164results about How to "Improve academic performance" patented technology

Apparatus and methods for plasticity in a spiking neuron network. In one implementation, a plasticity mechanism is configured based on a similarity measure between neuron post-synaptic and pre-synaptic activity. The similarity measure may comprise a cross-correlogram between the output spike train and input spike train, determined over a plasticity window. Several correlograms, corresponding to individual input connections delivering pre-synaptic input, may be combined. The combination may comprise for example a weighted average. The averaged correlograms may be used to construct the long term potentiation component of the plasticity. The long term depression component of the plasticity may comprise e.g., a monotonic function based on a statistical parameter associated with the adaptively determined long term potentiation component.

The invention discloses an image classification method based on a confrontation network generated through feature recalibration. The image classification method based on the confrontation network generated through feature recalibration is suitable for the field of machine learning and comprises the steps that to-be-classified image data are input into a confrontation network model for network training; a generator and a discriminator which are constituted by a convolutional network are constructed; random noise is initialized and input into the generator; the random noise is subjected to multilevel deconvolution operation in the generator through the convolutional network, and finally, generated samples are obtained; the generated samples and authentic samples are input into the discriminator; and the input samples are subjected to convolution and pooling operation in the discriminator through the convolutional network, thus a feature graph is obtained, a compressed and activated SENetmodule is imported into an intermediate layer of the convolutional network to calibrate the feature graph, thus the calibrated feature graph is obtained, global average pooling is used, and finally,image data classification is output. The SENet module is imported into the intermediate layer of the discriminator, the importance degree of each feature channel is automatically learned, useful features relevant to a task are extracted, features irrelevant to the task are restrained, and thus semi-supervised learning performance is improved.

Described are methods, devices, and systems for a novel, inexpensive, easy to use therapy for treatment of coma, post-traumatic stress disorder, Parkinson's disease, cognitive performance, and/or amblyopia. Described are methods and devices to treat coma, post-traumatic stress disorder, Parkinson's disease, cognitive performance, and/or amblyopia that involves no medication. Methods and devices described herein use alternating magnetic fields to gently “tune” the brain and affect symptoms of coma, post-traumatic stress disorder, Parkinson's disease, cognitive performance, and/or amblyopia.

The invention provides a method and a device for pushing learning resources. The method comprises steps: according to an acquired user historical question, a knowledge point in the historical question and right or wrong information for the user historical question are determined; based on the determined knowledge point in the historical question and the determined right or wrong information for the user historical question, the degree of mastering the knowledge point in the historical question by the user is judged; based on the judged degree of mastering the knowledge point by the user, a specific knowledge point in a to-be-recommended learning resource is determined; and the learning resource with the specific knowledge point is pushed to the user. The method and the device of the invention can recommend a learning resource which can effectively enhance academic performance according to the actual learning condition of the user.

Systems and methods of propagating maximum segment size and path maximum transmission unit of network paths between an intermediary device of a cluster with a plurality of destinations are described. A first core of a node including multiple cores and intermediary to a client and a plurality of servers may receive a response to a packet transmitted to a destination indicating that the packet has a size greater than a MTU of a network path between the node and a destination. The first core identifies the MTU of the network path and determines that the identified MTU is different than an MTU used by the first core. The first core replaces the MTU stored in an entry corresponding to the destination in a PMTU table maintained with the identified MTU. The first core transmits, to other cores of the node, the identified MTU to update each core's PMTU table.

The present invention discloses an English teaching language learning system. The system comprises a central processing unit, a power module, a teaching platform module, a study guide module, an online learning module, an online test module, a statistic analysis module, a user management module, an online forum module, a bulletin board management module, a testpaper making module, an item bank management module, a display module and a database module. The English teaching language learning system can allow students to perform consolidation exercise of knowledge points according to personal information to allow the students to improve school record through leak filling; teachers can rapidly monitor students' knowledge point grasping conditions so as to improve the working efficiency; the students can download the students' classroom teaching data and practice data through a data download module, and the students can upload their own learning data to share with other students through a data upload module; and an oral practice unit is employed to help the students with practice of spoken English and solution of the problem of nonstandard pronunciation of English.

