37 results about "Learning center" patented technology

A hybrid learning environment may include a hybrid learning environment system; a learning center, including a first client computer, and an online class display coupled to the first client computer to display instructional material; a second client computer at a remote location displaced from the learning center to present instructional material from the hybrid learning environment system server; a database accessible to the hybrid learning environment system to store at least one of the instructional material; and at least one network coupling said first client computer, said second client computer and said hybrid learning environment system server.

The invention discloses a classroom interaction teaching system which comprises a teacher terminal, a student terminal and a server side respectively connected with the teacher terminal and the student terminal. The teacher terminal consists of a teacher registration log-in module, a classroom center module, a classroom creation module, a class attending module, a classroom sign-in module, an answering control module and a class dismissing module. The student terminal includes a student registration and login module, a learning center module, a classroom searching module, a student sign-in module, an event control wake-up module, and an answering and feedback module. The server side includes a message communication server and a database. Disclosed in the invention also is a classroom interaction teaching method. Therefore, the classroom interaction threshold and constraints are minimized; the students and teachers only need mobile terminal equipment and networks like a mobile traffic or a campus network to build a bridge of classroom interaction without the need to erect any environment needed by equipment; the usage becomes convenient; and the cost is low. Meanwhile, the system can be used simply and easily; and the classroom interaction teaching system and method can be applied widely.

The invention discloses a method of generating a navigation learning path on a knowledge map. The method is characterized by comprising the following steps: (1) judging whether a general list Gen-T for storing the knowledge map is empty or not: if the general list Gen-T for storing the knowledge map is not empty, turning to the step (4) to excavate the learned knowledge of a user; (2) generating a total path t-nlr: computing the hierarchy level and learning centrality of a knowledge unit and secondarily ordering the knowledge unit according to the ascending order of the hierarchy level and the descending order of the learning centrality so as to obtain the total path t-nrl; (3) generating the general list Gen-T; (4) excavating the learned knowledge of the user: identifying the user type according to a user login account, generating the existing learned knowledge vector pre-kU of a learner U according to an excavating strategy for the learned knowledge of different types of users; (5) generating a user navigation learning path nlrU by reference to the total path t-nlr and the general list Gen-T according to the pre-kU of the learner U and an input learning goal OU. The user navigation learning path generated by the method provided by the invention has sufficiency, necessity and high efficiency for a leaner to understand the learning target.

A digitally-based, multi-media learning center is provided for an interactive learning experience. An expert-guided digital presentation of relevant evidence-based information is provided, such as relating to medical conditions. In addition to digitally-based information, live peer-to-peer, and interpersonal interaction, including with live patients, is preferably supported to supplement the learning experience.

The invention relates to a medical data joint learning system and method based on trusted computing and privacy protection. A joint learning center control layer receives non-sensitive meta-information uploaded by a data contributor through a data contributor management layer of a data node where the joint learning center control layer is located for filing, and original data is locally registered, stored and subjected to isolation calculation; and the joint learning center control layer processes a joint learning request initiated by the data miner through the data miner interaction layer, summarizes insensitive intermediate results obtained by performing local isolation calculation on the data nodes based on the original data in a safe calculation area, and returns a final joint learningresult to the data miner interaction layer. The invention provides a whole set of service system based on medical big data security sharing, trusted computing, deep mining, authority authentication and multi-platform joint learning, and solves the problems of scattered, single and incomplete medical data privacy protection and data mining at the present stage.

The invention relates to a learning system, and particularly discloses a personalization item bank learning system. The personalization item bank learning system includes a server and a client which is connected to the server through a network. The client includes a storage module, a display module, and an input module, wherein the display module and the input module are connected to the storage module. The server includes a core server and a data server which is connected to the core server; the core server is provided with a client service module, a data format module, a data transmission module, a database operation module, and a communication module; and the data server is provided with an item information module and a learning record module which can be updated in real time. The storage module is provided with a learning center module which is used for acquiring examinee answer information and receiving real-time updated information of the data server.

