in the technical field of humanoid robots.

The application provides a device for detecting prosocial behavior in mouse social behavior and a use method, relates to the technical field of animal behavior detection, and solves the technical problems of a small space of a behavior test device, inconvenient movement of a mouse, a long period, and the like in the prior art, which are not conducive to movement of the mouse after wearing a fiber and other facilities on the head; the technical scheme is that: a main test box body is provided, a larger test space is provided for the mouse, and an animal placing enclosure and a blank placing enclosure are symmetrically arranged on the left and right sides; the application can quickly obtain behavior comparison of the mouse in different environments, the required period is shorter, the behavior of the mouse can be observed and recorded from the top of the device as a whole, and image tracking and fiber recording are facilitated.

This disclosure provides a method, apparatus, edge computing device, and storage medium for constructing and statistically analyzing human behavior testing experiments, relating to the fields of human factors engineering and psychological behavior assessment technology. The method includes: testing subjects based on a pre-constructed human factors experiment, whereby the experiment is obtained after the user customizes stimulus presentation parameters, response conditions, and experimental procedures through an experiment editor; acquiring experimental data from the subjects, including behavioral data of the subjects' responses to stimuli according to response conditions when stimuli are presented; performing statistical analysis and norm calculation based on the behavioral data to obtain norm results; and generating a human factors experiment test report for the subjects based on the norm results. The method provided in this disclosure facilitates the flexible design of custom experiments, realizing a complete integrated process of experiment configuration, data acquisition and analysis, norm calculation, and result display.

The application provides a method for treating autism spectrum disorder (ASD) based on terahertz wave intervention and application thereof. The method comprises the following steps: dividing mice into four groups according to groups, each group having two types of mice; testing baseline behaviors of anxiety, motor ability and social ability of each group of mice; after a set time of completion of baseline behavior testing, using a THz-VNS device to intervene in each group of mice by THz-VNS; after the mice wake up, behavior testing is performed after a set time of completion of THz-VNS intervention; and statistically analyzing the behavior testing results to obtain the intervention results of THz-VNS intervention on ASD. By comparing the behavior testing results of wild type and ASD model mice before and after intervention, it is proved that the intervention method can improve the anxiety abnormality, motor dysfunction and social dysfunction of ASD model mice, which indicates that the intervention method can be used for the treatment of ASD. Meanwhile, the intervention method has a wide influence on the nervous system function, so the intervention is not limited to the treatment of ASD, but can also be extended to various nervous system diseases.

The application discloses a TATB / fluorine rubber interface micromechanics behavior test method. By performing interface mechanics behavior research on PBXs with different structural adhesive components, the relative change of the interface stress of the PBXs can be obtained. The method has high precision, can simultaneously obtain stress-strain change analysis, and can realize measurement of the force (displacement) load of the sample and collection of Raman spectrum while a small tensile force is applied to the PBX sample. The method is a new test method for evaluating the micro morphology and interface mechanics of energetic materials.

The present disclosure provides an abnormal behavior test method, an abnormal behavior test device, an electronic device, a non-transitory computer-readable storage medium, and a computer program product. The abnormal behavior test method comprises: acquiring a set of behaviors to be tested pertaining to a same session within a preset time window; adding a label to each behavior in the set of behaviors to be tested, and obtaining a label feature of the set of behaviors to be tested on the basis of the labels of all of the behaviors in the set of behaviors to be tested; on the basis of a preset embedded feature extraction model, mapping the label feature of the set of behaviors to be tested into an embedded feature; on the basis of the embedded feature of the set of behaviors to be tested and an embedded feature of a historical set of behaviors obtained in advance, determining whether the set of behaviors to be tested is abnormal.

The invention relates to the technical field of intelligent wearable equipment, in particular to an epilepsy auxiliary diagnosis and treatment system based on intelligent wearable equipment, which comprises a data acquisition module, an atlas construction module, a feature extraction module, a state judgment module and a strategy execution module, and is characterized in that the atlas construction module is used for constructing a personalized behavior physiological atlas based on a test data set; the feature extraction module is used for extracting a real-time feature vector of a current time window based on the monitoring data flow; the state judgment module is used for generating a state judgment result about the current behavior intention of the user; a personalized physiological reference map of a user is established by executing an active behavior test, a deliberate inhibition behavior adopted by the user due to perception of a thought is intelligently identified, and monitoring data corresponding to the behavior is isolated, so that the core problem that the performance of an epilepsy auxiliary diagnosis and treatment model is degraded due to reverse modeling of the user behavior in long-term use is effectively solved; and the response reliability of the monitoring system in a real attack scene is ensured.

The invention provides a construction method and application of a KIF5C gene knockout animal model, and relates to the technical field of biological medicines. The sgRNA for knocking out the KIF5C gene is characterized in that the sequence of the sgRNA is selected from at least one of SEQ ID No. 1, SEQ ID No. 2, SEQ ID No. 3 and SEQ ID No. 4. The invention further discloses a preparation method of the sgRNA for knocking out the KIF5C gene. The KIF5C gene knockout animal model disclosed by the invention can be used as an animal model for depression and disease research, the KIF5C gene knockout animal model is prepared by adopting a gene knockout technology, and animal behavioral detection shows that a mouse has depression-like symptoms (a sweet water preference experiment and a forced swimming experiment) and memory dysfunction (a Y maze experiment and a conditional fear experiment); the compound has depression symptoms, can be reversed through an antidepressant drug ketamine, and can be used for researching depression animal models and developing corresponding drugs.

The invention discloses a test system, method and device of a priority flow control function and a storage medium, and relates to the technical field of network function testing, and the test system of the priority flow control function comprises a control module, a switch and a test instrument; the control module is used for controlling the test instrument to increase the flow sending rate so as to trigger congestion, so that simulation of a real pressure scene is realized; the method comprises the following steps: sending a control frame to a test instrument through a switch so as to realize active behavior test on the switch under a congestion condition, and ensuring that a priority flow control function can be actively triggered; the test instrument captures the control frame and executes the flow sending pause command, so that verification of a congestion-back pressure-response control loop is realized, compliance behaviors of endpoint equipment in a real network are simulated, congestion and control are isolated in the priority to be tested, and smoothness of flow of other priorities is guaranteed.

The application discloses a system behavior testing method, device, equipment and storage medium. The method comprises the following steps: determining the current state of each target node in a system; if the current state of each target node is a preparation state, determining whether the system has been injected with a preset target exception; if the system has been injected with the target exception and the system satisfies a preset exception recovery condition, performing an exception recovery operation on the system; if the system has not been injected with the target exception and the system satisfies a preset exception injection condition, injecting the target exception into the system; obtaining a callback message of the system injected with the target exception; and determining a behavior test result of the system according to the callback message. The system can be tested for behavior, so that a staff member can determine the performance and reflection capability of the system according to the behavior test result of the system.

The invention provides application of diethyl phthalate (DEP) in an induced zebra fish depression model, and belongs to the technical field of animal models. The preparation method comprises the following steps: firstly dissolving a diethyl phthalate solution in DMSO (Dimethylsulfoxide), and then mixing with water to obtain diethyl phthalate feeding water; putting zebra fish into the diethyl phthalate feeding water for feeding; the depression-like phenotype of the zebra fish is confirmed through behavioral testing. The method is simple and convenient to operate, the constructed model can stably reproduce DEP-induced behaviors and molecular level changes, and the method is suitable for plasticizer toxicology screening and depression pathogenesis research; and an economic and efficient research tool capable of replacing mammalian experiments is provided for safety evaluation of DEP and research and development of nervous system drugs.