The invention provides an English learning platform system comprising a teacher client, a student client and a parent client, the teacher client comprises a teacher end book reading module, a publishing task module, a teaching note module, a task management module, a teacher end learning report module, a school class management module, a message system module and a teacher end point mall module; the student client comprises a student end book reading module, a reading scoring module, a learning task module, a student end learning report module, a word query module, a reading note module, a rating test module, a message notification module, a student end point mall module, a student overtime module and a student end payment module; the parent client comprises a learning task notification module, a learning result notification module, a learning score pushing module, an account management module and a parent end payment module. According to the invention, resource integration is realized, the book resources and the evaluation technology are combined, and a brand-new reading learning mode is formed.

The invention discloses a progressive learning management method. The method based on the current grade level of a learner is to continuously provide learning resources of which difficulty is moderately higher than the grade level of the learner and finally increase the school record of the learner; and the invention also provides a progressive learning system for increasing the school record. The method comprises the following steps: building a learning resource repository, providing learning resources for the learner, performing benchmark difficulty assessment to the learner, and judging whether the learner passes through the benchmark difficulty assessment until the passing of the learner. The method and system of the invention provide learning resources with different difficulty levels for the learner with different degrees of learning, thus the learner can perform adaptive learning and aim at continuously increasing the school record of the learner.

The invention provides a student achievement diagnosis and improving system, and belongs to the field of education. The student achievement diagnosis and improving system comprises an information collecting module, a structured question bank, an online testing module, a special training module, a test paper collecting module, a precise analysis module, a task distribution module, a learning condition tracking module, an electronic lesson preparation module and a social interaction module; the structured question bank stores problems identified with knowledge points as labels; the online testing module utilizes the structured question bank to test the knowledge level, the problem solving ability, the cognitive ability and the emotional ability of students, and a personalized diagnosis report is formed through the precise analysis module; the special training module conducts training in the four aspects according to the content of the report; the precise analysis module analyzes information according to the test paper collecting module and the online testing module and obtains diagnosis information; and the learning condition tracking module is used for feeding the learning conditionback to teachers and parents. Psychological cognitive factors and the emotional ability are introduced into the student achievement diagnosis and improving system, the ability improving path is effectively planned, training materials are effectively recommended, and the comprehensive ability of the students is improved.

The invention discloses a voice recognition-based children video teaching method. The method comprises the following steps of acquiring a teaching video set corresponding to the age of a target child;playing a teaching video in the teaching video set to the target child; acquiring the voice information of the target child in the process of playing the teaching video; judging the emotional state of the target child according to the voice information of the target child and a preset voice comparing chart; according to the emotional state of the child, adjusting the parameters of the currentlyplaying teaching video or replacing the currently playing teaching video.

The invention discloses a video teaching system based on mood of a child. The system includes a video acquiring module used for acquiring a teaching video set corresponding to the age of a target child; a video playing module used for playing a teaching video in the teaching video set to the target child; a voice collecting module used for collecting voice information of the target child during the teaching video playing process; a feature extracting module used for extracting target tone features in the voice information of the target child; a mood judging module used for judging the mood state of the target child according to the target one features and a preset voice comparison table; and a parameter adjusting module used for performing playing parameter adjustment for the currently playing teaching video or changing the currently playing teaching video according to the mood state of the child.

The invention discloses a classroom behavior detection system based on computer vision, which comprises an intelligent processing module, a data acquisition module and a storage module. The intelligent processing module is respectively connected with the data acquisition module and the storage module. The intelligent processing module comprises a data processing module, a human body attitude estimation module, a seat detection module and a face recognition module, the data processing module is respectively connected with the human body attitude estimation module, the seat detection module andthe face recognition module, The human body attitude estimation module comprises a body attitude estimation module, a head posture estimation module and a hand posture estimation module, wherein the body posture estimation module, the head posture estimation module and the hand posture estimation module are fixedly connected in series with each other; The data acquisition module comprises a videoacquisition module and a wireless transmission module, and the video acquisition module is connected with the camera. The invention improves the learning enthusiasm of the students by analyzing the learning behavior of each student in the classroom, and contributes to improving the learning performance of the students.