The invention discloses a training management system for self-study examination, and a training management method thereof. The training management system for self-study examination comprises a course center module, a course selection center module and a learning center module, wherein the course center module is used for saving course information; the course selection center module is used for selecting corresponding courses according to the course information in the course center module; and the learning center module is used for learning according to the courses selected by means of the course selection center module and recording learning progress and learning effect. according to the training management system, course associated information is set in the course information, the courses and industries of interest are selected according to preset questions associated with course selection, and learning ability and learning base level are tested according to a pretesting examination paper, so as to judge whether a student is suitable for learning the course.

The invention provides an intelligent health learning table. The intelligent health learning table comprises a liftable desktop, a learning panel, an intelligent lighting device, an intelligent printing scanning device and a learning table main control board, wherein the learning panel is rotationally connected with the desktop and can tilt relative to the desktop; and the learning table main control board is provided with a voice instrument module, and the learning table main control board is used for controlling a height adjustment bracket to ascend and descend to adjust the desktop height,controlling the inclination angle of the learning panel and controlling the illumination brightness of the intelligent lighting device according to a user voice instruction acquired by the voice instrument module or a preset instruction in the learning table main control board. The invention simultaneously provides an Internet of Things health learning center system, which is characterized by comprising the intelligent health learning table and a student interaction system, wherein the student interaction system comprises an information output terminal, an information acquisition terminal andan intelligent control display screen device.

The invention belongs to the technical field of radar target recognition, and particularly relates to a linear discriminant learning true and false target one-dimensional range profile feature extraction method. According to the method, various sample distribution center vectors are obtained through iterative learning; then, a learning center vector is used for replacing a sample mean vector to calculate an intra-class scattering matrix and an inter-class scattering matrix; the linear discriminant learning transformation matrix is obtained through calculation, the degree of intra-class aggregation and inter-class separation can still be well represented under the condition that target sample data distribution is non-Gaussian distribution, the defect that a conventional discriminant subspace is only suitable for sample data Gaussian distribution is overcome, and therefore the target recognition performance is improved.

The invention provides a federal learning model training method for large-scale industrial chain privacy calculation. The method comprises the steps that a federated learning center server node divides industrial chain business training data sets with non-independent identical distribution as a target, and distributes the industrial chain business training data sets to a plurality of federated learning worker nodes; the federated learning worker node iteratively trains the local model based on the target profit function; after aggregating the updated local model weight sent by each federated learning worker node, the aggregation server node calculates an earth movement distance corresponding to each federated learning worker node according to each local model weight distribution and the overall local model weight distribution, and removes federated learning worker nodes exceeding a preset distance threshold; and the remaining federal learning worker nodes continue to carry out model training. According to the method, data distribution with too large distribution difference is eliminated in the federated learning model training process, the precision loss caused by heterogeneous data is reduced, and the application reliability of a traditional algorithm in an industrial chain is improved.

The invention discloses an intelligent ecological marketing energized training platform in the technical field of marketing training platforms. The intelligent ecological marketing energized trainingplatform comprises a user login page, a user management module, a course management page, an authentication management page, an official network home page, an official network registration page, an official network login page, an official network learning center and an official network authentication center, wherein the user management module comprises user roles, user management, background usersand company administrators; the course management page comprises online courses, adding of courses, editing of courses and data importing; and the authentication management comprises a question banklist and a test question list. The platform mainly comprises the functions of login, user management, account setting, course management, certification management and the like, and is convenient for students to learn marketing skills on line, so that the flexibility of teaching is improved, the use of manpower and material resources is reduced, and the students can select and learn specifically and repeatedly.

The invention discloses a traffic information processing system and device for information security, and a storage medium. The system comprises a vehicle end and a center end. The vehicle end comprises a data acquisition module, a local processing module, a local storage module, a federated learning module, a judger, a communication module and a man-machine interaction module; and the center end comprises a federated learning center module and a communication module. According to the system, a federated learning mode is adopted, traffic information collected by a sensor is better processed, user privacy is protected while the number of data is increased, an overall model recognition level and a vehicle control level are improved, and an information security level is increased. According tothe invention, privacy-safe federated learning and encryption operation are adopted to protect privacy so that images acquired by the intelligent vehicle cannot be sent to the center end, and the privacy of a user is protected. In the invention, the user participates in confirmation and labeling of data arrangement and result analysis, the improved model is detected, a detection result asks the user to confirm, and the recognition level of the model and the vehicle control level are increased.