The invention discloses a campus student behavior analysis method and system based on wifi hotspots. The method comprises the steps: S1, recording the real-time positions of students through the wifi hotspots in a campus and the terminal equipment carried by the students; S2, gathering the real-time positions of the students, and generating daily tracks of the students in the campus; S3, carrying out the behavioral analysis of the daily tracks of the students based on a wireless ap, calculating the stay time of the students in each wifi hotspot region, and gathering the stay time. The method achieves the analysis of the behavioral tracks of the students in each time period according to the information and actual time collected by the system, so as to achieve the control of the activities and activity time of the students in the campus. Through the analysis of the behavioral track data of the students, the method achieves the comprehensive understanding of the daily conditions of the students in the campus, greatly improves the integrated management level of the students, and facilitates the improvement of the school record of the students and the school performance of the students on the basis of improving the effective management of the students.

The invention discloses an interactive classroom teaching system based on a cloud education platform. The system comprises a server, a cloud education interaction platform, a teacher client, a studentclient and a parent client. A cloud education interaction platform is built, and is connected with the teacher client, the student client and the parent client through an MSN information channel. Byutilizing a teacher operation module, a student operation module and a parent operation module, teachers, students and parents can perform online and offline effective interactive communication on thecloud education interaction platform, so that the classroom interactivity of the students and the teachers and the classroom management are enhanced, the interactive communication between the teachers and the parents is also enhanced, the learning conditions of the students are known, the students are supervised and urged according to feedback opinions of teachers, parents can fully participate in learning education of the students, and the academic achievements of students can be improved.

The invention discloses a high-performance compound material prepared by a recycled waste carpet PA66 material and a preparation method thereof. The composing formula of the material is formed by the following components by weight percentage: 54-60% of recycled waste carpet PA66; 0-10% of a flexibilizer; 30-35% of alcoholysis-resistant glass fiber; and 0-1% of a tackifier and an antioxidant. The beneficial effects of the high-performance compound material are as follows: firstly, the recycling of the recycled waste carpet material is realized, and the recycling of the resource is realized, the material is green and environmental; secondly, the recycled waste carpet PA66 is modified so as to improve the performance of the recycled waste carpet PA66 and the cohesiveness of the PA66 and the alcoholysis-resistant glass fiber interface, so the compound material has good mechanical property, hydrolysis resistance or alcoholysis resistance and so on; and the application for important parts, such as an automobile front-end module, an automobile engine fan, an oil pan and a radiator water chamber, can be realized.

The invention relates to the technical field of self-adaptive learning, and discloses a learner-centered self-adaptive learning system, which comprises an infrastructure support layer, a data resourcelayer, a core service layer and a visual presentation layer, wherein the infrastructure support layer is used for providing a development and operation environment, computing and storage resources and a data acquisition interface for the system; the data resource layer is used for providing data support and data archiving management service for the adaptive learning core business; the core business layer is used for realizing core business of adaptive learning; and the visual presentation layer is used for providing an input interface and output presentation for the system, providing visual interface service for self-adaptive teaching data retrieval and operation for a user and providing an operation and maintenance management service interface for system management. Students can be helped to construct a knowledge structure of the system, and learning efficiency is improved; teaching data service and teaching participation means are provided for teachers; and automatic generation anddigital asset conversion services of the domain knowledge model are provided for learning content service providers.

The invention discloses full-nutrition compound edible powder and relates to a compound wheaten food material, rich in various nutrient components required by the human body. The full-nutrition compound edible powder comprises the following components in parts by weight: 11-15 parts of yolk powder, 8-12 parts of powdered milk, 7-11 parts of peanut powder, 5-9 parts of sesame powder, 4-8 parts of walnut powder, 5-9 parts of raisin powder, 24-28 parts of soybean meal, 8-12 parts of rice powder, 10-14 parts of wheatmeal, 8-12 parts of cornmeal and 8-12 parts of millet powder. The full-nutrition compound edible powder is prepared by mixing and bagging the components. The invention has the advantages that according to the demand of nutrient balance of the human body, protein, mineral substances, vitamins, celluloses, amino acid, sugar, fat, and the like contained in coarse cereals and fruit are reasonably used and scientifically matched, thus the full-nutrition compound edible powder meets the health-care requirement of the human body; through the digestion and the absorption of the human body, the full-nutrition compound edible powder can be quickly converted into energy so as to meet the requirement of growth, development and various physiological functions, improve the resistance and the recovery capacity, effectively lighten fatigue and improve the working and learning efficiency.

The invention discloses a dynamic answer sheet template system based on intelligent marking, comprising an answer sheet generation module, wherein the answer sheet generation module is used for generating an answer sheet according to the answer sheet template; an identification module for identifying an image of the test paper and an image of the answer sheet; an association module, wherein the association module is used for making the questions of the test paper image correspond to the answers of the answer sheet image one by one; a judging and analyzing module, which is used for analyzing and judging the answers of the images of the answer sheets, and obtaining the region where the wrong answers are located and the wrong questions of the test paper images corresponding to the wrong answers; a background processing module which is used for sending the wrong title and the wrong answer to the server. The invention can precisely match the answer sheet with the corresponding test paper questions, thereby summarizing and obtaining the wrong question bank for repeated study by the students or the parents or the teachers of the students, so as to improve the correct rate of the answer sheet and improve the learning level of the students.

A nutritional supplement to improve learning, academic, and behavioral performance, particularly of children in academic settings, comprising a quantity of flavonoid compounds with oxygen radical absorbance capacity (ORAC) derived from a multitude of plant substances, lipoic-carotenoid compounds, and a neurotransmitter amino acid.

The invention discloses an artificial-intelligence English learning platform comprising a control module. The output terminal of the control module is electrically connected with a parent learning supervision management module, a synchronous course learning module, a specialized training module, a wisdom review module, a three-dimensional evaluation module, a leak filling and enhanced acceleratedlearning module electrically; the output terminal of the parent learning supervision management module is connected with a learning report module, a learning progress module, a learning arrangement module and a testing arrangement module electrically; and the output terminal of the three-dimensional evaluation module is connected with an English-Chinese module, a Chinese-English translation module, a voice evaluation module, a spelling evaluation module and a dictation evaluation module electrically. According to the invention, with the artificial-intelligence English learning platform, the students are assisted in improving the learning method and enhancing the learning efficiency; the children's learning enthusiasm is stimulated; the ability of taking examinations is enhanced; controlling of learning of children by parents is realized; on the basis of the VAK learning style, the classroom teaching is set reasonably, the teaching materials are selected reasonably, and the teaching activities are arranged reasonably; the teaching levels of teachers are improved; and the knowledge transmission mode is adjusted.

A server and method for managing learning is provided. A correct answer ratio is checked based on a real-time solving process and solving time of a question provided to a learner by using a terminal such as a computer or a portable terminal such as a smartphone to induce the learner to sincerely learn.

The invention discloses a student behavior prediction method based on an artificial neural network, which is characterized by comprising the following steps of 1 collecting the data, obtaining the student card data, the classroom attendance data and the student achievement data; 2 preprocessing the data for data cleaning, data integration, data selection and data transformation; 3 extracting the behavioral characteristics of the student; 4 generating a sample set of extracted behavioral characteristics of the students, and establishing a behavioral neural network model of the students; 5 according to the importance of students' behavioral characteristics, establishing a decision tree model of students' behavioral characteristics; 6 based on the decision tree model, predicting the students'behavior. The method of the invention collects the behavior characteristics of the students, sorts the behavior characteristics of the students, reduces the characteristics through the neural network, establishes the decision tree model, predicts the behavior of the students, finds the abnormality of the students in time, and supervises the students.