The invention discloses a node selection and aggregation optimization system and method for federated learning under a micro-service architecture, and the system comprises a node division module which is used for dividing nodes into data nodes and model nodes according to the specific privacy protection demands; the participation model aggregation node selection module is used for selecting model nodes participating in model aggregation and data nodes for verifying model parameters by the center party according to the node credibility; the node creditworthiness is generated based on the quality of transmission data or a model of the sensing node and the historical creditworthiness of the sensing node; and the credit chain and transaction chain construction module is used for establishing two block chains, namely a credit chain and a transaction chain, and respectively recording the credibility of the nodes and the types of exchange data or models between the federal learning center party and the nodes in each round. According to the method, a specific quality evaluation and model aggregation method is constructed for different privacy requirements of nodes, and the advantages of federated learning on node data privacy protection and non-tampering and traceability of a block chain are brought into full play.

The invention discloses a campus all-purpose card control system, which comprises a campus all-purpose card control center, the campus all-purpose card control center comprises a card affair center, an equipment center, a data center, a living center and a learning center, and the card affair center, the equipment center, the data center, the living center and the learning center carry out real-time data updating through a switch. The card service center comprises account opening, recharging, account selling, loss reporting and rehandling and temporary cards. The invention relates to the technical field of control systems. The invention discloses a campus all-purpose card control system. the campus all-purpose card can be used more intelligently. The intelligent campus management system issimple in structure and more convenient to operate, meets the requirements of an intelligent campus, constructs a digital space on the basis of a traditional campus to expand the time and space dimensions of the real campus, improve the operation efficiency of the traditional campus and expand the service function of the traditional campus, and finally achieves the purposes of comprehensive informatization of the education process and improvement of the management level and efficiency.

A method of instructing a plurality of students using a learning center, comprising providing a learning center, wherein the learning center includes a bench system having a two tier configuration and forming an arc of about ninety degrees. The bench system also includes a plurality of two-tier straight benches and a plurality of two-tier arcuate benches. The learning center further comprises shelves coupled to a back portion of the learning center. The method also includes providing a traditional classroom adjacent the learning center. The method further includes providing learning center rules, wherein the learning center rules include conduct rules and disciplinary rules. The method additionally includes pre-determining a single learning event at the learning center. Furthermore, the method includes holding the single learning event at the learning center following the learning center rules.

The invention discloses a basic medicine organ system interaction learning center and application thereof. The basic medicine organ system interaction learning center comprises a real object learning system and a virtual learning system, wherein the real object learning system is a sample and/or a model; the virtual learning system comprises a hardware device and software; the hardware device comprises a host computer, a controller and a display; the display is a 3D display and/or a touch display; the software is an interaction learning platform; the interaction learning platform comprises an administrator client and a student client; the administrator client is used for setting a teaching content and a test paper; the student client comprises a learning module and an evaluation module; the interaction learning platform operates in the host computer with the hardware device as an operation basis, display on the touch display and/or the 3D display is realized, and operation is carried out through the touch display or the controller. The student comprehensively learns contents of the basic medicine organ system through the virtual learning system, in combination with exhibited samples, the knowledge is deeply mastered, and the technical objective of integrated teaching of theory and practice is thus realized.

The invention discloses a power industry hoisting operation peccancy detection method based on reinforced federated learning, and the method comprises the following steps: S1, employing federated learning C, training a node A and a node B through employing local data, and obtaining a model; S2, inputting the model obtained in the step S1 into a reinforcement learning module, performing model fusion by using reinforcement learning DQN, and adjusting weights of the A node model and the B node model; S3, enabling the reinforcement learning module to generate a reinforcement fusion model through reinforcement learning; s4, performing model fusion on the models of the node A and the node B by the central node of the federated learning C by using a reinforced fusion model and weighted average; S5, issuing the fused model to the node A and the node B; and S6, repeating the steps S1 to S5 until model training is completed. The method has the beneficial effects that the joint modeling effect of federal learning is ensured by using reinforcement learning, high-quality nodes are selected to jointly establish a model, and the influence of a heterogeneity problem is reduced.

The invention provides a credit system enterprise safety management method and system, and relates to the field of enterprise management. The credit system enterprise safety management method comprises the following steps that employees obtain credits by learning safety production knowledge, reporting hidden dangers and solving the hidden dangers, exchange the credits with rewards set by enterprises, and actively improve the awareness of safety production; The credit system enterprise safety management system comprises a login part; a double-control prevention part: hidden danger reporting, hidden danger checking and risk grading; a training and examination part: a learning center and an examination center take a question every day; and an internal management part: reasonable suggestion, list system management and integral addition and subtraction. Employees are promoted to autonomously learn knowledge of safety production in an integral mode, and meanwhile, enterprise production management is facilitated.

The invention discloses a remote education digital learning center intelligent sending network system based on the Internet of Things and a management method. The system comprises a user side, an intelligent campus application layer, an intelligent application support platform and the Internet of Things. An intelligent sensing network layer can sense data of the user side and data of the intelligent campus and perform interaction and comprehensive analysis. Different users of the user side carry out next teaching, learning and management according to feedback data. Therefore, integration and application of resources are facilitated, an offline learning center becomes an offline digital learning environment support of an open education system, an auxiliary means is provided for teachers tomanage students, teaching management resources are saved to a certain extent, and teaching and learning quality improvement is promoted.

The invention discloses an English language learning auxiliary system, and belongs to the technical field of language learning systems, the English language learning auxiliary system comprises a CPU, appearance hardware and learning auxiliary software, the CPU is in data interconnection with the appearance hardware and the learning auxiliary software, through setting a matching competitive unit, the system is provided with multiple learning units in a student learning center, and the learning units are matched with the matching competitive unit. After exercises are practiced, the students can match with other users in a targeted content manner by matching the competitive units, the students improve personal segments in continuous competitive battles, the personal segments can be ranked in the same city and the whole country, the win and the learning desire of the students are motivated through competitive learning, the learning motivation of the students is enhanced, and the learning efficiency of the students is improved. Through the arrangement of the leisure and entertainment center, students can watch and train bilingual stories, film and television dubbing and bilingual music in spare time, video and audio contents of individual training are uploaded to corresponding units, other users can watch the uploaded video and audio contents, and the sociality of the system is improved.

The invention discloses an interactive multimedia online education system, and belongs to the technical field of online education. The system is characterized in that a user logs in the system for on-line learning, including in-learning courses, a learning center, in-teaching courses, my questions and answers and collected courses; the in-learning courses are used for displaying all the in-learning courses of the login user; the learning center is used for displaying the To Do List of learning and displaying the learning tasks of courses and classes in learning; the in-teaching courses are used for displaying the states of the courses; the my questions and answers are used for displaying the proposed questions and browsing/final reply conditions; and the collected courses are used for displaying the courses collected by the user. By arranging the learning center, the user can learn and select courses at any time, display learning tasks in learning and conveniently and directly enter learning; meanwhile, by means of a my answering interface, the user can click a question skipping detailed page to browse the latest answering situation, and interaction and communication between the user and teachers as well as between the user and other students are facilitated.

The invention discloses a research learning system, and the system comprises a teacher client, a student client, a parent client, a management client and a server, the teacher client comprises an account management unit, a class management unit, a learning center management unit, a research learning topic management unit and a question answering management unit; the research learning topic management unit comprises a topic identification module, a research tool module, a research data module, a research outline module, an evaluation report module, a statistical report module, an improvement scheme module, a discussion and question answering module and a learning note module. By creating and simulating a research learning environment, students purposefully and stepwise discover and grasp scientific rules, generate and construct scientific knowledge and change passive infusion into active research learning through human-computer interaction under the guidance of teachers and the drivingof tasks; a teacher-dominated and parent-supervised learning management mechanism is introduced to continuously follow and supervise the learning of students, so the continuity and effect of learningare ensured.